From BMI to functional body composition

Predictive Roles of Basal Metabolic Rate and Muscle Mass in Lung Function among Patients with Obese Asthma: A Prospective Cohort Study

BACKGROUND

The metabolic-status-related mechanisms underlying the deterioration of the lung function in obese asthma have not been completely elucidated.

OBJECTIVE

This study aimed to investigate the basal metabolic rate (BMR) in patients with obese asthma, its association with the lung function, and its mediating role in the impact of obesity on the lung function.

METHODS

A 12-month prospective cohort study (n = 598) was conducted in a real-world setting, comparing clinical, body composition, BMR, and lung function data between patients with obese (n = 282) and non-obese (n = 316) asthma. Path model mediation analyses for the BMR and skeletal muscle mass (SMM) were conducted. We also explored the effects of the BMR on the long-term lung function in patients with asthma.

RESULTS

Patients with obese asthma exhibited greater airway obstruction, with lower FEV1 (1.99 vs. 2.29 L), FVC (3.02 vs. 3.33 L), and FEV1/FVC (65.5 vs. 68.2%) values compared to patients with non-obese asthma. The patients with obese asthma also had higher BMRs (1284.27 vs. 1210.08 kcal/d) and SMM (23.53 vs. 22.10 kg). Both the BMR and SMM mediated the relationship between obesity and the lung function spirometers (FEV1, %FEV1, FVC, %FVC, and FEV1/FVC). A higher BMR or SMM was associated with better long-term lung function.

CONCLUSIONS

Our study highlights the significance of the BMR and SMM in mediating the relationship between obesity and spirometry in patients with asthma, and in determining the long-term lung function. Interventions for obese asthma should focus not only on reducing adiposity but also on maintaining a high BMR.

Insulin Resistance and N-Terminal Pro-B-Type Natriuretic Peptide Among Healthy Adults

Importance

It is unclear to what extent insulin resistance is associated with N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the general population after accounting for body composition.

Objective

To characterize the association of insulin resistance with NT-proBNP independently of measures of body composition in US adults.

Design, Setting, and Participants

In a cross-sectional design, data on participants aged 20 years or older were obtained from the 1999-2004 National Health and Nutrition Examination Survey with measures of NT-pro-BNP, body mass index (BMI), and dual energy x-ray absorptiometry (DEXA)-derived measures of body composition (fat and lean masses). Linear and logistic regression was used to characterize the associations of measures of body mass and composition (BMI, waist circumference, fat mass, and lean mass) with NT-proBNP, adjusting for cardiovascular risk factors. Linear regression was used to characterize the associations of homeostasis model assessment of insulin resistance [HOMA-IR] and NT-proBNP after adjusting for cardiovascular risk factors and body composition measures. The quantitative insulin sensitivity check index [QUICKI], triglyceride-glucose index [TyG index], insulin to glucose ratio [IGR], fasting insulin, and homeostasis model assessment of β-cell function (HOMA-β) were also examined. Data for this study were analyzed from August 10, 2022, to June 30, 2023.

Main Outcomes and Measures

Adjusted changes in NT-proBNP by insulin resistance levels.

Results

A total of 4038 adults without diabetes or cardiovascular disease were included (mean [SD] age, 44 years; 51.2% female; and 74.3% White). In sex-specific analyses, insulin resistance measures were inversely associated with NT-pro-BNP. After adjustment including cardiovascular risk factors, BMI, waist circumference, and DEXA-derived fat mass and lean mass, the percent change in NT-proBNP associated with an SD increase in HOMA-IR was -16.84% (95% CI, -21.23% to -12.21%) in women and -19.04% (95% CI, -24.14 to -13.59) in men. Similar associations were observed for other indices of insulin resistance, including QUICKI (women: 17.27; 95% CI, 10.92-23.99 vs men: 22.17; 95% CI, 15.27 to 29.48), TyG index women: -11.47; 95% CI, -16.12 to -6.57 vs men: -15.81; 95% CI, -20.40 to -10.95), IGR women: -15.15; 95% CI, -19.35 to -10.74 vs men: -16.61; 95% CI, -21.63 to -11.26), and fasting insulin (women: -16.32; 95% CI, -20.63 to -11.78 vs men: -18.22; 95% CI, -23.30 to -12.79), as well as HOMA-β (women: -10.71; 95% CI, -14.71 to -6.52 vs men: -11.72; 95% CI, -16.35 to -6.85).

Conclusions and Relevance

In a national sample of US adults, insulin resistance was inversely associated with NT-proBNP, even after rigorously accounting for multiple measures of fat mass and lean mass. These results suggest that the mechanisms linking NT-proBNP to insulin resistance are partially independent of excess adiposity and may be associated with hyperinsulinemia.

Body Composition Measures and N-terminal pro-B-type Natriuretic Peptide (NT-pro-BNP) in US Adults

BACKGROUND

The associations of N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) with dual energy x-ray absorptiometry (DEXA)-derived measures of body mass and composition are largely unknown.

METHODS

We included participants aged ≥20 years from the 1999-2004 National Health and Nutrition Examination Survey with NT-pro-BNP and DEXA-derived body composition (fat and lean mass) measures. We used linear and logistic regression to characterize the associations of measures of body mass and composition (body mass index [BMI], waist circumference [WC], fat mass, and lean mass) with NT-pro-BNP, adjusting for cardiovascular risk factors.

RESULTS

We conducted sex-specific analyses among 9134 adults without cardiovascular disease (mean age 44.4 years, 50.8% women, and 72% White adults). The adjusted mean NT-proBNP values were lowest in the highest quartiles of BMI, WC, fat mass, and lean mass. There were large adjusted absolute differences in NT-pro-BNP between the highest and lowest quartiles of DEXA-derived lean mass, -6.26 pg/mL (95% confidence interval [CI], -8.99 to -3.52) among men and -22.96 pg/mL (95% CI, -26.83 to -19.09) among women. Lean mass exhibited a strong inverse association with elevated NT-pro-BNP ≥ 81.4 pg/mL (highest quartile) - odds ratio (OR) 0.58 (95% CI, 0.39-0.86) in men and OR 0.59 (95% CI, 0.47-0.73) in women for highest lean mass quartile vs. lowest quartile. Further adjustment for fat mass, BMI, or WC did not appreciably alter the inverse association of lean mass with NT-pro-BNP.

CONCLUSIONS

In a national sample of US adults, lean mass was inversely associated with NT-pro-BNP.

Longitudinal analyses of serum neurofilament light and associations with obesity indices and bioelectrical impedance parameters

Neurofilament light is a constituent of the neuronal cytoskeleton and released into the blood following neuro-axonal damage. It has previously been reported that NfL measured in blood serum is inversely related to body mass index. However, no reports exist with regard to body composition assessed using bioelectrical impedance analysis or other indicators of obesity beyond BMI. We analyzed the relationship between sNfL and body composition according to the three compartment model. Additionally, associations between sNfL, body shape index, waist-to-height ratio, and BMI were examined. The sample consisted of 769 participants assessed during the baseline examination and 693 participants examined in the course of the follow-up of the BiDirect Study. Associations between sNfL, BMI, BSI, and WtHR were separately analyzed using linear mixed models. Body compartments operationalized as fat mass, extracellular cell mass, and body cell mass were derived using BIA and the relationship with sNfL was analyzed with a linear mixed model. Lastly, we also analyzed the association between total body water and sNfL. We found significant inverse associations of sNfL with BMI and WtHR. The analysis of the three compartment model yielded significant inverse associations between sNfL, body cell mass and body fat mass, but not extracellular mass. Furthermore, total body water was also inversely related to sNfL. A potential mechanism could involve body cell mass and body fat mass as highly adaptive body constituents that either directly absorb sNfL, or promote the formation of new vasculature and thereby increase blood volume.

Different associations between waist circumference and bone mineral density stratified by gender, age, and body mass index

Introduction

Investigations of the relationship between waist circumference (WC) and bone mineral density (BMD) have inconsistent and incomprehensive results.

We explored the association between WC and BMD at various sites in a large-scale population-based study.

Methods

We screened 5337 participants from National Health and Nutrition Examination Survey (NHANES) database. BMD was measured using dual-energy X-ray absorptiometry at various skeletal sites. The associations of WC with BMD were evaluated by weighted multivariable logistic regression models and conducted subgroup analyses for gender, age, and BMI. A weighted generalized additive model and a smooth curve fitting were performed to address non-linearity.

Results

Adjustments for all confounders, in males, WC was negatively correlated to BMD in different age and BMI groups (all the p < 0.05), except for in the lowest BMI group; in females, overall trends of relationships between WC and BMD were negative. However, statistical differences were insignificant in some cases. Additionally, every 1 cm increase in WC for individuals of all ages with normal BMI (18.5 ≤ BMI < 25) was associated with decrease in BMD at each skeletal site, as was the case for men with BMI ≥ 25 kg/m². For women, the negative association of WC with BMD was evident at the lumbar spine in the youngest age group (8 ≤ Age ≤ 18) with normal BMI.

Conclusions

The nonlinear associations between WC and BMD at various skeletal sites are gender-, age- and BMI-specific in the NHANES (2006–2006).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05736-5.

Barbosa F, Fleury M. Predictive Equations Overestimated the Rest Energy Expenditure by Indirect Calorimetry in Adults with Sickle Cell Disease

Background: Traditionally, hypermetabolism is described in sickle cell disease (SCD). Despite this, few studies have compared rest energy expenditure (REE) with estimated by predictive equations (EEE) in the assessment of adults with SCD. Aims:  To compare REE values determined by indirect calorimetry (IC) with that EEE in adults with SCD. Subjects and Methods: A cross-sectional observational study was performed with 46 individuals over 34 years old in the treatment from two reference centers for SCD located in the city of Rio de Janeiro, Brazil. The dual-energy X-ray absorptiometry (DXA) and IC  were used to assess BC and REE, respectively. Blood levels were measured to assess hemolytic and protein markers. Pearson’s correlation test was used in the univariate correlation. The Intraclass Correlation Coefficient (ICC) and the Bland-Altman analysis were used in the comparison between EEE and IC. P-values ≤ 0.05 were considered statistically significant. Results: Most participants were from the female sex, Hb SS genotype (80.4%) and with black color (52.2%). The mean age was 50 years old. Weight (r= 0.469; p=0,001), LM (r = 0.631; p=0.000), BMC (r = 0.508; p=0.000) and CRP(r=0.319; p = 0.002) correlated positively with the REE. There was no linear correlation between makers of hemolysis with REE. The REE was overestimated in the EEE when compared to IC (p<0.001). Conclusions: The prediction equations developed for healthy populations are not accurate enough to determine the energy requirements and more studies are needed to better understand how REE role in middle-aged and elderly adults with SCD.

Body Composition-Specific Asthma Phenotypes: Clinical Implications

Background: Previous studies have indicated the limitations of body mass index for defining disease phenotypes. The description of asthma phenotypes based on body composition (BC) has not been largely reported. Objective: To identify and characterize phenotypes based on BC parameters in patients with asthma. Methods: A study with two prospective observational cohorts analyzing adult patients with stable asthma (n = 541 for training and n = 179 for validation) was conducted. A body composition analysis was performed for the included patients. A cluster analysis was conducted by applying a 2-step process with stepwise discriminant analysis. Logistic regression models were used to evaluate the association between identified phenotypes and asthma exacerbations (AEs). The same algorithm for cluster analysis in the independent validation set was used to perform an external validation. Results: Three clusters had significantly different characteristics associated with asthma outcomes. An external validation identified the similarity of the participants in training and the validation set. In the training set, cluster Training (T) 1 (29.4%) was “patients with undernutrition”, cluster T2 (18.9%) was “intermediate level of nutrition with psychological dysfunction”, and cluster T3 (51.8%) was “patients with good nutrition”. Cluster T3 had a decreased risk of moderate-to-severe and severe AEs in the following year compared with the other two clusters. The most important BC-specific factors contributing to being accurately assigned to one of these three clusters were skeletal muscle mass and visceral fat area. Conclusion: We defined three distinct clusters of asthma patients, which had distinct clinical features and asthma outcomes. Our data reinforced the importance of evaluating BC to determining nutritional status in clinical practice.

Validation of the English Version of the General Dietary Behavior Inventory (GDBI-E)

In medical science and practice, dietary behavior is mostly assessed by item-extensive questionnaires (e.g., food-frequency-questionnaires) or by questionnaires focusing on psychological aspects of dietary behavior neglecting dietary quality or quantity. In consequence, these questionnaires do not capture the full bandwidth of dietary behavior or are less effective in the assessment of dietary behavior because of the large item pools. Therefore, the aim of this validation study was to translate the existing General Dietary Behavior Inventory (GDBI), which was constructed as a behavior-related, as well as effective, instrument, and verifying its construct and criterion validity. This inventory is based on the general nutrition recommendations of the World Health Organization (WHO). Our English-speaking convenience sample consisted of 263 participants. The study results confirmed convergent, as well as criterion validity of the English version of the GDBI (GDBI-E). Discriminant validity of the GDBI-E could mainly be verified. Different dietary behavior clusters were identified in a cluster analysis. The found clusters represented a rather healthy and a rather unhealthy dietary behavior in the sample according to the recommendations of the WHO. The results underpinned the validity of the GDBI-E. The GDBI-E is applicable in research and clinical practice to assess dietary behavior in the English-speaking population.

Association Between Adipose Tissue Proton Density Fat Fraction, Resting Metabolic Rate and FTO Genotype in Humans

BACKGROUND

The difference of proton density fat fraction (PDFF) between supraclavicular and gluteal adipose tissue might indicate the presence of brown adipose tissue (BAT). Aim of this cross-sectional study was to investigate the association between PDFF over the supraclavicular fat region as a proxy of BAT proportion and resting metabolic rate (RMR). In addition, the association between the single nucleotide polymorphism (SNP) rs1421085 at the fat mass and obesity associated (FTO) gene locus and both PDFF and RMR was investigated.

METHODS

Anthropometric, clinical, and lifestyle data from 92 healthy adults (66.3% females, mean age: 36.2 ± 13.0 years, mean body mass index: 24.9 ± 5.4 kg/m²) were included in the analysis. The RMR was measured by indirect calorimetry. The magnetic resonance imaging (MRI) was used for the measurement of visceral and subcutaneous adipose tissue (VAT, SAT) volumes and for the measurement of adipose tissue PDFF.

RESULTS

Mean RMR of the whole group was 1 474.8 ± 242.2 kcal. Genotype data was available for 90 participants. After adjustment for age, sex, weight change and fat-free mass (FFM), no association was found between supraclavicular PDFF (p = 0.346) and gluteal PDFF (p = 0.252), respectively, and RMR, whereas statistically significant evidence for a negative association between delta PDFF (difference between gluteal PDFF and supraclavicular PDFF) and RMR (p = 0.027) was obtained. No statistically significant evidence was observed for per FTO risk allele change in RMR, gluteal and supraclavicular PDFF maps or volumes of VAT and SAT.

CONCLUSIONS

Supraclavicular PDFF as a surrogate marker of BAT presence is not a determinant of RMR under basal conditions. In the present study, the FTO rs1421085 variant is not associated with either RMR or PDFF. Further studies are needed to elucidate the effect of BAT on RMR.

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.

Body composition-related functions: a problem-oriented approach to phenotyping

AIM

The objective of this study is to generate metabolic phenotypes based on structure-function relationships.

METHODS

In 459 healthy adults (54% females, 18 and 40 years old), we analyzed body composition by air-displacement densitometry (to assess fat mass, (FM) and fat-free mass (FFM)) and whole-body magnetic resonance imaging (to assess skeletal muscle mass (SMM) and masses of brain, heart, liver, kidneys, and subcutaneous (SAT) and visceral adipose tissue (VAT)), resting energy expenditure (REE) by indirect calorimetry, and plasma concentrations of insulin (Ins) and leptin (Lep).

RESULTS

Three "functional body composition-derived phenotypes" (FBCPs) were derived: (1) REE on FFM-FBCP, (2) Lep on FM-FBCP, and (3) Ins on VAT-FBCP. Assuming that being within the ± 5% range of the respective regression lines reflects a "normal" structure-function relationship, three "normal" FBCPs were generated with prevalences of 9.0%, 5.1%, and 6.8%, respectively, of the study population. The three "FBCPs" did not overlap and were independent from each other. When compared with the two other FBCPs, the "Lep on FM-FBCP" was leanest, whereas the "REE on FFM-FBCP" had the highest BMI and SAT. Taking into account FFM composition, a hierarchical multi-level model is proposed with brain at level 1, the liver at level 2, and SMM and FM at level 3 with insulin coordinating the interplay between level 1 and 2, whereas variance in plasma insulin levels impacts energy and substrate metabolism in SMM and AT.

CONCLUSION

Structure-function relationships can be used to generate FBCPs. Different FBCPs reflect different dimensions of normality (or health). This is evidence for the idea that there is no across the board "normal" state.

Recent advances in understanding body weight homeostasis in humans

Presently, control of body weight is assumed to exist, but there is no consensus framework of body weight homeostasis. Three different models have been proposed, with a "set point" suggesting (i) a more or less tight and (ii) symmetric or asymmetric biological control of body weight resulting from feedback loops from peripheral organs and tissues (e.g. leptin secreted from adipose tissue) to a central control system within the hypothalamus. Alternatively, a "settling point" rather than a set point reflects metabolic adaptations to energy imbalance without any need for feedback control. Finally, the "dual intervention point" model combines both paradigms with two set points and a settling point between them. In humans, observational studies on large populations do not provide consistent evidence for a biological control of body weight, which, if it exists, may be overridden by the influences of the obesogenic environment and culture on personal behavior and experiences. To re-address the issue of body weight homeostasis, there is a need for targeted protocols based on sound concepts, e.g. lean rather than overweight subjects should be investigated before, during, and after weight loss and weight regain. In addition, improved methods and a multi-level-multi-systemic approach are needed to address the associations (i) between masses of individual body components and (ii) between masses and metabolic functions in the contexts of neurohumoral control and systemic effects. In the future, simplifications and the use of crude and non-biological phenotypes (i.e. body mass index and waist circumference) should be avoided. Since changes in body weight follow the mismatch between tightly controlled energy expenditure at loosely controlled energy intake, control (or even a set point) is more likely to be about energy expenditure rather than about body weight itself.

Functional correlates of detailed body composition in healthy elderly subjects

Methods of body composition analysis are now widely used to characterize health status, i.e., nutritional status, metabolic rates, and cardiometabolic risk factors. However, the functional correlates of individual body components have not been systematically analyzed. In this study, we have used a two-compartment model, which was assessed by air displacement plethysmography. Detailed body composition was measured by whole body magnetic resonance imaging in a healthy population of 40 Caucasians, aged 65–81 yr (20 men; body mass index range: 18.6–37.2 kg/m2). Physical, metabolic, as well as endocrine functions included pulmonary function, handgrip strength, gait speed, sit-to-stand test, physical activity, blood pressure, body temperature, resting energy expenditure (REE), liver and kidney functions (glomerular filtration rate), insulin sensitivity [homeostasis model assessment (HOMA)], plasma lipids, plasma leptin, testosterone, dehydroepiandrosterone, insulin-like growth factor I levels, thyroid status, vitamins, and inflammation. Individual body compartments were intercorrelated, e.g., skeletal muscle mass (SM) correlated with visceral adipose tissue ( r = 0.53) and kidneys ( r = 0.62). For the functional correlates, SM ( r = 0.58) and liver volume ( r = 0.63) were associated with REE, SM correlated with handgrip strength ( r = 0.57), and kidneys with glomerular filtration rate ( r = 0.57). While visceral adipose tissue correlated with HOMA ( r = 0.59), subcutaneous adipose tissue was related to plasma leptin levels ( r = 0.84). The subcutaneous adipose tissue-to-leptin relationship was moderated by inflammation increasing the explained variance of leptin levels by 4.0%. In linear regression analysis, detailed body composition explained variances in REE (75.0%), HOMA (41.0%), and leptin (78.0%) compared with a body mass index-based model (REE 16.0%, HOMA 31.0%, leptin 45.0%). In addition, detailed body composition explained 39.0% of the variance in kidney function.

NEW & NOTEWORTHY BCA should be used to address specific body functions only. In clinical practice, there is need of a clear focus on the specific research question related to physical, metabolic, or endocrine functions.

Dual energy X-ray absorptiometry body composition reference values of limbs and trunk from NHANES 1999-2004 with additional visualization methods

Body Mass Index has traditionally been used as a measure of health, but Fat Mass Index (FMI) and Lean Mass Index (LMI) have been shown to be more predictive of mortality and health risk. Total body FMI and LMI reference curves have particularly been useful in quantifying sarcopenia and sarcopenic obesity. Research has shown regional composition has significant associations to health outcomes. We derived FMI and LMI reference curves of the regions of the body (leg, arm, and trunk) for 15,908 individuals in the 1999-2004 National Health and Nutrition Examination Survey data for each sex and ethnicity using the Lambda-Mu-Sigma (LMS) method and developed software to visualize this regional composition. These reference curves displayed differentiation between males and females during puberty and sharper limb LMI declines during late adulthood for males. For adults ages 30-50, females had 39%, 83%, and 47% larger arm, leg, and trunk FMI values than males, respectively. Males had 49%, 20%, and 15% higher regional LMI values than females for the arms, legs, and trunk respectively. The leg FMI and LMI of black females were 14% and 15% higher respectively than those of Hispanic and white females. White and Hispanic males had 37% higher trunk FMI values than black males. Hispanic females had 20% higher trunk FMI than white and black females. These data underscore the importance of accounting for sex and ethnicity in studies of regional composition. This study is the first to produce regional LMI and FMI reference tables and curves from the NHANES dataset. These reference curves provide a framework useful in studies and research involving sarcopenia, obesity, sarcopenic obesity, and other studies of compositional phenotypes. Further, the software tool we provide for visualizing regional composition will prove useful in monitoring progress in physical therapy, diets, or other attempts to attain healthier compositions.

Sex- and age-specific percentiles of body composition indices for Chinese adults using dual-energy X-ray absorptiometry

Purpose

The aims of the study were to develop sex- and age-specific percentiles for lean mass index (LMI), appendicular LMI (aLMI), fat mass index (FMI), and body fat distribution indices in Chinese adults using dual-energy X-ray absorptiometry (DXA), and to compare those indices with those of other ethnicities using the US NHANES data.

Methods

Whole-body and regional lean mass and fat mass (FM) were measured using DXA in 5688 healthy males (n = 1693) and females (n = 3995) aged 20–90 years. Body fat distribution indices were expressed as % fat trunk/% fat legs, trunk/appendicular FM ratio (FMR), and android/gynoid FMR. Percentile curves of LMI, aLMI, FMI, and body fat distribution indices were obtained by the Lambda–Mu–Sigma method.

Results

The aLMI and LMI were negatively associated with age, decreasing from the fifth decade for males, but were not associated with age in females. Females had more total FM than males, whereas males had greater central adiposity (% fat trunk/% fat legs ratio, trunk/appendicular FMR, and android/gynoid FMR) than females. Moreover, FMI and body fat distribution indices consistently increased with age in both sexes, especially in women. In comparison with white, black, and Mexican populations in the USA, Chinese adults had lower total FM, but had greater central adiposity (% fat trunk/% fat legs ratio and trunk/appendicular FMR). Additionally, older white and Mexican populations showed greater decreases for aLMI and LMI than their Chinese counterparts.

Conclusions

We present the sex- and age-specific percentiles for aLMI, LMI, FMI, and body fat distribution indices by DXA in Chinese adults, which may refine the individual assessment of the nutritional status of Chinese adults.

Obesity or obesities? Controversies on the association between body mass index and premature mortality

Obesity is still defined on the basis of body mass index (BMI) and BMI in itself is generally accepted as a strong predictor of overall early mortality. However, an inverse association between BMI and mortality has been reported in patients with many disease states and in several clinical settings: hemodialysis, cardiovascular diseases, hypertension, stroke, diabetes, chronic obstructive pulmonary disease, surgery, etc. This unexpected phenomenon is usually called obesity-survival paradox (OP). The contiguous concepts of metabolically healthy obesity (MHO, a phenotype having BMI ≥ 30 but not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance, HOMA, <2.5) and metabolically obese normal weight (MONW, normal-weight individuals displaying obesity-related phenotypic characteristics) have received a great deal of attention in recent years. The interactions that link MHO, MONW and OP with body composition, fat distribution, aging and cardiorespiratory fitness are other crucial areas of research. The article is an introductory narrative overview of the origin and current use of the concepts of MHO, MONW and OP. These phenomena are very controversial and appear as a consequence of the frail current diagnostic definition of obesity based only on BMI. A new commonly established characterization and classification of obesities based on a number of variables is needed urgently.

Beyond BMI: Conceptual Issues Related to Overweight and Obese Patients

BMI is widely used as a measure of weight status and disease risks; it defines overweight and obesity based on statistical criteria. BMI is a score; neither is it biologically sound nor does it reflect a suitable phenotype worthwhile to study. Because of its limited value, BMI cannot provide profound insight into obesity biology and its co-morbidity. Alternative assessments of weight status include detailed phenotyping by body composition analysis (BCA). However, predicting disease risks, fat mass, and fat-free mass as assessed by validated techniques (i.e., densitometry, dual energy X ray absorptiometry, and bioelectrical impedance analysis) does not exceed the value of BMI. Going beyond BMI and descriptive BCA, the concept of functional body composition (FBC) integrates body components into regulatory systems. FBC refers to the masses of body components, organs, and tissues as well as to their inter-relationships within the context of endocrine, metabolic and immune functions. FBC can be used to define specific phenotypes of obesity, e.g. the sarcopenic-obese patient. Well-characterized obesity phenotypes are a precondition for targeted research (e.g., on the genomics of obesity) and patient-centered care (e.g., adequate treatment of individual obese phenotypes such as the sarcopenic-obese patient). FBC contributes to a future definition of overweight and obesity based on physiological criteria rather than on body weight alone.

Application of standards and models in body composition analysis

The aim of this review is to extend present concepts of body composition and to integrate it into physiology. In vivo body composition analysis (BCA) has a sound theoretical and methodological basis. Present methods used for BCA are reliable and valid. Individual data on body components, organs and tissues are included into different models, e.g. a 2-, 3-, 4- or multi-component model. Today the so-called 4-compartment model as well as whole body MRI (or computed tomography) scans are considered as gold standards of BCA. In practice the use of the appropriate method depends on the question of interest and the accuracy needed to address it. Body composition data are descriptive and used for normative analyses (e.g. generating normal values, centiles and cut offs). Advanced models of BCA go beyond description and normative approaches. The concept of functional body composition (FBC) takes into account the relationships between individual body components, organs and tissues and related metabolic and physical functions. FBC can be further extended to the model of healthy body composition (HBC) based on horizontal (i.e. structural) and vertical (e.g. metabolism and its neuroendocrine control) relationships between individual components as well as between component and body functions using mathematical modelling with a hierarchical multi-level multi-scale approach at the software level. HBC integrates into whole body systems of cardiovascular, respiratory, hepatic and renal functions. To conclude BCA is a prerequisite for detailed phenotyping of individuals providing a sound basis for in depth biomedical research and clinical decision making.

Assessment of fat-free mass from bioelectrical impedance analysis in obese women with Prader-Willi syndrome

BACKGROUND

Fat-free mass (FFM) is lower in obese subjects with Prader-Willi syndrome (PWS) than in obese subjects without PWS. FFM prediction equations developed in non-PWS subjects may, thus, not work in PWS subjects.

AIM

To test whether the estimation of FFM from bioelectrical impedance analysis (BIA) in PWS subjects requires population-specific equations.

METHODS

Using dual-energy X-ray absorptiometry, this study measured FFM in 27 PWS and 56 non-PWS obese women and evaluated its association with the impedance index at 50 kHz (ZI50), i.e. the ratio between squared height and whole-body impedance at 50 kHz.

RESULTS

At the same level of ZI50, PWS women had a lower FFM than non-PWS women. However, when PWS-specific equations were used, FFM was accurately estimated at the population level. An equation employing a dummy variable coding for PWS status was able to explain 85% of the variance of FFM with a root mean squared error of 3.3 kg in the pooled sample (n = 83).

CONCLUSION

Population-specific equations are needed to estimate FFM from BIA in obese PWS women.

[Physical, clinical, and psychosocial parameters of adolescents with different degrees of excess weight]

OBJECTIVE:

To compare body composition, hemodynamic parameters, health-related physical fitness, and health-related quality of life of adolescents with anthropometric diagnosis of overweight, obesity, and severe obesity.

METHODS:

220 adolescents with excess body weight were enrolled. They were beginners in a intervention program that included patients based on age, availability, presence of excess body weight, place of residence, and agreement to participate in the study

.

This study collected anthropometric and hemodynamic variables, health-related physical fitness, and health-related quality of life of the adolescents. To compare the three groups according to nutritional status, parametric and non-parametric tests were applied. Significance level was set at p<0.05.

RESULTS:

There was no significant difference in resting heart rate, health-related physical fitness, relative body fat, absolute and relative lean mass, and health-related quality of life between overweight, obese, and severely obese adolescents (p>0.05). Body weight, body mass index, waist and hip circumference, and systolic blood pressure increased as degree of excess weightincreased (p<0.05). Dyastolic blood pressure of the severe obesity group was higher than the other groups (p<0.05). There was an association between the degree of excess weight and the prevalence of altered blood pressure (overweight: 12.1%; obesity: 28.1%; severe obesity: 45.5%; p<0.001). The results were similar when genders were analyzed separately.

CONCLUSION:

Results suggest that overweight adolescents presented similar results compared to obese and severely obese adolescents in most of the parameters analyzed.

Physical, clinical, and psychosocial parameters of adolescents with different degrees of excess weight

OBJECTIVE: To compare body composition, hemodynamic parameters, health-related physical fitness, and health-related quality of life of adolescents with anthropometric diagnosis of overweight, obesity, and severe obesity.METHODS: 220 adolescents with excess body weight were enrolled. They were beginners in a intervention program that included patients based on age, availability, presence of excess body weight, place of residence, and agreement to participate in the study. This study collected anthropometric and hemodynamic variables, health-related physical fitness, and health-related quality of life of the adolescents. To compare the three groups according to nutritional status, parametric and non-parametric tests were applied. Significance level was set at p<0.05.RESULTS: There was no significant difference in resting heart rate, health-related physical fitness, relative body fat, absolute and relative lean mass, and health-related quality of life between overweight, obese, and severely obese adolescents (p>0.05). Body weight, body mass index, waist and hip circumference, and systolic blood pressure increased as degree of excess weightincreased (p<0.05). Dyastolic blood pressure of the severe obesity group was higher than the other groups (p<0.05). There was an association between the degree of excess weight and the prevalence of altered blood pressure (overweight: 12.1%; obesity: 28.1%; severe obesity: 45.5%; p<0.001). The results were similar when genders were analyzed separately.CONCLUSION: Results suggest that overweight adolescents presented similar results compared to obese and severely obese adolescents in most of the parameters analyzed.

Functional body composition and related aspects in research on obesity and cachexia: report on the 12th Stock Conference held on 6 and 7 September 2013 in Hamburg, Germany

The 12th Stock Conference addressed body composition and related functions in two extreme situations, obesity and cancer cachexia. The concept of 'functional body composition' integrates body components into regulatory systems relating the mass of organs and tissues to corresponding in vivo functions and metabolic processes. This concept adds to an understanding of organ/tissue mass and function in the context of metabolic adaptations to weight change and disease. During weight gain and loss, there are associated changes in individual body components while the relationships between organ and tissue mass are fixed. Thus an understanding of body weight regulation involves an examination of the relationships between organs and tissues rather than individual organ and tissue masses only. The between organ/tissue mass relationships are associated with and explained by crosstalks between organs and tissues mediated by cytokines, hormones and metabolites that are coupled with changes in body weight, composition and function as observed in obesity and cancer cachexia. In addition to established roles in intermediary metabolism, cell function and inflammation, organ-tissue crosstalk mediators are determinants of body composition and its change with weight gain and loss. The 12th Stock Conference supported Michael Stocks' concept of gaining new insights by integrating research ideas from obesity and cancer cachexia. The conference presentations provide an in-depth understanding of body composition and metabolism.

Body Composition and Abdominal Obesity in Patients With and Without Coronary Heart Disease

Background

The body fat and its distribution is an important risk factor for coronary artery diseases. The aim of this study was to evaluate the relationship between body composition and abdominal obesity in patients with and without coronary involvement in stable angina.

Methods

One hundred and sixty-one patients who underwent coronary angiography for stable angina were divided into two groups: patients with or without coronary heart disease (CHD). Participants underwent bioimpedance analysis for measurement of adipose tissues and lean body mass.

Results

No significant difference in body mass index and weight was found between two groups. Mean levels of waist circumference, waist to hip ratio and fat mass were significantly higher in CHD group (P = 0.02, P = 0.04 and P = 0.01). Fat-free mass was also significantly higher in non-CHD group (P = 0.02).

Conclusions

Screening for adiposity in subjects by body composition measurement method and determining fat distribution could better identify those at higher risk for CHD.