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.

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.

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. 

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