Effects of Physical Activity on Disease Risk Factors
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About
Obesity is associated with increased risk of heart disease and diabetes (Kim et al., 2010). Appalachian children in Athens County, Ohio, experience higher rates of obesity compared to the national average (20.9% vs. 15.4%), which increases their risk of obesity-related diseases (Montgomery-Reagan, Bianco, Heh, Rettos, & Huston, 2009). Although physical activity (PA) is known to improve fitness and adiposity (Gutin & Owens, 2011; Yin et al., 2009), very little is known about the effects of PA on the progression of chronic disease risk factors (biomarkers) for obesity-related diseases in children, such as inflammatory markers, lipids, and glucose/insulin. This lack of knowledge is due to a limited understanding of the number of calories burned during children's free-play PA. This study will assess the impact of a PA program (ACT) of known energy cost on obesity-related disease markers in 2nd-4th grade children compared to a sedentary control group (SED). The study will recruit children from an after-school program in Athens County elementary schools. Baseline and posttest data will include measures of height, weight, body composition, blood pressure, and physical activity levels. Following baseline measures, children will be randomized into either the ACT or SED group for 8 weeks. The ACT group will play recess-type games previously determined to expend ≥100 calories in 30 minutes. The SED group children will play sedentary-type activities during the same time period. It is hypothesized that the ACT group children will demonstrate significant improvements in PA after 8 weeks compared to the SED group children and that these improvements will be related to positive changes in body weight and body composition.
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Inclusion criteria
- Attends participating after school program
Exclusion criteria
- cardiorespiratory, metabolic, and neurological disorders and physical impairments that would prevent them from being physically active, and were not taking any medications that would affect metabolism
Trial design
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Interventional model
Masking
13 participants in 2 patient groups, including a placebo group
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Data sourced from clinicaltrials.gov
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