6D-08 - Whose Health is Impacted by Income Inequality? Associations Between County-Level Income Inequality and Pharmacy Spending in an Insured Population

Background: Health is impacted not only by clinical and behavioral factors, but also by social and systemic factors like the quality of public schools and community safety. Income inequality is another such social factor found to be associated with population health.

Objectives: We assessed the relationship between county-level income inequality and pharmacy spending, with the hypothesis that inequality is associated with higher pharmacy spending due to worse health. We examined the strength of this association within patient subgroups defined by neighborhood income, age group, insurance type, and general health status.

Methods: This cross-sectional study combined publicly available data with claims data from a national health insurer. The sample included plan members of any age enrolled throughout 2019. Our primary measure of income inequality was the 2018 Gini coefficient for household income, which is a measure of the average household income gap ranging from 0 to 1, where 0 represents perfect income equality and 1 represents total income inequality. We ran linear multivariate regressions with log-transformed pharmacy spending as the outcome and the standardized Gini coefficient as the predictor. We also included many area-level and individual-level control variables in order to isolate the relationship between inequality and spending. The study population totaled 3,231,095, with average annual pharmacy costs of $850.

Results: County-level income inequality was associated with higher pharmacy spending, with a one standard-deviation increase in the Gini coefficient associated with 4.7% higher pharmacy spending [95% confidence interval (CI): 1.4-8.0%, or $12-$68 per member per year]. This estimate is similar regardless of the median household income of the member’s neighborhood. It is concentrated among members ages 18-64 with commercial insurance, rather than Medicaid or Medicare. Finally, the estimate is larger for members with generally good health (below the median Elixhauser Comorbidity Index); these members have 6.5% [95% CI: 3.2-9.8%, or $27-$84 per member per year] higher pharmacy spending in counties with one standard-deviation higher income inequality.

Conclusions: The positive association we observe between county income inequality and pharmacy spending supports the hypothesis that income inequality leads to worse health outcomes. This association was similar by neighborhood income (a proxy for individual income), so it was not driven by the pharmacy spending of the low or high end of the income distribution in unequal counties. County-level income inequality may be considered as a factor in predicting pharmacy utilization and assessing the whole health of a population.