In April 2012 the Economic Research Service (ERS) and the Food and Nutrition Service (FNS) in the U.S. Department of Agriculture embarked on an ambitious new data collection enterprise known as the National Household Food Acquisition and Purchase Survey (FoodAPS). FoodAPS is innovative in that it is the first nationally representative household survey to collect comprehensive data on household food expenditures and acquisitions, including those obtained using benefits from food assistance programs.
A growing body of research describes how individuals make food shopping decisions in both time and space. The FoodAPS dataset provides a unique opportunity for understanding these patterns among a large sample across income, SNAP status, and settings. We addressed three questions in our research: (1) Where do participants shop for food at home (FAH) and how do individual characteristics interact with store characteristics and distance? (2) How does the nutritional content of foods purchased change as time from SNAP distribution increases?
Monthly welfare programs such as the Supplementary Nutrition Assistance Program (SNAP) produce consistent cycles of expenditure and consumption amongst recipients. Food insecurity and negative behavioral outcomes track these cycles. This paper leverages new data from the USDA, the FoodAPS survey, and to answer a variety of questions related to these phenomena: Are consumption and expenditure cycles correlated? Who bears the burden of food shortages at the end of each benefit month? Does diet quality track food expenditure?
Our research aims to address understand how both the subjective experience and objective measures of the “distance problem” and “food price problem” are associated with household food insecurity and obesity. First, we estimate the association of perceived distance and low prices with food insecurity and obesity. Next, we estimate how objectively measured access to supermarkets – based on presence of supermarkets and prices – relate to food insecurity and obesity. Specifically, our research questions are as follows:
Whether Supplemental Nutrition Assistance Program (SNAP) benefits are adequate to provide food security for eligible households is an important and timely policy question. While the nominal value of SNAP benefits is fixed across states (except for Hawaii and Alaska), variation in food prices across geographic areas is dramatic, and the real value of SNAP benefits varies widely across the U.S. Our research provides new evidence on geographic variation in the adequacy of SNAP benefits to purchase the Thrifty Food Plan (TFP).
The objective of the study was to determine relationship between neighborhood food store availability, store choice and food purchasing habits among Supplemental Nutrition Assistance Program (SNAP) participating households. The study sample consisted of SNAP households (n=1581) and low income households participating in the USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) a nationally representative cross-sectional survey of American households with household food purchases and acquisitions data.
The Supplemental Nutrition Assistance Program (SNAP) is the largest nutritional safety net in the United States. Prior research has found that participants have higher consumption shortly after receiving their benefits, followed by lower consumption towards the end of the benefit month. This “SNAP benefit cycle” has been found to have negative effects on beneficiaries.
We tested the hypothesis that high costs of living, such as from high housing rents, reduce the healthfulness of food acquisitions.
Higher food prices may aggravate household food insecurity and hurt diet quality. Using a sample of low-income households from the National Household Food Acquisition and Purchase Survey (FoodAPS), this study examines whether local food prices affect food insecurity and nutritional quality of foods acquired, and how households use competent consumer behaviors to mitigate any adverse effects of price. Financial management practices, nutrition literacy, and conscientious food shopping practices were considered for consumer competency.
We employ multilevel models with neighborhood and state effects (fixed effects and random effects) to analyze the associations between household characteristics, neighborhood characteristics, regional attributes and dietary quality. We use data from the USDA National Household Food Acquisition and Purchase Survey. Our dependent variable is a Healthy Eating Index that incorporates dollars spent and amount of food in several categories. Key explanatory variables at the household level include variables household financial condition, housing burden, home ownership, car access, household size.