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


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.


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.


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.


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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John L. Walker, Tinker D. Murray, James Eldridge, William G. Squires, Jr., Pete Silvius and Erik Silvius

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Sarah E. Roth, Monique Gill, Alec M. Chan-Golston, Lindsay N. Rice, Catherine M. Crespi, Deborah Koniak-Griffin and Michael L. Prelip

students (5 males and 4 females). The survey was designed to take approximately 30 minutes to complete to limit the use of classroom time. Data on student fitness levels were collected during the same time periods as baseline and follow-up survey data collection using FitnessGram, a widely used fitness

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Stacy N. Scott, Cary M. Springer, Jennifer F. Oody, Michael S. McClanahan, Brittany D. Wiseman, Tyler J. Kybartas and Dawn P. Coe

-based shuttle run was developed to simulate a graded exercise test to assess aerobic fitness through the estimation of VO 2 peak ( 6 ). The FitnessGram™ (Cooper Institute for Aerobics Research, Dallas, TX) progressive aerobic cardiovascular endurance run (PACER) assessment was created based on the Leger shuttle

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Xiangli Gu, Senlin Chen and Xiaoxia Zhang

-related fitness; physical activity PE Metrics written test; FitnessGram; Actical monitor Standard 4: The physically literate individual exhibits responsible personal and social behavior that respects self and others. Not focused Not assessed Standard 5: The physically literate individual recognizes the value of

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Timothy Martinson, Stephen A. Butterfield, Craig A. Mason, Shihfen Tu, Robert A. Lehnhard and Christopher J. Nightingale

cardiovascular health. There has been a growing interest in health-related fitness education and assessment in schools ( 22 ). Several assessment tools, including Physical Best ( 16 ), FITNESSGRAM ( 15 ), and the President’s Fitness Challenge ( 17 ), include a battery of test items that evaluate the 5 primary

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Ryan D. Burns, James C. Hannon, Timothy A. Brusseau, Patricia A. Eisenman, Pedro F. Saint-Maurice, Greg J. Welk and Matthew T. Mahar

Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13–16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74–0.78), and prediction error (RMSE) ranged from 5.95 ml·kg-1, min-1 to 8.27 ml·kg-1.min-1. Criterion-referenced agreement into FITNESSGRAM’s Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31–0.62; Agreement = 75.5–89.9%; F = 0.08–0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM’s Healthy Fitness Zones.

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Julian A. Reed, Gilles Einstein, Erin Hahn, Steven P. Hooker, Virginia P. Gross and Jen Kravitz


To examine the impact of integrating physical activity with elementary curricula on fluid intelligence and academic achievement.


A random sample of 3rd grade teachers integrated physical activity into their core curricula approximately 30 minutes a day, 3 days a week from January 2008 to April 2008. Noninvasive fluid intelligence cognitive measures were used along with State-mandated academic achievement tests.


Experimental Group children averaged close to 1200 pedometer steps per integration day, thus averaging 3600 steps per week. Children in the Experimental Group performed significantly better on the SPM Fluid Intelligence Test. Children in the Experimental Group also performed significantly better on the Social Studies State mandated academic achievement test. Experimental Group children also received higher scores on the English/Language Arts, Math and Science achievements tests, but were not statistically significant compared with Control Group children. Children classified in Fitnessgram’s Healthy Fitness Zone for BMI earned lower scores on many of the SPM Fluid Intelligence components.


This investigation provides evidence that movement can influence fluid intelligence and should be considered to promote cognitive development of elementary-age children. Equally compelling were the differences in SPM Fluid Intelligence Test scores for children who were distinguished by Fitnessgram’s BMI cut points.

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Kevin Mercier and Stephen Silverman

The purpose of this study was to investigate the attitudes of high school students toward fitness testing. An instrument containing 18 items and four factors measuring student’s attitudes toward fitness testing: cognitive, affect-enjoyment, affect-feelings, and affect-teacher was completed by 524 boys and 675 girls (N = 1199). MANOVA indicated significant differences among the dependent variables for grade and gender. A stepwise discriminant function analysis (DFA) indicated affect-feelings then affect-enjoyment as variables that predicted these differences. Follow-up tests indicated that gender, and not grade, was the cause of the significant affect-feelings differences. MANOVA for fitness test types and the follow-up DFA indicated that students who completed the FitnessGram test had significantly higher cognitive attitudes than those who completed the President’s Challenge. The results suggest that student gender and the type of fitness test impact and lead to differences in attitudes.

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Wenhao Liu, Traci D. Zillifro and Randall A. Nichols

This study tracked health-related physical fitness in 11 year-old youths over their three-year middle school period. The Fitnessgram test battery was administered four times to 116 boys and 129 girls in the US during the period. Results indicated that BMI and estimated %BF tracked best, followed by PACER, sit and reach, push-up, and curl-up. Fitness levels in the estimated %BF and curl-up in the least fit quartiles (at baseline) tracked better than those in the fittest quartiles, and initially at-risk youths had higher probabilities of falling into at-risk categories three years later than those initially in healthy groups. In addition, boys became healthier in the estimated %BF and girls tracked poorer than boys in the PACER. Further, the numbers of girls in the at-risk categories increased considerably in four fitness measures (estimated %BF, BMI, PACER, and push-up) during the middle school period, whereas boys’ corresponding numbers either dropped or did not change in all the fitness measures.