A comparison of social drivers of health identification and intervention rates by sex among patients receiving primary care - Leah A. Holcomb; Elizabeth Crabtree Killen; Kelsey R. Ryan; Aimee L. McRae-Clark; Stacey Seipel; Rita Aidoo; Constance Guille (Biology of Sex Differences)
Abstract Background Social drivers of health (SDOH) significantly influence health behaviors and outcomes, yet sex-based disparities in these domains remain underexplored. Identifying these differences is essential for guiding equitable, evidence-based interventions. Methods We analyzed electronic health record (EHR) data from all patients with a documented male or female sex who had a primary care visit or inpatient stay at the Medical University of South Carolina (MUSC) between January 1, 2023, and December 31, 2024 (n = 493,920). SDOH screening responses were categorized as “affirmative” (at risk) or “negative” (not at risk) across 17 predefined domains using Epic’s logic-based risk classification. Descriptive statistics were calculated, and z-tests for proportions were used to assess sex-based differences. Race and ethnicity were included as descriptive variables; no inferential tests by race/ethnicity were conducted. Results Females were significantly more likely to report financial strain (7.96%), food insecurity (4.44%), housing instability (3.72%), intimate partner violence (2.03%), transportation barriers (2.20%), depression (3.93%), and stress (14.10%). Despite these risks, females also reported higher rates of protective behaviors such as physical activity (74.2%) and social connectedness (14.22%). In contrast, males had higher rates of alcohol use (4.67%), tobacco use (35.6%), and adolescent substance use (2.14%). Notably, White/Caucasian males reported the highest alcohol use (6.23%), and both White and Black males reported the highest tobacco use (42%). Conclusions Sex-based disparities in SDOH reflect broader structural and social inequities. Health systems should implement routine, EHR-integrated SDOH screening and use this data to inform tailored, gender-responsive interventions—such as increasing access to mental health support for women and addressing substance use among men—while also considering how intersecting factors like race, income, and caregiving burden compound these risks.