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Updated: Feb 17, 2026

Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Determinantes Socioeconómicos de la Enfermedad Arterial Periférica en Pacientes en Diálisis: Un Análisis a Nivel
George Liu1, Rishab Agarwal2, Neel Edupuganti1
1Medical College of Georgia, 1120 15(th) St, Augusta, Georgia, 30912, United States.
Objectives:
Peripheral artery diseases (PAD) are a growing public health problem globally and a common, debilitating comorbidity among dialysis patients. However, the impact of social determinants of health (SDH) on PAD within this population remains underexplored. This study evaluated associations between zip code-level socioeconomic indicators and PAD incidence and prevalence among U.S. dialysis patients.
Methods:
The 2022 Medicare Dialysis Facilities dataset was used to identify U.S. dialysis centers and matched associated zip codes with the Centers for Disease Control and Prevention and Agency for Toxic Substance and Disease Registry Social Vulnerability Index. Variables included community-level indicators of income, housing, employment, insurance, and access to care. Multivariable linear regression models were constructed in SPSS between SDH and PAD burden.
Results:
PAD incidence and prevalence were highest in the Northeast (M = 9.11, M = 18.66 respectively). Incidence was positively associated with poverty (β = 0.200, p < 0.001) and uninsurance (β = 0.052, p = 0.015), while housing burden, unemployment, education, and region showed inverse associations. For PAD prevalence, uninsurance remained positively associated (β = 0.088, p < 0.001); poverty, rurality, and region were negative predictors. Interaction terms (uninsurance × region; uninsurance × rurality) were significant for both outcomes. Model fit was modest (Adjusted R2 = 0.018-0.031).
Conclusions:
Uninsured status and poverty are key SDHs linked to PAD in dialysis patients, though effects vary by incidence and prevalence, reflecting the combined influence of structural, geographical, and facility disparities.
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