biostudies-literatureSalerno PRVONIMHD NIH HHS1766-1774https://www.ebi.ac.uk/biostudies/studies/S-EPMC11447680biostudies-literatureUnknown26(5)<h4>Aims</h4>To investigate high-risk sociodemographic and environmental determinants of health (SEDH) potentially associated with adult obesity in counties in the United States using machine-learning techniques.<h4>Materials and methods</h4>We performed a cross-sectional analysis of county-level adult obesity prevalence (body mass index ≥30 kg/m²) in the United States using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used in a classification and regression trees (CART) model to identify county-level clusters. The CART model was validated using a 'hold-out' set of counties and variable importance was evaluated using Random Forest.<h4>Results</h4>Overall, we analysed 2752 counties in the United States, identifying a nationaDiabetes, obesity & metabolismCounty-level socio-environmental factors and obesity prevalence in the United States.PMC11447680P50 MD017351Al-Kindi SDong WRajagopalan SNasir KQian ADeo SSalerno PRVOfalseCounty-level socio-environmental factors and obesity prevalence in the United States.<h4>Aims</h4>To investigate high-risk sociodemographic and environmental determinants of health (SEDH) potentially associated with adult obesity in counties in the United States using machine-learning techniques.<h4>Materials and methods</h4>We performed a cross-sectional analysis of county-level adult obesity prevalence (body mass index ≥30 kg/m²) in the United States using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used in a classification and regression trees (CART) model to identify county-level clusters. The CART model was validated using a 'hold-out' set of counties and variable importance was evaluated using Random Forest.<h4>Results</h4>Overall, we analysed 2752 counties in the United States, identifying a nationa2024-01-01T00:00:00Z2024 May2025-04-05T08:58:25.695Z2025-04-05T08:58:25.695ZS-EPMC114476803835605310.1111/dom.15488