The granular landscape of health disparities: a socio-spatial examination of chronic disease prevalence within New York City's community districts

Abstract

This study investigates the relationship between neighborhood Socioeconomic Position (SEP) and the prevalence of hypertension and coronary heart disease (CHD) across New York City's community districts. By using a composite SEP index derived from multiple socioeconomic indicators, the research seeks to uncover health disparities that may be obscured in broader geographic analyses. A primary objective is to identify community districts where hypertension and CHD prevalence is significantly higher than expected, even after adjusting for SEP. This focus helps pinpoint areas where targeted public health interventions may be urgently required, especially when the anticipated inverse relationship between SEP and health outcomes does not hold. A linear mixed-effects model (LMM) was used to analyze the association between SEP and these health outcomes, incorporating both fixed and random effects to account for variation across the city's 59 community districts. The analysis revealed a significant negative association between SEP and both hypertension and CHD, with higher SEP levels generally correlating with lower prevalence rates. However, some districts exhibited high random effects, indicating a higher-than-expected prevalence of these conditions, even after controlling for SEP. The authors suspect that additional factors-such as environmental exposures, healthcare accessibility, or community infrastructure-may contribute to these unexplained disparities. The findings emphasize the need for public health strategies that are sensitive to local contexts and the multifactorial nature of health inequities. Understanding the complex drivers behind these disparities can inform policies aimed at reducing health inequities in diverse urban environments.