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Mikihiro Sato, James Du and Yuhei Inoue

Background:

Although previous studies supported the health benefits of physical activity, these studies were limited to individual-level research designs. Building upon a social-ecological model, we examined the relationship between physical activity and community health—the health status of a defined group of people—while accounting for the potential endogeneity of physical activity to health.

Methods:

We obtained U.S. county-level data from the 2012 Behavioral Risk Factor Surveillance System survey and the 2014 County Health Ranking Database. We first conducted an ordinary least squares (OLS) regression analysis to examine the relationship between the rate of physical activity and community health measured by the average perceived health score for each county. We then conducted a 2-stage least squares (2SLS) regression analysis to investigate this relationship after accounting for potential endogeneity.

Results:

Results from the OLS analysis indicated that the rate of physical activity was positively associated with community health. Results from the 2SLS analysis confirmed that the physical activity rate remained positively associated with community health.

Conclusions:

In line with the social-ecological model, our findings provide the first evidence for the health benefits of county-level physical activity. Our results support extant research that has shown relationships between physical activity and individual-level, health-related outcomes.

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Katie M. Heinrich, Nancee N. Aki, Heidi Hansen-Smith, Mark Fenton and Jay Maddock

Background:

Policy changes were needed to reshape the built environment for active transportation.

Methods:

Using the social ecological model as a framework, the Healthy Hawaii Initiative worked with a contractor to develop a series of meetings, planning sessions, and workshops. Activities spanned 22 months between 2007 and 2009, and involved multiple stakeholders, including educational outreach for legislators and collaborative planning sessions with advocates.

Results:

Ultimately, with the help of the contractor to initiate the process, Complete Streets and Safe Routes to School (SRTS) legislation were introduced January 2009. Advocacy groups monitored bill progress, testified at hearings, and assisted in rewording the bills. The SRTS statute required the Department of Transportation (DOT) to administer the federal SRTS funds and the complete streets law tasked the state and county DOTs to adopt complete streets policies and review existing highway design standards and guidelines. Both bills were signed into law June 2009.

Conclusions:

Focusing efforts at multiple levels of the social ecological model involving champions and key stakeholders led to the successful passage of legislation supporting active transportation. Tracking policy implementation and evaluation over time will help determine actual impact on active transportation behaviors across Hawaii.

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Jeffrey P. Carpenter and Stephen Harvey

physical educators perceive in their uses of social media for professional purposes? and (b) What challenges do physical educators perceive in their uses of social media for professional purposes? Theoretical Framework A social ecological model was employed to frame the benefits and challenges educators

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Jeanette M. Garcia, Sean Healy and David Rice

Background:

The aim of this study was to use a social-ecological approach to examine the influence of individual, social, and environmental factors on moderate-to-vigorous physical activity (MVPA) and screen-time in a sample of 9-year-old children in Ireland.

Methods:

The sample was 1509 boys and girls from the Growing Up in Ireland (GUI) national study. MVPA, screen time, and individual, social, and environmental variables were assessed via questionnaires completed by children, their parents, and their teachers. Multiple regression was used to identify factors that correlated with children’s MVPA and screen-time levels.

Results:

For boys, factors such as activity with friends (P < .0001) and popularity (P < .01) were associated with MVPA, while factors such as BMI (P < .01) and MVPA (P < .01) were associated with screen time. Similarly for girls, factors such as activity with friends (P < .0001) and sociability were associated with MVPA, however factors such as BMI (P < .05), and access to play space (P < .05) were more closely associated with screen time.

Conclusion:

Social factors were more closely associated with MVPA, while individual factors were significantly correlated with screen time for both boys and girls. Correlates differed for boys and girls, suggesting that interventions should consider both the target population as well as the activity behavior.

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Basia Belza, Christina E. Miyawaki, Peg Allen, Diane K. King, David X. Marquez, Dina L. Jones, Sarah Janicek, Dori Rosenberg and David R. Brown

perspectives, to encourage walking and why mid-life and older adults chose to walk in those locations. As a study-guiding framework, we used the social-ecological model ( McLeroy, Bibeau, Steckler, & Glanz, 1988 ). The social-ecological model considers the dynamic interplay between personal and environmental

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Stephanie L. Silveira, Jessica F. Baird and Robert W. Motl

SCT include person level through social and environmental factors and can be aligned and studied through ecological frameworks ( Winett, Williams, & Davy, 2009 ). Social ecological models (SEMs), in particular, provide a guide for conceptualizing the unique influences of macro

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Susan B. Sisson, Stephanie T. Broyles, Birgitta L. Baker and Peter T. Katzmarzyk

Background:

The purposes were 1) to determine if different leisure-time sedentary behaviors (LTSB), such as TV/video/video game viewing/playing (TV), reading for pleasure (reading), and nonschool computer usage, were associated with childhood overweight status, and 2) to assess the social-ecological correlates of LTSB.

Methods:

The analytic sample was 33,117 (16,952 boys and 16,165 girls) participants from the 2003 National Survey of Children’s Health. The cut-point for excessive TV and nonschool computer usage was ≥ 2 hr/day. High quantities of daily reading for pleasure were classified as ≥ 31 min/day. Weighted descriptive characteristics were calculated on the sample (means ± SE or frequency). Logistic regression models were used to determine if the LTSB were associated with overweight status and to examine social-ecological correlates.

Results:

Over 35% of the sample was overweight. Odds of being overweight were higher in the 2 to 3 hr/day (OR: 1.48, 95% CI: 1.24, 1.76) and ≥ 4 hr/day (OR: 1.52, 95% CI: 1.22, 1.91) daily TV groups compared with none. Reading and nonschool computer usage was not associated with being overweight.

Conclusions:

TV was associated with overweight classification; however, nonschool computer usage and reading were not. Several individual, family, and community correlates were associated with high volumes of daily TV viewing.

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Chevelle M.A. Davis, Tetine L. Sentell, Juliana Fernandes de Souza Barbosa, Alban Ylli, Carmen-Lucia Curcio and Catherine M. Pirkle

social ecological model (SEM; McLeroy, Bibeau, Steckler, & Glanz, 1988 ), our objective was to examine factors at the individual level as well as at the interpersonal, organizational, and community levels to see how these are associated with older adults meeting the WHO’s PA guidelines of 150 min of

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Nicolas Hobson, Sherry L. Dupuis, Lora M. Giangregorio and Laura E. Middleton

framework of the social-ecological model (SEM). The SEM posits that behavior is affected by the complex and dynamic interaction of factors on multiple levels ( McLeroy et al., 1988 ). Framing issues within the SEM can help people to understand how macrolevel systems (e.g., the social and physical

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Andrea R. Taliaferro and Lindsay Hammond

Individuals with intellectual disabilities (ID) tend to have low rates of participation in voluntary or prescribed physical activity. The purpose of this study, therefore, was to identify the barriers, facilitators, and needs influencing physical activity participation of adults with ID within the framework of a social ecological model. A qualitative approach consisted of data collected from surveys and guided focus groups. Participants included adults with ID (n = 6) and their primary caregiver (n = 6). Barriers were categorized under three themes: organizational barriers, individual constraints, and external influences. Examples of subthemes included information dissemination, reliance on others, and caregiver considerations. Facilitators included primary caregivers as champions and camaraderie. Needs centered on family program involvement, improved programmatic structure, and programmatic support. Results indicate the need for community programs to examine barriers and facilitators applicable to their unique setting and population across all levels of a social ecological model.