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Body-composition differences between African American and white women: relation to resting energy requirements^1,2,3

¹ From the Department of Medicine, Obesity Research Center, St Luke’s—Roosevelt Hospital, Columbia University, College of Physicians and Surgeons, New York

² Supported by National Institutes of Health Grant RO1-NIDDK 42618 and by a National Institutes of Health Minority Fellowship Award (to AJ).

³ Reprints not available. Address correspondence to SB Heymsfield, St Luke’s—Roosevelt Hospital, Weight Control Unit, 1090 Amsterdam Avenue, 14th Floor, New York, NY 10025. E-mail: sbh2{at}columbia.edu.

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: Body composition differs between African American (AA) and white women, and the resting metabolic rate (RMR) is likely to be lower in AA women than in white women.

Objective: We tested 2 hypotheses: that AA women have a greater proportion of low-metabolic-rate skeletal muscle (SM) and bone than do white women and that between-race musculoskeletal differences are a function of body weight.

Design: Hypothesis 1 was tested by comparing SM, bone, adipose tissue, and high-metabolic-rate residual mass across 22 pairs of matched AA and white women. Magnetic resonance imaging and dual-energy X-ray absorptiometry were used to partition weight into 4 components, and RMR was both calculated from tissue-organ mass and measured. Hypothesis 2 was evaluated by measuring SM, bone, fat, and residual mass in 521 AA and white women with the use of dual-energy X-ray absorptiometry alone.

Results: Hypothesis 1: AA women had greater SM ( ± SD group difference: 1.52 ± 2.48 kg; P < 0.01) and musculoskeletal mass (1.72 ± 2.66 kg; P < 0.01) than did white women. RMR calculated from body composition and measured RMR did not differ; RMR estimated by both approaches tended to be lower (160 kJ/d) in AA women than in white women. Hypothesis 2: SM was significantly correlated with weight, height, age, and race x weight interaction; greater SM in the AA women was a function of body weight.

Conclusions: Lower RMRs in AA women than in white women are related to corresponding differences in the proportions of heat-producing tissues and organs, and these race-related body-composition differences increase as a function of body weight.

Key Words: Energy requirements • resting metabolic rate • obesity • nutritional assessment

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Of the energy that humans and other mammals expend over time, the largest fraction is resting metabolic rate (RMR; 1), which is reflective of the collective ongoing biological processes involved in cellular and tissue maintenance and repair (2). Interindividual variation in RMR, after adjustment for body size, is of intense research interest with respect to human energy requirements (2). A consistent observation has been that RMR is lower in African American (AA) women than in white women of comparable weight, height, age, and fat-free mass (FFM; 3-7). Some investigators suggest that a relatively low RMR in AA females may be a predisposing risk factor for long-term weight gain and obesity (7).

A new approach to the exploration of between-group RMR differences is the modeling of energy exchange in the context of tissue-organ body composition (1, 8). The RMR of each tissue and organ is derived as the product of organ mass and tissue-specific metabolic rate. Tissue and organ mass content are derived by whole-body magnetic resonance imaging (MRI; 8, 9). The specific metabolic rates are known and validated for adults aged <50 y (8). Earlier reports support the validity of this RMR estimation approach for MRI models ranging from 4 to 8 tissue-organ components (8-10).

The 4-compartment MRI model partitions body mass into adipose tissue, skeletal muscle (SM), bone, and residual mass (9-11). The residual component includes brain, liver, kidneys, heart, gastrointestinal tract, and other organs and tissues. Brain and visceral organs are high-metabolic-rate compartments that account for a disproportionately large fraction of RMR relative to their mass (12). Earlier reports suggest that AA women have a greater SM and bone mass than do white women of similar weight, height, and age (13, 14). SM and bone are low-metabolic-rate tissues (8, 12, 15, 16), and the extent to which the greater musculoskeletal mass in AA women is offset by a lower residual mass and adipose tissue mass than is seen in their equivalent-weight white counterparts remains unknown. Similarly, a lower residual mass in AA women correspondingly leads to a lower RMR than is seen in white women. Alternatively, a greater musculoskeletal mass accompanied by a lower adipose tissue mass would produce small effects on RMR.

The present study consisted of 2 linked experiments. The first experiment, based on earlier observations, was formulated on the basis of the hypothesis that adult AA women have a greater amount of SM (13, 14) and bone (13, 17) than do matched white women. In this framework, we examined corresponding differences in other body components and RMR with the ultimate aim of establishing whether and to what extent body-composition effects might account for observed differences in RMR between AA and white women. The initial results led us to propose a second hypothesis—that body-composition differences between the races are a function of body mass—and to conduct a second experiment to test that hypothesis.

	SUBJECTS AND METHODS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Experimental design and protocol
Experiment 1
Healthy adult AA and white women were included in the first phase of the study. Race was determined by each subject’s self-report that each parent and all 4 grandparents were of the same race. Age was limited to <50 y for RMR modeling purposes because the applied formulas are accurate in younger subjects but less reliable in older subjects (8, 10). The source database consisted of 220 women aged >18 y who were evaluated as part of a long-term body-composition study (18). Each AA woman was matched to a white woman by age (±10 y), weight (±4 kg), and height (±5 cm). Twenty-two matches were completed, for a total of 44 subjects. Women were all premenopausal and were studied independent of menstrual cycle activity.

Four tissue-organ compartments were evaluated: adipose tissue, SM, bone, and residual mass. Adipose tissue and SM mass were estimated by whole-body MRI scanning as previously reported (8-10). Bone mineral mass was measured by dual-energy X-ray absorptiometry (DXA), and bone mass was calculated as 1.8 x bone mineral mass (9, 11). Residual mass was then calculated as the difference between body mass and the sum of the 3 measured compartments.

RMR was measured after an overnight fast using a ventilated hood indirect calorimetry system (Delta-Trac II metabolic monitor; SensorMedics, Yorba Linda, CA). RMR was also calculated from body composition as the summed products of compartment mass and known specific metabolic rate. The specific metabolic rates, as previously estimated for adults aged <50 y, are for adipose tissue, SM, bone, and residual mass 18.8, 54.3, 9.6, and 225.7 kJ · kg^–1 · d^–1, respectively (9). We assume in this study that there are no race differences in these specific metabolic rates.

We also examined the relations between RMR estimates and FFM in the matched women and, for consistency, we calculated FFM from MRI estimates, rather than DXA, as the sum of SM, bone, residual, and fat-free adipose tissue mass. We assumed that fat-free adipose tissue mass is 15% of adipose tissue mass (9, 11). In an earlier study we found FFM, as analyzed by MRI, to be almost identical to FFM measured by DXA (9, 11).

All measurements were made within one day of each other. The subject’s body weight was measured to the nearest 0.01 kg using a digital scale (Weight-Tronix; Scale Electronics Development, New York). Standing barefoot height was measured to the nearest 0.1 cm with a wall-mounted Holtain stadiometer (Holtain Limited, Crosswell, United Kingdom).

Experiment 2
Once analyzed, the initial database confirmed a significant but small difference in SM mass between AA and white women. On the basis of a review of composite earlier studies (3-7) and our own new data, we advanced the second hypothesis: that the magnitude of race differences in SM mass is a function of body mass. Accordingly, we assembled a second data set of 521 healthy adult AA and white women from the center’s archives (14, 18). Each subject had completed a DXA scan, and we then evaluated the measured appendicular lean soft tissue mass by using Kim’s equation (19) to estimate total-body SM mass:

(1)

where SM and lean soft tissue are given in kg. The hypothesis was tested by examining SM in the women as a function of a race x weight interaction after control for weight, height, and age with the use of multiple regression analysis. DXA also provided in these subjects a measure of fat and bone mineral mass, and we were thus able to calculate residual mass as the difference between body mass and the sum of fat, SM, and bone mineral. This second residual mass definition differs slightly from that in experiment 1, in which residual mass was calculated as the difference between body mass and the sum of adipose tissue, SM, and bone mass. We then examined the relations between these compartments and weight, height, age, and race by using the same procedures are for the estimation of SM mass. An earlier study supported the use of a similar four-component model using DXA alone as a practical alternative to MRI estimates in exploring body composition–RMR relations (11).

The St Luke’s—Roosevelt Hospital Institutional Review Board approved both studies, and all subjects gave written informed consent before their participation.

Body composition
Magnetic resonance imaging
Whole-body MRI was carried out as previously reported by Heymsfield et al (9). The MRI scans were prepared by using a 1.5 T scanner (6X Horizon; General Electric, Milwaukee) with a T1-weighted, spin-echo sequence, a 210-ms repetition time, a 17-ms echo time, a 48-cm field of view, and a 256 x 256 matrix. The protocol involved acquisition of 40 axial images of 10-mm thickness at 40-mm intervals from head to toe. The procedure details are provided in reference 8. After this acquisition, the MRI scans were segmented into each of the 3 components (ie, adipose tissue, SM, and remainder) by a highly trained technician who used image analysis software (Tomovision Inc, Montreal). The volume of each component was calculated by using an equation:

(2)

where V is the total volume of the measured compartment, A_i is each scan’s cross-sectional area of the component, h is the between-slice interval, t is the thickness of each slice, and N is the number of total slices. Volume estimates for the components were converted to mass units (kg) by taking the product of volume (L) and tissue density (ie, adipose tissue = 0.92 kg/L; SM and remainder = 1.04 kg/L; 8).

Dual-energy X-ray absorptiometry
Whole-body DXA was used to measure bone mineral mass, appendicular lean soft tissue (14), and fat. The scan was completed with a Lunar DPX system with LUNAR DPX software (version 3.6; Lunar Radiation Corp, Madison, WI), as previously reported (14).

Resting metabolic rate
The Columbia Respiratory Chamber–Indirect Calorimeter (Columbia University, New York) was used to measure RMR with a plastic ventilated hood over a 40- to 60-min interval; details of the measurement methods were published elsewhere (8). Briefly, subjects were instructed to consume their normal diet and refrain from any vigorous physical activity on the day before the RMR test. On the day of the experiments, subjects arrived at the research center after a 12-h fast and rested for 20–30 min. Minute-by-minute energy expenditure data were acquired for the subsequent 60 min, and the data for the first 20–25 min were discarded from the analyses because they are often erratic. Oxygen consumption and carbon dioxide production were analyzed by using magnetopneumatic oxygen (Magnos 4G) and carbon dioxide (Magnos 3G) analyzers (Hartmann & Braun, Frankfurt, Germany), respectively. Gas exchange rates, evaluated during the stable measurement period, were used to calculate RMR as described by Weir (20).

Statistical methods
The first hypothesis was tested in experiment 1 by comparing musculoskeletal mass (ie, the sum of SM mass and bone) between AA and white women with the use of a paired t test and with statistical significance set at P < 0.05. Analysis of covariance was used to test the effects of age, body weight, height, SM mass, FFM, bone mass, and race on RMR. Other descriptive between-group comparisons were also tested for significance with paired tests. Group results are presented as means ± SDs in the text and tables and as means ± SEs in the figure.

The second hypothesis was tested in experiment 2 by using multiple regression analysis with SM as the dependent variable and weight, height, age, race, and race x weight as the predictor variables. Similar regression models were then prepared for fat, bone, and residual mass as dependent variables. All statistical evaluations were carried out with the use pf SPSS for WINDOWS software (version 10.0; SPSS Inc, Chicago).

	RESULTS

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Experiment 1
Subjects
The characteristics of the subjects in the first experiment are presented in Table 1. There were 22 subject pairs with no significant between-group differences in age, height, or body mass index.

The calculated fat-free component of adipose tissue comprised the smallest fraction of FFM in both groups, and the fractions were increasingly larger in bone, residual mass, and SM (observations not shown). The fraction of FFM as SM was larger (P < 0.05) in AA women than in white women, but the fat-free component of bone, residual mass, and adipose tissue as a percentage of FFM did not differ significantly between AA women and white women.

Musculoskeletal mass was 1.72 ± 2.66 kg larger (P < 0.01) in the AA women (25.9 ± 2.8 kg) than in the white women (24.2 ± 2.9 kg; Figure 1). Expressed as a fraction of FFM, musculoskeletal mass was significantly greater (P = 0.01) in the AA women (0.56 ± 0.05) than in the white women (0.53 ± 0.04), for a between-race fractional of 0.032 ± 0.060.

View larger version (36K): [in this window] [in a new window]   FIGURE 1. Mean (±SEM) musculoskeletal mass in African American and white women (n = 44) expressed as an absolute mass (upper panel) and as a fraction of the fat-free mass (FFM; lower panel). *Significantly different from the white women, P < 0.01 (paired t test).

Table 2

Table 3

Table 4

Similarly, the race x weight interaction term was a significant predictor of bone mineral mass (models 2 and 3) and residual mass (RM models 2 and 3). In contrast, race alone and race x weight failed to be a significant predictor of fat mass (model 1).

The magnitude of the race x weight term in body-composition prediction can be shown by using an example of 2 pairs of female subjects, in which one pair is AA and the other pair is white, both subjects in each pair are 165 cm in height and 25 y of age, but one subject has a body weight of 50 kg and the other has a body weight of 100 kg. The models in Table 4 can be used to calculate the mass of each component for the 4 women. In the pair of 50-kg women, SM and bone mineral mass would be larger by 1.0 and 0.3 kg, respectively, and residual mass smaller by 0.9 kg in the AA woman than in the white woman, and there would be no predicted differences in fat mass. We assume the small residual mass difference of 0.4 kg represents either model prediction error or a nonsignificant race difference in fat mass. In the 100-kg pair, the AA woman would have 2.0 kg and 0.5 kg more SM and bone mineral mass, respectively, and 1.8 kg less residual mass than would the white woman, and there would be no predicted differences in fat mass.

	DISCUSSION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
The present study was prompted by the finding in earlier studies of a lower RMR in AA women than in white women after adjustment for conventional measures, such as weight, height, and age; body composition as fat; and FFM (3-7, 21-29). In this study we explored additional body-composition and related energy expenditure measures under the general working theory that previously observed RMR differences may be accounted for by race variation in the proportions of tissue-organ components.

In the first experiment we used whole-body MRI and DXA to partition body mass into 4 compartments differing in metabolic activity, ie, adipose tissue, SM, bone, and residual mass. Our observations support the view that AA women have a greater musculoskeletal mass than do white women who are similar in age, weight, and height (13, 14, 17), and this difference persists even when musculoskeletal mass is expressed as a fraction of FFM. Similarly, AA girls matched to white girls for age, Tanner stage, and body mass index had greater limb lean body mass than did the white girls, as assessed by DXA (30). However, the absolute body-composition differences by race that were observed in the present study were not large—only 1.7 kg for the sum of SM and bone mass.

Because the between-group subject weights in the first experiment were matched, by necessity the AA women had 1.7 kg less of other components—0.6 kg of adipose tissue and 1.1 kg of residual mass—than did their white counterparts. The net result is that in AA women there was a slight shift in the proportion of heat-producing tissues favoring lower RMR SM and bone over higher RMR organ-containing residual mass; estimated heat production differences secondary to adipose tissue were negligible. Because we assumed that no race difference exists in tissue-organ–specific metabolic rates, this shift in tissue-organ distribution was reflected in a small, nonsignificantly lower predicted RMR of 167.2 kJ/d in the AA women. A small difference in the same direction and magnitude was observed in measured RMR. Thus, largely the combined effects of a greater musculoskeletal mass and lower residual mass could account for the difference between RMR in AA women and that in their white counterparts. This small metabolic rate effect combined with a relatively small sample size might be one reason for the nonsignificant between-group RMR difference.

The completion of the first experiment validated our body-composition hypothesis, but the magnitude of calculated and measured RMR differences was relatively small and statistically nonsignificant. Accordingly, we revisited earlier body-composition and RMR studies exploring these issues and noted 2 findings: either AA women were heavier than were their white counterparts, or both AA and white women were heavier than were the women evaluated in the current study. Most of the earlier studies reported absolute body-composition and RMR differences between AA and white subjects rather than differences expressed as a function of body mass. We therefore postulated a second hypothesis linking differences in body composition and, by inference, in RMR to body mass. Our observations in the second experiment support this hypothesis and show, in a large sample of women, increasing SM, bone, and residual mass differences between AA and white women as a function of body mass. According to the developed prediction models, RMR would differ by 167.2 kJ/d between AA women and white women weighing 50 kg, but this difference would be doubled between women weighing 100 kg. These differences would reflect a 3–5% lower RMR in AA women than in white women.

Previous studies in both children and adults reported either no race-related RMR differences or statistically significant RMR differences of 630–840 kJ/d (3-7, 21-29). The extent to which measurement error, small sample sizes, and subject characteristics contribute to these observed differences is unknown. The results of our study suggest that RMR differences between AA women and white women may be a function of body mass, and this phenomenon may account for some of the variation observed across studies. That is, there are between-race weight differences both within and between earlier studies. Our findings predict larger AA-white RMR differences in subject groups with greater body mass index.

In a study relevant to the present investigation, Hunter et al (4) examined RMR in AA and white women. Fat-free mass, fat mass, and regional lean tissue were also determined by DXA. The AA women had a lower RMR (506 kJ/d) than did the white women, and this significant difference persisted after adjustment for FFM and limb lean tissue mass, which is mainly SM, but it disappeared after adjustment for trunk lean tissue. The investigators suggest that relatively low volumes of metabolically active organs mediate the low RMR of AA women; this hypothesis is consistent with the findings of the present study. Similar results were observed in an earlier study of prepubertal girls (31). In that study, black girls had an RMR of 385 kJ/d, which was significantly lower than the RMR of white girls matched for age, Tanner stage, and body mass index, after adjusting for FFM. Specifically, after matching or control for body weight, our own findings show greater musculoskeletal muscle mass and correspondingly less higher-metabolic-rate residual mass in the AA women than in the white women.

Rather than providing definitive results, our findings suggest the need for future studies in a larger sample with well-defined characteristics along with direct MRI measurements of the high-metabolic-rate organs and tissues rather than of the less specific residual mass component. Other critical limitations of our study are that we assumed that no race differences exist in tissue- and organ-specific metabolic rates, and that we limited our study to subjects aged <50 y. Whereas the similar calculated and measured RMRs in both groups of women support our assumed specific metabolic rates, a need exists to move forward to direct measurements of organ metabolic rates in vivo. In vivo measurement of organ consumption of O₂ is now possible with positron emission tomography by using ¹⁵O inhalation (32), and future studies should examine whether differences in tissue- and organ-specific metabolic rates exist between race groups.

Conclusion
The present study results suggest that AA and white women differ in relative body composition as a function of body mass and that there are larger race differences at greater weights. These differences appear to be small overall, but quantifiable with appropriate methods and adequate sample size. Our analysis also supports the view that these differences in body composition translate to small differences in RMR and, potentially, in energy requirements. These observations help to reconcile the variable findings in earlier studies by showing the small magnitude of body-composition and, potentially, RMR effects that vary as a function of body mass. Finally, on the basis of the observed lower residual mass, our study also suggests a lower mass of higher-metabolic-rate visceral organs in AA women than in white women.

	ACKNOWLEDGMENTS

 
AJ, M-PS-O, and SBH were responsible for the study design; AJ, WS, DG, and ZW were responsible for data collection; AJ, WS, SH, ZW, and SBH were responsible for data analysis; and AJ, WS, DG, SH, M-PS-O, ZW, and SBH were responsible for writing the manuscript. None of the authors had any financial or personal conflict of interest.

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