摘要：Objectives. To examine the association of county-level cost of living with nutrition among low-income Americans. Methods. We used the National Household Food Acquisition and Purchase Survey (2012–2013; n = 14 313; including 5414 persons in households participating in the Supplemental Nutrition Assistance Program [SNAP]) to examine associations between county-level cost-of-living metrics and both food acquisitions and the Healthy Eating Index, with control for individual-, household-, and county-level covariates and accounting for unmeasured confounders influencing both area of living and food acquisition. Results. Living in a higher-cost county—particularly one with high rent costs—was associated with significantly lower volume of acquired vegetables, fruits, and whole grains; greater volume of acquired refined grains, fats and oils, and added sugars; and an 11% lower Healthy Eating Index score. Participation in SNAP was associated with nutritional improvements among persons living in higher-cost counties. Conclusions. Living in a higher-cost county (particularly with high rent costs) is associated with poorer nutrition among low-income Americans, and SNAP may mitigate the negative nutritional impact of high cost of living. Limited or uncertain access to adequate food—known as “food insecurity”—among low-income Americans is associated with poor nutrition, an increased risk of major nutrition-related chronic diseases, and poor clinical control of hypertension and type 2 diabetes. 1–5 Low-income Americans faced with food insecurity often engage in economic trade-offs—for example, sacrificing their food budgets to pay for major living expenditures, such as rent or medical bills. 6,7 High area-level cost of living may have a substantial impact on household budgets and, therefore, force such economic trade-offs. As a consequence, purchased foods may be of lower nutritional value, in part because perceived or real prices of healthier foods, such as fruits and vegetables, are often higher than those of calorie-dense, nutrient-poor food items. 8 To support nutrition among the food insecure, the nation’s largest nutritional assistance program—the Supplemental Nutrition Assistance Program (SNAP)—currently provides assistance to nearly 1 in 7 Americans. 9 Some research suggests that SNAP is associated with poorer nutrition and a higher risk of obesity 10,11 ; however, these associations generally are not observed in rigorous analyses accounting for unobserved confounders (e.g., the propensity for low-income households to live in areas with limited healthy food availability). 12,13 Furthermore, there are selection biases in comparing persons who enter into SNAP and those who do not. To our knowledge, the relationships between area-level cost of living, SNAP participation, and the healthfulness of food acquisitions have not been studied. Cost of living is of particular interest because SNAP benefits are currently based on a national average cost estimate of a basket of lower-cost foods. Previous studies suggest that the national estimate drastically underestimates food cost in some urban areas. 14 Hence, in 2013, an Institute of Medicine panel was called to assess strategies to ensure the adequacy of SNAP benefits. The panel recommended investigation into whether a smaller-area (e.g., county- or metro-level) cost-of-living adjustment could be applied to SNAP benefits, but noted the absence of sufficient local area-level cost data to perform this research. Since the panel report, comprehensive local area–level cost indices have been made available by the Bureau of Economic Analysis and the US Census. Using these newly available metrics, we sought to test 3 key hypotheses that attempt to decipher whether and under what contexts cost of living relates to the healthfulness of food acquisitions, and whether SNAP enrollment affects these associations. Our first hypothesis was that high area-level cost of living would be associated with less-healthy food acquisitions, because people would sacrifice their food budgets to pay for other costs, such as rent. Our second hypothesis was that SNAP participation would be associated with living in a lower-cost area, both because lower-income populations tend to live in lower-cost areas and because a SNAP dollar would be able to purchase more food in such areas, potentially making benefits “stretch” farther in such areas. Our third hypothesis was that SNAP participation would have a different impact on the healthfulness of food acquisitions in high- and low-cost areas, because area-level costs such as rent may affect how much SNAP users are able to stretch their SNAP allotments to cover not just less-healthy, cheaper foods but also healthier, potentially more-expensive foods.
