Bioimpedance Vector Patterns according to Age and Handgrip Strength in Adolescent Male and Female Athletes

Fat-free mass predictive equation using bioelectrical impedance and maturity offset in adolescent athletes: Development and cross-validation

OBJECTIVES

This is a cross-sectional study, aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using single-frequency bioelectrical impedance (BIA), considering the predicted age at peak height velocity (PHV) as a variable. Additionally, the study aims to test the FFM-BIA obtained using a previous predictive equation that used skeletal maturity as a variable.

METHOD

The participants (n = 169 male adolescent athletes) were randomly divided into two groups: development of a new predictive equation (n = 113), and cross-validation (n = 56). The concordance test between the FFM values obtained by Koury et al. predictive equation and DXA data was determined (n = 169). Bioelectrical data was obtained using a single-frequency analyzer.

RESULTS

Among the models tested, the new predictive equation has resistance index (height2/resistance) and predictive age at PHV as variables and presented R2 = 0.918. The frequency of maturity status using skeletal maturity and PHV diagnosis was inadequate (Kappa = 0.4257; 95%CI = 0.298-0.553). Bland-Altman plots and concordance correlation coefficient showed substantial concordance between the FFM-DXA values (48.8 ± 11.2 kg) and the new predictive equation (CCC = 0.960). The results showed that the new equation performed better than the equation developed by Koury et al. (CCC = 0.901).

CONCLUSIONS

Our results show that it is feasible to predict FFM in male adolescent athletes using predictive age at PHV, with moderate concordance. The calculation of FFM using more economical and less complex variables is viable and should be further explored.

Fat-free mass predictive equation using multifrequency bioelectrical impedance data in adolescent soccer athletes: development and cross-validation

OBJECTIVES

This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance analysis (BIA) data in adolescent soccer athletes.

METHODS

Male adolescent soccer athletes (n = 149; 13-19 y old) were randomly sorted using Excel and independently selected for development group (n = 100) or cross-validation group (n = 49). The FFM reference values were determined using dual-energy X-ray absorptiometry. Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient, according to McBride criteria, precision, accuracy, and standard error of estimate (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis was plotted to assess hydration status.

RESULTS

No differences (P > 0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using dual-energy X-ray absorptiometry. Bioelectrical impedance vector analysis tolerance showed that all participants presented adequate hydration status compared to the reference population. The new FFM predictive equation developed and validated: FFM (kg) = -7.064 + 0.592 × chronological age (y) + 0.554 × weight (kg) + 0.365 × height²/resistance (cm²/Ω), presented R² = 0.95; SEE = 1.76 kg; concordance correlation coefficient = 0.95, accuracy = 0.98, and strength of concordance = 0.99.

CONCLUSIONS

The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.

Bioelectrical impedance vector analysis is different according to the comorbidity burden in post-acute myocardial infarction

BACKGROUND

The prevalence of a high comorbidity burden in patients who suffered an acute myocardial infarction (AMI) is increasing with the aging population, and the nutrition status also may be a predictor of clinical outcomes for these patients. This study aimed to investigate the relationship between the comorbidity burden and the characteristics of the bioelectrical impedance vector analysis (BIVA) in patients post-AMI.

METHODS

This prospective observational cohort study was conducted with adult patients who were hospitalized with AMI. Pre-existing comorbidities were assessed by the Charlson comorbidity index (CCI) adjusted by age, and anthropometric and BIVA characteristics were evaluated after the hemodynamic stabilization. All patients were followed-up until hospital discharge, and their length of stay was observed.

RESULTS

A total of 184 patients (75% were males; mean age, 60.2 ± 12.3 years) were included. The most common comorbidities were dyslipidemia (73.9%), hypertension (62%), and type 2 diabetes (34.2%). A higher CCI (≥3) was associated with sex (P = 0.008) and age (P < 0.001). Regarding BIVA, statistically significant differences were detected between sex (P < 0.001), age (P < 0.001), and CCI (P = 0.003), with longer vectors in female, older adults, and those with CCI ≥ 3.

CONCLUSION

Finding a relationship between BIVA and CCI suggests the first identified coherent differences, potentially correlated with diseases, representing a first contribution to support this type of assessment. Therefore, with BIVA, healthcare professionals may monitor abnormalities and adopt preventive nutrition care measures on patients post-AMI to improve their clinical status.

One-Year Changes in Bioelectrical Impedance Data in Adolescent Athletes

Raw bioelectrical impedance (BI) data and vector analysis (BIVA) have been used to evaluate fat-free mass (FFM) cross-sectionally in adolescent athletes; however, there have been no longitudinal studies about it. This study aimed to assess the magnitude of changes in raw BI data (resistance [R], reactance [Xc], and phase angle [PhA]), BIVA, and FFM in adolescent athletes (n = 137, 40% female). BI data were collected using a single-frequency device at baseline and after one year of sports practice. Baseline chronological age categorized the participants (11, 12, or 13 years [y]). In females, Xc/H increased (13 to 14 y, p = 0.04) while R/H decreased in all age groups (p = 0.001). PhA (11 to 12 y, p = 0.048) and FFM (11 to 12 y and 12 to 13 y groups p = 0.001) increased and showed the lowest magnitude of changes in the 13 to 14 y group (p = 0.05). In males, Xc/H decreased (11 to 12 and 12 to 13 y groups, p = 0.001) with a higher magnitude of changes in the 13 to 14 y group (p = 0.004); R/H decreased (p = 0.001); FFM increased in all groups (p = 0.001); however, no magnitude of changes was observed. PhA increased in the 13 to 14 y group (p = 0.004). BIVA showed no differences among ellipse distances in females. In males, a high distance was observed in the 11 to 12 y group. "Time interval" influenced PhA and Xc/H in the female group and R/H and Xc/H in the male group. "Initial age" and "time interval" influenced the increase in PhA in the male group. Raw BI data and BIVA patterns can detect the magnitude of the changes in a sex-dependent manner.

Utilization of bioelectrical impedance vector analysis (BIVA) in children and adolescents without diagnosed diseases: a systematic review

Introduction. Bioelectrical impedance vector analysis (BIVA) emerges as a technique that utilizes raw parameters of bioelectrical impedance analysis and assumes the use of a reference population for information analysis.Objective. To summarize the reference values, main studies objectives, approaches, pre-test recommendations and technical characteristics of the devices employed in studies utilizing BIVA among children and adolescents without diagnosed diseases.Methods. A systematic search was conducted in nine electronic databases (CINAHL, LILACS, PubMed, SciELO, Scopus, SPORTDiscus, Science Direct, MEDLINE, and Web of Science). Studies with different designs which allowed extracting information regarding reference values of BIVA in children and adolescents without diagnosed diseases, aged 19 years or younger, were included. The systematic review followed PRISMA procedures and was registered in PROSPERO (registration: CRD42023391069).Results. After applying the eligibility criteria, 36 studies were included. Twenty studies (55.6%) analyzed body composition using BIVA, thirteen studies (36.1%) aimed to establish reference values for BIVA, and three studies (8.3%) investigated the association of physical performance with BIVA. There was heterogeneity regarding the reference populations employed by the studies. Fifteen studies used their own sample as a reference (41.6%), four studies used the adult population as a reference (11.1%), and five studies used reference values from athletes (13.9%).Conclusion. Nutricional status and body composition were the main studies objectives. References values were not always adequate or specific for the sample and population. Furthermore, there was no pattern of pre-test recommendations among the studies.

Relationship between Bioelectrical Impedance Phase Angle and Upper and Lower Limb Muscle Strength in Athletes from Several Sports: A Systematic Review with Meta-Analysis

The phase angle (PhA) of bioelectrical impedance is determined by primary factors such as age, body mass index and sex. The researchers' interest in applying PhA to better understand the skeletal muscle property and ability has grown, but the results are still heterogeneous. This systematic review with a meta-analysis aimed to examine the existence of the relationship between PhA and muscle strength in athletes. The data sources used were PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science and the study eligibility criteria were based on the PECOS. The searches identified 846 titles. From those, thirteen articles were eligible. Results showed a positive correlation between PhA and lower limb strength (r = 0.691 [95% CI 0.249 to 0.895]; p = 0.005), while no meta-analysis was possible for the relationships between PhA and lower limb strength. Furthermore, GRADE shows very low certainty of evidence. In conclusion, it was found that most studies showed a positive correlation between PhA and vertical jump or handgrip strength. The meta-analysis showed the relationship between PhA and vertical jump, however, little is known for the upper limbs as was not possible to perform a meta-analysis, and for the lower limbs we performed it with four studies and only with vertical jump.

The relationship between handgrip strength and performance scores in North American Collegiate Division I women’s artistic gymnasts

Maximal isometric handgrip strength (HGS) is used as an indicator of overall muscular strength and has also been found to be predictive of certain athletic events sporting prowess. Women’s artistic gymnastics requires athletes have high levels of relative muscular strength and power to be successful. This study examined the relationship between HGS and gymnastics performance scores for the 4 events of vault, uneven bars, beam, and floor in female collegiate artistic gymnasts. Twenty-five (n=25) female National Collegiate Athletic Association (NCAA) Division I North American collegiate women’s artistic gymnasts (age: 20.1±1.3 yrs; height: 158.9±5.6 cm; mass: 58.2±5.3 kg) were assessed for a one-time measurement of absolute HGS in kg and relative HGS (HGS/height in m2), as well as their average vault, uneven bars, beam, and floor performance scores across a competitive season. Pearson correlation coefficients (r) were determined between HGS and all performance scores. No significant (p > 0.05) correlations were found between absolute HGS (30.8±4.4 kg) or relative HGS (12.0±1.6 kg/m2) and any 4 gymnastics event’s performance scores (r range: -0.07 – 0.50 or r range: -0.06 – 0.31, respectively). In this female collegiate gymnastics’ population, 56% had an absolute HGS and 80% had a relative HGS, respectively, above the 50th percentile of all similarly aged adult females in the United States. In the current population of female collegiate gymnasts, absolute and relative HGS were not related to any gymnastics events performance scores and adds to the existing literature, supporting no relationships between HGS and sports performances where sports movements require a high degree of technical precision and accuracy. Findings from this investigation can be used by athletes, coaches, and practitioners in the collegiate women’s gymnastics realm to assess if athletes have attained sufficient absolute HGS, and especially relative HGS values, to be successful.

Age-, sex-, and maturity-associated variation in the phase angle after adjusting for size in adolescents

Background

Applied research using the phase angle (PhA) in children and adolescents has increased notably. Using multilevel modeling in a fully Bayesian framework, we examined the relationships between PhA, age, sex, biological maturity status, and body size in 10–16-year-old adolescents.

Methods

The sample comprised 519 adolescents (women, n = 241; men, n = 278) from Campinas, São Paulo, Brazil. Biological maturity status was assessed with self-examination of pubertal development for sexual maturity and maturity offset protocol to estimate age at peak height velocity (PHV) for somatic maturity status. Stature and body mass were measured by anthropometry. Phase angle was calculated based on raw resistance and reactance values (50 kHz frequency) obtained by bioelectrical impedance with the foot-to-hand technology.

Results

The multilevel regression analysis revealed that boys had significantly higher values of phase angle than girls, adjusting for age group and sexual maturity status. Overall, older and more mature adolescents had higher values of phase angle. When considering aligning variation in the phase angle by distance to estimated PHV (maturity offset), there was a higher association between the phase angle and time before and after predicted age at PHV for boys (r = 0.31, 90% CI: 0.23 to 0.39) than girls (r = 0.2, 90% CI: 0.11 to 0.28). When including body mass in the multilevel models, corresponding changes in the overall body mass mediate most of the influence of the maturity status and age group on the phase angle.

Conclusion

The present study demonstrated that the variability in phase angle is related to inter-individual variation in sex, age, and maturity status, as well as differences in body size. Research with adolescents considering phase angle should use multilevel modeling with standardized parameters as default to adjust for the concurrent influence of sex, age, maturity status, and body size.

Bioelectrical Impedance Analysis (BIA)- Derived Phase Angle in Children and Adolescents: A Systematic Review

Phase angle (PhA), a directly-measured bioelectrical impedance analysis variable, is suggested to be a proxy of body cell mass as well as extracellular/intracellular water ratio, and is related to cellular integrity and functions. The aim of this systematic review was to evaluate PhA in healthy youths in relation to sex, age, weight status, physical fitness, and sports activities. A systematic literature search (preferred reporting items for systematic reviews and meta-analyses criteria) until January 2022 was performed using PubMed, Embase, Scopus, and Web of Science regarding studies on PhA in healthy children and adolescents 4-18 years of age. Quality was assessed according to the National Institute of Health. After removing duplicates and studies not fulfilling the inclusion criteria, 22 cross-sectional and 1 longitudinal were considered appropriate. As for quality, 14 articles were rated fair and 9 good. Ten studies found that PhA increases with age: the increase was more marked after puberty, whereas changes in younger subjects are by far less defined. A clear sex difference was found in adolescents, likely due to pubertal development. Limited evidence suggests that PhA increases in participants with very high BMI. Limited data were reported on physically active youths without convincing findings. Positive associations of PhA with physical fitness and fat-free mass were found in few studies. In conclusion, partial and limited evidence suggests that changes in PhA over the first 2 decades of life reflect modification in body composition and fat-free mass composition. Further studies are needed for confirming PhA as a relevant marker of nutritional status in youths.