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  • Author: Kerry McIver x
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Russell R. Pate, Gregory J. Welk and Kerry L. McIver

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Alysia Cohen, Samantha McDonald, Kerry McIver, Russell Pate and Stewart Trost

The purpose of this study was to evaluate the validity and interrater reliability of the Observational System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N = 29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-second observe, 20-second record). Two observers simultaneously observed and recorded children’s PA intensity, practice context, social context, coach behavior, and coach proximity. Interrater reliability was based on agreement (Kappa) between the observer’s coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect interobserver agreement (Kappa = 0.67−0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49−0.90). A significant correlation (r = .73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children’s PA and contextual factors during a youth soccer practice.

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Dawn K. Wilson, Suzanne Domel Baxter, Caroline Guinn, Russell R. Pate and Kerry McIver

Background:

Qualitative methods were used to better understand how to obtain interviewer-administered recalls of physical activity from children.

Methods:

Subjects were 24 third- and fifth-grade children from 1 school in Columbia, South Carolina. Cognitive interviews targeted different retention intervals (about the same or previous school day). Round 1’s protocols used an open format and had 4 phases (obtain free recall, review free recall, obtain details, review details). Round 2’s protocols used a chronological format and had 3 phases (obtain free recall, obtain details, review details). Trained coders identified discrepancies across interview phases in children’s recalls of physical activity at physical education (PE) and recess. Based on the school’s schedule, children’s reports of PE and recess were classified as omissions (scheduled but unreported) or intrusions (unscheduled but reported).

Results:

Across interview phases, there were numerous discrepancies for Round 1 (regardless of grade, sex, or retention interval) but few discrepancies for Round 2. For Rounds 1 and 2, respectively, 0% and 0% of children omitted PE, while 33% and 0% intruded PE; 44% and 56% of children omitted recess, while 33% and 0% intruded recess.

Conclusions:

Results provide important information for facilitating interviewer-administered recalls of physical activity with elementary-age children.

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Natalie Colabianchi, Jamie L. Griffin, Kerry L. McIver, Marsha Dowda and Russell R. Pate

Background:

Numerous studies have focused on the role of environments in promoting physical activity, but few studies have examined the specific locations where children are active and whether being active in these locations is associated with physical activity levels over time.

Methods:

Self-reported locations of where physical activity occurred and physical activity measured via accelerometry were obtained for a cohort of 520 children in 5th and 6th grades. Latent class analysis was used to generate classes of children defined by the variety of locations where they were active (ie, home, school grounds, gyms, recreational centers, parks or playgrounds, neighborhood, and church). Latent transition analyses were used to characterize how these latent classes change over time and to determine whether the latent transitions were associated with changes in physical activity levels.

Results:

Two latent classes were identified at baseline with the majority of children in the class labeled as ‘limited variety.’ Most children maintained their latent status over time. Physical activity levels declined for all groups, but significantly less so for children who maintained their membership in the ‘greater variety’ latent status.

Conclusions:

Supporting and encouraging physical activity in a variety of locations may improve physical activity levels in children.

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Karin A. Pfeiffer, Marsha Dowda, Kerry L. McIver and Russell R. Pate

This study examined correlates of objectively measured physical activity (PA) in a diverse sample of preschool children (age 3–5 years; n = 331). Accelerometer min·hr−1 of moderate-to-vigorous physical activity (MVPA) and nonsedentary activity (NSA) were the outcome measures. Correlations among potential correlates and PA ranged from r = −0.12−0.26. Correlates in the final MVPA model were age, race, sex, BMI Z score, and parent perception of athletic competence, explaining 37% of the variance. The NSA model included the latter two variables, explaining 35% of the variance. Demographic factors were correlates of PA; parent perceptions of children’s competence may be important regarding preschoolers’ PA.

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Matthew T. Mahar, Gregory J. Welk, David A. Rowe, Dana J. Crotts and Kerry L. McIver

Background:

The purpose of this study was to develop and cross-validate a regression model to estimate VO2peak from PACER performance in 12- to 14-year-old males and females.

Methods:

A sample of 135 participants had VO2peak measured during a maximal treadmill test and completed the PACER 20-m shuttle run. The sample was randomly split into validation (n = 90) and cross-validation (n = 45) samples. The validation sample was used to develop the regression equation to estimate VO2peak from PACER laps, gender, and body mass.

Results:

The multiple correlation (R) was .66 and standard error of estimate (SEE) was 6.38 ml·kg−1·min−1. Accuracy of the model was confirmed on the cross-validation sample. The regression equation developed on the total sample was: VO2peak = 47.438 + (PACER*0.142) + (Gender[m=1, f=0]*5.134) − (body mass [kg]*0.197), R = .65, SEE = 6.38 ml·kg–1·min–1.

Conclusions:

The model developed in this study was more accurate than the Leger et al. model and allows easy conversion of PACER laps to VO2peak.

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Steven P. Hooker, Anna Feeney, Brent Hutto, Karin A. Pfeiffer, Kerry McIver, Daniel P. Heil, John E. Vena, Michael J. LaMonte and Steven N. Blair

Purpose:

This study was designed to validate the Actical activity monitor in middle-aged and older adults of varying body composition to develop accelerometer thresholds to distinguish between light and moderate intensity physical activity (PA).

Methods:

Nonobese 45 to 64 yr (N = 29), obese 45 to 64 yr (N = 21), and ≥65 yr (N = 23; varying body composition) participants completed laboratory-based sitting, household, and locomotive activities while wearing an Actical monitor and a portable metabolic measurement system. Nonlinear regression analysis was used to identify activity count (AC) cut-points to differentiate between light intensity (<3 METs) and moderate intensity (≥3METs) PA.

Results:

Using group-specific algorithms, AC cut points for 3 METs were 1634, 1107, and 431 for the obese 45 to 64 yr group, nonobese 45 to 64 yr group, and ≥65 yr group, respectively. However, sensitivity and specificity analysis revealed that an AC cut-point of 1065 yielded similar accuracy for detecting an activity as less than or greater than 3 METs, regardless of age and body composition.

Conclusion:

For the Actical activity monitor, an AC cut-point of 1065 can be used to determine light and moderate intensity PA in people ≥45 years of age.