Measuring and Mapping Obesogenic Environments with Composite Indices in Fairfax County, Virginia

• Activity Number: 460 - Causal Methods for Discovery, Confirmation and Mechanistic Evaluation
• Type: Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Quinton Neville* and Teja Pristavec and Josh Goldstein
• Companies: Columbia University Department of Biostatistics and University of Virginia Biocomplexity Institute, Social and Decision Analytics Lab and University of Virginia Biocomplexity Institute, Social and Decision Analytics Lab
• Keywords: Social Determinants of Health; Latent Variables; Factor Analysis; Data Science; Public Health; Composite Indices

Abstract

The Social Determinants of Health (SDOH), or simply the environments in which people live, have an astounding effect on individuals' health risks and outcomes. However, research in SDOH disparity is usually conducted at the county-level, providing limited insight for policy and decision-making at finer geographies. This study, partnered with Fairfax County, demonstrates the feasibility of examining SDOH at sub-county levels with novel use of publicly available data. Specifically, we construct obesogenic environment composite indices to measure the effectiveness of Live Healthy Fairfax, the county's public health policy initiative. Utilizing a synthetic American Community Survey population, housing stock data, and SDOH geospatial features, index scores are computed with an internally consistent three-factor SES, Food Environment, and Physical Environment latent variable model. Results highlight areas and environments where residents are at high risk for poor health outcomes, at geographies relevant for decision-making. Further, our approach provides a no or low-cost technique to better understand, measure, and improve the health of communities at the sub-county level.