Income, income inequality and health: what can we learn from aggregate data?
It has been suggested that, especially in countries with high per capita income, there is an independent effect of income distribution on the health of individuals. One source of evidence in support of this relative income hypothesis is the analysis of aggregate cross-section data on population health, per capita income and income inequality. We examine the empirical robustness of cross-section analyses by using a new data set to replicate and extend the methodology in a frequently cited paper. The estimated relationship between income inequality and population health is not significant in any of our estimated models. We also argue there are serious conceptual difficulties in using aggregate cross-sections as a means of testing hypotheses about the effect of income, and its distribution, on the health of individuals.
Gravelle
Hugh
H
National Primary Care Research and Development Centre, University of York, Heslington, UK. hg8@york.ac.uk
Wildman
John
J
Sutton
Matthew
M
D003430:Cross-Sectional Studies; D006304:Health Status; D019456:Health Transition; D006801:Humans; D007182:Income / Q000706:statistics & numerical data* / Q000639:trends; D008017:Life Expectancy; D008297:Male; D017059:Models, Econometric; D011203:Poverty / Q000706:statistics & numerical data* / Q000639:trends; D015203:Reproducibility of Results; D012107:Research Design; D012307:Risk Factors; D012959:Socioeconomic Factors; D018709:Statistics, Nonparametric; D016019:Survival Analysis