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Sex and Race Differences in Fat Distribution among Asian, African-American, and Caucasian Prepubertal Children

Obesity Research Center (Q.H., M.H., J.T., J.W., R.N.P., S.H., D.G.), St. Luke’s-Roosevelt Hospital, Institute of Human Nutrition (Q.H., D.G.), and Children’s Hospital of New York (M.H.), College of Physicians and Surgeons, Columbia University, New York, New York 10025

Address all correspondence and requests for reprints to: Mary Horlick, M.D., Body Composition Unit, St. Luke’s-Roosevelt Hospital, Plant Basement, New York, New York 10025. E-mail: . mnh1@columbia.edu

Abstract

Sexual dimorphism in fat distribution is thought to emerge during puberty. Truncal or android body fat distribution is characteristic of adult males but is also recognized as a human cardiovascular risk factor. Race differences in truncal fat are clearly evident in adults and have been described in prepubertal children but not between Asians and other race groups. The aim of this study in African-American, Asian, and Caucasian prepubertal children was to evaluate sex differences and race differences in body fat distribution. Analysis of covariance was used to explore fat distribution in 358 prepubertal children (176 girls and 182 boys; 143 Asians, 95 African-Americans, and 120 Caucasians), measured by skinfold thickness and dual-energy x-ray absorptiometry (DXA) in a cross-sectional study. Extremity and gynoid fat masses were evaluated after adjustment for trunk or android fat, respectively, and for covariates including age, weight, height, and interactions. In Asian children, sex differences were present in models for gynoid fat by DXA only (P < 0.001), with girls having greater gynoid fat than boys. In African-American and Caucasian children, sex differences were present in models for extremity and gynoid fat masses, measured by both methods. Among girls, Asians had generally lower adjusted extremity and gynoid fat than Caucasians and African-Americans. Among boys, Asians had lower adjusted extremity fat by DXA than Caucasians (P < 0.01) but greater gynoid fat by skinfolds than African-Americans (P < 0.01). This study of prepubertal children demonstrates that: 1) sex differences in body fat distribution are present in prepubertal children but that the specific characteristics for Asians differ from African-Americans and Caucasians, and 2) differences in body fat distribution in Asian children, compared with African-Americans and Caucasians, are present but vary by sex. This comparison of African-American, Asian, and Caucasian prepubertal children suggests phenotypic differences. Additional studies are needed to explore the metabolic and health risk implications of these findings.

THE IMPORTANCE OF fat distribution, in addition to total fat, as a risk factor for cardiovascular disease is recognized in both adults (1, 2, 3, 4) and children (5, 6). An android or male fat pattern, with relatively greater fat in the upper body region, is associated with negative metabolic predictors (6, 7, 8). A gynoid or female fat pattern, with relatively greater fat in the hip and thigh areas, is associated with less metabolic risk (9). Similarly, a pattern of fat deposits favoring trunk relative to extremities has also been linked to health risks (10, 11, 12). Identifying the timing of appearance and sex- and race-specific fat distribution patterns in healthy children will establish phenotypes to guide investigation of metabolic implications and possible mechanisms.

Sex differences in fat distribution have been observed in pubertal subjects (13, 14, 15, 16, 17). To our knowledge, only one study (18) reported sexual dimorphism of fat distribution in prepubertal children, using the waist to hip ratio, an index that has been questioned as a valid assessment of fat distribution in children (17). Previous studies have reported race differences in fat distribution in pubertal children (19) and in prepubertal children, including African-Americans and Caucasians (20, 21, 22). Although differences in sc fat and fat distribution in Asian adults, compared with Caucasians, have been described (23, 24), it is unknown whether this is true in prepubertal Asian children.

The aims of this study were to evaluate sex differences in body fat distribution in prepubertal children and race differences in fat distribution in African-American, Asian, and Caucasian children. Two independent methods of assessing fat distribution, anthropometry and dual-energy x-ray absorptiometry (DXA), were used to investigate relative gynoid and extremity fat mass in 358 healthy children.

Materials and Methods

Subjects

Participants were 176 prepubertal girls (52 African-Americans, 69 Asians, and 55 Caucasians) and 182 prepubertal boys (43 African-Americans, 74 Asians, and 65 Caucasians), volunteers in a cross-sectional body composition project (25), with age range 5–12 yr. Volunteers were recruited through local newspaper notices, announcements at schools and after-school centers, and word of mouth. Consent was obtained from each volunteer’s parent or guardian and assent was obtained from each volunteer as well. Consistent Asian, non-Hispanic African-American, or non-Hispanic Caucasian background of both parents and all four grandparents by questionnaire established ethnicity. The Asian volunteers were of Chinese and Korean background. There were no height or weight restrictions to entry into the study. A medical history from the parent or guardian and a physical examination confirmed normal health status. The Institutional Review Board of St. Luke’s-Roosevelt Hospital Center approved the study.

Pubertal status was established according to the criteria of Tanner (26) by the pediatric endocrinologist or nurse. Serum gonadal steroid and gonadotropin levels measured in a random sample of 29 study participants were consistent with prepubertal status.

Body composition measurement

All medical and body composition evaluations were carried out on the same day at least 1 h after a light meal, with the subject clothed in a hospital gown and wearing foam slippers.

Anthropometry

Body weight was measured to the nearest 0.1 kg (Weight Tronix, New York, NY) and height to the nearest 0.5 cm using a stadiometer (Holtain, Crosswell, Wales). Skinfold thicknesses were measured to the nearest 1.0 mm with a Lange caliper at the following sites: triceps, biceps, chest, subscapular, abdomen, suprailiac, thigh, and calf. All skinfold measurements were taken on the right side of the body, using the procedures recommended by Lohman et al. (27). The average of two readings was recorded with the measurement to ± 2 mm. Subjects were measured by one of two investigators during the study period. The intraclass correlation coefficients between the two investigators on skinfold measurement were triceps (0.97), biceps (0.89), chest (0.99), subscapular (0.92), abdomen (0.99), suprailiac (0.99), thigh (0.95), and calf (0.97). The skinfold thicknesses comprising trunk, extremity, android, and gynoid fat masses by anthropometry are presented in Table 1.

Total body fat, total body fat free mass, regional fat, and regional fat free mass were measured with a whole-body DXA scanner (DPX, Lunar Corp., Madison, WI) using pediatric software version 3.8G.

The calculation of regional soft tissue mass has been previously described in detail (28). Using specific anatomic landmarks, the legs and arms were isolated on the skeletal x-ray planogram (anterior view). The arm encompasses all soft tissue extending from the center of the arm socket to the phalange tips, avoiding contact with the ribs, pelvis, or greater trochanter. The leg consists of all soft tissue extending from an angled line drawn through the femoral neck to the phalange tips. The trunk consists of ribs, spine, pelvis, and greater trochanter. The system software provides the total mass, ratio of soft tissue attenuations, and bone mineral mass for the isolated regions. The ratio of soft tissue attenuation for each region was used to divide bone mineral free tissue of the extremities into fat and fat-free components. The DXA regions are seen in Fig. 1, and the regions comprising trunk, extremity, android, and gynoid fat masses by DXA are presented in Table 1.

Figure 1. DXA regions (head, arms, ribs, spine, pelvis, legs). Repeated daily measurements in three adult subjects showed a coefficient of variation (CV) of 5% for arm fat soft tissue, 1% for leg fat soft tissue, and 2% for trunk fat soft tissue. Reproducibility of DXA in children has been reported (29); however, because of concerns surrounding unnecessary radiation exposure in healthy children, scan reproducibility in children was not performed in our study.

Statistical analysis

Fat distribution has frequently been expressed as ratios (14, 18, 19). In this study we chose to use analysis of covariance models with gynoid or extremity fat as the dependent variable with other relevant variables as covariates, e.g. trunk fat was treated as a covariate when investigating extremity fat. This approach was chosen to avoid the numerous problems associated with the use of ratios in statistical analysis (30). Analysis of covariance was used to explore sex (female and male) and race (Asian, African-American, and Caucasian) differences in body fat distribution. Trunk or android fat mass, age, weight, and height and their interactions were included as covariates in these analyses. To achieve normal distribution of the residuals of the regression models, log transformation was used to transform both dependent variables and weight. Because of the large number of variables considered in each model, P less than 0.01 was set as the level for statistical significance. To explore race and sex interactions, least squares-mean (LS-mean) values were computed for each dependent variable. Adjusted multiple posthoc comparisons (P < 0.01) were used to evaluate the differences in adjusted means.

All statistics were computed using SAS software version 8 (31).

Models

Body fat distribution was explored using the four models shown in Table 1. Models 1–2 evaluate fat distribution measured by skinfold thicknesses, and models 3–4 consider fat distribution measured by DXA. All models included age, sex, race, body weight, height, and two-way interactions; however, only statistically significant interactions were retained. Models 1 and 3 have extremity fat as the dependent variable with trunk fat as a covariate. Models 2 and 4 have gynoid fat as the dependent variable with android fat as a covariate.

Results

The subject characteristics are summarized in Table 2. The mean weight and height percentiles for age of the study participants were at the 50th to 75th percentile of the Centers for Disease Control and Prevention growth charts (32).

Table 3. Analysis of covariance models with body fat measurement (skinfold thickness or DXA fat mass) as the dependent variable

 

Variable Extremity Gynoid Model 1 (skinfold) R2 = 0.83 P < 0.0001 Model 3 (DXA) R2 = 0.95 P < 0.0001 Model 2 (skinfold) R2 = 0.84 P < 0.0001 Model 4 (DXA) R2 = 0.94 P < 0.0001 ß t ß t ß t ß t Trunk 0.45 12.35 0.56 20.83 Android 0.55 11.32 0.48 17.55 Age 0.00 0.12 0.01 0.91 -0.01 -0.49 0.01 1.05 Sex1 -0.18 -4.78 -0.20 -6.32 -0.29 -6.28 -0.27 -8.26 A2 0.83 2.71 0.61 2.48 0.64 1.69 0.84 3.21 C2 0.49 1.63 0.34 1.41 0.19 0.52 0.40 1.55 Sex-A3 0.16 3.34 0.16 4.03 0.24 4.06 0.19 4.44 Sex-C3 0.09 1.76 0.13 3.08 0.08 1.29 0.10 2.35 Weight 0.79 5.61 0.82 6.46 1.06 5.97 0.81 5.69 Weight-A3 -0.26 -2.88 -0.23 -3.10 -0.20 -1.80 -0.29 -3.71 Weight-C3 -0.12 -1.37 -0.11 -1.55 -0.03 -0.30 -0.13 -1.77 Height -0.01 -3.27 -0.01 -2.47 -0.01 -3.09 -0.00 -1.35 Intercept 0.99 3.87 -1.29 -4.39 -0.19 -0.58 -1.07 -3.19

ß coefficients with a P value less than 0.01 are in bold.

¹ Sex: boy = 1; girl = 0.

² Race: A = 1 for Asian, A = 0 for otherwise; C = 1 for Caucasian; C = 0 for otherwise.

³ Interaction: sex and race; weight and race.

 A main effect for sex was found using both skinfold and DXA methods, with girls having greater extremity and gynoid fat deposits, compared with boys, after adjusting for covariates (models 1–4). A main effect for race was also found in some of the models (models 1 and 4). The effect of age was not significant in any of the models.

Because significant sex and race interactions were present in models 1–4 (Table 3), LS-mean and SE values were computed for the dependent variables (log extremity fat mass and log gynoid fat mass) adjusted for trunk or android fat, respectively, as well as for age, weight, height, and sex-race interactions. The LS-mean values by sex within race and by race within sex are all presented in Figs. 2 and 3.

Figure 2. Adjusted means and SE of log-transformed values for skinfold-derived extremity (a) and gynoid (b) fat and for DXA-derived extremity (c) and gynoid (d) fat. *, Adjusted multiple post hoc comparisons (P < 0.01) were used to evaluate the sex differences in adjusted means within each race group.

Figure 3. Adjusted means and SE of log-transformed values for skinfold-derived extremity (a) and gynoid (b) fat and for DXA-derived extremity (c) and gynoid (d) fat. *, Adjusted multiple post hoc comparisons (P < 0.01) were used to compare the adjusted means for Asians with those for African-Americans and Caucasians. Boys and girls were analyzed separately.

In Asians, fat distribution differed significantly between girls and boys in the DXA-derived gynoid fat model only (Fig. 2d), with greater gynoid fat deposit in girls than in boys (P < 0.001). However, sex differences in body fat distribution were found in all models for Caucasians (P < 0.01) and African-Americans (P < 0.0001), with girls having greater extremity and gynoid fat deposits than boys (Fig. 2).

Race

Among girls, Asians had less skinfold derived extremity (Fig. 3a) and gynoid fat (Fig. 3b) than Caucasians (P < 0.01) but were not significantly different from African-Americans. For DXA-derived extremity fat (Fig. 3c), Asians had less than Caucasians and African-Americans (P < 0.0001). For DXA-derived gynoid fat (Fig. 3d), Asians had less than African-Americans (P < 0.001) but were not significantly different from Caucasians.

Among boys, Asians had more skinfold-derived gynoid fat (Fig. 3b) than African-Americans (P < 0.001) but were not significantly different in skinfold-derived extremity fat from African-Americans (Fig. 3a). Asians and Caucasians did not differ in skinfold-derived extremity (Fig. 3a) and gynoid fat (Fig. 3b). For DXA-derived extremity fat (Fig. 3c), Asians had less than Caucasians (P < 0.01) but did not differ significantly from African-Americans. DXA-derived gynoid fat did not differ significantly among the three race groups in boys (Fig. 3d).

Discussion

This study, using two independent methods of regional fat measurement, is the first to compare body fat distribution in prepubertal African-Americans, Asians, and Caucasians. Although the manifestation of sexual dimorphism was different in Asian children, the results confirm that sex-specific patterns of greater relative extremity or gynoid fat deposition in girls start well before the appearance of the physical signs of puberty. Body fat distribution in Asian children differed from Caucasians and African-Americans, but the findings varied by sex. These findings demonstrate that phenotyping of body composition traits in children requires sex and race specificity. Such investigation is an essential prerequisite for accurate assessment of associated metabolic implication and health risks.

Sex difference in fat distribution

Sexual dimorphism of total body composition has been described in prepubertal children, with greater fat free mass and less fat mass in boys, compared with girls, after controlling for ethnicity, age, height, and weight (18, 33, 34, 35, 36, 37). Sexual dimorphism of body fat distribution had previously been reported to emerge during puberty (13, 14, 15, 17), implying that factors regulating sex-specific total body composition are present in prepubertal children but that those determining regional body composition appear during puberty. Mast et al. (18) reported sex differences in whole-body fat distribution in prepubertal children, using waist to hip ratio. Besides numerous problems associated with the use of ratios from a statistical analysis perspective (30), waist to hip ratio has been challenged as a valid assessment of fat distribution in children (17) because it reflects bone-related hip circumference as much as fat. In our study of anthropometric and DXA measures of fat in prepubertal children, using analysis of covariance rather than ratios, sex differences in fat distribution were evident. This investigation of sex differences in prepubertal children is consistent with the suggestion of the National Academy of Science’s Institute of Medicine that differences between males and females should be evaluated from womb to tomb (38). Additional studies are needed to understand the metabolic and health risk implications of the observed differences.

Gonadal steroids are the major mediators of sexual dimorphism of body composition in adults, including body fat patterning (39, 40), a role that is further substantiated by the identification of gonadal steroid receptors in adipose tissue (41, 42). The demonstration by Klein et al. (43), that prepubertal girls have greater levels of circulating E2 than prepubertal boys, suggests a role for gonadal steroids in the subtle sex differences in fat patterning observed in this study. Recent reports have shown that gonadotropins and gonadal steroids gradually increase from 5 yr of age in prepubertal children, implying that their effects may be more evident in older than younger prepubertal children (44, 45, 46). Other hormones with putative roles in body fat distribution include leptin and GH, which have distinct but interrelated diurnal patterns, but are also influenced by gonadal steroids (47).

The differences in fat distribution observed in this cross-sectional study of children with an age span of 5–12 yr did not change with age when other covariates were included in the analysis. This leads us to propose that fat distribution may not be mediated by gonadal steroids in prepubertal children but rather by other factors, including possible nonhormonal sex-specific mechanisms. Because of possible collinearity of age, height, weight, and fat variables, this analysis cannot definitively demonstrate if age affects fat distribution in prepubertal children. A potential limitation of this study is the fact that hormone levels were available in only a small subset of patients and therefore pubertal status could not be confirmed biochemically. Inclusion of hormonal and bone age information in future investigations in smaller numbers of prepubertal children across this age range would allow exploration of possible mechanisms for the observed sex differences in fat distribution.

Race differences in fat distribution

In studies of adult females, Asians had greater trunk sc fat than Caucasians (23), whereas Caucasians had greater limb sc fat (24). Malina et al. (19) reported that adolescent Asian girls had more trunk sc fat than Caucasian girls. The current study shows that adjusted mean skinfold- and DXA-derived extremity fat were lower in prepubertal Asians than Caucasian girls. Because body size (weight and height) was controlled when sex and race interactions in fat distribution were explored, we can infer that Asian girls have greater relative truncal or central fat mass.

In the current study, Asian boys had less adjusted mean DXA-derived extremity fat than Caucasians, whereas the skinfold method revealed no race differences. Others (24) have reported that Asian adults have more upper-body sc fat than Caucasians and that the magnitude of the race difference is greater in females than in males. Therefore, we propose that the greater Asian/Caucasian differences in fat distribution between women, compared with that between men, are already evident in prepubertal children.

The recognition of race differences in fat distribution is of clinical importance, especially because the metabolic implications of particular body composition parameters may vary among races. For example, the strength of association between specific fat depots and insulin sensitivity or high density lipoprotein-cholesterol was found to be different in black and white children (22, 48). The identification of race differences in fat distribution needs to be followed by metabolic studies to clarify associations with health risk.

The observed race and sex differences in fat distribution may reflect differences in physical activity, nutrition, or socioeconomic status of the family, information that was not available on our subjects (49). For example, it has been reported that physical activity has significant influence on total body composition (percentage body fat) in early childhood (50). It has been also reported that the increase of visceral adipose tissue is significantly less in children who exercise, compared with children who do not exercise (51). Data on activity as well as on nutrition and socioeconomic status would be important additions to future investigations of the sex and race differences in fat distribution observed in this study.

Sample selection bias may be a limitation of the current study because the subjects were recruited voluntarily through local newspaper advertisements and announcements at schools and after-school activity centers. However, because the mean weight and height percentiles for age of the study participants were at the 50th to 75th percentile of the Centers for Disease Control and Prevention growth charts (32), this information may be transferable to other healthy prepubertal pediatric populations.

In conclusion, our study demonstrates that sex differences in body fat distribution are present before the onset of puberty in African-American, Asian, and Caucasian children but that the specific characteristics differ with race. Race differences are also present, but these vary with sex. These findings emphasize the importance of sex- and race-specific interpretation of body composition results to define phenotypes and the need for further studies to explore their particular associations with health risks.

Acknowledgments

Footnotes

This work was supported in part by NIH Grants RO1-DK-37352 and R29-AG-14715 and an educational grant from Bristol-Myers Squibb Mead Johnson.

Abbreviations: CV, Coefficient of variation; DXA, dual energy x-ray absorptiometry; LS-mean, least squares-mean.

Received August 8, 2001.

Accepted January 16, 2002.

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