Objectives: Conflicting findings on associations between food and physical activity (PA) environments and children's weight status demand attention in order to inform effective interventions. We assess relationships between the food and PA environments in inner-city neighborhoods and children's weight status and address sources of conflicting results of prior research.

Methods: Weight status of children ages 3-18 was assessed using parent-measured heights and weights. Data were collected from 702 children living in four low-income cities in New Jersey between 2009 and 2010. Proximity of a child's residence to a variety of food and PA outlets was measured in multiple ways using geo-coded data. Multivariate analyses assessed the association between measures of proximity and weight status.

Results: Significant associations were observed between children's weight status and proximity to convenience stores in the 1/4 mile radius (OR = 1.9) and with presence of a large park in the 1/2 mile radius (OR = 0.41). No associations were observed for other types of food and PA outlets.

Conclusions: Specific aspects of the food and PA environments are predictors of overweight and obese status among children, but the relationships and their detection are dependent upon aspects of the geospatial landscape of each community.

Background

Few children accumulate the recommended ≥60 minutes of physical activity each day. Active travel to and from school (ATS) is a potential source of increased activity for children, accounting for 22% of total trips and time spent traveling by school-aged children.

Purpose

This study identifies the association of parents’ perceptions of the neighborhood, geospatial variables, and demographic characteristics with ATS among students in four low-income, densely populated urban communities with predominantly minority populations.

Methods

Data were collected in 2009–2010 from households with school-attending children in four low-income New Jersey cities. Multivariate logistic regression analyses (n=765) identified predictors of ATS. Analyses were conducted in 2012.

Results

In all, 54% of students actively commuted to school. Students whose parents perceived the neighborhood as very unpleasant for activity were less likely (OR=0.39) to actively commute, as were students living farther from school, with a 6% reduction in ATS for every 0.10 mile increase in distance to school. Perceptions of crime, traffic, and sidewalk conditions were not predictors of ATS.

Conclusions

Parents’ perceptions of the pleasantness of the neighborhood, independent of the effects of distance from school, may outweigh concerns about crime, traffic, or conditions of sidewalks in predicting active commuting to school in the low-income urban communities studied. Efforts such as cleaning up graffiti, taking care of abandoned buildings, and providing shade trees to improve neighborhood environments are likely to increase ATS, as are efforts that encourage locating schools closer to the populations they serve.

Background

The United States Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) is the country’s largest nutrition assistance program for low-income populations. Although SNAP has been shown to reduce food insecurity, research findings on the diet quality of program participants are inconsistent.

Objective

This study evaluated whether the community food environment is a potential moderator of the association between SNAP participation and eating behaviors.

Design

This cross-sectional study used participant data from a telephone survey of 2,211 households in four cities in New Jersey. Data were collected from two cross-sectional panels from 2009 to 2010 and 2014. Food outlet data were purchased from commercial sources and classified as supermarkets, small grocery stores, convenience stores, or limited service restaurants.

Participants/setting

Analysis is limited to 983 respondents (588 SNAP participants) with household incomes below 130% of the federal poverty level.

Main outcome measures

Eating behaviors were assessed as frequency of consumption of fruit, vegetables, salad, and sugar-sweetened beverages.

Statistical analyses performed

Interaction and stratified analyses using gamma regression determined the differences in the association between SNAP participation and eating behaviors by the presence or absence of food outlets adjusted for covariates.

Results

SNAP participation was associated with a higher frequency of consuming sugar-sweetened beverages (P<0.05) when respondents lived within ¼ to ½ mile of a small grocery store, supermarket, and limited service restaurant. SNAP participants who did not live close to a convenience store reported a lower frequency of sugar-sweetened beverage consumption (P=0.01), and those living more than ½ mile away from a supermarket reported a lower frequency of fruit consumption (P=0.03).

Conclusions

The findings from this study suggest that the community food environment may play a role in moderating the association between SNAP participation and eating behaviors. Although SNAP participation is associated with some unhealthy behaviors, this association may only hold true when respondents live in certain food environments.

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.

The maps in this chartbook describe the food environment in Vineland in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

• Food environment maps were created using geo-coded commercially available data of food outlets (Info USA, 2008 and Trade Dimensions, 2008) in Vineland and in a 1 mile buffer area around Vineland.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The maps in this chartbook describe the food environment in Trenton in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

•Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Trenton and in a 1 mile buffer area around Trenton.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The maps in this chartbook describe the food environment in ewark in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Newark and in a 1 mile buffer area around Newark.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The maps in this chartbook describe the food environment in ew Brunswick in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

• Food environment maps were created using geo-coded commercially available data of food outlets (Info USA, 2008 and Trade Dimensions, 2008) in New Brunswick and in a 1 mile buffer area around New Brunswick.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The maps in this chartbook describe the food environment in Camden in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Camden and in a 1 mile buffer area around Camden.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likeliliood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy food s in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five ew Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by RWJF'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.

Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy Kids and the five communities to address these information needs. The main components of the study include:

• A household survey of 1700 families with 3 -18 year old children

• De-identified heights and weights data from public school districts

• Assessment of the food and physical activity environments using objective data

Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.