In this cohort study, the features of residential environment that support physical activity and healthy diets were associated with lower incidence of type 2 diabetes during 5 years of follow-up. Associations between type 2 diabetes incidence and residential environment persisted after adjustment for individual-level variables, including age, sex, family history of diabetes, socioeconomic characteristics, smoking status, alcohol intake, physical activity level, and dietary factors. They were slightly reduced after additional adjustment for baseline BMI.
Considering the distal relationship between residential conditions and their biological manifestations, it is noteworthy that we found an effect of such large magnitude: at least 36% lower diabetes incidence during 5 years’ follow-up corresponding to a difference between the 90th and 10th percentiles in physical activity and food environments (or a 20% lower diabetes incidence when the neighborhood unit represented the interquartile range). The strength of the association was considerable and equivalent to a reduction in type 2 diabetes incidence associated with a BMI of 5 values lower in this sample. Associations of neighborhood resources with incident diabetes even persisted after controlling for baseline elevated glucose levels.
Our analyses only weakly suggested that individual-level dietary factors, physical activity level, and BMI were intermediaries in the association between neighborhood resources and diabetes incidence. This may reflect measurement error for individual health behaviors, which are notoriously difficult to measure. In addition, health behaviors were not measured at each follow-up visit (eg, dietary factors were measured only at baseline). Furthermore, teasing apart specific mediating pathways is difficult because of the distal relationships and time lags involved, as well as problems inherent in separating direct and indirect effects in regression analyses.28,29
Future analyses are being planned that will improve investigation of these intermediaries by examining direct associations between neighborhood resources and these hypothesized mediators (work that was outside the scope of this study) and by using forthcoming data collected over a longer follow-up period.
One of the strengths of the neighborhood data we used is that we assessed multiple dimensions of specific aspects of the physical environment that plausibly have direct relevance to the development of diabetes. The extent to which availability of resources relates to resource utilization remains a complex question that this study did not answer. However, our data ascertained neighborhood resource access, quality, quantity, and diversity, factors that impact population-level resource utilization.30–32
This study followed up participants for 5 years. However, type 2 diabetes develops slowly over a long period, making long-term chronic exposures most relevant. Most participants had resided in their neighborhoods for a long time (median, 17 years at baseline); therefore, to the extent that neighborhood environments remain stable over time, participants may have had long-term exposure to resources in their neighborhood. Although some participants moved out of their baseline neighborhood during the study, they tended to relocate to neighborhoods that shared similar characteristics, and there was high correlation between pre- and postmove neighborhood scores. Neighborhood effects on the incidence of type 2 diabetes were similar between movers and nonmovers.
Among the strengths of this study are that we assessed incident diabetes during multiple follow-up visits among a large, multisite, population-based, multiethnic sample. Very few studies have examined the effects of neighborhood resources on incident disease. Nevertheless, this study is subject to well-known limitations of using observational data for causal inference.33
For example, there is the possibility that residual confounding and self-selection into neighborhoods could account for some of the observed results (eg, active individuals tend to self-select neighborhoods that are suitable for being physically active).34,35
We used causal diagrams36
to anticipate important confounders and carefully adjusted for a number of individual-level variables. The ability of persons to self-select neighborhoods likely depends on personal characteristics (eg, income and race/ethnicity); therefore, we adjusted for these variables in multivariable regression. Replication of our results would increase confidence in our findings, and we encourage future research using a variety of study designs and methods to examine the effects of neighborhood resources on incident diabetes. Future research could evaluate changes in neighborhood environments via quasi-experiments (ie, “natural experiments”) or through specifically designed randomized trials. Yet, even those study designs can be suboptimal for answering our research question because there are logistical and ethical concerns as well as limitations to generalizability.37
Therefore, it is likely that multiple types of evidence, including observational data, will be needed to determine the desirability and effectiveness of policy interventions targeting neighborhood environments.
The prevalence of type 2 diabetes has increased substantially in the past 30 years. This makes it all the more urgent to identify environmental features that may mitigate risk of type 2 diabetes. Our results are consistent with the hypotheses that improving environmental features such as having nearby, pleasant, safe destinations within walking distance and improving the availability of healthy foods may halt increases in type 2 diabetes incidence. Many urban environments have developed with insufficient consideration for the ways that environments can promote or discourage healthy behaviors. Current efforts to foster health-promoting environments include designing and modifying physical environments, such as zoning residential neighborhoods to require safe sidewalks, creating parks and attractive public green spaces, and improving public transportation so that residents rely less on their cars38
; supporting fresh-food farmers’ markets in low-income, urban neighborhoods; and assisting stores in those neighborhoods in improving their selection of healthy foods.39,40
There is unlikely to be a panacea for the obesity epidemic and rising epidemic of type 2 diabetes. However, altering our environments so that healthier behaviors and lifestyles can be easily chosen may be one of the key steps in arresting and reversing these epidemics.