Report 31
December 2008
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/,672)7$%/(6,9 /,672)),*85(69 (;(&87,9(6800$5<9, &2//$%25$7,9(5(6($5&+$&7,9,7,(6 6FLHQWLILFPHHWLQJVDQGWHOHFRQIHUHQFHVDPRQJUHVHDUFKWHDP 1HZUHVHDUFKILQGLQJV 1.2.1 Current projects ...... 2 1.2.2 Completed projects ...... 42 1.2.3 Student projects in progress ...... 44 1.2.4 Student projects completed ...... 59 1.2.5 Student theses completed ...... 60 &21'8&72)6859(<6 FRKRUW6XUYH\±)LQDOUHVSRQVHUDWH FRKRUW6XUYH\±'DWDFROOHFWLRQ FRKRUW6XUYH\±3LORW 0(7+2'2/2*,&$/,668(6 'HILQLQJPHQRSDXVDOVWDWXV 3.1.1 Introduction ...... 85 3.1.2 Definition of menopause ...... 85 3.1.3 Decision tree for menopausal status ...... 86 3.1.4 Resolving inconsistencies for menopausal status ...... 94 3.1.5 References ...... 96 *HRFRGLQJ 3.2.1 Geocoding procedure used in the past ...... 96 3.2.2 Geocoding procedure to be used onwards from Survey 4 for the 1973-1978 cohort ...... 97 5HSODFLQJ550$ZLWK$5,$DVDPHDVXUHRIUXUDOLW\DQGUHPRWHQHVV 3.3.1 Background ...... 98 3.3.2 The problem with RRMA ...... 99 3.3.3 The solution ...... 100 3.3.4 Usage of ARIA+ ...... 100 3.3.5 Further reading ...... 102 3.3.6 References ...... 102 :DLVWFLUFXPIHUHQFHLQWKH FRKRUW 6XUYH\ 3.4.1 Background ...... 103 3.4.2 Usage ...... 104 3.4.3 References ...... 104 /LIH(YHQWVDQG3URSRUWLRQRI/LIH(YHQWV 3.5.1 Background ...... 105 3.5.2 Source items ...... 105 3.5.3 Notes regarding the method of standardisation ...... 106 3.5.4 SAS Code ...... 109 3.5.5 References ...... 109 0$,17(1$1&(2)&2+2576
ii 0DLQWHQDQFHVWUDWHJLHV 1DWLRQDO'HDWK,QGH[ &DXVHRI'HDWKFRGHV 8SGDWHRIVDPSOHDQGUHVSRQVHUDWHV 4.4.1 Survey 1, 1996 ...... 111 4.4.2 The sample for the longitudinal study ...... 111 '$7$/,1.$*( 3URJUHVVZLWKGDWDOLQNDJH 0$-255(32576 8VHDQGFRVWVRIPHGLFD WLRQVDQGR WKHUKHDOWKFDUHUHVR XUFHV )LQGLQJV IURPWKH$XVWUDOLDQ/RQJLWXGLQDO6WXG\RQ:RPHQ¶V+HDOWK 6.1.1 Aims of the report ...... 117 6.1.2 Summary of major findings ...... 118 6.1.3 Discussion ...... 122 ',66(0,1$7,212)678'<),1',1*6 :HEVLWH 3XEOLFDWLRQV 7.2.1 Conference proceedings published ...... 123 7.2.2 Papers published ...... 123 7.2.3 Papers accepted ...... 127 &RQIHUHQFHSUHVHQWDWLRQV 0HGLD 7.4.1 Press ...... 135 7.4.2 Television and radio ...... 136 $5&+,9,1* 352-(&767$)) $33(1',&(6 $SSHQGL[4XDUWHUO\XSGDWHV $SSHQGL[6XUYH\PDWHULDOV 10.2.1 1973-1978 cohort Pilot 5 brochure ...... 1 10.2.2 Evaluation forms for 1973-1978 cohort Pilot 5 ...... 1 10.2.3 1973-1978 cohort Pilot 5 reminder ...... 1 10.2.4 1973-1978 cohort Pilot 5 thank you ...... 1 10.2.5 1973-1978 cohort Survey 5 ...... 1 10.2.6 Change of Details insert ...... 1
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Table 2-1 Reporting of the 5th Survey of the 1946-1951 cohort ...... 64 Table 2-2 Response rates for the 5th Survey of the 1946-1951 cohort (at 31st August 2008) ...... 64 Table 2-3 Timetable for the 5th Survey of the 1921-1926 cohort (at 10th October 2008) ...... 65 Table 2-4 Response rates from the 5th Survey of the 1921-1926 cohort (at 10th October 2008) ...... 65 Table 2-5 Timetable for the 5th Survey of the 1973-1978 Pilot cohort (at 10th October 2008) ...... 66 Table 2-6 Response rates from the 5th Survey of the 1973-1978 Pilot cohort (at 10th October 2008) ...... 67 Table 2-7 Details of all items in the 5th Pilot Survey of the 1973-1978 cohort, including all changes (deletions, additions) from the 4th Survey of the 1973-1978 cohort...... 68 Table 2-8 Deletions from 4th Survey to 5th Pilot Survey of the 1973-1978 cohort ...... 83 Table 3-1 Codes and category labels for menopause status ...... 86 Table 3-2 Menopausal status for women in the 1946-1951 cohort (from 1996- 2007) ...... 88 Table 3-3 Menopausal status of women in the 1946-1951 cohort who responded to all surveys (1996-2007) ...... 90 Table 3-4 Breakdown of ‘unclassifiable’ menopausal status (from the unclassifiable category in Table 1) redefined by using available information; Surveys 1 to 5 for the 1946-1951 cohort ...... 92 Table 3-5 Combined menopausal status with reduced ‘unclassifiable’ category for women in the 1946-1951 cohort ...... 93 Table 3-6 Final menopausal status for the 1946-1951 cohort after redefining as many ‘unclassifiable’ as possible using longitudinal data and logical arguments ...... 95 Table 3-7 Geocoding procedure ...... 97 Table 3-8 Total female population of Australia classified by RRMA (1991) and RRMA (1996) ...... 100 Table 3-9 Diabetes and RRMA frequencies (row per cents) ...... 101 Table 3-10 Diabetes and ARIA+ frequencies (row per cents) ...... 101 Table 3-11 Responses to Q56: What is your waist circumference? Before conversion and corrections...... 103 Table 3-12 Analysis of women who responded to Q56 using both inches and centimetres...... 104 Table 3-13 Summary of responses to Q56 after conversion and corrections ...... 104 Table 3-14 Waist circumference risk categories, 1946-1951 cohort ...... 104 Table 3-15 Live event items common to all surveys for the 1973-1978 cohort ...... 107 Table 3-16 Life event items common to all surveys for the 1946-1951 cohort...... 108 Table 4-1 Confirmed deaths with and without COD codes by year of matching ...... 110 Table 4-2 Sociodemographic characteristics of the 1973-1978 cohort, the 1946- 1951 cohort and the 1921-1926 cohort and for women of the same age in the general population (ABS Census, 1996)...... 112 Table 4-3 Participation and retention of 1973-1978 cohort...... 113 Table 4-4 Participation and retention of 13 716 women in the 1946-1951 cohort who were 45-50 at Survey 1 in 1996...... 114 Table 4-5 Participation and retention of the 1921-1926 cohort of women ...... 115 Table 6-1 Schedule of Surveys for the Australian Longitudinal Study on Women’s Health ...... 117
iv /,672)),*85(6
Figure 3-1 Flow chart for menopausal status ...... 87 Figure 3-2 Menopausal status of women in the 1946-1951 cohort (1996-2007) ...... 89 Figure 3-3 Menopausal status of women from the 1946-1951 cohort who responded to all 5 surveys (1996-2007) ...... 91 Figure 3-4 Step 6 of the geocoding procedure ...... 98
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1. This report covers the six-month period from July to December 2008.
2. The cohorts of women in the Study have been renamed according to their birth years. The new cohort names are more precise and informative, do not rely on their relationship with the other cohorts, and will not change their meaning or relevance over time.
3UHYLRXVFRKRUWQDPH 1HZFRKRUWQDPH EDVHGRQ\HDUVRIELUWK 3. Survey 5 for the 1921-1926 cohort was mailed to 6998 participants on 17th March 2008. As at 10th November 2008, 77% of the surveys have been received. 4. Preparation has commenced for Survey 5 of the 1973-1978 cohort, scheduled to be mailed in March 2009. A pilot survey was sent to 290 participants on 28th August 2008. As at 10th November 2008, 46% of the pilot surveys have been returned. Follow-up of outstanding pilot surveys is in progress, and refinement of the survey questions for Survey 5 for the 1973-1978 cohort will continue into 2009. 5. A number of important methodological issues have been examined. Categories of menopause status have been defined, and the methods used by ALSWH to classify participants into these categories have been documented. There has been extensive work regarding accurate recording of area of residence, with a change in geocoding procedures to be used from the 1973-1978 cohort onwards, and the adoption of ARIA+ as the preferred measure of accessibility/remoteness for area of residence. Further work has also examined waist circumference in the 1946-1951 cohort at Survey 5, and the questions relating to life events. 6. ALSWH has now received ethical approval to link the ALSWH survey data with health information from the Medicare database from 1996 and the Pharmaceutical Benefits Scheme from 2002 without the need to ask for individual consent. 7. A major report has been prepared for the Department of Health and Ageing on the use and costs of medications and other health care resources amongst Australian women. Using linked data from 1995-2005, this report demonstrated the usefulness of data linkage. It examined the use and costs of medications and other health care resources, focusing on medications for depression, diabetes, gastric reflux and other common conditions, long-term use of medications, the impact of new health care items such as the 75+ Health Assessment and the Diabetes Annual Cycle of Care, and the use of complementary and alternative medical care. 8. Sixteen papers have been published or accepted for publication in national and international scientific journals during the reporting period. Forty presentations have been made to scientific and professional audiences both in Australia and internationally. Twenty-three postgraduate students are currently working on aspects of the project. vi &2//$%25$7,9(5(6($5&+$&7,9,7,(6 6FLHQWLILFPHHWLQJVDQGWHOHFRQIHUHQFHVDPRQJUHVHDUFK WHDP The Steering Committee is responsible for the overall direction of activities and resources to ensure that timelines and deliverables are met. Meetings and teleconferences are conducted at least once a month among the Steering Committee, with agendas, notes and minutes circulated to all investigators. Steering Committee membership is flexible and decided on an annual basis, so that a group of at least six investigators is involved at this level at any one time. The current Steering Committee members are: x Professor Annette Dobson (Chair) x Professor Julie Byles x Professor Christina Lee x Professor Wendy Brown x Assoc. Professor Nancy Pachana x Dr Deborah Loxton x Dr Jayne Lucke x Dr Leigh Tooth Steering Committee meetings during the reporting period have been held by teleconference on 18th June, 20th August, 17th September, 15th October and 10th December, and a face-to- face meeting was held in Brisbane on 10th November. The Data Management Group is responsible for all technical issues involving data quality, derivation of variables, checking and cleaning of data sets, linkage, and archiving. The group is chaired by David Fitzgerald (Data Manager – Surveys) with current members including Professor Annette Dobson (Study Director), Professor Julie Byles (Study Co-Director), Deborah Loxton (Project Manager), Jayne Lucke (Senior Research Fellow), Anna Graves (Data Manager – Cohorts), and project statisticians and other staff including Xenia Dolja- Gore, Richard Gibson, Richard Hockey, Jenny Powers, Melanie Watson, Danielle Herbert, Cath Chojenta, Sam Brilleman, Nelufa Begum and Elizabeth Kent. A quarterly update is provided to all investigators, staff, students, collaborators and others with an interest in the progress of the project. Quarterly updates for this reporting period are shown in Appendix 2. 1 1HZUHVHDUFKILQGLQJV &XUUHQWSURMHFWV Project: A104 Health costs of inactivity and overweight ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson Collaborative Investigator: x Richard Hockey (School of Population Health, University of Queensland) This study aims to quantify the relationships between physical activity, Body Mass Index (BMI) and Medicare and Pharmaceutical Benefits schemes (MBS and PBS) costs in the 1946-1951 and 1921-1926 cohorts of women participating in the Australian Longitudinal Study on Women’s Health, and to estimate the potential population cost savings of increasing physical activity and decreasing BMI in sedentary women. Analyses to date indicate that lower physical activity and higher BMI are associated with small individual, but significant population increases in healthcare costs. At the population level there would be significant cost savings if all sedentary mid-age and older women achieved at least low levels of physical activity, even if their BMI did not change. Greater investment by governments in ‘activating’ mid-age and older women appears to be a good public health strategy for reducing future healthcare costs. Investigators plan to further examine the relationships between both MBS and PBS costs in the 1946-1951 and 1921-1926 cohorts, and extend their work to include prospective analyses, with the outcome being the most recent costs for each cohort. A presentation on this work was made at the International Conference on Physical Activity and Public Health in Amsterdam in April 2008. Project: A137 Physical activity in Australian women ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson x Professor Julie Byles Collaborative Investigators: x Dr Kristiann Heesch (School of Human Movement Studies, University of Queensland) x Dr Yvette Miller (School of Human Movement Studies, University of Queensland) x Dr Nicola Burton (School of Human Movement Studies, University of Queensland) x Richard Hockey (School of Population Health, University of Queensland) Funding Source: Office for Women (Department of Families, Community Services and Indigenous Affairs), NHMRC program grant, NHMRC capacity building grant This project examined the associations between physical activity and health in mid-aged and older women in Australia and was conducted in several stages. The first involved a literature review of the evidence from prospective studies published since 1996 that examined physical activity and health outcomes in women. This found evidence that physical activity provided a protective effect against cardiovascular disease, type 2 2 diabetes, breast cancer, colon cancer, bladder cancer, endometrial cancer, poor psychological well being, and cognitive decline. Mixed evidence of associations between physical activity and gestational diabetes, pancreatic cancer, injury, depressive symptoms, and reproductive health outcomes was found, and no evidence was found of associations between physical activity and renal cell carcinoma, lung cancer, and osteoarthritis. The review also examined the amount of physical activity required for health benefits in mid- age and older women. While 150 minutes of moderate intensity physical activity per week (600 MET. mins) was associated with a range of health benefits, benefits in some areas (e.g. diabetes) were also seen in women who reported only 60 minutes per week (240 MET. mins). It may be necessary to accumulate greater amounts of physical activity to prevent some conditions, such as breast and colon cancer. There was little evidence to suggest that mid- age and older women will gain additional health benefits from vigorous physical activity, above those seen with brisk walking or moderate intensity physical activity, after adjustment for total energy expenditure. The second stage focused on new data from the ALSWH, and the proportion of Australian women who are currently achieving sufficient physical activity for health benefit. The proportion of women in the 1946-1951 cohort meeting or exceeding the National Physical Activity Guidelines (i.e. active) increased from 2001 (45%) to 2004 (54%); this was primarily attributable to walking. Between 2001 and 2004, approximately one third were consistently active, 18% decreased their physical activity, and 26% increased their physical activity. The proportion of active women in the 1921-1926 cohort declined from 34 to 30% between 1999 (when they were 73-78 years old) and 2005 (when they were 79-84 years old). The proportion of those who were sedentary increased from 31 to 44%. During this same period, 26% decreased and 16% increased their physical activity. The final stage included new analyses from the ALSWH data on the relationships between physical activity and selected health outcomes in the 1946-1951 cohort and the 1921-1926 cohort. Changes in physical activity were not related to menopausal symptoms in the 1946- 1951 cohort. Among the women in the 1921-1926 cohort, very low, low, moderate and high levels of activity (75+ mins/week) were associated with lower anxiety and depression scores. Memory complaints were slightly less likely among women in the 1921-1926 cohort who reported high levels of activity (i.e. 60+ mins/day). High levels of physical activity were associated with reduced risk of falls, and of broken or fractured bones in those who had not had a previous serious fall injury. Overall physical and mental well-being scores were significantly higher in women from the 1946-1951 cohort and the 1921-1926 cohort who were consistently active than in those who were consistently sedentary. Physical activity was inversely associated with healthcare costs in both cohorts, with the greatest differences being between sedentary women and those doing low levels of activity. A report on this work was submitted to the Department of Families, Housing, Community Services and Indigenous Affairs (FAHCSIA) in September 2007, was launched on 14th November 2008. The report is available at the FAHCSIA website:. http://www.ofw.facs.gov.au/publications/physical_activity/default.htm Findings from this work were presented at the Sixth National Physical Activity Conference in Adelaide, 2007. In 2008 one paper has been published in the Journal of Epidemiology and Community Health, and several have been submitted to journals including Preventive Medicine and the Journal of Rheumatology. 3 Project: A165 Exploratory analyses of relationships between physical activity and reproductive health and reproductive health symptoms in young and mid-age women ALSWH Investigator: x Professor Wendy Brown Collaborative Investigators: x Dr Yvette Miller (School of Psychology, University of Queensland) x Dr Mireille van Poppel (Department of Public and Occupational Health, Free University Amsterdam Medical School) The first phase of this study assessed the relationship between changes in physical activity and self-reported menopause-related vasomotor, somatic and psychological symptoms. Data were from Surveys 3 (2001) and 4 (2004) of the 1946-1951 cohort (N=3330). Results indicated that physical activity was not associated with total menopausal symptoms, or with vasomotor or psychological symptoms. A weak association with somatic symptoms was found. Weight gain was associated with increased total, vasomotor and somatic symptoms. Weight loss was associated with a reduction in total and vasomotor symptoms. It was concluded that changes in physical activity were not related to vasomotor or psychological symptoms, and only marginally to somatic symptoms. Changes in weight showed a stronger relationship with menopausal symptoms. A second phase examined the relationships between physical activity and menstrual symptoms in the 1973-1978 cohort. Analysis has been completed, and a paper is being written with collaborators Dr Hidde van der Ploeg and Professor Adrian Bauman from Sydney University. In addition, in 2008 a paper on menstrual symptoms was published in Menopause – Journal of the North American Menopause Society. A presentation on this project was made at the 6th Annual Conference of the International Society of Behavioural Nutrition and Physical Activity in Norway in 2007. Project: A171 Health costs of poor psychological health and inactivity ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson Collaborative Investigators: x Dr Nicola Burton (School of Human Movement Studies, University of Queensland) x Dr Kylie Ball (School of Exercise and Nutrition Sciences, Deakin University) x Richard Hockey (School of Population Health, University of Queensland) The aims of this study are to quantify the relationships between physical activity, poor psychological health and Medicare costs in the 1946-1951 and 1921-1926 cohorts of women participating in Australian Longitudinal Study on Women’s Health, and to estimate the potential population cost savings of increasing physical activity and decreasing poor psychological health in sedentary women. Planning for this project is underway, and preliminary examination of the data has commenced. 4 Project: A199 Weekend warriors: Frequency of physical activity and selected health outcomes in mid-age and older women ALSWH Investigator: x Professor Wendy Brown Collaborative Investigators: x Dr Kristi Heesch (School of Human Movement Studies, University of Queensland) x Paul Chang (School of Human Movement Studies, University of Queensland) Recent research suggests the benefits of 'accumulating' the recommended dose of physical activity (150 mins of moderate intensity/week) vary according to the frequency of exercise. This study will examine the association between frequency of physical activity and both hypertension and diabetes in the 1946-1951 and 1921-1926 cohorts. More frequent activity is expected to be associated with greater reduction in risk of health outcomes, than the same amount of activity accumulated in fewer sessions. For example, walking five days a week for 30 mins is expected to be more beneficial than walking once a week for 150 minutes (as occurs when playing golf and other ‘weekend warrior’ sports). Initial analyses have been conducted and work is continuing with data from the 1946-1951 cohort. Plans to work with data from the 1921-1926 cohort have been abandoned. Project: A200 Changes in prevalence estimates for physical inactivity and smoking over a 10 year period and associated impact on estimates of population attributable risk from these behaviours ALSWH Investigator: x Professor Wendy Brown Collaborative Investigators: x Dr Kristi Heesch (School of Human Movement Studies, University of Queensland) x Professor Adrian Bauman (School of Community Medicine, University of New South Wales) Funding Source: NHMRC program grant There is debate in the literature about the relative population attributable risks of smoking and physical inactivity (PIA). The aim of this study is to assess changes in the prevalence of physical activity and smoking over time in the 1973-1978 and 1946-1951 cohorts, in order to assess the changing population attributable risk of these behaviours over a 10 year period. It is expected that as the prevalence of inactivity increases and the prevalence of smoking decreases, the population attributable risk of these behaviours in young women will 'swap' - that is, PIA will become more important than smoking over a ten year period. Preliminary consideration of the data required for this study has commenced. Project: A201 Does sitting cause weight gain? ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson Collaborative Investigators: x Melanie Watson (School of Population Health, University of Queensland) x Dr Jannique van Uffelen (School of Human Movement Studies, University of Queensland) Funding Source: NHMRC program grant Previous analyses in the Australian Longitudinal Study on Women’s Health cohort have shown that sitting time is a predictor of weight gain in the 1946-1951 cohort. The objectives of the present study are to further examine the relationships between changes in sitting time 5 and weight, using both cross sectional and prospective analyses. Exploratory analyses in the 1946-1951 cohort have been completed using data from Surveys 3 and 4. Unadjusted analyses show that there is a cross sectional association between weight and sitting time at both surveys. There are also associations between increases in sitting time and increases in weight. The analysis for this project has been finalised. Results have been presented at the International Conference on Physical Activity and Public health, Amsterdam 2008, and the International Conference on Behavioural Medicine, Tokyo 2008. A paper is being prepared for submission to Obesity. Project: A202 Women in their 70s: Weight, weight change and health related quality of life ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson x Assoc. Professor Gita Mishra Collaborative Investigator: x Dr Jannique van Uffelen (School of Human Movement Studies, University of Queensland) Even though the relationships between weight, weight change, a variety of chronic health conditions and quality of life (QoL) in the elderly have been described well in the literature, only scarce information about the relationships between weight change and health related quality of life is available. This project will examine both the cross sectional and prospective relationships between weight, weight change and health related QoL in older women. A structural approach including several stages will be followed. The first stages will be exploratory and describe 1) cross sectional relationships between weight and QoL; and 2) the changes in weight and QoL over multiple measurements. In stage two, the relationships between weight and change in QoL, change in weight and QoL, and change in both weight and QoL will be addressed. Stage three will be modelling with the variables that are known to be determinants of QoL, such as physical activity level, depression, and number of chronic diseases. The primary question to be answered is: are weight or weight change predictors of health related QoL in older women? The main variables to be used are: weight/ BMI, health related QoL (SF-36), lifestyle data (e.g. smoking/ physical activity level/ dietary intake), and depression (CES-D) (as depression may be an important confounder of the relationship between BMI and well-being). The objectives are to examine relationships between weight and QoL, to describe patterns of change in weight and QoL over time, and to quantify the role of weight or change in weight as a predictor of QoL and QoL change (unadjusted and adjusted for determinants). Investigators have met to discuss the analyses, and further work has been put on hold pending a review of progress with project A203. 6 Project: A203 What is an optimal weight for women aged 70-75? ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson Collaborative Investigators: x Dr Jannique van Uffelen (School of Human Movement Studies, University of Queensland) x Dr Janneke Berecki (School of Population Health, University of Queensland) Current recommendations advise a BMI range of 20-25 for optimal health. However, information about the optimal BMI range in older adults in particular is scarce. Moreover the ‘optimal range’ may differ for various health conditions (e.g. osteoporosis, diabetes, depression, arthritis, heart disease and cancer). The objectives of this study are to examine the prospective associations between weight (BMI) in the 1921-1926 cohort at Survey 1 and incidence of chronic disease over 9 years and to recommend an optimal weight (BMI) range for each condition. The main variables used are: weight/BMI at Survey 1, lifestyle data (e.g. smoking/ physical activity level/ dietary intake) and chronic diseases at the following surveys. Analyses have been completed, and a manuscript is in preparation. Project: A215 The contribution of participation in sport and physical activity on the well-being of women ALSWH Investigator: x Professor Wendy Brown Collaborative Investigators: x Dr Rochelle Eime (School of Human Movement and Sport Sciences, University of Ballarat) x Dr Warwick Payne (School of Human Movement and Sport Sciences, University of Ballarat) x Dr Jack Harvey (School of Human Movement and Sport Sciences, University of Ballarat) This research project involved comparing ALSWH data with data collected from female participants who were involved in sport and physical activity to examine the contribution of participation in sport and physical activity on the well-being of women. Analysis is complete and a paper is in draft form. Project: A220 Does one hour of physical activity a day prevent weight gain in adult women? ALSWH Investigator: x Professor Wendy Brown Collaborative Investigator: x Paul Chang (School of Human Movement Studies, University of Queensland) Funding Source: NHMRC program grant This study examined changes in physical activity (PA) and weight, and relationships between these variables, over the course of the first four surveys of the 1921-1926 and 1946-1951 cohorts. The main research question was: ‘Does one hour of physical activity per week prevent weight gain?’ Linear regression was used to examine the relationship between PA (summary scores from four surveys) and weight change from Survey 1 to 4 in the whole cohort and in women categorised on the basis of weight change as: gainers; maintainers; or losers. Variables shown to be associated with weight and PA were included as covariates (smoking, education, 7 occupation, marital status, country of birth, sitting time, energy intake and use of oral contraceptive pill). The analysis for this study is completed and manuscript preparation will commence in late 2008. An oral presentation on this project was given at the Sports Medicine Australia 37th Annual State Conference in Surfers Paradise, 2008. Project: A227 Prevalence and impact of foot pain in older women ALSWH Investigators: x Professor Wendy Brown Collaborative Investigators: x Assoc. Professor Hylton Menz (Musculoskeletal Research Centre, LaTrobe University) x Elizabeth Barr (International Diabetes Institute) The aims of this project are to explore the prevalence, correlates and impact of foot pain among women in the 1921-1926 cohort; and the predictors of podiatry utilisation in women with foot pain The question ‘In the last 12 months have you had problems with one or both feet?’ will be used to address the first aim. This variable will be explored in relation to demographic factors, BMI and medical conditions to determine the characteristics of older women who have foot pain. To determine the impact of foot pain, comparisons will be made between those with and without foot pain on each subscale of the SF-36 and the Goldberg Anxiety and Depression Scale. The questions ‘Did you seek help for problems with one or both feet?’, and ‘Have you consulted any of the following people for your own health in the last 12 months?’ will be used to address the second aim. By examining associations of these variables with demographic factors and medical conditions, it will be possible to ascertain the typical profile of an older woman who accesses podiatry services, and perhaps more importantly, to determine the number of older women with foot pain who do not access health services for treatment. Project: W053 The validity of self reported height, weight, and physical activity among mid-age women ALSWH Investigators: x Professor Wendy Brown x Professor Annette Dobson Collaborative Investigators: x Dr Nicola Burton (School of Human Movement Studies, University of Queensland) x Dr Yvette Miller (School of Psychology, University of Queensland) x Dr Alison Marshall (School of Public Health, Queensland University of Technology) Funding Source: ALSWH, NHMRC program grant, NHMRC capacity building grant This study aims to compare self-reported height, weight and physical activity (PA) with objective measurements, and to determine the extent of participant misreporting in relation to BMI, health status, and sociodemographic characteristics. A secondary aim of the project is to obtain data on key PA indicators, such as the average number of steps taken per day (weekdays and weekends), frequency of incidental PA, and average time spent sitting per day. This study is limited to the 1946-1951 cohort of ALSWH participants living in Brisbane. Recruitment and a sample of data collection (telephone recruitment; mail surveys; and individual home visits to deliver PA monitors and logbooks, and assess height and weight; N=159) is complete. 8 Initial analyses have been completed and a manuscript (on the reliability and validity of the PA measures) has been accepted by the Australia and New Zealand Journal of Public Health. A second manuscript (reliability and validity of the BMI measure) is in preparation and work has commenced on the reliability and validity of the sitting time questions. An additional analysis exploring the associations between occupational sitting time, leisure activity and BMI has been completed, and a paper is in revision. A presentation was made at the American College of Sports Medicine 2008 Annual Meeting. Project: W059 Longitudinal study of sleeping difficulty and medication use among older women ALSWH Investigators: x Professor Julie Byles x Assoc. Professor Gita Mishra This work will extend our previous research into insomnia and the impact of sleeping difficulty on women’s quality of life. The analysis will involve three main objectives: x To obtain more data on medication use and data on longer-term health outcomes (survival, SF-36) and sleeping medication and undertake longitudinal analysis of differences in survival and quality of life for women with sleeping difficulties and women using sleeping medications. x To analyse qualitative data on sleeping medications and sleep. Project: A053 Volunteering and older women ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Dr Lynne Parkinson (Research Centre for Gender, Health and Ageing, University of Newcastle) x Assoc. Professor David Sibbritt (School of Medicine and Public Health,University of Newcastle) x Richard Gibson (Research Centre for Gender, Health and Ageing, University of Newcastle) x Dr Jeni Warburton (Australasian Centre on Ageing, University of Queensland) A recent review of the international literature proposed that a number of health indicators such as morbidity rates, functional health indices, self-reported health and life satisfaction may be affected by social involvement, such as volunteering. This evidence suggests that volunteering may be associated with better health. While it is very difficult to assert a causal relationship, there are suggestions that being active in the community through volunteering helps keep people healthy psychologically, and even physically. This may be particularly important for older women, who benefit from the social aspects associated with volunteering, and who are more likely to have a long term commitment as volunteers. However, some recent Australian evidence has suggested that volunteering might actually be bad for your health because it can be a stressful, time-consuming activity. Therefore the broad aim of this research was to explore the relationship between health and volunteering in older women, from a secondary analysis of Australian Longitudinal Study on Women’s Health data, across three survey periods. Volunteers were defined as those who undertook regular community or organisational volunteering (e.g. fundraising, community welfare, church activities, organising groups or classes), every day, every week, or every month. Those who never did this type of activity, or did it less than once a month, were defined as non-volunteers. Thirty-seven percent of women reported volunteering (2% every day, 20% every week, and 15% every month). Volunteers were more likely to live in a rural or remote area than in an urban area. Volunteers were also more likely to be younger, more educated, Australian born, to live alone, have private health insurance, be of English speaking background, to have income besides 9 the pension, and to report managing on their income, than non-volunteers. Volunteers rated their health as excellent to very good more often than did non-volunteers. Volunteers were also more likely to be healthier than non-volunteers on a variety of physical measures (health problems in last 12 months, GP visits in last 12 months, satisfaction with physical ability, eyesight, exercise level and alcohol intake) and psychosocial measures (depression, major personal illness or injury in last 12 months, major decline in health of spouse or partner in last 12 months, major life events last 12 months, social connections). Project: A071 Utilisation of oral health care services by women ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Assoc. Professor Deborah Cockrell (School of Medicine and Public Health, University of Newcastle) The aims of this research were to report the prevalence of consultation with a dentist by Australian women and to identify factors associated with consultation with a dentist. The analysis was conducted on information obtained from Survey 2 of 12 338 women from the 1946-1951 cohort (aged 47-52 years in 1998) and 10 434 women from the 1921-1926 cohort (aged 73-78 years in 1999). Women in the 1946-1951 cohort were more likely to have consulted a dentist in the previous year (57%) than women in the 1921-1926 cohort (35%). In both age groups, those who consulted a dentist were more likely to live in an urban area, be better educated, have a greater ability to manage on their income, and be in better physical health. They also tended to be higher users of both traditional and alternative health services. This study has highlighted not only the association between oral health care and other aspects of good health, but also a major source of inequity in the community. Given the breadth of evidence to support the importance of regular dental care in protecting other aspects of health, the under use of dental services by certain socioeconomic groups may be a major factor in health inequity. The final paper for this project is in preparation and covers the longitudinal analysis of the 1921-1926 cohort women’s consultation with a dentist over 3 survey periods (1999, 2002, and 2005). The findings from this work are that the percentage of women who consulted a dentist in the years 1999, 2002, and 2005 were 35%, 36%, and 37% respectively. Women were more likely to consult with a dentist if they lived in urban areas (OR=1.47; 95% CI: 1.36-1.58), were non-smokers (OR=1.61; 95% CI: 1.34-1.94), did not have diabetes (OR=1.25; 95% CI: 1.12- 1.40), did not have heart disease (OR=1.13; 95% CI: 1.04-1.24), had better physical health (OR=1.02;95% CI: 1.01-1.03) for every 5 point increase in SF-36 physical functioning score. Women were less likely to consult with a dentist if they were separated, divorced or widowed (OR=0.87; 95% CI: 0.81-0.93), found it difficult to live on their income some of the time (OR=0.83; 95% CI: 075-0.91), had no formal education (OR=0.25; 95% CI: 0.21-0.31), did not require home maintenance service (OR=0.81; 95% CI: 0.76-0.86). This study suggests that access to dentists and cost of consultations appear to be significant factors influencing visits to a dentist by elderly Australian women. In addition, those women who are in poorer health are less likely to consult with a dentist. Project: A077 Use of enhanced primary care services (EPC) by older Australian women ALSWH Investigators: x Professor Julie Byles x Dr Anne Young Collaborative Investigators: x Assoc. Professor Catherine D’este (Centre for Military and Veterans’ Health, University of Queensland) x Dr Virginia Wheway (Research Centre for Gender, Health and Ageing, University of Newcastle) 10 In November 1999, the Australian government introduced Medical Benefits Schedule item numbers for health assessments for people aged 75 years and over (items 700, 702). Assessments are to be conducted annually by a general practitioner or by another health care provider working on behalf of the general practitioner, and include a review of the person’s health and physical, psychological and social function and consideration of whether preventative health care and education should be offered to improve the person’s current and future function. The ALSWH includes 4646 women who were aged 75 to 78 years when the EPC items were introduced and who provided permission to access their Medicare records. Of these women, 58% had at least one health assessment between November 1999 and the end of 2005. Repeat assessments were less common: 40% of women had two or more assessments, 26% had three or more assessments, 14% had four or more, 6% had five or more, 2% had six or more, and only 3 women (0.1%) had an assessment every year since the introduction. Women who had at least one health assessment were those who made more visits to the GP, and who were more likely to have reported having hypertension, to be taking more than five prescribed medications, and to have been admitted to hospital in the 12 months prior to Survey 2 (before the introduction of the item in 1999). Among women who did not report heart disease, cancer, diabetes, or asthma/bronchitis, women who had at least one health assessment were more likely to have been born in Australia and more likely to live in rural areas when compared with women who did not have an assessment. These differences were not apparent for women who had any one or more of these conditions. Project: A101 Change in health status and health care use for women who have not had health assessments ALSWH Investigators: x Professor Julie Byles x Dr Anne Young Collaborative Investigator: x Xenia Dolja-Gore (Research Centre for Gender, Health and Ageing, University of Newcastle) This study will explore changes in health status and health care use for women who have and have not had health assessments. Previous analysis of data from the oldest cohort indicate that around one third of the women have had at least one health assessment in the two years following the introduction of these items in November 1999. In this analysis there were few pre-assessment differences for women who did and did not take up the assessment items. This analysis will explore the extent to which the uptake of assessments since 1999 is associated with subsequent changes in health and healthcare use measured in Survey 3 of the 1921-1926 cohort. Survival and health-related quality of life scores for women who were eligible for the 75+ assessment were examined according to whether or not the women had a health assessment since 1999 and whether or not they had a major condition (heart disease, cancer, diabetes, asthma/bronchitis). Health assessments had no great impact on survival. While there was a slight trend for women who had a health assessment to have better survival than women who had no assessments, interpretation of these data is difficult since assessments are dependent on survival. Among women who were still alive in 2004, there was no statistically significant difference between physical function scores for women who did and did not have health assessment. However, there was a small trend towards a lesser decline in scores for women having more than one assessment. There were no differences in SF-36 Mental Health sub- scale scores. 11 Project: A117B Further research on incontinence among women in Australia ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Cynthia Miller (Centre for Clinical Epidemiology and Biostatistics, University of Newcastle) x Assoc. Professor Pauline Chiarelli (School of Health Sciences, University of Newcastle) This study presents longitudinal data on the prevalence and incidence of incontinence among women in the 1921-1926 cohort, over nine years of follow-up. Over this time, 14.6% of the women in the study who had previously reported leaking urine ‘rarely’ or ‘never’ developed incontinence, and 27.2% of women participating in Survey 4 in 2005 reported leaking urine sometimes or often at that survey, with women being twice as likely to report incontinence at Survey 4 as they were six years earlier. Longitudinal models demonstrated association between incontinence and dementia, dissatisfaction with physical ability, falls to the ground, BMI, constipation, urinary tract infection, history of prolapse, and prolapse repair. Stroke, parity and hysterectomy, and number of visits to the general practitioner were less strongly associated with incontinence in the final longitudinal model. Incontinence was not significantly associated with area of residence, education, smoking, diabetes, attending support groups, or attending social groups. A revised version of a paper has been submitted to Age and Ageing for further review. Project: A127 Asthma amongst elderly women ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Professor Peter Gibson (Hunter Medical Research Institute) x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Ian Robinson (Research Centre for Gender, Health and Ageing, University of Newcastle) A question referring to asthma: ‘Have you been diagnosed or treated for asthma?’ has been included in all ALSWH surveys for all three cohorts and by Survey 4, around 30% of the 1973- 1978 cohort, 20% of the 1946-1951 cohort and 15% of the 1921-1926 cohort reported a diagnosis of asthma. Women from the 1921-1926 and 1946-1951 cohorts claiming for asthma medications (whether or not they reported having a diagnosis of asthma) were less likely to be married, and more likely to have difficulty managing on income than other women in the cohort. Women in the 1946-1951 cohort claiming for asthma medications (whether or not they reported the diagnosis of asthma) had lower levels of education. These effects were not as apparent for women in the 1921-1926 cohort. Across all cohorts, women with no self-reported asthma and no asthma medications had the lowest probability of reporting other conditions at Survey 4. Women who claimed for asthma medications were more likely to have depression than those who did not claim for asthma medications; similarly, depression was more common among women with asthma than among women without this condition. Among women in the 1973-1978 cohort and the 1921- 1926 cohort, back pain was also slightly more common among women with asthma than without, regardless of asthma medications; whereas for women in the 1946-1951 cohort, back pain was less common among women with asthma medications than among other women. Among women in the 1946-1951 cohort, heart disease and diabetes were more commonly reported by those identified as using asthma medications (regardless of self-reported 12 asthma). Similar results were observed for women in the 1921-1926 cohort, except there was no apparent difference in reporting of diabetes. Women in the 1973-1978 cohort were not asked if they had arthritis, but among women in the 1946-1951 cohort and 1921-1926 cohort, arthritis was most common among those with asthma (among 1921-1926 cohort) and among those with asthma and asthma medications (among 1946-1951 cohort). Women with PBS claims for asthma medications were more likely to report their health as fair or poor than women without medications. Similarly, women with asthma and medications were most likely to report fair or poor self-rated health (1946-1951 cohort and 1921-1926 cohort) and women with no asthma and no asthma medications were least likely to report only fair or poor health. Project: A133 Women and arthritis: The burden of suffering by older Australian women ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Dr Paul Kowal (World Health Organization) x Dr Lynne Parkinson (School of Medicine and Public Health, University of Newcastle) x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Mr Ian Robinson (School of Medicine and Public Health, University of Newcastle) Funding Source: Arthritis Australia and the Hunter Medical Research Institute The ALSWH survey question referring to arthritis asks about doctor-diagnosed arthritis. Although this includes all types of arthritis, osteoarthritis is expected to be the most common condition among women from the 1946-1951 cohort and the 1921-1926 cohort. Thirty-two per cent of 1946-1951 cohort women and 64% of the 1921-1926 cohort women reported having doctor-diagnosed arthritis by Survey 4 (in 2004 and 2005, respectively). x Not making any claims for arthritis medications was common among women with arthritis: 61% to 71% of 1946-1951 cohort women and 51% to 63% 1921-1926 cohort women who reported having arthritis did not make claims for arthritis medications across all years. x Most 1946-1951 cohort and 1921-1926 cohort women with doctor diagnosed arthritis and who had claims for arthritis medications, had claims for only one type of arthritis medication. x 1946-1951 cohort women who reported having arthritis and/or who had a claim for arthritis medication had lower levels of education and more difficulty managing on their income than women without arthritis or arthritis medication claims. x 1946-1951 cohort women with doctor-diagnosed arthritis and/or with claims for arthritis medication were more likely to be obese than those without claims. x Women with arthritis were more likely to report co-morbid conditions and poorer health and to score as depressed and anxious. Arthritis was associated with lower and decreasing scores for physical function and decreasing social functioning sub scales over time. The results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). A manuscript has been submitted to Age and Ageing for review. 13 Project: A149 Self-rated health, age and gender in longitudinal studies in Australia ALSWH Investigators: x Professor Julie Byles x Professor Annette Dobson Collaborative Investigator: x Professor Kaarin Anstey (Centre for Mental Health Research, Australian National University) Funding Source: Ageing Well Ageing Productively NHMRC grant There is now a large amount of data collected on ageing from Australian studies including the ALSWH. Through a project known as Dynamic Analyses to Optimise Ageing (DYNOPTA), the data from these studies are currently being examined and harmonised to investigate factors affecting health, including gender, as people age. The collaborative analysis of these data will greatly advance our knowledge of ageing in Australia. Project: A150A Adequacy and equity of treatment for depression among older Australian women ALSWH Investigators: x Professor Julie Byles x Dr Deborah Loxton Collaborative Investigators: x Dr Lynne Parkinson (Research Centre for Gender, Health and Ageing, University of Newcastle) x Richard Gibson (Research Centre for Gender, Health and Ageing, University of Newcastle) x Ian Robinson (Research Centre for Gender, Health and Ageing, University of Newcastle) Funding Source: Hunter Medical Research Institute grant Medications play an important role in the management of depression. In this study we examine claims to the Pharmaceutical Benefits Scheme (PBS) for ALSWH participants in the three age groups and those factors that are associated with claims for anti-depressant medications. The data are for women who have consented to the release of these data and who were alive and participating in the study in each calendar year 2003-2005. Medications for women in each cohort were grouped and described according to the Anatomical and Therapeutic Class (ATC) coding system developed by the World Health Organisation. Claims for nervous system drugs, particularly antidepressants were common among women born in 1973-1978 (used by 8%), 1946-1951 (14%), and 1921-1926 (18%). However not all women who reported a diagnosis of depression on the surveys were identified as having anti- depressant medications. Among women in the 1973-1978 cohort who reported a diagnosis of depression, 60% had no claims for any anti-depressant medication in 2005 and 40% had no claims at any time during the period 2002-2005. For women in the 1946-1951 cohort the corresponding percentages were 36% and 17%, and for women in the 1921-1926 cohort the percentages were 33% and 18%. Depression and claims for anti-depressant medications were associated with area of residence (women in rural areas were less likely to receive anti- depressant medications), marital status, socioeconomic status, health care use, and the presence of comorbid conditions such as arthritis, back pain and heart disease. Many women with depression continued to have claims for anti-depressant medications for long periods. Among those in the 1946-1951 and 1921-1926 cohorts, more than 50% had claims in both 2002 and 2005. Women in the 1973-1978 cohort were less likely to have claims in both periods, and were equally likely to cease, or take up anti-depressant medications, or to have no claims in either year. A significant improvement in scores on the SF-36 Mental Health Index was observed for women with self-reported depression who ceased anti-depressant medications between 2002 and 2005, indicating positive outcomes for women in this group. 14 A presentation from this project was made at the 2008 Population Health Congress in Brisbane. The results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). Project: A158 Use of the ‘polypill’ among older women ALSWH Investigators: x Professor Julie Byles x Dr Anne Young Collaborative Investigators: x Professor David Henry (School of Medicine and Public Health, University of Newcastle) x Dr Lynne Parkinson (School of Medicine and Public Health, University of Newcastle) Funding Source: University of Newcastle Strategic Pilot Research grant Cardiovascular diseases (CVD) are a major cause of morbidity and mortality among Australian women. CVD mainly comprises coronary heart disease, which leads to angina, heart attack and other heart conditions, and stroke. Many clinical trials provide evidence in support of the effectiveness of drug therapy in primary and secondary prevention of CVD. For instance, lipid lowering drugs (statins) can effectively reduce serum cholesterol, one of the major risk factors for coronary heart disease and stroke, and it is estimated that the use of these medications could reduced coronary heart disease by around 60% and stroke by around 17%. Anti-hypertensive agents that lower blood pressure (such as diuretics, beta- blockers, angiotensin converting enzyme inhibitors) could reduce around 40-50% of coronary heart disease and around 60% of stroke. Overall, it has been estimated that the combined effects of six preventive drugs in combination (three low-dose anti-hypertensives, a statin to lower cholesterol, aspirin, and folic acid) could prevent up to 88% of coronary heart disease and 80% of stroke. In this study we examined the prevalence of use of CVD chemoprophylaxis as ascertained from PBS data for women in the 1946-1951 and 1921-1926 cohorts. In both cohorts, angiotensin converting enzyme inhibitors (ACE)/angiotensin II receptor antagonists (AII) and statins were the most commonly identified class of CVD chemoprophylaxis. Statins were used by 14% of women in the 1946-1951 cohort and 39% of women in the 1921-1926 cohort. Use of these lipid lowering medications was more common among women reporting heart disease, diabetes, high blood pressure or stroke than among women who did not report these conditions. In the 1946-1951 cohort, only 10% of women with no history of any of these conditions were taking statins, whereas over 50% of women who had reported diabetes, stroke or heart disease were identified as using these medications. Among the 1921-1926 cohort, 30% of those who had not reported any of the conditions were using statins. In the 1946-1951 cohort, 30% of women were identified as taking any of the categories of CVD medications, and 10% were identified to be taking more than one agent; in the 1921- 1926 cohort 79% were taking at least one class of agent, and 52% were taking at least two classes in combination. The most common combination was the use of either an ACE inhibitor or angiotensin II receptor blocker in combination with a statin and with or without aspirin. Characteristics of women with at least one claim for CVD medications (thiazide, ACE/AII, beta blocker, statin) at any time from 2002 to 2005 were compared with women who had not been identified as having a claim for these medications. In this analysis CVD medications were more commonly used by women with higher body mass index, lower levels of education, more comorbidities (including diabetes), and fair or poorer self rated health. 15 The results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). Project: A166 Comparison of self-reported medications and PBS records ALSWH Investigators: x Professor Julie Byles x Dr Anne Young Collaborative Investigators: x Professor David Henry (School of Medicine and Public Health, University of Newcastle) x Dr Lynne Parkinson (School of Medicine and Public Health, University of Newcastle) Funding Source: University of Newcastle Strategic Pilot Research grant This study compared older women’s self-reported medication use as recorded on Survey 4 with PBS data for 4 687 participants who consented to the release of their MBS/PBS data. The agreement between these two sources of information was checked for particular classes of medication for common chronic conditions (insulin and analogues, oral blood glucose lowering drugs, anti-hypertensives, statins, aspirin and folic acid, anti-depressant medications, anxiolytics and hypnotics). For these medications prevalence of medication use was generally higher in PBS data except for aspirin intake. This could be accounted for by over the counter purchases of aspirin which do not appear in the PBS data. Specificity, the probability that a woman who is not taking a medication will not report this on her survey, was high for all medication use. Overall agreement and sensitivity (the probability that women identified as taking a medication according to PBS data reported this medication on the survey) were highest for glucose lowering drugs and lowest for nervous system medications. Positive and negative predictive values were generally high, except for aspirin and folic acid which can be purchased over-the-counter without prescription. In general, this analysis indicates good agreement between these two sources of medication information for most of the groups of medications assessed. Care must be taken when using PBS data as a source of information about drugs that can be bought over-the-counter or that are used as needed. Medications that are not covered under the PBS scheme will also be under-represented in PBS data and self-report is a better source of information on the use of these medicines. A manuscript is in preparation, and the results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). Project: A173 Transport for older women ALSWH Investigators: x Professor Julie Byles x Professor Annette Dobson Collaborative Investigators: x Dr Lynne Parkinson (Research Centre for Gender, Health and Ageing, University of Newcastle) x Richard Gibson (Research Centre for Gender, Health and Ageing, University of Newcastle) Among women in the 1921-1926 cohort in the ALSWH, driving is the major form of transport, especially for those in rural and remote areas. At Survey 3, 60% of the women in this cohort reported driving themselves as their main means of transport. The majority of these women (86%) also reported driving themselves as their main means of transport at Survey 4, but 10% 16 reported they were now being driven by someone else, and a small percentage were using taxis, buses and other options as their main means of transport. Change in main means of transport was not associated with Survey 3 area of residence; however women with lower levels of education were more likely to cease driving. Women were also more likely to cease driving if, at Survey 3, they reported taking five or more medications, being limited a lot in walking 100 metres, and if they had ever reported stroke or arthritis. Women were also more likely to cease driving if they had poor vision at Survey 3 (18% of those who ceased driving had poor vision at Survey 3, and 9% of those who continued driving had poor vision at Survey 3). There was no association between ceasing driving and change in marital status, or changes in difficulty in managing on income. Compared with women who continued driving, women who ceased driving as their main means of transport between surveys were more likely to report worse self-rated health and to needing help with daily tasks, and were less likely to have commenced caring for someone else. At Survey 4, women who ceased driving were more likely to report having made five or more GP visits, and to have made at least one specialist visit. They were less likely to be caring for someone else either in their own home or elsewhere. Women who ceased driving were also more likely to report trouble getting to places at night, getting to shops and services, and getting beyond their local neighbourhood. They were more likely to report that they had not been outside their home or outside their immediate neighbourhood, and that they had not been to movies, theatre etc, a sporting event, a restaurant, or attended a class or course. Work continues on this project, and further analyses, incorporating data from Survey 5 of the 1921-1926 cohort, are planned. Project: A175 Establishing common linear measures for the SF-36 for Australian women ALSWH Investigator: x Professor Julie Byles Collaborative Investigator: x Assoc. Professor Lindy Clemson (Faculty of Health Sciences, University of Sydney) x Professor Anita Bundy (Faculty of Health Sciences, University of Sydney) The aim of this analysis is to establish common linear measures for the SF-36 through Rash modelling, using Winsteps software. The analysis is currently in progress. The sample has been randomly divided into two groups with the first group being used to devise the measures and the second group used to validate the measures produced from the modelling. We are now applying a partial credit rating to explore the effectiveness of the category rating scales. We will also establish the validity of these measures for use with different cohorts and different subgroups within cohorts, and the item functioning over time. Subgroups will include people with different conditions and levels of comorbidities, and with and without need for help with daily tasks. 17 Project: A178 Regulatory and community response to discredited drugs ALSWH Investigators: x Professor Julie Byles x Dr Anne Young x Dr Lynne Parkinson Collaborative Investigators: x Professor David Henry (School of Health Sciences, University of Newcastle) x Xenia Dolja-Gore (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Richard Gibson (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Ian Robertson (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Dr Evan Doran (School of Medicine and Public Health, University of Newcastle) x Andrew Searles (Hunter Valley Research Foundation) x Dr Jane Robertson (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Dr Paul Kowal (World Health Organization) x Professor Glen Salkeld (School of Public Health, University of Sydney) x Dr Jennifer Stewart-Williams (School of Medicine and Public Health, University of Newcastle) Funding Source: NHMRC project grant This project will examine changes in medication use following negative publicity, revised advice, and withdrawal of key medications. The study focuses on two recent cases: revisions to advice regarding hormone replacement therapy; and withdrawal of coxib medications. Cyclooxygenase-2 inhibitors (commonly called coxibs), which include medicines such as rofecoxib (Vioxx), celecoxib (Celebrex), and meloxicam (Mobic/Movalis), were first approved for marketing in Australia in 1998, and were listed on the Pharmaceutical Benefits Scheme (PBS) from 2000. Rofecoxib was withdrawn by the manufacturer world-wide in September 2004 following concerns for the safety of this medication. Similar concerns were associated with other coxibs, but these medicines were not withdrawn. Rather, the Therapeutic Goods Administration (TGA) required manufacturers to place explicit warnings in product information about increased risk of CVD adverse events and advised that all medicines in the class of coxibs should be regarded as having an increased CVD risk. Researchers are analysing the changes in coxib and other non-steroidal anti-inflammatory drug prescriptions over time, and the characteristics of those women in the 1946-1951 and 1921-1926 cohorts whose prescriptions continued and those whose did not, Early results of the analysis for the 1921- 1926 cohort reveals evidence of effects of these regulatory actions within PBS data for women with arthritis over the period 2002 to 2005. The sudden cessation of rofecoxib availability in the fourth quarter of 2004 was at first matched by a rise in celecoxib and meloxicam prescriptions. However, this level of use dropped in the first quarter of 2005 and stayed comparatively steady for the remainder of 2005. Women in the 1921-1926 cohort with arthritis who remained on coxibs for 2003 (before withdrawal of rofecoxib) and 2005 (after withdrawal) were more likely to be partnered, less likely to have difficulty managing on income or be caring for someone who lives with them, and less likely to drink rarely or not at all, than women who had never used this medication (in either year) or who had ceased use by 2005. Further analysis of these effects and the effects for women in the 1946-1951 cohort with arthritis are in progress. 18 A sub-study involving in-depth interviews with women with arthritis is also underway. Advice regarding the use of hormone replacement therapy was modified in 2004 in response to evidence regarding increased risk of breast cancer for women using these therapies. This project will also analyse the change in HRT use among women in the 1946-1951 and 1921- 1926 cohorts that occurred since the announcement of these findings. The results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). Project: A188 Intake of fruit and vegetables and its association with socioeconomic status and health outcomes ALSWH Investigator: x Professor Julie Byles Collaborative Investigator: x Dr Zumin Shi (Research Centre for Gender, Health and Ageing, University of Newcastle) Funding Source: NSW Health fellowship (NIPH-HMRI) Fruits and vegetables are essential components of a healthy diet. However, only limited information is available about the fruit and vegetable intake of older women. This study describes the sociodemographic and health correlates of intake of fruit and vegetables among two large cohorts of Australian women – one group aged 50-55 years and one aged 79-84 years. Almost all women ate some fruit and vegetables each day. In each cohort, around 8- 9% of the women ate five or more serves of vegetables each day, and 30% ate four or more serves each day. In the 1946-1951 cohort, around 60% of the women ate two or more serves of fruit each day, and the corresponding proportion for the 1921-1926 cohort was 70%. Around 7-8% of each cohort could be considered to eat the national recommended intake of two serves of fruit and five serves of vegetables. Eating higher levels of fruit and vegetables was associated with country of birth, education, marital status, and with functional abilities and oral health. Longitudinal analyses describe trends in BMI, health-related quality of life and survival according to women’s fruit and vegetable intakes. Investigators hope to extend analyses to include data from Survey 5 of the 1921-1926 cohort, as this will be relevant to future research (Major Report E). Material from this project will appear as a section in a book, Nutrition for the Middle-Aged and Elderly. Project: A206 Changes in workforce participation among mid-age Australian women: The impact of socioeconomic, behavioural, environmental and health related factors ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Dr Sabrina Pitt (University of Newcastle) x Assoc. Professor Deborah Schofield (School of Public Health, University of Sydney) x Arul Earnest (School of Public Health, University of Sydney) The aims of this project are: x To examine the transitions of women in the 1946-1951 cohort into and out of the workforce and the impact of socioeconomic, behavioural, environmental and health- related factors on these workforce transitions. x To determine and compare for women in the 1946-1951 cohort, the costs of illness for those who work, have retired, have never worked or have returned to the workforce, and for women who are caregivers. 19 Data analysis has commenced. Project: A231 Exploring self report of osteoporosis in relation to urinary incontinence and pelvic organ prolapse ALSWH Investigator: x Professor Julie Byles Collaborative Investigators: x Assoc. Professor Pauline Chiarelli (School of Health Sciences, University of Newcastle) x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) This study will explore the association between osteoporosis, pelvic organ prolapse, and urinary incontinence in Australian women. The aims are: x To explore the development of pelvic organ prolapse in women diagnosed with osteoporosis and related variables. x To explore the onset of urinary incontinence and related variables longitudinally in relation to women diagnosed with osteoporosis. We expect that osteoporosis could be one factor in contributing to the development of incontinence in women, through the impact of back pain on abdominal muscles and on the effect of the altered spinal architecture on the structure of pelvic organs and pelvic organ pressure. Analysis is in progress. Project: A083A Major dietary patterns of young and middle-aged Australian women. ALSWH Investigators: x Professor Annette Dobson x Professor Wendy Brown x Assoc. Professor Gita Mishra x Dr Kylie Ball Collaborative Investigators: x Professor Graham Giles (Cancer Council of Victoria) x Dr Sarah McNaughton (School of Exercise and Nutrition Sciences, Deakin University) This project aims to assess the major dietary patterns among two age cohorts of Australian women using factor analysis of food frequency questionnaire (FFQ) data. The main research questions are: x Are there clearly distinctive dietary patterns among Australian women that can be identified by factor analysis of FFQ data obtained at survey 3 for the 1973-1978 and 1946-1951 cohorts of the ALSWH? x If there are clear patterns then what are the nutritional characteristics associated with these patterns? x How do these patterns relate to the sociodemographic characteristics of the women and selected behavioural risk factors? x To what extent do the patterns differ for the two cohorts? Analysis has been completed, and a draft paper is currently being circulated among investigators prior to submission to a nutrition journal. 20 Project: A090A To what extent does having babies contribute to weight gain in young women? ALSWH Investigators: x Professor Annette Dobson x Professor Wendy Brown Collaborative Investigator: x Richard Hockey (School of Population Health, University of Queensland) Disentangling the effects of increasing maturity, lifestyle changes and having babies on weight gain among young women is a challenge. This study aims to investigate the relative impact of childbearing patterns and behavioural and demographic variables on weight gain associated with each significant determinant of weight gain. A paper entitled ‘A prospective study of weight gain in young adult women: Effects of getting married and having a baby’ is in the final stages of preparation. Project: A151A Examining health risks across sexual identity groups ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Dr Ruth McNair (Department of General Practice, University of Melbourne) x Professor Tonda Hughes (College of Nursing, University of Illinois) x Assistant Professor Laura Szalacha (College of Nursing, University of Illinois) x Professor Sharon Wilsnack (Department of Clinical Neuroscience, University of North Dakota) Funding Source: Lesbian Health Fund, USA This study examines changes in sexual identity between two surveys of the 1973-1978 cohort. Two health areas will be investigated: x Health service usage comparisons across all sexual identities, with regression analyses to determine influences on health service usage, including socioeconomic status, education, satisfaction, mental health and physical health indicators. x Alcohol use and mental health comparisons according to sexual orientation. Health services use – (lead author Ruth McNair) Analyses focusing on health services use among 1973-1978 cohort in Survey 3 are almost complete. Findings include: poorer health status amongst non-heterosexual women, leading to higher health service usage, lower satisfaction and lower continuity of primary care amongst non-heterosexual (sexual minority) women indicating a need for improved cultural sensitivity of health services. Again bisexual and mainly heterosexual women appear to be the most disadvantaged. A paper is in preparation and should be completed by December 2008 or January 2009. Substance use and mental health – (lead author Tonda Hughes) These analyses are primarily cross sectional (from Survey 3 of the 1973-1978 cohort), but may include longitudinal models predicting alcohol, marijuana and other illicit drug use using mental health variables from Survey 2 of this cohort. In summary, significantly higher levels of substance use and poorer mental health amongst sexual minority women as compared with heterosexual women were found; bisexual and mainly heterosexual women appear to be at particularly high risk. Perceived stress is the 21 mental health variable most consistently and strongly associated with negative substance use and mental health outcomes. A paper for a peer-reviewed journal is in preparation. Violence - (lead author Laura Szalacha) There is a very strong presence of violence, of many kinds, in the lives of sexual minority women. From analysis of surveys of the 1973-1978 cohort, in every measure of violence in the past three years (that is, physical abuse, severe physical violence, emotional abuse, sexual abuse, and harassment, as well as ever having been in a violent relationship), those who identified as mostly heterosexual, bisexual and/or lesbian reported significantly more violence, by a factor of two to almost four times that reported by exclusively heterosexual respondents. Relationships among these experiences of violence, physical and mental health and substance use are being examined. Further analyses are planned, based on current research in the area of sexual minority women’s health. Preliminary analyses suggest that approximately 10% of the 1973-1978 cohort reported shifts in their sexual identity between Survey 2 and Survey 3. Project: A169 Men, women and ageing: Predictors of ageing well in the Australian Longitudinal Study on Women’s Health and the Perth Health in Men Study (‘MWA’) ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Professor Konrad Jamrozik (School of Population Health and Clinical Practice, University of Adelaide) x Dr Deirdre McLaughlin (School of Population Health, University of Queensland) x Dr Dimitrios Vagenas (School of Population Health, University of Queensland) x Assoc. Professor Jon Adams (School of Population Health, University of Queensland) x Professor Wendy Brown (School of Human Movement Studies, University of Queensland) x Assoc. Professor Nancy Pachana (School of Psychology, University of Queensland), x Professor Paul Norman (School of Surgery and Pathology, University of Western Australia) x Professor Osvaldo Almeida (Unit of Geriatric Psychiatry, University of Western Australia) x Professor Leon Flicker (Royal Perth Hospital) x Professor Graeme Hankey (Department of Neurology, Royal Perth Hospital) x Professor Julie Byles (School of Medicine and Public Health, University of Newcastle) Funding Source: NHMRC/ARC Ageing Well, Ageing Productively Program The aim of this project is to examine the determinants of ageing well and productively in Australia by combining and analysing data from two large longitudinal studies that have already been running for 10 years. Thus the project will capitalise on existing research investments to address specific strategic objectives. The data are from the 1921-1926 cohort of ALSWH and the Western Australian Health In Men Study (HIMS). The specific objectives are to: 22 x Identify social, demographic, behavioural and psychological determinants of survival and of healthy non-disabled life in men and women aged 70-90 years. x Use longitudinal data to assess the effects of changes in health-related lifestyle in old age (e.g. smoking cessation, physical activity) on mortality and compression of morbidity. x Compare the use of health services between older women and older men using the Western Australian Linked Records Database. x Assess factors associated with differing levels of health service use and explore inequities in relation to geographic location, gender, social factors, and physical health. x Identify health and lifestyle factors associated with social engagement and independent living in older age. x Assess the extent to which mental health factors, including depression, anxiety and positive well-being, are associated with healthy non-disabled life in older age. x Examine gender differences to assess the extent to which early intervention and prevention strategies for older people should target men and women separately. x Assess the combined impact of multiple diagnosed conditions (e.g. diabetes, depression), multiple modifiable risk factors (e.g. obesity, smoking) and social connectedness/isolation on mortality, morbidity and use of health services. The general hypothesis underlying the proposed project is that there are identifiable risk factors for mortality and chronic morbidity in old age that are potentially amenable to intervention, and that these risk factors are not necessarily the same as those operating in middle life. An additional study is being run in 2008 on all surviving HIMS participants (estimated 7513) in conjunction with a sub-study of the ALSWH 1921-1926 cohort who live in Perth, WA (estimated 300). The HIMS survey will collect information on a range of themes, including specific health conditions, psychological and social well being, medications, living arrangements, relationships and sexual behaviours. The ALSWH cohort were surveyed for the fifth time in 2008, so the sub-study of the Perth women is relatively brief and includes variables which were not measured in the ALSWH survey, in a format which matches that of the HIMS survey. Pilot testing of the ALSWH survey was completed in June 2008; the HIMS piloting was completed in May 2008. In addition to the questionnaires, telephone interviews of the HIMS participants and the Perth ALSWH women are being conducted. The interviews will collect data on cognitive status and mood, and are commencing, for both the men and women, in October 2008. Approval was received in March 2008 from the Data Linkage Unit of the Department of Health, WA, (DOHWA) for the Chief Investigators to access linked data for all women in the ALSWH 1921-1926 cohort currently or formerly residing in Western Australia. The linkages requested were for hospital morbidity, emergency, cancer registrations, mental health and Home and Community Care. These linkage areas mirror those that the HIMS investigators have obtained for the men. At the time of writing (October 2008), the Data Linkage Unit had provided ‘links files’ to each of the data custodians, who will extract the required data. Because of considerable backlogs in this data extraction, the Data Linkage Unit is unable to provide an estimated date that the linked data will be available. Approval has been granted by DOHWA to access the HIMS linked data. Approval for MBS and PBS linkages is pending. The following analyses have been approved: x Social networks in older Australian men and women x Antecedents, prognosis and prognostic factors for stroke x Mortality in relation to BMI in a large cohort of older Australian men and women x Major trauma in elderly people: causes, costs and consequences x The long shadow of smoking x Healthy ageing: The role of sexual health 23 x Non-response bias in two large cohorts of men and women x One-year survival conditional on survival to a given age x The role of sex hormones on mood disorders in older Australian men and women x An examination of residential age care usage patterns among men and women in WA A presentation relating to this project was made at the School of Population Health, University of Queensland in July 2008, and another will be made at the Australian Association of Gerontology conference in November 2008. Project: A196 Proton-pump inhibitors and comedications ALSWH Investigators: x Professor Annette Dobson x Professor Julie Byles Collaborative Investigators: x Dr Janneke Berecki (School of Population Health, University of Queensland) x Richard Hockey (School of Population Health, University of Queensland) x Xenia Dolja-Gore (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Richard Gibson (Research Centre for Gender, Health DQG Ageing, University of Newcastle) x Professor Nick Talley (Mayo Clinic College of Medicine) The prevalence of psychiatric disease among patients with unexplained gastrointestinal complaints is relatively high. In this study we aimed to test if there is an association between depression and anxiety, and acid-related disorders among middle aged women. We analysed cross sectional data of middle aged participants of the ALSWH. Women aged 56-61 years, who participated in a follow-up survey in 2007, and provided response to questions relating to heartburn, depression and anxiety were included (N=10 437). Adjusting for possible confounders, logistic regression was used to model the association between acid- related disorders and depression/anxiety. In the unadjusted analysis acid-related disorders were associated with depression (OR=1.59; 95%CI: 1.23-2.07), anxiety disorders (OR=1.61 95%CI:1.16-2.23) or both (OR=1.65;95%CI:1.12-2.04). After adjustment for sociodemographics, smoking, alcohol intake, body mass index, weight gain, arthritis, headaches/migraines and life events, acid-related disorders remained independently associated with having both depression and anxiety (OR=1.51; 95%CI: 1.12-2.04). In women from the 1946-1951 cohort there is an association between anxiety and depression, and acid- related disorders, that is not fully explained by sociodemographics, health and lifestyle factors. A presentation from this project was made at the 2008 Population Health Congress in Brisbane. Project: A207 Continuity and change in tobacco use among young women: A 10 year prospective analysis ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Professor Neville Owen (School of Population Health, University of Queensland) x Dr Liane McDermott (School of Population Health, University of Queensland) This project has the following broad research aims: 24 x To examine, prospectively, factors associated with continuity and change in smoking behaviour among young adult women over a 10 year period. x To examine trajectories of smoking among young adult women who have never had children over a 10 year period. This paper would include a thorough investigation of factors associated with long-term, high-rate smoking. x To examine factors associated with continuity and change in smoking behaviour before and after pregnancy, with a specific focus on smoking relapse. A range of explanatory variables will be examined including demographic, psychosocial, lifestyle risk behaviour and life-stage transition variables. The first aim has been completed and a paper is under resubmission with a peer-reviewed journal. The second aim has not as yet commenced, and a paper for a peer-reviewed journal has been initiated for the third aim of the project. A presentation was made at the 10th International Congress of Behavioral Medicine held in Tokyo, August 2008. A paper has been submitted. Project: A208 Regional variation in the health of elderly Australian women ALSWH Investigators: x Professor Annette Dobson x Professor Julie Byles x Assoc. Professor Nancy Pachana Collaborative Investigators: x Dr Deirdre McLaughlin (School of Population Health, University of Queensland) x Dr Dimitrios Vagenas (School of Population Health, University of Queensland) x Professor Konrad Jamrozik (School Of Population Health and Clinical Practice, University of Adelaide) Funding Source: NHMRC/ARC Ageing Well Ageing Productively Grant Older people may act as sensitive indicators of the effectiveness of health systems. For example they may help us understand the reasons for the higher mortality reported in the literature, in rural areas than in urban areas. The objectives of this study were to estimate in a sample of older women: (i) the mortality of urban and rural women as well as by jurisdiction (ii) differences in factors which could contribute to any mortality differences. Baseline and longitudinal analysis of data from the 1921-1926 cohort were used. Factors considered included: urban or rural residence in Australian States and Territories, sociodemographic characteristics, health related behaviour, survival up to the 1st of October 2006, physical and mental health scores, and the use of medical services. Mortality was higher in rural rather than in urban women (hazard ratio 1.14; 95%CI: 1.03- 1.26) but there were no differences between States and Territories. There were no consistent baseline or longitudinal differences between regions for physical or mental health, with or without adjustment for sociodemographic and behavioural factors. There were differences, however, between urban and rural women with respect to use of health services: rural women had fewer visits to general practitioners (OR= 0.54; 95%CI: 0.48-0.61) and medical specialists (OR=0.60; 95%CI: 0.55-0.65), consistently in most States and Territories. Differences in use of health services are a more plausible explanation for higher mortality in rural than urban areas than differences in other factors. Analyses of this data are complete and a paper entitled ‘Regional variations in the health of older Australian women: Grey canaries?’ has been submitted. 25 Project: A210 Access to medicines for cardiovascular health and primary care services in rural and remote Australia ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Lynelle Moon (National Centre for Epidemiology and Population Health, Australian National University) x Susana Senes (Australian Institute of Health and Welfare) x Anne Broadbent (Australian Institute of Health and Welfare) x John Woodall (Australian Institute of Health and Welfare) Funding Source: Department of Health & Ageing and the Australian Institute of Health & Welfare This project aims to: x Describe medicines used by women in the 1921-1926 cohort with history of cardiovascular conditions. x Describe cardiovascular medicines used by older women with or without reported cardiovascular conditions. x Compare reported use of cardiovascular medicines by women living in rural, remote and urban areas. x Assess associations with factors that may affect use of medicines, such as reported number of GP consultations, hospital admissions, number of medicines reported, whether managing on income available. x Assess migration of women who reported taking cardiovascular medicines between urban, rural and remote areas from Survey 1 to 4. Analysis of the ALSWH data has been completed. However, further progress with the project and compilation of the report has been hampered by delays in accessing Pharmaceutical Benefits Scheme data and Medicare Benefits Schedule data from the Department of Health and Ageing. The project is on hold until such data become available. Project: A226 Relative survival as an indicator of generalizability of results from longitudinal studies of older people ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Dr Leigh Tooth (School of Population Health, University of Queensland) x Richard Hockey (School of Population Health, University of Queensland) There purpose of this study is to explain and illustrate ‘relative survival’ as a tool for assessing generalizability of results from a cohort of older people among whom death is a potential threat to generalizability. Analyses will compare survival of ALSWH participants born in 1921- 1926 with life tables produced by the Australian Bureau of Statistics, and will also compare ALSWH survey data at baseline (1996) with results from the 1995 National Health Survey for women of the same age. A presentation of this project was made at the Population Health Congress, Brisbane, July 2008. 26 Project: W062 Depression and cardio-vascular disease in a cohort of mid-aged Australian women ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Dr Deirdre McLaughlin (School of Population Health, University of Queensland) x Dr Dimitrios Vagenas (School of Population Health, University of Queensland) x Dr Janneke Berecki (School of Population Health, University of Queensland) x Professor Sandy McFarlane (Centre for Military and Veterans Health, University of Adelaide) This study aims to: x Analyse longitudinal data from women from the ALSWH 1946-1951 cohort to examine the temporal relationship between depression and CVD in this group, particularly identifying women who have a history of depression and who may be at increased risk of developing CVD. x Explore the relationship between current diagnosis of CVD and depression and how demographic, social and healthcare utilisation factors mediate the impact of depression. This knowledge will contribute to the development of tailored care and prevention strategies for women at risk for depression as well as CVD. x Conduct a sub-study to collect additional data from women who have reported CVD. The study will obtain information on factors that may mediate the associations between depression and CVD (including social factors, professional support, medication, health and community services) and also to provide validation of diagnoses. Data collection for the sub-study is now underway. Project: A131 Partner violence and gynaecological health of 1946- 1951 cohort women ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Assoc. Professor Margot Schofield (School of Public Health, La Trobe University) x Dr Rafat Hussain (School of Health, University of New England) Partner violence is linked to cervical cancer and other gynaecological conditions. However, results of current research into associations between partner violence and cervical cancer screening have been inconclusive. Therefore, the current research investigates the association between partner violence and inadequate cervical cancer screening. Participants were 7312 women aged 45-50 years who responded to the Australian Longitudinal Study on Women’s Health population-based surveys in 1996 and 2004. The women self-reported frequency of Pap smears via mailed questionnaire. Women who had experienced partner violence at least six years earlier, compared with those who had not, were more likely to report current inadequate screening (OR=1.42; 95%CI: 1.21-1.66). After adjusting for known barriers to preventive screening (education, income management, marital status, general practitioner visits, chronic conditions) and depression, partner violence was still associated with inadequate Pap tests (OR=1.20; 95%CI: 1.01-1.42). 27 The significance of this study lies not just in confirming a negative relationship between cervical cancer screening and partner violence, but in suggesting that good access to a physician of choice appears to significantly decrease this negative relationship. This analysis found associations between partner violence and inadequate screening for cervical cancer. A paper is currently under consideration by Preventive Medicine. Analyses concerned with gynaecological outcomes will commence shortly. Project: A184 Investigating methods of analysing longitudinal qualitative data collected via free-text comments ALSWH Investigators: x Dr Deborah Loxton x Professor Wendy Brown Collaborative Investigator: x Lyn Adamson (Research Centre for Gender, Health and Ageing, University of Newcastle) The quantitative findings for the ALSWH report, Women’s Weight – Findings from the ALSWH (Major Report B) were illustrated with case studies that were drawn from the qualitative ALSWH data. A literature search has been completed and a draft paper is in progress. Project: A193 Alcohol consumption during pregnancy ALSWH Investigators: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) NHMRC alcohol guidelines for pregnant women were revised from total abstinence in 1992 to a low level of alcohol consumption (less than seven drinks per week) in 2001. Data from the 1973-1978 cohort were used to investigate whether changing the guidelines had an impact on drinking during pregnancy and what factors were associated with alcohol consumption during pregnancy. The level of abstinence was similar among women who were pregnant prior to 2001 and those who were first pregnant after the introduction of the revised guidelines. Women were more compliant with low alcohol guidelines than zero alcohol guidelines. The factor that had the most effect on alcohol intake during pregnancy was alcohol intake prior to pregnancy. A presentation of this project was made at the Population Health Congress, Brisbane, July 2008. Project: 216 Iodine-related food intake among pregnant, breast- feeding and other women ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Xenia Dolja-Gore (Research Centre for Gender, Health and Ageing, University of Newcastle) x Dr Dorothy Mackerras (Food Standards of Australia and New Zealand) x Professor Graham Giles (Cancer Council of Victoria) Iodine deficiency adversely affects the mental development of young children and is re- emerging in Australia. Data from the 1973-1978 cohort and the Cancer Council Victoria were 28 used to investigate whether pregnant and breastfeeding women consume more or less bread, dairy products and fish than their non-pregnant counterparts. Another aim was to estimate the impact of mandatory fortification of bread with iodine in pregnant and non-pregnant women. Pregnant and breastfeeding women reported eating more bread than other women. Current iodine intakes are well below dietary recommendations for non-pregnant women and further below levels recommended for pregnant women. Fortification of bread with iodine would have a greater impact on iodine levels in pregnant and breastfeeding women than non-pregnant women. A presentation from this project was made at a Nutritional Society of Australia meeting, Newcastle, August 2008. Project: A217 Symptoms and menopause ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Assoc. Professor Gita Mishra (Department of Epidemiology and Public Health, Royal Free and University College) The ALSWH data from the cohort of women born between 1946 and 1951 include lists of symptoms that these women report occurring never, rarely, sometimes or often. The aims of this study are firstly to identify clusters of symptoms amongst these women and changes in these clusters over the eleven years between 1996 and 2007. Finally we will identify groups of women who exhibit similar symptom trajectories. Preliminary examination of the data has begun. Project: A219 Marriage and de facto relationships ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Catherine Chojenta (Research Centre for Gender, Health and Ageing, University of Newcastle) x Dr Liane McDermott (School of Population Health, University of Queensland) Few studies have investigated the combined use of alcohol and tobacco consumption during pregnancy. The aims of this study are to describe the prevalence of tobacco and alcohol consumption before and during pregnancy and to investigate whether such use changes from pre-pregnancy to pregnancy. Additionally, the factors associated with use before pregnancy and with any change in use will be investigated. Preliminary results show a decline in both tobacco and alcohol consumption during pregnancy. Investigation of the data has revealed that it is not possible to ascertain illicit drug use during pregnancy. This project will examine alcohol and tobacco consumption during pregnancy. 29 Project: A222 Prescribed drug utilisation in women before, during and after pregnancy ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Xenia Dolja-Gore (Research Centre for Gender, Health and Ageing, University of Newcastle) x Michelle Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Dr Jane Robertson (Research Centre for Gender, Health and Ageing, University of Newcastle) This study aims to determine the prevalence and patterns of prescribed medication use before, during and after pregnancy as little is known about the use of prescribed medications among pregnant women. Data from the ALSWH were linked with Pharmaceutical Benefits Scheme (PBS) data to determine patterns of prescribed medications. From the 1973-1978 cohort (aged 27-32) 535 women were selected who had given birth to a child in 2005. PBS data were collected for one year before pregnancy, during pregnancy and one year after birth. Of the 535 younger women selected, 195 (37%) had taken prescribed medications at some stage during the period observed. Of the women taking prescribed medications, 142 (27%) had taken medications in the pre-pregnancy period, 88 (17%) had medication during their pregnancy and 93 (18%) took medications after the birth of the child. There were at least 33 different medications used by women. The most commonly prescribed medication used at least once during both the pre-pregnancy and pregnant period was antidepressant medication. Oral contraception pills were the most commonly prescribed medication in the year following birth, followed by antidepressants. In the pre-pregnancy, pregnant and post-pregnancy periods an average of 1.6 (max 9), 1.4 (max 5) and 1.3 (max 4) medications were used by women. A decrease of medication use occurred whilst pregnant, though a widespread use of antidepressant medications among pre-pregnancy, pregnancy and post-pregnancy women underscore the need for further investigations. A presentation of this project was made at the Population Health Congress, Brisbane, July 2008. Project: A223A Quality of life, emotional and general health, physical activity and medication use in survivors of cancer ALSWH Investigators: x Dr Deborah Loxton x Professor Julie Byles Collaborative Investigators: x Dr Efty Stavrou (Cancer Institute of NSW) x Ms Deborah Baker(Cancer Institute of NSW) x Ms Heather McElroy(Cancer Institute of NSW) This study examines whether having had cancer in the past (for which data are already registered in the Cancer Council Registry and hence available via data linkage) determines current lifestyle, health status, medications used and dietary intake. It is hypothesized that, compared with women from the 1946-1951 and 1921-1926 cohorts who have not previously been diagnosed with cancer, survivors of cancer will: x Have an increased use of anti-depression medication x Have a higher incidence of chronic disease (e.g. heart and lung disease) 30 x Consume more alcohol x Be less physically active x Have a similar diet x Have higher stress x Have poorer mental health (SF-36 MCS) x Have a lower self-reported quality-of-life Where possible, responses will be matched to recommendations of published guidelines, such as the NHMRC alcohol guidelines, the daily dietary intake guidelines (e.g. 2 fruit, 5 vegetables; low fat milk; breads & cereals recommendations) and the Australian guidelines for physical activity. The study further aims to determine changes in lifestyle which occur after a diagnosis of cancer. Comparison of lifestyle behaviours, diet, emotional stress and physical activity before and after date of cancer diagnosis may be investigated. Short and long term alterations in lifestyle may also be elicited. Comparison with cancer-free participants will also be conducted. It is hypothesized that compared with habits and lifestyle before diagnosis of cancer, short- term (5 years) changes following diagnosis will include: x Less alcohol consumption x More physical activity x Greater consumption of fruit and vegetables x Better mental health Further research is pending data linkage with the NSW Central Cancer Registry. Project: A225 The relationship between skin disease and psychological morbidity in young Australian women ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Dr Parker Magin (School of Medicine and Public Health, University of Newcastle) x Kylie Bailey (School of Medicine and Public Health, University of Newcastle) This project examines the relationship between skin problems and several measures of psychological morbidity (i.e. depression, stress, anxiety) employing longitudinal data analysis. Skin diseases are common and constitute a significant proportion of the morbidity within the community. There is a considerable literature concerning skin disease and psychological morbidity, and the consensus of opinion has long been that skin diseases are strongly associated with psychological illness and psychological distress. The literature on the psychological sequelae of skin disease, however, is far from consistent and is of variable (and often poor) methodological quality. Furthermore, all the studies in the literature are cross sectional in design. Thus no conclusions can be made regarding direction of causality in the direction of the relationship of skin disease and psychological morbidity. This is particularly problematic in that, while most attention has focused on the propensity of skin disease to cause psychological morbidity, there is also evidence of psychological distress precipitating or exacerbating skin disease. We will be providing the first longitudinal analyses examining the relationship between skin problems and psychological morbidity. Analyses will involve 3 separate longitudinal models using generalised estimating equations (GEEs). That is, one model with depression as the independent variable, another with anxiety as the independent variable and the other with stress as the independent variable. The 31 dependent variable for each model will be whether or not women have skin problems (binary). For all 3 models, all remaining variables will be included to ‘adjust’ the analyses. A paper is in preparation, and will be submitted to the British Journal of Dermatology. Project: A233 ALSWH: What can we learn from no contact? ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Jennifer Powers (Research Centre for Gender, Health and Ageing, University of Newcastle) x Anna Graves (Research Centre for Gender, Health and Ageing, University of Newcastle) Surveys of younger people have lower response rates often due to difficulty contacting the participants (no contact). The purpose of this analysis is to describe and explain ‘no contact’ as a potential way of assessing the generalisability of the results from the cohort of women born between 1973 and 1978. This project is in the early stages of analysis. Project: A156 Relationship between sexual violence, sleep problems and health ALSWH Investigator: x Dr Deborah Loxton Collaborative Investigators: x Professor Jill Astbury (School of Psychology, Victoria University) x Dr Gerard Kennedy (School of Psychology, Victoria University) It is hypothesised that women who report sexual violence compared with those who do not report such violence will have significantly higher rates of sleep problems, medication and other drug use, poorer health and higher rates of diagnosed mental health problems, but lower satisfaction with their health care. Since the last report, we have been focussing on finalizing the analysis of the data relating sleep problems and different kinds of interpersonal violence with a focus on distinguishing the contribution to poor sleep made by sexual violence compared with other types of violence taking into account the role of socioeconomic and other mediating variables. In examining the differences in the nature and extent of sleep problems of women who have experienced sexual violence compared with those who have experienced other forms of violence or no violence, we are also attempting to explicate how membership of these groups can be predicted by a range of health risk behaviours including the use of prescribed medications, alcohol and tobacco use and illicit drug use as well as various measures of mental health and well being. Project: A174 Young women’s changes in use of contraception after reproductive life events ALSWH Investigator: x Dr Jayne Lucke Collaborative Investigators: x Melanie Spallek (School of Population Health, University of Queensland) x Melanie Watson (School of Population Health, University of Queensland) x Danielle Herbert (School of Population Health, University of Queensland) 32 This project examines patterns of change in contraceptive use among young women over ten years as they move from their late teens/early twenties to late twenties/early thirties. There are two parts to the analysis: i) an examination of trends in the use/non-use of contraception and the methods used, from the 1973-1978 cohort Surveys 1-4, and ii) an analysis of changes in contraception use as a result of reproductive events including birth, miscarriage and termination. We found that contraception use increased from Survey 1 to Survey 2 and then decreased from Survey 2 to Survey 4 as women were more likely to try to become pregnant. Use of oral contraceptives decreased over time with other methods increasing in popularity. The analysis also examines factors associated with the use of contraception, and the use of specific methods. This work is currently in progress and forms one section of Major Report D due to the Department of Health and Ageing in 2009. A journal article is also in progress. A presentation of this work was made at the Population Health Congress, Brisbane, July 2008. Project: A229 The impact of having a baby and other life events on young women’s aspirations ALSWH Investigators: x Dr Jayne Lucke x Professor Christina Lee Collaborative Investigators: x Melissa Johnstone (School of Psychology, University of Queensland) This project examines to what degree Australian women’s motherhood and other aspirations are impacted by first birth. Studies have shown that having a baby can impact upon Australian women’s employment patterns, with many women reducing their employment hours or opting for part-time work after childbirth. Other studies have shown a degree of instability in fertility aspirations over time. These findings raise questions as to how having a baby impacts upon young Australian women and their aspirations. This project aims to investigate the longitudinal trends in motherhood aspirations, as well as the impact of having a baby upon women’s motherhood, and other aspirations using data from Surveys 1-4 of the 1973-1978 cohort. The research questions are: x What are the longitudinal trends for motherhood, relationship, employment, and educational aspirations? x What is the impact of having a baby (i.e. first birth) on motherhood aspirations, as well as education, employment, relationship and occupational aspirations? x What is the impact of other life events (e.g. relationship break-up, divorce, difficulty falling pregnant) on motherhood, employment and relationship aspirations? x Are there sociodemographic differences between women who do and do not change their motherhood aspirations, following the birth of a child or other life events? x Do women with changing aspirations have worse psychological health than those whose aspirations remain consistent? This work is currently in progress and forms one section of Major Report D due to the Department of Health and Ageing in 2009. A journal article is also in progress. 33 Project: A232 Factors associated with STIs and other indicators of risky sexual behaviour and poor sexual health ALSWH Investigators: x Dr Jayne Lucke x Dr Deborah Loxton Collaborative Investigators: x Danielle Herbert (School of Population Health, University of Queensland) x Melanie Watson (School of Population Health, University of Queensland) The first phase of this project examines whether there are common factors associated with a number of indicators of risky sexual behaviour and poor sexual health. Participants were 6840 women who participated in four surveys of women from the 1973-1978 cohort of the ALSWH. A series of logistic regression analyses examined factors associated with a number of indicators of risky sexual behaviour and poor sexual health. At Survey 3, a third of the women reported multiple sexual partners and at Survey 4, 13% had not adhered to Pap test recommendations. Around 18% of women had ever reported a sexually transmitted infection (STI) with 7% reporting an STI since 2003. Being single, working full-time and ever experiencing partner violence or child sexual abuse were all associated with increased odds of risky sexual behaviour and poor sexual health. A presentation from this project was made at the Population Health Congress, Brisbane, July, 2008, and a journal article is in preparation. The second phase of this project examines the characteristics at Survey 2 that predict the likelihood of a woman reporting an STI for the first time at Survey 3 or Survey 4. Preliminary results were presented as a oral poster at the Australasian Sexual Health Conference in Perth in September 2008. The analysis focuses on questions about sexually transmitted infections from the first four surveys of the 1973-1978 cohort which were completed by 6306 women. There were 269 women who reported an STI for the first time at Survey 3 or 4 and these were compared with 5214 women who did not report an STI at any of the four surveys. The explanatory variables in the analysis were a range of sociodemographic factors, sexual and relationship factors, health behaviour factors, physical and mental health measures and health service access factors. Women who reported an STI for the first time at Survey 3 or 4 were more likely to have had the following characteristics at Survey 2: a higher number of male sexual partners, more likely to have been divorced or separated in the previous 12 months, more likely to be unpartnered, less likely to have ever been pregnant, poorer reported access to Women’s Health or Family Planning Centres, and younger than 25 years old. The analysis shows that partner and relationship factors are important predictors of who goes on to develop an STI. A oral poster was presented at the Australasian Sexual Health Conference, Perth, September 2008, and a journal article is in progress. 34 Project: A190A Size and structure of social networks in older women: Changes over time ALSWH Investigators: x Assoc. Professor Nancy Pachana x Professor Annette Dobson Collaborative Investigator: x Dr Deidre McLaughlin (School of Population Health, University of Queensland) x Dr Dimitrios Vagenas (School of Population Health, University of Queensland) x Assoc. Professor Jon Adams (School of Population Health, University of Queensland) x Melanie Watson (School of Population Health, University of Queensland) An abbreviated form of the Duke Social Support Index was examined with respect to factors that might be expected to affect social support for older women over time. Two sub-scales were used: one describing the size and structure of the social network (four items) and the other perceived satisfaction with social support (six items). Over a three year period the network score increased among women whose life circumstances meant that they were likely to receive more support (e.g. recent widowhood). Likewise those women at risk of becoming more socially isolated (e.g. those with sensory loss) became less satisfied with their social support. Changes in both measures were tempered by women’s mental health and optimism. Thus, although these sub-scales do not fully reflect the complexity of social support, they are responsive to changes in the lives of older women and can be recommended for use in community-based epidemiological studies. This is a mixed methods analysis incorporating quantitative and qualitative data to describe changes in older women’s social networks over time. The analyses have been completed and a paper is in preparation. Project: A194 A comparison of the performance of the Goldberg Anxiety and Depression Scale in both mid-aged and older women ALSWH Investigator: x Assoc. Professor Nancy Pachana x Professor Annette Dobson Collaborative Investigators: x Dr Natasha Koloski (School of Psychology, University of Queensland) x Melanie Watson (School of Population Health, University of Queensland) Measures to assess anxiety and depression separately often incur difficulties due to overlap of these constructs, especially in older individuals. Using the Goldberg Anxiety and Depression Scale (GADS) we aimed to confirm the factor structure of the instrument, using data from the 1921-1926 cohort, to validate the instrument against other self-report information, and to assess its association with a variety of health-related outcomes. Participants were 7264 women (aged 75-82 years) enrolled in the ALSWH. Measures of anxiety and depression included the GADS, the mental health items of the Medical Outcomes Study SF-36, and self reported information on mental health diagnoses, symptoms and medications. The factor structure of the scale was examined using latent trait analysis, while receiver operating characteristic curves were used to explore the performance of the scale against other criteria. Latent trait analyses replicated prior findings demonstrating high correlations between anxiety and depression as measured by the GADS and suggesting a third factor related to sleeping 35 problems. Receiver operating characteristic curves showed that a simple score formed by summing responses to GADS items had high sensitivity and specificity in relation to other measures of anxiety and depression. This large study provides support for the hypothesis that anxiety and depression are not readily distinguishable entities in older women and that the GADS is a useful tool for measuring the composite construct for epidemiological studies. A paper from this study was published in Age and Ageing (July 2008). Project: A230 Life events across three cohorts over time ALSWH Investigators: x Assoc. Professor Nancy Pachana x Professor Annette Dobson Collaborative Investigator: x Sam Brilleman (School of Population Health, University of Queensland) The main hypotheses are: x That life events are not as significant as a predictor of physical health outcomes (SF-36), as SES, mood, other psychological variables, physical activity. x That life events are not as significant as a predictor of depression (SF-36), as SES, mood, other psychological variables, and physical activity. x That life events are not as significant as a predictor of use of health services, as SES, SF- 36, mood, other psychological variables, and physical activity. The primary objective of this research is a literature review. Methods of analysis will be fairly simple, e.g. correlations, regressions – data will be included to illustrate major methodological and substantive issues discussed. Data for all cohorts has now been analysed, and a literature review has been completed. A paper is in preparation. Project: A035 Prevalence of back pain in Australian women and its relationship to incontinence and respiratory disease ALSWH Investigators: x Professor Christina Lee Collaborative Investigators: x Anne Russell (School of Nursing and Midwifery, University of Queensland) x Dr Michelle Smith (School of Health DQG Rehabilitation Sciences, University of Queensland) x Dr Paul Hodges (School of Health DQG Rehabilitation Sciences, University of Queensland) Funding source: National Health and Medical Research Council Although the mechanism for the development of low back pain is not well understood, it has been extensively argued that it is associated with changes in control of the trunk muscles. Many trunk muscles, such as the diaphragm, transversus abdominis, and pelvic floor muscles, contribute to postural stability, but are also essential for respiration and continence. Altered function of these muscles in people with incontinence and respiratory disease may interfere with the physiology of spinal control, and provide a link to back pain. The aim of this project was to examine the association between back pain and disorders of continence and respiration in women. 36 Our initial cross sectional analysis of Survey 1 data has been published in the Australian Journal of Physiotherapy. This study found that disorders of continence and respiration were strongly related to frequent back pain after consideration of possible confounding factors. A secondary finding during this analysis was a strong relationship between gastrointestinal symptoms and back pain. Possible explanations for this relationship include referred pain through viscerosomatic convergence, altered pain perception, increased spinal loading when straining during defecation, or reduced support of the abdominal contents and spine secondary to changes in function of the abdominal muscles. Our second analysis involved calculation of univariate and multivariate prevalence ratios to determine the associations between the development of back pain and change in the presence of incontinence and breathing difficulty between Surveys 1 and 2. This study found that women with pre-existing incontinence and women who developed incontinence or breathing problems were more likely to develop back pain than women without such problems. This provides the first evidence that the presence and/or development of incontinence and breathing problems are associated with the future development of back pain. This paper has been submitted to a journal and is currently under review. Our final analysis involved division of women in each age cohort into subgroups who had no back pain, incontinence, breathing problems or allergy. Each data subset was analysed to determine the relationship between the development of the absent condition (i.e. back pain, incontinence, breathing problems or allergy) and the presence or development of the other conditions. This study identified that women with pre-existing and/or newly developed incontinence and breathing problems/allergy had an increase risk for the development of back pain, and women with pre-existing and newly developed back pain were more likely to develop incontinence and breathing problems. This suggests that common factors may contribute to the development of these conditions, at least in some individuals. As the trunk muscles contribute to each of these systems, altered muscular control may contribute to the development of these comorbidities. This paper has been written and will be submitted to a journal once the above-mentioned paper is in press. Project: A047 Mid-age women's use of counselling services ALSWH Investigator: x Professor Margot Schofield Collaborative Investigator: x Dr Asad Khan (School of Health DQG Rehabilitation Sciences, University of Queensland) While rates of psychological distress in the Australian community are on the rise, it appears that the use of counselling and psychological services is relatively low. This series of studies aims to understand factors associated with use of counselling services, first in cross sectional analyses, and then using longitudinal predictive analyses. Analyses will be undertaken to map use of services provided by a counsellor/psychologist/social worker in the past 12 monthV by women in the 1946-1951 cohort. In 2008, a paper was published in Counselling and Psychotherapy Research examining the psychosocial, health behaviour and demographic profile of women who had used counselling services at Survey 1. A second paper examined the health service use profile of women who had been to counselling services. Further papers are in advanced stages of preparation examining the mental and physical health profile of these women. Longitudinal analyses will then be conducted to predict use of counselling services, and how counselling service use predicts change in physical and mental health. It is planned to extend the analysis to examine how use of counselling services predicts mental and physical health at Surveys 4 and 5, controlling for other confounders. A paper was also published in 2008 in Women’s Health Issues. 37 Project: A102 Use of medication amongst mid-age women: Correlates of use and predicting change ALSWH Investigator: x Professor Margot Schofield Collaborative Investigator: x Dr Asad Khan (School of Health DQG Rehabilitation Sciences, University of Queensland) Increasing rates of prescription and use of medication have been noted in the Australian community. This series of analyses aims to examine use of medication by women from the 1946-1951 cohort, particularly use of medication for anxiety, depression and stress. The analyses also aim to determine factors associated with the use of these medications. The demographic profiles and the mental health and physical health of women who do and do not use medications will be mapped, and their use of health services will be examined. Analyses are currently underway and two papers are in preparation. Longitudinal analyses will be conducted in the future. Project: A038A Relationship between body mass index, diet quality, physical activity and health service utilisation ALSWH Investigator: x Dr Anne Young Collaborative Investigator: x Assoc. Professor Clare Collins (School of Health Sciences, University of Newcastle) x David Fitzgerald (School of Population Health, University of Queensland) This project has generated a diet quality score, the Australian Recommended Food Score (ARFS), for use within the analyses. It is a continuous score, with a number of subscales. The higher the ARFS score the higher the micronutrient intake and the lower the total fat and saturated fat. Initial cross sectional descriptive statistics have been reported across categories of BMI (healthy weight, overweight and obese), demographics, macronutrients (% energy from fat, protein and carbohydrate), core foods (fruit, vegetables, dairy, meat/protein, extras, alcohol), physical activity, general health, mental health, and health service usage (GP and specialists visits). We have also examined correlates of diet quality. Following this descriptive stage, association between variables will be examined, in particular diet-related predictors of health service utilization. The ALSWH survey data will be linked to the Medicare data for the 1946- 1951 cohort. Health care use and expenditure will be examined by quintiles of ARFS, and whether expenditure differs over time in those with high versus low ARFS will be investigated. Statistical analysis of the longitudinal Medicare data has been completed, and a manuscript is in preparation. The results from this project were reported in a presentation within the International Dietetic Congress, Japan, September 2008. Project: A081 Characteristics of CAM users and associated symptoms and conditions ALSWH Investigator: x Dr Anne Young Collaborative Investigators: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Assoc. Professor Jon Adams (School of Population Health, University of Queensland) 38 The project has recently focussed on determining the factors associated with complementary and alternative medicine (CAM) use among older Australian women over time. The percentage women in the ALSWH 1921-1926 cohort who consulted a CAM practitioner in the years 1996, 1999, 2002 and 2005 were 14.6%, 12.1%, 10.9% and 9.9% respectively. Use of CAM increased as the number of reported symptoms increased, as physical health decreased, and for non-urban residents compared with urban residents. Use of CAM amongst older women appears to be strongly influenced by poor physical health. There is also a suggestion that lack of access to conventional health care providers increases CAM use and there is an overall decline in the use of CAM among older women as they age. A paper has been accepted for publication in Age and Ageing in 2008. Project: A134 Health care for women with diabetes living in rural areas: A longitudinal study of access to care and health outcomes ALSWH Investigators: x Dr Anne Young x Professor Julie Byles Collaborative Investigators: x Dr Julia Lowe (School of Medicine and Public Health, University of Newcastle) x Xenia Dolja-Gore (Research Centre for Gender, Health DQG Ageing, University of Newcastle) Funding Source: Diabetes Australia Research Trust The ALSWH provides an opportunity to examine the health services provided to women with diabetes in Australia, as well as monitoring changes in their health and well being, and the impact of new initiatives in diabetes care including the Annual Cycle of Care Medicare item that was introduced in 2001. For this study, consenting women’s survey data were linked to Medicare (MBS) and Pharmaceutical Benefits Scheme (PBS) databases. This allowed women to be classified according to their use of specific Medicare items for haemoglobin A1C (HbA1c) analysis and Diabetes Annual Cycle of Care (ACC). Claims for ACC were identified for 29% of 403 women with diabetes from the 1946-1951 cohort, and 40% of 616 women with diabetes from the 1921-1926 cohort. In both age groups, women who had ACC were more likely to be those who were already overweight, had more GP visits and more medications, and who were more likely to have visits at ‘no cost’ than other women with diabetes. Women from the 1946-1951 cohort who had ACC were also more likely to have difficulty managing on their income and were less likely to have hypertension. Among women from the 1921-1926 cohort, those who had ACC were less likely to have difficulty managing on their income and less likely to have been born in Australia. There was no association between ACC and other comorbidities or country of birth. In both cohorts, women who developed diabetes after the first survey (incident cases) tended to have better SF-36 health profile scores and lower pharmaceutical and Medicare costs than those who reported diabetes on the first survey (prevalent cases). ACC was not associated with statistically significantly higher costs in any group. Among women in the 1946-1951 cohort with prevalent diabetes, those with ACC tended to have worse physical and social function scores at the time the ACC was introduced. These women continued to have poorer scores at subsequent surveys when compared with other women with diabetes. There was no difference in scores for women from the 1921-1926 cohort with diabetes according to whether they had ACC or not. The results of this study were included in the 2008 ALSWH Report to the Department of Health and Ageing ‘Use and costs of medications and other health care resources: Findings from the Australian Longitudinal Study on Women’s Health’ (Major Report C). 39 Project: A135 Alcohol consumption and poor mental health among mid-aged Australian women 1996-2007 ALSWH Investigator: x Dr Anne Young Collaborative Investigator: x Jennifer Powers (Research Centre for Gender, Health DQG Ageing, University of Newcastle) There has been considerable debate as to which comes first, poorer mental health or heavy alcohol consumption. In the fifth survey of the cohort of women born between 1946 and 1951, questions were asked about lifetime consumption of alcohol. Data from these questions and questions on quantity and frequency of alcohol consumed at each of the five surveys are being used to investigate the temporal relationship between mental health and alcohol consumption. A paper was published in Addiction in 2008. Project: W061 CAM use amongst mid-aged women: A national mixed- method study across the urban-rural divide ALSWH Investigators: x Dr Deborah Loxton x Assoc. Professor Jon Adams Collaborative Investigators: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Dr Anne Young (University of Newcastle) x Dr Alexander Broom (School of Humanities and Social Sciences, University of Newcastle) x Dr Marie Pirotta (School of Medicine, Dentistry DQG Health Services, University of Melbourne) x Professor John Humphreys (Medicine, Nursing and Health Science, Monash University) x Professor Marc Cohen (Health Sciences, Royal Melbourne Institute of Technology) x Dr Gavin Andrews (Department of Health, Ageing and Society, McMaster University) x Dr Deidre McLaughlin (School of Population Health, University of Queensland) x Assoc. Professor Joanne Barnes x Jon Wardle (School of Population Health, University of Queensland) Funding Source: NHMRC The aim of this project is to understand why higher proportions of women from the 1946-1951 cohort use complementary and alternative medicine (CAM) in rural areas than in urban areas of Australia. Women have been identified as major consumers of CAM in Australia – where CAM constitutes a diverse group of health-related substances, therapies and disciplines that are not considered to be part of mainstream medical care. The project will test whether higher levels of CAM use by women from the ALSWH cohort born 1946-1951 who live in rural areas is explained by: x limited access to conventional health care services x closer ties between rural GPs and CAM provision x ease of access to complementary health practitioners x dissatisfaction with conventional health care services x stronger informal community networks 40 x a greater perceived effectiveness of CAM The proposed study will use a sequential mixed-method design consisting of a mailed substudy survey of CAM users in 2008 (n=1690), telephone interviews with a subset (n=160) and diary methods (n=40), with the samples stratified by remoteness of area of residence. The project was awarded funding in April 2008 subject to ethics approval. An ethics application was approved in July by the University of Newcastle Human Ethics Research Committee and subsequently approved in August by the University of Queensland Ethics Committee. Funding was released by the NHMRC in October 2008 and recruitment for a Research Fellow is underway. The sub-study component of the project is planned for late May 2009 with participants from the 1946-1951 cohort. Project: A049 Weight control practices of mid-age women: Social determinants and health Impacts ALSWH Investigator: x Dr Anne Young Collaborative Investigators: x Dr Lauren Williams (School of Health Sciences, University of Newcastle) x Assoc. Professor John Germov (School of Humanities and Social Science, University of Newcastle) Funding Source: 2005 RGC, University of Newcastle The associations between social class and weight are relatively well established, but there are few population level studies of the relationship between social class, weight control practice and weight change. This study examined associations between self-defined social class, sociodemographic factors (income, education, occupation, area of residence) and weight control practices among 11 589 women from the 1946-1951 cohort (aged 47-52) participating in the ALSWH. The women who defined themselves as working class started with a higher mean BMI at Survey 1, and gained significantly more weight over the two year period (1.27 +/- 0.07kg), even after adjustment for baseline BMI and other potential confounders, compared with upper/middle class women (1.01 +/- 0.07kg). While the number of healthy weight women reporting a desire to weigh less occurred was higher in the upper/middle classes, nearly all of the women who were overweight or obese stated that they preferred to weigh less, irrespective of social class (91% of working class women and 93% of upper/middle class women). The working class women were found to have different patterns of weight control practices from the upper/middle class women. The upper/middle class women were more likely to use combinations of practices that included exercise, and women who identified as working class were significantly more likely to use potentially harmful weight control strategies (12.8%) than upper/middle class women (8.9%) (chi-squared test = 30.65, p<0.0001). The study showed that weight control practices are related to class, with this observation likely to at least partially explain the finding that working class women gained significantly more weight over a two year period than women who defined themselves as upper or middle class. The analysis on social determinants of weight control practices has been completed. A paper on these results is in preparation, and when it is submitted, the project will be completed. 41 Project: A049A Weight control practices of mid-age women: Social determinants and health Impacts ALSWH Investigator: x Dr Anne Young Collaborative Investigators: x Dr Lauren Williams (School of Health Sciences, University of Newcastle) x Assoc. Professor John Germov (School of Humanities and Social Science, University of Newcastle) Funding Source: 2005 RGC, University of Newcastle This extension of project A049 plans to examine longitudinal changes in strategies for maintaining and controlling weight by comparing the weight control practices used in Survey 2 with those in Survey 5. A planning meeting with statisticians has been held, and analysis is expected to begin in 2009. &RPSOHWHGSURMHFWV Project: A153 Physical activity, weight and mental health ALSWH Investigator: x Professor Wendy Brown Collaborative Investigators: x Dr Kylie Ball (School of Exercise DQG Nutrition Sciences, Deakin University) x Dr Nicola Burton (School of Human Movement Studies, University of Queensland) The aim of this study was to investigate the associations between physical activity, overweight/obesity and depressive symptoms in the ALSWH 1921-1926 cohort. Overweight and obese women were more likely to develop depressive symptoms than those of healthy weight. Active women were less likely to develop symptoms than those who were sedentary, though this was statistically significant only for low and high levels of activity after multivariable adjustment. Both an increase and a decrease in BMI over three years were significantly associated with increased risk of symptoms. Sedentary women who increased their activity over three years had a lower risk of symptoms than those who remained sedentary. Increases in activity were protective against depressive symptoms regardless of BMI changes, except for those women who increased BMI by more than 10%, amongst whom risk for depressive symptoms was comparable with those who remained sedentary. This project has been completed. A paper has been written and accepted for publication in Obesity. Project: A189 Height loss in elderly women ALSWH Investigator: x Professor Annette Dobson Collaborative Investigators: x Melanie Spallek (School of Population Health, University of Queensland) x Richard Hockey (School of Population Health, University of Queensland) x Dr Janneke Berecki (School of Population Health, University of Queensland) Height loss is associated with osteoporosis but little is known about its consequences. This study examined risk factors for height loss and symptoms. 42 Women in the 1921-1926 cohort (aged 70-75 in 1996) who provided data on height at any two consecutive surveys (held in 1996, 1999, 2002 and 2005) were included (N=9852). A regression model was fitted with height loss as the outcome and sociodemographics, osteoporosis and risk factors for falls as explanatory variables. Self-rated health and symptoms related to postural changes or raised intra-abdominal pressure were analysed using height loss as an explanatory variable. Over 9 years, average height loss per year was -0.12% (95%CI: -0.13 to -0.12) of height at Survey 1. Osteoporosis, underweight and medications for sleep and anxiety were risk factors. Heartburn/indigestion, constipation, stress incontinence and a decline in self-rated health were associated with height loss, adjusting for potential confounders. These findings highlight the importance for medical practitioners of monitoring height in older women as an early marker of health problems. Project: A186 The impacts of caesarean section in Australian women ALSWH Investigators: x Dr Deborah Loxton x Professor Julie Byles Collaborative Investigators: x Assoc. Professor Pauline Chiarelli (School of Health Sciences, University of Newcastle) x Michael K Drew (School of Health Sciences, University of Newcastle) x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) This study examined whether women in the 1946-1951 cohort who have had a caesarean section (CS) are at a higher risk of developing back problems over the longer term. In view of the fact that delivery by CS had steadily increased to 29% in 2004, with higher rates among older, privately insured mothers, it seemed reasonable to explore the impacts of such deliveries on health issues over the longer term. The pelvic floor muscles and diaphragm have dual roles involving postural and respiratory functions. During situations where demand for one of these functions is increased the muscle activity is altered. These alterations in muscle activity have been proposed to precipitate lower back pain (LBP). Similarly, this study hypothesized that trauma to the abdominal wall (such as occurs during caesarean section) might predispose women to LBP over the longer term. Such injury may precipitate LBP through biomechanical dysfunction arising from reduced muscle force capabilities with secondary deconditioning from pain inhibition during the postoperative period. The study showed that while parity may be associated with onset of LBP in younger women, it does not appear to be associated with back pain over the longer term and neither is CS. The fact that LBP is associated with urinary incontinence and breathing disorders is supported by this study. Women’s place of residence, education, menopause, arthritis, asthma, osteoporosis, stiff and painful joints, breathing disorders, urinary incontinence and smoking status all had a statistically significant association with back pain, however delivery by caesarean section did not increase the likelihood of self-reported back pain over the longer term in women in the 1946-1951 cohort. Analysis is now complete, and a paper is in press at the Australian Journal of Physiotherapy awaiting publication. 43 6WXGHQWSURMHFWVLQSURJUHVV Projects: A042/A166B Adjusting for death in longitudinal studies PhD Candidate: x Steven Bowe (Centre for Clinical Epidemiology and Biostatistics, University of Newcastle) Supervisors: x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Dr Anne Young (University of Newcastle) Expected Completion: July 2009 Project objectives: x To investigate the statistical methods used to account for death in longitudinal studies. x To apply the current statistical methods to ALSWH data for the 1921-1926 cohort and evaluate the advantages and disadvantages of the methods. x To determine whether there is a need to improve current statistical methods and apply and assess new strategies if applicable. x To examine the impact of diabetes on quality of life among older women - adjusting for deaths by applying the methods developed. Findings to date: 1. Observed longitudinal changes in physical health for women with diabetes may be poorly estimated due to loss of data through deaths and other reasons. 2. Analysis of changes in physical health, after including scores for participants who die, indicate poorer and worsening physical health for women with diabetes. 3. Longitudinal analysis including values for death, as well as imputing value missing for other reasons, may provide better estimates. 4. After including deaths and imputed scores, the mean probability of being healthy (in three years) for women who reported having diabetes was lower than when deaths and missing data were ignored. The next stage of this research project is to determine whether other proposed methods for accounting for deaths using Health Related Quality of Life (HR-QOL) outcomes would be valid for use with ALSWH data. There will also be an attempt to determine whether current methods can be improved and/or adapted to the ALSWH data. The first paper published from this project, ‘Transforming the SF-36 to account for death in longitudinal studies with three year follow-up’ has been cited 5 times, and was mentioned in a White Paper with Recommendations for the Medicare Health Outcomes Survey. An oral presentation was made in September 2008 at the International Epidemiological Association World Congress, Porto Alegre, Brazil. 44 Project: A205 The impact of health on lifetime earnings, labour force experience and retirement and the effects of all these factors on the degree of income and health inequalities post retirement PhD Candidate: x Joanne Flavel (National Institute of Labour Studies, Flinders University) Supervisors: x Professor Sue Richardson (National Institute of Labour Studies, Flinders University) x Dr Anna Ziersch Expected Completion: 2011 The project applies an economic framework to empirically analyse relationships between poor health and labour market outcomes in Australia. By discovering the ways in which poor health during working age can result in accumulating labour market disadvantage over the life course, this project will enable a better understanding of the effect of earlier health inequities on outcomes post retirement, particularly in relation to the degree of income and health inequities for retirees. It will build on previous research which studied the relationship between health and a number of individual labour market outcomes by conducting a thorough analysis of the extent to which poor health results in accumulating disadvantage across a range of outcomes. It is proposed that the effects of ill health on the earnings distribution and on labour force experience leads to increased income and health inequities post retirement. Research planning has progressed and a detailed analysis protocol has been developed, including a detailed and thorough review of the literature. Descriptive analyses have been commenced as a preliminary to more complex econometric analyses to determine the effect of health on labour market outcomes and the extent to which these effects are cumulative over the life course. A brief overview of the project was presented at the Flinders University Postgraduate Conference, ‘Thinking Synergy’ on the 29th September 2008. Project: A228 Economic analysis of BMI and employment patterns in Australian women PhD Candidate: x Nicole Au (Centre for Health Economics, Monash University) Supervisors: x Professor Wendy Brown (School of Human Movements, University of Queensland) x Assoc. Professor Bruce Hollingsworth Economic studies have claimed that the rise in overweight and obesity over the last few decades may be partly due to the increase in the labour force participation rates and hours worked, particularly by women. The main stumbling block to investigating the relationship between BMI and labour market participation is endogeneity, or the problem of reverse causality: it is unclear if BMI affects labour market participation and wages, or the other way round, or if there is no causal relation and (a set of) other variables affect jointly BMI and labour market variables. Longitudinal data are required to tackle this problem, because they allow separating variations between observations at one point in time from variations over, and a sequential analysis of events. This project uses longitudinal data from the ALSWH to investigate the relationship between labour market outcomes (employment status, income and hours worked) and obesity in women, using data from all surveys of the 1946-1951 and 1973-1978 cohorts. The main questions will be: 45 x Is there an association between a higher BMI and employment status? x Is there an association between longer work hours and a higher BMI in employed women? x Is there an association between lower wages and a higher BMI in employed women? Project: A044 Psychological adjustment after breast cancer diagnosis and treatment PhD Candidate: x Lisa Beatty (School of Psychology, Flinders University) Supervisors: x Assoc. Professor Tracey Wade (School of Psychology, Flinders University) x Professor Christina Lee (School of Psychology, University of Queensland) Funding Source: Australian Postgraduate Award, and the FMC Foundation Lyn Wrigley Award Expected Completion: March 2009 The overall aim of this project is to identify factors (using data from the ALSWH 1946-1951 cohort) that impact women’s adjustment to breast cancer (BC) diagnosis or treatment in order to develop an intervention workbook that addresses these issues. The project plans: x To explore group differences in quality of life, as measured by the eight SF-36 domains, between women who developed breast cancer at each survey and those who did not. x To determine if perceived stress mediates the relationship between initial life events and change in quality of life over time, using a subsample of women who did not have breast cancer at Survey 1, but who subsequently developed breast cancer at either Survey 2 or 3. The results from Study 1 influence the direction taken in subsequent studies (which do not use ALSWH data). Data analysis has been completed. Four non-overlapping groups of women were derived, with a final sample size of 10 543 women. The four groups of women were statistically compared over time for the eight quality of life outcomes using a multivariate analysis of variance (MANOVA). Significant interactions were found for bodily pain, general health, role physical, physical functioning and social functioning, suggesting that changes in functioning over time differ between groups. Further examination suggested that each BC group experienced significantly worse quality of life (QoL) functioning at the respective time points they had been diagnosed with BC compared with women who had never been diagnosed. The only exception to this was physical functioning, for which no differences were found. In order to prospectively test the hypothesis that perceived stress mediates the relationship between initial life events and change in QoL over time, the two groups of women who did not have breast cancer in Survey 1 but had developed breast cancer subsequently by Surveys 2 and 3 (BC-T2 and BC-T3) were combined for prospective analyses (n=140). Longitudinal modelling was then used to test the relationship between life events, stress and change over time in the eight SF-36 QoL domains. Initial life events and perceived stress predicted change in four QoL domains. There was prospective evidence for the predicted mediational relationship for the domains of role emotional and social functioning. Pre-BC life events and, particularly, stress have therefore been identified as important predictive factors for poorer outcomes in certain areas of functioning following diagnosis of BC. Future research can build 46 upon current findings by implementing and systematically evaluating a stress-management intervention for women at risk of poorer outcomes. A manuscript is in revision for the British Journal of Health Psychology and an intervention workbook to assist women in dealing with these (and other psychological) issues following BC diagnosis and treatment has been developed. Project: A170 The aspirations and life goals of young women during the period of emerging adulthood PhD Candidate: x Melissa Johnstone (School of Psychology, University of Queensland) Supervisors: x Professor Christina Lee (School of Psychology, University of Queensland) x Assoc. Professor Nancy Pachana (School of Psychology, University of Queensland) Funding source: APA Scholarship Expected completion: March 2009 This project aims to: x Examine young Australian women’s aspirations for work and family, with reference to the theory of Emerging Adulthood as well as Hakim’s Lifestyle Preference Theory. x Identify and understand young Australian women’s aspirations/goals/life plans and uncertainties, regarding employment, family, relationships, residence, living and finance, during their transition into adulthood. x Understand how young women successfully navigate and subjectively experience the passage into early adult life. Phase 1 Quantitative analyses of the data collected from Surveys 1, 2 and 3 of the 1973-1978 cohort of the ALSWH were conducted, both cross sectionally and longitudinally, focusing on responses to the questions regarding young women’s aspirations for employment, motherhood and relationship status at age 35. The results were assessed with reference to Hakim’s Lifestyle Preference Theory and the theory of Emerging Adulthood. It was found that Hakim’s Lifestyle Preference Theory did not adequately explain young women’s aspirations for work and family. Young women could not be easily categorised into Hakim’s Lifestyle Preference Groups: they were not consistently aspiring to a particular ‘type’ of lifestyle and they were not aligning their behaviour at Survey 3 with their aspirations from Survey 1. Based on these findings, two manuscripts have been prepared. One attempts to explain the longitudinal aspirations of the young women and discusses the discrepancies between Hakim’s model and the present data. A paper has been prepared and is being re- submitted to a journal on Women’s Studies. The second manuscript, which is under second review, examines individual and sociocultural differences between women with varying aspirations. Phase 2 The second phase of the project involved analysing the written comments obtained from Surveys 1, 2 and 3 of the 1973-1978 cohort of the ALSWH. This analysis focused on young women’s comments that were specific to the topic of aspirations and the transition into adulthood; particularly comments regarding employment, family, relationships, living, finance 47 and lifestyle. Currently, the comments from all three surveys have been read and prepared into a comparative discussion. Paid work, study, travel, living, relationships and motherhood were major themes that emerged from each survey. The young women described a large degree of change and instability in some of these areas. In addition, the tone of the comments changed across the surveys. Increasingly, the comments suggested that the women were becoming less self- focused and more considerate of other people, more self-reflective and more accepting of life’s challenges. They increasingly expressed concern about their futures and anticipated difficulties with fitting in everything they wanted to achieve. Some of the findings demonstrated similarities to Arnett’s theory of Emerging Adulthood, especially to the tenets of exploration, change and instability. A poster which gives consideration to whether these themes are a reflection of a specific period of the lifespan or reflects adult life more generally in the 21st Century, was presented at the Australian Society for Behavioural Health and Medicine Annual conference in Bondi at the end of January 2008. A manuscript to be submitted for publication is also in progress. Descriptive findings and analyses from Phase 1 examining women’s longitudinal aspirations for work and family, and qualitative comments referring to women’s aspirations from Phase 2 were presented at the Australian Institute of Family Studies Conference in July 2008. An invited paper, based on this presentation, is currently under review. Project: A218 Marriage and de facto relationships: Is there a difference? PhD Candidate: x Nicole Arthur (School of Psychology, University of Queensland) Supervisors: x Professor Christina Lee (School of Psychology, University of Queensland) Funding source: APA Scholarship Expected completion: March 2009 Social ties are integral to health and well-being, with marital relationship status being one of the most important predictors of health and well-being. Although contemporary research usually treats cohabiting relationships as equivalent to marriage, research suggests that significant differences in health and well-being may exist between married and cohabiting individuals. Because the majority of this research is cross sectional, however, it is not clear whether pre-existing differences lead individuals to select marriage or cohabitation, or whether the differences arise from the nature of the relationships. Additionally, evidence suggests that differences exist between men and women in the health and well-being correlates of various relationship states. These findings are important at both methodological and clinical levels. If these two groups are meaningfully distinct then it is important that they are treated separately in research. Secondly, if cohabiting relationships are different from marriages, or if different individuals move into them, this has relevance for both couple and individual therapy and potentially in the prevention of relationship breakdown. The ALSWH provides an opportunity to examine marriage and cohabitation longitudinally within a national sample of women. Women who were single at Survey 2 (N = 3868, aged 22- 27) were divided into three groups – those who would still be single at Survey 3, three years later, those who would be married, and those who would be in cohabiting relationships. Those with other statuses were excluded from analysis. Firstly, we explore pre-existing differences (at Survey 2, when all women were single) in sociodemographic, physical health, health behaviours and psychological variables. Secondly, we explore whether differences exist on 48 these same variables at Survey 3, after the transition, and thirdly whether post-transition differences can be explained by pre-existing differences between the groups of women. Using a selection of variables assessing sociodemographic status, health behaviours, physical health, and mental health, results suggest that there are both pre-existing differences between these three groups of women and differences that are apparent after the transition. Those who will go on to marry tend to have more conventional and less risky lifestyles, characterised by lower rates of smoking, unsafe use of alcohol, and illicit drug use, and fewer sexual partners, and to have the highest levels of mental well-being. Statistical adjustment for pre-existing differences attenuates, but does not completely remove, the post-transition differences. These findings suggest that both selection and social integration processes may be influential in determining women’s relationship status and health and well-being, and this has implications at both a methodological and clinical level. The analyses have been completed and the work is currently under examination in the form of a doctoral dissertation, submitted by the candidate for the degree of D Psych (Clinical). It is planned to revise the work for submission to a peer-reviewed journal. Project: A126 Coping with miscarriage: Young women’s experiences PhD Candidate: x Ingrid Rowlands (School of Psychology, University of Queensland) Supervisors: x Professor Christina Lee (School of Psychology, University of Queensland) x Assoc. Professor Nancy Pachana (School of Psychology, University of Queensland) Funding Source: University of Queensland Joint Research Scholarship Expected Completion: December 2008 This project combined quantitative and qualitative methods to examine both women’s psychological well-being after miscarriage and the specific coping strategies that are associated with coping well with this event. First, an epidemiological approach was taken by cross sectionally investigating the psychological correlates, and relevant sociodemographic, reproductive and health-related variables associated with miscarriage among the 1973-1978 cohort. Sociodemographic and reproductive variables were most strongly associated with having a miscarriage. Using the same data but applying longitudinal methods, whether women’s mental health, stress and optimism varied over time and according to women’s miscarriage status, was examined. Relevant sociodemographic and reproductive variables identified in the cross sectional analyses as possible confounding variables were controlled in these analyses. Miscarriage was found to affect young women’s mental health, stress and optimism over time, with poorer outcomes on all variables for women reporting miscarriage when compared with women who had never miscarried. Because miscarriage has significant effects on women’s mental health and wellbeing, the predictors of, and coping strategies related to coping well after miscarriage, were examined next. In the next stage, predictors of mental health among young women reporting miscarriage were investigated using quantitative methods. Optimism, social support and the number of miscarriages were strong predictors of mental health among women reporting miscarriage. In order to gain an in-depth understanding of women’s lived experiences of miscarriage, interviews were conducted with nine women to explore the specific coping strategies related to positive outcomes after miscarriage. Social support was reported as facilitating adjustment to miscarriage, consistent with the quantitative analyses. Acknowledgement and support from health professionals was also described as facilitating adjustment. While the quantitative analyses had also initially suggested that satisfaction with the general practitioner was an 49 important predictor of adjustment, this variable did not reach significance when other reproductive and psychological variables were controlled for. Taking all the results into consideration, it appears that changes to social norms and attitudes regarding miscarriage may help women to cope with this challenging and distressing experience. Interventions to help women cope with miscarriage need to be grounded in an understanding of women’s need for social and family support, and understanding from health professionals. A presentation from this project was made at Society of Reproductive and Infant Psychology Conference in London in September 2008. Project: W042 Childlessness and the role of choice in childless women’s reproductive outcome Student: x Heather McKay (Key Centre for Women’s Health in Society, School of Population Health, University of Melbourne) Supervisors: x Assoc. Professor Jane Fisher (Key Centre for Women’s Health in Society, School of Population Health, University of Melbourne). x Professor Christina Lee (School of Psychology, University of Queensland) Funding source: Melbourne Research Scholarship (Faculty-Based MRS). The Victorian component of data collection for this study is supported by a grant from the Helen Macpherson Smith Trust. Expected completion October 2009 Since the 1960’s significant economic, political, social and cultural changes have occurred in Australia that have affected the nature of families and family values. At the same time there has been a decline in our fertility rate and an increase in lifetime childless rates. It is now predicted that between 20 and 25% of Australian women will not give birth to a child and that increasingly women are choosing this reproductive outcome. This study aims to investigate why women remain biologically childless, the role of choice in this reproductive outcome, and its impact on women’s lives. In doing so it also seeks to develop and enhance knowledge of voluntary childlessness. ALSWH participants from the 1946-1951 cohort were chosen for this study because although their childless status is unchangeable, they are young enough to have lived their childbearing years after the baby boom (1961) and since effective contraception became widely available. Data for the project were obtained in two ways: firstly via secondary analysis of existing relevant information collected as part of the main ALSWH project, and secondly via a sub- study survey sent to a subset of the ALSWH 1946-1951 cohort participants who indicated in Survey 1 that they had never given birth to a child. The latter method was the main focus of this study. Secondary Analysis Phase: Motherhood status for the ALSWH 1946-1951 cohort participants was determined - of the 14 099 women in this cohort, 339 had inconsistent or missing data, and 119 were biologically childless, but performed a social mothering role (as a step or adoptive mother). This left an eligible sample of 13 641 and, when the standard study area weightings were applied, 91% of them were biological mothers and 9% childless. At mid-age, childless women were found to have higher levels of education and were more extensively engaged in the paid workforce than mothers. There were no differences in the health status between mothers and childless women; however, life satisfaction differences between the two groups were complex. 50 Sub-Survey Phase: Five hundred and thirty five sub-study surveys were sent with a response rate of 80%. Women responded well to being questioned about their choice in remaining childless, the priority they gave to having a child, and the reasons for their biological childlessness. Their answers allowed three categories of childless women to be formed according to the degree of choice women felt they had in this reproductive outcome. Although women’s reasons for remaining biologically childless were quite different, they generally recognised that there were numerous positive outcomes for themselves and others associated with their non-motherhood. However, women with less choice in the reproductive outcome were more likely to see negatives associated with their resultant lives. Women who believed they had some choice in their childlessness also reflected on their decision. Some indicated other people were involved in their choice and this other party was usually their male partner; however, women’s comments revealed there was a spectrum of involvement by these men in the decision to remain childless. Project: A213 Cardiovascular drugs utilisation in diabetic women Masters Student: x Nur Hikmayani (School of Medicine DQG Public Health, University of Newcastle) Supervisor: x Professor Julie Byles (ALSHW, Centre for Research and Education in Ageing, University of Newcastle) Expected completion December 2008 The aim of this study is to look at the pattern of how cardiovascular drugs, either individually or in combination, are utilised by diabetic individuals. The study will further seek to investigate the association between patterns and quality of life (QoL) scores across 4 domains (general health, physical functioning, mental health, and social functioning). This study is cross sectional and will use a sample from the fourth survey of the 1921-1926 cohort. Analysis is underway, and is expected to be completed this year. Project: A086 Resilience and coping: Predicting positive well-being following life transitions and major life events among young Australian women PhD Candidate: x Rachel Thompson (School of Psychology, University of Queensland) ALSWH Investigators: x Professor Christina Lee x Assoc. Professor Nancy Pachana Funding Source: ARC Discovery Grant A major set of papers is underway on the question of divorce and women’s well-being. These include x A literature review on evidence from longitudinal studies on the relationships between emotional well-being and divorce (submitted for publication). x A literature review on cross sectional and longitudinal evidence on the relationships between indicators of physical health (including mortality, morbidity, specific diagnoses, perceived health, and health behaviours) and divorce (in preparation). x A longitudinal analysis of the trajectory of mental health measures among the 1946-1951 cohort and the effect of divorce on this trajectory (planning stages). 51 Project: A185 An examination of trends in women’s sexual and reproductive health over 10 years: )indings from the ALSWH Doctorate candidate: x Danielle Herbert (School of Population Health, University of Queensland) Supervisors: x Dr Jayne Lucke (School of Population Health, University of Queensland) x Professor Annette Dobson (School of Population Health, University of Queensland) Funding source: University of Queensland mid-year scholarship Expected completion: August 2010 The main focus of this project is the analysis of sexual and reproductive health (SRH) as predictors of fecundity, fertility and infertility. This project is currently in Phase 1 of the research plan. Phase 1: Description of trends from Survey 1 (1996) to Survey 4 (2006). Increasing numbers of women are delaying their childbearing years and this trend is well recognised. Delayed childbearing, however, does not necessarily equate to no pregnancies prior to a live birth. Many women have had pregnancies not resulting in a live birth which therefore do not appear in fertility statistics. Recognised pregnancy losses include spontaneous loss: miscarriages, <20 weeks gestation, and stillbirths, 20+ weeks; and induced losses, terminations and ectopic pregnancies. Comprehensive reproductive histories are an important measure of both fecundity (reproductive ability) and fertility (live births). At age 18-23 more women reported terminations (7%) than miscarriages (4%). By 28-33 years the cumulative frequency of miscarriage (15%) was as common as termination (16%). For women aged 28-33 years who had ever been pregnant (n=5343), pregnancy outcomes were: birth only (50%); loss only (18%); and birth and loss (32%), of which half (16%) were birth and miscarriage. A comparison between first miscarriage and first birth (no miscarriage) showed that most first miscarriages occurred in women aged 18-23 years who also reported a first birth at the same survey (15%). Half (51%) of all first births and first miscarriages in women aged 18-19 ended in miscarriage. Early childbearers (before the age of 28 years) often had miscarriages around the same time period as their first live birth suggesting pro- active family formation. Delayed childbearers (32-33 years) had more first births than first miscarriages. Recognised pregnancy losses are an important measure of fecundity in the general population because they indicate successful conception and maintenance of pregnancy to varying reproductive end-points. Many recognised pregnancy losses will not be documented in medical records and therefore women’s self-reported histories are of particular value. It is imperative that government policy continues to support quality health services for induced pregnancy losses and management of spontaneous pregnancy losses. Such policies will protect the future fecundity and fertility of all women, and is particularly relevant for women who delay childbearing. Phase 2: How does early sexual and reproductive health influence later reproductive health outcomes? The trends identified from Phase 1 will be compared with the sexual and reproductive histories of women presenting to infertility specialists with primary or secondary infertility. The ability to conceive and/or respond to assisted reproduction technology (ART) treatments may be determined by individual sexual and reproductive histories. 52 Ethical approval was received from the UQ Medical Research Ethics Committee to survey women seeking fertility treatment at private clinics. A pilot study of the surveys was undertaken in June 2008 and completed in July 2008. The main survey collection period began at the end of July 2008 and will continue up to July 2009. Presentations of work from both phases were made at the 2008 Population Health Congress Brisbane, July, and a paper from this project has been accepted for publication in Women’s Health Issues. Project: A224 Miscarriage or termination of pregnancy in young and middle-aged Australian women: Are they infertile? Doctorate candidate: x Danielle Herbert (School of Population Health, University of Queensland) Supervisors: x Professor Annette Dobson ( School of Population Health, University of Queensland) x Dr Jayne Lucke (School of Population Health, University of Queensland) Expected completion: December 2009 Women with fertility problems who have used assisted reproduction technologies (ART) are recorded in data registries. This study identifies the factors associated with seeking advice and using treatment among a general population of women, not necessarily recorded in registries. Participants in the ALSWH cohort born 1973-1978 completed up to four mailed surveys over ten years (N=9145) and were aged 28-33 years in 2006. Binomial logistic regression was used to identify the sociodemographic, biological (including reproductive histories), and behavioural factors associated with seeking advice and using treatment among those who reported having fertility problems. Seventy-two percent (n=728) of women with fertility problems (n=1031) sought advice, but only 50% (n=356) used treatment. Women with fertility problems who were obese or daily smokers were less likely to seek advice compared with those of healthy weights or non- smokers. Women with a history of miscarriages only were more likely to seek advice than women who had births only, as compared with those who had never been pregnant. Women with polycystic ovary syndrome (PCOS) or endometriosis were most likely to seek advice, compared with women without either condition; those with PCOS were also more likely to use treatment. The majority of women with fertility problems do seek advice but two-thirds of these women will not use treatment. Women with an identifiable cause for their fertility problems, e.g. PCOS, are the most proactive in seeking advice and using ART. Findings from this study were presented at the Public Health Association of Australia Queensland State Conference (September 2008), the Fertility Society of Australia conference (October 2008), and the UQ School of Population Health, Research Higher Degree Conference (November 2008). 53 Project: A176 Predictors of post natal depression PhD Candidate: x Catherine Chojenta (School of Humanities and Social Science, University of Newcastle) Supervisors: x Dr Deborah Loxton (School of Humanities and Social Science, University of Newcastle) x Dr Jayne Lucke (School of Population Health, University of Queensland) Expected Completion: December 2012 Depressive episodes are the most common form of morbidity after childbirth. The reported prevalence of postnatal depression (PND) among Australian mothers is placed somewhere between 10 and 20%. The consequences of PND to the mother include neglect of the child, relationship breakdown, increased risk of suicidal ideation and self harm. Both psychosocial and childbirth experiences have been found to precede the onset of PND, however many of the past studies into PND have not been able to incorporate a wide spectrum of risk factors in one analysis. The ALSWH provides a unique opportunity to examine the patterns of prevalence of PND over an 11 year period and the longitudinal antecedents of PND among young Australian women. An examination of data collected from the first 4 surveys of the 1973-1978 cohort conducted by the ALSWH is currently underway. At Survey 4 in 2006, 37% of participants who had completed all four surveys had given birth to a child in the four years preceding the Survey. Ten per cent of these women reported being diagnosed or treated for PND in the last three years. A range of antecedents of PND were investigated such as socioeconomic factors, life events, social support and previous diagnoses of depression and anxiety. Of note, women who were diagnosed or treated for depression at Survey 2 or 3 were three times more likely than other women to report being diagnosed or treated for PND at Survey 4, and women who reported experiencing 5 or more life events at Survey 4 were also more than 3.5 times more likely to experience PND. Findings indicate a complex range of life events, and other mental health diagnoses precede a diagnosis of PND. A poster from this project was presented at the Marce Society International Conference in Sydney, September, 2008. Project: A179 When life’s a pain: The relationship between stress and modifiable psychosocial factors in arthritis PhD Candidate: x Melissa Harris (Health Behaviour Sciences, School of Medicine and Public Health, University of Newcastle) Supervisors: x Dr Deborah Loxton (Research Centre for Gender, Health and Ageing, University of Newcastle) x Assoc. Professor David Sibbritt (School of Medicine and Public Health, University of Newcastle) x Professor Julie Byles (Centre for Research and Education in Ageing, University of Newcastle) Expected Completion: December 2011 This study aims to: x Conduct a sequential cross sectional analysis across five time points in order to examine the psychosocial factors that distinguish middle aged women who develop arthritis from those who do not. 54 x Conduct a prospective predictive analysis using multiple linear regression in order to examine the psychosocial pathways that contribute to arthritis in middle aged women, as well as variables that may influence and modify the stress process. x Evaluate conceptual models of the psychosocial pathways in arthritis onset and psychosocial mediators and moderators of arthritis on health status, based upon theoretical knowledge and prior research, through structural equation models. x Compare patterns of health service use among women with joint pain and determine potential psychosocial barriers to seeking treatment. The project is exploratory in nature, and hypotheses the following: x Middle aged women diagnosed with arthritis will possess significantly higher levels of psychological stress than other middle aged women. x Middle aged women diagnosed with arthritis will use significantly more passive coping mechanisms in their attempt to minimise stress than other middle aged women x The relationship between stress and disease will be mediated by such factors as emotional distress, and pessimism and moderated by life control and social support. The identified psychosocial factors will also impact upon the help-seeking behaviour of middle aged women with joint pain. Project: A211 ‘In their own words’ healthy ageing in late modernity: An analysis of the ‘free-text’ comments from the older cohort of the Australian Longitudinal Study of Women’s Health Master candidate: x Lyn Adamson (Research Centre for Gender, Health and Ageing, University of Newcastle) Supervisors: x Assoc. Professor John Germov (Research Centre for Gender, Health and Ageing, University of Newcastle) x Dr Deborah Loxton (Research Centre for Gender, Health and Ageing, University of Newcastle) x Professor Julie Byles (Research Centre for Gender, Health and Ageing, University of Newcastle) Funding Source: Research Centre for Gender, Health and Ageing Expected Completion: 2011 This project intends to analyse the longitudinal qualitative data from the 1921-1926 cohort of the ALSWH to provide insights into the social experiences of ageing among women who have experienced and survived tremendous social and cultural change across the life course. A content analysis of the longitudinal free-text comments of the 764 participants of the 1921- 1926 cohort who completed the section ‘is there anything else you would like to tell us about your health’ at all four timepoints of the survey is in progress. The comments have been compiled into an appropriate database. These data are being coded to establish themes and content to allow further in-depth analysis to take place. Analysis of 300 has been completed so far. These results will be used to further focus the research. The researcher intends to add to the existing database the comments of any of the originally selected 764 participants who may have responded to this question at Survey 5. 55 Project: A144 The impact of trauma on young women’s health behaviours Professional Doctorate x Toni Lindsay (School of Behavioural Sciences, Candidate: University of Newcastle) Supervisors: x Dr Jenny Bowman (School of Behavioural Sciences, University of Newcastle) x Dr Deborah Loxton (Research Centre for Gender, Health and Ageing, University of Newcastle) Expected completion: February 2009 This project aims to examine the impact of traumatic life events on young women and their health behaviours including alcohol use, smoking, illicit drug use, as well as sexual practices. In order to examine this, the data from the first three 1973-1978 cohort surveys are being utilised. Final analyses are being completed. The data have been analysed using both ANCOVAs and Generalised Estimating Equations modelling. Preliminary results indicate that those younger women who are exposed to a major traumatic event in the year prior to the survey, are more likely to adopt negative health behaviours including smoking, drinking at a risky level, illicit drug use, and to have negative eating behaviours and self harming behaviours, and also to report suicidal ideation. In addition to this, results indicate that those who have more ongoing life events are also more likely to start adopting these negative behaviours compared with those with fewer ongoing life events. Women were also shown to increase their smoking, drinking and illicit drug use following a traumatic event. This study is in the final stages of editing and will be completed in the coming months. Project: A051 Declining fertility rates and the normalisation of technological control of reproduction among young Australian women PhD Candidate: x Rosie Mooney (School of Humanities and Social Science, University of Newcastle) Supervisors: x Dr Penny Warner-Smith (School of Humanities and Social Science, University of Newcastle) x Dr Ann Taylor (School of Humanities and Social Science, University of Newcastle) Funding Source: University of Newcastle Research Scholarship (External) DQGUniversity of Newcastle Project Grant Expected Completion: December 2009 This project explores the planned and expected timing of childbearing for young Australian women, through an investigation of the relationship between their perceptions and experiences of fertility, technology and motherhood. The research topic stems from government and societal concerns surrounding Australia’s ageing population, and changes in fertility patterns, including delayed childbearing, increased childlessness and smaller family size. The research follows a mixed method integrated and interactive design, consisting of three components and combining qualitative and quantitative data, forms of analysis and methodologies. Within this approach priority was given to qualitative methods and methodology, supporting the ontological belief in multiple realities through the use of methodological triangulation to achieve a complete picture of the research question. 56 Component one involved the analysis of existing qualitative data collected from ALSWH 1973-1978 cohort participants at Survey 1 (1996), Survey 2 (2000) and Survey 3 (2003) in response to the question: ‘Have we missed anything?’ The representativeness of those who wrote ‘reproductive’ comments was assessed using existing linked quantitative data from the corresponding surveys. For component two, young women aged 18 to 30 years were recruited to participate in focus group discussions and to complete a written survey about their reproductive decision-making. Twenty-four women participated in six focus groups and one interview in several urban areas around NSW. The discussions were audio taped and transcribed. Components one (written comments) and two (focus groups) were conducted concurrently with preliminary findings from each informing their ongoing conduct as the research progressed. Component three of the research was informed by preliminary findings from components one and two which emphasised the complexity women experience in finding the perceived ‘right time’ to have children and the consequent delaying of childbearing. Fifty participants from the 1973-1978 ALSWH cohort, then aged 27-32 years, participated in a sub-study about their reproductive decision-making, which involved the completion of a written survey and a semi- structured telephone interview. Eligibility criteria included living in a marriage or a de facto relationship, having no children, and not being currently pregnant. The interview data have been transcribed and the survey data entered and verified. The ALSWH written comment data, focus group transcripts and interview transcripts have and are being descriptively and thematically coded and analysed with the assistance of the qualitative software package N6 (NUD*DT version 6). Recent analyses of data from component three (telephone interviews) have explored the impact that young women’s perceptions of motherhood as a construct and identity has on their planned childbearing decisions. Issues of selfhood were a preoccupation in the interviews, with women expressing two broad concerns with regard to becoming a ‘mother’: whether they felt they could live up to the ideal of the ‘good’ mother that they and society have created, and a fear of loss of self due to perceptions about the all encompassing ‘selfless’ nature of the mother-role. With the latter issue being exacerbated by a general belief that society, and sometimes the interviewees themselves, did not value the mothering identity. These anxieties caused a thread of doubt to weave through the majority of the interviews and contributed to analyses that categorised around half of the women interviewed as being unsure or ambivalent about becoming a mother. However, combined with the fact that many also expressed an innate desire to have children, variously described as ‘inevitable’, being ‘clucky’, or a ’strong inner biological urge’, the fears manifested themselves in two common coping strategies. Firstly, awaiting perceived emotional maturity and personal readiness before embarking on motherhood, were seen to increase their ability to mother well and ’cope’ with the challenges the role is believed to present. While, achieving self-fulfilment in all areas of their life prior to having children, and continuing their career identity after having children, were described as potential answers to identity loss and being ’just a mum’. Both solutions focus on the need for precursors to motherhood, thus increasing the potential for delayed childbearing. Data collection for all components is now complete. Analyses of these data are ongoing, and findings from all three components are being triangulated at the interpretation phase of the research. 57 Project: W048 Work-life tensions: Time pressure, leisure and well-being among dual earner parents PhD Candidate: x Leanne Fray (School of Humanities and Social Science, University of Newcastle) Supervisors: x Dr Penny Warner-Smith (School of Humanities and Social Science, University of Newcastle) x Dr Kevin Lyons Expected Completion: December 2008 The PhD project attached to the Work-Life Tensions project titled ‘Children’s leisure and recreation across three generations’ is currently in the writing up phase. All data collection has been completed and a complete draft of the thesis is planned for completion by December 2008 with submission in early 2009. Project: A234 The impact of out-of-pocket costs on the use and distribution of cervical screening services Doctorate candidate: x Kees van Gool (University of Technology Sydney) Supervisors: x Dr Deborah Loxton (ALSWH, University of Newcastle) x Assoc. Professor Elizabeth Savage x Assoc. Professor Rosaline Viney Expected completion: April 2010 In 1991, Australia implemented a cervical screening program to encourage women from ages of about 18 to 70 to have a biennial Pap smear. General practitioners and pathology providers play a vital role in the delivery of the program. This research aims to examine the impact of out-of-pocket (OOP) costs on the use of screening services and the distribution of use amongst various income groups. The hypotheses to be tested are that higher OOP costs lead to a fall in cervical screening participation, and that participation will decrease more amongst low income women than amongst women in higher income groups. Longitudinal data from the ALSWH will be especially powerful for this analysis because they enable the analysis to focus on changes over time in terms of both cervical screening behaviour and OOP costs. Since receiving the ALSWH data in August 2008 preparatory work has commenced, including: x Selection of appropriate variables to be included in the analysis x Matching of variables and possible responses according to survey year and age cohort x Merging data files survey year and age cohort files Initial discussions have been held with ALWSH liaison regarding future contact and site visits for merging and analysing Medicare data. 58 6WXGHQWSURMHFWVFRPSOHWHG Project: W052B A functional model of falls risk Doctorate candidate: x Afsoon Hassani Mehraban (School of Health Sciences, Occupational Therapy, University of Newcastle) Supervisors: x Professor Julie Byles (ALSHW, Centre for Research and Education in Ageing, University of Newcastle) x Dr Lynette Mackenzie (Occupational Therapy, University of Newcastle) x Assoc. Professor Catherine D’Este (Centre for Clinical Epidemiology and Biostatistics, University of Newcastle) Expected completion: December 2008 This project explored and applied the newly developed International Classification of Functioning (ICF) developed by the World Health Organisation to data collected as part of a sub-study of the ALSWH. At Survey 4, 20% of the sub-sample reported that they had experienced a fall in the previous six months and more than half the respondents stated they were afraid that they may fall and hurt themselves in the next year. In logistic regression models, falls were predicted by a large number of factors that had been measured in previous ALSWH surveys. Using a step-wise approach, the ICF framework was applied to identify those factors that were predictive of falls in multivariable models. This approach revealed that some factors from all domains of the ICF framework were associated with falls (including general health, body function, personal factors, activity and participation and environmental factors). This analysis is the first to assess and demonstrate the appropriateness of the ICF as a model for understanding falls risk. The project has also collected a large amount of information on environmental hazards associated with falls risk in and around the homes of older women. Common hazards include unsecured mats, shiny floors, inaccessible baths and showers, high cupboards, steps without rails, and unsuitable chairs and bed heights. Analysis has been completed and papers are in preparation. Presentations from this project were made at the OT AUSTRALIA 23rd National Conference & Exhibition in Melbourne, 2008. Project: A161 Diet quality in young Australian women according to pregnancy status PhD candidate: x Alexis Hure (University of Newcastle) Supervisors: x Dr Anne Young (ALSWH, University of Newcastle) x Assoc. Professor Clare Collins (School of Health Sciences, University of Newcastle) x Professor Roger Smith Completion: December 2008 The aim of this research was to compare the diet quality of pregnant and non-pregnant women in the 1973-1978 ALSWH cohort. Variables of interest were: x All dietary intake data from Food Frequency Questionnaires (FFQ) x Age 59 x Marital/relationship status x Socioeconomic indicators: level of income, education, occupation, government entitlements etc. x Number of children and date of birth for each child x Complications of pregnancy (e.g. gestational diabetes, preeclampsia, postnatal depression) x Anthropometrics: height, weight, own birth weight x Body satisfaction x Dieting and weight history x Physical activity x Sedentary behaviours x Medications x Cigarette, alcohol and drug use x Illness and/or disability This project has been completed and any further analysis will be conducted as part of a new project in the future. A paper has been accepted by Public Health Nutrition. 6WXGHQWWKHVHVFRPSOHWHG Project/Title: A055 Socioeconomic inequalities in women’s use of health care services in Australia PhD Candidate: x Rosemary Korda (National Centre for Epidemiology and Population Health, The Australian National University) Supervisors and advisors: x Professor Jim Butler (Australian Centre for Economic Research on Health, The Australian National University) x Dr Mark Clements (National Centre for Epidemiology and Population Health, The Australian National University) x Dr Emily Banks (National Centre for Epidemiology and Population Health, The Australian National University) x Dr Jane Dixon (National Centre for Epidemiology and Population Health, The Australian National University) x Dr Anne Young (University of Newcastle) Funding Source: Australian Postgraduate Award (APA) and NCEPH supplementary scholarship Completion: Completed March 2008, approved August 2008 This project formed part of a PhD thesis on socioeconomic inequality in the use of health care in Australia, and the impact on health outcomes. The purpose of this research was to investigate whether or not there are inequalities in health care based on a person’s socioeconomic status (SES, as measured by income, occupational and educational status, as well as area-level measures of SES). 60 The results from this project (described in the December 2007 report) were included in the PhD thesis, which was submitted in March 2008. The thesis was approved on 28 August, 2008 and the project is now completed. Title: Biopsychosocial correlates of women’s mental health: A longitudinal analysis of self-reported mental health across three generations of Australian women PhD Candidate: x Nadine Smith (School of Population Health, University of Queensland) Supervisors and advisors: x Professor Annette Dobson (School of Population Health, University of Queensland) x Professor Christina Lee (School of Psychology, University of Queensland) x Dr Anne Young (University of Newcastle) Submitted: September 2008 Good mental health is widely accepted as being instrumental to quality of life, but even people who usually enjoy good mental health may face changing life circumstances that can trigger episodes of poor mental health. The deeper problem with poor mental health is that the burden is often heavy in personal, social, economic and healthcare terms, potentially reaching into every part of the life experience. Mental health is affected by biopsychosocial factors including sociodemographic, health behaviour and physical health factors. For example, previous research has established that poorer mental health outcomes are associated with being female, having low sociodemographic status, engaging in unhealthy behaviours and having poor physical health. The aim of the study was to explore the contribution of biopsychosocial factors of this type to the mental health of women across the lifespan. To achieve this aim it was necessary to consider measurement issues affecting components of mental health, such as the association between anxiety and depression, and the effect of mental health on the reporting of life events, selected as an example of one of the more complex biopsychosocial correlates of mental health. The associations between mental health and biopsychosocial factors were examined cross sectionally and longitudinally using data from ALSWH. Analyses were conducted on the ALSWH data from the 1996 and 2000 surveys of women born 1946-1951 (aged 45-50 years in 1996, n=14 099); and the 1996, 1999 and 2002 surveys of women born 1921-1926 (aged 70-75 years in 1996, n=12 940). Women were sent postal questionnaires containing 300 to 500 items on each occasion. Latent trait analysis was used to establish that the items from the Goldberg Anxiety and Depression Scale (GADS) formed a single factor of anxiety and depression among older women. Supporting evidence for the use of a single factor included the substantial correlation between sum scores from the anxiety subscale and the depression subscale (r=0.65). Further, it was established that retaining the physical health items in GADS did not diminish the psychometric properties of the scale. This was shown, for example, by the Cronbach’s alpha of 0.84 for sum scores both with and without the physical health related items included. The complex relationship among the mental health measures and biopsychosocial factors analysed in this study are typified by the effects of mental health on the reporting of life events and the corresponding effects of life events on mental health. Clear evidence was found that mental health affected the reporting of life events and correspondingly that the number of life events experienced in a twelve months period was predictive of poor mental health. 61 Cross sectional associations between mental health and sociodemographic, health behaviour and physical health factors were investigated using data from three age cohorts of women and from several measures of mental health. The measures of mental health used were: the multi-item measures Medical Outcome Short Form (36-item) Health Survey (SF-36) Mental Health Subscale (MHI-5), Center for Epidemiological Studies Depression scale (CESD-10) and GADS; and single item measures based on respondents reporting the symptom of depression, the symptom of anxiety, a doctor’s diagnosis of depression and a doctor’s diagnosis of anxiety. The cross sectional analyses undertaken established the consistency of effects across measures and age cohorts. Women from the three cohorts experiencing good mental health tended to be socially advantaged (for example, finding it easy to manage on the income available), had positive health behaviours (for example, being physically active) and good physical health (for example, reporting few physical symptoms). The next step was to explore trajectories of mental health (measured by MHI-5) over time. Women from the three cohorts reporting improved mental health tended to be socially advantaged and to have good physical health. For women in the 1946-1951 cohort, across the three surveys 73% reported consistently good mental health (MHI-5 greater than 53), 4% reported consistently poor mental health and 23% reported mental health that varied over time. Throughout the study period women from this cohort who had consistently poor mental health or varying mental health (compared with those with consistently good mental health) were more likely to be un-partnered, become re-partnered or become un-partnered; report difficulty managing on their income in at least one of the surveys; continually been a smoker, adopted or quit smoking; report being physically inactive in at least one of the surveys; report many GP visits in at least two of the surveys; report many physical health symptoms in at least one of the surveys. Further, women who had consistently poor mental health (compared with those with varying mental health) were more likely to have reported difficulty managing on their income in at least two surveys, reported seeing a GP many times in all three surveys, or reported many physical health symptoms in at least one survey. To verify the consistency of the results, variant (changeable) and invariant (stable) factors affecting mental health of the 1946-1951 cohort across three surveys were examined. Factors affecting mental health over time included change in: partner status, ability to manage on the available income, smoking, physical activity, visits to a general practitioner, and number of physical symptoms. Women with positive invariant states (such as always reporting few physical symptoms) had the best mental health across the three surveys, women with negative invariant states (such as always reporting many physical symptoms) had the poorest mental health across the three surveys, and women reporting a variant state (such as going from few to many physical symptoms) lay somewhere between these two extremes across the three surveys. The current study adds to the understanding of the biopsychosocial characteristics associated with mental health. The importance of studying changes in mental health for women over extended periods of time (2-5 years) within a population framework was established. Despite the prevalence of poor mental health remaining relatively stable over time, the mental health of some women was shown to change over time, in some cases quite markedly, according to their biopsychosocial characteristics. Australian women experiencing poor or declining mental health were found to be more socially disadvantaged, and have more negative health behaviours and poorer physical health. Importantly, measuring mental health on a continuum permitted sub-clinical levels of mental ill-health to be considered. The current study points to the importance of support and intervention well before mental health issues escalate to clinical levels. 62 Project: Investigating quality of life and depression in middle aged and older Australian women with cancer Psychology Doctoral x Leah Collins (Department of Psychology, University of Candidate: Melbourne) Supervisors and advisors: x Professor Christina Lee (School of Psychology, University of Queensland) x Dr Prasuna Reddy (Department of Psychology, University of Melbourne) x Ms Jane Fletcher Submitted: March 2008 This study investigated the quality of life (QoL) and the prevalence and impact of depressive symptomatology in Australian women with cancer, using data from the 1946-1951 and 1921- 1926 cohorts. One-hundred and ninety-three middle aged women with cancer and 299 older women with cancer were compared with 193 middle aged and 299 older women without cancer respectively. By examining two distinct age cohorts, this study aimed to extend the QoL and depression literature regarding women with cancer across different life stages. The QoL and depressive symptomatology of women with cancer was initially compared with age- related norms, and in two cross sectional studies aimed to explore the differences in QoL domains and depressive symptomatology between women with and without cancer (Study 1) and further explore the impact of both cancer and depression, separately and combined, on the QoL of women (Study 2). The results from this study suggest cancer is associated with an overall reduction in QoL of Australian women, regardless of age. The domains and manner in which QoL is affected are however, dependent on the age at which a woman is diagnosed with cancer and whether she experiences symptoms of depression. Middle aged women with cancer experience more widespread reductions in both physical and mental QoL than older women with cancer. Older women with cancer tend to experience more physical limitations, yet show some psychological and emotional resilience when diagnosed with cancer. This study also illustrated that depression symptomatology is highly prevalent amongst Australian women with cancer, regardless of age, and reduces their QoL. Where previous research has suggested depression is either less prevalent or less often reported within the older population, this study suggested this age based difference does not exist for women with cancer. Implications regarding the identification and treatment of mental health disorders in Australian women with cancer are discussed in relation to providing age appropriate psychosocial care and cancer support programs. 63 &21'8&72)6859(<6 FRKRUW6XUYH\±)LQDOUHVSRQVHUDWH Survey 5 of the 1946-1951 cohort was carried out in 2007, when the women were aged between 56 and 61. The planning, development and piloting were described in Reports 26 and 27, while the mailout and collection of the surveys was described in Reports 28, 29 and 30 (see Table 2-1). Table 2-2 details the final response rates to Survey 5 of the 1946-1951 cohort. 7DEOH 5HSRUWLQJRIWKHWK6XUYH\RIWKH FRKRUW 5HSRUW 5HSRUW 5HSRUW 5HSRUW 5HSRUW 7KLV 5HSRUW -XQ 'HF -XQ 'HF -XQ 'HF Planning and M5 development Pilot M5 Mailout and data M5 collection Data collection M5 Completion of data M5 collection Final response rate M5 7DEOH 5HVSRQVHUDWHVIRUWKHWK6XUYH\RIWKH FRKRUW DWVW$XJXVW 1 Completed surveys 10 638 8 Deceased 30 0 Withdrawn 268 2 Not this time 265 2 No response 1257 10 Total mailed 12 458 100 64 FRKRUW6XUYH\±'DWDFROOHFWLRQ The process of planning, development, piloting and mailing of Survey 5 for the 1921-1926 cohort was described in Reports 28, 29 and 30. Copies of the survey, thank you leaflet and targeted reminder leaflet were included in Report 30. An updated timetable for this survey is given in Table 2-3, while Table 2-4 gives the response rates at 10th October 2008. Completed questionnaires will continue to be received and the data incorporated into the dataset until the cut off date of 31st August 2009. 7DEOH 7LPHWDEOHIRUWKHWK6XUYH\RIWKH FRKRUW DWWK2FWREHU 'DWH0DLORXW ,WHPV 1XPEHU 17 March 2008 Mailout 1 Package mailed including survey, reply- 7144 mailed paid envelope, letter of invitationand change of details card 30 April 2008 Mailout 2 Firstreminderleafletmailedtoallnon- 2560 mailed respondents 16 May 2008 Mailout 3 Thankyouleafletmailedtoall 4583 mailed respondents June - Sept 2008 Extra Packages mailed (as for Mailout 1) 690 mailed mailouts* Oct - Nov 2008 Extra Packages to be mailed (as for Mailout 1) As required mailouts* June - Aug 2008 Phone Reminderphonecallstoallnon- 3254 calls to reminder respondents 1583 participants *Of these extra mailouts 36 were first packages sent to participants who had not yet been mailed a package. This gave a total of 7180 participants who were mailed at least one survey package. 7DEOH 5HVSRQVHUDWHVIURPWKHWK6XUYH\RIWKH FRKRUW DWWK2FWREHU 1 Completed surveys 5487 76 Deceased 110 Withdrawn 452 6 Not this tim 409 No response 722 10 Total mailed 7180 100 65 FRKRUW6XUYH\±3LORW Preparation for the fifth survey of the 1973-1978 cohort, which is scheduled to be mailed in March 2009, began in January 2008. These women will be aged between 31 and 36 when they receive this survey. For the pilot study for Survey 5, items that were no longer considered useful or of interest have been removed and replaced by other items which are of more contemporary interest such as HPV vaccine and physical and passive activities which could help predict future trends e.g. skin cancer items. Some items which have been asked in the previous surveys have been brought back into the survey, e.g. the Food Frequency Questionnaire (previously asked at Survey 3) and the number of sexual partners (previously asked at Survey 2). The addition of extra items has resulted in a 36-page survey compared with 32 pages for Surveys 2, 3 and 4, and 24 pages for Survey 1. The impact of these additional items on the time the survey takes to complete, the additional participant burden, and the possible resulting lower response rate to the survey is being carefully monitored. Table 2-7 shows the items included in the pilot survey, the source of the items, and changes, additions and deletions to the fifth pilot survey from the fourth survey. Table 2-8 lists the deletions from the fourth survey and the reasons for this deletion. Approval for the pilot testing of the fifth survey of the pilot cohort born between 1973 and 1978 was obtained from the University of Newcastle and University of Queensland Human Research Ethics Committees. The pilot survey was mailed to 290 women who have also served as pilot test participants for Surveys 1, 2, 3 and 4. Copies of the survey, the information brochure, the evaluation questionnaire for obtaining feedback, the reminder leaflet and the thank you leaflet appear in Appendix 10.2. Table 2-5 outlines the timeline for this survey, and Table 2-6 summarises the response rate at October 10, 2008. 7DEOH 7LPHWDEOHIRUWKHWK6XUYH\RIWKH 3LORWFRKRUW DW WK2FWREHU 'DWH0DLORXW ,WHPV 1XPEHU 25 August Mailout 1 Package mailed including survey, reply-paid 290 mailed 2008 envelope, letter of invitation and change of details card 1 Oct 2008 Mailout 2 First reminderleafletmailedtoallnon- 188 mailed respondents 28 Nov 2008 Mailout 3 Thankyouleaflettobemailedtoall As required respondents Oct - Nov Extra Packages to be mailed (as for Mailout 1) As required 2008 mailouts Oct – Nov Phone Reminder phone calls to all non-respondents As required 2008 reminder 66 7DEOH 5HVSRQVHUDWHVIURPWKHWK6XUYH\ RIWKH 3LORWFRKRUW DWWK 2FWREHU 1 Completed surveys 111 38 Deceased 0 0 Withdrawn 0 0 Not this tim 2 No response 178 61 Total mailed 291 100 67 7DEOH 'HWDLOVRIDOOLWHPVLQWKHWK3LORW6XUYH\RIWKH FRKRUWLQFOXGLQJDOOFKDQJHV GHOHWLRQVDGGLWLRQV IURPWKH WK6XUYH\RIWKH FRKRUW ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 1 1 Consultations WHA 2 2 Consultations Modified from ABS (1991) (allied health) 1989-1990 National Health Survey Users' Guide. Canberra: ABS. Cat No. 4363.0 3 3 Complementary WHA and alternative therapies 4 4 Hospital WHA admissions 5 5 GP visits WHA 6 6 GP satisfaction Modified from Davies AR & Ware JEJ. (1991). GHAA's consumer satisfaction survey and user's manual (2nd Ed). Washington DC: The Group Health Association of America (GHAA). 7 7 Female GP WHA 8 8 Health care ‘Access to maternal Modified from Davies AR & satisfaction and child health Ware JEJ. (1991). GHAA's services’ was added. consumer satisfaction survey and users’ manual (2nd Ed). Washington DC: The Group Health Association of America (GHAA). 68 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 9 9 Health care card WHA 10-11 10-11 Private health WHA - AUHS insurance 12 12 Diagnosis ‘Postnatal ‘None of these conditions’ made bold. Modified from ABS (1991) depression’, 1989-1990 National Health ‘Gestational ‘Please specify’ changed to ‘please write Survey Users' Guide. diabetes’ and on the line’ for ‘Other major physical Canberra: ABS. Cat No. ‘Hypertension illness’ and ‘Other major mental illness’. 4363.0 during pregnancy’ moved to q44. ‘Chlamydia’, ‘Genital herpes’, ‘Genital warts (HPV)’, ‘HIV or AIDS’, ‘Hepatitis B ‘A Sexually or C’ were added. These were the STI Transmitted questions from S2. Infection (e.g. Chlamydia, genital Cancer replaced with ‘skin cancer’ and herpes, etc)’ was ‘other cancer’. deleted. A response of ‘other please write on line’ ‘Cancer’ was was added. deleted. ‘Other than during pregnancy’ removed from option d. ‘Not postnatal’ removed from option h. In the question stem a prompt regarding pregnancy related questions was added: ‘Please record conditions related to pregnancy (gestational diabetes, hypertension during pregnancy, antenatal depression and postnatal depression) in the section relating to pregnancy later in the survey’. 69 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 13 13 Symptoms ‘Indigestion (heart burn)’ and ‘Breathing WHA difficulties’ were added 14 98 Date of Birth 15 99 Residential and postal postcode 16 ADDITIONAL Sun protection Skin is cancer one of National skin cancer ITEM most prevalent campaign evaluation survey cancers amongst (conducted over summer 06- women. Determining 07 & 07-08). preventative strategies women take in their 30s could help predict future cancer trends. 17 25 Pap Test Changed to: When did you last have Modified from ABS (1991) a Pap test? Your blood pressure 1989-1990 National Health checked? Your skin checked? (e.g. spots, Survey Users' Guide. lesions, moles). With response options: Canberra: ABS. Cat No. ‘Less than 2 years’, ‘2 to less than 3 years 4363.0 ago’, ‘3-5 years ago’, ‘More than 5 years ago’, ‘Never’, ‘Not sure’. 18 ADDITIONAL HPV Vaccine HPV Vaccine recently WHA ITEM became available to this age group. Usage in this cohort will be assessed. 70 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 19 ADDITIONAL Medication List Tick box ‘None’ added between question Format similar to WHA - previously used in ITEM stem and response boxes. Columns were m5q43 to obtain m5q43 formatted into two distinct columns and ‘in information on the the last 4 weeks’ was added to the medications and ‘over question stem. the counter’ vitamins and therapies women are taking. 20-30 14-24 SF-36 Ware JE & Sherbourne CD (1992) The MOS 36-Item Short-Form Health Survey (SF-36):1. Conceptual framework and item selection, Medical Care, 30(6): 473-483 31 ADDITIONAL Sexual partners No. sexual partners is WHA - previously used in ITEM an indicator of sexual Y3q29 risk taking. 32 ADDITIONAL Sexual Evidence exists to WHA - previously used in ITEM orientation suggest that sexual Y3q28 orientation can change over time. Included to gain current information on cohort’s sexual orientation. 33 27 Fertility WHA 71 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 34 28 Current Option (a) split into three: WHA Contraception I use a combined oral contraceptive pill (The Pill), I use a progestogen only oral contraceptive pill (The Mini Pill), I use the oral contraceptive pill but I don’t know what type. Further additional items include, ‘I use a copper intrauterine device (IUD)’, ‘I use a progestogen intrauterine device (IUD) (e.g. Mirena)’, ‘I use an injection (e.g. Depo-provera)’, ‘I use the safe period method (e.g. natural family planning, rhythm method, Billings method, body temperature method, periodic abstinence)’, ‘I use a vaginal ring (e.g. Nuvaring)’. A free text line added to ‘other method of contraception’ with instructions ‘please write on line’. 35 31 Pregnancy ‘I have found out’ ‘My partner has a low or zero sperm WHA removed as prefix to count’ was added. ‘I cannot have children’ and ‘My partner cannot have children’. 36 32 Currently WHA pregnant 37 33 Childbirth, ‘premature birth’ Responses A) ‘Live birth’ and B) ‘Live WHA miscarriage premature birth’ combined into A) ‘Live birth’. 72 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 38-39 ADDITIONAL Emotional well Added to ascertain Beyond Blue ITEM being what assistance women have received or been offered during pregnancy with regard to emotional wellbeing. Item designed to inform program developers in this area. 40 34 DOB Children Box added for 9th child. 41 36 Breastfeeding Responses were changed to 9 text boxes WHA for entry of the number of months for each child and instructions changed to ‘please write number of months in the boxes’. 42 ADDITIONAL Immediacy of Time it takes to first WHA ITEM breastfeeding breastfeed can affect success and duration of breastfeeding. Item added to be used in conjunction with q41. 73 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 43-44 35 Childbirth Split into 2 sections. Q43 childbirth WHA and Beyond Blue complications & complications & Q44 pregnancy diagnosis of diagnosis. ‘Premature birth’ & ‘Emotional conditions in distress’ added to Q44. ‘Antenatal pregnancy depression’, ‘Postnatal depression’, ‘Antenatal anxiety’, ‘Postnatal anxiety’, ‘Gestational diabetes’, ‘Hypertension (high blood pressure) during pregnancy’ all added. Question stem for childbirth complications unchanged, but question stem for diagnosis of conditions in pregnancy changed to ‘Were you diagnosed or treated. Mark all that apply on each line’. 45-47 37-39 Maternity leave Q47 moved so people who had not yet WHA given birth but were on maternity leave could answer it. Q45 changed to a text box with instruction ‘Please write the number of months in the boxes’. 48-49 40-41 Children living WHA with you 50-52 42-46 Child Care Q43 : ‘Do you ever use childcare (formal or informal)’ & Q45: ‘In general how satisfied are you with your child care arrangements’ deleted. 74 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 53 47 Height Feet and inches WHA boxes removed, cm now only option. 54 48 Weight Stones and pounds WHA boxes removed, kg now only response option. 55 ADDITIONAL Waist Instruction and Waist measurement Similar question used in M5. ITEM circumference response boxes for may be more accurate inches removed, cm than BMI at predicting now only response health outcomes. option compared with M5 56-58 49-51 Like to weigh/ Q50: ‘How often Q50 replaced with Modified from French SA, diet/ satisfaction have you gone on a Q56, the weight control Story M, Downes B, Resnick diet (that is limited strategies from M5. MD, Blum RW (1995). how much you ate) Frequent dieting among in order to lose adolescents: Psychosocial weight during the and health behaviour last year?’ deleted. correlates. American Journal of Public Health, 85(5): 695- 701 59-64 53-58 Smoking Modified from Australian Institute of Health and Welfare (AIHW; 1997) National Health Data Dictionary, Version 6.0. Standard questions on the use of tobacco among adults. 75 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 65-67 59-61 Alcohol Modified from National Heart Foundation of Australia (1990). Risk factor prevalence study Survey 3, 1989. National Heart Foundation of Australia and Australian Institute of Health. 68-69 ADDITIONAL Youth alcohol Item added as alcohol WHA ITEM patterns consumption in late teens and early twenties presented a gap in the data we have collected. 70 64 Drugs Ice and crystal meth added as alternative National Drug Strategy names for amphetamines. household survey: Survey GHB, Fantasy Liquid ecstasy added as report 1995 (1996) pending. examples of designer drugs. 71-88 ADDITIONAL FFQ - in the The FFQ may be used Ireland P, Jolley D, Giles G, ITEM same format as every second survey O'Dea K et al. Development Y3. as it provides useful of the Melbourne FFQ: A information about food frequency questionnaire nutritional intake. for use in an Australian prospective study involving an ethnically diverse cohort. Asia Pacific Journal of Clinical Nutrition 1994; 3:19- 31. 76 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 89 ADDITIONAL Soft drinks Item introduced to WHA - Previously used in ITEM compliment the FFQ M3. by providing additional information on soft drink intake from a cohort of high soft drink consumers. 90 71 Stress WHA 91 69 Social support Sherbourne CD, & Stewart AL (1991). The MOS social support survey. Social Science and Medicine, 32(6), 705-714. 92 70 Approach to life Revised & reduced Revised Life Orientation Test (LOT- R). Scheier MF, Carver CS,, Bridges MW. (1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self esteem): A re-evaluation of the life orientation test. Journal of Personality and Social Psychology, 67, 1063- 1078. 77 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 93 ADDITIONAL Daily time Physical & passive WHA ITEM allocation activities impact on general fitness and body mass index. Australia now arguably the most obese nation, ALSWH aims to collect data that can inform policy and practice that might help reduce obesity rates. This item was added to assist this aim. 94 72 Life events ‘None of these events’ was made bold. Modified from Norbeck JS. (1984). Modification of live event questionnaires for use with female respondents. Research in Nursing and Health, 7, 61-71. 95 73 GADS (only 9 Anxiety and depression anxiety items scales from: Goldberg D, used) Bridges K, Duncan-Jones P, & Grayson D. (1988). Detecting anxiety and depression in general medical settings. British Medical Journal, 297, 897- 899. 78 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 96 74 CES-D Andresen EM, Carter WB, Malmgren JA, & Patrick DL. (1994). Screening for depression in well older adults: Evaluation of a short form of the CES-D. American Journal of Preventive Medicine, 10(2), 77-82. Last item added by WHA. 97-98 75-76 Life isn’t worth Modified from Beck A, living / Self harm Schuyler D & Herman I. (1974) Development of the Suicide Intent Scale. In AT Beck, HLP Resnick, & DJ Lettieri (Eds.) The prediction of suicide. Bowie, MD: Charles Press Publishers. 99 77 Time use The explanation of Modified from ABS (1993) option (e): ‘Casual Time use survey, Australia, paid work’ removed 1992: User's guide. to avoid confusion. Canberra: ABS. Cat No. 4150.0. 100 78 Managing time Modified from Statistics Canada, Housing Family and Social Statistics Division (1987) General social survey analysis series. Ottawa: Canadian Government Publication Centre. ISSN 0836-043X 79 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 101 85 Care for others Modified from ABS (1993) Disability, Ageing & Carers Australia. Canberra: ABS. Cat. No. 4432.0 102 86 Need for care Modified from ABS (1993) Disability, Ageing & Carers Australia. Canberra: ABS. Cat. No. 4432.0 103 91 Partner Changed to ‘Have you ever had a partner or spouse?’ 104-105 92-94 Abuse Q93 deleted Response options for Q104 changed to ‘In the last 12 months’, ‘More than 12 months ago’ and ‘Never’. Stem changed to ‘This question asks about situations you may have experienced with current or past partners’. 106-107 65-66 Physical activity Active Australia, Armstrong T, Bauman A, Davies J. Physical activity patterns of Australian Adults: Results of the 1999 National Physical Activity Survey. AIHW Canberra 2000 108 89 Education Modified from ABS (1993) 1996 Census of population and housing: Nature and content of the census. Canberra: ABS. Cat No. 2008.0. 109 80 Employment ‘None of the above’ was made bold. WHA 110 81 Job security WHA 80 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 111 82 Happy with job Modified from ABS (1993) hours Time use survey, Australia, 1992: User's guide. Canberra: ABS. Cat No. 4150.0. 112 83 Occupation Modified from M2 and Australian standard classification of occupations. Second Edition. (1997). Catalogue No. 1220.0 (from the web). 113 84 Unemployed WHA 114 100 Income ‘Each week’ was added to option b. Modified from ABS (1996) Four additional tax brackets were added. Census Dictionary. ‘$1500-$1999 ($78 000- $103 999 Canberra: Australian annually)’, ‘$2000-$2499 ($104 000-$129 Government Publishing 999 annually)’, ‘$2500-$2999 ($130 000- Service. Cat No 2901.0, $155 999 annually)’ and ‘$3000 or more p240 ($156 000 or more annually)’. 115 101 People Modified from ABS (1996) dependent on Australian Social Trends income 1996. Canberra: ABS. Cat No. 4102.0. 116 102 Manage on WHA income 117 ADDITIONAL % of income on Included as a WHA ITEM housing contemporary issue affecting women. 118 ADDITIONAL Housing Included as a WHA ITEM situation contemporary issue affecting women. 81 ,WHP< 3LORW1R <,WHP1R 7RSLF 'HOHWLRQ &KDQJH $GGLWLRQWR,WHP 6RXUFH 119 87 Marital status Modified from ABS (1993) 1996 Census of population & housing: Nature & content of the census. Canberra: ABS. Cat No. 2008.0. 120 88 Who lives with Modified from ABS (1994) you Australian Housing Survey: User Guide. Canberra: ABS. Cat No. 4180.0 121 107 Satisfaction WHA 122 ADDITIONAL Sub-study Beyond Blue Beyond Blue QUESTION question Foundation expressed interest in conducting a substudy with women who participate in ALSWH to examine emotional wellbeing during pregnancy. Item included to ascertain the willingness of the participants to take part in a substudy. 123-124 Was part of Proxy Changed to the same format as O5 being WHA consent form in two questions that ask the participant if Y4 someone helped them fill in the survey and the reason for needing help as opposed to asking the proxy to provide their details if they filled the survey in on behalf of someone. 82 7DEOH 'HOHWLRQVIURPWK6XUYH\WRWK3LORW6XUYH\RIWKH FRKRUW 6LWHP QXPEHU 7RSLF 6RXUFH 'HOHWLRQ 26 Abnormal Pap test WHA ENTIRE QUESTION DELETED No longer considered useful for policy purposes. Replaced with ‘Have you ever had a vaccination for HPV’. 29 Pill (total years) Mod. from NCEPH (1992) Project ENTIRE ITEM DELETED Health Check. Item initially used as long term use of contraceptives has been linked to Ref: CS3310, ACT. endocrinology problems. However question is unable to measure dosage which would be necessary for analysis, so it is no longer considered useful. 30 Emergency WHA ENTIRE ITEM DELETED contraception At S4 only 10% of women reported using emergency contraception and of these women only 0.7% reported difficulties obtaining it therefore this question is no longer necessary. 43 & 45 Childcare WHA Q43 and Q45 were deleted, leaving 3 of the 5 original questions in the current survey. Change to format of childbirth items meant these items were no longer necessary. 50 Like to weigh/ diet/ Mod. from French SA, Story M, Q50 deleted (leaving 2 of the original 3 questions in the current survey). Replaced in satisfaction Downes B, Resnick MD, Blum RW the current survey with a more comprehensive weight loss question which asked (1995). Frequent dieting among specific techniques. adolescents: Psychosocial and health behaviour correlates. Amer J Pub Health, 85: 695-701. 52 Medications WHA ENTIRE ITEM DELETED The question listed various types of medications and gave some examples of these medications. This could be confusing as the medications could be administered for many different reasons so this question was deleted and replaced with Q18 which asks the same thing, but offers an open ended response line for answers. 62-63 Fruit and WHA ENTIRE ITEM DELETED vegetables Item deleted as the same information is covered in the Food Frequency Questionnaire. 67 PA in main job WHA ENTIRE ITEM DELETED Items deleted as a new item (Q93) has been added that more comprehensively covers this area. 83 6LWHP QXPEHU 7RSLF 6RXUFH 'HOHWLRQ 68 PA other activities WHA ENTIRE ITEM DELETED Items deleted as a new item (Q93) has been added that more comprehensively covers this area. 79 Share of activities WHA ENTIRE ITEM DELETED Item showed little variability across longitudinal analysis. 90 Living overseas WHA ENTIRE ITEM DELETED One of the main purposes of these questions was to see if overseas travel could explain non response to surveys. The majority of long term and permanent overseas travel is between the ages of 20-29. The women have now passed this age so retention of this question is not necessary. 93 Abuse Mod. from ABS (1996) Women's Q93 was deleted leaving 2 of the original 3 abuse questions in the current survey. Safety Australia. Canberra: ABS. This item only needed to be asked once as it asks about the participant’s childhood Cat No. 4128.0 and should not be variable. 95 Sense of well- WHA ENTIRE ITEM DELETED being Due increase in size of the current survey, these questions were removed. 96 Internet for WHA ENTIRE ITEM DELETED medical It is suggested that the patterns of usage would be strongly correlated to the information availability of broadband. At this point in time this question is limited due to limited broadband availability. 97 Main form of WHA ENTIRE ITEM DELETED transport Item deleted as analysis from Y4 showed a close link with availability of public transport. 103-106 Aspirations Mod. from Hakim C.(1991). Grateful ENTIRE ITEM DELETED slaves and self-made women: In This question deleted because some of the women have already reached, and others women's work orientations. Eur Soc are approaching the target age for their aspirations. Rev, 7,101-21. 84 0(7+2'2/2*,&$/,668(6 'HILQLQJPHQRSDXVDOVWDWXV Authors: Janneke Berecki and Nelufa Begum ,QWURGXFWLRQ Menopausal status is determined in the ALSWH cohort of women born 1946-1951, who have been surveyed five times, first in 1996, then in 1998 and subsequently once every three years. Here, the categories of menopause status are defined, and the methods used by ALSWH to classify participants into these categories are explained. 'HILQLWLRQRIPHQRSDXVH Menopause is the permanent cessation of menstruation and end of a woman's reproductive years. It occurs when the ovaries stop producing the female hormone oestrogen. This is characterised by a period of irregular menstrual bleeding, followed by an absence of bleeding altogether. Menopausal transition is often accompanied by vasomotor symptoms such as hot flushes and night sweats, and by vaginal dryness/irritation. A woman is menopausal after 12 months of amenorrhea (absence of menses). Surgical menopause Three categories of surgical menopause are defined: hysterectomy only (removal of the uterus), bilateral oophorectomy only (both ovaries removed), and both hysterectomy and bilateral oophorectomy; these are all referred to as surgical menopause. Once a woman has had surgical menopause her status cannot revert to pre-menopausal. Women who have had a bilateral oophorectomy with or without a hysterectomy will simultaneously go through spontaneous menopause, regardless of age (The Hysterectomy Association, 2004). If only a hysterectomy is performed, menstrual bleeding ceases although hormonal production may continue for several years. Hormone replacement therapy and oral contraceptives Hormone replacement therapy (HRT) is given to some women during or after the menopausal transition to provide a continued supply of some of the hormones produced by their bodies during the reproductive period. These hormones (oestrogen, progesterone, or both) can also be given to women who have undergone bilateral oophorectomy, to replace the oestrogen no longer produced by the ovaries. HRT is used to control menopausal symptoms. Like HRT, most oral contraceptive pills (OCP) include both oestrogen and progesterone. OCP are usually given to premenopausal women, but they can mask underlying menopause. Both HRT and OCP can induce periodic bleeding, or suppress periodic bleeding, regardless of underlying menopausal status. Women using OCP or HRT are therefore treated separately. Menopausal status based on self-reported menstrual pattern Menopausal status for women who had not undergone surgical menopause was based on the definitions of Guthrie et al. (1999). Women were defined as pre-menopausal if they had menstruated in the last 3 months and reported no change in menstrual frequency in the last 12 months, peri- menopausal if they reported changes in menstrual frequency or 3-11 months of amenorrhea, and naturally post-menopausal if they reported amenorrhea for 12 consecutive months or more. 85 'HFLVLRQWUHHIRUPHQRSDXVDOVWDWXV As hysterectomy and bilateral oophorectomy are both irreversible operations, responses at earlier survey/s were used for assignment with respect to these operations at later surveys; for example, status at Survey 2 was based on hysterectomy and bilateral oophorectomy data at Surveys 1 and 2. Similarly, post-menopausal women cannot revert to pre- or peri-menopause status: response at earlier surveys was used to determine status at later surveys. Furthermore, once a woman was defined as post-menopausal, she remained in this category regardless of later HRT or OCP use. This ensured consistency across surveys. The survey data was categorised according to a decision tree (Figure 3-1). First, surgically menopausal women were assigned menopausal status (hysterectomy only, bilateral oophorectomy only, or both hysterectomy and bilateral oophorectomy). From the remaining women, those currently taking HRT were categorised (as the HRT group), and then, from those women remaining, women taking OCP were categorised (as the OCP group). Finally, the women still remaining were categorised as pre-, peri- or post-menopausal according to their reported menstrual pattern. Menopausal status was categorised as missing if all relevant items were missing at a particular survey. Women who had completed the survey, but did not report one or more relevant items at that survey were considered as unclassifiable. 7DEOH &RGHVDQGFDWHJRU\ODEHOVIRUPHQRSDXVHVWDWXV &DWHJRU\ODEHO &RGH Surgical menopause (1) Hysterectomy only (2) Bilateral oophorectomy only (3)Hysterectomy and bilateral oophorectomy Menopausal status unknown due to (4) HRT hormonal treatment (5) OCP Pre-menopausal (6) Pre-menopausal Peri-menopausal (7) Peri-menopausal Post-menopausal (8) Post-menopausal Missing (9) Missing Unclassifiable (10) Unclassifiable It must be noted that these categories were used solely to determine menopausal status. Not all women currently taking HRT at a specific survey were included in the HRT category - if they were previously categorised as naturally postmenopausal, or surgically menopausal, they remained in those categories regardless of later use of hormone supplements. The HRT and OCP groups included only those women for whom menopausal status could not be determined longitudinally. 86 )LJXUH )ORZFKDUWIRUPHQRSDXVDOVWDWXV Results To define menopausal status, menopause related data from Surveys 1 to 5 of the 1946-1951 cohort was analysed. There were 13 716 women aged 45-50 years who responded to the first survey in 1996. The fifth survey was conducted in 2007; 10 565 women responded (their ages were then 56-61 years). Menopausal status for each survey is presented in Table 3-2. 87 7DEOH 0HQRSDXVDOVWDWXVIRUZRPHQLQWKH FRKRUW IURP 11111 Hysterectomy only 2325 17 2181 18 2171 19 2247 21 2238 21 Oophorectomy only 89 1 90 1 80 1 90 1 107 1 Hysterectomy and 796 6 936 8 995 9 1081 10 1149 11 oophorectomy Sub-total (surgical 3210 24 3207 26 3246 29 3418 31.3 3494 33 menopause) HRT 1243 91345 11 1784 161019 9 637 6 OCP 742 5478 4 239 253 1 9 0 Pre-menopausal 4576 33 2617 22 953 9 208 2 15 0 Peri-menopausal 3052 22 2696 22 1900 17 1004 9 199 2 Post-menopausal 736 5 1333 11 2662 24 4954 45 6059 57 Missing 5 02 0 3 0 0 0 2 0 Unclassifiable 152 1 660 5 413 4 249 2 150 1 Total 13 716 100 12 338 100 11 200 100 10 905 100 10 565 100 88 Figure 3-2 shows that the proportion of women with surgical menopause increased over the survey period (S1 to S5). In Survey 1, 17% and 6% women were in the ‘hysterectomy only’, or ‘hysterectomy and bilateral oophorectomy’ categories, respectively, and over 11 years, these percentages increased to 21% and 11%, respectively. The prevalence of ‘hysterectomy and bilateral oophorectomy’ almost doubled. The ‘oophorectomy only’ group also increased over time. The HRT group, for whom menopausal status could not be otherwise defined, increased up to 2001 (Survey 3), and then decreased. On the other hand, the OCP group consistently decreased over time. The pre-menopausal group decreased (from 33% to 0%) from Survey 1 to Survey 5, while the post-menopausal group dramatically increased (from 5% to 57%) over the same period. The peri- menopausal group decreased over time. )LJXUH 0HQRSDXVDOVWDWXVRIZRPHQLQWKH FRKRUW 100 90 80 70 60 50 40 30 20 10 0 1996 1998 2001 2004 2007 Surgical-menopausal HRT OCP Pre-menopausal Peri-menopausal Post-menopausal Menopausal status of responders to all surveys The menopausal status of women who responded to all 5 surveys is presented in Table 3-3 and Figure 3-3. 89 7DEOH 0HQRSDXVDOVWDWXVRIZRPHQLQWKH FRKRUWZKRUHVSRQGHGWRDOOVXUYH\V 11111 Hysterectomy only 1454 16 1565 17 1729 19 1828 20 1885 21 Oophorectomy only 46 1 63 1 63 1 70 1 87 1 Hysterectomy and 496 5 660 7 793 9 899 10 994 11 oophorectomy Sub-total (surgical 1996 22 2288 25 2585 28 2797 31 2966 33 menopause) HRT 829 91019 11 1473 16844 9 549 6 OCP 515 6395 4 205 247 1 9 0 Pre-menopausal 3259 36 2112 23 803 9 182 2 12 0 Peri-menopausal 2044 22 2095 23 1593 18 861 9 167 2 Post-menopausal 413 5 927 10 2154 24 4201 46 5312 58 Missing 1 0 2 0 2 0 0 0 2 0 Unclassifiable 73 1 292 3 315 4 198 2 113 1 Total 9130 1009130 100 9130 1009130 100 9130 100 The pattern of menopausal transitions shown in Table 3-3 (responders to all surveys) is very similar to the previous menopausal transitions presented in Table 3-2. 90 )LJXUH 0HQRSDXVDOVWDWXVRIZRPHQIURPWKH FRKRUWZKRUHVSRQGHGWRDOO VXUYH\V 100 90 80 70 60 50 40 30 20 10 0 1996 1998 2001 2004 2007 6XUYH\ Surgical menopausal HRT OCP Pre-menopausal Peri-menopausal Post-menopausal Unclassifiable menopausal status According to the definition of menopausal status, women who completed a survey but did not report one or more relevant items on that survey, were considered unclassifiable. Table 3-3 shows that, using this definition, menopausal status was unclassifiable in 1% to 5% of women. To reduce this unclassifiable number when information about hysterectomy, bilateral oophorectomy, HRT or OCP was missing, menopausal status was defined using all other information available (e.g. HRT, OCP and bleeding patterns). For example, women who did not report hysterectomy or bilateral oophorectomy, but reported use of HRT or OCP, were defined as menopausal status ‘HRT’ or ‘OCP’ based on available information. For women without surgical menopause, and who did not report HRT or OCP use, menopausal status was defined by their bleeding patterns (pre, peri or post). The breakdown of unclassifiable status is presented in Table 3-4. There were still some women whose menopausal status could not be defined. 91 7DEOH %UHDNGRZQRIµXQFODVVLILDEOH¶PHQRSDXVDOVWDWXV IURPWKHXQFODVVLILDEOH FDWHJRU\LQ7DEOH UHGHILQHG E\XVLQJDYDLODEOHLQIRUPDWLRQ 6XUYH\VWRIRU WKH FRKRUW 11111 HRT 18 12 11 2 87 21 36 15 31 21 OCP 43 006210 0 0 Pre- menopausal 37 24 218 33 55 13 10 4 2 1 Peri- menopausal 38 25 267 40 102 24 39 15 9 6 Post- menopausal 19 125 114 17 96 23 125 50 91 60 Unclassifiable 36 23 50 7 72 17 38 15 17 11 Total 152 100 660 100 413 100 249 100 150 100 Combined menopausal status Table 3-2 (previously defined menopausal status) and Table 3-4 (the breakdown of unclassifiable status) are combined and presented in Table 3-5. In this table the patterns of menopausal status are very similar to the previous analysis (Table 3-2) and the unclassifiable numbers are now very low (< 1%). 92 7DEOH &RPELQHGPHQRSDXVDOVWDWXVZLWKUHGXFHGµXQFODVVLILDEOH¶FDWHJRU\IRUZRPHQLQWKH FRKRUW 1 1 1 1 1 Hysterectomy only 2325 17 2181 18 2171 19 2247 21 2238 21 Oophorectomy only 89 1 90 1 80 1 90 1 107 1 Hysterectomy and 796 6 936 8 995 9 1081 10 1149 11 oophorectomy Sub-total (surgical 3210 24 3207 26 3246 29 3418 31 3494 33 menopause) HRT 1261 9 1356 11 1871 171055 10 668 6 OCP 746 5 478 4 245 254 1 9 0 Pre-menopausal 4613 34 2835 23 1003 9 218 2 17 0 Peri-menopausal 3090 23 2963 24 2002 18 1043 10 208 2 Post-menopausal 755 6 1447 12 2758 25 5079 47 6150 58 Missing 5 0 2 0 3 0 0 0 2 0 Unclassifiable 36 0 50 0 72 138 0 17 0 Total 13 716 100 12 338 100 11 200 100 10 905 100 10 565 100 93 5HVROYLQJLQFRQVLVWHQFLHVIRUPHQRSDXVDOVWDWXV Menopausal trajectories across all 5 surveys were analysed for inconsistencies. After re- categorising as many women in the ‘unclassifiable’ category as possible, some inconsistencies were observed in menopausal trajectories. One of the assumptions was that post-menopausal women cannot revert to pre or peri-menopausal status. However, several women were pre/peri menopausal in one survey; postmenopausal in the next survey and again pre/peri menopausal in the survey after that. In these cases, if the status in the middle survey was originally unclassifiable (i.e. one menopausal item missing), menopausal status was again defined in this survey as unclassifiable. Several women were classified as premenopausal in one survey, peri menopausal at the next survey and again premenopausal at the survey after that (‘pre-peri- pre’); in these cases menopausal status was redefined as ‘pre-pre-pre’. Similarly, ‘peri-pre-peri’, was redefined as ‘peri-peri-peri’. There was only one case where menopausal status was ‘HRT- post-peri’, and in that case, the middle menopausal status was redefined as unclassifiable. Final menopausalstatusfromSurvey1toSurvey5ispresentedinTable3-6. 94 7DEOH )LQDOPHQRSDXVDOVWDWXV IRUWKH FRKRUWDIWHUUHGHILQLQJDVPDQ\ µXQFODVVLILDEOH¶DVSRVVLEOHXVLQJ ORQJLWXGLQDO GDWD DQG ORJLFDODUJXPHQWV 11111 Hysterectomy only 2325 17.0 2181 17.7 2171 19.4 2247 20.6 2238 21.2 Oophorectomy only 89 1 90 1 80 1 90 1 107 1 Hysterectomy and 796 5.8 936 7.6 995 8.9 1081 9.9 1149 10.9 oophorectomy Sub-total (surgical 3210 24 3207 26 3246 29 3418 31 3494 33 menopause) HRT 1261 91356 11 1871 171055 10 668 6 OCP 746 5478 4 245 254 1 9 0 Pre-menopausal 4613 34 2797 22.7 1009 9 217 2 17 0 Peri-menopausal 3090 23 3001 24 1996 18 1044 10 208 2 Post-menopausal 755 6 1444 12 2756 25 5077 47 6150 58 Missing 5 02 0 3 0 0 0 2 0 Unclassifiable 36 1 53 1 74 1 40 0 17 0 Total 13 716 100 12 338 100 11 200 100 10 905 100 10 565 100 95 5HIHUHQFHV Guthrie JR, Dennerstein L, Dudley EC. Weight gain and the menopause: A 5-year prospective study. Climacteric 1999; 2:205-211. The Hysterectomy Association: www.hysterectomy-association.org.uk [Accessed 2004 February 15]. *HRFRGLQJ Author: Anna Graves The 1973-1978 cohort Survey 4 participant addresses are currently being prepared for geocoding. Geocoding is the process of assigning geographic coordinates (latitude and longitude) to addresses. Once these coordinates are assigned, they are used to allocate rural, remote and metropolitan area (RRMA) classifications, accessibility/remoteness index of Australia (ARIA, later versions are ARIA+) scores, and socioeconomic indexes for areas (SEIFA) scores, and these are the data found in the analysis datasets. This procedure begins by comparing the postcode in the survey mailing address to the postcodes given as answers to the following questions in the survey: Q99 What is your postcode? a. What is your RESIDENTIAL postcode? (where you live) b. What is the postcode of your POSTAL ADDRESS? (if different from residential) Recently, in order to save time and produce a more accurate demographic dataset, the procedure for producing these addresses was changed. Details of the changes are described below. Please note: responses to Question 99a are coded SRPC (Survey Residential Postcode) and responses to Question 99b are coded SPPC (Survey Postal Postcode). *HRFRGLQJSURFHGXUHXVHGLQWKHSDVW 1. Postcodes from the list of mailing addresses to which the surveys were sent were checked for validity and for the correct locality. If any errors occurred, corrections were made. 2. The residential and postal postcodes given as answers in the survey were checked for validity. 3. If the postcode from the mailing address matched the residential postcode (SRPC) or the postal postcode (SPPC) given as answers on the survey, then the mailing address was correct for geocoding. 4. If the postcode for the mailing address did not match the SRPC or SPPC, the next check was whether there had there been an address change since the survey mailout, and whether the new postcode matched the residential or postal postcode given as answers in the survey. If: i. Yes – the address was changed to the new address for geocoding. ii. No – the current mailing address was used for geocoding. Considerable effort has been made in the past to investigate why the mailing postcode and the survey postcodes differed. 96 *HRFRGLQJSURFHGXUHWREHXVHGRQZDUGVIURP6XUYH\IRUWKH FRKRUW 1. Postcodes from the list of mailing addresses to which the surveys were sent will be checked for validity and for the correct locality. If any errors occur, corrections will be made. 2. The residential and postal postcodes given as answers in the survey will be checked for validity. 3. If the postcode in the mailing address matches the SRPC then the mailing address is correct, and will be used for geocoding. 4. If the postcode in the mailing address matches the SPPC, the mailing address is a mail box or mail bag address. If the SRPC provided by the participant is valid, that postcode will be used for geocoding. (If the address for geocoding consists of only a postcode then the coordinates returned from the geocoding will be the centre of that postcode.) 5. If the postcode in the mailing address matches the SPPC and the SRPC is blank then the mailing address will be used for geocoding. (If the address for geocoding is a mail box or mail bag address then the coordinates returned by the geocoding will be the centre of that postcode.) 7DEOH *HRFRGLQJSURFHGXUH 0DLOLQJ 6XUYH\UHVLGHQWLDO 6XUYH\SRVWDO $FWLRQ SRVWFRGH SRVWFRGH 653& SRVWFRGH 633& 3& x x x, y or blank Step 3 - Use mailing address x y x Step 4 - Use SRPC x blank x Step 5 - Use mailing address x y or blank z or blank Step 6 6. If the postcode for the mailing address does not match the SRPC and it does not match the SPPC, a check will be made of whether there has there been an address change since the survey mailout, and whether the new address postcode matches the SRPC or SPPC. Then if: i. Yes – the new address will be used for geocoding. ii. No – a check will be made to see if the mailing postcode and survey postcode numbers are similar? Then if: i. Yes – the image will be checked to see if there has been a survey data entry error? Then if: i. Yes –the mailing address will be used for geocoding. ii. No – a check will be made whether the digits in the survey postcode have been transposed e.g, 3658 to 3568. Then if: i. Yes – the mailing address will be used for geocoding ii. No – the SRPC will be used on its own for geocoding. If there is no SRPC, the SPPC will be used. 97 )LJXUH 6WHSRIWKHJHRFRGLQJSURFHGXUH PC <> SRPC and PC<> SPPC Is there new address? Yes - then use new PC No, is PC close to SRPC or SPPC? No, is there a SRPC? Yes, is there survey, data input error? Yes – then use Yes, then use mailing address SRPC No – then use SPPC No, have the digits been transposed in the SRPC or SPPC Yes, then use mailing address No, is there a SRPC? PC = mailing postcode SRPC = survey residential postcode Yes – then use SRPC SPPC = survey postal postcode No – then use SPPC 5HSODFLQJ550$ZLWK$5,$DVDPHDVXUHRIUXUDOLW\DQG UHPRWHQHVV Author: Richard Hockey %DFNJURXQG Currently, analyses or presentations of ALSWH cohort data usually classify area of residence (i.e. urban/rural/remote) using the RRMA classification. The ALSWH website suggests: When doing longitudinal analyses, remember to weight for area of residence at Survey 1 (y1wtarea, m1wtarea, o1wtarea) in all crosstabs, frequencies and analyses to adjust for the initial deliberate oversampling in rural and remote areas. This is not required when running models that include area of residence (ALSWH, 2008a). 98 RRMA classifications were used to stratify the initial ALSWH sample and derive the weights because it was the classification used at the time by the Department of Health and Ageing (DoHA), and also was used for the sampling frame for the study. The RRMA classification was developed in 1994 by the Department of Primary Industries and Energy, and the then Department of Human Services and Health. RRMA classifies Statistical Local Areas (SLAs) as: x Capital cities (Metropolitan), M1 x Other metropolitan areas (Metropolitan), M2 x Large rural centres (Rural), R1 x Small rural centres (Rural), R2 x Other rural areas (Rural), R4 x Remote centres (Remote), RM1 x Other remote areas(Remote), RM2 However, RRMA is no longer the most appropriate measure of rurality or remoteness, as it measures remoteness based on population counts from the 1991 census. Since then two other measures have been developed by the National Centre for Social Applications of Geographic Information Systems (GISCA). These are ARIA (1997) and its successor ARIA+ (2001). The ARIA index scores categorise areas as: x Highly accessible (HA) x Accessible (A) x Moderately accessible (MA) x Remote (R) x Very remote (VR) ARIA+ scores categorise areas into the following Australian Standard Geographical Classification (ASGC) Remoteness Area categories: x Major cities (MC) x Inner regional (IR) x Outer regional (OR) x Remote (R) x Very remote (VR) (Information from ABS, 2007; AIHW, 2004) The Department of Health and Ageing now uses ARIA+ in preference to RRMA and it is also the standard Australian Bureau of Statistics (ABS) endorsed measure of remoteness. 7KHSUREOHPZLWK550$ RRMA is based on the 1991 Census and consequently does not reflect population growth since then. After the 1996 census DoHA and GISCA undertook a re-classification of SLAs according to the 1996 population figures. Large changes occurred in Queensland where the Sunshine Coast moved from 3 (large rural) and 4 (small rural) to 2 (other metropolitan), Cairns went from 3 to 2, and Gladstone and Hervey Bay from 4 to 3. Since 1996 even more changes have occurred. Thus, over time, RRMA increasingly misclassifies areas with respect to rurality/remoteness (DoHA, 2001). Table 3-8 compares the original RRMA classification based on 1991 census data with a revised RRMA based on the 1996 census using the same criteria as used in the original classification (DoHA, 2001). The biggest changes are those changing from R1 to M2 (19% of R1), R2 to R1 (19% of R2) and RM to R3 (17% of RM). 99 7DEOH 7RWDOIHPDOHSRSXODWLRQRI$XVWUDOLDFODVVLILHGE\550$ DQG550$ 550$ 550$ 0 0 5 5 5 50 0 5724241 0 0 0 0 0 (100.0) 0 0 696092 0 0 0 0 (100.0) 5 0 107785 443211 11527 0 0 (19.2) (78.8) (2.0) 5 0 38561 110436 420005 18507 6175 (6.5) (18.6) (70.8) (3.1) (1.0) 5 0 0 0 23168 1163445 7929 (1.9) (97.4) (0.7) 50 0 0 0 0 47179 222940 (17.5) (82.5) The main problem with RRMA is that a relationship with geographical area may not be found when one does exist. For example, if you look at the relationship between diabetes and geographical area in the 1946-1951 cohort at the fourth survey, there is no relationship when you use RRMA (chi-square test for association, p=0.91), but when diabetes is compared by ARIA+ categories there is a relationship (chi-square, p=0.03). (See Table 3-9 and Table 3-10 below) 7KHVROXWLRQ When looking for a possible relationship between geographical area and other characteristics of the ALSWH cohort, either ARIA or ARIA+ should be used. When controlling for area of residence as a confounder only, it is less important which measure is used. Using ARIA or ARIA+ is not a substitute for weighting, as the congruence between these measures and RRMA at Survey 1 is not good. A problem with ARIA and ARIA+ is that they are not available for all years. For example, for the 1946- 1951 cohort ARIA is available for Surveys 1 and 2, and ARIA+ is available for Surveys 2, 3, and 4. There is currently no ARIA+ for Survey 5 of this cohort. However, there is a postcode to ARIA+ translation that can be used as an interim measure until the GISCA information arrives. 8VDJHRI$5,$ ARIA+ (and ARIA) is a continuous measure, however, it is generally used as a categorical variable. It is planned that the standard ARIA+ categories as defined by the ABS, Remoteness Area (RA) be added to future releases of the ALSWH datasets. Details of how these categories are defined are supplied in the Data Dictionary Supplement (ALSWH, 2008b). 100 7DEOH 'LDEHWHVDQG550$IUHTXHQFLHV URZSHUFHQWV 550$ 6PDOO 2WKHU 8UEDQ /DUJH5XUDO 5XUDO UXUDO5HPRWH 7RWDO Diabetes No 6836 648 716 1731 9931 (95.5) (95.1) (95.3) (95.1) (95.4) Yes 324 34 36 89 482 (4.5) (4.9) (4.7) (4.9) (4.6) Total 7160 682 751 1819 10413 (100.0) (100.0) (100.0) (100.0) (100.0) 6WDWLVWLFVIRU7DEOH 6WDWLVWLF ') 9DOXH P Chi-Square 3 0.5484 0.9081 Likelihood Ratio 3 0.5430 0.9093 Chi-Square From Table 3-9 there is no evidence for an association between diabetes and area of residence (RRMA) 7DEOH 'LDEHWHVDQG$5,$IUHTXHQFLHV URZSHUFHQWV $5, $ 0DMRU ,QQHU 2XWHU 5HPRWH 7RWDO &LWLHV 5HJLRQDO 5HJLRQDO DQGYHU\ UHPRWH Diabetes No 6434 2305 1025 161 9925 (95.7) (94.9) (95.2) (91.4) (95.4) Yes 291 125 52 15 482 (4.3) (5.1) (4.8) (8.6) (4.6) Total 6725 2429 1077 176 10407.7 (100.0) (100.0) (100.0) (100.0) (100.0) 101 Statistics for Table 3-10 Statistic DF Value P &KL6TXDUH /LNHOLKRRG5DWLR &KL6TXDUH )URP7DEOH WKHUHLVVLJQLILFDQWHYLGHQFHIRU DQDVVRFLDWLRQEHWZHHQGLDEHWHVDQGDUHD RI UHVLGHQFH 1.1.1 Further reading 'R+$5HYLHZRIWKH5XUDO5HPRWHDQG0HWURSROLWDQ$UHDV 550$ &ODVVLILFDWLRQ'LVFXVVLRQ 3DSHU :LWKRXW3UHMXGLFH *ORYHU- 7HQQDQW6 5HPRWH$UHDV6WDWLVWLFDO*HRJUDSK\LQ$XVWUDOLD 1RWHVRQWKH $FFHVVLELOLW\5HPRWHQHVV,QGH[IRU$XVWUDOLD $5,$YHUVLRQ :RUNLQJ3DSHU6HULHV1R 3XEOLF +HDOWK,QIRUPDWLRQ'HYHORSPHQW8QLW$GHODLGH KWWS ZZZSXEOLFKHDOWKJRYDXSGIUHSRUWVBSDSHUVZRUNLQJBSDSHUVBRWKHUZNBSSU BUHPRWHQHVVBDULD SGI *,6&$$5,$YV550$ KWWS ZZZJLVFDDGHODLGHHGXDXZHEBDULD5XUDOB+HDOWKDULDBUUPD$5,$B550$KWPO 1.1.2 References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uthor: Richard Hockey %DFNJURXQG Waist circumference is useful as a measure of central obesity. It has been shown in studies to be independently associated with obesity related health outcomes and health care costs in addition to, or instead of, BMI (Hojgaard et al., 2008; Janssen et al., 2004). In the fifth survey of the 1946-1951 cohort respondents were asked for the first time to report their own waist circumference measurement. The question appeared as: 4 What is your waist measurement? Please measure your waist while in your underwear. If possible, get someone to help you take the measurement. Find your navel (belly button) and measure at that level. Be careful not to have the tape too tight. You should be able to slip your little finger under it comfortably. Write the measurement to the nearest centimetre (or inch if this is the only measure you have available). cm OR inches Of the 10 639 respondents 1160 (11%) did not fill in either box, 348(3%) filled in both boxes, with the remainder (9131, 86%) filling in either. A summary of the responses is given in Table 3-11 below. 7DEOH 5HVSRQVHV WR4 :KDWLV \RXU ZDLVWFLUFXPIHUHQFH" %HIRUHFRQYHUVLRQDQG FRUUHFWLRQV ,WHP 1 0HDQ 6WG'HY 0LQ 0D[ 0HGLDQ WK3FWO WK3FWO m5q56_in 3346 34.78(88.3) 6.52 (16.6) 0 98(248.9) 34 (86.4) 30 (76.2) 38 (96.5) m5q56_cm 6481 89.45 35.31 9 970 88 80 98 Centimetres box On examination of the data it was apparent that some women had entered the measurement in inches in the centimetre boxes or had entered the measurement in millimetres. These were corrected using the following rules: 1. If centimetres were greater than 250cm they were assumed to be millimetres and divided by 10. (10 cases) 2. If centimetres were less than 58cm they were assumed to be inches and multiplied by 2.54. (295 cases) Inches boxes If inches were greater than 66in (168cm) they were assumed to be centimetres. (11 cases) 103 Both boxes Of the 348 women where both units were completed, in only 28 cases did the difference in measurement exceed 2.5cm. It appeared most women doing this had attempted to fill in the measurement using both units and in general had succeeded. In all these cases the measurement in centimetres was used. An analysis of this group is given in Table 3-12 below. 7DEOH $QDO\VLVRIZRPHQZKRUHVSRQGHGWR4XVLQJERWKLQFKHVDQGFHQWLPHWUHV ,WHP 1 0HDQ 6WG'HY 0LQ 0D[ 0HGLDQ WK3FWO WK3FWO m5q56_in 348 34.97(88.8) 6.05 (15.4) 0 55(139.7) 34.5 (87.6) 31 (78.7) 38 (96.5) m5q56_cm 348 90.61 46.35 31 901 88.5 78 96.5 After all these corrections and conversion to centimetres, cases where the measurement appeared to be outside what would be considered plausible were set to missing. The cut-off values used were 58cm and 167cm (25 cases). These values were arrived at by reviewing other studies measuring women’s waist circumference in the US, Denmark and Scotland. After removing these cases there were 11% missing. A summary of the final data is given in Table 3-13 below. 7DEOH 6XPPDU\RIUHVSRQVHVWR4DIWHUFRQYHUVLRQDQGFRUUHFWLRQV 1 10LVVLQJ 0HDQ 6WG'HY 0LQ 0D[ 0HGLDQ WK3FWO WK3FWO 9454 1185 89.88 13.96 58 167 88.9 80 97 8VDJH Waist circumference can be used as either a continuous or categorical variable in analysis. The agreed cut-off values for waist circumference in adult women are equal to or greater than 80cm (increased risk) and equal to or greater than 88cm (substantially increased risk; NHMRC, 2003). The distribution in the 1946-1951 cohort at Survey 5 is given in Table 3-14. 7DEOH :DLVWFLUFXPIHUHQFHULVNFDWHJRULHV FRKRUW :DLVW&LUFXPIHUHQFH FP 1 < 80 2177 23 80 < 88 2469 26 88 4808 51 It is planned to include this question in future surveys of the 1973-1978 and 1946-1951 cohorts. 5HIHUHQFHV Hojgaard B, Gyrd-Hansen D, Olsen KR, Sogaard J, Sorensen TI. (2008) Waist circumference and body mass index as predictors of health care costs. PLoS ONE 3(7):e2619. Janssen I, Katzmarzyk PT, Ross R. (2004) Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 79(3):379-84. NHMRC. (2003) Clinical Practice Guidelines for the Management of Overweight and Obesity in Adults, NHMRC:Canberra. 2003. 104 /LIH(YHQWVDQG3URSRUWLRQRI/LIH(YHQWV Author: Sam Brilleman %DFNJURXQG In every survey there has been a question on life events. From this question the derived variable, ‘Proportion of Life Events’ (proplev) is calculated. This derived variable is a continuous value between zero and one. ‘Major stressful life events instruments ask respondents to report which of a list of events … happened to them in a specific time line, usually the last year. The events on the list are supposed to be representative of the population of major stressful life events that occur in people’s lives. … In general, the idea of life events instruments is that whatever major events do to us (e.g., require adaptation, induce negative affect and cognition), this accumulates as the number of events accumulate. The more events, the greater the stress.’ (Cohen, 2000) Researchers believe that increased stress due to major life events is likely to have a detrimental effect on an individual’s health. 6RXUFHLWHPV ‘Because it is impossible and undesirable to develop lists that include all possible life events, Dohrenwend et al. (1978) offered two criteria to guide item sampling: (a) The objective occurrence or event should be of sufficient magnitude to bring about changes in the usual activities of most individuals who experience the event, and (b) both events that represent universal human experiences (e.g., marriage, births, illnesses) and events that vary with social and cultural settings should be included.’ (Norbeck, 1984) In ALSWH, the items included in the life event question differ across cohorts and surveys. Some items are common to all, however researchers need to be aware that the exact items were designed specifically for each group. As an example, all surveys for the 1946-1951 cohort contain the item ‘Going through menopause’ whereas this item is not found in the 1973-1978 or 1921-1926 cohorts. The number of items included in the life event question also differs, however the proplev variable has been standardised such that it is comparable across both cohorts and surveys. Face validity Three items included in all life event questions in the ALSWH are for the sole purpose of face validity. These items should be excluded from any analysis, and are subsequently excluded from the calculation of proplev. They are ‘major personal illness’, ‘major personal injury’, and ‘major surgery’. Response format The questionnaire format for the life event question differs across surveys in the ALSWH. The possible formats for the response are outlined below: x Requests that the respondent reply ‘yes/no’ to the life event having occurred ’within the last 12 months’. (All cohorts were asked this question at Survey 1) x Respondent given the option to reply ‘yes’ (‘no’ is considered the default, i.e. for a non-response) to the life event having occurred ‘within the last 12 months’ and/or ’more than 12 months ago’. (Asked for the 1973-1978 cohort at Surveys 2, 3 &4; for the 1946-1951 cohort at Surveys 3 & 4) x Respondent given the option to reply ‘yes’ to the life event having occurred ‘within the last 12 months’ and/or ‘1-2 years ago’ and/or ‘more than 2 years (Asked for the 1946-1951 cohort at Survey 2) 105 x Respondent given the option to reply ‘yes’ to the life event having occurred ‘within the last 3 years.’ (Asked for the 1921-1926 cohort at Surveys 2, 3 & 4) For all ALSWH data sets, the proplev variable is calculated for life events occurring ‘within the last 12 months’, with the exception of the 1921-1926 cohort Surveys 2, 3 and 4 for which the proplev variable is calculated for life events occurring ‘within the last 3 years’. Coding from the data Researchers constructing a life event score themselves (i.e. not using the already constructed proplev variable in the data set) must be aware that there are different response scores. The score for a ‘No’ response is different at Survey 1. A response of ‘No’ is coded with a value of 2 in Survey 1, however for all later Surveys ‘No’ is coded with a value of 0. Any coding must take the scores into account. 1RWHVUHJDUGLQJWKHPHWKRGRIVWDQGDUGLVDWLRQ When considering the use of life events as a potential explanatory variable, three different methods for standardisation have been proposed. Each method has different merits and should be considered in the context of the research question. Method 1 Standardised scale (as with proplev) As has been done with the proplev variable, a standardised score based on all source items at the relevant survey can be calculated. This provides the proportion (or multiplied to represent a percentage) of all life events that have occurred for that survey. As previously mentioned the researcher needs to be aware that the specific source items contributing to this value at each survey may differ. The total number of items contributing may also differ. Method 2 Common items 1973-1978 and 1946-1951cohorts Table 3-15 and Table 3-16 give a list of items included in Surveys 1 to 4 for the 1973-1978 and 1946- 1951 cohorts. Researchers may only want to include these items when constructing a life events score to be used over time. When only considering common source items, the frequencies or counts will represent a standardised scale within a cohort. 1921-1926 cohort The common items have not been listed for the 1921-1926 cohort, since the data are not easily comparable across surveys. For the 1921-1926 cohort the time period for the question at Survey 1 is ‘within the last 12 months’ and at Surveys 2, 3 and 4 it is ‘within the last 3 years’. Method 3 Categorise the distribution based on percentiles For the 1973-1978 and 1946-1951 cohorts the life events distribution (for life events occurring ‘within the last 12 months’) at Survey 1 has a higher mean, median and variability than at any subsequent survey. With more variability in the distribution of a predictor there is an increased probability of observing an effect due to chance. To avoid this problem, it may be helpful to categorise the distribution based on percentiles. The underlying distribution of life events is non-continuous, so care needs to be taken when choosing percentile cut-points. In practice approximate percentiles are probably necessary. 106 7DEOH/LIHHYHQWLWHPVFRPPRQWRDOOVXUYH\VIRUWKH FRKRUW 6 666%ULHIGHVFULSWLRQ a a a a *Major personal illness b b b b *Major personal injury c c c c *Major surgery f g g f New relationship q s s r Death of close friend aa cc aa y Decreased income bb dd bb z Natural disaster/House fire cc ee cc aa Loss/Damage to property dd ff dd bb Being robbed ee gg ee cc Serious accident ff hh ff dd Pushed/Grabbed/Shoved gg ii gg ee Unwanted sexual activity hh jj hh ff Legal troubles/Court case ii kk ii gg Family member/Friend in jail i h h g Married/Moving in with someone k k k j Becoming sole parent l l l k Hassles with parents m m m l Conflict between family n n n m Parents divorced/remarried p o o n Death of partner/close family u u u s Difficulty finding a job v w w u Beginning/Resuming work x y x v Distressing harassment at work y z y w Loss of job *Items directly related to health, excluded from calculation of proplev. 107 7DEOH/LIHHYHQWLWHPVFRPPRQWRDOOVXUYH\VIRUWKH FRKRUW 6 666%ULHIGHVFULSWLRQ a a a a *Major personal illness *Major personal injury c c d e *Major surgery d d e f Going through menopause e e f g Decline in health of spouse f f g h Decline in health of family g g h i Starting new relationship h h i j Infidelity of spouse i i j k Break up of relationship j j k l Divorce k k l m Conflict with older children l l m n Child/Family leaving home m m n o Death of spouse/partner n n o p Death of child o o p q Death of other family member p p q r Death of close friend q q r s Change of work s s v x Decreased income t t w y Moving house u u x z Natural disaster v v y aa Major loss/Damage to property w w z bb Being robbed y y bb cc Pushed/Grabbed/Shoved/Hit z z cc dd Unwanted sexual activity aa aa dd ee Legal troubles/Court case bb bb ee ff Family/Friend in jail *Items directly related to health, excluded from calculation of proplev 108 6$6&RGH An example of the SAS code for constructing the proplev variable is given below. The first part of the example refers to the 1973-1978 cohort Survey 1, while the second part of the example refers to 1946-1951 cohort Survey 2. /*** Survey 1 - requires recoding of “No” response ***/ array y1q29(*) y1q29d--y1q29ii; do i = 1 to dim(y1q29); if y1q29(i) = 2 then y1q29(i) = 0; end; survey = y1survey; if survey = 1 then do; sumle = sum(of y1q29(*)); y1proplev = round(sumle/dim(y1q29),.0001); end; else if survey = 2 then y1proplev = . ; /*** Survey 2 onwards ***/ array m2q32(*) m2q32Ad--m2q32Abb; survey = m2survey; if survey = 1 then do; sumle = sum(of m2q32(*)); m2proplev =round(sumle/dim(m2q32),.0001); end; else if survey = 2 then m2proplev = . ; 5HIHUHQFHV Cohen, S. (2000). Measures of Psychological Stress. http://www.macses.ucsf.edu/Research/Psychosocial/notebook/stress.html Norbeck, J. S. (1984). Modification of Life Event Questionnaires for Use with Female Respondents. Research in Nursing and Health, 7, 61-71. 109 0$,17(1$1&(2)&2+2576 Authors: Anna Graves and Jenny Powers 0DLQWHQDQFH VWUDWHJLHV Cohort maintenance and tracking of ‘return-to-sender’ mail continues according to the strategies outlined in previous reports. The office team continues to track all women who responded to Survey 1 in 1996, and who are not known to have died or withdrawn from the project since then. This includes women who did not respond to Survey 2, Survey 3, Survey 4 or Survey 5. Participants for whom we have no current contact details remain in the tracking system unless they are positively identified as deceased, withdrawn, permanently emigrated, or otherwise ineligible or unwilling to participate. Secondary contacts, electoral rolls, and electronic white pages continue to be the main sources of information. Increasingly we are finding email addresses to be useful, especially among the 1973- 1978 cohort of women. While in previous years, email addresses seemed to be fairly short-lived and unstable, it now appears that individuals are likely to keep the same email address for some years. 1DWLRQDO'HDWK,QGH[ The National Death Index (NDI) is used on an annual basis to identify women who are recorded as being deceased. This not only adds to information provided to us by family members, but also provides administrative data on causes of death. A list of participants’ details, including unconfirmed deceased participants and participants who have withdrawn from the project, was sent to AIHW in November 2007 for matching against the NDI. Results from this record matching process were recorded in Report 30. The next round of matching of the women in our project to the NDI will commence in November 2008. &DXVHRI'HDWKFRGHV The list of matched deceased records that have no cause of death (COD) codes was sent to AIHW in April 2008 to obtain updated COD codes. Of the 3,630 deaths confirmed with NDI (including participants who have withdrawn) cause of death codes are available for 3186. Of the 444 deaths for which we have no COD information, all deaths occurred in the last two years and these matches were identified at the 2007 round of matching. COD codes for these deaths should become available within the next two years as the availability of COD codes lag behind the registration of deaths by up to 2 years. 7DEOH &RQILUPHGGHDWKVZLWKDQGZLWKRXW&2'FRGHVE\\HDURIPDWFKLQJ There can be up to 19 causes of death. The first cause of death is the underlying cause of death. All others are additional causes of death. Multiple cause of death coding was used from 1997 onwards. The codes for causes of death depend on when the person died and when their record was placed on the NDI. Those deaths that were registered in or before 1996 are recorded in ICD-9, those registered in 1997 and 1998 are a combination of ICD-9 and ICD-10 and those registered in 1999 and onwards are recorded in ICD-10. 110 8SGDWHRIVDPSOHDQGUHVSRQVHUDWHV 6XUYH\ Information provided in early reports has been repeated and updated here for completeness. The numbers provided in the Tables are up to date as at October 2008. More than 40 000 women responded to Survey 1 of the main cohorts in 1996. Because of uncertainties about the accuracy of the Medicare database (which was used as the sampling frame for the stratified random samples), response rates cannot be exactly specified. We have estimated that 41-42% of the 1973-1978 cohort, 53-56% of the 1946-1951 cohort, and 37-40% of the 1921-1926 cohort responded to the initial invitation to participate. Confidentiality restrictions meant that the names of the selected women were unknown to researchers. Usual methods of encouraging participation such as by telephone could not be used. The response rates were pleasing given that the invitation included a request for women to participate in the longitudinal study for up to 20 years. In light of these response rates, it is important to assess any response bias so that the generalisability of the study findings can be determined. A comparison of the demographic characteristics of respondents and non-respondents was not possible because privacy guidelines prevented the researchers from having any information about women who were selected to receive an invitation but did not respond. We were able, however, to obtain aggregate data for non-respondents’ use of health services (from the Australian Medicare database). These data suggest that there are small differences in use of health services among respondents and non-respondents, with non-respondents less likely, for example, to have visited a medical specialist in the last 2 years (from the 1946-1951 cohort 49% versus 54%; from the 1921-1926 cohort 65% versus 72%). There was not a significant difference in health service use between respondents and non-respondents from the 1973-1978 cohort. A proportion of this difference may be explained by the fact that some women who were selected may no longer be living in Australia or may have died, as the Medicare database is not routinely linked to emigration records or the National Death Index in Australia. Although we were not able to ascertain reasons for non-response (because we were not allowed to know any details about the selected women), we were able, through comparison with the 1996 census data, to confirm that the participants in each of the cohorts are reasonably representative of the general population of women of the same age in Australia (see Table 4-2). There is some response bias in terms of overrepresentation of women with tertiary education and under- representation of some groups of immigrant women. This information and Table 4-2 are taken from Brown, W. J., Dobson, A. J., Bryson, L., & Byles, J. E. Women's Health Australia: On the progress of the main cohort studies. Journal of Women's Health & Gender-Based Medicine, 1999; 8(5): 681-688. 7KHVDPSOHIRUWKHORQJLWXGLQDOVWXG\ Retention and representativeness Some women only completed Survey 1 in 1996 and did not provide any contact details (532 in the 1973-1978 cohort, 383 in the 1946-1951 cohort, and 508 in the 1921-1926 cohort). Hence, the numbers of women actually enrolled in the ALSWH were 14 247 in the 1973-1978 cohort, 13 716 in the 1946-1951 cohort and 12 432 in the 1921-1926 cohort. 111 7DEOH6RFLRGHPRJUDSKLFFKDUDFWHULVWLFVRIWKH FRKRUWWKH FRKRUWDQG WKH FRKRUWDQGIRUZRPHQRIWKHVDPHDJHLQWKHJHQHUDOSRSXODWLRQ $%6&HQVXV Among the 1973-1978 cohort, 69% responded to Survey 2 in 2000, 65% to Survey 3 in 2003 and 67% have responded to Survey 4 in 2006 (see Table 4-3). This retention compares well with other surveys of this highly mobile age group. The major reason for non-response among the 1973-1978 cohort has been that the research team was unable to contact the women (21% of eligible women at Survey 2, 28% at Survey 3 and 21% at Survey 4), despite using all possible methods of maintaining contact. Women in their twenties are characterised by high levels of mobility, change of surname on marriage, often not having telephone listings, not being registered to vote and making extended trips outside Australia for work, education or recreation. 112 7DEOH 3DUWLFLSDWLRQDQGUHWHQWLRQRI FRKRUW 6XUYH\ 6XUYH\ 6XUYH\ 6XUYH\ Age in years 18-23 22-27 25-30 28-33 Eligible at previous survey 14 247 14 116 13 886 Ineligible deceased between surveys 22 10 15 frailty (e.g. intellectual disability) 3 6 4 withdrawn before survey mailout 106 213 311 date Total ineligible 131 229 330 Eligible at current survey 14 116 13 887 13 557 Non-respondents withdrawn from the project 124 200 171 contacted but did not return 1332 654 1372 survey unable to contact participant 2972 3952 2869 Total non-respondents 4428 4806 4412 Respondents completed survey 14 247 9688 9081 9145 Retention rate as % eligible 69% 65% 68% Demographic characteristics (country of birth, marital status, education, employment and lone person household) of the 1973-1978 cohort respondents at Survey 1 (1996) and Survey 2 (2000) were compared with those of women of the same age in the Australian population, using data from the 1996 and 2001 Censuses, respectively. The comparisons revealed few differences - however there was some under-representation of women from non-English language countries at both surveys, a not unexpected finding given that Medicare routinely excludes overseas students. The disparity in education increased between 1996 and 2001. Whereas at the 1996 Census almost 70% of young women had no post school qualifications (ALSWH and the general population), 31% and 49% had no post school qualifications in the ALSWH sample in 2000 and the 2001 Census respectively. Some of these differences will be due to overseas graduates returning home and Australian graduates working overseas. ALSWH women were less likely to be employed compared with women of the same age in the 1996 Census (52% vs. 60%), but more likely to be employed than women of the same age in the 2001 Census (85% vs. 67%). Retention has been much higher among the 1946-1951 cohort of women; 91% responded to Survey 2 in 1998 and 84% responded to Survey 3 in 2001 and Survey 4 in 2004 (see Table 4-4). The major reasons for non-response among the 1946-1951 cohort were that the research team was unable to contact the women (6%, 7%, 8% and 7% of eligible women at Survey 2, Survey 3, Survey 4 and Survey 5, respectively) and non-return of questionnaires by women who could be contacted (2%, 8%, 7% and 8% of eligible women at the second, third, fourth and fifth surveys). Women of the 1946-1951 cohort typically lead busy lives, often working as well as caring for parents and their children. The women who could not be contacted were more likely to be separated, divorced or widowed. 113 7DEOH 3DUWLFLSDWLRQDQGUHWHQWLRQRIZRPHQLQWKH FRKRUWZKRZHUH DW6XUYH\LQ 6XUYH\ 6XUYH\ 6XUYH\ 6XUYH\ Age in years 47-52 50-55 53-58 56-61 Eligible at previous survey 13 716 13 606 13 310 12 979 Ineligible deceased between surveys 50 65 88 97 frailty (e.g. dementia, stroke) 7 14 14 19 withdrawn before survey mailout 53 217 229 167 date Total ineligible 110 296 331 283 Eligible at current survey 13 606 13 310 12 978 12 696 Non-respondents withdrawn from the project 156 155 136 217 contacted but did not return survey 254 999 886 998 unable to contact participant 858 930 1052 855 Total non-respondents 1268 2084 2074 2070 Respondents completed survey 12 338 11 226 10 905 10 626 Retention rate as % eligible 91% 84% 84% 84% Data from the 1996 and 2001 Censuses were used to compare demographic characteristics (country of birth, marital status, education, employment and lone person household) of women of the same age in the Australian population with the 1946-1951 cohort respondents at Survey 1 (1996) and Survey 3 (2001). There were few differences - however there was some under-representation of women from non-English language countries and women who were separated or divorced at both surveys. Of the 1921-1926 cohort of women, 91% responded to Survey 2 in 1999, 85% to Survey 3 in 2002 and 84% to Survey 4 in 2005 (see Table 4.6). Among the 1921-1926 cohort of women the major reason for non-response was non-return of the questionnaire (4%, 8% and 7% of eligible women at Surveys 2, 3 and 4 respectively) although increasingly the participant could not be contacted (3% at Surveys 2 and 3 and 6% at Survey 4). Non-respondent women tended to report poorer self-rated health at Survey 1 than respondents. 114 7DEOH 3DUWLFLSDWLRQDQGUHWHQWLRQRIWKH FRKRUWRIZRPHQ 6XUYH\ 6XUYH\ 6XUYH\ 6XUYH\ Age in years 70-75 73-78 76-81 79-84 Eligible at previous survey 12 432 11 535 10 187 Ineligible deceased between surveys 529 569 769 frailty (e.g. dementia, stroke) 106 263 381 withdrawn before survey 262 516 507 mailout date Total ineligible 897 1348 1657 Eligible at current survey 11 535 10 187 8530 Non-respondents withdrawn from the project 311 385 267 contacted but did not return 481 860 592 survey unable to contact participant 309 295 513 Total non-respondents 1101 1540 1372 Respondents completed survey 12 432 10 434 8647 7158 Retention rate as % eligible 91% 85% 84% Demographic characteristics (country of birth, marital status, education and lone person household) of the 1921-1926 cohort respondents at Survey 1 (1996) and Survey 3 (2002) were compared with those of women of the same age in the Australian population, using data from the 1996 and 2001 Censuses respectively. Comparisons showed few differences. There was some under-representation of women from non-English speaking countries in the ALSHW sample at both surveys. Comparisons are difficult for marital status and educational qualifications due to the high level of missing data in the Census. 115 '$7$/,1.$*( Author: Annette Dobson 3URJUHVVZLWKGDWDOLQNDJH Significant advances have been made in gaining approval for linkage of ALSWH data with data from the Medicare Benefits Scheme (MBS) and the Pharmaceutical Benefits Scheme (PBS), together with the corresponding data for benefits provided by the Department of Veterans Affairs for all participants (except any women who have asked for their data not be used in this way). With a great deal of help from staff of the Department of Health and Ageing (DoHA), a protocol for linkage of de-identified data has been developed and has been approved by the DoHA Ethics Committee. Use of linked data for all participants will overcome potential biases from analysing data only from those women who gave explicit signed consent to linkage, and it will increase the statistical power of the study for analysis of less common conditions, services or medications. For these reasons, the linkage under the new proposed protocol will provide better evidence for DoHA on which to base policy. The other situation where linkage to national data is required relates to use of aged care support among the 1921-1926 cohort women. It is apparent that increasing numbers of women in this cohort are using services provided through the Health and Community Care (HACC) and residential aged care systems. These women may become difficult to follow up through ALSWH tracing. While for many it may not be appropriate to continue to ask them to continue to complete surveys, it is important to be able to analyse patterns of service use in relation to the rich data on these women’s lives already obtained through ALSWH. The DoHA Ethics Committee approval includes these data linkages. In all States and Territories, health data linkage is also likely to improve substantially through the Population Health Research Network, which is funded under the Australian National Collaborative Research Infrastructure Strategy. Already various analyses are underway, or in advanced planning stages, based on linking ALSWH data with data from New South Wales Health, the Department of Health in Western Australia and other organisations in these states. These projects are forerunners of work that should be possible for other jurisdictions over the next few years. Additionally for the pilot survey for Survey 5 of the 1921-1926 cohort we tested a process for asking participants to consent to an even wider range of data linkage including cancer registers. Of 144 respondents to the pilot study, 128 provided consent, 14 did not sign the relevant section, and 2 indicated that they did not wish to consent. As a result, a request for consent to this wider range of data linkage was included in the main survey for the 1921-1926 cohort in 2008. 116 0$-25 5(32576 8VHDQGFRVWVRIPHGLFDWLRQVDQGRWKHUKHDOWKFDUHUHVRXUFHV )LQGLQJVIURPWKH$XVWUDOLDQ/RQJLWXGLQDO6WXG \RQ:RPHQ¶V +HDOWK Authors: Julie Byles, Deborah Loxton, Janneke Berecki, Xenia Dolja-Gore, Richard Gibson, Richard Hockey, Ian Robinson, Lynne Parkinson, Lyn Adamson, Jayne Lucke, Jennifer Powers, Anne Young, and Annette Dobson. Report prepared for the Australian Government Department of Health and Ageing $LPVRIWKHUHSRUW The Australian Longitudinal Study on Women’s Health (ALSWH) is a longitudinal population-based survey funded by the Australian Government Department of Health and Ageing. The project began in 1996 and involves three large, nationally representative, cohorts of Australian women representing three generations: x Women born in 1973-1978, aged 18 to 23 years when first recruited in 1996 (n=14 247) and now aged 30 to 35 years x Women born in 1946-1951 women, aged 45 to 50 years in 1996 (n=13 716), now aged 57 to 62 years x Women born in 1921-1926 cohort women, aged 70 to 75 years in 1996 (n=12 432), now aged 82 to 87 years The women have now been surveyed at least four times over the past 12 years providing a large amount of data on the women’s lifestyles, use of health services and health outcomes. The survey schedule is reported in Table 6-1. 7DEOH 6FKHGXOHRI6XUYH\VIRUWKH$XVWUDOLDQ/RQJLWXGLQDO6WXG\RQ:RPHQ¶V+HDOWK The report was prepared on the basis of discussions between the ALSWH research team and staff of the Australian Government Department of Health and Ageing and presents findings on claims for, and costs of, medications and other health care resources from four surveys of the three cohorts. The report makes use of Pharmaceutical Benefits Scheme and Medicare data that are linked to survey data and provide details on the women’s health, health behaviours, and social circumstances. Combined, these data provide unique and rich information on health service use by particular sub- groups of women, longitudinal changes and health outcomes. The report has the following aims: x To describe the major trends in medication claims and costs among the three age groups of women in the ALSWH according to urban, rural and remote area of residence. x For common conditions, to assess factors associated with medication claims by women with: o Depression o Asthma o Arthritis 117 o Cardiovascular disease o Diabetes The report: x Describes medications claims for the index condition. x Compares costs of medication and other health services for women with different conditions. x Assesses health outcomes associated with medication claims for selected conditions. o For common medications, to assess factors affecting the women’s long-term claims for: Statins Bisphosphonates Proton Pump Inhibitors o To assess the uptake of new health care items and the impact of these items on women’s use of health care services, costs, and health outcomes: 75+ Health Assessment Annual Cycle of Care for Diabetes. o To examine the use of complementary and alternative medical care by women in the three cohorts. 6XPPDU\RIPDMRUILQGLQJV Commonly used medications Medications play an important role in preventing and managing illness and improving quality of life for Australian women. In this report we examine claims to the Pharmaceutical Benefits Scheme (PBS) for ALSWH participants in the three age groups and those factors that are associated with medication claims for these women. The data are for women who have consented to the release of these data and who were alive and participating in the study in each calendar year 2003-2005. Medications for women in each cohort were grouped and described according to the Anatomical and Therapeutic Class coding system developed by the World Health Organisation. Using this coding system results revealed that women in the 1946-1951 cohort and the 1921-1926 cohort had claims for similar groups of medications except that the 1921-1926 cohort were more likely to have claims for each medication group. Women in the 1921-1926 cohort were least likely to be identified as having any PBS claims overall and within each group of medications. Among 1973-1978 cohort women, the most commonly identified PBS claims were for nervous system drugs, and particularly antidepressants (used by 8%). Antidepressants were also common among 1946-1951 cohort women (14% of 1946-1951 cohort women) and 1921-1926 cohort women (18%) and prevalence of these medications increased with age. However not all women who reported a diagnosis of depression on the surveys were identified as having antidepressant medications. Among 1973-1978 cohort women who reported a diagnosis of depression, 60% had no claims for any antidepressant medication in 2005 and 40% had no claims at any time during the period 2002-2005. For 1946-1951 cohort women the corresponding percentages were 36% and 17%, and for 1921-1926 cohort women the percentages were 33% and 18%. Depression and claims for antidepressant medications were associated with area of residence (women in rural areas were less likely to receive antidepressant medications), marital status, socioeconomic status, health care use, and the presence of comorbid conditions such as arthritis, back pain and heart disease. Many women with depression continued to have claims for antidepressant medications for long periods. Among 1946-1951 cohort and 1921-1926 cohort women, more than 50% of women had claims in both 2002 and 2005. Women from the 1973-1978 cohort were less likely to have claims in both periods, and were equally likely to cease, or take up antidepressant medications, or to have no claims in either year. A significant improvement in scores on the SF-36 Mental Health Index was observed for women with self-reported depression who ceased antidepressant medications between 2002 and 2005, indicating positive outcomes for women in this group. Among 1946-1951 cohort and 1921-1926 cohort women, the most common PBS claims were for cardiovascular medications, claimed for 28% of 1946-1951 cohort women and 75% of the 1921-1926 cohort women in 2005. The most commonly used combination of CVD medications for 1946-1951 cohort and 1921-1926 cohort women were angiotensin converting enzyme inhibitors (ACE) and 118 angiotensin II receptor agonists (AII) with statins, and ACE/AII with aspirin with or without statins. Statins were the main class of medications in this group (claimed for 16% of 1946-1951 cohort women and 38% of 1921-1926 cohort women). Statins were also the medications with the highest full-cost per woman (costing $588 per year per 1946-1951 cohort woman in the cohort, and $1022 per woman prescribed these medications), and the highest out-of-pocket costs with the median annual cost for each 1946-1951 cohort woman with claims for statins being $257. Between 2002 and 2005, PBS claims for statins increased in the 1946-1951 and 1921-1926 cohorts in line with the whole Australian population. In the 1946-1951 cohort claims for statins also increased after natural menopause as well as after ‘surgical’ menopause (hysterectomy and/or oophorectomy). 1946-1951 cohort women with claims for statins had lower levels of education, were less likely to be employed, had more difficulty managing on their income than women without statins and were also more likely to have diabetes, hypertension or heart disease (e.g. angina pectoris or a history of myocardial infarction). However, in many cases 1946-1951 cohort women did not use statins over the longer term. In the 1946-1951 cohort, half the women with statins missed a claim for this medication within five months of observation. Longer-term use was more likely among women who reported higher levels of physical activity, but was not associated with other sociodemographic or health variables. Alimentary tract medications were also common among 1946-1951 cohort and 1921-1926 cohort women (claimed for 22% and 57% of these women respectively in 2005), and were among the top five most commonly used medications in all age groups. The most common type of medication in this group was medications for peptic ulcer or gastro-oesophageal reflux disease (GORD) with claims identified in 2005 for 3% of the 1921-1926 cohort women, 16% of the 1946-1951 cohort women, and 38% of the 1921-1926 cohort women. The most common of these types of medications were Proton Pump Inhibitors (PPIs) which are used for the treatment of conditions causing heartburn or gastric pain, such as gastro-oesophageal reflux disease and peptic ulcers. Among 1946-1951 cohort and 1921-1926 cohort women, PPIs were commonly claimed in association with non-steroidal anti- inflammatory drugs (NSAIDs) and rarely in association with Helicobacter Pylori eradication treatment. PPI claims were mostly (64%) not associated with either of these conditions, but were more likely to be for the treatment of reflux disease. Claims for PPIs by 1946-1951 cohort and 1921-1926 cohort ALSWH participants, already considerable in 2002, increased between 2002 and 2005. This increase was not solely due to ageing. PPIs also appear to be used for long periods. For the initial treatment for reflux disease, two to four weeks of use of PPIs is recommended. In reality 60% of initial prescriptions between 2002 and 2005 contained five repeats. Of the women who initiated PPI treatment for reasons other than gastro- protection while taking NSAIDs or during the eradication of ulcer disease, more than two thirds had claims for more than six months. Women who had claims for PPIs were also more likely to have claims for NSAIDs and asthma medication, and they were also twice as likely to have claims for antidepressants. PPI script filling among 1946-1951 cohort women was associated with depression and anxiety as well as lower levels of education, more difficulties managing on available income, more frequent GP visits, and higher BMI. Likewise, depression was also associated with heartburn/indigestion and 1946-1951 cohort women who reported having this symptom ‘often’ were twice as likely to report depression as women who reported never having this symptom. Drugs for the musculoskeletal system were also among the most commonly used medications in the 1946-1951 and 1921-1926 cohorts, with 16% of 1946-1951 cohort women and 43% of 1921-1926 cohort women having claims for this class of medication in 2005. The use of these medications reflects the high prevalence of arthritis which was reported by 32% of 1946-1951 cohort women and 64% of the 1921-1926 cohort women by Survey 4. However, in 2005, 71% of 1946-1951 cohort women and 63% of 1921-1926 cohort women who reported having arthritis did not have PBS claims for arthritis medications. Those 1946-1951 cohort women who reported having arthritis and/or who had PBS claims for arthritis medication had lower levels of education and more difficulty managing on their income than women without arthritis or arthritis medication. Most 1946-1951 cohort and 1921- 1926 cohort women who had claims for arthritis medication had claims for only one type of arthritis medication. However, there were large changes in the types of arthritis medications during 2004, following changes to the availability of some of the coxib medications. 119 The other commonly claimed musculoskeletal medication was bisphosphonates. These drugs are for the treatment of osteoporosis and the subsequent prevention of fractures, and heartburn and dyspepsia are commonly reported side-effects. Claims for bisphosphonates by 1946-1951 cohort and 1921-1926 cohort women increased between 2002 and 2005. However, many women did not remain on bisphosphonates long-term, as is the intended use. Within six months of starting to claim bisphosphonates, more than half of the 1921-1926 cohort women were missing at least one expected claim for bisphosphonates (indicating discontinuous use). Women in the 1921-1926 cohort with a healthy lifestyle, in terms of physical activity and not smoking, were more likely to fill bisphosphonates prescriptions on time. Women claiming PBS medication for heartburn before starting to claim bisphosphonates were less likely to fill bisphosphonates prescriptions on time. Respiratory system drugs were among the five most commonly claimed medications among the 1921- 1926 cohort, and were also commonly claimed for 1946-1951 cohort and 1921-1926 cohort women. In 2005, 7% of 1921-1926 cohort women, 10% of 1946-1951 cohort women and 20% of 1921-1926 cohort women had claims for respiratory system drugs. Adrenergic inhalants were the third most common therapeutic sub-group claimed for 1921-1926 cohort women, and across all cohorts the most common medications claimed for asthma were beta-2 receptor agonists, adrenergics, glucocorticoids and anticholinergics. Women in the 1921-1926 cohort women were less likely to have claims for asthma medication than 1946-1951 cohort or 1921-1926 cohort women, possibly because 1921-1926 cohort women were more likely to buy over-the-counter medications which would not appear in PBS data. Across all cohorts, women with claims for asthma medication were more likely to be overweight or obese. Overweight and obesity were also strongly associated with claims for diabetes medication. Almost 90% of 1946-1951 cohort women and two thirds of 1921-1926 cohort women who had claims for diabetes medications were overweight or obese. Women who claimed for diabetes medications also had higher levels of morbidity, more GP visits and were more likely to see specialists, hospital doctors and pharmacists than other women. However, about half of the 1946-1951 cohort women and more than 40% of the 1921-1926 cohort women who had ever reported diabetes did not make claims for diabetes medications. Furthermore, many of these women did not report diabetes at Survey 4, suggesting that many of these women were being successfully managed by diet and lifestyle alone. Impact of new health care items Over the past several years, a number of new health care items have been introduced with the intention to improve health care and prevent disability for people with particular needs. This report examined women’s use of two groups of these items, the 75+ Health Assessments, and the Diabetes Annual Cycle of Care (ACC), and assessed associated costs and changes in quality of life. Health assessments are government-subsidised annual health check-ups for people aged 75 years and over and are designed to evaluate a person's health and physical, psychological and social function and to determine whether preventative healthcare and education should be considered. Of the 4020 women in the 1921-1926 cohort who consented to linkage to Medicare data and were eligible for a health assessment, 58% had at least one health assessment between November 1999 and the end of 2005 and 40% had two or more assessments. Women with at least one health assessment had more visits to the GP and took more medications than women who had no assessments. They were also more likely to rate their health as fair or poor and to have been admitted to hospital. However, health assessments did not have a measurable impact on survival. Also, among women who were still alive in 2004, there was no statistically significant difference in physical function scores between women who did and did not have health assessment. There was a small trend towards a lesser decline in scores for women who had more than one health assessment. The Diabetes Annual Cycle of Care was introduced as part of a national diabetes integrated program to provide incentives for GPs for early diagnosis and effective management of people with diabetes. The ACC includes pathology testing (including a haemoglobin A1c (HbA1c) test which indicates average blood glucose over a period of two to three months) and lifestyle risk factor assessment, as well as screening for retinopathy and foot problems. Of the women in the 1946-1951 cohort who consented to linkage to Medicare data and completed Survey 4 (2004), 6% reported being diagnosed with diabetes, up from 2% of the same women at 120 Survey 1 (1996). Of the women in the 1921-1926 cohort who consented to linkage to Medicare data and completed Survey 4, 6% reported being diagnosed with diabetes in Survey 1 (1996) and 14% reported diabetes at any survey, by Survey 4 (2005). For both 1946-1951 cohort and 1921-1926 cohort women, compared with uptake of HbA1c only, uptake of ACC was associated with a higher number of GP visits and bulk billing. However, MBS costs were similar for 1921-1926 cohort women with diabetes who did and did not have ACC. Among 1946-1951 cohort women MBS and PBS costs were higher for women with diabetes who had ACC compared with those who had HbA1c only, whereas PBS costs were almost identical for 1921-1926 cohort women with diabetes who had ACC compared with HbA1c only. Differences were also apparent between 1946-1951 cohort and 1921-1926 cohort women when health outcomes of ACC were examined. Furthermore, among 1946-1951 cohort women, differences in health outcomes emerged between prevalent and incident diabetes. Women in the 1946-1951 cohort with prevalent diabetes who went on to have ACC tended to have the poorest health at baseline, prior to the introduction of ACC. However, 1946-1951 cohort women with incident diabetes who had ACC tended to have similar health at baseline to those women with incident diabetes who did not go on to have ACC. Women in the 1946-1951 cohort with prevalent diabetes who had ACC continued to have poorer health than those who did not have ACC, although the decline in health was less pronounced than prior to the uptake of ACC. Those 1946-1951 cohort women with incident diabetes who had ACC experienced better physical health outcomes than 1946-1951 cohort women with incident diabetes who did not undertake ACC. These findings are important in assessing whether strategies such as the 75+ Health Assessments and Diabetes Annual Cycle of Care are achieving their objectives for better patient outcomes. Both sets of items seem to have been adopted fairly widely and are now a mainstream component of primary care. The data from ALSWH show some small health benefits from these items in terms of health related quality of life. A question remains as to whether these systems of care could be improved, to increase their uptake and efficiency and to enhance their impact. Complementary and alternative medical care Use of complementary and alternative medicine (CAM) is increasing worldwide. At Survey 1 in 1996, 19% of the 1973-1978 cohort, 28% of the 1946-1951 cohort and 15% of the 1921-1926 cohort reported having consulted an alternative health practitioner over the previous 12 months. CAM users in all three cohorts were more likely to live in non-urban areas; 1921-1926 cohort and 1946-1951 cohort CAM users also had higher levels of education and were more likely to be employed. CAM users also reported poorer physical and mental health, more symptoms and illness, and higher use of conventional health services than non-users, and use of non-prescription medication was more common among CAM users. Women with cancer and women reporting more illness were more likely to adopt CAM use than other women. Longitudinal analyses have shown that both 1946-1951 cohort and 1921-1926 cohort women with declining health were more likely to start using CAM. Among 1921-1926 cohort women, use of CAM declined as they aged but increased as the number of reported symptoms increased and for non- urban residents compared with urban residents. Among 1946-1951 cohort women those who ceased taking prescription medicines were more likely to start using CAM. In considering the use of specific providers, 1946-1951 cohort women who used chiropractic, osteopathy and acupuncture appear to be higher users of conventional health services and to be suffering from a wide range of symptoms. These results suggest that chiropractic, osteopathy and acupuncture are used in conjunction with conventional care and used within an overall health care regime. Because CAM is often used in conjunction with conventional care, there may be a need for increased communication and interfacing between CAM and conventional practitioners. Knowledge of the use of CAM is important as there is potential for drug interaction between conventional medicine and some CAM treatment. In addition, patient safety may be jeopardised by CAM users failing to inform their conventional medical practitioners about their CAM use and GPs underestimating their patient’s use of other medicines. 121 'LVFXVVLRQ Medications are an important part of women’s health care. The prevalence of medication use among women in the ALSWH increases with age and as chronic health conditions become more common, but use of some medication is likely for women in all cohorts. At older ages however, women are not only more likely to be using medications, but are also more likely to be using two or more medications in combination. The need for these medications may be due to the need to treat a number of co- existing conditions, or as in the case of the use of chemoprophylaxis for prevention of cardiovascular disease, to reduce a number of co-operative risk factors. In other cases, the need for some medications may be to treat the side effects of other medications or, as seen in the case of bisphosphonates, the addition of one medication may exacerbate another underlying condition. Both side effects and costs of medications may limit their longer-term use. This poses a particular problem for drugs such as statins and bisphosphonates that are designed for long-term use and to prevent potential health problems rather than treat existing symptoms. The effectiveness and cost- effectiveness of these preventative strategies may be severely hampered if those women who take up these strategies do not continue treatment long enough for them to be effective. The cost to the women of any single medication may not seem particularly large, but it needs to be considered that women who use one medication are also likely to be using another medication. This multiple medication use is not limited to older women. The cumulative out-of-pocket cost of medication can be substantial. Moreover, medications are more likely to be used by women who have less socioeconomic advantage and who have more difficulty managing on their income. An analysis of medications for women with common chronic conditions also shows that these conditions are often more widespread among people with socioeconomic disadvantage for whom the costs of medications may be a significant burden. These analyses also show a relationship between medication use and other health behaviours and risks. For example, body mass index and smoking were both associated with asthma and with asthma medications. Attention to these behaviours and conditions would appear to be important for reducing medication costs as well as improving health. 122 ',66(0,1$7,212)678'<),1',1*6 :HEVLWH The ALSWH study web site, maintained at the University of Newcastle, can be viewed at www.alswh.org.au. Each month the website content is updated with current lists of collaborators, ongoing and completed analyses, reports, and abstracts of all accepted and published papers. The password protected sections of the website for ‘Collaborators’ and ‘Investigators and Staff’ are also routinely revised with minutes of meetings, project notes and other internal documents. 3XEOLFDWLRQV &RQIHUHQFHSURFHHGLQJVSXEOLVKHG Byles J & Brown W. The impact of women's weight on health outcomes: A problem for now and in the future. 13th National Conference on Health Outcomes, Australian Health Outcomes Collaboration 2008. No abstract available. Byles J, Millar C, Sibbritt D & Chiarelli P. Living with urinary incontinence: A longitudinal study of older women. 13th National Conference on Health Outcomes, Australian Health Outcomes Collaboration 2008. No abstract available. 3DSHUVSXEOLVKHG Berecki J, Lucke J, Hockey R & Dobson A. Transitions into informal care and out of paid employment of women in their 50's: A study of cause and effect. Social Science and Medicine. 2008; 67(1)122- 127. Data from the Australian Longitudinal Study on Women’s Health were used to study the order of events leading to informal caregiving and changes in labour force participation in mid-aged women, taking into account health and socioeconomic status. This analysis included women who responded to the third (2001) and fourth (2004) surveys and providing data for the caring and employment variables used (n= 9857). Caring was defined as providing care for an ill, frail or disabled person at least seven hours per week. Between 2001 and 2004, the proportion of women caring increased from 12% to 14% (difference 2.3 % [95% CI: 1.6 - 3.1 %]). Paid employment participation decreased from 67% to 62% in 2004 (difference -5.2 % [95% CI: -6.1 - -4.4 %]). Logistic regression model results showed that taking up caring between 2001 and 2004 was not statistically significantly associated with employment status in 2001. Among women who took up caring, however, hours spent in paid employment in 2001 was negatively associated with hours spent caring in 2004 (rs -0.10, p=0.004). Amongst women working in 2001, taking up caring between 2001 and 2004 was associated with reduced participation in paid employment (OR=1.63; 95%CI: 1.34 - 1.98). In conclusion, among mid- aged women, transitions into caregiving were irrespective of time spent in paid employment, but were followed by a decrease in labour force participation. Policies could aim to support continuing labour force participation during caregiving by creating flexible working arrangements; re-employment programs could support women who quit work in getting back to paid employment after a period of caregiving Brown W, Burton N & Rowan P. Updating the evidence on physical activity and health in women. American Journal of Preventive Medicine. 2007; 33(5) 404-411. Objective: This narrative review updates evidence from the last 10 years on physical activity (PA) and the primary prevention of cardiovascular disease, diabetes, and cancer in women. 123 Methods: A literature search was conducted to identify prospective cohort studies published from January 1997 to February 2006. Results: There were significant reductions in risk in 12 of 17 studies of cardiovascular outcomes (risk reductions ranging from 28% to 58%), in seven of eight studies of diabetes (14% to 46%), in seven of ten studies of breast cancer (11% to 67%), in two of two studies of endometrial cancer (68% to 90%), and in one of three studies of colorectal cancer (31% to 46%). There was mixed evidence for PA preventing gestational diabetes (three studies) and a range of other cancers (13 studies). Protective benefits for cardiovascular disease and diabetes were reported with as little as 60 minutes of moderate-intensity physical activity per week (240 Metabolic Equivalent (MET) minutes or 4 MET hours), with walking and moderate-intensity physical activity providing risk reductions comparable to those for the equivalent energy expenditure from more vigorous-intensity physical activity. Conclusions: There is strong evidence of a role for PA in the primary prevention of cardiovascular disease, diabetes, and some cancers in women. There was no evidence of additional health benefits from vigorous-intensity PA, over and above those achieved from walking or moderate-intensity PA. This may be because, in most studies, there was limited reporting of vigorous PA by women. For some health outcomes, the amount of PA required for health benefits in middle-aged and older women might be lower than current national recommendations. Collins C, Young A & Hodge A. Diet quality is associated with higher nutrition intake and self-rated health in mid-aged women. Journal of the American College of Nutrition. 2008; 27(1)146-157. Objective: To develop a diet quality score reflecting adherence to national dietary recommendations for the Australian Longitudinal Study on Women’s Health (ALSWH) and to compare this against energy standardized nutrient intakes and indices of health. Design: Cross sectional survey in a nationally representative sample of mid-aged women participating in a cohort study. Subjects: Data from 9895 women aged 50-55 who participated in the 2001 survey and had four or less missing values on their food frequency questionnaires were used to calculate the Australian Recommended Food Score (ARFS) based on adherence to Australian Dietary Guidelines. Measure of outcome: Correlates of ARFS were investigated including, mean nutrient intakes and indices of self-rated health and health service use. Associations were examined using ANOVA for continuous variables and Chi-squared tests for categorical variables. Area of residence and educational attainment were used as covariates in all modeling, to adjust for sampling frame and socioeconomic status. Results: The maximum ARFS was 74, with a mean of 33.0 ± 9.0 and 21% achieving a score > 40. Higher ARFS was associated with indicators of higher socioeconomic status, better self-rated health and lower health service use, p<0.0001, higher intakes of micronutrients and lower percentage of energy as total or saturated fat, p<0.0001. Conclusion: The Australian Recommended Food Score can be used to rank mid-aged women in terms of diet quality and nutrient intake and is associated with indices of self-rated health and health service use. The ARFS can be used to measure future associations with health outcomes and mortality. Furuya H, Young AF, Powers JR & Byles JE. Alcohol consumption and physical health-related quality of life in older women using the transformation of SF-36 to account for death. Japanese Journal of Alcohol & Drug Dependence. 2008; 43(2) 97-109. Moderate alcohol consumption has been associated with health benefits in several studies, but few studies investigating such association for elders have been done. So, we explored the relationship between alcohol intake and changes in physical health-related quality of life (HRQoL). As analyses of longitudinal HRQoL data excluding diseased participants produced overestimated results, we 124 compared the methods with and without incorporating death and estimated valid physical HRQoL and its decline over time. Study subjects were women from the Australian Longitudinal Study on Women's Health, ages 70-75 years at Survey 1 in 1996 (n =12 432), and were followed-up at 3 yearly intervals for 6 years. The level of alcohol consumption was divided into seven categories to identify possible harmful alcohol level for older women. We measured Physical Component Score (PCS) of Medical Outcomes Study Short-Form (SF-36), and applied the transformed PCS incorporating death as a valid score to estimate HRQoL changes for each alcohol group with adjustment for potential confounders. Significant declines of values were observed and the values of 'non-drinker' and 'rare drinker' were lower than the other groups during 6 years in both PCS and the transformed PCS. Analysis of the PCS showed significant Alcohol × Time interaction effects for non-drinker and rare drinker groups, as the scores were overestimated towards higher values at Survey 2 due to loss to follow-up of women who died. In the transformed PCS, these interaction effects diminished, and a clearer dose-response relationship between alcohol and physical HRQoL was observed at the third survey. We examined the influence of deaths on the study conclusions with using PCS and its transformed value which included deaths. Being a nondrinker of alcohol was associated with greater risk of mortality and poorer physical HRQoL. Moderate alcohol consumption was not harmful, and may carry some health benefits for older women. Koloski N, Smith N, Pachana N & Dobson A. Performance of the Goldberg Anxiety and Depression Scale in older women. Age & Ageing. 2008; 37(4) 464-467. Background: Measures to assess anxiety and depression separately often incur difficulties due to overlap of these constructs, especially in older individuals. Using the Goldberg Anxiety and Depression Scale (GADS) we aimed to confirm the factor structure of the instrument in a large cohort of older Australian women, to validate the instrument against other self-report information, and to assess its association with a variety of health-related outcomes. Method: Participants were 7264 women (aged 75-82 years) enrolled in the Australian Longitudinal Study on Women’s Health. Measures of anxiety and depression included the GADS, the mental health items of the Medical Outcomes Study SF-36, and self reported information on mental health diagnoses, symptoms and medications. The factor structure of the scale was examined using latent trait analysis, while receiver operating characteristic curves were used to explore the performance of the scale against other criteria. Results: Latent trait analyses replicated prior findings demonstrating high correlations between anxiety and depression as measured by the GADS and suggesting a third factor related to sleeping problems. Receiver operating characteristic curves showed that a simple score formed by summing responses to GADS items had high sensitivity and specificity in relation to other measures of anxiety and depression. Conclusion: This large study provides support for the hypothesis that anxiety and depression are not readily distinguishable entities in older women and that the GADS is a useful tool for measuring the composite construct for epidemiological studies. Lowe J, Young A, Dolja-Gore X, & Byles J. Costs of medications for older women. Australian & New Zealand Journal of Public Health. 2008;32(1) 89. With chronic diseases such as diabetes on the increase the uptake of medications are required for patients to maintain a quality of life, these costs are unfairly incurred by older women. The mean co- payment medication costs to older women increased by $25.60 for women without diabetes and $29.75 for women with diabetes, giving an 18% increase between 2004 and 2005 compared to aged pensions which had a 3% CPI increase. 125 Pachana N, Smith N, Watson M, McLaughlin D & Dobson A. Responsiveness of the Duke Social Support Sub-scales in older women. Age & Ageing. 2008; Oct 1. [Epub ahead of print] Objective: An abbreviated form of the Duke Social Support Index (DSSI) as used in a large longitudinal study of older Australian women was examined with respect to factors that might be expected to affect social support for older women over time. Methods: In this large cohort study two sub-scales of the DSSI, one describing the size and structure of the social network (four items) and the other perceiving satisfaction with social support (six items), were analysed in relation to outcome and exploratory variables. Results: Over a 3-year period, the network score increased among women whose life circumstances meant that they were likely to receive more support (e.g. recent widowhood). Likewise, those women at risk of becoming more socially isolated (e.g. those with sensory loss) became less satisfied with their social support. Changes in both measures were tempered by women’s mental health and optimism. Conclusions: Although the sub-scales of the DSSI may not fully reflect the complexity of social support paradigms, they are responsive to changes in the lives of older women and can be useful in community-based epidemiological studies. Scofield M & Khan A. Australian women seeking counselling have higher use of health services. Women's Health Issues. 2008;18(5) 399-405. Purpose: Despite a high prevalence of psychological distress and poor mental health in the Australian community, use of counselling services is very low. There has been only limited research examining the profile of those who do access counselling services, mainly in terms of demographic and health behaviour variables. To extend our understanding of those who currently access counselling services, this study aimed to examine the broader pattern of health service utilisation by women who consulted counsellors, psychologists or social workers in the past year compared with those who did not, among a population-based sample of middle-aged Australian women, and to determine whether health service utilization was independently associated with use of counselling services controlling for other known predictors. Methods: The cross sectional population-based mail survey data came from the third survey of the mid-aged cohort of the Australian Longitudinal Study on Women’s Health, conducted in 2001. The sample comprised 11 201 women aged 50–55. The main study variable was a question asking whether they had consulted a Counsellor/Psychologist/Social Worker in the past year. Findings: Only 6.9% of women had consulted a Counsellor/Psychologist/Social Worker in the past year. After controlling for self-reported mental health status, health behaviours and demographic variables in multivariate analysis, consulting a Counsellor/Psychologist/Social Worker in the past year was significantly and positively associated with consultations with general practitioners (5 or more consultations, (OR=4.14; 95%CI: 2.35-7.27, P<0.0001), specialist (3 or more consultations, OR= 2.09; 95%CI: 1.66-2.63, P<0.0001), and hospital doctor (OR=1.35; 95%CI: 1.10-1.66, P=0.004). Use of counselling services was not associated with use of other allied and complementary health services in multivariate analyses. Conclusions: Further research is needed to determine whether the strong independent link between self-reported use of counselling and other medical and health services among middle-aged women is best explained by general practice referral patterns, availability of services, economic factors, or different help-seeking patterns among women. 126 Smith M, Russell A, & Hodges P. How common is back pain in women with gastrointestinal problems? Clinical Journal of Pain. 2008; 24 199-203. Objective: This study examined the relationship between back pain and gastrointestinal (GI) symptoms in a large scale population study with consideration of possible confounding factors. Methods: Cross sectional analysis of survey data from the Australian Longitudinal Study on Women's Health was conducted using multinomial logistic regression to model 4 frequencies of back pain in relation to number of GI symptoms (including constipation, haemorrhoids, and other bowel problems). A total of 38,050 women from 3 age cohorts were included in analysis. Results: After adjustment for confounding factors, the number of GI symptoms was significantly associated with back pain among all age cohorts. Odds ratios for experiencing back pain "rarely," "sometimes," and "often" increased with the number of GI symptoms. Young, mid-age, and older women who experience 2 or 3 GI symptoms had adjusted odds ratios of 3.3 (2.5 to 4.4), 3.0 (2.5 to 3.7) and 2.8 (2.3 to 3.4), respectively, for "often" having back pain. Discussion: This study has identified a strong association between back pain and GI symptoms in women. Possible factors that may account for this relationship include referred pain through viscerosomatic convergence, altered pain perception, increased spinal loading when straining during defecation, or reduced support of the abdominal contents and spine secondary to changes in function of the abdominal muscles. 3DSHUVDFFHSWHG Adams J, Sibbritt D & Young A. A longitudinal analysis of 6044 older Australian women's consultations with complementary and alternative medicine (CAM) practitioners, 1996-2005. Age & Ageing Objectives: To determine the factors associated with complementary and alternative medicine (CAM) use among older Australian women over time. Design: A longitudinal analysis of postal questionnaires completed in 1996, 1999, 2002, and 2005 as part of the Australian Longitudinal Study on Women’s Health. Subjects: 12 432 women aged 70-75 years (in 1996), randomly selected from the Medicare database, with over-sampling of women from rural and remote areas of Australia. Main outcome measures: Consultation with an alternative health practitioner in the twelve months prior to each survey. Results: The percentage of women who consulted a CAM practitioner in the years 1996, 1999, 2002 and 2005 were 14.6%, 12.1%, 10.9% and 9.9% respectively. Use of CAM increased as the number of reported symptoms increased, as physical health decreased, and for non-urban residents compared to urban residents. Conclusions: Use of CAM amongst older women appears to be strongly influenced by poor physical health. There is also a suggestion that lack of access to conventional health care providers increases CAM use. There is also an overall decline in the use of CAM among older women as they age. Ball K, Burton N W & Brown W J. A prospective study of overweight, physical activity and depressive symptoms in young women. Obesity Objective: To examine prospective associations of body mass index (BMI), physical activity (PA), changes in BMI, and changes in PA, with incident depressive symptoms. 127 Research Methods and Procedures: This three-year prospective study used self-reported data on height, weight, PA, selected sociodemographic and health variables and depressive symptoms (CESD-10) provided by 6677 young adult women (22-27 years in 2000) participating in the Australian Longitudinal Study on Women’s Health (ALSWH). Results: Odds of developing depressive symptoms were higher in overweight (OR=1.22, 95% CI 1.03-1.45) and obese (OR=1.34, 95% CI 1.07-1.67) women than in healthy weight women, and lower in active than in sedentary women. Changes in BMI were significantly associated with increased risk of depressive symptoms, and sedentary women who increased their activity had lower risk of symptoms than those who remained sedentary. Increases in activity were protective against depressive symptoms regardless of BMI changes, except for those women who increased BMI by more than 10%, amongst whom risk for depressive symptoms was comparable with those who remained sedentary. Conclusions: Overweight and obese young women are at risk of developing depressive symptoms. PA appears to be protective against the development of depressive symptoms associated with minor weight gain. Brown WJ, Burton NW, Marshall AL and Miller YD. Reliability and validity of a modified self administered version of the Active Australia Physical Activity survey in a sample of mid-aged women. Australian & New Zealand Journal of Public Health Objective: To assess the test-retest reliability and validity of a modified self administered version of the Active Australia physical activity survey. Methods: One hundred and fifty-nine women from the 1946-1951 cohort (aged 54-59 years) completed a mailed physical activity questionnaire before recording daily pedometer step counts for seven consecutive days. A random subsample (n=44) also wore an accelerometer during this period. Participants then completed the physical activity questionnaire again. Spearman’s ȡ and per cent agreement were used to assess test-retest reliability. Self reported physical activity data (time 2) were compared with pedometer and accelerometer data using box plots and Spearman’s correlations to assess validity. Results: Median time between surveys was 13 days. Median frequency and duration of moderate and vigorous physical activity were the same at both surveys, but median walking frequency was slightly higher at time 2 than time 1. Reliability coefficients for frequency/time in each domain of physical activity ranged from 0.56-0.64 and per cent agreement scores ranged from 40% to 65% for the physical activity categories, and 76% for ‘meeting guidelines’. Correlations (ȡ) between self-reported physical activity and 1) weekly pedometer steps and 2) accelerometer data for duration of at least moderate intensity physical activity were 0.43 and 0.52 respectively. Conclusions: The measurement properties of this modified self-administered physical activity survey are similar to those reported for the original computer assisted telephone interview survey. Implications: This modified version of the Active Australia survey is suitable for use in self-administered format. Heesch K & Brown W. Do walking and leisure-time physical activity protect against arthritis in older women? Journal of Epidemiology & Community Health Objective: To examine dose-response relationships between both leisure-time physical activity (LTPA) and walking and 6-year incidence of self-reported arthritis in older women. Design, setting and participants: Older participants in the Australian Longitudinal Study on Women's Health (aged 73-78 years in 1999) completed mailed surveys in 1999, 2002 and 2005. LTPA and walking were measured in 1999. Women were classified as cases if they reported in 2002 or 2005 diagnosis of, or treatment for, arthritis over the previous 3 years. Logistic regression modeling was used to examine associations between first (1) all LTPA and then (2) only walking and self-reported arthritis. Main results: Data from 3563 women who did not report arthritis in 1999 were included in these analyses. Over the 6-year follow up, 41.1% of respondents reported arthritis. There was a clear 128 inverse relationship between both LTPA and walking with odds of self-reported arthritis. Women who reported low (75-<150 minutes of moderate-intensity LTPA per week), moderate (150-<300 minutes), and high ( 300 minutes) LTPA levels had 20%, 31%, and 34% lower odds of reporting arthritis, respectively, than those who were sedentary (p<0.01). There was a 40% reduced odds of arthritis in women who reported at least 200 minutes of walking per week and no other LTPA. Tests for linear trend revealed a dose-response relationship between each activity variable and the outcome (p<0.001). Conclusions: The results support an inverse dose-response relationship between both LTPA and walking and 6-year incidence of self-reported arthritis in older women. Herbert D, Lucke J & Dobson A. Pregnancy losses in young Australian women: Findings from the Australian Longitudinal Study on Women's Health. Women's Health Issues Little research has examined total pregnancy losses in the general population. Ten years of data from an Australian cohort study provide an opportunity to quantify pregnancy losses otherwise unobtainable at a national level. Participants in the Australian Longitudinal Study on Women’s Health (ALSWH) aged 28-33 years (n=9145) completed up to four mailed surveys. The women were categorised into mutually exclusive pregnancy outcome groups: birth, both birth and loss, loss, or no pregnancy. Associations between pregnancy outcomes and health-related factors were analysed by logistic regression. Fifty-nine percent (59.1%) of women experienced pregnancy in the previous ten years: birth (28.4%); both birth and loss (20.4%); or loss (10.3%). Women in professional occupations (OR=5.51, 95%CI: 3.88-7.83) and trade/service occupations (OR=3.84, 95%CI: 2.74-5.38) were much more likely to have experienced pregnancy losses than women in manual occupations. Pregnancy losses were strongly associated with recent diagnosis of a STI (OR 2.69, 95% CI 1.49-4.85), daily smoking (OR=2.15, 95%CI: 1.53-3.03), risky levels of alcohol consumption (OR=2.66, 95%CI: 1.37- 5.16), and recent marijuana use (OR=4.85, 95%CI: 3.34-7.04). For every woman in Australia aged 28-33 years who has given birth, there is a woman who has experienced a pregnancy loss. Based on self-report data, highly skilled occupations and negative lifestyle factors were strongly associated with pregnancy loss. Knowledge of modifiable lifestyle choices will improve pregnancy outcomes. These findings provide a comprehensive review of reproductive histories of women prior to potential experiences of infertility beyond 35 years of age. McDermott L, Dobson A & Owen N. Determinants of continuity and change over 10 years in young women’s smoking. Addiction Introduction: Few prospective studies have examined factors associated with smoking behaviour among young adult women. We used data from a population-based, prospective study of women initially aged 18-23 years, to examine continuity and change in smoking behaviour and associated attributes over 10 years. Methods: Participants in the Australian Longitudinal Study on Women’s Health completed postal questionnaires in 1996, 2000, 2003 and 2006. The analysis sample was 6840 women who participated in all surveys and provided complete smoking data. Multiple logistic regression models were used to examine attributes that differentiated continuing smokers from quitters; relapsers from ex-smokers; and, adopters from never smokers. Explanatory variables included smoking history, demographic, psychosocial, lifestyle-risk behaviour and life-stage transition factors. Results: Over the 10 years, 23% of participants either quit, re-started, adopted, or experimented with smoking. Recent illicit drug use and risky or high-risk drinking predicted continued smoking, relapse and smoking adoption. Marriage or being in a committed relationship was significantly associated with quitting, remaining an ex-smoker and not adopting smoking. Living in a rural or remote area and lower educational attainment were associated with continued smoking; moderate and high physical activity levels were positively associated with remaining an ex-smoker. Conclusions: Lifestyle and life-stage factors are significant determinants of young women’s smoking behaviour. Future research needs to examine the inter-relationships between tobacco, alcohol and illicit drug use, and to identify the determinants of continued smoking among women living in rural and remote areas. Cessation strategies could examine the role of physical activity in relapse prevention. 129 Polimeni A, Austin S & Kavanagh A. Sexual orientation and weight, body image and weight control practices among young Australian women. Journal of Women's Health Objective: We compare weight, body image and weight control practices of young adult Australian women according to sexual orientation. Methods: Cross sectional analyses of the second survey of 9683 young adult women in the Australian Longitudinal Study on Women’s Health (ALSWH); the weight, weight control practices, and body image of exclusively heterosexual, mainly heterosexual, bisexual and lesbian women were compared. Results: Lesbians were less likely to be dissatisfied with their body shape (OR=0.54; 95%CI 0.32- 0.92) than exclusively heterosexual women. Compared with exclusively heterosexual women, bisexual women were more likely to weight cycle (OR=2.22; 95%CI: 1.22-4.03) and mainly heterosexual and bisexual women were more likely to engage in unhealthy weight control practices such as smoking (mainly heterosexuals: OR=1.83; 95%CI: 1.38-2.44 and bisexuals: OR=3.80; 95%CI: 1.94-7.44), and cutting meals (mainly heterosexuals: OR=1.58; 95%CI: 1.23-2.02 and bisexual women: OR=3.45; 95%CI: 1.82-6.54); mainly heterosexual women were more likely to vomit (mainly heterosexuals: OR=2.41; 95%CI: 1.73-3.36) and use laxatives (mainly heterosexuals: OR=1.56; 95%CI: 1.12-2.19). Conclusions: Future research should explore why bisexual and mainly heterosexual women are at higher risk of disordered eating behaviours. Understanding why lesbians have a healthier body image would also provide insights into how to improve the body image of other groups. It is critical that public health policy and practice addresses less healthy weight control practices of sexual minority groups. Weisberg E, Bateson D, Read C, Estoesta J & Lee C. Fertility control? Middle-aged Australian women’s retrospective reports of their pregnancies. Australian & New Zealand Journal of Public Health Objective: To assess mid-age Australian women’s retrospective reports of the intendedness and wantedness, and degree of happiness, associated with their pregnancy histories. Methods: A self-report survey was sent to 1000 participants in the Mid-Age cohort of the Australian Longitudinal Study on Women’s Health. Results: Responses from 811 women (81%) showed that, although 32% of first pregnancies were unplanned and 29% were unwanted, most women recall being happy with their pregnancies and termination rates were very low. The second pregnancy was associated with the highest levels of happiness, planning and wantedness. Conclusions: While the majority of mid-age women report having been happy to be pregnant, and the majority of pregnancies are described retrospectively as planned and wanted, a significant proportion of pregnancies are unwanted, unplanned, or resulting from unintended contraceptive failure. Implications: The data support the continuing need for widely available, affordable and sensitive fertility control services. 130 &RQIHUHQFH SUHVHQWDWLRQV Population Health Congress, 6-9 July 2008, Brisbane, Queensland. 'REVRQ$ Combined host organisations oration: Harnessing Australia’s health information 7DIW$ :DWVRQ/. Depression, pregnancy termination and births among young Australian women: The confounding effect of partner violence /XFNH-:DWVRQ0/R[WRQ' +HUEHUW'The sexual health of Australian women in their twenties and thirties +REEV07DIW $ $P LU/ The emergency contraceptive pill (ECP) rescheduled: Exploring women’s knowledge, attitudes and experiences :DWVRQ0/XFNH - +HUE HUW ' Changing patterns of contraceptive use in young Australian women: 1996 - 2006 3RZHUV- /R[WRQ'How do pregnant women respond to alcohol guidelines? 'ROMD*RUH; /R[WRQ'Prescribed medication use before, during and after pregnancy 3DUNLQVRQ/ % \OHV- *LEVRQ5 5RELQVRQ, Women and arthritis: Burden of illness and management of arthritis in older Australian women +HUEHUW'/XFNH- 'R EVRQ$Pregnancy losses in young Australian women: Findings from the Australian Longitudinal Study on Women’s Health %\OHV-*LEVRQ 5 %HUHFNL-+RFNH\5 'REVRQ$Adherence to bisphosphonates by elderly women 7RRWK/'REVRQ$ +RFNH\5Relative survival as an indicator of generalizability for longitudinal studies of older people 0DFNHUUDV'3RZHUV-%RRUPDQ-/R[WRQ' *LOHV* Estimating the impact on pregnant and post-partum women of fortifying bread with iodine %\OHV-'ROMD*RUH; 3RZHUV-Contribution to breakfast session; Perinatal and paediatric epidemiology 131 Other Conference presentations %URZQ: &KDQJ3 How much physical activity to prevent weight gain? Sports Medicine Australia 37th Annual State Conference, Surfers Paradise, Queensland, 24 May 2008. %URZQ:+RFNH\5 'REVRQ$. Health care and pharmaceutical costs associated with physical inactivity: Interactions with obesity. Second International Congress on Physical Activity and Public Health, Amsterdam, Netherlands, 13-16 April 2008. %\OHV- Ageing population and gender issues. 4th Annual Australia’s, Ageing Population Summit, Melbourne, Victoria, 23 - 24 July 2008. %\OHV- Promoting healthy ageing. National Public, Health Reform Summit, Sydney, NSW, 7 August 2008. %\OHV- Women's increasing weight: A threat to healthy ageing. Australian Association of Gerontology 41st National Conference Ageing Landscapes, Fremantle, Western Australia, 19 November 2008. %\OHV-. Special session: Longitudinal studies of ageing: A key to optimal ageing. 4th World Ageing & Generations Congress, St Gallen, Switzerland, 28 - 30 August 2008. %\OHV-. Obesity: The new global threat to healthy ageing and longevity. Ageing and Globalization: Identifying Gaps, Challenging Perspectives, Sydney, NSW, 25 September 2008. &KRMHQWD&/XFNH- /R[WRQ' Does social support reduce the likelihood of postnatal depression in Australian mothers? Poster presentation at the Marce Society International Conference, Sydney, NSW, 10-13 September 2008. &ROOLQV&'ROMD*RUH; +HUEHUW'/XFNH- 'REVRQ$. Seeking advice and using treatment for fertility problems in Australian Women aged 28-33 years. Research Higher Degrees Conference, Brisbane, Queensland, 7 November 2008. 132 +HUEHUW'/XFNH- 'REVRQ$ Seeking advice and using treatment for fertility problems in Australian women aged 28-33 years. Fertility Society of Australia Annual Conference: Working Together For Reproductive Health, Brisbane, Queensland, 20-22 October 2008. +HUEHUW'/XFNH- 'REVRQ$ Prior pregnancy outcomes and seeking treatment for fertility problems in Australian women aged 28-33 years. Public Health Association Australia (Qld) State Conference, Emerging Issues in Public Health, Brisbane, Queensland, 4-5 September 2008. +RGJHV3. Incontinence, breathing disorders and back pain: An inseparable triad? International Continence Society, Cairo, Egypt 20-24 October, 2008. -RKQVWRQH0 /HH& Young Australian women's aspirations for family and work in the 21st century. 10th Australian Institute of Family Studies Conference - Families Through Life, Melbourne, Victoria, 9- 11 July 2008. /XFNH-:DWVRQ0+HUEHUW' /R[WRQ'. Factors associated with STI among young women: Findings from the Australian Longitudinal Study on Women’s Health. Oral poster presentation at the Australasian Sexual Health Conference 2008, Perth, Western Australia, 16 September 2008. 0DFNHQ]LH/ 0HKUDEDQ$. Development of a self-report version of the Home Falls and Accidents Screening Tool (HOME FAST). OT Australia 23rd National Conference & Exhibition 2008, Melbourne, Victoria, 11-13 September 2008. 0DFNHQ]LH/ 0HKUDEDQ$ Do occupational therapists and older people assess home environments for falls hazards differently? OT Australia 23rd National Conference & Exhibition 2008, Melbourne, Victoria, 11 - 13 September 2008. 0F'HUPRWW/'REVRQ$ 2ZHQ1 Predictors of continued smoking and smoking relapse among young adult women over 10 years. 10th International Congress of Behavioural Medicine, Tokyo, Japan, 27-30 September 2008. 0F/DXJKOLQ'. Social networks in older Australian men and women. Australian Association of Gerontology 41st National Conference Ageing Landscapes, Fremantle, Western Australia, 18 November 2008. 5RZODQGV, /HH& Looking on the bright side of life: The role of optimism in women's adjustment to miscarriage. Society of Reproductive and Infant Psychology Conference, London, United Kingdom, September 2008. 133 7RRWK/5XVVHOO$/XFNH-%\UQH*/HH&:LOVRQ$ 'REVRQ$ Few urban-rural differences in older carers’ access to community services. Australian Association of Gerontology 41st National Conference Ageing Landscapes, Fremantle, Western Australia, 20 November 2008. 7XGRU/RFNH&%XUWRQ1%URZQ: Steps/day, BMI in 54-59 year old women by self-reported occupational sitting and leisure physical activity. American College of Sports Medicine 2008 Annual Meeting, Indianapolis, Indiana USA, May 28-31 2008. YDQ8IIHOHQ-:DWVRQ0'REVRQ$ %URZQ: Is self-reported weekday and weekend day sitting-time associated with weight in mid-aged women? Tenth International Congress of Behavioural Medicine, Tokyo, Japan, 27 - 30 August 2008. 134 0HGLD 3UHVV 'DWH 0HGLD 7LWOH $/6:+ &ROODERUDWRU 23/05/08 The University of Media Release Dr Anne Young / Newcastle A/Prof Jon Adams 23/05/08 The University of Media Release Dr Anne Young / Queensland A/Prof Jon Adams 23/05/08 AAP Newswire Women Fuel Vitamin A/Prof Jon Adams National/Australia Supplement Industry 24/05/08 www.medicalnewstoday. WHA CAM Sub-study A/Prof Jon Adams com 24/05/08 Northern Daily Leader Women Fuel Vitamin A/Prof Jon Adams Tamworth Supplement Industry 24/05/08 Western Advocate Middle Aged Women are A/Prof Jon Adams Bathurst NSW increasingly … 24/05/08 Townsville Bulletin Women Hope for Vitamin Boost A/Prof Jon Adams 26/05/08 consultmagazine.net WHA CAM Sub-study Dr Anne Young 26/05/08 Newcastle Herald Women Turning to Vitamins A/Prof Jon Adams 01/06/08 The Jean Hailes Women & Alcohol: To drink or Jenny Powers foundation winter 2008 not to drink magazine – national 14/06/08 The Newcastle Herald Saturday H2 Feature - Dr Anne Young / Considering Alternatives A/Prof Jon Adams 17/06/08 Caboolture Shire Herald Study probes health choices Dr Anne Young / Brisbane WHA CAM Sub-study A/Prof Jon Adams 18/06/08 West Australian Alcohol Report (re Jean Hailes Jenny Powers foundation magazine. Article on alcohol consumption) 18/06/08 North West News / Alternative Research WHA CAM Dr Anne Young / Brisbane Substudy A/Prof Jon Adams 18/06/08 South West News / Alternate Research WHA CAM Dr Anne Young / Brisbane Substudy A/Prof Jon Adams 18/06/08 Pine Rivers Press Study into alternatives WHA Dr Anne Young / Strathpine CAM Substudy A/Prof Jon Adams 18/06/08 Redcliffe & Bayside Examining treatments WHA Dr Anne Young / Herald CAM Substudy A/Prof Jon Adams 18/06/08 Wynnum Herald Brisbane Alternate Means WHA CAM Dr Anne Young / Substudy A/Prof Jon Adams 7/07/08 The West Australian Withdrawal method routine for Dr Jayne Lucke 10 percent of women 7/07/08 The Sydney Morning Women using unreliable Dr Jayne Lucke Herald withdrawal method 7/07/08 The Australian Women using 'unreliable' Dr Jayne Lucke contraception 7/07/08 The Age Women using unreliable Dr Jayne Lucke withdrawal method 135 'DWH 0HGLD 7LWOH $/6:+ &ROODERUDWRU 7/07/08 Top News A third of Oz women have slept Dr Jayne Lucke with six or more men by 25! 7/07/08 News Beta One India A third of Oz women have slept Dr Jayne Lucke with six or more men by 25! 7/07/08 Chinese News Australian 30-year old women's Dr Jayne Lucke sexual health is worrying 8/07/08 Daily Liberal Survey pulls out latest results on Dr Jayne Lucke sexual health 8/07/08 Launceston Examiner Withdrawal method routine for Dr Jayne Lucke 10pc of women: survey 8/07/08 Sunraysia Daily Withdrawal method routine for Dr Jayne Lucke some 8/07/08 Western Advocate Unreliable birth control still used Dr Jayne Lucke 11/08/08 Newcastle Herald Health/Nutrition Diet A/Prof Clare Collins 9/10/08 In Touch Newsletter of the Public Health WHA / 11th Association of Australia National Immunisation Conference 14/11/08 The Melbourne Age Older women pounding the Prof Wendy Brown pavement more 7HOHYLVLRQDQGUDGLR 'DWH 0HGLD 7LWOH $/6:+&ROODERUDWRU 23/05/08 Radio 2SM / Sydney + WHA/CAM Dr Anne Young 12 syndicated stations Substudy 26/05/08 ABC Radio / Canberra WHA/CAM Substudy A/Prof Jon Adams 26/05/08 ABC Radio / South Australia WHA/CAM Substudy A/Prof Jon Adams 26/05/08 ABC Radio / Newcastle WHA/CAM Substudy Dr Anne Young 28/05/08 ABC Radio / Bundaberg WHA/CAM Substudy A/Prof Jon Adams 16/06/08 ABC Radio / Canberra Alcohol Report Jenny Powers 16/06/08 2GO FM / Gosford + Alcohol Report Jenny Powers syndicated to 49 regional radio stations 5/08/08 NBN TV Newcastle/Coffs HMRI Research Prof Julie Byles Harbour/Gosford/Tamworth/Gold Tour/Women's Coast/Lismore Health Australia 3/09/08 2NUR Newcastle The ALSWH, Dr Deborah Loxton overview, trends, focus on intimate partner violence 13/11/08 ABC Radio / Brisbane Hysterectomies Dr Janneke Berecki don’t add weight 136 $5&+,9,1* A requirement of the contract with the Department of Health and Ageing is that the ASLWH data are archived with the Australian Social Sciences Data Archive (ASSDA) at the Australian National University on an annual basis. Each year we archive the most recently completed data set and any new data sets that have been created, and may re-archive earlier data sets if there have been changes to these. To date, data have been archived for Surveys 1, 2, 3 and 4 of the 1973-1978 cohort, the 1946-1951 cohort, and the 1921-1926 cohort. The data set for Survey 5 of the 1946-1951 cohort will be archived in 2009. The files most recently deposited with ASSDA consisted of: x Completed ASSDA forms x 1973-1978 cohort Survey 4 Questionnaire x 1973-1978 cohort Survey 4 level ‘A’ and ‘B’ data sets in both SAS and text format x 1973-1978 cohort Survey 4 formats and labels in text format x The latest version of the Data Dictionary x The most recent heights and weights data set for all phases of the 1973-1978 cohort, in both SAS and text format, and its format file. As well as being a valuable and reliable off-site backup of all ALSWH data, archiving will make the data available for future use by other researchers, subject to certain conditions. 137 352-(&767$)) 5HVHDUFK&HQWUHIRU*HQGHU+HDOWKDQG$JHLQJ 8QLYHUVLW\RI1HZFDVWOH &R'LUHFWRU$/6:+5&*+$'LUHFWRU Professor Julie Byles 3URMHFW0DQDJHU Dr Deborah Loxton 6WDWLVWLFLDQV Ms Jenny Powers Ms Xenia Dolja-Gore 'DWD0DQDJHU&RKRUWV Mrs Anna Graves 'DWDDVVLVWDQW Mr Ashutosh Kabra &RPPXQLFDWLRQ 5HVHDUFK2IILFHU Mrs Catherine Chojenta 5HVHDUFK$VVLVWDQWV Ms Jenny Helman Ms Stacey Hosking ([HFXWLYH$VVLVWDQW Mrs Lyn Adamson $GPLQLVWUDWLYH2IILFHU Ms Melanie Moonen &DVXDO3URMHFW$VVLVWDQWV Ms Hannah Bourke Ms Penne Cappas Ms Laura Croger Ms Nicola Evans Ms Elizabeth Kent Ms Monica O’Neil Ms Jane Rich Ms Claire Rooney Ms Amy Sales Ms Megan Wilson At the University of Newcastle, Mr Daniel Odd resigned his position as part-time Data Assistant and Mr Ashutosh Kabra started in this position. 6FKRRORI3RSXODWLRQ+HDOWK 8QLYHUVLW\RI4XHHQVODQG 3URMHFW'LUHFWRU Professor Annette Dobson 6HQLRU5HVHDUFK)HOORZV3URMHFW&RRUGLQDWRUV Dr Jayne Lucke Dr Leigh Tooth 5HVHDUFK)HOORZ Dr Janneke Berecki 'DWD0DQDJHU6XUYH\V Mr David Fitzgerald 5HVHDUFK3URMHFW0DQDJHU Ms Megan Ferguson $GPLQLVWUDWLRQ2IILFHU Ms Leonie Gemmell 5HVHDUFK$VVLVWDQWV6WDWLVWLFLDQV Dr Nelufa Begum Dr Samantha Bjone Mr Sam Brilleman Ms Danielle Herbert Mr Richard Hockey Ms Melissa Johnstone Ms Irene Moyer Ms Melanie Spallek Ms Melanie Watson 138 $33(1',&(6 $SSHQGL[ 4XDUWHUO\XSGDWHV Monthly Progress Notes for Research Team, Associates and Colleagues, June 2008 Here’s the latest news from Women’s Health Australia. 5HSRUWVDQG'HOLYHUDEOHV Extension of ALSWH contract with the Department of Health and Ageing We are very pleased to announce that we have received further funding from DoHA up to the end of December 2008. This will allow us to continue work while negotiations continue towards a new contract from January 2009. Ethics Committee clearance from Department of Health and Ageing We have received news that the DoHA Ethics Committee has approved our request for a three year extension to the original approved protocol for ALSWH to obtain Medicare (MBS and PBS) data for women who provided consent. Second Carers Contract The ALSWH team at the University of Queensland have been successful in attracting an additional $126,000 for a 12 month contract with DoHA. The project is due to start in September 2008 and the contract is currently being finalised. This work builds on previous work conducted by the ALSWH-UQ team during 2006-7 examining issues for employed carers in the 1946-1951 cohort. The new project will involve three phases: x Phase 1: Further in-depth analysis of the data from the pilot study of 1946-1951 cohort women (collected as part of our first Carers Contract with DoHA) x Phase 2: Further analysis of data collected as part of an NHMRC grant: “How well do health and community services help older people with neurodegenerative disorders and family caregivers”. x Phase 3: Further analysis of caregiving by the 1921-1926 cohort of ALSWH, providing cross sectional and longitudinal analysis of data from Survey 1 to 4. For further information contact Dr Leigh Tooth, [email protected]. 139 3URMHFW1HZV Surveys 2OGHU6XUYH\ 70% (approximately 5,000) surveys have been returned. One third of the missing page telephone calls are complete. Telephone reminders and English speaking phone interviews are in progress. Over 400 participants spoken to in the telephone reminder, who have misplaced their survey, will be mailed an extra survey in the first week in July. 2WKHU$FWLYLWLHV People, meetings and visitors Congratulations to Dr Deborah Loxton, ALSWH Project Manager at the University of Newcastle and family. Mathew David, Deb’s grandson, was born on Friday 13th June (at 3pm Minneapolis time), 5lbs 1 oz, 18 inches long. All are healthy and doing well. This month we say farewell to Bree Waters who has been Research Project Officer at UQ for the last two years and we wish her the very best with her future plans. One of Bree’s important roles has been putting together the 6-monthly Technical Reports which involves compiling all the updates for current projects. Please now direct all enquiries to Leonie Gemmell who is the principal point of contact for enquiries to ALSWH at UQ. Leonie’s hours of work are 8am to 3pm (QLD time) Tuesday to Friday and her contact details are: Ph: (07) 3346 4723; Email: [email protected] or [email protected]. That’s all for this month! Please keep us posted as to the latest WHA news and activities. Our best contact is [email protected]. Dr Jayne Lucke Senior Research Fellow ALSWH-UQ www.alswh.org.au 140 Progress Notes for Research Team, Associates and Colleagues, July - September 2008 Here’s the latest news from Women’s Health Australia. 5HSRUWVDQG'HOLYHUDEOHV Major Report D: Reproductive Health Work is progressing on Major Report D, which focuses on reproduction and reproductive health, examining both cross sectional and longitudinal data. The Working Group has been meeting monthly via teleconference, and progressing on the different sections, which comprise: x Family planning x Aspirations: Who wants to have children? x Fertility and infertility x Maternal health x Prenatal and maternal health behaviours x Motherhood and paid work A face-to-face meeting in Brisbane is planned for 13-14 October, and the draft report is due to be sent to the Department of Health and Ageing in March 2009. Technical Report #31 Emails requesting submissions for the December 2008 Technical Report have been sent. Please return all your information promptly to Megan Ferguson or Leonie Gemmell (the request email will specify who) by 10th October. The information you provide will also be used for the Annual Report for 2008, so please include as much information as possible, so we can provide a thorough overview of everyone’s hard work throughout the year. 3URMHFW1HZV Surveys 2OGHU6XU YH\ 5 474 surveys (76% of the number mailed) have been received. A number of reasons have been cited for non-respondents, including a growing number suggesting they are getting too old or sick to participate. 141 0LG6XUYH\ A small number of women are being contacted about missing pages. Publications and projects update: Updated Expression of Interest (EoI) documents are available at http://www.alswh.org.au/infodata.html. Please ensure that these documents are used for all new or amended EoIs. These projects were approved by the Publications, Substudies and Analyses Subcommittee during the period July - September 2008. 1HZSURMHFWV x A234 - The impact of out-of-pocket costs on the use and distribution of cervical screening services x A235 - A shift in thinking: comparing baby boomer narrative over time x A236 - Risk factors associated with endometriosis and pelvic pain x A237 - Long term health impacts of intimate partner violence on mid-aged Australian women x A238 - Insomnia in Australian women their late 20s: demographic factors and health-related behaviours x A239 - Longitudinal approach to menopausal transitions x A241 - Risk factors for emergency and non-emergency caesarean births among women in NSW $PHQGHG8SGDWHGSURMHFWV x A076A - The health and wellbeing of sole mothers x A090A - To what extent does having babies contribute to weight gain in young women? x A150A - Adequacy and equity of treatment for depression among older Australian women 3DSHUVSXEOLVKHG %URZQ:%XUWRQ1 5 RZDQ3 Updating the evidence on physical activity and health in women. American Journal of Preventive Medicine, 2007, 33(5),404-411. &ROOLQV& .RORVNL 16P LWK13DFKDQ D1 'R EVRQ $. Performance of the Goldberg Anxiety and Depression Scale in older women. Age and Ageing. 2008, 37 (4), 464-467. 3DSHUVDFFHSWHGIRUSXEOLFDWLRQ $GDPV - 6LEEULWW' 142 %DOO. %XUWRQ1 : %URZQ :- . A prospective study of overweight, physical activity and depressive symptoms in young women. Obesity %URZQ :-%XUWRQ 1:0DUVKDOO $/ 0LOOHU <'. Reliability and validity of a modified self administered version of the Active Australia Physical survey in a sample of mid-aged women. Australian and New Zealand Journal of Public Health Issues. +HUEHUW'/XFNH- 'REVRQ$ Pregnancy losses in young Australian women: Findings from the Australian Longitudinal Study on Women’s Health. Women’s Health Issues 6FRILHOG0 .KDQ $ Australian women seeking counselling have higher use of health services. Women’s Health Issues. :HLVEHUJ(%DWHVRQ'5HDG&(VWRHVWD- /HH&. Fertility control? Middle-aged Australian women’s retrospective reports of their pregnancies. Australian and New Zealand Journal of Public Health We’re all keen to read about ALSWH research, so please remember to keep us updated with your recent publications! 2WKHU$FWLYLWLHV ALSWH was well represented at the recent Population Health Congress 2008 held in Brisbane from 6-9 July. Annette Dobson gave the Combined Host Organisation oration, ‘Harnessing Australia’s Health Information’, and staff presentations were: x Depression, Pregnancy Termination and Births among Young Australian Women: The Confounding Effect of Partner Violence. Taft A & Watson L. x The Sexual Health of Australian Women in their Twenties and Thirties. Lucke J, Watson M, Loxton D & Herbert D. x The Emergency Contraceptive Pill (ECP) Rescheduled: Exploring Women’s Knowledge, Attitudes and Experiences. Hobbs M, Taft A & Amir L. x Changing Patterns of Contraceptive Use in Young Australian Women: 1996 – 2006. Watson M, Lucke J & Herbert D. x How do Pregnant Women Respond to Alcohol Guidelines? Powers J & Loxton D. x Prescribed Medication use Before, During and After Pregnancy. Dolja-Gore X & Loxton D. x Women and Arthritis: Burden of Illness and Management of Arthritis in Older Australian Women. Parkinson L, Byles J, Gibson R & Robinson I. x Pregnancy Losses in Young Australian Women: Findings from the Australian Longitudinal Study on Women’s Health. Herbert D, Lucke J & Dobson A. x Treatment for Depression Among Older Australian Women. Byles J, Gibson R, Young A, Loxton D, Robinson I &Parkinson L, x Annual Health Assessments for Older Australian Women. Byles J, Dolja-Gore X & Young A. x Adherence to Bishoposphonates by Elderly Women. Berecki J, Hockey R & Dobson A. x Relative Survival as an Indicator of Generalizability for Longitudinal Studies of Older People. Tooth L, Dobson A & Hockey R, 143 x Estimating the Impact on Pregnant and Post-Partum Women of Fortifying Bread with Iodine. Mackerras D, Powers J, Boorman J, Loxton D & Giles G. x Contribution to Breakfast Session; Perinatal and Paediatric Epidemiology. Powers J 1HZVIURP(XURSH Julie Byles convened a symposium of the 4th World Congress on Ageing and Generations in St Gallen, Switzerland 27-30th August. The symposium was called: Longitudinal Studies: A key to Healthy Ageing, and included presentations on ALSWH data as well as work by Richard Suzman (National Institute of Ageing USA), Paul Kowal (World Health Organisation), and Nadia Mincuci (University of Padova). 1HZVIURPWKH86$ Recently Annette Dobson spent a few days in the USA and was able to meet with Dr Ellen Gold to talk about collaboration with SWAN (Study of Women Across the Nation). Melanie Watson and Jayne Lucke attended the Australasian Sexual Health Conference held in Perth from the 15th to 17th September and presented an oral examining the factors associated with women acquiring a sexually transmitted infection in their 20s and 30s. Cath Chojenta attended the Marce Society International Conference in Sydney on 10-13 September. The Marce Society is an organisation concerned with perinatal mental health issues. Cath presented a poster titled “Does social support reduce the likelihood of postnatal depression in Australian mothers?” People, meetings and visitors Congratulations to Janneke Berecki and her husband Geza on the arrival of their son Alexander Geza, born Wednesday, October 8 and weighing 3.8kg. Dad reports all are healthy and doing well! Megan Ferguson has joined UQ group as Research Project Manager. At the University of Newcastle, Mr Ashutosh Kabra has begun work as part-time Data Assistant. Web updates The ALSWH data access policy documents have recently been updated. You can find these in the ‘Information for Data Users’ section of the website (www.alswh.org.au/infodata.html). You will also find other useful tools, such as the ALSWH Data Dictionary and the Data Dictionary Supplement, which are regularly updated. That’s all this time! Please keep us posted as to the latest WHA news and activities. Our best contact is [email protected]. Megan Ferguson Research Project Manager ALSWH-UQ www.alswh.org.au 144 $SSHQGL[ 6XUYH\PDWHULDOV FRKRUW3LORWEURFKXUH (YDOXDWLRQIRUPVIRU FRKRUW3LORW FRKRUW3LORWUHPLQGHU FRKRUW3LORWWKDQN\RX FRKRUW6XUYH\ &KDQJHRI'HWDLOVLQVHUW 145 Contact Us Website: www.alswh.org.au Email: [email protected] Freecall: Linking to 1800 068 081 Mail: Women’s Health Australia the past Thanks again for the great Reply Paid 70 “ Hunter Region MC opportunity to participate in NSW 2310 this survey. It has the added to provide bonus of me working out where I’m going / how I’m doing as well! ” answers for If you have any complaints about this project and would prefer to discuss these with an independent Younger participant, Survey 3 SHUVRQ\RXVKRXOGIHHOIUHHWRFRQWDFWWKH8QLYHUVLW\RI1HZFDVWOH¶V+XPDQ5HVHDUFK(WKLFV2I¿FHU (02) 4921 6333 or write to them at the University of Newcastle, University Drive, Callaghan, NSW, 2308. 7KH$XVWUDOLDQ(OHFWRUDO&RPPLVVLRQ $(& KDVVXSSOLHGQDPHDGGUHVVJHQGHUDQGDJHUDQJH information for this medical research study in conformity with Item 2 of subsection 90B(4) of the &RPPRQZHDOWK(OHFWRUDO$FW DQGVXEUHJXODWLRQ D RIWKH(OHFWRUDODQG5HIHUHQGXP5HJXODWLRQV 7KHLQIRUPDWLRQKDVEHHQSURYLGHGE\WKH$(&RQDFRQ¿GHQWLDOEDVLVDQGZLOOQRWEHIRUZDUGHGRQ or sold or otherwise disclosed or used for any purpose other than to contact participants for this medical research project. st our participation over the past As the project heads further into the 21 century the team at Women’s Health Ythirteen years has contributed Australia is assessing new ways to conduct research. to the advancement of the understanding of the health trends and health care service use of all Past Change Future Australian women. The Women’s Health Australia project is the most Changing technology means it is now comprehensive longitudinal study In the future, the data may be linked In the past, data of consenting possible, with your permission, to on women’s health ever undertaken with data collected from sources such participants has been linked to data undertake linkage with many different as midwives registers, hospital and in Australia. The response rate from sourced from Medicare. This has been data collected from other sources. pathology records, cancer registries your age group at the last survey was most successful in providing policy This linkage will reduce the number of and screening records to name a few. amazing and we were particularly makers with evidence of the need for questions in future surveys and provide Opportunities for wider linkage will help changes to health services. a bigger picture of health trends and pleased to receive surveys from over plan future health policy in Australia. service usage of all Australian women. 500 women we had previously lost contact with. We would like to take this opportunity to thank you all for How does this process work? your commitment to this project. The enclosed survey, the fifth for your age group, reflects the many differing lifestyles amongst all women of your generation. It may 10110010001 seem longer than usual, however we CONSENT 00101110010 10010010110 are asking you to complete only the 01010001010 10101010100 sections that apply to you. 10111001010 01001011001 01000101010 Your participation is voluntary. If you would like to discontinue your involvement in the project, please Anyyyg identifying Your results are Onlyy ID numbers are Your complp eted information, such as entered and recorded Your ID number links used when other phone, email or write to us. surveyy is returned to the consent form, is usinggyy onlyy your ID this surveyyy to your data sets are linked. us for processing. removed. number. previous surveys. Analyyysts only ever see linked data with ID numbers, never Yours sincerely, names and addresses. Professor Annette Dobson With both survey information and health service records information, the picture of Project Director women’s health becomes clearer. $VRXWOLQHGLQWKHEURFKXUHDFFRPSDQ\LQJWKLVVXUYH\\RXDUHRQHRIRXUSLORWJURXS $VZHOODVFRPSOHWLQJWKHVXUYH\ZHZRXOGOLNHWRNQRZZKDW\RXWKLQNRILW :HPD\PDNHFKDQJHVEHIRUHVHQGLQJLWWRRWKHUVLQ\RXUDJHJURXSLQ 3OHDVHKHOSE\DQVZHULQJWKHTXHVWLRQVEHORZ :HUHWKHUHDQ\TXHVWLRQV\RXIRXQGGLIILFXOWWRXQGHUVWDQG" We recently sent you a survey but have not heard back from you. If you don’t have a survey please contact us: Freecall 1800 068 081 Email [email protected] Did you know that... of younger women say they are 58% happy with their share of domestic work of women in your age group use 72% WKHLQWHUQHWWR¿QGLQIRUPDWLRQ about health or health care of younger women rate their 60% health as either excellent or very good Freecall number 1800 068 081 Email [email protected] Website www.alswh.org.au Address Reply Paid 70, Hunter Region MC NSW 2310 Thank you We have received your completed survey. Congratulations on your ongoing commitment to the Women’s Health Australia project. With your help we have provided accurate information to the government about the health needs of women across Australia. Did you know that... of younger women take vitamins 83% or minerals of women in your age group rate their number of GPs to choose 32% from as either excellent or very good of younger women do unpaid 11% voluntary work Freecall number 1800 068 081 Email [email protected] Website www.alswh.org.au Address Reply Paid 70, Hunter Region MC NSW 2310 B LA C K Pantone 2597C Fifth survey for young women 2008 WHA Yng5-2008-V7 07-08-08 BLACK How to complete this survey Pantone 2597C This is the fifth ‘pilot’ survey for young women. As the purpose of the project is to look at changes over time, some of the questions are the same as those in previous surveys. Please answer every question you can. If you are unsure about how to answer a question, mark the response for the closest answer to how you feel. Please answer the survey for the time period indicated even if you are pregnant or your circumstances are unusual in some way (unless the question states otherwise). Please read the instructions above each question carefully. Some require you to answer only those options which are applicable to you. Other questions require you to mark one answer on each line. The questions may also refer to different time periods. INSTRUCTIONS: • Use a black or blue biro • Do not fold or bend this survey Cross the boxes like this: In general, would you say your health is: (Mark one only) Excellent Very good Good You would cross this box if you think your health is good Fair Poor Print clearly in the boxes like this: What is your postcode? 2308 (PRINT clearly in the boxes) Correct mistakes like this: When you go to a General Practitioner: Most of Some- Rarely or (Mark one on each line) Always the time times never Do you go to the same place? If you make a mistake simply scribble it out and clearly mark the correct answer with a cross. If you need help to answer any questions, please ring 1800 068 081 (This is a FREECALL number) * If you are concerned about any of your health experiences and would like some help, you may like to contact: • your nearest Women’s Health Centre or Community Health Centre • your General Practitioner for advice about who would be the best person in your community for you to talk to. * If you feel distressed now and would like someone to talk to, you could ring Lifeline on 13 11 14 (local call). 2 WHA Yng5-2008-V7 07-08-08 BLACK is about using health services Pantone 2597C Q1 How many times have you consulted the following people for your own health in the last 12 months? (Mark one on each line) More 1-2 3-4 5-6 7-9 10-12 than None times times times times times 12 times a A family doctor or another General Practitioner (GP) b A specialist doctor c A dentist Q2 Have you consulted the following services for your own health in the last 12 months? (Mark one on each line) Yes No a A hospital doctor (eg in outpatients or casualty) b A midwife c A counsellor or other mental health worker d A chiropractor e An osteopath f A massage therapist g An acupuncturist h A naturopath / herbalist i Another alternative health practitioner (eg aromatherapist, homeopath, reflexologist, iridologist) j A community nurse, practice nurse, or nurse practitioner k A physiotherapist Q3 How often have you used the following therapies for your own health in the last 12 months? (Mark one on each line) Never Rarely Sometimes Often a Vitamins / minerals b Yoga or meditation c Herbal medicines d Aromatherapy oils e Chinese medicines f Prayer or spiritual healing g Other alternative therapies Q4 Have you been admitted to hospital in the last 12 months for any of these reasons? (Mark one on each line) Yes No a Normal childbirth b Problems during pregnancy c All other reasons 3 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q5 When you go to a General Practitioner: (Mark one on each line) Most of Rarely or Always the time Sometimes never a Do you go to the same place? b Do you usually see the same doctor? Q6 Here are some questions about your most recent visit to a General Practitioner. In terms of your satisfaction, how would you rate each of the following? (Mark one on each line) Very Excellent good Good Fair Poor a The amount of time you spent with the doctor b The doctor’s explanation of your problem and treatment c The doctor’s interest in how you felt about having the tests, treatment or the advice given d Your opportunity to ask all the questions you wanted e The technical skills (thoroughness, carefulness, competence) of the doctor f The personal manner (courtesy, respect, sensitivity, friendliness) of the doctor g The cost to you of the visit (Mark here if No Cost ) Q7 In general, do you prefer to see a female doctor? (Mark one only) Yes, always Yes, but only for certain things No Don’t care Q8 Thinking about your own health care, how would you rate the following now? (Mark one on each line) Very Don’t Excellent good Good Fair Poor know a Access to medical specialists if you need them b Access to a hospital if you need it c Access to after-hours medical care d Access to a GP who bulk bills e Access to a female GP f Hours when a GP is available g Number of GPs you have to choose from h Ease of seeing the GP of your choice i Ease of obtaining a Pap test j Access to Women’s Health or Family Planning services k Access to maternal and child health services 4 WHA Yng5-2008-V7 07-08-08 BLACK Q9 Do you have a Health Care Card? This is a card that entitles you to discounts and assistance Pantone 2597C with medical expenses. This is not the same as a Medicare card. (Mark one only) Yes No Q10 Do you have private health insurance for hospital cover? If not, mark the main reason why. (Mark one only) Yes No – because I can’t afford the cost No – because I don’t think you get value for money No – because I don’t think I need it No – another reason Q11 Do you have private health insurance for ancillary services (eg dental, physiotherapy)? If not, mark the main reason why. (Mark one only) Yes No – because I can’t afford the cost No – because I don’t think you get value for money No – because I don’t think I need it No – because the services are not available where I live No – another reason Q12 In the last 3 years, have you been diagnosed or treated for: (Mark all that apply) Please record conditions related to pregnancy (gestational diabetes, hypertension during Yes, in pregnancy, antenatal depression and postnatal depression) in the section relating to pregnancy the last 3 later in the survey. years a Insulin dependent (Type 1) diabetes b Non-insulin dependent (Type 2) diabetes c Heart disease d Hypertension (high blood pressure) e Low iron (iron deficiency or anaemia) f Asthma g Bronchitis h Depression i Anxiety disorder j Endometriosis k Polycystic Ovary Syndrome l Urinary tract infection m Chlamydia n Genital herpes o Genital warts (HPV) p HIV or AIDS q Hepatitis B or C r Skin cancer s Other cancer (Please write on line) ______t Other major physical illness (Please write on line) ______u Other major mental illness (Please write on line) ______v Other sexually transmitted infection (Please write on line) ______w Other (Please write on line) ______x None of these conditions 5 08-08 WHA Yng5-2008-V7 07-08-08 BLACK is about coping with common problems Pantone 2597C Q13 In the last 12 months, have you had any of the following: If yes, did you If you did (Mark one on each line. For all that apply, seek help for seek help, also answer columns B and C) this problem? please mark if you were not satisfied with A BCthat help. Mark here if Mark here if Some- you you were not Never Rarely times Often did seek help satisfied a Allergies, hay fever, sinusitis b Headaches / migraines c Severe tiredness d Indigestion (heart burn) e Breathing difficulties f Stiff or painful joints g Back pain h Problems with one or both feet i Urine that burns or stings j Leaking urine k Constipation l Haemorrhoids (piles) m Other bowel problems n Vaginal discharge or irritation o Premenstrual tension p Irregular periods q Heavy periods r Severe period pain s Skin problems t Difficulty sleeping u Depression v Episodes of intense anxiety (eg panic attacks) w Other mental health problems x Palpitations (feeling that your heart is racing or fluttering in your chest) 6 WHA Yng5-2008-V7 07-08-08 BLACK Q14 What is your date of birth? 19 Pantone 2597C (Write date in boxes) Day Month Year Q15 What is your postcode? a What is your RESIDENTIAL postcode? (where you live) b What is the postcode of your POSTAL ADDRESS? (if different from residential) Q16 When you are outside on a typical summer day, how often do you do the following things to protect yourself from the sun? (Mark one on each line) Never Rarely Sometimes Usually Always a Wear a hat b Wear clothing that protects your skin c Wear sunglasses d Stay in the shade when outdoors e Apply sunscreen to face f Apply sunscreen to exposed body parts Q17 When did you last have: Less 2 to less More (Mark one on each line) than two than 3 3-5 than five years years years years ago ago ago ago Never Not sure a A Pap test? b Your blood pressure checked? c Your skin checked? (eg spots, lesions, moles) Q18 Have you ever had a vaccination for HPV (genital warts, cervical cancer)? (Mark one only) Yes No Q19 Please write down the names of all your medications, vitamins, supplements or herbal therapies that you have taken in the last 4 weeks. Where possible, copy names from the packets. (Please write in block letters) None a h b i c j d k e l f m g n 7 08-08 WHA Yng5-2008-V7 07-08-08 BLACK is about how you are feeling Pantone 2597C The questions on this page ask only about now - how your health is now and about how your health limits certain activities now. Q20 In general, would you say your health is: (Mark one only) Excellent Very good Good Fair Poor Q21 Compared to one year ago, how would you rate your health in general now? (Mark one only) Much better now than one year ago Somewhat better now than one year ago About the same as one year ago Somewhat worse now than one year ago Much worse now than one year ago Q22 The following questions are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much? (Mark one on each line) Yes, Yes, No, limited limited not limited a lot a little at all a Vigorous activities such as running, lifting heavy objects, participating in strenuous sports b Moderate activities, such as moving a table, pushing a vacuum cleaner, bowling or playing golf c Lifting or carrying groceries d Climbing several flights of stairs e Climbing one flight of stairs f Bending, kneeling or stooping g Walking more than one kilometre h Walking half a kilometre i Walking 100 metres j Bathing or dressing yourself 8 WHA Yng5-2008-V7 07-08-08 BLACK Q23 During the past 4 weeks, have you had any of the following problems with your work Pantone 2597C (including your work outside the home and housework) or other regular daily activities as a result of your physical health? (Mark one on each line) Yes No a Cut down on the amount of time you spent on work or other activities b Accomplished less than you would like c Were limited in the kind of work or other activities d Had difficulty performing the work or other activities (for example it took extra effort) Q24 During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)? (Mark one on each line) Yes No a Cut down on the amount of time you spent on work or other activities b Accomplished less than you would like c Didn’t do work or other activities as carefully as usual Q25 During the past 4 weeks, to what extent has your physical health or emotional problems interfered with your normal social activities with family, friends, neighbours or groups? (Mark one only) Not at all Slightly Moderately Quite a bit Extremely Q26 How much bodily pain have you had during the past 4 weeks? (Mark one only) None Very mild Mild Moderate Severe Very severe Q27 During the past 4 weeks, how much did pain interfere with your normal work (including both work outside the home and housework)? (Mark one only) Not at all A little bit Moderately Quite a bit Extremely 9 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q28 For each question, please give the one answer that comes closest to the way you have been feeling. How much of the time during the past 4 weeks: (Mark one on each line) All of Most A good Some A little None the of the bit of the of the of the of the time time time time time time a Did you feel full of life? b Have you been a very nervous person? c Have you felt so down in the dumps that nothing could cheer you up? d Have you felt calm and peaceful? e Did you have a lot of energy? f Have you felt down? g Did you feel worn out? h Have you been a happy person? i Did you feel tired? Q29 During the past 4 weeks, how much of the time has your physical health or emotional problems interfered with your social activities (like visiting friends, relatives)? (Mark one only) All of the time Most of the time Some of the time A little of the time None of the time Q30 How true or false is each of the following statements for you? (Mark one on each line) Definitely Mostly Don’t Mostly Definitely true true know false false a I seem to get sick a little easier than other people b I am as healthy as anybody I know c I expect my health to get worse d My health is excellent 10 WHA Yng5-2008-V7 07-08-08 BLACK is about sexual and reproductive health Pantone 2597C Q31 How many sexual partners have you had? (Write a number in each box. Write ‘0’ if none.) Don’t want to answer a Male sexual partners b Female sexual partners Q32 Which of these most closely describes your sexual orientation? (Mark one only) I am exclusively heterosexual I am mainly heterosexual I am bisexual I am mainly homosexual (lesbian) I am exclusively homosexual (lesbian) I don’t know I don’t want to answer Q33 Have you and your partner (current or previous) ever had problems with fertility - that is, tried unsuccessfully for 12 months or more to get pregnant? (Mark one only) No, have never tried to get pregnant No, have had no problem with fertility Yes, but have not sought help / treatment Yes, and have sought help / treatment Q34 What forms of contraception do you use now?(Mark all that apply) a I use a combined oral contraceptive pill (The Pill) b I use a progestogen only oral contraceptive pill (The Mini Pill) c I use the oral contraceptive pill but I don’t know what type d I use condoms e I use emergency contraception (eg morning after pill) f I use an implant (eg Implanon) g I use the withdrawal method h I use a copper intrauterine device (IUD) i I use a progestogen intrauterine device (IUD) (eg Mirena) j I use an injection (eg Depo-provera) k I use a safe period method (eg natural family planning, rhythm method, Billings method, body temperature method, periodic abstinence) l I use a vaginal ring (eg Nuvaring) m I use another method of contraception (please write on the line) ______n I don’t use contraception 11 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q35 Do any of the following apply to you? (Mark one on each line) Yes No a I am pregnant now / have recently had a baby b I am trying to become pregnant c I have had a tubal ligation d I have had a hysterectomy e My partner has had a vasectomy f I cannot have children g My partner cannot have children h My partner has a low or zero sperm count i I have no male sexual partners now j I am using / have used In Vitro Fertilisation (IVF) k I am using / have used fertility hormones (eg Clomid) Q36 Are you currently pregnant? (Mark one only) No Less than 3 months 3 to 6 months More than 6 months Don’t know The next questions apply only if you have ever been pregnant. If you have never been pregnant, please go to Question 48. Q37 How many times have you had each of the following? (Mark one on each line) 5 or None One Two Three Four more a Live birth b Stillbirth c Miscarriage d Termination (abortion) for medical reasons (eg fetal abnormalities) e Termination (abortion) for other reasons f Ectopic pregnancy (tubal pregnancy) Q38 For your most recent pregnancy, were you: (Mark one on each line) Yes, both during Yes, pregnancy Yes, during following and following Never pregnancy birth birth a Given any information about emotional well being during pregnancy and early parenthood (eg about depression, anxiety, parenting stress)? b Asked any questions by a midwife, GP, child health nurse or other professional about your emotional well being (eg given a questionnaire to complete)? 12 WHA Yng5-2008-V7 07-08-08 BLACK Q39 If you experienced any level of depression, anxiety or distress during If you were offered Pantone 2597C or after your most recent pregnancy, were you offered a referral, a referral, treatment treatment or further follow-up: or further follow-up, (Mark one on each line. For all that apply, did you take up this also answer column B) ABoffer? Mark here if you Yes No did take up this offer a During the pregnancy? b Following birth? c Did not experience The next seven questions are for women who have given birth to a child. If you have never given birth to a child go to Question 47. Q40 If you have ever given birth to a child, please write the date of each birth in the box. (If you had twins, please write the date twice) 1st 2nd 3rd 4th 5th 6th 7th 8th 9th Q41 How many complete months have you breastfed each of your children? (Please write the number of MONTHS in the boxes) 1st 2nd 3rd 4th 5th 6th 7th 8th 9th Child Child Child Child Child Child Child Child Child Q42 After the birth of your last child how soon were they offered breastmilk? (Mark one only) Never Immediately after birth Within half an hour of birth Within an hour of birth Within 4 hours of birth Within 24 hours of birth More than 24 hours after birth 13 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q43 Did you experience any of the following? (Mark all that apply on each line) Never experi- enced 1st 2nd 3rd 4th 5th 6th 7th 8th 9th this Child Child Child Child Child Child Child Child Child a Premature birth b Caesarean section before going into labour c Caesarean section after labour started d Labour lasting more than 36 hours e Episiotomy (cutting of vagina) f A vaginal tear requiring stitches g Forceps or Ventouse suction (‘vacuum’) h Medical removal of placenta and / or blood clots by hand i Excessive blood loss requiring extra blood or fluid by drip (IV infusion) j A low birth weight baby (weighing less than 2500 grams or 5 ½ pounds) k Epidural or spinal block l Gas or injection for pain relief m Emotional distress Q44 Were you diagnosed or treated for: (Mark all that apply on each line) Never experi- enced 1st 2nd 3rd 4th 5th 6th 7th 8th 9th this Child Child Child Child Child Child Child Child Child a Antenatal depression? b Postnatal depression? c Antenatal anxiety? d Postnatal anxiety? e Gestational diabetes? f Hypertension (high blood pressure) during pregnancy? Q45 After the birth of your last child, how soon did you go back to paid work? (Please write the number of MONTHS in the boxes) Months Did not return to paid work Q46 Thinking about the birth of your last child: (Mark one on each line) Don’t Yes No know a Were you entitled to paid maternity leave? b Did you take paid maternity leave? c Were you entitled to unpaid maternity leave? d Did you take unpaid maternity leave? 14 WHA Yng5-2008-V7 07-08-08 BLACK Q47 Are you currently on maternity leave? (Mark one only) Pantone 2597C Yes No Q48 Do you have children living with you (your own, your partner’s, fostered etc)? (Mark one only) Yes No If no, go to Q53 Q49 If you have children living with you (your own, your partner’s, fostered etc), how many are: (Mark one on each line) Four NoneOne Two Three or more a Under 12 months? b 12 months - 5 years? c 6 - 12 years? d 13 - 16 years? Most parents need someone to care for their children when they cannot. Formal child care includes before and / or after school care, long day care, family day care, occasional care and preschool. Informal child care includes care by family, friends (paid or unpaid) and a paid babysitter. Q50 Whether you use child care or not, please answer the following questions. (Mark one on each line) Don’t Yes No know a Is formal child care located in an area convenient to you? b Are formal child care places available to you? c Is the cost of formal child care a problem for you? d Is informal child care available to you? Q51 In a normal week, how often do you usually use child care? (Mark one on each line) Do not use this type of Less than More than child care 5 hrs 5-10 hrs 11-20 hrs 21-30 hrs 31-40 hrs 40 hrs a Formal care b Informal care Q52 In general, how satisfied are you with the amount of child care you use? (Mark one on each line) I would like to I would like to use I am satisfied with use more hours fewer hours the hours I use a Formal care b Informal care 15 08-08 WHA Yng5-2008-V7 07-08-08 BLACK is about health habits Pantone 2597C Q53 How tall are you without shoes? (If you are not sure, please estimate) cms Q54 How much do you weigh without clothes or shoes? If you are pregnant now, write in the weight you were in the month prior to kgs pregnancy. (If you are not sure, please estimate) Q55 What is your waist measurement? Please measure your waist while in your underwear. If possible, get someone to help you take the measurement. Find your navel (belly button) cms and measure at that level. Be careful not to have the tape too tight. You should be able to slip your little finger under it comfortably. Write the measurement to the nearest centimetre. Q56 Have you used any of these methods to lose weight or to control your weight or shape in the last twelve months? (Mark one on each line) Yes No a Commercial weight loss programs (eg Weight Watchers®, Lite n’ Easy, Sureslim®, Jenny Craig®) b Meal replacements or slimming products (eg OPTIFAST®, Herbalife®) c Exercise d Cut down on the size of meals or between meal snacks e Cut down on fats (low fat) and / or sugars f Low glycaemic index (GI) diet g Diet book diets (eg Atkins, Zone, CSIRO diet, Liver Cleansing diet) h Laxatives, diuretics or diet pills (eg Xenical®, Reductil®) i Fasting j Smoking k Other (please write on the line) ______ Q57 How much would you like to weigh now? (Mark one only) Happy as I am 1 – 5 kg more Over 5 kg more 1 – 5 kg less 6 – 10 kg less Over 10 kg less Q58 In the past month, how dissatisfied have you felt about: (Mark one on each line) Not at all Slightly Moderately Markedly dissatisfied dissatisfied dissatisfied dissatisfied a Your weight b Your shape 16 WHA Yng5-2008-V7 07-08-08 BLACK Q59 How often do you currently smoke cigarettes or any tobacco products? (Mark one only) Pantone 2597C Daily Go to Q60a At least weekly (but not daily) Go to Q60b Less often than weekly Go to Q61 Not at all Q60 a. If you smoke daily, on average how many cigarettes do you smoke each day? PRINT the number in the box cigarettes per day Go to Q64 b. If you smoke, but not daily, on average how many cigarettes do you smoke per week? PRINT the number in the box cigarettes per week Q61 In your lifetime, would you have smoked at least 100 cigarettes Yes No (or equivalent)? (Mark one only) If no, go to Q65 Yes No Q62 Have you ever smoked daily? (Mark one only) If no, go to Q65 Q63 At what age did you finally stop smoking daily? (Write age in boxes) years old Q64 At what age did you start smoking daily? (Write age in boxes) years old Q65 How often do you usually drink alcohol? (Mark one only) I never drink alcohol Go to Q68 On 3 or 4 days a week Less than once a month On 5 or 6 days a week Less than once a week Every day On 1 or 2 days a week Q66 On a day when you drink alcohol, how many standard drinks do you usually have? (Mark one only) 1 or 2 drinks per day 5 to 8 drinks per day 3 or 4 drinks per day 9 or more drinks per day Q67 How often do you have five or more standard drinks of alcohol on one occasion? (Mark one only) Never About once a week Less than once a month More than once a week About once a month Q68 At what age did you first have five or more drinks on one occasion? (Write age in boxes) years old Have never drunk five or more drinks on one occasion 17 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q69 How often did you have five or more drinks on one occasion when you were: Less About About More than once once a once a than once Never a month month week a week a Sixteen years old b Seventeen years old c Eighteen years old d Nineteen years old e Twenty years old f Twenty one years old Remember that any information you give us is kept confidential. Q70 The following question asks about the use of drugs for non-medicinal purposes. We want to know about general patterns of use. Please do not give details of specific instances of use. If you have never used any of these drugs, mark here and go to Q71 Never used If ‘yes’ to A, please answer B and C. (Mark all that apply) Have you used HaveA you ever At aboutBC what it in the last 12 tried this? age did you months? Mark if yes first try this? Mark if yes a Marijuana (cannabis, hash, grass, dope, pot, yandi) b Amphetamines (eg speed, uppers, methamphetamine, MDA, ice, crystal meth) c LSD (acid, trips) d Natural hallucinogens (eg magic mushrooms) Tranquillisers (eg tranks, sleepers, Mandrax, e Serapax, Rohypnol) f Cocaine (coke, crack, blow) Ecstasy / designer drugs (eg E, eccies, MDMA, g GHB, fantasy, liquid ecstasy) h Inhalants (eg glue, petrol, solvents) i Heroin (smack, junk) j Barbiturates (eg barbs, downers, purple hearts) 18 WHA Yng5-2008-V7 07-08-08 This section is about your usual eating habits over the past 12 months. Where possible give only BLACK one answer per question for the type of food you eat most often. (If you can’t decide which type you have most often, answer for the types you usually eat.) Pantone 2597C Q71 How many pieces of fresh fruit do you Q76 How many slices of bread do you usually eat usually eat per day? (Count ½ cup of diced per day? (Include all types, fresh or toasted fruit, berries or grapes as one piece) and count one bread roll as 2 slices) (Mark one only) (Mark one only) I don’t eat fruit Less than 1 slice per day Less than 1 piece of fruit per day 1 slice per day 1 piece of fruit per day 2 slices per day 2 pieces of fruit per day 3 slices per day 3 pieces of fruit per day 4 slices per day 4 or more pieces of fruit per day 5-7 slices per day 8 or more slices per day Q72 How many different vegetables do you usually eat per day? (Count all types, fresh, Q77 Which spread do you usually put on bread? frozen or tinned) (Mark one only) (Mark all that apply) Less than 1 vegetable per day a I don’t usually use any fat spread 1 vegetable per day b Margarine of any kind 2 vegetables per day c Polyunsaturated margarine 3 vegetables per day d Monounsaturated margarine 4 vegetables per day e Butter and margarine blends 5 vegetables per day f Butter 6 or more vegetables per day Q78 On average, how many teaspoons of sugar do you usually use per day? (Include sugar Q73 What type of milk do you usually use? taken with tea and coffee and on breakfast (Mark all that apply) cereal etc) (Mark one only) a None None b Full cream milk 1 to 4 teaspoons per day c Reduced fat milk 5 to 8 teaspoons per day d Skim milk 9 to 12 teaspoons per day e Soya milk More than 12 teaspoons per day Q74 How much milk do you usually use per day? Q79 On average, how many eggs do you usually (Include flavoured milk and milk added to tea, eat per week? (Mark one only) coffee, cereal etc) (Mark one only) I don’t eat eggs None Less than 1 egg per week Less than 250 ml (1 large cup or mug) 1 to 2 eggs per week Between 250 and 500 ml (1-2 cups) 3 to 5 eggs per week Between 500 and 750 ml (2-3 cups) 6 or more eggs per week 750 ml (3 cups) or more Q80 What types of cheese do you usually eat? (Mark all that apply) Q75 What type of bread do you usually eat? (Mark all that apply) a I don’t eat cheese a I don’t eat bread b Hard cheeses, eg parmesan, romano b High fibre white bread c Firm cheeses, eg cheddar, edam c White bread d Soft cheeses, eg camembert, brie d Wholemeal bread e Ricotta or cottage cheese e Rye bread f Cream cheese f Multi-grain bread g Low fat cheese 19 08-08 WHA Yng5-2008-V7 07-08-08 BLA CK Pantone 2597C For each food shown on this page, indicate how much on average you would usually have eaten at main meals during the pastp 12 months. When answering each question, think of the amount of that food you usually ate, even though you may rarely have eaten the food on its own. If you usually ate more than one helping, mark the box for the serving size closest to the total amount you ate. Q81 When you ate potato, did you usually eat: I never ate potato 60gABC 100g 150g Less than A A Between A & B B Between B & C C More than C Q82 When you ate vegetables, did you usually eat: I never ate vegetables 130gABC 250g 415g Less than A A Between A & B B Between B & C C More than C Q83 When you ate steak, did you usually eat: I never ate steak 100gABC 125g 175g Less than A A Between A & B B Between B & C C More than C Q84 When you ate meat orr vegetable casserole, did you usually eat: I never ate casserole 100gABC 180g 270g Less than A A Between A & B B Between B & C C More than C 20 WHA Yng5-2008-V7 07-08-08 BLACK Q85 Over the last 12 months, on average, how often did you eat the following foods? Pantone 2597C (Mark one on each line) Less than 1 to 3 1 2 3 to 4 5 to 6 1 2 3 or more once times time times times times time times times TIMES YOU HAVE EATEN Never per month per week per day Cereal, Foods, Sweets & Snacks a All BranTM b Sultana BranTM, FibrePlusTM, BranflakesTM c Weet BixTM, Vita BritsTM, WeetiesTM d Cornflakes, NutrigrainTM, Special KTM e Porridge f Muesli g Rice h Pasta or noodles (include lasagne) i Crackers, crispbreads, dry biscuits j Sweet biscuits k Cakes, sweet pies, tarts and other sweet pastries l Meat pies, pasties, quiche and other savoury pastries m Pizza n Hamburger with a bun o Chocolate p Flavoured milk drink (cocoa, MiloTM etc) q Nuts r Peanut butter or peanut paste s Corn chips, potato crisps, TwistiesTM etc t Jam, marmalade, honey or syrups u VegemiteTM, MarmiteTM or PromiteTM Dairy Products, Meat & Fish a Cheese b Ice-cream c Yoghurt d Beef e Veal f Chicken g Lamb h Pork i Bacon j Ham k Corned beef, luncheon meats or salami l Sausages or frankfurters m Fish, steamed, grilled or baked n Fish, fried (include take-away) o Fish, tinned (salmon, tuna, sardines etc) Fruit a Tinned or frozen fruit (any kind) b Fruit juice c Oranges or other citrus fruit d Apples e Pears f Bananas 21 08-08 WHA Yng5-2008-V7 07-08-08 BLACK TIMES YOU HAVE EATEN Less than 1 to 3 1 2 3 to 4 5 to 6 1 2 3 or more Pantone 2597C once times time times times times time times times CONTINUED Never per month per week per day Fruit g Watermelon, rockmelon (cantaloupe), honeydew etc h Pineapple i Strawberries j Apricots k Peaches or nectarines l Mango or paw paw m Avocado Vegetables (including fresh, frozen and tinned) a Potatoes roasted or fried (include hot chips) b Potatoes cooked without fat c Tomato sauce, tomato paste or dried tomatoes d Fresh or tinned tomatoes e Peppers (capsicum) f Lettuce, endive, or other salad greens g Cucumber h Celery i Beetroot j Carrots k Cabbage or Brussels sprouts l Cauliflower m Broccoli n Silverbeet or spinach o Peas p Green beans q Bean sprouts or alfalfa sprouts r Baked beans s Soy beans, soy bean curd or tofu t Other beans (include chick peas, lentils etc) u Pumpkin v Onion or leeks w Garlic (not garlic tablets) x Mushrooms y Zucchini Q86 Over the last 12 months, how often did you drink beer, wine and / or spirits? (Mark one on each line) If you do NOT drink alcohol, mark here and go to Q89. I do not drink alcohol Less than 1 to 3 once days 1 day 2 days 3 days 4 days 5 days 6 days every TIMES THAT YOU DRANK day Never per month per week a Beer (low alcohol) b Beer (full strength) c Red wine d White wine (include sparkling wines) e Fortified wines, port, sherry etc f Spirits, liqueurs etc 22 WHA Yng5-2008-V7 07-08-08 BLACK When answering the next two questions, please convert the amounts you drink into glasses Pantone 2597C using the examples given below. For spirits, liqueurs, and mixed drinks containing spirits, please count each nip (30 ml) as one glass. 1 can or stubby of beer = 2 glasses 1 bottle wine (750 ml) = 6 glasses 1 large bottle beer (750 ml) = 4 glasses 1 bottle of port or sherry (750 ml) = 12 glasses Q87 Over the last 12 months, on days when you were drinking, how many glasses of beer, wine and / or spirits altogether did you usually drink? Ten or (Mark one only) One Two Three Four Five Six Seven Eight Nine more Total number of glasses per day Q88 Over the last 12 months, what was the maximum number of glasses of beer, wine and / or spirits that you drank in 24 hours? 19 or (Mark one only) 1-2 3-4 5-6 7-8 9-10 11-12 13-14 15-16 17-18 more Maximum number of glasses per 24 hours Questions 71 to 88 are from the Cancer Council of Victoria Food Frequency Questionnaire and are used with their permission. Q89 Over the last 12 months, on average, how often did you drink the following? Less than 1 to 3 1 2 3 to 4 5 to 6 1 2 3 or more once times time times times times time times times (Mark one on each line) Never per month per week per day a Cola drinks - not diet (eg Coke) b Diet cola drinks (eg Diet CokeTM) c Other carbonated (eg fizzy / soft drinks) d Cordials, fruit or sport drinks e Milk or soya milk (including flavoured varieties) f Fruit or vegetable juices g Tea h Herbal tea i Coffee j Water (including soda or plain mineral water) Q90 Over the last 12 months, how stressed have you felt about the following areas of your life? (Mark one on each line) Not Not at all Somewhat Moderately Very Extremely applicable stressed stressed stressed stressed stressed a Own health b Health of family members c Work / employment d Living arrangements e Study f Money g Relationship with parents h Relationship with partner / spouse i Relationship with other family members j Relationship with friends k Motherhood / children 23 08-08 WHA Yng5-2008-V7 07-08-08 BLACK is about family and friends Pantone 2597C Q91 People sometimes look to others for companionship, assistance, or other types of support. How often is each of the following kind of support available to you if you need it? (Mark one on each line) None of A little of Some of Most of All of the the time the time the time the time time a Someone to help you if you are confined to bed b Someone you can count on to listen to you when you need to talk c Someone to give you good advice about a crisis d Someone to take you to the doctor if you need it e Someone who shows you love and affection f Someone to have a good time with g Someone to give you information to help you understand a situation h Someone to confide in or talk to about yourself or your problems i Someone who hugs you j Someone to get together with for relaxation k Someone to prepare your meals if you are unable to do it yourself l Someone whose advice you really want m Someone to do things with to help you get your mind off things n Someone to help with daily chores if you are sick o Someone to share your most private worries and fears with p Someone to turn to for suggestions about how to deal with a personal problem q Someone to do something enjoyable with r Someone who understands your problems s Someone to love and make you feel wanted 24 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q92 Thinking about your current approach to life, please indicate how much you think each statement describes you: (Mark one on each line) Strongly Strongly disagree Disagree Neutral Agree agree a In uncertain times, I usually expect the best b If something can go wrong for me, it will c I’m always optimistic about my future d I hardly ever expect things to go my way e I rarely count on good things happening to me f Overall, I expect more good things to happen to me than bad Q93 We would like to know more about how you spent your time yesterday. Please think about yesterday from the time you got up through to when you got up this morning. Please estimate the time you spent in each of the following activities. Please use ‘0’ to indicate no time in an activity. The total may be less than 24 hours – don’t worry if this is the case – we know you spent some time doing other things! What day was it yesterday? (Mark one only) Monday Tuesday Wednesday Thursday Friday Saturday Sunday a TRANSPORT hours minutes Passive b (eg sitting in a car, bus, train etc) Active c (eg walking, cycling) AT WORK (paid or unpaid) hours minutes Sitting d (eg at a desk or computer) ‘On your feet’ e (standing or moving about as nurses, teachers, shop workers do) Brisk walking f (for at least ten minutes at a time) g Heavy manual labour (the sort a builder or landscape gardener would do) LEISURE TIME hours minutes Passive leisure h (eg TV, internet, reading, socialising, movies etc) Active moderate intensity leisure i (eg brisk walking, cycling, swimming etc) Active vigorous leisure j (eg competitive sport, jogging, aerobics etc) DOMESTIC WORK (house and yard) hours minutes Light house / garden work k (eg cooking, child care, doing laundry, sweeping etc) Heavy house / garden work l (eg scrubbing floors, cleaning windows, pushing mower etc) SLEEPING hours minutes Sleeping m Includes lying down, even if not asleep 25 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q94 Have you experienced any of the following events? (Mark all that apply) A B Yes – In Yes – More the last 12 than 12 months months ago a Major personal illness b Major personal injury c Major surgery (not including dental work) d Birth of a child e Having a child with a disability or serious illness f Starting a new, close personal relationship g Getting married (or starting to live with someone) h Problem or break-up in a close personal relationship i Divorce or separation j Becoming a sole parent k Increased hassles with parents l Serious conflict between members of your family m Parents getting divorced, separated or remarried n Death of partner or close family member o Death of a child p Stillbirth of a child q Miscarriage r Death of a close friend s Difficulty finding a job t Return to study u Beginning / resuming work outside the home v Distressing harassment at work w Loss of job x Partner losing a job y Decreased income z Natural disaster (fire, flood, drought, earthquake etc) or house fire aa Major loss or damage to personal property bb Being robbed cc Involvement in a serious accident dd Being pushed, grabbed, shoved, kicked or hit ee Being forced to take part in unwanted sexual activity ff Legal troubles or involvement in a court case gg Family member / close friend being arrested / in gaol hh None of these events 26 WHA Yng5-2008-V7 07-08-08 BLACK Q95 Next are some specific questions about your health and how you have been feeling in Pantone 2597C the past month. (Mark one on each line) Yes No a Have you felt keyed up or on edge? b Have you been worrying a lot? c Have you been irritable? d Have you had difficulty relaxing? e Have you been sleeping poorly? f Have you had headaches or neck aches? g Have you had any of the following: trembling, tingling, dizzy spells, sweating, diarrhoea or needing to pass urine more often than usual? h Have you been worried about your health? i Have you had difficulty falling asleep? Q96 Below is a list of the ways you might have felt or behaved. Please indicate how often you have felt this way during the last week? (Mark one on each line) Rarely or Occasionally none of the Some or a or a moderate time little of the amount of the Most or all of (less than 1 time time the time day) (1-2 days) (3-4 days) (5-7 days) a I was bothered by things that don’t usually bother me b I had trouble keeping my mind on what I was doing c I felt depressed d I felt that everything I did was an effort e I felt hopeful about the future f I felt fearful g My sleep was restless h I was happy i I felt lonely j I could not ‘get going’ k I felt terrific Q97 In the past week, have you been feeling that life isn’t worth Yes No living? (Mark one only) Q98 In the past 6 months, have you ever deliberately hurt yourself Yes No or done anything that you knew might have harmed or even killed you? (Mark one only) If you answered yes to either of the last 2 questions, you might like to talk to someone about how you are feeling. You could ring Lifeline on 13 11 14 (local call). 27 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q99 In a usual week, how much time in total do you spend doing the following things? (Mark one on each line) I don’t do this 1-15 16-24 25-34 35-40 41-48 49 hours activity hours hours hours hours hours or more a Active leisure (eg walking, exercise, sport) b Passive leisure (eg TV, music, reading, relaxation) c Full-time permanent paid work d Part-time permanent paid work e Casual paid work f Work without pay (eg family business) g Studying h Unpaid voluntary work i Home duties (own / family home) j Looking after your / your partner’s children Q100 Managing time is often difficult. How often do you feel: (Mark one on each line) A few About About Every times a once a once a day week week month Never a That you are rushed, pressured, too busy? b That you have time on your hands that you don’t know what to do with? Q101 Do you regularly provide unpaid care or assistance (eg personal care, Yes No transport) to any other person because of their long-term illness, disability or frailty? (Mark one only) Q102 Do you regularly need help with daily tasks because of a long-term Yes No illness or disability (eg help with personal care, getting around, preparing meals etc)? (Mark one only) 28 WHA Yng5-2008-V7 07-08-08 BLACK The following questions ask about difficult situations you may have experienced. Some people prefer not to answer questions of this nature. If this is true for you, please go to Question 106. Pantone 2597C Yes No Q103 Have you ever had a partner or spouse? (Mark one only) If no, go to Q106 Q 10 4 This question asks about situations you may have experienced with current or past partners. (Mark as many as apply on each line) In the last More than 12 My Partner: 12 months months ago Never a Told me that I wasn’t good enough b Kept me from medical care c Followed me d Tried to turn my family, friends and children against me e Locked me in the bedroom f Slapped me g Forced me to take part in unwanted sexual activity h Told me that I was ugly i Tried to keep me from seeing or talking to my family j Threw me k Hung around outside my house l Blamed me for causing their violent behaviour m Harassed me over the telephone n Shook me o Harassed me at work p Pushed, grabbed or shoved me q Used a knife or gun or other weapon r Became upset if dinner / housework wasn’t done when they thought it should be s Told me that I was crazy t Told me that no one would ever want me u Took my wallet and left me stranded v Hit or tried to hit me with something w Did not want me to socialise with my female friends x Refused to let me work outside the home y Kicked me, bit me or hit me with a fist z Tried to convince my friends, family or children that I was crazy aa Told me that I was stupid bb Beat me up Yes No Q105 Have you ever been in a violent relationship with a partner / spouse? (Mark one only) If you feel distressed about any experiences of violence and abuse and would like some help to deal with this, please consider contacting one of the following: * Your nearest Women’s Health Centre or Community Health Centre * Your General Practitioner for advice about who would be the best person in your community to talk to * A Lifeline counsellor on 13 11 14 (local call). 29 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C The next question is about the amount of physical activity you did last week. Q106 Please state how many times you did each type of activity and how much time you spent altogether doing each type of activity last week. Only count activities that lasted for 10 minutes or more; add up all the times you spent in each activity to get the total time for each activity. (If you did not do an activity, please write ‘0’ in the boxes) Total time in this activity Number of times hours minutes a Walking briskly (for recreation or exercise, or to get from place to place) b Moderate leisure activity (like social tennis, moderate exercise classes, recreational swimming, dancing) c Vigorous leisure activity (that makes you breathe harder or puff and pant like aerobics, competitive sport, vigorous cycling, running, swimming) d Vigorous household or garden chores (that make you breathe harder or puff and pant) Now think about all of the time you spend sitting during each day while at home, at work, while getting from place to place or during your spare time. Q107 How many hours in total do you typically spend sitting down while doing things like visiting friends, driving, reading, watching television, or working at a desk or computer? a On a usual week day hours minutes b On a usual weekend day hours minutes Q108 What is the highest qualification you have completed? (Mark one only) No formal qualifications Year 10 or equivalent (eg School Certificate) Year 12 or equivalent (eg Higher School Certificate) Trade / apprenticeship (eg hairdresser, chef) Certificate / diploma (eg child care, technician) University degree Higher university degree (eg Grad Dip, Masters, PhD) 30 WHA Yng5-2008-V7 07-08-08 BLACK Q109 Do you normally do any of the following kinds of paid work? (Mark all that apply) Pantone 2597C a I don’t do any paid work Go to Q111 b Paid shift work c Paid work with irregular hours d Paid work on short-term contract (less than one year) e Paid work in more than one job f Paid work at night g Paid work from home h Self employment i None of the above Q110 How secure or insecure do you feel about your paid job or jobs? (Mark one only) I worry all the time about losing my job Sometimes I worry about losing my job I rarely or never worry about losing my job Don’t know Q 111 Are you happy with the number of hours of paid work you do? (Mark one only, even if you have no paid work) Yes, happy as is No, would like to do more No, would like to do less Q112 We would like to know your main occupation now (Mark one only) Manager or administrator (eg magistrate, farm manager, general manager, director of nursing, school principal) Professional (eg scientist, doctor, registered nurse, allied health professional, teacher, artist) Associate professional (eg technician, manager, youth worker, police officer) Tradesperson or related worker (eg hairdresser, gardener, florist) Advanced clerical or service worker (eg secretary, personal assistant, flight attendant, law clerk) Intermediate clerical, sales or service worker (eg typist, word processing / data entry operator, receptionist, child care worker, nursing assistant, hospitality worker) Intermediate production or transport worker (eg sewing machinist, machine operator, bus driver) Elementary clerical, sales or service worker (eg filing / mail clerk, parking inspector, sales assistant, telemarketer, housekeeper) Labourer or related worker (eg cleaner, factory worker, general farm hand, kitchenhand) No paid job Q113 Are you currently unemployed and actively seeking work? (Mark one only) No Yes, unemployed for less than 6 months Yes, unemployed for 6 months or more 31 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q114 a What is the average gross (before tax) income that you receive each week, including pensions, allowances and financial support from parents? b What is the average gross (before tax) income of your household each week (eg you and your partner, or you and your parents sharing a house?) (Mark one for yourself and one for your household) a. Self b. Household No income $1-$119 ($1-$6,239 annually) $120-$299 ($6240-$15,599 annually) $300-$499 ($15,600-$25,999 annually) $500-$699 ($26,000-$36,399 annually) $700-$999 ($36,400-$51,999 annually) $1,000-$1,499 ($52,000-$77,999 annually) $1,500-$1,999 ($78,000-$103,999 annually) $2,000-$2,499 ($104,000-$129,999 annually) $2,500-$2,999 ($130,000-$155,999 annually) $3,000 or more ($156,000 or more annually) Don’t know Don’t want to answer I live alone (household income is the same as mine) Q115 How many people (including yourself), are dependent on this household income? (Write number in boxes) Q116 How do you manage on the income you have available? (Mark one only) It is impossible It is difficult all the time It is difficult some of the time It is not too bad It is easy Q117 How much of your gross household income do you spend on your housing (eg rent, mortgage repayments)? % (Write percentage in boxes) Q118 Which one of the following best describes your housing situation? (Mark one only) Private rental (including rent paid to real estate agents) State Department of Housing public rental Departments of Defence, Education and Health public rental Owned home with a mortgage Owned home without a mortgage Other (please write on line) ______ 32 WHA Yng5-2008-V7 07-08-08 BLACK Q119 What is your present marital status? Pantone 2597C (Mark one only) Never married Married De facto (opposite sex) De facto (same sex) Separated Divorced Widowed Q120 Who lives with you? (Mark all that apply) a No one, I live alone b Partner / spouse c Own children d Someone else’s children e Parents f Other adults Q121 In general, how satisfied are you with what you have achieved in each of the following areas of your life? (Mark one on each line) Very Very satisfied Satisfied Dissatisfied dissatisfied a Work b Career c Study d Family relationships e Partner / closest personal relationship f Friendships g Social activities h Motherhood / children Not applicable Q122 If you are currently pregnant or have recently had a baby, or are thinking of Yes No having a baby in the next two years, would you be happy for us to contact you in the future about taking part in an additional study? (Mark one only) This study will ask about the information and assistance pregnant women and new mothers might be given about emotional well being. 33 08-08 WHA Yng5-2008-V7 07-08-08 BLACK Pantone 2597C Q123 Did someone help you fill in this survey? (Mark one only) No Yes, but I told them the answers I wanted Yes, but the helper answered for me using his / her own judgement Q124 What was the MAIN reason for your needing help to fill in this survey? (Please describe) Have we missed anything? If you have anything else you would like to tell us, please write on the lines below. You may also like to take a moment to check you have not missed any questions or pages. Thank you for taking the time to complete this survey. If you need help to answer any of the questions, you can contact us by telephoning 1800 068 081(Freecall) When you have completed the survey, please sign the next page and send the survey back to us as soon as possible. We will detach the consent form and store it in a separate locked room. 34 WHA Yng5-2008-V7 07-08-08 perf Consent I agree to the research team following health and other records relating to me, including hospital and health service use records and cancer registers and other chronic conditions registers as described to me in the accompanying brochure. I also understand this means I agree to Medicare releasing information concerning services provided to me under Medicare, the Department of Veterans’ Affairs, the Pharmaceutical Benefits Scheme and the Repatriation Pharmaceutical Benefits Scheme, including past information, for the duration of the study, as outlined in the enclosed brochure. (Mark one only) Yes No Please sign below and send the completed survey back to us in the envelope supplied as soon as possible. We will detach the consent form and store it in a separate locked room. I consent to the researchers ‘matching’ the information provided in this survey with that given in previous surveys so that any change in my health can be noted. Signature: Date: // What is your Maiden Name? (Please print in the boxes) Have you remembered to measure your waist? Page 16 Question 55 Help us keep in touch Sometimes we lose touch with our participants. It would be helpful if you could give us your mobile phone number and email address. Mobile Email It would be helpful also, if you could give us details of parents, a relative or friend who will be able to help us find you, after checking that the relative or friend is happy for you to provide these details. Name: Address: Town/ State Postcode Suburb Phone: Relationship ( ) to you: Name: Address: Town/ State Postcode Suburb Phone: Relationship ( ) to you: 08-08 perf WHA Yng5-2008-V7 07-08-08 perf Please post this back in the Reply Paid envelope provided. No stamp required if posted in Australia Reply Paid 70 Hunter Region MC NSW 2310 Please let us know your new details if you move, change your name or your telephone number. Freecall Number 1800 068 081 Austral ian Longitud inal Stud y o n Women’s Heal t h The University of Newcastle, Callaghan NSW 2308. Phone: 02 4913 8872 Fax: 02 4913 8888 Email: [email protected] Web: www.alswh.org.au WHA Yng5-2008-V7 07-08-080 Women’s Health Australia Reply Paid 70 Hunter Region MC NSW 2310 Ph: 1800 068 081 Email: [email protected] Web: www.alswh.org.au TITLE FIRSTNAME SURNAME ID PREADDRESS ADDRESS SUBURB STATE POSTCODE HAVE YOUR DETAILS CHANGED? If you have changed your name, address or contact details, please advise us by completing and returning this form with your survey in the reply paid envelope provided or by calling FREECALL 1800 068 081. NAME: TITLE GIVEN NAME/S SURNAME ADDRESS: SUBURB STATE POSTCODE PH (HOME): () PH (WORK): () PH (MOBILE): EMAIL: Y5 2008 www.alswh.org.au December 2008