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Sharon A. Plowman, Charles L. Sterling, Charles B. Corbin, Marilu D. Meredith, Gregory J. Welk and James R. Morrow Jr.

Initially designed by Charles L. Sterling as a physical fitness “report card” FITNESSGRAM ® / ACTIVITYGRAM ® is now an educational assessment and reporting software program. Based on physiological/epidemiological, behavioral, and pedagogical research, FITNESSGRAM is committed to health-related physical fitness, criterion-referenced standards, an emphasis on physical activity including behavioral based recognitions, and the latest in technology. The evolution of these major concepts is described in this history of FITNESSGRAM.

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Michael P. Ernst, Charles B. Corbin, Aaron Beighle and Robert P. Pangrazi

While the FITNESSGRAM ® test battery is widely used in schools, not all users are aware of the FITNESSGRAM position paper as outlined in the Reference Manual, and for this reason may fail to use FITNESSGRAM materials as intended. The purpose of this paper is to outline the many appropriate uses, and some inappropriate uses, of FITNESSGRAM. Because California is a state that employs the FITNESSGRAM as its state fitness test, examples from California are used. Suggestions for future uses of fitness testing are included.

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David A. Rowe and Matthew T. Mahar

Background:

The purpose of the study was to evaluate race-specific FITNESSGRAM® body mass index (BMI) standards in comparison to the recommended standards, i.e., percent fat (%BF) ≥25 in boys and %BF ≥32 in girls.

Methods:

BMI and %BF were estimated in 1,968 Black and White children ages 6-14 years, using methods similar to those used to develop the current FITNESSGRAM standards. Multiple regression was employed to develop age-, sex-, and race-specific BMI standards. Percent agreement and modified kappa (κq) were used to evaluate agreement with the %BF standards, and sensitivity and specificity were used to evaluate classification accuracy.

Results:

Race significantly (p < .05) and meaningfully (β = 2.3% fat) added to the relationship between BMI and %BF. Agreement of the race-specific BMI standards with %BF standards was moderate to high (κq = .73–.88), and classification accuracy improved on the current FITNESSGRAM BMI standards.

Conclusions:

Race-specific BMI standards appear to be a more accurate representation of unhealthy %BF levels than the current FITNESSGRAM BMI standards.

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Michelle Ihmels, Gregory J. Welk, James J. McClain and Jodee Schaben

Background:

Advances in BIA offer practical alternative approaches to assessing body composition in young adolescents and have not been studied for comparability.

Methods:

This study compared reliability and convergent validity of three field tests (2-site skinfold, Omron and Tanita BIA devices) on young adolescents. Reliability was determined using intraclass correlation coefficients, convergent validity was examined by computing correlations among the three estimates, differences in estimated body fat values were evaluated using repeated-measures ANOVA, and classification agreement was computed for achieving FITNESSGRAM ® Healthy Fitness Zone.

Results:

ICC values of all three measures exceeded .97. Correlations ranged from .74 to .81 for males and .79 to .91 for females. Classification agreement values ranged from 82.8% to 92.6%.

Conclusions:

Results suggest general agreement among the selected methods of body composition assessments in both boys and girls with the exception that percent body fat in boys by Tanita BIA is significantly lower than skinfold estimation.

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Norman S. Hannibal III, Sharon Ann Plowman, Marilyn A. Looney and Jason Brandenburg

Background:

Strength, muscular endurance, and flexibility are important components of healthy back function. This study determined the reliability and evaluated the validity of selected low back field tests (FITNESSGRAM ® Trunk Extension [FG-TE] and Box 90° Dynamic Trunk Extension [B-90° DTE]) when compared to laboratory tests (Parallel Roman Chair Dynamic Trunk Extension [PRC-DTE], Parallel Roman Chair Static Trunk Extension [PRC-STE], and Dynamometer Static Back Lift [DSBL]).

Methods:

Forty males age 15.1 ± 1.2 yr and 32 females age 15.5 ± 1.2 yr participated.

Results:

Intraclass test-retest reliability coefficients (one-way ANOVA model for a single measure) ranged from .940 to .996. Validity coefficients determined by Pearson product moment correlation coefficients for males and females, respectively, were as follows: B-90° DTE vs. PRC-DTE = .82, .62 (p < .05); B-90° DTE vs. PRC-STE = .55, .38 (p < .05); B-90° DTE vs. DSBL = −.29, −.23; FG-TE vs. PRC-DTE = .23, −.11; FG-TE vs. PRC-STE = −.15, .33; and FG-TE vs. DSBL = −.04, −.36.

Conclusions:

B-90° DTE was shown to be a valid field test when compared to PRC-DTE, but only for the males. Further research on the PRC-DTE and PRC-STE items for adolescents is recommended.

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Jacob S. Tucker, Scott Martin, Allen W. Jackson, James R. Morrow Jr., Christy A. Greenleaf and Trent A. Petrie

Purpose:

To investigate the relations between sedentary behaviors and health-related physical fitness and physical activity in middle school boys and girls.

Methods:

Students (n = 1515) in grades 6–8 completed the Youth Risk Behavior Survey sedentary behavior questions, the FITNESSGRAM physical fitness items, and FITNESSGRAM physical activity self-report questions.

Results:

When students reported ≤ 2 hours per day of sedentary behaviors, their odds of achieving the FITNESSGRAM Healthy Fitness Zone for aerobic capacity, muscular strength and endurance, flexibility, and body composition increased. Similarly, the odds of achieving physical activity guidelines for children increased when students reported ≤ 2 hours per day of sedentary behaviors.

Conclusions:

Results illustrate the importance of keeping sedentary behaviors to ≤ 2 hours per day in middle school children, thus increasing the odds that the student will achieve sufficient health-related fitness benefits and be more likely to achieve the national physical activity guidelines.

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Michael W. Beets and Kenneth H. Pitetti

Background:

To examine the Healthy Fitness Zone (pass/fail) criterion-referenced reliability (CRR) and equivalency (CRE) of the 1-mile run/walk (MRW) and Progressive Aerobic Cardiovascular Endurance Run (PACER) in adolescents (13 to 18 years).

Methods:

Seventy-six girls and 165 boys were randomly assigned to complete 2 trials of each test.

Results:

CRR for the boys on the MRW (Pa = 77%, κq = 0.53) was lower than on the PACER (Pa = 81%, κq = 0.63); girls were classified more similarly on the MRW (Pa = 83%, κq = 0.67) than on the PACER (Pa = 79%, κq = 0.58). The CRE between the MRW and PACER indicated boys (Pa = 77%, κq = 0.55) were classified more consistently on both tests than girls (Pa = 73%, κq = 0.46).

Conclusions:

No test provided greater consistency. Practitioners may consider other features, such as ease of administration, environmental conditions, and comparative use in the literature.

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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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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