Health and income: a meta-analysis to explore cross-country, gender and age differences.
BACKGROUND
Evidence of an effect of income on self-reported poor health (SRPH) is widely available in the literature. We compare this effect across age, different countries and between men and women using meta-analysis. Studies that report on an effect of income lack a homogenous effect size. To overcome this problem we propose a method to derive a homogenous effect size to enable us to compare the effect of income across groups.


METHODS
We take a meta-analytical approach to examine the effect of income on SRPH. The data consists of reported and calculated odds ratios as a measure of effect for SRPH outcomes across different income categories. Self-reported health outcomes are dichotomised into 'good' and 'poor'. With least-squares techniques, we estimate the functional parameters that describe the log-linear association between income and SRPH. Subsequently, F-tests are performed to show variations between the groups.


RESULTS
The relationship between income and SRPH is log-linear for most countries but not significantly for Sweden and the Netherlands. Our results show significant differences in the effect of income between countries. We find that men require a higher income than women to achieve comparable SRPH outcomes, and that the effect of income depends on age.


CONCLUSIONS
There is significant income related variation in SRPH between different countries even if the levels of income or the standards of living are comparable. For women income affects SRPH differently than for men. The effect of income on SRPH depends on the age of the individual respondent.
Department of Health, Ethics and Society, Faculty of Health, Medicine and Life Sciences, School Caphri, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands. c.furnee@maastrichtuniversity.nl
Carina A
CA
Furnée
Wim
W
Groot
Gerard A
GA
Pfann
D000367:Age Factors; D005060:Europe; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008297:Male; D015233:Models, Statistical; D012737:Sex Factors; D011795:Surveys and Questionnaires; D014481:United States