Abstract
OBJECTIVE: To analyze cause-specific mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of São Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95%CI: 2.60;14.53); ischemic heart disease (5.47 per 10,000 [95%CI 0.76;10.17]); HIV/AIDS (3.58 per 10,000 [95%CI 0.58;6.57]); and respiratory diseases (3.56 per 10,000 [95%CI 0.18;6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had significantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95%CI 0.86;4.74]), as well as among males (27.37 per 10,000 [95%CI 6.19;48.55]) and females (15.07 per 10,000 [95%CI 3.65;26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specific mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.
Highlights
The association between income and health can be assessed through two distinct mechanisms: the absolute income effect and the relative income effect
The relative income hypothesis posits that an individual’s health status is determined by his/her relative social position, which depends on the income level
We applied a statistical method known as propensity score matching to control for potential confounders of the association between income inequality and health, as highly deprived neighborhoods can have relatively equal distribution of income
Summary
The association between income and health can be assessed through two distinct mechanisms: the absolute income effect and the relative income effect. The absolute income effect is exemplified by the well-established association between income, poverty and death and illness. Those living in poverty have lower access to health services, clean water, secure jobs, decent education, as well as are more vulnerable to violence and natural disasters.[18]. The relative income hypothesis posits that an individual’s health status is determined by his/her relative social position, which depends on the income level. An individual with a given income would have worse health status when living in close proximity to wealthier individuals compared to others with a similar standard of living. To paraphrase Seneca in Epistles to Lucilius, “poor in the midst of riches, which is the sorest kind of poverty.”
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