Geo-clustered chronic affinity: pathways from socio-economic disadvantages to health disparities
Eun Kyong Shin, Youngsang Kwon, Arash Shaban-Nejad

TL;DR
This study introduces a new concept called affinity to analyze co-occurring chronic conditions at the neighborhood level, revealing socio-economic disparities and aiding targeted public health interventions.
Contribution
It develops and validates the affinity measure as a population-level surrogate for multimorbidity using publicly available data.
Findings
Higher chronic affinity linked to socio-economic deprivation.
Crime prevalence significantly associated with increased affinity.
Disadvantaged areas show concentrated chronic affinity patterns.
Abstract
Our objective was to develop and test a new concept (affinity) analogous to multimorbidity of chronic conditions for individuals at census tract level in Memphis, TN. The use of affinity will improve the surveillance of multiple chronic conditions and facilitate the design of effective interventions. We used publicly available chronic condition data (Center for Disease Control and Prevention 500 Cities project), socio-demographic data (US Census Bureau), and demographic data (Environmental Systems Research Institute). A geo-distinctive pattern of clustered chronic affinity associated with socio-economic deprivation wasobserved. Statistical results confirmed that neighborhoods with higher rates of crime, poverty, and unemploy-ment were associated with an increased likelihood of having a higher affinity among major chronic conditions.With the inclusion of smoking in the model, however,…
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