eng Science and Education Publishing Journal of Physical Activity Research 2017-05-22 2 1 32 38 10.12691/jpar-2-1-6 JPAR2017216 article Jan Perkins 1 Michael Jack Wierenga wiere1mj@cmich.edu 2 William A. Saltarelli 3 Miranda Moncada-Sullivan 4 Doctoral Program in Physical Therapy, Herbert H. and Grace A. Dow College of Health Professions, Central Michigan University, Mt Pleasant, MI 48859 Exercise Physiology, Herbert H. and Grace A. Dow College of Health Professions, Central Michigan University, Mt Pleasant, MI 48859 School of Health Sciences, Central Michigan University, Mount Pleasant, MI 48859 Hayes Green Beach Memorial Hospital, 321 East Harris Street, Charlotte, MI 48813 BACKGROUND: Childhood metabolic syndrome increases health risks in later life. Physical activity may moderate risk factors and incidence. Pedometers are a valid means of tracking physical activity in children. This study was developed to examine the impact of physical activity, as measured by pedometer counts, on risk factors in middle school children in a rural Midwestern community. METHODS: The Cardiovascular Health Intervention Program (CHIP) measures cardiovascular disease risk factors in rural Midwestern middle school students, and includes blood pressure, waist circumference, fasting blood glucose, high density lipoprotein, and triglyceride levels, allowing determination of metabolic syndrome incidence. In one community activity of fifth and sixth grade students pedometer monitoring was added for two separate weeks (December and April). Analysis was done with one way ANOVA and T-Tests. RESULTS: Fifty-four students participated in CHIP, 36 in the pedometer project. Winter and Spring step counts were different (p=0.00). Boys had a trend for higher step counts than girls, but sample size prevented this reaching significance (p=0.16). Two (3.7%) students met criteria for metabolic syndrome. Lower step counts were associated with HDL levels meeting risk factor criteria (p=0.028). CONCLUSIONS: Rates of metabolic syndrome and component risk were similar to those seen nationally. Seasonal weather variation may explain differences between December and April step counts. Additional studies of rural students are suggested, allowing pooling of populations to attain greater sample sizes. http://pubs.sciepub.com/jpar/2/1/6/jpar-2-1-6.pdf adolescents physical activity assessment metabolic syndrome risk factors pedometers