A collection of scholarly work created by the ASU Food Policy and Environment Research Group under the leadership of Professor Punam Ohri-Vachaspati. The group examines policies, programs, and environments that influence food consumption and physical activity behaviors and health outcomes in disadvantaged populations. We aim to improve the health of children and families through comprehensive policy and environmental approaches. 
 

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Description

Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined

Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined the availability of different types of food stores by census tract characteristics over time (2009–2017). Outlets were classified as supermarkets, small grocery stores, convenience stores, and pharmacies using multiple sources of data and a rigorous protocol. Census tracts were categorized by median household income and race/ethnicity of the population each year. Significant declines were observed in convenience store prevalence in lower- and medium-income and majority black tracts (p for trend: 0.004, 0.031, and 0.006 respectively), while a slight increase was observed in the prevalence of supermarkets in medium-income tracts (p for trend: 0.059). The decline in prevalence of convenience stores in lower-income and minority neighborhoods is likely attributable to declining incomes in these already poor communities. Compared to non-Hispanic neighborhoods, Hispanic communities had a higher prevalence of small groceries and convenience stores. This higher prevalence of smaller stores, coupled with shopping practices of Hispanic consumers, suggests that efforts to upgrade smaller stores in Hispanic communities may be more sustainable.

ContributorsOhri-Vachaspati, Punam (Author) / DeWeese, Robin (Author) / Acciai, Francesco (Author) / DeLia, Derek Michael, 1969- (Author) / Tulloch, David (Author) / Tong, Daoqin (Author) / Lorts, Cori (Author) / Yedidia, Michael J., 1946- (Author)
Created2019-07-03
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Description

Background

The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the

Background

The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life.

Methods

The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks.

Discussion

Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.

ContributorsBruening, Meg (Author) / Ohri-Vachaspati, Punam (Author) / Brewis, Alexandra (Author) / Laska, Melissa (Author) / Todd, Michael (Author) / Hruschka, Daniel (Author) / Schaefer, David (Author) / Whisner, Corrie M (Author) / Dunton, Genevieve (Author)
Created2016-08-30
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Description

In response to lack of access to healthy foods, many low-income communities are instituting local healthy corner store programs. Some stores also participate in the United States Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and the Supplemental Nutrition Assistance Program (SNAP). This study used

In response to lack of access to healthy foods, many low-income communities are instituting local healthy corner store programs. Some stores also participate in the United States Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and the Supplemental Nutrition Assistance Program (SNAP). This study used two assessment tools to compare the healthfulness of offerings at stores participating in local healthy store programs (upgraded stores), WIC, and/or SNAP to that of similar non-participating stores.

Based on store audits conducted in 315 New Jersey corner stores in 2014, we calculated healthy food availability scores using subsections of the Nutrition Environment Measures Survey for Corner Stores (NEMS-CS-Availability) and a short-form corner store audit tool (SCAT). We used multivariable regression to examine associations between program participation and scores on both instruments.

Adjusting for store and block group characteristics, stores participating in a local healthy store program had significantly higher SCAT scores than did non-participating stores (upgraded: M = 3.18, 95% CI 2.65–3.71; non-upgraded: M = 2.52, 95% CI 2.32–2.73); scores on the NEMS-CS-Availability did not differ (upgraded: M = 12.8, 95% CI 11.6–14.1; non-upgraded: M = 12.5, 95% CI 12.0–13.0). WIC-participating stores had significantly higher scores compared to non-participating stores on both tools. Stores participating in SNAP only (and not in WIC) scored significantly lower on both instruments compared to non-SNAP stores.

WIC-participating and non-SNAP corner stores had higher healthfulness scores on both assessment tools. Upgraded stores had higher healthfulness scores compared to non-upgraded stores on the SCAT.

ContributorsDeWeese, Robin (Author) / Todd, Michael (Author) / Karpyn, Allison (Author) / Yedidia, Michael J., 1946- (Author) / Kennedy, Michelle (Author) / Bruening, Meg (Author) / Wharton, Christopher M. (Author) / Ohri-Vachaspati, Punam (Author)
Created2016-06-29
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Description

Introduction

The US Preventive Services Task Force recommends that all patients be screened for obesity and, if needed, be provided weight-loss advice. However, the prevalence of such advice is low and varies by patient demographics. This study aimed to describe the determinants of receiving weight-loss advice among a sample with

Introduction

The US Preventive Services Task Force recommends that all patients be screened for obesity and, if needed, be provided weight-loss advice. However, the prevalence of such advice is low and varies by patient demographics. This study aimed to describe the determinants of receiving weight-loss advice among a sample with a high proportion of low-income, racial/ethnic minority individuals.

Methods

Data were collected from a telephone survey of 1,708 households in 2009 and 2010 in 5 cities in New Jersey. Analyses were limited to 1,109 overweight or obese adults. Multivariate logistic regression determined the association of participants’ characteristics with receiving weight-loss advice from their health care provider. Two models were used to determine differences by income and insurance status.

Results

Of all overweight or obese respondents, 35% reported receiving advice to lose weight. Receiving advice was significantly associated with income in multivariate analysis. Compared with those with an income at or below 100% of the federal poverty level (FPL), those within 200% to 399% of the FPL had 1.60 higher odds of receiving advice (P = .02), and those with an income of 400% or more of the FPL had 1.73 higher odds of receiving advice (P = .03). The strength of the association did not change after adjusting for health insurance.

Conclusion

Income is a significant predictor of whether or not overweight or obese adults receive weight-loss advice after adjustment for demographic variables, health status, and insurance status. Further work is needed to examine why disparities exist in who receives weight-loss advice. Health care providers should provide weight-loss advice to all patients, regardless of income.

ContributorsLorts, Cori (Author) / Ohri-Vachaspati, Punam (Author)
Created2016-10-06
Description

In March 2020, the COVID-19 pandemic triggered a sudden and severe economic downturn. Between February and May 2020, the number of unemployed individuals rose by more than 14 million, resulting in an unprecedented increase in the unemployment rate, which went from 3.8% in February to 14.4% in April. Even though unemployment

In March 2020, the COVID-19 pandemic triggered a sudden and severe economic downturn. Between February and May 2020, the number of unemployed individuals rose by more than 14 million, resulting in an unprecedented increase in the unemployment rate, which went from 3.8% in February to 14.4% in April. Even though unemployment has declined in recent months, with some individuals returning to work, the rate is still much higher than it was one year ago (7.9% in September 2020 vs. 3.5% in September 2019). Further, as of September 2020, there are 19.4 million persons unable to work due to the pandemic, as well as 6.3 million persons working only part time even though they would prefer to work more.

Created2020-11
Food Assistance Program Participation among US Household during COVID-19 Pandemic
Description

In the face of the coronavirus (COVID-19) pandemic, food assistance programs adapted quickly and in unprecedented ways to meet the challenges of high unemployment, disruptions in the food supply, and school closures. Supported by US Department of Agriculture’s COVID-19 program-specific waivers, some programs relaxed their eligibility criteria, while others improvised

In the face of the coronavirus (COVID-19) pandemic, food assistance programs adapted quickly and in unprecedented ways to meet the challenges of high unemployment, disruptions in the food supply, and school closures. Supported by US Department of Agriculture’s COVID-19 program-specific waivers, some programs relaxed their eligibility criteria, while others improvised on delivery modalities or temporarily increased benefits.1 To examine food assistance program participation and participant experiences during the first few months of the pandemic, we collected online survey data in July 2020 from a sample of over 1,500 U.S. households, representative of the US population. This brief summarizes participation in key food assistance programs, namely, the Supplemental Nutrition Assistance Program (SNAP), the Special Supplemental Program for Women Infants and Children (WIC), School Food Programs, as well as emergency food assistance provided through Food Pantries

Created2020-11
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Description

Programs such as the Healthy Corner Store Initiative have been widely adopted in recent years to increase the availability of healthy foods in small retail food stores. Valid and reliable measures are necessary to evaluate the effectiveness of these programs. The validated instruments currently available for assessments require in-person evaluations,

Programs such as the Healthy Corner Store Initiative have been widely adopted in recent years to increase the availability of healthy foods in small retail food stores. Valid and reliable measures are necessary to evaluate the effectiveness of these programs. The validated instruments currently available for assessments require in-person evaluations, with surveys taking up to 30 minutes per store to complete. This instrument was developed by researchers at Arizona State University to simplify the process of evaluating the effectiveness of healthy store interventions, and to enable community partners and practitioners to conduct their own evaluations of food access. The SCAT was validated against an adapted version of the Nutrition Environment Measures Survey for Corner Stores, and tested for feasibility of use over the telephone. The SCAT was found to discriminate between corner stores in the top 20% of healthfulness scores from those in the lower 80% with 89% accuracy.

In 2015 a panel of experts was convened by Healthy Eating Research, a program of the Robert Wood Johnson Foundation, to establish a set of minimum guidelines small retail food stores could reach to be classified as meeting basic or preferred stocking levels. Work is currently in progress to assess how the SCAT scores correlate with basic and preferred levels. 

ContributorsDeWeese, Robin (Creator) / Ohri-Vachaspati, Punam (Creator) / Todd, Michael (Creator) / Karpyn, Allison (Creator) / Yedidia, Michael J., 1946- (Creator) / Kennedy, Michelle (Creator) / Bruening, Meg (Creator) / Wharton, Christopher M. (Creator)
Created2015
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Description

This brief summarizes the different types of food stores open in New Brunswick, New Jersey and in a one mile radius around the city during 2008 to 2014.

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Description

With more than 19 million confirmed COVID-19 cases across the United States1 and over 500,000 in Arizona as of December 2020, the ongoing pandemic has had devastating impacts on local, national, and global economies. Prior to the pandemic (February 2020), based on U.S. Bureau of Labor Statistics data, the unemployment rate

With more than 19 million confirmed COVID-19 cases across the United States1 and over 500,000 in Arizona as of December 2020, the ongoing pandemic has had devastating impacts on local, national, and global economies. Prior to the pandemic (February 2020), based on U.S. Bureau of Labor Statistics data, the unemployment rate in Arizona was 6.5%, compared to 4.9% at the national level.3 Since the beginning of the COVID-19 pandemic (March 2020), the United States has experienced striking increases in the unemployment rate, reaching 13.2% in April. Similarly, in Arizona, the unemployment rate jumped to over 13.5% in April. The unemployment rates have since declined both nationally and in Arizona but remain higher compared to February 2020. In November 2020 (the most recent data available), the national unemployment rate was 6.7%, while in Arizona the rate was 7.8%—the 10th highest unemployment rate among all U.S. states.

Created2020-12