Type 2 diabetes prevalence is increasing among U.S. adults (Centers for Disease Control and Prevention, 2022a) with 11.3% of the U.S. population estimated to have type 2 diabetes. Type 2 diabetes is the highest cost chronic condition in the U.S (Centers for Disease Control and Prevention, 2022a). Glycemic control helps to prevent complications including eye disease, kidney disease, nerve damage, stroke, and heart disease as over 50% of lifetime medical costs due to type 2 diabetes are related to disease complications (Zhuo et al., 2013).

Healthy diet, physical activity and weight management are cornerstones of effective diabetes self-management in conjunction with pharmacologic interventions (Pillay et al., 2015; Wing et al., 2013; Colberg et al., 2016; Gray et al., 2000; National Institute of Diabetes and Digestive and Kidney Diseases, 2016; Davies et al., 2022). In addition, social determinants such as living environment may contribute to diabetes management (Davies et al., 2022). An important part of living environments is the neighborhood built environment, defined as physical, contextual characteristics of where people live, work and play (Centers for Disease Control and Prevention, 2022b). Indeed, the built environment has been associated with diet and physical activity (Dixon et al., 2021) and body weight (Buszkiewicz et al., 2021) as well as health outcomes including hypertension and type 2 diabetes (De la Fuente et al., 2020; Frank et al., 2022; den Braver et al., 2018; Chandrabose et al., 2019). The built environment could influence glycemic control (Howell et al., 2022) through its associations with physical activity and diet, as well as through other factors that affect type 2 diabetes management such as stress and sleep (Davies et al., 2022).

Limited evidence has associated the built environment to glycemic control measured with hemoglobin A1c (HbA1c) values (lower is better). A New York City diabetes registry study found that living in, or moving to, ZIP codes with more access to “neutral” or “healthy” food outlets and higher walkability was associated with lower HbA1c over 7 years (Tabaei et al., 2018). A key limitation of the study was geocoding at the ZIP code level and the inability to disentangle which specific built environment variables were most associated with glycemic control. In a Kaiser Permanente Northern California diabetes registry, loss of supermarket availability within 1 mile of a residential census block was associated with higher HbA1c over 4 years, particularly for those with moderate or poor glycemic control at baseline (Zhang et al., 2017). Paradoxically, gaining a supermarket was also associated with worse HbA1c among people with poor glycemic control at baseline (Zhang et al., 2017).

It remains unclear whether specific built environment variables, including residential density, proximity to supermarkets, and proximity to parks, are associated with glycemic control among people with type 2 diabetes. The goal of this study was to leverage access to historical electronic health record (EHR) and residential address data to examine whether exposure to different neighborhood built environment features was associated with longitudinal changes in HbA1c in people with type 2 diabetes over long-term follow-up independent of socioeconomic status, demographics, and severity of diabetes. Overcoming limitations in prior studies, we measured built environment exposures at the address level rather than ZIP code or census tract level and included examination of parks and residential density. We hypothesized that greater residential density, proximity to parks, and food access (e.g., lower fast food outlet density and higher supermarket density) would be associated with better HbA1c, after accounting for socioeconomic status (as measured by individual-level residential property values).