Associations between Income Inequality, HIV Diagnosis Rate and Primary Care Access: 2008-2013 Open Access

Ahlschlager, Lauren (2016)

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Background: Income inequality has been increasing in the United States for decades, making the U.S. one of the most inequitable nations in the developed world. Previous studies have shown positive associations between income inequality and poor health outcomes, namely mortality, however none have assessed HIV as an outcome in these analyses. In an attempt to identify ways to ameliorate this growing issue, some studies have demonstrated a mediating effect of access to healthcare on the relationship between income inequality and population health.

Objective: This analysis sought to describe the association between HIV diagnosis rates and income inequality among U.S. counties and states and further aimed to detect any presence of a mediating effect of primary care physician supply on this relationship.

Methods: We used publicly available data to examine the association both between HIV diagnosis rate and income inequality as well as all-cause age-adjusted mortality rate and income inequality using log-transformed linear regression. We calculated mean rate ratios (MRR) to describe these relationships at both county and state levels. Further, primary care physician rate was examined as a possible mediator of these associations.

Results: Associations between income inequality and both HIV diagnosis rate and all-cause mortality rate were observed across 499 U.S. counties and 50 states. Higher levels of income inequality were significantly associated with higher HIV diagnosis rates (MRR for a 5 point increase in Gini Index=1.25, 95% CI: 1.17, 1.35). This relationship was also observed at the state level (MRR for a 1 point increase in Gini index=1.19, 95% CI: 1.09, 1.30). Mixed results were obtained for the association between Gini index and mortality rate for both counties and states. The significant associations between income inequality and HIV diagnosis rate did not appear to be mediated by primary care physician supply.

Discussion: Income inequality is a significant independent predictor of HIV diagnosis rates at both the county and state levels. Future analyses should examine the extent to which alternative measures of access to care might mitigate the effect of income inequality on HIV diagnosis rates in order to better inform potential intervention efforts.

Table of Contents




Descriptive Analysis 8

Bivariate Analyses 10

Model Selection 11

Mediation Analysis 17


Limitations 23

Future Directions 25



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