Importance: Social Determinants of Health (SDOH) have been found to be associated with health outcome disparities in patients with peripheral artery disease (PAD). However, the association of specific components of SDOH and amputation has not been well described.
Objective: To evaluate whether individual components of SDOH and race are associated with amputation rates in the most populous counties of the US.
Design, setting, and participants: In this population-based cross-sectional study of the 100 most populous US counties, hospital discharge rates for lower extremity amputation in 2017 were assessed using the Healthcare Cost and Utilization Project State Inpatient Database. Those data were matched with publicly available demographic, hospital, and SDOH data. Data were analyzed July 3, 2022, to March 5, 2023.
Main outcome and measures: Amputation rates were assessed across all counties. Counties were divided into quartiles based on amputation rates, and baseline characteristics were described. Unadjusted linear regression and multivariable regression analyses were performed to assess associations between county-level amputation and SDOH and demographic factors.
Results: Amputation discharge data were available for 76 of the 100 most populous counties in the United States. Within these counties, 15.3% were African American, 8.6% were Asian, 24.0% were Hispanic, and 49.6% were non-Hispanic White; 13.4% of patients were 65 years or older. Amputation rates varied widely, from 5.5 per 100 000 in quartile 1 to 14.5 per 100 000 in quartile 4. Residents of quartile 4 (vs 1) counties were more likely to be African American (27.0% vs 7.9%, P < .001), have diabetes (10.6% vs 7.9%, P < .001), smoke (16.5% vs 12.5%, P < .001), be unemployed (5.8% vs 4.6%, P = .01), be in poverty (15.8% vs 10.0%, P < .001), be in a single-parent household (41.9% vs 28.6%, P < .001), experience food insecurity (16.6% vs 12.9%, P = .04), or be physically inactive (23.1% vs 17.1%, P < .001). In unadjusted linear regression, higher amputation rates were associated with the prevalence of several health problems, including mental distress (β, 5.25 [95% CI, 3.66-6.85]; P < .001), diabetes (β, 1.73 [95% CI, 1.33-2.15], P < .001), and physical distress (β, 1.23 [95% CI, 0.86-1.61]; P < .001) and SDOHs, including unemployment (β, 1.16 [95% CI, 0.59-1.73]; P = .03), physical inactivity (β, 0.74 [95% CI, 0.57-0.90]; P < .001), smoking, (β, 0.69 [95% CI, 0.46-0.92]; P = .002), higher homicide rate (β, 0.61 [95% CI, 0.45-0.77]; P < .001), food insecurity (β, 0.51 [95% CI, 0.30-0.72]; P = .04), and poverty (β, 0.46 [95% CI, 0.32-0.60]; P < .001). Multivariable regression analysis found that county-level rates of physical distress (β, 0.84 [95% CI, 0.16-1.53]; P = .03), Black and White racial segregation (β, 0.12 [95% CI, 0.06-0.17]; P < .001), and population percentage of African American race (β, 0.06 [95% CI, 0.00-0.12]; P = .03) were associated with amputation rate.
Conclusions and relevance: Social determinants of health provide a framework by which the associations of environmental factors with amputation rates can be quantified and potentially used to guide interventions at the local level.