High performing/Low poverty
Low performing/High poverty
Sit and reach
Castelli, Hillman, Buck, and Erwin
Mean Score by School Performance/Poverty Index
*Significantly different at p < .01; **significantly different at p < .05.
high-performing/low poverty schools and low-performing/high poverty schools. Pearson product-moment correlation analyses were initially conducted on the three dependent variables (total academic achievement, mathematics achievement, reading achievement), individual Fitnessgram scores (PACER, push-ups, curl-ups, mean back-saver sit and reach, BMI) and a composite measure of total fitness (i.e., subtraction of BMI within each age group from the aggregated z score of the other four Fitnessgram subtests (PACER, push-ups, curl-ups, mean back-saver sit and reach), age, sex (coded as 0 = females, 1 = males), school (coded as 0 = low per- forming, 1 = high performing), and poverty index (coded as 0 = low poverty index, 1 = high poverty index; see Table 2). The other variables (age, sex, school, and poverty index) were included to identify covariates for inclusion in the regression analyses. Only the variables that correlated with either academic achievement or fitness were included in subsequent regression analyses. Results of the correlation analyses indicated that three subscales of the Fitnessgram (PACER, push-ups, curl-ups) and total fitness were positively correlated with all three achievement test measures (p < .01). Mean scores for the back-saver sit and reach were positively correlated with total academic achievement and math achievement (p < .05) but were unrelated to reading achievement (p = .09). School was positively correlated with total academic achievement and reading achievement (p < .02), and negatively correlated with push-ups (p = .03). Body mass index was negatively correlated with the three achievement test measures (p < .001). In addition, age was positively cor- related with back-saver sit and reach (p = .005), and sex was positively correlated with PACER and push-ups, and negatively correlated with back-saver sit and reach (p < .02). Finally, poverty index was unrelated with all other measures (p > .07).
A series of analyses were performed that regressed the three academic achieve- ment measures (total achievement, reading, mathematics) on the total fitness com- posite score. In the case of total achievement and reading achievement, a positive correlation was observed with school, warranting inclusion of this variable in the model. As such, two-step hierarchical regressions were performed that included school in the first step and the total fitness composite score in the second step. In both analyses (i.e., total achievement, reading achievement), the first step exhibited a s i g n i fi c a n t r e l a t i o n s h i p , a d j u s t e d R 2 ≥ . 0 1 8 , F ( 2 , 2 5 7 ) ≥ 5 . 8 , p < . 0 2 , i n d i c a t i n that higher performing schools were associated with higher academic achievement g