Accuracy of Bioelectrical Impedance Analysis in Estimated Longitudinal Fat-Free Mass Changes in Male Army Cadets

Langer, Raquel David; Matias, Catarina N.; Borges, Juliano Henrique; Cirolini, Vagner X.; Páscoa, Mauro Alexandre; Guerra‐Júnior, Gil; Gonçalves, Ezequiel Moreira

doi:10.1093/milmed/usx223

Cited by 11 publications

(12 citation statements)

References 31 publications

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“…Very few studies have previously validated the ability of a whole-body single-frequency BIA to assess changes in body composition over time, compared to DXA. Similar to our findings, previous results show high imprecision of FFM BIA to track changes at the individual level (limits of agreement of ±3e4 kg) compared to DXA, in healthy subjects during loss [22] or gain [23] in FFM. Among obese individuals during weight loss, correlation between change in FFM BIA and FFM DXA was intermediate at r ¼ 0.35, but varied greatly with DXA scanner [22].…”

Section: Discussionsupporting

confidence: 91%

Use of bioelectrical impedance analysis to monitor changes in fat-free mass during recovery from colorectal cancer– a validation study

Bärebring

Kværner

Skotnes

et al. 2020

Clinical Nutrition ESPEN

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Background & aims: Although previous research show high correlation between fat-free mass (FFM) measured by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA), the validity of BIA to track longitudinal changes in FFM is uncertain. Thus, the aim of this study was to validate the ability of BIA to assess changes in FFM during 6 months of recovery from non-metastatic colorectal cancer (CRC). Methods: A total of 136 women and men (50e80 years) with stage I-III CRC and a wide range of baseline FFM (35.7e73.5 kg) were included in the study. Body composition was measured at study baseline within 2e9 months of surgery and again 6 months later. Whole-body BIA FFM estimates (FFM BIA) were calculated using three different equations (manufacturer's, Schols' and Gray's) before comparison to FFM estimates obtained by DXA (FFM DXA). Results: Correlation between changes in FFM BIA and FFM DXA was intermediate regardless of equation (r z 0.6). The difference in change of FFM BIA was significant compared to FFM DXA , using all three equations and BIA overestimated both loss and gain. However, BIA showed 100% sensitivity and about 90% specificity to identify individuals with !5% loss in FFM, using all three equations. Sensitivity of FFM BIA to detect a smaller loss of FFM (60e76%) or a gain in FFM of !5% (33e62%) was poor. Conclusion: In a well-nourished population of non-metastatic CRC patients, a single-frequency wholebody BIA device yielded imprecise data on changes in FFM, regardless of equation. BIA is thus not a valid option for quantifying changes in FFM in individuals. However, BIA could be used to identify patients with loss in FFM !5% in this population. The validity of BIA to monitor changes in FFM warrants further investigation before implementation in clinical praxis.

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Section: Discussionsupporting

confidence: 91%

Use of bioelectrical impedance analysis to monitor changes in fat-free mass during recovery from colorectal cancer– a validation study

Bärebring

Kværner

Skotnes

et al. 2020

Clinical Nutrition ESPEN

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“…We have used BI as the method to assess the BFP in the participants which is a fast, practical, noninvasive, and widely used method. Several studies have validated the use of BI as a standard for body fat estimation [23][24]. BMI is specific for race and hence, we agree to the conclusion of researchers like Piers et al [25], who have concluded that BMI is useful and convenient for population studies but ill-applied in individuals.…”

Section: Discussionsupporting

confidence: 87%

Tailoring Body Mass Index for Prediction of Obesity in Young Adults: A Multi-Centric Study on MBBS Students of Southeast India

Behera¹,

Mishra²,

Esther³

et al. 2021

Cureus

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Introduction: Body mass index (BMI) has been used for a long period as a surrogative measure for obesity. But BMI does not differentiate between fat and nonfat tissue (blood, bone, and muscle) due to which it is not considered accurate anymore. But since BMI is easier to estimate and used widely for assessment of obesity, it is better if it is re-standardized according to the body fat percentage (BFP) of a specific population, community, and their ethnicity. Objective: To estimate and propose the BMI cut-off values in young Indian population especially MBBS students taking BFP as a standard. Design: This is a cross-sectional study. Anthropometric data (age, gender, height, weight, waist circumference, and hip circumference) were collected from the participants after taking consent. BMI was calculated using Quetelet’s Rule. BFP was estimated using Omron Body fat Monitor (HBF 385). It measures the BFP by the bioelectrical impedance (BI) method. Data were analyzed with appropriate statistical tests and receiver operating curve (ROC) curves were drawn to find the cut-off values of BMI to determine obesity. Setting: The present study is a multi-centric study conducted in four medical colleges (two in each state; Odisha and Andhra Pradesh, India). Participants: Apparently healthy MBBS students aged 18-24 years were included in this study. Students having any chronic or acute illnesses were excluded from the study. Out of 904 students contacted from four medical colleges, 863 (430 males and 433 females) consented and participated. Results: Some 863 MBBS students have participated in this study. After adjusting for age, BMI was found to be higher in males. BMI was found to be 29.33 for males and in females it was 29.06. BFP was higher in females (34.23) as compared to males (20.77). Waist hip ratio was found to be higher in females (0.92) than in males (0.84). Whereas, fat free mass (FFM) and fat free mass index (FFMI) are higher in males, i.e., 56.24 and 18.48 respectively. Most appropriate cut-off value for obesity on ROC curve was found to be 22.09 (sensitivity 84.5%, specificity 83.46%) in males and that of females was 23.73 (sensitivity 85.26, specificity 81.23). Whereas, the conventional cut-off of 25 for males had sensitivity of only 46% and that of females was 70.5%. For total population BMI cut-off value was found to be 22.2 with 81% sensitivity and 74% specificity. Conclusion: We propose the cut-off value for overweight/obesity in males to be 22.09 kg/m 2 and for females to be 23.73 kg/m 2 in young adult Indian population. These values were found to have more sensitivity and specificity than current BMI cut-off value.

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“…PhA was assessed using tetrapolar bioelectrical impedance analysis (BIA), single frequency (50 kHz), model Quantum II (RJL Systems, Detroit, MI, USA), which has been previously validated in adolescents [22]. Participants were instructed to remove all metallic objects before a BIA measurement was taken.…”

Section: Peak Height Velocity (Phv)mentioning

confidence: 99%

“…The reproducibility of the parameters provided by BIA was determined by the coefficient of variation and the technical error of measurement, based on the test-retest method as performed in 23 participants of the study population of an another study [22].…”

Section: Peak Height Velocity (Phv)mentioning

confidence: 99%

Phase Angle is Determined by Body Composition and Cardiorespiratory Fitness in Adolescents

et al. 2020

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The phase angle is used to evaluate nutritional status and is an indicator of cellular health. Cardiorespiratory fitness and body composition are strong indicators of health during adolescence. We aimed to evaluate if body composition and cardiorespiratory fitness have an association with phase angle among adolescents. 203 girls and 220 boys (12.8±1.3 years) were evaluated. Peak height velocity, percentage fat mass, fat-free mass, cardiorespiratory fitness, and phase angle measurements were collected. Linear regression adjusted by peak height velocity was used to verify if predictor variables were associated with phase angle among adolescents. Phase angle showed correlation with fat-free mass (girls: r=0.42 and boys: r=0.37); with percent fat mass (girls: r=0.23); and with cardiorespiratory fitness (boys: r=0.19). Linear regression showed that percentage fat mass (in girls) and cardiorespiratory fitness (in boys) had an effect of 11 and 17% in phase angle, respectively, while fat-free mass had an effect of 22 and 26% in phase angle for girls and boys, respectively. Changes in phase angle seem to be more associated with the percentage fat mass in girls, cardiorespiratory fitness in boys, and fat-free mass in both when controlled by peak height velocity.

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Accuracy of Bioelectrical Impedance Analysis in Estimated Longitudinal Fat-Free Mass Changes in Male Army Cadets

Cited by 11 publications

References 31 publications

Use of bioelectrical impedance analysis to monitor changes in fat-free mass during recovery from colorectal cancer– a validation study

Use of bioelectrical impedance analysis to monitor changes in fat-free mass during recovery from colorectal cancer– a validation study

Tailoring Body Mass Index for Prediction of Obesity in Young Adults: A Multi-Centric Study on MBBS Students of Southeast India

Phase Angle is Determined by Body Composition and Cardiorespiratory Fitness in Adolescents

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