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Food and Nutrition Assistance Research Database

The RIDGE Program summarizes research findings of projects that were awarded 1-year grants through its partner institutions. All projects were conducted under research grants from ERS, and the views expressed are those of the authors and not necessarily those of ERS or USDA. For more information about publications or other project outputs for a specific RIDGE study, contact the investigator or research center that awarded the grant. For a customized list of RIDGE projects and summaries, search by keyword(s), project, research center, investigator, or year:

Impact of Local Food Prices on the Relationship Between Food Stamp Program Participation and Bodyweight Status of Adults in the South

Year: 2007

Research Center: Southern Rural Development Center, Mississippi State University

Investigator: Zhang, Qi, and Zhuo (Adam) Chen

Institution: Old Dominion University

Project Contact:
Qi (Harry) Zhang
School of Community and Environmental Health
Old Dominion University
3138 Health Sciences Building
Norfolk, VA 23529
Phone: 757-683-6870


The Food Stamp Program (FSP) is the principal food assistance program in the United States. It is designed to provide a nutritional safety net via benefits paid to households or individuals with low socioeconomic status (SES). Recent studies suggest that FSP participation affects individuals’ dietary intake and increases the risk of obesity. In addition, lower prices for unhealthy food are positively related to a higher prevalence of obesity. However, little is known about the interaction between food prices and FSP participation and how both of these factors jointly affect the body weight status of low-income individuals. While the obesity epidemic affects all U.S. racial/ethnic groups and social classes, populations with low socioeconomic status bear a disproportionate burden. Identification of the economic mechanisms that promote weight gain among low-income Americans will enable policymakers to design and implement effective policy instruments, which will help address the obesity epidemic in the United States.

Two national datasets, the National Longitudinal Survey of Youth 1979 (NLSY79) cohort data and the American Chamber of Commerce Researchers’ Association (ACCRA) price data, were merged using geographic identifiers to provide complete information on long-term FSP participation, body weight status, and local food prices. NLSY79 was a survey of 12,686 males and females ages 14-22 in 1979. Follow-up surveys were conducted each year between 1979 until 1994, and then biennially from 1994 to 2002. These data provided complete information on personal financial information, including income, assets, poverty status, and public assistance support sources. Self-reported height and weight were available in each wave of the surveys. The NLSY79 data also included geographic identifiers, such as respondents’ State, county, and metropolitan area of residence in each survey year. The Metropolitan Statistical Area (MSA), county, and State codes were used as linking variables to the ACCRA data. ACCRA data collected quarterly prices of consumer goods in approximately 225 metropolitan and rural areas in the United States. The data included the prices of 21 foods, typically consumed at home, and three foods typically consumed away from home.

Body mass index (BMI) and obesity (BMI greater than or equal to 30) were the outcome variables in the study. The respondent was defined as an FSP participant if any FSP benefits were received in the previous year. The eligibility of FSP participants was determined as having an annual family income of less than 130 percent of the poverty threshold for a given household size. Weighted food price indexes were calculated by using the expenditure weight provided in the ACCRA data based on the Consumer Expenditure Survey (CES). Due to the strong colinearity between healthy and unhealthy food price indexes, only unhealthy food price indexes were used in the analyses. The respondent’s age, gender, race/ethnicity, marital status, family sizes, household income, highest degree completed, urban/rural residence, and regions were all controlled. “South” was defined as the following 13 States: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, and Virginia.

The interactive term between FSP participation and unhealthy food prices was added in the regression models. The logistic regression model was used with obesity as the outcome variable. The fixed effects model took advantage of the longitudinal dataset and examined the long-term causation effect of unhealthy food prices and FSP participation on body weight status.

No significant FSP effect on BMI or obesity was observed among men. Among women, FSP participation contributed to a higher BMI (?=0.26, p=0.02). The unhealthy food prices had a negative effect on BMI (?=-0.27, p=0.001). The interaction term between unhealthy food prices and FSP participation had a negative effect on BMI (?=-0.26, p=0.01). The results indicated that higher unhealthy food prices could partially offset the positive effect of FSP participation on BMI. When the outcome was obesity, FSP participation was associated with a greater chance of being obese (odds ratio=1.37, p=0.09), whereas the unhealthy food prices were strongly related to a decreased chance of being obese (odds ratio=0.60, p=0.001). However, the interaction term was no longer significant (odds ratio=1.04, p=0.86). Therefore, the impact of higher unhealthy food prices was not significant enough to change the likelihood of being obese among FSP participants. In addition, the interaction between FSP and South was tested in the models and was not significant. Therefore, there was no significant disparity of FSP effects across regions.

The analyses of NLSY79 panel data and ACCRA price data indicated that the FSP effect on body weight status was not isolated, but was affected by other economic factors, such as food prices. The study found an additional economic mechanism that contributed to body weight gain among low-income populations. The FSP effects on BMI may have been more severe in regions with lower prices for unhealthy food, which helps explain the dramatic geographic variation in the prevalence of obesity in the United States. This study also suggested potential benefits of taxing unhealthy food. Compared with middle- or high-income groups, low-income populations were more sensitive to unhealthy food taxes. The tax may partially offset the positive impact of FSP participation on BMI. Besides the education of FSP participants, the tax may be another policy instrument that reduces the body weight disparity between FSP participants and nonparticipants.

Direct inquiries about this study to the Project Contact listed above.

Last updated: Tuesday, June 11, 2013

For more information contact: Alex Majchrowicz

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