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Mary O. Hearst, John R. Sirard, Leslie Lytle, Donald R. Dengel and David Berrigan

Background:

The association of physical activity (PA), measured 3 ways, and biomarkers were compared in a sample of adolescents.

Methods:

PA data were collected on 2 cohorts of adolescents (N = 700) in the Twin Cities, Minnesota, 2007–2008. PA was measured using 2 survey questions [Modified Activity Questionnaire (MAQ)], the 3-Day Physical Activity Recall (3DPAR), and accelerometers. Biomarkers included systolic (SBP) and diastolic blood pressure (DBP), lipids, percent body fat (%BF), and body mass index (BMI) percentile. Bivariate relationships among PA measures and biomarkers were examined followed by generalized estimating equations for multivariate analysis.

Results:

The 3 measures were significantly correlated with each other (r = .22–.36, P < .001). Controlling for study, puberty, age, and gender, all 3 PA measures were associated with %BF (MAQ = −1.93, P < .001; 3DPAR = −1.64, P < .001; accelerometer = −1.06, P = .001). The MAQ and accelerometers were negatively associated with BMI percentile. None of the 3 PA measures were significantly associated with SBP or lipids. The percentage of adolescents meeting the national PA recommendations varied by instrument.

Conclusions:

All 3 instruments demonstrated consistent findings when estimating associations with %BF, but were different for prevalence estimates. Researchers must carefully consider the intended use of PA data when choosing a measurement instrument.

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Anne Samuelson, Leslie Lytle, Keryn Pasch, Kian Farbakhsh, Stacey Moe and John Ronald Sirard

Background:

This article describes policies, practices, and facilities that form the physical activity climate in Minneapolis/St. Paul, Minnesota metro area middle and high schools and examines how the physical activity climate varies by school characteristics, including public/private, school location and grade level.

Methods:

Surveys examining school physical activity practices, policies and environment were administered to principals and physical education department heads from 115 middle and high schools participating in the Transdisciplinary Research on Energetics and Cancer-Identifying Determinants of Eating and Activity (TREC-IDEA) study.

Results:

While some supportive practices were highly prevalent in the schools studied (such as prohibiting substitution of other classes for physical education); other practices were less common (such as providing opportunity for intramural (noncompetitive) sports). Public schools vs. private schools and schools with a larger school enrollment were more likely to have a school climate supportive of physical activity.

Conclusions:

Although schools reported elements of positive physical activity climates, discrepancies exist by school characteristics. Of note, public schools were more than twice as likely as private schools to have supportive physical activity environments. Establishing more consistent physical activity expectations and funding at the state and national level is necessary to increase regular school physical activity.

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John R. Sirard, Karin A. Pfeiffer, Marsha Dowda and Russell R. Pate

The purpose of this study was to identify racial differences in physical activity (PA), fitness, and BMI in female 8th-grade sports participants and nonparticipants. Girls from 31 South Carolina middle schools (N = 1,903, 48% White; mean age = 13.6 ± 0.63) reported PA and previous year sports-team participation, completed a submaximal fitness test, and had height and weight measured. Sports team participation was positively associated with PA and negatively associated with television viewing and BMI, in a dose-response manner. Compared with Whites, African-Americans reported less PA and more television viewing, and had greater BMI scores. Whereas PA intervention programs that incorporate a sports-team component could benefit all girls, African-American girls could be specifically targeted because of their lower physical activity.

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Sofiya Alhassan, John R. Sirard, Tirzah R. Spencer, Ann Varady and Thomas N. Robinson

Background:

The purpose of this study was to develop a data-driven approach for analyzing incomplete accelerometer data from field-base studies.

Methods:

Multiple days of accelerometer data from the Stanford Girls health Enrichment Multi-site Studies (N = 294 African American girls) were summed across each minute of each day to produce a composite weekday and weekend day. Composite method estimates of physical activity were compared with those derived from methods typically described in the literature (comparison methods).

Results:

The composite method retained 99.7% and 100% of participants in weekday and weekend-day analysis, respectively, versus 84.7% to 94.2% and 28.6% to 99.0% for the comparison methods. Average wearing times for the composite method for weekday and weekend day were 99.6% and 98.6%, respectively, 91.7% to 93.9% and 82.3% to 95.4% for the comparison methods. Composite-method physical activity estimates were similar to comparison-methods estimates.

Conclusion:

The composite method used more available accelerometer data than standard approaches, reducing the need to exclude periods within a day, entire days, and participants from analysis.

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John R. Sirard, Peter Hannan, Gretchen J. Cutler and Dianne Nuemark-Sztainer

Background:

The purpose of this paper is to evaluate self-reported physical activity of young adults using 1-week and 1-year recall measures with an accelerometer as the criterion measure.

Methods:

Participants were a subsample (N = 121, 24 ± 1.7 yrs) from a large longitudinal cohort study. Participants completed a detailed 1-year physical activity recall, wore an accelerometer for 1 week and then completed a brief 1-week physical activity recall when they returned the accelerometer.

Results:

Mean values for moderate-to-vigorous physical activity (MVPA) from the 3 instruments were 3.2, 2.2, and 13.7 hours/wk for the accelerometer, 1-week recall, and 1-year recall, respectively (all different from each other, P < .001). Spearman correlations for moderate, vigorous, and MVPA between the accelerometer and the 1-week recall (0.30, 0.50, and 0.40, respectively) and the 1-year recall (0.31, 0.42, and 0.44, respectively) demonstrated adequate validity.

Conclusions:

Both recall instruments may be used for ranking physical activity at the group level. At the individual level, the 1-week recall performed much better in terms of absolute value of physical activity. The 1-year recall overestimated total physical activity but additional research is needed to fully test its validity.

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Marsha Dowda, Russell R. Pate, James F. Sallis, Patty S. Freedson, Wendell C. Taylor, John R. Sirard and Stewart G. Trost

Parents and 531 students (46% males, 78% white) completed equivalent questionnaires. Agreement between student and parent responses to questions about hypothesized physical activity (PA) correlates was assessed. Relationships between hypothesized correlates and an objective measure of student’s moderate- to-vigorous physical activity (MVPA) in a subset of 177 students were also investigated. Agreement between student and parent ranged from r = .34 to .64 for PA correlates. Spearman correlations between MVPA and PA correlates ranged from −.04 to .21 for student report and −.14 to .32 for parent report, and there were no statistical differences for 8 out of 9 correlations between parent and student. Parents can provide useful data on PA correlates for students in Grades 7–12.

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Carrie D. Patnode, Leslie A. Lytle, Darin J. Erickson, John R. Sirard, Daheia J. Barr-Anderson and Mary Story

Background:

While much is known about the overall levels of physical activity and sedentary activity among youth, few studies have attempted to define clusters of such behaviors. The purpose of this study was to identify and describe unique classes of youth based on their participation in a variety of physical activity and sedentary behaviors.

Methods:

Latent class analysis was used to characterize segments of youth based on patterns of self-reported and accelerometer-measured participation in 12 behaviors. Children and adolescents (N = 720) from 6th-11th grade were included in the analysis. Differences in class membership were examined using multinomial logistic regression.

Results:

Three distinct classes emerged for boys and girls. Among boys, the 3 classes were characterized as “Active” (42.1%), “Sedentary” (24.9%), and “Low Media/Moderate Activity” (33.0%). For girls, classes were “Active” (18.7%), “Sedentary” (47.6%), and “Low Media/Functional Activity” (33.7%). Significant differences were found between the classes for a number of demographic indicators including the proportion in each class who were classified as overweight or obese.

Conclusions:

The behavioral profiles of the classes identified in this study can be used to suggest possible audience segments for intervention and to tailor strategies appropriately.

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Sofiya Alhassan, John R. Sirard, Laura B. F. Kurdziel, Samantha Merrigan, Cory Greever and Rebecca M. C. Spencer

Purpose:

The purpose of this study was to cross-validate previously developed Actiwatch (AW; Ekblom et al. 2012) and AcitGraph (AG; Sirard et al. 2005; AG-P, Pate et al. 2006) cut-point equations to categorize free-living physical activity (PA) of preschoolers using direct observation (DO) as the criterion measure. A secondary aim was to compare output from the AW and the AG from previously developed equations.

Methods:

Participants’ (n = 33; age = 4.4 ± 0.8 yrs; females, n=12) PA was directly observed for three 10-min periods during the preschool-day while wearing the AW (nondominant wrist) and AG (waist). Device specific cut-points were used to reduce the AW-E (Ekblom et al. 2012) and AG (AG-S, Sirard et al. 2005; AG-P, Pate et al. 2006) data into intensity categories. Spearman correlations (rsp) and agreement statistics were used to assess associations between the DO intensity categories and device data. Mixed model regression was used to identify differences in times spent in activity intensity categories.

Results:

There was a significant correlation between AW and AG output across all data (rsp = 0.41, p < .0001) and both were associated with the DO intensity categories (AW: rsp = 0.47, AG: rsp = 0.47; p < .001). At the individual level, all devices demonstrated relatively low sensitivity but higher specificity. At the group level, AW-E and AG-P provided similar estimates of time spent in moderate-to-vigorous PA (MVPA, AW-E: 4.7 ± 4.1, AG-P: 4.4 ± 3.3), compared with DO (5.1 ± 3.5). Conclusion: The AW-E and AG-P estimated times spent in MVPA were similar to DO, but the weak agreement statistics indicate that neither device cut-point equations provided accurate estimates at the individual level.