Normalized sensitivity of multi-dimensional body composition biomarkers for risk change prediction.

The limitations of BMI as a measure of adiposity and health risks have prompted the introduction of many alternative biomarkers. However, ranking diverse biomarkers from best to worse remains challenging. This study aimed to address this issue by introducing three new approaches: (1) a calculus-derived, normalized sensitivity score (NORSE) is used to compare the predictive power of diverse adiposity biomarkers; (2) multiple biomarkers are combined into multi-dimensional models, for increased sensitivity and risk discrimination; and (3) new visualizations are introduced that convey complex statistical trends in a compact and intuitive manner. Our approach was evaluated on 23 popular biomarkers and 6 common medical conditions using a large database (National Health and Nutrition Survey, NHANES, N ~ 100,000). Our analysis established novel findings: (1) regional composition biomarkers were more predictive of risk than global ones; (2) fat-derived biomarkers had stronger predictive power than weight-related ones; (3) waist and hip are always elements of the strongest risk predictors; (4) our new, multi-dimensional biomarker models yield higher sensitivity, personalization, and separation of the negative effects of fat from the positive effects of lean mass. Our approach provides a new way to evaluate adiposity biomarkers, brings forth new important clinical insights and sets a path for future biomarker research.

Prognostic value of energy expenditure and respiratory quotient measuring in patients with liver cirrhosis.

BACKGROUND & AIMS: Resting energy expenditure (REE) and respiratory quotient (RQ) as measured by indirect calorimetry (IC) may correlate with muscle mass and represent prognostic indicators in treating patients with liver cirrhosis. We aimed to assess the correlation of IC-measured REE and RQ with skeletal muscle mass (SM), mortality, and REE values as estimated by Harris-Benedict, European guidelines (EG), and Brazilian guidelines-DITEN (BG) equations in patients with liver cirrhosis. METHODS: In this prospectively designed study, REE was measured in 126 male patients with liver cirrhosis by IC and predicted by Harris-Benedict, EG (35 kcal/kg current weight), and BG (30 kcal/kg current weight) guidelines. Measurements were obtained at the time of admission to the study. Body composition was determined by whole-body dual-energy X-ray absorptiometry. The association between REE and 3-year survival was investigated. RESULTS: Cirrhosis etiology was classified as alcohol related (59.0%), viral (20.1%), cryptogenic (11.8%), or other (9.0%). Mean Child-Pugh and MELD indexes were 8.30 ± 2.0 and 14.38 ± 6.12, respectively. RQ showed a moderate correlation with SM (r = 0.64), while IC-measured REE was inversely associated with mortality (multivariate Cox Regression, HR = 0.88, 95% CI: 0.78; 1, p = 0.04). Among the predictive equations for REE, only Harris-Benedict yielded values close to the IC, with a positive Pearson correlation (r = 0.77), excellent accuracy (Cb = 0.98), and positive Lin's concordance correlation (CCC = 0.75). However, a large standard deviation was observed; HB-measured REE did not correlate with mortality. CONCLUSIONS: RQ and REE, as measured by IC, may be valuable tools for evaluating the severity of cirrhosis, by reflecting SM and predicting mortality, respectively. The predictive equations for REE included in this study cannot replace IC for this purpose. REGISTERED AT: www.clinicalTrials.gov (NCT02421848).

Human energy expenditure: advances in organ-tissue prediction models.

Humans expend energy at rest (REE), and this major energy exchange component is now usually estimated using statistical equations that include weight and other predictor variables. While these formulas are useful in evaluating an individual's or group's REE, an important gap remains: available statistical models are inadequate for explaining underlying organ-specific and tissue-specific mechanisms accounting for resting heat production. The lack of such systems level REE prediction models leaves many research questions unanswered. A potential approach that can fill this gap began with investigators who first showed in animals and later in humans that REE reflects the summated heat production rates of individual organs and tissues. Today, using advanced imaging technologies, REE can be accurately estimated from the measured in vivo mass of 10 organ-tissue mass components combined with their respective mass-specific metabolic rates. This review examines the next frontier of energy expenditure models and discusses how organ-tissue models have the potential not only to better predict REE but also to provide insights into how perturbations in organ mass lead to structure-function changes across other interacting organ systems. The introductory ideas advanced in this review provide a framework for future human energy expenditure modelling research.

A review of machine learning in obesity.

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods that predict and/or classify such as linear and logistic regression, artificial neural networks, deep learning and decision tree analysis. We also review methods that describe and characterize data such as cluster analysis, principal component analysis, network science and topological data analysis. We introduce each method with a high-level overview followed by examples of successful applications. The algorithms were then applied to National Health and Nutrition Examination Survey to demonstrate methodology, utility and outcomes. The strengths and limitations of each method were also evaluated. This summary of machine learning algorithms provides a unique overview of the state of data analysis applied specifically to obesity.

Clinically applicable optical imaging technology for body size and shape analysis: comparison of systems differing in design.

BACKGROUND/OBJECTIVES: Recent advances have extended anthropometry beyond flexible tape measurements to automated three-dimensional optical devices that rapidly acquire hundreds of body surface dimensions. Three new devices were recently introduced that share in common inexpensive optical cameras. The design, and thus potential clinical applicability, of these systems differ substantially leading us to critically evaluate their accuracy and precision. SUBJECTS/METHODS: 113 adult subjects completed evaluations by the three optical devices (KX-16 (16 stationary cameras), Proscanner (1 vertically oscillating camera), and Styku scanner (1 stationary camera)), air displacement plethysmography (ADP), dual-energy X-ray absorptiometry (DXA) and a flexible tape measure. Optical measurements were compared to reference method estimates that included results acquired by flexible tape, DXA and ADP. RESULTS: Optical devices provided respective circumference and regional volume estimates that overall were well-correlated with those obtained from flexible tape measurements (for example, hip circumference: R2, 0.91, 0.90, 0.96 for the KX-16, Proscanner, and Styku scanner, respectively) and DXA (for example, trunk volume: R2, 0.97, 0.97, and 0.98). Total body volumes measured by the optical devices were highly correlated with those from the ADP system (all R2s, 0.99). Coefficient of variations obtained from duplicate measurements (n, 55) were larger in optical than in reference measurements and significant (P<0.05) bias was present for some optical measurements relative to reference method estimates. CONCLUSIONS: Overall, the evaluated optical imaging systems differing in design provided body surface measurements that compared favorably with corresponding reference methods. However, our evaluations uncovered system measurement limitations, such as discrepancies in landmarking, that with correction have the potential to improve future developed devices.

Nationally representative equations that include resistance and reactance for the prediction of percent body fat in Americans.

BACKGROUND/OBJECTIVES: Resistance and reactance collected by bioelectrical impedance (BIA) can be used in equations to estimate percent body fat at relatively low cost and subject burden. To our knowledge, no such equations have been developed in a nationally representative sample. SUBJECTS/METHODS: Dual-energy X-ray absorptiometry assessed percent body fat from the 1999 to 2004 National Health and Nutrition Survey was the criterion method for development of sex-specific percent body fat equations using up to 6467 males or 4888 females 8-49 years of age. Candidate variables were studied in multiple mathematical forms and interactions using the Least Absolute Shrinkage and Selection Operator. Models were fit in 2/3's of the data and validated in 1/3 of the data selected at random. Final coefficients, R2 values and root mean square error (RMSE) were estimated in the full data set. RESULTS: Models that included age, ethnicity, height, weight, BMI and BIA assessments (resistance, reactance and height2/resistance) had R2 values of 0.831 in men and 0.864 in women in the full data set. RMSE measurements were between 2 and 3 body fat percentage points, and all equations showed low bias across groups formed by age, race/ethnicity or body mass index category. The addition of triceps skinfold and waist circumference increased the R2 to 0.905 in males and 0.883 in females. Adding other anthropometrics (plus menses in females) had little impact on performance. Reactance and resistance alone (in multiple mathematical forms) performed poorly with R2~0.2. CONCLUSIONS: Equations that included BIA assessments along with demographic and anthropometric variables provided percent body fat assessments that had high generalizability, strong predictive ability and low bias.

Assessment of human energy exchange: historical overview.

Energy exchange is fundamental to life and is a cornerstone in the study of human physiology, metabolism and nutrition. A global effort is underway to further our understanding of human energy exchange and its components as a means of establishing the mechanistic underpinnings of the evolving obesity and chronic disease epidemics. The current report establishes a conceptual historical framework for examining the evolution of energy exchange concepts and measurement methods. We review developments taking place over more than 2000 years during which humans endeavored to establish the source of body heat, the 'fire of life'. Major conceptual and methodological advances over the past three centuries have incrementally advanced the field and created the energy exchange paradigm within which we now work. As in the past, innovative experimental ideas and measurement methods are now needed to answer important questions brought to light by the obesity and chronic disease epidemics. Nevertheless, older classical measurement methods based on calorimetry techniques still hold a strong position in the field as many diet and weight-related questions remain unanswered.

Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: comparison with a reference laser imaging system.

BACKGROUND/OBJECTIVES: Anthropometry for measuring body composition, shape, surface area and volume is important for human clinical research and practice. Although training and technical skills are required for traditional tape and caliper anthropometry, a new opportunity exists for automated measurement using newly developed relatively low-cost three-dimensional (3D) imaging devices. The aim of this study was to compare results provided by a Kinect-based device to a traditional laser 3D reference system. SUBJECTS/METHODS: Measurements made by the evaluated device, a hybrid of commercially purchased hardware (KX-16; TC(2), Cary, NC, USA) with our additional added software, were compared with those derived by a high-resolution laser scanner (Vitus Smart XXL; Human Solutions North America, Cary, NC, USA). Both imaging systems were compared with additional linear (stadiometer-derived height) and volumetric (total volume, air-displacement plethysmography) measurements. Subjects (n=101) were healthy children (age ≥5 years) and adults varying in body mass index. RESULTS: Representative linear (4), circumferential (6), volumetric (3) and surface area (1) measurements made by the Kinect-based device showed a consistent pattern relative to the laser system: high correlations (R(2)s= 0.70-0.99, all P<0.001); 1-3% differences for large linear (for example, height, X±s.d., -1.4±0.5%), circumferential (for example, waist circumference, -2.1±1.8%), volume (for example, total body, -0.8±2.2%) and surface area (whole-body, -1.7±2.0%) estimates. By contrast, mean measurement differences were substantially larger for small structures (for example, forearm volume, 31.3±31.4%). CONCLUSIONS: Low-cost 3D Kinect-based imaging systems have the potential for providing automated accurate anthropometric and related body measurements for relatively large components; further hardware and software developments may be able to improve system small-component resolution.

Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review.

Body mass index (BMI) is now the most widely used measure of adiposity on a global scale. Nevertheless, intense discussion centers on the appropriateness of BMI as a phenotypic marker of adiposity across populations differing in race and ethnicity. BMI-adiposity relations appear to vary significantly across race/ethnic groups, but a collective critical analysis of these effects establishing their magnitude and underlying body shape/composition basis is lacking. Accordingly, we systematically review the magnitude of these race-ethnic differences across non-Hispanic (NH) white, NH black and Mexican American adults, their anatomic body composition basis and potential biologically linked mechanisms, using both earlier publications and new analyses from the US National Health and Nutrition Examination Survey. Our collective observations provide a new framework for critically evaluating the quantitative relations between BMI and adiposity across groups differing in race and ethnicity; reveal new insights into BMI as a measure of adiposity across the adult age-span; identify knowledge gaps that can form the basis of future research and create a quantitative foundation for developing BMI-related public health recommendations.

Prediction of percent body fat measurements in Americans 8 years and older.

BACKGROUND/OBJECTIVES: Although numerous equations to predict percent body fat have been published, few have broad generalizability. The objective of this study was to develop sets of equations that are generalizable to the American population 8 years of age and older. SUBJECTS/METHODS: Dual-emission X-ray absorptiometry (DXA) assessed percent body fat from the 1999-2006 National Health and Nutrition Examination Survey (NHANES) was used as the response variable for development of 14 equations for each gender that included between 2 and 10 anthropometrics. Other candidate variables included demographics and menses. Models were developed using the Least Absolute Shrinkage and Selection Operator (LAASO) and validated in a » withheld sample randomly selected from 11 884 males or 9215 females. RESULTS: In the final models, R(2) ranged from 0.664 to 0.845 in males and from 0.748 to 0.809 in females. R(2) was not notably improved by development of equations within, rather than across, age and ethnic groups. Systematic over or under estimation of percent body fat by age and ethnic groups was within 1 percentage point. Seven of the fourteen gender-specific models had R(2) values above 0.80 in males and 0.795 in females and exhibited low bias by age, race/ethnicity and body mass index (BMI). CONCLUSIONS: To our knowledge, these are the first equations that have been shown to be valid and unbiased in both youth and adults in estimating DXA assessed body fat. The equations developed here are appropriate for use in multiple ethnic groups, are generalizable to the US population and provide a useful method for assessment of percent body fat in settings where methods such as DXA are not feasible.

Multi-component molecular-level body composition reference methods: evolving concepts and future directions.

Excess adiposity is the main phenotypic feature that defines human obesity and that plays a pathophysiological role in most chronic diseases. Measuring the amount of fat mass present is thus a central aspect of studying obesity at the individual and population levels. Nevertheless, a consensus is lacking among investigators on a single accepted 'reference' approach for quantifying fat mass in vivo. While the research community generally relies on the multi-component body volume class of 'reference' models for quantifying fat mass, no definable guide discerns among different applied equations for partitioning the four (fat, water, protein and mineral mass) or more quantified components, standardizes 'adjustment' or measurement system approaches for model-required labelled water dilution volumes and bone mineral mass estimates, or firmly establishes the body temperature at which model physical properties are assumed. The resulting differing reference strategies for quantifying body composition in vivo leads to small, but under some circumstances, important differences in the amount of measured body fat. Recent technological advances highlight opportunities to expand model applications to new subject groups and measured components such as total body protein. The current report reviews the historical evolution of multi-component body volume-based methods in the context of prevailing uncertainties and future potential.

Energy balance measurement: when something is not better than nothing.

Energy intake (EI) and physical activity energy expenditure (PAEE) are key modifiable determinants of energy balance, traditionally assessed by self-report despite its repeated demonstration of considerable inaccuracies. We argue here that it is time to move from the common view that self-reports of EI and PAEE are imperfect, but nevertheless deserving of use, to a view commensurate with the evidence that self-reports of EI and PAEE are so poor that they are wholly unacceptable for scientific research on EI and PAEE. While new strategies for objectively determining energy balance are in their infancy, it is unacceptable to use decidedly inaccurate instruments, which may misguide health-care policies, future research and clinical judgment. The scientific and medical communities should discontinue reliance on self-reported EI and PAEE. Researchers and sponsors should develop objective measures of energy balance.

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.

Weight loss composition is one-fourth fat-free mass: a critical review and critique of this widely cited rule.

Maximizing fat loss while preserving lean tissue mass and function is a central goal of modern obesity treatments. A widely cited rule guiding expected loss of lean tissue as fat-free mass (FFM) states that approximately one-fourth of weight loss will be FFM (i.e. ΔFFM/ΔWeight = ∼0.25), with the remaining three-fourths being fat mass. This review examines the dynamic relationships between FFM, fat mass and weight changes that follow induction of negative energy balance with hypocaloric dieting and/or exercise. Historical developments in the field are traced with the 'Quarter FFM Rule' used as a framework to examine evolving concepts on obesity tissue, excess weight and what is often cited as 'Forbes' Rule'. Temporal effects in the fractional contribution of FFM to changes in body weight are examined as are lean tissue moderating effects such as ageing, inactivity and exercise that frequently accompany structured low-calorie diet weight loss protocols. Losses of lean tissue with dieting typically tend to be small, raising questions about study design, power and applied measurement method reliability. Our review elicits important questions related to the fractional loss of lean tissues with dieting and provides a foundation for future research on this topic.

Assessing body composition in taller or broader individuals using dual-energy X-ray absorptiometry: a systematic review.

BACKGROUND/OBJECTIVES: Dual-energy X-ray absorptiometry (DXA) is an accurate and reliable method for determining body composition, but a limiting feature is the restricted scanning areas (∼190 × 60 cm(2)). This shortcoming is relevant not only to athletes involved in sports where height is a major performance determinant but also to obese individuals with a large trunk mass and breadth in whom body dimensions frequently exceed the scan area. This study reviews solutions for DXA length and/or width limitations and its accuracy for body composition assessment using the PRISMA statement guidelines. SUBJECTS/METHODS: Reviewed studies included English language articles from MEDLINE and Thomson Reuters Web of Knowledge platform (1990-2013), and were selected if procedures to overcome the scan area limitations and its validity in assessing the body composition of healthy participants were addressed. Search terms included: DXA, scan, height, width, length, wide, large, tall and obese. RESULTS: A total of seven studies met the criteria and were selected. The sum of two DXA scans and adopting a knee-bent position are alternative procedures proposed for evaluating individuals using pencil and fan-beam Hologic instruments, who are taller than the scan area, whereas a half-body scan is recommended for overcoming the limitations of whole-body measurements in subjects who are wider than the scan area width of Lunar densitometers. CONCLUSIONS: Overall, the proposed procedures are useful and valid, in particular the half-body scan alternative, which avoids unnecessary radiation exposure and scanning time. However, these alternatives were developed for specific densitometers, models and scan mode, and applicability to other instruments requires further research.

Adiposity rebound is misclassified by BMI rebound.

BACKGROUND/OBJECTIVES: Adiposity rebound (AR) is defined as the nadir or the inflexion point of body mass index (BMI) percentiles between the age of 3 and 7 years. An early rebound is seen as a risk of obesity and, thus, AR is considered as a suitable time period for prevention. As BMI does not reflect body composition, we aimed to examine the rebounds of fat mass index (FMI) and fat-free mass index (FFMI) together with BMI. SUBJECTS/METHODS: Cross-sectional data of 19 264 children aged 3-11 years were pooled from three German studies (Kiel Obesity Prevention Study, the project 'Better diet. More exercise. KINDERLEICHT-REGIONS' and regular examinations of Jena children). Height and weight were measured. Fat mass (FM) and fat-free mass (FFM) were obtained from bioelectrical impedance analysis and analysed using a population-specific algorithm. Percentiles of BMI, FMI and FFMI were constructed by the LMS method. RESULTS: Both BMI and FMI percentiles showed a rebound, whereas FFMI percentiles steadily increased with age. On P90, FMI rebound was about 1.6-1.8 years later compared with that of BMI, that is, at ages 4.2 years (BMI) and 5.8 years (FMI) in boys and at 4.2 years (BMI) and 6.0 years (FMI) in girls. At AR, the slope of the BMI-P90 was explained by increases in FFMI rather than FMI. By contrast, at FMI rebound, the slope of BMI was strongly related to FMI. CONCLUSIONS: BMI rebound does not equal the rebound of FM. At AR, the slope in BMI is determined by the increase in FFMI. AR should be defined as FMI rebound rather than BMI rebound.

Can a weight loss of one pound a week be achieved with a 3500-kcal deficit? Commentary on a commonly accepted rule.

Despite theoretical evidence that the model commonly referred to as the 3500-kcal rule grossly overestimates actual weight loss, widespread application of the 3500-kcal formula continues to appear in textbooks, on respected government- and health-related websites, and scientific research publications. Here we demonstrate the risk of applying the 3500-kcal rule even as a convenient estimate by comparing predicted against actual weight loss in seven weight loss experiments conducted in confinement under total supervision or objectively measured energy intake. We offer three newly developed, downloadable applications housed in Microsoft Excel and Java, which simulates a rigorously validated, dynamic model of weight change. The first two tools available at http://www.pbrc.edu/sswcp, provide a convenient alternative method for providing patients with projected weight loss/gain estimates in response to changes in dietary intake. The second tool, which can be downloaded from the URL http://www.pbrc.edu/mswcp, projects estimated weight loss simultaneously for multiple subjects. This tool was developed to inform weight change experimental design and analysis. While complex dynamic models may not be directly tractable, the newly developed tools offer the opportunity to deliver dynamic model predictions as a convenient and significantly more accurate alternative to the 3500-kcal rule.

Optimal scaling of weight and waist circumference to height for maximal association with DXA-measured total body fat mass by sex, age and race/ethnicity.

BACKGROUND: Body mass index (BMI; weight (Wt)/height (Ht) (in kg m(-2)) and waist circumference (WC) are widely used as proxy anthropometric measures for total adiposity. Little is known about what scaling power of 'x' in both Wt(kg)/Ht(m)(x) and WC(m)/Ht(m)(x) is maximally associated with measured total body fat mass (TBFM). Establishing values for x would provide the information needed to create optimum anthropometric surrogate measures of adiposity. OBJECTIVE: To estimate the value of 'x' that renders Wt/Ht(x) and WC/Ht(x) maximally associated with DXA-measured TBFM. SUBJECTS: Participants of the NHANES 1999-2004 surveys, stratified by sex (men, women), race/ethnicity (non-Hispanic whites, non-Hispanic blacks, Mexican-Americans), and age(18-29, 30-49, 50-84 years). METHODS: We apply a grid search by increasing x from 0.0-3.0 by increments of 0.1 to the simple regression models, TBFM=b0+b1*(Wt/Ht(x)) and TBFM=b0+b1*(WC/Ht(x)) to obtain an estimate of x that results in the greatest R(2), taking into account complex survey design features and multiply imputed data. RESULTS: R(2)'s for BMI are 0.86 for men (N=6544) and 0.92 for women (N=6362). The optimal powers x for weight are 1.0 (R(2)=0.90) for men and 0.8 (R(2)=0.96) for women. The optimal power x for WC is 0, that is, no scaling of WC to height, for men (R(2)=0.90) or women (R(2)=0.82). The optimal powers for weight across nine combinations of race/ethnicity and age groups for each sex vary slightly (x=0.8-1.3) whereas the optimal scaling powers for WC are all 0 for both sexes except for non-Hispanic black men aged 18-29y (x=0.1). Although the weight-for-height indices with optimal powers are not independent of height, they yield more accurate TBFM estimates than BMI. CONCLUSION: In reference to TBFM, Wt/Ht and Wt/Ht(0.8) are the optimal weight-for-height indices for men and women, respectively, whereas WC alone, without Ht adjustment, is the optimal WC-for-height index for both sexes. Thus, BMI, an index independent of height, may be less useful when predicting TBFM.