Density of fat-free body mass: relationship with race, age, and level of body fatness

Validity of total body water measured by multi-frequency bioelectrical impedance devices in a multi-ethnic sample

BACKGROUND & AIMS

Total body water (TBW) is the largest component of fat free mass and therefore is commonly used in multi-compartment body composition models and as a stand-alone method to assess body composition. Previous literature has not validated bioelectrical impedance spectroscopy device estimates of TBW in racial and ethnic minority populations; previous studies have focused on bioelectrical impedance analysis devices that rely on proprietary algorithms and participant characteristics for accuracy. The purpose of this study was to assess the validity of two bioelectrical impedance spectroscopy devices for measures of TBW compared to a deuterium dilution criterion in a multi-ethnic sample.

METHODS

109 individuals (55% female, Age: 26.6 ± 6.9 yrs, BMI: 25.3 ± 4.0 kg/m²) identifying as Asian, African American/Black, Caucasian/White, Hispanic, and Multi-racial were enrolled. After a 12 h fast, participants provided a saliva sample for the criterion baseline TBW measure and completed two bioelectrical impedance device (BIS, IB) measurements of TBW. Participants then ingested deuterium oxide (D₂O). After an equilibration period, participants provided a second saliva sample for analysis of TBW.

RESULTS

For the total multi-ethnic sample, BIS estimates demonstrated good to fairly good agreement (Total error [TE] = 2.56 L, R² = 0.951) and IB estimates were excellent to very good (TE = 1.95 L, R² = 0.975). Validity results did not vary meaningfully between race and ethnicity.

CONCLUSIONS

The results suggest the BIS and IB devices evaluated can produce valid TBW estimates compared to D₂O in a multi-ethnic sample. TBW estimates from the IB may have better agreement with D₂O compared to the BIS when using the default settings.

Determination of Fat-Free Mass Density and its Components in Older Hispanic Adults by In Vivo Methods

The densitometry method estimates body composition based on cadaver reference values, mainly the fat-free mass density value of 1.100 g/cm³. However, several changes in fat-free mass components by aging, ethnicity, and excess adiposity could influence their density and affect body composition estimations. The present study aimed to compare the mean fat-free mass component values in older Hispanic adults to cadaver reference values. This cross-sectional study included a sample of 420 subjects aged ≥60 yr from northern Mexico. Fat-free mass was determined by the four-compartment model using air displacement plethysmography, the deuterium dilution technique, and dual-energy X-ray absorptiometry for body density, aqueous and mineral fractions of body weight, respectively. A 1-sample t test was used to compare the fat-free mass density and aqueous, mineral, and residue fractions of fat-free mass from subjects in the study to the assumed cadaver reference values. The mean fat-free mass density value for the total sample of older Hispanic adults (1.096 ± 0.011 g/cm³) was significantly (p < 0.001) lower than the assumed value of 1.100 g/cm³, except in obese older men. The mean aqueous fraction of fat-free mass (74.8 ± 3.3%) was higher than the assumed value of 73.8%, and the mean residue fraction of fat-free mass value was lower (18.3 ± 3.4%) than the reference value of 19.4%. Indeed, only the mean mineral fraction of fat-free mass value (6.8 ± 0.8%) was similar to the reference value. In the total sample, all characteristic mean fat-free mass values in these older Hispanic adults differed from cadaver reference values, except the mineral fraction of fat-free mass value.

Are methods of estimating fat-free mass loss with energy-restricted diets accurate?

BACKGROUND/OBJECTIVES

Fat-free mass (FFM) often serves as a body composition outcome variable in weight loss studies. An important assumption is that the proportions of components that make up FFM remain stable following weight loss; some body composition models rely on these "constants". This exploratory study examined key FFM component proportions before and following weight loss in two studies of participants with overweight and obesity.

SUBJECTS/METHODS

201 men and women consumed calorie-restricted moderate- or very-low carbohydrate diets leading to 10-18% weight loss in 9-15 weeks. Measured total body fat, lean mass, bone mineral, total body water (TBW), and body weight at baseline and follow-up were used to derive FFM and its chemical proportions using a four-component model.

RESULTS

A consistent finding in both studies was a non-significant reduction in bone mineral and a corresponding increase (p < 0.001) in bone mineral/FFM; FFM density increased significantly in one group of women and in all four participant groups combined (both, p < 0.05). FFM hydration (TBW/FFM) increased in all groups of men and women, one significantly (p < 0.01), and in the combined sample (borderline, p < 0.10). The proportion of FFM as protein decreased across all groups, two significantly (p < 0.05-0.01) and in the combined sample (p < 0.05).

CONCLUSION

FFM relative proportions of chemical components may not be identical before and after short-term weight loss, an observation impacting some widely used body composition models and methods. Caution is thus needed when applying FFM as a safety signal or to index metabolic evaluations in clinical trials when these body composition approaches are used.

Validity of Body-Composition Methods across Racial and Ethnic Populations

Multi-compartment body-composition models that divide the body into its multiple constituents are the criterion method for measuring body fat percentage, fat mass, and fat-free mass. However, 2- and 3-compartment body-composition devices such as air displacement plethysmography (ADP), DXA, and bioelectrical impedance devices [bioelectrical impedance analysis (BIA)] are more commonly used. Accurate measures depend on several assumptions, including constant hydration, body proportion, fat-free body density, and population characteristics. Investigations evaluating body composition in racial and ethnic minorities have observed differences in the aforementioned components between cohorts. Consequently, for racial/ethnic minority populations, estimates of body composition may not be valid. The purpose of this review was to comprehensively examine the validity of common body-composition devices in multi-ethnic samples (samples including >1 race/ethnicity) and in African-American, Hispanic, Asian, and Native American populations. Based on the literature, DXA produces valid results in multi-ethnic samples and ADP is valid for Hispanic and African American males when utilizing race-specific equations. However, for DXA and ADP, there is a need for validity investigations that include larger, more racially diverse samples, specifically including Hispanic/Latinx, Asian, Native American adults, and African-American females. Technology has advanced significantly since initial validity studies were conducted; therefore, conclusions are based on outdated models and software. For BIA, body-composition measures may be valid in a multi-ethnic sample, but the literature demonstrates disparate results between races/ethnicities. For BIA and ADP, the majority of studies have utilized DXA or hydrostatic weighing as the criterion to determine validity; additional studies utilizing a multi-compartment model criterion are essential to evaluate accuracy. Validity studies evaluating more recent technology in larger, more racially/ethnically diverse samples may improve our ability to select the appropriate method to accurately assess body composition in each racial/ethnic population.

Multicomponent density models for body composition: Review of the dual energy X-ray absorptiometry volume approach

Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air-displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual-energy X-ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual-energy X-ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air-displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual-energy X-ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.

Evaluation of Fluid Loss and Customary Fluid Intake among a Selected Group of Young Swimmers: A Preliminary Field Study

This study aimed to assess fluid loss (FL) and customary fluid intake (FI) during a training session, and the relationship between FL and total body water (TBW) content in a selected group of young swimmers. The study involved 17 (seven females, 10 males) individuals whose anthropometric and body composition analyses and FI during training units were carried out. The total average FI and total actual FL oscillated around 531 mL and −513 mL for the whole study group (469 mL and −284 mL for females, 574 mL and −674 mL for males). The dependent and independent sample t-tests, the Cohen’s d effect size and Pearson’s correlation coefficient were analysed. Significant differences were observed between pre-workout and post-workout body weights after training without FI in the whole group (66.5 kg vs. 66.0 kg, p < 0.001, d = 0.06), in females (61.2 kg vs. 60.9 kg, p = 0.015, d = 0.04) and males (70.3 kg vs. 69.6 kg, p < 0.001, d = 0.9). For the TBW content and fat-free mass (FFM) before and after training, significant differences were observed only in males (TBW: 43.8 L vs. 43.2 L, p = 0.002, d = 0.14; and 62.4% vs. 61.7%, p < 0.001, d = 0.36; FFM: 59.8 kg vs. 59.1 kg, p = 0.002, d = 0.12). Moreover, the relationship between the actual FL and TBW before training was observed in the whole (mL vs. %: r = −0.64, p = 0.006; mL vs. L: r = −0.84, p < 0.001) and the male group (mL vs. L: r = −0.73, p = 0.017). These results indicated FL in young swimmers during training and the relationship between FL and pre-training TBW content, which suggests that it is important to also pay special attention to effective hydration procedures before and during training in aquatic environments.

Evaluation of fat-free mass hydration in athletes and non-athletes

PURPOSE

To evaluate the hydration of fat-free mass (FFM) in athletes and non-athletes.

METHODS

We analyzed the data of 128 healthy young adults (athletes: 61 men, 36 women; non-athletes: 19 men, 12 women) using the two-component (2C), 3C and 4C models. Under-water weighing or air-displacement plethysmography and deuterium dilution methods were used for estimating body density and total body water, respectively. The bone mineral content (BMC) was determined using whole-body scans by dual-energy X-ray absorptiometry.

RESULTS

There was no significant difference in FFM hydration between the athletes (men, 72.3 ± 1.3%; women, 71.8 ± 1.3%) and non-athletes (men, 72.1 ± 1.2%; women, 72.2% ± 1.0%) in the 3C model. The total mean FFM hydration (72.1% ± 1.3%) was similar to the corresponding value in the literature (~ 73%). The estimation error of the percentage fat by the 2C vs the 4C model was significantly and highly correlated with hydration (r = 0.96), BMC (r = - 0.70), and total body protein (r = - 0.86) in the 4C model FFM.

CONCLUSION

Although FFM hydration was similar in athletes and non-athletes, it would be underestimated or overestimated when the 2C model is used for evaluation, and the biological FFM hydration value deviates from the 73% value inter-individually. Despite that this inter-individual variation in FFM hydration is low in terms of between-individual standard deviation (1.3%), the BMC and total body protein differ greatly in athletes, and when it affects FFM hydration, it may also affect the percentage fat measurement in the 2C model. Thus, FFM hydration would not be affected by FFM, percent body fat, or the athletic status.

Associations of age and body mass index with hydration and density of fat-free mass from 4 to 22 years

BACKGROUND

Most body composition techniques assume constant properties of fat free mass (FFM) (hydration and density) regardless of nutritional status, which may lead to biased values.

AIM

To evaluate the interactive associations of age and body mass index (BMI) with hydration and density of FFM.

METHODS

Data from subjects aged between 4 and 22 years old from several studies conducted in London, UK were assessed. Hydration (H_FFM) and density (D_FFM) of FFM obtained from the four-component model in 936 and 905 individuals, respectively, were assessed. BMI was converted in to z-scores, and categorised into five groups using z-score cut-offs (thin, normal weight, overweight, obese, and severely obese). Linear regression models for H_FFM and D_FFM were developed using age, sex, and BMI group as predictors.

RESULTS

Nearly 30% of the variability in H_FFM was explained by models including age and BMI groups, showing increasing H_FFM values in heavier BMI groups. On the other hand, ∼40% of variability in D_FFM was explained by age, sex, and BMI groups, with D_FFM values decreasing in association with higher BMI group.

CONCLUSION

Nutritional status should be considered when assessing body composition using two-component methods, and reference data for H_FFM and D_FFM is needed for higher BMI groups to avoid bias. Further research is needed to explain intra-individual variability in FFM properties.

Optimal composition of fluid-replacement beverages

The objective of this article is to provide a review of the fundamental aspects of body fluid balance and the physiological consequences of water imbalances, as well as discuss considerations for the optimal composition of a fluid replacement beverage across a broad range of applications. Early pioneering research involving fluid replacement in persons suffering from diarrheal disease and in military, occupational, and athlete populations incurring exercise- and/or heat-induced sweat losses has provided much of the insight regarding basic principles on beverage palatability, voluntary fluid intake, fluid absorption, and fluid retention. We review this work and also discuss more recent advances in the understanding of fluid replacement as it applies to various populations (military, athletes, occupational, men, women, children, and older adults) and situations (pathophysiological factors, spaceflight, bed rest, long plane flights, heat stress, altitude/cold exposure, and recreational exercise). We discuss how beverage carbohydrate and electrolytes impact fluid replacement. We also discuss nutrients and compounds that are often included in fluid-replacement beverages to augment physiological functions unrelated to hydration, such as the provision of energy. The optimal composition of a fluid-replacement beverage depends upon the source of the fluid loss, whether from sweat, urine, respiration, or diarrhea/vomiting. It is also apparent that the optimal fluid-replacement beverage is one that is customized according to specific physiological needs, environmental conditions, desired benefits, and individual characteristics and taste preferences.

Body composition analysis by air displacement plethysmography in normal weight to extremely obese adults

OBJECTIVE

To compare body composition parameters estimated by air displacement plethysmography (ADP) to dual X-ray absorptiometry (DXA) in body mass index (BMI) classifications that include extremely obese (BMI ≥ 40.0 kg/m(2) ), and to examine if differences between analyses were influenced by BMI.

METHODS

Fat-free mass (FFM, kg), fat mass (FM, kg), and body fat (BF, %) were analyzed with both technologies.

RESULTS

All outcome measures of ADP and DXA were highly correlated (r ≥ 0.95, P < 0.001 for FFM, FM, and BF), but Bland-Altman analyses revealed significant bias (P < 0.01 for all). ADP estimated greater FFM and lower FM and BF (P < 0.01 for all). BMI explained 27% of the variance in differences between FFM measurements (P < 0.001), and 37 and 33% of the variances in differences between FM and BF measurements, respectively (P < 0.001 for both). Within normal weight and overweight classifications, ADP estimated greater FFM and lower FM and BF (P < 0.001 for all), but the opposite occurred within the extremely obese classification; ADP estimated lower FFM and greater FM and BF (P < 0.05 for all).

CONCLUSIONS

Body composition analyses by the two technologies were strongly congruent, but systematically different and influenced by BMI. Caution should be taken when utilizing ADP to estimate body composition parameters over a wide range of BMI classifications that include extremely obese.

Body composition in 18- to 88-year-old adults--comparison of multifrequency bioimpedance and dual-energy X-ray absorptiometry

OBJECTIVE

This study compared bioimpedance analysis (BIA) in the assessment of body composition with dual-energy X-ray absorptiometry (DXA) in 18- to 88-year-old adults.

DESIGN AND METHODS

Body composition of 882 adults was estimated by eight-polar BIA and DXA. In addition, estimates of lean mass, fat mass, and percentage of fat were investigated across a range of age and leisure time physical activity (LTPA) groups.

RESULTS

Compared to DXA, larger lean masses (mean difference 2.9 and 1.6 kg) and smaller fat masses (3.1 and 2.6 kg) were estimated by BIA in both women and men, respectively. Differences between the methods' mean values were evident in all age and LTPA groups, except in the oldest men (over 70 years). Age, waist circumference, grip strength, and LTPA explained 21% or less of the variance observed in the differences between methods.

CONCLUSIONS

Compared to DXA, BIA provided systematically different body composition estimates throughout the adult age span with considerable amount of intraindividual variation. The differences between estimates may be related to the BIAs' algorithm or body geometry or composition of the population used in this study. Knowledge about the methodological limitations and device comparability is essential for researchers, clinicians, and persons working in rehabilitation and sport centers.

National Athletic Trainers' Association position statement: safe weight loss and maintenance practices in sport and exercise

OBJECTIVE

To present athletic trainers with recommendations for safe weight loss and weight maintenance practices for athletes and active clients and to provide athletes, clients, coaches, and parents with safe guidelines that will allow athletes and clients to achieve and maintain weight and body composition goals.

BACKGROUND

Unsafe weight management practices can compromise athletic performance and negatively affect health. Athletes and clients often attempt to lose weight by not eating, limiting caloric or specific nutrients from the diet, engaging in pathogenic weight control behaviors, and restricting fluids. These people often respond to pressures of the sport or activity, coaches, peers, or parents by adopting negative body images and unsafe practices to maintain an ideal body composition for the activity. We provide athletic trainers with recommendations for safe weight loss and weight maintenance in sport and exercise. Although safe weight gain is also a concern for athletic trainers and their athletes and clients, that topic is outside the scope of this position statement.

RECOMMENDATIONS

Athletic trainers are often the source of nutrition information for athletes and clients; therefore, they must have knowledge of proper nutrition, weight management practices, and methods to change body composition. Body composition assessments should be done in the most scientifically appropriate manner possible. Reasonable and individualized weight and body composition goals should be identified by appropriately trained health care personnel (eg, athletic trainers, registered dietitians, physicians). In keeping with the American Dietetics Association (ADA) preferred nomenclature, this document uses the terms registered dietitian or dietician when referring to a food and nutrition expert who has met the academic and professional requirements specified by the ADA's Commission on Accreditation for Dietetics Education. In some cases, a registered nutritionist may have equivalent credentials and be the commonly used term. All weight management and exercise protocols used to achieve these goals should be safe and based on the most current evidence. Athletes, clients, parents, and coaches should be educated on how to determine safe weight and body composition so that athletes and clients more safely achieve competitive weights that will meet sport and activity requirements while also allowing them to meet their energy and nutritional needs for optimal health and performance.

Predicting fat percent by skinfolds in racial groups: Durnin and Womersley revisited

PURPOSE

Despite their widespread use in research and fitness settings, Durnin and Womersley's (DW) 1974 prediction equations using skinfold thickness to estimate body fat percent by hydrodensitometry have not been systematically evaluated in racial or ethnic groups using body fat percent measured by dual-energy x-ray absorptiometry (%BF(DXA)) as the standard.

METHODS

This cross-sectional, population-based study examined whether the DW skinfold equations predict %BF(DXA) in a large, multiracial sample. Four skinfold measures (biceps, triceps, subscapular, and suprailiac), other clinical anthropometrics, and %BF(DXA) were obtained from 1675 healthy adults, age 18-110 yr, who were classified into four racial or ethnic categories: Caucasian, African American, Hispanic, or Asian. Predicted body fat percent using DW equations was compared with %BF(DXA) and evaluated within race/ethnicity- and sex-specific groups.

RESULTS

Mean body fat percent predicted by DW equations was significantly different from %BF(DXA) in four of eight race/ethnicity- and sex-specific groups, particularly in Asian women and African American men (3.3 and 2.4 percentage point overestimates, respectively, P < 0.0001). New linear regression equations were developed estimating %BF(DXA) specific to each race/ethnicity and sex group, using the original DW skinfold sites. Body weight, height, and waist circumference independently predicted fat percent and were also included in the new equations.

CONCLUSIONS

The 1974 DW equations did not predict %BF(DXA) uniformly in all races or ethnicities. Using %BF(DXA) as the criterion measure, the original DW skinfold equations have been updated specific to sex and race/ethnicity while maintaining the DW options for a minimalistic model using fewer predictors.

Assessment of analytical methods used to measure changes in body composition in the elderly and recommendations for their use in phase II clinical trials

It is estimated that in the next 20 years, the amount of people greater than 65 years of age will rise from 40 to 70 million, and will account for 19% of the total population. Age-related decreases in muscle mass and function, known as sarcopenia, have been shown to be related to functional limitation, frailty and an increased risk of morbidity and mortality. Therefore, with an increasing elderly population, interventions that can improve muscle mass content and/or function are essential. However, analytical techniques used for measurement of muscle mass in young subjects may not be valid for use in the elderly. Therefore, the purpose of this review is to examine the applied specificity and accuracy of methods that are commonly used for measurement of muscle mass in aged subjects, and, to propose specific recommendations for the use of body composition measures in phase II clinical trials of function-promoting anabolic therapies.

Comparison of DXA and CT in the assessment of body composition in premenopausal women with obesity and anorexia nervosa

Accurate methods for assessing body composition in subjects with obesity and anorexia nervosa (AN) are important for determination of metabolic and cardiovascular risk factors and to monitor therapeutic interventions. The purpose of our study was to assess the accuracy of dual-energy X-ray absorptiometry (DXA) for measuring abdominal and thigh fat, and thigh muscle mass in premenopausal women with obesity, AN, and normal weight compared to computed tomography (CT). In addition, we wanted to assess the impact of hydration on DXA-derived measures of body composition by using bioelectrical impedance analysis (BIA). We studied a total of 91 premenopausal women (34 obese, 39 with AN, and 18 lean controls). Our results demonstrate strong correlations between DXA- and CT-derived body composition measurements in AN, obese, and lean controls (r = 0.77-0.95, P < 0.0001). After controlling for total body water (TBW), the correlation coefficients were comparable. DXA trunk fat correlated with CT visceral fat (r = 0.51-0.70, P < 0.0001). DXA underestimated trunk and thigh fat and overestimated thigh muscle mass and this error increased with increasing weight. Our study showed that DXA is a useful method for assessing body composition in premenopausal women within the phenotypic spectrum ranging from obesity to AN. However, it is important to recognize that DXA may not accurately assess body composition in markedly obese women. The level of hydration does not significantly affect most DXA body composition measurements, with the exceptions of thigh fat.

Percent body fat estimations in college men using field and laboratory methods: a three-compartment model approach

BACKGROUND

Methods used to estimate percent body fat can be classified as a laboratory or field technique. However, the validity of these methods compared to multiple-compartment models has not been fully established. The purpose of this study was to determine the validity of field and laboratory methods for estimating percent fat (%fat) in healthy college-age men compared to the Siri three-compartment model (3C).

METHODS

Thirty-one Caucasian men (22.5 +/- 2.7 yrs; 175.6 +/- 6.3 cm; 76.4 +/- 10.3 kg) had their %fat estimated by bioelectrical impedance analysis (BIA) using the BodyGram computer program (BIA-AK) and population-specific equation (BIA-Lohman), near-infrared interactance (NIR) (Futrex(R) 6100/XL), four circumference-based military equations [Marine Corps (MC), Navy and Air Force (NAF), Army (A), and Friedl], air-displacement plethysmography (BP), and hydrostatic weighing (HW).

RESULTS

All circumference-based military equations (MC = 4.7% fat, NAF = 5.2% fat, A = 4.7% fat, Friedl = 4.7% fat) along with NIR (NIR = 5.1% fat) produced an unacceptable total error (TE). Both laboratory methods produced acceptable TE values (HW = 2.5% fat; BP = 2.7% fat). The BIA-AK, and BIA-Lohman field methods produced acceptable TE values (2.1% fat). A significant difference was observed for the MC and NAF equations compared to both the 3C model and HW (p < 0.006).

CONCLUSION

Results indicate that the BP and HW are valid laboratory methods when compared to the 3C model to estimate %fat in college-age Caucasian men. When the use of a laboratory method is not feasible, BIA-AK, and BIA-Lohman are acceptable field methods to estimate %fat in this population.

Scaling of human body composition to stature: new insights into body mass index

BACKGROUND

Although Quetelet first reported in 1835 that adult weight scales to the square of stature, limited or no information is available on how anatomical body compartments, including adipose tissue (AT), scale to height.

OBJECTIVE

We examined the critical underlying assumptions of adiposity-body mass index (BMI) relations and extended these analyses to major anatomical compartments: skeletal muscle (SM), bone, residual mass, weight (AT+SM+bone), AT-free mass, and organs (liver, brain).

DESIGN

This was a cross-sectional analysis of 2 body-composition databases: one including magnetic resonance imaging and dual-energy X-ray absorptiometry (DXA) estimates of evaluated components in adults (total n=411; organs=76) and the other a larger DXA database (n=1346) that included related estimates of fat, fat-free mass, and bone mineral mass.

RESULTS

Weight, primary lean components (SM, residual mass, AT-free mass, and fat-free mass), and liver scaled to height with powers of approximately 2 (all P<0.001); bone and bone mineral mass scaled to height with powers >2 (2.31-2.48), and the fraction of weight as bone mineral mass was significantly (P<0.001) correlated with height in women. AT scaled weakly to height with powers of approximately 2, and adiposity was independent of height. Brain mass scaled to height with a power of 0.83 (P=0.04) in men and nonsignificantly in women; the fraction of weight as brain was inversely related to height in women (P=0.002).

CONCLUSIONS

These observations suggest that short and tall subjects with equivalent BMIs have similar but not identical body composition, provide new insights into earlier BMI-related observations and thus establish a foundation for height-normalized indexes, and create an analytic framework for future studies.

Development of methods for body composition studies

This review is focused on experimental methods for determination of the composition of the human body, its organs and tissues. It summarizes the development and current status of fat determinations from body density, total body water determinations through the dilution technique, whole and partial body potassium measurements for body cell mass estimates, in vivo neutron activation analysis for body protein measurements, dual-energy absorptiometry (DEXA), computed tomography (CT) and magnetic resonance imaging (MRI, fMRI) and spectroscopy (MRS) for body composition studies on tissue and organ levels, as well as single- and multiple-frequency bioimpedance (BIA) and anthropometry as simple easily available methods. Methods for trace element analysis in vivo are also described. Using this wide range of measurement methods, together with gradually improved body composition models, it is now possible to quantify a number of body components and follow their changes in health and disease.

A novel method to determine lean body water using localized skin biopsies: correlation between lean skin water and lean body water in an overhydration model

To determine the relationship between total body water (TBW) fraction and local water content measured in the skin (SW) this study assessed eight anesthetized piglets in an overhydration model. TBW was assessed by deuterium oxide dilution and body mass measurements taken throughout the experiments, and by whole body carcass analysis at the end of each experiment. Additionally, extracellular water and plasma volume were assessed using bromide dilution and Evan's blue dilution, respectively. SW was assessed by tissue biopsies taken at 60-min intervals throughout the experiment. Lean body water (LBW) fraction and lean skin water (LSW) fraction were assessed by extracting the fat from the carcass and biopsy samples. A correlation does exist between TBW fraction and SW fraction with r2=0.58 (P<0.05); however, the strongest correlation occurred between the LBW fraction and LSW fraction with r2=0.87 (P<0.05) and an SE of prediction of 0.77%. These data demonstrate that LSW gives an accurate and precise estimate of LBW and could therefore be used to determine the hydration index in appropriate research settings.

Skinfold prediction equation for athletes developed using a four-component model

INTRODUCTION

Skinfold (SKF) equations exist to predict percent body fat (%BF) in athletes; however, none have been derived from multicomponent model reference measures.

PURPOSE

To develop and cross-validate a %BF prediction equation based on SKF in athletes using a four-component model as the reference measure.

METHODS

Subjects were 132 collegiate athletes (20.7 +/- 2.0 yr; 78 males: 28 black, 50 white; 54 females: 10 black, 44 white). Four-component model estimates of %BF (%BF4C) included measures of total body water from deuterium dilution, bone mineral by dual- energy x-ray absorptiometry (DXA), and body density by densitometry using underwater weighing. SKF measures included subscapular, triceps, chest, midaxillary, suprailiac, abdominal, and thigh sites (7SKF). A prediction equation was developed on 102 athletes using 7SKF, race, and gender as predictor variables. Cross-validation was performed on a representative holdout sample of 30 athletes.

RESULTS

The equation cross-validated well (slope and intercept both not different (P > 0.05) from the line of identity (LOI); r(YY') = 0.85, total error (TE) = 3.76%BF) and was better than the existing athlete SKF equations (intercept and slope both different from LOI (P < 0.01); r(YY') = 0.76, TE = 4.51%BF). Notably, a prediction equation developed using 3SKF sites (abdomen, thigh, and triceps) produced a similar accuracy (intercept and slope both not different from LOI (P > 0.05); r(YY') = 0.85, TE = 3.66%BF).

CONCLUSIONS

The new 7SKF equation improved on SKF equations developed using densitometry. The final equation based on the whole sample was %BF' = 10.566 + 0.12077*(7SKF) - 8.057*(gender) - 2.545*(race). Moreover, a 3SKF equation was comparable in accuracy to the 7SKF equation: BF' = 8.997 + 0.24658*(3SKF) - 6.343*(gender) - 1.998*(race).

Water balance, hydration status, and fat-free mass hydration in younger and older adults

BACKGROUND

Older adults are at increased risk of dehydration, yet water balance is understudied in this population.

OBJECTIVE

This controlled diet study assessed the effect of age on water input, output, and balance in healthy adults. Hydration status (plasma osmolality and urine specific gravity) and body composition were also measured.

DESIGN

Eleven men and 14 women aged 23-46 y and 10 men and 11 women aged 63-81 y were subjects. Water balance was assessed during days 7-10 of three 18-d controlled feeding trials with protein intakes of 0.50, 0.75, and 1.00 g . kg(-1) . d(-1). Total water input included water from the provided foods and beverages, ad libitum intake, and metabolic production. Water output included the losses in urine and stool and the insensible losses from respiration and nonsweating perspiration.

RESULTS

Ad libitum water consumption, total water intake, water output through urine, total water output, and net water balance were not different in the older subjects than in the younger subjects. Markers of hydration status were within the range of clinical normalcy for all groups. Total body water (TBW) was not significantly different, fat-free mass (FFM) was significantly lower (P < 0.05), and FFM hydration (TBW:FFM) was significantly higher (P < 0.05) in the older subjects than in the younger subjects. Dietary protein intake did not influence any of these results.

CONCLUSIONS

These results show that healthy older adults maintain water input, output, and balance comparable to those of younger adults and have no apparent changes in hydration status. The results support that the hydration of FFM is increased in older men and women.

Comparison of body composition methods in overweight and obese children

The objective of the present study was to investigate the accuracy of percent body fat (%fat) estimates from dual-energy X-ray absorptiometry, air-displacement plethysmography (ADP), and total body water (TBW) against a criterion four-compartment (4C) model in overweight and obese children. A volunteer sample of 30 children (18 male and 12 female), age of (mean ± SD) 14.10 ± 1.83 yr, body mass index of 31.6 ± 5.5 kg/m, and %fat (4C model) of 41.2 ± 8.2%, was assessed. Body density measurements were converted to %fat estimates by using the general equation of Siri (ADPSiri) (Siri WE. Techniques for Measuring Body Composition. 1961) and the age- and gender-specific constants of Lohman (ADPLoh) (Lohman TG. Exercise and Sport Sciences Reviews. 1986). TBW measurements were converted to %fat estimates by assuming that water accounts for 73% of fat-free mass (TBW73) and by utilizing the age- and gender-specific water contents of Lohman (TBWLoh). All estimates of %fat were highly correlated with those of the 4C model ( r ≥ 0.95, P < 0.001; SE ≤ 2.14). For %fat, the total error and mean difference ± 95% limits of agreement compared with the 4C model were 2.50, 1.8 ± 3.5 (ADPSiri); 1.82, -0.04 ± 3.6 (ADPLoh); 2.86, -2.0 ± 4.1 (TBW73); 1.90, -0.3 ± 3.8 (TBWLoh); and 2.74, 1.9 ± 4.0 DXA (dual-energy X-ray absorptiometry), respectively. In conclusion, in overweight and obese children, ADPLoh and TBWLoh were the most accurate methods of measuring %fat compared with a 4C model. However, all methods under consideration produced similar limits of agreement.

Magnitude and variation of fat-free mass density: a cellular-level body composition modeling study

The mean density of fat-free mass (FFM) is remarkably stable at 1.10 g/cm(3) in healthy adult humans, and this stability is a cornerstone of the widely applied densitometry-based two-compartment model for estimating total body fat. At present, the usual means of exploring FFM density is by in vitro or in vivo experimental studies. The purpose of the present investigation was to develop a cellular-level body composition model that includes seven factors that determine FFM density. The model, when applied with available empirical coefficients, predicted an FFM density similar to that observed in vivo. An analysis of the seven model components indicates that the ratio of extracellular solids to total body water is a major determinant of individual variation in FFM density. The difference in FFM density across sex, race, and age groups was examined with the developed model. The present study thus provides a conceptual framework for the systematic study of FFM density in humans.

Relation of bone mineral density and content to mineral content and density of the fat-free mass

Differences in the mineral fraction of the fat-free mass (M(FFM)) and in the density of the FFM (D(FFM)) are often inferred from measures of bone mineral content (BMC) or bone mineral density (BMD). We studied the relation of BMC and BMD to the M(FFM) and D(FFM) in a heterogeneous sample of 216 young men (n = 115) and women (n = 101), which included whites (n = 155) and blacks (n = 61) and collegiate athletes ( n = 132) and nonathletes (n = 84). Whole body BMC and BMD were determined by dual-energy X-ray absorptiometry (DXA; Hologic QDR-1000W, enhanced whole body analysis software, version 5.71). FFM was estimated using a four-component model from measures of body density by hydrostatic weighing, body water by deuterium dilution, and bone mineral by DXA. There was no significant relation of BMD to M(FFM) (r = 0.01) or D(FFM) (r = -0.06) or of BMC to M(FFM) (r = -0.11) and a significant, weak negative relation of BMC to D(FFM) (r = -0.14, P = 0.04) in all subjects. Significant low to moderate relationships of BMD or BMC to M(FFM) or D(FFM) were found within some gender-race-athletic status subgroups or when the effects of gender, race, and athletic status were held constant using multiple regression, but BMD and BMC explained only 10-17% of the variance in M(FFM) and 0-2% of the variance in D(FFM) in addition to that explained by the demographic variables. We conclude that there is not a significant positive relation of BMD and BMC to M(FFM) or D(FFM) in young adults and that BMC and BMD should not be used to infer differences in M(FFM) or D(FFM).

Effect of race and resistance training status on the density of fat-free mass and percent fat estimates

The impact of race and resistance training status on the assumed density of the fat-free mass (D(FFM)) and estimates of body fatness via hydrodensitometry (%Fat(D)) vs. a four-component model (density, water, mineral; %Fat(D,W,M)) were determined in 45 men: white controls (W; n = 15), black controls (B; n = 15), and resistance-trained blacks (B-RT; n = 15). Body density by hydrostatic weighing, body water by deuterium dilution, and bone mineral by dual-energy X-ray absorptiometry were used to estimate %Fat(D,W,M). D(FFM) was not different between B and W (or 1.1 g/ml); however, D(FFM) in B-RT was significantly lower (1.091 +/- 0.012 g/ml; P < 0.05). Therefore, %Fat(D) using the Siri equation was not different from %Fat(D,W,M) in W (17.5 +/- 5.0 vs. 18.3 +/- 5.4%) or B (14.9 +/- 5.6 vs. 15.7 +/- 5.7%) but significantly overestimated %Fat(D,W,M) in B-RT (14.0 +/- 5.9 vs. 10.4 +/- 6.0%; P < 0.05). The use of a race-specific equation (assuming D(FFM) = 1.113 g/ml) did not improve the agreement between %Fat(D) and %Fat(D,W,M), resulting in a significantly greater mean (+/-SD) discrepancy for B (1.7 +/- 1.8% fat) and B-RT (6.2 +/- 4.3% fat). Thus race per se does not affect D(FFM) or estimates of %Fat(D); however, B-RT have a D(FFM) lower than 1.1 g/ml, leading to an overestimation of %Fat(D).

Attenuation of skeletal muscle and strength in the elderly: The Health ABC Study

Although loss of muscle mass is considered a cause of diminished muscle strength with aging, little is known regarding whether composition of aging muscle affects strength. The skeletal muscle attenuation coefficient, as determined by computed tomography, is a noninvasive measure of muscle density, and lower values reflect increased muscle lipid content. This investigation examined the hypothesis that lower values for muscle attenuation are associated with lower voluntary isokinetic knee extensor strength at 60 degrees/s in 2,627 men and women aged 70-79 yr participating in baseline studies of the Health ABC Study, a longitudinal study of health, aging, and body composition. Strength was higher in men than in women (132.3 +/- 34.5 vs. 81.4 +/- 22.0 N x m, P < 0.01). Men had greater muscle attenuation values (37.3 +/- 6.5 vs. 34.7 +/- 7.0 Hounsfield units) and muscle cross-sectional area (CSA) at the midthigh than women (132.7 +/- 22.4 vs. 93.3 +/- 17.5 cm(2), P < 0.01 for both). The strength per muscle CSA (specific force) was also higher in men (1.00 +/- 0.21 vs. 0.88 +/- 0.21 N x m x cm(-2)). The attenuation coefficient was significantly lower for hamstrings than for quadriceps (28.7 +/- 8.7 vs. 41.1 +/- 6.9 Hounsfield units, P < 0.01). Midthigh muscle attenuation values were lowest (P < 0.01) in the eldest men and women and were negatively associated with total body fat (r = -0.53, P < 0.01). Higher muscle attenuation values were also associated with greater specific force production (r = 0.26, P < 0.01). Multivariate regression analysis revealed that the attenuation coefficient of muscle was independently associated with muscle strength after adjustment for muscle CSA and midthigh adipose tissue in men and women. These results demonstrate that the attenuation values of muscle on computed tomography in older persons can account for differences in muscle strength not attributed to muscle quantity.

Muscularity and the density of the fat-free mass in athletes

The purpose of this study was to use estimates of body composition from a four-component model to determine whether the density of the fat-free mass (D(FFM)) is affected by muscularity or musculoskeletal development in a heterogenous group of athletes and nonathletes. Measures of body density by hydrostatic weighing, body water by deuterium dilution, bone mineral by whole body dual-energy X-ray absorptiometry (DXA), total body skeletal muscle estimated from DXA, and musculoskeletal development as measured by the mesomorphy rating from the Heath-Carter anthropometric somatotype were obtained in 111 collegiate athletes (67 men and 44 women) and 61 nonathletes (24 men and 37 women). In the entire group, D(FFM) varied from 1.075 to 1.127 g/cm3 and was strongly related to the water and protein fractions of the fat-free mass (FFM; r = -0.96 and 0.89) and moderately related to the mineral fraction of the FFM (r = 0.65). Skeletal muscle (%FFM) varied from 40 to 68%, and mesomorphy varied from 1.6 to 9.6, but neither was significantly related to D(FFM) (r = 0.11 and -0.14) or to the difference between percent fat estimated from the four-component model and from densitometry (r = 0.09 and -0.16). We conclude that, in a heterogeneous group of young adult athletes and nonathletes, D(FFM) and the accuracy of estimates of body composition from body density using the Siri equation are not related to muscularity or musculoskeletal development. Athletes in selected sports may have systematic deviations in D(FFM) from the value of 1.1 g/cm3 assumed in the Siri equation, resulting in group mean errors in estimation of percent fat from densitometry of 2-5% body mass, but the cause of these deviations is complex and not simply a reflection of differences in muscularity or musculoskeletal development.

Validation of body composition estimates in male and female distance runners using estimates from a four-component model

This study used estimates of body composition from a four-component model (%Fat(d,w,m)) to determine whether the assumed density (D(ffm)) and the composition of the fat-free mass (FFM), and estimates of body composition from methods based on two- and three-component models are valid in distance runners. Measures of body density (D(b)) by underwater weighing, total body water by deuterium dilution, and bone mineral by dual-energy X-ray absorptiometry (DXA) were obtained in 10 female and 12 male runners and an equal number of controls matched for age, height, weight, gender, and ethnicity. D(ffm) of the runners did not differ from 1.1 g.cm(-3) or from the controls even though the composition of the FFM differed from that assumed. Therefore, percentage of body fat (%Fat) from densitometry did not differ from %Fat(d,w,m) in the runners, although individual variation was substantial (-5.3 to 3.0% body mass, SD(diff) = 2.1% body mass). Three-component model estimates of %Fat from D(b) and body water agreed quite closely with %Fat(d,w,m) (x </= 1.6% body mass, SD(diff) = 0.5% body mass), whereas those from D(b) and body mineral (x(diff) = 1.6-2.9% body mass, SD(diff) = 2.3% body mass) and from DXA (x(diff) = 2.2-4.0% body mass, SD(diff) = 2.1% body mass) were less accurate and underestimated %Fat(d,w,m). We conclude that D(ffm) does not differ from 1.1 g.cm(-3) and that densitometry is a valid method to estimate group mean body composition, but that measurement of D(b) and total body water are necessary for accurate individual estimates of body composition in male and female distance runners. Am. J. Hum. Biol. 12:301-314, 2000. Copyright 2000 Wiley-Liss, Inc.

Effects of diet and exercise on the density and composition of the fat-free mass in obese women

PURPOSE

The purpose of this study was to determine whether the density (D(FFM)) and composition of the fat-free mass (FFM) and the accuracy of estimates of body composition from body density (%Fat(d)) are affected by diet and exercise.

METHODS

Twenty-nine obese women (body mass index (BMI) = 25.0-43.7 kg x m(-2) and %Fat(d) = 35.7-47.1%) were assigned to one of three groups: diet only (DO, N = 9); diet and aerobic exercise (DE, N = 9); or control (C, N = 11). Measures of body density by hydrostatic weighing, body water by deuterium dilution, and bone mineral by whole-body dual-energy x-ray absorptiometry, and estimates of body composition from body density and from a four-component model were obtained before and after a 16-wk diet and exercise intervention.

RESULTS

Mean (+/- SD) changes in body mass were -7.2 +/- 7.4, -3.9 +/- 3.3, and +1.2 +/- 2.8 kg for the DO, DE, and C, respectively. The density and composition of the FFM did not change significantly (P > 0.05) in any of the groups. Individual changes in D(FFM) (-0.011 to +0.011 g x mL(-1)), and differences between changes in %Fat estimated using a four-component model and %Fat(d) (-2.1 to +2.7% body mass) were not related to changes in body mass (r = -0.08). Individual changes in D(FFM) were most strongly related to changes in water fraction (r = -0.95) and protein fraction (r = +0.88), and were unrelated to changes in the mineral fraction (r = +0.04) of the FFM.

CONCLUSIONS

We conclude that in obese women, the density and composition of the FFM are unaltered and densitometry correctly assesses group mean changes in body composition with moderate weight loss induced by diet or diet and aerobic exercise. However, individual deviations in D(FFM) from the assumed value of 1.1 g x mL(-1) are substantial, and a multi-component model in which body water is measured is needed to accurately assess individual body composition changes resulting from diet and exercise.