DESCRIBING POPULATION HEALTH IN SIX DOMAINS: COMPARABLE RESULTS FROM 66 HOUSEHOLD SURVEYS

Ritu Sadana Ajay Tandon Christopher JL Murray Irina Serdobova Yang Cao Wan Jun Xie Somnath Chatterji Bedirhan L Ustün

Global Programme on Evidence for Health Policy Discussion Paper No. 43

World Health Organization March 2002 Abstract

One of the World Health Organization's longest standing mandates is the collection and routine reporting of information on population health. In addition to estimates of mortality and disease, assessment of health status from population based surveys contribute to estimates of population health. The first section of the paper briefly introduces the conceptual and operational basis to measure health, where health is measured through six domains (affect, cognition, pain, mobility, self-care and usual activities). The second section briefly notes that the main objective of this paper is to report on the average levels of health by age and sex groups for each domain of health across 66 population based surveys. The third section of this paper describes how we have applied the hierarchical ordered probit (HOPIT) model using vignettes to calibrate responses across survey populations, to self-reported levels of health on six domains. The data comes from the WHO Health Survey Study 2000-2001, from 66 population based surveys in 57 countries, representative of individuals 18 years and older. The fourth section provides results on comparable levels of health for each domain across populations, by age groups and sex. In order to further facilitate comparisons across countries, age-standardized aggregated results across all age groups, by sex, are also presented and compared to external data, such as GDP per capita (PPP) and life expectancy. The fifth section discusses the information content of the surveys, the added-value of the multi-dimensional approach and the comparability of responses across countries. The final section recommends additional analyses to be conducted.

Comments on this discussion paper are most welcome and should be forwarded to:

Dr. Ritu Sadana Evidence and Information for Policy World Health Organization Avenue Appia 20 CH-1211 Geneva 27 Switzerland

Email: [email protected] I. Introduction 1.1 BACKGROUND

The World Health Report 2000 (WHO 2000) proposed a framework defining the three intrinsic goals to which health systems should contribute. The first intrinsic goal is considered as the defining goal of a health system, that is, to improve health, both the average level of population health and its distribution within a population. It is not surprising that one of the World Health Organization’s longest standing mandates has been the collection and routine reporting of information on population health. Along with Member States, research institutions, and technical experts, WHO has expended considerable efforts over the past decades to enhance the information content and comparability of population health covering mortality and its risk factors. Over the past decade, the locus of these efforts has extended to the improvement and standardization of methods to assess non-fatal health (covering epidemiological estimates of morbidity and disability, and assessment of health status from population based surveys), reflecting the conclusion that mortality alone does not provide a complete picture of population health. Following the Global Burden of Disease Study (Murray and Lopez 1996), more recent work includes the further development of summary measures of population health (Murray et al. forthcoming), a critical review of the validity and comparability of existing population based survey data on health status (Sadana et al 2000), the finalization of The International Classification of Functioning, Disability and Health (ICF), (WHO 2001) and the implementation of the WHO Multi-Country Survey Study on Health and Responsiveness 2000-20001 (WHO Multi-Country Survey Study) (Üstün et al. 2001).

This paper reports on the average level of population health, focusing on the self-reported health status in six domains assessed through 66 population-based surveys conducted in 57 countries included within the WHO Multi-Country Survey Study. The results presented in this paper provide more comparable information on the self-reported average level of population health across countries than was previously possible from survey data, and have been used in subsequent analyses to estimate healthy life expectancy (Mathers et al. 2001).

1.2 MULTIPLE DOMAINS OF HEALTH

The WHO definition of health notes that health is a multi-dimensional concept. There are potentially three sets of domains that can be specified in order to describe health and contribute to its operational measurement: (1) core domains of health that almost all people agree upon; (2) additional domains of health that some people consider as core domains; and (3) other domains that are related to health and serve as good proximate measures of the experience of health – health related domains. Based on an extensive review of existing health state measurement instruments and health measurement literature, some 24 candidate domains to describe health were proposed and discussed within technical consultations on measuring health status over the past two years (Figure 3). Of these, 18 describe different aspects of health status directly, such as affect, pain, dexterity or fertility (e.g., domains in the gray shaded box), while the remaining six are proximate domains that indirectly assess health. Based on the reviews, technical discussions and linkage with the ICF, six domains were selected as domains that almost all people agree upon for inclusion across all survey modes with the WHO Multi-Country Survey Study. These include affect, cognition, mobility, pain, self-care and usual activities. This paper restricts its analyses to describe the average level of health on each of these six domains, across all 66 surveys thus far analyzed.

1 Figure 1. Candidate core domains assessed to describe health across populations

Domains indirectly assessing health Domains directly describing health General health Sexual activity Discrimination/stigma Affect* Fertility Participation barriers Cognition* Hearing Self-care* Communication Speech Shame/embarrassment Dexterity Vision Social functioning Mobility* Breathing Usual activities* Pain* Eating Skin & bodily disfigurement Digestion Energy/vitality Bodily excretion * Domains selected for standardized health status module

It is important to stress that the ability to engage in usual activities or self-care does not describe health per se, but limitations or performance in these areas may be associated with lower levels of health in the domains directly describing health (e.g., proximate domains are likely to be more highly correlated with domains that directly assess health, than domains that directly assess health are with one another). Furthermore, although we would prefer to assess health directly, the self-report of limitations in usual activities or self-care may be reported in a more reliable or consistent manner, than the self-report of health in some of the other domains. For this reason, proximate domains are often included in standardized, interview based health status assessment instruments (McDowell and Newell 1996). Nevertheless, other domains directly assessing health listed in Figure 1 are assessed within the in-depth household surveys included in the WHO Multi-Country Survey. The analysis and critical review of data on these additional domains will be presented separately.

1.3 CROSS-POPULATION COMPARABILITY

One of the main advantages of data collected through household surveys is that they provide person or household based health statistics rather than data collected through health services or disease registries, which are episode or event based (United Nations 1995). Self-reported responses in household or other types of interview based survey data are therefore widely used for assessing the health status of populations. These data typically take the form of ordered categorical (ordinal) responses, such as excellent/ very good/ good/ poor/ bad or none/ mild/ moderate/ severe/ extreme. One key analytical issue is that these self-reported ordinal responses are not necessarily comparable across or even within populations primarily because of response category cut-point shifts. This phenomenon differs from other numerous factors -- such as differences in language or measurement error -- that may also contribute to the difference between what is observed and what is reported within an interview, discussed elsewhere (Sadana et al. 2000; Murray et al. 2001).

If the self-reported response results from a mapping between an underlying unobserved latent variable (e.g., level of one domain of health, such as mobility) and categorical response categories, cut-points are threshold levels on the latent variable that characterize the transition from one observed categorical response to the next. If cut-points differ systematically across populations, or even across socio-demographic groups within a population, then the observed ordinal responses are not cross-population comparable since they will not imply the same

2 level on the underlying latent variable that we are trying to measure (Figure 2). Another way of characterizing this problem is that, for the same level of the latent variable on any given domain, the probability of an individual responding in any given response category is different across populations.

Figure 2. Hypothetical shifts in response category cut-points

A BC N

N Mi

N Mo Mi

S Mi

Mo

Mo E S

S Cut-points

E

E

Latent mobility scale N = None, Mi = Mild, Mo = Moderate, S = Severe, E = Extreme

The main self-report question on the domain of mobility from this survey is: "Overall in the past 30 days, how much difficulty did you have with moving around?" Respondents are asked to classify themselves using one of five response categories: "1=Extreme/Cannot do; 2=Severe difficulty; 3=Moderate difficulty; 4=Mild difficulty; 5=No difficulty." We can hypothesize that cut-points may vary between populations because of different cultural or other expectations on each domain of health. Figure 1 illustrates the case when individuals in population C may respond with "extreme" difficulty while individuals in population A with the same true level of mobility may respond with "mild" up to "extreme" difficulty. Given these shifts in cut-points, the differences in the proportion of each population within each response category are not comparable. Cut-points are also likely to vary across cultural or socio-demographic groups, levels of health insurance or other benefits and entitlements, or over time. For example, the cut-points for older individuals may shift as their expectations for level of health on a particular domain diminish with age, i.e., they may under-report difficulties. Men may be more likely to deny declines in health so that their cut-points may be systematically shifted as compared to women, i.e., they may under-report difficulties. Contact with health services may influence expectations for a domain and thus also shift cut-points, i.e., difficulties may be over-reported. These hypothetical shifts in cut-points may be tested with the appropriate methods. However, until recently, most users of data from health interview surveys have interpreted self-reported reported responses at face value.

A recent re-analysis of 64 household interview survey data on health from 46 countries provided further evidence suggesting cross-population cut-point shifts (Sadana et al. 2000). In this previous analysis due to the paucity of data information on all domains of health was combined. Although no external means to calibrate responses were included within these existing and available data sets, the analysis documented that the information content and comparability of the surveys were limited. Many surveys re-analysed did not meet basic criteria, for example that a range of health states (spanning mild to severe) exist at the population level or that health status declines with age These and other limitations prevented valid comparisons of the level of health by age and sex groups within regions as well as across regions. In this earlier analysis, another approach to evaluate the information content and cross-population comparability of the level of health was to interpret the data from

3 surveys in conjunction with other, non-health data from the same countries. A scatter plot of the per capita GDP and the average level of health for the over 65 population (males and females combined), for each of the 46 countries included within this earlier analysis, shows higher levels of per capita GDP are correlated with lower average levels of health. This suggests the existence of cross-population cut-point shifts (Figure 3). Although this evidence based on cross-sectional data is not conclusive, it does suggest that with more information, resources and exposure to health services, population norms and expectations differ for the same age group, and that these differences appear to contribute to the self-report of health. This negative correlation, even if weak, is consistent with earlier findings in that countries, regions, or socio-demographic groups that are wealthier and spend more resources on health, also report worse levels of health (Kroeger et al. 1988; Waidmann et al 1995; Murray 1996), where as the reverse is expected.

Figure 3. Per capita GDP (PPP) vs. Self Reported Level of Health, 65 years and older age group, 46 Countries

100 90 80 70 60 50 40

Level of Health 30 20 10 0 100 1000 10000 100000 Per Capita GDP

Bearing in mind these limitations, the data collection and analysis methods of the WHO Multi-Country Survey are an attempt to enhance the comparability of routine assessments of population health obtained through interview based surveys. Based on the critical evaluation of these methods, improvements will be introduced within the next survey and analysis phase, the World Health Survey.

II. Objectives

The main objective of this paper is to report on the average levels of health by age and sex groups for each domain of health across 66 population based surveys within the WHO Multi- Country Survey. In doing so, we provide an empirical test of new data collection and analysis methods developed to enhance the cross-population comparability of self-reported health. A secondary objective is to provide descriptive data on health for input to other analyses and estimates, such as the estimation of inequalities in the distribution of health or the calculation of summary measures of population health.

III. Methods

4 III.1 DATA: SURVEYS, QUALITY, REPRESENTATIVENESS, SAMPLE SIZE AND RESPONDENT CHARACTERISTICS

3.1.1 WHO Multi-Country Survey Study on Health and Responsiveness 2000-2001. Although WHO routinely collects mortality and morbidity data, the data used within this analyses represents the first effort by WHO to collect data on self-reported health status from population representative surveys, in conjunction with Member States, research institutions and survey organizations. The WHO Multi-Country Survey includes 71 surveys in 61 countries. The survey has a range of modules including: health status description, health state valuations, responsiveness, mental health, chronic health conditions, adult mortality, environmental factors and health financing. Information on the development of content of the overall survey instrument, translation protocols, the various survey modes, selection of sites, sample frames, data collection and management, and quality of the data (e.g., sample population deviation index for age-sex groups, response rates, item missing values, test-retest reliability coefficients, among other attributes), are detailed elsewhere (Üstün et al. 2001). Selected aspects relevant to the data collection, analysis and interpretation of the health status description module are amplified below.

Addressing the challenge of cross population cut-point shifts, two external means to calibrate responses were included within the data collection component of the surveys, vignettes for each of the domains assessed (all 66 surveys) and measured performance tests in domains covering mobility, cognition and vision (limited to the 10 in-depth household surveys). The results presented in this paper reflect the use of the vignette approach to calibrate responses. Each set of vignettes provides a description of a range of fixed levels of ability on each of the domains assessed (domains have between 6-8 vignettes). The concept of vignettes is based on the following reasoning: (i) vignettes fix the level of ability so that variations in categorical responses are attributable to variations in response category cut-points; (ii) the introduction of exogenous information in the form of ratings of vignettes allows us to identify the effects of different covariates (e.g., age, sex, education, country) on both the level of the underlying latent variable (e.g., mobility, affect, etc.), as well as on the cut-points. See Salomon et al (2001) for further details and assumptions on the use of vignettes as a means for enhancing cross-population comparability. A critical evaluation of vignettes as a strategy to calibrate responses across surveys will be presented separately (Sadana et al. 2001), as will the use of measured performance tests (Tandon et al. 2001).

3.1.2 Surveys, Quality. Data available on health status description at the time of this analysis covers 66 population representative surveys in 57 countries using four different modes1. These include 10 in-depth household surveys (interviews lasting around 90 minutes each), 27 brief household surveys (interviews lasting around 35 minutes each), 27 postal surveys (self-administered with questionnaires similar to the brief household surveys), and 2 computer assisted telephone interviews (questionnaires similar to the brief household surveys). Individuals interviewed reported on their own health status, i.e., individuals did not provide proxy reports for others in the household as is the case for many other household surveys including health modules. On average, response rates were highest for the in-depth household surveys (84 per cent), than for the other survey modes, i.e., brief (64 per cent), postal (46 per cent) and telephone (40 per cent). On average, respondent missing data across all items also varied across modes, and was lowest for the brief household surveys (1.5 per cent), followed by telephone (2.1 per cent), postal (6.8 per cent) and in-depth household (12.1 per cent). Two different survey modes were used in Canada, China, Czech Republic, Egypt, Finland, France, Indonesia, Netherlands and Turkey. The average level of health by domain is reported separately for each survey within this paper: a detailed investigation of differences

1 The survey instruments are available on the web: www.who.int/evidence/hhsr-survey/

5 by mode will be provided in a separate analysis. Within the 10 in-depth household surveys, approximately 10 per cent of the sample was re-interviewed in order to estimate test-retest reliability. Weighted Cohen's kappa statistics (corrected for chance agreement) were applied to categorical data. The average values for questions within the six domains assessed of health (affect, cognition, mobility, pain, self-care and usual activities) varied from 0.60 to 0.71, largely indicating substantial agreement. Variations in the reliability of survey items appear greater across countries than across questions within the health module.

3.1.3 Sample size, Representativeness, Respondent characteristics. Table 1 lists the country and survey mode, the mean age, the mean number of years of education, the sample size, age groups excluded (if any) and the per cent that each survey contributes to the overall analysis sample. For inclusion in this analysis, individuals interviewed must have responded to at least one of the core domain questions on health status. The overall analysis sample size is 117,192 respondents from 66 survey in 57 countries. Across all surveys, the average age is 42.0 (range 15 - 115) and the average number of years of education is 10.3 (range 0 - 30). Sample size varies considerably across surveys: the ten in-depth household surveys (n=59,618) contribute just over 50 per cent of the overall analysis sample. The number of surveys included within this analysis from each of the WHO regions is as follows: AFRO (1); AMRO (10); EMRO (7); EURO (39); SEARO (4); WPRO (5).

In general, the surveys provide data that are nationally representative of the civilian, non- institutionalized population 18 years of age and older. Some exceptions to geographic coverage are documented for selected surveys: Canada (both surveys exclude Yukon, Northwest Territories or Nunavut), China (in-depth household survey: includes different socio-economic groups from Shandong, Henan, Gansu Provinces; postal: includes Shandong Province), Columbia (excludes a few areas making up less than 2% of the population such as Orinoquia, the Amazonian Triangle among others), Georgia (excludes Abkhazia and Tskhinvali regions), India (includes Andhra Pradesh State), Indonesia (household: excludes Papua, Aceh and Maluku Provinces), Nigeria (includes Oyo State) and United Arab Emirates (excludes most foreign workers primarily in low skilled jobs).

Based on the individuals sampled and the inclusion criteria in this analysis of the health status description module, age groups2 with insufficient observations (<10) by survey and sex are noted in Table 1, Column IV. These exclusions are primarily restricted to individuals 80 years and over, with the main exceptions being Bahrain, China postal, Jordan, Oman, Republic of Korea, United Arab Emirates and Venezuela where some exclude individuals 60 years and over. In the overall analysis sample, the ratio of males to females is 0.88 (53.3 per cent females and 46.7 per cent males). This ratio varies considerably across surveys. Twenty-two surveys have a ratio greater than or equal to 1.0, with four greater than or equal to 1.5 including Czech Republic brief (1.52), Greece (1.59), Turkey household (1.72) and Republic of Korea (3.09), where as eight surveys have a ratio less than or equal to 0.7, with four less than or equal to 0.6 including Kyrgyzstan (0.60), Columbia (0.53), Ukraine (0.53) and Thailand (0.43). Further details on sampling strategy, the achieved sample characteristics in comparison to the expected characteristics based on census estimates, and sample weights for each survey are found elsewhere (Üstün et al. 2001).

Despite these limitations in geographic, age and sex representativeness, this data set from 66 surveys across 57 countries includes the greatest number of population representative surveys on self-reported health status using the same survey module, to date.

Table 1. Sixty-six surveys from 57 countries: sample size and respondent characteristics I II III IV VVI Mean Mean Age Groups

2 Age groups used to present average level of health match those for input to the estimation of healthy life expectancy: 15-29, 30-44, 45-59, 60-69, 70-79, 80+

6 Age (yrs) Education N Excluded N % of N Country and Survey Mode (yrs) Females Males Females Males

Argentina brief 43.6 10.1 408 366 80+ 80+ 774 0.66 Australia postal 52.8 12.2 511 674 1185 1.01 Austria postal 50.5 11.3 523 506 1029 0.88 Bahrain brief 34.7 11.2 349 447 60+ 70+ 796 0.68 Belgium brief 44.2 13.5 568 531 1099 0.94 Bulgaria brief 45.0 13.7 508 487 80+ 80+ 995 0.85 Canada postal 43.6 14.0 226 180 80+ 80+ 406 0.35 Canada telephone 44.7 14.0 195 190 70+ 80+ 385 0.33 Chile postal 47.7 12.2 509 521 1030 0.88 China household 39.8 9.1 4418 5023 9441 8.06 China postal 40.0 11.4 602 769 60+ 70+ 1371 1.17 Columbia household 40.0 7.4 3939 2080 6019 5.14 Costa Rica brief 37.9 7.4 377 375 80+ 80+ 752 0.64 Croatia brief 47.8 10.6 862 637 1499 1.28 Cyprus postal 47.7 11.9 293 362 80+ 655 0.56 Czech Republic brief 44.1 14.3 425 644 80+ 80+ 1069 0.91 Czech Republic postal 48.7 12.5 613 403 80+ 80+ 1016 0.87 Denmark postal 46.3 13.0 780 723 1503 1.28 Egypt household 39.1 8.0 2518 1967 4485 3.83 Egypt postal 36.8 13.6 675 714 80+ 80+ 1389 1.19 Estonia brief 47.6 9.8 573 427 1000 0.85 Finland brief 47.2 10.0 573 448 1021 0.87 Finland postal 50.6 11.8 797 535 1332 1.14 France brief 43.2 13.6 521 482 80+ 80+ 1003 0.86 France postal 45.1 11.8 360 222 80+ 80+ 582 0.5 Georgia household 45.8 12.2 5692 4154 9846 8.4 Germany brief 46.9 12.9 585 534 80+ 1119 0.95 Greece postal 49.4 11.9 333 529 80+ 862 0.74 Hungary postal 46.6 11.2 696 800 1496 1.28 Iceland brief 39.4 16.0 266 223 80+ 80+ 489 0.42 India household 40.1 3.8 2734 2398 80+ 80+ 5132 4.38 Indonesia household 40.0 7.5 5452 4499 9951 8.49 Indonesia postal 36.3 13.7 1284 1310 70+ 80+ 2594 2.21 Ireland brief 42.5 12.4 352 359 80+ 80+ 711 0.61 Italy brief 45.4 12.3 520 482 80+ 1002 0.86 Jordan brief 34.8 10.3 407 391 70+ 70+ 798 0.68 Kyrgyzstan postal 43.9 12.7 669 403 80+ 80+ 1072 0.91 Latvia brief 48.9 11.8 338 422 80+ 760 0.65 Lithuania postal 47.2 10.2 997 768 1765 1.51 Luxembourg telephone 45.3 13.6 400 319 80+ 80+ 719 0.61 Malta brief 47.4 11.7 256 244 80+ 80+ 500 0.43 Mexico household 41.8 9.4 2576 1760 4336 3.7 Morocco brief 35.9 7.4 376 376 70+ 80+ 752 0.64 Netherlands brief 44.1 13.6 591 493 80+ 1084 0.92 Netherlands postal 50.5 13.6 277 308 80+ 585 0.5 New Zealand postal 48.6 13.0 969 732 1701 1.45 Nigeria household 35.9 8.0 2788 1779 4567 3.9 Oman brief 33.5 11.4 382 502 60+ 60+ 884 0.75 (continued)

Table 1. Sixty-six surveys from 57 countries: sample size and respondent characteristics (continued)

7 I II III IV V VI Mean Mean Age Groups Age (yrs) Education n Excluded N % of N Country and Survey Mode (yrs) Females Males Females Males

Poland postal 45.1 11.9 438 430 868 0.74 Portugal brief 45.3 8.7 557 444 1001 0.85 Republic of Korea postal 52.0 11.0 87 269 70+ <30; 80+ 356 0.3 Romania brief 45.4 13.7 530 521 80+ 1051 0.9 Russian Federation brief 42.7 14.9 857 744 80+ 1601 1.37 Slovakia household 42.3 11.9 647 531 80+ 1178 1.01 Spain brief 43.4 11.4 512 486 80+ 998 0.85 Sweden brief 48.1 10.2 536 463 999 0.85 Switzerland postal 45.9 12.4 204 265 80+ 80+ 469 0.4 Thailand postal 40.9 8.1 836 359 80+ 70+ 1195 1.02 Trinidad and Tobago postal 42.4 11.8 821 503 1324 1.13 Turkey household 32.5 10.2 1716 2947 80+ 80+ 4663 3.98 Turkey postal 34.0 9.2 1325 1072 80+ 80+ 2397 2.05 Ukraine postal 44.4 13.1 502 268 80+ 80+ 770 0.66 United Arab Emirates brief 33.8 12.9 407 451 60+ 60+ 858 0.73 United Kingdom postal 51.0 13.1 531 444 975 0.83 United States postal 52.7 14.1 531 657 1188 1.01 Venezuela brief 34.7 10.8 362 378 60+ 60+ 740 0.63 Total 42.0 10.3 62462 54730 117192 % 53.3 46.7 100

8 III.3 QUESTIONS, RESPONSE SCALES, RECALL PERIODS

Based on the six domains assessed selected to describe health, questions assessing each domain were selected from existing standardized surveys that have already been pilot tested in multi-country studies (Üstün et al. in press). Table 2 lists the main question for each domain and the number and topics of the auxiliary questions for each domain assessed. For all questions, the recall period is the last 30 days, the most common time frame in standardized health status assessment instruments. Questions either asked the respondent to assess the degree to which a particular state was experienced, or the amount of difficulty associated with a particular state, by domain.

Table 2. Main and Auxiliary Questions for Six Domains, using standard response scale (None, Mild, Moderate, Severe, Extreme), WHO Multi-Country Survey on Health and Responsiveness 2000-2001 Domain Main Question Number and Content of Auxiliary Questions

Affect Overall in the last 30 days, how much distress, (4) time spent feeling happy and cheerful/ sad, sadness or worry did you experience? empty, depressed/ irritable or in a bad mood/ worried a lot Cognition Overall in the last 30 days, how much difficulty (4) difficulty in concentrating on doing something did you have with concentrating or remembering for 10 minutes/remembering to do important things? things/ analyzing and solving problems in day to day life/ learning a new task Mobility Overall in the last 30 days, how much difficulty (4) difficulty to stand up from sitting down/moving did you have with moving around? around inside one's home/ climbing several flights of stairs or walking up a steep hill/ performance of vigorous activities such as running, lifting heavy objects, participating in strenuous sports Pain Overall in the last 30 days, how much pain or (1) amount of bodily pain or discomfort discomfort did you have? Self-Care Overall in the last 30 days, how much difficulty (3) difficulty in washing your whole body/getting did you have with self-care, such as washing or dressed/staying by yourself for a few days dressing yourself? Usual Overall in the last 30 days, how much difficulty (3) difficulty in taking care of household Activities did you have with work or household activities? responsibilities/getting all the housework done that you needed to do/being limited in the type of household work

III.4 TREATMENT OF ITEM LEVEL MISSING DATA

As noted, for inclusion in the analysis on health status description, individuals interviewed must have responded to at least one of the domain questions on health status (Table 2). If a respondent had answered none of the domain questions, then this respondent was dropped from the analysis: using this criteria less than 50 cases were dropped across all 66 surveys. If a respondent had answered all six domain questions, then this respondent was considered as a case. For all intermediary situations, i.e., individuals who had responded between one to five of the domain questions, all were also considered as cases. Key socio-demographic information required for all cases included age, sex and years of education, along with the survey (i.e., country and mode of survey). For all cases, missing data concerning age, sex, years of education and level of health on up to five of the core domain questions were subsequently estimated using the multiple imputation method employed by the software program AMELIA and its EMis algorithm (Honaker et al. 1999). The per cent of missing data for the background variables imputed on average for all cases was very low across all but one of the surveys: sex (<0.1%), age (<0.5%), and years of education (<0.1% excluding Indonesia household, where years of education was missing for 16% of cases). Likewise, the per cent of missing data for the main question assessing each domain of health imputed for all cases was very low across surveys, <0.5% for each of the six main questions. Missing data at

9 the item level on auxiliary questions for each of the six domains assessed in the in-depth household surveys (i.e., 10 of the 66 surveys), were not imputed.

III.5 ANALYSIS METHOD TO ENHANCE COMPARABILITY: ADJUSTING FOR CROSS-POPULATION CUT-POINT SHIFTS

The analysis approach addresses the key challenge concerning the comparability of self reported health status data collected through interview based surveys: cross-population cut- point shifts. In conjunction with the data collection strategies that incorporate an external means to calibrate responses, the analytical methods applied here should be viewed as a significant improvement over previous methods used to enhance cross-population comparability on existing data sources without external calibration methods (see Sadana et al. 2000; Tandon et al. 2001).

3.5.1 Hierarchical ordered probit (HOPIT) model. We have applied the hierarchical ordered probit (HOPIT) model, a variant of the standard ordered probit model and to some degree, of the partial credit model from item response theory. The key innovations in the HOPIT model are that: (a) cut-points are allowed to be functions of explanatory variables, (b) vignettes are used to estimate cut-points across different populations, and (c) interval regression is applied to self-report questions in order to estimate cross-population comparable levels of ability on any given domain. See Tandon et al. (2001) for details on the background, development and testing of the statistical model on simulated data.

The HOPIT model is estimated using maximum likelihood techniques. In brief, there are several components to the likelihood function. The first component utilizes information from responses to vignettes. In this component of the likelihood function, the model assumes there is an underlying latent variable for the set of vignettes, addressing a particular domain of health, Y*. Each vignette v=1,…,V represents a fixed level on this latent variable, i.e., mobility, affect, pain, etc. This latent variable is not observed. What are observed are categorical responses for each of the vignettes Yv. In other words, respondents evaluate each of the vignettes using the same 5-point response category scale and with regard to the same question as the main self-reported question for any given domain. The mapping from the latent variable to the observed categorical responses is defined by a series of cut-points which are allowed to differ by socio-demographic characteristics of the individual (e.g., age, sex, years of education, and country of residence). These categorical responses are the left-hand side variable in the first component of the HOPIT model (each vignette response being a separate observation). On the right-hand side are dummies for each of V-1 vignettes, with the first vignette (describing the best ability level) being set to be the absorbed category and therefore equivalent to 0. In essence, the model fixes the level of ability on the underlying latent variable (i.e., each domain of health) scale such that any differences in response categories are attributed to cut-point shifts. The coefficients on these for each of V-1 vignettes dummy variables are the fixed levels on the underlying latent variable. Mathematically, this implies that:

Y*v = f (dummy variable for each vignette)

And the observation mechanism such that categorical response Yv is chosen:

Yv = 1 if -A < Y*v < 1 Yv = 2if 1 < Y*v < 2 … Yv = 5 if 4 < Y*v < +A

Plus,

10 ’s = f (socio-demographic characteristics)

The second component of the likelihood function utilizes information from self-report responses. Cut-points are estimated from the vignettes section of the likelihood to calibrate the self-report responses so as to make them cross-population comparable. In this sense, there is parametric dependence between these two different components of the likelihood function. The mean variable of the latent variable now refers to the individual’s latent variable and this is assumed to be a function of socio-demographic characteristics. Mathematically,

Y*s = f (socio-demographic characteristics)

And the observation mechanism for the main self-report Ys:

Ys = 1 if -A < Y*s < 1 Ys = 2if 1 < Y*s < 2 … Ys = 5 if 4 < Y*s < +A

And,

’s = f (socio-demographic characteristics)

3.5.2 Compound Hierarchical Ordered Probit (CHOPIT) Model (HOPIT with auxiliary questions). The third component of the likelihood function uses information from auxiliary questions. The mean level of the latent variable is assumed to be the same as that for the main self-report question. Cut-points for this component are not linked to the vignettes. However, since the scale is being set as the same as that for the main question, the cut-points are comparable to the ones recovered for the main self-report question. Mathematically,

Y*s = f (socio-demographic characteristics)

The observation mechanism for each of the auxiliary questions Ya is such that:

Ya = 1 if -A < Y*s < 1 Ya = 2if 1 < Y*s < 2 … Ya = 5 if 4 < Y*s < +A

And,

’s = f (socio-demographic characteristics)

In this data set, auxiliary questions exist only for the 10 in depth household surveys.

3.5.3 Random Effect. If there is an individual-level random effect in the data -- i.e., when covariates in our model do not capture all the systematic variation in the latent variable -- then there remains information content in the set of responses (when more than one question per domain exists) on the level of health for each individual that has not been fully exploited, or there are covariates missing from the model. In order to exploit the information content in the set of responses we can make use of Bayes' theorem to obtain estimates of the mean level of the latent variable conditional on the observed set of responses for a given individual (see

11 Tandon et al. 2001 for an evaluation of this approach using simulated data). For now within HOPIT we assume that the random effect captures about 50 per cent of the variation in estimated variance of the error term. Under this assumption, the posterior prediction of the Y* for each of the six domains for all 66 surveys, conditional on the observed pattern of responses, has been computed.

3.5.4 Evaluation of model fit. Assessing goodness-of-fit for categorical data is not straightforward. One can compute a simple count-R² which is a measure of the proportion of correct responses obtained for a given sample. For ordinal data, the predicted categorical response would be the one associated with the maximum predicted probability. Other options include a pseudo-R² measure, which in software such as STATA, is a likelihood-based comparison of the model with all the parameters to one with only the intercept (Long and Freese 2001). Rasch-based models use measures of fit such as "outfit" and "infit": "outfit" is a chi-square test based on the sum of the standardized deviation of observed versus expected values of a response. "Infit" is also a chi-square test which utilizes an information-weighted sum by adjusting for extreme responses using weights (Write and Mok 2000). In order to assess model fit, a standard likelihood ratio test can be used. These tests compare the log- likelihood value of the full model with a constrained version of the same model (i.e., a model that is nested within the full model) to assess the contribution of the dropped covariates to the likelihood function. Assume L0 is the log-likelihood value associated with the full model and L1 is the log-likelihood value of the constrained model. Then -2(L1-L0) is distributed χ² with d0-d1 degrees of freedom, where d0 and d1 are the model degrees of freedom associated with the full and the constrained models on exactly the same sample, respectively (Long and Freese 2001).

III.6 AVERAGE LEVEL OF HEALTH ON SIX DOMAINS: RESCALE, AGE STANDARDIZATION

3.6.1 Rescale. Using the predicted level of health for each domain Y* incorporating the individual-level random effect, we re-scale our results across surveys, for each domain separately. This is so as the scale of the predicted level of health Y* is arbitrary and differs for each domain. For presentation purposes we equalize the scale across populations while maintaining the relative differences and distribution of severity within each population across the 66 surveys. We apply a simple transformation of the predicted Y* to a 0 to 100 scale, by domain. We truncate the end-points of the estimated level of health Y* to provide greater stability and confidence in the comparability of end points selected. Rather than using the observed minimum and maximum Y* per domain across all 66 surveys in the transformation, we equate the bottom 2.5 % and top 97.5% of the distribution of predicted level of health Y* by domain, to 0 and 100, respectively. For different sex and age-groups3, the mean value of this estimated level is reported for all 66 surveys and for each of the six domains. The posterior estimates of health, Y* are relative to one another and do not reflect an absolute scale (for each domain). Comparisons of the estimated level of health may be made within each domain of health, not across domains.

3.6.2 Age Standardization. In order to facilitate comparisons across countries, we calculated age-standardized aggregated results for all age groups, by sex, for each of the 66 survey included within this analysis. We apply the UN Population Division 1999 revised World Standard Population (Ahmad et al. 2000) to males and females. We then summarize the level of health by domain across all age groups, reflecting the age groups actually sampled, by sex and survey.

3 except for those with <10 observations as noted in Table 1 column IV.

12 III.7 EVALUATION OF METHODS

We now turn to a general evaluation of this method before presenting our results across surveys. Unlike Tandon et al. (2001) who provide an evaluation of the HOPIT model based on simulated data where "truth" is known, we either test or provide examples of the impact of each step of the methods applied to the WHO Multi-Country Survey data where "truth" is unknown. We subsequently discuss whether our methods appear to enhance the information content and comparability of data.

The following tests or examples are provided:

S Evidence of cut-point shifts across countries (the first component of the likelihood function) S Posterior estimates (HOPIT with and without random effect component) S Estimated level of health: comparison of ordinal responses and estimated level of health, by domain (the second component of the likelihood function) S Estimated level of health: HOPIT vs. HOPIT with auxiliary questions (the third component of the likelihood function) S Model fit: likelihood ratio test for full and nested model (addressing addition of covariates to cut-points)

3.7.1 Evidence of cut-point shifts across countries (the first component of the likelihood function). Two null hypotheses concerning this first approach are proposed. The first is that the response pattern on the rating of vignettes for each domain is constant across surveys. Figure 4 illustrates the proportion of responses in each response category for each of the seven vignettes for the domain of Self Care: in-depth household surveys in India (Andhra Pradesh) and China (three provinces) illustrate that these proportions differ. Figure 5 summarizes these differences by illustrating the mean rating of vignettes in two other domains assessed, Affect and Pain, for one survey from each WHO Region (AFRO: Nigeria; AMRO: Argentina; EMRO: Jordan; EURO: Croatia; SEARO: Thailand; WPRO: Australia). For any set of vignettes, the response distribution in each of the five categories differs by country, as well as by other covariates (not shown), and therefore are not constant across surveys. A critical evaluation of vignettes as a means to calibrate responses across populations within the health status analysis is beyond the scope of this paper and will be provided elsewhere.

Figure 4. Proportion of responses in each category (in depth household surveys conducted in India and China), seven vignettes addressing domain of Self Care

100 100

80 80

60 60 % % 7 40 40 7 6 6 5 20 5 4 20 Self Care 4 Self Care 3 Vignettes 3 0 0 vignettes 2 2 1 1 2 1 2 1 3 3 4 4 5 5 Response Category -- Response Category -- India China

13 Figure 5. Mean ratings of Vignette Sets (one survey from each WHO Region) for Affect and Pain

5 5

4.5 4.5

4 4 Nigeria Nigeria 3.5 Argentina 3.5 Argentina Jordan Jordan 3 3 Croatia Croatia 2.5 Thailand 2.5 Thailand Mean Rating Mean Rating Mean Australia A ustralia 2 2

1.5 1.5

1 1 123456 1234567 Affect Vignettes Pain Vignettes

The second null hypothesis is that the cut-points on the latent variable for each domain do not vary given differences in covariates (e.g., age, sex, years of education, and survey population). In this paper, we focus on differences across survey populations. Figure 6 illustrates the distribution of mean cut-points (t1-t4) for each domain: cut-points vary by survey. For each cut-point, each data point in the distribution represents one of the 66 surveys. The x-axis notes: t1 which is the transition from the ordinal category "extreme difficulty" to the next best ordinal category, "severe difficulty"; t2, the transition from "severe" to "moderate"; t3, the transition from "moderate" to "mild"; and t4, the transition from "mild" to "no difficulty" or the best category. The y-axis represents the latent variable scale for each domain, with the horizontal lines being the coefficients on each of the vignettes from the first component of the likelihood function (the best vignette is set to 0). These coefficients set the scale on the underlying latent variable across all surveys. A distribution exists for t1-t4 and these shifts in cut-points reflect mean differences across surveys (see Tandon et al. 2001).

Figure 7 provides further detail on the domain of cognition. From the first part of the likelihood function, the vignette describing the best state of cognition has a coefficient of 0, and the vignette describing the worst state of cognition, has a coefficient almost equivalent to -4. Let us focus on a fixed level of cognition (on the y axis: -2.5). This level corresponds roughly to the following vignette describing difficulties in concentration and memory: “Mr X is easily distracted, and within 10 minutes of beginning a task, his attention shifts to something else. He can remember important facts when he tries, but several times a week he finds that he has to struggle to recollect what people have said or recent events.” On average, individuals from Indonesia will rate this level of cognition “mild difficulty”, while individuals from 11 other surveys (from Greece, France, Trinadad & Tobago, Chile, Luxembourg, Belgium, Nigeria, Bulgaria, Denmark, Iceland or Netherlands) on average will rate this same level of cognition, "moderate difficulty.” Differences across selected countries are significant: for example, t2 for Indonesia (-2.96) vs. Netherlands (-2.33).

We interpret these differences to mean that for the populations in the 11 countries noted, on average, they have higher standards or norms for what constitutes “mild” difficulty in comparison to “moderate” difficulty, for cognition, in comparison to Indonesia: Indonesians on average have lower norms -- this is why Indonesia’s cut-points are found at the lower end of each cut-point distribution -- shown here for cut-point 2 and 3. As noted, cut-points are

14 also allowed to vary by age, years of education and sex. Appendix 1 details the mean cut- points (t1-t4) values for all 66 surveys, for the domain of cognition.

Figure 6. Distribution of cut-points (t1-t4) and mean vignettes' coefficients (Cognition, Mobility, Usual Activities), for each of the 66 surveys

Cognition

1

0

-1

-2

-3 Vignettes' Coefficients Main question - Cognition

-4

-5 t1 t2 t3 t4 cut-points

Mobility

1

0

-1

-2

-3 Vignettes' Coefficients Main question - Mobility

-4

-5 t1 t2 t3 t4 cut-points

Usual Activities

1

0

-1

-2

-3 Vignettes' Coefficients Main question - Usual Activities -4

-5 t1 t2 t3 t4 cut-points

Figure 6 (continued). Distribution of cut-points (t1-t4) and mean vignettes' coefficients

15 (Affect, Pain, Self-Care), for each of the 66 surveys Affect

1

0

-1

-2

-3 Main question - Affect Vignettes' Coefficients -4

-5

-6 tau1 tau2 tau3 tau4 cut-points

Pain

3

2

1

0

-1 Main question - Pain Vignettes' Coefficients -2

-3

-4 tau1 tau2 tau3 tau4 cut-points

Self Care

1

0

-1

-2

-3 Vignettes' Coefficients Main question - Self Care

-4

-5 tau1 tau2 tau3 tau4 cut-points

16 Figure 7. Distribution of mean cut-points, by survey: same estimated level of Cognition, different cut-points, using vignette strategy to calibrate responses across surveys

Cognition

1

Greece, France, Trinadad & Tobago, Chile, 0 Luxembourg, Belgium, Nigeria, Bulgaria, Denmark, Iceland, Netherlands

-1

-2

-3 Indonesia Vignettes' Coefficients Vignettes' Main question - Cognition - Main question

-4 Indonesia

-5 t1 t2 t3 t4 cut-points

Another way of looking at this same distribution of cut-points for Cognition, is that real data can parallel the simulation by Tandon et al. (2001): here Andhra Pradesh is similar to population A, with lower standards for what is good health, and Luxembourg is similar to population B, with higher standards for what constitutes good health (Figure 8). Across cut- points for both populations, we find that for each cut point spanning different levels of cognition, Luxembourg has higher standards for cognition, before it transitions to next "mildest" difficulty category, in comparison to individuals from Andhra Pradesh: on average, they transition to the next "mildest" difficulty category at lower levels of cognition.

Figure 8. Distribution of mean cut-points, by survey: evidence of systematic cut-point shifts between two survey populations (Luxembourg and India (Andhra Pradesh))

Cognition

1 LUX

0 LUX -1 LUX

-2 IND LUX -3 IND Vignettes' Coefficients Vignettes' Main question - Cognition Main question

-4 IND

IND -5 t1 t2 t3 t4 cut-points

17 Given that Luxembourg has the highest GDP (PPP) and India, one of the lowest, among populations included within this analysis, differences in norms, standards and expectations for health on different domains are not surprising. Of course, other health and non health system factors, and socio-cultural and economic correlates are likely to contribute to these differences in mean cut-points across countries: similar results are found for the other five domains. The interesting point is here we have evidence that collectively such differences do influence, in a seemingly systematic way, the rating of standardized descriptions of health on different domains, i.e., the vignettes. The new methods use this information to calibrate or adjust people’s self-report of their own health status on the same domains, across survey populations.

3.7.2 Estimated level of health: HOPIT with and without posterior estimates (addressing random effect). Based on the assumption that the random effect captures about 50 per cent of the variation in estimated variance of the error term, the posterior prediction of individual level of health is compared to the prediction of individual level of health without this random effect component. Across all 66 surveys, the correlation of the estimated level of health, Y* based on the prior and posterior estimates by domain, vary between 0.72 and 0.92 (i.e., Affect: 0.72; Cognition: 0.72; Pain: 0.81; Mobility: 0.84; Self Care: 0.92; Usual Activities: 0.80.).

Tandon et al. (2001:13-14) demonstrate with a simulated data set where truth is known, the R-squared between "True Mobility" and the predicted Y* of Mobility using the HOPIT model only with covariates is 0.055: however, with the posterior estimate, the R-squared jumps to 0.334. They conclude that the posterior estimates significantly improves the estimation of health in the simulated data set. For the survey data, we are unable to evaluate whether the addition of a correction for individual random effect performs better. We have simply assumed that the random effect captures 50 per cent of the variation, and we hypothesize that we capture more of the systematic variation on the latent variable due to covariates not measured.

3.7.3 Estimated level of health: comparison of ordinal responses and estimated level of health, by domain (the second component of the likelihood function). To evaluate the overall impact of the analysis approach applied, we compare mean ordinal responses (the five categories) for each age and the estimated level of health Y* (based on our posterior estimates from the HOPIT model), for all six domains assessed of health. We extend our comparison between Luxembourg and India (Andhra Pradesh), to illustrate the difference our methods make on the estimated level of health, across all domains. These results appear quite remarkable (Figure 9).

Across all domains, a higher score is better health. If we only look at the self-reported ratings using five categories (the circles on the graphs), there is not much difference in the distribution of mean responses for each single year of age, between Luxembourg, on the left, and Andhra Pradesh, on the right, concerning the level of self-reported health across most domains. Most analyses on health status data from surveys stops here. However, if we instead focus on the estimated level of health based on our new methods (the triangles), we see that the mean levels of health tend to be lower in Andhra Pradesh than Luxembourg for most domains, and that the drop across age4 is steeper for Andhra Pradesh across most domains, in comparison to Luxembourg.

4 The spread of mean level of health Y* (triangles in Figure 9 most prominent in self-care) by age reflects that in our estimate of Y* for each domain, the covariate age is divided into four categories, rather than as a continuous variables.

18 Figure 9. Mean response on ordinal categories vs. posterior estimated level of health (Affect, Cognition, Mobility), Luxembourg and India

Luxembourg (n=719) India (n=5132) Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100 bourg 4 4 E. India

3 3 BAY R.E. Luxem PIT & BAY R. PIT

2 2 Mean HO Y* Mean categorical response - Affect Mean categorical response - Affect - response categorical Mean Mean Y* HOPIT & & HOPIT Y* Mean

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100

4 4

3 3

2 2 Mean Y* HOPIT & BAY R.E. India Mean categorical response - Cognition Mean categorical response - Cognition Mean Y* HOPIT & BAY R.E. Luxembourg

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100 bourg 4 4 BAY R.E. India 3 3 BAY R.E. Luxem

2 2 Mean Y* HOPIT & & HOPIT Mean Y* Mean categorical response - Mobility - response Mean categorical Mobility - response Mean categorical Mean Y* HOPIT & & HOPIT Mean Y*

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

(continued)

19 Figure 9. Mean response on ordinal categories vs. posterior estimated level of health (Pain, Self Care, Usual Activities), Luxembourg and India (continued)

Luxembourg (n=719) India (n=5132) Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100 bourg 4 4

3 3 BAY R.E. Luxem

2 2 Mean categorical response - Pain Mean Y* HOPIT & BAY R.E. India Mean categorical response - Pain response Mean categorical Mean Y* HOPIT & & HOPIT Mean Y*

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100

4 4

3 3

2 2 Mean Y* HOPIT & BAY R.E. India & BAY R.E. Mean Y* HOPIT Mean categorical response self - care Mean categorical response self - care Mean Y* HOPIT & BAY R.E. Luxembourg & BAY R.E. Mean Y* HOPIT

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

Mean response 5 categories Mean Y* HOPIT & BAY R.E. Mean response 5 categories Mean Y* HOPIT & BAY R.E.

5 100 5 100

4 4

3 3

2 2 Mean Y* HOPIT India & BAY R.E. Mean Y* HOPIT Luxembourg & BAY R.E. Mean categorical response - Usual Activities Mean categorical response - Usual Activities

1 0 1 0 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Age Age

Although each population rates average levels of health on domains assessed in a similar fashion using categorical responses across ages, based on evidence of shifts in response category cut-points, these mean ratings using ordinal categories are not comparable across the two survey populations. That Luxembourg has higher life expectancy for both males and females, as well as the lower incidence and prevalence of a wide range of diseases, it is not surprising that for many domains of health, Luxembourg has higher levels in comparison to

20 Andhra Pradesh. We propose that our posterior estimates based on the HOPIT model have greater face validity given expected differences in health status between the two countries, than those based on the ordinal responses. Another indication that the information content of the survey data has improved, is that the large ceiling effects (i.e., proportion of respondents in the best ordinal response category) that are often in population based surveys have also been reduced (for example, Luxembourg, self-care). Additional comparisons based on the results from the HOPIT model, with those where the t1-t4 do not vary by covariates, is underway.

3.7.4 Estimated level of health: HOPIT vs. CHOPIT (the third component of the likelihood function). We now turn to the in-depth household surveys (n=59,618) that contain auxiliary questions addressing each core domain of health, and consider if auxiliary questions add information content to the estimated average level of health, Y* for each domain. We explore this question by comparing the correlation of our prior estimates of Y* with and without auxiliary questions, as well as comparing the distribution of the levels of health for one domain in the 10 in-depth household surveys. For the domain of Mobility, the correlation is 0.99 within each of the in-depth household surveys: almost no difference exists in results between the current versions of HOPIT and CHOPIT models using the same vignettes and covariates. For example, the cumulative frequency of different levels of mobility based on HOPIT and CHOPIT for data from Mexico and Egypt (Figure 10) are very similar (shifted), as is the smoothness of these distributions (e.g., a smoother distribution of the cumulative frequency would reflect finer distinctions between different severity levels.)

Figure 10: Cumulative Frequency Distribution of different levels of Mobility, based on prior estimates Y* from HOPIT vs. CHOPIT Models

Mexico (n=4336) Egypt (n=4485) Cond. cdf of HOPIT Cond. cdf of CHOPIT Cond. cdf of HOPIT Cond. cdf of CHOPIT

1 1

Hopit Y* Chopit Y*

.5 .5 Cummulative Frequency Distribution Cummulative Frequency Distribution

0 0 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Level of Mobility -- Mexico Level of Mobility -- Egypt

A comparison of the posterior estimates from HOPIT and CHOPIT may offer different results, and is currently being pursued. In addition, further work is under way on one hand to investigate whether auxiliary questions add information content beyond what is contained in the main question addressing each domain, and on the other hand gauge the minimum number of questions required (e.g. item reduction strategies). Results in this paper across all 66 surveys are based on posterior estimates Y* reflecting the HOPIT model.

21 3.7.5 Model fit: likelihood ratio test for full and nested models (addressing addition of covariates on the cut-points to the basic model where cut-points are invariable).

We compare the full HOPIT model with vignettes and covariates (age, sex, years of education, and survey population) on cut-points (e.g., t1-t1), with the nested model with no covariates on the cut-points (i.e., t1-t4 do not vary by age, sex, years of education, or survey population) for the following two domains as an example.

Affect Mobility χ²(280) = 8144.36 χ²(280) = 10013.74 Prob > χ² = 0.000 Prob > χ² = 0.000

Both tests compare the log-likelihood value of the full model with the constrained version of the model on exactly the same sample: this test shows that adding all of the covariates on the cut-points significantly adds to the explanatory power of the model applied to either domain of health. Across the six domains, differences across age groups are significant across most cut-points (i.e., t1-t4). Sex and years of education are usually significant, but not always (not shown).

IV. Results

Using the methods developed and evaluated in section 3, we have estimated the average level of health for each of six domains assessed of health, for males and females, in six age groups based on the self-report of health within 66 surveys from 57 countries included within the WHO Multi-Country Survey. We also estimated the average level of health by domain for the total population sampled in each survey, by sex, in order to facilitate comparisons across countries. The posterior estimates of health, Y* are domain-specific, on a scale defined by the coefficients of vignettes for each domain, and then rescaled 0 to 100, as described earlier. In all of the figures and tables presented, 100 is the best level of self-reported health, whereas 0 is the worst5 level of self-reported health, across the 66 surveys analyzed. Comparisons of the estimated level of health may be made within each domain of health, not across domains. A higher level of pain actually refers to the absence of pain, which is better health.

IV.1 ESTIMATION RESULTS: HOPIT BY DOMAIN ACROSS ALL 66 SURVEYS

Before detailing the average levels of health by domain, we provide the HOPIT model estimates on key variables (Table 3). Neither dummy variables for each survey nor covariates across cut-points are shown (see Appendix II for the complete set of covariates and estimates, including for each cut-point, for the domain of Cognition). The coefficients on the vignettes fix the scale of the latent variable, with the vignette describing the best level of health in each domain being set to 0 (see Figure 6): except for the domain of pain, the coefficients on each vignette are in the expected order given the severity level described. The estimates on covariates should be interpreted in relation to the absorbed categories or baseline values for covariates (age group 15-29; 0 years of education; females; and the survey from United Arab Emirates6). Across all domains, the estimated level of health Y* decreases for each age group, increases with years of education, and on average is higher for males than for females (Table 3).

5 Zero is not equivalent to death but to the worst level of self-reported health reported 6 United Arab Emirates is the baseline country only due to its abbreviation in the analysis "ARE" and is the first country listed in alphabetical order.

22 IV.2 ESTIMATED LEVEL OF HEALTH ON EACH DOMAIN, BY AGE -SEX GROUPS

Age-specific estimates for the average level of health by domain are presented for the following age groups, by sex: 15-29; 30-44, 45-59, 60-69, 70-79, 80 and over. Figures 11 - 16 each cover one domain and include all 66 surveys: Canada, China, Czech Republic, Egypt, Finland, France, Indonesia, Netherlands and Turkey are listed twice, with the different survey modes noted across all 66 surveys. These results across ages are grouped by the six WHO regions. For the European Region which has the largest number of surveys included within this analysis, countries are sub-divided into four groups of graphs.

The average level of health for each domain (affect, cognition, mobility, pain, self care and usual activities) within age groups and trends across age groups should be reviewed separately. For example, across age and sex groups, average levels of affect are better in Mexico, Egypt, Indonesia, Ireland and China, in comparison to other countries in the same region. However, the same pattern does not exist across all domains. For example, the highest average level of mobility is not always achieved by the same country across age and sex groups within each region. Furthermore, some domains have much greater variation across age groups (i.e., mobility or cognition) than others (i.e., affect).

IV.3 LEVEL OF HEALTH ON EACH DOMAIN, AGGREGATED FOR THE TOTAL SURVEY POPULATION, BY SEX

Country level age-specific estimates for health by sex were aggregated to estimate the age- standardized level of health by domain to facilitate comparison across all survey populations. Table 4 presents these results by domain for all 66 surveys in alphabetical order by survey population. Tables 5-10 provide these results in rank order based on the average estimated level for males and females combined, and also include the ratio of male to female level of health, for each domain. Figures 17-22 illustrate these results by domain, as well as compare the average level of health for each domain between males and females with life expectancy (Lopez et al. 2001) for males and females respectively, and the combined average for both sexes, with per capita GDP (Evans et al. 2001).

Countries at the top and bottom across domains are similar, but not identical. For males and females combined, the data collected through these surveys indicate that Indonesia (household) has the highest level of self-reported affect (Table 5), followed by Ireland, Nigeria, Germany, Luxembourg, Belgium, Spain and Mexico. The lowest self-reported level of affect is in Kyrgystan, followed by Turkey (postal), Ukraine, Latvia, Romania, Lithuania, Croatia, Poland, Hungary and Cyprus. Except for Costa Rica and Venezuela, males report equal or higher levels of affect than women across all surveys: a male to female ratio of greater than or equal to 1.15 is noted in Chile, Czech Republic (postal), Columbia, Egypt (postal), Argentina, Morocco, Cyprus, Lithuania, Romania, Ukraine, Turkey (postal), and Kyrgyzstan. At higher levels of average health for both sexes in this domain, the male to female ratio tends to be smaller, than at lower average levels of affect.

For cognition (Table 6), Ireland has the highest self-reported level followed by Nigeria, Spain, Russian Federation, Germany, Mexico, Finland, Indonesia (household), Luxembourg, Egypt (household). The lowest self-reported level of cognition is in Kyrgystan, followed by Turkey (postal), Trinidad & Tobago, Lithuania, Egypt (postal), Morocco, Thailand, Indonesia (postal), Ukraine and Poland. The striking difference between estimates from Indonesia and Egypt based on household and postal surveys requires further examination, beyond the scope of this paper. Except for Canada (telephone), Costa Rica and Venezuela, males report equal or higher levels of cognition than women across all surveys: a male to female ratio of greater

23 than or equal to 1.15 is noted in Egypt (household and postal), Italy, Argentina, Columbia, India, Turkey (household and postal), China (household), United States, Romania, Croatia, Cyprus, Bahrain, Portugal, Republic of Korea, Jordan, Poland, Ukraine, Indonesia (postal), Thailand, Lithuania, Trinidad and Tobago, Kyrgyzstan and Morocco (at 1.63). At higher levels of average health for both sexes in this domain, the male to female ratio tends to be smaller, than at lower average levels of cognition.

For mobility (Table 7), Indonesia (postal and then in-depth household) has the highest self- reported level followed by Italy, Spain, Luxembourg, France (brief), Greece, Ireland and Denmark. The lowest self-reported level of mobility is in Kyrgystan, followed by Lithuania, Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan, Croatia, and Slovenia. Except for Costa Rica, males report equal or higher levels of mobility than women across all surveys: a male to female ratio of greater than or equal to 1.15 is noted in Chile, Georgia, Iceland, Portugal, Bahrain, Republic of Korea, Russian Federation, Netherlands (brief), Egypt (household and postal), Thailand, India, Romania, Slovakia, Croatia, Jodran, Ukraine, Turkey (postal), Lithuania, Kyrgyzstan and Morocco (at 1.58). At higher levels of average health for both sexes in this domain, the male to female ratio tends to be smaller, than at lower average levels of mobility.

For pain (Table 8), United Arab Emirates has the highest self-reported absence of pain followed by Ireland, Spain, Nigeria, China (household), Oman, Mexico, Italy, Germany, and China (postal). The highest self-reported level of pain is in Kyrgystan, followed by Republic of Korea, Indonesia (postal), Turkey (postal), Lithuania, Ukraine, Cyprus, Poland Egypt (postal) and Austria. The lowest self-reported level of mobility is in Kyrgystan, followed by Lithuania, Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan, Croatia, and Slovenia. In all surveys males report equal or higher levels of absence of pain than women: in 29 surveys, a male to female ratio of greater than or equal to 1.15 is noted. Those over 1.25 include Morocco (1.37), Romania (1.26), Cyprus (1.3), Lithuania (1.26), Turkey postal (1.32), Indonesia postal (1.27) and Kyrgyzstan (1.47). At higher levels of average health for both sexes in this domain, the male to female ratio tends to be smaller, than at lower average levels of the absence of pain.

For self care (Table 9), Luxembourg has the highest self-reported level of self care, followed by Nigeria, China (postal), Ireland, Sweden, Finland, Iceland, Canada (telephone), Switzerland, and Spain. The lowest self-reported level of self care is in Kyrgystan, followed by Turkey (postal), Egypt (postal), Morocco, Ukraine, Lithuania, Indonesia (postal), Republic of Korea, Thailand, India. In all surveys males report equal or higher levels of self care than women: a male to female ratio of greater than or equal to 1.15 is noted in Egypt (household and postal), Jordan, India (1.25), Thailand, Republic of Korea, Morocco (1.27), Turkey (postal) and Kyrgyzstan. At lower levels of average health for both sexes in this domain, the male to female ratio tends to be greater, than at higher average levels of self care.

For usual activities (Table 10), Nigeria has the highest self-reported level of usual activities, followed by Ireland, Spain, Luxembourg, Mexico, Argentina, France (brief), Indonesia (household), Finland and Columbia. The lowest self-reported level of usual activities is in Kyrgystan, followed by Ukraine, Turkey (postal), Morocco, Lithuania, Egypt (postal), Poland, Romania, Czech Republic (postal), and Latvia. In all surveys males report equal or higher levels of usual activities than women: in 16 surveys, a male to female ratio of greater than or equal to 1.15 is noted. Those over 1.25 include Turkey (postal, 1.29) and Morocco (1.51). At lower levels of average health for both sexes in this domain, the male to female ratio tends to be greater, than at higher average levels of usual activities.

24 Table 3. Estimation results, HOPIT, by domain, across all 66 surveys (excluding dummy variables for each survey and covariates on cut-points*) Affect Pain Variable Coefficient Std. Err. z P>|z| Variable Coefficient Std. Err. z P>|z| Vignettes Vignettes vignette2 -1.890 0.011 -173.09 0.000 vignette2 -0.769 0.009 -85.32 0.000 vignette3 -2.447 0.011 -217.44 0.000 vignette3 -1.237 0.009 -134.90 0.000 vignette4 -2.618 0.011 -230.76 0.000 vignette4 -1.501 0.009 -160.59 0.000 vignette5 -3.246 0.012 -275.72 0.000 vignette5 -1.419 0.009 -153.20 0.000 vignette6 -4.293 0.013 -340.09 0.000 vignette6 -1.333 0.009 -144.77 0.000 Mean vignette7 -2.730 0.010 -263.91 0.000 Age 30-44 -0.097 0.015 -6.33 0.000 Mean Age 45-59 -0.305 0.017 -18.02 0.000 Age 30-44 -0.220 0.015 -14.49 0.000 Age 60+ -0.521 0.019 -27.88 0.000 Age 45-59 -0.554 0.017 -33.35 0.000 Male 0.270 0.012 23.33 0.000 Age 60+ -1.041 0.018 -57.50 0.000 Education (yrs) 0.022 0.001 15.05 0.000 Male 0.221 0.011 19.84 0.000 Intercept -1.223 0.711 -17.19 0.000 Education (yrs) 0.032 0.001 22.71 0.000 log(s) 0.351 0.004 81.06 0.000 Intercept 1.389 0.079 17.60 0.000 Cognition* log(s) 0.283 0.004 64.90 0.000 Variable Coefficient Std. Err. z P>|z| Self Care Vignettes Variable Coefficient Std. Err. z P>|z| vignette2 -1.703 0.011 -160.57 0.000 Vignettes vignette3 -1.892 0.011 -177.88 0.000 vignette2 -1.901 0.011 -179.71 0.000 vignette4 -2.048 0.011 -191.49 0.000 vignette3 -2.077 0.011 -195.36 0.000 vignette5 -2.534 0.011 -231.10 0.000 vignette4 -2.488 0.011 -229.16 0.000 vignette6 -2.637 0.011 -241.02 0.000 vignette5 -2.555 0.011 -234.95 0.000 vignette7 -3.235 0.011 -287.41 0.000 vignette6 -2.827 0.011 -256.67 0.000 vignette8 -3.896 0.012 -331.09 0.000 vignette7 -3.740 0.012 -321.22 0.000 Mean Mean Age 30-44 -0.036 0.015 -2.46 0.014 Age 30-44 -0.218 0.025 -8.73 0.000 Age 45-59 -0.282 0.016 -17.31 0.000 Age 45-59 -0.666 0.027 -25.05 0.000 Age 60+ -0.701 0.018 -39.43 0.000 Age 60+ -1.482 0.029 -51.97 0.000 Male 0.180 0.011 16.32 0.000 Male 0.149 0.017 8.81 0.000 Education (yrs) 0.030 0.001 21.78 0.000 Education (yrs) 0.058 0.002 27.25 0.000 Intercept -0.726 0.068 -10.72 0.000 Intercept 0.619 0.107 5.77 0.000 log(s) 0.242 0.005 49.67 0.000 log(s) 0.486 0.007 64.84 8.000 Mobility Usual Activities Variable Coefficient Std. Err. z P>|z| Variable Coefficient Std. Err. z P>|z| Vignettes Vignettes vignette2 -0.193 0.009 -22.13 0.000 vignette2 -1.784 0.010 -173.94 0.000 vignette3 -1.810 0.008 -227.55 0.000 vignette3 -1.953 0.010 -187.76 0.000 vignette4 -2.681 0.008 -321.06 0.000 vignette4 -1.991 0.010 -192.14 0.000 vignette5 -3.063 0.009 -358.16 0.000 vignette5 -2.272 0.010 -216.80 0.000 vignette6 -4.384 0.009 -462.84 0.000 vignette6 -2.674 0.011 -251.17 0.000 Mean vignette7 -2.760 0.011 -257.87 0.000 Age 30-44 -0.245 0.015 -15.91 0.000 vignette8 -3.409 0.011 -304.48 0.000 Age 45-59 -0.658 0.017 -39.65 0.000 Mean Age 60+ -1.292 0.018 -71.57 0.000 Age 30-44 -0.219 0.019 -11.55 0.000 Male 0.202 0.011 18.47 0.000 Age 45-59 -0.589 0.020 -28.75 0.000 Education (yrs) 0.039 0.001 28.86 0.000 Age 60+ -1.304 0.022 -58.79 0.000 Intercept -0.660 0.068 -9.72 0.000 Male 0.200 0.014 14.71 0.000 log(s) 0.227 0.005 43.46 0.000 Education (yrs) 0.048 0.002 28.29 0.000 Intercept -0.010 0.083 -0.13 0.901 * See Appendix II for complete set of estimates for Cognition log(s) 0.443 0.005 82.51 0.000

25 Figure 11: Level of Health, Affect: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Reported Level of Affect by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001 10 0 90 80 70 60 50 40 30 male, Nigeria(h) 20 female,Nigeria(h) 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Reported Level of Affect by Age Group, M ale, AM RO, Self Reported Level of Affect by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001

10 0 Ar genti na(b) 10 0 Ar genti na(b)

90 Canada(p) 90 Canada(p) 80 80 Canada(t) Canada(t) 70 70 Chile(p) Chile(p) 60 Colombia(h) 60 Colombia(h)

50 Costa Rica(b) 50 Costa Rica(b) 40 Mexico(h) 40 Mexico(h) 30 T r i ni dad and 30 T obago(p) Trinidad and 20 T obago(p) Uni ted States(p) 20 Uni ted States(p) 10 Venezuel a(b)

10 Venezuel a(b) 0 15-29 30-44 45-59 60-69 70-79 80+ 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Affect by Age Group, M ale, EM RO, Self Reported Level of Affect by Age Group, Female, WHO Health & Responsiveness Surveys, 2001 EM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n(b) Bahr ai n(b) 90 90

80 Egypt(h) 80 Egypt(h)

70 Egypt(p) 70 Egypt(p) 60 60 Jor dan(b) 50 50 Jor dan(b)

40 Mor occo(b) 40 Mor occo(b) 30 30 Oman(b) Oman(b) 20 20

United Ar ab 10 10 Uni ted Ar ab Emir ates(b) Emir ates(b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+

Age groups Age groups

26 Self Reported Level of Affect by Age Group, M ale, SEARO, Self Reported Level of Affect by Age Group, Female, WHO Health & Responsiveness Surveys, 2001 SEARO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 90 Indi a(h) 90 Indi a(h) 80 80 70 70 Indonesi a(h Indonesi a(h) 60 60 ) 50 50

Indonesi a(p 40 Indonesi a(p) 40 ) 30 30 20 20 Thailand(p) T hai l and(p) 10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Affect by Age Group, Male, EURO- Self Reported Level of Affect by Age Group, Female, EURO- C, WHO Health & Responsiveness Surveys, 2001 C, WHO Healt h & Responsiveness Surveys, 2001 10 0 10 0 Bul gar i a(b) Bul gar i a( b) 90 Cr oati a(b) 90 Cr oati a(b) 80 Cypr us(p) 80

70 Czech 70 Cypr us(p) Republ i c(b) 60 Czech 60 Republ i c(p) Czech 50 Hungar y(p) 50 Republ i c( b)

40 Mal ta(b) 40 Czech Republ i c( p) 30 Pol and(p) 30 Hungar y(p ) 20 Romania(b) 20

Mal ta(b) 10 Slovaki a(h) 10

0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Affect by Age Group, Male, EURO- Self Reported Level of Affect by Age Group, Female, EURO- E, WHO Health & Responsiveness Surveys, 2001 E, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Estoni a(b) Estoni a(b) 90 90 Geor gi a(h) Geor gi a(h) 80 80 Kyr gyzstan(p) Kyr gyzstan(p) 70 70 Latvi a(b) Latvi a(b) 60 60

50 Li thuani a(p) 50 Li thuani a(p) 40 Russian 40 Russian Feder ati on(b) Feder ati on(b) 30 Tur key(h) 30 Tur key(h)

20 Tur key(p) 20 Tur key(p) 10 Ukr ai ne(p) 10 Ukr ai ne(p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+

Age groups Age groups

27 Self Reported Level of Affect by Age Group, Male, EURO- Self Report ed Level of A f f ect by Age Group, Female, EURO- N, WHO Health & Responsiveness Surveys, 2001 N, WHO Health & Responsiveness Surveys, 2001

10 0 10 0 Austr i a(p) Austr i a(p) 90 90 Denmar k(p) Denmar k(p)

80 80 Fi nl and(b) Fi nl and(b) 70 70 Fi nl and(p) Fi nl and(p) 60 60 Ger many(b) Ger many(b) 50 50 Icel and(b) Icel and(b) 40 40 Nether l ands(b Nether l ands(b ) ) 30 30 Nether l ands(p Nether l ands(p ) ) 20 20 Sweden(b) Sweden(b) 10 10 Swi tzer l and(p) Swi tzer l and(p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Affect by Age Group, Male, EURO- Self Reported Level of Affect by Age Group, Female, EURO- W, WHO Health & Responsiveness Surveys, 2001 W, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Belgium(b) Belgium(b) 90 90 Fr ance(b) Fr ance(b) 80 80 Fr ance(p) Fr ance(p) 70 70 Gr eece(p) Gr eece(p) 60 60 Ir el and(b) Ir el and(b) 50 50 Italy(b) Italy(b) 40 40 Luxembour g(t) Luxembour g(t) 30 30 Por tugal (b) Por tugal (b) 20 20 Spain(b) Spain(b) 10 10 United United Ki ngdom(p) 0 Ki ngdom(p) 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+

Age groups Age groups

Self Reported Level of Affect by Age Group, M ale, WPRO, Self Reported Level of Affect by Age Group, Female, WHO Health & Responsiveness Surveys, 2001 WPRO, WHO Healt h & Responsiveness Surveys, 2001 10 0 10 0 A ustralia( 90 Australia(p) 90 p)

80 80 China(h) Chi na(h) 70 70

60 60 China(p) Chi na(p) 50 50 40 40 Newzeala Newzeal and(p) nd(p) 30 30 Republ i c 20 Republ i c of 20 of Kor ea(p) Korea(p) 10 10 15-29 30- 45-59 60- 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ 44 69 Age groups Age groups

28 Figure 12: Level of Health, Cognition: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Reported Level of Cognition by Age Group, AFRO, WHO Healt h & Responsiveness Surveys, 2001 10 0 male, Nigeria(h) 90 female,Nigeria(h) 80 70 60 50 40 30 20 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognit ion by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 AM RO, WHO Health & Responsiveness Surveys, 2001

10 0 Ar genti na (b) 10 0 A r genti na (b)

90 Canada (p) 90 Canada (p)

80 Canada (t) 80 Canada (t)

70 Chile (p) 70 Chile (p)

Colombia (h) 60 60 Colombia (h)

Costa Rica (b) 50 50 Costa Rica (b) Mexico (h) 40 40 Mexico (h)

T r i ni dad and 30 30 T r i ni dad and T obago (p) T obago (p) Uni ted States 20 20 Uni ted States (p) (p) Venezuel a (b) 10 10 Venezuel a (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognit ion by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001 EM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n (b) Bahr ai n (b) 90 90

80 Egypt (h) 80 Egypt (h) 70 70 Egypt (p) Egypt (p) 60 60 Jor dan (b) Jor dan (b) 50 50

40 Mor occo (b) 40 Mor occo (b) 30 30 Oman (b) Oman (b) 20 20

10 Uni ted Ar ab 10 United Ar ab Emir ates (b) Emir ates (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

29 Self Reported Level of Cognition by Age Group, Male, Self Repo rt ed Level of Cognit ion by A ge Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001 SEARO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Indi a (h) India (h) 90 90 Indonesi a (h) Indonesi a (h)

80 Indonesi a (p) 80 Indonesi a (p) Thailand (p) 70 T hai l and (p) 70 60 60

50 50 40 40 30 30 20 20 10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognition by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys, 2001 EURO-C, WHO Health & Responsiveness Surveys, 2001 10 0 Hungar y (p) 10 0 Hungar y (p) 90 Bul gar i a (b) 90 Bul gar i a (b) 80 Cr oati a (b) 80 Cr oati a (b) 70 70 Cypr us (p) Cypr us (p) 60 60 Czech Czech Republ i c (b) Republ i c (b) 50 50 Czech Czech Republ i c (p) Republ i c (p) 40 40 Malta (b) Malta (b) 30 30 Pol and (p) Pol and (p) 20 20 Romania (b) Romania (b)

10 Slovaki a (h) 10 Slovaki a (h) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Cognit ion by Age Group, M ale, Self Reported Level of Cognition by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001 EURO-E, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Estoni a (b) Estoni a (b) 90 90 Geor gi a (h) Geor gi a (h) 80 80 Kyr gyzstan (p) Kyr gyzstan (p) 70 70 Latvi a (b) Latvi a (b) 60 60 Li thuani a (p) 50 50 Li thuani a (p) Russian 40 40 Russian Feder ati on (b) Feder ati on (b) 30 Turkey (h) 30 Turkey (h)

20 Turkey (p) 20 Turkey (p)

10 Ukr ai ne (p) 10 Ukr ai ne (p)

0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

30 Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognit ion by Age Group, Female, EURO-N, WHO Health & Responsiveness Surveys, 2001 EURO-N, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Austr ia Austr ia (p) (p) 90 90 Denmar k Denmar k (p) (p) 80 80 Fi nl and Fi nl and (b) (b) 70 70 Fi nl and Fi nl and (p) (p) 60 60 Ger many Ger many (b) (b) 50 50 Icel and Icel and (b) (b) 40 40 Nether l an Nether l ands ds (b) 30 (b) 30 Nether l an ds (p) Nether l ands 20 (p) 20 Sweden Sweden (b) (b) 10 10 Sw i t z er l a nd (p) 0 Swi tzer l and 0 (p) 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognit ion by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys, 2001 EURO-W, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Belgium (b) Belgium (b) 90 90 Fr ance (b) Fr ance (b) 80 80 Fr ance (p) Fr ance (p) 70 70 Gr eece (p) Gr eece (p) 60 60 Ir el and (b) Ir el and (b) 50 50 Italy (b) Italy (b) 40 40 Luxembour g (t) Luxembour g (t) 30 30 Por tugal (b) Por tugal (b)

20 Spain (b) 20 Spain (b)

10 United 10 United Ki ngdom (p) Ki ngdom (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Cognition by Age Group, Male, Self Reported Level of Cognition by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001 WPRO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 90 90

80 80

70 70 60 60 50 50 40 40

30 Australia (p) 30 Australia (p) Chi na (h) Chi na (h) 20 20 Chi na (p) Chi na (p) Newzeal and (p) Newzeal and (p) 10 10 Republ i c of Kor ea (p) Republ i c of Kor ea (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

31 Figure 13: Level of Health, Mobility: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Reported Level of M obility by Age Group, AFRO, WHO Healt h & Responsiveness Surveys, 2001 10 0 male, Nigeria(h) 90 female,Nigeria(h) 80 70 60 50 40 30 20 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Reported Level of Mobility by Age Group, Male, Self Reported Level of Mobility by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 AM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Ar genti na (b) Ar genti na (b) 90 90 Canada (p) Canada (p) 80 80 Canada (t) Canada (t) 70 70 Chile (p) Chile (p) 60 60 Colombia (h) Colombia (h) 50 50 Costa Rica Costa Rica (b) (b) 40 40 Mexico (h) Mexico (h)

30 T r i ni dad and 30 T r i ni dad and T obago (p) T obago (p) 20 Uni ted States (p) 20 Uni ted States (p) 10 Venezuel a (b) 10 Venezuel a (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Mobility by Age Group, Male, Self Reported Level of M obility by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001 EM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n (b) Bahr ai n (b) 90 90 80 Egypt (h) 80 Egypt (h)

70 70 Egypt (p) Egypt (p) 60 60 Jor dan (b) Jor dan (b) 50 50

40 Mor occo (b) 40 Mor occo (b) 30 30 Oman (b) Oman (b) 20 20

10 Uni ted Ar ab 10 United Ar ab Emir ates (b) Emir ates (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

32 Self Reported Level of M obility by Age Group, M ale, Self Reported Level of M obility by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001 SEARO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 90 90 80 80 70 70 60 60

50 50 40 40

30 Indi a (h) 30 Indi a (h) 20 Indonesi a (h) 20 Indonesi a (h) Indonesi a (p) Indonesi a (p) 10 10 T hai l and (p) T hai l and (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of M obility by Age Group, Male, EURO- Self Reported Level of M obility by Age Group, Female, C, WHO Health & Responsiveness Surveys, 2001 EURO-C, WHO Health & Responsiveness Surveys, 2001 10 0 Hungar y (p) 10 0 Hungar y (p) 90 Bul gar i a (b) 90 Bul gar i a (b) 80 Cr oati a (b) 80 Cr oati a (b) 70 70 Cypr us (p) Cypr us (p) 60 60 Czech Czech Republ i c (b) Republ i c (b) 50 50 Czech Czech Republ i c (p) Republ i c (p) 40 40 Malta (b) Malta (b) 30 30 Pol and (p) Pol and (p) 20 20 Romania (b) Romania (b)

10 Slovaki a (h) 10 Slovaki a (h) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of M obility by Age Group, Male, Self Reported Level of M obility by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001 EURO-E, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Estoni a (b) Estoni a (b) 90 90 Geor gi a (h) Geor gi a (h) 80 80 Kyr gyzstan (p) Kyr gyzstan (p) 70 70 Latvi a (b) Latvi a (b) 60 60

Li thuani a (p) Li thuani a (p) 50 50 Russian 40 40 Russian Feder ati on (b) Feder ati on (b) 30 Turkey (h) 30 Turkey (h)

20 Turkey (p) 20 Turkey (p)

10 Ukr ai ne (p) 10 Ukr ai ne (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

33 Self Reported Level of M obility by Age Group, Male, EURO- Self Reported Level of Mobility by Age Group, Female, N, WHO Health & Responsiveness Surveys, 2001 EURO-N, WHO Healt h & Responsiveness Surveys, 2 001 10 0 10 0 Austr ia (p) Austr ia (p) 90 90 Denmar k (p) Denmar k (p) 80 80 Fi nl and (b) Fi nl and (b) 70 70 Fi nl and (p) Fi nl and (p) 60 60 Ger many (b) Ger many (b)

50 Icel and (b) 50 Icel and (b) 40 40 Nether l ands Nether l ands (b) 30 (b) 30 Nether l ands Nether l ands (p) (p) 20 Sweden (b) 20 Sweden (b)

10 Sw i t z er l an d 10 Swi tzer l and (p) (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of M obility by Age Group, Male, EURO- Self Reported Level of M obility by Age Group, Female, W, WHO Health & Responsiveness Surveys, 2001 EURO-W, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Belgium (b) Belgium (b) 90 90 Fr ance (b) Fr ance (b) 80 80 Fr ance (p) Fr ance (p) 70 70 Gr eece (p) Gr eece (p) 60 60 Ir el and (b) Ir el and (b)

50 Italy (b) 50 Italy (b) 40 40 Luxembour g (t) Luxembour g (t) 30 30 Por tugal (b) Por tugal (b) 20 20 Spain (b) Spain (b)

10 United 10 United Ki ngdom (p) Ki ngdom (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of M obility by Age Group, M ale, Self Reported Level of M obility by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001 WPRO, WHO Healt h & Responsiveness Surveys, 2001 10 0 10 0 90 90 80 80

70 70 60 60

50 50 40 40

30 Austr alia (p) 30 Australia (p) Chi na (h) Chi na (h) 20 20 Chi na (p) Chi na (p) Newzeal and (p) Newzeal and (p) 10 10 Republ i c of Kor ea (p) Republ i c of Kor ea (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

34 Figure 14: Level of Health, Pain: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Report ed Level of Pain by A ge Group, A FRO, WHO Health & Responsiveness Surveys, 2001 10 0 male, Nigeria(h) 90 female,Nigeria(h) 80 70 60 50 40 30 20 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Reported Level of Pain by A ge Group, M ale, AM RO, Self Reported Level of Pain by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Ar genti na (b) Ar genti na (b) 90 90 Canada (p) Canada (p) 80 80 Canada (t) Canada (t) 70 70 Chile (p) Chile (p) 60 60 Colombia (h) Colombia (h)

50 50 Costa Rica (b) Costa Rica (b)

40 40 Mexico (h) Mexico (h)

30 30 T r i nidad and T r i ni dad and T obago (p) T obago (p) 20 20 Uni ted States (p) Uni ted States (p) 10 10 Venezuel a (b) Venezuel a (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Pain by Age Group, M ale, EM RO, Self Reported Level of Pain by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n (b) Bahr ai n (b) 90 90

80 Egypt (h) 80 Egypt (h) 70 70 Egypt (p) Egypt (p) 60 60 Jor dan (b) Jor dan (b) 50 50

40 Mor occo (b) 40 Mor occo (b) 30 30 Oman (b) Oman (b) 20 20

10 Uni ted Ar ab 10 Uni ted Ar ab Emir ates (b) Emir ates (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

35 Self Reported Level of Pain by Age Group, M ale, SEARO, Self Reported Level of Pain by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Indi a (h) Indi a (h) 90 90 Indonesi a (h) Indonesi a (h)

80 Indonesi a (p) 80 Indonesi a (p) T hai l and (p) 70 T hai l and (p) 70 60 60

50 50 40 40 30 30 20 20 10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Pain by Age Group, M ale, EURO-C, Self Reported Level of Pain by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 Hungar y (p) 10 0 Hungar y (p) 90 Bul gar i a (b) 90 Bul gar i a (b) 80 Cr oati a (b) 80 Cr oati a (b) 70 70 Cypr us (p) Cypr us (p) 60 60 Czech Czech Republ i c (b) Republ i c (b) 50 50 Czech Czech Republ i c (p) Republ i c (p) 40 40 Malta (b) Malta (b) 30 30 Pol and (p) Pol and (p) 20 20 Romania (b) Romania (b)

10 Slovaki a (h) 10 Slovaki a (h) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Pain by Age Group, M ale, EURO-E, Self Reported Level of Pain by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Estoni a (b) Estoni a (b) 90 90 Geor gi a (h) Geor gi a (h) 80 80 Kyr gyzstan (p) Kyr gyzstan (p) 70 70 Latvi a (b) Latvi a (b) 60 60

Li thuani a (p) Li thuani a (p) 50 50 Russian 40 40 Russian Feder ati on (b) Feder ati on (b) 30 Turkey (h) 30 Turkey (h)

20 Turkey (p) 20 Turkey (p)

10 Ukr ai ne (p) 10 Ukr ai ne (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

36 Self Rep ort ed Level of Pain by Age Group, M ale, EURO-N, Self Reported Level of Pain by Age Group, Female, EURO- WHO Health & Responsiveness Surveys, 2001 N, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Austr ia (p) Austr ia (p) 90 90 Denmar k (p) Denmar k (p) 80 80 Fi nl and (b) Fi nl and (b) 70 70 Fi nl and (p) Fi nl and (p) 60 60 Ger many (b) Ger many (b) 50 50 Icel and (b) Icel and (b) 40 40 Nether l ands Nether l ands (b) (b) Nether l ands 30 30 Nether l ands (p) (p) Sweden (b) 20 20 Sweden (b) Sw i t z er l a nd 10 10 Swi tzer l and (p) 0 (p) 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Pain by Age Group, M ale, EURO-W, Self Reported Level of Pain by Age Group, Female, EURO- WHO Health & Responsiveness Surveys, 2001 W, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Belgium (b) Belgium (b) 90 90 Fr ance (b) Fr ance (b) 80 80 Fr ance (p) Fr ance (p) 70 70 Gr eece (p) Gr eece (p) 60 60 Ir el and (b) Ir el and (b)

50 Italy (b) 50 Italy (b) 40 40 Luxembour g (t) Luxembour g (t) 30 30 Por tugal (b) Por tugal (b)

20 Spain (b) 20 Spain (b)

United 10 United 10 Ki ngdom (p) Ki ngdom (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Pain by Age Group, M ale, WPRO, Self Reported Level of Pain by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001 WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Australia (p) Australia (p) 90 Chi na (h) 90 China (h) Chi na (p) China (p) 80 80 Newzeal and (p) Newzeal and (p) 70 Republ i c of Kor ea (p) 70 Republ i c of Kor ea (p) 60 60 50 50 40 40 30 30

20 20

10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

37 Figure 15: Level of Health, Self Care: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Reported Level of Self care by Age Group, AFRO, WHO Healt h & Responsiveness Surveys, 2001 10 0 male, Nigeria(h) 90 female,Nigeria(h) 80 70 60 50 40 30 20 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Reported Level of Self care by Age Group, M ale, Self Reported Level of Self care by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 AM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Ar genti na (b) Ar genti na (b) 90 90 Canada (p) Canada (p) 80 80 Canada (t) Canada (t) 70 70 Chile (p) Chile (p)

60 60 Colombia (h) Colombia (h)

50 50 Costa Rica (b) Costa Rica (b)

40 40 Mexico (h) Mexico (h)

30 T r i ni dad and 30 T r i ni dad and T obago (p) T obago (p) 20 20 Uni ted States Uni ted States (p) (p) 10 10 Venezuel a (b) Venezuel a (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Self care by Age Group, Male, Self Reported Level of Self care by Age Group, Female, EMRO, WHO Health & Responsiveness Surveys, 2001 EM RO, WHO Healt h & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n (b) Bahr ai n (b) 90 90

80 Egypt (h) 80 Egypt (h) 70 70 Egypt (p) Egypt (p) 60 60 Jor dan (b) Jor dan (b) 50 50

40 Mor occo (b) 40 Mor occo (b) 30 30 Oman (b) Oman (b) 20 20

10 Uni ted Ar ab 10 Uni ted Ar ab Emir ates (b) Emir ates (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

38 Self Reported Level of Self care by Age Group, Male, Self Reported Level of Self care by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001 SEARO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Indi a (h) Indi a (h) 90 90 Indonesi a (h) Indonesi a (h)

80 Indonesi a (p) 80 Indonesi a (p) T hai l and (p) 70 T hai l and (p) 70 60 60

50 50 40 40 30 30 20 20

10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Repo rt ed Level of Self care by Age Group, Male, EURO- Self Reported Level of Self care by Age Group, Female, C, WHO Health & Responsiveness Surveys, 2001 EURO-C, WHO Health & Responsiveness Surveys, 2001 10 0 Hungar y (p) 10 0 Hungar y (p) 90 Bul gar i a (b) 90 Bul gar i a (b) 80 Cr oati a (b) 80 Cr oati a (b) 70 70 Cypr us (p) Cypr us (p) 60 60 Czech Czech Republ i c (b) Republ i c (b) 50 50 Czech Czech Republ i c (p) Republ i c (p) 40 40 Malta (b) Malta (b) 30 30 Pol and (p) Pol and (p) 20 20 Romania (b) Romania (b)

10 Slovaki a (h) 10 Slovaki a (h) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Self care by Age Group, Male, Self Report ed Level of Self care by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001 EURO-E, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Estoni a (b) Estoni a (b) 90 90 Geor gi a (h) Geor gi a (h) 80 80 Kyr gyzstan (p) Kyr gyzstan (p) 70 70 Latvi a (b) Latvi a (b) 60 60

Li thuani a (p) Li thuani a (p) 50 50 Russian 40 40 Russian Feder ati on (b) Feder ati on (b) 30 Turkey (h) 30 Turkey (h)

20 Turkey (p) 20 Turkey (p)

10 Ukr ai ne (p) 10 Ukr ai ne (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

39 Self Rep ort ed Level of Self care by Age Group, Male, EURO- Self Reported Level of Self care by Age Group, Female, N, WHO Health & Responsiveness Surveys, 2001 EURO-N, WHO Healt h & Responsiveness Surveys, 2 001 10 0 10 0 Austr ia (p) Austr ia (p) 90 90 Denmar k (p) Denmar k (p) 80 80 Fi nl and (b) Fi nl and (b)

70 70 Fi nl and (p) Fi nl and (p)

60 60 Ger many (b) Ger many (b)

50 50 Icel and (b) Icel and (b) 40 40 Nether l ands Nether l ands (b) (b) 30 30 Nether l ands Nether l ands (p) (p) 20 20 Sweden (b) Sweden (b) 10 10 Swi tzer l and Sw i t z er l a nd (p) (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Self care by Age Group, Male, EURO- Self Reported Level of Self care by Age Group, Female, W, WHO Health & Responsiveness Surveys, 2001 EURO-W, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Belgium (b) Belgium (b) 90 90 Fr ance (b) Fr ance (b) 80 80 Fr ance (p) Fr ance (p) 70 70 Gr eece (p) Gr eece (p) 60 60 Ir el and (b) Ir el and (b) 50 50 Italy (b) Italy (b) 40 40 Luxembour g (t) Luxembour g (t) 30 30 Por tugal (b) Por tugal (b)

20 Spain (b) 20 Spain (b)

10 United 10 United Ki ngdom (p) Ki ngdom (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Reported Level of Self care by Age Group, Male, Self Reported Level of Self care by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001 WPRO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Australia (p) Australia (p) 90 China (h) 90 China (h) China (p) China (p) 80 80 Newzeal and (p) Newzealand (p) 70 Republ i c of Kor ea (p) 70 Republ i c of Kor ea (p) 60 60

50 50 40 40 30 30

20 20 10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

40 Figure 16: Level of Health, Usual Activities: Comparison of Age groups, Surveys grouped by Region, Male and Female

Self Reported Level of Usual Activities by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001 10 0 male, Nigeria(h) 90 female,Nigeria(h) 80 70 60 50 40 30 20 10 0 15-29 30-44 45-59 60-69 70-79 80+ Age groups

Self Report ed Level of Usual act ivit ies by A ge Group, M ale, Self Report ed Level of Usual act ivit ies by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001 AM RO, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Ar gentina (b) Ar genti na (b) 90 90 Canada (p) Canada (p) 80 80 Canada (t) Canada (t) 70 70 Chile (p) Chile (p) 60 60 Colombia (h) Colombia (h) 50 50 Costa Rica (b) Costa Rica (b) 40 40 Mexico (h) Mexico (h)

30 T r i ni dad and 30 Trinidad and T obago (p) T obago (p) 20 Uni ted States (p) 20 Uni ted States (p) 10 Venezuel a (b) 10 Venezuel a (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Repo rt ed Level of Usual act ivit ies by A ge Group, M ale, Self Report ed Level of Usual act ivit ies by A ge Group, EMRO, WHO Health & Responsiveness Surveys, 2001 Female, EM RO, WHO Healt h & Responsiveness Surveys, 2001 10 0 10 0 Bahr ai n (b) Bahr ai n (b) 90 90 Egypt (h) Egypt (h) 80 80 70 Egypt (p) 70 Egypt (p) 60 60 Jor dan (b) Jor dan (b) 50 50

40 Mor occo (b) 40 Mor occo (b) 30 30 Oman (b) Oman (b) 20 20

10 Uni ted Ar ab 10 Uni ted Ar ab Emir ates (b) Emir ates (b) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

41 Self Repo rt ed Level of Usual act ivit ies by A ge Group, M ale, Self Report ed Level of Usual act ivit ies by A ge Group, SEARO, WHO Health & Responsiveness Surveys, 2001 Female, SEARO, WHO Health & Responsiveness Surveys, 10 0 2001 10 0 Indi a (h) 90 Indi a (h) Indonesi a (h) 90 Indonesi a (h) 80 Indonesi a (p) 80 Indonesi a (p) T hai l and (p) 70 70 T hai l and (p) 60 60

50 50 40 40 30 30 20 20 10 10 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Repo rt ed Level of Usual act ivit ies by A ge Group, M ale, Self Report ed Level of Usual act ivit ies by A ge Group, EURO-C, WHO Health & Responsiveness Surveys, 2001 Female, EURO-C, WHO Health & Responsiveness Surveys, 10 0 2001 Hungar y (p) 10 0 Hungar y (p) 90 Bul gar i a (b) 90 Bul gar i a (b) 80 80 Cr oati a (b) Cr oati a (b) 70 70 Cypr us (p) Cypr us (p)

60 60 Czech Czech Republ i c (b) Republ i c (b) 50 Czech 50 Czech Republ i c (p) Republ i c (p) 40 Malta (b) 40 Malta (b)

30 Pol and (p) 30 Pol and (p)

20 Romania (b) 20 Romania (b)

10 Slovaki a (h) 10 Slovaki a (h) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Report ed Level of Usual act ivit ies by Age Group, Male, Self Report ed Level of Usual act ivit ies by A ge Group, EURO-E, WHO Health & Responsiveness Surveys, 2001 Female, EURO-E, WHO Health & Responsiveness Surveys, 10 0 10 0 2001 Estoni a (b) Estoni a (b) 90 90 Geor gi a (h) Geor gi a (h) 80 80 Kyr gyzstan (p) Kyr gyzstan (p) 70 70 Latvi a (b) Latvi a (b) 60 60 Li thuani a (p) 50 50 Li thuani a (p) Russian 40 40 Russian Feder ati on (b) Feder ati on (b) 30 Turkey (h) 30 Turkey (h)

20 Turkey (p) 20 Turkey (p)

10 Ukr aine (p) 10 Ukr ai ne (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

42 Self Rep ort ed Level of Usual act ivit ies by Age Group, Male, Self Reported Level of Usual Activities by Age Group, EURO-N, WHO Healt h & Responsiveness Surveys, 2 001 Female, EURO-N, WHO Health & Responsiveness Surveys, 2001 10 0 10 0 Austr ia (p) Austr ia (p) 90 90 Denmar k (p) Denmar k (p) 80 80 Fi nl and (b) Fi nl and (b) 70 70 Fi nl and (p) Fi nl and (p) 60 60 Ger many (b) Ger many (b) 50 50 Icel and (b) Icel and (b) 40 40 Nether lands Nether lands (b) 30 (b) 30 Nether lands Nether lands (p) 20 (p) 20 Sweden (b) Sweden (b) 10 10 Sw i t z er l a nd Sw i t z er l and (p) 0 (p) 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Report ed Level of Usual act ivit ies by Age Group, Male, Self Report ed Level of Usual act ivit ies by A ge Group, EURO-W, WHO Health & Responsiveness Surveys, 2001 Female, EURO-W, WHO Health & Responsiveness Surveys, 10 0 2001 Belgium (b) 10 0 Belgium (b) 90 Fr ance (b) 90 Fr ance (b)

80 Fr ance (p) 80 Fr ance (p)

70 Gr eece (p) 70 Gr eece (p)

60 Ir el and (b) 60 Ir el and (b) 50 Italy (b) 50 Italy (b) 40 Luxembour g (t) 40 Luxembour g (t) 30 Por tugal (b) 30 Por tugal (b)

20 Spai n (b) 20 Spain (b)

10 United 10 United Ki ngdom (p) Ki ngdom (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

Self Repo rt ed Level of Usual act ivit ies by A ge Group, M ale, Self Report ed Level of Usual act ivit ies by A ge Group, WPRO, WHO Health & Responsiveness Surveys, 2001 Female, WPRO, WHO Healt h & Responsiveness Surveys, 10 0 10 0 2001 90 90

80 80

70 70 60 60 50 50 40 40

30 Australia (p) 30 Australia (p) Chi na (h) China (h) 20 20 Chi na (p) China (p) Newzeal and (p) Newzeal and (p) 10 10 Republ i c of Kor ea (p) Republ i c of Kor ea (p) 0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age groups Age groups

43 Table 4. Average level of health by domain, age-standardized, 66 surveys, WHO Multi-Country Survey Study on Health and Responsiveness, 2000-2001 Affect Cognition Mobility Pain Self Care Usual Activities Survey Males Females Males Females Males Females Males Females Males Females Males Females Argentina brief 59.22 49.53 66.01 56.87 66.98 59.77 60.09 51.29 75.85 71.00 82.04 74.55 Australia postal 73.92 71.20 59.13 57.06 66.29 61.62 65.73 63.00 75.36 71.50 73.09 68.46 Austria postal 67.69 67.65 43.40 42.59 58.39 53.70 43.18 39.93 58.15 55.03 61.60 57.52 Bahrain brief 71.98 63.32 53.42 43.00 57.35 48.81 76.43 63.21 49.81 44.72 52.89 43.02 Belgium brief 87.66 79.23 73.72 66.99 64.70 57.43 64.60 54.59 64.39 59.34 64.02 56.58 Bulgaria brief 69.01 61.20 67.12 60.10 69.97 62.56 60.46 54.30 61.25 56.76 59.27 51.89 Canada postal 73.73 67.20 62.54 58.89 58.47 53.21 58.41 51.30 65.86 62.55 65.63 61.33 Canada telephone 68.04 67.34 57.67 60.29 66.31 64.89 68.99 66.52 82.43 80.38 70.65 67.86 Chile postal 71.21 61.61 58.86 51.96 62.84 54.63 63.12 55.79 47.76 43.06 58.50 52.26 China household 82.64 76.64 58.07 49.89 73.10 65.89 80.49 72.75 70.30 64.50 59.76 53.76 China postal 64.85 60.27 51.76 50.35 65.32 62.30 73.57 66.48 85.85 82.77 65.95 63.49 Columbia household 65.57 56.92 64.41 54.39 68.84 62.16 59.21 50.71 67.60 62.85 75.28 69.34 Costa Rica brief 56.55 57.17 48.20 48.48 58.64 59.00 47.85 47.64 58.09 55.76 65.65 64.92 Croatia brief 53.36 47.25 53.07 45.51 48.01 40.95 46.13 39.42 47.88 42.64 50.87 45.53 Cyprus postal 56.84 48.27 52.91 45.01 71.37 66.89 40.55 31.11 65.69 61.51 57.74 51.55 Czech Republic brief 71.73 71.03 64.72 62.32 47.25 44.26 59.50 57.44 66.68 63.44 62.34 61.54 Czech Republic postal 67.80 57.57 56.72 51.31 44.23 40.60 54.18 48.09 46.06 43.46 44.88 41.16 Denmark postal 84.75 76.82 66.24 59.96 75.36 69.67 57.75 50.90 64.87 60.69 69.42 62.35 Egypt household 83.28 76.72 75.60 65.92 51.93 42.21 69.70 60.75 45.73 39.41 55.93 47.14 Egypt postal 59.05 50.30 33.78 26.31 43.38 36.05 44.02 35.63 22.62 19.43 43.66 35.24 Estonia brief 65.40 57.53 65.38 58.34 62.37 56.76 54.19 46.05 70.20 65.66 63.68 58.88 Finland brief 83.91 77.94 78.14 73.84 63.09 58.74 67.53 61.75 83.55 80.72 76.64 71.72 Finland postal 72.18 64.59 66.85 63.66 68.66 65.60 54.60 49.22 69.14 67.00 64.75 61.35 France brief 83.10 75.99 70.65 63.06 78.43 71.38 72.99 64.24 73.87 68.88 80.05 72.10 France postal 78.62 71.06 49.04 48.11 75.88 68.38 69.02 59.82 65.48 60.45 67.19 60.96 Georgia household 63.16 55.73 74.70 65.89 58.03 50.62 59.77 52.29 44.88 40.83 57.54 51.83 Germany brief 87.91 82.02 80.74 75.15 64.31 58.31 75.63 67.97 71.53 66.57 68.95 62.95 Greece postal 62.47 58.45 61.49 55.95 76.11 71.42 66.94 59.75 76.95 73.83 67.14 61.82 Hungary postal 52.95 51.93 54.47 52.01 47.46 44.63 48.91 45.93 50.95 47.81 52.56 49.96 Iceland brief 77.63 72.22 55.30 49.49 57.30 49.80 61.12 54.58 84.48 78.95 70.02 61.90 India household 78.83 72.15 63.56 53.15 51.48 42.28 71.36 60.84 42.37 33.99 58.97 49.39 Indonesia household 95.47 90.83 78.57 70.50 86.17 79.98 70.48 63.11 71.71 66.26 78.20 72.44 Indonesia postal 72.54 65.51 38.42 32.92 87.28 83.53 26.82 21.09 32.76 29.15 48.89 44.19

(continued)

44 Table 4. Average level of health by domain, age-standardized, 66 surveys, WHO Multi-Country Survey Study on Health and Responsiveness, 2000-2001 (continued) Affect Cognition Mobility Pain Self Usual Survey Males Females Males Females Males Females Males Females Males Females Males Females Ireland brief 93.90 88.01 91.87 86.22 76.36 71.11 83.59 76.69 86.06 82.46 82.78 76.73 Italy brief 84.79 76.50 66.44 57.90 80.54 72.54 78.67 68.59 75.73 71.06 69.88 61.51 Jordan brief 62.58 55.17 44.46 35.25 48.89 39.10 67.32 58.39 41.59 34.93 50.73 41.07 Kyrgyzstan postal 26.95 19.56 21.72 16.92 15.55 12.58 20.57 13.96 11.17 9.64 25.28 20.52 Latvia brief 47.90 48.13 58.63 57.93 53.39 51.59 51.95 52.05 52.03 49.10 43.25 43.41 Lithuania postal 54.62 43.76 32.07 25.92 36.30 30.86 35.95 28.57 31.90 29.33 40.05 35.80 Luxembourg telephone 87.79 80.28 77.37 71.05 79.13 71.14 66.29 56.44 89.24 85.40 82.17 75.40 Malta brief 81.56 76.33 58.02 52.63 61.58 54.61 65.69 59.43 66.85 61.73 68.93 62.37 Mexico household 86.08 78.85 81.83 73.12 76.11 68.56 78.04 69.96 73.34 67.75 81.85 75.48 Morocco brief 60.99 46.44 37.76 23.24 49.59 31.30 52.61 38.42 29.13 22.93 41.66 27.51 Netherlands brief 77.32 67.83 64.07 57.76 51.41 44.00 48.91 41.07 59.23 53.20 58.35 49.46 Netherlands postal 81.91 74.82 58.13 52.40 55.59 48.63 56.41 50.27 78.56 72.03 66.34 58.26 New Zealand postal 77.11 69.62 51.75 46.60 67.88 63.04 67.47 61.31 63.22 59.49 64.61 58.66 Nigeria household 86.94 83.55 90.34 86.58 69.04 62.95 79.45 76.19 87.81 83.61 88.76 86.46 Oman brief 72.46 67.78 47.10 42.08 58.67 52.12 77.53 71.70 52.75 50.39 52.19 44.96 Poland postal 54.48 48.13 42.80 36.26 52.08 46.50 41.49 35.55 40.64 36.61 42.63 38.84 Portugal brief 74.96 64.14 52.18 41.13 58.13 48.94 61.65 51.66 55.27 49.11 57.73 48.53 Republic of Korea postal 59.24 54.63 45.01 36.77 55.92 47.10 22.33 20.78 38.95 33.62 58.94 50.04 Romania brief 54.86 42.30 56.88 45.05 50.15 40.92 50.06 39.69 48.65 42.57 47.26 38.19 Russian Federation brief 65.75 57.89 83.38 77.27 51.99 45.07 56.15 48.13 50.80 46.66 51.29 43.25 Slovakia household 76.88 69.22 67.69 61.24 48.79 41.52 58.75 51.23 52.65 48.52 53.89 47.45 Spain brief 86.59 79.16 85.09 75.75 79.27 71.93 84.04 75.47 78.46 72.76 82.88 74.94 Sweden brief 83.41 77.56 62.94 58.83 58.75 52.65 61.74 55.66 84.49 81.51 66.28 59.90 Switzerland postal 79.29 76.82 54.82 49.81 68.59 65.85 60.74 58.88 80.71 80.13 68.72 67.31 Thailand postal 81.68 72.78 37.67 30.94 50.92 43.11 65.15 54.92 40.34 34.88 50.65 43.69 Trinidad and Tobago postal 68.92 61.25 25.26 19.58 58.01 51.25 61.71 54.59 43.39 39.34 55.90 51.23 Turkey household 68.68 62.14 61.75 53.51 64.17 56.18 62.76 54.20 52.51 47.88 62.93 55.96 Turkey postal 32.07 27.02 25.26 19.58 44.50 37.07 34.00 25.71 22.43 18.80 27.87 21.62 Ukraine postal 44.46 35.29 40.99 35.04 46.11 38.76 38.10 32.00 28.30 25.23 27.20 22.03 United Arab Emirates brief 75.25 68.67 61.29 55.98 58.48 55.59 83.55 79.67 53.74 53.63 61.26 57.26 United Kingdom postal 72.41 65.92 59.40 56.02 70.79 66.32 60.19 52.51 65.48 61.75 69.65 65.19 United States postal 74.18 66.95 55.58 48.13 60.45 54.71 51.81 45.95 56.84 51.73 71.03 65.20 Venezuela brief 63.99 65.89 48.97 51.03 56.32 55.24 68.15 68.28 55.45 52.52 65.63 64.77

45

Table 5. Average level of AFFECT, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio Indonesia household 95.5 90.8 93.1 1.05 Ireland brief 93.9 88.0 91.0 1.07 Nigeria household 86.9 83.5 85.2 1.04 Germany brief 87.9 82.0 85.0 1.07 Luxembourg telephone 87.8 80.3 84.0 1.09 Belgium brief 87.7 79.2 83.4 1.11 Spain brief 86.6 79.2 82.9 1.09 Mexico household 86.1 78.8 82.5 1.09 Finland brief 83.9 77.9 80.9 1.08 Denmark postal 84.8 76.8 80.8 1.10 Italy brief 84.8 76.5 80.6 1.11 Sweden brief 83.4 77.6 80.5 1.08 Egypt household 83.3 76.7 80.0 1.09 China household 82.6 76.6 79.6 1.08 France brief 83.1 76.0 79.5 1.09 Malta brief 81.6 76.3 78.9 1.07 Netherlands postal 81.9 74.8 78.4 1.09 Switzerland postal 79.3 76.8 78.1 1.03 Thailand postal 81.7 72.8 77.2 1.12 India household 78.8 72.1 75.5 1.09 Iceland brief 77.6 72.2 74.9 1.07 France postal 78.6 71.1 74.8 1.11 New Zealand postal 77.1 69.6 73.4 1.11 Slovakia household 76.9 69.2 73.1 1.11 Netherlands brief 77.3 67.8 72.6 1.14 Australia postal 73.9 71.2 72.6 1.04 United Arab Emirates brief 75.3 68.7 72.0 1.10 Czech Republic brief 71.7 71.0 71.4 1.01 United States postal 74.2 67.0 70.6 1.11 Canada postal 73.7 67.2 70.5 1.10 Oman brief 72.5 67.8 70.1 1.07 Portugal brief 75.0 64.1 69.6 1.17 United Kingdom postal 72.4 65.9 69.2 1.10 Indonesia postal 72.5 65.5 69.0 1.11 Finland postal 72.2 64.6 68.4 1.12 Canada telephone 68.0 67.3 67.7 1.01 Austria postal 67.7 67.6 67.7 1.00 Bahrain brief 72.0 63.3 67.7 1.14 Chile postal 71.2 61.6 66.4 1.16 Turkey household 68.7 62.1 65.4 1.11 Bulgaria brief 69.0 61.2 65.1 1.13 Trinidad and Tobago postal 68.9 61.2 65.1 1.13 Venezuela brief 64.0 65.9 64.9 0.97 Czech Republic postal 67.8 57.6 62.7 1.18 China postal 64.9 60.3 62.6 1.08 Russian Federation brief 65.7 57.9 61.8 1.14 Estonia brief 65.4 57.5 61.5 1.14 Columbia household 65.6 56.9 61.2 1.15 Greece postal 62.5 58.5 60.5 1.07 Georgia household 63.2 55.7 59.4 1.13 Jordan brief 62.6 55.2 58.9 1.13 Republic of Korea postal 59.2 54.6 56.9 1.08 Costa Rica brief 56.6 57.2 56.9 0.99 Egypt postal 59.1 50.3 54.7 1.17 Argentina brief 59.2 49.5 54.4 1.20 Morocco brief 61.0 46.4 53.7 1.31 Cyprus postal 56.8 48.3 52.6 1.18 Hungary postal 53.0 51.9 52.4 1.02 Poland postal 54.5 48.1 51.3 1.13 Croatia brief 53.4 47.2 50.3 1.13 Lithuania postal 54.6 43.8 49.2 1.25 Romania brief 54.9 42.3 48.6 1.30 Latvia brief 47.9 48.1 48.0 1.00 Ukraine postal 44.5 35.3 39.9 1.26 Turkey postal 32.1 27.0 29.5 1.19 Kyrgyzstan postal 27.0 19.6 23.3 1.38

47 Table 6. Average level of COGNITION, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio Ireland brief 91.9 86.2 89.0 1.07 Nigeria household 90.3 86.6 88.5 1.04 Spain brief 85.1 75.7 80.4 1.12 Russian Federation brief 83.4 77.3 80.3 1.08 Germany brief 80.7 75.2 77.9 1.07 Mexico household 81.8 73.1 77.5 1.12 Finland brief 78.1 73.8 76.0 1.06 Indonesia household 78.6 70.5 74.5 1.11 Luxembourg telephone 77.4 71.0 74.2 1.09 Egypt household 75.6 65.9 70.8 1.15 Belgium brief 73.7 67.0 70.4 1.10 Georgia household 74.7 65.9 70.3 1.13 France brief 70.7 63.1 66.9 1.12 Finland postal 66.8 63.7 65.3 1.05 Slovakia household 67.7 61.2 64.5 1.11 Bulgaria brief 67.1 60.1 63.6 1.12 Czech Republic brief 64.7 62.3 63.5 1.04 Denmark postal 66.2 60.0 63.1 1.10 Italy brief 66.4 57.9 62.2 1.15 Estonia brief 65.4 58.3 61.9 1.12 Argentina brief 66.0 56.9 61.4 1.16 Netherlands brief 64.1 57.8 60.9 1.11 Sweden brief 62.9 58.8 60.9 1.07 Canada postal 62.5 58.9 60.7 1.06 Columbia household 64.4 54.4 59.4 1.18 Canada telephone 57.7 60.3 59.0 0.96 Greece postal 61.5 55.9 58.7 1.10 United Arab Emirates brief 61.3 56.0 58.6 1.09 India household 63.6 53.1 58.4 1.20 Latvia brief 58.6 57.9 58.3 1.01 Australia postal 59.1 57.1 58.1 1.04 United Kingdom postal 59.4 56.0 57.7 1.06 Turkey household 61.8 53.5 57.6 1.15 Chile postal 58.9 52.0 55.4 1.13 Malta brief 58.0 52.6 55.3 1.10 Netherlands postal 58.1 52.4 55.3 1.11 Czech Republic postal 56.7 51.3 54.0 1.11 China household 58.1 49.9 54.0 1.16 Hungary postal 54.5 52.0 53.2 1.05 Iceland brief 55.3 49.5 52.4 1.12 Switzerland postal 54.8 49.8 52.3 1.10 United States postal 55.6 48.1 51.9 1.15 China postal 51.8 50.4 51.1 1.03 Romania brief 56.9 45.1 51.0 1.26 Venezuela brief 49.0 51.0 50.0 0.96 Croatia brief 53.1 45.5 49.3 1.17 New Zealand postal 51.7 46.6 49.2 1.11 Cyprus postal 52.9 45.0 49.0 1.18 France postal 49.0 48.1 48.6 1.02 Costa Rica brief 48.2 48.5 48.3 0.99 Bahrain brief 53.4 43.0 48.2 1.24 Portugal brief 52.2 41.1 46.7 1.27 Oman brief 47.1 42.1 44.6 1.12 Austria postal 43.4 42.6 43.0 1.02 Republic of Korea postal 45.0 36.8 40.9 1.22 Jordan brief 44.5 35.2 39.9 1.26 Poland postal 42.8 36.3 39.5 1.18 Ukraine postal 41.0 35.0 38.0 1.17 Indonesia postal 38.4 32.9 35.7 1.17 Thailand postal 37.7 30.9 34.3 1.22 Morocco brief 37.8 23.2 30.5 1.63 Egypt postal 33.8 26.3 30.0 1.28 Lithuania postal 32.1 25.9 29.0 1.24 Trinidad and Tobago postal 25.3 19.6 22.4 1.29 Turkey postal 25.3 19.6 22.4 1.29 Kyrgyzstan postal 21.7 16.9 19.3 1.28

48 Table 7. Average level of MOBILITY, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio Indonesia postal 87.3 83.5 85.4 1.04 Indonesia household 86.2 80.0 83.1 1.08 Italy brief 80.5 72.5 76.5 1.11 Spain brief 79.3 71.9 75.6 1.10 Luxembourg telephone 79.1 71.1 75.1 1.11 France brief 78.4 71.4 74.9 1.10 Greece postal 76.1 71.4 73.8 1.07 Ireland brief 76.4 71.1 73.7 1.07 Denmark postal 75.4 69.7 72.5 1.08 Mexico household 76.1 68.6 72.3 1.11 France postal 75.9 68.4 72.1 1.11 China household 73.1 65.9 69.5 1.11 Cyprus postal 71.4 66.9 69.1 1.07 United Kingdom postal 70.8 66.3 68.6 1.07 Switzerland postal 68.6 65.9 67.2 1.04 Finland postal 68.7 65.6 67.1 1.05 Bulgaria brief 70.0 62.6 66.3 1.12 Nigeria household 69.0 63.0 66.0 1.10 Canada telephone 66.3 64.9 65.6 1.02 Columbia household 68.8 62.2 65.5 1.11 New Zealand postal 67.9 63.0 65.5 1.08 Australia postal 66.3 61.6 64.0 1.08 China postal 65.3 62.3 63.8 1.05 Argentina brief 67.0 59.8 63.4 1.12 Germany brief 64.3 58.3 61.3 1.10 Belgium brief 64.7 57.4 61.1 1.13 Finland brief 63.1 58.7 60.9 1.07 Turkey household 64.2 56.2 60.2 1.14 Estonia brief 62.4 56.8 59.6 1.10 Costa Rica brief 58.6 59.0 58.8 0.99 Chile postal 62.8 54.6 58.7 1.15 Malta brief 61.6 54.6 58.1 1.13 United States postal 60.4 54.7 57.6 1.10 United Arab Emirates brief 58.5 55.6 57.0 1.05 Austria postal 58.4 53.7 56.0 1.09 Canada postal 58.5 53.2 55.8 1.10 Venezuela brief 56.3 55.2 55.8 1.02 Sweden brief 58.8 52.6 55.7 1.12 Oman brief 58.7 52.1 55.4 1.13 Trinidad and Tobago postal 58.0 51.3 54.6 1.13 Georgia household 58.0 50.6 54.3 1.15 Iceland brief 57.3 49.8 53.5 1.15 Portugal brief 58.1 48.9 53.5 1.19 Bahrain brief 57.3 48.8 53.1 1.17 Latvia brief 53.4 51.6 52.5 1.03 Netherlands postal 55.6 48.6 52.1 1.14 Republic of Korea postal 55.9 47.1 51.5 1.19 Poland postal 52.1 46.5 49.3 1.12 Russian Federation brief 52.0 45.1 48.5 1.15 Netherlands brief 51.4 44.0 47.7 1.17 Egypt household 51.9 42.2 47.1 1.23 Thailand postal 50.9 43.1 47.0 1.18 India household 51.5 42.3 46.9 1.22 Hungary postal 47.5 44.6 46.0 1.06 Czech Republic brief 47.3 44.3 45.8 1.07 Romania brief 50.1 40.9 45.5 1.23 Slovakia household 48.8 41.5 45.2 1.18 Croatia brief 48.0 40.9 44.5 1.17 Jordan brief 48.9 39.1 44.0 1.25 Ukraine postal 46.1 38.8 42.4 1.19 Czech Republic postal 44.2 40.6 42.4 1.09 Turkey postal 44.5 37.1 40.8 1.20 Morocco brief 49.6 31.3 40.4 1.58 Egypt postal 43.4 36.0 39.7 1.20 Lithuania postal 36.3 30.9 33.6 1.18 Kyrgyzstan postal 15.6 12.6 14.1 1.24

49 Table 8. Average level of PAIN, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio United Arab Emirates brief 83.6 79.7 81.6 1.05 Ireland brief 83.6 76.7 80.1 1.09 Spain brief 84.0 75.5 79.8 1.11 Nigeria household 79.4 76.2 77.8 1.04 China household 80.5 72.7 76.6 1.11 Oman brief 77.5 71.7 74.6 1.08 Mexico household 78.0 70.0 74.0 1.12 Italy brief 78.7 68.6 73.6 1.15 Germany brief 75.6 68.0 71.8 1.11 China postal 73.6 66.5 70.0 1.11 Bahrain brief 76.4 63.2 69.8 1.21 France brief 73.0 64.2 68.6 1.14 Venezuela brief 68.2 68.3 68.2 1.00 Canada telephone 69.0 66.5 67.8 1.04 Indonesia household 70.5 63.1 66.8 1.12 India household 71.4 60.8 66.1 1.17 Egypt household 69.7 60.8 65.2 1.15 Finland brief 67.5 61.8 64.6 1.09 France postal 69.0 59.8 64.4 1.15 New Zealand postal 67.5 61.3 64.4 1.10 Australia postal 65.7 63.0 64.4 1.04 Greece postal 66.9 59.8 63.3 1.12 Jordan brief 67.3 58.4 62.9 1.15 Malta brief 65.7 59.4 62.6 1.11 Luxembourg telephone 66.3 56.4 61.4 1.17 Thailand postal 65.2 54.9 60.0 1.19 Switzerland postal 60.7 58.9 59.8 1.03 Belgium brief 64.6 54.6 59.6 1.18 Chile postal 63.1 55.8 59.5 1.13 Sweden brief 61.7 55.7 58.7 1.11 Turkey household 62.8 54.2 58.5 1.16 Czech Republic brief 59.5 57.4 58.5 1.04 Trinidad and Tobago postal 61.7 54.6 58.2 1.13 Iceland brief 61.1 54.6 57.8 1.12 Bulgaria brief 60.5 54.3 57.4 1.11 Portugal brief 61.6 51.7 56.7 1.19 United Kingdom postal 60.2 52.5 56.3 1.15 Georgia household 59.8 52.3 56.0 1.14 Argentina brief 60.1 51.3 55.7 1.17 Slovakia household 58.7 51.2 55.0 1.15 Columbia household 59.2 50.7 55.0 1.17 Canada postal 58.4 51.3 54.9 1.14 Denmark postal 57.7 50.9 54.3 1.13 Netherlands postal 56.4 50.3 53.3 1.12 Russian Federation brief 56.2 48.1 52.1 1.17 Latvia brief 51.9 52.0 52.0 1.00 Finland postal 54.6 49.2 51.9 1.11 Czech Republic postal 54.2 48.1 51.1 1.13 Estonia brief 54.2 46.1 50.1 1.18 United States postal 51.8 45.9 48.9 1.13 Costa Rica brief 47.8 47.6 47.7 1.00 Hungary postal 48.9 45.9 47.4 1.06 Morocco brief 52.6 38.4 45.5 1.37 Netherlands brief 48.9 41.1 45.0 1.19 Romania brief 50.1 39.7 44.9 1.26 Croatia brief 46.1 39.4 42.8 1.17 Austria postal 43.2 39.9 41.6 1.08 Egypt postal 44.0 35.6 39.8 1.24 Poland postal 41.5 35.5 38.5 1.17 Cyprus postal 40.6 31.1 35.8 1.30 Ukraine postal 38.1 32.0 35.0 1.19 Lithuania postal 36.0 28.6 32.3 1.26 Turkey postal 34.0 25.7 29.9 1.32 Indonesia postal 26.8 21.1 24.0 1.27 Republic of Korea postal 22.3 20.8 21.6 1.07 Kyrgyzstan postal 20.6 14.0 17.3 1.47

50 Table 9. Average level of Self Care, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio Luxembourg telephone 89.2 85.4 87.3 1.04 Nigeria household 87.8 83.6 85.7 1.05 China postal 85.8 82.8 84.3 1.04 Ireland brief 86.1 82.5 84.3 1.04 Sweden brief 84.5 81.5 83.0 1.04 Finland brief 83.5 80.7 82.1 1.04 Iceland brief 84.5 78.9 81.7 1.07 Canada telephone 82.4 80.4 81.4 1.03 Switzerland postal 80.7 80.1 80.4 1.01 Spain brief 78.5 72.8 75.6 1.08 Greece postal 76.9 73.8 75.4 1.04 Netherlands postal 78.6 72.0 75.3 1.09 Australia postal 75.4 71.5 73.4 1.05 Argentina brief 75.8 71.0 73.4 1.07 Italy brief 75.7 71.1 73.4 1.07 France brief 73.9 68.9 71.4 1.07 Mexico household 73.3 67.7 70.5 1.08 Germany brief 71.5 66.6 69.0 1.07 Indonesia household 71.7 66.3 69.0 1.08 Finland postal 69.1 67.0 68.1 1.03 Estonia brief 70.2 65.7 67.9 1.07 China household 70.3 64.5 67.4 1.09 Columbia household 67.6 62.8 65.2 1.08 Czech Republic brief 66.7 63.4 65.1 1.05 Malta brief 66.8 61.7 64.3 1.08 Canada postal 65.9 62.6 64.2 1.05 United Kingdom postal 65.5 61.7 63.6 1.06 Cyprus postal 65.7 61.5 63.6 1.07 France postal 65.5 60.4 63.0 1.08 Denmark postal 64.9 60.7 62.8 1.07 Belgium brief 64.4 59.3 61.9 1.09 New Zealand postal 63.2 59.5 61.4 1.06 Bulgaria brief 61.2 56.8 59.0 1.08 Costa Rica brief 58.1 55.8 56.9 1.04 Austria postal 58.1 55.0 56.6 1.06 Netherlands brief 59.2 53.2 56.2 1.11 United States postal 56.8 51.7 54.3 1.10 Venezuela brief 55.5 52.5 54.0 1.06 United Arab Emirates brief 53.7 53.6 53.7 1.00 Portugal brief 55.3 49.1 52.2 1.13 Oman brief 52.8 50.4 51.6 1.05 Slovakia household 52.6 48.5 50.6 1.09 Latvia brief 52.0 49.1 50.6 1.06 Turkey household 52.5 47.9 50.2 1.10 Hungary postal 51.0 47.8 49.4 1.07 Russian Federation brief 50.8 46.7 48.7 1.09 Bahrain brief 49.8 44.7 47.3 1.11 Romania brief 48.7 42.6 45.6 1.14 Chile postal 47.8 43.1 45.4 1.11 Croatia brief 47.9 42.6 45.3 1.12 Czech Republic postal 46.1 43.5 44.8 1.06 Georgia household 44.9 40.8 42.9 1.10 Egypt household 45.7 39.4 42.6 1.16 Trinidad and Tobago postal 43.4 39.3 41.4 1.10 Poland postal 40.6 36.6 38.6 1.11 Jordan brief 41.6 34.9 38.3 1.19 India household 42.4 34.0 38.2 1.25 Thailand postal 40.3 34.9 37.6 1.16 Republic of Korea postal 39.0 33.6 36.3 1.16 Indonesia postal 32.8 29.1 31.0 1.12 Lithuania postal 31.9 29.3 30.6 1.09 Ukraine postal 28.3 25.2 26.8 1.12 Morocco brief 29.1 22.9 26.0 1.27 Egypt postal 22.6 19.4 21.0 1.16 Turkey postal 22.4 18.8 20.6 1.19 Kyrgyzstan postal 11.2 9.6 10.4 1.16

51 Table 10. Average level of Usual Activities, age-standardized, 66 surveys, 2000-2001 Survey Males Females M F Average M/F Ratio Nigeria household 88.8 86.5 87.6 1.03 Ireland brief 82.8 76.7 79.8 1.08 Spain brief 82.9 74.9 78.9 1.11 Luxembourg telephone 82.2 75.4 78.8 1.09 Mexico household 81.8 75.5 78.7 1.08 Argentina brief 82.0 74.6 78.3 1.10 France brief 80.1 72.1 76.1 1.11 Indonesia household 78.2 72.4 75.3 1.08 Finland brief 76.6 71.7 74.2 1.07 Columbia household 75.3 69.3 72.3 1.09 Australia postal 73.1 68.5 70.8 1.07 Canada telephone 70.7 67.9 69.3 1.04 United States postal 71.0 65.2 68.1 1.09 Switzerland postal 68.7 67.3 68.0 1.02 United Kingdom postal 69.6 65.2 67.4 1.07 Iceland brief 70.0 61.9 66.0 1.13 Germany brief 69.0 62.9 66.0 1.10 Denmark postal 69.4 62.3 65.9 1.11 Italy brief 69.9 61.5 65.7 1.14 Malta brief 68.9 62.4 65.7 1.11 Costa Rica brief 65.7 64.9 65.3 1.01 Venezuela brief 65.6 64.8 65.2 1.01 China postal 66.0 63.5 64.7 1.04 Greece postal 67.1 61.8 64.5 1.09 France postal 67.2 61.0 64.1 1.10 Canada postal 65.6 61.3 63.5 1.07 Sweden brief 66.3 59.9 63.1 1.11 Finland postal 64.8 61.4 63.1 1.06 Netherlands postal 66.3 58.3 62.3 1.14 Czech Republic brief 62.3 61.5 61.9 1.01 New Zealand postal 64.6 58.7 61.6 1.10 Estonia brief 63.7 58.9 61.3 1.08 Belgium brief 64.0 56.6 60.3 1.13 Austria postal 61.6 57.5 59.6 1.07 Turkey household 62.9 56.0 59.4 1.12 United Arab Emirates brief 61.3 57.3 59.3 1.07 China household 59.8 53.8 56.8 1.11 Bulgaria brief 59.3 51.9 55.6 1.14 Chile postal 58.5 52.3 55.4 1.12 Georgia household 57.5 51.8 54.7 1.11 Cyprus postal 57.7 51.6 54.6 1.12 Republic of Korea postal 58.9 50.0 54.5 1.18 India household 59.0 49.4 54.2 1.19 Netherlands brief 58.3 49.5 53.9 1.18 Trinidad and Tobago postal 55.9 51.2 53.6 1.09 Portugal brief 57.7 48.5 53.1 1.19 Egypt household 55.9 47.1 51.5 1.19 Hungary postal 52.6 50.0 51.3 1.05 Slovakia household 53.9 47.5 50.7 1.14 Oman brief 52.2 45.0 48.6 1.16 Croatia brief 50.9 45.5 48.2 1.12 Bahrain brief 52.9 43.0 48.0 1.23 Russian Federation brief 51.3 43.2 47.3 1.19 Thailand postal 50.7 43.7 47.2 1.16 Indonesia postal 48.9 44.2 46.5 1.11 Jordan brief 50.7 41.1 45.9 1.23 Latvia brief 43.2 43.4 43.3 1.00 Czech Republic postal 44.9 41.2 43.0 1.09 Romania brief 47.3 38.2 42.7 1.24 Poland postal 42.6 38.8 40.7 1.10 Egypt postal 43.7 35.2 39.5 1.24 Lithuania postal 40.0 35.8 37.9 1.12 Morocco brief 41.7 27.5 34.6 1.51 Turkey postal 27.9 21.6 24.7 1.29 Ukraine postal 27.2 22.0 24.6 1.23 Kyrgyzstan postal 25.3 20.5 22.9 1.23

52 Figure 17: Average Level of Health, age-standardized, 66 surveys: Affect

Male vs. Female Self Report of Affect Average Level of Affect vs. Male/Female Ratio of WHO 2000 - 2001 Survey Affect, WHO Survey 2000-2001

1.6 100 90 1.5 80 1.4 70 1.3 60 1.2 50 40 1.1 Females 30 1.0 20 Ratio of Male/Female 0.9 10 0 0.8 0 102030405060708090100 020406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Affect Self Reported Affect World Standardized Population World Standardized Population 100 100 90

t 90 80 t 80 70 70 60 60 50 50 40 40 30 30 20 Self Reported Affec Reported Self 20 10 Self Reported Affec 10 0 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Affect World Standardized Population

100

t 90 80 70 60 50 40 30 20 Self Reported Affec Reported Self 10 0 0 5000 10000 15000 20000 25000 30000 35000 Pe r Capita GDP

53 Figure 18: Average Level of Health, age-standardized, 66 surveys: Cognition

Male vs. Female Self Report of Cognition Average Level of Cognition vs. Male/Female Ratio of WHO 2000 - 2001 Survey Cognition, WHO Survey 2000-2001

100 1.6 90 1.5 80 1.4 70 60 1.3 50 1.2 40

Females 1.1 30 1.0 20

10 Ratio of Male/Female 0.9 0 0.8 0 102030405060708090100 0 20406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Cognition Self Reported Cognition World Standardized Population World Standardized Population

100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 Self Reported Cognition

Self Reported Cognition 10 0 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Cognition World Standardized Population

100 90 80 70 60 50 40 30 20 10 Self Reported Cognition Self Reported 0 0 5000 10000 15000 20000 25000 30000 35000 Per Capita GDP

54 Figure 19: Average Level of Health, age-standardized, 66 surveys: Mobility

Male vs. Female Self Report of Mobility Average Level of Mobility vs. Male/Female Ratio of WHO 2000 - 2001 Survey Mobility, WHO Survey 2000-2001

100 1.6 90 1.5 80 1.4 70 60 1.3 50 1.2 40

Females 1.1 30 1.0 20

10 Ratio of Male/Female 0.9 0 0.8 0 102030405060708090100 0 20406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Mobility Self Reported Mobility World Standardized Population World Standardized Population

100 100 90 90 ility 80 80 70 70 60 60 50 50 40 40 30 30 20 20

Self Mob Reported 10 Self Reported Mobility Reported Self 10 0 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Mobility World Standardized Population

100 90 80 70 60 50 40 30 20

Self Reported Mobility 10 0 0 5000 10000 15000 20000 25000 30000 35000 Per Capita GDP

55 Figure 20: Average Level of Health, age-standardized, 66 surveys: Pain (higher level, absence of pain)

Male vs. Female Self Report of Pain Average Level of Pain vs. Male/Female Ratio of Pain, WHO 2000 - 2001 Survey WHO Survey 2000-2001

100 1.6 90 1.5 80 1.4 70 60 1.3 50 1.2 40

Females 1.1 30 1.0 20

10 Ratio of Male/Female 0.9 0 0.8 0 102030405060708090100 0 20406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Pain Self Reported Pain World Standardized Population World Standardized Population

100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20

Self Reported Pain 20 Self Reported Pain Reported Self 10 10 0 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Pain World Standardized Population

100 90 80 70 60 50 40 30 20 Self Reported Pain 10 0 0 5000 10000 15000 20000 25000 30000 35000 Per Capita GDP

56 Figure 21: Average Level of Health, age-standardized, 66 surveys: Self Care

Male vs. Female Self Report of Self-care Average Level of Self-care vs. Male/Female Ratio of WHO 2000 - 2001 Survey Self-care, WHO Survey 2000-2001

100 1.6 90 1.5 80 1.4 70 60 1.3 50 1.2 40

Females 1.1 30 1.0 20

10 Ratio of Male/Female 0.9 0 0.8 0 102030405060708090100 0 20406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Self-care Self Reported Self-care World Standardized Population World Standardized Population

100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 Self Reported Self-care

Self Reported Self-care 10 0 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Self-care World Standardized Population

100 90 80 70 60 50 40 30 20 10 Self Reported Self-care 0 0 5000 10000 15000 20000 25000 30000 35000 Per Capita GDP

57 Figure 22: Average Level of Health, age-standardized, 66 surveys: Usual Activities

Male vs. Female Self Report of Usual Activities Average Level of Usual Activities vs. Male/Female WHO 2000 - 2001 Survey Ratio of Usual Activities, WHO Survey 2000-2001

100 1.6 90 1.5 80 1.4 70 60 1.3 50 1.2 40

Females 1.1 30 1.0 20

10 Ratio of Male/Female 0.9 0 0.8 0 102030405060708090100 0 20406080100 Males Average Level for Males and Females Combined

Male Life Expectancy at birth (2000) vs. Female Life Expectancy at birth (2000) vs. Self Reported Usual Activities Self Reported Usual Activities World Standardized Population World Standardized Population

100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 Self Reported Usual Activities 0 ReportedSelf Usual Activities 0 40 45 50 55 60 65 70 75 80 85 40 45 50 55 60 65 70 75 80 85 Life Expectancy at birth Life Expectancy at birth

Per Capita Gross Domestic Product (PPP 1998) vs. Self Reported Usual Activities World Standardized Population

100 90 80 70 60 50 40 30 20 10

Self ReportedSelf Usual Activities 0 0 5000 10000 15000 20000 25000 30000 35000 Per Capita GDP

58 V. Discussion

We address the main objective of this paper: whether the estimated mean levels of health by age and sex groups, or the mean aggregate, age standardized level by sex, for six domains of health are comparable across 66 population based surveys. Specifically, we consider whether our new data collection and analyses methods applied to 66 surveys in 57 countries have enhanced:

S the information content on health status data collected through surveys, and S the comparability of this information across survey populations.

To do so, we include a comparison of selected results from this analysis with those from our previous approach to estimate levels of health, based on 64 existing data sets from 46 countries -- data sets that did not contain a means to calibrate self-reported responses across survey populations nor information on a range of domains (see Sadana et al. 2000).

Concerning an evaluation of the validity of our new methods using the vignette strategy to calibrate responses, there is no gold standard or measurement of "truth" that captures all aspects of each domain of health. Instead, several approaches to estimate validity are required as no single aspect of validity would provide a definitive evaluation. Three basic criteria provide necessary evidence that the new methods have enhanced the information content and comparability of health status data collected through surveys include: (i) that the estimated levels of health should decrease as age increases (criterion validity); (ii) that the differences in the estimated levels of health, for most domains, should reflect expected differences within and across populations, for example between males and females, between populations with high child and high adult mortality vs. those with low child and adult mortality or between populations with high and low GDP per capita (face validity); and (iii) that besides covering the key concepts of health, each of the domains assessed of health as measured should provide unique information (content validity).

V.1 INFORMATION CONTENT 5.1.1 DIFFERENCE BETWEEN ORDINAL RESPONSE AND ESTIMATED LEVEL OF HEALTH

In section 3.7.3, we provide illustrations comparing the ordinal response and the estimated level of health across all domains (Figure 9) for one population from the WHO EURO A mortality sub-group (Luxembourg) and another from the WHO SEARO D mortality sub-group (Andhra Pradesh, India). The mean ordinal responses by age for affect, cognition, self-care and usual activities, particularly in Luxembourg, show very little variation over age. These same mean ordinal responses are similar for the two populations across all age groups, particularly for cognition, mobility and pain. However, the posterior estimated levels of health across five of the six domains assessed (with the exception to some degree of affect), shows clearly that the level of health decreases as age increases. Furthermore, the requirement of face validity that levels of health in certain domains, such as mobility, is significantly better in Luxembourg than in Andhra Pradesh, is met. 5.1.2 ADDED VALUE OF MULTI-DIMENSIONAL APPROACH

Based on the posterior estimated level of health, a correlation matrix of all survey data combined shows that the four domains that directly assess health (e.g. affect, cognition, mobility, pain) clearly provide unique information, with correlations ranging between 0.54 and 0.68. These are below 0.70, the standard cut-off used in psychometrics to assess the similarity or difference of different constructs (Nunnally and Bernstein 1994). As expected, domains that serve as proximate measures of health, self-care and usual activities, are more highly correlated with each other (0.81), and more highly correlated with mobility or pain ( 0.71 and 0.78 respectively), and less so with those directly assessing mental health (i.e., 0.56 to 0.64 with affect or cognition). These results provide some evidence that each of the domains that directly assess health provide unique information, that the

59 assessment of health as a multi-dimensional construct is useful in terms of the enhanced information content. Additional tests that build on confirmatory factor analyses approaches for six domains assessed, as more stringent tests of construct validity, are being considered.

Table 11. Correlation Matrix Across Domains, Estimated Level of Health, 66 surveys Domain Affect Cognition Mobility Pain Self Care Usual Activities Affect 1.0000 Cognition 0.5558 1.0000 Mobility 0.5686 0.5435 1.0000 Pain 0.6259 0.5989 0.6673 1.0000 Self Care 0.5575 0.5867 0.7563 0.7160 1.0000 Usual Activities 0.5639 0.6417 0.7847 0.7117 0.8075 1.0000

V.2 COMPARABILITY

5.2.1 COMPARISON OF NEW METHODS WITH PREVIOUS ANALYSES: SELECTED RESULTS BY AGE -SEX GROUPS

We focus our comparison on two populations, one from WHO AMRO A mortality sub-region (USA) and another from WHO WPRO B mortality sub-region (China -- selected regions as noted). Figure 23 illustrates the estimated level of health (uni-dimensional from the previous analysis)7 with our current results (selected domains shown), across age and sex groups for both populations. The previous analysis showed almost no decrement to full health, across all age groups from eight provinces included from China8. The data set from the USA is the NHANES III completed in 1994. Both surveys had extensive questions on self-reported health, using ordinal response scales.

Given the mean age group and sex results, based on our previous analysis, we did not assume that these data were comparable, nor that the Chinese data actually reflected the health status of the population. Furthermore, separate analysis on the NHANES III data has shown evidence of cut-point shifts using measured performance tests to calibrate self-reported responses across socio-economic groups, within the USA population (Iburg et al. 2002).

Our current analysis approach, with results illustrating estimates for mobility, pain and cognition, do not show the high ceiling effects from the China in-depth household survey (sample covering Shandong, Henana and Gansu Provinces)9. We believe, by taking into account cut-point shifts, this data is more comparable across age and sex groups, both within each population and across the two populations. It is interesting to note that the comparison between the two countries differs depending upon the domain of health examined from our new analysis, i.e., mobility, pain or cognition shown. That such differences exist provide additional evidence that a multi-dimensional approach to assess health status may provide more comprehensive and complex insights on the health status of a population.

7 Given limitations in existing data sets, our previous analysis was based on one, general latent variable assessing health, rather than six domains (see Sadana et al. 2000). 8 The China Health and Nutrition Survey 1993 in eight provinces was conducted with the assistance of the Carolina Population Centre, University of North Carolina, and is part of a longitudinal, integrated survey. 9 Two of the provinces, Shandong and Henan, overlap with the survey conducted by CPC/UNC in 1993.

60 Figure 23. Estimated levels of health, USA and selected regions of China, by age and sex groups

Level of health China, male Level of Mobility China, male China, female (1999-2000 analysis) China, female (2000-2001 analysis) USA, male USA, male USA, female USA, female 100 100

80 80

60 60

40 40

20 20

0 0 0 5 15 25 35 45 55 65 75+ 15-29 30-44 45-59 60-69 70-79 80+ Age Group Age Group

Leve l of Pain China, male China, male China, female Level of Cognition (2000-2001 analysis) China, female USA, male (2000-2001 analysis) USA, male USA, female USA, female 100 80

80 60

60 40 40

20 20

0 0 15-29 30-44 45-59 60-69 70-79 80+ 15-29 30-44 45-59 60-69 70-79 80+ Age Group Age Group

61 5.2.2 SELECTED RESULTS, AGGREGATED AND AGE-STANDARIZED

We highlight the age standardized results, aggregated across age groups, by sex. Figure 24 shows the estimated level of health (mobility shown here, see Figures 17 - 22 for all domains), and life expectancy by sex. We document that higher levels of life expectancy are correlated with higher estimated levels of health (+0.3), in this case for mobility, for either males or females. For the other five domains, this correlation is positive as well. Alternatively, although the determinants of health (mobility shown) and life expectancy are not identical, some similarity is expected, as these results suggest (criterion validity).

Figure 24. Estimated level of health and life expectancy, for males and females, Mobility

2000-2001 analysis (57 countries, 66 surveys) 2000-2001 analysis (57 countries, 66 surveys)

100 100 90 90 80 80 70 70 60 60 Mobility 50 50 40 40 30 30 Level of of Level 20 Mobility Level of 20 10 10 0 0 40 50 60 70 80 90 40 50 60 70 80 Life Expectancy at birth, females Life Expectancy at birth, males

Another approach to evaluate the information content and cross-population comparability of the results is to interpret the data from surveys in conjunction with data external to health, from the same countries. Such data may include the per capita gross domestic product or the per capita total health expenditures (criterion validity). Figure 25 illustrates the aggregated, age standardized estimates, averaged for both males and females, in comparison with GDP (PPP). We document that higher levels of GDP (PPP), are correlated with higher estimated levels of health (+0.4 ), for the domain of mobility, as expected (see Figures 17 - 22 for all domains, showing a positive correlation).

Figure 26 groups the average estimated level of health for each domain, by sex, for 51 countries into four geographic or economic strata. For both males and females, average levels of affect, mobility, pain, self-care and usual activities are highest in a subset of OECD member countries, followed by Latin American countries, former Socialist economies, and then countries in the Eastern Mediterranean area including Turkey and Kyrgystan. Only minor deviations from this pattern are noted for cognition and pain. This pattern is not surprising and contributes to further face validity.

Although not sufficient, these and other results suggest face and criterion validity of our estimates based on new methods. Based on our review of the new methods to collect and analyze self-reported data on health, our confidence in the information content of interview-based surveys has increased. We consider these results as a significant step forward in the use of self-reported data on health. These results have been incorporated within the calculation of healthy life expectancy (Mathers et al. 2001) and in the estimation of inequalities in the distribution of health (Gakidou et al. 2001), among other analyses.

62 Figure 25. GDP (PPP) and Estimated level of health (average for males and females)

(2000-2001 analysis)

100 90 80 70 60 50 40 30 20 Level of Level Mobility 10 0 100 1000 10000 100000 Per Capita GDP (PPP)

Figure 26. Multi-dimensional Health Profile, selected surveys and countries

Eastern Mediterranean (9 countries) Former Socialist (13 countries) Latin American (9 countries) OECD subset (22 countries)

90

80

70

60

50

40

30

Estimated Level of Health of Level Estimated 20

10

0 Aff M Aff F Cog M Cog F Mob M Mob F Pain M Pain F Self M Self F Usual M Usual F Dom ains

63 VI. NEXT STEPS

The next steps will focus on three areas: (i) additional analyses on the existing data, (ii) updating of our methods, and (iii) surveys in additional countries.

Additional analysis will include those highlighted through out the text of this paper, in order to provide further evidence concerning validity -- both the extent to which the new methods measure what it is intended to measure, or more broadly, the range of interpretations that cam be reasonably attributed to the estimated levels of health, by domain. Across all 66 surveys, these analyses will address:

S more stringent tests of hypotheses stated S parameter uncertainty estimates

For the ten in-depth household surveys, these analyses will address:

S measured performance tests strategy for calibration: cognition, vision, mobility S posterior estimates: comparison between HOPIT and CHOPIT S auxiliary questions: information content and item reduction strategies S classical psychometric properties concerning additional domains from the in-depth household surveys

Along with a critical evaluation of the vignette strategy to calibrate responses, these analyses will be an input to update the survey module on health status. This will include a revision, as necessary, of the questions addressing each core domain of health and the corresponding set of vignettes. This updated module, within the planned WHO World Health Survey, will then be implemented in surveys in additional countries, particularly in the African region.

Given that the current sampling strategy includes the non-institutionalized population, the further expansion of the sampling protocol and adaptation of methods to include representative samples of individuals in long-term care facilities (of any type), is under consideration.

Acknowledgements

We thank the following individuals for their contributions: Nicole Valentine and Juan Pablo Ortiz for fruitful discussions on parallel analytical efforts in the area of health system responsiveness; Josh Salomon for the conception of the vignette adjustment strategy; Colin Mathers for contributing to the development of the health status assessment module and comments on this manuscript; Pierre Lewalle for his contribution in coordinating the language translation protocols, the first step towards cross-population comparability; Can Celik for obtaining and managing data sets from survey sites; Lydia Bendib and Maria Villanueva for their contribution in coordinating data collection across the 66 survey sites; Melroy Menezes and René Lavallée for their assistance in preparing graphs within this manuscript; and Emre Ozaltin for comments on this manuscript.

64 VII. References

Ahmad O, Boschi-Pinto C, Lopez AD, Murray CLJ, Lozano R, Inoue M (2000). Age standardization: the new WHO world standard population. Global Programme on Evidence for Health Policy, Discussion Paper # 31, World Health Organization.

Evans DE, Bendib L, Tandon A, Lauer J, Ebener S, Hutubessy R, Asada Y, Murray CJL. Estimates of income per capita, literacy, educational attainment, absolute poverty and income Gini coefficients for the World Health Report 2000. Geneva, World Health Organization, 2000 (GPE Discussion Paper No. 7).

Gakidou E, Sadana R, Salomon J et al (2002). Inequality in health states Global, Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

Honaker J, Joseph A, King G et al. (1999). Amelia: A program for missing data. Department of Government, Harvard University, Cambridge, Massachusetts.

Iburg KM, Salomon JA, Tandon A, Murry CJL (2002). Cross-population comparability of self- reported and physician-assessed mobility levels: evidence from the Third National Health and Nutrition Examination Survey. In CJL Murray et al., Summary Measures of Population Health, World Health Organization, Geneva.

Kroeger A, Zurita A, Perez-Samaniego C, Berg H. Illness perception and use of health services in North-East Argentina. Health Policy and Planning 1988 3: 141-151.

Long, J.S., and J. Freese (2001), Regression Models for Categorical Dependent Variables using STATA, College Station, Texas: STATA Press.

Mathers CD, Murray CJL, Lopez AD, Salomon JA, Sadana R, Ustün TB, Chatterji S (2001). Estimates of healthy life expectancy for 191 countries in the year 2000: methods and results. Global Programme on Evidence for Health Policy, World Health Organization, Geneva.

McDowell I, Newell C (1996). Measuring health: a guide to rating scales and questionnaires. second edition, Oxford University Press, Oxford.

Murray CJL and Lopez AD, eds. (1996) The Global Burden of Disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2030, Global Burden of Disease and Injury Series, Vol.1, Harvard University Press, Cambridge

Murray CJL, Mathers CD, Lopez AD, Salomon J, Lozano R (eds). Summary measures of population health, Geneva, World Health Organization. Forthcoming

Murray CJL, Tandon A, Salomon JA and Mathers CD. (2000) Enhancing cross-population comparability of survey results. Global Programme on Evidence for Health Policy, Discussion Paper # 35, World Health Organization, Geneva.

Murray CJL (1996), Epidemiology and Morbidity Transitions in India, in DasGupta, M., L.C. Chen, and T.N. Krishnan (eds.), Health, Poverty and Development in India, Delhi: Oxford University Press. Murray C.J.L., A. Tandon, J. Salomon, C.D. Mathers, and R. Sadana (2001), "Cross-Population Comparability of Evidence for Health Policy," Global Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

65 Nunnally JC and Bernstein IR Psychometric Theory. Third edition. McGraw Hill, 1994 New York.

Sadana R, Salomon J, Tandon A, Chatterji S, Murray CJL. Health state vignettes: design, empirical analysis and critical assessment. Global Programme on Evidence for Health Policy, Discussion Paper # --, World Health Organization, Geneva.

Sadana, R., C.D. Mathers, A.D. Lopez, C.J.L. Murray, and K. Iburg (2000), "Comparative analyses of more than 50 household surveys on health status," GPE Discussion paper #15, Geneva: World Health Organization

Salomon, J.A., A. Tandon, C.J.L. Murray (2001), "Using Vignettes to Improve Cross-Population Comparability of Health Surveys: Concepts, Design and Evaluation Techniques," Global Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

Tandon, A, S Chatterji, B Ustun, JA Salomon, and CJL Murray (2001), "Cross-Validation of Cut- Point Estimation Using Measured Tests and Vignettes: The Case of Vision," Global Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

Tandon, A., C.J.L. Murray, J.A. Salomon, and G. King (2001), “Statistical Models for Enhancing Cross-Population Comparability,” Global Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

United Nations (1995). Guidelines for household surveys on health. Department for economic and social information and policy analysis. Statistical Division, New York.

Üstün TB, Chatterji S, Rehm J, Kennedy C, Prieto L, Epping-Jordan J, Saxena S, and Pull C in collaboration with WHO/NIH Joint Project Collaborators. World Health Organization Disability Assessment Schedule II (WHO DAS II): Development and Psychometric Testing. In press.

Üstün, T.B., S. Chatterji, M. Villanueva et al. (2001), WHO Multi-Country Household Survey Study on Health and Responsiveness 2000-2001, Global Programme on Evidence for Health Policy Discussion Paper, Geneva: World Health Organization.

World Health Organization (2000). World Health Report 2000. Geneva, World Health Organization

World Health Organization (2001). International Classification of Functioning, Disability and Health (ICF). Geneva: World Health Organization

Wright, B.D., and M. Mok (2000), Rasch Models Overview Journal of Applied Measurement 1(1):83-106.

66 Appendix 1: Distribution of mean cut-points (t1-t4) on latent variable scale-Cognition, 66 surveys Survey Tau 1 Survey Tau 2 Survey Tau 3 Survey Tau 4 36. INDh -4.445 12. CHNh -3.220 35. IDNp -2.525 35. IDNp -1.228 34. IDNh -4.363 58. SVKh -3.145 12. CHNh -2.281 40. JORb -1.109 58. SVKh -4.343 33. HUNp -2.997 7. BHRb -2.212 53. OMNb -1.098 12. CHNh -4.333 35. IDNp -2.960 53. OMNb -2.184 46. MARb -1.074 21. EGYh -4.218 7. BHRb -2.950 58. SVKh -2.083 7. BHRb -1.064 22. EGYp -4.086 52. NZLp -2.938 42. KORp -2.059 12. CHNh -1.047 33. HUNp -4.040 13. CHNp -2.907 40. JORb -2.039 33. HUNp -0.995 52. NZLp -4.014 53. OMNb -2.888 1. AREb -2.013 1. AREb -0.959 23. ESPb -3.978 23. ESPb -2.884 33. HUNp -1.972 14. COLh -0.957 14. COLh -3.976 1. AREb -2.874 36. INDh -1.946 66. VENb -0.903 53. OMNb -3.960 3. AUSp -2.828 48. MLTb -1.941 36. INDh -0.897 47. MEXh -3.908 42. KORp -2.821 43. LTUp -1.934 10. CHEp -0.883 43. LTUp -3.853 40. JORb -2.813 10. CHEp -1.931 55. PRTb -0.881 29. GBRp -3.841 66. VENb -2.811 41. KGZp -1.902 48. MLTb -0.878 7. BHRb -3.832 43. LTUp -2.809 39. ITAb -1.881 34. IDNh -0.869 37. IRLb -3.813 34. IDNh -2.796 49. NGAh -1.880 41. KGZp -0.857 13. CHNp -3.808 10. CHEp -2.780 13. CHNp -1.870 58. SVKh -0.855 60. THAp -3.806 9. CANt -2.775 55. PRTb -1.870 15. CRIb -0.842 40. JORb -3.794 14. COLh -2.773 52. NZLp -1.869 57. RUSb -0.840 9. CANt -3.785 37. IRLb -2.766 23. ESPb -1.849 47. MEXh -0.833 1. AREb -3.785 21. EGYh -2.761 34. IDNh -1.838 32. HRVb -0.828 19. DEUb -3.784 36. INDh -2.758 66. VENb -1.811 23. ESPb -0.803 55. PRTb -3.780 39. ITAb -2.751 46. MARb -1.810 43. LTUp -0.803 18. CZEp -3.779 60. THAp -2.749 60. THAp -1.790 27. FRAb -0.797 30. GEOh -3.778 48. MLTb -2.746 47. MEXh -1.785 39. ITAb -0.790 2. ARGb -3.777 64. UKRp -2.742 28. FRAp -1.778 30. GEOh -0.783 17. CZEb -3.767 57. RUSb -2.727 16. CYPp -1.776 21. EGYh -0.782 48. MLTb -3.762 47. MEXh -2.727 4. AUTp -1.759 56. ROMb -0.778 65. USAp -3.758 29. GBRp -2.719 56. ROMb -1.757 5. BELb -0.778 24. ESTb -3.756 65. USAp -2.713 14. COLh -1.752 42. KORp -0.747 39. ITAb -3.755 19. DEUb -2.711 64. UKRp -1.748 50. NLDb -0.731 10. CHEp -3.747 45. LVAb -2.709 65. USAp -1.738 4. AUTp -0.731 45. LVAb -3.745 17. CZEb -2.706 9. CANt -1.735 52. NZLp -0.730 35. IDNp -3.741 4. AUTp -2.682 57. RUSb -1.731 11. CHLp -0.723 4. AUTp -3.741 15. CRIb -2.679 17. CZEb -1.720 9. CANt -0.722 6. BGRb -3.731 46. MARb -2.668 21. EGYh -1.712 37. IRLb -0.712 57. RUSb -3.726 2. ARGb -2.653 45. LVAb -1.712 44. LUXt -0.700 32. HRVb -3.721 30. GEOh -2.650 8. CANp -1.712 63. TURp -0.696 15. CRIb -3.690 32. HRVb -2.649 3. AUSp -1.711 22. EGYp -0.695 8. CANp -3.690 56. ROMb -2.648 37. IRLb -1.705 16. CYPp -0.693 42. KORp -3.690 8. CANp -2.637 27. FRAb -1.695 45. LVAb -0.691 3. AUSp -3.687 55. PRTb -2.627 29. GBRp -1.666 62. TURh -0.691 62. TURh -3.675 22. EGYp -2.622 5. BELb -1.666 60. THAp -0.688 49. NGAh -3.674 41. KGZp -2.602 63. TURp -1.655 2. ARGb -0.687 64. UKRp -3.654 16. CYPp -2.595 20. DNKp -1.645 49. NGAh -0.675 31. GRCp -3.647 62. TURh -2.573 26. FINp -1.644 59. SWEb -0.672 59. SWEb -3.641 25. FINb -2.573 32. HRVb -1.644 64. UKRp -0.664 25. FINb -3.636 54. POLp -2.557 19. DEUb -1.644 17. CZEb -0.630 66. VENb -3.598 26. FINp -2.553 25. FINb -1.640 20. DNKp -0.617 54. POLp -3.597 18. CZEp -2.547 15. CRIb -1.640 8. CANp -0.611 56. ROMb -3.546 59. SWEb -2.546 30. GEOh -1.637 28. FRAp -0.611 63. TURp -3.525 63. TURp -2.543 54. POLp -1.632 65. USAp -0.605 11. CHLp -3.524 28. FRAp -2.538 22. EGYp -1.627 25. FINb -0.602 61. TTOp -3.502 24. ESTb -2.531 59. SWEb -1.625 6. BGRb -0.600 46. MARb -3.501 31. GRCp -2.520 62. TURh -1.623 19. DEUb -0.597 26. FINp -3.487 27. FRAb -2.496 24. ESTb -1.619 13. CHNp -0.591 28. FRAp -3.465 61. TTOp -2.490 2. ARGb -1.603 3. AUSp -0.547 16. CYPp -3.455 11. CHLp -2.479 61. TTOp -1.568 24. ESTb -0.526 5. BELb -3.450 44. LUXt -2.470 38. ISLb -1.546 61. TTOp -0.524 51. NLDp -3.422 5. BELb -2.454 44. LUXt -1.540 54. POLp -0.522 27. FRAb -3.401 49. NGAh -2.449 31. GRCp -1.526 29. GBRp -0.512 44. LUXt -3.399 6. BGRb -2.432 18. CZEp -1.520 38. ISLb -0.507 38. ISLb -3.391 20. DNKp -2.430 11. CHLp -1.500 26. FINp -0.498 50. NLDb -3.370 38. ISLb -2.387 6. BGRb -1.487 31. GRCp -0.477 20. DNKp -3.304 51. NLDp -2.341 50. NLDb -1.412 18. CZEp -0.393 41. KGZp -3.200 50. NLDb -2.334 51. NLDp -1.369 51. NLDp -0.361

67 Appendix 2: Complete estimates from HOPIT, means and cut-points, COGNITION

Vignettes Coef. Std. Err. z P>z [95% Conf. Interval] vignette2 -1.703 0.011 -160.57 0.000 -1.724 -1.682 vignette3 -1.892 0.011 -177.88 0.000 -1.913 -1.872 vignette4 -2.048 0.011 -191.49 0.000 -2.069 -2.027 vignette5 -2.534 0.011 -231.1 0.000 -2.555 -2.512 vignette6 -2.637 0.011 -241.02 0.000 -2.659 -2.616 vignette7 -3.235 0.011 -287.41 0.000 -3.257 -3.213 vignette8 -3.896 0.012 -331.09 0.000 -3.919 -3.873

Mean Coef. Std. Err. z P>z [95% Conf. Interval] _Iagedummy_2 -0.036 0.015 -2.46 0.014 -0.066 -0.007 Age 30-44 _Iagedummy_3 -0.282 0.016 -17.31 0.000 -0.314 -0.250 Age 45-59 _Iagedummy_4 -0.701 0.018 -39.43 0.000 -0.736 -0.666 Age 60+ sex 0.180 0.011 16.32 0.000 0.158 0.202 Male educ 0.030 0.001 21.78 0.000 0.027 0.033 Education (yrs) _Icountry_2 0.256 0.092 2.79 0.005 0.076 0.436 Argentina brief _Icountry_3 0.109 0.083 1.31 0.189 -0.054 0.272 Australia postal _Icountry_4 -0.277 0.083 -3.33 0.001 -0.440 -0.114 Austria postal _Icountry_5 0.384 0.086 4.44 0.000 0.214 0.553 Belgium brief _Icountry_6 0.177 0.086 2.05 0.040 0.008 0.347 Bulgaria brief _Icountry_7 -0.097 0.092 -1.06 0.289 -0.277 0.083 Bahrain brief _Icountry_8 0.128 0.110 1.16 0.247 -0.088 0.344 Canada postal _Icountry_9 0.084 0.113 0.74 0.459 -0.137 0.304 Canada telephone _Icountry_10 -0.036 0.105 -0.34 0.732 -0.242 0.170 Switzerland postal _Icountry_11 0.007 0.085 0.09 0.930 -0.159 0.174 Chile postal _Icountry_12 0.093 0.067 1.39 0.166 -0.038 0.224 China household _Icountry_13 -0.087 0.080 -1.08 0.278 -0.245 0.070 China postal _Icountry_14 0.259 0.069 3.77 0.000 0.124 0.393 Columbia household _Icountry_15 -0.036 0.091 -0.4 0.689 -0.214 0.142 Costa Rica brief _Icountry_16 -0.111 0.094 -1.18 0.237 -0.295 0.073 Cyprus postal _Icountry_17 0.153 0.085 1.8 0.072 -0.014 0.321 Czech Republic brief _Icountry_18 -0.022 0.084 -0.26 0.796 -0.186 0.143 Czech Republic postal _Icountry_19 0.602 0.087 6.95 0.000 0.433 0.772 Germany brief _Icountry_20 0.219 0.080 2.74 0.006 0.062 0.376 Denmark postal _Icountry_21 0.574 0.071 8.13 0.000 0.435 0.712 Egypt household _Icountry_22 -0.746 0.078 -9.6 0.000 -0.898 -0.593 Egypt postal _Icountry_23 0.703 0.091 7.74 0.000 0.525 0.881 Spain brief _Icountry_24 0.267 0.086 3.11 0.002 0.099 0.435 Estonia brief _Icountry_25 0.649 0.088 7.38 0.000 0.477 0.821 Finland brief _Icountry_26 0.309 0.081 3.8 0.000 0.149 0.468 Finland postal _Icountry_27 0.289 0.088 3.3 0.001 0.117 0.460 France brief _Icountry_28 -0.132 0.098 -1.35 0.177 -0.323 0.059 France postal _Icountry_29 0.068 0.085 0.8 0.423 -0.099 0.236 United Kingdom postal _Icountry_30 0.393 0.067 5.88 0.000 0.262 0.524 Georgia household _Icountry_31 0.178 0.088 2.01 0.044 0.005 0.351 Greece postal _Icountry_32 -0.113 0.078 -1.44 0.149 -0.266 0.041 Croatia brief _Icountry_33 -0.043 0.079 -0.54 0.588 -0.198 0.112 Hungary postal _Icountry_34 0.688 0.067 10.21 0.000 0.556 0.820 Indonesia household _Icountry_35 -0.576 0.073 -7.91 0.000 -0.719 -0.433 Indonesia postal _Icountry_36 0.347 0.070 4.96 0.000 0.210 0.484 India household _Icountry_37 0.976 0.103 9.44 0.000 0.773 1.178 Ireland brief _Icountry_38 -0.174 0.101 -1.72 0.085 -0.373 0.024 Iceland brief _Icountry_39 0.203 0.087 2.34 0.019 0.033 0.372 Italy brief

68 _Icountry_40 -0.342 0.089 -3.84 0.000 -0.517 -0.168 Jordan brief _Icountry_41 -1.071 0.081 -13.26 0.000 -1.229 -0.912 Kyrgyzstan postal _Icountry_42 -0.311 0.111 -2.81 0.005 -0.528 -0.094 Republic of Korea postal _Icountry_43 -0.663 0.075 -8.84 0.000 -0.810 -0.516 Lithuania postal _Icountry_44 0.497 0.096 5.17 0.000 0.308 0.685 Luxembourg telephone _Icountry_45 0.089 0.091 0.98 0.328 -0.089 0.267 Latvia brief _Icountry_46 -0.533 0.089 -6 0.000 -0.707 -0.359 Morocco brief _Icountry_47 0.695 0.071 9.77 0.000 0.556 0.835 Mexico household _Icountry_48 0.024 0.103 0.23 0.818 -0.177 0.225 Malta brief _Icountry_49 1.136 0.072 15.7 0.000 0.994 1.277 Nigeria household _Icountry_50 0.134 0.084 1.59 0.113 -0.032 0.299 Netherlands brief _Icountry_51 -0.022 0.097 -0.22 0.823 -0.211 0.168 Netherlands postal _Icountry_52 -0.147 0.077 -1.91 0.057 -0.298 0.004 New Zealand postal _Icountry_53 -0.277 0.088 -3.13 0.002 -0.450 -0.104 Oman brief _Icountry_54 -0.426 0.085 -5 0.000 -0.594 -0.259 Poland postal _Icountry_55 -0.192 0.084 -2.28 0.022 -0.357 -0.027 Portugal brief _Icountry_56 -0.147 0.084 -1.76 0.079 -0.312 0.017 Romania brief _Icountry_57 0.619 0.082 7.52 0.000 0.457 0.780 Russian Federation brief _Icountry_58 0.266 0.085 3.12 0.002 0.099 0.432 Slovakia household _Icountry_59 0.264 0.086 3.08 0.002 0.096 0.431 Sweden brief _Icountry_60 -0.439 0.080 -5.5 0.000 -0.596 -0.283 Thailand postal _Icountry_61 -0.058 0.080 -0.72 0.472 -0.216 0.100 Trinidad and Tobago postal _Icountry_62 0.131 0.070 1.89 0.059 -0.005 0.267 Turkey household _Icountry_63 -0.876 0.072 -12.13 0.000 -1.018 -0.735 Turkey postal _Icountry_64 -0.479 0.088 -5.46 0.000 -0.651 -0.307 Ukraine postal _Icountry_65 -0.094 0.082 -1.15 0.250 -0.254 0.066 United States postal _Icountry_66 -0.190 0.091 -2.08 0.037 -0.369 -0.011 Venezuela brief _cons -0.726 0.068 -10.72 0.000 -0.859 -0.593

Cut-point 1 Coef. Std. Err. z P>z [95% Conf. Interval] _Iagedummy_2 0.019 0.010 1.87 0.062 -0.001 0.039 Age 30-44 _Iagedummy_3 0.011 0.011 0.95 0.341 -0.011 0.033 Age 45-59 _Iagedummy_4 -0.045 0.013 -3.5 0.000 -0.070 -0.020 Age 60+ sex -0.007 0.008 -0.86 0.388 -0.022 0.009 Male educ 0.000 0.001 -0.37 0.713 -0.002 0.002 Education (yrs) _Icountry_2 0.018 0.063 0.29 0.770 -0.105 0.142 Argentina brief _Icountry_3 0.117 0.057 2.05 0.041 0.005 0.228 Australia postal _Icountry_4 0.059 0.059 1 0.320 -0.057 0.174 Austria postal _Icountry_5 0.348 0.056 6.24 0.000 0.238 0.457 Belgium brief _Icountry_6 0.067 0.059 1.14 0.253 -0.048 0.182 Bulgaria brief _Icountry_7 -0.047 0.062 -0.75 0.451 -0.168 0.075 Bahrain brief _Icountry_8 0.107 0.074 1.45 0.148 -0.038 0.252 Canada postal _Icountry_9 0.010 0.078 0.12 0.902 -0.144 0.163 Canada telephone _Icountry_10 0.048 0.072 0.66 0.508 -0.093 0.189 Switzerland postal _Icountry_11 0.274 0.057 4.76 0.000 0.161 0.386 Chile postal _Icountry_12 -0.544 0.045 -11.96 0.000 -0.633 -0.455 China household _Icountry_13 -0.022 0.056 -0.4 0.688 -0.132 0.087 China postal _Icountry_14 -0.187 0.046 -4.05 0.000 -0.277 -0.096 Columbia household _Icountry_15 0.100 0.061 1.63 0.104 -0.020 0.220 Costa Rica brief _Icountry_16 0.340 0.063 5.4 0.000 0.216 0.463 Cyprus postal _Icountry_17 0.029 0.058 0.5 0.616 -0.084 0.142 Czech Republic brief _Icountry_18 0.022 0.058 0.38 0.704 -0.092 0.136 Czech Republic postal _Icountry_19 0.016 0.057 0.28 0.782 -0.097 0.128 Germany brief _Icountry_20 0.492 0.053 9.36 0.000 0.389 0.595 Denmark postal _Icountry_21 -0.430 0.048 -8.97 0.000 -0.524 -0.336 Egypt household

69 _Icountry_22 -0.294 0.057 -5.16 0.000 -0.406 -0.182 Egypt postal _Icountry_23 -0.180 0.061 -2.95 0.003 -0.300 -0.060 Spain brief _Icountry_24 0.044 0.059 0.75 0.454 -0.072 0.160 Estonia brief _Icountry_25 0.164 0.058 2.85 0.004 0.051 0.276 Finland brief _Icountry_26 0.315 0.053 5.89 0.000 0.210 0.420 Finland postal _Icountry_27 0.395 0.056 7.09 0.000 0.286 0.504 France brief _Icountry_28 0.330 0.067 4.93 0.000 0.199 0.461 France postal _Icountry_29 -0.039 0.059 -0.66 0.511 -0.155 0.077 United Kingdom postal _Icountry_30 0.019 0.044 0.44 0.661 -0.068 0.106 Georgia household _Icountry_31 0.151 0.060 2.52 0.012 0.034 0.268 Greece postal _Icountry_32 0.078 0.053 1.46 0.144 -0.027 0.183 Croatia brief _Icountry_33 -0.241 0.056 -4.31 0.000 -0.350 -0.131 Hungary postal _Icountry_34 -0.575 0.046 -12.59 0.000 -0.664 -0.485 Indonesia household _Icountry_35 0.045 0.050 0.92 0.358 -0.052 0.143 Indonesia postal _Icountry_36 -0.656 0.049 -13.4 0.000 -0.752 -0.560 India household _Icountry_37 -0.015 0.064 -0.23 0.818 -0.139 0.110 Ireland brief _Icountry_38 0.402 0.067 6.01 0.000 0.271 0.533 Iceland brief _Icountry_39 0.044 0.058 0.76 0.445 -0.069 0.158 Italy brief _Icountry_40 -0.005 0.061 -0.08 0.939 -0.124 0.115 Jordan brief _Icountry_41 0.594 0.054 11.07 0.000 0.489 0.699 Kyrgyzstan postal _Icountry_42 0.112 0.078 1.43 0.153 -0.042 0.265 Republic of Korea postal _Icountry_43 -0.056 0.052 -1.07 0.284 -0.158 0.046 Lithuania postal _Icountry_44 0.399 0.061 6.6 0.000 0.281 0.518 Luxembourg telephone _Icountry_45 0.058 0.062 0.93 0.353 -0.064 0.180 Latvia brief _Icountry_46 0.287 0.059 4.84 0.000 0.171 0.403 Morocco brief _Icountry_47 -0.116 0.047 -2.44 0.015 -0.208 -0.023 Mexico household _Icountry_48 0.036 0.070 0.51 0.610 -0.101 0.173 Malta brief _Icountry_49 0.117 0.046 2.52 0.012 0.026 0.208 Nigeria household _Icountry_50 0.426 0.054 7.82 0.000 0.319 0.532 Netherlands brief _Icountry_51 0.380 0.066 5.79 0.000 0.251 0.508 Netherlands postal _Icountry_52 -0.215 0.055 -3.91 0.000 -0.323 -0.107 New Zealand postal _Icountry_53 -0.175 0.063 -2.76 0.006 -0.299 -0.051 Oman brief _Icountry_54 0.201 0.058 3.46 0.001 0.087 0.315 Poland postal _Icountry_55 0.019 0.058 0.32 0.746 -0.095 0.133 Portugal brief _Icountry_56 0.252 0.056 4.48 0.000 0.142 0.363 Romania brief _Icountry_57 0.072 0.053 1.35 0.177 -0.032 0.176 Russian Federation brief _Icountry_58 -0.549 0.064 -8.63 0.000 -0.673 -0.424 Slovakia household _Icountry_59 0.158 0.057 2.77 0.006 0.046 0.270 Sweden brief _Icountry_60 -0.019 0.056 -0.33 0.740 -0.129 0.092 Thailand postal _Icountry_61 0.290 0.054 5.33 0.000 0.184 0.397 Trinidad and Tobago postal _Icountry_62 0.113 0.046 2.45 0.014 0.023 0.204 Turkey household _Icountry_63 0.262 0.049 5.35 0.000 0.166 0.357 Turkey postal _Icountry_64 0.142 0.061 2.34 0.019 0.023 0.261 Ukraine postal _Icountry_65 0.045 0.056 0.8 0.423 -0.065 0.155 United States postal _Icountry_66 0.186 0.060 3.09 0.002 0.068 0.304 Venezuela brief _cons -3.787 0.046 -82.65 0.000 -3.877 -3.697

Cut-Point 2 Coef. Std. Err. z P>z [95% Conf. Interval] _Iagedummy_2 0.012 0.008 1.5 0.133 -0.004 0.027 Age 30-44 _Iagedummy_3 0.039 0.009 4.4 0.000 0.021 0.056 Age 45-59 _Iagedummy_4 0.031 0.010 3.21 0.001 0.012 0.051 Age 60+ sex -0.021 0.006 -3.5 0.000 -0.033 -0.009 Male educ 0.001 0.001 1.52 0.130 0.000 0.003 Education (yrs) _Icountry_2 0.216 0.050 4.32 0.000 0.118 0.314 Argentina brief _Icountry_3 0.033 0.047 0.71 0.478 -0.059 0.126 Australia postal

70 _Icountry_4 0.180 0.047 3.82 0.000 0.088 0.272 Austria postal _Icountry_5 0.410 0.046 8.86 0.000 0.319 0.501 Belgium brief _Icountry_6 0.431 0.047 9.11 0.000 0.338 0.524 Bulgaria brief _Icountry_7 -0.074 0.050 -1.46 0.144 -0.173 0.025 Bahrain brief _Icountry_8 0.225 0.060 3.76 0.000 0.108 0.343 Canada postal _Icountry_9 0.089 0.062 1.42 0.154 -0.033 0.211 Canada telephone _Icountry_10 0.086 0.058 1.48 0.139 -0.028 0.200 Switzerland postal _Icountry_11 0.384 0.047 8.12 0.000 0.291 0.477 Chile postal _Icountry_12 -0.348 0.036 -9.57 0.000 -0.419 -0.277 China household _Icountry_13 -0.042 0.045 -0.94 0.345 -0.130 0.046 China postal _Icountry_14 0.098 0.037 2.64 0.008 0.025 0.171 Columbia household _Icountry_15 0.198 0.050 3.99 0.000 0.101 0.295 Costa Rica brief _Icountry_16 0.268 0.053 5.05 0.000 0.164 0.372 Cyprus postal _Icountry_17 0.158 0.047 3.4 0.001 0.067 0.250 Czech Republic brief _Icountry_18 0.313 0.046 6.74 0.000 0.222 0.404 Czech Republic postal _Icountry_19 0.152 0.046 3.29 0.001 0.062 0.242 Germany brief _Icountry_20 0.433 0.044 9.78 0.000 0.346 0.519 Denmark postal _Icountry_21 0.112 0.038 2.96 0.003 0.038 0.186 Egypt household _Icountry_22 0.248 0.043 5.71 0.000 0.163 0.333 Egypt postal _Icountry_23 -0.017 0.048 -0.35 0.727 -0.110 0.077 Spain brief _Icountry_24 0.333 0.047 7.03 0.000 0.240 0.426 Estonia brief _Icountry_25 0.293 0.047 6.23 0.000 0.201 0.385 Finland brief _Icountry_26 0.307 0.044 6.93 0.000 0.220 0.394 Finland postal _Icountry_27 0.369 0.047 7.9 0.000 0.277 0.460 France brief _Icountry_28 0.326 0.056 5.78 0.000 0.215 0.436 France postal _Icountry_29 0.141 0.047 2.98 0.003 0.048 0.233 United Kingdom postal _Icountry_30 0.214 0.036 5.93 0.000 0.143 0.284 Georgia household _Icountry_31 0.344 0.049 7.06 0.000 0.249 0.440 Greece postal _Icountry_32 0.214 0.043 4.97 0.000 0.130 0.299 Croatia brief _Icountry_33 -0.132 0.044 -2.99 0.003 -0.218 -0.045 Hungary postal _Icountry_34 0.077 0.036 2.14 0.032 0.007 0.148 Indonesia household _Icountry_35 -0.090 0.040 -2.23 0.025 -0.169 -0.011 Indonesia postal _Icountry_36 0.119 0.038 3.15 0.002 0.045 0.193 India household _Icountry_37 0.101 0.051 1.98 0.048 0.001 0.201 Ireland brief _Icountry_38 0.476 0.057 8.43 0.000 0.366 0.587 Iceland brief _Icountry_39 0.114 0.047 2.43 0.015 0.022 0.207 Italy brief _Icountry_40 0.062 0.050 1.25 0.210 -0.035 0.160 Jordan brief _Icountry_41 0.260 0.046 5.68 0.000 0.170 0.350 Kyrgyzstan postal _Icountry_42 0.044 0.064 0.68 0.495 -0.081 0.168 Republic of Korea postal _Icountry_43 0.056 0.042 1.33 0.184 -0.027 0.139 Lithuania postal _Icountry_44 0.392 0.051 7.74 0.000 0.293 0.491 Luxembourg telephone _Icountry_45 0.156 0.050 3.14 0.002 0.059 0.254 Latvia brief _Icountry_46 0.210 0.050 4.19 0.000 0.112 0.308 Morocco brief _Icountry_47 0.142 0.038 3.75 0.000 0.068 0.216 Mexico household _Icountry_48 0.117 0.057 2.05 0.041 0.005 0.229 Malta brief _Icountry_49 0.427 0.038 11.31 0.000 0.353 0.501 Nigeria household _Icountry_50 0.529 0.046 11.62 0.000 0.440 0.618 Netherlands brief _Icountry_51 0.519 0.056 9.34 0.000 0.410 0.628 Netherlands postal _Icountry_52 -0.078 0.044 -1.78 0.075 -0.163 0.008 New Zealand postal _Icountry_53 -0.011 0.050 -0.22 0.827 -0.109 0.087 Oman brief _Icountry_54 0.309 0.048 6.44 0.000 0.215 0.403 Poland postal _Icountry_55 0.242 0.046 5.23 0.000 0.151 0.333 Portugal brief _Icountry_56 0.216 0.046 4.66 0.000 0.125 0.306 Romania brief _Icountry_57 0.136 0.043 3.15 0.002 0.051 0.221 Russian Federation brief _Icountry_58 -0.279 0.047 -5.92 0.000 -0.371 -0.187 Slovakia household

71 _Icountry_59 0.318 0.047 6.8 0.000 0.226 0.410 Sweden brief _Icountry_60 0.119 0.044 2.7 0.007 0.033 0.205 Thailand postal _Icountry_61 0.375 0.045 8.33 0.000 0.287 0.464 Trinidad and Tobago postal _Icountry_62 0.307 0.038 8.17 0.000 0.234 0.381 Turkey household _Icountry_63 0.333 0.040 8.36 0.000 0.255 0.411 Turkey postal _Icountry_64 0.120 0.050 2.4 0.017 0.022 0.218 Ukraine postal _Icountry_65 0.146 0.045 3.22 0.001 0.057 0.235 United States postal _Icountry_66 0.062 0.050 1.25 0.212 -0.036 0.160 Venezuela brief _cons -2.889 0.037 -77.15 0.000 -2.962 -2.815

Cut-Point 3 Coef. Std. Err. z P>z [95% Conf. Interval] _Iagedummy_2 0.030 0.008 3.88 0.000 0.015 0.046 Age 30-44 _Iagedummy_3 0.072 0.009 8.21 0.000 0.055 0.090 Age 45-59 _Iagedummy_4 0.115 0.010 11.68 0.000 0.096 0.135 Age 60+ sex -0.022 0.006 -3.56 0.000 -0.033 -0.010 Male educ 0.002 0.001 2.54 0.011 0.000 0.003 Education (yrs) _Icountry_2 0.391 0.050 7.87 0.000 0.294 0.489 Argentina brief _Icountry_3 0.259 0.046 5.59 0.000 0.168 0.350 Australia postal _Icountry_4 0.217 0.046 4.68 0.000 0.126 0.308 Austria postal _Icountry_5 0.319 0.046 6.94 0.000 0.229 0.410 Belgium brief _Icountry_6 0.496 0.048 10.36 0.000 0.402 0.589 Bulgaria brief _Icountry_7 -0.196 0.048 -4.08 0.000 -0.290 -0.102 Bahrain brief _Icountry_8 0.273 0.061 4.5 0.000 0.154 0.392 Canada postal _Icountry_9 0.251 0.061 4.09 0.000 0.131 0.371 Canada telephone _Icountry_10 0.055 0.058 0.95 0.340 -0.058 0.168 Switzerland postal _Icountry_11 0.480 0.048 9.99 0.000 0.386 0.574 Chile postal _Icountry_12 -0.276 0.035 -7.96 0.000 -0.344 -0.208 China household _Icountry_13 0.128 0.044 2.93 0.003 0.042 0.213 China postal _Icountry_14 0.253 0.036 7.07 0.000 0.183 0.323 Columbia household _Icountry_15 0.373 0.049 7.6 0.000 0.277 0.470 Costa Rica brief _Icountry_16 0.206 0.053 3.89 0.000 0.102 0.310 Cyprus postal _Icountry_17 0.267 0.046 5.83 0.000 0.177 0.357 Czech Republic brief _Icountry_18 0.454 0.047 9.69 0.000 0.362 0.546 Czech Republic postal _Icountry_19 0.337 0.046 7.36 0.000 0.247 0.426 Germany brief _Icountry_20 0.337 0.044 7.63 0.000 0.250 0.423 Denmark postal _Icountry_21 0.294 0.037 8.05 0.000 0.223 0.366 Egypt household _Icountry_22 0.376 0.043 8.78 0.000 0.292 0.460 Egypt postal _Icountry_23 0.141 0.046 3.06 0.002 0.051 0.231 Spain brief _Icountry_24 0.364 0.047 7.68 0.000 0.271 0.457 Estonia brief _Icountry_25 0.344 0.047 7.4 0.000 0.253 0.435 Finland brief _Icountry_26 0.329 0.044 7.4 0.000 0.242 0.416 Finland postal _Icountry_27 0.293 0.046 6.3 0.000 0.202 0.384 France brief _Icountry_28 0.206 0.057 3.64 0.000 0.095 0.317 France postal _Icountry_29 0.305 0.047 6.53 0.000 0.213 0.396 United Kingdom postal _Icountry_30 0.345 0.035 9.92 0.000 0.277 0.413 Georgia household _Icountry_31 0.453 0.049 9.19 0.000 0.356 0.549 Greece postal _Icountry_32 0.337 0.043 7.94 0.000 0.254 0.421 Croatia brief _Icountry_33 0.013 0.042 0.32 0.752 -0.069 0.095 Hungary postal _Icountry_34 0.168 0.035 4.83 0.000 0.100 0.236 Indonesia household _Icountry_35 -0.520 0.039 -13.47 0.000 -0.596 -0.445 Indonesia postal _Icountry_36 0.064 0.036 1.76 0.078 -0.007 0.136 India household _Icountry_37 0.286 0.051 5.62 0.000 0.186 0.385 Ireland brief _Icountry_38 0.445 0.058 7.74 0.000 0.333 0.558 Iceland brief _Icountry_39 0.104 0.046 2.28 0.023 0.015 0.194 Italy brief _Icountry_40 -0.025 0.048 -0.53 0.598 -0.120 0.069 Jordan brief

72 _Icountry_41 0.083 0.045 1.84 0.066 -0.005 0.172 Kyrgyzstan postal _Icountry_42 -0.083 0.062 -1.34 0.181 -0.205 0.039 Republic of Korea postal _Icountry_43 0.051 0.041 1.24 0.213 -0.029 0.131 Lithuania postal _Icountry_44 0.440 0.051 8.63 0.000 0.340 0.540 Luxembourg telephone _Icountry_45 0.267 0.049 5.43 0.000 0.171 0.363 Latvia brief _Icountry_46 0.207 0.049 4.22 0.000 0.111 0.303 Morocco brief _Icountry_47 0.213 0.037 5.82 0.000 0.141 0.285 Mexico household _Icountry_48 0.041 0.056 0.73 0.464 -0.068 0.149 Malta brief _Icountry_49 0.132 0.037 3.63 0.000 0.061 0.204 Nigeria household _Icountry_50 0.573 0.046 12.47 0.000 0.483 0.663 Netherlands brief _Icountry_51 0.604 0.058 10.47 0.000 0.491 0.717 Netherlands postal _Icountry_52 0.107 0.042 2.55 0.011 0.025 0.189 New Zealand postal _Icountry_53 -0.166 0.048 -3.49 0.000 -0.259 -0.073 Oman brief _Icountry_54 0.354 0.048 7.35 0.000 0.260 0.449 Poland postal _Icountry_55 0.121 0.045 2.67 0.008 0.032 0.210 Portugal brief _Icountry_56 0.225 0.045 4.96 0.000 0.136 0.314 Romania brief _Icountry_57 0.254 0.042 6.05 0.000 0.172 0.337 Russian Federation brief _Icountry_58 -0.091 0.044 -2.05 0.040 -0.178 -0.004 Slovakia household _Icountry_59 0.357 0.046 7.71 0.000 0.267 0.448 Sweden brief _Icountry_60 0.210 0.043 4.89 0.000 0.126 0.294 Thailand postal _Icountry_61 0.423 0.045 9.39 0.000 0.335 0.511 Trinidad and Tobago postal _Icountry_62 0.400 0.037 10.92 0.000 0.328 0.471 Turkey household _Icountry_63 0.363 0.039 9.24 0.000 0.286 0.440 Turkey postal _Icountry_64 0.235 0.049 4.75 0.000 0.138 0.332 Ukraine postal _Icountry_65 0.230 0.045 5.15 0.000 0.142 0.317 United States postal _Icountry_66 0.204 0.049 4.15 0.000 0.107 0.300 Venezuela brief _cons -2.053 0.036 -56.98 0.000 -2.123 -1.982

Cut-Point 4 Coef. Std. Err. z P>z [95% Conf. Interval] _Iagedummy_2 0.023 0.010 2.41 0.016 0.004 0.042 Age 30-44 _Iagedummy_3 0.075 0.011 6.96 0.000 0.054 0.096 Age 45-59 _Iagedummy_4 0.101 0.012 8.44 0.000 0.078 0.125 Age 60+ sex -0.030 0.007 -4.06 0.000 -0.044 -0.015 Male educ 0.003 0.001 3.57 0.000 0.001 0.005 Education (yrs) _Icountry_2 0.257 0.061 4.24 0.000 0.138 0.376 Argentina brief _Icountry_3 0.374 0.056 6.65 0.000 0.264 0.484 Australia postal _Icountry_4 0.195 0.055 3.55 0.000 0.087 0.303 Austria postal _Icountry_5 0.154 0.055 2.81 0.005 0.047 0.262 Belgium brief _Icountry_6 0.328 0.057 5.72 0.000 0.216 0.441 Bulgaria brief _Icountry_7 -0.099 0.057 -1.75 0.080 -0.210 0.012 Bahrain brief _Icountry_8 0.318 0.074 4.29 0.000 0.173 0.464 Canada postal _Icountry_9 0.209 0.075 2.79 0.005 0.062 0.355 Canada telephone _Icountry_10 0.053 0.068 0.77 0.442 -0.081 0.187 Switzerland postal _Icountry_11 0.206 0.056 3.68 0.000 0.096 0.316 Chile postal _Icountry_12 -0.091 0.041 -2.2 0.028 -0.172 -0.010 China household _Icountry_13 0.353 0.053 6.6 0.000 0.248 0.458 China postal _Icountry_14 0.000 0.043 0 0.997 -0.084 0.083 Columbia household _Icountry_15 0.125 0.059 2.13 0.033 0.010 0.241 Costa Rica brief _Icountry_16 0.238 0.064 3.74 0.000 0.114 0.363 Cyprus postal _Icountry_17 0.302 0.056 5.4 0.000 0.193 0.412 Czech Republic brief _Icountry_18 0.529 0.057 9.21 0.000 0.416 0.641 Czech Republic postal _Icountry_19 0.331 0.056 5.91 0.000 0.221 0.441 Germany brief _Icountry_20 0.312 0.053 5.92 0.000 0.209 0.415 Denmark postal _Icountry_21 0.177 0.044 4.04 0.000 0.091 0.263 Egypt household _Icountry_22 0.253 0.051 4.94 0.000 0.152 0.353 Egypt postal

73 _Icountry_23 0.137 0.056 2.43 0.015 0.027 0.247 Spain brief _Icountry_24 0.408 0.058 7.06 0.000 0.295 0.521 Estonia brief _Icountry_25 0.334 0.057 5.87 0.000 0.222 0.445 Finland brief _Icountry_26 0.424 0.054 7.82 0.000 0.317 0.530 Finland postal _Icountry_27 0.136 0.056 2.45 0.014 0.027 0.245 France brief _Icountry_28 0.323 0.069 4.7 0.000 0.188 0.457 France postal _Icountry_29 0.407 0.057 7.09 0.000 0.294 0.519 United Kingdom postal _Icountry_30 0.148 0.042 3.55 0.000 0.066 0.229 Georgia household _Icountry_31 0.452 0.060 7.56 0.000 0.335 0.570 Greece postal _Icountry_32 0.104 0.051 2.05 0.040 0.005 0.203 Croatia brief _Icountry_33 -0.060 0.050 -1.2 0.229 -0.157 0.038 Hungary postal _Icountry_34 0.091 0.042 2.18 0.029 0.009 0.172 Indonesia household _Icountry_35 -0.278 0.045 -6.11 0.000 -0.367 -0.189 Indonesia postal _Icountry_36 0.072 0.044 1.66 0.097 -0.013 0.158 India household _Icountry_37 0.227 0.063 3.59 0.000 0.103 0.351 Ireland brief _Icountry_38 0.425 0.070 6.1 0.000 0.288 0.561 Iceland brief _Icountry_39 0.143 0.056 2.57 0.010 0.034 0.253 Italy brief _Icountry_40 -0.147 0.056 -2.64 0.008 -0.256 -0.038 Jordan brief _Icountry_41 0.075 0.054 1.38 0.168 -0.032 0.182 Kyrgyzstan postal _Icountry_42 0.181 0.076 2.39 0.017 0.033 0.329 Republic of Korea postal _Icountry_43 0.133 0.049 2.72 0.007 0.037 0.228 Lithuania postal _Icountry_44 0.227 0.061 3.7 0.000 0.107 0.347 Luxembourg telephone _Icountry_45 0.238 0.060 3.96 0.000 0.120 0.356 Latvia brief _Icountry_46 -0.105 0.057 -1.83 0.067 -0.216 0.007 Morocco brief _Icountry_47 0.116 0.044 2.64 0.008 0.030 0.203 Mexico household _Icountry_48 0.052 0.066 0.79 0.431 -0.078 0.182 Malta brief _Icountry_49 0.289 0.045 6.46 0.000 0.202 0.377 Nigeria household _Icountry_50 0.199 0.054 3.66 0.000 0.092 0.305 Netherlands brief _Icountry_51 0.559 0.069 8.1 0.000 0.424 0.694 Netherlands postal _Icountry_52 0.193 0.050 3.84 0.000 0.095 0.292 New Zealand postal _Icountry_53 -0.132 0.056 -2.37 0.018 -0.240 -0.023 Oman brief _Icountry_54 0.413 0.059 7.04 0.000 0.298 0.527 Poland postal _Icountry_55 0.063 0.055 1.15 0.251 -0.045 0.171 Portugal brief _Icountry_56 0.151 0.055 2.75 0.006 0.043 0.258 Romania brief _Icountry_57 0.089 0.051 1.76 0.079 -0.010 0.188 Russian Federation brief _Icountry_58 0.085 0.054 1.56 0.118 -0.021 0.191 Slovakia household _Icountry_59 0.261 0.055 4.71 0.000 0.152 0.370 Sweden brief _Icountry_60 0.263 0.053 4.97 0.000 0.159 0.367 Thailand postal _Icountry_61 0.414 0.054 7.62 0.000 0.308 0.521 Trinidad and Tobago postal _Icountry_62 0.282 0.044 6.43 0.000 0.196 0.368 Turkey household _Icountry_63 0.272 0.048 5.71 0.000 0.178 0.365 Turkey postal _Icountry_64 0.264 0.059 4.45 0.000 0.148 0.381 Ukraine postal _Icountry_65 0.310 0.054 5.75 0.000 0.204 0.416 United States postal _Icountry_66 0.059 0.058 1.01 0.310 -0.055 0.174 Venezuela brief _cons -1.008 0.043 -23.68 0.000 -1.092 -0.925 s _cons 0.242 0.005 49.67 0.000 0.232 0.251

74