Effect of muscle distribution and fat distribution on standing long jump in young adults

Abstract

Abstract Background Standing long jump is the most reliable method to test the explosive power of lower limbs, and research on its relationship with body composition may be of significance to public health. Objective To study the effect of muscle distribution and fat distribution on Standing long jump in healthy young adults Methods A total of 609 male and 1556 female Chinese college students were recruited. Total body muscle mass (TMM), trunk muscle mass (TKMM), upper limb muscle mass (ULMM), lower limb muscle mass (LLMM), total body fat mass (TFM), trunk fat mass (TKFM), upper limb fat mass (ULFM), and lower limb fat mass (LLMM) were measured with a body composition analyzer. The standing long jump (SLJ) test was conducted according to the “Chinese Student Physical Health Standard.” SLJ scores were divided into four groups: <60 group, 60–79 group, 80–89 group, and ≥ 90 group. Results The correlation analysis showed that the SLJ performance of male participants was significantly positively correlated with TMM (r = 0.135, P < 0.01), TKMM (r = 0.142, P < 0.01), ULMM (r = 0.098, P < 0.05), and LLMM (r = 0.107, P < 0.01). Moreover, it was significantly negatively correlated with TFM (r = − 0.280, P < 0.01), TKFM (r = − 0.298, P < 0.01), ULFM (r = − 0.154, P < 0.01), and LLFM (r = − 0.237, P < 0.01).the SLJ performance of female participants was significantly positively correlated with TMM (r = 0.192, P < 0.01), TKMM (r = 0.224, P < 0.01), ULMM (r = 0.117, P < 0.01), and LLMM (r = 0.089, P < 0.01). Moreover, it was significantly negatively correlated with TFM (r = − 0.100, P < 0.01), TKFM (r = − 0.100, P < 0.01), ULFM (r = − 0.104, P < 0.01), and LLFM (r = − 0.091, P < 0.01). We controlled for weight and then performed a partial correlation analysis. The results were similar to the previous ones. The SLJ performance of male participants was significantly positively correlated with TMM (r = 0.441, P < 0.01), TKMM (r = 0.333, P < 0.01), ULMM (r = 0.145, P < 0.01), and LLMM (r = 0.304, P < 0.01). Moreover, it was significantly negatively correlated with TFM (r = − 0.440, P < 0.01), TKFM (r = − 0.430, P < 0.01), ULFM (r = − 0.140, P < 0.01), and LLFM (r = − 0.385, P < 0.01). Similar to the SLJ performance of male participants, the SLJ performance of female participants was significantly positively correlated with TMM (r = 0.292, P < 0.01), TKMM (r = 0.291, P < 0.01), ULMM (r = 0.119, P < 0.01), and LLMM (r = 0.090, P < 0.01). Moreover, it was significantly negatively correlated with TFM (r = − 0.292, P < 0.01), TKFM (r = − 0.272, P < 0.01), ULFM (r = − 0.267, P < 0.01), and LLFM (r = − 0.268, P < 0.01). The multiple linear regression analysis showed that TKMM, TKFM, and LLMM were the significant influencing factors of SLJ in males, and the regression coefficients were 1.706 (P < 0.01), − 3.795 (P < 0.01), and 1.970 (P < 0.01), respectively. Moreover, TKMM, TKMM, and ULMM were the significant influencing factors of SLJ in females, and the regression coefficients were 3.002 (P < 0.01), − 1.886 (P < 0.01), and 2.069 (P < 0.01). Conclusions This study found that high muscle distribution and low fat distribution were beneficial to the SLJ performance in young adults. TKMM, TKFM, and LLMM had a great impact on the SLJ performance of male participants, whereas TKMM, TKFM, and ULMM had a great impact on the SLJ performance of female participants. This finding indicates that during SLJ, gender differences exist in the coordination of the upper and lower bodies. Men have good lower body coordination, and women have good upper body coordination. These findings provide substantial evidence for a close relationship between body composition and the SLJ.