BackgroundThe evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves.ObjectivesWe situated vulnerability to heat in geographic space and identified potential areas for intervention and further research.MethodsWe mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value.ResultsFour factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat.ConclusionsThese methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.

Recreational facilities and the resources they offer are not equitably distributed. The presence of parks in poor and minority areas suggest that improving the types and quality of resources in parks could be an important strategy to increase physical activity and reduce racial/ethnic and socioeconomic disparities.

Measuring features of the local food environment has been a major challenge in studying the effect of the environment on diet. This study examined associations between alternate ways of characterizing the local food environment by comparing Geographic Information System (GIS)-derived densities of various types of stores to perception-based measures of the availability of healthy foods. Survey questions rating the availability of produce and low-fat products in neighborhoods were aggregated into a healthy food availability score for 5,774 residents of North Carolina, Maryland, and New York. Densities of supermarkets and smaller stores per square mile were computed for 1 mile around each respondent's residence using kernel estimation. The number of different store types in the area was used to measure variety in the food environment. Linear regression was used to examine associations of store densities and variety with reported availability. Respondents living in areas with lower densities of supermarkets rated the selection and availability of produce and low-fat foods 17% lower than those in areas with the highest densities of supermarkets (95% CL, −18.8, −15.1). In areas without supermarkets, low densities of smaller stores and less store variety were associated with worse perceived availability of healthy foods only in North Carolina (8.8% lower availability, 95% CL, −13.8, −3.4 for lowest vs. highest small-store density; 10.5% lower 95% CL, −16.0, −4.7 for least vs. most store variety). In contrast, higher smaller store densities and more variety were associated with worse perceived healthy food availability in Maryland. Perception-and GIS-based characterizations of the environment are associated but are not identical. Combinations of different types of measures may yield more valid measures of the environment.KEYWORDS Environment, Neighborhoods, Food, GIS, Survey assessment.Several studies have linked local food environments to diet quality, 1-11 although the extent to which these associations reflect causal processes remains a topic of research. A major challenge in this work has been developing valid and reliable measures of the local food environment. Many studies have characterized food environments by counting the number of certain types of stores (usually supermarkets) in the census tracts or zip codes in which study participants live. [12][13][14][15][16] This approach relies on the assumptions that only supermarkets offer an array of healthy foods and that the range and quality of healthy foods offered by supermarkets are invariant over space.

Availability of resources may be 1 of several environmental factors that influence individuals' physical activity behaviors.