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

Age showed positive associations with aerobic capacity and muscular fitness measures in male adolescents.

• Study involved 195 male adolescents aged 10-16 years assessed at three time points across two academic years (2018-2019), yielding 449 observations.
• Age was positively associated with 20-m shuttle run performance (β̂ = 0.25, 68% CI = [0.19, 0.31]).
• Age was positively associated with sit-up performance (β̂ = 0.31, 68% CI = [0.25, 0.37]).
• Age was positively associated with standing long jump (β̂ = 0.36, 68% CI = [0.30, 0.41]) and medicine ball throw (β̂ = 0.57, 68% CI = [0.50, 0.64]).
• The effect of age on medicine ball throw was reduced after adjustment for body mass and individual variability.

Age showed negative associations with 20-m sprint and agility times, reflecting improvements in speed and agility performance.

• Negative associations were observed for the 20-m sprint (β̂ = -0.27, 68% CI = [-0.31, -0.22]), indicating faster sprint times with increasing age.
• Negative associations were also observed for the 4-m shuttle run (β̂ = -0.29, 68% CI = [-0.35, -0.23]), reflecting enhanced agility.
• These patterns were confirmed after adjustment for body mass and individual variability.
• Multilevel Bayesian hierarchical models incorporated varying intercepts and slopes to account for individual differences.

Phase angle demonstrated consistent positive associations with multiple physical fitness domains over the longitudinal follow-up period.

• PhA was derived from single-frequency bioelectrical impedance analysis (BIA) and used as a non-invasive indicator of cellular health and body composition.
• Fitness measures assessed included cardiorespiratory fitness, muscular endurance, flexibility, muscular power, speed, and agility.
• Associations between PhA and fitness outcomes were estimated using multilevel Bayesian hierarchical models with standardized fitness outcomes.
• The positive associations between PhA and fitness were observed consistently across multiple fitness domains, not limited to a single component.

Physical fitness components improved with age across all measured domains during adolescence.

• Fitness was assessed at three time points across two academic years (2018 and 2019) in a school in Campinas, São Paulo, Brazil.
• Improvements were observed in aerobic capacity (20-m shuttle run), muscular endurance (sit-up), muscular power (standing long jump and medicine ball throw), speed (20-m sprint), and agility (4-m shuttle run).
• Flexibility (sit-and-reach) was also assessed, though the abstract does not specifically report the age-related direction of change for this measure.
• The sample was restricted to male adolescents aged 10-16 years, limiting generalizability to other sexes and populations.

The study used Bayesian multilevel hierarchical modeling to account for individual variability in repeated-measures fitness and PhA data.

• Models estimated associations between standardized fitness outcomes, age, PhA, and their interaction.
• Varying intercepts and slopes were incorporated to account for individual differences across the three measurement time points.
• A total of 449 observations were derived from 195 participants, indicating an unbalanced repeated-measures design.
• 68% credible intervals were reported alongside posterior mean estimates (β̂) for all associations.

The authors propose that phase angle could be integrated into school-based health screenings to identify adolescents at risk for poor fitness trajectories.

• PhA is described as 'practical, non-invasive' and 'cost-effective' relative to other fitness biomarkers.
• The authors suggest PhA could be used to evaluate the effectiveness of physical activity interventions in school settings.
• The study notes that the relationship between PhA and fitness during adolescence was 'underexplored' prior to this work.
• The authors call for further research in girls and across diverse populations to establish reference values and intervention thresholds.