Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network

• Type of Material: Article
• Authors: Jalal Uddin, University of Alabama, Birmingham; Sha Zhu, University of Alabama, Birmingham; Samrachana Adhikari, New York University; Cara M. Nordberg, Geisinger; Carrie R. Howell, University of Alabama, Birmingham; Gargya Malla, University of Alabama, Birmingham; Suzanne E. Judd, University of Alabama, Birmingham; Andrea L. Cherrington, University of Alabama, Birmingham; Pasquale E. Rummo, New York University; Priscilla Lopez, New York University; Rania Kanchi, New York University; Karen R. Siegel, Emory University; Shanika A. De Silva, Drexel University; Yasemin Algur, Drexel University; Gina S. Lovasi, Drexel University; Nora L. Lee, Drexel University; April P. Carson, University of Mississippi; Annemarie G. Hirsch, Geisinger; Lorna E. Thorpe, New York University; D. Leann Long, University of Alabama, Birmingham
• Language: English
• Date: 2023-11-01
• Publisher: Elsevier
• Publication Version: Final Published Version
• Copyright Statement: © 2023 The Authors
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): https://doi.org/10.1016/j.ssmph.2023.101541
• Title of Journal or Parent Work: SSM - Population Health
• Volume: 24
• Start Page: 101541
• Grant/Funding Information: This research was conducted by the Diabetes LEAD Network, funded through the Centers for Disease Control and Prevention's cooperative agreements U01DP006293 (Drexel University), U01DP006296 (Geisinger-Johns Hopkins University), U01DP006299 (New York University School of Medicine), and U01DP006302 (University of Alabama at Birmingham), in collaboration with the U.S. Centers for Disease Control and Prevention, Division of Diabetes Translation. The REasons for Geographic and Racial Differences in Stroke (REGARDS) project was supported by cooperative agreement U01 NS041588 co-funded by the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA), National Institutes of Health, Department of Health and Human Service.
• Keywords: community types; Neighborhood socioeconomic environment; type 2 diabetes; health disparities
• Research Categories: Health Sciences, Epidemiology; Health Sciences, Public Health

Abstract

Objective Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations. Research design and methods We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE. Results Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities. Conclusions The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.