Dataset Information

Prediction of fat-free mass in a multi-ethnic cohort of infants using bioelectrical impedance: Validation against the PEA POD.

ABSTRACT:

Background

Bioelectrical impedance analysis (BIA) is widely used to measure body composition but has not been adequately evaluated in infancy. Prior studies have largely been of poor quality, and few included healthy term-born offspring, so it is unclear if BIA can accurately predict body composition at this age.

Aim

This study evaluated impedance technology to predict fat-free mass (FFM) among a large multi-ethnic cohort of infants from the United Kingdom, Singapore, and New Zealand at ages 6 weeks and 6 months (n = 292 and 212, respectively).

Materials and methods

Using air displacement plethysmography (PEA POD) as the reference, two impedance approaches were evaluated: (1) empirical prediction equations; (2) Cole modeling and mixture theory prediction. Sex-specific equations were developed among ∼70% of the cohort. Equations were validated in the remaining ∼30% and in an independent University of Queensland cohort. Mixture theory estimates of FFM were validated using the entire cohort at both ages.

Results

Sex-specific equations based on weight and length explained 75-81% of FFM variance at 6 weeks but only 48-57% at 6 months. At both ages, the margin of error for these equations was 5-6% of mean FFM, as assessed by the root mean squared errors (RMSE). The stepwise addition of clinically-relevant covariates (i.e., gestational age, birthweight SDS, subscapular skinfold thickness, abdominal circumference) improved model accuracy (i.e., lowered RMSE). However, improvements in model accuracy were not consistently observed when impedance parameters (as the impedance index) were incorporated instead of length. The bioimpedance equations had mean absolute percentage errors (MAPE) < 5% when validated. Limits of agreement analyses showed that biases were low (< 100 g) and limits of agreement were narrower for bioimpedance-based than anthropometry-based equations, with no clear benefit following the addition of clinically-relevant variables. Estimates of FFM from BIS mixture theory prediction were inaccurate (MAPE 11-12%).

Conclusion

The addition of the impedance index improved the accuracy of empirical FFM predictions. However, improvements were modest, so the benefits of using bioimpedance in the field remain unclear and require further investigation. Mixture theory prediction of FFM from BIS is inaccurate in infancy and cannot be recommended.

SUBMITTER: Lyons-Reid J

PROVIDER: S-EPMC9606768 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Prediction of fat-free mass in a multi-ethnic cohort of infants using bioelectrical impedance: Validation against the PEA POD.

Lyons-Reid Jaz J Ward Leigh C LC Derraik José G B JGB Tint Mya-Thway MT Monnard Cathriona R CR Ramos Nieves Jose M JM Albert Benjamin B BB Kenealy Timothy T Godfrey Keith M KM Chan Shiao-Yng SY Cutfield Wayne S WS

Frontiers in nutrition 20221013

<h4>Background</h4>Bioelectrical impedance analysis (BIA) is widely used to measure body composition but has not been adequately evaluated in infancy. Prior studies have largely been of poor quality, and few included healthy term-born offspring, so it is unclear if BIA can accurately predict body composition at this age.<h4>Aim</h4>This study evaluated impedance technology to predict fat-free mass (FFM) among a large multi-ethnic cohort of infants from the United Kingdom, Singapore, and New Zeal ...[more]

PMID: 36313113

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Project description:BackgroundLoss of skeletal muscle mass (SMM) increases the risk of frailty and, together with excess fat mass (FM), is a risk factor for cardio-metabolic disease. However, use of body composition measurements in nutritional surveillance and routine clinical practice is limited by the lack of reference data. Our aim was to produce age-specific and sex-specific reference values for SMM and FM in the White ethnic adult population in the UK. Secondary objectives were to examine the tracking over time using a subsample of the population with repeated measures of body composition and to assess the validity of these reference values in different ethnic subgroups.MethodsWe used data from segmental bioelectrical impedance analysis (BIA) in 390 565 participants, aged 40-69 years, in the UK Biobank, and data from dual-energy X-ray absorptiometry from n = 905 participants to validate the BIA measurements. SMM was calculated as the sum of the predicted muscle mass from the limbs. The LMS method was used to produce percentile curves for the SMM index (SMMI = SMM/height2 ) and the FM index (FMI = FM/height2 ). We investigated the validity of the White ethnic reference values by plotting z-scores (99.7% confidence interval) from Black and Asian groups to check if their confidence interval included zero. Longitudinal trajectories were predicted based on the baseline z-scores and the correlation between repeated measurements at follow-up.ResultsThe percentile curves show that SMMI declines in men from the age of 40, whereas in women, SMMI is more stable and decreases only slightly among women in the higher percentiles. FMI increases with age in both men and women. Women have higher FMI and lower SMMI than men in all age groups. The validity of the White-based reference values for non-White ethnic groups is poor. Longitudinal trajectories in body composition in the subsample of participants with a follow-up assessment show regression towards the mean in both men and women, with some evidence of declining SMMI only among men. The predicted 90% limits for the expected 5 year trajectories of SMMI and FMI can be used to identify people with unusual trajectories and in clinical practice to identify and track individuals at risk of excessive loss of SMM.ConclusionsThese body composition reference values developed from BIA in a middle/older-aged healthy White ethnic population in the UK could be used as a simple assessment tool for nutritional surveillance and to identify individuals with low SMMI or high FMI who may be at increased risk of disease and/or frailty.

Project description:BackgroundThe fat-to-muscle mass ratio (FMR) might be an indicator to assess type 2 diabetes risk independent of general obesity. However, no longitudinal studies have explored the extent to which total and regional FMRs may confer risks. We aimed to measure the sex-specific associations between FMRs of the arm, leg, trunk and whole body and incident type 2 diabetes.MethodsA total of 464 817 participants (207 286 men and 257 531 women, mean age 56.5 ± 8.2 and 56.2 ± 8.0 years old, respectively) free of diabetes at baseline were included in this prospective cohort study with UK Biobank data. Fat mass and muscle mass were estimated using a bioelectrical impedance assessment device (Tanita BC 418MA). FMR was calculated as fat mass divided by muscle mass in corresponding body parts (total body, arm, leg and trunk). Cox proportional hazard models were used to estimate the aforementioned associations among men and women. Interaction analyses were performed between FMRs and body mass index (BMI) categories (BMI < 25 kg/m2 and BMI ≥ 25 kg/m2 ).ResultsOver the median 11.0 years (5 057 534 person-years) of follow-up, we documented 11 618 cases of type 2 diabetes. There was a significantly positive association between total and regional FMR and incident type 2 diabetes, even after adjusting for BMI and other covariates. Compared with other body parts, FMRs of the whole body and leg showed the strongest relationship among men and women, respectively (hazard ratio per 1 SD, 95% confidence interval: 1.67, 1.55-1.80; 1.45, 1.39-1.53). A significant interaction (P for interaction < 0.001) between BMI category and FMRs of different body parts was observed. In the stratified analysis by BMI category and tertiles of FMRs, overweight/obese individuals with a high FMR tertile tended to have the highest hazard ratio, ranging from 5.91 to 7.94 in whole body and regional areas.ConclusionsIn this large prospective study, higher total and regional FMRs were associated with a higher risk of developing type 2 diabetes, independent of BMI. This association was markedly strengthened in participants with BMI ≥ 25 kg/m2 .

Project description:BackgroundBioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.MethodsCross-sectional study of children aged 8-10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM?=?linear combination(height+weight+Z); B: FFM?=?linear combination(height(2)/Z); C: FFM?=?linear combination(height(2)/Z+weight)}.ResultsEthnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set.ConclusionsEthnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.

Project description:BACKGROUND: The measurements of body mass index (BMI) and percentage of body fat are used in many clinical situations. However, special tools are required to measure body fat. Many formulas are proposed for estimation but these use constant coefficients of age. Age spectrum might affect the predicted value of the body composition due to body component alterations, and the coefficient of age for body fat prediction might produce inconsistent results. The objective of this study was to identify variations of BMI and body fat across the age spectrum as well as compare results between BMI predicted body fat and bioelectrical impedance results on age. METHODS: Healthy volunteers were recruited for this study. Body fat was measured by bioelectrical impedance. The age spectrum was divided into three groups (younger: 18-39.9; middle: 40-59.9; and older: ≥60 years). Comparison of body composition covariates including fat mass (FM), fat free mass (FFM), percentage FM (PFM), percentage FFM (PFFM), FM index (FMI) and FFM index (FFMI) in each weight status and age spectrum were analyzed. Multivariable linear regression coefficients were calculated. Coefficient alterations among age groups were tested to confirm the effect of the age spectrum on body composition covariates. Measured PFM and calculated PFM from previous formulas were compared in each quarter of the age spectrum. RESULTS: A total of 2324 volunteers were included in this study. The overall body composition and weight status, average body weight, height, BMI, FM, FFM, and its derivatives were significantly different among age groups. The coefficient of age altered the PFM differently between younger, middle, and older groups (0.07; P = 0.02 vs 0.13; P < 0.01 vs 0.26; P < 0.01; respectively). All coefficients of age alterations in all FM- and FFM-derived variables between each age spectrum were tested, demonstrating a significant difference between the younger (<60 years) and older (≥60 years) age groups, except the PFFM to BMI ratio (difference of PFM and FMI [95% confidence interval]: 17.8 [12.8-22.8], P < 0.01; and 4.58 [3.4-5.8], P < 0.01; respectively). The comparison between measured PFM and calculated PFM demonstrated a significant difference with increments of age. CONCLUSION: The relationship between body FM and BMI varies on the age spectrum. A calculated formula in older people might be distorted with the utilization of constant coefficients.

Dataset Information

Prediction of fat-free mass in a multi-ethnic cohort of infants using bioelectrical impedance: Validation against the PEA POD.

Background

Aim

Materials and methods

Results

Conclusion

Publications

Prediction of fat-free mass in a multi-ethnic cohort of infants using bioelectrical impedance: Validation against the PEA POD.

Similar Datasets

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