Welfare State Matters: A Typological Multilevel Analysis of Wealthy Countries Hae-Joo Chung, RPh, MSc Department of Health Policy and Management, The Johns Hopkins School of Public Health

Summary of Todays Presentation To assess the relevance of welfare-state typologies to public health research, And to extend the social epidemiology based on the income inequality paradigm We analyzed 3 level conditional hierarchical models of the population health data from 19 wealthy countries of the last 35 years As a result, the regime-type effects, especially social democratic regime type had a strong explanatory power And we could see that the social democracies had maintained better population health status for the last 35 years

Welfare State Typologies Welfare-state typology has been proved to be a useful explanatory device for the emergence of welfare states, including national health policies Three (Esping-Andersen) or four (Huber & Stephens) regime- type clusters based on qualitatively different arrangements between state, market and family Liberal Welfare States Wage Earner Welfare States Conservative-Corporatist Welfare States Social Democratic Welfare States Esping-Andersen G. (1990) The Three Worlds of Welfare Capitalism Huber E and Stephens JD (2001) Development and Crisis of the Welfare State More generous

The Field of Political · Welfare State Determinants of Health The Relative Income Hypothesis and Political and Welfare- state determinants of Health, two possible mechanisms Welfare state variables are used to determine the structural mechanism through which economic inequality affects population health status Studies suggest that welfare state variables (e.g., access to health care) could be important predictors of population health outcomes However, only one study included a comprehensive number of political variables that adjust for economic determinants Coburn, 2000; Conley & Springer, 2001; Navarro & Shi, 2001; Macinko, Starfield, & Shi, 2003; Macinko, Shi, & Starfield, 2004; Muntaner, Lynch, Hillemeier, Lee, David, Benach et al., 2002

Methodological Individualism in Comparative Health Policy Analyses Assumes covariances Among the observations within each country Not between/ among countries Outcomes of a country are explained by explanatory variables of that country Countries are independent from each other Country A Year Obs 1990 a 1991 b 1992 c. Country A Year Obs 1990 a 1991 b 1992 c. Country B Year Obs 1990 a´ 1991 b´ 1992 c´. Country B Year Obs 1990 a´ 1991 b´ 1992 c´. Country-level fixed-effects models using panel datasets These are dependent These are independent

Aim To develop a more realistic model for comparative health policy analyses than widely used country-level fixed effects model To examine the change in selected population health indicators in advanced capitalist countries in the last 35 years ( ), especially before and after the neo-liberal welfare reform

Hypothesis Generosity of the Welfare-state System Better Health Worse Health Generosity of the Welfare-state System [ A Linear Distribution ] [ A Distribution as Clusters ] SocialDemocracies ChristianDemocracies WageEarner Liberal

Countries and Categorizations 19 wealthy countries, (35 years) Social Democratic Denmark Finland Norway Sweden Christian Democratic Austria Belgium France Italy Luxembourg* Netherlands Switzerland (West) Germany Wage Earner Australia Japan* New Zealand Liberal Canada Ireland The United Kingdom The United States of America

Outcome Variables and Data Sources Outcome variables The infant mortality rate (IMR) The Low birth weight rate (LBW) Data source The OECD Health Data 2000

k 2 =0 k 2 =1 Three-level Conditional Hierarchical Mixed-effects Models: A Diagram Level k: Welfare state regimes k 1 =0, 1, 2, 3, or k 2 =0, 1 Fixed effects Level j: Countries j=1, 2, 3, …, 19 Random effects Level i: Years i=0, 1, 2, …, 34 Random effects k 1 =0k 1 =1k 1 =2k 1 =3 … … …

Statistical Analyses Two outcomes (IMR and LBW) were analyzed separately SAS version 8.2 was used to obtain the estimates through the REML method Type of the Model No. of Welfare State Categories Years analyzed 3-level conditional hierarchical mixed-effects model 4 (SD, CD, WE, L) (35 years) 3-level conditional hierarchical mixed-effects model 2 (SD, Others) (35 years) 3-level conditional hierarchical mixed-effects model 2 (SD, Others) , , , , separately 1 2 3

Values for Fixed Intercepts for IMR and LBW in the 4 Regime Types All intercepts p<0.001

Results from the Analysis with 4 Welfare State Regime Types

Results from the Analysis with 2 Welfare State Groups, Variance components for year and country-level random-effects are highly significant All fixed-effects intercepts for welfare state regime types are highly significant F-test is significant for both outcomes

Change in Excess Infant Mortality Rate and Excess Low Birth Weight Rate: Social Democracies vs Others IMR LBW (μ 0 -μ 1 ) μ 0

Variance Components IMR LBW

Summary Our results provide a more appropriate account of country and regime effects than the usual pooled regression analysis used in comparative health policy analysis. Our results confirm that countries as clusters or groups share certain characteristics pertaining to them, as opposed to countries as individuals The Social Democratic regime was significantly different from other countries as a whole During the era of welfare state retrenchment, the difference in the low birth weight rate between social democracies and other countries was magnified

These Findings Could Be Due to, The development of domestic welfare state social policies universal access to health care higher female employment in the labor market higher unemployment compensation subsidies to single mothers and divorced women active labour-market intervention to ensure full employment, especially among women Or any supra-national structure: EU, NAFTA, etc. Or the geographical proximity (policy diffusion)

Implications of the Different Pattern between IMR and LBW The Social Democratic countries managed to maintain a healthier social environment, including smaller economic inequality, even after 1979, the era of welfare state retrenchment This finding is also consistent with Huber & Stephens (2001) finding: in the changed environment of the 1980s, the active, service-oriented Social Democratic welfare states were in a stronger position than the passive, transfer-oriented Christian Democratic welfare states (p.321) This statement also applies to the Liberal and Wage Earner welfare states that had started ideologically driven cuts (p.320) in the state welfare funding much earlier in time

Contributions and Limitations This study shows that population- level health indicators, such as infant mortality rate and low birth weight, have components of variance at the welfare state type supranational level (15% to 50% or more of the total variability) This study combined a longitudinal approach with a multi-level modeling approach to get stronger inferences We do not know for sure if the observed distinctive characteristics in population health are because of policy/ political differences or just reflections of geographical difference. (i.e., All Social Democratic Countries are located in Nothern Europe, whereas all Liberal countries are outside Europe, except the UK, which is a island) We do not know what aspect of welfare state regimes resulted in the difference in population health levels CONTRIBUTIONSLIMITATIONS

Conclusion and Future Directions Welfare state policies affecting maternal and child health indicators begin at a supranational level Comparative health policy studies should not consider countries as being independent from one anther The differences in population health indicators among these countries distribute as distinctive clusters of welfare state regime types More protective types of welfare state regimes, namely Social Democratic countries as a group, were able to provide a more population health- friendly environment to its citizens in the last 35 years Future studies should investigate the specific welfare regime features (i.e., by using explanatory variables) that account for welfare regime effects on maternal and child health and other related population health indicators CONCLUSION FUTURE DIRECTIONS

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