Validity of Body-Composition Methods across Racial and Ethnic Populations

Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing

Body composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessibility and cost remain barriers to widespread adoption. The integration of AI-powered image analysis may help explain tissue differentiation, whereas mobile health apps offer real-time metabolic monitoring and personalized feedback. New apps such as MeThreeSixty and Made Health and Fitness offer the advantages of clinic-based imaging techniques from the comfort of home. These innovations hold the potential for individualizing strategies and interventions, optimizing clinical outcomes, and empowering informed decision-making for both healthcare professionals and patients/clients. Navigating the intricacies of these emerging tools, critically assessing their validity and reliability, and ensuring inclusivity across diverse populations and conditions will be crucial in harnessing their full potential. By integrating advancements in body composition assessment, healthcare can move beyond the limitations of traditional methods and deliver truly personalized, data-driven care to optimize well-being.

Health professional attitudes and perceptions of prehabilitation and nutrition before haematopoietic cell transplantation

BACKGROUND

Nutritional prehabilitation may improve haematopoietic cell transplantation (HCT) outcomes, although little evidence exists. The present study aimed to understand healthcare professional (HCP) perceptions of prehabilitation and nutritional care pre-HCT in UK centres.

METHODS

An anonymous online survey (developed and refined via content experts and piloting) was administered via email to multidisciplinary HCPs in 39 UK adult centres, between July 2021 and June 2022. Data are presented as proportions of responses. Routine provision denotes that care was provided >70% of time.

RESULTS

Seventy-seven percent (n = 66) of HCPs, representing 61.5% (n = 24) of UK adult HCT centres, responded. All HCPs supported prehabilitation, proposing feasible implementation between induction chemotherapy (60.4%; n = 40) and first HCT clinic (83.3%; n = 55). Only 12.5% (n = 3) of centres had a dedicated prehabilitation service. Nutrition (87.9%; n = 58), emotional wellbeing (92.4%; n = 61) and exercise (81.8%; n = 54) were considered very important constituents. HCPs within half of the HCT centres (n = 12 centres) reported routine use of nutrition screening pre-HCT with a validated tool; 66.7% of HCPs (n = 36) reported using the malnutrition universal screening tool (MUST). Sixty-two percent (n = 41) of HCPs reported those at risk, received nutritional assessments, predominantly by dietitians (91.6%; n = 22) using the dietetic care process (58.3%; n = 14). Body mass index (BMI) was the most frequently reported body composition measure used by HCPs (70.2%, n = 33). Of 59 respondents, non-dietitians most routinely provided dietary advice pre-HCT (82.4%; n = 28 vs. 68%; n = 17, p = 0.2); including high-energy/protein/fat and neutropenic diet advice. Prophylactic enteral feeding pre-HCT was rare, indicated by low BMI and significant unintentional weight loss. Just under half (n = 25 of 59, 42.4%) HCPs reported exercise advice was given routinely pre-HCT.

CONCLUSIONS

Nutrition and prehabilitation pre-HCT are considered important and deliverable by HCPs, but current provision in UK centres is limited and inconsistent.

Adult obesity diagnostic tool: A narrative review

Obesity is a complex chronic metabolic disorder characterized by abnormalities in lipid metabolism. Obesity is not only associated with various chronic diseases but also has negative effects on physiological functions such as the cardiovascular, endocrine and immune systems. As a global health problem, the incidence and prevalence of obesity have increased significantly in recent years. Therefore, understanding assessment methods and measurement indicators for obesity is critical for early screening and effective disease control. Current methods for measuring obesity in adult include density calculation, anthropometric measurements, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, computerized imaging, etc. Measurement indicators mainly include weight, hip circumference, waist circumference, neck circumference, skinfold thickness, etc. This paper provides a comprehensive review of the literature to date, summarizes and analyzes various assessment methods and measurement indicators for adult obesity, and provides insights and guidance for the innovation of obesity assessment indicators.

The Effect of a Combined Intermittent Fasting Healthy Plate Intervention on Anthropometric Outcomes and Body Composition Among Adults With Overweight and Obesity: Nonrandomized Controlled Trial

BACKGROUND

Adult obesity and overweight pose a substantial risk to global public health and are associated with various noncommunicable diseases. Although intermittent fasting (IF) is increasingly used as a relatively new dietary strategy for weight loss, the effectiveness of 2 days per week of dry fasting remains unknown.

OBJECTIVE

This study aims to evaluate the effectiveness of a combined dry IF and healthy plate (IFHP) and healthy plate (HP) intervention in improving anthropometric outcomes and body composition.

METHODS

This nonrandomized controlled trial involved 177 adults who were overweight and obese. Among them, 91 (51.4%) were allocated to the IFHP group and 86 (48.6%) were allocated to the HP group. The overall study duration was 6 months (October 2020 to March 2021). The intervention was divided into 2 phases: supervised (3 months) and unsupervised (3 months). The data were collected at baseline, after the supervised phase (month 3), and after the unsupervised phase (month 6). Anthropometric (weight, height, waist circumference, and hip circumference) and body composition (body fat percentage, body fat mass, skeletal muscle mass, and visceral fat area) data were measured at all 3 data collection points. Sociodemographic data were obtained using a questionnaire at baseline.

RESULTS

Most participants were female (147/177, 83.1%) and Malay (141/177, 79.7%). After 3 months, there were significant reductions in weight (difference -1.68; P<.001), BMI (difference -0.62; P<.001), body fat percentage (difference -0.921; P<.001), body fat mass (difference -1.28; P<.001), and visceral fat area (difference -4.227; P=.008) in the IFHP group, whereas no significant changes were observed in the HP group. Compared to baseline, participants in the IFHP group showed a significant decrease in weight (difference -1.428; P=.003), BMI (difference -0.522; P=.005), body fat percentage (difference -1.591; P<.001), body fat mass (difference -1.501; P<.001), visceral fat area (difference -7.130; P<.001), waist circumference (difference -2.304; P=.001), and hip circumference (difference -1.908; P=.002) at month 6. During the unsupervised phase, waist (IFHP difference -3.206; P<.001, HP difference -2.675; P=.004) and hip (IFHP difference -2.443; P<.001; HP difference -2.896; P<.001) circumferences were significantly reduced in both groups (P<.01), whereas skeletal muscle mass (difference 0.208; P=.04) and visceral fat area (difference -2.903; P=.003) were significantly improved in the IFHP group only. No significant difference in the between-group comparison was detected throughout the intervention (all P>.05).

CONCLUSIONS

A combined IFHP intervention was effective in improving anthropometric outcomes and body composition in adults with overweight and obesity.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/33801.

Investigating the potential causal association between consumption of green tea and risk of lung cancer: a study utilizing Mendelian randomization

Background

Lung cancer is the most common global cancer in terms of incidence and mortality. Its main driver is tobacco smoking. The identification of modifiable risk factors isa public health priority. Green tea consumption has been examined in epidemiological studies, with inconsistent findings. Thus, we aimed to apply Mendelian randomization to clarify any causal link between green tea consumption and the risk of lung cancer.

Methods

We utilized a two-sample Mendelian randomization (MR) approach. Genetic variants served as instrumental variables. The goal was to explore a causal link between green tea consumption and different lung cancer types. Green tea consumption data was sourced from the UK Biobank dataset, and the genetic association data for various types of lung cancer were sourced from multiple databases. Our analysis included primary inverse-variance weighted (IVW) analyses and various sensitivity test.

Results

No significant associations were found between green tea intake and any lung cancer subtypes, including non-small cell lung cancer (adenocarcinoma and squamous cell carcinoma) and small cell lung cancer. These findings were consistent when applying multiple Mendelian randomization methods.

Conclusion

Green tea does not appear to offer protective benefits against lung cancer at a population level. However, lung cancer's complex etiology and green tea's potential health benefitssuggest more research is needed. Further studies should include diverse populations, improved exposure measurements and randomized controlled trials, are warranted.

Evaluation and management of body composition changes in cancer patients

Wasting in cancer patients has long been recognized as a condition that adversely affects cancer patients' quality of life, treatment tolerance, and oncological outcomes. Historically, this condition was mainly evaluated by changes in body weight. However, this approach is not quite accurate because body weight is the overall change of all body compartments. Conditions such as edema and ascites can mask the severity of muscle and adipose tissue depletion. Changes in body composition assessment in cancer patients have historically been underappreciated because of the limited availability of measurement tools. As more evidence highlighting the importance of body composition has emerged, it is imperative to apply a more precise evaluation of nutritional status and a more targeted approach to provide nutritional support for cancer patients. In this review, we will discuss the modalities for evaluating body composition and how to manage body composition changes in cancer patients.

Prediction of body fat percentage: Development and validation of new anthropometric equations

INTRODUCTION

The aim of this study was to test the validity of existing equations, retrieved from the literature, in the Algerian adult population. To develop, and validate, new predictive equations for body fat percentage (%BF) using simple and easy-to-measure anthropometric parameters.

METHODS

This is a cross-sectional study including 877 Algerian adults who underwent a body composition assessment by the direct segmental multi-frequency bioelectrical impedance technique (Inbody-770). Participants were randomly divided into two groups: the development group (n = 577) and the validation group (n = 300). To develop the equations, multiple linear regression models were analyzed. The predictive performance of the developed equations was compared with the direct technique. The following validation tests were used: Student's t-test for paired samples, correlation, and Bland-Altman diagram. Diagnostic accuracy has also been assessed.

RESULTS

Four existing equations were tested, and all showed statically significant bias. Four new equations were developed; all had satisfactory predictive performance, with a correlation coefficient ranging from 0.72 to 0.94 in men and 0.87 to 0.93 in women. The best-fitting equation was based on body mass index, waist-to-hip ratio, and chest circumference. The diagnostic accuracy of this equation was 96.7% in men and 95.3% in women.

CONCLUSION

The newly developed equations based on anthropometric parameters can serve as a simple tool for the accurate prediction of BF% in adult subjects, at both individual and epidemiological levels.

Deuterium oxide validation of bioimpedance total body water estimates in Hispanic adults

Background

To date, body composition assessments in Hispanics, computed via bioimpedance devices, have primarily focused on body fat percent, fat mass, and fat-free mass instead of total body water (TBW). Additionally, virtually no information is available on which type of bioimpedance device is preferred for TBW assessments in Hispanic populations.

Purpose

The purpose of this study was to validate two bioimpedance devices for the estimate of TBW in Hispanics adults when using a criterion deuterium oxide (D2O) technique.

Methods

One-hundred thirty individuals (males: n = 70; females: n = 60) of Hispanic descent had TBW estimated via D2O, single-frequency bioimpedance analysis ([SF-BIA] Quantum V, RJL Systems) and bioimpedance spectroscopy ([BIS] SFB7 Impedimed).

Results

The mean values for SF-BIA were significantly lower than D2O when evaluating the entire sample (37.4 L and 38.2 L, respectively; p < 0.05). In contrast, TBW values were not statistically significant when comparing D2O against BIS (38.4 L, p > 0.05). Bland-Altman analysis indicated no proportional bias when evaluating the entire sample for SF-BIA or BIS. The standard error of estimate and total error values were ≤ 2.3 L and Lin's concordance correlation coefficient were ≥ 0.96 for all comparisons.

Conclusion

The SF-BIA and BIS devices evaluated in the current study hold promise for accurate estimation of TBW in Hispanic adults. While both methods demonstrated relatively low errors relative to the D2O criterion, BIS exhibited a more consistent performance, particularly at the group level. These findings provide essential information for researchers and clinical nutrition practitioners assessing TBW in Hispanic adults.

Body mass index and all-cause mortality in a 21st century U.S. population: A National Health Interview Survey analysis

INTRODUCTION

Much of the data on BMI-mortality associations stem from 20th century U.S. cohorts. The purpose of this study was to determine the association between BMI and mortality in a contemporary, nationally representative, 21st century, U.S. adult population.

METHODS

This was a retrospective cohort study of U.S. adults from the 1999-2018 National Health Interview Study (NHIS), linked to the National Death Index (NDI) through December 31st, 2019. BMI was calculated using self-reported height & weight and categorized into 9 groups. We estimated risk of all-cause mortality using multivariable Cox proportional hazards regression, adjusting for covariates, accounting for the survey design, and performing subgroup analyses to reduce analytic bias.

RESULTS

The study sample included 554,332 adults (mean age 46 years [SD 15], 50% female, 69% non-Hispanic White). Over a median follow-up of 9 years (IQR 5-14) and maximum follow-up of 20 years, there were 75,807 deaths. The risk of all-cause mortality was similar across a wide range of BMI categories: compared to BMI of 22.5-24.9 kg/m2, the adjusted HR was 0.95 [95% CI 0.92, 0.98] for BMI of 25.0-27.4 and 0.93 [0.90, 0.96] for BMI of 27.5-29.9. These results persisted after restriction to healthy never-smokers and exclusion of subjects who died within the first two years of follow-up. A 21-108% increased mortality risk was seen for BMI ≥30. Older adults showed no significant increase in mortality between BMI of 22.5 and 34.9, while in younger adults this lack of increase was limited to the BMI range of 22.5 to 27.4.

CONCLUSION

The risk of all-cause mortality was elevated by 21-108% among participants with BMI ≥30. BMI may not necessarily increase mortality independently of other risk factors in adults, especially older adults, with overweight BMI. Further studies incorporating weight history, body composition, and morbidity outcomes are needed to fully characterize BMI-mortality associations.

Learning Effects in Air Displacement Plethysmography

Air displacement plethysmography (ADP) is a widespread technique for assessing global obesity in both health and disease. The reliability of ADP has been demonstrated by studies focused on duplicate trials. The present study was purported to evaluate learning effects on the reliability of body composition assessment using the BOD POD system, the sole commercially available ADP instrument. To this end, quadruplicate trials were performed on a group of 105 subjects (51 women and 54 men). We estimated measurement error from pairs of consecutive trials-(1,2), (2,3), and (3,4)-to test the hypothesis that early measurements are subject to larger errors. Indeed, statistical analysis revealed that measures of reliability inferred from the first two trials were inferior to those computed for the other pairs of contiguous trials: for percent body fat (%BF), the standard error of measurement (SEM) was 1.04% for pair (1,2), 0.71% for pair (2,3), and 0.66% for pair (3,4); the two-way random effects model intraclass correlation coefficient (ICC) was 0.991 for pair (1,2), and 0.996 for pairs (2,3) and (3,4). Our findings suggest that, at least for novice subjects, the first ADP test should be regarded as a practice trial. When the remaining trials were pooled together, the reliability indices of single ADP tests were the following: ICC = 0.996, SEM = 0.70%, and minimum detectable change (MDC) = 1.93% for %BF, and ICC = 0.999, SEM = 0.49 kg, and MDC = 1.35 kg for fat-free mass (FFM). Thus, the present study pleads for eliminating learning effects to further increase the reliability of ADP.

Evaluation of Skinfold Techniques in People with Down Syndrome: Development of a New Equation

The primary aim of this study was to evaluate the accuracy of skinfold thickness (SFT) measurements for the estimation of %Fat when compared to dual energy X-ray absorptiometry (DXA) in individuals with Down syndrome (DS). The secondary aim was to develop a new SFT-based body fat equation (SFT_NICKERSON). SFT-based %Fat was estimated using a body fat equation from González-Agüero (SFT_G-A) and body density conversion formulas from Siri (SFT_SIRI) and Brozek (SFT_BROZEK). Criterion %Fat was measured via DXA. SFT_G-A, SFT_SIRI, and SFT_BROZEK were significantly lower than DXA (mean differences ranged from -7.59 to -13.51%; all p < 0.001). The SEE values ranged from 3.47% (SFT_BROZEK) to 8.60% (SFT_G-A). The 95% limits of agreement were greater than ±10% for all comparisons. Mid-axilla and suprailium were significant predictors of %Fat (both p < 0.05). %Fat SFT_NICKERSON = 10.323 + (0.661 × mid-axilla) + (0.712 × suprailium). Age and all other skinfold sites were not statically significant in the regression model (all p > 0.05). Current findings indicate that SFT_G-A, SFT_SIRI, and SFT_BROZEK erroneously place an individual with excessive adiposity in a normal healthy range. Accordingly, the current study developed a new equation (SFT_NICKERSON) that can easily be administered in people with DS in a quick and efficient time frame. However, further research is warranted in this area.

Imaging modalities for measuring body composition in patients with cancer: opportunities and challenges

Body composition assessment (ie, the measurement of muscle and adiposity) impacts several cancer-related outcomes including treatment-related toxicities, treatment responses, complications, and prognosis. Traditional modalities for body composition measurement include body mass index, body circumference, skinfold thickness, and bioelectrical impedance analysis; advanced imaging modalities include dual energy x-ray absorptiometry, computerized tomography, magnetic resonance imaging, and positron emission tomography. Each modality has its advantages and disadvantages, thus requiring an individualized approach in identifying the most appropriate measure for specific clinical or research situations. Advancements in imaging approaches have led to an abundance of available data, however, the lack of standardized thresholds for classification of abnormal muscle mass or adiposity has been a barrier to adopting these measurements widely in research and clinical care. In this review, we discuss the different modalities in detail and provide guidance on their unique opportunities and challenges.

Validity of anthropometric equation-based estimators of fat mass in Samoan adults

INTRODUCTION

In 1999, a set of highly accurate Polynesian-specific equations to estimate adult body fat from non-invasive field measures of age, sex, height, and weight (Equation 1), age, sex, height, weight, and bioelectrical impedance analysis (BIA) resistance (Equation 2), and age, sex, height, weight, and the sum of two skinfold thicknesses (Equation 3) were published. The purpose of this study was to evaluate the performance of the equation-based estimators in a sample of Samoan adults recruited 20 years later between 2017 and 2019.

METHODS

Age, sex, height, weight, BIA resistance, skinfold thickness, and fat mass as measured using dual energy x-ray absorptiometry (DXA) were available for 432 Samoan adults (mean age 50.9 years, 56% female) seen in 2017/2019. We compared equation-derived fat mass and DXA-derived fat mass using scatterplots and Pearson correlation coefficients. We then updated the equation coefficient estimates in a training set (2/3 of the sample) and evaluated the performance of the updated equations in a testing set (the remaining 1/3 of the sample).

RESULTS

Equation-derived fat mass was strongly correlated with DXA-derived fat mass for Equation (1) (r2  = 0.95, n = 432), Equation (2) (r2  = 0.97, n = 425), and Equation (3) (r2  = 0.95, n = 426). Updating the equation coefficient estimates resulted in mostly similar coefficients and nearly identical testing set performance for Equation (1) (r2  = 0.96, n = 153), Equation (2) (r2  = 0.98, n = 150), and Equation (3) (r2  = 0.96, n = 150).

CONCLUSIONS

The Polynesian-specific body fat estimation equations remained stable despite changing social and environmental factors and marked increase in obesity prevalence in Samoa.

A comparison of associations of body mass index and dual-energy x-ray absorptiometry measured percentage fat and total fat with global serum metabolites in young women

OBJECTIVE

Body mass index (BMI) does not directly measure adiposity, whereas dual-energy x-ray absorptiometry (DXA) provides valid direct estimates of adiposity. Therefore, this study evaluated usefulness of BMI as a measure of adiposity in serum metabolomics studies.

METHODS

A cross-sectional analysis was conducted of 202 women aged 25 to 29 years in the Dietary Intervention Study in Children Follow-Up Study. Heights and weights were measured, and body composition was quantified using clinical DXA protocols. Serum metabolomic profiling was performed by liquid chromatography-tandem mass spectrometry. Partial correlations of BMI, percentage fat (%FAT), and total fat (TOTFAT) with log transformed serum metabolites were calculated.

RESULTS

There was significant overlap in the 93 metabolites that correlated with BMI, %FAT, and/or TOTFAT; 9 differently correlated with BMI and %FAT, whereas 15 differently correlated with BMI and TOTFAT. Even for these metabolites, absolute differences were modest. Metabolite set enrichment analysis identified diacylglycerol and sphingolipid metabolism as overrepresented among metabolites significantly correlated with all three measures of adiposity.

CONCLUSIONS

BMI can be a good proxy for DXA measured %FAT and TOTFAT in descriptive metabolomic studies of healthy, young White women. Larger studies in more diverse populations are needed to endorse more generalized conclusions.

Dual energy X-ray absorptiometry produces larger measurement error in non-Hispanic Caucasians than Hispanics

BACKGROUND

Dual energy X-ray absorptiometry (DXA) is often used as a criterion measure in body composition research and in clinical settings for the estimate of body fat percent (%Fat). The accuracy of DXA for predicting %Fat has primarily been conducted in non-Hispanic populations.

AIM

The purpose of this study was to determine the agreement of DXA-derived %Fat in Hispanic and non-Hispanic Caucasian adults.

METHODS

The sample consisted of Hispanic males (n = 96) and females (n = 102) and non-Hispanic Caucasian males (n = 145) and females (n = 161). The %Fat of a whole-body DXA scan was compared against a criterion 4-compartment (4C) model via constant error (CE = DXA - 4C model) and 95% limits of agreement. Also, a 2 × 2 factorial ANOVA, using CE as a dependent variable, was conducted to examine the main and interaction effects of sex and ethnicity.

RESULTS

When compared to the 4C model, DXA overestimated %Fat by 4.0% in Hispanics and 5.5% in non-Hispanic Caucasians (all p < 0.05). The 95% limits of agreement ranged from ±5.5% to ±5.9% for all group comparisons. The 2 × 2 factorial ANOVA indicated the CE was greater in non-Hispanic Caucasians than Hispanics (CE difference = 1.5%; p < 0.05).

CONCLUSION

Our findings revealed that DXA significantly overestimates %Fat in both populations (Hispanics and non-Hispanic Caucasians), when compared to a 4C model, regardless of sex (male or female). However, the error is more profound in non-Hispanic Caucasian adults. It is worth nothing that DXA may be useful for tracking changes in body composition that occur throughout a lifestyle intervention. Nonetheless, practitioners should be aware that the estimate of %Fat from DXA may be larger than the actual values obtained from a 4C model.

Body composition and functional correlates of CF youth experiencing pulmonary exacerbation and recovery

BACKGROUND

Youth with cystic fibrosis (CF) and pulmonary exacerbation (PEx) often experience weight loss, then rapid weight gain. Little is known about body composition and its relationship to functional outcomes during this critical period.

METHODS

Twenty CF youth experiencing PEx were assessed on the day following admission and 7-17 days later at discharge for body mass index (BMI), fat mass index (FMI), lean mass index (LMI), skeletal muscle mass index (SMMI), and functional measures: percent predicted forced expiratory volume in 1 second (FEV1) (ppFEV1), maximal inspiratory and expiratory pressures (MIPs and MEPs), and handgrip strength (HGS). Changes from admission to discharge and correlations among body composition indices and functional measures at both times are reported.

RESULTS

Upon admission, participant BMI percentile and ppFEV1 varied from 2 to 97 and 29 to 113, respectively. Thirteen had an LMI below the 25th percentile and nine had a percent body fat above the 75th percentile. BMI and FMI increased significantly (p = 0.03, 0.003) during hospitalization. LMI and SMMI did not change. FEV1 and MIPS increased (p = 0.0003, 0.007), independent of weight gain, during treatment. HGS did not improve.

CONCLUSIONS

Many youth with CF, independent of BMI, frequently carried a small muscle mass and disproportionate fat at the time of PEx. During hospital treatment, weight gain largely represented fat deposition; muscle mass and strength did not improve. A need for trials of interventions designed to augment muscle mass and function, and limit fat mass accretion, at the time of PEx is suggested by these observations.

Smartwatch-based bioimpedance analysis for body composition estimation: precision and agreement with a 4-compartment model

Given that the prevalence of smartwatches has allowed them to become a hallmark in health monitoring, they are primed to provide accessible body composition estimations. The purpose of this study was to evaluate the precision and agreement of smartwatch-based bioimpedance analysis (SW-BIA) and multifrequency bioimpedance analysis (MFBIA) against a 4-compartment (4C) model criterion. A total of 186 participants (114 females) underwent body composition assessments necessary for a 4C model and SW-BIA and MFBIA. Values of total body water (TBW) from each device were compared with those obtained from bioimpedance spectroscopy. Precision was adequate though slightly lower for the smartwatch compared with other methods. No device demonstrated equivalence with the 4C model. Specifically, the SW-BIA overestimated and MFBIA underestimated body fat. MFBIA, but not SW-BIA, demonstrated equivalence for TBW. Overall error was higher for males using the smartwatch compared with females. While these findings do not invalidate the use of smartwatch-based estimates, clinicians should consider that there may be large errors relative to clinical measures. If this wearable device is intended to be used to monitor body composition change over time, these findings demonstrate the need for future research to evaluate its accuracy during follow-up testing.

The role of predicted lean body mass and fat mass in non-alcoholic fatty liver disease in both sexes: Results from a secondary analysis of the NAGALA study

Objective

High body mass index (BMI) is an important risk factor for non-alcoholic fatty liver disease (NAFLD). However, the association of body composition such as fat mass (FM) and lean body mass (LBM) with NAFLD has not been adequately studied. The purpose of this study was to clarify the contribution of body composition FM and LBM to NAFLD.

Methods

We analyzed data from 7,411 men and 6,840 women in the NAGALA cohort study. LBM and FM were estimated for all subjects using validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey (NHANES). Using multiple logistic regression and restricted cubic spline (RCS) to analyze the association and the dose-response curve of predicted LBM and FM with NAFLD in both sexes.

Results

The prevalence of NAFLD in man and woman subjects was 27.37 and 6.99%, respectively. Predicted FM was positively and linearly associated with NAFLD in both sexes, with each 1 kg increase in predicted FM associated with a 27 and 40% increased risk of NAFLD in men and women, respectively. In contrast, predicted LBM was negatively associated with NAFLD in both sexes, with each 1 kg increase in predicted LBM reducing the risk of NAFLD by 4 and 19% in men and women, respectively. In addition, according to the RCS curve, the risk of NAFLD did not change in men when the predicted LBM was between 47 and 52 kg, and there seemed to be a saturation effect; further, the threshold value of the saturation effect was calculated to be about 52.08 kg by two-piecewise logistic regression, and the protective effect on NAFLD would be significantly enhanced when the man predicted LBM was greater than 52.08 kg.

Conclusion

The current findings suggested that body composition LBM and FM had opposite associations with NAFLD in both sexes, with higher LBM associated with a lower risk of NAFLD and higher FM increasing the risk of NAFLD, especially in women.

Comparison of body fat percentage assessments by bioelectrical impedance analysis, anthropometrical prediction equations, and dual-energy X-ray absorptiometry in older women

Background

Individuals with high body fat have a higher risk of mortality. Numerous anthropometric-based predictive equations are available for body composition assessments; furthermore, bioelectrical impedance analysis (BIA) estimates are available. However, in older adults, the validity of body fat estimates requires further investigation.

Objective

To assess the agreement between percentage body fat (BF%) estimates by BIA and five predictive equations based on anthropometric characteristics using dual X-ray absorptiometry (DXA) as reference method. A secondary objective was to identify whether excluding short-stature women improves the agreement of BF% estimates in a group of community-dwelling, older Mexican women.

Methods

A concordance analysis of BF% was performed. A total of 121 older women participated in the study. Anthropometric information, BIA, and DXA body composition estimates were obtained. Five equations using anthropometric data were evaluated in order to determine body fat percentage (BF%) using DXA as reference method. Paired t-test comparisons and standard error of estimates (SEE) were obtained. The Bland-Altman plot with 95% limits of agreement and the concordance correlation coefficient (CCC) were used to evaluate the BF% prediction equations and BIA estimates.

Results

The mean age of the study participants was 73.7 (±5.8) years old. BIA and the anthropometric based equations examined showed mean significant differences when tested in the entire sample. For the taller women (height > 145 cm), no significant difference in the paired comparison was found between DXA and BIA of BF% estimates. The mean BF% was 40.3 (±4.8) and 40.7 (±6.2) for DXA and BIA, respectively. The concordance between methods was good (CCC 0.814), (SEE 2.62). Also, in the taller women subset, the Woolcott equation using waist-to-height ratio presented no significant difference in the paired comparison; however, the error of the estimates was high (SEE 3.37) and the concordance was moderate (CCC 0.693).

Conclusion

This study found that BIA yielded good results in the estimation of BF% among women with heights over 145 cm. Also, in this group, the Woolcott predictive equation based on waist circumference and height ratio showed no significant differences compared to DXA in the paired comparison; however, the large error of estimates observed may limit its application. In older women, short stature may impact the validity of the body fat percentage estimates of anthropometric-based predictive equations.

improvement of cardiorespiratory fitness in healthy women after a 12-week Classical Pilates training

Aims: to evaluate the effects of 12 weeks of Pilates training (Classical Method) on cardiorespiratory fitness and heart rate responses of healthy sedentary women. Method: fifteen women (average age 29±4) performed 12 weeks of Pilates training for 60 minutes, three times per week (Pilates Group). Thirteen women (average age 29±5) as controls maintained their routine activities (Control Group). The exercises’ introduction was by the degree of difficulty with changes in the plane of movements; smaller base of support; spinal rotations and extensions; use of abdominal muscles in prone position. Heart rate was monitored and recorded during all sessions using a heart frequency meter. Results: ANOVA analysis results revealed significant difference in Pilates Group (p < 0.05) between pre and post measures of VO2peak (+13%), fat percentage (- 3.3%), free fat mass (+ 2.8 kg), and muscular endurance in the abdominal area (+61%), lower limbs (+75%) and upper limbs (+68%). The percent of Maximum Heart Rate achieved in the 6th (79.25%) and 12th (79.86%) weeks of training increased from the first week (73.4%). Physical fitness in Control Group remained unchanged. Conclusion: twelve weeks of Pilates training positively affected overall physical fitness in previously sedentary healthy women. Furthermore, the increase in VO2peak and achieved Maximum Heart Rate was significant even with no specific aerobic training.

Associations between visceral adipose tissue estimates produced by near-infrared spectroscopy, mobile anthropometrics, and traditional body composition assessments and estimates derived from dual-energy X-ray absorptiometry

Assessments of visceral adipose tissue (VAT) are critical in preventing metabolic disorders; however, there are limited measurement methods that are accurate and accessible for VAT. The purpose of this cross-sectional study was to evaluate the association between VAT estimates from consumer-grade devices and traditional anthropometrics and VAT and subcutaneous adipose tissue (SAT) from dual-energy X-ray absorptiometry (DXA). Data were collected from 182 participants (female = 114; White = 127; Black/African-American (BAA) = 48) which included anthropometrics and indices of VAT produced by near-infrared reactance spectroscopy (NIRS), visual body composition (VBC) and multifrequency BIA (MFBIA). VAT and SAT were collected using DXA. Bivariate and partial correlations were calculated between DXAVAT and DXASAT and other VAT estimates. All VAT indices had positive moderate–strong correlations with VAT (all P < 0·001) and SAT (all P < 0·001). Only waist:hip (r = 0·69), VATVBC (r = 0·84), and VATMFBIA (r = 0·86) had stronger associations with VAT than SAT (P < 0·001). Partial associations between VATVBC and VATMFBIA were only stronger for VAT than SAT in White participants (r = 0·67, P < 0·001) but not female, male, or BAA participants individually. Partial correlations for waist:hip were stronger for VAT than SAT, but only for male (r = 0·40, P < 0·010) or White participants (r = 0·48, P < 0·001). NIRS was amongst the weakest predictors of VAT which was highest in male participants (r = 0·39, P < 0·010) but non-existent in BAA participants (r = –0·02, P > 0·050) after adjusting for SAT. Both anthropometric and consumer-grade VAT indices are consistently better predictors of SAT than VAT. These data highlight the need for a standardised, but convenient, VAT estimation protocol that can account for the relationship between SAT and VAT that differs by sex/race.

Cross-sectional and longitudinal associations between subcutaneous adipose tissue thickness and dual-energy X-ray absorptiometry fat mass

The present study examined cross-sectional and longitudinal relationships between total and segmental subcutaneous tissue thicknesses from ultrasonography (US) and total and segmental fat mass (FM) estimates from dual-energy X-ray absorptiometry (DXA). Traditional US FM estimates were also examined. Twenty resistance-trained males (mean ± SD; age: 22.0 ± 2.6 years; body mass: 74.8 ± 11.5 kg; DXA fat: 17.5 ± 4.5%) completed a 6-week supervised resistance training programme while consuming a hypercaloric diet. Pre- and post-intervention body composition was assessed by DXA and B-mode US. Data were analysed using Pearson's correlation (r), Lin's correlation coefficient (CCC), paired t-tests, Wilcoxon signed-rank tests and Bland-Altman analysis, as appropriate. Cross-sectionally, correlations were observed between total DXA FM and total subcutaneous tissue thickness (r = 0.88). Longitudinally, a correlation was observed between total DXA FM changes and total subcutaneous tissue changes (r = 0.49, CCC = 0.38). Correlations of similar magnitudes were observed for the upper body and trunk estimates, but DXA FM changes were unrelated to subcutaneous tissue changes for the lower body and arms. Cross-sectionally, US 2-compartment FM and DXA FM were correlated (r = 0.91, CCC = 0.83). Longitudinally, a weaker correlation was observed (r = 0.47, CCC = 0.33). In summary, longitudinal associations between US and DXA are weaker than cross-sectional relationships; additionally, correlations between US subcutaneous tissue and whole-body DXA FM appear to be driven by the trunk region rather than appendages. Reporting raw skinfold thicknesses rather than FM estimates alone may improve the utility of techniques based on subcutaneous tissue thickness, such as US and skinfolds.