A Bayesian multilevel analysis exploring population-level effects mediating the relationship between area-level poverty and community-acquired Methicillin-resistant Staphylococcus aureus (CA-MRSA) infection across California communities.

Abstract

Poverty is an often-cited driver of health disparities, and associations between poverty and community-acquired Methicillin-resistant Staphylococcus aureus (CA-MRSA) infection are well documented. However, the pathways through which poverty influences infection have not been thoroughly examined. This project aims to identify mediating variables, or mechanisms, explaining why area-level poverty is associated with CA-MRSA infection in Californians. Bayesian multilevel models accounting for spatial confounding were developed to test whether the association between area-level poverty and CA-MRSA infection is mediated by living in a primary care shortage area (HCSA), living near an adult correctional facility, and residential environmental degradation. The association between area-level poverty and CA-MRSA infection can be partially explained by spatial autocorrelation, living in an HCSA, and environmental degradation in the neighborhood. Combined, the mediators explain approximately 6% of the odds of CA-MRSA infection for individuals living in neighborhoods with high poverty rates and 50% of the statistical association between area-level poverty and CA-MRSA infection. The statistical association between area-level poverty and infection was completely explained by the mediators for individuals living in neighborhoods with low poverty rates.