Research Projects and Publications
ERS and external researchers are actively involved in rigorous research using FoodAPS data to examine food demand relationships that previously could not be investigated in detail because the requisite data did not exist. A list of published research and work in progress follows:
- Published research
- Work in progress
A report by Michelle Saksena, Abigail Okrent, Tobenna D. Anekwe, Clare Cho, Chris Dicken, Howard Elitzak, Joanne Guthrie, Karen Hamrick, Jeffrey Hyman, Young Jo, Biing-Hwan Lin, Lisa Mancino, Patrick W. McLaughlin, Ilya Rahkovsky, Katherine Ralston, Travis A. Smith, Hayden Stewart, Jessica E. Todd, and Charlotte Tuttle examines the growing availability of food away from home (FAFH). The report presents research on food choices and availability; nutrition and diet quality; and food policies, including menu labeling and food assistance programs; it also examines how FAFH choices relate to diet quality and socio-demographic characteristics.Consumers Balance Time and Money in Purchasing Convenience Foods
A report by Ilya Rahkovsky, Young Jo, and Andrea Carlson examines how consumers' financial resources, time constraints, prices, and the food environment in which they live influence their purchases of restaurant meals and food from grocery stores (June 2018).The Association Between Nutrition Information Use and the Healthfulness of Food Acquisitions
A report by Eliana Zeballos and Tobenna D. Anekwe constructs a Nutrition Information Use (NIU) index to summarize consumers' use of nutrition information and to test for a correlation between consumers' NIU and their purchases of more healthful food. The report then explores how this correlation compares for food at home and food away from home (April 2018).Nutritional Quality of Foods Acquired by Americans: Findings From USDA’s National Household Food Acquisition and Purchase Survey
A report by Lisa Mancino, Joanne Guthrie, Michele Ver Ploeg, and Biing-Hwan Lin. This study investigates possible influences on the foods that Americans purchase or otherwise acquire, including consumer income levels, food sources (stores and other sources), food-source access, and participation in the Supplemental Nutrition Assistance Program, SNAP (February 2018).USDA's National Household Food Acquisition and Purchase Survey: Methodology for Imputing Missing Quantities To Calculate Healthy Eating Index-2010 Scores and Sort Foods Into ERS Food Groups
In a report by Lisa Mancino, Jessica E. Todd, and Benjamin Scharadin, responses from USDA's FoodAPS survey are used to measure the nutritional quality of household food acquisitions against the 2010 Healthy Eating Index. ERS researchers have developed a method for imputing missing food quantities used to assess effects of economic and socio-demographic factors on respondents' food intake (January 2018).The Relationship Between Patronizing Direct-to-Consumer Outlets and a Household’s Demand for Fruits and Vegetables
A report by Hayden Stewart and Diansheng Dong. This study uses data from USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) to investigate whether patronizing farmers markets, roadside stands, and other direct-to-consumer (DTC) outlets increases a household’s spending for fruits and vegetables, including purchases at both DTC and non-direct food retailers (January 2018).The Influence of Food Store Access on Grocery Shopping and Food Spending
A report by Michele Ver Ploeg, Elizabeth Larimore, and Parke E. Wilde. Low access to foodstores such as supermarkets may mean that households rely on nearby retailers like convenience stores or fast-food restaurants that do not offer a variety of healthful foods. The report assesses how the local food environment, household mobility, and assets are related to where households shop for food (October 2017).The Food-Spending Patterns of Households Participating in the Supplemental Nutrition Assistance Program: Findings From USDA's FoodAPS
A report by Laura Tiehen, Constance Newman, and John A. Kirlin. This study uses data from USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) to compare food expenditures of SNAP households with those of eligible nonparticipant households and all households. The researchers examined variations in food spending by SNAP households' characteristics, the contribution of SNAP benefits to household food expenditures, and changes in food-spending patterns during the month after receiving benefits (August 2017).
A report by Young Jo. Using data from USDA’s 2012 National Household Food Acquisition and Purchase Survey (FoodAPS), this study examines characteristics of households with and without obese children to understand potential reasons behind the dissimilar risks of child obesity (September 2017).
A report by Dawn Marie Clay, Michele Ver Ploeg, Alisha Coleman-Jensen, Howard Elitzak, Christian Gregory, David Levin, Constance Newman, and Matthew P. Rabbitt. Data from USDA's National Household Food Acquisition and Purchase Survey (FoodAPS), the first nationally representative household survey to collect data on foods purchased or acquired during a survey week, are compared with data from other national-level, food-related surveys (July 2016).Where Households Get Food in a Typical Week: Findings from USDA’s FoodAPS
A report by Jessica E. Todd and Benjamin Scharadin. Understanding where U.S. households acquire food, what they acquire, and what they pay is essential to identifying which food and nutrition policies might improve diet quality. This report uses USDA’s National Household Food Acquisition and Purchase Survey (FoodAPS) to study where households acquired food during a 7-day period in 2012 (July 2016).WIC Household Food Purchases Using WIC Benefits or Paying Out of Pocket: A Case Study of Cold Cereal Purchases
A report by Diansheng Dong, Hayden Stewart, Elizabeth Frazão, Andrea Carlson, and Jeffrey Hyman. WIC households incur no cost for WIC-approved foods, and economic theory suggests that they may be less sensitive to prices when using WIC benefits than when paying out of pocket. ERS examines this assumption in a case study of WIC households' choices in purchasing cold cereals (May 2016).Where Do Americans Usually Shop for Food and How Do They Travel To Get There? Initial Findings from the National Household Food Acquisition and Purchase Survey
A report by Michele Ver Ploeg, Lisa Mancino, Jessica E. Todd, Dawn Marie Clay, and Benjamin Scharadin. This report compares food shopping patterns of (1) Supplemental Nutrition Assistance Program (SNAP) households to nonparticipant households, (2) participants in the Special Supplemental Nutrition Assistance Program for Women Infants and Children (WIC) to nonparticipants, and (3) food-insecure to food-secure households. On March 31, 2015, ERS hosted a webinar: First Findings from USDA's FoodAPS that provided an overview of FoodAPS and this report.
Published reports and articles based on FoodAPS data are also searchable in the ERS Food and Nutrition Assistance Research Reports Database.
"Supermarkets, Schools, and Social Gatherings: Where SNAP and Other U.S. Households Acquire Their Foods Correlates With Nutritional Quality"—by Lisa Mancino and Joanne Guthrie (February 2018).
"Households With at Least One Obese Child Differ in Several Ways From Those Without"—by Young Jo (December 2017).
"Nearly 30 Percent of the Times That USDA SNAP Households Acquire Food, the Food Is Free"—by Jessica E. Todd (November 2017).
"USDA’s FoodAPS: Providing Insights Into U.S. Food Demand and Food Assistance Programs"—by Jessica E. Todd, Laura Tiehen, and Dawn Marie Clay (August 2017).
"FoodAPS Data Now Available to the General Public"—by Elizabeth Larimore, Elina T. Page, and John A. Kirlin (December 2016).
"Recent Evidence on the Effects of Food Store Access on Food Choice and Diet Quality"—by Michele Ver Ploeg and Ilya Rahkovsky (May 2016).
"Most U.S. Households Do Their Main Grocery Shopping at Supermarkets and Supercenters Regardless of Income"—by Rosanna Mentzer Morrison and Lisa Mancino (August 2015).
"The National Household Food Acquisition and Purchase Survey: Innovations and Research Insights,"—Elina T. Page, Elizabeth Larimore, John A. Kirlin, and Mark Denbaly, Applied Economic Perspectives and Policy. This article provides a thorough overview of FoodAPS, including the rationale for the survey, recent research findings and insights on American diet quality, food assistance programs, and food environment, as well as the challenges encountered from developing, collecting, and processing the data. This innovative survey collected nationally-representative data on household food purchases and acquisitions, including from low-income households and households participating in the Supplemental Nutrition Assistance Program (SNAP). https://academic.oup.com/aepp/advance-article/doi/10.1093/aepp/ppy034/5372475?searchresult=1#131940446 (March 2019).
"Diet Quality Over the Monthly Supplemental Nutrition Assistance Program Cycle,"—by Eliza D. Whiteman, Benjamin W. Chrisinger, and Amy Hillier, American Journal of Preventive Medicine. This article used FoodAPS data to better understand the "SNAP-cycle"—a pattern where both food spending and caloric intake among recipients decrease over the month following benefit receipt. The study explored differences in diet quality between SNAP and non-SNAP households and the association between the SNAP-cycle and diet quality. The results of this study provide evidence of low dietary quality throughout the SNAP-cycle, with significantly lower Healthy Eating Index scores in the final 10 days of the benefit month. This suggests less healthy purchasing occurs when resources are diminished, but overall that current SNAP levels are insufficient to consistently purchase foods according to dietary guidelines. https://doi.org/10.1016/j.amepre.2018.04.027 (June 2018).
"Re-Examining the SNAP Benefit Cycle Allowing for Heterogeneity,"—by Jeffrey H Dorfman, Christian Gregory, Zhongyuan Liu, and Ran Huo, Applied Economic Perspectives and Policy, ppy013. This article re-examines the spending patterns of recipients in the Supplemental Nutrition Assistance Program (SNAP), specifically the well-known feature that some recipients spend a disproportionate amount of their monthly benefit early in the month. Using FoodAPS data and a finite mixture model that optimally separates households into two groups, results show that a minority of SNAP recipients cause the benefit cycle by spending, on average, two-thirds of their monthly benefit within the first four days. A potential implication of these findings is that more frequent SNAP benefit disbursal or educational programs designed to encourage smoother spending over the month might be of benefit to some SNAP households (May 2018).
Review of WIC food packages: Improving balance and choice: Final report.—National Academies of Sciences, Engineering, and Medicine. Washington, DC: The National Academies Press. In response to a Congressional mandate, USDA asked the National Academies of Sciences, Engineering, and Medicine in 2014 to convene an expert committee to review and assess the nutritional status and food and nutritional needs of the WIC-eligible population and provide specific scientifically-based recommendations based on its review and grounded in the most recently available science. In addition, the committee was charged to ensure that recommendations for revising the WIC food packages are consistent with the Dietary Guidelines for Americans and address the health and cultural needs of the WIC participant population. Finally, the committee’s recommendations should operate efficiently and be effectively administered across the geographic scope of the program.
doi: https://doi.org/10.17226/23655. (2017).
"Re-evaluating associations between the Supplemental Nutrition Assistance Program participation and body mass index in the context of unmeasured confounders"—by Joseph Rigdon, Seth A. Berkowitz, Hilary K. Seligman, and Sanjay Basu, Social Science and Medicine, 192: 112-24. This article evaluated the association between participation in the Supplemental Nutrition Assistance Program (SNAP) and body mass index (BMI), using an analytical technique—near-far matching—that may help control for unmeasured confounding. Adjusted regression results showed that SNAP was associated with increased BMI. Near-far matching showed a null SNAP-BMI association (November 2017).
"Discrete Choice Model of Food Store Trips Using National Household Food Acquisition and Purchase Survey (FoodAPS)"—by Amy Hillier, Tony E. Smith, Eliza D. Whiteman, and Benjamin W. Chrisinger, International Journal of Environmental Research and Public Health, 14: 1133. This article analyzed data from the National Household Food Acquisition and Purchase Survey (FoodAPS), using a conditional logit model to determine where participants shop for food at home and how individual and household characteristics of food shoppers interact with store characteristics and distance from home in determining store choice. Overall, participants were more likely to choose larger stores, conventional supermarkets rather than super-centers and other types of stores, and stores closer to home. Interaction effects show that participants receiving Supplemental Nutrition Assistance Program (SNAP) were even more likely to choose larger stores. This study demonstrates the value of explicitly spatial discrete choice models and provides evidence of national trends consistent with previous smaller, local studies (September 2017).
"The Association Between Consumer Competency and Supplemental Nutrition Assistance Program Participation on Food Insecurity"—by Yunhee Chang, Jinhee Kim, and Swarn Chatterjee, Journal of Nutrition Education and Behavior, 2017, 49(8): 657-666. This article examines whether Supplemental Nutrition Assistance Program (SNAP) participants exhibited lower food insecurity when they also demonstrated desirable behaviors in the areas of financial management, nutrition literacy, and conscientious food shopping. Using data from FoodAPS, this study examined whether consumer competency is a factor that affects food insecurity. Consumer competency-related factors such as financial management ability, not defaulting on bill payments within the previous 6 months, and using the nutrition panel frequently when shopping were found to be negatively associated with food insecurity and very low food security after controlling for a number of other demographic, socioeconomic, and behavioral characteristics (September 2017).
"Grocery Purchase Quality Index-2016 Scores Are Moderately Correlated with Healthy Eating Index-2010 Scores in the Food Acquisition and Purchase Survey, 2012–13"—by Philip James Brewster, Patricia M. Guenther, Carrie M. Durward, and John F Hurdle, The FASEB Journal, 2017, 31(1). This study evaluates the Grocery Purchase Quality Index-2016 (GPQI-2016), a new tool developed at the University of Utah for assessing household grocery food purchase quality. The GPQI-2016 is based on the expenditure shares for the 29 food categories found in the USDA Food Plans. The authors mapped the food group classifications in the FoodAPS database to the 29 food categories used in USDA's Food Plan market baskets to estimate expenditure shares. The Healthy Eating Index-2010 (HEI-2010) was used as the reference standard; the 8-digit USDA food codes, provided in the FoodAPS database, were used to calculate the HEI-2010. Overall, the association of the GPQI-2016 and the HEI-2010 was moderate, and it varied by component. The process used to map the FoodAPS data to the USDA Food Plan categories could be refined by mapping at the food item level rather than at the food group level and may result in higher correlations in future versions of the GPQI (April 2017).
"Nonresponse and Underreporting Errors Increase over the Data Collection Week Based on Paradata from the National Household Food Acquisition and Purchase Survey"—by Mengyao Hu, Garrett W. Gremel, John A. Kirlin, and Brady T. West, The Journal of Nutrition, 2017, 147(5): 964-975. This article looks at the errors associated with food acquisition diary surveys which are important for studying food expenditures, factors affecting food acquisition decisions, and relationships between these decisions and selected measures of health. Because these errors can bias survey estimates and research findings, the authors use paradata to assess survey errors in FoodAPS. To evaluate the patterns of nonresponse over the diary period, the authors fit a multinomial logistic regression model to data from this 1-week diary survey. They also assessed factors influencing respondents’ probability of reporting food acquisition events during the diary process and studied factors influencing respondents’ perceived ease of participation in the survey. As the diary period progressed, nonresponse increased, especially for those starting the survey on Friday (where the odds of a refusal increased by 12 percent with each fielding day). Nonresponse and underreporting of food acquisition events tended to increase in FoodAPS as data collection proceeded. This analysis of paradata available in the FoodAPS revealed these errors and suggests methodological improvements for future food acquisition surveys (March 2017).
"Rethinking Household Demand for Food Diversity"—by Andrea M. Leschewski, Dave D. Weatherspoon, and Annemarie Kuhns, British Food Journal, 2017, 119(6): 1176-1188. The authors developed a group-based food diversity index, which represents diversity in household expenditures across food subgroups, by adapting the U.S. Healthy Food Diversity Index. Using FoodAPS data, the results show that the group and product code indices capture different forms of food diversity. Education, gender, age, household size, race, SNAP and food expenditures are found to significantly affect food diversity. However, the magnitude and direction of the effects vary between group and product code indices. Given these differences, it is essential that studies select a diversity index that corresponds to their objective. Results suggest that group-based indices are appropriate for informing food and nutrition policy, while product code-based indices are ideal for guiding food industry management’s decision making (2017).
"Moderation of the Relation of County-Level Cost of Living to Nutrition by the Supplemental Nutrition Assistance Program"—by Sanjay Basu, Christopher Wimer, and Hilary Seligman, American Journal of Public Health, 106 (11): 2064-70. This article uses the National Household Food Acquisition and Purchase Survey (2012–2013; n = 14,313, including 5,414 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 (HEI). The study controls for individual-, household-, and county-level covariates and accounts for unmeasured confounders influencing both area of living and food acquisition. Living in a higher-cost county—particularly one with high rents—was associated with a significantly lower volume of acquired vegetables, fruits, and whole grains; a greater volume of acquired refined grains, fats and oils, and added sugars; and an 11 percent lower HEI score. Participation in SNAP was associated with nutritional improvements among persons living in higher-cost counties (2016).
"Population Density, Poverty, and Food Retail Access in the United States: An Empirical Approach"—by Parke Wilde, Joseph Llobrera, and Michele Ver Ploeg, International Food and Agribusiness Management Review, 17 (Special Issue A). This article uses a random sample of census block groups to describe the adequacy of the local food retail environment in the continental United States. It builds upon simple empirical relationships between population density, poverty rates, vehicle access, and proximity to the nearest supermarket. In contrast with the conventional wisdom, the results show that high-poverty block groups had closer proximity to the nearest supermarket than other block groups did, on average: 85.6 percent of high-poverty block groups had a supermarket within 1 mile, while 76.8 percent of lower-poverty block groups had a supermarket within this distance. Population density is a strong predictor of proximity to the nearest supermarket. Block groups with very high population density generally had very close proximity to a nearest supermarket. In block groups lacking a nearby supermarket, rates of automobile access generally were quite high (more than 95 percent), although this still leaves almost 5 percent of the population in these areas lacking both an automobile and a nearby supermarket (2014).
"Food Store Choices of Poor Households: A Discrete Choice Analysis of the National Household Food Acquisition and Purchase Survey (FoodAPS)"—by Rebecca Taylor and Sofia B. Villas-Boas, American Journal of Agricultural Economics 98 (4): 513-32. This article uses FoodAPS data to estimate consumer food outlet choices as a function of outlet type and household attributes in a multinomial mixed logit model. More specifically, the authors allow for the composition of the local retail food environment to play a role in explaining household store choice decisions and food acquisition patterns. The study found that households are willing to pay more per week in distance traveled to shop at superstores, supermarkets, and fast food outlets than at farmers markets and smaller grocery stores, and that willingness to pay is heterogeneous across income group, Supplemental Nutrition Assistance Program participation, and other household and food environment characteristics (July 2016).
"The Effects of Benefit Timing and Income Fungibility on Food Purchasing Decisions among Supplemental Nutrition Assistance Program Households"—by Travis Smith, Joshua P. Berning, Xiaosi Yang, Gregory Colson, and Jeffrey H. Dorfman, American Journal of Agricultural Economics 98 (2): 564-80. This article uses FoodAPS data to examine the "SNAP benefit cycle" where SNAP participants have higher consumption shortly after receiving their benefits, followed by lower consumption toward the end of the benefit month. The authors find evidence of two behavioral responses, working in tandem to drive much of the cycle: (1) short-run impatience—a higher preference to consume today, and (2) fungibility of income—the degree of substitutability between a SNAP dollar and a cash dollar. However, the degree of short-run impatience and fungibility of income are found to differ significantly across poverty levels and use of grocery lists to plan food purchases (January 2016).
The National Bureau of Economic Research (NBER), with support from USDA's Economic Research Service and the Food and Nutrition Service (FNS), has organized a new two-year research initiative consisting of ten distinct projects that will leverage the FoodAPS data set to address issues related to food security, nutrition, and health in the United States. The first year of funding for the NBER grants is fiscal year 2016.
The Effect of SNAP and School Food Programs on Food Spending, Diet Quality, and Food Security: Sensitivity to Program and Income Reporting Error
Investigator and institution: Robert Moffitt, Krieger-Eisenhower Professor of Economics, Johns Hopkins University.
The Nature, Consequences and Geographic Variation of Misreporting of SNAP Participation
Investigators and institutions: Bruce D. Meyer, McCormick Foundation Professor at Chicago Harris School of Public Policy, University of Chicago, and Nikolas Mittag, Assistant Professor at Cerge, Charles University, Czech Republic.
Is There an Nth of the Month Effect? The Timing of SNAP Issuance, Food Expenditures, and Grocery Prices
Investigators and institutions: Jacob S. Goldin, Fellow, Stanford Law School, Tatiana Homonoff, Assistant Professor, Department of Policy Analysis and Management, Cornell University, and Katherine H. Meckel, EPIC Postdoctoral Scholar, University of Chicago and Assistant Professor of Economics, Texas A&M University.
Is SNAP Like Cash for Recipients and Stores? Evidence from FoodAPS
Investigators and institutions: Marianne Bitler, Professor of Economics, UC Davis, and Timothy Beatty, Associate Professor, Agricultural and Resource Economics, UC Davis.
USDA Food Assistance Programs (SNAP, the National School Lunch Program, and the School Breakfast Program) and Healthy Food Choices: Quasi-Experimental Evidence from Geographic Variation in Food Prices
Investigators and institutions: Erin Bronchetti, Associate Professor of Economics, Swarthmore College, Benjamin Hansen, Associate Professor of Economics, University of Oregon, and Garret Christensen, Center for Effective Global Action, UC Berkeley.
The Role of School Meal Programs in the Food Environment Experienced by Children
Investigators and institutions: David E. Frisvold, Assistant Professor, Department of Economics, Henry Tippie College of Business, University of Iowa, and Joseph Price, Associate Professor, Department of Economics, Brigham Young University.
School Lunch and Children’s Food Consumption In and Out of School
Investigator and institution: Amy Ellen Schwartz, Daniel Patrick Moynihan Professor of Public Affairs and Professor of Economics and Public Administration, Maxwell School, Syracuse University and NYU Institute for Education and Social Policy.
Investigating Causal Effects of SNAP and WIC on Food Insecurity Using FoodAPS
Investigators and institutions: Helen H. Jensen, Professor of Economics, Iowa State University, Brent Kreider, Professor of Economics, Iowa State University, and Oleksandr Zhylyevskyy, Associate Professor of Economics, Iowa State University.
The Economic Geography of WIC
Investigators and institutions: Di Fang, Assistant Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas, Rodolfo Nayga, Professor and Tyson Chair in Food Policy Economics, Department of Agricultural Economics and Agribusiness, University of Arkansas, and Michael Thomsen, Professor of Agricultural Economics and Agribusiness, University of Arkansas.
The Impacts of SNAP on Food Insecurity, Obesity, and Food Purchases: Who Misreports and Does it Matter?
Investigators and institutions: Charles J. Courtemanche, Associate Professor of Economics, Andrew Young School of Policy Studies, Georgia State University, Rusty Tchernis, Associate Professor of Economics, Andrew Young School of Policy Studies, Georgia State University, and Augustine Denteh, Ph.D. Student, Department of Economics, Andrew Young School of Policy Studies, Georgia State University.
The University of Kentucky Center for Poverty Research (UKCPR), in cooperation with ERS, has competitively awarded grants to qualified individuals and institutions to provide rigorous research that utilizes FoodAPS to expand our understanding of household food behaviors and the Supplemental Nutrition Assistance Program (SNAP). Research issues of interest include: benefit adequacy, diet quality, cost of a healthy diet, food security, and the role of the local food environment and other geographic factors. In addition to the FoodAPS data, geographically-linked data on the local food environment and food prices compiled as part of the FoodAPS Geography Component (FoodAPS-GC) are available for awardees. Three grants have been awarded for 2016, and 12 grants were awarded in 2014.
Household Responses to Per-Capita Reductions to Food Stamp Benefits: School’s Out and So are School Meals
Investigators and institutions: Lorenzo Almada (PI), Columbia University, and Ian McCarthy (Consultant), Emory University.
Food acquisition and health outcomes among new SNAP recipients since the Great Recession
Investigators and institutions: Jay Bhattacharya (PI), Stanford University, and Rita Hamad (Co-PI), Stanford University.
Food Acquisitions, the Thrifty Food Plan, and Benefit Adequacy for SNAP Participants
Investigators and institutions: Wen You (PI), Virginia Tech University, and George Davis (Co-PI), Virginia Tech University.
In 2014, twelve grants were awarded across two topical domains: (1) household food behaviors and the Supplemental Nutrition Assistance Program (SNAP) program, including the issues of benefit adequacy, diet quality, cost of a healthy diet, and food security, and (2) the role of the local food environment and other geographic factors on household food purchase and acquisition decisions. The final reports are available as 2016 discussion papers.
How much are we Valuing Food Access: A Hedonic Analysis
Investigators and institutions: Wen You (PI) Xinde Ji, Virginia Tech.
Nutrition, Money, and Time: An Assessment of SNAP Benefit Adequacy
Investigators and institutions: Wen You (PI), George Davis, Ruoding Shi, Virginia Tech.
Evaluation of 2012 FoodAPS
Investigators and institutions: Brady West (PI), Megyao Hu, and Wolf Gremel, University of Michigan.
Consumer Level Food Loss: An Update of Estimates for Cooking Loss and Uneaten Food at the Consumer Level
Investigators and institutions: Mary Muth (PI), Shawn Karns, Jenna Brophy, and Michaela Coglaiti, RTI.
Does the Amount of SNAP Benefits Influence Food Choices and Expenditures?
Investigators and institutions: Becca Jablonski (PI), Rebecca Cleary, and Alessandro Bonanno, Colorado State.
FoodAPS-2 Geography Study
Investigators and institutions: Parke Wilde (PI) and Mehreen Ismail, Tufts University.
Examining Consumer Food Purchasing and Acquisition Behavior, Food-Related Greenhouse Gas Emissions and Nutritional Quality
Investigators and institutions: Sean B. Cash (PI) and Rebecca Nemec Boehm, Tufts University.
FoodAPS Data Quality and Usability
Investigators and institutions: Edward Jaenicke (PI) and Benjamin Scharadin, Pennsylvania State University, and Jessica Todd, ERS (completed, June 2017).
Heterogeneity in SNAP Benefit Redemption: Causes and Characteristics
Investigators and institutions: Travis A. Smith (PI), Jeff Dorfman, Chen Zhen, Pourya Valizadeh, Zhongyuan Liu, Ran Huo, and Wenying Li, University of Georgia.
FoodAPS Geography Study
Investigators and institutions: Parke Wilde (PI), Tufts University, and Craig Gundersen, University of Illinois, Urbana-Champaign.
The Salient Features of the Local Food Retail Environment for Low-Income Americans in FoodAPS
Investigators and institutions: Parke Wilde (PI) and Abigail Steiner, Tufts University, and Michele Ver Ploeg, ERS.
Correlations between the Dietary Quality of Food Purchases and Diabetes Prevalence across US Counties
Investigator and institution: Maya Vadiveloo (PI), Elie Perraud and Haley Parker, University of Rhode Island.
The Roles of Food Retail Environment, SNAP and Private Food Assistance Programs in Determining Store and Food Choices
Investigator and institution: Linlin Fan (PI), Mississippi State, Craig Gundersen and Kathy Baylis, University of Illinois, Urbana-Champaign.
The Fill-In Trip Purchase Decision by SNAP and WIC Participants: An Analysis of Pricing, Nutrition and Store Choices
Investigator and institution: Adam Rabinowitz (PI), Grace Melo, University of Georgia, and Yizao Liu, Penn State University.
Nutritional Inequality: the Role of Prices, Preferences and Income
Investigator and institution: Joseph Altonji (PI) and Noriko Amano Patino, Yale University.
The Supplemental Nutrition Assistance Program: Current Restricted Expenditures
Investigator and institution: Andrea Leschewski (PI), South Dakota State University.
Analysis of SNAP Misreporting and Other Methodological Issues
Investigator and institution: John Kirlin (PI), Kirlin Analytic Services.
SNAP Adequacy for Households with Adolescents
Investigator and institution: James Ziliak (PI), University of Kentucky Research Foundation.
The Role of Time-Constraints in Dietary Decision-Making
Investigator and institution: Stephanie Rogus (PI), New Mexico State University.
Food Environment Ellipse
Investigator and institution: Benjamin Scharadin (PI), Washington and Lee University.
Food Retailers’ Response to SNAP
Investigator and institution: Jessie Handbury (PI), University of Pennsylvania.
Climate Change and U.S. Food Choices
Investigator and institution: Rebecca Nemec, University of Connecticut.
Exploring Household Food Outcomes Among the Elderly, the Disabled, and Residents of Suburban and Rural Communities
Investigator and institution: Scott Allard, University of Washington.
Evaluation of the Grocery Purchase Quality Index-2016 Using FoodAPS and the Healthy Eating Index-2010
Investigators and institutions: Patricia M. Guenther (PI), Philip J. Brewster, and John F. Hurdle, University of Utah, and Carrie M. Durward, Utah State University.
Restaurant Locations, Menus and Demand for Food
Investigators and institutions: Esteban Petruzzello (PI), University of Miami, and Guillermo Marshall, University of Illinois at Urbana-Champaign.
Examining Geographic, Structural, and Household Factors Associated with Food Store Shopping Behaviors
Investigators and institutions: Megan Gilster (PI), Barbara Baquero, Cristian Meier, and Adriana Maldonado, University of Iowa.
The Effect of SNAP on Food Purchases and Family Nutrition
Investigators and institutions: Jesse Shapiro (PI), Justine Hastings, Diego Focanti, Ryan Kessler, Diego Gentile, Yusheng Fei, and Jeffrey Nelson, Brown University.
Food Consumption Patterns and their Determinates: A Disaggregated Analysis
Investigators and institution: Madan Dey (PI) and Issac Sitienei, Texas State.
Salience, Food Security, and SNAP Participation
Investigator and institution:Travis Smith (PI), University of Georgia.
Kids' Meal Purchase
Investigator and institution: Seung Hee Lee-Kwan (PI), Centers for Disease Control and Prevention.
Foods Purchased at the Workplace
Investigator and institution: Stephen Onufrak (PI), Centers for Disease Control and Prevention.
Beverage Purchase Price
Investigator and institution: Sohyun Park (PI), Centers for Disease Control and Prevention.
The Effects of Food Stamp Benefits on Food Insecurity, Diet Quality, and Other Household Expenditures
Investigators and institutions: Ian McCarthy (PI), Emory University, and Lorenzo Almada, Columbia University.
SNAP, Obesity, and Unmeasured Confounders
Investigators and institution: Sanjay Basu (PI) and Joseph Rigdon, Stanford University.
The Influence of the Food Environment on Childhood Obesity
Investigators and institution: Sara Bleich (PI), Kelly Bower, Rachel Johnson Thornton, and Julia Wolfson, Johns Hopkins University.
Assessing the Impact of Food Restrictions under SNAP on Food Choice by Children and Families
Investigators and institutions: Chen Zhen (PI), University of Georgia, Shawn Karns and David Chrest, Research Triangle Institute (RTI), and Biing-Hwan Lin, ERS.
Exploring FoodAPS Data for SNAP and WIC
Investigators and institution: Sangeetha Malaiyandi (PI), Danielle Berman, Wesley Dean, and Dennis Ranalli, Food and Nutrition Service, USDA.