byJustin Jackson, Medical Xpress

Credit: Nataliya Vaitkevich from Pexels

Children's Hospital Los Angeles researchers report that physical inactivity, routine checkups, binge drinking, lack of insurance, and food insecurity were the strongest correlates of diagnosed diabetes in Southern California. National models also brought additional factors into focus.

Diabetes affected 38.4 million people in 2021, or 11.6% of the US population, with disproportionate burdens among American Indian and Alaskan Native, Black, Hispanic, and Asian American groups. Southern California includes a large Hispanic community, often of Mexican origin, creating a regional need for targeted public health strategies.

Previous studies connected social and behavioral conditions to diabetes, but many analyses used composite indices that obscure the role of individual factors. Pandemic-era disruptions altered behavior and access to care drastically enough to motivate an updated model.

In the study, "Social and Behavioral Factors Associated With Diabetes in Southern California vs. the US,"publishedinJAMA Network Open, researchers designed an ecological, cross-sectional, hypothesis-generating analysis to identify social and behavioral correlates of diagnosed diabetes in Southern California and to compare those findings with national data.

Southern California analyses covered 5,420 census tracts comprising about 18.5 million adults. National analyses covered 62,480 tracts comprising about 253 million adults. Outcome and correlates were drawn from CDC PLACES 2024 modeled estimates at the census-tract level.

Extreme gradient boosting modeled diagnosed diabetes prevalence as a function of 24 prespecified census-tract indicators expressed as percentages. Data were split into training and test sets with balanced diabetes distributions. Shapley additive explanations assigned each predictor a contribution value for every tract, reflecting how much that tract's value of a variable pushed the model's estimate above or below the dataset mean.

Model performance reached values that explained 96% of between-tract variance in Southern California and 95% nationally.

Ranking in Southern California identified five key correlates meeting a ≥5% threshold that together explained 67% of total contribution. Dependence plots showed nonlinear patterns, including inflection points near 40% for no leisure-time physical activity, 50% for food insecurity, and 10% for lack of health insurance, with plateaus for routine checkups andbinge drinking.

In Southern California, 5 tract-level correlates accounted for 67% of the modeled contribution. Key drivers were no leisure-timephysical activity31%, routine checkups 14%, lack of health insurance 6%, andfood insecurity5%.

Binge drinking showed an 11% inverse association where, as binge drinking increased, the predicted diabetes prevalence tended to decrease.

Overlap existed with Southern California, with additional national-only key drivers of obesity, receipt of food stamps, persons aged 65 years or older, and racial or ethnic minority status.

Mean diagnoseddiabetes prevalencemeasured 11.29% in Southern California and 11.52% nationally. Patterns suggest thatdiabetesprevalence may be shaped by region-specific factors tied to behavior, access, and economic conditions. More research is needed to determine why these differences appear and how they might inform more targeted prevention efforts.

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More information: Alexandra Descarpentrie et al, Social and Behavioral Factors Associated With Diabetes in Southern California vs the US, JAMA Network Open (2025). DOI: 10.1001/jamanetworkopen.2025.38377 Journal information: JAMA Network Open