Multilevel Analysis Of Student- And School-level Variables On Students’ Health-related Fitness

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There is a need to understand how schools and educators can create healthier school environments through improved physical activity (PA) and nutrition offerings. Many programs exist that promote physical activity (PA) and nutrition in schools, but limited information is available regarding the impact that programming has on the health-related fitness of their students. PURPOSE: To determine the amount of variance in V02max and body mass index (BMI) explained by school- and student-level variables. School-level variables included the percentage of students receiving free or reduced lunch, school size, amount of health-related funding, number of community partnerships, and the number of PA, nutrition, and health programs. Student-level variables included age, gender, V02max, and BMI. METHODS: School-level variables were collected from 31 schools that had completed the second year of the Healthy Zone School Recognition Program created by The Cooper Institute® and United Way of Metropolitan Dallas. Participants included 11639 elementary and middle school students (Mage = 9.86, SD = 1.39; 51% boys). Students completed the FITNESSGRAM® tests for aerobic capacity (i.e., PACER; n = 7789) and body composition (n = 11155) at the end of the second year of the program to obtain estimates of V02max and BMI. RESULTS: Multi-level analysis indicated that there were significant differences in schools’ mean V02max and BMI (p < .01). The school context accounted for 16.68% and 11.37% of the variance in V02max and BMI (Model 1), respectively, and the school-level variables accounted for 51.43% and 32.23% of the variance explained in V02max and BMI in the school context (Model 2). In addition, the student-level variables explained 27.51% and 17.65% of the variance in V02max and BMI (Model 3), respectively, that remained unexplained by the school context. CONCLUSION: The school context, in addition to the student-level variables, plays an important role in the health-related fitness of students. Future research in schools should continue to use multi-level analysis with nested data to account for differences between and within schools. This approach will help determine the extent to which schools might influence students’ healthy behaviors and health-related fitness.