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Cathy S. McMillan and Loran D. Erdmann

This study tracked health-related physical fitness measurements in children, including sum of triceps and medial calf skinfolds, timed 1-mile run/walk, 1-min bent-knee sit-up, pull-up, and sit-and-reach values. Results are from 409 boys and 409 girls tested in kindergarten and fifth grade, also retaining their first, second, third, and fourth grade data. In separate gender analyses, Spearman’s rho correlations were significant (p < .001) for all grade level pair combinations for each variable. Five-yr tracking of adiposity and all health-related physical fitness measurements for boys and girls was generally moderate from early childhood to the upper elementary ages.

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Angelos K. Chanias, Greg Reid and Michael L. Hoover

A meta-analysis was conducted to determine the effects of exercise on health-related physical fitness of individuals with an intellectual disability. The data came from 21 individual studies yielding 100 effect sizes (ESs). Large effects were demonstrated for muscular and cardiovascular endurance, moderate for muscular strength, and small for flexibility. No significant effects were found for body composition. Document source and program length influenced muscular and cardiovascular endurance outcomes, as published studies and longer programs produced larger ESs. In addition, program type influenced muscular strength (resistance programs produced larger ESs than combined programs), and program frequency influenced flexibility (higher frequency programs had larger ESs than lower frequency programs). It was concluded that additional research is needed to investigate means to improve body composition, flexibility, and muscular strength. Future studies should upgrade their standards for reporting appropriate statistical information and information related to sample and exercise prescription components.

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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.

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Dartagnan P. Guedes, Jaime Miranda Neto, Vitor Pires Lopes and António José Silva

Background:

This study investigated the association between sociodemographic and behavioral factors and health standards based on physical fitness component scores in a sample of Brazilian schoolchildren.

Methods:

A sample of 1457 girls and 1392 boys aged 6 to 18 years performed a test battery of 5 items: 1) sit-and-reach, 2) curl-up, 3) trunk-lift, 4) push-up, and 5) progressive endurance run (PACER). The cut-off scores for gender and age suggested by the FitnessGram were adopted.

Results:

The findings showed that the sociodemographic and behavioral factors significantly associated with the ability of schoolchildren of meeting the health standards varied according to the fitness test. In the 5 tests used girls presented lower chance of meeting the health standards. Age and socioeconomic class were negatively associated with the performance in all physical tests. Schoolchildren aged ≤ 9 years or from families of lowest socioeconomic class presented approximately twice the chance of meeting the health standards than those aged ≥ 15 years and from more privileged families, specifically in the push-up (OR = 2.40; 95% CI 2.01–2.82) and PACER (OR = 2.18; 95% CI 1.84–2.54) tests.

Conclusions:

Interventions to promote health-related physical fitness should not only consider gender and age of schoolchildren, but also selected sociodemographic and behavioral factors, especially socioeconomic class and leisure activities.

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Jerry R. Thomas, Jack K. Nelson and Gabie Church

Data for the analysis were the health related fitness scores, anthropometric measures, and physical activity information from the National Children and Youth Fitness Study. The subjects were 6,800 boys and 6,523 girls, ages 6 through 18. Multiple regression produced linear composites that were used as covariates to evaluate physical and environmental characteristics that relate to gender differences. The distance runs, chin-ups, and sit-ups displayed similar patterns in gender differences across age. Before puberty the important covariates are mainly physical, namely skinfolds. Following puberty the major factors that reduce gender differences are skinfolds and the amount of exercise done outside of school time.

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Russell R. Pate, Stewart G. Trost, Marsha Dowda, Alise E. Ott, Dianne S. Ward, Ruth Saunders and Gwen Felton

This study examined the tracking of selected measures of physical activity, inactivity, and fitness in a cohort of rural youth. Students (N = 181, 54.7% female, 63.5% African American) completed test batteries during their fifth- (age = 10.7 ± 0.7 years), sixth-, and seventh-grade years. The Previous Day Physical Activity Recall (PDPAR) was used to assess 30-min blocks of vigorous physical activity (VPA), moderate-to-vigorous physical activity (MVPA), TV watching and other sedentary activities, and estimated energy expenditure (EE). Fitness measures included the PWC 170 cycle ergometer test, strength tests, tnceps skinfold thickness, and BMI. Intraclass correlation coefficients (ICCs) for VPA, MVPA, and after-school EE ranged from 0.63 to 0.78. ICCs ranged from 0.49 to 0.71 for measures of inactivity and from 0.78 to 0.82 for the fitness measures. These results indicate that measures of physical activity, inactivity, and physical fitness tend to track during the transition from elementary to middle school.

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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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Xiangli Gu, Senlin Chen and Xiaoxia Zhang

skills ( Silverman & Mercier, 2015 ), or reaching the healthy fitness zone (HFZ) of health-related physical fitness components ( Corbin, 2016 ). Comprehensive assessments that capture all of these areas simultaneously are currently lacking. The PE Metrics ™ was developed to assess the extent to which

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Brendan T. O’ Keeffe, Ciaran MacDonncha, Kwok Ng and Alan E. Donnelly

). Therefore, little is known about teachers’ approaches to fitness testing in schools ( Cale et al., 2014 ), particularly in countries where a standardized approach to health-related physical fitness (HRPF) monitoring does not exist. Physical fitness is a complex and multifaceted construct that includes

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You Fu, Zan Gao, James C. Hannon, Ryan D. Burns and Timothy A. Brusseau Jr.

Background:

This study aimed to examine the effect of a 9-week SPARK program on physical activity (PA), cardiorespiratory endurance (Progressive Aerobic Cardiovascular Endurance Run; PACER), and motivation in middle-school students.

Methods:

174 students attended baseline and posttests and change scores computed for each outcome. A MANOVA was employed to examine change score differences using follow-up ANOVA and Bonferroni post hoc tests.

Results:

MANOVA yielded a significant interaction for Grade × Gender × Group (Wilks’s Λ = 0.89, P < .001). ANOVA for PA revealed significant differences between SPARK grades 6 and 7 (Mean Δ = 8.11, P < .01) and Traditional grades 6 and 8 (Mean Δ = –6.96, P < .01). ANOVA also revealed greater PACER change for Traditional boys in grade 8 (P < .01) and SPARK girls in grade 8 (P < .01). There were significant interactions with perceived competence differences between SPARK grades 6 and 8 (Mean Δ = 0.38, P < .05), Enjoyment differences between SPARK grades 6 and 7 (Mean Δ = 0.67, P < .001), and SPARK grades 6 and 8 (Mean Δ = 0.81, P < .001).

Conclusions:

Following the intervention, SPARK displayed greater increases on PA and motivation measures in younger students compared with the Traditional program.