Local food environments vary substantially by neighborhood racial/ethnic and socioeconomic composition and may contribute to disparities in health.

There is growing interest in understanding how food environments affect diet, but characterizing the food environment is challenging. The authors investigated the relation between global diet measures (an empirically derived "fats and processed meats" (FPM) dietary pattern and the Alternate Healthy Eating Index (AHEI)) and three complementary measures of the local food environment: 1) supermarket density, 2) participant-reported assessments, and 3) aggregated survey responses of independent informants. Data were derived from the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis, a US study of adults aged 45-84 years. A healthy diet was defined as scoring in the top or bottom quintile of AHEI or FPM, respectively. The probability of having a healthy diet was modeled by each environment measure using binomial regression. Participants with no supermarkets near their homes were 25-46% less likely to have a healthy diet than those with the most stores, after adjustment for age, sex, race/ethnicity, and socioeconomic indicators: The relative probability of a healthy diet for the lowest store density category versus the highest was 0.75 (95% confidence interval: 0.59, 0.95) for the AHEI and 0.54 (95% confidence interval: 0.42, 0.70) for FPM. Similarly, participants living in areas with the worst-ranked food environments (by participants or informants) were 22-35% less likely to have a healthy diet than those in the best-ranked food environments. Efforts to improve diet may benefit from combining individual and environmental approaches.

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.

The authors examined associations among fast-food consumption, diet, and neighborhood fast-food exposure by using 2000-2002 Multi-Ethnic Study of Atherosclerosis data. US participants (n = 5,633; aged 45-84 years) reported usual fast-food consumption (never, <1 time/week, or > or =1 times/week) and consumption near home (yes/no). Healthy diet was defined as scoring in the top quintile of the Alternate Healthy Eating Index or bottom quintile of a Western-type dietary pattern. Neighborhood fast-food exposure was measured by densities of fast-food outlets, participant report, and informant report. Separate logistic regression models were used to examine associations of fast-food consumption and diet; fast-food exposure and consumption near home; and fast-food exposure and diet adjusted for site, age, sex, race/ethnicity, education, and income. Those never eating fast food had a 2-3-times higher odds of having a healthy diet versus those eating fast food > or =1 times/week, depending on the dietary measure. For every standard deviation increase in fast-food exposure, the odds of consuming fast food near home increased 11%-61% and the odds of a healthy diet decreased 3%-17%, depending on the model. Results show that fast-food consumption and neighborhood fast-food exposure are associated with poorer diet. Interventions that reduce exposure to fast food and/or promote individual behavior change may be helpful.

No abstract

Healthy foods were less available for black participants. Low availability of healthy foods was associated with a lower-quality diet. The extent to which improvements in the availability of healthy foods results in higher-quality diets deserves further investigation.

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.