Programs and Communities
The collection collates collections by schools, centers, programs, and research groups.
Filtering by
- Creators: Yedidia, Michael J., 1946-
- Creators: Lorts, Cori
- Peer-reviewed: Peer-reviewed
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.
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.
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.
Objective: The Social Ecological Model (SEM) has been used to describe the aetiology of childhood obesity and to develop a framework for prevention. The current paper applies the SEM to data collected at multiple levels, representing different layers of the SEM, and examines the unique and relative contribution of each layer to children's weight status.
Design: Cross-sectional survey of randomly selected households with children living in low-income diverse communities.
Setting: A telephone survey conducted in 2009-2010 collected information on parental perceptions of their neighbourhoods, and household, parent and child demographic characteristics. Parents provided measured height and weight data for their children. Geocoded data were used to calculate proximity of a child's residence to food and physical activity outlets.
Subjects: Analysis based on 560 children whose parents participated in the survey and provided measured heights and weights.
Results: Multiple logistic regression models were estimated to determine the joint contribution of elements within each layer of the SEM as well as the relative contribution of each layer. Layers of the SEM representing parental perceptions of their neighbourhoods, parent demographics and neighbourhood characteristics made the strongest contributions to predicting whether a child was overweight or obese. Layers of the SEM representing food and physical activity environments made smaller, but still significant, contributions to predicting children's weight status.
Conclusions: The approach used herein supports using the SEM for predicting child weight status and uncovers some of the most promising domains and strategies for childhood obesity prevention that can be used for designing interventions.
The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on
who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.
The main components of the study were:
• A household telephone survey of 1700 families with 3–18 year old children,
• De-identified heights and weights measured at public schools,
• Assessment of the food and physical activity environments using objective data.
This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.
The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on
who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.
The main components of the study were:
• A household telephone survey of 1700 families with 3–18 year old children,
• De-identified heights and weights measured at public schools,
• Assessment of the food and physical activity environments using objective data.
This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.
The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on
who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.
The main components of the study were:
• A household telephone survey of 1700 families with 3–18 year old children,
• De-identified heights and weights measured at public schools,
• Assessment of the food and physical activity environments using objective data.
This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.
The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on
who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.
The main components of the study were:
• A household telephone survey of 1700 families with 3–18 year old children,
• De-identified heights and weights measured at public schools,
• Assessment of the food and physical activity environments using objective data.
This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.
Many factors influence children’s health behaviors and health outcomes. The Social Ecological Model (SEM) groups these factors into interactive layers, creating a framework for understanding their influence and for designing interventions to achieve positive change. The layers of influence in the SEM include individual, interpersonal, organizational, community, and policy factors.
