The Diabetes Location, Environmental Attributes, and Disparities Network: Protocol for Nested Case Control and Cohort Studies, Rationale, and Baseline Characteristics.

Annemarie G Hirsch,Lorna E Thorpe,Brian S Schwartz,Brian Elbel,Karen Siegel,Carla Mercado,Priscilla Lopez,Tara Mcalexander,Leslie A Mcclure,April P Carson,Melissa N Poulsen,D Leann Long,Nyesha C Black,Nora L Lee

doi:10.2196/21377

Abstract

BackgroundDiabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes.ObjectiveThis paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk.MethodsThe Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region.ResultsThe Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement.ConclusionsThe Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States.International Registered Report Identifier (IRRID)DERR1-10.2196/21377

Highlights

BackgroundAn estimated 10.5% of the US population has diabetes, and these 34 million individuals are at an increased risk for coronary artery disease, cerebrovascular disease, and other complications [1,2]
The increasing availability of longitudinal, individual-level data from electronic health record (EHR) networks [28] and cohort studies, coupled with advances in geographic information systems (GISs), provides new opportunities to examine the effects of community factors on health
In 2017, the Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network was established to identify the contributions of modifiable community factors on type 2 diabetes (T2D) risk

Summary

Introduction

BackgroundAn estimated 10.5% of the US population has diabetes, and these 34 million individuals are at an increased risk for coronary artery disease, cerebrovascular disease, and other complications [1,2]. 90% to 95% of people with diabetes have type 2 diabetes (T2D) [1] Another 88 million individuals have prediabetes, defined as having elevated glucose levels above normal but below the threshold for diabetes, and are at elevated risk of developing T2D [3,4]. Diabetes prevalence and incidence vary substantially by geographic region [5,6,7]. Identifying the community factors driving T2D disparities and the pathways through which these factors influence T2D is essential to informing geographically targeted policy interventions that reduce the risk of T2D and related outcomes. Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes

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