Longitudinal relationships between physical fitness and phase angle as a biomarker of cellular health in Brazilian male adolescents: a Bayesian analysis

The phase angle (PhA), derived from bioelectrical impedance analysis (BIA), has gained attention as a non-invasive indicator of cellular health and body composition. However, its relationship with physical fitness development during adolescence remains underexplored. This study aimed to prospectively investigate the longitudinal associations between phase angle and changes in multiple physical fitness components in male adolescents, examining whether PhA serves as a biomarker for fitness development over time. We conducted a repeated-measures study involving 195 male adolescents aged 10-16 years from a school in Campinas, S & atilde;o Paulo, Brazil. Physical fitness and BIA-derived PhA were assessed at three time points across two academic years (2018-2019), yielding 449 observations. Fitness measures included cardiorespiratory fitness (20-m shuttle run), muscular endurance (sit-up), flexibility (sit-and-reach), muscular power (standing long jump, medicine ball throw), speed (20-m sprint), and agility (4-m shuttle run). Phase angle was calculated using single-frequency BIA. Multilevel Bayesian hierarchical models estimated associations between standardized fitness outcomes, age, PhA, and their interaction, incorporating varying intercepts and slopes to account for individual differences. Age showed positive associations with performance in the 20-m shuttle run (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = 0.26$$\end{document}, 68% CI = [0.19, 0.31]), sit-up (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = 0.31$$\end{document}, 68% CI = [0.25, 0.37]), standing long jump (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = 0.36$$\end{document}, 68% CI = [0.30, 0.41]), and medicine ball throw (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = 0.57$$\end{document}, 68% CI = [0.50, 0.64]), indicating improvements in aerobic capacity and muscular fitness. Negative associations were observed for the 20-m sprint (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = -0.27$$\end{document}, 68% CI = [-0.31, -0.22]) and 4-m shuttle run (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta = -0.29$$\end{document}, 68% CI = [-0.35, -0.23]), reflecting enhanced speed and agility. Adjustment for body mass and individual variability confirmed these patterns, though the effect of age on medicine ball throw was reduced. Physical fitness improved with age during adolescence, and phase angle demonstrated consistent positive associations with multiple fitness domains over time. These findings suggest that PhA may serve as a practical, non-invasive biomarker for monitoring physical fitness development in adolescents. Given its ease of implementation and cost-effectiveness, PhA could be integrated into school-based health screenings and fitness assessment programs to identify adolescents at risk for poor fitness trajectories and to evaluate the effectiveness of physical activity interventions. Further research should examine these relationships in girls and across diverse populations to establish reference values and intervention thresholds.