Overview of the Texas Youth Fitness Study

Morrow,

doi:10.5641/027013610x13100547897951

Cited by 3 publications

(2 citation statements)

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“…This system has already been adopted by several states, thereby creating the potential for pooling school-based data for surveillance and research. 5 –7…”

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confidence: 99%

Fitness Trends and Disparities Among School-Aged Children in Georgia, 2011-2014

2017

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Objectives: Although FitnessGram fitness data on aerobic capacity and body mass index (BMI) have been collected in public schools in Georgia since the 2011-2012 school year, the data have not been analyzed. The primary objective of our study was to use these data to assess changes in fitness among school-aged children in Georgia between 2011 and 2014. A secondary objective was to determine if student fitness differed by school size and socioeconomic characteristics. Methods:FitnessGram classifies fitness into the Healthy Fitness Zone (HFZ) or not within the HFZ for aerobic capacity and BMI. We used data for 3 successive school years (ie, 2011-2012 to 2013-2014) obtained from FitnessGram testing of students in >1600 schools. We calculated the percentage of students who achieved the HFZ for aerobic capacity and BMI. We used growth curve models to estimate the annual changes in these proportions, and we determined the effect of school size and socioeconomic status on these changes. Results: Both elementary school boys (b ¼ 1.31%, standard error [SE] ¼ 0.23%, P < .001) and girls (b ¼ 1.53%, SE ¼ 0.26%, P < .001) had significant annual increases in achievement of HFZ for aerobic capacity. Elementary school boys (b ¼ 3.11%, SE ¼ 0.32%, P < .001) and girls (b ¼ 3.09%, SE ¼ 0.32%, P < .001) also had significant increases in their BMI HFZ achievement proportions, although these increases occurred primarily between 2011-2012 and 2012-2013. Body mass index HFZ achievement proportions were mixed for middle school students, and we did not observe increases for high school students. Larger school size and higher school socioeconomic status were associated with better aerobic capacity and BMI fitness profiles. Conclusions: Surveillance results such as these may help inform the process of designing state and local school-based fitness promotion and public health programs and tracking the results of those programs.

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“…This system has already been adopted by several states, thereby creating the potential for pooling school-based data for surveillance and research. 5 –7…”

mentioning

confidence: 99%

Fitness Trends and Disparities Among School-Aged Children in Georgia, 2011-2014

2017

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“…10,11 The Texas Youth Fitness Study was able to track longitudinal BMI trends from 2008 to 2009 using FitnessGram version 10 to gain knowledge concerning the health status of students, and another study suggested that statewide, school-based fitness tests have the potential to inform policies related to PE and physical activity opportunities in youth. 12,13…”

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confidence: 99%

Physical education teachers’ and principals’ perspectives on the use of FitnessGram

et al. 2019

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Objectives:FitnessGram is commonly used to measure physical fitness and improve physical activity and health in youth. However, little is known about its use for informing physical activity and health promotion policy within schools and school districts, especially from the perspective of key decision-makers like principals. Therefore, this study examined physical education teachers’ and principals’ perceptions of FitnessGram use and its relationship with school and district efforts to promote physical activity.Methods:Principal and physical education teacher surveys were developed, converted to an online format, and then emailed along with a project description and instructions to all Delaware public and charter school physical education teachers (N = 183) and principals (N = 193) with a valid email.Results:Completed surveys were received from 35.5% of the teachers and 21.2% of the principals. All teachers and 95.1% of the principals reported their school used FitnessGram the past academic year. FitnessGram was significantly more likely to be used if FitnessGram results better aligned with school/district policies (r = 0.39) and were considered important in the school’s decision-making process (r = 0.53). Significantly more principals than teachers said that FitnessGram results were important in their school’s decision-making process and that FitnessGram results were used to inform policy-/decision-making.Conclusion:Use of FitnessGram was correlated with how well it related to school/district policy. Unfortunately, most of the physical education teachers and principals did not think FitnessGram was adequately integrated into the policy-/decision-making process.

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