Criterion-Related Validity of Field-Based Methods and Equations for Body Composition Estimation in Adults: A Systematic Review

Science behind policy: implementing a modern circumference-based body fat equation with a physical fitness threshold is associated with lower musculoskeletal injury risk

BACKGROUND

Body composition influences physical fitness (PF) and risk of musculoskeletal injury (MSKI). Assessing the relationship between body fat (BF), PF and MSKI risk in a large diverse military population may provide evidence basis informing health-care policies, practices, and programs for military and civilian populations.

OBJECTIVE

Evaluate the validity of expedient methods to estimate BF (e.g., circumference-based equation (CBE) and bioelectrical impedance analysis (BIA)) and investigate relationships between BF and PF with MSKI risk in a large diverse population.

METHODS

Participants were 1904 active-duty Soldiers (643 F) representing Army demographics sex, race/ethnicity (R/E), and age. PF, defined as the most recent Army Combat Fitness Test (ACFT) score and incidence of MSKI, were obtained from Army records. BF was determined by dual-energy x-ray absorptiometry (%BFDXA), bioelectrical impedance analysis (%BFBIA), and CBE using 3-site (Hodgdon, %BFHE) and 1-site (Taylor-McClung, %BFTM) equations. Results were stratified by race and sex, to evaluate differences in accuracy of estimated %BF (weighted root mean squared error from %BFDXA). Associations of BF and PF with MSKI risk were evaluated with logistic regression.

RESULTS

CBE and BIA underestimated %BF compared to %BFDXA. %BFBIA differed from %BFDXA overall and by sex. %BFTM underestimation was uniform across both sex and R/E compared to %BFDXA. Mean differences from %BFDXA by sex (M;F) were lower when measured by %BFTM (4.38; 4.59) compared to %BFHE (5.88; 4.39). Individuals had a greater likelihood of MSKI if they failed BF standards (odds ratio 1.32). Scoring ≥ 540 total on ACFT exhibited a 31% (95% CI: 0.52, 0.92) lower MSKI risk during the following 12 months than those with a lower score.

CONCLUSIONS

A single-site BF equation (%BFTM) maintained similar accuracy across the Soldier population by sex, age, and R/E. Implementing a PF score threshold in lieu of passing Army BF standards was associated with lower MSKI risk.

A Comparison of Commonly Used Prediction Equations for Estimating Resting Metabolic Rate in Adults With Down Syndrome

BACKGROUND

Resting metabolic rate (RMR), the energy required by the body at rest, is the largest part of total daily energy expenditure. Commonly used prediction equations may overestimate RMR in adults with Down syndrome (DS). The purpose of this study was to assess the equivalency of prediction equations for estimating RMR in adults with DS.

METHODS

Twenty-five adults with DS (24 ± 5 years of age, 64% female) completed RMR assessments at an academic medical centre in the United States between November 2021 and July 2023. Measured RMR (kilocalories per day) was compared to estimated RMR from eight prediction equations using a null hypothesis significance (i.e., a paired t-test) and equivalence (i.e., a two one-sided test) tests. Bland-Altman plots, Pearson correlations and linear regressions were used to evaluate the bias between the measured and predicted RMR values.

RESULTS

Measured RMR in adults with DS was 1090 ± 136 kcal/day. Prediction equations overestimated RMR by 8 ± 16% (76 ± 165 kcal/day) to 45 ± 16% (488 ± 165 kcal/day) except for the Bernstein fat-free mass equation which underestimated RMR by 0.2 ± 11.5% (8 ± 123 kcal/day) and was statistically equivalent to measured RMR in our sample (p = 0.027).

CONCLUSIONS

The Bernstein fat-free mass equation offers better accuracy in adults with DS than other RMR prediction equations, but the equation needs to be evaluated in larger, more diverse samples of adults with DS.

Criterion Validity of Screening Tools and Field-Based Tests for Health-Related Physical Fitness in Inflammatory Bowel Disease

BACKGROUND

Monitoring health-related physical fitness (HRPF) may benefit proactive Inflammatory Bowel Disease (IBD) management. However, knowledge regarding HRPF in patients with IBD is limited and gold standard tests are impractical for widespread use, necessitating simpler methods.

AIM

This study evaluated the criterion validity of screening tools and field-based tests compared to gold standard tests for HRPF in patients with IBD.

METHODS

Adult patients with IBD completed screening tools, field-based tests, and gold standard tests for HRPF. Criterion validity was examined through (intraclass) correlation coefficients and Bland-Altman plots. Predictive capacity of the screening tools was examined with receiver operating curve analysis.

RESULTS

Among 53 included patients, screening tools demonstrated poor-to-moderate validity compared to the cardiopulmonary exercise test (CPET) for cardiorespiratory fitness. Very strong correlations were found for four-site skinfold thickness and multi-frequency bioimpedance analysis (BIA) with deuterium oxide dilution for body fat percentage (ICC = 0.90, ICC = 0.93), and between the steep ramp test and CPET (r = 0.95) for cardiorespiratory fitness. The steep ramp test also correlated strongly with isokinetic quadriceps (r > 0.75) and hamstring (r > 0.74) strength. Hand-held dynamometry and the sit-to-stand test showed strong correlations with hamstring strength (r > 0.80, r > 0.76). Negligible correlations were found for field-based tests compared to isokinetic quadriceps and hamstring endurance.

CONCLUSIONS

Four-site skinfold thickness and BIA showed good agreement with the gold standard for body fat measurement. The steep ramp test demonstrated strong correlations with the gold standard tests for cardiorespiratory fitness and quadriceps and hamstring strength, while hand-held dynamometry and the sit-to-stand test showed strong correlations with hamstring strength.

Development and validation of a new anthropometric equation to predict fat mass percentage in a heterogeneous Caucasian population

OBJECTIVE

(1) To develop a new regression equation for estimating fat mass percentage (%FM) from anthropometric measurements in a heterogeneous Caucasian population and (2) to compare it with the Durnin and Womersley equation, which is one of the most used anthropometric equations for FM assessment.

DESIGN

Body mass, stature and four skinfolds (biceps, triceps, subscapular and supracrestal) were assessed by an accredited anthropometrist, according to the International Society for Advancement in Kinanthropometry. Participants completed a dual-energy X-ray absorptiometry (DXA) whole-body scan to determine their %FM. A new anthropometric equation to estimate %FM was developed using multiple forward regression analyses with DXA as the reference method. Tests for the accuracy of the different equations included mean differences, coefficient of determination, SE of the estimate (SEE), concordance correlation coefficient (CCC) and Bland-Altman plots.

SETTING

Spain.

PARTICIPANTS

Two hundred and eighteen healthy Caucasian participants aged 18-65 years participated in this cross-sectional study.

RESULTS

Our proposed equation explained 89·9 % of the variance in the DXA-derived %FM, with a low random error (SEE = 3·00 %), a very strong agreement (CCC = 0·93), no fixed or proportional bias and a relatively low individual variability (5·84 %). However, the Durnin and Womersley equations obtained a fixed bias of -3·65 % when compared with DXA and a greater individual variability (6·74 %).

CONCLUSIONS

The proposed equation can accurately estimate %FM in a heterogeneous Caucasian population with a wide age range (18-65 years). Additionally, the Durnin and Womersley equation was inadequate when applied to our participants.

Development and cross-validation of prediction equations for body composition in adult cancer survivors from the Korean National Health and Nutrition Examination Survey (KNHANES)

Epidemiological studies frequently use indices of adiposity related to mortality. However, no studies have validated prediction equations for body composition in adult cancer survivors. We aimed to develop and cross-validate prediction equations for body fat mass (BFM), lean body mass (LBM), trunk fat mass (TFM), and appendicular lean mass (ALM) in adult cancer survivors using sociodemographic, anthropometric, and laboratory test data. This study included adult cancer survivors from the Korean National Health and Nutrition Examination Survey 2008-2011 with complete data on Dual-energy X-ray absorptiometry (DXA) measurements. A total of 310 participants were randomly divided into development and cross-validation groups (5:5 ratio). Age, height, weight, waist circumference, serum creatinine levels, and lifestyle factors were included as independent variables The predictive equations were developed using a multiple linear regression and their predictive performances were primarily evaluated with R2 and Concordance Correlation Coefficient (CCC). The initial equations, which included age, height, weight, and waist circumference, showed different predictive abilities based on sex for BFM (total: R2 = 0.810, standard error of estimate [SEE] = 3.072 kg, CCC = 0.897; men: R2 = 0.848, SEE = 2.217 kg CCC = 0.855; women: R2 = 0.791, SEE = 2.194 kg, CCC = 0.840), LBM (total: R2 = 0.736, SEE = 3.321 kg, CCC = 0.838; men: R2 = 0.703, SEE = 2.450 kg, CCC = 0.774; women: R2 = 0.854, SEE = 2.234 kg, CCC = 0.902), TFM (total: R2 = 0.758, SEE = 1.932 kg, CCC = 0.844; men: R2 = 0.650, SEE = 1.745 kg, CCC = 0.794; women: R2 = 0.852, SEE = 1.504 kg, CCC = 0.890), and ALM (total: R2 = 0.775, SEE = 1.726 kg, CCC = 0.876; men: R2 = 0.805, SEE = 1.320 kg, CCC = 0.817; women: R2 = 0.726, SEE = 1.198 kg, CCC = 0.802). When additional factors, such as creatinine, smoking, alcohol consumption, and physically inactive were included in the initial equations the predictive performance of the equations were generally improved. The prediction equations for body composition derived from this study suggest a potential application in epidemiological investigations on adult cancer survivors.

Associations of change in body fat percentage with baseline body composition and diabetes remission after bariatric surgery

OBJECTIVE

The objective of this study was to determine the role of body fat percentage (BFP) changes in diabetes remission (DR) and the association between baseline body composition and its changes after bariatric surgery.

METHODS

We analyzed 203 patients with type 2 diabetes who underwent Roux-en-Y gastric bypass. Body composition was measured using a gold-standard-derived predictive equation and magnetic resonance imaging. Body composition changes were calculated as 100 × (baseline value - follow-up value)/baseline value. We verified the results in a laparoscopic sleeve gastrectomy cohort with 311 patients.

RESULTS

Compared with non-remission patients in the Roux-en-Y gastric bypass cohort, those who achieved DR showed a higher baseline fat-free mass index (FFMI) and experienced the most significant changes in BFP (p < 0.001). In comparative analyses, BFP changes were significantly better than BMI changes in identifying short- and long-term DR. Linear regression analysis identified FFMI as the most significant baseline variable correlated with BFP changes (p < 0.001). Baseline BMI was positively correlated with changes in BFP but negatively correlated with changes in FFMI. These findings were replicated in the laparoscopic sleeve gastrectomy cohort.

CONCLUSIONS

BFP changes determine DR after bariatric surgery, and baseline FFMI is crucial for BFP changes. A low initial BMI is associated with a smaller BFP reduction and greater FFMI loss after bariatric surgery.

Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass

Currently available anthropometric body composition prediction equations were often developed on small participant samples, included only several measured predictor variables, or were prepared using conventional statistical regression methods. Machine learning approaches are increasingly publicly available and have key advantages over statistical modeling methods when developing prediction algorithms on large datasets with multiple complex covariates. This study aimed to test the feasibility of predicting DXA-measured appendicular lean mass (ALM) with a neural network (NN) algorithm developed on a sample of 576 participants using 10 demographic (sex, age, 7 ethnic groupings) and 43 anthropometric dimensions generated with a 3D optical scanner. NN-predicted and measured ALM were highly correlated (n = 116; R2, 0.95, p < 0.001, non-significant bias) with small mean, absolute, and root-mean square errors (X ± SD, -0.17 ± 1.64 kg and 1.28 ± 1.04 kg; 1.64). These observations demonstrate the application of NN body composition prediction algorithms to rapidly emerging large and complex digital anthropometric datasets. Clinical Trial Registration: NCT03637855, NCT05217524, NCT03771417, and NCT03706612.

Human metabolism and body composition: prospects for novel studies

CONTEXT

Most articles on gut microbiota argue the importance of body composition assessment in patients; however, body composition assessments are fragile (ie, with methodological limitations) in the most recent studies.

OBJECTIVE

To present two suggestions for further research using the human body composition assessment.

METHODS

The methods used in this study are based on a Pinto et al article published in Nutrition Reviews.

DATA EXTRACTION

On the basis of data.

obtained from the PubMed, SCOPUS, LILACS, and Web of Science databases, Pinto et al provided a current survey of intermittent fasting protocols and an understanding of the outcomes to date in terms of the profile of the intestinal microbiota in obese organisms.

DATA ANALYSIS

Of the 82 original articles identified from the databases, 35 were eliminated because of duplication and 32 were excluded for not meeting the inclusion criteria. Two additional articles found in a new search were added, yielding a total of 17 studies to be included in this review. Among the protocols, alternate-day fasting and time-restricted feeding were the most common, and they were shown to have different mechanisms of metabolic signaling. Time-restricted feeding influences body mass control and biochemical parameters by regulating the circadian system and improving satiety control systems by acting on leptin secretion. In contrast, alternate-day fasting leads to a reduction of ±75% of all energy consumption regardless of dietary composition, in addition to promoting hormonal adjustments that promote body mass control. Furthermore, both protocols could remodel the intestinal microbiota by changing the Firmicutes to Bacteroidetes ratio and increasing the abundance of strains such as Lactobacillus spp. and Akkermansia that have a protective effect on metabolism against the effects of body mass gain.

CONCLUSION

Changes in adipose tissue (eg, body mass loss, control, gain) should be interpreted via the sum of skinfolds in absolute values, waist perimeter, and patients' body proportionality, because fat is just a fraction of the adipocyte (lipid).

Comparison of Several Anthropometric Indices Related to Body Fat in Predicting Cardiorespiratory Fitness in School-Aged Children-A Single-Center Cross-Sectional Study

Body fat (BF) and cardiorespiratory fitness (CRF) are important health markers that ought to be considered in screening exams. The aim of this study was to assess the value of six indicators, i.e., tri-ponderal mass index (TMI), relative fat mass (RFM), waist-BMI ratio, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and body mass index (BMI) in predicting CRF in school-aged children. The analysis was based on the data coming from the examination of 190 children participating in school physical education (PE) classes. Their body weight (BW) and height (BH), waist and hip circumference (WC; HC) and percentage of body fat (%BF) were measured; the CRF test was performed with the use of the 20 m shuttle run test (20 mSRT); peak heart rate (HRpeak) was measured; TMI, relative fat mass pediatric (RFMp), waist-BMI ratio, WHtR, BMI and WHR were calculated. Statistical analysis was mainly conducted using regression models. The developed regression models, with respect to the sex and age of the children, revealed RFMp as the strongest CRF indicator (R2 = 51.1%) and WHR as well as waist-BMI ratio as the weakest ones (R2 = 39.2% and R2 = 40.5%, respectively). In predicting CRF in school-aged children, RFMp turned out to be comparable to body fat percentage obtained by means of the bioimpedance analysis (BIA) (R2 = 50.3%), and as such it can be used as a simple screening measure in prophylactic exams of school children. All of these models were statistically significant (p < 0.001).

Association between nickel exposure and body compositions in the United States: a population-based cross-sectional study

BACKGROUND

Increasing body fat or decreasing muscle and bone mass were associated with worse health outcomes in the adult population. The effects of nickel exposure on body composition are not known. The aim of the current study was to investigate the relationship between urinary nickel levels and body compositions.

MATERIALS AND METHODS

Two thousand seven hundred sixty-two participants were included in the analysis from the National Health and Nutrition Examination Surveys of 2017-2018 after excluding participants who have missing data on urinary nickel and those with missing all body mass component data. We used weighted generalized linear models to explore the relationship between urinary nickel and body mass components under interpolating missing covariable values. Simultaneously, sensitivity analyses and subgroup analysis were conducted to verify stability of analysis result. Curve fitting and saturation effect analysis were used to explore the possible nonlinear relationship between urine nickel and body compositions.

RESULTS

Among the 2,762 participants, the average urinary nickel level was 1.58 ug/L. The weighted generalized linear models, the sensitivity analyses and subgroup analyses found no significant linear relationship between urinary nickel and body compositions. For body weight, BMI, TLM, ALM, TRF, TOF and BMC, the urine nickel saturation effect values were 0.76, 0.74, 0.5, 0.67, 0.64, 0.48, and 0.45 ug/L, respectively. For each 1 ug/L rise in urinary nickel levels at levels below the turning point, body weight increases (β = 9.06, 95% CI = 2.75, 15.36, p = 0.01), BMI increases (β = 3.20, 95% CI = 1.36, 5.05, p =  < 0.001), TLM decreases (β = -47.39, 95% CI = -97.38, 2.59, p = 0.06), ALM decreases (β = -37.25, 95% CI = -63.25, -11.24, p = 0.01), TRF increases (β = 20.68, 95% CI = 1.50, 39.86, p = 0.03), TOF increases (β = 57.92, 95% CI = -0.12, 115.95, p = 0.05), and BMC decreases (β = -6.84, 95% CI = -12.64, -1.04, p = 0.02).

CONCLUSIONS

In summary, our study demonstrated that a dose-response relationship exists between urinary nickel and body compositions, with a low inflection point level of urinary nickel for the saturation effect.

Effects of physical activity interventions on anthropometric indicators and health indices in Chilean children and adolescents: A protocol for systematic review and/or meta-analysis

INTRODUCTION

Physical activity interventions have been a proven effective means of preventing or treating overweight and obesity in children and adolescents. The results of these interventions in many cases are based on the determination of the effect they produce on anthropometric evaluations, which allow the calculation of health indices. However, the effects of physical activity interventions on anthropometric assessments in Chilean children and adolescents have not been systematized. The objective of this study is to provide a detailed protocol for a systematic review with meta-analysis that synthesizes the available evidence on the effect of physical activity interventions on anthropometric indicators and health indices in Chilean children and adolescents and identifies the field-based methods and health indices most used for body composition estimation.

METHODS

This protocol was performed according to the PRISMA declaration. MEDLINE (PubMed), Web of Science, Scopus, and Scielo databases will be systematically searched. Eligible studies will include randomized controlled trials (RCTs), non-RCTs and pre-post studies.

CONCLUSION

This systematic review and meta-analysis protocol is designed to provide up-to-date evidence that could significantly assist public health policy makers and implementers of physical activity interventions through evidence-based guidance and recommendations.