The biophysical response of the human body to electric current is widely appreciated as a barometer of fluid distribution and cell function. From distinct raw bioelectrical impedance (BIA) variables assessed in the field of body composition, phase angle (PhA) has been repeatedly indicated as a functional marker of the cell’s health and mass. Although resistance training (RT) programs have demonstrated to be effective to improve PhA, with varying degrees of change depending on other raw BIA variables, there is still limited research explaining the biological mechanisms behind these changes. Here, we aim to provide the rationale for the responsiveness of PhA determinants to RT, as well as to summarize all available evidence addressing the effect of varied RT programs on PhA of different age groups. Available data led us to conclude that RT modulates the cell volume by increasing the levels of intracellular glycogen and water, thus triggering structural and functional changes in different cell organelles. These alterations lead, respectively, to shifts in the resistive path of the electric current (resistance, R) and capacitive properties of the human body (reactance, Xc), which ultimately impact PhA, considering that it is the angular transformation of the ratio between Xc and R. Evidence drawn from experimental research suggests that RT is highly effective for enhancing PhA, especially when adopting high-intensity, volume, and duration RT programs combining other types of exercise. Still, additional research exploring the effects of RT on whole-body and regional BIA variables of alternative population groups is recommended for further knowledge development.

Despite bioelectrical impedance analysis (BIA)-derived phase angle (PhA) being recognized as a global marker of health, reflecting both cellular integrity and fluid distribution, its biological determinants still need to be described in youth. This narrative review provides a comprehensive framework examining to what extent dielectric properties shaping PhA are influenced by qualitative and quantitative determinants at multiple levels of body composition in healthy and clinical pediatric populations. At the atomic-molecular level, water content, glycogen, lipids, and ionic concentrations are expected to influence PhA by affecting electrical conductivity and/or capacitance. While the increase in the absolute values of intracellular (ICW) and extracellular water (ECW) enhances electric conductivity, an increase in the relative portion of ECW is expected to reflect hydration imbalances with an impact on electrical pathways. At the cellular level, body cell mass is a key determinant of PhA, mainly due to the presence of skeletal muscle cells favoring conductive and capacitive properties. At the tissue level, skeletal muscle architecture and orientation strongly influence conductivity, while increases in skeletal muscle mass positively impact PhA by enhancing electric conductivity and capacitance. Beyond the theoretical insights presented in this review, careful interpretation of dielectric data remains crucial due to the lack of methodological standardization. Future research should prioritize validated reference methods, investigate longitudinal changes, integrate localized BIA, and explore additional BIA models to refine the interpretation of PhA.

Evidence on correlates relies on subjective metrics and fails to include correlates across all levels of the ecologic model. We determined which correlates best predict sensor-based physical activity (PA), sedentary time (ST), and self-reported cell phone screen time (CST) in a large sample of youth, while considering a multiplicity of correlates. Using sensor-based accelerometry, we assessed the PA and ST of 2179 youths. A χ2 automatic interaction detection algorithm was used to hierarchize the correlates associated with too much ST (> 50th percentile), insufficient moderate-to-vigorous PA (MVPA) (<60 min/day), and prolonged CST (≥2 h/day). Among youth 10-14 years old, the correlates for being inactive consisted of being a girl, not having sport facilities in the neighborhood, and not perceiving the neighborhood as a safe place, whereas in the youth 15-18 years old, the correlate for being inactive was not performing sports (9.7% chance of being active). The correlates for predicting high ST in the younger group was not performing sports (55.8% chance for high ST), and in the older group, the correlates were not owning a pet, perceiving the neighborhood as safe, and having inactive parents (63.7% chance for high ST). In the younger group, the greatest chances of having high CST were among those who were in the last elementary school years, who were girls, and who did not have friends in the neighborhood (73.1% chance for high CST), whereas in the older group, the greatest chance for having high CST was among those who were girls and had a TV in the bedroom (74.3% chance for high CST). To counteract ST and boost MVPA among youths, a specific focus on girls, the promotion of sport participation and facilities, neighborhood safety, and involvement of family must be prioritized.

Raw bioelectrical impedance analysis (BIA) parameters, particularly phase angle (PhA), are essential clinical and performance markers. However, their potential as body composition markers remains underexplored in youth. This investigation examined the associations between PhA and other series- and parallel-transformed raw BIA parameters and multiple body components organized at the molecular, cellular, and tissue levels in youth. A cross-sectional sample of 681 youth (10-17 years, 49 % females) was assessed using a phase-sensitive BIA device (50 kHz), dual-energy X-ray absorptiometry, and a freezing point depression osmometer. Multiple linear regression examined each raw BIA parameter's unadjusted and adjusted relationships with body components. PhA was associated with all body components in females (molecular level: β = |0.170| to |0.584|; cellular level: β = 0.409 to 0.582; tissue level: β = 0.170 to 0.569) and males (molecular level: β = |0.542| to |0.729|; cellular level: β = 0.612 to 0.729; tissue level: β = 0.714; p ≤ 0.05), independently of relevant confounders. No relationship was found between PhA and fat mass and adipose tissue in males (p > 0.05). Other raw BIA parameters were shown to be even more associated with body composition than PhA in females (molecular level: β = |0.172| to |0.827|; cellular level: β = |0.292| to |0.713|; tissue level: β = |0.635| to |0.821|) and males (molecular level: β = |0.555| to |0.926|; cellular level: β = |0.554| to |0.870|; tissue level: β = |0.827| to |0.916|; p ≤ 0.05). In both sexes, the association power of these BIA parameters was lower regarding fat-related parameters (β = non-significant to |0.460|). PhA was moderately associated with most body components in youth, except for fat-related components in males, independent of confounding variables. Resistance adjusted to stature consistently emerged as the most relevant marker, highlighting its potential to inform about body composition at an early age.

Despite the health importance of identifying correlates of physical fitness in youth, no investigation to date has explored the influence of behavioral, health-related, and contextual correlates simultaneously. We investigated the hierarchical relationship of multiple modifiable correlates favoring or diminishing cardiorespiratory and muscular fitness in youth. Cross-sectional investigation. In a sample of 5174 children and adolescents, 31 correlates were hierarchized according to their impact on cardiorespiratory and muscular fitness assessed using the FITESCOLA® fitness battery. A Chi-squared Automatic Interaction Detection approach was employed and measures of correlation and association were used to investigate the relationship between physical fitness and correlates. In children, body mass index was the most relevant factor to discriminate between high and low cardiorespiratory and muscular fitness of the upper, middle, and lower body. While body mass index was more important than any other correlate to differentiate levels of upper and lower body muscular fitness during adolescence, specific characteristics of sports participation emerged as key factors to discriminate between high and low cardiorespiratory fitness and middle body muscular fitness. Other correlates, including the self-report of active recess time, active commuting to school, favorable neighborhood conditions, and limited time on screens and cellphones, were demonstrative of favorable physical fitness levels. Both body composition and sports-related characteristics emerged as the two most relevant factors of physical fitness in youth. Additional health benefits may be obtained from building supportive environments for sports and healthy exercise habits within the household and at different school education levels.

The hypothesis that people may increase sedentary behavior (SB), referred to as “compensation” in response to exercise interventions, have raised concern. The evidence on “compensation” is contradictory and mostly derived from moderate-intensity continuous training (MICT) interventions lasting less than 1 year. The aim was to investigate whether two types of iso-energetic training (MICT and high-intensity interval training (HIIT), both combined with resistance training) resulted in compensations on SB, in patients with T2D. Eighty volunteers were randomly assigned to one of three groups (control, MICT, or HIIT), and 54 (59.2 ± 8.2 years) completed a supervised program for 1 year. Physical activity and SB were measured using Actigraph accelerometers at baseline and in the final month of intervention. Sitting-time and screen-time were measured by the long-version of the International Physical Activity Questionnaire. ANCOVA analysis was used to examine differences between groups at the end of the intervention adjusting for the baseline. No differences in objectively measured and self-reported SB were observed between groups, but women from the HIIT group reduced their sitting time (Δ = 170-minutes; P = .048). The absence of change in SB domains between baseline and follow up suggests that engaging in MICT and HIIT exercise programs in patients with T2D is unrelated to compensatory increases in SB.