DESCRIBING POPULATION HEALTH IN SIXDOMAINS: 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 OrganizationMarch 2002

Abstract

One of the World Health Organization's longest standing mandates is the collection androutine reporting of information on population health. In addition to estimates of mortalityand disease, assessment of health status from population based surveys contribute to estimatesof population health. The first section of the paper briefly introduces the conceptual andoperational 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 thatthe main objective of this paper is to report on the average levels of health by age and sexgroups for each domain of health across 66 population based surveys. The third section ofthis paper describes how we have applied the hierarchical ordered probit (HOPIT) modelusing vignettes to calibrate responses across survey populations, to self-reported levels ofhealth 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 andolder. The fourth section provides results on comparable levels of health for each domainacross populations, by age groups and sex. In order to further facilitate comparisons acrosscountries, age-standardized aggregated results across all age groups, by sex, are alsopresented 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 themulti-dimensional approach and the comparability of responses across countries. The finalsection recommends additional analyses to be conducted.

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

Dr. Ritu SadanaEvidence and Information for PolicyWorld Health OrganizationAvenue Appia 20CH-1211 Geneva 27Switzerland

Email: sadanar@who.int

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I . Introduction1.1 BACKGROUND

The World Health Report 2000 (WHO 2000) proposed a framework defining the threeintrinsic goals to which health systems should contribute. The first intrinsic goal isconsidered as the defining goal of a health system, that is, to improve health, both the averagelevel of population health and its distribution within a population. It is not surprising that oneof the World Health Organization’s longest standing mandates has been the collection androutine reporting of information on population health. Along with Member States, researchinstitutions, and technical experts, WHO has expended considerable efforts over the pastdecades to enhance the information content and comparability of population health coveringmortality and its risk factors. Over the past decade, the locus of these efforts has extended tothe improvement and standardization of methods to assess non-fatal health (coveringepidemiological estimates of morbidity and disability, and assessment of health status frompopulation based surveys), reflecting the conclusion that mortality alone does not provide acomplete picture of population health. Following the Global Burden of Disease Study(Murray and Lopez 1996), more recent work includes the further development of summarymeasures of population health (Murray et al. forthcoming), a critical review of the validityand comparability of existing population based survey data on health status (Sadana et al2000), the finalization of The International Classification of Functioning, Disability andHealth (ICF), (WHO 2001) and the implementation of the WHO Multi-Country SurveyStudy 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-reportedhealth status in six domains assessed through 66 population-based surveys conducted in 57countries included within the WHO Multi-Country Survey Study. The results presented inthis paper provide more comparable information on the self-reported average level ofpopulation health across countries than was previously possible from survey data, and havebeen 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 arepotentially three sets of domains that can be specified in order to describe health andcontribute to its operational measurement: (1) core domains of health that almost all peopleagree 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 theexperience of health – health related domains. Based on an extensive review of existing healthstate measurement instruments and health measurement literature, some 24 candidate domainsto describe health were proposed and discussed within technical consultations on measuringhealth status over the past two years (Figure 3). Of these, 18 describe different aspects ofhealth status directly, such as affect, pain, dexterity or fertility (e.g., domains in the grayshaded 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 wereselected as domains that almost all people agree upon for inclusion across all survey modeswith 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 ofhealth on each of these six domains, across all 66 surveys thus far analyzed.

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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 notdescribe health per se, but limitations or performance in these areas may be associated withlower levels of health in the domains directly describing health (e.g., proximate domains arelikely to be more highly correlated with domains that directly assess health, than domains thatdirectly assess health are with one another). Furthermore, although we would prefer to assesshealth directly, the self-report of limitations in usual activities or self-care may be reported ina more reliable or consistent manner, than the self-report of health in some of the otherdomains. For this reason, proximate domains are often included in standardized, interviewbased health status assessment instruments (McDowell and Newell 1996). Nevertheless,other domains directly assessing health listed in Figure 1 are assessed within the in-depthhousehold surveys included in the WHO Multi-Country Survey. The analysis and criticalreview 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 provideperson or household based health statistics rather than data collected through health servicesor disease registries, which are episode or event based (United Nations 1995). Self-reportedresponses in household or other types of interview based survey data are therefore widelyused for assessing the health status of populations. These data typically take the form ofordered categorical (ordinal) responses, such as excellent/ very good/ good/ poor/ bad ornone/ mild/ moderate/ severe/ extreme. One key analytical issue is that these self-reportedordinal responses are not necessarily comparable across or even within populations primarilybecause of response category cut-point shifts. This phenomenon differs from other numerousfactors -- such as differences in language or measurement error -- that may also contribute tothe difference between what is observed and what is reported within an interview, discussedelsewhere (Sadana et al. 2000; Murray et al. 2001).

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

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

Figure 2. Hypothetical shifts in response category cut-points

Latent mobility scale

A B C

E

S

Mo

Mi

N

E

ES

S

Mo

Mo

Mi

MiN

N

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

Cut-points

The main self-report question on the domain of mobility from this survey is: "Overall in thepast 30 days, how much difficulty did you have with moving around?" Respondents are askedto 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 canhypothesize that cut-points may vary between populations because of different cultural orother expectations on each domain of health. Figure 1 illustrates the case when individuals inpopulation C may respond with "extreme" difficulty while individuals in population A withthe same true level of mobility may respond with "mild" up to "extreme" difficulty. Giventhese shifts in cut-points, the differences in the proportion of each population within eachresponse category are not comparable. Cut-points are also likely to vary across cultural orsocio-demographic groups, levels of health insurance or other benefits and entitlements, orover time. For example, the cut-points for older individuals may shift as their expectationsfor level of health on a particular domain diminish with age, i.e., they may under-reportdifficulties. Men may be more likely to deny declines in health so that their cut-points may besystematically shifted as compared to women, i.e., they may under-report difficulties. Contactwith 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 testedwith the appropriate methods. However, until recently, most users of data from healthinterview surveys have interpreted self-reported reported responses at face value.

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

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surveys in conjunction with other, non-health data from the same countries. A scatter plot ofthe per capita GDP and the average level of health for the over 65 population (males andfemales combined), for each of the 46 countries included within this earlier analysis, showshigher levels of per capita GDP are correlated with lower average levels of health. Thissuggests the existence of cross-population cut-point shifts (Figure 3). Although this evidencebased 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 thesame 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

Bearing in mind these limitations, the data collection and analysis methods of the WHOMulti-Country Survey are an attempt to enhance the comparability of routine assessments ofpopulation health obtained through interview based surveys. Based on the critical evaluationof 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 sexgroups 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 analysismethods developed to enhance the cross-population comparability of self-reported health. Asecondary objective is to provide descriptive data on health for input to other analyses andestimates, such as the estimation of inequalities in the distribution of health or the calculationof summary measures of population health.

III. Methods

0

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100 1000 10000 100000

Per Capita GDP

Leve

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ealth

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III.1 DATA: SURVEYS, QUALITY, REPRESENTATIVENESS, SAMPLE SIZEAND 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 thisanalyses represents the first effort by WHO to collect data on self-reported health status frompopulation representative surveys, in conjunction with Member States, research institutionsand survey organizations. The WHO Multi-Country Survey includes 71 surveys in 61countries. The survey has a range of modules including: health status description, healthstate valuations, responsiveness, mental health, chronic health conditions, adult mortality,environmental factors and health financing. Information on the development of content of theoverall survey instrument, translation protocols, the various survey modes, selection of sites,sample frames, data collection and management, and quality of the data (e.g., samplepopulation deviation index for age-sex groups, response rates, item missing values, test-retestreliability coefficients, among other attributes), are detailed elsewhere (Üstün et al. 2001).Selected aspects relevant to the data collection, analysis and interpretation of the health statusdescription module are amplified below.

Addressing the challenge of cross population cut-point shifts, two external means to calibrateresponses were included within the data collection component of the surveys, vignettes foreach of the domains assessed (all 66 surveys) and measured performance tests in domainscovering mobility, cognition and vision (limited to the 10 in-depth household surveys). Theresults 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 thedomains assessed (domains have between 6-8 vignettes). The concept of vignettes is basedon the following reasoning: (i) vignettes fix the level of ability so that variations incategorical responses are attributable to variations in response category cut-points; (ii) theintroduction of exogenous information in the form of ratings of vignettes allows us to identifythe effects of different covariates (e.g., age, sex, education, country) on both the level of theunderlying latent variable (e.g., mobility, affect, etc.), as well as on the cut-points. SeeSalomon et al (2001) for further details and assumptions on the use of vignettes as a meansfor enhancing cross-population comparability. A critical evaluation of vignettes as a strategyto calibrate responses across surveys will be presented separately (Sadana et al. 2001), as willthe use of measured performance tests (Tandon et al. 2001).

3.1.2 Surveys, Quality. Data available on health status description at the time of thisanalysis covers 66 population representative surveys in 57 countries using four differentmodes1. These include 10 in-depth household surveys (interviews lasting around 90 minuteseach), 27 brief household surveys (interviews lasting around 35 minutes each), 27 postalsurveys (self-administered with questionnaires similar to the brief household surveys), and 2computer assisted telephone interviews (questionnaires similar to the brief householdsurveys). Individuals interviewed reported on their own health status, i.e., individuals did notprovide proxy reports for others in the household as is the case for many other householdsurveys including health modules. On average, response rates were highest for the in-depthhousehold 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 acrossall items also varied across modes, and was lowest for the brief household surveys (1.5 percent), followed by telephone (2.1 per cent), postal (6.8 per cent) and in-depth household (12.1per 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 domainis 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/

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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-retestreliability. Weighted Cohen's kappa statistics (corrected for chance agreement) were appliedto categorical data. The average values for questions within the six domains assessed ofhealth (affect, cognition, mobility, pain, self-care and usual activities) varied from 0.60 to0.71, largely indicating substantial agreement. Variations in the reliability of survey itemsappear greater across countries than across questions within the health module.

3.1.3 Sample size, Representativeness, Respondent characteristics. Table 1 lists thecountry and survey mode, the mean age, the mean number of years of education, the samplesize, age groups excluded (if any) and the per cent that each survey contributes to the overallanalysis sample. For inclusion in this analysis, individuals interviewed must have respondedto at least one of the core domain questions on health status. The overall analysis sample sizeis 117,192 respondents from 66 survey in 57 countries. Across all surveys, the average age is42.0 (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 ofsurveys 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 geographiccoverage are documented for selected surveys: Canada (both surveys exclude Yukon,Northwest Territories or Nunavut), China (in-depth household survey: includes differentsocio-economic groups from Shandong, Henan, Gansu Provinces; postal: includes ShandongProvince), Columbia (excludes a few areas making up less than 2% of the population such asOrinoquia, the Amazonian Triangle among others), Georgia (excludes Abkhazia andTskhinvali regions), India (includes Andhra Pradesh State), Indonesia (household: excludesPapua, 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 statusdescription module, age groups2 with insufficient observations (<10) by survey and sex arenoted in Table 1, Column IV. These exclusions are primarily restricted to individuals 80 yearsand over, with the main exceptions being Bahrain, China postal, Jordan, Oman, Republic ofKorea, United Arab Emirates and Venezuela where some exclude individuals 60 years andover. In the overall analysis sample, the ratio of males to females is 0.88 (53.3 per centfemales and 46.7 per cent males). This ratio varies considerably across surveys. Twenty-twosurveys have a ratio greater than or equal to 1.0, with four greater than or equal to 1.5including Czech Republic brief (1.52), Greece (1.59), Turkey household (1.72) and Republicof Korea (3.09), where as eight surveys have a ratio less than or equal to 0.7, with four lessthan or equal to 0.6 including Kyrgyzstan (0.60), Columbia (0.53), Ukraine (0.53) andThailand (0.43). Further details on sampling strategy, the achieved sample characteristics incomparison to the expected characteristics based on census estimates, and sample weights foreach survey are found elsewhere (Üstün et al. 2001).

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

Table 1. Sixty-six surveys from 57 countries: sample size and respondent characteristicsIMean

IIMean

III IVAge Groups

V VI

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

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Country and Survey ModeAge (yrs) Education

(yrs)N Excluded N % of N

Females Males Females Males

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

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Country and Survey Mode

IMeanAge (yrs)

IIMeanEducation(yrs)

III

n

IVAge GroupsExcluded

V

N

VI

% of N

Females Males Females Males

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

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III.3 QUESTIONS, RESPONSE SCALES, RECALL PERIODS

Based on the six domains assessed selected to describe health, questions assessing eachdomain were selected from existing standardized surveys that have already been pilot testedin multi-country studies (Üstün et al. in press). Table 2 lists the main question for eachdomain and the number and topics of the auxiliary questions for each domain assessed. For allquestions, the recall period is the last 30 days, the most common time frame in standardizedhealth status assessment instruments. Questions either asked the respondent to assess thedegree to which a particular state was experienced, or the amount of difficulty associated witha 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 andResponsiveness 2000-2001Domain Main Question Number and Content of Auxiliary

Questions

Affect Overall in the last 30 days, how much distress,sadness or worry did you experience?

(4) time spent feeling happy and cheerful/ sad,empty, depressed/ irritable or in a bad mood/worried a lot

Cognition Overall in the last 30 days, how much difficultydid you have with concentrating or rememberingthings?

(4) difficulty in concentrating on doing somethingfor 10 minutes/remembering to do importantthings/ analyzing and solving problems in day today life/ learning a new task

Mobility Overall in the last 30 days, how much difficultydid you have with moving around?

(4) difficulty to stand up from sitting down/movingaround inside one's home/ climbing several flightsof stairs or walking up a steep hill/ performance ofvigorous activities such as running, lifting heavyobjects, participating in strenuous sports

Pain Overall in the last 30 days, how much pain ordiscomfort did you have?

(1) amount of bodily pain or discomfort

Self-Care Overall in the last 30 days, how much difficultydid you have with self-care, such as washing ordressing yourself?

(3) difficulty in washing your whole body/gettingdressed/staying by yourself for a few days

UsualActivities

Overall in the last 30 days, how much difficultydid you have with work or household activities?

(3) difficulty in taking care of householdresponsibilities/getting all the housework done thatyou needed to do/being limited in the type ofhousehold work

III.4 TREATMENT OF ITEM LEVEL MISSING DATA

As noted, for inclusion in the analysis on health status description, individuals interviewedmust have responded to at least one of the domain questions on health status (Table 2). If arespondent had answered none of the domain questions, then this respondent was droppedfrom the analysis: using this criteria less than 50 cases were dropped across all 66 surveys. Ifa respondent had answered all six domain questions, then this respondent was considered as acase. For all intermediary situations, i.e., individuals who had responded between one to fiveof the domain questions, all were also considered as cases. Key socio-demographicinformation required for all cases included age, sex and years of education, along with thesurvey (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 weresubsequently estimated using the multiple imputation method employed by the softwareprogram AMELIA and its EMis algorithm (Honaker et al. 1999). The per cent of missing datafor the background variables imputed on average for all cases was very low across all but oneof the surveys: sex (<0.1%), age (<0.5%), and years of education (<0.1% excludingIndonesia household, where years of education was missing for 16% of cases). Likewise, theper cent of missing data for the main question assessing each domain of health imputed for allcases was very low across surveys, <0.5% for each of the six main questions. Missing data at

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

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

The analysis approach addresses the key challenge concerning the comparability of selfreported health status data collected through interview based surveys: cross-population cut-point shifts. In conjunction with the data collection strategies that incorporate an externalmeans to calibrate responses, the analytical methods applied here should be viewed as asignificant improvement over previous methods used to enhance cross-populationcomparability 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 hierarchicalordered probit (HOPIT) model, a variant of the standard ordered probit model and to somedegree, of the partial credit model from item response theory. The key innovations in theHOPIT 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) intervalregression is applied to self-report questions in order to estimate cross-population comparablelevels 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 areseveral components to the likelihood function. The first component utilizes information fromresponses to vignettes. In this component of the likelihood function, the model assumes thereis an underlying latent variable for the set of vignettes, addressing a particular domain ofhealth, 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 arecategorical responses for each of the vignettes Yv. In other words, respondents evaluate eachof the vignettes using the same 5-point response category scale and with regard to the samequestion as the main self-reported question for any given domain. The mapping from thelatent variable to the observed categorical responses is defined by a series of cut-points whichare 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-handside variable in the first component of the HOPIT model (each vignette response being aseparate observation). On the right-hand side are dummies for each of V-1 vignettes, with thefirst vignette (describing the best ability level) being set to be the absorbed category andtherefore equivalent to 0. In essence, the model fixes the level of ability on the underlyinglatent variable (i.e., each domain of health) scale such that any differences in responsecategories are attributed to cut-point shifts. The coefficients on these for each of V-1 vignettesdummy variables are the fixed levels on the underlying latent variable. Mathematically, thisimplies that:

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

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

Yv = 1 if -� < Y*v < �1

Yv = 2 if �1 < Y*v < �2

…Yv = 5 if �

4 < Y*v < +�

Plus,

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�’s = f (socio-demographic characteristics)

The second component of the likelihood function utilizes information from self-reportresponses. Cut-points are estimated from the vignettes section of the likelihood to calibratethe self-report responses so as to make them cross-population comparable. In this sense, thereis 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 thisis 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 -� < Y*s < �1

Ys = 2 if �1 < Y*s < �2

…Ys = 5 if �

4 < Y*s < +�

And,

�’s = f (socio-demographic characteristics)

3.5.2 Compound Hierarchical Ordered Probit (CHOPIT) Model (HOPIT with auxiliaryquestions). The third component of the likelihood function uses information from auxiliaryquestions. The mean level of the latent variable is assumed to be the same as that for the mainself-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 arecomparable 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 -� < Y*s < �1

Ya = 2 if �1 < Y*s < �2

…Ya = 5 if �

4 < Y*s < +�

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., whencovariates in our model do not capture all the systematic variation in the latent variable -- thenthere remains information content in the set of responses (when more than one question perdomain exists) on the level of health for each individual that has not been fully exploited, orthere are covariates missing from the model. In order to exploit the information content in theset of responses we can make use of Bayes' theorem to obtain estimates of the mean level ofthe latent variable conditional on the observed set of responses for a given individual (see

12

Tandon et al. 2001 for an evaluation of this approach using simulated data). For now withinHOPIT we assume that the random effect captures about 50 per cent of the variation inestimated 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 ofresponses, has been computed.

3.5.4 Evaluation of model fit. Assessing goodness-of-fit for categorical data is notstraightforward. One can compute a simple count-R² which is a measure of the proportion ofcorrect responses obtained for a given sample. For ordinal data, the predicted categoricalresponse would be the one associated with the maximum predicted probability. Other optionsinclude a pseudo-R² measure, which in software such as STATA, is a likelihood-basedcomparison of the model with all the parameters to one with only the intercept (Long andFreese 2001). Rasch-based models use measures of fit such as "outfit" and "infit": "outfit" isa chi-square test based on the sum of the standardized deviation of observed versus expectedvalues of a response. "Infit" is also a chi-square test which utilizes an information-weightedsum by adjusting for extreme responses using weights (Write and Mok 2000). In order toassess 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 modelthat is nested within the full model) to assess the contribution of the dropped covariates to thelikelihood function. Assume L0 is the log-likelihood value associated with the full model andL1 is the log-likelihood value of the constrained model. Then -2(L1-L0) is distributed χ² withd0-d1 degrees of freedom, where d0 and d1 are the model degrees of freedom associated withthe full and the constrained models on exactly the same sample, respectively (Long andFreese 2001).

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

3.6.1 Rescale. Using the predicted level of health for each domain Y* incorporating theindividual-level random effect, we re-scale our results across surveys, for each domainseparately. This is so as the scale of the predicted level of health Y* is arbitrary and differs foreach domain. For presentation purposes we equalize the scale across populations whilemaintaining the relative differences and distribution of severity within each population acrossthe 66 surveys. We apply a simple transformation of the predicted Y* to a 0 to 100 scale, bydomain. We truncate the end-points of the estimated level of health Y* to provide greaterstability and confidence in the comparability of end points selected. Rather than using theobserved 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 ofthis estimated level is reported for all 66 surveys and for each of the six domains. Theposterior estimates of health, Y* are relative to one another and do not reflect an absolutescale (for each domain). Comparisons of the estimated level of health may be made withineach domain of health, not across domains.

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

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

13

III.7 EVALUATION OF METHODS

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

The following tests or examples are provided:

� Evidence of cut-point shifts across countries (the first component of the likelihoodfunction)

� Posterior estimates (HOPIT with and without random effect component)� Estimated level of health: comparison of ordinal responses and estimated level of health,

by domain (the second component of the likelihood function)� Estimated level of health: HOPIT vs. HOPIT with auxiliary questions (the third

component of the likelihood function)� 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 likelihoodfunction). Two null hypotheses concerning this first approach are proposed. The first is thatthe 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 theseven vignettes for the domain of Self Care: in-depth household surveys in India (AndhraPradesh) and China (three provinces) illustrate that these proportions differ. Figure 5summarizes these differences by illustrating the mean rating of vignettes in two other domainsassessed, Affect and Pain, for one survey from each WHO Region (AFRO: Nigeria; AMRO:Argentina; EMRO: Jordan; EURO: Croatia; SEARO: Thailand; WPRO: Australia). For anyset of vignettes, the response distribution in each of the five categories differs by country, aswell as by other covariates (not shown), and therefore are not constant across surveys. Acritical evaluation of vignettes as a means to calibrate responses across populations within thehealth 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 inIndia and China), seven vignettes addressing domain of Self Care

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14

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

The second null hypothesis is that the cut-points on the latent variable for each domain do notvary given differences in covariates (e.g., age, sex, years of education, and surveypopulation). In this paper, we focus on differences across survey populations. Figure 6illustrates the distribution of mean cut-points (t1-t4) for each domain: cut-points vary bysurvey. For each cut-point, each data point in the distribution represents one of the 66surveys. The x-axis notes: t1 which is the transition from the ordinal category "extremedifficulty" 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 transitionfrom "mild" to "no difficulty" or the best category. The y-axis represents the latent variablescale for each domain, with the horizontal lines being the coefficients on each of the vignettesfrom the first component of the likelihood function (the best vignette is set to 0). Thesecoefficients set the scale on the underlying latent variable across all surveys. A distributionexists for t1-t4 and these shifts in cut-points reflect mean differences across surveys (seeTandon et al. 2001).

Figure 7 provides further detail on the domain of cognition. From the first part of thelikelihood 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 correspondsroughly to the following vignette describing difficulties in concentration and memory: “Mr Xis easily distracted, and within 10 minutes of beginning a task, his attention shifts tosomething else. He can remember important facts when he tries, but several times a week hefinds 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 individualsfrom 11 other surveys (from Greece, France, Trinadad & Tobago, Chile, Luxembourg,Belgium, Nigeria, Bulgaria, Denmark, Iceland or Netherlands) on average will rate this samelevel of cognition, "moderate difficulty.” Differences across selected countries aresignificant: 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, onaverage, they have higher standards or norms for what constitutes “mild” difficulty incomparison to “moderate” difficulty, for cognition, in comparison to Indonesia: Indonesianson average have lower norms -- this is why Indonesia’s cut-points are found at the lower endof each cut-point distribution -- shown here for cut-point 2 and 3. As noted, cut-points are

1

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15

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

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16

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

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17

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

Another way of looking at this same distribution of cut-points for Cognition, is that real datacan parallel the simulation by Tandon et al. (2001): here Andhra Pradesh is similar topopulation A, with lower standards for what is good health, and Luxembourg is similar topopulation 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 ofcognition, 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 shiftsbetween two survey populations (Luxembourg and India (Andhra Pradesh))

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18

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

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 about50 per cent of the variation in estimated variance of the error term, the posterior prediction ofindividual level of health is compared to the prediction of individual level of health withoutthis random effect component. Across all 66 surveys, the correlation of the estimated level ofhealth, 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; UsualActivities: 0.80.).

Tandon et al. (2001:13-14) demonstrate with a simulated data set where truth is known, theR-squared between "True Mobility" and the predicted Y* of Mobility using the HOPIT modelonly with covariates is 0.055: however, with the posterior estimate, the R-squared jumps to0.334. They conclude that the posterior estimates significantly improves the estimation ofhealth in the simulated data set. For the survey data, we are unable to evaluate whether theaddition of a correction for individual random effect performs better. We have simplyassumed that the random effect captures 50 per cent of the variation, and we hypothesize thatwe capture more of the systematic variation on the latent variable due to covariates notmeasured.

3.7.3 Estimated level of health: comparison of ordinal responses and estimated level ofhealth, by domain (the second component of the likelihood function). To evaluate theoverall impact of the analysis approach applied, we compare mean ordinal responses (the fivecategories) for each age and the estimated level of health Y* (based on our posterior estimatesfrom the HOPIT model), for all six domains assessed of health. We extend our comparisonbetween Luxembourg and India (Andhra Pradesh), to illustrate the difference our methodsmake on the estimated level of health, across all domains. These results appear quiteremarkable (Figure 9).

Across all domains, a higher score is better health. If we only look at the self-reported ratingsusing five categories (the circles on the graphs), there is not much difference in thedistribution 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 mostdomains. Most analyses on health status data from surveys stops here. However, if weinstead focus on the estimated level of health based on our new methods (the triangles), wesee that the mean levels of health tend to be lower in Andhra Pradesh than Luxembourg formost domains, and that the drop across age4 is steeper for Andhra Pradesh across mostdomains, in comparison to Luxembourg.

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

19

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)M

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20

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

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

21

Andhra Pradesh. We propose that our posterior estimates based on the HOPIT model havegreater 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 ofthe survey data has improved, is that the large ceiling effects (i.e., proportion of respondentsin the best ordinal response category) that are often in population based surveys have alsobeen reduced (for example, Luxembourg, self-care). Additional comparisons based on theresults from the HOPIT model, with those where the t1-t4 do not vary by covariates, isunderway.

3.7.4 Estimated level of health: HOPIT vs. CHOPIT (the third component of thelikelihood function). We now turn to the in-depth household surveys (n=59,618) that containauxiliary questions addressing each core domain of health, and consider if auxiliary questionsadd information content to the estimated average level of health, Y* for each domain. Weexplore this question by comparing the correlation of our prior estimates of Y* with andwithout auxiliary questions, as well as comparing the distribution of the levels of health forone domain in the 10 in-depth household surveys. For the domain of Mobility, the correlationis 0.99 within each of the in-depth household surveys: almost no difference exists in resultsbetween the current versions of HOPIT and CHOPIT models using the same vignettes andcovariates. For example, the cumulative frequency of different levels of mobility based onHOPIT 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 cumulativefrequency would reflect finer distinctions between different severity levels.)

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

Mexico (n=4336) Egypt (n=4485)

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

Hopit Y* Chopit Y*

22

3.7.5 Model fit: likelihood ratio test for full and nested models (addressing addition ofcovariates 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 ofeducation, and survey population) on cut-points (e.g., t1-t1), with the nested model with nocovariates on the cut-points (i.e., t1-t4 do not vary by age, sex, years of education, or surveypopulation) for the following two domains as an example.

Affect Mobilityχ²(280) = 8144.36 χ²(280) = 10013.74Prob > χ² = 0.000 Prob > χ² = 0.000

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

IV. Results

Using the methods developed and evaluated in section 3, we have estimated the average levelof health for each of six domains assessed of health, for males and females, in six age groupsbased on the self-report of health within 66 surveys from 57 countries included within theWHO Multi-Country Survey. We also estimated the average level of health by domain forthe total population sampled in each survey, by sex, in order to facilitate comparisons acrosscountries. The posterior estimates of health, Y* are domain-specific, on a scale defined by thecoefficients of vignettes for each domain, and then rescaled 0 to 100, as described earlier. Inall of the figures and tables presented, 100 is the best level of self-reported health, whereas 0is the worst5 level of self-reported health, across the 66 surveys analyzed. Comparisons of theestimated level of health may be made within each domain of health, not across domains. Ahigher 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 modelestimates on key variables (Table 3). Neither dummy variables for each survey nor covariatesacross 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 vignettesfix the scale of the latent variable, with the vignette describing the best level of health in eachdomain being set to 0 (see Figure 6): except for the domain of pain, the coefficients on eachvignette are in the expected order given the severity level described. The estimates oncovariates should be interpreted in relation to the absorbed categories or baseline values forcovariates (age group 15-29; 0 years of education; females; and the survey from United ArabEmirates6). 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 (Table3).

5 Zero is not equivalent to death but to the worst level of self-reported health reported6 United Arab Emirates is the baseline country only due to its abbreviation in the analysis "ARE" and isthe first country listed in alphabetical order.

23

IV.2 ESTIMATED LEVEL OF HEALTH ON EACH DOMAIN, BY AGE -SEXGROUPS

Age-specific estimates for the average level of health by domain are presented for thefollowing 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 differentsurvey modes noted across all 66 surveys. These results across ages are grouped by the sixWHO regions. For the European Region which has the largest number of surveys includedwithin 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 andusual activities) within age groups and trends across age groups should be reviewedseparately. For example, across age and sex groups, average levels of affect are better inMexico, Egypt, Indonesia, Ireland and China, in comparison to other countries in the sameregion. However, the same pattern does not exist across all domains. For example, the highestaverage level of mobility is not always achieved by the same country across age and sexgroups within each region. Furthermore, some domains have much greater variation acrossage groups (i.e., mobility or cognition) than others (i.e., affect).

IV.3 LEVEL OF HEALTH ON EACH DOMAIN, AGGREGATED FOR THETOTAL 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 surveypopulation. Tables 5-10 provide these results in rank order based on the average estimatedlevel for males and females combined, and also include the ratio of male to female level ofhealth, for each domain. Figures 17-22 illustrate these results by domain, as well as comparethe 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 bothsexes, with per capita GDP (Evans et al. 2001).

Countries at the top and bottom across domains are similar, but not identical. For males andfemales 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 levelof affect is in Kyrgystan, followed by Turkey (postal), Ukraine, Latvia, Romania, Lithuania,Croatia, Poland, Hungary and Cyprus. Except for Costa Rica and Venezuela, males reportequal or higher levels of affect than women across all surveys: a male to female ratio ofgreater than or equal to 1.15 is noted in Chile, Czech Republic (postal), Columbia, Egypt(postal), Argentina, Morocco, Cyprus, Lithuania, Romania, Ukraine, Turkey (postal), andKyrgyzstan. At higher levels of average health for both sexes in this domain, the male tofemale 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 byTurkey (postal), Trinidad & Tobago, Lithuania, Egypt (postal), Morocco, Thailand, Indonesia(postal), Ukraine and Poland. The striking difference between estimates from Indonesia andEgypt based on household and postal surveys requires further examination, beyond the scopeof this paper. Except for Canada (telephone), Costa Rica and Venezuela, males report equal orhigher levels of cognition than women across all surveys: a male to female ratio of greater

24

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 higherlevels of average health for both sexes in this domain, the male to female ratio tends to besmaller, 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 andDenmark. The lowest self-reported level of mobility is in Kyrgystan, followed by Lithuania,Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan, Croatia, andSlovenia. Except for Costa Rica, males report equal or higher levels of mobility than womenacross 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 ofaverage health for both sexes in this domain, the male to female ratio tends to be smaller, thanat lower average levels of mobility.

For pain (Table 8), United Arab Emirates has the highest self-reported absence of painfollowed by Ireland, Spain, Nigeria, China (household), Oman, Mexico, Italy, Germany, andChina (postal). The highest self-reported level of pain is in Kyrgystan, followed by Republicof Korea, Indonesia (postal), Turkey (postal), Lithuania, Ukraine, Cyprus, Poland Egypt(postal) and Austria. The lowest self-reported level of mobility is in Kyrgystan, followed byLithuania, Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan,Croatia, and Slovenia. In all surveys males report equal or higher levels of absence of painthan 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 ofaverage health for both sexes in this domain, the male to female ratio tends to be smaller, thanat lower average levels of the absence of pain.

For self care (Table 9), Luxembourg has the highest self-reported level of self care, followedby Nigeria, China (postal), Ireland, Sweden, Finland, Iceland, Canada (telephone),Switzerland, and Spain. The lowest self-reported level of self care is in Kyrgystan, followedby Turkey (postal), Egypt (postal), Morocco, Ukraine, Lithuania, Indonesia (postal),Republic of Korea, Thailand, India. In all surveys males report equal or higher levels of selfcare 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 thisdomain, 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 inKyrgystan, followed by Ukraine, Turkey (postal), Morocco, Lithuania, Egypt (postal),Poland, Romania, Czech Republic (postal), and Latvia. In all surveys males report equal orhigher levels of usual activities than women: in 16 surveys, a male to female ratio of greaterthan 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 femaleratio tends to be greater, than at higher average levels of usual activities.

25

Table 3. Estimation results, HOPIT, by domain, across all 66 surveys (excluding dummyvariables for each survey and covariates on cut-points*)Affect PainVariable Coefficient Std. Err. z P>|z| Variable Coefficient Std. Err. z P>|z|Vignettes Vignettesvignette2 -1.890 0.011 -173.09 0.000 vignette2 -0.769 0.009 -85.32 0.000vignette3 -2.447 0.011 -217.44 0.000 vignette3 -1.237 0.009 -134.90 0.000vignette4 -2.618 0.011 -230.76 0.000 vignette4 -1.501 0.009 -160.59 0.000vignette5 -3.246 0.012 -275.72 0.000 vignette5 -1.419 0.009 -153.20 0.000vignette6 -4.293 0.013 -340.09 0.000 vignette6 -1.333 0.009 -144.77 0.000Mean vignette7 -2.730 0.010 -263.91 0.000Age 30-44 -0.097 0.015 -6.33 0.000 MeanAge 45-59 -0.305 0.017 -18.02 0.000 Age 30-44 -0.220 0.015 -14.49 0.000Age 60+ -0.521 0.019 -27.88 0.000 Age 45-59 -0.554 0.017 -33.35 0.000Male 0.270 0.012 23.33 0.000 Age 60+ -1.041 0.018 -57.50 0.000Education (yrs) 0.022 0.001 15.05 0.000 Male 0.221 0.011 19.84 0.000Intercept -1.223 0.711 -17.19 0.000 Education (yrs) 0.032 0.001 22.71 0.000log(s) 0.351 0.004 81.06 0.000 Intercept 1.389 0.079 17.60 0.000Cognition* log(s) 0.283 0.004 64.90 0.000Variable Coefficient Std. Err. z P>|z| Self CareVignettes Variable Coefficient Std. Err. z P>|z|vignette2 -1.703 0.011 -160.57 0.000 Vignettesvignette3 -1.892 0.011 -177.88 0.000 vignette2 -1.901 0.011 -179.71 0.000vignette4 -2.048 0.011 -191.49 0.000 vignette3 -2.077 0.011 -195.36 0.000vignette5 -2.534 0.011 -231.10 0.000 vignette4 -2.488 0.011 -229.16 0.000vignette6 -2.637 0.011 -241.02 0.000 vignette5 -2.555 0.011 -234.95 0.000vignette7 -3.235 0.011 -287.41 0.000 vignette6 -2.827 0.011 -256.67 0.000vignette8 -3.896 0.012 -331.09 0.000 vignette7 -3.740 0.012 -321.22 0.000Mean MeanAge 30-44 -0.036 0.015 -2.46 0.014 Age 30-44 -0.218 0.025 -8.73 0.000Age 45-59 -0.282 0.016 -17.31 0.000 Age 45-59 -0.666 0.027 -25.05 0.000Age 60+ -0.701 0.018 -39.43 0.000 Age 60+ -1.482 0.029 -51.97 0.000Male 0.180 0.011 16.32 0.000 Male 0.149 0.017 8.81 0.000Education (yrs) 0.030 0.001 21.78 0.000 Education (yrs) 0.058 0.002 27.25 0.000Intercept -0.726 0.068 -10.72 0.000 Intercept 0.619 0.107 5.77 0.000log(s) 0.242 0.005 49.67 0.000 log(s) 0.486 0.007 64.84 8.000Mobility Usual ActivitiesVariable Coefficient Std. Err. z P>|z| Variable Coefficient Std. Err. z P>|z|Vignettes Vignettesvignette2 -0.193 0.009 -22.13 0.000 vignette2 -1.784 0.010 -173.94 0.000vignette3 -1.810 0.008 -227.55 0.000 vignette3 -1.953 0.010 -187.76 0.000vignette4 -2.681 0.008 -321.06 0.000 vignette4 -1.991 0.010 -192.14 0.000vignette5 -3.063 0.009 -358.16 0.000 vignette5 -2.272 0.010 -216.80 0.000vignette6 -4.384 0.009 -462.84 0.000 vignette6 -2.674 0.011 -251.17 0.000Mean vignette7 -2.760 0.011 -257.87 0.000Age 30-44 -0.245 0.015 -15.91 0.000 vignette8 -3.409 0.011 -304.48 0.000Age 45-59 -0.658 0.017 -39.65 0.000 MeanAge 60+ -1.292 0.018 -71.57 0.000 Age 30-44 -0.219 0.019 -11.55 0.000Male 0.202 0.011 18.47 0.000 Age 45-59 -0.589 0.020 -28.75 0.000Education (yrs) 0.039 0.001 28.86 0.000 Age 60+ -1.304 0.022 -58.79 0.000Intercept -0.660 0.068 -9.72 0.000 Male 0.200 0.014 14.71 0.000log(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

26

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

Self Reported Level of Af fect by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001

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male, Nigeria(h)female,Nigeria(h)

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Ar genti na(b)

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Chi l e(p)

Col ombi a(h)

Costa Ri ca(b)

M exi co(h)

T r i ni dad andT obago(p)

Uni ted States(p)

Venezuel a(b)

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Chi l e(p)

Col ombi a(h)

Costa Ri ca(b)

M exi co(h)

T r i ni dad andT obago(p)Uni ted States(p)

Venezuel a(b)

Self Reported Level of Af fect by Age Group, M ale, EM RO, WHO Health & Responsiveness Surveys, 2001

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Bahr ai n(b)

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Egypt (p)

Jor dan(b)

M or occo(b)

Oman(b)

Uni ted A r abEmi r ates(b)

Self Reported Level of Af fect by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001

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Oman(b)

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

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Indi a(h)

Indonesi a(h)

Indonesi a(p)

T hai l and(p)

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Indonesi a(p)

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Bul gar i a(b)

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Hungar y(p)

M al ta(b)

Pol and(p)

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Estoni a(b)

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Self Reported Level of Affect by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

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Ger many(b)

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29

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

Self Reported Level of Cognit ion by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001

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male, Nigeria(h)female,Nigeria(h)

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Ar gent i na (b)

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Self Reported Level of Cognit ion by Age Group, M ale, SEARO, WHO Health & Responsiveness Surveys, 2001

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31

Self Reported Level of Cognit ion by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

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Aust r i a(p)Denmar k(p)Fi nl and(b)

Fi nl and(p)Ger many(b)Icel and(b)Nether l ands (b)Nether l ands (p)

Sweden(b)Swi tzer l and (p)

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Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)

Nether l ands(p)

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Swi tzer l and(p)

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Cognit ion by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Cognit ion by Age Group, M ale, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

Self Reported Level of Cognit ion by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

32

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 Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Age groups

male, Nigeria(h)female,Nigeria(h)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca(b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States(p)

Venezuel a (b)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States (p)

Venezuel a (b)

Self Reported Level of M obility by Age Group, M ale, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

Self Reported Level of M obility by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

33

Self Reported Level of M obility by Age Group, M ale, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of M obility by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of M obility by Age Group, M ale, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)

CzechRepubl i c (p)M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of M obility by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)CzechRepubl i c (p)

M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of M obility by Age Group, M ale, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latv i a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

Self Reported Level of M obility by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latv i a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

34

Self Reported Level of M obility by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)Sweden (b)

Swi tzer l and(p)

Self Reported Level of M obility by Age Group, Female, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)Sweden (b)

Swi tzer l and(p)

Self Reported Level of M obility by Age Group, M ale, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of M obility by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of M obility by Age Group, M ale, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

Self Reported Level of M obility by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

35

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

Self Reported Level of Pain by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Age groups

male, Nigeria(h)female,Nigeria(h)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States(p)

Venezuel a (b)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States (p)

Venezuel a (b)

Self Reported Level of Pain by Age Group, M ale, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

Self Reported Level of Pain by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

36

Self Reported Level of Pain by Age Group, M ale, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Pain by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Pain by Age Group, M ale, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)

CzechRepubl i c (p)M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Pain by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)CzechRepubl i c (p)

M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Pain by Age Group, M ale, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latvi a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

Self Reported Level of Pain by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latvi a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

37

Self Reported Level of Pain by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)Sweden (b)

Swi tzer l and(p)

Self Reported Level of Pain by Age Group, Female, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)

Sweden (b)

Swi tzer l and(p)

Self Reported Level of Pain by Age Group, M ale, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Pain by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Pain by Age Group, M ale, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

Self Reported Level of Pain by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

38

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 Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Age groups

male, Nigeria(h)female,Nigeria(h)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States(p)

Venezuel a (b)

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

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States(p)

Venezuel a (b)

Self Reported Level of Self care by Age Group, M ale, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

Self Reported Level of Self care by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

39

Self Reported Level of Self care by Age Group, M ale, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Self care by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Self care by Age Group, M ale, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)

CzechRepubl i c (p)M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Self care by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)CzechRepubl i c (p)

M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Self care by Age Group, M ale, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latvi a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

Self Reported Level of Self care by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latvi a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

40

Self Reported Level of Self care by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)

Sweden (b)

Swi tzer l and(p)

Self Reported Level of Self care by Age Group, Female, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)Sweden (b)

Swi tzer l and(p)

Self Reported Level of Self care by Age Group, M ale, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Self care by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Self care by Age Group, M ale, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

Self Reported Level of Self care by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

41

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

Self Reported Level of Usual Act ivit ies by Age Group, AFRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Age groups

male, Nigeria(h)female,Nigeria(h)

Self Reported Level of Usual activit ies by Age Group, M ale, AM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States(p)

Venezuel a (b)

Self Reported Level of Usual act ivit ies by Age Group, Female, AM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Ar gent i na (b)

Canada (p)

Canada (t )

Chi l e (p)

Col ombi a (h)

Costa Ri ca (b)

M exi co (h)

T r i ni dad andT obago (p)

Uni ted States (p)

Venezuel a (b)

Self Reported Level of Usual act ivit ies by Age Group, M ale, EM RO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

Self Reported Level of Usual act ivit ies by Age Group, Female, EM RO, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Bahr ai n (b)

Egypt (h)

Egypt (p)

Jor dan (b)

M or occo (b)

Oman (b)

Uni ted A r abEmi r ates (b)

42

Self Reported Level of Usual act ivit ies by Age Group, M ale, SEARO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Usual act ivit ies by Age Group, Female, SEARO, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Indi a (h)

Indonesi a (h)

Indonesi a (p)

T hai l and (p)

Self Reported Level of Usual act ivit ies by Age Group, M ale, EURO-C, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)CzechRepubl i c (p)

M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Usual act ivit ies by Age Group, Female, EURO-C, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Hungar y (p)

Bul gar i a (b)

Cr oat i a (b)

Cypr us (p)

CzechRepubl i c (b)CzechRepubl i c (p)

M al ta (b)

Pol and (p)

Romani a (b)

Sl ovaki a (h)

Self Reported Level of Usual act ivit ies by Age Group, M ale, EURO-E, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latv i a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

Self Reported Level of Usual act ivit ies by Age Group, Female, EURO-E, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Estoni a (b)

Geor gi a (h)

Kyr gyzstan (p)

Latv i a (b)

Li thuani a (p)

Russi anFeder at i on (b)

T ur key (h)

T ur key (p)

Ukr ai ne (p)

43

Self Reported Level of Usual act ivit ies by Age Group, M ale, EURO-N, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)

Sweden (b)

Swi tzer l and(p)

Self Reported Level of Usual Act ivit ies by Age Group, Female, EURO-N, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r i a (p)

Denmar k (p)

Fi nl and (b)

Fi nl and (p)

Ger many (b)

Icel and (b)

Nether l ands(b)Nether l ands(p)Sweden (b)

Swi tzer l and(p)

Self Reported Level of Usual act ivit ies by Age Group, M ale, EURO-W, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Usual act ivit ies by Age Group, Female, EURO-W, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Bel gi um (b)

Fr ance (b)

Fr ance (p)

Gr eece (p)

I r el and (b)

I tal y (b)

Luxembour g (t )

Por tugal (b)

Spai n (b)

Uni tedK i ngdom (p)

Self Reported Level of Usual act ivit ies by Age Group, M ale, WPRO, WHO Health & Responsiveness Surveys, 2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

Self Reported Level of Usual act ivit ies by Age Group, Female, WPRO, WHO Health & Responsiveness Surveys,

2001

0

10

20

30

40

50

60

70

80

90

100

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

Aust r al i a (p)

Chi na (h)

Chi na (p)

Newzeal and (p)

Republ i c of Kor ea (p)

44

Table 4. Average level of health by domain, age-standardized, 66 surveys, WHO Multi-Country Survey Study on Health and Responsiveness, 2000-2001Affect Cognition Mobility Pain Self Care Usual Activities

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

45

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

47

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

48

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

49

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

50

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

51

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

52

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

53

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

Male vs. Female Self Report of AffectWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100Average Level for Males and Females Combined

Ratio

of M

ale/

Fem

ale

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Self

Rep

orte

d A

ffect

Male Life Expectancy at birth (2000) vs. Self Reported Affect

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Sel

f Rep

orte

d Af

fect

Female Life Expectancy at birth (2000) vs. Self Reported Affect

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Self

Rep

orte

d A

ffect

54

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

Male vs. Female Self Report of CognitionWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100

Average Level for Males and Females Combined

Ratio

of M

ale/

Fem

ale

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Sel

f Rep

orte

d C

ogni

tion

Male Life Expectancy at birth (2000) vs. Self Reported Cognition

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Self

Rep

orte

d C

ogni

tion

Female Life Expectancy at birth (2000) vs. Self Reported Cognition

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85Life Expectancy at birth

Sel

f Rep

orte

d Co

gniti

on

55

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

Male vs. Female Self Report of MobilityWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100

Average Level for Males and Females Combined

Ratio

of M

ale/

Fem

ale

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Sel

f Rep

orte

d M

obilit

y

Male Life Expectancy at birth (2000) vs. Self Reported Mobility

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Self

Repo

rted

Mob

ility

Female Life Expectancy at birth (2000) vs. Self Reported Mobility

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Sel

f Rep

orte

d M

obili

ty

56

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

Male vs. Female Self Report of PainWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100

Average Level for Males and Females Combined

Ratio

of M

ale/

Fem

ale

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Sel

f Rep

orte

d Pa

in

Male Life Expectancy at birth (2000) vs. Self Reported Pain

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Sel

f Rep

orte

d Pa

in

Female Life Expectancy at birth (2000) vs. Self Reported Pain

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Sel

f Rep

orte

d P

ain

57

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

Male vs. Female Self Report of Self-careWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100

Average Level for Males and Females Combined

Ratio

of M

ale/

Fem

ale

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Self

Rep

orte

d S

elf-c

are

Male Life Expectancy at birth (2000) vs. Self Reported Self-care

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Self

Rep

orte

d S

elf-c

are

Female Life Expectancy at birth (2000) vs. Self Reported Self-care

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Sel

f Rep

orte

d Se

lf-ca

re

58

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

Male vs. Female Self Report of Usual ActivitiesWHO 2000 - 2001 Survey

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100

Males

Fem

ales

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

0.80.91.01.11.21.31.41.51.6

0 20 40 60 80 100

Average Level for Males and Females Combined

Rat

io o

f Mal

e/Fe

mal

e

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

World Standardized Population

0102030405060708090

100

0 5000 10000 15000 20000 25000 30000 35000

Per Capita GDP

Self

Rep

orte

d U

sual

Act

ivitie

s

Male Life Expectancy at birth (2000) vs. Self Reported Usual Activities

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85

Life Expectancy at birth

Self

Rep

orte

d U

sual

Act

ivitie

s

Female Life Expectancy at birth (2000) vs. Self Reported Usual Activities

World Standardized Population

0102030405060708090

100

40 45 50 55 60 65 70 75 80 85Life Expectancy at birth

Self

Rep

orte

d U

sual

Act

ivitie

s

59

V. Discussion

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

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

To do so, we include a comparison of selected results from this analysis with those from ourprevious 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 populationsnor 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 calibrateresponses, there is no gold standard or measurement of "truth" that captures all aspects of eachdomain of health. Instead, several approaches to estimate validity are required as no single aspect ofvalidity would provide a definitive evaluation. Three basic criteria provide necessary evidence thatthe new methods have enhanced the information content and comparability of health status datacollected through surveys include: (i) that the estimated levels of health should decrease as ageincreases (criterion validity); (ii) that the differences in the estimated levels of health, for mostdomains, should reflect expected differences within and across populations, for example betweenmales and females, between populations with high child and high adult mortality vs. those with lowchild 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 asmeasured should provide unique information (content validity).

V.1 INFORMATION CONTENT

5.1.1 DIFFERENCE BETWEEN ORDINAL RESPONSE AND ESTIMATED LEVEL OFHEALTH

In section 3.7.3, we provide illustrations comparing the ordinal response and the estimated level ofhealth 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 inLuxembourg, show very little variation over age. These same mean ordinal responses are similar forthe two populations across all age groups, particularly for cognition, mobility and pain. However, theposterior estimated levels of health across five of the six domains assessed (with the exception tosome 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 asmobility, 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 combinedshows that the four domains that directly assess health (e.g. affect, cognition, mobility, pain) clearlyprovide 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 highlycorrelated with mobility or pain ( 0.71 and 0.78 respectively), and less so with those directlyassessing mental health (i.e., 0.56 to 0.64 with affect or cognition). These results provide someevidence that each of the domains that directly assess health provide unique information, that the

60

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

Table 11. Correlation Matrix Across Domains, Estimated Level of Health, 66 surveysDomain Affect Cognition Mobility Pain Self Care Usual

ActivitiesAffect 1.0000Cognition 0.5558 1.0000Mobility 0.5686 0.5435 1.0000Pain 0.6259 0.5989 0.6673 1.0000Self Care 0.5575 0.5867 0.7563 0.7160 1.0000Usual 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: SELECTEDRESULTS 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). Figure23 illustrates the estimated level of health (uni-dimensional from the previous analysis)7 with ourcurrent results (selected domains shown), across age and sex groups for both populations. Theprevious analysis showed almost no decrement to full health, across all age groups from eightprovinces 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 thatthese data were comparable, nor that the Chinese data actually reflected the health status of thepopulation. Furthermore, separate analysis on the NHANES III data has shown evidence of cut-pointshifts using measured performance tests to calibrate self-reported responses across socio-economicgroups, within the USA population (Iburg et al. 2002).

Our current analysis approach, with results illustrating estimates for mobility, pain and cognition, donot show the high ceiling effects from the China in-depth household survey (sample coveringShandong, Henana and Gansu Provinces)9. We believe, by taking into account cut-point shifts, thisdata is more comparable across age and sex groups, both within each population and across the twopopulations. It is interesting to note that the comparison between the two countries differs dependingupon 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 assesshealth status may provide more comprehensive and complex insights on the health status of apopulation.

7 Given limitations in existing data sets, our previous analysis was based on one, general latent variableassessing 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 theCarolina 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.

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

Le ve l o f M ob ility(2000-2001 analys is )

0

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40

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5.2.2 SELECTED RESULTS, AGGREGATED AND AGE-STANDARIZED

We highlight the age standardized results, aggregated across age groups, by sex. Figure 24 shows theestimated level of health (mobility shown here, see Figures 17 - 22 for all domains), and lifeexpectancy by sex. We document that higher levels of life expectancy are correlated with higherestimated levels of health (+0.3), in this case for mobility, for either males or females. For the otherfive 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 resultssuggest (criterion validity).

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

Another approach to evaluate the information content and cross-population comparability of theresults is to interpret the data from surveys in conjunction with data external to health, from the samecountries. Such data may include the per capita gross domestic product or the per capita total healthexpenditures (criterion validity). Figure 25 illustrates the aggregated, age standardized estimates,averaged for both males and females, in comparison with GDP (PPP). We document that higherlevels of GDP (PPP), are correlated with higher estimated levels of health (+0.4 ), for the domain ofmobility, 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 intofour 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 byLatin American countries, former Socialist economies, and then countries in the EasternMediterranean area including Turkey and Kyrgystan. Only minor deviations from this pattern arenoted 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 estimatesbased on new methods. Based on our review of the new methods to collect and analyze self-reporteddata 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), amongother analyses.

2000-2001 analysis (57 countries, 66 surveys)

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2000-2001 analysis (57 countries, 66 surveys)

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Life Expectancy at birth, males

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63

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

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

(2000-2001 analysis)

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Per Capita GDP (PPP)

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Eas tern Mediterranean (9 countries ) Form er Socialis t (13 countries )Latin Am erican (9 countries ) OECD subset (22 countries )

64

VI. NEXT STEPS

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

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

� more stringent tests of hypotheses stated� parameter uncertainty estimates

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

� measured performance tests strategy for calibration: cognition, vision, mobility� posterior estimates: comparison between HOPIT and CHOPIT� auxiliary questions: information content and item reduction strategies� 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 bean input to update the survey module on health status. This will include a revision, as necessary, ofthe questions addressing each core domain of health and the corresponding set of vignettes. Thisupdated module, within the planned WHO World Health Survey, will then be implemented insurveys in additional countries, particularly in the African region.

Given that the current sampling strategy includes the non-institutionalized population, the furtherexpansion of the sampling protocol and adaptation of methods to include representative samples ofindividuals 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 Ortizfor fruitful discussions on parallel analytical efforts in the area of health system responsiveness; JoshSalomon for the conception of the vignette adjustment strategy; Colin Mathers for contributing to thedevelopment of the health status assessment module and comments on this manuscript; PierreLewalle for his contribution in coordinating the language translation protocols, the first step towardscross-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 the66 survey sites; Melroy Menezes and René Lavallée for their assistance in preparing graphs withinthis manuscript; and Emre Ozaltin for comments on this manuscript.

65

VII. References

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

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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 andNutrition Examination Survey. In CJL Murray et al., Summary Measures of PopulationHealth, World Health Organization, Geneva.

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

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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.

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

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Sadana R, Salomon J, Tandon A, Chatterji S, Murray CJL. Health state vignettes: design, empiricalanalysis 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 analysesof 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-PopulationComparability of Health Surveys: Concepts, Design and Evaluation Techniques," GlobalProgramme on Evidence for Health Policy Discussion Paper, Geneva: World HealthOrganization.

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," GlobalProgramme on Evidence for Health Policy Discussion Paper, Geneva: World HealthOrganization.

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

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

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

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Appendix 1: Distribution of mean cut-points (t1-t4) on latent variable scale-Cognition, 66 surveysSurvey Tau 1 Survey Tau 2 Survey Tau 3 Survey Tau 436. INDh -4.445 12. CHNh -3.220 35. IDNp -2.525 35. IDNp -1.22834. IDNh -4.363 58. SVKh -3.145 12. CHNh -2.281 40. JORb -1.10958. SVKh -4.343 33. HUNp -2.997 7. BHRb -2.212 53. OMNb -1.09812. CHNh -4.333 35. IDNp -2.960 53. OMNb -2.184 46. MARb -1.07421. EGYh -4.218 7. BHRb -2.950 58. SVKh -2.083 7. BHRb -1.06422. EGYp -4.086 52. NZLp -2.938 42. KORp -2.059 12. CHNh -1.04733. HUNp -4.040 13. CHNp -2.907 40. JORb -2.039 33. HUNp -0.99552. NZLp -4.014 53. OMNb -2.888 1. AREb -2.013 1. AREb -0.95923. ESPb -3.978 23. ESPb -2.884 33. HUNp -1.972 14. COLh -0.95714. COLh -3.976 1. AREb -2.874 36. INDh -1.946 66. VENb -0.90353. OMNb -3.960 3. AUSp -2.828 48. MLTb -1.941 36. INDh -0.89747. MEXh -3.908 42. KORp -2.821 43. LTUp -1.934 10. CHEp -0.88343. LTUp -3.853 40. JORb -2.813 10. CHEp -1.931 55. PRTb -0.88129. GBRp -3.841 66. VENb -2.811 41. KGZp -1.902 48. MLTb -0.8787. BHRb -3.832 43. LTUp -2.809 39. ITAb -1.881 34. IDNh -0.86937. IRLb -3.813 34. IDNh -2.796 49. NGAh -1.880 41. KGZp -0.85713. CHNp -3.808 10. CHEp -2.780 13. CHNp -1.870 58. SVKh -0.85560. THAp -3.806 9. CANt -2.775 55. PRTb -1.870 15. CRIb -0.84240. JORb -3.794 14. COLh -2.773 52. NZLp -1.869 57. RUSb -0.8409. CANt -3.785 37. IRLb -2.766 23. ESPb -1.849 47. MEXh -0.8331. AREb -3.785 21. EGYh -2.761 34. IDNh -1.838 32. HRVb -0.82819. DEUb -3.784 36. INDh -2.758 66. VENb -1.811 23. ESPb -0.80355. PRTb -3.780 39. ITAb -2.751 46. MARb -1.810 43. LTUp -0.80318. CZEp -3.779 60. THAp -2.749 60. THAp -1.790 27. FRAb -0.79730. GEOh -3.778 48. MLTb -2.746 47. MEXh -1.785 39. ITAb -0.7902. ARGb -3.777 64. UKRp -2.742 28. FRAp -1.778 30. GEOh -0.78317. CZEb -3.767 57. RUSb -2.727 16. CYPp -1.776 21. EGYh -0.78248. MLTb -3.762 47. MEXh -2.727 4. AUTp -1.759 56. ROMb -0.77865. USAp -3.758 29. GBRp -2.719 56. ROMb -1.757 5. BELb -0.77824. ESTb -3.756 65. USAp -2.713 14. COLh -1.752 42. KORp -0.74739. ITAb -3.755 19. DEUb -2.711 64. UKRp -1.748 50. NLDb -0.73110. CHEp -3.747 45. LVAb -2.709 65. USAp -1.738 4. AUTp -0.73145. LVAb -3.745 17. CZEb -2.706 9. CANt -1.735 52. NZLp -0.73035. IDNp -3.741 4. AUTp -2.682 57. RUSb -1.731 11. CHLp -0.7234. AUTp -3.741 15. CRIb -2.679 17. CZEb -1.720 9. CANt -0.7226. BGRb -3.731 46. MARb -2.668 21. EGYh -1.712 37. IRLb -0.71257. RUSb -3.726 2. ARGb -2.653 45. LVAb -1.712 44. LUXt -0.70032. HRVb -3.721 30. GEOh -2.650 8. CANp -1.712 63. TURp -0.69615. CRIb -3.690 32. HRVb -2.649 3. AUSp -1.711 22. EGYp -0.6958. CANp -3.690 56. ROMb -2.648 37. IRLb -1.705 16. CYPp -0.69342. KORp -3.690 8. CANp -2.637 27. FRAb -1.695 45. LVAb -0.6913. AUSp -3.687 55. PRTb -2.627 29. GBRp -1.666 62. TURh -0.69162. TURh -3.675 22. EGYp -2.622 5. BELb -1.666 60. THAp -0.68849. NGAh -3.674 41. KGZp -2.602 63. TURp -1.655 2. ARGb -0.68764. UKRp -3.654 16. CYPp -2.595 20. DNKp -1.645 49. NGAh -0.67531. GRCp -3.647 62. TURh -2.573 26. FINp -1.644 59. SWEb -0.67259. SWEb -3.641 25. FINb -2.573 32. HRVb -1.644 64. UKRp -0.66425. FINb -3.636 54. POLp -2.557 19. DEUb -1.644 17. CZEb -0.63066. VENb -3.598 26. FINp -2.553 25. FINb -1.640 20. DNKp -0.61754. POLp -3.597 18. CZEp -2.547 15. CRIb -1.640 8. CANp -0.61156. ROMb -3.546 59. SWEb -2.546 30. GEOh -1.637 28. FRAp -0.61163. TURp -3.525 63. TURp -2.543 54. POLp -1.632 65. USAp -0.60511. CHLp -3.524 28. FRAp -2.538 22. EGYp -1.627 25. FINb -0.60261. TTOp -3.502 24. ESTb -2.531 59. SWEb -1.625 6. BGRb -0.60046. MARb -3.501 31. GRCp -2.520 62. TURh -1.623 19. DEUb -0.59726. FINp -3.487 27. FRAb -2.496 24. ESTb -1.619 13. CHNp -0.59128. FRAp -3.465 61. TTOp -2.490 2. ARGb -1.603 3. AUSp -0.54716. CYPp -3.455 11. CHLp -2.479 61. TTOp -1.568 24. ESTb -0.5265. BELb -3.450 44. LUXt -2.470 38. ISLb -1.546 61. TTOp -0.52451. NLDp -3.422 5. BELb -2.454 44. LUXt -1.540 54. POLp -0.52227. FRAb -3.401 49. NGAh -2.449 31. GRCp -1.526 29. GBRp -0.51244. LUXt -3.399 6. BGRb -2.432 18. CZEp -1.520 38. ISLb -0.50738. ISLb -3.391 20. DNKp -2.430 11. CHLp -1.500 26. FINp -0.49850. NLDb -3.370 38. ISLb -2.387 6. BGRb -1.487 31. GRCp -0.47720. DNKp -3.304 51. NLDp -2.341 50. NLDb -1.412 18. CZEp -0.39341. KGZp -3.200 50. NLDb -2.334 51. NLDp -1.369 51. NLDp -0.361

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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 -1.682vignette3 -1.892 0.011 -177.88 0.000 -1.913 -1.872vignette4 -2.048 0.011 -191.49 0.000 -2.069 -2.027vignette5 -2.534 0.011 -231.1 0.000 -2.555 -2.512vignette6 -2.637 0.011 -241.02 0.000 -2.659 -2.616vignette7 -3.235 0.011 -287.41 0.000 -3.257 -3.213vignette8 -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 Maleeduc 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

69

_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 Maleeduc 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

70

_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 Maleeduc 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

71

_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

72

_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 Maleeduc 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

73

_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 Maleeduc 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

74

_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