Longitudinal Associations Between Neighborhood Physical and Social Environments and Incident Type 2 Diabetes Mellitus

Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations

“…GIS integrates topologic geometry, which can manipulate geographic information, with automated cartography, enabling users to compile digital or hard-copy maps. GIS can quantify buffer distance between an exposure source and a human receptor and may be used to characterize proximity to roadways, factories, green spaces, water bodies, and other land uses that have either potentially adverse (e.g., ambient pesticide exposure from agricultural use) (75) or salutogenic exposures (e.g., density of healthy food stores or recreational establishments) (15). For example, NISMap, a threedimensional GIS-based propagation model of exposure to ambient radiofrequency (RF) electromagnetic fields from cellular telephone base stations for use in epidemiological studies, has been developed to integrate building geometry and damping, topographical, and antenna/transmitter data (8) (Figure 2).…”

Commentary: Reconsidering the Role of Context in Diabetes Prevention

“…With the broad adoption of geographical information systems (GIS) technologies, and the growing evidence that "place" matters, it has become possible to visualize these inequalities in new ways that are relevant to closing the translation gap. 2 As a result of residential segregation, non-Hispanic Blacks are more likely to live in neighborhood contexts that both increase exposure to stressors (ie, crime, poverty, housing instability) and constrain opportunities to self-regulate when faced with stress. 3,4 However, racial differences in diabetes among groups living in the same types of neighborhoods are strongly attenuated and in some cases eliminated, 4,5 demonstrating the influence of context in explaining variability in diabetes risk in the population.…”

“…Similar situations are repeated across the US: diabetes risk is concentrated in low-SES contexts. 2,[4][5][6] While prior work has noted the importance of environmental context for addressing disparities [4][5][6] and there are broad calls to develop place-based interventions, there is a lack of theo- 2,7 repeatedly find that these types of attributes are not strongly associated with development of diabetes. A recent study examined both objectively assessed (eg, density of food outlets per square mile) and subjectively assessed (eg, perceived availability of fresh fruits/vegetables) aspects of the built environment, and found that only the latter were predictive of incident diabetes.…”

“…A recent study examined both objectively assessed (eg, density of food outlets per square mile) and subjectively assessed (eg, perceived availability of fresh fruits/vegetables) aspects of the built environment, and found that only the latter were predictive of incident diabetes. 2 This suggests that it is not the case that we can address disparities by solely intervening on the environment. Moreover, it points to the need to consider why subjective perceptions of environmental context are related to diabetes at all, and how this might relate to social disparities in risk.…”

Neighborhood Walking Environment and Activity Level Are Associated With OSA

“…Walkability is associated with greater physical activity levels, 20,21 and exercise interventions have been found to reduce the risk and severity of sleep apnea, independent of inducing weight loss. 22,23 Recent studies have found an association between walkability and incident diabetes, 24,25 which has risk factors similar to those of OSA.…”