Social Determinants of Health and Incident Type 2 Diabetes Risk: Real-World Evidence from The Houston Methodist CV Learning Health System (HM-CV-LHS) Registry

Résumé fourni par la source

Background: Modern electronic medical record (EMR) registries offer unique opportunities to assess distinct social determinants of health (SDoH) phenotypes of patients with diverse cardiovascular disease risk profiles. While SDoH has been correlated with type 2 diabetes mellitus (T2DM) risk, little is known about the longitudinal impact of aggregate social burden on new-onset T2DM using real-world EMR data in a contemporary, integrated, health system setting. Methods: We conducted a retrospective cohort study of patients ≥ 18 years from the 2016-2023 Houston Methodist -CV-Learning Health System (HM-CV-LHS) registry. SDoH domains included difficulty affording medication, food insecurity, transportation barriers and mental health, aggregated to create a composite index and categorized into high, low and optimal risk. Cox proportional hazards models were used to predict the risk of new-onset T2DM in those without diabetes at baseline, based on individual and aggregate SDoH burden. Results: Among the 1.2 million patients in the HM-CV-LHS registry, 156,677 with available data on all 4 SDoH domains were included in the final analytic sample. During mean follow-up of 3.5 years (7 years total), 8% developed new-onset T2DM. T2DM incidence exhibited a consistent, dose-response relationship with increasing SDoH burden. In models fully adjusted for traditional risk factors, patients experiencing the highest SDoH burden were nearly twice as likely to experience incident diabetes, compared to those with optimal social profile (aHR=1.95; 95% CI=1.81,2.11). Conclusions: SDoH are robust, independent predictors of T2DM. Proactive incorporation of SDoH data into patient care could optimize social interventions to prevent T2DM risk and reduce health disparities. Article Highlights: · What is already known on this topic? Social determinants of health (SDoH) influence risk for type 2 diabetes mellitus (T2DM), but real-world, EMR-based evidence assessing longitudinal impact is limited. · What is added by this report? This study uses a large integrated EMR registry to show a strong, dose-dependent relationship between cumulative SDoH burden and incident T2DM, independent of traditional risk factors. · What are the implications for public health practice? Routine screening and integration of SDoH data into clinical care can enable targeted interventions and community resource navigation to prevent T2DM and reduce health disparities.

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