The Availability and Price of Healthy Food in Seattle by Neighborhood Sociodemographic Characteristics.

INTRODUCTION: Unequal access to healthy food in the local food retail environment contributes to diet quality disparities. We assessed whether in-store availability and prices of healthy foods differ by neighborhood-level income and racial and ethnic composition in a representative sample of food stores in Seattle, Washington. METHODS: We developed and validated an in-store survey tool and surveyed 134 stores. We measured availability and prices of 19 items. For each store, we calculated a healthy food availability score (range, 0-25), and mean prices within each category. Using census tract data, we identified the median household income and proportions of Black and Hispanic residents for each store's neighborhood and grouped them by tertiles of these neighborhood characteristics across Seattle census tracts. We used Wald tests to compare mean availability scores and prices between tertiles and applied postestimation weights to reflect store-type distributions within each tertile. RESULTS: Neighborhoods with lower income and a larger proportion of Black residents had lower healthy food availability scores compared with neighborhoods with higher income (8.06 [95% CI, 7.04-9.07] vs 12.40 [95% CI, 10.63-14.17], P < .001) and fewer Black residents (8.88 [95% CI, 7.79-9.98] vs 12.32 [95% CI, 10.51-14.14], P = .003). Availability did not differ by Hispanic population proportions. Mean prices of grains, eggs, and meat were lower in neighborhoods with larger proportions of Black residents. CONCLUSION: We found systematic differences in healthy food availability based on neighborhood-level income and racial composition. In-store assessments of the food retail environment can inform local, tailored strategies to improve healthy food access.

Diet Quality and Depression in a Cohort of American Indians: The Strong Heart Family Study.

Diet quality has been shown to be inversely associated with depression, but this has not been studied in American Indians (AIs). We examined the prospective association of diet quality and probable depression in a family-based cohort of rural AIs. Using data from the Strong Heart Family Study, we included 1,100 AIs ≥14 years old who were free of probable depression at baseline. We defined probable depression as the presence of moderate or severe depressive symptoms on the Center for Epidemiologic Studies Depression Scale or current use of antidepressant medications. We calculated baseline diet quality from food frequency questionnaires using the Alternative Healthy Eating Index-2010 (AHEI). We used GEE-based multivariate logistic regression to estimate the odds ratio of probable depression at follow up associated with a 10-point higher AHEI score at baseline, adjusted for demographic, psychosocial, and health factors. At follow up, 19% (n = 207) of the sample reported probable depression. Diet quality was not associated with report of probable depression at follow up (OR = 1.16, 95% CI [0.96, 1.39]). Research is needed to examine other temporal dimensions of this relationship and unique aspects of rural AI diets and psychosocial factors that may influence depression.

Menu Labeling Utilization and Socioeconomic Status in West Virginia and Mississippi.

OBJECTIVE: Determine the association between socioeconomic status and self-reported noticing and using calorie menu labels in 2 states with high poverty and obesity. DESIGN: Cross-sectional study of responses to the 2016 Behavioral Risk Factor Surveillance System Menu Labeling Module. PARTICIPANTS: Representative sample of noninstitutionalized adults aged ≥ 18 years in West Virginia and Mississippi (n = 9,469). MAIN OUTCOME MEASURES: The outcomes were reported noticing and using menu labels to make decisions at fast-food restaurants. Independent variables were highest attained education and federal poverty level (% FPL). ANALYSIS: Generalized linear models estimated prevalence ratios for noticing and using menu labels. Models mutually adjusted for education, % FPL, age, sex, race/ethnicity, and body mass index. RESULTS: Eighty-six percent of respondents reported noticing, and 56% reported using menu labels. Compared with individuals with less than high school education, college graduates were 11% more likely to report noticing (95% confidence interval, 1.06-1.18; P < 0.001) and 18% more likely to report using (95% confidence interval, 1.06-1.30; P < 0.01) menu labels. Patterns were similar for % FPL. CONCLUSIONS AND IMPLICATIONS: These data support further investigation of menu labels among subgroups and a larger geographic scope. Limitations of the menu labeling module question and the cross-sectional nature of the existing literature warrant additional research.