Human body composition: yesterday, today, and tomorrow

The Critical Role of Body Composition Assessment in Advancing Research and Clinical Health Risk Assessment across the Lifespan

Obesity and low muscle mass are major public health concerns, especially in older adults, due to their strong links to cardiovascular disease, cancer, and mortality. Beyond body mass index, body composition metrics including skeletal muscle, fat mass, and visceral adipose tissue offer deeper insights into nutrition and disease risk. These measures are essential for both cross-sectional assessments and longitudinal tracking, providing a clearer picture of health changes over time. Selecting body composition assessment tools requires balancing cost, practicality, accuracy, and data quality. The right tools enhance research, refine clinical assessments, and inform targeted interventions. Aligning methods with specific research or clinical goals improves disease risk stratification and advances personalized treatments. This review highlights the importance of integrating body composition assessment into research and clinical practice, addressing knowledge gaps across diverse populations and emphasizing its potential in advancing precision medicine. It also highlights recent advancements in body composition assessment techniques that warrant consideration when evaluating techniques for a specific application. Future efforts should focus on refining these tools, expanding their accessibility, and developing comprehensive risk models that incorporate body composition alongside behavioral, environmental, and genetic factors to improve disease prediction and prevention strategies.

Investigating the impact of body composition on the estimation of resting metabolic rate: new equations for adults aged ≥65 years developed using cross-sectional data

BACKGROUND

Due to changes in body composition during aging, the inclusion of body composition measures as a variable within equations to predict resting metabolic rate (RMR) may improve their predictive accuracy.

OBJECTIVES

This analysis of cross-sectional data aimed to develop and validate new RMR equations for older adults (≥65 y) incorporating variables for body composition, to predict performance and accuracy, and to explore the relative contribution of body composition variables acting directly or potentially via fat-free mass (FFM) to RMR.

METHODS

Analyses were conducted utilizing a unique international dataset of gold standard measures developed for this purpose. RMR was predicted from potential predictive variables using stepwise multiple regression. Predictive performance of the final model was assessed using double cross-validation. The new prediction equation was compared with published prediction equations for similar populations and with previously published RMR prediction equations that did not include FFM. Direct associations between the determined predictor variables and RMR with indirect effects mediated via FFM were examined using mediation final (or pathway) analysis.

RESULTS

The dataset contained 1238 participants. The predictive equations {utilizing either FFM (Equation 1) or lean body weight [LBW](Equation 2)} follow. Equation 1: RMR = 8.645 × height + 23.684 × weight - 29.717 × age + 38.213 × FFM + 209.637 × sex + 2693.223; Equation 2: RMR = -30.570 × age + 80.736 × LBW - 186.825 × sex + 3956.822 where RMR (kJ/d); height (cm); weight (kg); age (y); FFM (kg); LBW (kg); sex (M = 1, F = 0). The equation performed similarly to some anthropometric-based prediction equations. Predictors using FFM performed marginally better than those using LBW. All variables had significant (P < 0.001) direct effects upon RMR and significant (P < 0.001) indirect effects for sex, weight, and height.

CONCLUSIONS

New prediction equations predict RMR at the population level with minimal bias; however, the difference in performance with anthropometry-based equations is minimal. This may be explained by the contribution of FFM to weight, whereby equations that include weight are already accounting for FFM.

The Shape of Success: A Scoping Review of Somatotype in Modern Elite Athletes Across Various Sports

This scoping review aimed to determine the somatotype of modern elite athletes across various sports. The literature search followed the PRISMA guidelines for scoping reviews. Four databases were consulted, PubMed, Scopus, Web of Science, and Clarivate InCites, as well as platforms such as Google Scholar, Taylor & Francis Online, Books Ovid, CAB eBooks, MyiLibrary, and Core Collection. Eligibility criteria included articles published between 1995 and 2024 involving athletes at the elite level, such as junior, senior, Olympic, first-division professionals, world-class competitors, national competitors, black belts, master athletes, non-professional athletes with at least 10 years of experience, those ranked in the national or international top 10, and high-level collegiate athletes. A total of 66 studies were included. Modern male elite athletes predominantly exhibited an endomorphic mesomorphic somatotype, whereas female athletes were classified as central. The present study was the first to synthesize data from 66 articles, encompassing athletes of varying elite levels, both males and females, while providing detailed information on age, weight, height, BMI, somatotype and its classification, and complemented by somatoplot references. Future research is recommended to include a greater diversity of sports and a more significant number of elite female athletes to enhance the representativeness of elite athletes.

Increased adiposity in juvenile idiopathic arthritis - A comparison of the bioelectrical impedance analysis and dual-energy X-ray absorptiometry for the assessment of body composition

AIM

Higher adiposity and increased risk of cardiovascular diseases have been reported in juvenile idiopathic arthritis (JIA), but body composition measurements have produced inconsistent results. This controlled cross-sectional study assessed body composition with two methods to evaluate adiposity in children with JIA.

METHODS

We measured body composition by dual- energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) from 79 JIA-patients in two Finish university hospitals in 2017-2019. Their age- and sex-matched controls (n = 79) were selected from the Physical Activity and Nutrition in Children- study and through National Registry.

RESULTS

Body fat percentage measured by BIA was higher (mean, SD) in patients compared to controls (23.1 ± 9.3% vs. 20.1 ± 7.5%, p = 0.047). Also, using DXA, there was a tendency of higher body fat percentage in patients (27.1 ± 9.1% vs. 24.6 ± 8.6, p = 0.106). BIA and DXA showed strong correlation (r from 0.810 to 0.977) in all body composition variables.

CONCLUSION

Increased adiposity was observed in patients with JIA. Evaluation of body composition should be included in the multidisciplinary care of JIA to reduce the possible risk of cardiovascular diseases in adulthood. BIA could be a useful tool for assessing body composition due to its clinical availability and safety.

Development of a bioelectrical impedance analysis-based prediction equation for body composition of rural children aged 4-8 years in Myanmar

Background: Reliable and accurate estimates of body composition are essential when studying the various health correlates of disease. Bioelectrical impedance analysis (BIA) is an affordable and feasible body composition assessment technique for clinical and field settings. Total body water (TBW) and hence fat-free mass is estimated by predictive regression algorithms using anthropometric measurements plus the resistance index. Aim: The study aimed to develop a BIA prediction equation for TBW in children in Myanmar using the deuterium dilution technique as the reference method. Methods: The study design was cross-sectional in a school setting with convenience sampling of participants. One hundred and two healthy children (57 boys and 45 girls) with aged 4 and 8 years participated; randomly divided into the prediction group (29 boys and 22 girls) and cross-validation group (28 boys and 23 girls). Whole-body impedance, anthropometric and TBW (by D2O dilution) measurements. The prediction equation was cross-validated using a split-group design and compared to published equations for contemporaneous populations. Results: TBW could be predicted by the following equation. TBW = 0.4597 * Weight (kg) + 0.1564 * Impedance index + 0.6075 (R2 = 0.891, P < 0.0001) with a correlation coefficient of 0.942 and limits of agreement of 0.98 kg TBW on cross-validation. Conclusions: This equation can be used to predict body composition in young (aged 4-8 years) children in Myanmar but because the age range of the participants in the present study was relatively narrow, more research in different age groups is required to establish its broader applicability.

Bioelectrical impedance analysis as a clinical marker of health status in adult patients with benign gastrointestinal disease: A systematic review

BACKGROUND

Body composition reflects nutritional status, disease status and progression, and treatment responses. Mounting evidence supports the use of bioelectrical impedance analysis (BIA) as a non-invasive tool to assess body composition. Patients with benign gastrointestinal (GI) disease experience disease-related alterations in their body composition, and bioimpedance outcomes in patients with benign GI diseases have not previously been summarized. We aimed to evaluate BIA as a clinical body composition marker for benign GI diseases and describe its association with physical health status.

METHODS

We systematically searched PubMed, Scopus, Web of Science, Embase, and CINAHL from inception to October 2023 (PROSPERO registration: CRD42021265866). Of 971 screened studies, 26 studies were included in the final analysis, comprising a total of 2398 adult patients with benign GI disease. The main outcome was raw impedance data.

RESULTS

The most frequently reported BIA outcome was phase angle (PhA) (reported in 18 of 26 studies), followed by fat-free-mass (FFM) (reported in 13 of 26 studies). The consensus view of the included studies illustrates that BIA can be a useful tool for evaluating body composition in patients with benign GI diseases, and low PhA and FFM were associated with increased nutritional risk, abnormal physical characteristics, and increased mortality risk.

CONCLUSION

To fully utilize BIA as a clinical marker of health in patients with benign GI disease, standardized protocols specific to this population are needed and prospective studies testing cut-offs and ranges, accuracy, and other raw BIA parameters for classifying disease status.

Improved Physical Health in Middle-Older Aged Golf Caddies Following 24 Weeks of High-Volume Physical Activity

BACKGROUND

The physical demands of golf caddying, including walking while carrying a golf bag, may potentially affect body composition, and markers of metabolic, cardiovascular, and musculoskeletal health. Therefore, this study examined the impact of 24 weeks of caddying on physical health in middle-older aged males.

METHODS

Eleven full-time experienced male caddies (age: 59 [8] y; caddying experience: 14 [12] y) were recruited from a local golf course. The following were assessed at preseason and after 24 weeks of caddying (March-September 2022): body composition, heart rate, blood pressure, blood lipids, and performance tests (static and dynamic balance, strength, and submaximal fitness). Physical activity (PA) levels were assessed at preseason and at the mid-point of the caddying season. Across the caddying season, participants completed a monthly average of 24.0 (3.8) rounds.

RESULTS

Following the caddying season, improvements in static balance (Δ = 13.5 s), dynamic balance (Δ = -1.8 s), and lower back absolute strength (Δ = 112.8 N), and muscle quality (Δ = 2.0 N·kg-1) were observed (all P < .05). Additionally, blood lipids, including total cholesterol (Δ = -0.6 mmol·L-1), high-density lipoprotein cholesterol (Δ = 0.1 mmol·L-1), low-density lipoprotein cholesterol (Δ = -0.6 mmol·L-1) (all P < .05), and body composition, including body mass (Δ = -2.7 kg), fat mass (Δ = -1.9 kg), fat percentage (Δ = -1.4%), fat-to-muscle ratio (Δ = -0.03), and body mass index (Δ = -0.9 kg·m-2) (all P < .05) improved. Caddying did not offer beneficial changes to cardiovascular variables or cardiorespiratory fitness (P > .05), while coronary heart disease risk score decreased (Δ = -3.3%) (P < .05). In relation to PA, light- (Δ = 145 min) and moderate-intensity (Δ = 71 min) PA, moderate to vigorous PA (Δ = 73 min), and total PA (Δ = 218 min) between preseason and the mid-point of the caddying season increased, while sedentary time (Δ = -172 min) decreased (all P < .05).

CONCLUSION

Golf caddying can provide several physical health benefits such as improvements in various markers of cardiometabolic health, lower back absolute strength, and static and dynamic balance. The physical health improvements that caddying offers is likely contributed to by increased PA volume and intensity through walking on the golf course. Therefore, caddying may represent a feasible model for increasing PA volume and intensity and achieve physical health-related benefits.

Associations between body composition profile and hypertension in different fatty liver phenotypes

Background

It is currently unclear whether and how the association between body composition and hypertension varies based on the presence and severity of fatty liver disease (FLD).

Methods

FLD was diagnosed using ultrasonography among 6,358 participants. The association between body composition and hypertension was analyzed separately in the whole population, as well as in subgroups of non-FLD, mild FLD, and moderate/severe FLD populations, respectively. The mediation effect of FLD in their association was explored.

Results

Fat-related anthropometric measurements and lipid metabolism indicators were positively associated with hypertension in both the whole population and the non-FLD subgroup. The strength of this association was slightly reduced in the mild FLD subgroup. Notably, only waist-to-hip ratio and waist-to-height ratio showed significant associations with hypertension in the moderate/severe FLD subgroup. Furthermore, FLD accounted for 17.26% to 38.90% of the association between multiple body composition indicators and the risk of hypertension.

Conclusions

The association between body composition and hypertension becomes gradually weaker as FLD becomes more severe. FLD plays a significant mediating role in their association.

Early life predictors of body composition trajectories from adolescence to mid-adulthood

OBJECTIVES

Guatemala has experienced rapid increases in adult obesity. We characterized body composition trajectories from adolescence to mid-adulthood and determined the predictive role of parental characteristics, early life factors, and a nutrition intervention.

METHODS

One thousand three hundred and sixty-four individuals who participated as children in a nutrition trial (1969-1977) were followed prospectively. Body composition characterized as body mass index (BMI), fat mass index (FMI), and fat-free mass indices (FFMI), was available at four ages between 10 and 55 years. We applied latent class growth analysis to derive sex-specific body composition trajectories. We estimated associations between parental (age, height, schooling) and self-characteristics (birth order, socioeconomic status, schooling, and exposure to a nutrition supplement) with body composition trajectories.

RESULTS

In women, we identified two latent classes of FMI (low: 79.6%; high: 20.4%) and BMI (low: 73.0%; high: 27.0%), and three of FFMI (low: 20.2%; middle: 55.9%; high: 23.9%). In men, we identified two latent classes of FMI (low: 79.6%; high: 20.4%) and FFMI (low: 62.4%; high: 37.6%), and three of BMI (low: 43.1%; middle: 46.9%; high: 10.0%). Among women, self's schooling attainment inversely predicted FMI (OR [being in a high latent class]: 0.91, 95% CI: 0.85, 0.97), and maternal schooling positively predicted FFMI (OR: 1.16, 95% CI: 0.97, 1.39). Among men, maternal schooling, paternal age, and self's schooling attainment positively predicted FMI. Maternal schooling positively predicted FFMI, whereas maternal age and paternal schooling were inverse predictors. The nutrition intervention did not predict body composition class membership.

CONCLUSIONS

Parents' age and schooling, and self's schooling attainment are small but significant predictors of adult body composition trajectories.

Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity

BACKGROUND

The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown.

OBJECTIVES

This study aimed to evaluate 3DO's accuracy and precision by subgroups of age, body mass index, and ethnicity.

METHODS

A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test-retest precision. Student's t tests were performed between 3DO and DXA by subgroup to determine significant differences.

RESULTS

Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038).

CONCLUSIONS

A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).

The Significance of Dual-Energy X-ray Absorptiometry (DXA) Examination in Cushing's Syndrome-A Systematic Review

In recent years, the usefulness of dual-energy X-ray absorptiometry (DXA) as a valuable complementary method of assessing the content and distribution of adipose and lean tissue as well as bone mineral density and estimating the risk of fractures has been increasingly confirmed. The diagnosis and treatment of Cushing's syndrome remain challenging, and monitoring the effects of treatment is often necessary. DXA tests offer a potential solution to many problems related to the availability of a quick, detailed, and reliable analysis of changes in the content and distribution of individual body composition components. The article discusses total body DXA scans (FMI, VAT, ALMI), lumbar spine scans (VFA, TBS), and osteoporosis scans (BMD, T-score, Z-score)-all are of potential interest in Cushing's syndrome. The article discusses the use of the most important indicators obtained from a DXA test (FMI, VAT, ALMI, BMD, T-score, Z-score, VFA, TBS) and their clinical significance in Cushing's syndrome was verified. The literature from the last decade was used for the study, available in MEDLINE, Web of Science, and ScienceDirect.

Growth patterns in childhood and adolescence and adult body composition: a pooled analysis of birth cohort studies from five low and middle-income countries (COHORTS collaboration)

OBJECTIVE

We examined associations among serial measures of linear growth and relative weight with adult body composition.

DESIGN

Secondary data analysis of prospective birth cohort studies.

SETTINGS

Six birth cohorts from Brazil, Guatemala, India, the Philippines and South Africa.

PARTICIPANTS

4173 individuals followed from birth to ages 22-46 years with complete and valid weight and height at birth, infancy, childhood and adolescence, and body composition in adult life.

EXPOSURES

Birth weight and conditional size (standardised residuals of height representing linear growth and of relative weight representing weight increments independent of linear size) in infancy, childhood and adolescence.

PRIMARY OUTCOME MEASURES

Body mass index, fat mass index (FMI), fat-free mass index (FFMI), fat mass/fat-free mass ratio (FM/FFM), and waist circumference in young and mid-adulthood.

RESULTS

In pooled analyses, a higher birth weight and relative weight gains in infancy, childhood and adolescence were positively associated with all adult outcomes. Relative weight gains in childhood and adolescence were the strongest predictors of adult body composition (β (95% CI) among men: FMI (childhood: 0.41 (0.26 to 0.55); adolescence: 0.39 (0.27 to 0.50)), FFMI (childhood: 0.50 (0.34 to 0.66); adolescence: 0.43 (0.32 to 0.55)), FM/FFM (childhood: 0.31 (0.16 to 0.47); adolescence: 0.31 (0.19 to 0.43))). Among women, similar patterns were observed, but, effect sizes in adolescence were slightly stronger than in childhood. Conditional height in infancy was positively associated with FMI (men: 0.08 (0.03 to 0.14); women: 0.11 (0.07 to 0.16)). Conditional height in childhood was positively but weakly associated with women's adiposity. Site-specific and sex-stratified analyses showed consistency in the direction of estimates, although there were differences in their magnitude.

CONCLUSIONS

Prenatal and postnatal relative weight gains were positive predictors of larger body size and increased adiposity in adulthood. A faster linear growth in infancy was a significant but weak predictor of higher adult adiposity.

Agreement between mechanical and digital skinfold callipers

Background: Skinfold callipers are often used in clinical practice to estimate subcutaneous adipose tissue thickness. Recently, LipoTool emerged as a potential digital system to measure skinfolds, however comparisons with competing equipment are lacking. Aim: The aim of this study was to test the agreement between two competing skinfold callipers (digital and mechanical). Methods: The sample included 22 healthy male adult participants. A certified observer measured eight skinfolds twice using different skinfold callipers (digital and mechanical). Differences between equipment were tested using Wilcoxon signed rank test The distribution of error was examined using the normality test Results: Differences between skinfold callipers were significantly in five skinfolds: triceps (Z  =  -3.546; P < 0.001), subscapular (Z  =  -3.984; P < 0.001), suprailiac (Z  =  3.024; P  =  0.002), supraspinale (Z  =  3.885; P < 0.001), abdominal (Z z = -2.937; P  =  0.003), thigh (Z  =  -2.224; P  =  0.026) and calf (Z  =  -2.052; P  =  0.040). Differences between callipers were constant. Conclusions: Mechanical and digital callipers tended to record different values of skinfold thickness. Clinical examination should consider equipment-related variation in fat mass estimation.

Field-based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning

Loss of adipose tissue in vertebrate wildlife species is indicative of decreased nutritional and health status and is linked to environmental stress and diseases. Body condition indices (BCI) are commonly used in ecological studies to estimate adipose tissue mass across wildlife populations. However, these indices have poor predictive power, which poses the need for quantitative methods for improved population assessments. Here, we calibrate bioelectrical impedance spectroscopy (BIS) as an alternative approach for assessing the nutritional status of vertebrate wildlife in ecological studies. BIS is a portable technology that can estimate body composition from measurements of body impedance and is widely used in humans. BIS is a predictive technique that requires calibration using a reference body composition method. Using sea turtles as model organisms, we propose a calibration protocol using computed tomography (CT) scans, with the prediction equation being: adipose tissue mass (kg) = body mass - (-0.03 [intercept] - 0.29 * length2/resistance at 50 kHz + 1.07 * body mass - 0.11 * time after capture). CT imaging allows for the quantification of body fat. However, processing the images manually is prohibitive due to the extensive time requirement. Using a form of artificial intelligence (AI), we trained a computer model to identify and quantify nonadipose tissue from the CT images, and adipose tissue was determined by the difference in body mass. This process enabled estimating adipose tissue mass from bioelectrical impedance measurements. The predictive performance of the model was built on 2/3 samples and tested against 1/3 samples. Prediction of adipose tissue percentage had greater accuracy when including impedance parameters (mean bias = 0.11%-0.61%) as predictor variables, compared with using body mass alone (mean bias = 6.35%). Our standardized BIS protocol improves on conventional body composition assessment methods (e.g., BCI) by quantifying adipose tissue mass. The protocol can be applied to other species for the validation of BIS and to provide robust information on the nutritional and health status of wildlife, which, in turn, can be used to inform conservation decisions at the management level.

Influence of Upper-Extremity and Lower-Extremity Resistance Exercise on Segmental Body Composition and Body Fluid Estimates

ABSTRACT

Rodriguez, C, Florez, CM, Prather, J, Zaragoza, J, Tinnin, M, Brennan, KL, Taylor, L, and Tinsley, GM. Influence of upper-extremity and lower-extremity resistance exercise on segmental body composition and body fluid estimates. J Strength Cond Res XX(X): 000-000, 2022-The purpose of this analysis was to determine if acute, localized resistance exercise (RE) artificially influences total and regional estimates of body composition from dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). Recreationally active male (n = 14) and female (n = 18) subjects completed 3 testing visits: rest (R), upper-extremity RE (U), and lower-extremity RE (L). Dual-energy X-ray absorptiometry scans were completed before exercise and 60 minutes after exercise. Bioelectrical impedance analysis was completed immediately before and after exercise and at 15, 30, and 60 minutes after exercise. Subjects were not allowed to intake fluid during the exercise session or during the postexercise assessment period. The effects of the acute RE session on DXA and BIA estimates were analyzed using linear mixed-effects models with a random intercept for subject. Condition by time interactions were observed for most BIA outcomes. Relative to the reference model (i.e., R condition at baseline), total body water and fat-free mass estimates were, on average, approximately 1 and approximately 1.2 kg higher, in the U condition. In contrast, lower-extremity RE exerted little or no impact on most BIA variables. Some DXA estimates exhibited time main effects, but the magnitude of changes was negligible. An acute bout of localized RE, particularly upper-extremity RE, can artificially influence BIA body fluid and composition estimates, whereas DXA may be robust to the acute biological error introduced by RE. Although body composition assessments should ideally be conducted under standardized conditions, DXA may be suitable in less standardized situations. In addition, BIA is differentially influenced by upper-extremity and lower-extremity resistance exercise.

Official Position of the Brazilian Association of Bone Assessment and Metabolism (ABRASSO) on the evaluation of body composition by densitometry-part II (clinical aspects): interpretation, reporting, and special situations

OBJECTIVE

To present an updated and evidence-based guideline for the use of dual-energy x-ray absorptiometry (DXA) to assess body composition in clinical practice.

MATERIALS AND METHODS

This Official Position was developed by the Scientific Committee of the Brazilian Association of Bone Assessment and Metabolism (Associação Brasileira de Avaliação Óssea e Osteometabolismo, ABRASSO) and experts in the field who were invited to contribute to the preparation of this document. The authors searched current databases for relevant publications in the area of body composition assessment. In this second part of the Official Position, the authors discuss the interpretation and reporting of body composition parameters assessed by DXA and the use of DXA for body composition evaluation in special situations, including evaluation of children, persons with HIV, and animals.

CONCLUSION

This document offers recommendations for the use of DXA in body composition evaluation, including indications, interpretation, and applications, to serve as a guiding tool in clinical practice and research for health care professionals in Brazil.

Commercial Devices Provide Estimates of Energy Balance with Varying Degrees of Validity in Free-Living Adults

BACKGROUND

The challenges of accurate estimation of energy intake (EI) are well-documented, with self-reported values 12%-20% below expected values. New approaches rely on gold-standard assessments of the other components of energy balance, energy expenditure (EE) and energy storage (ES), to estimate EI.

OBJECTIVES

The purpose of this study was to evaluate the validity, repeatability, and measurement error of consumer devices when estimating energy balance in a free-living population.

METHODS

Twenty-four healthy adults (14 women, 10 men; mean ± SD age: 30.7 ± 8.2 y) completed two 14-d assessment periods, including assessments of EE and ES using gold-standard [doubly labeled water (DLW) and DXA] and commercial devices [Fitbit Alta HR activity monitor (Alta) and Fitbit Aria wireless body composition scale (Aria)], and of EI by dietician-administered recalls. Accuracy and validity were assessed using Spearman correlation, interclass correlation, mean absolute percentage error, and equivalency testing. We also applied linear measurement error modeling including error in gold-standard devices and within-subject repeated-measures design to calibrate consumer devices and quantify error.

RESULTS

There was moderate to strong agreement for EE between the Fitbit Alta and DLW at each time point (rs = 0.82 and 0.66 for Times 1 and 2, respectively). There was weak agreement for ES between the Fitbit Aria and DXA (rs = 0.15 and 0.49 for Times 1 and 2, respectively). Correlations between methods to assess EI ranged from weak to strong, with agreement between the DXA/DLW-calculated EI and dietary recalls being the highest (rs = 0.63 for Time 1 and 0.73 for Time 2). Only EE from the Fitbit Alta at Time 1 was equivalent to the DLW value using equivalency testing.

CONCLUSIONS

Commercial devices provide estimates of energy balance in free-living adults with varying degrees of validity compared to gold-standard techniques. EE estimates were the most robust overall, whereas ES estimates were generally poor.

Whole-body Composition Profiling Using a Deep Learning Algorithm: Influence of Different Acquisition Parameters on Algorithm Performance and Robustness

OBJECTIVES

To develop, test, and validate a body composition profiling algorithm for automated segmentation of body compartments in whole-body magnetic resonance imaging (wbMRI) and to investigate the influence of different acquisition parameters on performance and robustness.

MATERIALS AND METHODS

A segmentation algorithm for subcutaneous and visceral adipose tissue (SCAT and VAT) and total muscle mass (TMM) was designed using a deep learning U-net architecture convolutional neuronal network. Twenty clinical wbMRI scans were manually segmented and used as training, validation, and test datasets. Segmentation performance was then tested on different data, including different magnetic resonance imaging protocols and scanners with and without use of contrast media. Test-retest reliability on 2 consecutive scans of 16 healthy volunteers each as well as impact of parameters slice thickness, matrix resolution, and different coil settings were investigated. Sorensen-Dice coefficient (DSC) was used to measure the algorithms' performance with manual segmentations as reference standards. Test-retest reliability and parameter effects were investigated comparing respective compartment volumes. Abdominal volumes were compared with published normative values.

RESULTS

Algorithm performance measured by DSC was 0.93 (SCAT) to 0.77 (VAT) using the test dataset. Dependent from the respective compartment, similar or slightly reduced performance was seen for other scanners and scan protocols (DSC ranging from 0.69-0.72 for VAT to 0.83-0.91 for SCAT). No significant differences in body composition profiling was seen on repetitive volunteer scans (P = 0.88-1) or after variation of protocol parameters (P = 0.07-1).

CONCLUSIONS

Body composition profiling from wbMRI by using a deep learning-based convolutional neuronal network algorithm for automated segmentation of body compartments is generally possible. First results indicate that robust and reproducible segmentations equally accurate to a manual expert may be expected also for a range of different acquisition parameters.

Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

BACKGROUND

The accurate assessment of total body and regional body circumferences, volumes, and compositions are critical to monitor physical activity and dietary interventions, as well as accurate disease classifications including obesity, metabolic syndrome, sarcopenia, and lymphedema. We assessed body composition and anthropometry estimates provided by a commercial 3-dimensional optical (3DO) imaging system compared to criterion measures.

METHODS

Participants of the Shape Up! Adults study were recruited for similar sized stratifications by sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and across five ethnicities (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander). All participants received manual anthropometry assessments, duplicate whole-body 3DO (Styku S100), and dual-energy X-ray absorptiometry (DXA) scans. 3DO estimates provided by the manufacturer for anthropometry and body composition were compared to the criterion measures using concordance correlation coefficient (CCC) and Bland-Altman analysis. Test-retest precision was assessed by root mean square error (RMSE) and coefficient of variation.

RESULTS

A total of 188 (102 female) participants were included. The overall fat free mass (FFM) as measured by DXA (54.1 ± 15.2 kg) and 3DO (55.3 ± 15.0 kg) showed a small mean difference of 1.2 ± 3.4 kg (95% limits of agreement -7.0 to +5.6) and the CCC was 0.97 (95% CI: 0.96-0.98). The CCC for FM was 0.95 (95% CI: 0.94-0.97) and the mean difference of 1.3 ± 3.4 kg (95% CI: -5.5 to +8.1) reflected the difference in FFM measures. 3DO anthropometry and body composition measurements showed high test-retest precision for whole body volume (1.1 L), fat mass (0.41 kg), percent fat (0.60%), arm and leg volumes, (0.11 and 0.21 L, respectively), and waist and hip circumferences (all <0.60 cm). No group differences were observed when stratified by body mass index, sex, or race/ethnicity.

CONCLUSIONS

The anthropometric and body composition estimates provided by the 3DO scanner are precise and accurate to criterion methods if offsets are considered. This method offers a rapid, broadly available, and automated method of body composition assessment regardless of body size. Further studies are recommended to examine the relationship between measurements obtained by 3DO scans and metabolic health in healthy and clinical populations.

Comparison of Anthropometry, Bioelectrical Impedance, and Dual-energy X-ray Absorptiometry for Body Composition in Cirrhosis

Background & aims

This study was planned to evaluate triceps skinfold thickness (TSFT), mid-arm muscle circumference (MAMC) and bioelectrical impedance analysis (BIA) for assessing body composition using dual-energy X-ray absorptiometry (DEXA) (reference) and to predict fat mass (FM) and fat-free mass (FFM) in patients with cirrhosis.

Methods

FM and FFM were assessed by using DEXA and BIA. Skin-fold calliper was used for measuring TSFT, and MAMC was calculated. Bland-Altman plot was used to determine agreement and linear regression analysis for obtaining equations to predict FM and FFM.

Results

Patients with cirrhosis (n = 302, 241 male, age 43.7 ± 12.0 years) were included. Bland-Altman plot showed very good agreement between BIA and DEXA for the estimation of FM and FFM. Majority of patients were within the limit of agreement: FM (98%) and FFM (96.4%). BIA shows a positive correlation with DEXA:FM (r = 0.73, P ≤ 0.001) and FFM (r = 0.86, P ≤ 0.001). DEXA (FM and FFM) shows a positive correlation with TSFT (r = 0.69, P ≤ 0.01) and MAMC (r = 0.61, P ≤ 0.01). The mean difference between the observed and predicted value of FM and FFM by BIA in the developmental set was 0.01 and 0.05, respectively; whereas in the validation set, it was -0.13 and 0.86, respectively. The mean difference between the observed and predicted value of TSFT and MAMC in the developmental set was 0.43 and 0.07; whereas, in the validation set, it was 0.16 and 0.48, respectively.

Conclusion

Anthropometry (TSFT and MAMC) and BIA are simple and easy to use and can be a substitute of DEXA for FM and FFM assessment in routine clinical settings in patients with cirrhosis.

Body composition in patients with rheumatoid arthritis: a narrative literature review

There is growing interest in the alterations in body composition (BC) that accompany rheumatoid arthritis (RA). The purpose of this review is to (i) investigate how BC is currently measured in RA patients, (ii) describe alterations in body composition in RA patients and (iii) evaluate the effect on nutrition, physical training, and treatments; that is, corticosteroids and biologic Disease Modifying Anti-Rheumatic Disease (bDMARDs), on BC in RA patients. The primary-source literature for this review was acquired using PubMed, Scopus and Cochrane database searches for articles published up to March 2021. The Medical Subject Headings (MeSH) terms used were 'Arthritis, Rheumatoid', 'body composition', 'sarcopenia', 'obesity', 'cachexia', 'Absorptiometry, Photon' and 'Electric Impedance'. The titles and abstracts of all articles were reviewed for relevant subjects. Whole-BC measurements were usually performed using dual energy x-ray absorptiometry (DXA) to quantify lean- and fat-mass parameters. In RA patients, lean mass is lower and adiposity is higher than in healthy controls, both in men and women. The prevalence of abnormal BC conditions such as overfat, sarcopenia and sarcopenic obesity is significantly higher in RA patients than in healthy controls; these alterations in BC are observed even at an early stage of the disease. Data on the effect treatments on BC in RA patients are scarce. In the few studies published, (a) creatine supplementation and progressive resistance training induce a slight and temporary increase in lean mass, (b) exposure to corticosteroids induces a gain in fat mass and (c) tumour necrosis factor alpha (TNFα) inhibitors might be associated with a gain in fat mass, while tocilizumab might be associated with a gain in lean mass. The available data clearly demonstrate that alterations in BC occur in RA patients, but data on the effect of treatments, especially bDMARDs, are inconsistent and further studies are needed in this area.

New bioelectrical impedance analysis equations for children and adolescents based on the deuterium dilution technique

BACKGROUND AND AIMS

Body composition in childhood is not only a marker of the prevalence of obesity, but it can also be used to assess associated metabolic complications. Bioelectrical impedance analysis (BIA) shows promise as an easy to use, rapid, and non-invasive tool to evaluate body composition. The objectives of this study were to: (a) develop BIA prediction equations to estimate total body water (TBW) and fat-free mass (FFM) in European children and early adolescents and to validate the analysis with the deuterium dilution as the reference technique and (b) compare our results with previously published paediatric BIA equations.

METHODS

The cohort included 266 healthy children and adolescents between 7 and 14 years of age, 46% girls, in five European countries: Bosnia and Herzegovina, Latvia, Montenegro, North Macedonia, and Portugal. TBW and FFM were the target variables in the developed regression models. For model development, the dataset was randomly split into training and test sets, in 70:30 ratio, respectively. Model tuning was performed with 10-fold cross-validation that confirmed the unbiased estimate of its performance. The final regression models were retrained on the whole dataset.

RESULTS

Cross-validated regression models were developed using resistance index, weight, and sex as the optimal predictors. The new prediction equations explained 87% variability in both TBW and FFM. Limits of agreement between BIA and reference values, were within ±17% of the mean, (-3.4, 3.7) and (-4.5, 4.8) kg for TBW and FFM, respectively. BIA FFM and TBW estimates were within one standard deviation for approximately 83% of the children. BIA prediction equations underestimated TBW and FFM by 0.2 kg and 0.1 kg respectively with no proportional bias and comparable accuracy among different BMI-for-age subgroups. Comparison with predictive equations from published studies revealed varying discrepancy rates with the deuterium dilution measurements, with only two being equivalent to the equations developed in this study.

CONCLUSIONS

The small difference between deuterium dilution and BIA measurements validated by Bland-Altman analysis, supports the application of BIA for epidemiological studies in European children using the developed equations.

A Cohort Study Assessing the Association Between Body Composition Parameters and Symptomatic Hypocalcemia After Total Thyroidectomy

BACKGROUND

Postoperative hypocalcemia is one of the major concerns following thyroidectomy and the most frequent cause of prolonged hospital stay. The aim of this study was to evaluate the relationship between body composition parameters and symptomatic hypocalcemia following total thyroidectomy. In addition, the effects of disease- and patient-related factors on hypocalcemia were investigated.

METHODS

A total of 144 patients were prospectively included between March 2014 and September 2017. Patients were divided into 2 groups according to the presence or absence of clinical symptoms of hypocalcemia. Subsequently, the relationship between body composition parameters and hypocalcemia was evaluated.

RESULTS

Postoperative hypocalcemia-related symptoms occurred in 28 patients (19.4%). Permanent hypocalcemia was not encountered in any patient. Patients with hypocalcemic symptoms were more likely to have nodules ≥40 mm (39.3% vs. 17.2%, P = .011), retrosternal goiters (25.0% vs. 7.8%, P = .017), central lymph node dissection (LND) (32.1% vs. 11.2%, P = .015), and parathyroid autotransplantation (28.6% vs. 3.4%, P < .001) than those without symptoms. However, no differences were observed in the body composition parameters between symptomatic and asymptomatic patients. On multivariate analysis, lower preoperative intact parathyroid hormone (iPTH) levels (odds ratios (ORs) .96, 95% confidence intervals (CIs) .93-.99), the presence of retrosternal goiters (OR 10.26, 95% CI 2.23-47.14), central LND (OR 16.05, 95% CI 3.90-66.07), and parathyroid autotransplantation (OR 36.22, 95% CI 6.76-194.13) predicted hypocalcemia.

DISCUSSION

This study demonstrates that patients with lower preoperative iPTH levels, retrosternal goiters, central LND, and parathyroid autotransplantation are at an increased risk of developing clinical symptoms of hypocalcemia. Body composition parameters have no effect on the incidence of hypocalcemia after total thyroidectomy.

Body fat percentage prediction in older adults: Agreement between anthropometric equations and DXA

BACKGROUND

It is difficult to measure body fat percentage in clinical settings. Equations using anthropometric measures are more feasible and can be used to estimate body fat. However, there is a need to analyze their accuracy in older adults. Our study aims to validate the use of anthropometric equations to estimate body fat percentage in older men and women.

METHODS

This study evaluated data from 127 Brazilian individuals aged between 60 and 91 years. Weight, height, skinfold thickness and waist and hip circumferences were measured. Seventeen anthropometric equations were tested using the crossed validity criteria suggested by Lohman and the graph analysis proposed by Bland and Altman and by Lin was also performed. The gold-standard method for comparing the anthropometric equations was the dual-energy absorptiometry X-ray (DXA).

RESULTS

The average body fat percentage was 30.2 ± 8.6% in men and 43.4 ± 7.9% in women (p < 0.001). In men, the equations which used skinfold thickness presented amplitude of 11.48%, while in women, amplitude's constant error (CE) was 22.88%. The equations based on circumferences and BMI presented CE variation from -5.3% to 29.68% on the estimation of body fat percentage, which means that a same male individual can have the total body adiposity diagnosed with 34.98% of variation, depending on the selection of the employed equation. For women this CE variation was 12.44%.

CONCLUSION

Overall, all the equations yielded different results from the DXA. However, the best equations for male were the one of Lean et al. (1996), which uses the waist circumference, and for women the one of Deurenberg et al. (1991), developed from the body mass index. The need of developing specific equations for older adults still remains, since even the two best equations showed considerable limitations on predicating body fat percentage.

Five-component model validation of reference, laboratory and field methods of body composition assessment

This study reports the validity of body fat percentage (BF%) estimates from several commonly employed techniques as compared with a five-component (5C) model criterion. Healthy adults (n 170) were assessed by dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), multiple bioimpedance techniques and optical scanning. Output was also used to produce a criterion 5C model, multiple variants of three- and four-component models (3C; 4C) and anthropometry-based BF% estimates. Linear regression, Bland-Altman analysis and equivalence testing were performed alongside evaluation of the constant error (CE), total error (TE), se of the estimate (SEE) and coefficient of determination (R2). The major findings were (1) differences between 5C, 4C and 3C models utilising the same body volume (BV) and total body water (TBW) estimates are negligible (CE ≤ 0·2 %; SEE < 0·5 %; TE ≤ 0·5 %; R2 1·00; 95 % limits of agreement (LOA) ≤ 0·9 %); (2) moderate errors from alternate TBW or BV estimates in multi-component models were observed (CE ≤ 1·3 %; SEE ≤ 2·1 %; TE ≤ 2·2 %; R2 ≥ 0·95; 95 % LOA ≤ 4·2 %); (3) small differences between alternate DXA (i.e. tissue v. region) and ADP (i.e. Siri v. Brozek equations) estimates were observed, and both techniques generally performed well (CE < 3·0 %; SEE ≤ 2·3 %; TE ≤ 3·6 %; R2 ≥ 0·88; 95 % LOA ≤ 4·8 %); (4) bioimpedance technologies performed well but exhibited larger individual-level errors (CE < 1·0 %; SEE ≤ 3·1 %; TE ≤ 3·3 %; R2 ≥ 0·94; 95 % LOA ≤ 6·2 %) and (5) anthropometric equations generally performed poorly (CE 0·6- 5·7 %; SEE ≤ 5·1 %; TE ≤ 7·4 %; R2 ≥ 0·67; 95 % LOA ≤ 10·6 %). Collectively, the data presented in this manuscript can aid researchers and clinicians in selecting an appropriate body composition assessment method and understanding the associated errors when compared with a reference multi-component model.

Fat-free mass characteristics of Hispanic adults: Comparisons with non-Hispanic Caucasians and cadaver reference values

BACKGROUND

A four-compartment (4C) model quantifies fat, water, mineral and residual. As such, 4C models are more accurate than two-compartment (2C) models based off cadaver reference values (RV), which necessitate assumptions regarding fat-free mass (FFM) characteristics. Nonetheless, research has yet to determine whether the FFM characteristics of Hispanics are similar to non-Hispanic Caucasians and RV.

AIM

The aim of this analysis was to compare the FFM characteristics of Hispanics to non-Hispanic Caucasians and cadaver RV.

METHODS

Data from 2 separate research centers were pooled to create a sample of 100 and 119 Hispanic males and females (age: 18-54 yrs; BMI: 16.46-42.27 kg/m²), respectively, and 47 and 55 non-Hispanic Caucasian males and females (age: 18-54 yrs; BMI: 16.00-36.67 kg/m²), respectively (n = 331). A 4C model was determined using bioimpedance analysis for hydration, dual energy X-ray absorptiometry for mineral, and air displacement plethysmography for body density (4C-ADP). FFM was calculated via the 4C-ADP and FFM characteristics (i.e., density [D_FFM], water [TBW:FFM], bone mineral [Mo:FFM], and residual [R:FFM]) were compared between sexes and ethnicities using a one-way ANOVA and against RV via a one sample t-test.

RESULTS

In Hispanics, all FFM characteristics significantly differed from cadaver RV (all p < 0.05). In contrast, D_FFM and TBW:FFM of non-Hispanic Caucasians were similar to cadaver RV for both sexes (all p > 0.05). Moreover, the R:FFM of non-Hispanic Caucasian females did not differ from cadaver RV (p = 0.403) whereas all other comparisons were significantly different (all p < 0.05). Sex comparisons within Hispanic participants revealed FFM characteristics were similar between males and females other than Mo:FFM (p < 0.001) whereas all FFM characteristics were similar between non-Hispanic Caucasian males and females (all p > 0.05). All of the ethnicity comparisons within males were statistically significant (all p < 0.05). Moreover, ethnicity comparisons within females were statistically significant for all comparisons other than Mo:FFM (p = 0.258).

CONCLUSION

The observed differences in FFM characteristics of Hispanics as compared to non-Hispanics Caucasians and reference values indicate that allied health professionals should employ appropriate caution when estimating body composition via 2C models in Hispanic populations.

3-Dimensional optical scanning for body composition assessment: A 4-component model comparison of four commercially available scanners

BACKGROUND & AIMS

Body composition assessment via 3-dimensional optical (3DO) scanning has emerged as a rapid and simple evaluation method. The aim of this study was to establish the precision of body composition estimates from four commercially available 3DO scanners and evaluate their validity as compared to a reference 4-component (4C) model.

METHODS

The body composition of 171 participants was assessed using four commercially-available 3DO scanners (FIT3D®, Naked Labs®, Size Stream®, and Styku®) and a 4C model utilizing data from dual-energy x-ray absorptiometry, air displacement plethysmography, and bioimpedance spectroscopy. Body composition estimates were compared via equivalence testing, Deming regression, Bland-Altman analysis, concordance correlation coefficients (CCC), root mean square error (RMSE), and related metrics. Precision metrics, including the root mean square coefficient of variation (RMS-%CV), precision error, and intraclass correlation coefficient, were generated for duplicate scans in 139 participants.

RESULTS

All scanners produced reasonably reliable estimates, with RMS-%CV of 2.3-4.3% for body fat percentage (BF%), 2.5-4.3% for fat mass (FM), and 0.7-1.4% for fat-free mass (FFM). ICC values ranged from 0.975 to 0.996 for BF% and 0.990 to 0.999 for FM and FFM. All scanners except Styku® demonstrated equivalence with 4C, using 5% equivalence regions, and constant errors of <1% for BF% and ≤0.5 kg for FM and FFM. However, the slopes of regression lines differed from the line of identity for most scanners and variables. CCC values ranged from 0.74 to 0.90 for BF%, 0.85 to 0.95 for FM, and 0.93 to 0.97 for FFM. RMSE values ranged from 3.7 to 6.1% for BF% and 2.8-4.6 kg for FM and FFM. Bland-Altman analysis indicated proportional bias of varying magnitudes was present for all scanners.

CONCLUSIONS

Commercially available 3DO scanners produce relatively reliable body composition estimates. Three out of four scanners demonstrated equivalence with a 4C model for assessments of BF%, FM, and FFM, although other metrics of validity varied among scanners, and proportional bias was present for all scanners.

Body composition in children with chronic inflammatory diseases: A systematic review

BACKGROUND & AIMS

Aberrations in body composition are expected in children suffering from chronic inflammatory conditions. The objective is to examine whether children with inflammatory bowel disease (IBD: Crohn's disease and ulcerative colitis), coeliac disease, asthma and juvenile idiopathic arthritis (JIA) have an altered body composition as compared to healthy children.

METHODS

A systematic review, registered in Prospero (registration number: CRD42018107645), was conducted according to PRISMA guidelines. We conducted a search of three databases, Pubmed, Cochrane and Scopus. An assessment of the quality of the study was performed.

RESULTS

Data from 50 studies, 32 with IBD, 8 with coeliac disease, 2 with asthma and 8 with JIA, involving 2399 children were selected for review after applying the eligibility criteria. In all but 4 studies, children with Crohn's disease exhibited decreased amounts of fat mass and fat free mass. Reductions in fat mass were also evident in studies in children with coeliac disease. It is uncertain whether body composition is altered in children with asthma or JIA.

CONCLUSIONS

Children with Crohn's disease manifest with lowered adiposity and lean mass and therefore are likely to be at risk for suffering malnutrition-related clinical complications. Apart from Crohn's disease, data examining body composition in children with chronic inflammatory conditions are scarce and there is a paucity of reports examining the relationship between inflammation and body composition. Interpretation of the current study results is hampered by the low quality of the studies and due to the fact that the analyses have been habitually secondary outcomes.

Digital anthropometry via three-dimensional optical scanning: evaluation of four commercially available systems

BACKGROUND

Digital anthropometry is increasingly accessible due to commercial availability of three-dimensional optical scanners (3DO).

METHODS

One hundred and seventy-nine participants were assessed by four 3DO systems (FIT3D®, Size Stream®, Styku®, and Naked Labs®) in duplicate, air displacement plethysmography (ADP), and dual-energy x-ray absorptiometry (DXA). Test-retest precision was evaluated, and validity of total and regional volumes was established.

RESULTS

All scanners produced precise estimates, with root mean square coefficient of variation (RMS-%CV) of 1.1-1.3% when averaged across circumferences and 1.9-2.3% when averaged across volumes. Precision for circumferences generally decreased in the order of: hip, waist and thigh, chest, neck, and arms. Precision for volumes generally decreased in the order of: total body volume (BV), torso, legs, and arms. Total BV was significantly underestimated by Styku® (constant error [CE]: -10.1 L; root mean square error [RMSE]: 10.5 L) and overestimated by Size Stream® (CE: 8.0 L; RMSE: 8.3 L). Total BV did not differ between ADP and FIT3D® (CE: -3.9 L; RMSE: 4.2 L) or DXA BV equations (CE: 0-1.4 L; RMSE: 0.7-1.5 L). Torso volume was overestimated and leg and arm volumes were underestimated by all 3DO. No total or regional 3DO volume estimates exhibited equivalence with reference methods using 5% equivalence regions, and proportional bias of varying magnitudes was observed.

CONCLUSIONS

All 3DO produced precise anthropometric estimates, although variability in specific precision estimates was observed. 3DO BV estimates did not exhibit equivalence with reference methods. Conversely, DXA-derived total BV exhibited superior validity and equivalence with ADP.

Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults

Aim

To develop predictive equations of lean body mass (LBM) suitable for healthy southern Chinese adults with a large sample. LBM measured by dual-energy X-ray absorptiometry (DXA) are considered as the standard ones.

Methods

Retrospective analysis was conducted on the consecutive people who did total body measurement with DXA from July 2005 to October 2015. People with diseases that might affect LBM were excluded and overall 12,194 subjects were included in this study. Information about the 10,683 subjects (2,987 males and 7,696 females) from July 2005 to November 2014 was used to establish equations. These subjects were grouped by sex and then subdivided according to their body mass index (BMI). The female group was divided into another two subgroups: the premenopausal and postmenopausal subgroups. Equations were developed through stepwise multilinear regression analysis of height, weight, age, and BMI. Information about the 1,511 subjects (395 males and 1116 females) from December 2014 to October 2015 was used to verify the established equations.

Results

BMI, height, weight, and age were introduced into the equations as independent variables in the male group, while age was proved to have no influence on LBM in the female group. Regrouping according to BMI or menopause did not increase the predictive ability of equations. Good agreement between LBM evaluated by equation (LBM_PE) and LBM measured by DXA (LBM_DXA) was observed in both the male and female groups.

Conclusion

Predictive equations of LBM suitable for healthy southern Chinese adults are established with a large sample. BMI was related to LBM content; however, there is no need for further group based on BMI or menopause while developing LBM questions.