title: Does inequality in self-assessed health predict inequality in survival by income? Evidence from Swedish data.
abstract: This paper empirically addresses two questions using a large, individual-level Swedish data set which links mortality data to health survey data. The first question is whether there is an effect of an individual's self-assessed health (SAH) on his subsequent survival probability and if this effect differs by socioeconomic factors. Our results indicate that the effect of SAH on mortality risk declines with age-probably because of adjustment towards 'milder' overall health evaluations at higher ages-but does not seem to differ by indicators of socioeconomic status (SES) like income or education. This finding suggests that there is no systematic adjustment of SAH by SES and therefore that any measured income-related inequality in SAH is unlikely to be biased by reporting error. The second question is: how much of the income-related inequality in mortality can be explained by income-related inequality in SAH? Using a decomposition method, we find that inequality in SAH accounts for only about 10% of mortality inequality if interactions are not allowed for, but its contribution is increased to about 28% if account is taken of the reporting tendencies by age. In other words, omitting the interaction between age and SAH leads to a substantial underestimation of the partial contribution of SAH inequality by income. These results suggest that the often observed inequalities in SAH by income do have predictive power for the-less often observed-inequalities in survival by income.
authors.affiliation: Department of Health Policy and Management, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam, Netherlands. vandoorslaer@bmg.eur.nl
authors.forename: Eddy
authors.initials: E
authors.lastname: van Doorslaer
authors.forename: Ulf G
authors.initials: UG
authors.lastname: Gerdtham
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D004522:Educational Status; D036262:Empirical Research; D005260:Female; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000145:classification / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009026:Mortality; D016016:Proportional Hazards Models; D012307:Risk Factors; D012649:Self Concept; D012959:Socioeconomic Factors; D016019:Survival Analysis; D013548:Sweden / Q000453:epidemiology