Wage inequality, the health system, and infant mortality in wealthy industrialized countries, 1970-1996.
This pooled, cross-sectional, time-series study assesses the impact of health system variables on the relationship between wage inequality and infant mortality in 19 OECD countries over the period 1970-1996. Data are derived from the OECD, World Value Surveys, Luxembourg Income Study, and political economy databases. Analyses include Pearson correlation and fixed-effects multivariate regression. In year-specific and time-series analyses, the Theil measure of wage inequality (based on industrial sector wages) is positively and statistically significantly associated with infant mortality rates--even while controlling for GDP per capita. Health system variables--in particular the method of healthcare financing and the supply of physicians--significantly attenuated the effect of wage inequality on infant mortality. In fixed effects multivariate regression models controlling for GDP per capita and wage inequality, variables generally associated with better health include income per capita, the method of healthcare financing, and physicians per 1000 population. Alcohol consumption, the proportion of the population in unions, and government expenditures on health were associated with poorer health outcomes. Ambiguous effects were seen for the consumer price index, unemployment rates, the openness of the economy, and voting rates. This study provides international evidence for the impact of wage inequalities on infant mortality. Results suggest that improving aspects of the healthcare system may be one way to partially compensate for the negative effects of social inequalities on population health.
Macinko
James A
JA
Department of Health Administration and Planning, National School of Public Health/Fundação Oswaldo Cruz, Rio de Janeiro, Brazil. jmacinko@jhu.edu
Shi
Leiyu
L
Starfield
Barbara
B
D003256:Community Participation; D003695:Delivery of Health Care / Q000191:economics*; D019049:Developed Countries / Q000191:economics* / Q000706:statistics & numerical data; D019981:Health Care Sector; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000145:classification; D007226:Infant Mortality / Q000639:trends*; D007231:Infant, Newborn; D008137:Longitudinal Studies; D017059:Models, Econometric; D010820:Physicians / Q000600:supply & distribution; D017149:Private Sector / Q000191:economics; D017150:Public Sector / Q000191:economics; D012044:Regression Analysis; D012456:Salaries and Fringe Benefits / Q000145:classification / Q000639:trends*; D012959:Socioeconomic Factors; D012962:Sociology, Medical