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PURPOSE: This study compares the efficacy of a behavioral skills mentoring program (Mentored Planning to Be Active [MBA]) to a teacher-led program (Planning to Be Active [PBA]) for increasing physical activity in Appalachian teens on health outcomes (weight loss, body mass index (BMI), and body fat). METHODS: Secondary analysis of a larger group-randomized controlled trial was conducted in 20 rural Appalachian schools. Descriptive Pearson correlations and multivariate analyses with between-subject effects were conducted. Effect sizes (ES) using Cohen's d and odds ratios (OR) with 95% confidence intervals were calculated. FINDINGS: The obese MBA group lost 77.5% more weight by T3 compared to the PBA group; T2 was (F = 8.51, P = .000) and T3 was (F = 7.62, P = .000). ES was 0.34. OR = 1.45 (95% CI: 0.558-3.792) at T2 and OR = 3.32 (95% CI: 1.103-9.978) at T3. Extremely obese in the MBA group lost 80.0% more weight compared to the PBA group; T2 was (F = 5.23, P = .025) and at T3 (F = 6.33, P = .015) ES was 0.58. OR = 4.36 (95% CI: 0.981-19.34). Extremely obese females lost more weight compared to males (F = 4.75, P = .034). BMI and body fat had similar results; youth in the MBA group had the most improvement. CONCLUSIONS: Rural Appalachian youth are disproportionately extremely obese. BMI does not capture adiposity or cardiovascular risk. BMI, BMI percentile, raw weight, fat mass, and percent body fat are more complete analyses of adiposity and cardiovascular risk.

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BACKGROUND: To better understand the unique challenges of Appalachians, community-based studies are needed to establish benchmark rates. This study compares obesity rates and obesogenic behaviors among Appalachian adolescents to other adolescent populations or clinical recommendations. METHODS: This study was conducted in 11 Appalachian schools. Body mass index, body mass index percentile, and body fat percentage were measured using a Tanita DC-430U analyzer. Physical activity was measured using Actigraph wGT3X-BT accelerometers. Sugar-sweetened beverage consumption was self-reported. Pearson's correlations, independent t tests, and multivariate analyses with tests of between-subject effects were conducted. RESULTS: Mean (n = 345) age was 15.23 (SD = 1.02) years. Appalachian adolescents were extremely obese (13.1%) by more than double that of national adolescent rates. Nearly 29% of males and over 55% of females were at increased cardiovascular risk. Only 15% were moderately active for at least 60 minutes a day, but only for 1 day per week. Mean afterschool sedentary time was 4.75 hours. Only 2.1% recorded vigorous activity for a minimum of 10 minutes at 1 day per week. Nearly all regularly consumed sugar-sweetened beverages. CONCLUSION: Obesogenic health disparities were evident in Appalachia. Rates of obesogenic factors among Appalachian adolescents exceed national rates. Appalachian adolescents were far less active, and extreme obesity is a major health concern.

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BACKGROUND: Rural Appalachian populations have poorer health and fewer positive health-related behaviors compared to other United States populations. Appalachians are the most sedentary U.S. population and teens are particularly sedentary. Obesity prevention through improving physical activity is a top priority in Rural Healthy People 2020. Obesity prevalence among Appalachian teens exceeds the national rates of 13.9% and has consistently been greater than 26%. Organized sports has not been effective at improving daily physical activity or health outcomes for Appalachian teens. The purpose of this study is to test the efficacy of a 10-week school-based intervention in promoting self-regulation of physical activity among adolescents not participating in organized sports. By using accelerometers, our study will measure both sedentary time and planned exercise during waking hours. METHODS: The design for this four-year study is a group-randomized controlled trial (G-RCT). We will recruit high schools in 3 waves, with 4 in Wave 1, 8 in Wave 2, and 8 in Wave 3, for a total of 20 schools. For each wave of schools, we will randomly assign half of the schools to each condition--intervention (peer-to-peer mentoring [MBA]) and comparison (teacher-led [PBA])--for a total of 10 schools in each of the two conditions by study's end. We will collect data at baseline (T1), 3 months post intervention (T2), and 6 months post intervention (T3). Linear Mixed Models (LMMs) and Generalized Linear Mixed Models (GLMMs) will be used to test the main hypotheses. Power for this study was based the primary analysis comparing BMI outcomes at T2 between the groups, adjusting for baseline BMI values. DISCUSSION: This study provides age-appropriate lifestyle education and skill building. Peer-to-peer mentoring by local high school students and school-based tailored support strengthens sustainable behavioral change. Focusing on unique healthy-lifestyle challenges prevalent in low-resource areas such as Appalachia such as overcoming environmental, social, and psychological barriers may improve adherence to physical activity. Serving as role models, peer mentors may improve their own lifestyle behaviors, providing a dual intervention. TRIAL REGISTRATION: NCT02329262 .

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Despite national guidelines for regular physical activity, most adolescents are not physically active. Schools serve an estimated 60 million youth and provide an educational environment to meet the current physical activity guidelines. The obesity epidemic and chronic disease comorbidities associated with physical inactivity are not likely to be reversed without a strong contribution from local schools. This article describes how a structured peer-mentoring method provides a feasible, flexible, and tailored means to meet the current guidelines for best practice in a school setting. Structured peer mentoring using trained high school mentors to support behavior change in younger peers is an innovative method to meeting the School Health Guidelines to Promote Healthy Eating and Physical Activity Through structured peer mentoring, adolescents are provided consistent social support in a caring and personalized manner. This support builds skills and competencies enhancing self-efficacy to sustain a lifetime of physical activity behavior.

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BACKGROUND: There is a scientific and practical need for high-quality effectiveness studies of physical activity interventions in "real-world" settings. OBJECTIVE: To use a community-based participatory research (CBPR) approach to develop, implement, operate, and evaluate an intervention for promoting physical activity called Neighborhoods on the Move. METHODS: Two communities with similar physical and social characteristics participated in this study. One community was involved in Neighborhoods on the Move; the other (comparison community) participated only in the assessments. Academic personnel and residents/organizations in the Neighborhoods on the Move community worked together to create a community environment that was more conducive for physical activity. Pre- and posttest data on new initiatives promoting physical activity, existing physical activity initiatives, and business policies supporting physical activity were collected simultaneously in both communities. RESULTS: The success of the CBPR approach was evidenced by several developments, including substantial resident involvement and the formation of a leadership committee, marketing campaign, and numerous community partnerships. The number of businesses with policies promoting physical activity and breadth of existing physical activity initiatives (participants, activities, hours) increased substantially more in the Neighborhoods on the Move community than in the comparison community. A total of sixty new initiatives promoting physical activity were implemented in the Neighborhoods on the Move community during the intervention. CONCLUSION: The CBPR approach is an effective strategy for inducing environmental changes that promote physical activity. Additional research is needed to assess the portability and sustainability of Neighborhoods on the Move.

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Assessment of physical activity needs to improve in order to gain a more comprehensive understanding of the relationship between characteristics of the environment and physical activity. Our study evaluated a method [Block Walk Method (BWM)] for observing physical activity along residential sidewalks and streets. The BWM was utilized in 12 U.S. Census block groups over a three-month period. Examination transportation routes (ETRs), 1,524 m in length, were constructed and examined in each block group. On 6 days, ETRs were traversed by a trained observer for 50 min. Physical activities, street names, and geographical locations (e.g., addresses) were recorded. We found encouraging results for the BWM. The level of agreement between independent observers was >98% for activity type. The number of individuals seen walking, running, or biking did not differ significantly between the days of the week or observation times. The number of individuals observed was correlated with block group characteristics (e.g., percent walking/biking to work) and weather (e.g., temperature). The BWM is an easy to use, economically viable observational approach to obtaining reliable information concerning physical activities performed on residential streets and sidewalks. Its use could help advance our understanding about the environment-physical activity relationship.

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BACKGROUND: Manipulating the physical environment may be an efficacious way to promote physical activity. This study examined the relationships between features of the neighborhood environment and walking in the neighborhood by U.S. adults. METHODS: A random sample of women (n =266) and men (n =208) aged >18 years participated. Door-to-door interviews were conducted in 2003 to collect information about demographics, walking behavior, and features of the neighborhood environment. RESULTS: The analyses conducted in 2004 revealed that women were more likely to walk for exercise (odds ratio [OR]=4.6, 95% confidence interval [CI]=1.01-20.72) or walk a dog (OR=3.3, 95% CI=1.01-11.08) in the neighborhood if neighborhood safety was average as opposed to below average (p <0.05). Women with an average number of neighborhood destinations were more likely to walk for transportation in the neighborhood (OR=5.7, 95% CI=1.63-19.73) than women with a below average number of neighborhood destinations (p <0.01). In men, none of the neighborhood features were significantly associated with walking for exercise or walking a dog. Men were less likely to walk for transportation in the neighborhood if the functional (OR=0.22, 95% CI=0.06-0.89) or aesthetic (OR=0.17, 95% CI=0.03-0.89) features of the neighborhood were average versus below average. CONCLUSIONS: Prospective studies are needed to determine if changes in neighborhood safety and awareness of neighborhood destinations promote increases in walking by women. Evaluations of the relationships between other environmental features and walking behavior in men are warranted.

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PURPOSE: To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. METHODS: High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. RESULTS: Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. CONCLUSIONS: Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.

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