Connected Community Classification (C3): Development, Validation, and Geospatial Application for Population Health Promotion and Equity

Abstract

Context: Social determinants of health (SDOH) impact population health. Leveraging community-level strengths related to SDOH through a social infrastructure perspective can optimize health behaviors and health outcomes to promote health equity. Objective: Our aims were to develop, validate, and apply the Connected Community Classification (C3) as comprehensive community-level measure of protective SDOH and structural factors in the Four Corners states region of the United States. Design: C3 was developed using an iterative principal component analysis of publicly available data mapped to 5 SDOH domains. Regional clustering of C3 by zip code tabulation area (ZCTA) was identified using spatial autocorrelation methods. Main Outcomes: In adjusted spatial autoregressive models, we analyzed the association of C3 with high-risk health behaviors and chronic disease prevalence using publicly available data for population-level estimates of fruit and vegetable intake, physical activity, obesity, smoking, alcohol use, coronary heart disease (CHD), diabetes, and cancer. Results: C3 was found to be reliable and valid; a C3 value of 10 indicates communities with greater connection (high), while a value of 1 indicates communities with greater separation (low) to social infrastructure. Lower connection, as measured by C3, was significantly inversely associated with lower fruit and vegetable intake, lower physical activity, and higher rates of obesity, smoking, CHD, diabetes, and cancer. C3 was significantly positively associated with heavy alcohol use. Conclusions: These findings demonstrate that communities connected to social infrastructure have better population health outcomes. C3 captures protective community attributes and can be used in future applications to assist health researchers, practitioners, nonprofits, and policymakers to advance social connection and health equity in geographically diverse underserved regions.