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 New 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.
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 (see figure). The New Jersey Child Health Study (NJCHS) was designed to examine how specific layers of the SEM, particularly food and physical activity environments in schools and communities, affect obesity outcomes in children
Methods First-year students’ meal plan and residence information was provided by a large, public, southwestern university for the 2015-2016 academic year. A subset of students (n=619) self-reported their food security status. Logistic generalized estimating equations (GEEs) were used to determine if meal plan purchase and use were associated with food insecurity. Linear GEEs were used to examine several potential reasons for lower meal plan use. Logistic and Linear GEEs were used to determine similarities in meal plan purchase and use for a total of 599 roommate pairs (n=1186 students), and 557 floormates.
Results Students did not use all of the meals available to them; 7% of students did not use their meal plan for an entire month. After controlling for socioeconomic factors, compared to students on unlimited meal plans, students on the cheapest meal plan were more likely to report food insecurity (OR=2.2, 95% CI=1.2, 4.1). In Fall, 26% of students on unlimited meal plans reported food insecurity. Students on the 180 meals/semester meal plan who used fewer meals were more likely to report food insecurity (OR=0.9, 95% CI=0.8, 1.0); after gender stratification this was only evident for males. Students’ meal plan use was lower if the student worked a job (β=-1.3, 95% CI=-2.3, -0.3) and higher when their roommate used their meal plan frequently (β=0.09, 99% CI=0.04, 0.14). Roommates on the same meal plan (OR=1.56, 99% CI=1.28, 1.89) were more likely to use their meals together.
Discussion This study suggests that determining why students are not using their meal plan may be key to minimizing the prevalence of food insecurity on college campuses, and that strategic roommate assignments may result in students’ using their meal plan more frequently. Students’ meal plan information provides objective insights into students’ university transition.
Beginning in March 2020, the COVID-19 pandemic triggered a sudden and severe economic downturn and led to disruptions in domestic and international food systems and supply chains. Over the first few months of the pandemic, in the United States, many stores had empty shelves, bars and restaurants closed, and children could no longer go to school. The unemployment rate increased from 3.5% in February 2020 to 14.8% in April 2020, leading to economic instability for many households. As a result, household food insecurity, defined as having limited or inconsistent access to nutritious and affordable food, increased rapidly.
During the first months of 2021, vaccinations began rolling out, more individuals returned to in-person work, children to schools, and restrictions were gradually phased out. Unemployment has decreased since the April 2020 peak to 5.4% in July 2021, but remains above pre-pandemic levels. This brief describes the prevalence of household food insecurity, job disruptions, and food-related behaviors as reported by a nationally representative sample of 1,643 U.S. adults, both in the year prior to the COVID-19 pandemic (March 2019 – March 2020) and during the first four months of 2021 (January – April 2021), a period representing approximately one year since the onset of the pandemic.
Relationships between food and physical activity (PA) environments and children's related behaviors are complex.
Latent class analyses derived patterns from proximity to healthy and unhealthy food outlets, PA facilities and parks, and counts of residential dwellings and intersections. Regression analyses examined whether derived classes were related to food consumption, PA, and overweight among 404 low-income children.
Compared to children living in Low PA-Low Food environments, children in High Intersection&Parks-Moderate Density&Food, and High Density-Low Parks-High Food environments, had significantly greater sugar-sweetened beverage consumption (ps<0.01) and overweight/obesity (ps<0.001). Children in the High Density-Low Parks-High Food environments were more likely to walk to destinations (p = 0.01)
Recognizing and leveraging beneficial aspects of neighborhood patterns may be more effective at positively influencing children's eating and PA behaviors compared to isolating individual aspects of the built environment.
Purpose: To develop a valid and feasible short-form corner store audit tool (SCAT) that could be used in-store or over the phone to capture the healthfulness of corner stores.
Design: Nonexperimental.
Setting: Four New Jersey cities.
Subjects: Random selection of 229 and 96 corner stores in rounds 1 and 2, respectively.
Measures: An adapted version of the Nutrition Environment Measures Survey for Corner Stores (NEMS-CS) was used to conduct in-store audits. The 7-item SCAT was developed and used for round 2 phone audits.
Analysis: Exploratory factor analysis and item response theory were used to develop the SCAT.
Results: The SCAT was highly correlated with the adapted NEMS-CS ( r = .79). Short-form corner store audit tool scores placed stores in the same healthfulness categories as did the adapted NEMS-CS in 88% of the cases. Phone response matches indicated that store owners did not distinguish between 2% and low-fat milk and tended to round up the fruit and vegetable count to 5 if they had fewer varieties.
Conclusion: The SCAT discriminates between higher versus lower healthfulness scores of corner stores and is feasible for use as a phone audit tool.
Background: Understanding determinants of high consumption of sugar-sweetened beverages (SSBs), a highly prevalent obesogenic behavior, will help build effective customized public health interventions.
Objective: Our aim was to identify child and parent lifestyle and household demographic factors predictive of high SSB consumption frequency in children from low-income, ethnically diverse communities that may help inform public health interventions.
Design: We used a cross-sectional telephone household survey.
Participants/setting: Participants were 717 boys and 686 girls aged 3 to 18 years old from the New Jersey Childhood Obesity Study living in five low-income cities (Camden, New Brunswick, Newark, Trenton, and Vineland). The adult most knowledgeable about household food shopping completed a questionnaire over the telephone inquiring about their and their child's dietary and physical activity habits, and household-, parent-, and child-level demographics.
Main outcome measures: Child's SSB consumption frequency was measured.
Statistical analysis performed: Multivariate ordered logit models were designed to investigate a variety of variables hypothesized to affect the frequency of SSB consumption. Exploratory stratified analyses by race, sex, and age were also conducted.
Results: Eight percent of our study participants never consumed SSBs, 45% consumed SSBs at least once per day, and 23% consumed twice or more per day. SSB consumption was higher among children 12 to 18 years vs 3 to 5 years (P<0.0001), of non-Hispanic black vs non-Hispanic white race/ethnicity (P=0.010), who were moderate fast food consumers vs never consumers (P=0.003), and those whose parents were high vs low SSB consumers (P<0.0001). Living in a non-English-speaking household (P=0.030), having a parent with a college or higher education vs less than high school (P=0.003), and having breakfast 6 to 7 days/wk vs never to 2 days/wk or less were associated with lower SSB consumption (P=0.001).
Conclusions: We identified a number of household-, parent-, and child-level predictors of SSB consumption, which varied by race, sex, and age, useful for building customized interventions targeting certain behaviors in ethnically diverse, low-income children.