What does Eurostat's Labour Force Survey say about health and ...

What does Eurostat’s Labour Force Survey say about health and health inequalities in the European Union?

Stefano Mazzuco, Department of Statistics, Padua University, Italy Marc Suhrcke, School of Medicine, Health Policy and Practice, University of East Anglia, United Kingdom

What does Eurostat’s Labour Force Survey say about health and health inequalities in the European Union?

Stefano Mazzuco, Department of Statistics, Padua University, Italy Marc Suhrcke, School of Medicine, Health Policy and Practice, University of East Anglia, United Kingdom

Keywords HEALTH STATUS DISPARITIES HEALTH STATUS INDICATORS DATA COLLECTION EMPLOYMENT - statistics and numerical data SOCIOECONOMIC FACTORS EUROPEAN UNION ISBN 978 92 890 0218 9 Suggested citation Mazzuco S, Suhrcke M (2010). What does Eurostat’s Labour Force Survey say about health and health inequalities in the European Union? Copenhagen, WHO Regional Office for Europe. Address requests about publications of the WHO Regional Office for Europe to: Publications WHO Regional Office for Europe Scherfigsvej 8 DK-2100 Copenhagen Ø, Denmark Alternatively, complete an online request form for documentation, health information, or for permission to quote or translate, on the Regional Office web site (http://www.euro.who.int/pubrequest). © World Health Organization 2010 All rights reserved. The Regional Office for Europe of the World Health Organization welcomes requests for permission to reproduce or translate its publications, in part or in full. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by the World Health Organization to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either express or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall the World Health Organization be liable for damages arising from its use. The views expressed by authors, editors, or expert groups do not necessarily represent the decisions or the stated policy of the World Health Organization.

Edited by Elizabeth Goodrich Book design and layout by Marta Pasqualato Cover photo ©iStockphoto.com/james knighten The photographs in this material are used for illustrative purposes only; they do not imply any particular health status, attitudes, behaviours, or actions on the part of any person who appears in the photographs.

Abstract This publication presents extensive analysis of newly available data from Eurostat’s Labour Force Survey (LFS) to measure health and socioeconomic inequalities in health in 25 European countries, in a period including 1983–2004 at most. The study first defined several, predominantly labour market-related health indicators plus one weighted, overall health index. The authors documented the limitations of using this information for the measurement of average national health status, and focused on the use of the health information for the assessment of socioeconomic inequalities in health. Standard concentration indices were calculated using five different proxies for socioeconomic status. After decomposing the inequality data into its trend and seasonal component, health inequalities were found to have been increasing for most but by no means all countries and health indicators. These results do not appear to be sensitive to the various proxies for socioeconomic status employed. Overall, while not without problems, the LFS may well add a useful and hitherto unexploited resource for measuring socioeconomic inequalities in health across European countries and over time.

Acknowledgements We gratefully acknowledge the financial and other support provided by the Department of Health of England (United Kingdom) and the WHO European Office for Investment for Health and Development, WHO Regional Office for Europe for the production of this report. We thank in particular Cristina Comunian (WHO European Office for Investment for Health and Development , WHO Regional Office for Europe) for her continued advice and her (almost) infinite patience. We have benefited greatly from the comments by Teresa Lavin (Institute of Public Health in Ireland), Margaret Whitehead and Frances M. Drever (Division of Public Health, University of Liverpool), and Enrique Loyola (Health Intelligence Service, WHO Regional Office for Europe). We are also indebted to Elizabeth Goodrich who copy-edited the text. Any errors are the sole responsibility of the authors. Stefano Mazzuco, Department of Statistics, Padua University, Italy Marc Suhrcke, School of Medicine, Health Policy and Practice, University of East Anglia, United Kingdom

WHO European Office for Investment for Health and Development The WHO European Office for Investment for Health and Development, which coordinated the activities leading to this publication, was set up by the WHO Regional Office for Europe, with cooperation and support from the Ministry of Health and the Veneto Region of Italy. One of its key responsibilities is to provide evidence on and act upon the social and economic determinants of health. The Office systematically reviews what is involved in drawing together the concepts, scientific evidence, technology and policy action necessary to achieve effective investment for the promotion of health and synergy between social, economic and health development. The Office fulfils two interrelated main functions: • to monitor, review and systematize the policy implications of the social and economic determinants of population health; and • to provide services to help Member States in the WHO European Region increase their capacity to invest in health by addressing these policy implications and integrating them into the agenda for development. iii

Contents Abbreviations

iv

List of tables

v

List of figures

v

Executive summary

vi

1.

Introduction

1

2.

Related literature

3

3.

Description of the LFS data

4

4. A first look at our data

6

5. A second look at our data

14

6.

Socioeconomic inequalities in health

18

7.

Concluding remarks

24

References

25

Annex 1. Average health indices by country and sex

27

Annex 2. Health inequality indices by country and sex

58

Abbreviations CRWA

continued reduction in working ability

EAP

exclusion from active population

ECHP

European Community Household Panel

EGP

Erikson and Goldthorpe’s class categories

EU

European Union

EU-25

countries belonging to the European Union prior to 2007

EU-SILC

European Union-Statistics on Income and Living Conditions

ISCED

International Standard Classification of Education

ISCO

International Standard Classification of Occupations

ISEI

International Socio-Economic Index of Occupational Status

LFS

Labour Force Survey

PIW

permanent inability to work

SES

socioeconomic status

SHARE

Survey of Health, Ageing and Retirement in Europe

SIOPS

Standard International Occupational Prestige Scale

THLI

Total Health Limitation Index

TIW

temporary inability to work

TRWA

temporary reduction in working ability

UNESCO

United Nations Educational, Scientific and Cultural Organization iv

List of tables Table 1. LFS questions relating to health issues

5

Table 2. Health indicators defined on the basis of LFS health questions

5

Table 3. Health limitation indices (standardized by age) for European countries, men, 2004

6

Table 4. Health limitation indices (standardized by age) for European countries, women, 2004

7

Table 5. Results of generalized additive model for generosity index

15

Table 6. Inequality of several health indices in European countries, men, second quarter, 2004

19

Table 7. Inequality of several health indices in European countries, women, second quarter, 2004

20

List of figures Fig. 1. TIW index (standardized by age) for representative European countries

8

Fig. 2. TRWA index (standardized by age) for representative European countries

8

Fig. 3. CRWA index (standardized by age) for representative European countries

9

Fig. 4. EAP index (standardized by age) for representative European countries

10

Fig. 5. PIW1 index (standardized by age) for representative European countries

10


11

Fig. 7. THLI (standardized by age) for representative European countries

11

Fig. 8. Scatter plots of THLI and prevalence of self-reported chronic illness

12

Fig. 9. Scatter plots of THLI and log of standardized mortality ratio

13

Fig. 10. Scatter plots of THLI and log of life expectancy at 15

13

Fig. 11. THLI before and after weighting with the inverse of generosity score, men, six countries

16

Fig. 12. Decomposition of THLI time series, Italy, men

17

Fig. 13. Health inequality index, Italy

21

Fig. 14. Decomposition of CRWA inequality time series, Italy

22

Fig. 15. Average level and inequality index of TRWA in European countries, second quarter, 2004

23

v

Executive summary This paper uses newly available data from Eurostat’s1 Labour Force Survey (LFS) to measure health and socioeconomic inequalities in health in 25 European Union (EU) countries, at most from 1983 to 2004. We believe no other Europewide survey offers LFS’s degree of coverage in terms of both time period and number of countries. Lacking such coverage has previously limited the degree of comparability over time and across countries in similar analyses. While the potential of the LFS dataset is significant, it also has a potentially serious drawback from a health perspective: its relatively limited health information is all related to a series of dimensions of sickness absence from the workplace or, from being employed in the first place. Despite encouraging results from some epidemiological literature suggesting that sickness absence is a reliable predictor of mortality, the economics literature highlights a possibly significant bias from generous sickness absence provisions in some social security systems: that is, sickness absence would likely be higher in a country with a more generous social security system than in a country with a less generous one, even if actual health were identical. This paper reports how we tried to extract the relevant health information from LFS’s rich sickness absence data. We first defined several health indicators plus one weighted, overall health index. Our first look at these data confirmed the hypothesis of a bias driven by the generosity of social security systems: data from Scandinavian countries indicated significantly worse health indicators than, for instance, eastern European countries, a finding widely believed to be false. In a second step, we adjusted our health indicators by weighting them according to each country’s degree of generosity. While the adjusted indices appeared slightly more plausible than the unadjusted ones, we would at this stage not claim that our proposed method successfully transformed the health information into a valid measure of population health. Assuming that social security incentives differ more between than within countries, we felt far more comfortable using the LFS health data to measure the size and evolution of socioeconomic inequalities in health. We calculated standard concentration indices, using five different proxies – related to educational attainment and occupational categories – for socioeconomic status. Once we decomposed the inequality data series into its trend and seasonal components, we found that health inequalities have been increasing for most but by no means all countries and health indicators. These results do not appear to be sensitive to the various proxies for socioeconomic status we employed. As one might expect, eastern European countries have higher levels of inequality, and western central countries have the lowest levels. We conclude that, while not without problems, the LFS may well add a useful and hitherto unexploited resource for measuring socioeconomic inequalities in health across European countries and over time. Future research should use the LFS data to try to identify and measure the drivers of health inequalities in the region.

1

Eurostat is the statistical office of the European Union and is tasked with providing European level statistics that enable comparisons between countries and regions (Eurostat, 2010).

vi

1.

Introduction

Finding appropriate data on morbidity and ill health (as opposed to mortality) for a large set of European countries is a challenge for researchers, as there are very few data sources providing comparable sets of health indicators. Particularly challenging is finding surveys that combine both relevant health information and socioeconomic indicators in a way that allows analyses of relevant socioeconomic patterns and the determinants or consequences of health. The recent Survey of Health, Ageing and Retirement in Europe (SHARE) is an exception, but it focuses only on the over50 population and to date has had only two rounds. Also available is the European Union Statistics on Income and Living Conditions (EU-SILC), a “new edition” of the European Community Household Panel (ECHP). This dataset represents the entire population of EU countries and provides some (though not very detailed) information on health status as well as reasonable coverage of socioeconomic data. However, due to the recent switch from the ECHP to the EU-SILC format, a discontinuity exists in the survey design as well as the questionnaire, so longitudinal analysis over several years cannot be carried out (yet). Moreover, the ECHP survey was limited to 8 years and covered a maximum of only 15 countries. In this paper we leverage a different and newly available source of survey information: Eurostat’s2 Labour Force Survey (LFS). To the best of our knowledge the LFS dataset has not yet been comprehensively exploited for any health-related purpose. The version of the LFS available for our analyses is a harmonized collection of data coming from all the labour force surveys conducted in the 25 European countries.3 The final result is a huge database with impressive coverage across countries and years: for many countries data are available from 1983 to 2004.4 We believe no other EU-wide survey offers this degree of coverage in terms of both time period and number of countries. The LFS also has a large variety of socioeconomic indicators, although they focus on the labour market.5 The main disadvantage for our purposes is that the information on health is rather limited and mainly relates to a series of dimensions of sickness absence from workplaces or from being employed in the first place.6 Despite the potential drawbacks and in light of the scarcity of cross-country European household surveys that can be used to analyse the socioeconomic aspects of health (or even of health per se), we consider the LFS too promising a source to ignore, even if the health information is limited to the sickness-absence dimension. We also draw comfort from the fact that sickness absence is in fact regularly used in the public health literature as a health proxy (Kivimäki et al., 2003). The fundamental question that arises of course – and that we seek to determine in the present paper – is: what, if anything, can be learnt from the LFS data about health and about the socioeconomic distribution of health? This is a far from trivial issue, since sickness-absence data cannot readily be interpreted as unbiased health information. As the economics literature on the subject amply demonstrates (e.g. Osterkamp and Röhn, 2007; Frick and Malo, 2005; Bonato and Lusinyan, 2004), sickness-absence rates respond sharply to incentives in social security systems and are unlikely to exclusively reflect health aspects: holding other factors constant, in particular the true level of health, the more generous the social protection system, the more likely workers will claim sickness absence. The task then becomes one of purifying the reported sickness-absence data of such distortions. To do so, we constructed a set of health indices taking into account this source of bias. Provided that absenteeism is induced by the generosity of the sickness-leave system, weighting the health indices with a measure of this generosity would at least partly remove the generosity’s spurious effect on the sickness-absence data. This exercise builds on the efforts of other researchers who,

2

Eurostat is the statistical office of the European Union and is tasked with providing European level statistics that enable comparisons between countries and regions (Eurostat, 2010). 3 This includes the 25 countries belonging to the European Union prior to 2007 (EU-25) countries (except the United Kingdom) plus Norway and Iceland. 4 At the time of our analysis, LFS data were available covering up to the year 2004. Very recently, additional survey years, extending up to 2007, became available. 5 Another unique feature of the LFS is that in many countries and years it was carried out more than once a year – a feature that offers opportunities as well as challenges: while in principle it allows for the analysis of seasonal, cyclical patterns that go unnoticed in the standard annual data, it is not immediately clear how to arrive at the “right” annualized value of any given indicator. 6 A further, perhaps minor disadvantage could be that responses to health questions in a survey that is dominated by non-health questions may differ from responses to health questions in a survey primarily seeking health information. Respondents in the former may consider the health questions less important and answer with less attention and effort.

1

without being specifically interested in health, have attempted to measure generosity in a country’s social security system (e.g. Scruggs, 2006). If one or several unbiased and thus comparable health indices can be created in this way, they could say something about health in Europe for a uniquely large set of countries over many years. Taking one step further, it will then also be interesting to look not only at average health comparisons across countries and time, but also at socioeconomic inequalities in health within countries. Bias from generosity in a social security system is likely to be less relevant if one limits measurement of socioeconomic inequalities to individual countries. For this exercise, we followed the methodology proposed by O’Donnel et al. (2008). Increasing work tries to assess the patterns and trends of health inequalities across countries in Europe (Mackenbach et al., 2008), but the degree of comparability over time and between countries in these data may be constrained by their use of data from often different surveys. This problem can be overcome with the help of the LFS data. The paper is organized as follows: in section 2 we review the relevant previous literature on sickness absence. In section 3 we describe LFS, presenting its relevant health questions. We also describe the proposed health indicators that we derived from these questions. In section 4 we provide cross-county tables and figures based on our proposed indicators and compare them with other macro-correlates, e.g. self-reported health from other surveys. The comparison will show that the LFS-based health indicators, if left unchanged, are inadequate for measuring true health. In section 5 we first describe how we attempted to purify the LFS-based health indicators from their assumed bias. We also compare the revised health indicators with the original ones and with the macro-correlates. Section 6 presents results from measuring the socioeconomic inequalities, while section 7 concludes by exploring future research needs and possibilities.

2

2.

Related literature

At least two distinct branches of literature must be considered when trying to interpret sickness-absence data as a proxy for health status: the labour economics literature and the public health literature. Somewhat surprisingly, these branches appear to have largely ignored each other so far. At the risk of over-simplifying, on the one hand the economics literature views and analyses sickness absence exclusively as a reflection of incentives and hardly makes any link between sickness absence and health status (e.g. Ichino and Riphahn, 2005; Rae, 2005; or Holmlund, 2004). In stark contrast, the relevant public health literature exploring sickness absence considers it entirely as a health proxy, worrying little or not at all that sickness-absence data might be distorted by incentives in the social security system (e.g. Kivimäki et al., 2003 or Christensen et al., 2008). Some economics literature provides notable exceptions to the neglect of the health dimension of sickness absence. Bonato and Lusinyan (2004), for instance, tried to compare country-level sickness-absence rates across 18 European countries. While they found that incentives explain a large share of the cross-country variation, they also found a significant conditional role for life expectancy (as a proxy of health) in that countries with higher life expectancies have lower sickness-absence rates.7 More encouraging evidence supporting the potential utility of sickness absence as a health indicator comes from the public health literature. For instance, Kivimäki et al. (2003) showed that the rate of certified sickness absence was an even more powerful predictor of mortality than established self-reported health measures and available medically diagnosed measures of specific conditions. Christiansen et al. (2008) examined the socioeconomic distribution of sickness-absence rates and found gradients similar to those found when using other health variables. In the present paper we seek to combine the insights from both branches. We adopt from the public health literature the aspiration to interpret sickness absence as a potential measure of health, while we adopt from the economics literature the insight that reported sickness-absence rates also reflect factors unrelated to health that must be statistically removed to arrive at the influence of health in sickness-absence figures.

7 Osterkamp and Röhn (2007) also sought to explain cross-country differences in sickness-absence rates in industrial countries but did not consider health as a potential explanatory factor. Frick and Malo (2005) also explored differences in sickness-absence rates across and within European countries, albeit using micro-data. After controlling for institutional factors, they found a significant impact of work-related health problems on sickness absence.

3

3.

Description of the LFS data

The LFS is unique for its cross-country and time coverage. In 1983 Eurostat started collecting LFS microdata from Belgium, Denmark, France, Greece, Ireland, Italy, Luxembourg, and the Netherlands. Data from other countries was collected after their EU entry (e.g. Austria, Sweden and Finland in 1995). Thus, the LFS provides data for 25 EU Member States, plus Norway and Iceland, with some exceptions: data for Germany cover only the period since 2002, and data for Malta and United Kingdom are not available.8 LFS data covering only the first or second quarter of the year are made available for the years 1983 to 1997. Subsequently, data from all quarters have become progressively available. Eurostat maintains that “the degree of comparability of the EU [European Union] Labour Force Survey results is considerably higher than that of any other existing set of statistics on employment or unemployment available for Member States” (Charlier and Franco, 2001). However, comparability over time and across countries remains problematical as any of the following may change: the reference period for a given country, the sampling designs and the order of the questions in the questionnaire. Moreover, since 1998, Member States have not simultaneously transitioned to a continuous, quarterly survey (where the reference weeks are spread uniformly throughout the year). This generates an inevitable break in the time-series statistics for each country, which may further limit comparability. LFS’s main focus is, not surprisingly, the labour market. However, several parts of the questionnaire ask respondents indirectly about their health status. In particular, they are asked for reasons for not working in the reference week, for having worked less than usual, etc., as listed in Table 1. The questionnaire offers to respondents several reasons to explain their answers, such as “own illness, injury or temporary disability”. Based on these variables and building on the work of Campostrini and Bellini (2000), we constructed several health indicators (see Table 2). However, we standardized the indicators by age in order to account for differences in age structure between countries and over time. One way to standardize by age is to sum the age-specific rates, thus constructing an indicator that is similar to the total fertility rate. The formula is: x=65

R=Σrx

(1)

x=15

where R is the final rate, rx is the age-specific rate and x the age. We computed the indicators separately for men and women. Table 2 describes how we defined age-specific rates. The age for all indices is 15–64, since most of them are not relevant for individuals outside working age. We can use each of these indicators separately, or we can use them collectively to construct a synthetic health index. The latter is obtained as a weighted average of some of the indicators. The weights are defined such that more importance is given to indicators that affect a greater proportion of the total population. For instance, those who were not working at the time of the interview but had had a job in the previous eight years may be a small fraction of the population compared to working people. It should be noted that we used only the second permanent inability to work (PIW) indicator (PIW2) to compute the total health limitation index (THLI), since the first cannot be calculated for some years. Also, we did not use the temporary inability to work (TIW) indicator as we found it is much more related to the degree of absenteeism than to health status. One possible limitation of this set of indices, particularly the synthetic one, is that we have no information on the severity of health problems they refer to. We assume that a temporary inability to work may be caused by a cold or flu, whereas a continued reduction of working ability is likely to indicate a more serious health issue, so greater weight should be given to the latter indicator than to the former. However, while this may be plausible, we have no way of testing this assumption. It is also to be borne in mind that we do not really have any other true health indicator that

8

Data on the United Kingdom were made available very recently after the results of a disclosure and therefore were not included in the dataset we analysed.

4

could serve as our benchmark in the present case. One might expect that mortality or life expectancy could serve as a legitimate proxy for true population health, but then again life expectancy varies little between developed countries, while morbidity – our focus here – is (possibly much) less than perfectly correlated with mortality. Thus, the question remains of what the best benchmark would be.

Table 1. LFS questions relating to health issues Question Reference population Reason for not having worked at all though having a job Working population Main reason for hours actually worked during the reference Working population week being different from the person’s usual hours Main reason for leaving last job or business Inactive population with a job episode ended at most 8 years before interview Main reason for not being available to start working within Inactive population two weeks if work were found now Main reason for working part-time Part-time working population Main reason for not seeking employment during previous four Inactive population weeks

Table 2. Health indicators defined on the basis of LFS health questions Indicator Temporary inability to work (TIW): not working in the reference week due to illness, injury or temporary disability Temporary reduction in working ability (TRWA): absenteeism due to illness, injury or temporary disability Continued reduction in working ability (CRWA): part-time work due to illness, injury or temporary disability Exclusion from active population (EAP): retirement due to illness, injury or temporary disability Permanent inability to work (PIW1): not seeking a job due to illness, injury or temporary disability Permanent inability to work (PIW2): not seeking a job due to illness, injury or temporary disability

Numerator Number of persons who did not work in the reference week, despite having a job, because of health problems Number of persons who worked less than usual due to illness, injury or temporarily disability Number of persons who work part-time due to illness, injury or temporarily disability Number of persons who left their last job because of health problems

Denominator Number of persons having a job

Number of persons having a job

Number of persons having a job

Number of not-working people who had a job in the previous 8 years

Number of persons not working and not Number of not-working people seeking a job because of own illness or disability Number of persons not working and not Number of not-working people available to start working immediately because of own illness or incapacity

Note: All indicators are age-specific. The overall index was then calculated using formula (1).

5

4.

A first look at our data

This section provides cross-country tables and figures on our proposed indicators and compares them with other macrocorrelates. This attempt to use the LFS-based indicators to measure true health proves disappointing but provides a basis for understanding our second look at these data, which proves more promising.

Table 3. Health limitation indices (standardized by age) for European countries, men, 2004 Country Greece Ireland Slovenia Italy France Lithuania Slovakia Portugal Netherlands Germany Spain Belgium Finland Estonia Sweden Latvia Denmark Czech Republic Austria Poland Norway Hungary Cyprus Iceland Luxembourg

TIW 0.007 0.152 0.262 0.131 0.329 0.048 0.103 0.187 0.273 0.159 0.301 0.334 0.27 0.102 0.497 0.062 0.208 0.35 0.126 0.179 0.51 0.173 0.189 0.129 0.197

TRWA 0.006 0.021 0.082 0.049 0.041 0.003 0.013 0.018 0.098 0.024 0.021 0.048 0.055 0.011 0.175 0.018 0.087 0.022 0.028 0.01 0.109 0.012 0.067 0.058 0.002

CRWA 0.008 0.026 0 0.028 0.04 0.052 0.07 0.094 0.048 0.04 0.009 0.035 0.023 0.049 0.192 0.057 0.056 0.075 0.036 0.188 0.134 0.09 0.067 0 0.015

EAP 0.947 1.722 0.697 0.637 0.837 1.553 0.926 1.563 1.506 1.036 1.554 1.548 1.469 1.732 0.62 1.661 1.301 2.065 1.844 1.414 3.418 2.138 2.307 2.708 2.018

PIW2 0.185 0.014 0.162 0.269 0.14 0.234 0.173 0.07 0.023 0.704 0.608 0.319 0.308 0.317 0 0.683 0.303 1.286 1.64 0.542 1.184 1.581 0.557 0.111 NA

THLI 0.118 0.127 0.153 0.174 0.204 0.242 0.247 0.26 0.274 0.301 0.314 0.327 0.334 0.351 0.363 0.365 0.372 0.438 0.47 0.479 0.505 0.561 NA NA NA

Note: Rows are ordered by THLI score, from lowest to highest.

With seven health indicators for 25 countries, separated into males and females, for many years, we ask the reader to forgive us for not displaying all possible tables in the body of this report, relegating most to Annex 1. Tables 3 (men) and 4 (women) show the values of the indices for 2004. Fig. 1–7 present graphs illustrating trends over time for each indicator by gender for what we consider a representative subset of countries. We chose Italy to represent Mediterranean countries, France the western-central countries, Sweden the Scandinavian ones, Lithuania the eastern European ones, and Belgium and the Netherlands the central European ones. Our selection was influenced by the fact that these countries have relatively good quality data (e.g. Germany was not chosen because its data cover only 2004). Fig. 1 shows the trend for the TIW index for our sample of countries.

6

Table 4. Health limitation indices (standardized by age) for European countries, women, 2004 Country Greece Slovenia Ireland Lithuania Italy Spain Luxembourg Slovakia France Germany Belgium Estonia Latvia Portugal Finland Austria Netherlands Poland Czech Republic Hungary Denmark Sweden Norway Cyprus Iceland

TIW 0.006 0.247 0.136 0.048 0.113 0.248 0.184 0.092 0.31 0.135 0.273 0.055 0.044 0.153 0.246 0.118 0.253 0.16 0.317 0.167 0.191 0.446 0.45 0.169 0.1

TRWA 0.005 0.31 0.033 0.148 0 0.196 0.017 0.038 0.029 0.031 0.007 0.008 0.08 0.089 0.016 0.01 0.023 0.031 0.018 0.104 0.024 0.089 0.036

CRWA 0.009 0 0.015 0.029 0.069 0.01 0.047 0.068 0.15 0.083 0.099 0.041 0.038 0.16 0.034 0.066 0.108 0.245 0.124 0.1 0.094 0.35 0.137 0.078 0

EAP 0.495 0.29 1.273 1.073 0.572 0.8 1.214 0.806 0.757 0.808 1.292 1.212 0.636 1.373 1.049 1.155 1.878 1.054 1.311 1.764 1.515 0.866 3.876 1.141 2.969

PIW2 0.098 0.052 0.035 0.029 0.279 0.328 0.983 0.14 0.155 0.615 0.183 0.209 0.563 0.159 0.217 0.919 0.094 0.514 0.899 1.577 0.277 0 1.086 0.531 0.093

THLI 0.069 0.091 0.092 0.165 0.181 0.214 0.232 0.246 0.262 0.266 0.27 0.274 0.292 0.31 0.316 0.383 0.402 0.447 0.491 0.501 0.511 0.607 0.667 NA NA

Note: Rows are ordered by THLI score, from lowest to highest.

Interestingly, the TIW index shows some counter-intuitive patterns over time and across countries. First, it might seem odd that the index is higher (and hence the health status lower) in the Netherlands and Sweden than in Lithuania – an issue we return to below in “a second look at the data”. Second, one might expect – on the basis of overall mortality trends and assuming a positive (if imperfect) correlation between mortality and non-fatal illness – that ill health prevalence has decreased (and hence health improved) throughout the period. However, for some countries, such as Belgium and Sweden, TIW increased, whereas it decreased for the Netherlands and Lithuania, and remained roughly stable for other countries. It should be borne in mind that the TIW index measures the short-term prevalence of sickness absence. In most TIW cases, the health issues generating absence from work are of ordinary nature (e.g. influenza, colds). Such relatively common and generally far from life-threatening diseases are unlikely to be closely related to mortality, so this counter-intuitive and mixed-trend picture may be less surprising than at first glance. A third, no less surprising feature of Fig. 1 is the much-increased fluctuation of the trend, starting around the year 2000, in those countries that switched to subannual data reporting. This suggests a seasonal fluctuation in health status (as in indicators of economic activity) that goes completely unnoticed in the commonly used annual data. The precise nature and explanation of this seasonality is recommended for future research below. The same pattern applies to the TRWA index (Fig. 2), which measures a temporary reduction of working hours for health reasons. Prevalence is lower than TIW, but we still observe that the Netherlands and Sweden lines dominate the others. The Netherlands line is on the same level as those of other countries until 1992, after which its TRWA index

7

suddenly rises and drops again9 to approximately the same level as Belgium, Italy and France. Sweden, on the other hand, is constantly far higher than the other countries. (The LFS does not cover France until 1999.) Also, the TRWA index figures show a gender difference, with men’s prevalence averaging less than women’s, a difference that did not appear in the TIW index (Fig. 1).

Fig. 1. TIW index (standardized by age) for representative European countries

1.0

Men Italy France Sweden Lithuania Belgium Netherlands

0.0

0.0

0.2

0.2

Health Index 0.4 0.6

0.8

Italy France Sweden Lithuania Belgium Netherlands


0.8

1.0

Women

1985

1990

1995 Year

2000

2005

1985

1990

1995 Year

2000

2005

2000

2005

Fig. 2. TRWA index (standardized by age) for representative European countries

Men 1.0 0.0

0.2

0.2 0.0 1985

9



0.8



0.8

1.0

Women

1990

1995 Year

2000

2005

1985

1990

1995 Year

This rise and drop are likely the effects of a structural changes in the survey design and/or the questionnaire.

8

The CRWA index measures continued reduction in the ability to work, i.e., the prevalence of people working only parttime due to health problems. We might expect that the health problems that force people to permanently reduce their working time would be more serious and less frequent than those forcing a temporary absence (TIW) or a temporary reduction in working hours (TRWA). As expected, the level of CRWA is lower than those of TIW and TRWA. Yet again, the Sweden and the Netherlands lines are far higher than the others. However, part-time jobs are much more supported in the Netherlands and Scandinavian countries than in the rest of the EU, which may help explain the gap as in the case of the temporary health indicators.

Fig. 3. CRWA index (standardized by age) for representative European countries

Men 0.5



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Fig. 4 reports the trends in the EAP index, capturing those who retired because of illness, injury or temporary disability. In principle, one would expect that the prevalence of health problems causing this level of work reduction would be even lower than those measured by TIW, TRWA and CRWA. In practice, the index is far higher than the others. This is because the denominator of the EAP index is different from that of other indices and in some cases can be very small. We also note that the EAP index is extremely variable. Italy, for example, experienced a substantial drop in 1992, probably the result of pension reform implemented that year. Here, Sweden has approximately the same level as France and Lithuania, with a peak in 2000–2001, whereas the Netherlands has the highest proportion of people retired due to health issues. The PIW1 index (not seeking a job due to illness, injury or temporary disability) also fluctuates considerably (see, for example, the line for Belgium) and is, therefore, difficult to interpret (Fig. 5). Moreover, the data for this index are unavailable until 1992. Given these shortcomings, we did not use this index in creating the THLI. Instead, we used the second version of PIW (PIW2), which is far less variable, available for all years, and based on respondents’ declared availability to start a job were it found quickly. Apart from a strange rise and fall for Belgium, the PIW2 lines are much more stable (Fig. 6). The PIW2 shows an increasing trend, particularly in France, but the level is quite low, so this index has little influence on the THLI.

9

Fig. 4. EAP index (standardized by age) for representative European countries

Men 2.5


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Finally, we look in Fig. 7 at the THLI, a weighted average of TIW, TRWA, CRWA, EAP and PIW2; each index’s weight is proportional to the population share on which the indicator is defined.

10


Men Italy France Sweden Lithuania Belgium Netherlands

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Fig. 7. THLI (standardized by age) for representative European countries

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Do the numbers represented in Fig. 1–7 present an accurate picture of adult health status, especially of morbidity? This is of course hard to judge without a comparable objective morbidity measure. It is, however, disconcerting to see how consistently the Scandinavian countries, which are generally at the top of international health rankings, fare worse than even the new EU countries in eastern Europe, which generally exhibit unexceptional health performance (see also Tables 3 and 4). One way of assessing the usefulness of these data as health proxy would be to compare them to self-reported health data from other surveys, in particular those reporting chronic disease. As a benchmark for such

11

comparison, we selected information on adults (aged 18+) who have any long-standing illness or disability that limits their activities in any way, as provided by the European Quality of Life Survey 2003.10 Fig. 8 shows that, while a significant positive correlation exists between the THLI and self-reported chronic illness, the correlation is rather low. The correlation is even lower when we compare the THLI with mortality indicators, such as the log of the standardized mortality ratio (Fig. 9) or the log of life expectancy at age 15 (Fig. 10). These comparisons make us suspect that, as proposed by the economics literature on the issue of sickness absence, factors other than social security generosity and ill health influence how people use or report sickness absence. (Of course self-reported chronic illness is also not a genuine benchmark of ill health here, as we do not know how much bias underlies those numbers. However, despite the well-documented existence of bias in self-reported health measures, these indicators have nevertheless been shown to be very reliable predictors of mortality (Ferraro and Farmer, 1999).) Interestingly, men show a lower correlation between the THLI and other health proxies used in Fig. 8–10, so if there is a bias, it could be particularly pronounced among men, perhaps because they are more active in the labour market and therefore more exposed to the incentives embedded in social security.

Fig. 8. Scatter plots of THLI and prevalence of self-reported chronic illness

Men R-squared = 0.204 Intercept = 0.145 (0.081) HU Slope = 0.006 (0.003)

DK HU NL FI LV

PT EE BEDE FR

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DK ES

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15 20 25 30 35 Self-reported chronic illness

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R-squared = 0.134 Intercept = 0.137 (0.104) Slope = 0.006 (0.004)

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15 20 25 30 35 Self-reported chronic illness

40

Note: Abbreviations represent the following countries: AT is Austria; BE is Belgium; DE is Germany; DK is Denmark; EE is Estonia; ES is Spain; FI is Finland; FR is France; GR is Greece; HU is Hungary; IR is Ireland; IT is Italy; LT is Lithuania; LV is Latvia; NL is the Netherlands; NO is Norway; PL is Poland; PT is Portugal; SE is Sweden; and SI is Slovenia.

As noted earlier, the literature suggests a systematic bias in data related to sickness absence. Part of the evidence comes precisely from Sweden, where welfare is recognized to be more generous than in other countries (e.g. Henrekson and Persson, 2004; Johansson and Palme, 2002). Northern European countries in general are known to have generous welfare systems, including sick-leave policies, and this may provide an explanation for the results exposed above. Using timeseries data, Henrekson and Persson (2004) found that Sweden’s reforms that entailed more generous compensation for sick leave tended to be associated with permanent increases in total sick leave granted per person employed and vice versa.

10

This survey is owned by the European Foundation for the Improvement of Living and Working Conditions. For more details see http://www. eurofound.europa.eu/areas/qualityoflife/eqls/2003/eqls.htm, accessed 15 July 2010.

12

Fig. 9. Scatter plots of THLI and log of standardized mortality ratio

Men

Women NO

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IT IR

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R-squared = 0.005 SI Intercept = 0.095 (0.79) Slope = 0.04 (0.145)

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LT R-squared = 0.055 SI Intercept = -0.079 (0.426) Slope = 0.064 (0.068)

IR GR

5.2 5.4 5.6 5.8 6.0 Log Standardised Mortality Ratio (25-64)

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Fig. 10. Scatter plots of THLI and log of life expectancy at 15

Men HU 0.5

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NL PT

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R-squared = 0.002 Intercept = -0.578 (5.6) Slope = 0.213 (1.335)

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FR R-squared = 0.051 SI Intercept = 1.97 (1.835) Slope = -0.405 (0.45) 3.95

IR

4.00 4.05 4.10 Log life expentancy at 15

GR 4.15

5.

A second look at our data

The descriptive analysis above clearly shows that the indicators we defined need to be “purified” somehow. Having the Scandinavian countries display fairly high sickness-absence rates particularly confirms this belief in light of other very favourable health indicators from those countries. As we argued before, this finding of high sickness-absence rates is likely to be a spurious effect of a greater degree of absenteeism among countries that is likely driven by more generous sick-leave packages. If we could measure this degree of generosity, we would expect to be able to remove its spurious effect. (Since we focus only on eliminating this specific bias, we cannot be certain that we have eliminated any other possible bias.) Measuring the degree of generosity in a social security system is fraught with difficulties. It has often been measured by the level of social expenditure, ignoring some of the more subtle incentives provided in relevant legislation. Fortunately, we have a body of literature that has already attempted to measure what is not easily measurable. Osterkamp and Röhn (2007) defined a “generosity index” as an unweighted sum of seven variables on sick leave: waiting period, self-certification, total maximum duration of payment, employer maximum duration of payment, employer amount of payment, sickness fund amount of payment, and external proof. Not surprisingly, these authors found that Sweden and Norway had the highest levels of generosity, confirming our argument. However, their information is not entirely sufficient for our purposes: the index was calculated only for a small number of countries and only for the period 1996–2002. Scruggs (2006) defined a broader generosity index that took into account income replacement rate (including sickness replacement rate), social insurance coverage and recipients. This author calculated an index of “expected welfare benefit” as the product of the replacement rate and the coverage rate summed over three programmes (unemployment, sickness and pensions). Scruggs did this for 18 countries of the Organisation for Economic Co-operation and Development for each year from 1972 to 2002, so this index is a good candidate for purifying our health indices, but it does not cover all the countries and years in the LFS dataset. Therefore, we tried to impute the missing values of the generosity index by using a reasonable set of proxies, as follows: the Eurostat database offers some information on country “public expenditure on labour market policies”. In particular, three types of expenditure are potentially useful proxies of welfare generosity: (1) “labour market services”, which includes all interventions where participants’ main activity is job-search related; (2) “out-of-work income and maintenance and support” refers to interventions providing financial assistance to individuals who, for different reasons, are not working temporarily or permanently; and (3) “early retirement” refers to interventions supporting people who retire early. Table 5 shows our results from a non-linear regression between the Scruggs’s generosity index and these variables. The fit is not perfect but satisfactory (R-squared is 0.71), so the parameters estimated can be used with some degree of confidence to impute the value of the generosity index where it is missing.11 After having calculated the generosity index for all countries and years, we used it to weigh the indices defined above: countries with a high level of generosity are given an (inversely proportional) small weight, while countries with a low level of generosity are given a high weight. In order to see how the weights affected the indices, we report in Fig. 11 the trend of one (THLI for men) before and after weighting, for the same countries considered in Fig. 1–7. The graphs clearly document that the health limitation was overestimated in Sweden and the Netherlands because of generosity in the welfare system and underestimated in Italy because of its comparatively less-developed welfare system. The weights barely affected the France, Belgium and Lithuania indices. Note that even after the indices are weighted, Scandinavian countries still have the highest levels of sickness. This might suggest that we have not fully removed the spurious effect of generosity from the indices. Once again, though, in the absence of an objective benchmark, it remains hard to know what the true level of the health index should be.

11

The fit is rather good with the exception of eastern European countries, for which the predicted value of the generosity index is sensibly larger than the original value (when it is available). Therefore, we rescaled the predicted values in order to have an index whose magnitude is consistent with Scruggs’s original index.

14

Table 5. Results of generalized additive model for generosity index Variable (Intercept) Out of work, node 1 Out of work, node 2 Out of work, node 3 Early retirement, node 1 Early retirement, node 2 Early retirement, node 3 Year

Estimate -148.192 -111.094 23.638 -44.012 1.924 -22.831 -2.175 0.1079

Std. Error 100.821 13.291 3.09681 8.637 4.310 3.534 2.045 0.0506

t value -1.470 -8.358 7.633 -5.096 0.447 -6.460 -1.064 2.135

Pr (>|t|) 0.144 0.000*** 0.000*** 0.000*** 0.656 0.000*** 0.289 0.035*

Note: *** indicates significance at 1% level, * indicates significance at 10% level.

Another interesting feature we noticed in the unweighted indices was the increasing trend over time for some countries (Belgium and Sweden). For France, this feature is even reinforced after weighting, with the new index increasing over time (meaning that health had deteriorated), whereas the sickness level is approximately constant in Italy and Lithuania. The Netherlands has a first phase when the trend increases and a second when it decreases slightly. It appears difficult, if not impossible, to reconcile those trends, whether in their corrected or uncorrected version, with trends in mortality-based indicators in those countries, most of which would point towards a steady improvement. While this does not necessarily suggest that the LFS-based indicators are poor health proxies, it does no doubt raise concerns and calls for further investigation.

A comment on data seasonality A common characteristic of Fig. 1–8 is the marked fluctuation of the health indices for all countries, starting in 1998, when data became available for all quarters, allowing us to measure subannual variation. In order to better understand both what the actual trend was and what precise pattern of seasonality was at work, the actual observed time series can be decomposed into (1) its long-term trend and (2) its seasonal component.12 This is illustrated in Fig. 12 for the example of Italy, using the overall health index, THLI. Fig. 12’s first panel shows the actual time series data; the second shows the “de-seasoned” trend; and the third shows the seasonal component only. It turns out that after having been de-seasoned, the time series trend is clearly descending, indicating an increasing health improvement over time, if health is correctly measured by the THLI. The seasonality has the following nature: the THLI is higher in the first and last quarters (measured in the 7th and the 46th weeks of the year) and lower in the other quarters (the 20th and the 33rd weeks). It may not be surprising to see a (cyclical) decline in health in winter and improvement in summer. This also broadly follows the typical subannual variation in economic activity (which declines in winter and improves in spring and summer), but it may well have to do with the climate’s seasonal variation rather than national economic cycles. Some economics literature has examined how health responds to economic cycles (e.g. Ruhm, 2000), using, however, only annual data. The counter-intuitive, but fairly consistent finding from that literature is that health improves during economic downturns and deteriorates during booms. We can only note that at least in the case depicted in Fig. 12, our findings at the subannual level contradict those previous findings. It is, however, beyond the scope of this paper to explore this point in detail. Suffice it to note that on preliminary inspection the seasonal pattern does vary by health indicator and by country, recommending more research.

12

The decomposition was done assuming an additive model with a quadratic specification of the trend component. Moreover, from the time series available, we used data only until 2003, because for Italy the THLI shifted in 2004 (see Fig. 7), which would have confounded the trend estimation. (This shift is probably due to the fact that in 2004 the LFS data collection in Italy changed dramatically: from a quarterly to a continuous survey. Other changes [e.g. from computer-assisted personal interviewing to computer-assisted telephone interviewing] may have caused or affected the shift.)

15

Fig. 11. THLI before and after weighting with the inverse of generosity score, men, six countries

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Fig. 12. Decomposition of THLI time series, Italy, men

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17

6.

Socioeconomic inequalities in health

We are also interested in knowing what can be said on socioeconomic inequalities in health within countries on the basis of the LFS data. The issue of health inequality is increasingly a concern both in industrialized and developing countries (Marmot, 2005). Arguably, the issue of bias generated by a country’s social security system that we had to grapple with (without overwhelming success) in the previous section is less relevant when measuring socioeconomic inequalities within a given country. More specifically, the two major questions are the following. (1) Which countries have the highest inequality levels (and which ones the lowest)? (2) Has inequality increased in the last few years, as some research suggests?13 Following guidelines from O’Donnel et al. (2008) for measuring socioeconomic inequalities in health, we constructed a health inequality index using the following formula: n

ν ν-1 C(ν) = 1- — nμ Σhi(1-Ri)

(2)

i=1

where C is the measure of inequality or concentration index, n is the sample size, hi is the ill health indicator for individual i, μ is the mean level of ill health, and Ri is the fractional rank in the living standard distribution of individual i. This index is an extended version of the concentration index, the latter being twice the area between the concentration curve and the line of equity. Conventionally, the index is constructed so that it takes a negative value when ill health is disproportionately concentrated among the poor. The parameter ν is an inequality-aversion parameter; when ν=2 we have an ordinary concentration index. Therefore, we needed an appropriate indicator of living standard in order to calculate the concentration index in formula (2). Unfortunately, the LFS does not give us income variables, and we also do not have other asset indicators. We do, however, have different versions of educational attainment (following the classification of the International Standard Classification of Education (ISCED)14) and occupational status that we can use in measuring socioeconomic status (SES). Since the size and evolution of health inequalities results may well be sensitive to the well-being proxy used in the index calculations, we try to check the robustness of our main findings through the application of different SES indicators. While the use of the available education variable is fairly straightforward in that it follows an obvious ordinal pattern, occupational status is less easily converted into an ordinal well-being indicator. In order to use occupational category as a proxy of well-being, we transformed it into an ordinal variable. There are three possible choices of ordinal transformation of categories of International Standard Classification of Occupations (ISCO), namely, International Socio-Economic Index of Occupational Status (ISEI), Standard International Occupational Prestige Scale (SIOPS) and (Erikson and Goldthorpe’s class categories (EGP). SIOPS is a prestige measure of occupational status, generated from the popular evaluation of occupational standing; ISEI comes as a socioeconomic scale, created by computing a weighted sum of the socioeconomic characteristics (usually education and income) of each position; EGP differs from the previous two because of its discrete nature (SIOPS and ISEI are scores; EGP is a classification with 11 ordered categories). We use the scales calculated by Ganzeboom and Treiman (1996). Overall, we measured socioeconomic health inequalities with five possible proxies of well-being, two based on education (ISCED1D and ISCED2D classification) and three based on occupation (EGP, SIOPS and ISEI). In order to avoid an excessively long paper, we focus on the EGP-based results, knowing that – as we have tested – SIOPS and ISEI produce perfectly consistent results. Similarly, the results we obtained for EGP indices are consistent with those obtained using education as a proxy of well-being. 13

See e.g. Mackenbach (2006). ISCED is an international classification standard of education created by the United Nations Educational, Scientific and Cultural Organization (UNESCO). Several levels of ISCED classification have been generated, and the higher the level, the more detailed the classification. The LFS gives us ISCED1D classification (with three categories, “low”, “medium” and “high”) and ISCED2D classification (with six categories).

14

18

Tables 6 (for men) and 7 (for women) answer the first question – Where are the biggest (or smallest) health inequalities? – focusing on four LFS-based health indicators (TIW, CRWA, TRWA and THLI).15 From this ranking we cannot draw a straightforward geographic pattern: many eastern European countries show a high inequality, but the highest is in Portugal. The level of health inequality in Finland, furthermore, is close to that of Estonia. The lowest inequality levels are in Belgium and Austria. Luxembourg, by contrast, has one of the highest inequality levels. Interestingly, the ranking of women is a bit different from that of men. Luxembourg, for instance, has a relatively low level of inequality among the women compared to men.

Table 6. Inequality of several health indices in European countries, men, second quarter, 2004 Country Portugal Slovakia Poland Luxembourg Estonia Finland France Lithuania Sweden Germany Czech Republic Denmark Slovenia Italy Latvia Ireland Greece Hungary Norway Netherlands Spain Austria Belgium Cyprus Iceland

TIW -0.183 -0.354 -0.195 -0.473 -0.311 -0.531 -0.255 -0.389 -0.236 -0.186 -0.081 -0.480 0.046 -0.189 -0.199 -0.178 -0.007 -0.186 -0.334 -0.199 -0.133 -0.298 -0.253 -0.608 -0.362

TRWA -0.673 -0.188 -0.418 -0.840 -1.306 -0.308 -0.293 0.663 -0.270 -0.124 -0.453 0.076 -0.232 -0.114 -0.628 -0.147 -0.202 -0.190 -0.145 -0.042 -0.070 -0.107 -0.171 -0.133 -0.450

CRWA -0.738 -0.487 -0.462 -0.315 -0.090 -0.410 -0.282 -0.315 -0.241 -0.425 -0.234 -0.432 0 -0.400 -0.098 -0.108 -0.173 -0.150 -0.237 -0.373 -0.005 -0.011 0.231 -0.213 0

THLI -0.695 -0.492 -0.438 -0.402 -0.394 -0.325 -0.323 -0.315 -0.297 -0.263 -0.234 -0.229 -0.227 -0.194 -0.188 -0.182 -0.180 -0.152 -0.114 -0.101 -0.079 -0.037 0.023 NA NA

Note: Rows are sorted by inequality rank in THLI, from most inequality to least.

Fig. 13 attempts to answer the second question – How have health inequalities evolved over time? – by looking at the example of Italy for all six health indicators. While the overall trend in the health inequality indices appears to be decreasing (implying that the concentration of ill health among the poorest increased between 199316 and 2004), it is almost impossible to distil the time trend upon mere visual inspection due to the very marked fluctuations, which again start when the survey data are available at subannual intervals.

15 16

Annex 2 has the other health indicators. The inequality index cannot be calculated for the years 1983–1992 because the proxies of well-being are not reported.

19

Table 7. Inequality of several health indices in European countries, women, second quarter, 2004 Country Lithuania Estonia Poland Slovakia Portugal Hungary Italy Spain Czech Republic Finland Ireland France Norway Slovenia Greece Sweden Denmark Latvia Luxembourg Netherlands Austria Germany Belgium Cyprus Iceland

TIW 0.069 -0.618 0.133 -0.084 -0.106 -0.230 -0.239 -0.125 -0.170 -0.336 -0.112 -0.165 -0.045 0.040 -0.301 -0.203 -0.086 -0.258 -0.337 -0.077 0.059 -0.024 -0.111 0.092 0.013

TRWA NA -1.275 -0.317 -0.229 -0.191 -0.151 -0.203 -0.186 -0.269 -0.225 0.169 -0.137 -0.101 -0.176 -0.074 -0.043 -0.259 -0.538 0.511 0.080 0.227 0.270 0.256 -0.156 -0.202

CRWA -0.962 -0.750 -0.527 -0.60 -0.655 -0.333 -0.334 -0.307 -0.315 -0.370 -0.346 -0.238 -0.307 0 -0.424 -0.340 -0.013 0.454 -0.180 -0.241 -0.085 -0.161 -0.029 -0.304 0

THLI -0.962 -0.779 -0.494 -0.441 -0.377 -0.356 -0.320 -0.301 -0.275 -0.238 -0.214 -0.182 -0.180 -0.176 -0.170 -0.147 -0.109 -0.095 -0.046 -0.018 0.011 0.021 0.106 NA NA

Note: Rows are sorted by inequality rank in THLI, from most inequality to least.

Hence, not only the average health indices, but even the distribution of the health indicators within a country shows a seasonal pattern. To be better able to detect the trend as well as the shape of the seasonal pattern, we again performed a decomposition analysis. Fig. 14 illustrates the decomposition of CRWA indices for Italy. It turns out that health inequalities have on average been increasing for men. For women the pattern is less straightforward: the line rises (indicating that health inequality decreases) until 2001 and falls thereafter. The seasonality component seems to indicate that during one year, the highest level of inequality occurred in the second quarter (on average in the fourteenth week) for both sexes. Interestingly, this does not correspond to the quarter when seasonality is at the highest level for the average of the CRWA index (which is the first one, when the seasonality of inequality is at the lowest level). Thus, there is no straightforward link between average health seasonality and health inequality seasonality. This implies that the health responses to the seasonal cycle differ by socioeconomic group. This again points to a potential parallel to the above-mentioned literature that used annual data to look at the association between business cycles and health. While the literature generally only looks at how average population health responds to either economic up- or down-turns, some papers have tried to shed light on the distributional health effects of those cycles (e.g. Kondo et al., 2008; Edwards, 2008; Valkonen et al., 2000). This (rather scarce) literature tends to confirm the differential health response across socioeconomic groups.

20

Fig. 13. Health inequality index, Italy Men (standardized by age) 1.0

1.0

Women (standardized by age)

TIW CRWA TRWA PIW2 THLI

Health Inequality 0.0 - 1.0

- 1.0

- 0.5

- 0.5

Health Inequality 0.0

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TIW CRWA TRWA PIW2 THLI

1995

2000 Year

2005

1995

2000 Year

2005

Importantly, the other countries do not replicate the pattern found for CRWA in Italy. While it would be interesting to analyse with more depth all the seasonal components of all countries for all health indicators, doing so would be beyond the scope of this paper.

Trade-offs between average health and health inequalities? Thus far we have looked separately at average health and its distribution. There is, however, reason to believe that a trade-off may exist between health and its distribution (Bommier and Stecklov, 2002). Understanding this phenomenon is important when considering what policy objectives to set in any given country. If a trade-off exists, difficult decisions will have to be made on how the two worthwhile objectives of improving average population health and reducing health inequalities will be balanced (Wagstaff, 2002).

21

-0.1 -0.5

Data

Fig. 14. Decomposition of CRWA inequality time series, Italy

1998

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Women Men

Fig. 15 is a scatter plot comparing the average level of purified TRWA with its inequality index. Given the way the health indicator and the inequality index are defined – the higher the TRWA, the lower the health, and the higher the inequality index, the more pro-poor the distribution – we would expect to see a positive linear relationship if a trade-off indeed exists. This example does not overwhelmingly confirm such relationship: the trade-off is not widely confirmed, but we do notice a slight, positive correlation between the two measures.17 However, it should be borne in mind that this pattern is not stable across the different health indicators used here. For other indices, such as the TIW and CRWA, the trade-off between average level of health and inequality is even harder to detect. The same applies to THLI, for which the relationship between average health level and inequality is not clear-cut. Taken literally, this suggests that there may not be too much of a trade-off between average health and the distribution of health. Hence, there may be ways for countries to simultaneously achieve both an improvement in average health and a reduction in health inequalities. One might be tempted to conclude from these findings that it is possible to 17

The lowest regression line was drawn with the exclusion of two outliers: Lithuania and Sweden.

22

reconcile a good average level of health with low inequality: the two do not appear to be opposed to each other. We caution, however, against a too literal interpretation of this possibility in light of the severe doubts about the extent to which the average level of the health indicators is a reliable proxy of true health.

0.15

Fig. 15. Average level and inequality index of TRWA in European countries, second quarter, 2004

TRWA: average level 0.05 0.10

SE

SI

IT FI FR BE PT LV

0.00

NO NL DK

EE

CZ PL

LU - 1.0

AT

DE IE SK ES HU GR

-0.5 0.0 TRWA: inequality index

LT 0.5

Note: Abbreviations represent the following countries: AT is Austria; BE is Belgium; CZ is the Czech Republic; DE is Germany; DK is Denmark; EE is Estonia; ES is Spain; FI is Finalnd; FR is France; GR is Greece; HU is Hungary; IE is Ireland; IT is Italy; LT is Lithuania; LU is Luxembourg; LV is Latvia; NL is the Netherlands; NO is Norway; PL is Poland; PT is Portugal; SE is Sweden; SI is Slovenia; and SK is Slovakia.

23

7.

Concluding remarks

The present work was primarily explorative in nature. Our intention was to determine the utility of a major Europeanwide household survey, hitherto unexploited by health researchers, to measure health as well as socioeconomic inequalities in health. Judging whether the resulting health data are indeed reliable proxies for true health is of course compromised by the problem that true health is unobservable. The health information from the LFS is limited in that it considers health only as a reason for different dimensions of “less than normal” labour supply or labour market participation. The epidemiological literature had shown, on the basis of other survey data, that this kind of sicknessabsence-related data may after all be a good predictor of later mortality. On the other hand, the economics literature pointed to a strong bias in sickness-absence data in response to the incentives embedded in countries’ social security systems. We thus had to “purify” the LFS health information by each country’s degree of generosity. Nevertheless, while the corrected values appeared slightly more “plausible” than the uncorrected ones, we would at this stage not argue that our proposed method has successfully transformed the health information into a valid measure of countries’ average population health. Assuming that the incentives embedded in any social security system differ more between than within countries, we felt far more comfortable in using the health data to measure the size and evolution of socioeconomic inequalities in health. We calculated standard concentration indices, using five different proxies – based on educational attainment and occupational categories – for socioeconomic status. Our results were broadly robust to the different SES proxies, both in terms of the size of inequalities and in terms of trends. Once we decomposed the inequality data series into its trend and seasonal components, it became clear that overall, for most countries and most health indicators, health inequalities have been increasing, a result that confirms other recent research (Mackenbach, 2006). In contrast to earlier research, however, we based our conclusions on a significantly larger sample for a longer period of time. Given the chiefly exploratory nature of our analysis, we have probably raised more questions than we have answered. There remains significant scope to explain the pattern and trends in the average health indicators we have employed. We were particularly surprised to see rather pronounced fluctuations in both health and health inequalities for essentially all health indicators and years as soon as the survey data became available at subannual intervals. Not least, further research should also seek to decompose the pattern and trends in health inequality into its drivers.

24

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Mackenbach JP (2006). Health inqualities: Europe in profile. Rotterdam: Erasmus Medical Centre Rotterdam. Mackenbach JP et al. (2008). Socioeconomic inequalities in health in 22 European countries. New England Journal of Medicine, 23:2468–2481. Marmot M (2005). Social determinants of health inequalities. Lancet, 365:1099–1104. O’Donnel O et al. (2008). Analysing Health Equity Using Household Survey Data: A Guide to Techniques and Their Implementation. Washington DC, World Bank (World Bank Institute Learning Resources Series). Osterkamp R, Röhn O (2007). Being on sick leave: possible explanations for differences of sick-leave days across countries. CESifo Economic Studies, 53(1):97–114. Rae D (2005). How to Reduce Sickness Absences in Sweden: Lessons from International Experience. Paris, OECD Economics Department (Working Paper ECO/WKP(2005)29). Ruhm C (2000). Are recessions good for your health? Quarterly Journal of Economics, 115:617–650. Scruggs L (2006). The generosity of social insurance, 1971–2002. Oxford Review of Economic Policy, 22(3):349– 364. Valkonen T et al. (2000). Changes in socioeconomic inequalities in mortality during an economic boom and recession among middle-aged men and women in Finland. European Journal of Public Health, 10:274–280. Wagstaff A (2002). Inequality aversion, health inequalities and health achievement. Journal of Health Economics, 21(4):627–641.

26

Annex 1. Average health indices by country and sex

Table 1. Health indices, Austria, men Year 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.252 0.243 0.227 0.211 0.246 NA NA NA 0.186 0.059 NA NA 0.251 NA NA NA 0.311 NA NA NA 0.277 0.187 NA NA 0.270 0.162 0.173 0.250

CRWA 0.049 0.086 0.056 0.029 0.022 NA NA NA 0.018 0.015 NA NA 0.019 NA NA NA 0.020 NA NA NA 0.043 0.032 NA NA 0.021 0.046 0.019 0.044

TRWA 0.070 0.078 0.056 0.089 0.074 NA NA NA 0.056 0.034 NA NA 0.062 NA NA NA 0.051 NA NA NA 0.087 0.022 NA NA 0.062 0.036 0.024 0.048

EAP 0.646 0.529 0.579 0.690 0.697 NA NA NA 0.665 0.804 NA NA 0.571 NA NA NA 0.599 NA NA NA 0.888 0.998 NA NA 1.898 2.364 2.501 2.369

PIW 1.088 0.840 0.741 0.803 0.838 NA NA NA 1.013 1.092 NA NA 1.021 NA NA NA 0.820 NA NA NA 1.299 1.497 NA NA 1.387 1.614 1.617 1.512

PIW2 0.129 0.165 0.607 0.310 0.327 NA NA NA 0.406 0.296 NA NA 0.088 NA NA NA 0.140 NA NA NA 0.182 0.188 NA NA 1.706 2.103 2.221 2.063

THLI 0.208 0.217 0.226 0.219 0.201 NA NA NA 0.185 0.153 NA NA 0.190 NA NA NA 0.216 NA NA NA 0.328 0.280 NA NA 0.584 0.602 0.613 0.626

CRWA 0.068 0.068 0.072 0.043 0.053 NA NA NA 0.051 0.036

TRWA 0.101 0.084 0.051 0.104 0.068 NA NA NA 0.062 0.037

EAP 0.669 0.615 0.533 0.609 0.785 NA NA NA 0.556 0.531

PIW 0.440 0.334 0.312 0.389 0.303 NA NA NA 0.390 0.317

PIW2 0.032 0.081 0.237 0.149 0.241 NA NA NA 0.369 0.203

THLI 0.224 0.205 0.199 0.194 0.215 NA NA NA 0.188 0.138

Table 2. Health indices, Austria, women Year 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000

Quarter 1 1 1 1 1 2 3 4 1 2

TIW 0.195 0.242 0.162 0.254 0.247 NA NA NA 0.196 0.069

27

Year 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW NA NA 0.218 NA NA NA 0.270 NA NA NA 0.248 0.166 NA NA 0.250 0.152 0.153 0.214

CRWA NA NA 0.041 NA NA NA 0.038 NA NA NA 0.051 0.055 NA NA 0.099 0.085 0.084 0.088

TRWA NA NA 0.057 NA NA NA 0.075 NA NA NA 0.129 0.017 NA NA 0.050 0.020 0.024 0.042

EAP NA NA 0.358 NA NA NA 0.662 NA NA NA 0.696 0.679 NA NA 1.381 1.481 1.720 1.556

PIW NA NA 0.326 NA NA NA 0.333 NA NA NA 0.536 0.462 NA NA 0.645 0.654 0.649 0.612

PIW2 NA NA 0.095 NA NA NA 0.287 NA NA NA 0.277 0.275 NA NA 1.219 1.178 1.293 1.349

THLI NA NA 0.147 NA NA NA 0.270 NA NA NA 0.304 0.237 NA NA 0.513 0.491 0.572 0.571

CRWA NA 0.010 0.020 0.025 0.016 0.011 0.015 0.017 0.018 0.023 0.025 0.018 0.021 0.012 0.026 0.020 0.037 0.014 0.024 0.023 0.032 0.023 0.038 0.023 0.033

TRWA NA 0.016 0.014 0.017 0.005 0.007 0.011 0.016 0.012 0.011 0.015 0.009 0.012 0.021 0.019 0.017 0.064 0.045 0.029 0.049 0.063 0.038 0.034 0.059 0.066

EAP NA 0.868 1.127 1.185 0.896 1.096 1.235 1.357 1.283 1.489 1.383 1.279 1.395 1.435 1.322 1.418 1.497 1.508 1.674 1.695 1.536 1.664 1.450 1.678 1.474

PIW NA NA NA NA NA NA NA NA NA 1.973 1.878 1.760 1.884 1.895 1.831 1.786 0.054 0.064 0.060 0.142 0.096 0.082 0.087 0.080 0.145

PIW2 NA 0.131 0.182 0.066 0.095 0.072 0.194 0.070 0.106 0.991 0.727 0.670 0.867 0.786 0.708 0.931 0.130 0.181 0.119 0.140 0.152 0.130 0.121 0.164 0.178

THLI NA 0.089 0.113 0.113 0.074 0.077 0.090 0.092 0.094 0.312 0.289 0.273 0.300 0.308 0.280 0.327 0.312 0.285 0.287 0.312 0.295 0.280 0.254 0.319 0.299

Table 3. Health indices, Belgium, men Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1

TIW NA 0.148 0.159 0.153 0.114 0.094 0.128 0.083 0.086 0.132 0.130 0.137 0.134 0.151 0.119 0.187 0.275 0.246 0.278 0.233 0.281 0.315 0.267 0.262 0.346

28

Year 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.280 0.313 0.300 0.329 0.334 0.216 0.261 0.365 0.227 0.273 0.320 0.284 0.279 0.205 0.276

CRWA 0.041 0.032 0.025 0.030 0.042 0.038 0.032 0.023 0.044 0.021 0.034 0.035 0.030 0.064 0.024

TRWA 0.047 0.024 0.041 0.030 0.032 0.035 0.038 0.038 0.020 0.041 0.054 0.036 0.040 0.025 0.031

EAP 1.316 1.430 1.366 1.418 1.526 1.508 1.555 1.202 1.209 1.277 1.363 1.029 1.292 1.253 1.331

PIW 0.181 0.122 0.111 0.123 0.149 0.157 0.160 0.138 0.183 0.091 0.137 0.080 0.155 0.147 0.119

PIW2 0.233 0.204 0.174 0.221 0.242 0.186 0.248 0.230 0.183 0.133 0.230 0.130 0.266 0.222 0.168

THLI 0.277 0.277 0.282 0.276 0.308 0.287 0.330 0.256 0.247 0.242 0.295 0.216 0.273 0.271 0.258

CRWA NA 0.031 0.021 0.028 0.036 0.045 0.026 0.033 0.025 0.039 0.038 0.029 0.034 0.032 0.040 0.033 0.079 0.082 0.053 0.043 0.083 0.069 0.054 0.046 0.086 0.053 0.047 0.049

TRWA NA 0.011 0.021 0.009 0.005 0.011 0.013 0.013 0.005 0.013 0.018 0.019 0.018 0.027 0.011 0.032 0.044 0.030 0.022 0.033 0.074 0.066 0.036 0.051 0.025 0.050 0.027 0.039

EAP NA 0.729 0.926 0.799 0.804 0.793 1.005 1.009 0.962 0.971 0.993 0.887 0.948 1.016 0.883 1.045 1.187 1.232 0.911 1.079 1.349 1.286 0.962 1.148 1.127 1.269 0.970 1.056

PIW NA NA NA NA NA NA NA NA NA 0.523 0.577 0.580 0.605 0.662 0.629 0.694 0.048 0.026 0.051 0.035 0.062 0.054 0.047 0.051 0.051 0.078 0.107 0.105

PIW2 NA 0.155 0.093 0.080 NA 0.146 0.041 NA 0.042 0.610 0.674 0.657 0.530 0.583 0.511 0.749 0.120 0.149 0.196 0.143 0.157 0.141 0.174 0.132 0.233 0.191 0.203 0.199

THLI NA 0.068 0.068 0.062 NA 0.066 0.054 NA 0.061 0.200 0.227 0.221 0.219 0.240 0.203 0.273 0.247 0.247 0.195 0.214 0.272 0.257 0.196 0.218 0.239 0.245 0.206 0.226

Table 4. Health indices, Belgium, women Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4

TIW NA 0.157 0.153 0.118 0.118 0.095 0.098 0.084 0.085 0.124 0.140 0.144 0.130 0.179 0.154 0.174 0.224 0.179 0.187 0.295 0.363 0.287 0.234 0.256 0.269 0.233 0.266 0.267

29

Year 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.284 0.298 0.180 0.219 0.317 0.201 0.216 0.254 0.248 0.228 0.200 0.233

CRWA 0.095 0.085 0.059 0.067 0.087 0.102 0.069 0.066 0.067 0.082 0.084 0.068

TRWA 0.046 0.036 0.022 0.025 0.040 0.025 0.029 0.057 0.049 0.026 0.026 0.040

EAP 1.038 1.290 1.254 1.173 1.107 1.215 1.197 1.161 1.021 1.078 1.090 0.993

PIW 0.071 0.072 0.069 0.069 0.085 0.073 0.065 0.075 0.070 0.063 0.079 0.069

PIW2 0.162 0.155 0.161 0.175 0.192 0.181 0.236 0.198 0.142 0.153 0.190 0.177

THLI 0.234 0.265 0.245 0.241 0.241 0.253 0.251 0.250 0.218 0.225 0.244 0.223

TRWA 0.042 0.022 0.025 0.018 0.025 0.034 0.017 0.012 0.018 0.039 0.023 0.020 0.029 0.046 0.019 0.015 0.019 0.029 0.030 0.016 0.021 0.037 0.060 0.021 0.043 0.022 0.024 0.009 0.024

EAP 3.506 2.795 2.995 2.825 2.667 2.373 2.302 2.288 2.236 0.505 1.014 0.717 2.450 2.073 2.197 2.336 2.287 2.308 2.466 2.389 2.420 2.308 2.494 2.616 2.607 2.130 2.240 2.363 2.551

PIW 0.652 3.174 3.357 3.330 3.283 3.031 2.835 2.766 2.791 2.625 2.760 2.919 2.902 2.665 2.792 2.962 2.895 2.916 3.060 2.985 2.914 3.001 3.114 3.193 3.186 2.822 2.882 2.988 3.070

PIW2 0.031 0.074 0.083 0.070 0.050 0.044 0.061 0.056 0.056 0.056 0.054 0.063 0.098 0.122 0.130 0.118 0.108 0.865 1.256 1.293 1.155 1.232 1.360 1.366 1.364 1.278 1.395 1.494 1.655

THLI 0.476 0.399 0.428 0.394 0.396 0.393 0.377 0.365 0.372 0.172 0.233 0.190 0.417 0.390 0.379 0.387 0.377 0.454 0.481 0.458 0.461 0.472 0.517 0.509 0.540 0.483 0.475 0.489 0.528

Table 5. Health indices, the Czech Republic, men Year 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.368 0.379 0.350 0.284 0.310 0.436 0.274 0.244 0.307 0.440 0.293 0.254 0.286 0.550 0.405 0.392 0.457 0.493 0.399 0.399 0.396 0.672 0.466 0.409 0.464 0.415 0.379 0.341 0.391

CRWA 0.104 0.091 0.102 0.080 0.082 0.082 0.087 0.081 0.077 0.073 0.086 0.076 0.086 0.083 0.080 0.074 0.073 0.078 0.075 0.081 0.093 0.091 0.089 0.090 0.105 0.106 0.082 0.093 0.089

30

Table 6. Health indices, the Czech Republic, women Year 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.541 0.505 0.429 0.334 0.431 0.584 0.416 0.291 0.402 0.540 0.365 0.341 0.418 0.524 0.388 0.370 0.426 0.447 0.363 0.373 0.384 0.621 0.423 0.364 0.406 0.351 0.344 0.291 0.360

CRWA 0.139 0.124 0.114 0.106 0.116 0.101 0.098 0.104 0.119 0.107 0.104 0.110 0.126 0.125 0.138 0.158 0.144 0.146 0.143 0.143 0.140 0.138 0.136 0.145 0.149 0.130 0.134 0.115 0.115

TRWA 0.042 0.037 0.032 0.018 0.037 0.042 0.024 0.015 0.034 0.055 0.050 0.019 0.030 0.042 0.025 0.020 0.029 0.040 0.045 0.022 0.039 0.072 0.026 0.021 0.029 0.049 0.033 0.014 0.024

EAP 2.109 1.608 1.683 1.622 1.585 1.516 1.433 1.507 1.552 0.425 0.539 0.619 1.401 1.270 1.376 1.305 1.350 1.446 1.473 1.528 1.449 1.363 1.465 1.489 1.506 1.330 1.423 1.380 1.399

PIW 0.498 1.735 1.826 1.788 1.744 1.678 1.652 1.650 1.669 1.572 1.666 1.715 1.680 1.569 1.564 1.525 1.607 1.610 1.663 1.693 1.668 1.674 1.707 1.738 1.731 1.649 1.715 1.709 1.707

PIW2 0.051 0.077 0.070 0.057 0.081 0.072 0.054 0.057 0.072 0.081 0.078 0.089 0.086 0.072 0.083 0.081 0.075 0.575 0.801 0.850 0.839 0.876 0.938 0.944 0.951 0.939 0.976 0.963 0.893

THLI 0.520 0.481 0.495 0.484 0.514 0.484 0.445 0.473 0.509 0.251 0.270 0.277 0.472 0.431 0.457 0.455 0.460 0.527 0.544 0.544 0.526 0.517 0.521 0.550 0.566 0.514 0.532 0.508 0.512

CRWA NA 0.023 0.049 0.028 0.025 0.032 0.035 0.039 0.046 0.025 0.019 0.010 0.023

TRWA NA 0.065 0.046 0.064 0.071 0.079 0.060 0.052 0.050 0.069 0.072 0.042 0.046

EAP NA 1.335 1.273 1.161 1.150 1.105 1.165 1.218 1.003 1.443 1.094 0.658 0.823

PIW NA NA NA NA NA NA NA NA NA 0.952 0.879 0.661 1.007

PIW2 NA 0.096 0.062 0.061 0.124 0.029 0.066 0.067 0.122 0.165 0.159 0.148 0.129

THLI NA 0.245 0.216 0.179 0.200 0.197 0.207 0.216 0.211 0.326 0.291 0.210 0.229

Table 7. Health indices, Denmark, men Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2

TIW NA 0.123 0.116 0.147 0.129 0.114 0.116 0.119 0.127 0.100 0.129 0.104 0.077

31

Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.116 0.086 0.152 0.153 0.101 0.105 0.152 0.144 0.131 0.130 0.129 0.213 0.189 0.154 0.196 0.253 0.236 0.188 0.256 0.224 0.165 0.162 0.177 0.254 0.187 0.164 0.218

CRWA 0.034 0.032 0.025 0.017 0.047 0.026 0.041 0.029 0.067 0.034 0.031 0.037 0.047 0.065 0.048 0.036 0.054 0.046 0.055 0.053 0.057 0.051 0.064 0.061 0.050 0.032 0.064

TRWA 0.036 0.062 0.041 0.078 0.061 0.045 0.090 0.133 0.044 0.039 0.078 0.124 0.051 0.040 0.103 0.095 0.045 0.039 0.079 0.088 0.044 0.070 0.062 0.070 0.078 0.058 0.097

EAP 1.005 1.068 0.993 1.260 1.188 1.387 1.264 1.138 1.250 1.271 1.105 1.375 1.508 1.433 1.496 1.382 1.537 1.323 1.295 1.350 1.514 1.247 1.372 1.029 1.168 1.368 1.728

PIW 1.140 0.845 0.936 0.937 0.958 1.173 1.032 1.481 1.584 1.548 1.601 1.524 1.664 1.716 1.424 1.465 1.609 1.515 1.467 1.567 1.478 1.415 1.419 1.435 1.652 1.570 1.843

PIW2 0.263 0.152 0.228 0.322 0.235 0.249 0.294 0.254 0.433 0.242 0.256 0.304 0.269 0.254 0.294 0.474 0.303 0.376 0.359 0.312 0.305 0.268 0.301 0.226 0.272 0.192 0.389

THLI 0.296 0.291 0.264 0.371 0.331 0.337 0.371 0.361 0.360 0.278 0.300 0.424 0.367 0.324 0.417 0.409 0.376 0.320 0.375 0.397 0.386 0.341 0.391 0.334 0.334 0.321 0.437

CRWA NA 0.026 0.028 0.042 0.044 0.040 0.052 0.054 0.036 0.032 0.021 0.036 0.038 0.029 0.036 0.046

TRWA NA 0.083 0.057 0.076 0.081 0.095 0.102 0.095 0.055 0.087 0.103 0.061 0.069 0.058 0.071 0.064

EAP NA 1.102 0.942 1.002 1.312 1.219 1.250 1.196 1.105 1.709 1.483 0.760 0.955 1.240 1.205 1.149

PIW NA NA NA NA NA NA NA NA NA 1.165 1.012 0.769 0.894 1.005 0.949 0.898

PIW2 NA 0.120 0.098 0.045 0.122 0.103 0.058 0.032 0.081 0.180 0.303 0.156 0.323 0.357 0.299 0.222

THLI NA 0.241 0.197 0.210 0.259 0.256 0.284 0.274 0.236 0.470 0.472 0.319 0.425 0.493 0.454 0.413

Table 8. Health indices, Denmark, women Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

TIW NA 0.160 0.182 0.232 0.186 0.157 0.175 0.191 0.174 0.142 0.191 0.133 0.170 0.173 0.158 0.185

32

Year 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.162 0.109 0.136 0.160 0.206 0.135 0.119 0.187 0.204 0.154 0.140 0.182 0.239 0.211 0.174 0.235 0.207 0.157 0.149 0.172 0.241 0.171 0.151 0.206

CRWA 0.041 0.057 0.053 0.056 0.096 0.072 0.066 0.049 0.053 0.056 0.041 0.065 0.057 0.063 0.074 0.085 0.075 0.097 0.092 0.079 0.109 0.085 0.113 0.091

TRWA 0.085 0.056 0.061 0.085 0.170 0.100 0.070 0.146 0.152 0.066 0.058 0.080 0.111 0.082 0.077 0.128 0.140 0.078 0.058 0.103 0.124 0.093 0.053 0.127

EAP 1.325 1.376 1.311 1.266 1.094 1.318 1.453 1.344 1.258 1.334 1.469 1.455 1.542 1.390 1.554 1.642 1.299 1.561 1.607 1.388 1.262 1.360 1.361 1.572

PIW 0.959 1.021 0.996 0.932 1.336 1.437 1.537 1.692 1.526 1.479 1.497 1.420 1.428 1.453 1.602 1.411 1.525 1.560 1.582 1.508 1.652 1.553 1.558 1.721

PIW2 0.272 0.204 0.462 0.243 0.300 0.296 0.360 0.542 0.311 0.358 0.269 0.358 0.403 0.423 0.597 0.411 0.358 0.502 0.379 0.455 0.340 0.249 0.292 0.513

THLI 0.463 0.450 0.486 0.448 0.485 0.461 0.445 0.489 0.481 0.449 0.417 0.470 0.489 0.439 0.524 0.583 0.498 0.547 0.522 0.508 0.512 0.459 0.450 0.547

CRWA 0.026 0.043 0.019 0.008 NA 0.010 0.020 0.007 0.027 0.008 0.016 0.028 0.007 0.013 0.050 0.016 0.009 0.016 0.007

TRWA 0.030 0.045 0.028 0.172 0.022 0.038 0.035 0.009 0.025 0.026 0.016 NA 0.025 NA NA NA NA NA 0.007

EAP 1.274 1.447 1.479 1.003 1.539 1.477 1.329 1.551 1.758 1.624 1.147 1.417 1.553 1.307 1.387 1.464 1.463 1.598 1.372

PIW 1.788 2.226 2.141 1.667 2.051 2.138 1.927 2.064 2.100 2.034 2.193 2.258 2.294 2.269 2.387 2.388 2.455 2.498 2.502

PIW2 0.021 0.212 0.157 0.202 0.098 0.062 0.138 0.170 0.128 0.143 0.160 0.316 0.352 0.276 0.348 0.262 0.040 0.336 0.398

THLI 0.275 0.329 0.352 0.357 0.337 0.325 0.343 0.351 0.369 0.338 0.266 0.317 0.339 0.268 0.326 0.286 0.224 0.278 0.272

Table 9. Health indices, Estonia, men Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.106 0.131 0.129 0.160 0.094 0.050 0.097 0.144 0.052 0.033 0.106 0.067 0.047 0.162 0.069 0.330 0.022 0.039 0.113

33

Year 2004 2004 2004 2004

Quarter 1 2 3 4

TIW 0.055 0.098 0.035 0.071

CRWA 0.014 0.047 0.015 0.011

TRWA 0.037 0.011 0.010 0.019

EAP 1.346 1.675 1.911 1.607

PIW 2.455 2.389 2.334 2.321

PIW2 0.258 0.306 0.329 0.359

THLI 0.284 0.339 0.333 0.287

CRWA 0.005 0.023 0.021 0.029 0.009 0.049 0.094 0.060 0.036 0.106 0.089 0.039 0.030 0.031 0.024 0.046 0.014 NA 0.020 0.037 0.040 0.042 0.006

TRWA 0.024 0.022 0.059 0.053 0.027 0.006 0.022 0.022 0.016 0.025 0.052 0.011 0.017 0.007 0.049 0.040 0.028 0.033 NA 0.019 0.006 NA NA

EAP 1.082 0.963 1.015 0.770 0.861 1.050 1.237 1.306 1.497 0.993 1.045 1.182 1.372 0.979 0.861 0.816 0.939 0.918 0.757 0.975 1.171 0.785 0.685

PIW 1.394 1.226 1.364 1.023 1.392 1.476 1.380 1.218 1.474 1.183 1.356 1.507 1.575 1.432 1.321 1.301 1.486 1.422 1.172 1.413 1.653 1.306 1.157

PIW2 0.287 0.227 0.105 0.172 0.038 0.165 0.183 0.096 0.172 0.088 0.088 0.385 0.258 0.357 0.276 0.233 0.214 0.144 0.115 0.070 0.202 0.106 0.228

THLI 0.345 0.289 0.304 0.255 0.222 0.291 0.396 0.372 0.387 0.297 0.328 0.340 0.348 0.284 0.261 0.250 0.243 0.222 0.177 0.221 0.265 0.179 0.160

CRWA 0.062 0.053 0.061 0.055 0.054 0.043 0.037 0.040 0.037 0.028 0.042 0.045

TRWA 0.024 0.065 0.081 0.153 0.072 0.066 0.112 0.163 0.062 0.060 0.103 0.184

EAP 1.379 1.393 1.138 NA 1.260 NA NA NA 1.121 1.223 1.222 1.114

PIW 1.130 0.827 1.765 1.930 2.076 2.245 2.249 2.118 2.363 2.422 2.235 2.270

PIW2 0.171 0.108 0.152 0.193 0.319 0.169 0.180 0.179 0.299 0.285 0.232 0.229

THLI 0.303 0.320 0.305 NA 0.332 NA NA NA 0.351 0.339 0.405 0.450

Table 10. Health indices, Estonia, women Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.109 0.127 0.116 0.081 0.034 0.086 0.020 0.126 0.052 0.018 0.091 0.067 0.032 0.162 0.055 0.313 0.022 0.039 0.081 0.055 0.053 0.035 0.051

Table 11. Health indices, Finland, men Year 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000

Quarter 2 2 2 1 2 3 4 1 2 3 4 1

TIW 0.160 0.177 0.173 0.231 0.211 0.160 0.197 0.240 0.189 0.158 0.182 0.222

34

Year 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.188 0.194 0.232 0.334 0.259 0.237 0.315 0.356 0.284 0.244 0.308 0.244 0.234 0.216 0.258 0.286 0.248 0.192 0.227

CRWA 0.046 0.042 0.040 0.020 0.034 0.031 0.036 0.037 0.027 0.017 0.014 0.028 0.019 0.013 0.025 0.020 0.021 0.027 0.016

TRWA 0.091 0.094 0.101 0.148 0.079 0.071 0.093 0.141 0.079 0.085 0.124 0.113 0.056 0.066 0.098 0.086 0.050 0.080 0.093

EAP 1.308 1.380 1.240 1.343 1.373 1.403 1.271 1.241 1.354 1.341 1.238 1.237 1.341 1.370 1.322 1.262 1.346 1.309 1.320

PIW 2.617 2.719 2.484 2.424 2.690 2.626 2.407 2.277 2.527 2.624 2.448 2.203 2.296 2.415 2.295 2.191 2.422 2.465 2.495

PIW2 0.273 0.309 0.279 0.297 0.317 0.251 0.342 0.196 0.380 0.309 0.310 0.251 0.271 0.268 0.311 0.251 0.283 0.307 0.320

THLI 0.399 0.398 0.403 0.452 0.394 0.370 0.411 0.432 0.414 0.371 0.411 0.359 0.307 0.300 0.356 0.334 0.306 0.309 0.342

CRWA 0.122 0.073 0.061 0.078 0.099 0.087 0.101 0.075 0.054 0.071 0.045 0.059 0.051 0.075 0.048 0.055 0.047 0.038 0.044 0.033 0.033 0.053 0.041 0.035

TRWA 0.046 0.107 0.103 0.167 0.047 0.083 0.136 0.231 0.089 0.100 0.133 0.212 0.113 0.095 0.146 0.217 0.103 0.092 0.135 0.193 0.122 0.107 0.162 0.143

EAP 1.213 1.076 0.748 NA 0.731 NA NA NA 0.929 0.954 0.966 0.972 1.042 1.000 0.956 0.910 0.923 0.982 1.067 1.072 1.100 1.051 1.050 1.078

PIW 0.954 0.632 1.275 1.535 1.326 1.617 1.609 1.681 1.655 1.731 1.778 1.775 1.838 1.835 1.770 1.752 1.815 1.898 1.897 1.900 2.016 2.001 1.843 1.747

PIW2 0.192 0.153 0.147 0.162 0.135 0.158 0.152 0.250 0.227 0.226 0.230 0.262 0.250 0.283 0.247 0.233 0.209 0.205 0.260 0.201 0.371 0.306 0.289 0.230

THLI 0.362 0.342 0.265 NA 0.243 NA NA NA 0.366 0.384 0.404 0.474 0.407 0.400 0.414 0.450 0.351 0.352 0.426 0.448 0.423 0.395 0.441 0.369

Table 12. Health indices, Finland, women Year 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1

TIW 0.223 0.217 0.217 0.201 0.189 0.203 0.249 0.296 0.233 0.188 0.281 0.271 0.259 0.203 0.269 0.276 0.206 0.197 0.284 0.277 0.243 0.229 0.279 0.216

35

Year 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4

TIW 0.201 0.193 0.242 0.246 0.226 0.173 0.201

CRWA 0.039 0.035 0.030 0.028 0.031 0.036 0.038

TRWA 0.066 0.075 0.128 0.132 0.082 0.102 0.111

EAP 1.048 1.089 1.033 1.006 0.961 0.922 1.001

PIW 1.815 1.778 1.721 1.640 1.713 1.778 1.619

PIW2 0.274 0.373 0.314 0.240 0.199 0.255 0.220

THLI 0.308 0.332 0.357 0.344 0.289 0.301 0.329

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.052 0.048 0.053 0.056 0.049 0.045 0.040 0.034 0.041 0.049 0.044

TRWA NA 0.049 0.034 0.052 0.028 0.045 0.026 0.041 0.035 0.030 0.038 0.029 0.043 0.037 0.041 0.054 0.044 0.027 0.037 0.031 0.069 0.031 0.026 0.069 0.056 0.042 0.026 0.044

EAP NA 0.885 0.794 0.800 0.820 0.822 0.753 0.619 0.614 0.964 0.894 0.785 0.825 0.804 0.843 0.775 0.825 0.916 1.102 1.020 0.896 0.961 0.937 0.868 0.860 0.855 0.819 0.759

PIW NA NA NA NA NA NA NA NA NA 0.118 0.125 0.116 0.185 0.172 0.162 0.176 0.191 0.194 0.219 0.246 0.099 0.071 0.094 0.090 0.087 0.076 0.077 0.062

PIW2 NA 0.042 0.030 0.046 0.074 0.034 0.046 0.056 0.033 0.053 0.041 0.057 0.041 0.076 0.035 0.054 0.068 0.102 0.120 0.087 0.173 0.195 0.189 0.202 0.155 0.143 0.175 0.147

THLI NA 0.133 0.110 0.122 0.109 0.114 0.093 0.087 0.079 0.169 0.169 0.152 0.160 0.158 0.165 0.164 0.166 0.197 0.223 0.206 0.242 0.221 0.213 0.236 0.219 0.208 0.207 0.205

CRWA NA NA NA NA

TRWA NA 0.041 0.047 0.050

EAP NA 0.987 0.932 0.985

PIW NA NA NA NA

PIW2 NA 0.088 0.052 0.072

THLI NA 0.128 0.116 0.122

Table 13. Health indices, France, men Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 4 1 2 3 4

TIW NA 0.205 0.203 0.217 0.170 0.171 0.171 0.168 0.211 0.208 0.215 0.198 0.211 0.219 0.225 0.240 0.245 0.230 0.315 0.327 0.369 0.375 0.291 0.347 0.351 0.336 0.257 0.335

Table 14. Health indices, France, women Year 1983 1984 1985 1986

Quarter 1 1 1 1

TIW NA 0.218 0.240 0.221

36

Year 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 4 1 2 3 4

TIW 0.195 0.187 0.176 0.228 0.234 0.213 0.266 0.223 0.262 0.271 0.230 0.283 0.284 0.283 0.284 0.309 0.339 0.359 0.255 0.328 0.325 0.317 0.248 0.309

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.161 0.161 0.176 0.150 0.135 0.123 0.155 0.150 0.153 0.152 0.144

TRWA 0.031 0.044 0.028 0.049 0.042 0.036 0.046 0.038 0.039 0.039 0.041 0.055 0.070 0.038 0.043 0.055 0.088 0.042 0.036 0.077 0.075 0.039 0.030 0.057

EAP 0.827 0.688 0.674 0.671 0.575 0.699 0.710 0.673 0.758 0.759 0.735 0.573 0.599 0.672 0.727 0.839 0.718 0.684 0.680 0.695 0.730 0.773 0.709 0.659

PIW NA NA NA NA NA 0.062 0.067 0.071 0.080 0.076 0.077 0.087 0.096 0.094 0.111 0.117 0.052 0.040 0.043 0.046 0.043 0.040 0.034 0.041

PIW2 0.056 0.080 0.049 0.081 0.125 0.072 0.055 0.060 0.074 0.071 0.063 0.071 0.091 0.085 0.077 0.107 0.173 0.225 0.233 0.160 0.154 0.158 0.156 0.098

THLI 0.102 0.096 0.087 0.098 0.088 0.144 0.149 0.143 0.160 0.161 0.160 0.144 0.157 0.237 0.251 0.275 0.279 0.247 0.242 0.277 0.281 0.268 0.259 0.248

CRWA 0.035 0.049 0.061 0.089 0.089 0.077 0.059 0.059 0.055 0.052 0.051 0.065 0.062 0.060 0.058 0.053 0.053 0.053 0.047

TRWA 0.020 0.035 0.020 0.036 0.023 0.018 0.025 NA NA NA NA 0.019 0.013 0.014 0.017 0.024 0.018 0.015 0.016

EAP NA 2.347 2.203 2.309 2.521 2.585 2.544 2.294 2.343 2.440 2.385 2.172 2.294 2.364 2.356 2.247 2.297 2.311 2.306

PIW 0.582 0.397 0.373 1.151 1.271 1.344 1.430 1.438 1.540 1.629 1.569 1.534 1.582 1.611 1.671 1.650 1.697 1.694 1.706

PIW2 0.103 0.038 0.077 1.664 1.838 1.991 2.017 1.857 1.838 1.860 1.786 1.841 1.894 1.851 1.873 1.893 2.120 1.994 2.041

THLI NA 0.598 0.530 0.757 0.779 0.788 0.781 0.702 0.677 0.677 0.657 0.652 0.652 0.632 0.654 0.644 0.649 0.621 0.634

Table 15. Health indices, Hungary, men Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.163 0.138 0.162 0.165 0.125 0.110 0.134 0.139 0.094 0.103 0.122 0.146 0.178 0.137 0.177 0.193 0.164 0.191 0.198

37

Year 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4

TIW 0.248 0.161 0.189 0.178 0.215 0.173 0.140 0.157

CRWA 0.085 0.081 0.079 0.080 0.083 0.090 0.087 0.087

TRWA 0.035 0.020 0.020 0.020 0.042 0.012 0.019 0.015

EAP 1.974 2.034 2.088 2.082 1.986 2.139 2.234 2.068

PIW 1.515 1.652 1.723 1.754 1.784 1.901 1.912 1.936

PIW2 1.259 1.485 1.668 1.583 1.573 1.582 1.511 1.367

THLI 0.594 0.578 0.590 0.588 0.586 0.561 0.569 0.532

CRWA 0.068 0.120 0.087 0.069 0.075 0.090 0.108 0.090 0.096 0.101 0.110 0.086 0.086 0.093 0.111 0.097 0.106 0.117 0.114 0.134 0.103 0.106 0.121 0.119 0.100 0.100 0.097

TRWA 0.060 0.061 0.057 0.047 0.034 0.019 0.024 NA NA NA NA 0.042 0.040 0.018 0.013 0.025 0.018 0.009 0.014 0.039 0.023 0.011 0.021 0.036 0.015 0.013 0.032

EAP NA 1.755 1.627 1.850 1.876 1.946 1.890 1.816 1.851 1.845 1.855 1.748 1.739 1.746 1.778 1.739 1.786 1.811 1.867 1.662 1.673 1.707 1.637 1.837 1.765 1.743 1.743

PIW 0.364 0.263 0.234 0.872 0.901 0.962 1.054 1.106 1.124 1.154 1.162 1.163 1.172 1.145 1.166 1.180 1.172 1.183 1.208 1.245 1.314 1.359 1.376 1.421 1.431 1.420 1.436

PIW2 0.093 0.074 0.071 1.644 1.716 1.741 1.848 1.812 1.845 1.773 1.882 1.723 1.861 1.900 1.846 1.870 1.922 1.965 1.889 1.439 1.465 1.620 1.525 1.592 1.577 1.484 1.357

THLI NA 0.626 0.509 0.685 0.701 0.719 0.743 0.648 0.655 0.641 0.650 0.590 0.602 0.594 0.612 0.586 0.610 0.634 0.651 0.586 0.557 0.578 0.570 0.538 0.501 0.494 0.493

CRWA NA 0.013 0.011 0.013

TRWA NA 0.058 0.043 0.046

EAP NA 1.535 1.314 1.444

PIW NA NA NA NA

PIW2 NA 0.125 0.121 0.125

THLI NA 0.223 0.189 0.200

Table 16. Health indices, Hungary, women Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.268 0.190 0.198 0.253 0.188 0.161 0.182 0.181 0.149 0.126 0.155 0.137 0.165 0.129 0.173 0.182 0.164 0.176 0.185 0.231 0.154 0.182 0.163 0.204 0.167 0.137 0.146

Table 17. Health indices, Ireland, men Year 1983 1984 1985 1986

Quarter 2 2 2 2

TIW NA 0.231 0.210 0.201

38

Year 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.188 0.176 0.192 0.159 0.170 0.163 0.169 0.155 0.127 0.115 0.120 0.101 0.126 0.110 0.106 0.156 0.102 0.092 0.101 0.170 0.186 0.167 0.149 0.152 0.161 0.132 0.153 0.243 0.192 0.185 0.221 0.193 0.170 0.135 0.175

CRWA 0.020 0.021 0.013 0.018 0.019 0.018 0.017 0.026 0.030 0.015 0.020 0.026 0.030 0.029 0.034 0.035 0.037 0.029 0.037 0.035 0.032 0.032 0.034 0.036 0.032 0.029 0.027 0.033 0.031 0.034 0.037 0.034 0.029 0.023 0.026

TRWA 0.042 0.047 0.042 0.040 0.033 0.034 0.031 0.030 0.028 0.035 0.022 0.017 0.015 0.012 0.017 0.026 0.014 0.009 0.019 0.018 0.021 0.009 0.010 0.013 0.013 0.008 0.011 0.016 0.020 0.012 0.023 0.021 0.023 0.013 0.012

EAP 1.582 1.441 1.480 1.660 1.476 1.988 1.494 2.007 2.105 1.376 1.514 1.533 1.692 1.815 1.860 1.964 2.083 2.106 1.418 2.131 1.919 2.059 1.956 2.079 1.937 2.029 1.871 2.384 2.504 2.328 2.248 1.908 1.921 2.059 2.060

PIW NA NA NA NA NA 0.487 0.383 0.437 0.478 0.329 0.402 0.427 0.499 0.609 0.591 0.648 0.615 0.733 0.730 0.635 0.697 0.734 0.771 0.644 0.622 0.594 0.612 0.783 0.845 0.657 0.591 0.580 0.583 0.556 0.612

PIW2 0.094 0.067 0.138 0.096 0.081 0.061 0.060 0.060 0.049 0.053 0.052 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.044 0.038 0.023 0.015 0.033 0.016 0.038 0.029

THLI 0.207 0.184 0.180 0.169 0.160 0.336 0.260 0.291 0.297 0.198 0.204 0.167 0.121 0.121 0.129 0.136 0.132 0.122 0.131 0.126 0.122 0.131 0.135 0.141 0.125 0.128 0.128 0.164 0.168 0.157 0.167 0.144 0.142 0.140 0.135

CRWA NA 0.025 0.027 0.037 0.026 0.033 0.031 0.025

TRWA NA 0.051 0.047 0.052 0.041 0.041 0.040 0.038

EAP NA 1.778 1.489 1.593 1.389 1.631 1.317 1.472

PIW NA NA NA NA NA NA NA NA

PIW2 NA 0.116 0.114 0.143 0.177 0.062 0.100 0.100

THLI NA 0.160 0.136 0.149 0.131 0.134 0.115 0.118

Table 18. Health indices, Ireland, women Year 1983 1984 1985 1986 1987 1988 1989 1990

Quarter 2 2 2 2 2 2 2 2

TIW NA 0.224 0.212 0.181 0.185 0.219 0.225 0.168

39

Year 1991 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.208 0.168 0.219 0.165 0.206 0.148 0.178 0.197 0.166 0.139 0.154 0.209 0.177 0.142 0.161 0.155 0.169 0.147 0.126 0.136 0.140 0.112 0.136 0.214 0.170 0.171 0.196 0.176 0.151 0.126 0.149

CRWA 0.032 0.025 0.021 0.031 0.029 0.023 0.019 0.029 0.024 0.021 0.027 0.030 0.029 0.029 0.030 0.026 0.031 0.031 0.028 0.017 0.018 0.014 0.016 0.031 0.035 0.038 0.045 0.034 0.017 0.024 0.025

TRWA 0.045 0.039 0.034 0.044 0.028 0.031 0.026 0.020 0.017 0.011 0.014 0.038 0.017 0.015 0.019 0.018 0.021 0.010 0.019 0.025 0.021 0.015 0.012 0.016 0.024 0.010 0.029 0.028 0.020 0.010 0.018

EAP 1.514 1.414 1.227 1.425 1.497 1.128 1.050 1.237 1.298 1.337 1.216 1.305 1.398 1.321 1.179 1.522 1.380 1.402 1.390 1.272 1.392 1.402 1.335 1.465 1.664 1.741 1.827 1.387 1.421 1.595 1.497

PIW NA 0.088 0.091 0.116 0.104 0.071 0.117 0.128 0.131 0.140 0.147 0.149 0.153 0.145 0.184 0.163 0.154 0.160 0.159 0.137 0.160 0.145 0.154 0.177 0.170 0.143 0.128 0.140 0.136 0.147 0.160

PIW2 0.031 0.053 0.036 0.025 0.047 0.044 0.060 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.030 0.003 0.059 0.059 0.033 0.039 0.016 0.014

THLI 0.123 0.224 0.201 0.208 0.219 0.162 0.161 0.164 0.084 0.085 0.087 0.100 0.091 0.089 0.097 0.088 0.094 0.099 0.102 0.079 0.085 0.089 0.089 0.102 0.115 0.129 0.151 0.116 0.103 0.111 0.117

Table 19. Health indices, Italy, men Year

Quarter

TIW

CRWA

TRWA

EAP

PIW

PIW2

THLI

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

2 2 2 2 2 2 2 2 2 3 2 2

NA 0.182 0.160 0.155 0.162 0.167 0.146 0.170 0.161 0.118 0.096 0.104

NA 0.046 0.034 0.035 0.040 0.040 0.040 0.032 0.035 0.024 0.024 0.023

NA 0.116 0.088 0.071 0.072 0.070 0.057 0.066 0.074 0.048 0.074 0.049

NA 1.682 1.522 1.337 1.154 1.321 1.139 1.301 1.382 1.260 1.057 0.828

NA NA NA NA NA NA NA NA NA 1.816 1.600 1.402

NA 0.008 0.011 0.012 0.010 0.006 0.011 0.008 0.003 0.035 0.035 0.043

NA 0.208 0.167 0.148 0.143 0.147 0.131 0.133 0.144 0.210 0.208 0.172

40

Year

Quarter

TIW

CRWA

TRWA

EAP

PIW

PIW2

THLI

1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

0.106 0.117 0.111 0.101 0.103 0.088 0.098 0.141 0.092 0.085 0.096 0.168 0.085 0.067 0.075 0.109 0.108 0.081 0.076 0.107 0.117 0.078 0.076 0.117 0.111 0.077 0.081 0.219 0.165 0.142 0.182

0.020 0.022 0.016 0.020 0.019 0.019 0.024 0.019 0.023 0.023 0.019 0.017 0.012 0.017 0.018 0.014 0.012 0.011 0.013 0.019 0.017 0.020 0.014 0.014 0.013 0.015 0.014 0.032 0.036 0.034 0.044

0.051 0.047 0.057 0.080 0.038 0.028 0.048 0.090 0.041 0.028 0.041 0.107 0.043 0.019 0.038 0.055 0.044 0.026 0.031 0.043 0.034 0.024 0.044 0.031 0.049 0.022 0.041 0.074 0.061 0.030 0.051

0.792 0.700 0.627 0.604 0.658 0.676 0.673 0.518 0.597 0.702 0.681 0.544 0.588 0.594 0.651 0.576 0.616 0.633 0.614 0.561 0.570 0.563 0.637 0.578 0.599 0.597 0.603 0.704 0.802 0.915 0.867

1.356 1.279 1.198 1.068 1.134 1.223 1.167 0.996 1.032 1.111 1.137 0.965 1.026 1.102 1.136 1.098 1.063 1.126 1.171 1.032 1.079 1.107 1.118 1.117 1.105 1.150 1.180 1.483 1.609 1.708 1.565

0.031 0.036 0.025 0.018 0.023 0.016 0.028 0.031 0.023 0.028 0.037 0.027 0.028 0.012 0.012 0.022 0.023 0.038 0.022 0.022 0.015 0.013 0.015 0.021 0.019 0.016 0.027 0.252 0.339 0.300 0.287

0.169 0.155 0.147 0.160 0.141 0.132 0.152 0.154 0.134 0.138 0.143 0.164 0.123 0.104 0.127 0.127 0.123 0.111 0.113 0.118 0.111 0.104 0.123 0.108 0.120 0.095 0.114 0.209 0.219 0.203 0.226

CRWA NA 0.082 0.068 0.069 0.060 0.057 0.054 0.059 0.064 0.028 0.030 0.018

TRWA NA 0.131 0.100 0.088 0.073 0.084 0.066 0.073 0.078 0.052 0.086 0.054

EAP NA 2.198 2.107 1.876 1.745 1.787 1.605 1.791 1.705 0.688 0.550 0.511

PIW NA NA NA NA NA NA NA NA NA 0.492 0.433 0.467

PIW2 NA 0.001 NA 0.018 0.003 0.006 NA 0.004 0.011 0.011 0.016 0.010

THLI NA 0.203 0.172 0.155 0.144 0.151 0.133 0.139 0.141 0.124 0.116 0.097

Table 20. Health indices, Italy, women Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Quarter 2 2 2 2 2 2 2 2 2 3 2 2

TIW NA 0.187 0.154 0.163 0.167 0.163 0.155 0.183 0.183 0.117 0.110 0.125

41

Year 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.133 0.127 0.142 0.134 0.106 0.090 0.092 0.151 0.093 0.070 0.089 0.163 0.081 0.074 0.079 0.100 0.094 0.073 0.068 0.096 0.105 0.068 0.062 0.103 0.103 0.067 0.072 0.186 0.142 0.118 0.158

CRWA 0.023 0.028 0.033 0.019 0.022 0.026 0.024 0.022 0.022 0.019 0.023 0.019 0.016 0.015 0.032 0.031 0.022 0.022 0.021 0.025 0.023 0.027 0.031 0.027 0.019 0.024 0.017 0.080 0.087 0.112 0.098

TRWA 0.077 0.040 0.073 0.068 0.068 0.022 0.047 0.097 0.051 0.024 0.048 0.131 0.037 0.026 0.045 0.043 0.037 0.016 0.026 0.042 0.026 0.017 0.041 0.037 0.046 0.022 0.044 0.070 0.045 0.035 0.067

EAP 0.492 0.480 0.410 0.401 0.381 0.415 0.453 0.373 0.349 0.385 0.399 0.368 0.388 0.382 0.366 0.345 0.350 0.396 0.368 0.342 0.394 0.423 0.416 0.372 0.367 0.447 0.458 0.730 0.720 0.812 0.785

PIW 0.494 0.469 0.440 0.434 0.418 0.416 0.440 0.393 0.367 0.367 0.378 0.364 0.365 0.371 0.361 0.347 0.353 0.376 0.380 0.343 0.345 0.360 0.365 0.356 0.332 0.388 0.379 0.678 0.653 0.636 0.616

PIW2 0.020 0.031 0.019 0.008 0.012 0.011 0.010 0.009 0.013 0.010 0.010 0.014 0.023 0.008 0.017 0.014 0.016 0.013 0.019 0.014 0.010 0.012 0.018 0.008 0.010 0.014 0.012 0.340 0.351 0.319 0.289

THLI 0.109 0.098 0.100 0.087 0.088 0.074 0.091 0.097 0.079 0.069 0.082 0.108 0.075 0.064 0.078 0.073 0.069 0.063 0.065 0.069 0.067 0.069 0.081 0.070 0.070 0.069 0.079 0.241 0.228 0.244 0.242

CRWA 0.195 0.164 0.147 0.188 0.143 0.161 0.141 0.155 0.042 0.038 0.044 0.061

TRWA 0.013 0.019 0.017 0.022 0.018 0.015 0.021 0.008 0.046 0.027 0.015 0.043

EAP NA NA NA NA NA NA 0.290 0.361 1.215 0.712 1.176 0.973

PIW NA NA NA NA NA NA 0.323 0.456 1.740 1.234 1.848 1.377

PIW2 0.025 0.010 0.008 0.031 0.012 0.017 0.117 0.018 0.357 0.364 0.355 0.507

THLI 0.145 0.122 0.106 0.143 0.103 0.112 0.173 0.167 0.335 0.235 0.272 0.322

Table 21. Health indices, Latvia, men Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002

Quarter 2 4 2 4 2 4 2 4 1 2 3 4

TIW 0.038 0.062 0.050 0.074 0.048 0.030 0.080 0.034 0.141 0.050 0.083 0.065

42

Year 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4

TIW 0.182 0.105 0.061 0.047 0.124 0.061 0.004 0.044

CRWA 0.045 0.040 0.048 0.061 0.063 0.057 0.042 0.034

TRWA 0.036 0.012 0.019 0.046 0.020 0.018 NA NA

EAP 1.082 1.204 1.281 1.496 1.194 1.657 1.561 1.688

PIW 1.807 1.869 1.879 1.962 1.715 2.053 1.824 1.896

PIW2 0.431 0.694 0.520 0.596 0.440 0.681 0.186 0.506

THLI 0.308 0.335 0.343 0.370 0.334 0.364 0.376 0.331

CRWA 0.278 0.284 0.205 0.216 0.239 0.225 0.252 0.183 0.263 0.023 0.126 0.011 0.063 0.028 0.077 0.067 0.023 0.038 0.074 0.132

TRWA 0.012 0.044 0.023 0.012 0.018 0.012 0.040 0.018 0.101 0.076 NA 0.028 0.020 NA NA 0.035 0.014 0.033 0.006 0.015

EAP NA NA NA NA NA NA 0.307 0.318 0.925 0.718 0.691 0.959 0.988 0.890 0.848 0.725 0.799 0.635 0.761 0.830

PIW NA NA NA NA NA NA 0.315 0.349 1.198 1.022 1.075 1.071 1.190 1.064 0.842 1.116 0.900 1.251 0.788 1.245

PIW2 0.014 0.025 0.019 0.007 0.008 0.016 0.132 0.032 0.287 0.244 0.363 0.373 0.416 0.408 0.234 0.404 0.330 0.562 0.094 0.496

THLI 0.168 0.190 0.132 0.125 0.140 0.135 0.241 0.179 0.454 0.250 0.291 0.284 0.329 0.280 0.238 0.288 0.230 0.291 0.236 0.336

CRWA 0.014 0.055 NA NA 0.005 0.033 0.037 0.017 0.058 0.054 0.060

TRWA NA NA 0.004 0.010 0.005 0.025 0.010 0.004 0.003 0.008 NA

EAP 0.111 0.104 NA 0.163 0.980 1.136 1.163 1.277 1.295 1.377 1.619

PIW 0.017 0.078 0.043 NA 1.726 1.738 1.811 1.895 1.900 2.082 2.173

PIW2 0.027 0.072 NA 0.005 0.014 0.245 0.213 0.218 0.277 0.352 0.285

THLI 0.027 0.069 NA 0.023 0.193 0.301 0.289 0.310 0.327 0.306 0.321

Table 22. Health indices, Latvia, women Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.035 0.064 0.032 0.044 0.046 0.029 0.080 0.034 0.123 0.050 0.083 0.034 0.166 0.069 0.061 0.030 0.110 0.044 0.004 0.044

Table 23. Health indices, Lithuania, men Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002

Quarter 2 4 2 4 2 4 2 4 1 2 3

TIW 0.062 0.139 0.111 0.152 0.095 0.045 0.165 0.070 0.081 0.042 0.048

43

Year 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 4 1 2 3 4 1 2 3 4

TIW 0.023 0.088 0.049 0.039 0.033 0.027 0.046 0.027 0.033

CRWA 0.014 0.068 0.051 0.018 0.016 0.036 0.050 0.031 0.035

TRWA 0.011 NA 0.003 0.003 NA 0.010 0.003 NA NA

EAP 1.500 1.206 1.921 1.707 1.560 1.399 1.485 1.840 1.650

PIW 2.156 2.159 2.248 2.361 2.371 2.288 2.263 2.508 2.332

PIW2 0.153 0.178 0.149 0.194 0.063 0.235 0.224 0.065 0.071

THLI 0.275 0.266 0.307 0.265 0.227 0.238 0.232 0.228 0.214

CRWA 0.043 0.064 NA NA 0.016 0.123 0.071 0.063 0.107 0.013 0.036 0.029 0.031 0.035 0.032 0.038 0.028 0.027 0.056 0.030

TRWA NA NA 0.004 0.003 NA 0.034 0.007 0.010 0.016 0.006 0.021 0.004 0.007 0.004 NA 0.020 0.020 NA NA 0.007

EAP NA NA NA NA 0.654 0.862 0.875 1.040 0.690 0.959 0.830 0.697 0.897 0.905 0.802 0.795 0.946 1.026 0.851 0.900

PIW 0.142 0.034 0.047 0.032 1.258 1.362 1.308 1.545 1.402 1.609 1.573 1.356 1.608 1.573 1.502 1.419 1.285 1.468 1.564 1.286

PIW2 0.011 0.005 0.014 0.024 NA 0.412 0.377 0.202 0.248 0.244 0.326 0.191 0.044 0.040 0.198 0.075 0.137 0.028 0.060 0.056

THLI NA NA NA NA 0.129 0.318 0.266 0.267 0.232 0.207 0.224 0.172 0.168 0.161 0.172 0.166 0.181 0.157 0.156 0.158

CRWA NA 0.023 0.014 0.003 0.025 0.002 0.010 0.008 0.002 0.019

TRWA NA 0.036 0.031 0.021 0.042 0.023 0.034 0.029 0.031 0.026

EAP NA 1.809 1.882 1.381 1.821 1.598 1.813 1.820 2.259 NA

PIW NA NA NA NA NA NA NA NA NA 1.824

PIW2 NA NA NA NA 0.122 NA 0.042 0.048 NA 0.481

THLI NA NA NA NA 0.140 NA 0.120 0.115 0.148 0.051

Table 24. Health indices, Lithuania, women Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.078 0.155 0.086 0.114 0.113 0.097 0.139 0.070 0.081 0.042 0.039 0.023 0.088 0.049 0.039 0.033 0.027 0.046 0.027 0.025

Table 25. Health indices, Luxembourg, men Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992

Quarter 2 2 2 2 2 2 2 2 2 2

TIW NA 0.150 0.128 0.125 0.139 0.119 0.090 0.092 0.097 0.141

44

Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 1 2 1 2 3 4

TIW 0.155 0.141 0.108 0.118 0.091 0.089 0.092 0.057 0.120 0.109 0.136 0.136 0.201 0.201 0.201 0.201

CRWA 0.009 0.006 0.002 0.004 NA 0.024 0.006 0.006 0.006 0.005 0.002 0.002 0.015 0.015 0.015 0.015

TRWA 0.035 0.018 0.036 0.011 0.016 0.019 0.018 0.033 0.016 0.008 0.009 0.009 0.002 0.002 0.002 0.002

EAP 2.095 1.488 2.594 2.299 2.405 2.782 2.122 1.766 1.803 1.865 1.981 1.981 2.051 2.051 2.051 2.051

PIW 1.887 1.547 2.295 2.103 2.119 2.406 1.885 1.592 1.610 1.561 2.168 2.168 2.305 2.305 2.305 2.305

PIW2 0.147 0.072 0.588 NA 0.451 0.346 NA NA 0.037 NA 0.606 0.606 NA NA NA NA

THLI 0.270 0.192 0.348 NA 0.327 0.343 NA NA 0.221 NA 0.242 0.242 NA NA NA NA

TRWA NA 0.027 0.038 0.019 0.031 0.015 0.011 0.011 0.009 0.022 0.030 0.040 0.009 0.004 0.019 0.035 0.016 0.024 0.018 0.007 0.017 0.017 0.008 0.008 0.008 0.008

EAP NA 0.825 0.876 1.009 0.704 0.675 1.021 1.016 0.810 NA 1.203 1.018 1.342 1.086 1.044 1.251 0.894 0.841 0.716 1.142 1.284 1.284 1.234 1.234 1.234 1.234

PIW NA NA NA NA NA NA NA NA NA 0.190 0.246 0.254 0.272 0.228 0.254 0.319 0.187 0.233 0.225 0.253 0.431 0.431 0.440 0.440 0.440 0.440

PIW2 NA NA 0.037 NA NA 0.061 NA NA NA 0.188 0.017 0.251 NA NA 0.800 NA 0.191 0.171 0.107 0.922 NA NA 0.999 0.999 0.999 0.999

THLI NA NA 0.060 NA NA 0.040 NA NA NA 0.022 0.174 0.176 0.177 NA 0.180 NA 0.128 0.106 0.115 0.178 NA NA 0.236 0.236 0.236 0.236

Table 26. Health indices, Luxembourg, women Year 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 3 4

TIW NA 0.104 0.067 0.119 0.069 0.041 0.094 0.105 0.120 0.112 0.206 0.108 0.121 0.085 0.135 0.069 0.098 0.086 0.102 0.057 0.123 0.123 0.187 0.187 0.187 0.187

CRWA NA 0.007 0.014 0.007 0.013 0.008 0.021 0.018 0.028 0.004 0.004 0.029 0.013 0.007 NA 0.008 0.031 0.018 0.013 0.019 0.031 0.031 0.048 0.048 0.048 0.048

45

Table 27. Health indices, the Netherlands, men Year 1983 1985 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW NA 0.244 0.227 0.283 0.277 0.313 0.299 0.345 0.353 0.244 0.273 0.254 0.267 0.261 0.267 0.361 0.295 0.237 0.297 0.378 0.368 0.307 0.389 0.365 0.300 0.256 0.313 0.292 0.246 0.212 0.253 0.266 0.226 0.197 0.238

CRWA NA 0.086 0.092 0.079 0.105 0.096 0.107 0.208 0.271 0.238 0.254 0.250 0.239 0.212 0.188 0.029 0.035 0.041 0.044 0.058 0.044 0.050 0.051 0.020 0.038 0.028 0.022 0.024 0.035 0.037 0.039 0.034 0.040 0.040 0.036

TRWA NA 0.130 0.085 0.098 0.114 0.094 0.103 0.138 0.153 0.130 0.125 0.140 0.143 0.162 0.161 0.232 0.171 0.150 0.181 0.195 0.163 0.149 0.184 0.117 0.097 0.078 0.124 0.116 0.093 0.071 0.118 0.102 0.081 0.085 0.106

EAP NA 1.751 2.154 2.055 1.608 2.225 2.195 2.240 2.121 1.755 1.563 1.394 1.572 1.647 1.912 1.400 1.629 1.701 1.870 1.698 1.738 2.000 1.977 NA NA NA NA 1.418 1.473 1.426 1.405 1.236 1.244 1.346 1.343

PIW NA NA NA NA NA NA NA 2.318 2.129 1.979 1.949 1.767 1.900 2.019 2.198 1.726 2.084 2.128 2.263 2.241 2.408 2.776 2.697 1.050 1.819 1.422 1.542 1.398 2.176 2.140 2.093 1.926 1.969 1.996 1.967

PIW2 NA 0.060 0.074 0.068 0.094 0.094 0.170 0.092 0.139 0.110 0.119 0.105 0.126 0.135 0.141 0.224 0.212 0.204 0.159 0.039 0.027 0.027 0.019 0.019 0.032 0.028 0.031 0.020 0.021 0.021 0.027 0.020 0.019 0.017 0.021

THLI NA 0.284 0.323 0.320 0.331 0.303 0.319 0.519 0.583 0.506 0.495 0.470 0.479 0.467 0.477 0.374 0.336 0.328 0.379 0.388 0.343 0.358 0.383 0.124 0.129 0.104 0.138 0.252 0.245 0.234 0.281 0.243 0.226 0.241 0.263

TRWA NA 0.131 0.091 0.113 0.105 0.101 0.111

EAP NA 1.394 1.063 1.258 1.441 1.434 1.467

PIW NA NA NA NA NA NA NA

PIW2 NA 0.056 0.083 0.084 0.072 0.090 0.102

THLI NA 0.178 0.182 0.215 0.237 0.211 0.208

Table 28. Health indices, the Netherlands, women Year 1983 1985 1987 1988 1989 1990 1991

Quarter 2 2 2 2 2 2 2

TIW NA 0.276 0.224 0.290 0.329 0.319 0.363

CRWA NA 0.094 0.075 0.080 0.077 0.100 0.068

46

Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.404 0.414 0.354 0.342 0.304 0.296 0.369 0.395 0.485 0.378 0.275 0.328 0.339 0.330 0.278 0.356 0.333 0.270 0.231 0.288 0.266 0.225 0.185 0.236 0.244 0.209 0.182 0.216

CRWA 0.212 0.202 0.240 0.201 0.177 0.190 0.246 0.258 0.078 0.090 0.090 0.081 0.089 0.097 0.100 0.098 0.050 0.062 0.052 0.058 0.052 0.087 0.084 0.082 0.083 0.089 0.096 0.086

TRWA 0.156 0.163 0.148 0.152 0.148 0.153 0.152 0.186 0.255 0.180 0.159 0.184 0.203 0.165 0.163 0.209 0.155 0.121 0.111 0.149 0.156 0.118 0.098 0.163 0.147 0.122 0.096 0.141

EAP 1.292 1.362 1.316 1.086 1.101 1.180 1.258 1.327 1.341 1.298 1.335 1.408 1.298 1.345 1.411 1.498 NA NA NA NA 1.428 1.433 1.468 1.548 1.467 1.551 1.519 1.511

PIW 0.641 0.675 0.692 0.693 0.680 0.785 0.839 0.934 1.101 1.215 1.265 1.322 1.363 1.435 1.425 1.463 0.591 1.027 0.815 0.940 0.880 1.386 1.444 1.503 1.447 1.479 1.472 1.489

PIW2 0.067 0.092 0.121 0.146 0.157 0.136 0.187 0.204 0.248 0.203 0.255 0.310 0.138 0.111 0.097 0.123 0.127 0.110 0.092 0.109 0.083 0.083 0.088 0.075 0.096 0.077 0.085 0.071

THLI 0.380 0.394 0.408 0.376 0.362 0.369 0.412 0.452 0.409 0.355 0.356 0.390 0.372 0.349 0.359 0.403 0.159 0.143 0.128 0.159 0.306 0.308 0.304 0.361 0.339 0.332 0.318 0.341

CRWA 0.035 0.032 0.034 0.048 0.055 0.079 0.078 0.067 0.078 0.079 0.076 0.055 0.062 0.078 0.084

TRWA NA 0.063 0.080 0.060 0.061 NA 0.052 NA NA NA 0.065 NA NA NA 0.060

EAP 2.328 NA NA 2.466 2.631 NA 2.424 NA NA NA 2.801 NA NA NA 2.625

PIW 2.815 2.296 2.177 2.167 2.104 2.070 2.184 2.238 2.175 2.017 2.152 2.056 2.125 1.968 2.089

PIW2 NA 0.653 0.736 0.414 0.558 NA 0.569 NA NA NA 1.077 NA NA NA 0.732

THLI 0.211 0.200 0.218 0.279 0.305 NA 0.314 NA NA NA 0.338 NA NA NA 0.350

Table 29. Health indices, Norway, men Year 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002

Quarter 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2

TIW 0.167 0.226 0.208 0.182 0.234 0.267 0.269 0.255 0.262 0.422 0.363 0.308 0.392 0.439 0.398

47

Year 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4

TIW 0.347 0.381 0.409 0.341 0.323 0.448 0.427 0.369 0.264 0.326

CRWA 0.094 0.090 0.094 0.082 0.073 0.059 0.083 0.097 0.068 0.074

TRWA NA NA NA 0.084 NA NA NA 0.079 NA NA

EAP NA NA NA 2.599 NA NA NA 2.476 NA NA

PIW 2.022 1.977 2.093 2.076 2.120 1.946 1.946 2.017 1.870 1.945

PIW2 NA NA NA 0.767 NA NA NA 0.857 NA NA

THLI NA NA NA 0.366 NA NA NA 0.366 NA NA

CRWA 0.035 0.045 0.053 0.058 0.088 0.069 0.086 0.079 0.089 0.079 0.108 0.097 0.098 0.089 0.116 0.113 0.107 0.123 0.111 0.103 0.099 0.097 0.100 0.092 0.091

TRWA NA 0.119 0.132 0.135 0.126 NA 0.113 NA NA NA 0.109 NA NA NA 0.131 NA NA NA 0.130 NA NA NA 0.142 NA NA

EAP 2.243 NA NA 2.306 2.403 NA 2.234 NA NA NA 2.757 NA NA NA 2.657 NA NA NA 2.683 NA NA NA 2.808 NA NA

PIW 2.142 1.682 1.375 1.615 1.699 1.562 1.500 1.643 1.503 1.585 1.483 1.568 1.665 1.638 1.700 1.634 1.587 1.673 1.746 1.718 1.668 1.651 1.725 1.618 1.660

PIW2 NA 0.856 0.756 0.654 0.793 NA 0.681 NA NA NA 0.817 NA NA NA 0.838 NA NA NA 0.867 NA NA NA 0.787 NA NA

THLI 0.296 0.307 0.280 0.418 0.452 NA 0.404 NA NA NA 0.415 NA NA NA 0.481 NA NA NA 0.494 NA NA NA 0.483 NA NA

CRWA 0.179 0.171 0.128 0.137

TRWA NA NA NA NA

EAP NA NA NA NA

PIW 3.194 3.173 3.054 2.765

PIW2 NA NA NA NA

THLI 0.115 0.110 0.078 0.080

Table 30. Health indices, Norway, women Year 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.239 0.296 0.309 0.284 0.317 0.359 0.345 0.304 0.374 0.355 0.327 0.272 0.351 0.381 0.343 0.298 0.347 0.359 0.317 0.284 0.403 0.382 0.326 0.238 0.294

Table 31. Health indices, Poland, men Year 1997 1998 1999 2000

Quarter 2 2 1 1

TIW 0.179 0.173 0.233 0.197

48

Year 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.132 0.112 0.104 0.193 0.149 0.109 0.141 0.151 0.127 0.099 0.115 0.157 0.127 0.118 0.125 0.171 0.169 0.141 0.119

CRWA 0.104 0.122 0.120 0.222 0.226 0.206 0.223 0.259 0.279 0.235 0.192 0.205 0.210 0.222 0.231 0.188 0.178 0.182 0.204

TRWA NA NA NA 0.023 0.015 0.007 0.016 0.010 0.007 0.008 0.016 0.015 0.011 0.008 0.019 0.014 0.009 0.014 0.014

EAP NA NA NA 1.856 1.801 1.861 1.823 1.599 1.638 1.579 1.594 1.404 1.435 1.499 1.480 1.282 1.337 1.448 1.394

PIW 2.675 2.752 2.754 2.530 2.485 2.513 2.466 2.279 2.274 2.277 2.248 2.186 2.234 2.325 2.251 2.126 2.179 2.347 2.341

PIW2 NA NA NA 0.090 0.093 0.077 0.096 0.103 0.075 0.074 0.108 0.109 0.046 0.060 0.081 0.479 0.513 0.630 0.700

THLI 0.061 0.073 0.072 0.492 0.476 0.460 0.500 0.487 0.488 0.444 0.445 0.412 0.402 0.411 0.422 0.458 0.453 0.487 0.498

CRWA 0.400 0.349 0.285 0.255 0.252 0.239 0.229 0.176 0.192 0.183 0.200 0.250 0.282 0.246 0.199 0.246 0.266 0.259 0.227 0.204 0.231 0.241 0.249

TRWA NA NA NA NA NA NA NA 0.044 0.021 0.014 0.023 0.021 0.013 0.010 0.017 0.016 0.022 0.008 0.006 0.023 0.009 0.019 0.019

EAP NA NA NA NA NA NA NA 1.385 1.431 1.359 1.306 1.219 1.213 1.181 1.172 1.063 1.080 1.074 1.061 0.939 0.997 1.005 0.970

PIW 2.272 2.156 2.142 1.927 1.813 1.905 1.890 1.740 1.713 1.681 1.661 1.618 1.622 1.601 1.563 1.504 1.479 1.493 1.464 1.471 1.491 1.459 1.438

PIW2 NA NA NA NA NA NA NA 0.072 0.051 0.041 0.039 0.049 0.034 0.030 0.051 0.035 0.036 0.029 0.032 0.430 0.486 0.506 0.417

THLI 0.201 0.178 0.143 0.120 0.120 0.114 0.107 0.405 0.407 0.382 0.393 0.389 0.395 0.374 0.365 0.345 0.357 0.349 0.338 0.397 0.423 0.438 0.421

Table 32. Health indices, Poland, women Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.197 0.202 0.287 0.222 0.146 0.133 0.143 0.176 0.130 0.102 0.112 0.134 0.111 0.092 0.094 0.133 0.127 0.111 0.113 0.156 0.152 0.130 0.116

49

Table 33. Health indices, Portugal, men Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.306 0.282 0.282 0.216 0.226 0.273 0.383 0.360 0.329 0.319 0.334 0.299 0.277 0.242 0.235 0.227 0.229 0.179 0.189 0.222 0.247 0.204 0.262 0.217 0.374 0.360 0.296 0.363 0.444 0.398 0.362 0.371 0.281 0.261 0.226 0.262 0.222 0.204 0.198 0.235

CRWA 0.110 0.111 0.095 0.105 0.101 0.115 0.083 0.131 0.147 0.093 0.088 0.101 0.167 0.156 0.156 0.159 0.172 0.187 0.201 0.211 0.189 0.166 0.158 0.161 0.186 0.187 0.161 0.179 0.181 0.209 0.187 0.181 0.131 0.130 0.119 0.123 0.123 0.103 0.100 0.086

TRWA 0.070 0.071 0.063 0.059 0.062 0.080 0.049 0.047 0.049 0.033 0.040 0.053 0.031 0.045 0.022 0.023 0.034 0.021 0.024 0.021 0.031 0.017 0.015 0.025 0.017 0.029 0.033 0.024 0.058 0.038 0.031 0.041 0.031 0.031 0.025 0.028 0.020 0.020 0.016 0.026

EAP 3.661 3.593 3.972 3.855 3.911 3.842 3.211 0.352 0.276 0.256 0.362 0.458 2.295 2.080 1.858 1.635 1.533 1.673 1.719 1.944 2.039 2.002 2.063 2.135 2.971 3.052 3.064 2.957 3.314 3.388 3.503 3.307 1.904 1.914 2.030 1.835 1.648 1.708 1.742 1.580

PIW NA NA NA NA NA NA 0.203 0.240 0.170 0.153 0.206 0.185 2.827 2.848 2.945 3.040 2.711 3.109 2.983 3.066 3.280 3.258 3.124 3.131 3.751 3.768 3.666 3.432 3.890 3.759 3.999 3.604 2.258 2.432 2.393 2.349 2.137 2.013 2.044 1.941

PIW2 0.073 0.099 0.066 0.114 0.007 0.236 0.174 0.336 0.268 0.306 0.237 0.166 0.231 0.185 0.093 0.100 0.195 0.214 0.255 0.093 0.298 0.176 0.122 0.298 0.423 0.355 0.313 0.379 0.346 0.467 0.451 0.467 0.269 0.193 0.198 0.206 0.117 0.077 0.138 0.061

THLI 0.443 0.426 0.406 0.385 0.374 0.385 0.428 0.192 0.195 0.142 0.152 0.177 0.404 0.362 0.314 0.306 0.318 0.334 0.353 0.385 0.386 0.340 0.333 0.365 0.455 0.465 0.464 0.469 0.525 0.552 0.563 0.582 0.355 0.352 0.350 0.338 0.296 0.284 0.292 0.269

CRWA 0.187 0.142

TRWA 0.076 0.068

EAP 3.628 3.738

PIW NA NA

PIW2 0.100 0.051

THLI 0.407 0.389

Table 34. Health indices, Portugal, women Year 1986 1987

Quarter 2 2

TIW 0.285 0.299

50

Year 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.278 0.267 0.249 0.292 0.483 0.417 0.404 0.315 0.381 0.365 0.374 0.325 0.279 0.285 0.304 0.242 0.269 0.244 0.301 0.300 0.295 0.292 0.314 0.330 0.252 0.318 0.372 0.322 0.298 0.309 0.223 0.225 0.191 0.232 0.197 0.167 0.156 0.205

CRWA 0.179 0.219 0.217 0.223 0.144 0.145 0.184 0.149 0.134 0.159 0.255 0.264 0.250 0.258 0.227 0.226 0.243 0.217 0.231 0.226 0.179 0.179 0.261 0.256 0.262 0.287 0.307 0.329 0.308 0.307 0.211 0.206 0.215 0.208 0.184 0.175 0.173 0.167

TRWA 0.076 0.068 0.072 0.088 0.094 0.083 0.053 0.046 0.037 0.071 0.030 0.038 0.027 0.015 0.028 0.020 0.027 0.024 0.024 0.022 0.032 0.022 0.033 0.023 0.014 0.016 0.037 0.042 0.021 0.046 0.035 0.038 0.020 0.047 0.029 0.027 0.019 0.023

EAP 3.648 3.649 3.527 3.168 3.091 0.588 0.540 0.424 0.434 0.486 2.121 2.043 1.975 1.991 1.806 1.768 1.746 1.776 1.632 1.562 1.695 1.651 2.129 2.299 2.502 2.382 2.712 2.746 2.834 2.913 1.679 1.794 1.792 1.695 1.533 1.501 1.491 1.444

PIW NA NA NA NA 0.067 0.102 0.076 0.053 0.070 0.071 1.540 1.452 1.447 1.418 1.451 1.495 1.512 1.468 1.447 1.452 1.464 1.419 1.811 1.801 1.897 1.731 1.961 1.963 2.182 2.023 1.267 1.391 1.307 1.283 1.130 1.034 1.054 1.063

PIW2 0.020 0.010 0.084 0.072 0.284 0.745 0.252 0.169 0.193 0.392 0.042 0.232 0.157 0.153 0.221 0.121 0.132 0.113 0.144 0.142 0.212 0.168 0.160 0.310 0.342 0.152 0.212 0.238 0.182 0.189 0.203 0.158 0.119 0.114 0.126 0.174 0.092 0.136

THLI 0.406 0.429 0.430 0.405 0.555 0.267 0.227 0.177 0.170 0.232 0.446 0.447 0.427 0.435 0.393 0.369 0.382 0.379 0.362 0.339 0.339 0.340 0.439 0.460 0.498 0.504 0.579 0.594 0.594 0.656 0.395 0.406 0.397 0.404 0.352 0.339 0.330 0.328

CRWA 0.097 0.051 0.054 0.064 0.067

TRWA 0.027 0.015 0.016 0.018 0.037

EAP 1.584 1.738 1.745 1.700 1.226

PIW 0.541 0.555 0.518 0.579 0.500

PIW2 0.033 0.039 0.034 0.025 0.024

THLI 0.405 0.400 0.402 0.392 0.337

Table 35. Health indices, Slovakia, men Year 1998 1998 1998 1998 1999

Quarter 1 2 3 4 1

TIW 0.229 0.265 0.218 0.265 0.309

51

Year 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.233 0.224 0.272 0.351 0.179 0.222 0.214 0.311 0.251 0.181 0.206 0.226 0.221 0.142 0.190 0.250 0.130 0.137 0.114 0.205 0.127 0.128 0.152

CRWA 0.074 0.063 0.077 0.082 0.064 0.059 0.064 0.070 0.103 0.093 0.085 0.076 0.082 0.070 0.059 0.058 0.064 0.054 0.057 0.064 0.087 0.075 0.075

TRWA 0.033 0.017 0.040 0.058 0.028 0.017 0.038 0.032 0.036 0.015 0.022 0.033 0.027 0.030 0.025 0.036 0.039 0.024 0.031 0.026 0.016 0.014 0.016

EAP 1.163 1.172 1.163 1.168 1.137 1.190 1.237 0.794 0.835 0.986 1.065 1.105 1.238 1.362 1.199 0.956 1.044 1.025 1.129 1.101 1.147 1.321 1.306

PIW 0.463 0.417 0.478 0.412 0.371 0.377 0.372 2.107 2.128 2.294 2.324 2.102 2.161 2.251 2.155 1.941 2.124 2.188 2.104 2.217 2.374 2.465 2.405

PIW2 0.023 0.021 0.018 0.027 0.015 0.024 0.026 0.166 0.176 0.214 0.214 0.201 0.210 0.336 0.197 0.179 0.200 0.170 0.151 0.238 0.214 0.193 0.221

THLI 0.336 0.324 0.342 0.381 0.333 0.323 0.345 0.260 0.290 0.305 0.318 0.327 0.351 0.386 0.310 0.279 0.288 0.252 0.281 0.317 0.307 0.309 0.312

CRWA 0.168 0.118 0.115 0.112 0.057 0.058 0.058 0.066 0.065 0.061 0.065 0.081 0.082 0.068 0.064 0.074 0.055 0.062 0.066 0.072

TRWA 0.082 0.033 0.025 0.021 0.048 0.021 0.015 0.048 0.076 0.035 0.018 0.036 0.038 0.012 0.012 0.019 0.023 0.018 0.018 0.034

EAP 1.399 1.407 1.374 1.333 1.146 1.109 1.091 1.179 1.224 1.207 1.181 1.189 1.063 1.089 1.161 1.203 1.021 0.937 0.944 0.896

PIW 0.489 0.454 0.451 0.467 0.430 0.373 0.310 0.283 0.280 0.290 0.270 0.295 1.608 1.633 1.627 1.638 1.509 1.507 1.497 1.426

PIW2 0.041 0.029 0.031 0.039 0.034 0.030 0.028 0.034 0.022 0.030 0.031 0.037 0.155 0.156 0.165 0.240 0.260 0.229 0.247 0.332

THLI 0.607 0.551 0.537 0.531 0.466 0.440 0.434 0.487 0.510 0.486 0.468 0.480 0.339 0.328 0.344 0.387 0.333 0.305 0.310 0.335

Table 36. Health indices, Slovakia, women Year 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.266 0.244 0.246 0.251 0.358 0.283 0.213 0.183 0.303 0.171 0.111 0.195 0.289 0.229 0.181 0.206 0.226 0.187 0.113 0.176

52

Year 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4

TIW 0.233 0.130 0.137 0.114 0.190 0.114 0.116 0.140

CRWA 0.082 0.086 0.083 0.097 0.101 0.084 0.104 0.066

TRWA 0.037 0.049 0.021 0.038 0.036 0.029 0.024 0.028

EAP 0.945 0.878 0.887 0.880 0.901 0.998 1.038 1.180

PIW 1.360 1.365 1.294 1.248 1.353 1.385 1.435 1.524

PIW2 0.303 0.169 0.174 0.154 0.210 0.173 0.134 0.212

THLI 0.318 0.279 0.267 0.284 0.307 0.304 0.302 0.335

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

TRWA 0.044 0.105 0.027 0.077 0.055 0.028 0.034 0.250 0.056 0.230 0.275 0.159 0.055 0.129 0.161 0.050 0.040 0.026 0.036 0.032 0.016 0.038 0.043 0.056 0.082 0.051 0.060

EAP 0.468 0.726 0.419 0.556 0.362 0.638 0.635 0.671 0.414 0.346 0.349 0.486 0.398 0.446 0.505 0.472 0.387 0.425 0.638 0.617 0.359 0.600 1.145 0.729 0.700 0.691 0.640

PIW 0.627 0.301 0.435 0.285 0.312 0.286 0.242 1.184 1.113 1.131 0.863 1.122 0.957 0.823 0.938 0.973 1.019 0.949 0.889 0.939 0.938 0.934 1.004 1.201 1.292 1.227 1.289

PIW2 0.411 0.457 0.862 0.561 1.027 0.521 1.022 0.056 0.148 0.116 0.124 0.106 0.120 0.158 0.128 0.268 0.179 0.069 0.122 0.104 0.098 0.090 0.169 0.128 0.163 0.086 0.152

THLI 0.155 0.248 0.188 0.198 0.190 0.168 0.218 0.254 0.100 0.210 0.240 0.172 0.093 0.152 0.181 0.111 0.086 0.070 0.109 0.100 0.058 0.103 0.183 0.140 0.154 0.120 0.132

CRWA NA NA NA NA

TRWA 0.051 0.113 0.091 0.095

EAP 0.409 0.441 0.284 0.293

PIW 0.369 0.273 0.221 0.224

PIW2 0.723 0.524 0.613 0.459

THLI 0.175 0.202 0.174 0.154

Table 37. Health indices, Slovenia, men Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.234 0.263 0.264 0.399 0.257 0.264 0.308 0.364 0.246 0.245 0.243 0.264 0.193 0.257 0.277 0.275 0.209 0.218 0.258 0.257 0.261 0.236 0.286 0.400 0.263 0.221 0.288

Table 38. Health indices, Slovenia, women Year 1996 1997 1998 1999

Quarter 2 2 2 1

TIW 0.285 0.259 0.367 0.399

53

Year 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.267 0.210 0.305 0.344 0.235 0.263 0.295 0.231 0.184 0.234 0.277 0.267 0.201 0.209 0.228 0.257 0.261 0.215 0.262 0.352 0.248 0.200 0.281

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

TRWA 0.028 0.041 0.058 0.238 0.066 0.182 0.254 0.139 0.035 0.181 0.203 0.053 0.063 0.014 0.035 0.049 0.060 0.048 0.039 0.060 0.080 0.029 0.060

EAP 0.251 0.347 0.374 0.310 0.398 0.372 NA 0.225 0.217 0.246 0.154 NA 0.234 0.258 0.212 0.298 0.271 0.198 0.327 0.272 0.291 0.297 0.302

PIW 0.207 0.200 0.308 0.828 0.705 0.773 0.746 0.794 0.597 0.662 0.676 0.613 0.700 0.817 0.751 0.630 0.712 0.643 0.792 0.840 0.901 0.785 0.871

PIW2 0.640 0.642 0.895 0.180 0.192 0.129 0.104 0.029 0.088 0.241 0.122 0.094 0.093 0.114 0.122 0.168 0.062 0.070 0.093 0.051 0.052 0.083 0.086

THLI 0.121 0.151 0.189 0.196 0.108 0.173 NA 0.112 0.057 0.164 0.151 NA 0.074 0.049 0.060 0.080 0.075 0.061 0.079 0.077 0.091 0.069 0.089

CRWA NA 0.019 0.016 0.017 0.015 0.012 0.007 0.012 0.011 0.012 0.014 0.009 0.007 0.007 0.006 0.006 0.011 0.007 0.009 0.008

TRWA NA 0.054 0.032 0.022 0.023 0.025 0.016 0.014 0.025 0.019 0.015 0.012 0.017 0.011 0.013 0.012 0.023 0.017 0.007 0.012

EAP NA 0.711 0.630 0.692 0.687 0.662 1.185 1.000 0.960 1.078 1.070 1.179 1.042 1.076 1.124 1.115 1.236 1.313 1.365 1.345

PIW NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 1.613 1.777 1.828 1.831

PIW2 NA 0.056 0.053 0.044 0.061 0.077 0.090 0.057 0.060 0.064 0.067 0.073 0.074 0.089 0.075 0.066 0.475 0.524 0.492 0.527

THLI NA 0.130 0.104 0.098 0.098 0.098 0.235 0.232 0.237 0.245 0.237 0.243 0.203 0.202 0.201 0.199 0.291 0.286 0.277 0.291

Table 39. Health indices, Spain, men Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4

TIW 0.178 0.149 0.174 0.172 0.181 0.188 0.190 0.199 0.183 0.187 0.180 0.188 0.168 0.158 0.157 0.155 0.170 0.203 0.182 0.172

54

Year 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.211 0.188 0.186 0.189 0.240 0.237 0.199 0.232 0.237 0.246 0.221 0.232 0.251 0.225 0.231 0.232 0.236 0.255 0.256 0.235

CRWA 0.011 0.011 0.009 0.006 0.009 0.010 0.007 0.008 0.008 0.009 0.007 0.007 0.009 0.004 0.006 0.005 0.005 0.008 0.009 0.005

TRWA 0.021 0.014 0.008 0.015 0.017 0.017 0.010 0.016 0.016 0.017 0.010 0.013 0.015 0.013 0.009 0.016 0.011 0.018 0.012 0.017

EAP 1.371 1.472 1.525 1.488 1.361 1.517 1.516 1.497 1.299 1.359 1.345 1.325 1.265 1.303 1.328 1.313 1.248 1.317 1.327 1.325

PIW 1.987 2.031 2.098 2.073 1.998 2.044 2.076 2.013 1.821 1.933 1.868 1.818 1.767 1.805 1.832 1.772 1.750 1.782 1.801 1.779

PIW2 0.534 0.555 0.541 0.544 0.506 0.535 0.432 0.470 0.491 0.610 0.525 0.540 0.470 0.500 0.444 0.451 0.512 0.515 0.489 0.452

THLI 0.293 0.294 0.289 0.295 0.273 0.290 0.266 0.280 0.258 0.274 0.255 0.268 0.253 0.249 0.243 0.258 0.255 0.266 0.255 0.257

CRWA NA 0.038 0.026 0.024 0.023 0.018 0.014 0.017 0.011 0.018 0.008 0.010 0.010 0.009 0.006 0.008 0.005 0.010 0.010 0.010 0.013 0.017 0.012

TRWA NA 0.043 0.023 0.023 0.025 0.020 0.009 0.012 0.023 0.026 0.015 0.013 0.017 0.012 0.008 0.010 0.023 0.016 0.011 0.014 0.018 0.015 0.019

EAP NA 0.493 0.414 0.374 0.376 0.384 0.603 0.691 0.648 0.667 0.686 0.684 0.605 0.569 0.578 0.606 0.640 0.622 0.677 0.753 0.836 0.844 0.830

PIW NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.377 0.408 0.414 0.414 0.468 0.477 0.464

PIW2 NA 0.068 0.045 0.060 0.046 0.068 0.038 0.035 0.021 0.047 0.026 0.040 0.037 0.030 0.038 0.038 0.234 0.267 0.263 0.343 0.294 0.310 0.261

THLI NA 0.063 0.052 0.050 0.052 0.054 0.109 0.134 0.132 0.144 0.137 0.140 0.117 0.110 0.111 0.117 0.167 0.169 0.178 0.208 0.208 0.210 0.199

Table 40. Health indices, Spain, women Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000

Quarter 2 2 2 2 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3

TIW 0.151 0.110 0.129 0.162 0.171 0.187 0.199 0.193 0.164 0.192 0.183 0.210 0.192 0.161 0.145 0.168 0.182 0.207 0.175 0.200 0.219 0.204 0.188

55

Year 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.216 0.194 0.193 0.165 0.197 0.202 0.214 0.179 0.192 0.205 0.187 0.192 0.192 0.192 0.210 0.214 0.197

CRWA 0.012 0.019 0.012 0.009 0.009 0.007 0.013 0.009 0.012 0.009 0.009 0.010 0.006 0.008 0.009 0.009 0.006

TRWA 0.022 0.012 0.013 0.013 0.014 0.019 0.021 0.005 0.010 0.017 0.010 0.006 0.015 0.013 0.014 0.013 0.016

EAP 0.856 0.792 0.787 0.761 0.766 0.673 0.679 0.722 0.743 0.745 0.739 0.737 0.732 0.673 0.678 0.710 0.751

PIW 0.484 0.484 0.490 0.477 0.478 0.431 0.488 0.485 0.466 0.479 0.465 0.461 0.466 0.451 0.458 0.468 0.473

PIW2 0.320 0.312 0.278 0.244 0.311 0.222 0.330 0.314 0.295 0.248 0.289 0.291 0.263 0.245 0.278 0.249 0.295

THLI 0.216 0.198 0.190 0.178 0.194 0.165 0.190 0.186 0.192 0.185 0.186 0.186 0.185 0.173 0.182 0.178 0.194

CRWA 0.121 0.133 0.101 0.115 0.141 0.123 0.129 0.143 0.135 0.123 0.134 0.128 0.137 0.139 0.170 0.167 0.157 0.172 0.153 0.168 0.168 0.154

TRWA 0.096 0.075 0.093 0.105 0.149 0.133 0.205 0.116 0.097 0.150 0.180 0.125 0.102 0.179 0.231 0.144 0.131 0.217 0.194 0.153 0.116 0.202

EAP 0.347 0.358 0.285 0.326 0.350 0.966 1.086 0.935 0.205 0.250 0.354 0.396 0.461 0.510 0.648 0.808 0.757 0.702 0.535 0.543 0.520 0.428

PIW 0.223 0.213 0.238 0.237 0.296 0.338 0.384 0.393 0.352 0.380 0.365 0.394 0.406 0.418 0.459 0.418 0.454 0.429 0.342 0.390 0.389 0.375

PIW2 0.033 0.004 NA 0.010 0.004 0.112 0.108 0.113 0.095 0.082 0.072 0.082 0.068 0.080 NA NA NA NA NA NA 0.071 0.075

THLI 0.214 0.204 0.180 0.205 0.260 0.241 0.317 0.253 0.226 0.260 0.304 0.263 0.248 0.320 0.394 0.345 0.322 0.397 0.339 0.318 0.298 0.342

Table 41. Health indices, Sweden, men Year 1995 1996 1997 1998 1999 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.169 0.144 0.123 0.190 0.208 0.244 0.513 0.464 0.422 0.489 0.523 0.469 0.430 0.495 0.605 0.563 0.500 0.537 0.496 0.436 0.400 0.429

56

Table 42. Health indices, Sweden, women Year 1995 1996 1997 1998 1999 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.243 0.206 0.232 0.272 0.361 0.396 0.457 0.419 0.378 0.431 0.465 0.417 0.388 0.449 0.544 0.497 0.446 0.485 0.440 0.390 0.353 0.380

CRWA 0.215 0.242 0.233 0.199 0.222 0.210 0.233 0.225 0.236 0.246 0.234 0.248 0.250 0.233 0.304 0.331 0.336 0.337 0.287 0.307 0.299 0.304

TRWA 0.156 0.117 0.149 0.140 0.242 0.231 0.309 0.219 0.163 0.257 0.292 0.243 0.178 0.276 0.349 0.255 0.199 0.340 0.313 0.271 0.202 0.313

57

EAP 0.573 0.368 0.548 0.329 0.285 1.186 1.144 1.144 0.339 0.396 0.434 0.577 0.647 0.633 0.790 0.853 0.776 0.783 0.722 0.759 0.735 0.777

PIW 0.266 0.287 0.308 0.322 0.426 0.545 0.498 0.613 0.561 0.553 0.489 0.502 0.518 0.529 0.596 0.593 0.511 0.549 0.464 0.520 0.523 0.539

PIW2 0.070 0.078 0.036 0.058 0.022 0.085 0.093 0.094 0.103 0.103 0.091 0.065 0.100 0.093 NA NA NA NA NA NA 0.071 0.073

THLI 0.363 0.327 0.356 0.295 0.373 0.381 0.471 0.402 0.370 0.453 0.471 0.459 0.416 0.477 0.592 0.550 0.506 0.613 0.544 0.532 0.489 0.581

Annex 2. Health inequality indices by country and sex

Table 43. Health inequality indices, Austria, men Year 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.193 -0.216 -0.160 -0.243 -0.125 NA NA NA -0.267 -0.063 NA NA -0.142 NA NA NA -0.109 NA NA NA -0.088 -0.132 NA NA -0.142 -0.298 -0.204 -0.247

CRWA -0.092 -0.373 -0.143 -0.043 -0.248 NA NA NA -0.306 -0.467 NA NA -0.168 NA NA NA -0.297 NA NA NA -0.271 0.059 NA NA 0.110 -0.011 -0.100 0.090

TRWA 0.053 -0.106 -0.245 0.081 0.035 NA NA NA 0.240 0.176 NA NA 0.092 NA NA NA -0.249 NA NA NA 0.083 0.060 NA NA -0.001 -0.107 0.163 0.247

PIW2 -0.515 NA 0.041 0.209 NA NA NA NA 0.570 0.545 NA NA -0.248 NA NA NA -0.076 NA NA NA -0.852 NA NA NA NA NA NA NA

THLI -0.034 -0.152 -0.211 0.072 -0.050 NA NA NA 0.072 0.026 NA NA 0.050 NA NA NA -0.243 NA NA NA -0.121 0.018 NA NA 0.016 -0.037 -0.004 0.192

CRWA -0.183 -0.082 -0.164 -0.072 -0.160 NA NA NA -0.106 -0.144

TRWA 0.105 0.071 -0.044 0.220 0.165 NA NA NA 0.214 0.445

PIW2 0.380 -1.075 -0.537 -0.007 -0.272 NA NA NA 0.060 -0.064

THLI 0.081 -0.014 -0.125 0.106 -0.079 NA NA NA 0.040 0.115

Table 44. Health inequality indices, Austria, women Year 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000

Quarter 1 1 1 1 1 2 3 4 1 2

TIW 0.088 0.030 -0.022 0.059 -0.031 NA NA NA 0.104 0.037

58

Year 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW NA NA 0.009 NA NA NA 0.011 NA NA NA -0.088 -0.081 NA NA 0.031 0.059 -0.037 -0.145

CRWA NA NA -0.268 NA NA NA -0.037 NA NA NA -0.305 -0.430 NA NA -0.117 -0.085 -0.202 -0.029

TRWA NA NA 0.008 NA NA NA 0.116 NA NA NA 0.351 -0.006 NA NA 0.081 0.227 0.159 0.354

PIW2 NA NA -0.209 NA NA NA 0.217 NA NA NA 0.643 NA NA NA 1.617 NA NA NA

THLI NA NA -0.147 NA NA NA 0.075 NA NA NA 0.211 -0.306 NA NA -0.044 0.011 -0.020 0.058

CRWA 0.001 -0.183 0.013 -0.405 -0.081 -0.344 -0.148 -0.456 -0.619 -0.277 -0.443 -0.312 -0.066 -0.036 0.074 -0.189 -0.060 -0.469 -0.312 -0.350 -0.090 -0.045 0.087 -0.213 -0.042

TRWA 0.001 -0.057 -0.194 0.122 -0.120 -0.225 -0.383 -0.212 -0.521 -0.354 -0.317 -0.166 -0.006 -0.227 -0.368 -0.253 -0.165 -0.243 0.098 -0.091 -0.025 -0.181 -0.451 0.007 -0.092

PIW2 NA 0.659 -0.143 -0.719 -0.434 0.245 0.095 0.245 -0.223 -0.358 NA 0.493 -0.705 -0.134 -0.226 NA NA NA NA NA NA NA 0.112 NA 0.534

THLI 0.001 -0.045 -0.063 -0.087 -0.114 -0.295 -0.281 -0.252 -0.465 -0.309 -0.401 -0.161 -0.077 -0.156 -0.118 -0.188 -0.077 -0.322 -0.031 -0.189 -0.226 -0.128 -0.169 -0.063 -0.130

Table 45. Health inequality indices, Belgium, men Year 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003

Quarter 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2

TIW 0.001 -0.200 -0.266 -0.339 -0.223 -0.301 -0.261 -0.315 -0.422 -0.389 -0.304 -0.314 -0.191 -0.238 -0.074 -0.218 -0.172 -0.304 -0.366 -0.179 -0.273 -0.276 -0.297 -0.385 -0.285

59

Year 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4

TIW -0.169 -0.263 -0.297 -0.253 -0.289 -0.321

CRWA -0.202 -0.518 -0.253 0.231 -0.166 -0.559

TRWA 0.034 0.198 -0.268 -0.171 -0.089 -0.144

PIW2 NA NA NA NA -1.220 0.385

THLI -0.149 -0.093 -0.220 0.023 -0.338 -0.318

CRWA 0.001 -0.056 -0.109 0.066 -0.247 -0.081 0.098 NA -0.118 -0.237 -0.136 -0.134 -0.008 0.276 -0.075 -0.270 -0.168 -0.264 0.075 -0.284 -0.002 -0.041 -0.228 -0.115 -0.166 -0.350 -0.067 0.050 -0.029 -0.176 -0.267

TRWA NA 0.394 -0.008 0.006 -0.146 -0.034 -0.228 -0.113 0.066 -0.262 -0.085 -0.316 -0.005 -0.011 0.325 -0.286 0.057 -0.238 -0.128 -0.190 -0.015 -0.179 0.398 0.238 -0.171 -0.276 -0.415 -0.199 0.256 0.091 0.064

PIW2 NA -0.170 0.531 0.798 -0.236 NA 0.021 0.472 0.227 -0.281 -0.241 0.144 -0.509 0.172 NA NA -0.309 NA -0.272 NA NA NA NA NA NA -0.995 NA -0.362 -0.371 -0.463 -0.218

THLI 0.001 0.055 -0.080 0.018 -0.208 -0.054 -0.146 -0.058 -0.028 -0.229 -0.126 -0.201 0.003 -0.049 0.059 -0.255 -0.037 -0.219 -0.005 -0.232 -0.052 -0.083 0.104 -0.029 -0.136 -0.293 -0.365 -0.107 0.106 -0.076 -0.059

TRWA -0.098 -0.194

PIW2 NA NA

THLI -0.113 -0.178

Table 46. Health inequality indices, Belgium, women Year 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.001 -0.033 0.033 0.058 -0.017 -0.050 -0.109 -0.064 -0.195 -0.149 -0.072 -0.066 0.059 0.010 -0.153 -0.128 -0.051 -0.059 -0.139 -0.135 -0.125 -0.219 -0.236 -0.031 -0.083 -0.164 -0.051 0.035 -0.111 -0.140 -0.199

Table 47. Health inequality indices, the Czech Republic, men Year 1997 1998

Quarter 2 1

TIW -0.247 -0.246

CRWA -0.214 -0.240

60

Year 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.268 -0.259 -0.219 -0.226 -0.203 -0.289 -0.232 -0.247 -0.184 -0.178 -0.004 -0.352 -0.314 -0.303 -0.284 -0.370 -0.356 -0.234 -0.318 -0.263 -0.188 -0.222 -0.203 -0.236 -0.081 -0.170 -0.317

CRWA -0.286 -0.314 -0.349 -0.373 -0.506 -0.396 -0.492 -0.230 -0.382 -0.353 -0.336 -0.128 -0.212 -0.103 0.077 -0.032 -0.059 -0.258 -0.321 -0.307 -0.208 -0.262 -0.347 -0.174 -0.234 -0.211 -0.066

TRWA -0.005 0.182 0.009 -0.087 0.077 0.082 -0.086 -0.085 -0.236 -0.088 -0.094 -0.049 -0.259 -0.214 -0.372 -0.089 -0.175 0.350 -0.165 -0.060 -0.110 -0.098 -0.139 -0.164 -0.453 -0.488 -0.188

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA -0.055 0.814 0.815 -0.032 -0.559 -0.419 0.257 0.192 0.209 0.331 0.139

THLI -0.242 -0.182 -0.222 -0.201 -0.375 -0.264 -0.351 -0.258 -0.377 -0.323 -0.256 -0.128 -0.255 -0.146 0.012 0.011 -0.069 -0.112 -0.202 -0.201 -0.125 -0.207 -0.312 -0.101 -0.234 -0.240 -0.146

TRWA -0.104 -0.313 -0.092 -0.218 -0.325 -0.176 -0.386 -0.370 0.168 -0.117 -0.197 -0.174 -0.152 -0.258 -0.198 -0.016

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.253 -0.250 -0.119 -0.166 -0.306 -0.229 -0.315 -0.224 -0.072 -0.112 -0.026 0.085 0.010 -0.070 -0.274 -0.188

Table 48. Health inequality indices, the Czech Republic, women Year 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001

Quarter 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3

TIW -0.171 -0.189 -0.224 -0.133 -0.163 -0.048 -0.140 -0.191 -0.190 -0.178 -0.273 -0.211 -0.238 -0.198 -0.210 -0.156

CRWA -0.291 -0.229 -0.196 -0.221 -0.282 -0.312 -0.254 -0.190 -0.144 -0.030 0.149 0.081 0.021 -0.064 -0.305 -0.304

61

Year 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.101 -0.161 -0.166 -0.214 -0.130 -0.166 -0.277 -0.246 -0.160 -0.248 -0.170 -0.175 -0.244

CRWA -0.303 -0.369 -0.321 -0.326 -0.270 -0.189 -0.244 -0.221 -0.297 -0.305 -0.315 -0.234 -0.306

TRWA -0.266 -0.157 0.100 -0.241 -0.262 0.008 -0.210 -0.020 -0.106 -0.053 -0.269 0.096 0.164

PIW2 NA -0.120 -0.128 -0.311 -0.428 -0.628 -0.430 -0.402 -1.201 -0.200 0.253 0.550 0.729

THLI -0.257 -0.279 -0.113 -0.278 -0.238 -0.074 -0.202 -0.214 -0.265 -0.208 -0.275 -0.139 -0.170

CRWA -0.637 -0.336 0.333 0.017 -0.434 -0.266 -0.241 0.033 -0.398 -0.342 -0.182 -0.029 0.239 -0.090 -0.524 -0.542 -0.566 -0.453 0.302 -0.086 -0.321 -0.371 -0.447 -0.203 -0.405 -0.102 -0.565 -0.573 -0.432 -0.203

TRWA -0.196 -0.156 0.028 -0.163 -0.027 -0.441 -0.329 -0.213 0.104 -0.099 0.054 -0.040 -0.140 0.145 0.033 -0.024 -0.137 -0.296 -0.095 0.260 -0.140 0.001 -0.180 0.149 0.041 -0.239 0.030 -0.222 0.076 -0.152

PIW2 NA -0.146 NA NA 0.186 NA NA NA -0.784 -0.210 0.001 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.198 -0.141 0.127 -0.142 -0.149 -0.373 -0.273 -0.138 -0.307 -0.090 -0.015 -0.028 -0.022 0.020 -0.146 -0.100 -0.376 -0.373 0.044 0.092 -0.218 -0.192 -0.269 0.005 -0.255 -0.236 -0.277 -0.342 -0.229 -0.154

Table 49. Health inequality indices, Denmark, men Year 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004

Quarter 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3

TIW -0.228 -0.183 -0.314 -0.503 -0.431 -0.373 -0.255 -0.322 -0.172 -0.407 -0.199 -0.299 -0.360 -0.159 -0.407 -0.263 -0.435 -0.298 -0.332 -0.307 -0.265 -0.313 0.012 -0.157 -0.463 -0.230 -0.223 -0.323 -0.480 -0.095

62

Year 2004

Quarter 4

TIW -0.240

CRWA -0.362

TRWA 0.038

PIW2 NA

THLI -0.243

CRWA 0.099 0.036 -0.223 -0.459 -0.429 -0.033 -0.084 -0.190 -0.191 0.169 -0.274 -0.474 -0.159 -0.141 -0.061 -0.355 -0.078 -0.406 -0.311 -0.360 -0.303 -0.486 -0.349 -0.400 -0.389 -0.267 -0.488 -0.348 -0.013 -0.339 -0.463

TRWA 0.101 -0.110 -0.062 -0.059 -0.048 -0.039 -0.201 -0.167 0.206 -0.125 -0.057 -0.124 -0.313 0.025 -0.265 -0.132 0.061 -0.040 -0.395 -0.032 -0.130 0.054 -0.160 -0.159 -0.194 0.075 -0.186 -0.032 -0.259 -0.163 -0.038

PIW2 0.399 -0.333 -0.715 0.073 0.110 -0.233 -0.062 -0.151 -0.221 -0.197 -0.939 NA -0.344 NA -0.628 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI 0.118 -0.020 -0.126 -0.201 -0.148 0.142 -0.055 -0.199 0.152 0.085 -0.093 -0.207 -0.291 -0.024 -0.180 -0.172 -0.017 -0.162 -0.280 -0.143 -0.178 -0.173 -0.176 -0.244 -0.251 -0.012 -0.382 -0.115 -0.109 -0.351 -0.233

CRWA 0.062 -0.407 0.074 0.700 NA 0.075 0.219

TRWA 0.214 0.384 0.029 -0.445 0.697 0.166 1.197

PIW2 NA 0.055 -0.565 NA NA NA NA

THLI -0.028 0.096 -0.128 -0.302 0.697 0.006 0.783

Table 50. Health inequality indices, Denmark, women Year 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.075 -0.145 -0.139 -0.017 -0.213 -0.176 -0.012 -0.127 -0.157 -0.159 -0.391 -0.034 0.047 -0.370 -0.162 -0.155 0.058 -0.275 -0.148 -0.183 -0.097 -0.117 -0.162 -0.146 -0.312 -0.235 -0.185 -0.164 -0.086 0.004 -0.215

Table 51. Health inequality indices, Estonia, men Year 1997 1998 1999 2000 2000 2000 2000

Quarter 2 2 2 1 2 3 4

TIW -0.273 -0.079 0.003 0.224 -0.121 -0.287 -0.399

63

Year 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.038 0.065 0.796 -0.255 -0.169 -0.185 -0.153 -0.036 -0.291 -0.272 -0.592 -0.526 0.343 -0.311 -0.707 -0.290

CRWA -0.873 -0.816 0.304 -0.272 -0.551 0.012 0.611 -0.781 -0.774 0.329 -0.245 -0.865 -1.089 -0.090 -0.075 0.694

TRWA -0.843 -0.067 -0.228 -0.768 NA 0.588 NA NA NA NA NA 0.127 0.042 -1.306 0.829 0.773

PIW2 NA NA NA NA NA NA NA NA -0.908 NA NA NA NA NA NA NA

THLI -0.858 -0.369 -0.095 -0.625 -0.551 0.396 0.611 -0.781 -0.818 0.329 -0.245 -0.369 -0.241 -0.394 0.377 0.747

CRWA -0.693 -0.711 -0.145 -0.430 -0.302 -0.251 -0.202 -0.199 -0.609 -0.640 -0.406 -0.612 -0.617 -0.551 -0.476 -0.627 -1.071 NA -0.103 -0.592 -0.750 0.321 0.506

TRWA -0.012 -0.241 -0.625 -0.160 -0.449 -0.339 0.255 -0.160 -0.709 -0.362 0.224 0.679 0.978 0.581 -0.333 -0.434 1.078 -0.745 NA 0.466 -1.275 NA NA

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA -0.348 NA 0.644 NA

THLI 0.039 -0.387 -0.307 -0.301 -0.413 -0.239 -0.146 -0.218 -0.687 -0.611 -0.196 -0.289 -0.093 -0.268 -0.396 -0.555 0.004 -0.745 -0.103 -0.324 -0.779 0.321 0.506

Table 52. Health inequality indices, Estonia, women Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.002 0.026 -0.285 -0.319 -0.737 -0.231 0.472 -0.069 -1.002 0.195 -0.035 0.118 0.326 -0.206 -0.557 -0.239 -0.829 0.403 -0.184 -0.633 -0.618 0.510 -0.576

64

Table 53. Health inequality indices, Finland, men Year 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.286 NA -0.219 NA NA -0.317 -0.136 -0.151 -0.443 -0.305 -0.217 -0.331 -0.179 -0.283 -0.362 -0.285 -0.192 -0.232 -0.195 -0.177 -0.399 -0.538 -0.477 -0.555 -0.426 -0.592 -0.531 -0.449 -0.475

CRWA -0.243 NA -0.874 NA NA -0.197 -0.277 0.009 0.153 -0.096 -0.162 -0.037 -0.045 -0.044 -0.393 -0.434 -0.148 -0.116 -0.516 -0.293 -0.490 -0.100 0.344 -0.826 -0.335 -0.407 -0.410 -0.492 -0.343

TRWA -0.167 NA 0.208 NA NA -0.181 -0.217 -0.216 -0.037 -0.059 0.048 -0.194 -0.196 -0.042 -0.079 -0.017 -0.112 0.010 -0.154 -0.235 -0.021 -0.445 -0.289 -0.506 -0.352 -0.481 -0.308 -0.440 -0.439

PIW2 NA NA NA NA NA NA -0.894 -0.253 NA -0.231 0.057 -0.895 -0.382 NA -0.296 -0.817 0.423 -0.127 -1.306 0.524 0.242 -1.013 NA -1.291 NA -1.181 -0.403 NA -0.175

THLI -0.207 NA -0.113 NA NA NA -0.200 -0.075 -0.087 -0.052 -0.065 -0.147 -0.184 -0.047 -0.073 -0.183 -0.214 -0.035 -0.245 -0.265 -0.083 -0.386 -0.066 -0.539 -0.333 -0.458 -0.325 -0.398 -0.418

CRWA 0.179 NA -0.258 NA NA -0.112 0.027 -0.328 -0.237 -0.243 0.008 -0.082 -0.119

TRWA 0.072 NA -0.319 NA NA -0.136 0.060 -0.028 -0.018 -0.031 0.110 -0.049 -0.164

PIW2 NA NA NA NA NA NA -0.292 -0.742 0.335 -0.585 0.098 NA NA

THLI 0.028 NA -0.372 NA NA NA 0.029 -0.004 -0.017 -0.020 0.066 -0.002 -0.118

Table 54. Health inequality indices, Finland, women Year 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000

Quarter 2 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.159 NA -0.108 NA NA -0.048 -0.117 -0.018 -0.197 -0.184 -0.061 -0.139 -0.079

65

Year 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.146 -0.183 -0.136 -0.111 -0.313 -0.062 -0.164 -0.107 -0.325 -0.332 -0.451 -0.400 -0.361 -0.336 -0.285 -0.418

CRWA -0.066 -0.047 -0.051 -0.304 -0.288 0.005 -0.242 -0.098 -0.593 -0.235 -0.349 -0.101 -0.355 -0.370 -0.093 -0.095

TRWA -0.085 -0.069 -0.144 -0.033 0.029 0.028 0.183 -0.003 -0.202 -0.482 -0.343 -0.211 -0.177 -0.225 -0.248 -0.226

PIW2 0.077 -0.440 -0.477 -0.620 -0.165 0.048 -0.587 -0.762 0.409 -0.628 -0.428 -0.405 0.015 0.137 0.103 -0.567

THLI -0.060 -0.021 -0.028 -0.078 -0.009 0.054 -0.022 -0.011 -0.268 -0.377 -0.279 -0.176 -0.243 -0.238 -0.204 -0.196

CRWA NA NA NA NA NA NA NA NA -0.344 -0.430 -0.428 -0.413 -0.268 -0.359 -0.417 -0.485 -0.282 -0.248 -0.413

TRWA -0.029 -0.250 -0.239 -0.083 -0.197 -0.289 -0.182 -0.072 -0.256 -0.162 -0.032 -0.025 -0.262 -0.175 -0.088 -0.107 -0.293 -0.134 -0.242

PIW2 -0.887 -0.075 -0.771 -0.614 NA NA -0.070 -0.745 -0.275 -0.110 -0.592 -0.333 -0.006 -1.034 -0.914 -0.385 -0.850 -0.108 NA

THLI -0.030 -0.250 -0.239 -0.084 -0.197 -0.289 -0.179 -0.081 -0.314 -0.251 -0.146 -0.220 -0.312 -0.211 -0.200 -0.174 -0.323 -0.235 -0.289

CRWA NA NA NA NA

TRWA -0.133 -0.125 -0.123 -0.019

PIW2 0.847 -0.459 -1.144 0.010

THLI -0.131 -0.126 -0.125 -0.020

Table 55. Health inequality indices, France, men Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 1 1 1 1 1 1 1 2 3 4 1 2 3 4

TIW -0.373 -0.184 -0.223 -0.225 -0.285 -0.241 -0.193 -0.282 -0.252 -0.252 -0.235 -0.191 -0.136 -0.168 -0.234 -0.213 -0.255 -0.281 -0.235

Table 56. Health inequality indices, France, women Year 1992 1993 1994 1995

Quarter 1 1 1 1

TIW -0.194 0.001 -0.040 -0.007

66

Year 1996 1997 1998 1999 2000 2001 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 1 1 1 1 1 1 1 2 3 4 1 2 3 4

TIW -0.101 -0.054 -0.087 -0.125 -0.141 -0.089 -0.085 0.009 0.037 -0.041 -0.128 -0.110 -0.165 -0.188 -0.130

CRWA NA NA NA NA -0.254 -0.121 -0.187 -0.283 -0.265 -0.248 -0.213 -0.244 -0.238 -0.204 -0.075

TRWA 0.022 -0.050 0.076 -0.108 0.034 -0.104 -0.201 -0.206 -0.283 -0.167 0.001 -0.146 -0.137 -0.097 0.075

PIW2 0.960 0.205 0.075 -0.102 -0.299 -0.404 -0.121 0.072 -0.622 -0.272 -0.179 -0.098 -0.360 -0.029 NA

THLI 0.025 -0.049 0.078 -0.114 -0.144 -0.114 -0.186 -0.258 -0.278 -0.191 -0.073 -0.123 -0.182 -0.211 -0.047

CRWA -0.334 -0.062 -0.481 -0.337 -0.329 -0.354 -0.346 -0.402 -0.494 -0.188 -0.168 -0.446 -0.206 -0.196 -0.230 -0.109 -0.236 -0.351 -0.318 -0.203 -0.193 -0.316 -0.931 -0.704 -0.520 -0.447 0.044 -0.190

TRWA -0.338 -0.355 -0.193 -0.220 -0.324 -0.121 -0.201 -0.069 0.072 0.046 -0.245 -0.328 -0.378 -0.144 0.130 -0.137 -0.055 -0.063 -0.061 -0.427 -0.222 0.135 0.094 -0.268 -0.269 -0.255 -0.358 -0.384

PIW2 -0.219 -0.144 NA 0.874 0.785 NA -0.517 NA 0.694 NA 1.334 0.306 -0.622 -1.102 NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.351 -0.214 -0.310 -0.235 -0.341 -0.235 -0.285 -0.286 -0.236 0.042 -0.009 -0.350 -0.272 -0.282 -0.102 -0.158 -0.145 -0.387 -0.234 -0.238 -0.175 -0.200 -0.204 -0.412 -0.369 -0.394 -0.246 -0.302

Table 57. Health inequality indices, Greece, men Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2

TIW 0.054 -0.009 -0.048 0.001 -0.264 0.072 -0.154 -0.123 0.011 -0.184 -0.232 -0.384 -0.196 -0.211 -0.369 -0.275 -0.348 -0.109 -0.019 0.199 0.215 -0.020 -0.674 -0.251 -0.296 -0.342 0.027 0.212

67

Year 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4

TIW 0.122 -0.117 -0.012 -0.007 -0.116 -0.053

CRWA -0.025 0.013 -0.107 -0.173 -0.060 -0.143

TRWA -0.048 -0.202 -0.350 -0.202 -0.256 -0.399

PIW2 NA NA -0.182 NA NA NA

THLI -0.041 -0.183 -0.145 -0.180 -0.062 -0.253

CRWA -0.279 0.134 -0.390 -0.405 -0.082 -0.149 -0.096 -0.283 -0.295 0.554 0.243 -0.289 -0.146 -0.216 0.149 -0.132 -0.052 -0.100 -0.140 -0.115 -0.211 0.038 0.087 -0.214 -0.210 -0.238 0.142 -0.240 -0.176 -0.104 -0.498 -0.424 -0.222 -0.285

TRWA -0.381 -0.045 -0.229 -0.181 -0.151 -0.158 -0.096 -0.156 -0.156 0.087 -0.042 -0.363 -0.060 -0.179 -0.374 -0.241 0.167 0.024 0.368 0.397 0.493 0.620 0.337 -0.289 -0.449 -0.639 -0.079 -0.260 0.237 -0.134 -0.426 -0.074 0.021 0.389

PIW2 0.713 NA NA -0.436 NA NA 0.087 0.038 -0.096 NA NA -1.137 NA NA NA NA 0.201 0.192 0.210 0.221 0.188 0.167 0.442 -0.165 -0.130 NA NA NA -0.176 -0.183 -0.364 0.685 -0.186 -1.064

THLI -0.419 0.002 -0.250 -0.225 -0.130 -0.186 -0.164 -0.152 -0.239 0.332 0.113 -0.244 -0.055 -0.194 -0.005 -0.096 -0.003 -0.072 0.027 -0.104 -0.023 0.338 0.233 -0.344 -0.372 -0.419 -0.101 -0.126 0.207 -0.181 -0.508 -0.170 -0.181 -0.051

Table 58. Health inequality indices, Greece, women Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.007 0.031 -0.045 0.147 0.016 0.281 -0.271 -0.018 0.266 -0.229 -0.023 -0.190 0.274 -0.062 0.217 0.052 0.109 0.201 -0.344 -0.302 -0.444 -0.136 -0.037 0.127 0.263 0.066 0.353 -0.010 0.106 0.050 0.340 -0.301 -0.204 -0.152

68

Table 59. Health inequality indices, Hungary, men Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.062 -0.254 -0.165 -0.205 -0.116 -0.049 -0.162 -0.142 -0.107 -0.107 -0.134 -0.181 -0.009 -0.272 -0.226 -0.485 -0.408 -0.245 -0.012 -0.280 -0.225 -0.249 -0.157 -0.209 -0.186 -0.060 -0.168

CRWA -0.455 -0.250 -0.329 -0.259 -0.277 -0.238 -0.190 -0.158 -0.156 0.011 -0.082 -0.058 -0.044 -0.083 -0.254 -0.113 -0.047 0.043 -0.091 -0.117 -0.151 -0.159 -0.158 -0.106 -0.150 -0.183 -0.172

TRWA -0.054 -0.153 0.131 0.098 0.036 -0.107 -0.038 NA NA NA NA -0.020 -0.414 -0.247 -0.227 -0.253 -0.207 0.173 -0.310 0.175 -0.082 -0.221 0.008 0.013 -0.190 -0.085 -0.030

PIW2 NA -0.365 0.742 0.276 -0.260 NA 0.690 -1.269 0.532 0.579 NA NA NA NA NA NA NA NA NA NA NA NA -0.804 NA NA NA NA

THLI NA -0.291 -0.107 -0.126 -0.173 -0.231 -0.257 -0.158 -0.155 0.011 -0.082 -0.058 -0.146 -0.097 -0.185 -0.134 -0.086 0.070 -0.166 0.011 -0.101 -0.170 -0.103 -0.098 -0.152 -0.150 -0.168

CRWA -0.390 -0.370 -0.519 -0.436 -0.488 -0.476 -0.518 -0.345 -0.413 -0.326 -0.385 -0.334 -0.413 -0.309 -0.312

TRWA 0.056 -0.209 -0.070 -0.027 -0.202 -0.062 0.061 NA NA NA NA -0.079 -0.465 -0.249 -0.187

PIW2 NA 0.293 -0.342 -0.095 -0.120 -0.109 -0.797 NA 0.103 NA 0.746 NA NA NA NA

THLI NA -0.282 -0.315 -0.191 -0.321 -0.318 -0.290 -0.345 -0.400 -0.326 -0.384 -0.206 -0.450 -0.304 -0.250

Table 60. Health inequality indices, Hungary, women Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.098 0.058 -0.177 -0.211 -0.180 -0.168 -0.190 0.026 -0.165 -0.239 -0.179 -0.365 -0.284 -0.326 -0.151

69

Year 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.117 -0.229 -0.085 -0.231 -0.237 -0.067 -0.140 -0.093 -0.061 -0.230 -0.292 -0.160

CRWA -0.343 -0.397 -0.404 -0.347 -0.229 -0.325 -0.402 -0.334 -0.363 -0.333 -0.427 -0.405

TRWA -0.212 0.011 -0.296 -0.372 0.053 NA -0.498 -0.111 -0.012 -0.151 -0.462 -0.066

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.259 -0.286 -0.405 -0.314 -0.124 -0.127 -0.393 -0.311 -0.311 -0.356 -0.316 -0.362

CRWA -0.419 -0.875 -0.289 -0.192 -0.769 -0.520 -0.464 -0.561 NA NA NA NA NA NA

TRWA -0.333 -0.298 -0.056 -0.095 -0.047 -0.169 0.069 0.064 -0.042 -0.158 0.017 -0.450 -0.593 0.120

PIW2 -1.208 -0.708 -1.233 0.218 0.431 0.630 -0.862 -0.912 NA NA NA NA NA NA

THLI -0.439 -0.474 -0.320 -0.147 -0.233 -0.217 -0.159 -0.013 -0.042 -0.158 0.017 -0.450 -0.593 0.120

CRWA 0.006 -0.159 0.029 0.061 -0.147 -0.153 -0.224 -0.392 NA NA NA NA NA

TRWA -0.079 -0.070 -0.092 0.449 -0.121 -0.165 0.089 -0.035 0.480 0.379 -0.219 -0.202 -0.101

PIW2 -0.381 NA NA NA NA NA -0.510 -0.499 NA NA NA NA NA

THLI -0.141 -0.145 -0.047 0.315 -0.186 -0.196 -0.156 -0.211 0.480 0.379 -0.219 -0.202 -0.101

Table 61. Health inequality indices, Iceland, men Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 1 2 1 2 3 4

TIW -0.297 -0.224 -0.454 -0.049 -0.540 -0.300 -0.288 -0.388 -0.059 -0.192 -0.054 -0.362 -0.723 -0.107

Table 62. Health inequality indices, Iceland, women Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 1 2 1 2 3

TIW -0.101 -0.063 0.138 -0.036 0.233 -0.061 -0.386 -0.265 -0.042 0.010 -0.058 0.013 0.118

70

Year 2004

Quarter 4

TIW -0.356

CRWA NA

TRWA -0.031

PIW2 NA

THLI -0.031

CRWA -0.624 -0.220 -0.112 -0.006 -0.277 -0.353 -0.274 -0.267 -0.395 -0.409 -0.336 -0.544 -0.326 -0.251 -0.304 -0.381 -0.334 -0.239 -0.152 -0.267 -0.132 -0.274 -0.376 -0.293 -0.411 -0.365 -0.268 -0.108 0.008 -0.093

TRWA 0.024 -0.030 -0.040 0.083 -0.084 -0.135 0.087 -0.084 0.323 -0.472 0.115 0.075 0.083 -0.010 -0.007 -0.134 -0.502 0.033 -0.051 -0.315 0.103 0.108 -0.137 -0.247 -0.108 0.039 -0.092 -0.147 -0.405 -0.151

PIW2 0.313 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.190 -0.075 -0.052 0.066 -0.126 -0.135 -0.143 -0.191 -0.171 -0.373 -0.099 -0.328 -0.231 -0.227 -0.099 -0.280 -0.450 -0.141 -0.117 -0.336 -0.103 -0.110 -0.208 -0.287 -0.341 -0.188 -0.160 -0.182 -0.139 -0.179

CRWA -0.143 -0.107 -0.182 0.157 0.053 -0.113 -0.387 -0.372

TRWA 0.028 -0.256 -0.033 0.226 0.003 0.052 -0.013 -0.076

PIW2 NA NA NA NA NA NA NA NA

THLI -0.028 -0.137 -0.099 0.106 -0.001 0.074 -0.228 -0.224

Table 63. Health inequality indices, Ireland, men Year 1992 1993 1994 1995 1996 1997 1998 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.060 -0.184 -0.090 -0.075 -0.106 -0.121 -0.275 -0.292 -0.243 -0.255 -0.250 -0.361 -0.187 -0.262 -0.225 -0.266 -0.355 -0.302 -0.332 -0.300 -0.256 -0.397 -0.231 -0.347 -0.206 -0.233 -0.306 -0.178 -0.250 -0.244

Table 64. Health inequality indices, Ireland, women Year 1992 1993 1994 1995 1996 1997 1998 1999

Quarter 2 2 2 2 2 2 2 2

TIW -0.043 -0.031 0.016 -0.033 -0.069 0.062 -0.165 -0.122

71

Year 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.082 -0.176 -0.110 -0.099 -0.045 -0.027 -0.063 -0.051 -0.138 -0.126 -0.088 -0.021 -0.070 -0.081 -0.030 -0.187 -0.187 -0.118 -0.054 -0.112 -0.187 -0.146

CRWA -0.107 -0.149 -0.074 -0.219 0.054 -0.279 -0.368 -0.274 -0.199 -0.328 -0.379 -0.328 -0.212 -0.168 -0.273 -0.208 -0.371 -0.337 -0.240 -0.346 -0.490 -0.253

TRWA 0.324 -0.461 -0.096 0.161 -0.205 -0.019 -0.073 -0.307 -0.434 -0.259 0.028 0.096 0.064 -0.458 NA 0.015 -0.057 -0.257 0.074 0.169 -0.013 0.230

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI 0.011 -0.230 -0.077 -0.075 -0.007 -0.206 -0.235 -0.242 -0.249 -0.306 -0.123 -0.065 -0.034 -0.247 -0.204 -0.105 -0.262 -0.334 -0.073 -0.214 -0.306 -0.074

Table 65. Health inequality indices, Italy, men Year

Quarter

TIW

CRWA

TRWA

PIW2

THLI

1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001

3 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3

-0.172 -0.191 -0.213 -0.158 -0.153 -0.219 -0.228 -0.141 -0.265 -0.141 -0.160 -0.241 -0.116 -0.096 -0.164 -0.145 -0.266 -0.253 -0.237 -0.193 -0.217

-0.135 -0.263 -0.083 -0.593 -0.337 -0.074 0.090 -0.189 -0.085 -0.204 0.136 -0.062 -0.244 -0.068 -0.231 -0.194 -0.159 -0.122 -0.399 -0.202 0.030

-0.148 -0.201 -0.150 -0.158 -0.264 -0.218 -0.031 -0.226 -0.197 -0.188 -0.206 -0.060 -0.333 -0.085 -0.092 -0.232 -0.149 -0.133 -0.263 -0.216 -0.167

-0.411 0.257 NA 0.167 -0.259 0.110 -0.826 -0.844 0.133 -0.338 -0.785 -0.370 -0.258 -1.040 -0.282 -0.472 NA -0.204 -0.266 -0.783 0.307

-0.156 -0.220 -0.132 -0.228 -0.294 -0.169 -0.014 -0.202 -0.147 -0.195 -0.180 -0.060 -0.300 -0.064 -0.149 -0.215 -0.090 -0.104 -0.276 -0.210 -0.095

72

Year

Quarter

TIW

CRWA

TRWA

PIW2

THLI

2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

4 1 2 3 4 1 2 3 4 1 2 3 4

-0.208 -0.201 -0.117 -0.229 -0.130 -0.096 -0.144 -0.141 -0.125 -0.218 -0.189 -0.180 -0.209

-0.285 -0.374 -0.393 -0.005 -0.092 -0.199 0.010 -0.140 -0.188 -0.163 -0.400 -0.350 -0.174

-0.242 -0.179 -0.151 -0.256 -0.225 -0.145 -0.161 -0.364 -0.108 -0.115 -0.114 -0.271 -0.011

-0.799 -1.258 -0.801 -0.808 0.236 -0.528 NA NA -0.821 0.109 -0.787 -0.215 -0.589

-0.275 -0.230 -0.232 -0.156 -0.210 -0.145 -0.073 -0.316 -0.100 -0.135 -0.194 -0.300 -0.030

CRWA -0.341 -0.332 -0.181 -0.174 -0.253 -0.180 -0.232 -0.346 -0.521 -0.512 -0.202 -0.348 -0.123 -0.175 -0.095 -0.322 -0.092 -0.105 -0.149 -0.305 -0.286 -0.167 -0.140 -0.157 -0.409 -0.147 -0.306 -0.204 -0.262 -0.516

TRWA -0.292 -0.195 -0.205 -0.164 -0.053 -0.190 0.042 -0.025 -0.277 0.010 -0.125 -0.164 -0.054 -0.087 -0.180 -0.067 -0.119 -0.027 0.055 -0.136 -0.124 -0.228 0.102 -0.009 -0.412 -0.192 -0.045 -0.230 -0.052 -0.154

PIW2 -0.447 NA -0.058 -0.156 -0.241 NA NA 0.351 0.129 0.527 -0.380 -0.171 -0.108 0.044 -0.096 -0.496 0.039 0.050 NA NA -0.479 -0.419 -0.124 -0.733 -0.002 -0.122 NA -0.760 -1.049 NA

THLI -0.304 -0.233 -0.192 -0.154 -0.197 -0.242 -0.012 -0.083 -0.402 -0.152 -0.162 -0.184 -0.074 -0.132 -0.165 -0.129 -0.119 -0.036 -0.019 -0.219 -0.202 -0.177 0.015 -0.092 -0.365 -0.098 -0.128 -0.229 -0.235 -0.250

Table 66. Health inequality indices, Italy, women Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003

Quarter 3 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.061 -0.089 0.021 -0.041 -0.124 -0.190 -0.131 -0.071 -0.258 -0.096 -0.183 -0.219 -0.214 -0.106 -0.085 0.006 -0.143 -0.204 -0.124 -0.117 -0.066 -0.098 -0.121 -0.199 -0.305 -0.130 -0.179 -0.091 -0.025 -0.055

73

Year 2004 2004 2004 2004

Quarter 1 2 3 4

TIW -0.221 -0.239 -0.128 -0.190

CRWA -0.266 -0.334 -0.253 -0.197

TRWA -0.269 -0.203 -0.166 -0.053

PIW2 -0.388 -0.112 -0.292 -0.331

THLI -0.311 -0.320 -0.203 -0.172

CRWA -0.595 -0.614 -0.608 -0.717 -0.769 -0.834 -0.425 -0.704 -0.088 -0.433 0.290 -0.657 -1.160 -0.514 -1.088 -0.537 -0.695 -0.098 -0.402 -0.215

TRWA 0.315 -0.212 -0.004 -0.299 0.021 -0.430 -0.828 0.073 -0.016 -0.244 -0.343 0.021 -0.345 -0.319 -0.777 -0.375 -0.961 -0.628 NA NA

PIW2 NA NA NA NA NA NA NA NA NA 0.626 NA -1.242 NA -0.936 1.365 -1.214 -0.802 0.330 -0.645 NA

THLI -0.480 -0.476 -0.507 -0.573 -0.700 -0.706 -0.566 -0.768 0.155 -0.272 0.106 -0.453 -0.504 -0.390 -0.905 -0.494 -0.652 -0.188 -0.402 -0.215

CRWA -0.608 -0.600 -0.629 -0.613 -0.879 -0.480 -0.635 -0.626 -0.117 -0.506 -0.808 0.319 0.064 -0.319 -0.388

TRWA 0.281 -0.105 0.434 0.052 -0.299 -0.367 -0.407 -0.300 -0.488 -0.232 NA -0.013 0.450 NA NA

PIW2 NA NA NA NA NA NA NA NA -0.262 NA -0.622 NA -0.158 NA NA

THLI -0.518 -0.451 -0.274 -0.580 -0.748 -0.438 -0.587 -0.605 -0.235 -0.369 -0.771 0.102 0.032 -0.319 -0.388

Table 67. Health inequality indices, Latvia, men Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.283 -0.139 -0.315 -0.164 -0.227 0.440 0.402 -0.049 0.123 0.055 -0.168 0.403 -0.078 -0.346 -0.284 -0.228 -0.152 -0.199 -0.755 -0.656

Table 68. Health inequality indices, Latvia, women Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003 2003

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2 3

TIW -0.260 -0.065 -0.348 0.041 0.074 -0.321 -0.039 -0.103 0.061 -0.107 -0.500 -0.165 -0.199 0.260 0.027

74

Year 2003 2004 2004 2004 2004

Quarter 4 1 2 3 4

TIW 0.358 0.005 -0.258 -0.744 -0.021

CRWA -0.153 -0.172 0.454 -0.591 -0.372

TRWA -0.001 0.279 -0.538 -0.195 -0.759

PIW2 1.346 0.658 -1.336 NA NA

THLI 0.142 0.094 -0.095 -0.591 -0.372

CRWA -0.615 -0.753 NA NA 0.475 -0.001 -0.640 -0.508 -0.513 -0.394 -0.249 0.094 -0.286 -0.326 -0.335 0.352 -0.299 -0.315 -0.348 -0.365

TRWA NA NA 1.023 0.749 -1.170 0.068 -1.092 0.684 -0.616 -1.135 NA -0.794 NA 0.630 -1.284 NA -0.624 0.663 NA NA

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA -1.267 NA NA NA

THLI -0.615 -0.753 1.023 0.749 -0.347 0.200 -0.734 -0.210 -0.527 -0.445 -0.249 -0.227 -0.286 -0.206 -0.493 0.352 -0.426 -0.315 -0.348 -0.365

CRWA 0.053 -0.362 NA NA 0.199 -0.421 -0.707 0.026 -0.545 -0.055 -0.513 -0.945 0.085 -0.600

TRWA NA NA -0.050 -0.070 NA -1.205 -0.625 -1.293 -0.684 -0.606 -1.025 1.187 -0.351 -0.047

PIW2 NA NA NA NA NA NA NA NA -0.692 -0.203 NA NA -0.616 NA

THLI 0.053 -0.362 -0.050 -0.070 0.199 -0.628 -0.768 -0.298 -0.581 -0.113 -0.637 -0.809 -0.107 -0.501

Table 69. Health inequality indices, Lithuania, men Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.381 0.125 -0.281 -0.130 -0.425 -0.005 0.116 -0.186 -0.401 0.230 0.122 -0.610 0.031 0.297 -0.195 -0.181 -0.237 -0.389 0.149 -0.234

Table 70. Health inequality indices, Lithuania, women Year 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2002 2002 2003 2003

Quarter 2 4 2 4 2 4 2 4 1 2 3 4 1 2

TIW -0.183 -0.229 -0.269 0.106 0.193 0.394 0.040 0.043 0.011 -0.027 0.088 -0.236 -0.134 0.377

75

Year 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4

TIW -0.268 -0.265 -0.541 0.069 0.245 -0.718

CRWA -0.501 -0.247 -0.386 -0.962 -0.397 -0.450

TRWA NA -0.690 -0.320 NA NA 0.049

PIW2 NA NA NA NA NA -0.278

THLI -0.501 -0.432 -0.324 -0.962 -0.397 -0.459

CRWA -0.160 -0.116 -0.819 0.645 0.129 NA -0.102 -0.384 -0.104 0.467 -0.610 -0.557 -0.557 -0.315 -0.315 -0.315 -0.315

TRWA 0.088 -0.448 0.142 0.150 0.606 -0.159 0.125 -0.081 0.381 -0.095 -0.411 -0.274 -0.274 -0.840 -0.840 -0.840 -0.840

PIW2 NA -1.136 NA NA NA -0.478 NA NA NA NA NA NA NA NA NA NA NA

THLI -0.039 -0.279 -0.132 0.150 0.507 -0.166 -0.036 -0.120 0.297 0.040 -0.537 -0.330 -0.330 -0.402 -0.402 -0.402 -0.402

CRWA -0.767 0.103 -0.410 -0.154 -0.281 NA -0.725 -0.264 0.040 -0.401 -0.641 -0.410 -0.410 -0.180 -0.180 -0.180

TRWA -0.253 0.097 0.011 -0.533 -0.434 -0.230 -0.545 0.173 -0.155 0.198 -0.483 0.220 0.220 0.511 0.511 0.511

PIW2 -0.517 0.130 NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.392 0.170 -0.087 -0.290 -0.387 -0.230 -0.590 0.016 -0.057 -0.119 -0.627 -0.227 -0.227 -0.046 -0.046 -0.046

Table 71. Health inequality indices, Luxembourg, men Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 3 4

TIW -0.392 -0.392 -0.217 -0.402 -0.443 -0.346 -0.408 -0.536 -0.467 -0.456 -0.482 -0.421 -0.421 -0.473 -0.473 -0.473 -0.473

Table 72. Health inequality indices, Luxembourg, women Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2003 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 3

TIW -0.234 NA -0.078 -0.025 -0.207 -0.192 -0.261 -0.253 0.070 -0.151 0.150 -0.067 -0.067 -0.337 -0.337 -0.337

76

Year 2004

Quarter 4

TIW -0.337

CRWA -0.180

TRWA 0.511

PIW2 NA

THLI -0.046

CRWA -0.145 -0.231 -0.196 -0.299 -0.237 -0.318 -0.273 -0.240 -0.048 -0.380 -0.197 -0.193 -0.162 0.011 -0.153 0.030 -0.110 -0.337 -0.165 -0.310 -0.229 -0.375 -0.218 -0.474 -0.420 -0.373 NA NA

TRWA -0.110 -0.163 -0.089 -0.204 -0.102 -0.105 -0.046 -0.011 -0.099 -0.128 -0.039 -0.111 -0.088 -0.120 -0.104 -0.123 -0.038 -0.086 -0.075 -0.171 -0.006 -0.117 -0.128 -0.025 -0.045 -0.042 NA NA

PIW2 NA NA 0.254 0.158 0.412 NA NA NA NA NA NA NA 1.556 0.754 -0.500 0.132 -0.253 -0.214 -0.353 -0.665 -0.984 -0.769 -0.311 NA 0.988 1.026 NA NA

THLI -0.149 -0.199 -0.177 -0.227 -0.164 -0.181 -0.098 -0.128 -0.103 -0.163 -0.020 -0.102 -0.104 -0.119 -0.103 -0.107 -0.025 -0.152 -0.111 -0.175 -0.094 -0.171 -0.120 -0.093 -0.105 -0.101 NA NA

TRWA 0.016 -0.082 -0.055 0.015 -0.276 -0.033 0.255 -0.076 0.044 0.084

PIW2 -0.434 -1.241 -0.320 0.037 -0.341 -0.495 0.954 0.557 -0.349 -0.142

THLI -0.048 -0.063 -0.081 0.074 -0.177 -0.021 -0.007 -0.036 -0.035 0.069

Table 73. Health inequality indices, the Netherlands, men Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.258 -0.276 -0.280 -0.228 -0.299 -0.284 -0.204 -0.182 -0.159 -0.188 -0.221 -0.199 -0.220 -0.253 -0.276 -0.260 -0.218 -0.219 -0.176 -0.161 -0.222 -0.170 -0.244 -0.291 -0.271 -0.199 NA NA

Table 74. Health inequality indices, the Netherlands, women Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000

Quarter 2 2 2 2 2 2 2 2 1 2

TIW -0.055 -0.185 -0.030 -0.028 -0.013 -0.041 -0.163 -0.073 -0.108 -0.080

CRWA -0.083 -0.072 -0.070 0.092 -0.121 -0.011 -0.123 -0.040 -0.211 -0.021

77

Year 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.093 -0.111 -0.145 -0.092 -0.108 -0.065 -0.082 -0.036 -0.013 -0.089 -0.099 -0.070 -0.014 -0.088 -0.157 -0.077 NA NA

CRWA 0.073 0.355 0.040 0.020 0.196 0.224 -0.232 -0.159 -0.284 -0.163 -0.188 -0.138 -0.196 -0.199 -0.205 -0.241 NA NA

TRWA 0.076 -0.029 0.028 -0.014 -0.142 -0.014 0.115 -0.198 -0.011 -0.090 0.012 -0.057 0.013 -0.016 0.038 0.080 NA NA

PIW2 NA 0.316 -0.126 0.519 -0.549 -0.129 -0.303 -0.507 -0.124 0.010 -0.857 -0.425 -0.659 -0.293 -0.550 -0.209 NA NA

THLI 0.104 0.105 0.014 -0.048 0.013 0.009 0.037 -0.067 -0.052 -0.029 -0.018 -0.097 -0.072 -0.056 -0.052 -0.018 NA NA

CRWA -0.525 -0.073 -0.361 -0.400 -0.284 -0.505 -0.470 -0.231 -0.360 -0.327 -0.280 -0.459 -0.569 -0.553 -0.251 -0.364 -0.301 -0.374 -0.482 -0.170 -0.214 -0.237 -0.570 -0.481

TRWA -0.161 -0.106 0.071 -0.115 NA 0.030 NA NA NA -0.148 NA NA NA -0.086 NA NA NA -0.053 NA NA NA -0.145 NA NA

PIW2 -1.000 -0.355 -0.684 -0.590 NA -0.245 NA NA NA -0.368 NA NA NA -0.255 NA NA NA NA NA NA NA NA NA NA

THLI -0.204 -0.108 -0.064 -0.256 NA -0.101 NA NA NA -0.171 NA NA NA -0.268 NA NA NA -0.098 NA NA NA -0.114 NA NA

Table 75. Health inequality indices, Norway, men Year 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.436 -0.230 -0.208 -0.430 -0.316 -0.258 -0.304 -0.314 -0.275 -0.299 -0.356 -0.368 -0.310 -0.286 -0.230 -0.276 -0.376 -0.321 -0.276 -0.284 -0.335 -0.334 -0.332 -0.324

78

Table 76. Health inequality indices, Norway, women Year 1995 1996 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW NA -0.140 -0.106 -0.113 -0.177 -0.080 -0.144 -0.106 -0.070 -0.123 -0.063 -0.179 -0.109 -0.098 -0.069 -0.075 -0.138 -0.064 -0.130 -0.120 -0.088 -0.090 -0.045 -0.184 -0.094

CRWA NA -0.285 0.262 -0.244 -0.269 -0.226 -0.210 -0.341 -0.293 -0.344 -0.356 -0.301 -0.311 -0.410 -0.244 -0.312 -0.352 -0.341 -0.410 -0.321 -0.275 -0.344 -0.307 -0.247 -0.515

TRWA NA -0.035 0.015 0.069 -0.062 NA -0.082 NA NA NA -0.102 NA NA NA -0.041 NA NA NA 0.003 NA NA NA -0.101 NA NA

PIW2 NA -0.129 -0.255 -0.172 -0.144 NA -0.208 NA NA NA 0.168 NA NA NA -0.531 NA NA NA NA NA NA NA NA NA NA

THLI NA -0.058 0.038 -0.015 -0.124 NA -0.182 NA NA NA -0.162 NA NA NA -0.165 NA NA NA -0.122 NA NA NA -0.180 NA NA

CRWA -0.416 -0.508 -0.230 -0.449 -0.188 -0.273 -0.024 -0.163 -0.356 -0.234 -0.278 -0.243 -0.143 -0.211 -0.111 -0.275 -0.246

TRWA NA NA NA NA NA NA NA -0.499 -0.487 -0.347 -0.601 -0.471 -0.263 -0.214 -0.605 0.495 -0.239

PIW2 NA NA NA NA NA NA NA -0.719 NA 1.451 0.010 0.216 NA NA 0.246 -0.973 NA

THLI -0.416 -0.508 -0.230 -0.449 -0.188 -0.273 -0.024 -0.379 -0.312 -0.166 -0.347 -0.250 -0.149 -0.202 -0.253 -0.164 -0.197

Table 77. Health inequality indices, Poland, men Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003

Quarter 2 2 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2

TIW 0.130 0.068 -0.017 -0.048 -0.024 0.030 -0.064 0.037 -0.170 0.014 0.090 0.016 0.140 0.100 0.200 0.063 -0.043

79

Year 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4

TIW 0.048 -0.129 -0.081 -0.195 -0.054 -0.175

CRWA -0.265 -0.396 -0.482 -0.462 -0.471 -0.620

TRWA -0.289 -0.075 0.089 -0.418 -0.296 -0.221

PIW2 -1.116 -1.099 -0.706 -0.880 -0.890 -0.616

THLI -0.249 -0.266 -0.334 -0.438 -0.425 -0.581

CRWA -0.481 -0.477 -0.447 -0.492 -0.495 -0.393 -0.467 -0.307 -0.611 -0.547 -0.526 -0.523 -0.466 -0.393 -0.612 -0.542 -0.451 -0.340 -0.456 -0.740 -0.527 -0.517 -0.519

TRWA NA NA NA NA NA NA NA -0.231 -0.582 -0.494 -0.215 -0.588 -0.484 -0.621 -0.653 -0.438 -0.373 -0.153 -0.400 -0.227 -0.317 -0.443 -0.431

PIW2 NA NA NA NA NA NA NA 0.365 -1.043 NA -0.275 -0.394 NA NA 0.805 -1.020 -0.952 -0.880 -0.020 -0.083 -0.119 -0.121 -0.095

THLI -0.481 -0.477 -0.447 -0.492 -0.495 -0.393 -0.467 -0.287 -0.522 -0.515 -0.471 -0.614 -0.472 -0.455 -0.572 -0.531 -0.508 -0.254 -0.473 -0.464 -0.494 -0.477 -0.429

CRWA -0.103 -0.553 -0.592 -0.420 -0.440 -0.674 -0.669 -0.725 -0.699 -0.655

TRWA -0.176 -0.368 -0.327 -0.229 -0.535 -0.280 -0.319 -0.006 -0.504 -0.423

PIW2 NA NA NA NA NA NA -0.316 -0.239 NA -1.100

THLI -0.167 -0.539 -0.509 -0.383 -0.477 -0.479 -0.515 -0.466 -0.654 -0.630

Table 78. Health inequality indices, Poland, women Year 1997 1998 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW 0.093 0.050 -0.079 0.079 0.176 0.104 -0.004 -0.157 0.147 0.117 -0.071 0.090 0.207 0.056 -0.054 0.147 -0.072 -0.199 0.250 -0.039 0.133 -0.001 -0.023

Table 79. Health inequality indices, Portugal, men Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998

Quarter 2 2 2 2 2 2 1 2 3 4

TIW -0.302 -0.194 -0.253 -0.187 -0.146 -0.166 -0.233 -0.182 -0.074 -0.104

80

Year 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.239 -0.221 -0.217 -0.199 -0.278 -0.184 -0.117 -0.214 -0.153 -0.232 -0.186 -0.126 -0.099 -0.098 -0.125 -0.142 -0.277 -0.125 -0.022 -0.182 -0.160 -0.183 -0.140 -0.137

CRWA -0.801 -0.765 -0.718 -0.681 -0.702 -0.820 -0.732 -0.569 -0.679 -0.702 -0.683 -0.771 -0.746 -0.738 -0.713 -0.830 -0.802 -0.737 -0.634 -0.575 -0.793 -0.738 -0.725 -0.850

TRWA -0.355 -0.488 -0.254 -0.453 -0.210 -0.805 -0.209 -0.201 -0.225 -0.707 -0.518 NA -0.291 0.112 -0.411 -0.252 -0.354 -0.242 -0.144 0.032 -0.317 -0.673 -0.107 -0.241

PIW2 -0.763 -0.436 -1.149 NA NA NA -0.682 -0.891 NA NA -0.566 -0.502 NA NA NA NA NA -0.548 NA NA NA NA NA NA

THLI -0.582 -0.713 -0.554 -0.668 -0.602 -0.812 -0.664 -0.453 -0.668 -0.697 -0.661 -0.605 -0.602 -0.545 -0.671 -0.663 -0.595 -0.622 -0.553 -0.432 -0.512 -0.695 -0.576 -0.634

CRWA -0.227 -0.343 -0.408 -0.278 -0.489 -0.369 -0.371 -0.417 -0.413 -0.345 -0.575 -0.576 -0.433 -0.334 -0.152 -0.200 -0.183 -0.145 -0.674

TRWA -0.187 -0.179 -0.264 -0.138 0.042 -0.199 -0.264 -0.348 -0.694 -0.526 -0.261 -0.207 -0.293 -0.340 -0.268 -0.405 -0.256 0.104 -0.784

PIW2 NA NA NA NA NA NA -0.124 0.188 -0.512 NA -0.538 NA -0.390 0.154 -0.193 -0.539 -0.553 NA NA

THLI -0.222 -0.258 -0.345 -0.189 -0.347 -0.293 -0.398 -0.235 -0.516 -0.390 -0.429 -0.472 -0.558 -0.179 -0.225 -0.314 -0.134 0.080 -0.667

Table 80. Health inequality indices, Portugal, women Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1

TIW -0.061 -0.015 -0.042 -0.161 -0.101 -0.040 -0.199 -0.107 -0.206 -0.188 -0.230 -0.175 -0.255 -0.329 -0.060 -0.162 -0.059 -0.181 -0.028

81

Year 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.186 -0.138 -0.047 -0.161 -0.081 -0.121 0.041 -0.109 -0.076 -0.026 -0.080 -0.085 -0.106 -0.177 -0.147

CRWA -0.714 -0.611 -0.682 -0.689 -0.689 -0.635 -0.507 -0.518 -0.651 -0.321 -0.338 -0.406 -0.655 -0.630 -0.504

TRWA -0.124 0.032 0.054 -0.698 -0.404 -0.349 -0.123 -0.373 -0.416 -0.390 -0.361 -0.457 -0.191 -0.055 -0.278

PIW2 NA NA NA NA NA NA 0.150 NA NA 0.367 NA -1.272 -1.276 NA NA

THLI -0.558 -0.515 -0.529 -0.702 -0.501 -0.550 -0.470 -0.514 -0.520 -0.310 -0.227 -0.390 -0.377 -0.371 -0.439

CRWA 0.015 0.168 0.098 -0.328 -0.250 -0.278 -0.341 0.114 0.128 0.070 0.047 -0.017 -0.200 -0.167 -0.015 -0.062 -0.149 -0.263 -0.138 -0.083 -0.059 -0.151 -0.169 -0.274 -0.502 -0.487 -0.230 -0.316

TRWA -0.507 -0.023 -0.343 0.121 -0.302 -0.286 -0.615 -0.384 -0.287 -0.064 -0.416 -0.231 -0.251 0.051 -0.388 -0.025 0.016 0.007 -0.228 -0.104 -0.017 -0.053 -0.402 0.345 0.265 -0.188 0.494 -0.376

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.126 0.042 0.070 -0.154 -0.242 -0.220 -0.385 -0.146 -0.179 0.032 -0.067 -0.154 -0.213 -0.086 -0.014 -0.101 -0.127 -0.118 -0.162 -0.019 -0.132 -0.098 -0.094 -0.021 -0.201 -0.492 -0.094 -0.290

Table 81. Health inequality indices, Slovakia, men Year 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.346 0.053 -0.070 -0.134 -0.175 -0.158 -0.246 -0.288 -0.131 -0.244 -0.186 -0.291 -0.061 -0.032 0.033 -0.083 -0.128 -0.151 -0.143 -0.013 -0.080 0.091 0.006 -0.230 -0.001 -0.354 -0.278 -0.057

82

Table 82. Health inequality indices, Slovakia, women Year 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.215 -0.017 -0.260 -0.166 -0.039 -0.007 -0.152 0.110 -0.060 -0.200 -0.255 0.006 -0.340 -0.121 -0.007 -0.101 -0.261 -0.308 -0.269 -0.152 -0.202 -0.254 -0.291 -0.301 -0.361 -0.084 -0.213 -0.202

CRWA -0.426 -0.505 -0.598 -0.557 -0.418 -0.527 -0.536 -0.592 -0.456 -0.497 -0.417 -0.463 -0.516 -0.541 -0.515 -0.580 -0.524 -0.561 -0.509 -0.532 -0.575 -0.554 -0.397 -0.410 -0.551 -0.600 -0.629 -0.486

TRWA 0.030 -0.143 -0.217 -0.065 0.045 0.043 0.229 -0.194 0.180 0.486 0.238 -0.421 -0.005 -0.009 -0.348 0.074 0.377 0.327 -0.029 0.449 -0.065 -0.049 -0.555 -0.316 -0.100 -0.229 -0.593 -0.403

PIW2 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

THLI -0.243 -0.386 -0.417 -0.477 0.005 -0.204 -0.360 -0.443 -0.049 -0.242 -0.257 -0.490 -0.371 -0.401 -0.539 -0.392 -0.283 -0.245 -0.216 -0.130 -0.435 -0.338 -0.423 -0.247 -0.431 -0.441 -0.530 -0.433

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

TRWA 0.009 0.013 0.174 0.170 0.336 -0.346 -0.098 -0.202 -0.041 0.111 0.063 0.213 -0.205 -0.273

PIW2 -0.183 NA -0.870 NA 0.786 0.458 -0.998 -0.667 -1.067 -1.376 -0.789 NA -1.184 NA

THLI 0.026 0.013 0.164 0.170 0.341 -0.314 -0.140 -0.203 -0.047 0.105 0.062 0.213 -0.208 -0.273

Table 83. Health inequality indices, Slovenia, men Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3

TIW -0.225 -0.120 -0.249 -0.176 -0.030 -0.027 0.012 -0.078 -0.018 -0.104 -0.055 -0.208 0.023 -0.056

83

Year 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.080 0.037 -0.296 0.024 -0.057 -0.135 -0.199 -0.242 -0.237 -0.016 0.046 0.065 0.146

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA

TRWA -0.151 -0.106 -0.102 -0.589 0.059 0.096 -0.053 -0.114 -0.252 -0.004 -0.232 -0.396 -0.074

PIW2 -0.021 -0.129 NA 0.688 0.464 0.058 -1.222 NA -0.110 1.240 0.292 -1.182 0.754

THLI -0.148 -0.124 -0.102 -0.584 0.059 0.114 -0.087 -0.114 -0.240 0.002 -0.227 -0.403 -0.070

CRWA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

TRWA -0.105 -0.224 0.213 0.092 -0.143 -0.190 0.345 -0.084 -0.222 -0.268 -0.244 0.096 -0.061 -0.053 -0.155 -0.106 -0.100 0.098 -0.154 0.286 0.035 -0.291 0.196 -0.153 -0.176 0.223 0.261

PIW2 0.130 -0.656 -0.648 -0.033 -0.818 0.826 NA NA -0.764 -0.134 0.048 NA NA -0.106 NA -0.898 0.776 NA NA NA NA NA -0.104 NA NA NA 0.897

THLI -0.076 -0.230 0.095 0.095 -0.147 -0.175 0.345 -0.084 -0.234 -0.267 -0.241 0.096 -0.061 -0.051 -0.155 -0.115 -0.096 0.098 -0.154 0.286 0.035 -0.291 0.209 -0.153 -0.176 0.223 0.270

Table 84. Health inequality indices, Slovenia, women Year 1996 1997 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.084 -0.286 0.068 0.140 0.194 0.006 0.084 0.239 0.017 -0.233 -0.225 0.143 0.009 0.124 0.035 0.183 -0.007 -0.030 -0.054 -0.113 -0.077 -0.146 -0.056 0.196 0.040 -0.055 0.051

84

Table 85. Health inequality indices, Spain, men Year 1992 1993 1994 1995 1996 1997 1998 1998 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.096 -0.186 -0.135 -0.232 -0.080 -0.172 -0.256 -0.157 -0.133 -0.210 -0.205 -0.158 -0.206 -0.262 -0.180 -0.224 -0.222 -0.125 -0.236 -0.194 -0.223 -0.211 -0.179 -0.176 -0.218 -0.218 -0.185 -0.215 -0.206 -0.220 -0.215 -0.133 -0.193 -0.170

CRWA -0.259 -0.397 0.014 -0.166 -0.261 -0.389 -0.392 -0.189 -0.387 0.060 -0.316 -0.149 -0.537 -0.605 -0.614 -0.597 -0.534 -0.684 -0.263 -0.115 -0.261 -0.375 -0.220 -0.088 0.262 -0.034 -0.049 0.001 -0.219 -0.091 -0.143 -0.005 -0.155 0.017

TRWA 0.078 -0.339 -0.147 -0.230 -0.199 -0.188 -0.213 -0.357 -0.074 -0.229 -0.147 -0.165 -0.248 -0.156 -0.180 -0.365 -0.263 -0.325 -0.309 -0.301 -0.238 -0.097 -0.022 -0.157 -0.388 -0.295 -0.117 -0.102 -0.321 -0.416 -0.117 -0.070 -0.187 0.136

PIW2 -0.374 0.895 0.313 NA -0.548 0.574 -0.249 -0.614 -0.587 -1.174 NA -0.484 -0.708 -0.919 -0.560 -0.130 -0.841 -0.087 -0.541 -0.368 -0.106 0.796 -0.377 -0.173 NA 0.598 0.215 -0.728 0.176 -0.458 -0.248 -0.741 -0.362 -0.185

THLI -0.074 -0.386 -0.174 -0.275 -0.218 -0.282 -0.282 -0.355 -0.213 -0.210 -0.189 -0.184 -0.383 -0.200 -0.297 -0.428 -0.408 -0.386 -0.223 -0.164 -0.205 -0.247 -0.152 -0.089 -0.190 -0.194 -0.125 -0.172 -0.320 -0.369 -0.153 -0.079 -0.359 0.109

CRWA -0.222 -0.272 -0.322 -0.104 -0.260 -0.323 0.029 -0.146

TRWA -0.558 0.047 -0.228 0.037 -0.208 -0.257 -0.276 -0.131

PIW2 -0.369 0.017 0.673 -0.057 0.146 -0.143 -0.259 -0.829

THLI -0.486 -0.186 -0.223 0.006 -0.159 -0.250 -0.151 -0.226

Table 86. Health inequality indices, Spain, women Year 1992 1993 1994 1995 1996 1997 1998 1998

Quarter 2 2 2 2 2 2 1 2

TIW -0.068 0.012 -0.123 -0.068 -0.118 -0.195 -0.114 -0.165

85

Year 1998 1998 1999 1999 1999 1999 2000 2000 2000 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.151 -0.125 -0.077 -0.088 -0.106 -0.036 -0.150 -0.224 -0.135 -0.155 -0.097 -0.072 -0.170 -0.056 -0.146 -0.181 -0.153 -0.049 -0.160 -0.161 -0.115 -0.156 -0.089 -0.125 -0.179 -0.192

CRWA -0.234 -0.266 -0.213 -0.168 0.112 -0.245 -0.536 -0.542 -0.349 -0.570 -0.436 -0.550 -0.052 -0.471 -0.228 -0.540 -0.513 -0.412 -0.461 -0.400 -0.299 -0.134 -0.329 -0.307 -0.209 -0.286

TRWA -0.297 -0.503 -0.285 -0.238 -0.380 -0.132 -0.263 -0.046 0.005 -0.391 -0.336 -0.259 -0.247 -0.006 -0.348 -0.069 -0.291 0.197 -0.035 -0.027 -0.330 -0.104 0.134 -0.186 0.005 -0.266

PIW2 -0.189 -0.035 -0.041 -0.238 -0.266 0.073 0.356 -0.318 -0.755 -0.600 0.847 -0.370 -0.098 0.010 -0.281 -0.449 -0.049 0.070 0.226 -0.435 -0.493 -0.268 0.185 -0.068 0.070 0.036

THLI -0.292 -0.339 -0.294 -0.162 -0.266 -0.166 -0.348 -0.181 -0.191 -0.481 -0.311 -0.311 -0.194 -0.188 -0.380 -0.185 -0.458 -0.093 -0.100 -0.129 -0.316 -0.093 0.030 -0.301 -0.071 -0.241

CRWA -0.486 -0.577 -0.391 -0.350 -0.207 -0.143 -0.413 -0.214 -0.287 -0.147 -0.274 -0.130 -0.270 -0.229 -0.394 -0.382 -0.299

TRWA -0.170 -0.267 -0.041 -0.212 -0.184 -0.103 -0.154 -0.142 -0.052 -0.215 -0.228 -0.170 -0.173 -0.202 -0.231 -0.149 -0.216

PIW2 NA 0.961 0.206 0.026 -0.141 -0.147 -0.662 -0.934 -0.338 -0.609 -0.496 -0.559 NA NA NA NA NA

THLI -0.263 -0.342 -0.124 -0.262 -0.215 -0.148 -0.251 -0.188 -0.098 -0.240 -0.282 -0.174 -0.244 -0.260 -0.299 -0.224 -0.267

Table 87. Health inequality indices, Sweden, men Year 1997 1998 1999 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004

Quarter 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1

TIW -0.146 -0.195 -0.316 -0.460 -0.357 -0.285 -0.264 -0.201 -0.257 -0.281 -0.279 -0.334 -0.315 -0.294 -0.300 -0.303 -0.312

86

Year 2004 2004 2004

Quarter 2 3 4

TIW -0.236 -0.311 -0.215

CRWA -0.241 -0.208 -0.386

TRWA -0.270 -0.147 -0.103

PIW2 NA NA NA

THLI -0.297 -0.201 -0.155

CRWA -0.404 -0.331 -0.349 -0.454 -0.290 -0.326 -0.256 -0.202 -0.209 -0.254 -0.303 -0.287 -0.228 -0.294 -0.257 -0.375 -0.325 -0.340 -0.325 -0.333

TRWA 0.098 -0.131 0.055 -0.005 -0.113 -0.054 -0.112 -0.068 0.017 -0.047 -0.001 -0.014 0.010 -0.039 -0.041 -0.038 -0.039 -0.043 -0.132 -0.021

PIW2 0.243 0.554 0.529 0.234 -0.203 -0.138 -0.331 -0.294 0.104 0.158 0.155 0.109 NA NA NA NA NA NA NA NA

THLI 0.039 -0.145 -0.076 -0.152 -0.185 -0.142 -0.217 -0.160 -0.073 -0.119 -0.130 -0.122 -0.058 -0.149 -0.155 -0.152 -0.133 -0.147 -0.232 -0.147

Table 88. Health inequality indices, Sweden, women Year 1997 1998 1999 2000 2001 2001 2001 2001 2002 2002 2002 2002 2003 2003 2003 2003 2004 2004 2004 2004

Quarter 2 2 2 2 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

TIW -0.144 -0.113 -0.174 -0.219 -0.155 -0.140 -0.163 -0.129 -0.177 -0.162 -0.173 -0.181 -0.176 -0.182 -0.214 -0.131 -0.166 -0.203 -0.217 -0.142

87

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