Body-composition differences between African American and white women: relation to resting energy requirements

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  
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 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  
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  
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:

RESULTS  
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.

View this table:
TABLE 1. Baseline characteristics and body composition of subjects in experiment 1¹

 
Body composition
The results of experiment 1 body-composition studies are summarized in Table 1. Body weight was not significantly different in the matched groups: AA women weighed 67.0 ± 13.5 kg, and white women weighed 66.9 ± 12.5 kg. Adipose tissue, residual mass, and bone mass did not differ significantly between AA and white women. AA women, however, had greater SM mass than did white women (between-group difference: 1.52 ± 2.48 kg; P < 0.01).

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):
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).

 
Resting metabolic rate
The calculated and measured RMR results are summarized in Table 2. Measured and calculated RMR did not differ significantly between the AA women and the white women. The RMR was 160 kJ/d lower in AA women by both estimation methods, but this difference was not statistically significant. Analysis of covariance also showed no significant effect (P = 0.29) of race on RMR values after control for age, weight, height, and body composition. As expected, age, body weight, and height were significant predictors of RMR (P < 0.01; data not shown).

View this table:
TABLE 2. Resting metabolic rate (RMR) results¹

 
Experiment 2
The second evaluated cohort consisted of 521 women (171 AA and 350 white), and the group’s demographic and body-composition characteristics are summarized in Table 3. The regression model results are presented in Table 4.

View this table:
TABLE 3. Baseline characteristics and body composition of subjects in experiment 2¹

 

View this table:
TABLE 4. Multiple regression models for body composition¹

 
SM mass was predicted by weight, height, age, and race as separate independent variables, each of which was statistically significant (SM model 1 in Table 4: P < 0.05). SM mass was also predicted by weight, height, age, and the race x weight interaction term (model 2), although the model correlation coefficient and SE of estimate were similar to those in model 1 with race alone as a predictor. Race was not a significant predictor variable for SM mass when added separately to the interaction model including the race x weight term (model 3).

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  
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.

REFERENCES  

1. Wang Z, Heshka S, Zhang K, Boozer CN, Heymsfield SB. Resting energy expenditure: systematic organization and critique of prediction methods. Obes Res 2001;9:331–6.
2. FAO/WHO/UNU. Energy and protein requirements. Rome: FAO, 1985.
3. Gannon B, Dipietro L, Poehlman ET. Do African Americans have lower energy expenditure than Caucasians? Int J Obes Relat Metab Disord 2000;24:4–13.
4. Hunter GR, Weinsier RL, Darnell BE, Zuckerman PA, Goran MI. Racial differences in energy expenditure and aerobic fitness in premenopausal women. Am J Clin Nutr 2000;71:500–6.
5. Wong WW, Butte NF, Ellis KJ, et al. Pubertal African-American girls expend less energy at rest and during physical activity than Caucasian girls. J Clin Endocrinol Metab 1999;84:906–11.
6. Yanovski JA. Resting energy expenditure in African American and white children. Am J Clin Nutr 2001;73:149–50.
7. Tershakovec AM, Kuppler KM, Zemel B, Stallings VA. Age, sex, race, body composition, and resting energy expenditure of obese African American and white children and adolescents. Am J Clin Nutr 2002;75:867–71.
8. Gallagher D, Belmonte D, Deurenberg P, et al. Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass. Am J Physiol 1998;275:E249–58.
9. Heymsfield SB, Gallagher D, Kotler DP, Wang Z, Allison DB, Heshka S. Body-size dependence of resting energy expenditure can be attributed to non-energetic homogeneity of fat-free mass. Am J Physiol 2002;282:E132–8.
10. Gallagher D, Allen A, Wang ZM, Heymsfield SB, Krasnow N. Smaller organ tissue mass in the elderly fails to explain lower resting metabolic rate. Ann N Y Acad Sci 2000;904:449–55.
11. Hayes M, Chustek M, Wang Z, et al. DXA: potential for creating a metabolic map of organ-tissue resting energy expenditure components. Obes Res 2002;10:969–77.
12. Elia M. Organ and tissue contribution to metabolic rate. In: Kinney JM, Tucker HN, eds. Energy metabolism: tissue determinants and cellular corollaries. New York: Raven Press, 1992:61–80.
13. Ortiz O, Russell M, Daley TL, et al. Differences in skeletal muscle and bone mineral mass between black and white females and their relevance to estimates of body composition. Am J Clin Nutr 1992;55:8–13.
14. Gallagher D, Visser M, De Meersman RE, et al. Appendicular skeletal muscle mass: effects of age, gender, and race. J Appl Physiol 1997;83:229–39.
15. Holliday MA, Potter D, Jarrah A, Bearg S. The relation of metabolic rate to body weight and organ size. Pediatr Res 1967;1:185–95.
16. Grande F. Nutrition and energy balance in body composition studies. In: Broek J, Jensdell A, eds. Techniques for measuring body composition. Washington, DC: National Academy of Sciences/National Research Council, 1961:168–88.
17. Wagner DR, Heyward VH. Measures of body composition in blacks and whites: a comparative review. Am J Clin Nutr 2000;71:1392–402.
18. Pierson RN Jr, Wang J, Heymsfield SB. Measuring body fat: calibrating the rulers. intermethod comparisons in 389 normal Caucasian subjects. Am J Physiol 1991;261:E103–8.
19. Kim J, Wang Z, Heymsfield SB, Baumgartner RN, Gallagher D. Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method. Am J Clin Nutr 2002;76:378–83.
20. Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol 1949;109:1–9.
21. Henry CJK, Rees DG. New predictive equations for the estimation of basal metabolic rate in tropical peoples. Eur J Clin Nutr 1991;45:177–85.
22. Lawrence M, Thongprasert K, Durnin JVGA. Between-group differences in basal metabolic rates: an analysis of data collected in Scotland, The Gambia and Thailand. Eur J Clin Nutr 1988;42:877–91.
23. Soares MJ, Francis DG, Shetty PS. Predictive equations for basal metabolic rates of Indian males. Eur J Clin Nutr 1993;47:389–94.
24. Soares MJ, Piers LS, O’Dea K, Shetty PS. No evidence for a race influence on basal metabolism: an examination of data from India and Australia. Br J Nutr 1998;79:333–41.
25. Sun M, Gower BA, Bartolucci AA, Hunter GR, Figueroa-Colon R, Goran MI. A longitudinal study of resting energy expenditure relative to body composition during puberty in African American and white children. Am J Clin Nutr 2001;73:308–15.
26. Albu J, Shur M, Curi M, Murphy L, Heymsfield SB, Pi-Sunyer FX. Resting metabolic rate in obese, premenopausal black women. Am J Clin Nutr 1997;66:531–8.
27. Foster GD, Wadden TA, Swain RM, Anderson, Vogt RA. Changes in resting energy expenditure after weight loss in obese African American and Caucasian women. Am J Clin Nutr 1999;69:13–7.
28. Weyer C, Snitker S, Bogardus C, Ravussin E. Energy metabolism in African Americans: potential risk factors for obesity. Am J Clin Nutr 1999;70:13–20.
29. Sharp TA, Bell ML, Grunwald GK, et al. Difference in resting metabolic rate between white and African-American young adults. Obes Res 2002;10:726–32.
30. Yanovski JA, Yanovski SZ, Filmer KM, et al. Differences in body composition of black and white girls. Am J Clin Nutr 1996;64:833–9.
31. Yanovski SZ, Reynolds JC, Boyle AJ, Yanovski JA. Resting metabolic rate in African-American and Caucasian girls. Obes Res 1997;5:321–5.
32. Iida H, Rhodes CG, Araujo LI, et al. Noninvasive quantification of regional myocardial metabolic rate for oxygen by use of ¹⁵O₂ inhalation and positron emission tomography. Circulation 1997;94:792–807.