Impact of Gender on Care of Type-2 Diabetes

in Varkala, Kerala

Mini P. Mani

Dissertation submitted in partial fulfilment of the requirements for the award of the degree of Master of Public Health

Achutha Menon Centre for Health Science Studies Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India 2008

Declaration

I hereby declare that this dissertation work titled “IMPACT OF GENDER

ON CARE OF TYPE-2 DIABETES IN VARKALA, KERALA” is the result of original research and it has not been submitted for the award of any degree in any other university or institution.

Thiruvananthapuram

October 2008 Mini P. Mani

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Certificate

I hereby certify that the work in this dissertation titled “IMPACT OF GENDER ON CARE

OF TYPE-2 DIABETES IN VARKALA, KERALA” is a certified record of original research work undertaken by Dr Mini P.Mani in partial fulfillment of requirement for the purpose of award of Master of Public Health Degree under my guidance and supervision.

Dr. Mala Ramanathan Additional Professor Achutha Menon Centre for Health Science Studies Sree Chitra Tirunal Institute for Medical Sciences and Technology Thiruvananthapuram 695011, Kerala, India

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Acknowledgements

This work would not have been materialised without the contributions of the individuals who are gratefully acknowledged here.

Though the crude idea of doing this study resulted from my personal and professional experiences, it was my guide Dr. Mala Ramanathan, Additional Professor, AMCHSS who was with me at each step of developing every component of the study, patiently listening to me, correcting the mistakes, clearing the doubts, teaching me the right language to speak and write the subject, in short holding my hand and making me walk through every step till now, with so much care and affection. With a brimming heart I acknowledge my gratitude to her.

It was Dr. V. Raman Kutty, Professor, AMCHSS who suggested the possibility of doing the study in Varkala, with the help of Health Action by People (HAP). I acknowledge my sincere thanks to him.

I got valuable advice and directions from Dr. T.K Sundari Ravindran, Honorary Professor, AMCHSS during the initial stages of the study when I was preparing the questionnaire and Dr. Manju R Nair, Scientist, AMCHSS who asked me the gender questions that set me thinking. I am thankful to both of them for their contributions.

Maths and statistics were nightmares till I met Dr. P. Sankara Sarma, Additional Professor, AMCHSS- the best maths teacher I have come across. He helped me move ahead in the right path, all through my study, from sample size calculation till the final analysis phase. I take this opportunity to thank him for all the help he did.

I consider myself fortunate to have been able do my work in association with Dr.CR Soman and his organisation Health Action by People (HAP). He was so supportive and encouraging from the very beginning, and offered all help from his team, which I received till the last day. A few unforgettable persons are Mr. Ajayan, the Sr. Project Officer [Research], Mr. Sajikumar, the Sr.Project Officer [Clinical] and Ms. Tessy who is in charge of the field activities in Varkala. Had these persons not been there, the work would not have run so easy and smooth. The gratitude I have for them is beyond words.

Becoming a student again, after a gap of ten years was not a cakewalk. My classmates were my informal teachers who spent hours in hostel helping me, especially with the modules which contained numbers more than words. I am thankful to each of them for tolerating my ignorance never showing an unpleasant face, and sparing their valuable time for me.

It would be improper if I do not mention Mr. Shyam and family and Ms. Tessy and family, who were like my second homes, all through this study period. No words can explain how valuable their presence was for me in completing this study.

Two years would not have been so easy without the immense support the two wonderful persons in my family extended to me. The lady who asks “how many pages finished” or “how many more slides to make”, every time we talk over the phone, so she can roughly estimate the next day I will be with her again- that is my daughter who behaves more mature than her seven years of age, understanding and coping up with my absence, the greatest support for me. Her dad, adjusting with the life without me beyond all ‘gender roles and norms’, extends his support every moment, across the miles. It will not be enough if I only thank them. So I just say “It is because of you, I am.”

Last but not the least, I remember each and every participant of my study with heartfelt thanks. The people who took me into trust and opened their hearts out, many inviting me for tea and lunch, a few women who broke into tears during the interview – I am deeply indebted to each of them for the successful completion of my study. iv

Abstract

Background and objective: India contains the largest number of diabetic patients in the world and Kerala, the state within it despite being applauded for its achievements in health indicators, has the highest proportion of non-communicable diseases, especially diabetes. Many studies elsewhere have revealed the vulnerability of women to poor NCD management and outcome, but few have examined the gendered dimensions of diabetes management. The key objective of this study is to explore the disease management outcome among the cases of Type 2 Diabetes Mellitus in a selected population, with special focus on the gender mediated factors that affect the ability to manage the disease.

Methodology: The sample of 200 diabetic patients selected from a sample frame of 504 diagnosed diabetics in two Panchayats of Varkala ICDS block of Trivandrum district, Kerala, contained equal number of male and female participants. A structured pretested interview schedule in Malayalam was administered after obtaining informed consent. The socio-demographic, disease and gender related variables were analysed to capture the gender mediated factors which determine the management outcome of diabetes mellitus.

Results: Good diabetes management outcome of the study population was 23.5 percent (29 percent of men and 18 percent of women) with a statistically significant difference between men and women (Chi-square p value 0.045, OR=1.330). This sex difference was found to be mediated in terms of women’s roles at homes as caregivers, values that prevent woman from prioritising their health and inequitable access to resources that prevent woman from early diagnosis.

Conclusion: The study establishes the linkages of gender roles, norms and values that exert significant influences on all phases of diabetes management, which in turn results in poor management of DM among women. There is a need for developing NCD control programmes, incorporating these gendered factors.

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CHAPTER 1 INTRODUCTION

Non Insulin Dependent Diabetes Mellitus- NIDDM is a disease that affects the endocrine system but infiltrates almost all the vital organs of the body. For decades, Diabetes has been a ‘rich man’s problem’ – a burden of industrialised countries to solve. But as the sugar disease, as it is often called, has penetrated the

United States and other developed nations, it has also made inroads deep into the far more populous developing world. According to the UN, the world has now reached the point, where more people are overweight than undernourished. The prevalence of type 2 diabetes was as high as 50% among the offspring of conjugal type 2 diabetic parents in India, which is the highest prevalence rate reported until now. Throughout the world, Type 2 diabetes, once predominantly a disease of the old, has been striking younger people. Because Indians have such a pronounced genetic vulnerability to the disease, they tend to contract it ten years earlier than people in developed countries. It is because India is so youthful — half the population is under

25 - that the future of diabetes here is so chilling. Prevalence among adults in India is estimated at about six percent, two-thirds of that in the United States, but the illness is spreading faster, particularly in the country’s large cities.

The risk factors for the increasing prevalence among Asian Indians included high racial susceptibility, central obesity and insulin resistance even with a low Body Mass Index. The so called “Asian Indian Phenotype” refers to certain unique clinical and biochemical abnormalities in Indians which include increased insulin resistance, greater abdominal adiposity i.e., higher waist circumference 1

despite lower body mass index, lower adiponectin and higher high sensitive C- reactive protein levels.

Epidemiology of diabetes in India has a long history. Charaka

Samhita, the ancient Indian medical treatise, describes this condition and suggests that being obese was a major risk factor. It was commented that fat asymmetry impairs strength and shortens lifespan; this may have been an indication of increased incidence of diabetes among the asymmetrically obese.

The prevalence of DM in Kerala ranges from six percent in rural areas to nearly 20 percent in the cities. Reported prevalence of known diabetes mellitus was 9.0%.

Women have made many strides in promoting equity in their social status; nevertheless, there are entrenched values and structures in our society that continue to negatively affect the health of women in general. Research has shown that many risk factors for diabetes (weight gain, obesity, lack of physical activity) are more common among women than men in all population subgroups.

Mainstreaming gender into analysis, formulation and monitoring of policies to minimise inequalities, were seen in the health sector too. The term

“Engendering Health” came into use, which suggests to see and analyse the health system, and its components in a gender perspective, to identify and solve the problems related to it. New indicators like Gender Development Index (GDI) and

Gender Empowerment Measure (GEM) came into use, which supplemented Human

2

Development Index (HDI) to focus on gender inequalities in all the aspects related to development, including health. In general, women are the initial providers of primary care to family members or to their extended family. Many women work and provide support to family and community members. At the same time, self-care or preventive care may not be a priority for many women who work outside of or in the home, women who are heads of households, women who are poor or nearly poor, and women responsible for providing for their parents and members of their extended family. Circumstances such as retirement from employment, separation, divorce, and widowhood may make middle-aged women vulnerable to low family incomes and inadequate health care coverage so that they may forego needed services, including preventive care for serious diseases like diabetes and hypertension.

Until the mid- 1900s, the maternal role was thought to require so much energy that other activities such as physical activity and intellectual pursuits were not promoted for women. Implicit in this assumption was the perception that women are inferior to men. This gender bias created a social environment where women’s work and concerns were not taken seriously. Moreover, this perception dictated that the primary focus of women’s health to be on their reproductive function, and many other aspects of their general health were neglected. The same bias that resulted in women’s health historically being viewed primarily in the context of their reproductive organs may still influence women’s health priorities, particularly those with diabetes or other chronic illnesses.

Diabetes related complications are coronary artery disease, peripheral vascular disease, neuropathy, retinopathy, nephropathy, etc. Though it is 3

largely known that diabetes leads to very serious and expensive complications, patients are seen only treating the complications rather than implementing stringent steps preventing them. Only very rarely, Keralites are seen investing money and time, in preventive health care. (Preventive health care involve periodic medical examination, extensive laboratory evaluation, diet, drugs and daily exercises based on expert advice). The onset of disease is generally around the later reproductive years. And there is a considerable increase in body weight and BMI in the women, around the peri and post menopausal age group- which adds to the risk factors of developing diabetes mellitus. The picture gets worse when we read it with the fact that there are no programs in our existing health system, which addresses the needs of the women in this vulnerable age group. Cancer cervix screening programme is the only one program targeting women in the later reproductive years, but that is too specific and is centred around the pap smear testing alone and doesn’t pay any attention on the other systems or risk factors for any other diseases.

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Chapter 2

REVIEW OF LITERATURE

This chapter is reviewing the available literature under four broad headings – burden of non communicable diseases, the Indian scenario, Kerala situation and Gender and diabetes.

2.1 Burden of Diabetes and other non communicable diseases

Type 2 Diabetes Mellitus (NIDDM) is the major cause of morbidity and mortality affecting millions of people worldwide, placing a noteworthy strain on

Public Health funding1. It has been predicted that worldwide the prevalence of diabetes in adults would increase to 5.4 percent by the year 2025 from the prevalence rate of 4.0 percent in 1995. More people worldwide now die from chronic diseases like diabetes than from communicable diseases. The total number of people with diabetes is projected to rise from 171 million in 2000 to 366 million in 2030. The prevalence of diabetes is higher in men than women, but there are more women with diabetes than men. The urban population in developing countries is projected to double between 2000 and 2030. With increasing proportion of elderly and the higher risk of obesity, the accompanying rise in diabetes is inevitable2. The "diabetes epidemic" will continue even if levels of obesity remain constant. Given the increasing prevalence of obesity, it is likely that these figures provide an underestimate of future diabetes prevalence3

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The World Health Organisation expects that, of the more than 350 million diabetics projected in 2025, three-fourths will inhabit the Third World. While a 42percent increase is expected in developed countries, a 170percent increase is expected in the developing countries. In the latter, most of the diabetic patients are in the age range of 45–64 years. Therefore diabetic patients in developing countries are even more vulnerable to develop the micro- vascular complications of diabetes including diabetic nephropathy4. In the future, diabetes will be increasingly concentrated in urban areas. Worldwide surveillance of diabetes is a necessary first step toward its prevention and control, which is now recognized as an urgent priority5.. A major handicap in establishing a true global picture has been the lack of uniformity in defining and classifying diabetes, and an additional limiting factor has been the grouping of different types of diabetes in published prevalence data. It appears the prevalence of insulin dependent (Type 1) and non-insulin dependent

(Type 2) diabetes varies between and within ethnic groups, e.g. rural versus urban dwellers, thus making it difficult to compare data from different countries6. Regardless of the exact levels of diabetes prevalence, preventing the spread of this epidemic is of urgent importance, and evidence suggests that an intensive lifestyle intervention designed to induce modest weight loss may work7.

2.2 Indian Scenario

Asian-Indians have been identified as one of the ethnic groups with a high prevalence of type 2 diabetes and a high familial aggregation of type 2 diabetes. As India passes through the state of demographic transition, non communicable diseases are on the rise, especially Diabetes mellitus. India holds the

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maximum number of diabetic patients in the world today. Migration from rural areas to urban slums leading to obesity, glucose intolerance, and dyslipidaemia, ‘Fast food culture’, ‘Sedentarism’ and the epidemiological transition are the main drivers of

Diabetic Epidemic in India. Among the states in India, Kerala holds the maximum proportion of diabetics8. There are many studies pointing towards the ethnic and genetic vulnerability of Asian- Indian population to diabetes. There appears to be certain genes which predispose Indians to diabetes while other genes (for example

Pro 12 Ala polymorphism of PPAR gamma gene) which afford protection against diabetes and insulin resistance to Caucasians, do not appear to protect Indians9.

Indians with Type 2 Diabetes had a 5-fold higher risk of metabolic syndrome (MS) than the general population group. The high frequency of MS and of hypertriglyceridemia in Indians with type 2 diabetes highlights the need for screening and management of MS in this population facing a high cardiovascular risk10.

The age at which the peak prevalence of diabetes was reached was approximately 10 years younger in Indian compared with Chinese and Japanese subjects11. Industrial populations located in highly urbanized centres were observed to have an inverse graded relationship (i.e., higher-education groups had lower prevalence) for tobacco use, hypertension, diabetes, and overweight, whereas in less- urbanized locations, such a relationship was found only for tobacco use and hypertension. It indicates the growing vulnerability of lower socioeconomic groups to

Coronary heart disease (CHD), and suggests that preventive strategies to reduce major

CHD risk factors should focus on effectively addressing these social disparities12.

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Added to that, Asians compared to other ethnic origins, have lesser physical activity which predisposes them more towards the development of the disease. Europeans are found to be more physically active than Indians, Pakistanis or

Bangladeshis. Similar findings are reported for men and women. In particular,

European men and women participated more frequently in moderate and vigorous sport and recreational activities. In general, level of physical activity was inversely correlated with body mass index (BMI), waist measurement, systolic blood pressure, and blood glucose and insulin in all ethnic groups. South Asians report significantly lower levels of habitual physical activity than Europeans. This is likely to contribute to the higher levels of diabetes and cardiovascular risk in these populations. So, measures to increase physical activity in these populations are urgently needed13.

Another study says that levels of physical activity are lower in all South Asian groups than the general population and patterns of activity differed, and the differences were substantial, particularly among women and older people14. Diabetes was significantly related to obesity in women but not in men. The prevalence of diabetes is high among urban Indians and is comparable with the high prevalence seen in migrant Indian populations15. The cost of treating diabetes lifelong is huge.

Treatment costs increased with duration of diabetes, presence of complications, hospitalization, surgery, insulin therapy, and urban setting. Lower-income groups spend a higher proportion of their income on diabetes care. The highest increase in percentage of household income devoted to diabetes care is in the lowest economic group. The economic burden on urban families in developing countries is rising, and the total direct cost has doubled from 1998 to 200516. Complications of diabetes add to the mortality generally, and some studies suggests that Preventive strategies have

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to be evolved to ensure that blindness due to diabetic retinopathy does not become a public health problem in India17.

2.3 Kerala situation

Kerala’s achievements in health have been universally recognized.

The dramatic decline in fertility and child mortality, the high life expectancy of 73 during the last four decades has given Kerala reputation as the healthiest state in

India. Kerala has experienced a health transition from that of a high child mortality- high morbidity picture to that of low child mortality- high adult morbidity situation in just over one generation time. The prevalence of diabetes mellitus and high blood pressure in Kerala is much higher than the reported estimates in the West. The diabetic patients need lifetime management involving lifestyle modifications, drugs and diet. The economic cost of managing diabetes in Kerala is enormous. The prevalence in Kerala ranges from six percent in rural areas to nearly 20 percent in the cities. Risk factor prevalence varied with area of residence, with urban population reporting highest prevalence for type 2 diabetes and obesity18. Reported prevalence of diagnosed diabetes mellitus was 9.0% ( Total-276/3069); (Male-8.7% and Female-

9.2%), according to a study done in Kerala, where we can see the prevalence of reported DM is more among females19.

2.4 Gender and Diabetes

The Department of Gender, Women and Health (GWH), WHO brings attention to the ways in which biological and social differences between women and men affect health and the steps needed to achieve health equity. Main 9

areas of work include integrating gender into health policies and programmes through strategies like Increasing knowledge and evidence on how sex differences and gender inequalities impact upon specific health problems, health services and successful responses, and developing tools to promote and expand health sector policies, interventions and programmes at the regional and country level that systematically address gender concerns. Gender norms and values, however, also give rise to gender inequalities that is, differences between men and women which systematically empower one group to the detriment of the other. The fact that, throughout the world, women on average have lower cash incomes than men is an example of a gender inequality. Across continents and cultures, established gender norms and values mean that women typically control less power and fewer resources than men. Not surprisingly, this often gives men an advantage - in the economic, political, and educational arenas, but also with regard to health and health care20.

As gendered understanding of morbidity started to evolve in the late 20th century, many problems and issues related to this particular context started getting identified. Women have made many strides in promoting equity in their social status; nevertheless, there are entrenched values and structures in our society that continue to negatively affect the health of women in general. Research has shown that many risk factors for diabetes (weight gain, obesity, lack of physical activity) are more common among women than men in all population subgroups21.

There are many factors that play significant roles in determining women’s health status, in general. Gender inequality damages the physical and mental health of millions of females across the globe, and policy briefings are 10

currently being done to combat this unequal, unfair ineffective and inefficient situation22.Women’s greater longevity itself is a cause of higher rates of morbidity.

So women make up the majority of elderly people in the world, and older women are more susceptible to some disabling diseases than men23. Women are more likely to suffer reproductive health problems than men, like cancer of cervix, breast cancer, genito-urinary infections etc. The protective mechanism provided by oestrogen, against cardiovascular risks, tends to wane after menopause, when the blood level of oestrogen goes down. Many symptoms of major systemic diseases are less likely to be interpreted correctly in women, for example angina pain is often regarded as of gastric or muscular origin due to the presumption that cardiovascular risk in women is lesser24.

Till recent times, gender was not considered to play any significant role in causation and progress of ill health and the concept of women's health was tethered strongly to reproductive health. In a study, the cause of death data for women aged 15-34 years and 35-44 years was examined for nine less developed countries.

Deaths associated with pregnancy and child birth, and HIV were compared with deaths due to three chronic disease categories (cancer, cardiovascular disease, and diabetes). In less developed countries, chronic disease is the most important cause of female death even during childbearing years and for women with young families25.

Diabetes whether treated properly or not, may not display any obvious symptoms in the first five to ten years. The appearance of complications in the vital organs is a slow and silent process. Because of its silent nature, it is a common finding that diabetes is totally ignored until something drastic happens. So unless one undergoes routine check up beyond the age of 35 or 40 years, diabetes is difficult to be detected in 11

early stage. In case of females, routine health check up without any symptoms is very very rarely done, and many of the diabetic women are detected only in the later stages after the complications develop, in which stage it is difficult to treat.26

Identifying cultural definitions of health and diabetes is critically important to developing effective diabetes prevention program. In-home qualitative interviews were conducted with 79 American Indian women from three tribal clinics in northeast Oklahoma to identify a cultural definition of health and diabetes.

Grounded theory was used to analyze verbatim transcripts. The women interviewed defined health in terms of physical functionality and absence of disease, with family members and friends serving as treatment promoters. Conversely, the women considered their overall health to be a personal issue addressed individually without burdening others. The women presented a fatalistic view of diabetes, regarding the disease as an inevitable event that destroys health and ultimately results in death.

Further understanding of the perceptions of health in at-risk populations will aid in developing diabetes prevention programs.27 Social factors play significant and distinct roles in men and women in case of NCD initiation and progression. The association between hypertension and socioeconomic status was complex and differed between men and women. Among men, those with lower educational and occupational status but who were richer were more likely to be hypertensive. More women with lower occupational and economic status were hypertensive.28

The life expectancy of women currently exceeds that of men by almost seven years, yet women spend approximately twice as many years disabled prior to death as their male counterparts. The diseases that account for death and 12

health care utilization in older women (heart disease, cancer, stroke, fracture, pneumonia, osteoarthritis, cataracts) are also major contributors to disability. One study suggests that risk factors for falls and fractures should be assessed and, where possible, modified, adequate intakes of calcium, vitamin D, fruits, and vegetables should be encouraged, weight should be monitored, screening for B12 deficiency is to be done, women should be engaged in a shared decision-making process about the use of hormone replacement therapy for longterm prevention of heart disease and fractures, regular screening for breast and colo-rectal cancer to be done and women should be encouraged to engage in enjoyable physical activities, including walking for 30 minutes daily, as these interventions have the potential to delay the onset and improve the course of many chronic conditions that prevail in later life.29

Many studies in the arena of Noncommunicable diseases show that women are getting more affected compared to the men. For example, a study in

Japan, on Metabolic syndrome– effect of MetS is more pronounced in women than in men.30A study in Washington found that presence of depression and diabetes in women increased their susceptibility to CHD.31 A study in USA on Diabetes,

Gender and Left ventricular Hypertrophy says that prevalence of left ventricular hypertrophy was higher in women, and those with diabetes had higher prevalence of left ventricular hypertrophy, and of increased wall thickness32 . A Study on Health related quality of life (HRQOL) in Greece found that female gender is the most important predictor of impaired HRQOL in diabetic patients33.

Various studies suggest that diabetes increases the susceptibility of women to a wide range of other diseases from UTI34,35 to breast cancer as insulin 13

resistance has been linked to an increased risk of breast cancer and is also characteristic of type 2 diabetes36 . In a study it was found that endogenous sex hormones may differentially modulate glycemic status and risk of type 2 diabetes in men and women. High testosterone levels are associated with higher risk of type 2 diabetes in women but with lower risk in men; the inverse association of serum hormone binding globulin (SHBG) with risk was stronger in women than in men37.

Post menopausal women are at a higher risk since the protective effect by the female hormone estrogen is not there anymore. Prehypertension is common and was associated with increased risk of myocardial infarction, stroke, heart failure, and cardiovascular death in white and non-white postmenopausal women38. In another study, among postmenopausal women with coronary heart disease, the presence of diabetes predicted disease progression, but metabolic syndrome did not39. Coronary artery disease is the leading cause of mortality in women, with incidence after menopause equal to that of men. Diabetes and postmenopausal status without hormone replacement therapy are the strongest risk factors. According to some studies, coexistence of diabetes and depression diminishes the protective effect of female gender on Coronary Heart Disease (CHD)40. As in all NCDs generally, post menopausal women are at a higher risk for developing diabetes. An association between both a postmenopausal increase in blood pressure and CHD that coincide with loss of ovarian function suggests that estrogen and/or progesterone may be protective against hypertension and CHD. Diabetes removes the normal sex difference in the prevalence of CHD. Increased mortality in women with CHD and diabetes compared with women without diabetes has been observed41.

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Women with CAD are more likely to have atypical symptoms and physicians should maintain a high level of suspicion. Newer non-invasive stress imaging modalities provide greater diagnostic accuracy than traditional exercise stress testing, but the tests are still less accurate for women42. With respect to metabolic syndrome, the differences between the components of atherogenic dyslipidemia in patients with acute ischemic syndromes were related to the patients’ gender: men significantly more frequently had increased TG concentration and women – decreased HDL-C concentration43. Many social and economic factors like lack of availability, accessibility and affordability of health care services affect women more adversely compared to men44. A study done in Japan says that women have higher in hospital mortality than men, due to AMI45. A study in USA on gender disparities in lipid management has found that women receive poorer lipid management than men among patients with diabetes mellitus46 .

Regarding the preventive aspects of DM, physical activity is important for type 2 diabetes prevention among older women47. A qualitative study done among diabetic women in Australia finds that analysis of gender relations is useful for understanding the social context of health related behavioural change required for diabetic self care, and women may require additional strategies to support the initiation and maintenance of these changes. This can be enhanced by involving family members particularly male partners in the diabetic education programmes to support the changes48.

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CHAPTER 3 OBJECTIVES AND METHODOLOGY

In this chapter we have included the objectives of the study and provided a description of the methodology used to achieve these objectives.

3.1. Objective and research questions

Objective: The key objective is to study the disease management outcome among the subjects with type 2 Diabetes Mellitus in a selected population, with special focus on the gender mediated factors that affect the ability to manage the disease.

The research questions:

1. How effectively does the study population manage their diabetic status – in

other words, what is the extent of treatment compliance, with regard to

management of diabetes mellitus?

2. How does, in this community, gender affect :

a. the initial diagnosis of DM ?

b. the treatment options available ?

c. the utilization of various treatment option ?

d. the ability to adhere to the recommended treatment regimes?

e. the prevention of possible complications of DM?

3. How does gender influence the compliance to recommended treatment

regimes in this community?

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3.2 Outcome Variable

The key outcome variable identified is good management outcome. It is defined as a state in which the patient is assessed to be in good glycaemic control (blood glucose level maintained within normal limits

(FBS<_115mg% and / or RBS/PPBS<_150MG%), by investigation done within the last 3 months, the results of which is verified by the investigator) and remains without developing any signs or symptoms of complications of DM.

Good management outcome is the culmination of the series of processes, events and strategies adopted by the patients through the course of the disease, starting from diagnosis. It includes timely diagnosis, good adherence to pharmacological and non-pharmacological management, detecting, reporting and seeking treatment for diabetic complications if any. All these elements can be influenced by a wide range of factors, of which gender will be examined in detail by this study.

Early diagnosis (defined as diagnosis before developing complications) is a component of care that is essential for the management of DM.

3.3 Predictor Variables

These variables can be broadly classified as (A) general (B) diabetes related

and (C) those which contribute to the gender analysis. These were decided,

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based on the literature review and discussions with medical colleagues who

had experience of treating diabetes for many years.

(A) General variables: Basic socio demographic characteristics like: age, sex,

marital status, education status, occupation, type of diet, smoking and

alcohol use. More males were found to have diagnosed their disease earlier

than females, so it is assumed that they are able to take care of the disease

much better.

(B) Disease related variables: Details of nature and circumstances related to

diagnosis, presence of co-morbidities, treatment, diet, exercise and symptoms

of complications.

(C) Gender related variables: Ability for decision making on health related

matters, accessibility of health facilities, ability to meet treatment cost by self,

history of default of treatment, support system in the family to manage the

diabetic condition, history and frequency of hospitalisation due to complications

of DM, perceived ‘caregiver’ role of woman – both by the patient and the family.

3.4 Study setting :

The most difficult phase of the study was to identify a site for the study. A population whose diabetic status is already known was needed. Initially

(during late October 2007 when the topic was just selected) it was thought that patients attending the diabetic clinic or endocrinology OP in medical college can be selected as the study population. But it was pointed out during the discussion with experts in the field that since accessibility is one of the criteria, a hospital based

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study can be biased in the selection process itself. To capture the true picture of inaccessibility, if any, patient should be seen at his / her residence. Getting the reliable details of all diabetic patients in a defined geographic area from a single source at a short notice was the main problem.

We learnt of an extensive study in Varkala ICDS block, Kerala by a Health Research Organization working on community health called Health Action by People. Health Action By People (Henceforth referred to as HAP) is an organisation, which was launched in 1992 with the objectives of research and action in the field of public health. The organisation undertakes studies in urban and rural areas of Trivandrum district, the rural population being the 7 panchayats in Varkala block, Trivandrum district.

There are 2 main streams of studies, namely Prolife (Population

Registry of lifestyle diseases) and PURE (Prospective Urban Rural Epidemiology).

PROLIFE was launched in 2000. All families in the 7 panchayats falling under the jurisdiction of 'Varkala' block have been enrolled in a survey that addresses demographic, socio economic and food consumption issues. All individuals aged 20 years, as on 1st March 2001 have been registered for detailed lifestyle enquiry. Vital events like birth, death, hospitalisations have been recorded.

The PURE study is basically on diabetes, in the urban and rural populations in Trivandrum. The rural component of the study consists of selected

Panchayats in Varkala Block. This study includes the population above 20 years of age. Diabetes detection camps are conducted in these areas to detect and record all 19

old and new diabetes cases. When PROLIFE included all the eligible population in 7

Panchayats, PURE study selected a few wards from some Panchayats for the action, viz., 4 wards from Chemmaruthy Panchayat, one cluster population each from Ottoor and Cherunniyoor panchayats. We sought and obtained permission from the chairperson of HAP, Dr CR Soman, to undertake the study in these selected blocks of Chemmaruthi, Ottoor and Cherunniyoor panchayats.

HAP has a team of dedicated office staff, field workers and trained technicians. They propose to monitor the population on an ongoing process.

The sample frame consisted of the list of diabetic patients available with HAP, detected as part of the PURE study, from the Panchayats of Chemmaruthy and Cherunniyoor. The Panchayats Chemmauthy and Cherunniyoor were selected because; the enumeration and listing of diabetic patients were complete in these 2

Panchayats at the time of data collection.

The age sex profile of Varkala block of Chirayinkil taluk that is more or less co-terminous with the Varkala ICDS block was compared for validation and there were no significant distortions in the age sex patterns between the census profile and that of the PURE study.

VARKALA

This place is situated 51 kilometers north of the district headquarters ,Trivandrum, in Kerala state. The Community development (CD)

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Block, Varkala is constituted with the Varkala town (municipality) and 7 adjoined panchayats namely Cherunniyoor, Chemmaruthy, Ottur, Manambur, Vettoor,

Elakamon and Edava, which come under the Chirayinkeezhu Taluk ( subdistrict ) of

Thiruvananthapuram.

Figure 3.1 Varkala ICDS Block (shaded area) in Trivandrum district, showing the panchayats (Source : HAP)

Varkala Municipality : This is the main town area and the headquarters of the Block. The town has excellent telecommunication facilities, an average-rated water supply system, fire station, several post offices and police station. The town has a government-run hospital in addition to nearly 10 private hospitals and some dental clinics. Varkala is the second most important railway hub in the district of Thiruvanthapuram, after the Trivandrum Central Station. Varkala is an important hub for neighbouring places like Attingal, Kadakkavur, Edava,

Kallambalam , Kappil, Parippally, and Kilimanoor. Varkala is a well-known Tourist destination with a nature cure hospital. Varkala has an average literacy rate of 78%, higher than the national average of 59.5%: male literacy is 77%, and female literacy

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is 79%. 11% of the population is under 6 years of age. Sex ratio of Varkala CD block is 1162, and that in the 0-6 age group is 979 per 1000 males. There are about 23.2% main workers and 6.9% marginal workers in Varkala CD Block. They are mainly employed as cultivators, agricultural laborers and in the household industry. A large proportion of them work outside India, mainly in the Middle East. A general information on Varkala block is given in annexure (table 3.1).

Out of the 7 Panchayats, the study comprises of only 2, they are

Chemmaruthy and Cherunniyoor panchayats. A profile of these two panchayats are provided in the annexure (table nos. 3. 2 and 3.3)

Chemmaruthy panchayat had a literacy rate of 79.5%. Total workers constitute more than a third of the population (34.5%) of which 26.8% are main workers and 7.8% are marginal workers. Cherunniyoor panchayat had a literacy rate of 78%. Total workers constitute more than a third of the population (32.8%) of which 24.8% are main workers and 8% are marginal workers.

The area under the study comes under the rural part of Varkala.

Chemmaruthy does not have coastal area, but part of Cherunniyoor is sea coast. The main source of drinking water is private well and tap water. There are no serious endemic diseases in the area, the only public health threat being outbreaks of diarrhoeal diseases and viral fever. There are PHCs in all the panchayats.

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3.5 Sample size estimation

The total no. of diabetic patients in Chemmaruthi (4 wards) and

Cherunniyoor (1 ward) was 504 (222 males and 282 females). This formed the sample frame for the study.

Since treatment adherence is being studied, with special focus on gender related factors, it is assumed that 52% of the females are adherent to treatment regime49. Making the worst acceptable level as 43% and calculated with

Epi-info StatCalc, the sample size obtained is 96, for one stratum. It is doubled to obtain equal number of male participants to correlate, the sample size is 192, and it is rounded to 200.

3.6 Sample selection procedure :

The List of 504 DM patients in Chemmaruthi and Cherunniyoor

was obtained from HAP and two separate lists for males and females were made.

One hundred patients each were selected from each stratum randomly, after

assigning random number to each patient. Address and phone number of the

selected patients were collected from HAP, and these were used to fix appointment

for personal interviews.

3.7 Design of the Study:

The study was designed as a cross-sectional descriptive analysis. A pre-tested interview schedule was developed incorporating questions required to undertake the gender analysis. It contained eight sections: 1)background socio 23

demographic characteristics 2)personal habits including substance use and diet,

3)diagnosis and co morbidities 4)treatment details 5)controlled diet 6)physical activity 7)complications of DM and 8)questions relating to gender analysis. In all there were 121 questions covering all these eight sections.

To incorporate gender analysis, various frameworks for gender

analysis were considered50. The WHO gender analysis framework51 examines the

gender impact of any disease in terms of the biological and other factors

including gender roles, values, access to and control over resources, and how

these shape the vulnerability, health seeking, access to healthcare, treatment

options, (preventive promotive and curative), discriminations by health

professionals, the outcomes and the consequences.

Informed consent was obtained from the participants before the

interview. All data collection tools were translated into Malayalam, the language

of the local community. Data collection was done through house-visits at the

community level.

3.8 Duration and methods of the study:

Data collection was undertaken between 15 June to 10 September

2008. Data analysis and report preparation were completed in September-October

2008. The staff in the regional office of HAP had been briefed about the nature of

the study and was of immense help in locating the selected participants in the field.

Telephonic appointments were fixed with those accessible by phone, prior to the

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house-visit and field visits were fixed between 9.00 hours to 16.00 hours, six days a

week, excepting Mondays. Undertaking field work on Sundays enabled interviews

with subjects who are working. In all, 200 interviews were completed by the

researcher keeping to a pattern of about 4-5 interviews a day. Each interview in

Malayalam took approximately 30 minutes to complete.

3.9 Data Entry and Analysis:

Data was entered in Microsoft Excel 2007, in a codebook prepared for the purpose. The data entry was done entirely by the principal investigator, and frequent and random cross checks were done regularly to detect any wrong entry and corrective measures adopted. After completion, the data was exported to SPSS for

Windows version 11.5, cleaned and analysed. Simple bi-variate tables and non parametric tests like chi-squares were used to test the strength of association between the outcome variables such as ‘good management outcome of DM and its correlates including gender. For interpretation, p value of less than 0.05 was considered to be significant, and indicated by * in the tables.

3.10 Ethical considerations:

The proposal for the project was submitted to the SCTIMST ethics committee and given approval. Informed consent was obtained from all of the respondents. Participant confidentiality was respected during and after the study. All materials which identify the respondent are kept strictly confidential and will never be made public or will be brought to the public domain. The original data that was analysed did not contain any identifiers but only codes.

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CHAPTER 4 RESULTS

This chapter is divided into 3 sections broadly. The first section provides a description of population. The second section provides a description of diabetes related variables, and variables which contribute to gender analysis and the last section contains gender Analysis

4.1 Socio-Economic And Behavioural Profile Of Study Participants

Two hundred patients of NIDDM – 161 from the 4 wards of

Chemmaruthi and 39 from one ward of Cherunniyoor Panchayat were interviewed.

There were 100 males and 100 females. The demographic profile of this population including age, education, socio economic status, occupation, marital status, tobacco and alcohol use are explained in this section

4.1.1Age: More than 50 percent belonged to 45-60 age group, and there were 20 people belonging to less than 44 years age group suggesting the increasing trends of the disease among young population.

Table 4.1.1Distribution of the study population by age-sex; 2008

Age Male (%) Female (%) Total (%) <_30 0 (0) 1 (1) 1 (0.5) 31-44 11 (11) 9 (9) 20 (10) 45-60 47 (47) 55 (55) 102 (51) 61+ 42 (42) 35 (35) 77 (38.6) Total% 100 (100) 100 (100) 200 (100)

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For the male patients, age ranged between 34 and 85 years, the mean age being 59.21 years. For female patients, youngest was 28 years old, and the oldest was 80 years of age and the mean age was 57.11.

4.1.2 Education: Noticeable difference was seen in the education status between the sexes.

Table 4.1.2 Distribution of the study population by education status and sex; 2008 Education Status Male (%) Female (%) Total (%) Illiterate 0 (0) 13 (13) 13 (6.5) Primary 35 (35) 37 (37) 72 (36) Secondary 54 (54) 49 (49) 103 (56.5) Graduate and above 11 (11) 1 (1) 12 (6) Total % 100 (100) 100 (100) 200 (100)

All the 13 illiterate participants were females. Among the 12 graduates, 11 were males.

4.1.3 Occupation: A majority of the males had some history of working abroad in the middle east. As most of these migrants work in areas around Arabian gulf, this phenomenon is called ‘Gulf migration’, and Varkala is called ‘mini gulf’ with more than one fourth of the men (28 out of 100) just returned from the gulf.

Table 4.1.3(a) Distribution of the study population by occupation and sex; 2008 Occupation Male (%) Female (%) Total (%) Home maker/ Housewife 11(11) 84 (84) 95 (47.5) Private sector 35 (35) 7 (7 ) 42 (21) Government employee 2 (2) 2 (2) 4 (2 ) Others 1 (1) 0 (0) 1 (0.5) Retired 23 (23 ) 7 (7 ) 30 (15) Gulf returned 28 (28 ) 0 (0) 28 (14) Total % 100 (100) 100 (100) 200 (100)

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Many of the males who classified themselves to be homemakers were previously working in Gulf, though for shorter periods not worth mentioning. Others were private sector employees, and only a minor proportion were government employees. 84% of the women were housewives.

For convenience of analysis, the occupation was divided into 3.

Table 4.1.3(b) – Distribution of the study population by major occupation groups and sex; 2008 Male (%) Female (%) Total (%) Chi Square p value Housewife, homemaker 11 (11) 84 (84) 95 (47.5) Pvt sector + govt 38 (38) 9 (9) 47 (23.5) 0.000* employee + others Retired + gulf returned 51 (51) 7 (7) 58 (29) Total 100 (100) 100 (100) 200 (100)

Occupation also showed significant difference between the sexes.

4.1.4 SES: The Socio-economic status (SES) has been classified based on

NFHS-2 criteria, which was based on the assets of the household the patient lived in, and did not consider the personal income.

Table 4.1.4(a) Distribution of the study population by socio-economic status and sex; 2008 SES Male (%) Female (%) Total (%) High 76 (76 ) 61 (61 ) 137 (68.5 ) Average 24 (24 ) 35 (35) 59 (29.5)

Low 0 (0) 4 (4 ) 4 (2) Total% 100 (100) 100 (100) 200 (100)

More than two thirds of the population (68.5%) fall into high SES, a higher proportion being males. There were only 4 participants who fell into the poor category and all of them were females. If the classification considered income too, the difference in the SES between the sexes which is already significant, would have been more

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severe in case of females because many of the women who did live in households which fell into high SES did not have any income of their own and they were totally dependent on others for their disease management and day to day expenses, and many of the households which fell in the high SES would have been come down to average or even lower.

Since the number of ‘low’ category was too less and had no men in that group, SES was regrouped into 2, that is high and average and low combined.

Table 4.1.4(b) Distribution of the study population by broad SES categories and sex-2008 Chi Square Male (%) Female (%) Total (%) p value High SES 76(76) 61(61) 137 (68.5) 0.016* Average + low 24 (24) 39 (39) 63 (31.5)

Total 100 (100) 100 (100) 200(100)

There was a statistically strong association between SES and sex with high proportion of men belonging to higher SES group.

4.1.5 Marital Status: Widowed and separated women comprised 34% of the total female patients, while 95% of males were currently married. The rest were 3 widowers, and 2 unmarried.

Table 4.1.5 (a) Distribution of the study population by marital status and sex-2008 Marital Status Male (%) Female (%) Total (%) Never married 2 (2) 0 (0) 2 (1) Currently married 95 (95) 66 (66) 161 (80.5) Widow/widower 3 (3) 29 (29) 32 (16) Divorced/separated 0(0) 5 (5) 5 (2.5) Total 100 (100) 100 (100) 200 (100)

Out of 34 widowed/separated women 8 were staying alone in their house without anyone to help or support.

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Table 4.1.5(b) Distribution of the study population by broad MS categories and sex-2008 Chi Square Male (%) Female (%) Total (%) p value

Currently Married 95 (95) 66 (66) 161 (80.5) 0.000* Not Currently Married 5 (5) 34 (34) 39 (19.5) Total 100 (100) 100 (100) 200 (100)

When seen as two groups of ‘currently married’ and ‘currently not married’, a statistically significant association between marital status and sex was seen, with more men belonging to the currently married and high percentage of women in the currently not married category.

4.1.6 Tobacco and alcohol use: these were found to be more or less of equal prevalence in the current use- 19 and 17 percent respectively. The difference between men and women, in both tobacco and alcohol use were found to be significant, obviously.

Table 4.1.6 Distribution of the study population by substance use (current) and sex-2008 Tobacco Male (%) Female (%) Total (%)

Only Smoking(current) 30 (30) 0 30 (15%)

Only Smokeless(current) NIL 4 (4) 4 (2)

Both 36 (36) NIL 36 (18)

Non users 64(64) 96 (96) 160 (80)

Total 100 (100) 100 (100) 200 (100)

Current alcohol users 35 (35) NIL 35 (17.5)

Total 100 (100) 100 (100) 200 (100)

Four women reported the use of smokeless tobacco, they were of education up to 4th grade, and belonged to the average and poor SES. And they were of 45,

70 and 78 years of age. Usually there is no stigma attached to older women using tobacco.

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That may be the reason why they disclosed it. It is possible that reporting of tobacco use among women is low but we have no means of determining the same.

4.2 Diabetes Related Variables and Variables Which Contribute To

Gender Analysis.

4.2.1 (a) Mode of diagnosis: mode of diagnosis which is a major determinant of treatment outcome because early diagnosis is one of the factors comprising the good diabetes management, also showed significant difference between males and females.

Table 4.2.1 Distribution of study population by modes of diagnosis and co morbidities and sex, 2008 Male (%) Female (%) Total (%) χ2 p value Tested because you wanted to 43 (43) 25 (25%) 68 (34) know Tested when Doctor advised, when 46 (46) 49 (49) 95 (47.5) Discoverin visited for some other purpose g diabetic Investigated for non-healing ulcer 11 (11) 13 (13) 24 (12) status or frequent specs change Tested after developing any other 0 (0) 13 (13) 13 (6.5) diabetic complication Site of Government hospital 7 (7) 15 (15) 22 (11) 0.056* diagnosis Private Hospital/ Laboratory 93 (93) 85 (85) 178 (89) Hypertension 55 (55) 58 (58) 113 (56.5) 0.388 Experience Cardiac Problems 27 (27) 12 (12) 39 (19.5) 0.006* of co- morbidities Elevated Cholesterol 38 (38) 46 (46) 84 (42) 0.335 Neurologic Problems 11 (11) 10 (10) 21 (10.5) 0.586 Total 100 (100) 100 (100) 200 (100)

Early diagnosis before developing any significant symptom or complication, first done as a part of routine health check up was found to be more among males. Out of 68 participants who thus got diagnosed, 43 were males. Among the 24 people who got diagnosed after developing impaired vision or diabetic ulcer,

13 were females. Those who got diagnosed after developing other complications

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(which included recurrent skin infections, urinary infection, chest infection, recurrent syncope, fainting attacks etc) were all females (13 nos).

4.2.1 (b) Place of diagnosis: More females than males depended on government facilities, may be because of financial reasons, though altogether most of the patients- 89 percent - got diagnosed at private facilities. Significant difference was found in the place of diagnosis too, as among the 22 people who got diagnosed at government hospital, 15 were females. Surprisingly 7 of them were from the rich

SES, may be suggestive of the poor financial freedom and low accessibility of health facilities of these women, though they hail from the high SES category.

4.2.1 (c) Co morbidities of hypertension and elevated serum cholesterol were more in females while cardiac and neurological problems were found to be more in male patients. The ‘metabolic syndrome’ consists of Diabetes, Hypertension and High cholesterol. Accordingly females can be considered as being at a higher risk than males because co morbidities of hypertension and high cholesterol are seen more among them, though the difference was not found to be statistically significant. The mean age of men and women with hypertension alone as co morbidity was 62 and 60 respectively, and high cholesterol was 60 and 57 respectively. Those who had hypertension and high cholesterol along with diabetes had mean age 62 for men and 60 for women. It suggests that women are getting affected at a younger age than men.

4.2.2 Details of Treatment

There was no significant difference at the place of treatment, distance to the health facility, maintaining the random blood sugar (RBS) at a normal level, and keeping the treatment records safe and accessible, proportion that got advice regarding 32

the diet regimes and history of hypoglycaemic attacks, between the sexes. Majority

(78%) of men and women depended on private health facilities for the diabetes

management.

Table 4.2.2 Distribution of study population by treatment options and sex, 2008

Male (%) Female (%) Total (%) Chi Square p value Govt hosp 18 (18) 19 (19) 37 (18.5) Pvt hosp 78 (78) 78 (78 ) 156 (78 ) 0.670 Not treating now 1 ( 1) 1 (1 ) 2 (1 ) Treatment Place Govt/pvt acc to 1 (1 ) 2 (2 ) 3 (1.5 ) convenience Others 2 (2 ) 0 (0 ) 2 (1 ) Him/herself 80 (80 ) 22 (22 ) 102 (51 ) Who pays mostly for D/s Spouse 3 ( 3) 28 (28 ) 31 (15.5 ) NA Management Children 17 ( 17) 48 (48 ) 65 (32.5 ) Others 0 ( 0) 2 (2 ) 2(1 ) Those who know the names of 50 ( 50) 23 (23 ) 73 (36.5 ) medicines they are on 0.000* Walking distance 9 (9 ) 14 (14 ) 23 (11.5 ) How far is the health facility? < 10 km 67 (67 ) 59 (59 ) 126 (68 ) 0.412 >10 km 24 (24 ) 27 (27 ) 51 (25.5 ) As the physician advised 44 (44 ) 40 (40 ) 84 (42 ) When get time 10 (10 ) 9 (9 ) 19 (9.5 ) 0.016* How often do you visit the facility? When medicines are over 24 (24 ) 11 (11 ) 35 (17.5 ) When feel sick 21 (21 ) 33 (33 ) 54 (27 ) Others 1 (1 ) 7 (7 ) 8 (4 ) Patients who are advised diabetic 82 (82 ) 78 (78 ) 160 (80 ) diet 0.296 Those who follow it(out of 80) 52 (63.4 ) 51 (65.3 ) 103 (64.3 ) 0.462 Patients who are advised Exercise 80 (80 ) 70 (70 ) 150 (75 ) regimes 0.071 Those who follow it(out of 75) 36 (45 ) 22 (31.4 ) 58 (38.6 ) 0.062 < 30 days 52 (52 ) 55 (55 ) 107 (53.5 ) 1m -3 m 43 (43 ) 33 (33 ) 76 (38 ) When last checked RBS 3-6 months 3 (3 ) 9 (9 ) 12 (6 ) >6 months 2 (2 ) 3 (3 ) 5 (2.5 ) Normal 42 (42 ) 32 (32 ) 74 (37 ) NA Result Not normal 58 (58 ) 66 (66 ) 124 (62 ) Don’t know 0 (0 ) 2 (2 ) 2 (1 ) < 30 days 28 (28 ) 29 (29 ) 57 (28.5 ) 1m -3 m 25 (25 ) 15 (15 ) 40 (20 ) When last checked U.Sugar 3-6 months 1 (1 ) 4 (4 ) 5 (2.5 ) >6 months 1 (1 ) 1 (1 ) 2 (1 ) Don’t remember 45 (45 ) 51 (51 ) 96 (48 ) Normal 23 (23 ) 21 (21 ) 44 (22 ) Result Not normal 31 (31 ) 24 (24 ) 55 (27.5 ) Don’t know 46 (46 ) 55 (55 ) 101 (50.5 ) Those who said they keep 84 (84 ) 83 (83 ) 167 (83.5 ) them safe and accessible 0.500 Treatment records Those verified 74 (88 ) 67 (80 ) 141 (84 ) (out of 167) Those who had another diabetic 23 (23 ) 28 (28 ) 51 (25.5 ) patient in the same household Yes 17 (17 ) 23 (23 ) 40 (20 ) 0.299 Those with history of hypoglycaemic No 75 (75 ) 65 (65 ) 140 (70 ) attacks Don’t know 8 (8 ) 12 (12 ) 20 (10 ) TOTAL 100 (100 ) 100 (100 ) 200 (100 )

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Significant difference was found in the frequency of visits to the facility, awareness of the medicines they are on, treatment expenses borne and those who are advised and following the exercise regimes as part of the disease management.

Eighty percent of male patients were able to pay for the treatment themselves, of which 61 belonged to the high and 19 to the average SES. Only 22% of females were able to pay for their own treatment and 11 of them were from the high, 9 from poor and 2 from the low SES. The rest depended on spouse (28%) and kids (48%) for the financial support. The women who depended on children were mostly widows and divorced (25%) and others were currently married (23%).

4.2.3 Non medical management of diabetes

This consisting of the diet and exercise elements were seen to be somewhat ignored. Though most were advised on the diet and exercise requirements and claimed to be following them, when asked in detail, a very small proportion were actually following the recommended diet and exercise regimes. WHO recommends 8 servings of vegetables and fruits daily, for the diet to be called ideal, and 30 minutes of moderate intensity exercise is what is needed minimum. There too, females were

16 and 9, among the 46 and 25 patients getting adequate exercise and following recommended dietary pattern respectively.

4.2.3 (a) Diet: Significant difference was shown between the numbers of males and females who got adequate amount of green leafy vegetables which was recommended as

34

ideal. Inability to restrict favourite food items was the common cause which was stated by both men and women, for not following strict diet regimes.

Table 4.2.3(a) Distribution of study population by diet component and sex, 2008 Male ( %) Female(%) Total (% ) Chi Square p value Green Leafy Those taking regularly 61 (61) 52 (52 ) 113 (56.5 ) Vegetables In adequate amount 19 (31 ) 6 ( 11.5) 25 (22 ) (out of 113) 0.010* Other Those taking regularly 92 (92) 83 (83 ) 175 (87.5 ) Vegetables In adequate amount 30 ( 32.6) 18 ( 21.6) 48 (27.4 ) (out of 175) Fruits Those taking regularly 68 (68 ) 58 ( 58) 126 ( 63) In adequate amount 31 ( 45.6) 24 (41.3 ) 55 (43.6 ) (out of 126) 0.384 Total 100 (100 ) 100 (100 ) 200 (100 )

When asked about the reasons for not following exercise, many of the men said medical reasons like cardiac problems, COPD and joint pains and some said they are lazy and didn’t think exercise was necessary. But the women said they cannot find time to do exercise because of too much work at home. And some said it is difficult to go out early morning or late evening alone, without anyone to accompany.

About not following diet restrictions, majority said they can not restrict cereals and tubers like tapioca, which are their favourite foods. One male patient said since his wife expired, no one to monitor his diabetic diet, so he stopped maintaining diet regimes. While 58 percent of men said that they get special diabetic diet cooked at home, only 39percent of females enjoyed such a privilege. The difference was significant. In most households, food is cooked by the women, and when she herself becomes the patient, cooking something extra becomes too much a

35

burden for her and she tries to adjust with whatever she cooks for the rest of the family, consciously or unconsciously ignoring her special dietary needs.

4.2.3 (b) Exercise: About exercise, there was a significant difference between the number of male and female patients who received the recommended amount of exercise. Altogether, only 46 (23%) followed adequate exercise regimes, among whom there were only 16 females.

Table 4.2.3(b) Distribution of study population by exercise component and sex, 2008

Male (%) Female Total (%) χ2p value (%)

Those who get at least 30 minutes 30 (30) 16 (16) 46 (23) 0.006* of moderate intensity exercise x 5 days per week

Total 100 (100%) 100 (100%) 200 (100%)

Male patients mostly had medical reasons for not following exercise like Asthma, Arthritis, Cardiac and neurologic problems. Some of them were engaged in sedentary occupations which did not permit any exercise. Women reported too much household works and lack of time to spare, and being unable to go out alone in the early hours as the reasons. Some women reported that they were too obese to do any exercise. Some reported that they were too old.

4.2.4 Probable manifestations of diabetic complications

In all kinds of complication signs, more females are affected than males. But the proportion who sought care and who got immediate care (ie within 30 days of onset of symptoms) are more among male patients. When cross tabulated

36

with mode of diagnosis, frequency of visits to the health facility, SES, marital status and who bears the treatment expenses, we found that, those who were from the high

SES, currently married status, who pay themselves for their treatment, who got diagnosed early and those who visit the facility according to the provider’s advise were found to be more among those who got immediate treatment for complications, in case they developed.

Table 4.2.4 Distribution of study population with experience of probable symptoms of diabetic complications, the treatment sought and the delay incurred in seeking treatment for the same, by sex, 2008 Male (%) Female (%) Total (%) Type of Those Those who could Those Those who could Those Those who Complication who who seek care in who who seek care who who could experien sought < 30 days experien sought in < 30 experienc sought seek ced care (out of those ced care days ed care care in (out of those who sought (out of (out of those (out of < 30 who care) those who who sought those who days (out experienced) experience care) experience of those d) d) who sought care) Signs of 54 40 20 62 37 9 116 77 29 Retinopathy (54) (74 ) (50 ) ( 62) ( 59.6) (24.3 ) (58 ) ( 66.3) (37.6 ) Signs of 24 18 6 18 14 3 42 32 9 Vasculopathy (24 ) (75) (33 ) (18 ) ( 77) (21.4 ) (21 ) ( 76) (28 ) Signs of 47 28 9 66 38 7 113 66 16 Neuropathy (47 ) (60 ) (32 ) (66 ) (57.5 ) ( 18.4) (56.5 ) (58.4 ) ( 24.2) Signs of 17 12 7 26 8 3 43 20 10 Nephropathy (17 ) ( 70.5) ( 58) (26 ) (30.7 ) (37.5 ) (21.5 ) ( 46.5) (50 ) Total 100 (100 ) 100 (100 ) 200 ( 100)

In all kinds of complication signs, more women were affected than men. But the proportion who sought care and who got immediate care (that is, within

30 days of onset of symptoms) are more among men. When cross checked with mode of diagnosis, frequency of visits to the health facility, SES, marital status and who bears the treatment expenses, the following findings were got.

Those who were from the high SES, currently married status, who pay themselves for their treatment, who got diagnosed early and those who visit the

37

facility according to the provider’s advise were found to be more among those who got immediate treatment for complications, in case they developed.

4.2.5 Gender Analysis of medical and non medical management of DM:

Significant differences were observed all through the gender analysis of the disease management.

Table 4.2.5 Distribution of study population by identified gendered factors and sex, 2008 Male (%) Female Total (%) χ2p (%) value Those who could take own 100 (100 ) 75 (75 ) 175 (87.5 ) NA decisions in health seeking Those who thought health facilities 75 (75 ) 45 (45 ) 120 (60 ) are accessible in all ways 0.000* Who pays for the disease Self 81 (81) 23 (23 ) 104 (52 ) management? Spouse 1 ( 1) 28 ( 28) 29 (14.5 ) 0.000* Children 18 ( 18) 47 ( 47) 65 ( 32.5) Default due to Lack of money 19 ( 19) 31 (31 ) 50 (25 ) None to accompany 1 ( 1) 6 (6 ) 7 (3.5 ) 0.022* No Default 70 ( 70) 52 (52 ) 122 (61 ) Diet monitored in 93 (93 ) 72 (72 ) 165 (82.5 ) 0.000* by Self 15 (16 ) 50 ( 69) 65 (39.4) (out of 165) Spouse 73 ( 78.5) 5 (7) 78 (47.3 ) 0.000* Children 4 (4.3) 17 (23.6 ) 21 ( 12.7) Medicine intake monitored in 98 ( 98) 76 (76 ) 174 (87 ) 0.000* by Self 58 (59 ) 48 (63) 106 (61) (out of 174) Spouse 32 (32.6) 11 ( 14.5) 43 (24.7) 0.006* Children 8 (8.2 ) 16 (21) 24 ( 13.7) Special (diabetic)food cooked for 58 ( 58) 39 ( 39) 97 (48.5 ) 0.005* Those who thinks exercise is a 56 (56 ) 35 (35 ) 91 ( 45.5) main part of DM Mgt 0.002* Those who felt they had good 89 (89 ) 47 (47 ) 136 (68 ) support system in the family- 0.000* Supported mainly by Self 6 ( 6.7) 11 (23.4) 17 (12.5) (out of 136) Spouse 77 (86.5) 15 (32 ) 92 (67.6 ) 0.000* Children 4 ( 4.5) 22 (47) 26 (19) Those who felt they get support to 94 (94 ) 62 ( 62) 156 (78 ) manage DM from their family 0.000* support mainly by Self 25 (26.6 ) 23 (37 ) 48 (30.8) (out of 156) Spouse 59 (62.7 ) 15 (24.2) 74 (47.4) 0.000* Children 8 (8.5 ) 24 (38.7 ) 32 (20.5 ) Those who had h/o hospitalisation 24 (24 ) 31 ( 31) 55 ( 27.5) 0.213 due to DM complications Admitted once 18 (75) 18 (58) 36 (65) 0.153

More than once 6 (25 ) 13 (42 ) 19 (35) (out of 55) Those who are diagnosed to be 33 (33 ) 44 ( 44) 77 (38.5 ) having complications of DM 0.183 Rate the attention given to your Most important 71 (71 ) 22 ( 22) 93 ( 46.5) health in your family Equally important 29 (29 ) 41 ( 41) 70 (35 ) NA Least important 0 ( 0) 37 ( 37) 37 (18.5 ) Whose health is most important for Your own 40 ( 40) 21 (21 ) 61 ( 30.5) you in your family Spouse’s 28 (28 ) 30 ( 30) 58 (29 ) 0.001* Children’s 12 ( 12) 35 (35 ) 47 (23.5 ) Total 100 (100) 100 (100) 200 (100) 38

Decision making on health seeking – all men and 75percent of women claimed to be able to take decisions on health seeking, while 75percent of men and only 45percent of women thought the health facilities were accessible to them in every way.

Significant difference was observed in the expenses borne-

81percent of men had the financial freedom to spend for their treatment but women were dependant on spouse(28%) and children(47%).

Obviously, more females – 31percent- had to default treatment due to lack of money. Unemployment may be a reason for this, as 84percent of the women are housewives. Among men, 19percent had the history of defaulting.

Among those who never defaulted treatment, men were more in number and the difference was significant. Majority were from the high SES, males and females.

Marital status found to be a crucial factor because currently married men and women were majority among those who never defaulted. But among women, of 52 never defaulters 16 were widows (where there are only 29 widows totally). This may be suggesting that though widowhood is a most unfortunate state in the cultural context, somehow the woman finds more time for herself – to attend better to the treatment protocols, with the help of the children, as evident from the table. Women non- defaulters were found more among those who get assistance from the children, than those pay on their own or get paid by the spouse. But among men, those who pay for themselves were more among the never defaulters. Though 78 percent of both men and women seek treatment in private facilities, it affects the compliance of women more because most of them (84%) are unemployed and financially dependant. 39

A favourable atmosphere and support system to manage the disease at home was assessed by the monitoring of medicine intake and attention given to the special dietary requirements and support to do exercise. Women were found to be less advantaged in all these areas. The difference is significant. Among the currently married,

66percent of the men got support from their spouses to manage the disease, but only

35percent of women got the support from the spouse. This was reflected in the higher prevalence of diagnosed complications, and history of hospitalisation on more than one occasions due to advanced diabetic status being more prevalent in women.

The aspects of gender norms, roles and values were assessed by questions regarding the perception of attention given to their health in their own household, and the importance given by the patient, to the health of his/her family members. None of the females said that their health got the highest preference at home, while 71percent of the men did so. 21percent of women and 40percent of men gave the highest preference to their own health. Proportion of men and women who considered their spouse’s health more important than their own, was reversed across the high and average SES. While 26percent of men and 34percent women in the high

SES gave more importance to their spouse’s health, in the average SES it was reverse

– 33 percent and 25 percent respectively. The difference was significant.

4.3 Gender Analysis

What had been described so far were the responses from the patients to the queries regarding the disease management, and some questions helping to obtain information on the gender perspectives of DM management.

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From the initial descriptive statistics we have seen that significant differences exist between men and women in the basic sociodemographic as well as the disease related factors. The information obtained from the interviews on various sociodemographic variables and disease related factors are examined for the interlinkages they have and the interactions with the patient’s gender roles and norms and the implications of these on the final management outcome is examined in this section. In short, how gendered are the sex differences already found out? Before going into the gender analysis proper, some important variables have to be introduced, some of them were present in the original questionnaire itself and some were newly created. All these are crucial determinants of DM management, being protective and risk factors which play important role in moulding the outcome variable, that is the good outcome of the disease management.

1. Socioeconomic status- In the study, SES was calculated based on the NFHS-2

criteria- the standard of living index (SLI) is calculated based on the

household assets and based on the scores SES is devided into high, average

and Low. In the field, it was felt to be a bit unreliable since in kerala, even

those people who can be called poor, will be having a pukka house, and a

flush toilet, and all the necessary articles which are needed to add SLI scores

in the NFHS criteria. And finally when the analysis was done, there were

only 4 participants in the low SES, and all those were women. So for the

convenience of analysis SES is clubbed into 2 categories- high and average

and low together. High SES is considered to be protective.

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2. Marital status : the original 4 strata were clubbed into 2 – currently married

and not currently married, and marital status is assumed to be protective.

3. Time of diagnosis- the responses obtained about the circumstances that lead

to diagnosis were clubbed into 2 variables namely diagnosis before

complication and after complication, of which diagnosis before developing

complication ( early diagnosis) is considered to be protective.

4. Visit to the facility: those who visit the facility according to the physician’s

advise and as and when the medicines are over are classified under regular

visitors and all others under ‘no regular visit’ group. Regular visit is protective.

5. Defaulting medicines: those who never default the medicine intake, and those

who default due to various reasons are separated. ‘No defaulting’ is a

protective factor.

6. Receiving required intake of vegetables in the daily diet – Those who take 4

or more servings of vegetables and those who don’t, were grouped. Vegetable

intake is protective.

7. Receiving adequate exercise – 30 min or more of moderate physical activity

atleast 5 days a week was essential. Those who get it are considered to be

protected and others not.

8. Maintenance of good glycaemic control: Maintaining the blood sugar level

under normal limits, by investigations done in the past 3 months, and the

results seen and verified by the PI is considered to be a protective variable.

9. Prevention of complications: those who don’t show any signs or symptoms of

DM complications are considered as protected.

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10. Variables 4 and 5 (visit to the facility and defaulting medicines) are components of

“good pharmacological management” and it is considered as another variable.

11. The variables 8 and 9 (good glycaemic control and prevention of

complications) are clubbed to form the final outcome variable ie the “GOOD

MANAGEMENT OUTCOME OF DM” since these are the end results of the

wide spectrum of events ranging from the diagnosis and pharmac and non-

pharmac modes of management, the awareness of patient and the ability to

take decision and seek care in need.

12. Sex of the patient: since this study focuses on the gender impacts on disease

management, all the variables are examined in relation to the sex of the patient.

Based on the literature review, being female is a risk which compromises the

individual in many ways, with regard to the disease management. So for the

purpose of analysis, male sex is considered as protective.

Disease related variables are cross tabulated with both men and women, who are stratified into 4

1. High SES / Average+Low SES

2. Currently married/ Not currently married

And the results were analysed.

SES and marital status from the general profile are taken as two criteria on which the patients are stratified and the disease management outcome analysed. From the initial data it is evident that high socioeconomic status and currently married status act protective to the women since majority of them are unemployed and dependant financially on their spouses and other family members.

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Majority of the currently not married, unemployed, illiterate and poor people are women. All aspects of disease care are dependent on the accessibility which in turn is determined by the financial freedom and the support system the patient has, hence these two factors that are co-variates, these have been selected for analysis in greater detail.

4.3.1 Stratified analysis on SES and MS

Now the four strata namely high SES, average + low SES, currently married and currently not married were taken separately to see the individual protective / hazardous effects of socio economic status and marital status on disease management protocols and outcome. Bivariate analysis was done- Chi- square significance and odds ratio of each risk factor was calculated. The results are described. Please refer tables 4.3.1(a),(b),(c) and (d) In annexure.

Early Diagnosis, being a crucial factor determining the treatment outcome of DM shows significant difference between men and women.

By the term early diagnosis it is meant that patient gets his/her blood sugar checked as part of routine health check up, either at own will to know the diabetic status or following the advice of a health provider when he visits the provider for some other purpose. Thus the patient gets diagnosed at an early stage where there are no obvious symptoms, or manifestations of diabetic complications.

Men and women among those who got diagnosed early were mostly married and from high SES, and SES was found to be protective though the

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difference was not statistically significant in High SES. Financial and family support creates a favourable atmosphere to get timely care and early diagnosis. All the men said that they have the decision making capacity in the health seeking matters, and this too renders them capable of getting their diabetic status diagnosed at an early stage.

Education plays an important role. It makes the individual about the possibility of getting affected by the disease and the need of getting the necessary investigations done. Among the total 13 graduates, 12 were able to diagnose the disease early. It group includes one woman, the only graduate in the sample.

Marital Status: This can be observed to play a very complex role in case of disease diagnosis. In a family, the man is considered to be the breadwinner, and his health is counted as the most important because he has the responsibility of bearing the expenses for the whole family. So, every spell of ill health or each mild symptom faced by the man is subjected to investigation and it subsequently leads to early diagnosis of diabetes. Whereas in case of women, the role is that of the caretaker of the whole family. Confined to the domestic atmosphere, the woman holds the responsibility of taking care of the men, children and elderly in the family.

As a result, her own health problems or health needs take a lower position in the priority order, and subsequently get overlooked or neglected. This can be the explanation of the lower number of women getting early diagnosis. Low educational status and socio economic status and lack of income of one’s own may exacerbate this situation by making the women dependant on the earning members of the family, mostly men, for the investigation / management needs.

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Management

Pharmacological management is highly dependent on the financial freedom of the individual. It naturally compromises the woman from taking the treatment without default which requires visit to the facility either as advised by the provider or as and when the medicines are over. This reflects the decision-making power, accessibility of services by the patients and the gender roles of the individual that is assigned by himself/herself or the family or the society.

As in the case of diagnosis, pharmacological management also closely reflects the decision making power, accessibility of facilities for various reasons and the different gender roles and norms of the individual. Majority of women (84%) are unemployed and depend on private facilities (78%) for management. So chances of defaulting treatment are more among women.

When the components of good pharmacological management are considered separately, we can see that High SES acts as a protective measure and currently married status is an adverse factor for women. Women from High SES are able to visit the facility regularly but the medicine intake is defaulted more often than men due to some reason. It is assumed that getting involved in household chores may tend them to forget or miss the doses more often, than currently not married women.

Non Pharmacological management is one area which indicates the sharp gender disparity in diabetes management. It demands special attention on patient’s special dietary needs, allowing time and convenience for physical exercise and adjustment of other members of the family accordingly. 46

Diet

Number of women who get adequate amount of vegetables is found to be very low. More men are from the high SES and all the men are currently married.

Fish and tapioca are the integral parts and regular ingredient of the daily diet in Varkala. If a diabetic person has to follow a recommended diet, he/she has to stop tapioca and introduce more green leafy vegetables in the diet. Inability to restrict favourite food items was the common cause which was stated by both men and women, for not following strict diet regimes. While 58percent of men said that they get special diabetic diet cooked at home, only 39percent of women enjoyed such a privilege. The difference was significant.

In case of men, the explanations for not following the diet restrictions were, “it is difficult to stop eating tapioca/ reduce the rice and non- vegetarian food intake where as women expressed the difficulty of cooking something extra for themselves, because the other members of the family were not willing to adjust to the vegetable diet and they needed the regular diet. Some women said vegetables are too costly to include in the daily diet. One widower said when his wife was alive he could maintain a diet regime but not now as there is no one to take care.

Gender roles and norms can be discerned by examining the stratified analysis. Significant difference is seen between men and women who get 47

adequate diabetic diet within the high SES, but not so in average+low SES. Same in the case of exercise where SES does not exert any protective effect on women. This indicates the vulnerability of women in decision making and getting adequate support for maintaining the DM despite being sound financially.

Marital status shows surprising influence in the diet component. All the currently not married men (even though very few in number) reported not getting adequate diabetic diet. This shows how rigid the gender roles are, that designates cooking the right kind of food for man as the woman’s task, and in the absence of a woman, men are unable to maintain the required diet regime. Cooking food is not considered to be a ‘manly’ work and the men who are currently not married, are on an unrestricted diet. The currently married group too shows a significant difference between men and women in getting required diet. In most households, food is cooked by the women, and when she herself becomes the patient, cooking something extra becomes too much a burden for her and she may avoid preparing a special diet for herself.

Exercise

This is an area where the difference between men and women was found most drastic, both in the numbers who got the recommended exercise and in the underlying causes which lead to compliance/ non compliance. The proportion of men and women who got the recommended amount of physical activity was 37 and

20 respectively and their SES and marital status were as shown in the table.

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Married status and high SES are not protective factors for women.

One reason is, married women can not find time for doing exercise ( explained in the table of reasons for not following exercise regimes). Another factor is that women from high SES re mostly confined at home, while those from lower SES do some kind of physical activity like manual labour, going to market to sell agricultural products, graze cattle etc.

There was a noticeable difference even in the awareness of men and women, about the role of exercise in disease management. More men than women were aware that exercise is part of DM management, and the explanation obtained from men ranged from ‘exercise is good for health’ to clear and to-the-point answers like ‘more calories burnt, more energy spent and blood glucose brought down’. No woman could give a satisfactory response with respect to this question.

The mode of physical activity also differed- most men had cycling to/from the work place daily, some others used to walk every morning or evening just for getting exercise. In case of women, the exercise was mostly as part of their work as such, going to fish/ vegetable market daily by walk, or grazing the cattle. A washerwoman walked most of the daytime as part of her work. Very few women were found to be doing exercise, just for the sake of it. The reasons stated for not following the required exercise regime were different between men and women.

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Table 4.3.2 Reasons stated by men and women for not following the prescribed exercise regimes, in the order of frequency, the responses reflecting the gender roles and norms

Reasons for not Males Females following exercise regimes 1. Lazy. 1.No time to spare after household works Most frequent 2. medical reasons – 2. No one to accompany, to go out in the early Asthma,Arthritis,Heart diseases morning or evening hours 1.Never thought it is important 1.medical reasons – CAD, COPD, OA Less frequent 2. occupation is sedentary 2. tiredness, obesity 1.Tiredness disabilities Least frequent 2.disabilities No one to accompany, to go out 1.Didn’t know it is important Rare 2. Lazy.

No time to spare after household Occupation is sedentary Never works

Male patients mostly had medical reasons for not following exercise like COPD, OA, Cardiac and neurologic problems. Some of them were engaged in sedentary occupations which did not permit any exercise. Females had too much household works and lack of time to spare, and being unable to go out alone in the early hours as the reasons. Some females were too obese to do any exercise. Some were too old.

Good Management outcome: Good glycaemic control – the component of management outcome was found to be influenced by SES. Those from high SES did not show significant difference in maintaining the blood sugar level but in the lower SES group the difference was significant. In all the 4 strata, women are found to be at a higher risk of having a bad management outcome. The association was found to be stronger in the average and low SES, and the currently not married strata. Clearly, management of DM is mediated by SES for men and women for better consequences, but currently married status does not have the same protective effects for women as it does for men.

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Summarisation of the findings in a gender analysis framework Table 4.3.3.GENDER ANALYSIS OF DIABETES – The impact of different characteristics of gender on management of Diabetes mellitus in men and women, in the study population

In Relation to Are there sex differences in How do biological How do the different roles and How do gender norms and values affect men and women’s How do access to and control over resources Diabetes differences between activities of men and women affect affect men and women’s men and women their influence their Vulnerability Significant difference in 84% of women housewives, dependant 1. Attention given to own health by family members was rated 1. 81 % of men and 23% of women are able to pay diagnosis on other family members ‘least’ by 0 men and 37 women- significant difference for the healthcare expenses by themselves. This 2. 40% men and 21% women considered their own health as significant difference reflects in all the subsequent most important to them – significant difference aspects of DM management. Health seeking Women are more in number Least consideration given to women’s health hampers health behaviour than men among who got ,, seeking in the right time ,, diagnosed at government facilities Ability to access Majority (75%) of men High rate of unemployment and financial Above reason make the women restrict the visits to facility to financial dependency on others hamper women’s health services reported that facilities are dependency on others make the facilities only on unavoidable situations accessibility to services accessible to them, when only less accessible to women. 45% of women felt so. Preventive and Awareness of the role and 1.Number of those who get special 1.Significant difference between numbers of men and women 1.Around 80% of women don’t have access to and treatment options, necessity of exercise as part of diabetic food cooked at home , and diet who got family support to manage DM 2.Number of men and control on resources- they depend on their spouses responses to DM management differs monitored by spouse differ significantly women who got their spouses support to manage DM is and children for treatment expenses treatment and significantly between men and between men and women significantly different 2. H/o default is significantly more among women rehabilitation women- more men are aware 2. None of the currently unmarried men are getting prescribed diabetic diet. Experience with Number of men and women 1. Number of women who visit facilities Reasons for defaulting exercise regimes differ between men More women default treatment than men, because Health service and who knows the names of the regularly are significantly less than men. and women. Men say laziness and medical reasons are the of unavailability of medicines in govt hospitals, and health providers medicines they are on, are excuses while women cannot spare time after household no one to accompany different significantly chores Outcome of health Good pharmacological Most families, men are the earning Less value assigned to women’s health in turn lead to Glycemic control shows significant difference problem- e.g.- management outcome differ members and women bear the caretaker neglecting the regular intake of medicines, hence the difference between men and women in Avg+Low SES - recovery, disability, significantly between men and role, thereby fixing the health priorities in outcome. death women in both SE strata. accordingly Consequences Late diagnosis, poor Lower educational, occupation profile Norms and values which restrict the woman’s mobility –result Unemployment – no income – no access on / (economic & social, management of the disease – leading to bad socio economic in an adverse health condition for women due to their inability control over resources – low self esteem- low value including attitudinal) higher level of morbidity – consequences – economic dependency to undertake physical exercises as mandated for management for self health – result in not prioritising own health less number of productive on male members of the family for the of DM for women and also dependence on children and days – bad economic women others for pharmacological management – consequences for women therefore delayed treatment seeking for complications of DM 51

SUMMARY OF THE GENDER ANALYSIS FRAMEWORK

MEN WOMEN

Role-Breadwinner Role- Caregiver Value-Higher Value- Lower

Frequency of Frequency of investigation & investigation & Chances of diagnosis Chances of higher EARLY EARLY diagnosis DIAGNOSIS DIAGNOSIS lower

X2p= Access to and Unemployed control over 0.005 No Access on resources resources

Decision making No decision making power; More health GOOD PHARMAC GOOD PHARMAC less health seeking MGT MGT seeking

X2p= 0.005 Higher value Lower value More frequency of Less frequency of visits to facility. visits to facility. More access to Less access to resources resources Less default. GOOD NON- GOOD NON- More default. PHARMAC MGT PHARMAC MGT

Lower value Higher value More 2 care. X p= 0.006 Self neglect. Married status protective in diet Gendered role of needs. cooking food.

More mobility- more Restricted mobility hampers exercise exercise. GOOD MANAGEMENT OUTCOME

X2p= 0.047

Note: Favourable factors are indicated by Green arrows and Adverse factors by Red arrows. 52

CHAPTER 5 DISCUSSION

This chapter summarises the findings of the study drawn from the analysis, results of the key research questions, explore the strengths and weaknesses of the study and suggests policy recommendations that may be relevant.

5.1 Summary

Management outcome of the study population- assessed by the criteria of the patient being in a state where his/her blood glucose is maintained at the optimal levels and there are no symptoms of any complications of diabetes mellitus, was 23.5 percent (29 percent of men and 18 percent of women),with a significant difference between men and women (chi square p value 0.047 and OR =1.330).

As it is known, the good management outcome of diabetes mellitus is a result of a series of components such as early diagnosis, regular visits to facility, intake of medicines without default, compliance to diet and exercise regimes prescribed, maintaining the blood glucose in optimum levels, timely detection and treatment of complications of any. We have tried to explore the gendered factors that work in the management of diabetes mellitus.

In this study population, though the number of men and women were equal (100) there were notable differences in the socio-demographic characteristics. Marital and socio economic status, education and occupation profiles were not similar for men and women. Women showed a picture of being socially and

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economically vulnerable, constituting more of the illiterate (100%), unemployed

(88%), widowed/separated (92%) and lower socioeconomic status (62%) share of the sample. Universally the access to resources determined by education and occupation is lower for women and it is reiterated in this study with in high proportion of women belonging to the lower SES.

This study analyses diabetes management in three phases. Diagnosis, treatment proper and prevention and/care of the complications of diabetes.

Diagnosis- Getting diagnosed as a diabetic before the disease seriously affect the systems, is an indicator of good health seeking behaviour and accessibility to services, which in turn reflects the decision making power , control of the resources of the individual. These factors are strongly influenced by the gender, because as we have seen already, the basic socio demographic profile favours the men in terms of employment, education, socio economic and marital status. More than half of those who had early diagnosis (55%) were men. This difference was proven to be statistically significant in high SES and currently married strata, but not in lower SES which indicates that higher SES is not protective for women in case of diagnosis. Women’s lower access to resources and inability to prioritise their health over and above their caregiver role do affect their options for early diagnosis.

Treatment options were further divided into pharmacological

(medicines and insulin) and non pharmacological management (dietary and exercise components) for analysis. The results show that High SES is not protective for women in case of the pharmacological and non pharmacological management, where 54

diet and exercise components did not show any significant difference for the low socio economic stratum. It can be explained that though the women belonged to the high SES

(note: SES assessed by household assets, as in NFHS criteria, not on individual income), they did not have the decision making power in health seeking or the access on or control over the resources which can be utilised to facilitate the good treatment outcome. More than 80 percent of women were unemployed, and they depended mostly on their children for resources for obtaining treatment or medications.

There was a significant difference in the support system men and women had within their family, to effectively manage the disease condition. Most of the men said their medicine intake and special dietary needs were taken care of by their wives, while less number of women reported to have such a support system at home. It was evident even at the time of data collection when many men said they did not know which tablet to be taken how many times a day, and it is all taken care of by the woman at his home. Very few women reported to get such a support from their spouses; rather, most women were looked after by the children, if it is not done by the patient herself. As a result, when women somehow managed to take the medicines regularly, the diet component was seen to be neglected. This may be because of the higher value assigned to the man’s health, who is the earning member and breadwinner of the family.

Higher SES was not protective in non medical management either, for women, as it did not give them the time off from their care giving roles to care for themselves either by exercise or dietary management. Physical activity is restricted for women in higher SES compared to those in the lower SES, and the food cooked 55

may be not ideal which contains enough vegetables. Moreover, more women reported inability to take regular exercise due to the need to have an accompanying person. The reasons for not following exercise regimes were found to be deeply gendered. Men mostly had medical reasons. Some were engaged in sedentary occupations which did not permit any exercise. Women had too much household works and lack of time to spare, and being unable to go out alone in the early hours as the reasons, and it stems from the culture that is restrictive to women’s mobility.

Some women were too obese to do any exercise. Some were too old too. The type of physical activity among those who got it varied between men and women. For women, it was mostly part of their routine chores like grazing cattle or taking agricultural products to market, rather than the actual exercise. That is why women from the lower SES were found to have more physical activity.

When marital status is considered, though currently married status was assumed to be protective, in case of women it was not found so when the individual components of disease management are considered. Pharmacological management was seen to be protected by currently married status probably because of the financial and family support the patient gets. Married status did not have any protective effect on non-pharmacological management in case of women. But for men, diet component of non-pharmacological management was strongly associated with currently married status, as wives take a gendered role of caretaker with respect to required diet preparation. However, this protective feature does not operate for women. Again here most of the men has this protective effect as a majority are currently married (95%).

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Prevention and management of complications of DM :

In all kinds of complication signs, more women were affected than men. But the proportions who sought care and who got immediate care were more among men. This again can be gendered due to the lower value assigned to the health of women.

5.2 Conclusions

The study provides information on the linkages of gender roles, norms and values which in turn exert significant influences on all phases of diabetes care. From the responses to questions formed based on the gender analysis tool, it was understood that women predominantly adapt the ‘caregiver’ role in the family and values the health of other family members much more important than her own.

The health expenditure is borne by others in the family and it compromises the pharmacological management. Majority of women (84%) are unemployed and depend on private facilities (78%) for management. So chances of defaulting treatment are more among women. Lack of time to spare for exercise and less options to have her own special diet at home adversely affect the non pharmacological component of diabetes management of women.

All these factors act alone or together and add to the higher level of poor management among women, and this highlights the comparatively neglected gender dimensions of non communicable diseases, where women were thought to be benefitted by just being a female under the ‘protective umbrella of female sex hormones’ and draws attention to the need of developing or reframing the NCD

57

control policies, incorporating the components that mitigate for these gendered disabilities that women experience.

5.3 Strengths and Weaknesses of the study

Strength: Gender dimensions of disease management is a comparatively under-explored area in NCD research in Kerala, despite the evidence of higher rates of poor management and outcome in women, from studies done elsewhere. This study tries to capture some inter-linkages among the various socio-demographic and gender related components which exerts significant influences in the management of type 2 diabetes in Kerala – the state with the highest proportion of the disease in the diabetic capital of the world.

Weaknesses:

1. It is a cross sectional study. We meet the cases only at one point of a time, so

can not capture the evolution of the disease, or how it gets influenced by the

various factors across time by following up the population.

2. Inability to examine the synergistic effects by doing multivariate analysis

because of small sample numbers with specific characteristics.

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5.4 Policy recommendations

Improving the efficiency of government institutions:

Health programmes should be geared towards addressing the current non-communicable disease epidemic more effectively. Some practical approaches that can be adopted are

a. Incorporate NCD monitoring and supervising its management in the job

responsibilities of male and female multipurpose health workers (JHI s

and JPHNs) – by enumerating the DM patients in the catering area of

each PHC and keeping their list at PHCs, fixing targets for the number of

NCDs effectively managed in each health worker’s area, along with the

other targets they have to meet in the current scenario- like the number of

the immunisation and sterilisation cases.

b. Ensure availability of oral hypoglycaemic agents and insulin in PHCs for

these patients.

c. IEC (information,education and communication) and BCC (behaviour

change communication) of the public with regard to the risk factors of

DM and encourage them to get investigated, and the need of maintaining

a good management outcome and prevention of complications in case of

those who are already diabetic.

d. Sensitise the Panchayati raj institutions about the current NCD epidemic and

the need of intervention in the area of diet and exercise like making

vegetables more available and cheaper (group farming by women self-help

groups like Kudumbasree) and encouraging physical activity by providing

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walking areas/playgrounds/bicycle tracks – to improve physical activity of

the public.

Gender sensitive programs for management of DM including

a. Multipurpose health workers should be given instructions to give special

attention to the diabetic women in their respective areas. They can counsel

the family members of the patient during their house visits and sensitise

them about the need of support the patient needs, for her special dietary and

physical activity requirements. Adequate ways to enhance the intake of

fruits, and vegetables should be devised. Weight should be monitored.

Women should be encouraged to engage in enjoyable physical activities,

including walking, for 30 minutes daily and LSGs (local self governments)

should be encouraged to provide ‘safe zones’ for such activities.

b. Engaging families of diabetic women in a shared process of taking

responsibility for effective management of diabetes mellitus.

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28. Minh HV, Byass P, Chuc NT, Wall S. Gender differences in prevalence and socioeconomic determinants of hypertension: findings from the WHO STEPs survey in a rural community of Vietnam. J Hum Hypertens. 2006 Feb;20(2):109-15

29. La Croix AZ, Newton KM, Leveille SG, Wallace J. Healthy aging. A women's issue. West J Med. 1997 Oct;167(4):220-32

30. Kawamoto R, Tomita H, Inoue A, Ohtsuka N and Kamitani A. Metabolic syndrome may be a risk factor for early carotid atherosclerosis in women, but not in men. J Atheroscler Thromb 2007; 14:36-43

31. Clouse RE, Lustman PJ, Freedland KE, Griffith LS, McGill JB and Carney RM. Depression and Coronary Heart Disease in Women With Diabetes. Psychosomatic Medicine 2003; 65:376-83

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32. Foppa M, Duncan BB, Arnett DK, Benjamin EJ, Liebson P, Manolio TA and Skelton TN. Diabetes, gender, and left ventricular structure in African-Americans: the atherosclerosis risk in communities study. Cardiovasc Ultrasound 2006; 4: 43

33. Papadopoulose AA, Kontodimopoulose N, Frydas A, Ikonomakis E, and Niakas D. Predictors of health-related quality of life in type II diabetic patients in Greece. BMC Public Health 2007; 7:186

34. Boyko EJ, Fihn SD, Scholes D, Chen CL, Normand EH, Yarbro P. Diabetes and the risk of acute urinary tract infection among postmenopausal women. Diabetes Care. 2002 Oct;25(10):1778-83

35. Hu KK, Boyko EJ, Scholes D, Normand E, Chen CL, Grafton J, Fihn SD. Risk factors for urinary tract infections in postmenopausal women. Arch Intern Med. 2004 May 10;164(9):989-93

36. Michels KB, Solomon CG, Hu FB, Rosner BA, Hankinson SE, Colditz GA, Manson JE; Nurses' Health Study. Type 2 diabetes and subsequent incidence of breast cancer in the Nurses' Health Study. Diabetes Care. 2003 Jun;26(6):1752-8

37. Ding EL, Song Y, Malik VS, Liu S. Sex differences of endogenous sex hormones and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA. 2006 Mar 15;295(11):1288-99

38. Hsia J, Margolis KL, Eaton CB, Wenger NK, Allison M, Wu L, LaCroix AZ et al., Prehypertension and cardiovascular disease risk in the Women's Health Initiative. Circulation. 2007 Feb 20;115(7):855-60

39. Mellen PB, Cefalu WT, Herrington DM. Diabetes, the metabolic syndrome, and angiographic progression of coronary arterial disease in postmenopausal women. Arterioscler Thromb Vasc Biol. 2006 Jan;26(1):189-93

40. Clouse RE, Lustman PJ, Freedland KE, Griffith LS, McGill JB and Carney RM. Depression and Coronary Heart Disease in Women With Diabetes. Psychosomatic Medicine 2003; 65:376-83

41. Sowers JR. Diabetes mellitus and cardiovascular disease in women. Arch Intern Med. 1998 Mar 23;158(6):617-21

42. Chiamvimonvat V, Sternberg L. Coronary artery disease in women. Can Fam Physician. 1998 Dec;44:2709-17

43. Remigijus Žaliūnas, Rimvydas Šlapikas, Rūta Babarskienė, Birutė Šlapikienė, Dalia Lukšienė et al., The prevalence of the metabolic syndrome components and their combinations in men and women with acute ischemic syndromes. Medicina (Kaunas) 2008; 44 (7): 521-528

44. Gender and health: technical paper. What do we mean by gender? page 16

45. Kosuge M, Kimura K, Kojima S, Sakamoto T, Ishihara M, Asada Y et al. Sex Differences in Early Mortality of Patients Undergoing Primary Stenting for Acute Myocardial Infarction . Circulation 2006; 70: 217-21

46. Kim C, Kerr EA, Bernstein SJ and Krein SL. Gender Disparities in Lipid Management: The Presence of Disparities Depends on the Quality Measure. Am J Manag Care 2006;12:133-6

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47. Folsom AR, Kushi LH, Hong CP. Physical activity and incident diabetes mellitus in postmenopausal women. Am J Public Health. 2000 Jan;90(1):134-8

48. J Hepworth. Gender and the capacity of women with NIDDM to implement medical advice. Scand J Public Health 1999;27:260-6

49. Nagpal J,Bhartia A. Quality of diabetes care in middle and high income group populace: The Delhi database community (DEDICOM) Survey. Diabetes care,2006 Nov;29(11):2341-8

50. Gender analysis in health-a review of selected tools,department of gender and women’s health,world health organisation pp 43-73

51. (Gender analysis in health-a review of selected tools,department of gender and women’s health,world health organisation pp 17,35,73-9)

IV

Information about the Researcher and the Study

I am Mini P.Mani, a post graduate student in Public Health studying at Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology in Trivandrum, Kerala. For my thesis I am conducting a study on the “Impact of Gender on type 2 diabetes care in Varkala”. The details of diabetes patients’ awareness about the disease and its treatment, about how they perceive the management of the disease, and especially the gender mediated factors that affect the effective care of diabetic status will be studied.

I would like to ask you some questions about you and your illnesses, which will take 30- 45 minutes time. This is a routine procedure to obtain informed consent from the participant in a study.

The information given by you will not be disclosed to anyone under any circumstances anywhere in the public at any time and kept confidential and will be used for research purposes only.

Though there is no direct benefit for you from participating in this study, the inferences of the study may help develop policies for better management of diabetes in our state, which carries the highest proportion of diabetes patients in India.

Participation in this study is purely of voluntary nature. If at any time you want to stop answering questions or not answer some of the questions you may refuse to do so.

If you have any queries or doubt please feel free to clarify those. I will try my level best to answer to any of your queries right now or in future as well. In case you need any clarifications about my credentials or the study you can also contact Dr. Anoop Kumar Thekkuveettil, Member-Secretary of the Institutional Ethical Committee at SCTIMST, Trivandrum.

V

Informed Consent

I have talked with the researcher, and have gone through/ been read out the details of this study and the researcher. I understand my role in it, and the purpose of this interview. I understand that the information collected will be kept strictly confidential and be used for research purposes only. I have been told that my participation is purely voluntary, and i can withdraw from the study at any time, if i am not comfortable with it. I know whom I should contact, in case of any doubts about the Investigator or the study. I hereby declare my willingness to participate in the study.

______

Signature of the participant

Name of the participant

______

Thumb impression

Date:

VI

D.2 Questionnaire for the interview

AMCHSS- SCTIMST

IMPACT OF GENDER ON TYPE 2 DIABETES CARE IN VARKALA, KERALA

QUESTIONNAIRE

Strictly confidential. For research purposes only.

Background/ Socio demographic Details

Identification Code 101.1Name

102 Address

103 Age in completed years 104 Sex 1. Male 2. Female 105 Edu.status - years of education 106 Occupation 1. Home maker/ Housewife 2. Labourer/Farmer/Private Informal 3. Private formal 4. Govt. Employee 5. Professional 6. Retired 7. Others specify ...... 107 Marital Status 1. Never married 2. Currently married 2. Widow/widower 3. Divorced/separated 108 Type of Family 1. Nuclear 2. Joint 3.Extended 109 Total number of Household members 110 Socio-economic Status 1. High 2. Medium 3. Low Personal Habits

201 Your diet is 1. Pure Vegetarian (no egg)

2. Predominantly vegetarian ( non vegetarian diet once in a week or less frequent)

3. Mixed ( daily diet contain both vegetarian and non vegetarian dishes)

202 Have you ever used any tobacco product? 1. Yes 2. No

203 Do you currently use any tobacco products? 1. Yes 2. No

204 Do you currently use any smokeless tobacco 1. Yes 2. No products?

205 Have you ever used any alcoholic Beverage? 1. Yes 2. No

206 Do you currently consume any alcoholic products? ( At 1. Yes 2. No least one serving in the last 2 weeks)

Disease and Treatment related factors

Diagnosis

1. You went and checked because you wanted to know 301 How did you come to know that you are a 2. Your doctor advised when you went for some other VII

diabetic? purpose 3. Following investigations of non healing ulcer/ frequent changing of specs/ 4. Any other complications? Specify…………… 302 Where did you check? 1. Govt. Hospital 2. Pvt hosp/ lab 3. Home 4. Others(specify) 303 Do you have any other illness associated? 304 Hypertension 1. Yes 2. No 3. Don’t Know 305 Heart Disease 1. Yes 2. No 3. Don’t Know 306 High cholesterol 1. Yes 2. No 3. Don’t Know 307 Neurological Problems (Stroke/Paralysis/ 1. Yes 2. No 3. Don’t Know Weakness) 308 Any others Specify...... Treatment

401 Where are you taking treatment from, for 1. Government hosp 2. Pvt hosp 3.Not treating now your diabetes? 4. Both places, according to convenience 5. Others(specify) 402 Who pays mostly for your travel. Consultation, 1. Yourself 2. Spouse 3. In-laws investigations and medicines? 4. arents 5. Children 6.Others ( specify) 403 Do you know the names of all medicines 1. Yes 2. No you are on? 404 How far is the health facility from your home? 1. Walking distance 2. Upto 10 km 3. > 10 km 405 How often do you visit the facility? 1. As per advised by the provider 2. When I get time 3.When medicines are over 4. When I feel sick 406 Has your doctor prescribed you any 1. Yes 2. No 3. Don’t Know particular restricted diet/ diabetic diet? 407 Are you observing diet restriction? 1. Yes 2. No 408 If no,why? 409 Is any exercise regime prescribed by your 1. Yes 2. No 3. Don’t Know doctor? 410 Are you following Exercise regime? 1. Yes 2. No 411 If no, why? 412 When was the last time you checked your 1. 3 month - 6 months 2. Don’t remember Blood sugar level? 413 Was it within normal limits? 1. Yes 2. No 3. Don’t Know 414 When was the last time you checked your 1. Last 30 days 2. 1 - 3 month urine sugar level? 3. 3 month - 6 months 4. Don’t remember 415 Was it normal? 1. Yes 2. No 3. Don’t Know 416 Do you keep your treatment records safe in 1. Yes 2. No an accessible place? 417 If yes, can I see the same? 1. Verified 2. Not verified 418 Does anyone else in your family is diabetic? 1. Yes 2. No 3. Don’t Know 419 If yes, who? Specify ...... 420 Have you ever fallen sick ( attack of blackout 1. Yes 2. No 3. Don’t Know / vertigo / dizziness) because your blood sugar level dropped ( confirmed by doctor/ self check by glucometer) 421. If yes, how many times in the last one year? ...... 422. What did you do during the experience of ...... such a fall? Diet

Does your daily diet include

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501 Green leafy vegetables ( Amaranthus/ 1. Yes 2. No palak/spinach/drumstick leaves) 502 If yes, how much? 1. at least 1 cup 2. less than 1 cup 503 Other vegetables, cooked/chopped/raw 1. Yes 2. No ( Excluding potato and tubers) 504 If yes, how much? 1.half a cup at least 2. less than half a cup 505 Vegetable Juice (Bittergourd/ Cucumber/ 1. Yes 2. No Carrot/ Ashgourd) 506 If yes, how much? 1. half a cup 2. less than half a cup 507 Fresh fruit (Mango/ Banana/ Papaya/ 1. Yes 2. No Orange/ Grapes/ Apple/ Jackfruit) 508 If yes, how much? 1. one medium sized piece 2. (apple/banana) 3. less than that 509 Chopped/ cooked/ canned fruit 1. Yes 2. No (Mango/ Pineapple/ Jackfruit) 510 If yes, how much? 1. at least half a cup 2. less than half a cup 511 Fruit juice ( Orange/ Mango/ Grapes) 1. Yes 2. No 512 If yes, how much? 1. at least half a cup 2. less than half a cup Exercise

601 Do you do any vigorous intensity sports/ fitness/ recreation activity for at least 1. Yes 2. No 10 minutes continuously? 602 In a typical week, on how many days do you do vigorous intensity sports/ fitness/recreational activities? 603 How much time do you spend doing vigorous intensity sports/fitness/recreational activities on a typical day? Hours: Minutes 604 Do you do any moderate intensity sports/ fitness/ recreation activity for at 1. Yes 2. No least 10 minutes continuously? 605 In a typical week, on how many days do you do moderate intensity sports/ fitness/recreational activities? 606 How much time do you spend doing moderate intensity sports/fitness/recreational activities on a typical day? Hours: Minutes Complications

Symptom If Yes If Yes

Did you seek How long did you suffer the medical help? symptom before you sought treatment?

701 Impairment of vision 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 702 Frequent changing of glasses 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 703 Non-healing ulcer 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 704 Delayed wound healing 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month IX

705 Abnormal sensation ( tingling) of 1. Yes 1. Yes 1. I sought treatment almost extremitie 2. No 2. No immediately 2. Within 1 month 3. > 1 month 706 Numbness/ loss of sensation of 1. Yes 1. Yes 1. I sought treatment almost extremities 2. No 2. No immediately 2. Within 1 month 3. > 1 month 707 Changes in urine output 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 708 Puffiness of face 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 709 Oedema 1. Yes 1. Yes 1. I sought treatment almost 2. No 2. No immediately 2. Within 1 month 3. > 1 month 710 Were you diagnosed to have any other diabetic 1. Yes 2. No complications, by a doctor?

If yes, specify ......

Gender Analysis

801 If you wanted to seek health care, will you be able to 1. Yes 2. No decide on your own? 802 Do you think the health facilities are accessible to you in 1. 1. Yes 2. No all aspects? 803 If no- what is the problem you find mostly? 1. too far 2. male doctor / female doctor 3. doctor not available 4. too costly for me to afford 5. health care providers are not friendly 6. medicine not available in the government hospital 7. Others Specify...... 804 Who pays mostly for your travel, medicine, consultation, 1. Yourself 2. your spouse investigations 3. In laws 4. Parents 5.Children 6.Others Specify 805 Have you ever been unable to meet the required regime 1. lack of money and advices due to any of these? 2. being physically ill 3. having no one to accompany 4. because the facility is too far 5. Others Specify ------6. None 806 Does anyone monitor your food consumption practices 1. Yes 2. No at home? 807 if yes, who 1.Yourself 2. your spouse 3. In laws 4. Parents 5.Children 6.Others Specify 808 does anyone monitor your consumption of prescribed 1. Yes 2. No medication at home? 809 if yes, who 1.Yourself 2. your spouse 3. In laws 4. Parents 5.Children 6.Others Specify X

810 Do you manage to get the prescribed diabetic diet at 1. Yes 2. No your home without fail? 3. No advice from doctor 811 Any occasions when you are unable to follow the 1. Yes 2. No diabetic diet instructions? 812 If yes, when? Specify? 813 Do you get any special food cooked to suit your dietary 1. Yes 2. No advice? 814 Do you think exercise can help you in managing your ……………………………. disease better, in addition to taking medicines? 815 If yes, how? Explain? 1. Yes 2. No 816. Are you able to observe the exercise advice given to 1. Yes 2. No 3. No advice from doctor you by your doctor? 817 If no, What prevents you from observing the exercise 1. lack of time regime prescribed by your physician? 2. I don’t feel it is needed 3. I don’t get support from family to follow it 4. Others Specify...... 818 Do you think you have a good support system within 1. Yes 2. No your family? 819 Who supports you mostly? 1.Yourself 2. your spouse 3. In laws 4. Parents 5.Children 6.Others Specify 820 Do you receive any help to maintain your diabetic diet, 1. Yes 2. No medication, exercise and follow up check up, from within your family? 821 If yes, who supports you? 1.Yourself 2. your spouse 3. In laws 4. Parents 5.Children 6.Others Specify 822 Have you ever suffered from any acute diabetic 1. Yes 2. No 3. Don’t know complications and been hospitalized? 823. If yes, what was the problem? 824 How many times? 1. once 2. more than once 825. When was it? ...... 826 Were you diagnosed to have any other diabetic 1. Yes 2. No complications, by a doctor? 827 If yes, specify 828 If you have any complications why do you think it 1. delay in diagnosis happened? 2. Irregular treatment 3. Not following diet or exercise advice 4. Others (specify) 829 How do you rate the attention given to your health 1. Most important among that of your family members 2. Equally important 3. Least important 830 Among your Family members, whose health do you 1. Yours consider the most important? 2. Your spouse 3. Your children 4. Parents 5. All are equal to me 6. Others (specify)

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Standard Of Living Index To Determine Socioeconomis Status: NFHS 2 Facility Types Value Score House Pucca 4 Semi pucca 2 Kutchha 0 Toilet facility Own flush toilet 4 Public/shared flush toilet/own pit toilet 2 Shared/public pit toilet 1 No facility 0 Source of lighting Electricity 2 Kerosene, gas, oil 1 Other 0 Main fuel for cooking Electricity/LPG/biogas 2 Coal/charcoal/kerosene 1 Other 0 Drinking water source Pipe, hand pump, well in residence/yard/plot 2 Public tap/hand pump/well 1 Other 0 Separate room for Yes 1 cooking No 0 House ownership Yes 2 No 0 Agricultural land > 5 acres 4 ownership 2-4.9 acres 3 <2 acres/acreage not known 2 No agricultural land 0 Irrigated land Some irrigated land 2 ownership No irrigated land 0 Livestock ownership Cattle 4 Poultry 2 No 0 Ownership of durable Car 4 goods Tractor 4 Moped/scooter/motorcycle 3 Telephone 3 Refrigerator 3 Color TV 3 Bicycle 2 Electric fan 2 Radio/transistor 2 Sewing machine 2 Black and White TV 2 Water pump 2 Bullock cart 2 Thresher 2 Mattress 1 Pressure cooker 1 Chair 1 Cot/bed 1 Table 1 Clock/watch 1

0-14=LOW; 15-24=MEDIUM; 25- 67=HIGH

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Varkala ICDS Block- General Information Panchayat/ House Sl No Area(sq.km) Wards Male Female Total Municipality holds 1 Manambur 15.8 15 4959 10460 12098 22558 2 Ottoor 9.47 12 3707 7037 8322 15359 3 Cheruniyoor 10.87 13 4069 8192 9726 17918 4 Chemmaruthy 16.42 18 7057 14468 16450 30918 5 Vettoor 8.82 13 3893 8992 10309 19301 6 Edava 9.14 16 5145 12292 14611 26903 7 Elakamon 16.15 15 5645 11339 13046 24385 8 Municipality 15.42 30 _ 20784 21489 42273 Total 102.09 132 93,564 1,06,051 1,99,615

Table 3.2 Demographic profile of Chemmaruthy panchayat Name of Number of Total Population ( including institutional and houseless) Panchayat/Ward Households Persons Males Females Chemmaruthy 7057 30918 14468 16450 Ward No. - 01 441 2251 1100 1151 Ward No. - 02 490 2173 1000 1173 Ward No. - 03 447 2073 997 1076 Ward No. - 04 503 2110 962 1148 Ward No. - 05 589 2639 1259 1380 Ward No. - 06 560 2421 1137 1284 Ward No. - 07 560 2339 1092 1247 Ward No. - 08 495 1972 905 1067 Ward No. - 09 590 2483 1186 1297 Ward No. - 10 522 2302 1017 1285 Ward No. - 11 470 2006 930 1076 Ward No. - 12 441 1887 859 1028 Ward No. - 13 507 2231 1031 1200 Ward No. - 14 442 2031 993 1038

Table 3.3 Demographic profile of Cherunniyoor panchayat Name of Number of Total Population ( including institutional and houseless) Panchayat/Ward Households Persons Males Females Cherunniyoor 4069 17918 8192 9726 Ward No. - 01 527 2338 1085 1253 Ward No. - 02 263 1188 532 656 Ward No. - 03 408 1918 915 1003 Ward No. - 04 417 1962 911 1051 Ward No. - 05 353 1511 697 814 Ward No. - 06 378 1530 662 868 Ward No. - 07 434 1757 801 956 Ward No. - 08 391 1745 759 986 Ward No. - 09 463 2044 944 1100 Ward No. - 10 435 1925 886 1039

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Table 4.3.1(a) stratified analysis of the components of DM care by high SES/sex

Components of Parameters Men Women Total Chi OR 95% CI Care of each (%) (%) (%) Sq Sig Before 68 45 (73.7) 113 complications (89.4) (82.5) Diagnosis 0.015* 3.022* 1.194-7.648 After 8 (10.5) 16 (26.2) 24 complication (17.5) Visits to As 47(61.8) 30 (49.2) 77 (56.2) facility advised/regular 0.095 1.675 0.846-3.315 No regular visit 29 31 (50.8) 60 (38.2) (43.8) Medicine No Default 55 32 (52.4) 87 Pharmacological (72.3) (63.5) intake 0.013* 2.374* 1.166-4.832 management Default 21 29 (47.5) 50 (27.6) (36.5) Pharmac Good 38 (50) 21 (34.4) 59 (43.1) mgt 0.049* 1.905* 0.952-3.811 Not good 38 (50) 40 (65.5) 78 (56.9) Diet Adequate 14 3 (4.9) 17 (30.4) (12.4) 0.015* 4.366* 1.193-15.976 Not adequate 62 58 (95) 120 Non Pharmac (81.5) (87.6) management Exercise Getting 30 10 (16.4) 40 Recommended (39.5) (29.2) 0.002* 3.326* 1.466-7.546 Not getting 46 51 (83.6) 97 recommended (60.5) (70.8) Glycemic Good 30 22 (36) 52 (38) (39.5) control 0.409 1.156 0.576-2.319 Not good 46 51 (83.6) 97 Treatment (60.5) (70.8) outcome Prevention Complication 52 34 (55.7) 86 of absent (68.4) (62.8) 0.089 1.721 0.855-3.463 complication Complication 24 27 (44.3) 51 present (31.5) (37.2) Final Outcome good 21 12 (19.6) 33 (27.6) (24.1) Management 0.189 1.559 0.696-3.494 Outcome not 55 49 (80.3) 104 outcome of DM good (72.4) (75.9) TOTAL (%) 76 61 (100) 137 (100) (100)

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Table 4.3. 1 (b) stratified analysis of the components of DM care by average+low SES/sex ,2008

Components of Parameters Men Women Total Chi OR 95% CI Care of each (%) (%) (%) Sq Sig Before 21 29 (74.3) 50 complications (87.5) (70.4) Diagnosis 0.177 2.414 0.591-9.858 After 3 (12.5) 10 (25.6) 13 complication (20.6) Visits to As 21 21 (54) 42 facility advised/regular (87.5) (66.7) 0.005* 6.000* 1.534-23.464 No regular visit 3 (12.5) 18 (46.2) 21 (33.3) Medicine No Default 15 20 (51.3) 35 Pharmacological (62.5) (55.6) intake 0.272 1.583 0.561-4.470 management Default 9 (37.5) 19 (48.7) 28 (44.4) Pharmac Good 13 11 (28.2) 24 (83.3) (38.1) mgt 0.037* 3.008* 1.039-8.714 Not good 11 28 (71.8) 39 (45.8) (61.9) Diet Adequate 5 (20.8) 3 (7.7) 8 (12.7) Not adequate 19 36 (92.3) 55 0.130 3.158 0.680-14.664 (79.2) (87.3) Non Pharmac Exercise Getting 7 (29.2) 10 (25.6) 17 (27) management Recommended 0.490 1.194 0.383-3.720 Not getting 17 29 (74.3) 46 (73) recommended (70.8) Glycemic Good 12 (50) 10 (25.6) 22 (34.9) control 0.045* 2.900* 0.989-8.502 Not good 12 (50) 29 (74.3) 41 Treatment (65.1) outcome Prevention Complication 15 22 (56.4) 37 of absent (62.5) (58.7) 0.417 1.288 0.455-3.647 complication Complication 9 (37.5) 17 (43.6) 26 present (41.3) Final Outcome good 8 (33.3) 6 (15.4) 14 Management (22.2) 0.089 2.750 0.816-9.271 outcome of DM Outcome not 16 33 (84.6) 49 good (66.6) (77.8) TOTAL (%) 24 39 (100) 63 (100) (100)

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Table 4.1.(c) stratified analysis of the components of DM care by currently married status/sex - 2008

Components of Parameters Men Women Total Chi OR 95% CI Care of each (%) (%) (%) Sq Sig Before 84 52 (78.8) 136 complications (88.42) (84.5) Diagnosis 0.076 2.056 0.868-4.869 After 11 21.2) 25 complication (11.5) (15.5) Visits to As 64 33 (50) 64 facility advised/regular (67.4) (39.8) 0.020* 2.065* 1.083-3.937 No regular visit 31 33 (50) 64 (32.6) (39.8) Medicine No Default 66 36 (54.5) 102 Pharmacological (69.5) (63.4) intake 0.039* 1.897* 0.988-3.641 management Default 29 30 (45.5) 59 (30.5) (36.6) Pharmac Good 47 24 (36.4) 71 (49.5) (44.1) mgt 0.068 1.714 0.901-3.259 Not good 48 42 (63.6) 90 (50.5) (55.9) Diet Adequate 19 (20) 3 (4.5) 22 (13.7) 0.004* 5.25* 1.485-18.557 Not adequate 76 (80) 63 (95.5) 139 Non Pharmac (86.3) management Exercise Getting 36 14 (21.2) 50 Recommended (37.9) (31.1) 0.018* 2.266* 1.102-4.661 Not getting 59 52 (78.8) 111 recommended (62.1) (68.9) Glycemic Good 39 (41) 23 (34.8) 62 (38.5) control 0.265 1.302 0.679-2.496 Not good 56 43 (65.2) 99 Treatment (58.9) (61.5) outcome Prevention Complication 63 36 (54.5) 99 of absent (66.3) (61.5) 0.090 1.641 0.861-3.126 complication Complication 32 30 (45.5) 62 present (33.7) (38.5) Final Outcome good 27 12 (18) 39 (28.4) (24.2) Management 0.095 1.787 0.829-3.852 Outcome not 68 54 (82) 122 outcome of DM good (71.6) (75.8) TOTAL (%) 95 66 (100) 161 (100) (100)

XVI

Table 4.3.1(d) stratified analysis of the components of DM care by currently not married status/sex ,2008

Components of Parameters Men Women Total Chi OR 95% CI Care of each (%) (%) (%) Sq Sig Before 5 (100) 22 (64.7) 27 complications (69.2) Diagnosis NA After 0 (0) 12 (35.3) 12 complication (30.8) Visits to As 4 (80) 18 (53) 22 facility advised/regular (56.4) 0.262 3.556 0.359-35.197 No regular visit 1 (20) 16 (47) 17 (43.6) Medicine No Default 4 (80) 16 (47) 20 Pharmacological (51.3) intake 0.187 4.500 0.455- 44.546 management Default 1 (20) 18 (53) 19 (48.7) Pharmac Good 4 (80) 8 (23.5) 12 (30.8) mgt 0.025* 13.000* 1.265- 133.638 Not good 1 (20) 26 (76.5) 27 (69.2) Diet Adequate 0 (0) 3 (8.8) 3 (7.7) Not adequate 5 (100) 31 (91.2) 36 NA (92.3) Non Pharmac Exercise Getting 1 (20) 6 (17.6) 7(17.9) management Recommended 0.650 1.167 0.110-12.381 Not getting 4 (80) 28 (82.4) 32 recommended (82.1) Glycemic Good 3 (60) 9 (26.5) 12 (30.8) control 0.159 4.167 0.596-29.130 Not good 2 (40) 25 (73.5) 27 Treatment (69.2) outcome Prevention Complication 4 (80) 20 (58.8) 24 of absent (61.5) 0.351 2.800 0.282- 27.796 complication Complication 1 (20) 14 (41.2) 15 present (38.5) Final Outcome good 2 (40) 6 (17.6) 8 (20.5) Management Outcome not 3 (60) 28 (82.4) 31 0.268 3.111 0.423- 22.826 outcome of DM good (79.5) TOTAL (%) 5 (100) 34 39 (100) (100)

XVII