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Quantifying Physical Activity in Physical Education via Pedometry: A Further Analysis of Steps/Min Guidelines

Philip W. Scruggs

Background:

The validity of common pedometer steps/min guidelines for 1st−12th grade physical education physical activity (PA) recommendations (ie, 33% and 50% PA) was investigated.

Methods:

Data sets from previous research, where physical education PA was quantified via pedometry, were combined. Participants (1st−12th grade, N = 1152) with concurrent steps/min and observed %PA scores were included. Data were analyzed using correlation, regression, and receiver-operator-characteristic (ROC) statistics. Alpha was set at .05.

Results:

Overall, by gender and school level group (ie, 1st−6th, 7th−12th) PA outcome measures were strongly correlated and significant (r = .85–.92). Steps/min2, lesson time3, stature4, and BMI5 were significant predictors (r 12•345=.91) of %PA1. Steps/min accounted for 85.4% of the variance for %PA; however, the other predictors only accounted for an additional 0.5%. ROC analyses indicated that steps/min was an excellent discriminator (AUC ≥ .90) of %PA guideline achievement. Steps/min values of 60.6 and 82.2 were the most accurate cut points overall for the 33% and 50% PA guidelines, respectively. Steps/min cut points for gender and school level demonstrated agreement with the overall steps/min cut points.

Conclusions:

These findings support the contention that common steps/min guidelines can be applied in the surveillance of physical education PA.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 10 (2013): Issue 5 (Jul 2013)

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Quantifying Activity Time via Pedometry in Fifth- and Sixth-Grade Physical Education

Philip W. Scruggs

Background:

The aim of this study was to advance physical activity (PA) surveillance in physical education (PE) by establishing a steps/min guideline that would accurately classify fifth and sixth graders as engaging in PA for 10 min or one-third of the PE lesson time.

Methods:

Data were collected on 147 (11.48 ± 0.83 y) girls and boys in 14 intact classes from five schools. PA was assessed via behavioral observation (i.e., criterion) and pedometry (i.e., predictor). Logistic and linear regression techniques were employed to generate pedometer steps/min cut points. Classification of outcome probability (c), sensitivity, specificity, and receiver-operating-characteristic (ROC) curve statistics tested the decision accuracy of generated steps/min cut points.

Results:

PA measures were strongly correlated (r ≥ 0.80, P < 0.01). A steps/min interval of 60 to 62 was the best cut point indicator of students meeting the PA guidelines.

Conclusions:

Findings support steps/min as an accurate quantifier of PA time in structured PA programs. PA surveillance via pedometry in PE using empirically derived criteria is an objective, valid, and practical mechanism for assessing a primary PE and public health outcome.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 4 (2007): Issue 2 (Apr 2007)

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Increasing Children’s School Time Physical Activity Using Structured Fitness Breaks

Philip W. Scruggs, Sandy K. Beveridge, and Doris L. Watson

Fifth-grade students’ physical activity levels were examined via heart rate telemetry and pedometry during school fitness and recess breaks. Twenty-seven students with a mean age of 11.03 (-.32) years participated in morning recess (MR), lunch recess (LR), and fitness breaks (FB) for three days. Structured FB’s consisted of students engaging in locomotor and nonlocomotor activities within an obstacle course framework, while recess breaks followed a traditional model. Results from repeated measures ANOVAs indicated students engaged in significantly more physical activity during FB than MR and LR. Fitness breaks provided a viable method for increasing children’s school time activity levels.

Cover Pediatric Exercise Science

In Pediatric Exercise Science Volume 15 (2003): Issue 2 (Jan 2003)

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Chapter 1 Setting the Stage: Coordinated Approaches to School Health and Physical Education

Steven H. Kelder, Grace Goc Karp, Philip W. Scruggs, and Helen Brown

Is there anything more important than the health, well-being and education of a nation’s children? This paper takes the position that school is the most important place to educate children about health and to develop lifelong health promoting skills. We believe that health promotion programs and activities are integral to the school’s educational program, not as extracurricular, but as central to school’s educational mission. In this chapter, we highlight the importance of physical education and physical activity as key components of a well-designed coordinated school health program. We also outline the skills that PE teachers must learn to take a leadership role in the school health movement.

Cover Journal of Teaching in Physical Education

In Journal of Teaching in Physical Education Volume 33 (2014): Issue 4 (Jan 2014)

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Chapter 10 Implications for Comprehensive School Physical Activity Program Implementation

Grace Goc Karp, Philip W. Scruggs, Helen Brown, and Steven H. Kelder

Cover Journal of Teaching in Physical Education

In Journal of Teaching in Physical Education Volume 33 (2014): Issue 4 (Jan 2014)

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The Impact of Low Accelerometer Wear Time on the Estimates and Application of Sedentary Behavior and Physical Activity Data in Adults

Ryan McGrath, Chantal A. Vella, Philip W. Scruggs, Mark D. Peterson, Christopher J. Williams, and David R. Paul

Background: This investigation sought to determine how accelerometer wear (1) biased estimates of sedentary behavior (SB) and physical activity (PA), (2) affected misclassifications for meeting the Physical Activity Guidelines for Americans, and (3) impacted the results of regression models examining the association between moderate to vigorous physical activity (MVPA) and a clinically relevant health outcome. Methods: A total of 100 participants [age: 20.6 (7.9) y] wore an ActiGraph GT3X+ accelerometer for 15.9 (1.6) hours per day (reference dataset) on the hip. The BOD POD was used to determine body fat percentage. A data removal technique was applied to the reference dataset to create individual datasets with wear time ranging from 15 to 10 hours per day for SB and each intensity of PA. Results: Underestimations of SB and each intensity of PA increased as accelerometer wear time decreased by up to 167.2 minutes per day. These underestimations resulted in Physical Activity Guidelines for Americans misclassification rates of up to 42.9%. The regression models for the association between MVPA and body fat percentage demonstrated changes in the estimates for each wear-time adherence level when compared to the model using the reference MVPA data. Conclusions: Increasing accelerometer wear improves daily estimates of SB and PA, thereby also improving the precision of statistical inferences that are made from accelerometer data.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 14 (2017): Issue 12 (Dec 2017)