The purpose of this study was two-fold: to analyze the association between muscular fitness (MF) and clustering of metabolic syndrome (MetS) components, and to determine if fatness parameters mediate the association between MF and MetS clustering in Colombian collegiate students. This cross-sectional study included a total of 886 (51.9% women) healthy collegiate students (21.4 ± 3.3 years old). Standing broad jump and isometric handgrip dynamometry were used as indicators of lower and upper body MF, respectively. Also, a MF score was computed by summing the standardized values of both tests, and used to classify adults as fit or unfit. We also assessed fat mass, body mass index, waist-to-height ratio, and abdominal visceral fat, and categorized individuals as low and high fat using international cut-offs. A MetS cluster score was derived by calculating the sum of the sample-specific zscores from the triglycerides, HDL cholesterol, fasting glucose, waist circumference, and arterial blood pressure. Linear regression models were used to examine whether the association between MF and MetS cluster was mediated by the fatness parameters. Data were collected from 2013 to 2016 and the analysis was done in 2016. Findings revealed that the best profiles (fit + low fat) were associated with lower levels of the MetS clustering (p 0.001 in the four fatness parameters), compared with unfit and fat (unfit + high fat) counterparts. Linear regression models indicated a partial mediating effect for fatness parameters in the association of MF with MetS clustering. Our findings indicate that efforts to improve MF in young adults may decrease MetS risk partially through an indirect effect on improvements to adiposity levels. Thus, weight reduction should be taken into account as a complementary goal to improvements in MF within exercise programs.
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)