Functional Clustering for Longitudinal Associations between Social Determinants of Health and Stroke Mortality in the US

TL;DR

This study introduces a novel clustering method using a regularized EM algorithm to analyze how social determinants of health relate to stroke mortality over time across US counties, revealing regional disparities.

Contribution

The paper develops a new regularized EM clustering approach that simultaneously identifies key SDOH and groups counties based on their longitudinal associations with stroke mortality.

Findings

Identified 18 key SDOH influencing stroke mortality.

Divided US counties into two distinct clusters based on SDOH associations.

Revealed significant regional heterogeneity in SDOH-stroke mortality relationships.

Abstract

Understanding the longitudinally changing associations between Social Determinants of Health (SDOH) and stroke mortality is essential for effective stroke management. Previous studies have uncovered significant regional disparities in the relationships between SDOH and stroke mortality. However, existing studies have not utilized longitudinal associations to develop data-driven methods for regional division in stroke control. To fill this gap, we propose a novel clustering method to analyze SDOH -- stroke mortality associations in US counties. To enhance the interpretability of the clustering outcomes, we introduce a novel regularized expectation-maximization algorithm equipped with various sparsity-and-smoothness-pursued penalties, aiming at simultaneous clustering and variable selection in longitudinal associations. As a result, we can identify crucial SDOH that contribute to longitudinal changes in stroke mortality. This facilitates the clustering of US counties into different regions based on the relationships between these SDOH and stroke mortality. The effectiveness of our proposed method is demonstrated through extensive numerical studies. By applying our method to longitudinal data on SDOH and stroke mortality at the county level, we identify 18 important SDOH for stroke mortality and divide the US counties into two clusters based on these selected SDOH. Our findings unveil complex regional heterogeneity in the longitudinal associations between SDOH and stroke mortality, providing valuable insights into region-specific SDOH adjustments for mitigating stroke mortality.