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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.

ContributorsOhri-Vachaspati, Punam (Contributor) / Yedidia, Michael J., 1946- (Contributor) / New Jersey Child Health Study (Contributor, Contributor) / Stevens, Clinton (Contributor) / Rutgers Center for State Health Policy (Contributor) / ASU College of Health Solutions (Contributor)
Created2019-10
Description

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

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

ContributorsOhri-Vachaspati, Punam (Contributor) / Eliason, Jessica (Contributor) / Yedidia, Michael J., 1946- (Contributor) / New Jersey Child Health Study (Contributor) / Rutgers Center for State Health Policy (Contributor) / ASU College of Health Solutions (Contributor)
Created2019-10
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Description

According to the Centers for Disease Control and Prevention (CDC), more people die in the U.S. from heat than from all other natural disasters combined. According to the Environmental Protection Agency (EPA), more than 1,300 deaths per year in the United States are due to extreme heat. Arizona, California and

According to the Centers for Disease Control and Prevention (CDC), more people die in the U.S. from heat than from all other natural disasters combined. According to the Environmental Protection Agency (EPA), more than 1,300 deaths per year in the United States are due to extreme heat. Arizona, California and Texas are the three states with the highest burden, accounting for 43% of all heat-related deaths according to the CDC.

Although only 5% of housing in Maricopa County, Arizona, is mobile homes, approximately 30% of indoor heat-related deaths occur in these homes. Thus, the residents of mobile homes in Maricopa County are disproportionately affected by heat. Mobile home residents are extremely exposed to heat due to the high density of mobile home parks, poor construction of dwellings, lack of vegetation, socio-demographic features and not being eligible to get utility and financial assistance.

We researched numerous solutions across different domains that could help build the heat resilience of mobile home residents. As a result we found 50 different solutions for diverse stakeholders, budgets and available resources. The goal of this toolbox is to present these solutions and to explain how to apply them in order to get the most optimal result and build About this Solutions Guide People who live in mobile homes are 6 to 8 times more likely to die of heat-associated deaths. heat resilience for mobile home residents. These solutions were designed as a coordinated set of actions for everyone — individual households, mobile home residents, mobile home park owners, cities and counties, private businesses and nonprofits serving mobile home parks, and other stakeholders — to be able to contribute to heat mitigation for mobile home residents.

When we invest in a collective, coordinated suite of solutions that are designed specifically to address the heat vulnerability of mobile homes residents, we can realize a resilience dividend in maintaining affordable, feasible, liveable housing for the 20 million Americans who choose mobile homes and manufactured housing as their place to live and thrive.

ContributorsVarfalameyeva, Katsiaryna (Author) / Solís, Patricia (Author) / Phillips, Lora A. (Author) / Charley, Elisha (Author) / Hondula, David M. (Author) / Kear, Mark (Author)
Created2021
Food insecurity and food assistance program participation in the U.S.: One year into the COVID-19 pandemic
Description

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

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.

Created2021-08