Neighborhood Socioeconomic Status, Health Insurance, and CKD Prevalence: Findings From a Large Health Care SystemPlain-Language Summary

• Main Authors: Lama Ghazi, Theresa L. Osypuk, Richard F. MacLehose, Russell V. Luepker, Paul E. Drawz
• Format: Article
• Language: English
• Published: Elsevier 2021-07-01
• Series: Kidney Medicine
• Subjects: Chronic kidney disease; Medicaid; prevalence; socioeconomic status; electronic health records
• Online Access: http://www.sciencedirect.com/science/article/pii/S2590059521000972

Rational &amp; Objective: Neighborhood socioeconomic status (SES) and health insurance status may be important upstream social determinants of chronic kidney disease (CKD), but their relationship remains unclear. The aim of this study was to determine whether neighborhood SES and individual-level health insurance status were independently associated with CKD prevalence. Study Design: Observational study using electronic health records (EHRs). Setting &amp; Participants: EHRs of patients (n = 185,269) seen at a health care system in the 7-county Minneapolis/St Paul area (2017-2018). Exposures: Census tract neighborhood SES measures (median value of owner-occupied housing units [wealth], percentage of residents aged >25 years with bachelor’s degree or higher [education]) and individual-level health insurance status (aged <65 years: Medicaid vs other insurance; ≥65 years: Medicare vs Medicare and supplemental insurance plan) were obtained from the American Community Survey and EHR data. Neighborhood SES was operationalized into quartiles, comparing low (first quartile) versus high (fourth quartile) neighborhood SES. Outcomes: CKD prevalence: estimated glomerular filtration rate < 60 mL/min/1.73 m2 or proteinuria. Analytic Approach: Multilevel Poisson regression with robust error variance with a random intercept at the census-tract level, adjusted for demographic and clinical covariates, was used to estimate the association between neighborhood SES, insurance, and CKD. Results: Neighborhood SES and insurance were independently associated with CKD prevalence. In covariate-adjusted models, patients living in low versus high neighborhood SES had a higher CKD prevalence among both younger and older patients. For example, the prevalence ratios of CKD in low versus high neighborhood SES as defined by education among patients younger than 65 and 65 years and older were 1.11 (95% CI, 1.05-1.18) and 1.08 (95% CI, 1.04-1.12), respectively. Patients younger than 65 years receiving Medicaid had higher CKD prevalence versus those with other insurance (1.51 [95% CI, 1.43-1.6]). For patients 65 years and older, insurance was not associated with prevalence of CKD in the fully adjusted model. Limitations: One health care system and selection bias. Conclusions: Living in low neighborhood SES as defined by wealth and education and having Medicaid for patients younger than 65 years were associated with higher CKD prevalence.