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1 From the Department of Human Sciences, Loughborough University (NC, PLG, MMW, CB, NCD), Loughborough, United Kingdom, and the Mineral Metabolism Research Unit, University of the Witwatersrand (JMP, SAN), Johannesburg, South Africa.
2 The Birth to Twenty birth cohort study receives financial and logistic support from the Urbanisation and Health Programme of the Medical Research Council of South Africa; the Anglo-American Chairman's Fund; Child, Youth, and Family Development of the Human Sciences Research Council of South Africa; and the University of the Witwatersrand. The Bone Health study is financially supported by the Wellcome Trust (United Kingdom). 3 Reprints not available. Address correspondence to N Cameron, Department of Human Sciences, Loughborough University, Loughborough, LE11 3TU, United Kingdom. E-mail: n.cameron{at}lboro.ac.uk.
ABSTRACT
Background: The regression equations of Slaughter and Dezenberg, which are based on mixed ethnic samples, are currently recommended for predicting body fat from skinfold-thickness measures in prepubescent children of African ancestry. These equations contain methodologic problems that could make them inappropriate for African children.
Objective: The objective was to apply the Slaughter and Dezenberg equations to predict body fat in African prepubertal children and to compare the results with body fat measured by dual-energy X-ray absorptiometry (DXA). If significantly different outcomes were observed, then the objective was to develop new prediction equations and validate them on African children.
Design: The Slaughter and Dezenberg equations were applied to a cross-sectional sample of 214 prepubescent (Tanner stage 1) African children (118 boys). Body fat was determined by DXA, and subcutaneous fat at triceps, biceps, subscapular, suprailiac, thigh, and calf sites was measured with use of Holtain calipers. A randomly selected sample of 134 participants (78 boys) was used to generate new prediction equations that were validated on the remaining 80 participants (40 boys).
Results: The Slaughter and Dezenberg equations significantly underestimated (P < 0.001) body fat compared with DXA in both boys and girls. The best combination of skinfold thicknesses to predict body fat in African prepubertal boys, controlling for chronologic age, was triceps, biceps, subscapular, suprailiac, and thigh (SEE = 2.87), and for girls it was biceps, subscapular, suprailiac, thigh, and calf (SEE = 3.51).
Conclusion: The Slaughter and Dezenberg equations are unsuitable for predicting body fat in 9-y-old African prepubertal children. New equations that are based on skinfold-thickness combinations from African children provide more accurate estimates.
Key Words: Body fat • children • prepubertal children • African children • skinfold thickness • DXA • birth cohort
INTRODUCTION
The prediction of total body fat from subcutaneous fat assessed by anthropometry has become an accepted indirect method of determining body composition. Of the prediction equations that exist for children only those developed by Slaughter et al (1) and Dezenberg et al (2) were recommended for children of African (specifically African American) ancestry. Both sources used mixed Caucasoid and African American samples to derive prediction equations for prepubertal children. Although the former (1) developed equations specifically for black children, the latter (2) produced equations for ethnically mixed samples.
There are, however, several problems with the Slaughter et al (1) and, to a lesser extent the Dezenberg et al (2), methodologies. First, the Tanner staging technique for pubertal development was misapplied. Tanner (3) assigned a 5-point scale to pubertal development as seen in the development of breasts and pubic hair in girls and genitalia and pubic hair in boys. A further stage 6 could be applied to pubic hair when "... the pubic hair spreads further ... in the mid-twenties or later..." (3, p 33). However, Slaughter et al (4) and Dezenberg et al (2) assigned children with Tanner stage 2 into the "prepubescent" groups when, by definition, they were pubertal. Similarly, children in Tanner stage 4 were assigned by Slaughter et al (1) to a "postpubescent" group when puberty is not finished until Tanner stage 5. Thus, according to Slaughter and colleagues puberty only occurred in Tanner stage 3.
Second, it is not possible to have a single rating in the Tanner scale because the staging technique involves assessment of 2 aspects of pubertal development: pubic hair in both sexes, breast development in girls, and genitalia development in boys. No indication is provided by Slaughter et al (1, 4) or Dezenberg et al (2) of exactly how the Tanner scale was applied to result in a single rating figure, although a group described as "adult" by Slaughter et al (1), because they were in "Tanner stage 6," implies that pubic hair development was the criterion measure of puberty. In addition, Dezenberg et al (2) report that not all of their participants were actually assigned a Tanner stage and were simply assumed to be prepubertal. Although such assumptions could be valid for the younger end of the sample, they are certainly not valid for the older end, a fact acknowledged by Dezenberg et al (2) by describing this lack of Tanner staging as a limitation to their study.
Third, although Slaughter et al (1, 4) provided detailed descriptions of sample sizes, they did not provide the sample size of the black participants. Sample sizes of mixed ethnic groups were, in any case, small (50 prepubescent males and 16 females) and apparently not determined by power analysis. Dezenberg et al (2) also do not appear to use power analysis, although their African American samples are statistically more reasonable at 31 boys and 38 girls.
To test the applicability of the Slaughter and Dezenberg equations to African children, we applied them to prepubertal black participants, ie, children in Tanner stage 1 for breasts and genitalia and for pubic hair, from a birth cohort study set in South Africa. This paper reports on that application and the subsequent use of the anthropometric data to develop prediction equations for total body fat that are applicable to African children.
SUBJECTS AND METHODS
Subjects
The Birth to Twenty (BT20) study is a longitudinal study that tracked a cohort of 3274 children of all ethnic groups born between April and June 1990 living in Soweto and Johannesburg, South Africa, and was described in detail elsewhere (5, 6). A subsample of children from this study was used to undertake a separate bone health study from the age of 9 y (n = 369). A sample of prepubertal African children from the bone health study was used in the current analysis (n = 225). Nine children were excluded from the analysis because of missing anthropometric data, and a further 2 were excluded because sum of skinfold data for the triceps and subscapular regions was >35 mm, hence making the Slaughter equation used inappropriate for these individuals. Therefore, data from 214 African children (boys = 118; girls = 96) aged 9.51 ± 0.28 y were available for this analysis. All children were prepubescent, ie, in Tanner stage 1, for both breast and genitalia and for pubic hair.
Measurements
Anthropometric measurements were taken for all of the children with use of standard techniques (7). These measurements include height, weight, and skinfold-thickness measurements (with use of a Holtain Tanner/Whitehouse skinfold caliper; Holtain Ltd, Crymych, Wales) at the triceps, biceps, subscapular, suprailiac, midthigh, and medial calf sites. Each skinfold-thickness measurement was taken 3 times and a mean was calculated. A trained anthropometrist made all measurements, and the intraobserver variation for the skinfold measurements ranged between 2.0% and 2.7%. Pubertal development was assessed by trained same-sexed observers with use of the Tanner scaling technique on breasts and genitalia and pubic hair. A fan-beam densitometer (model QDR 4500A; Hologic Inc, Bedford, MA) was used to obtain dual-energy X-ray absorptiometry (DXA) readings of bone and body-composition components in the entire skeleton. Body composition [fat mass (kg), lean tissue mass (kg), and bone mineral content (g)] was assessed by using software version 8.21 (Hologic Inc) under standardized patient positioning and scan analysis. A spine phantom was scanned daily to determine the intrinsic CV of the machine. During the course of the study CVs for bone mineral content, bone area, and bone mineral density were 0.48%, 0.39%, and 0.35%, respectively. A trained technician for DXA performed all scans, and intraobserver variation for our study was found to be below 1% for all skeletal sites.
In recent publications [Tylavsky et al (8, 9)] the effectiveness of DXA as the criterion measure of body composition in adults was questioned. In a sample of overweight and obese adults Tylavsky et al (8) found small absolute differences in the loss of whole body lean soft-tissue mass and fat mass between the fan-beam and pencil-beam DXA system. Both units showed the same relation between changes in whole body lean soft-tissue mass and changes in total body water. In a sample of 58 adults aged 70–79 y Tylavsky et al (9) found systematically higher estimates of fat-free mass and lower estimates of fat mass from DXA as opposed to a 4-compartment model of body composition. However, those studies were on samples of adults who were either overweight or obese (8) or aged (9). In children and adolescents Gately et al (10) and Roemmich et al (11) showed that estimates of percentage body fat from DXA are significantly comparable to the 4-compartment model.
Ethics
All procedures were approved by the Committees for Research on Human Subjects of the Faculty of Health Sciences of the University of the Witwatersrand, South Africa, and Loughborough University, United Kingdom.
Analysis
Slaughter equations
An estimate of percentage body fat was calculated with the use of sex-specific Slaughter equations (1) for sum of skinfolds for triceps + subscapular, and triceps + calf, developed for prepubertal children with a triceps + subscapular skinfold <35 mm. The equations for boys are the following: percentage fat = 1.21(triceps + subscapular) – 0.008(triceps + subscapular)2 – 3.2 and percentage fat = 0.735(triceps + calf) + 1.0. The equations for girls are the following: percentage fat = 1.33(triceps + subscapular) – 0.013(triceps + subscapular)2 – 2.5 and percentage fat = 0.610(triceps + calf) +5.1.
The percentage fat values obtained from the Slaughter equations were regressed against percentage body fat from DXA in the South African sample with use of linear regression analysis with sex included as a covariate. The resulting SEE and R2 were then compared with those given by Slaughter (1) on the basis of the US sample.
Dezenberg equations
Fat mass was determined with use of the Dezenberg et al (2) equations for their first 4 stepwise variable combinations (weight, weight + triceps skinfold, weight + triceps + sex, weight + triceps + sex + ethnicity). Abdominal skinfolds (step 5) were not assessed in the BT20 study, and Dezenberg et al (2) stipulate that this skinfold is not essential. In addition to comparisons of descriptive statistics, the fat mass values obtained from the Dezenberg equations were regressed against percentage body fat found by DXA with use of linear regression analysis.
New prediction equations
The sum of skinfold combinations (from 2 to 6 skinfolds) from the BT20 data was also used in regression to determine whether they were more accurate than the Slaughter and Dezenberg equations in predicting body fat from DXA. Each regression model controlled for child's age and included a squared term for the sum of skinfolds to account for the nonlinear association between percentage body fat and the sum of skinfolds. In addition, an interaction term between age and the sum of skinfolds was also tested for significance.
New prediction equations were generated with use of subsamples of 78 boys and 56 girls who were randomly selected from the main sample. These prediction equations were subsequently validated with use of the remaining 40 boys and 40 girls in the BT20 sample. (A power analysis, with Z = 1.96 and Zß = 0.84, demonstrated that >31 subjects were needed to detect a difference of 5% body fat between the prediction equations and the DXA values in a validation sample.) The best predictors of percentage body fat on the basis of the highest R2 value and the lowest SEE for each combination of 2–6 skinfold measures were identified. All analyses were undertaken with use of SPSS statistical software, version 11 (SPSS Inc, Chicago).
Bland-Altman plots were used to determine bias and to investigate limits of agreement between the prediction equations and DXA in the validation groups for boys and girls. Bias was measured by considering predicted percentage body fat (from our own models or from Slaughter's models) minus percentage body fat from DXA on the y-axis and the mean of predicted body fat and DXA percentage body fat on the x-axis. Limits of agreement were assessed with use of 95% CIs defined by the mean differences ± 2 SDs. In addition, for the best combination for each number of skinfolds, DXA percentage body fat was regressed against predicted fat from the validation study, separately for boys and girls. Predicted values were deemed to be valid if Student t test revealed no significant deviation from the line of identity (intercept = 0, slope = 1).
RESULTS
Fat mass and percentage body fat determined by DXA were significantly greater (independent t test; P < 0.01, P < 0.001, respectively) in girls compared with boys, whereas SDs and interquartile ranges were similar (Table 1). Mean values for age, height, and weight were not different for boys and girls. Percentage body fat calculated by the 2 Slaughter equations (triceps + calf and triceps + subscapular) are shown in Table 2 and mean fat mass from the Dezenberg equations in Table 3.
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TABLE 1. Means and medians for age, height, weight, percentage body fat, and total body fat in boys and girls1
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TABLE 2. Predicted mean and median percentage body fat by using Slaughter's equation on the sample of African prepubertal children
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TABLE 3. Mean and SD of fat mass from dual-energy X-ray absorptiometry (DXA) and Dezenberg regression equations
Slaughter's triceps and calf skinfold combinations were significantly greater (paired t test; P < 0.001) than the values calculated from triceps and subscapular combinations (Table 2). The values for percentage body fat predicted from the Slaughter equations were significantly less (paired t test; P < 0.001) than those from DXA illustrated in Table 1 with differences between the medians varying between 6.1% and 14.1%.
Dezenberg predictions of fat mass were significantly different from DXA estimates (paired t test; P < 0.001) for regression steps 2 through 4 when the sexes were combined. When sexes were tested separately, predictions were significantly different for all steps in both sexes (paired t test; P < 0.001).
To compare how well Slaughter's 2-skinfold combinations predicted body fat in the US and African samples, the R2 and SEE values from predicting fat as measured by density, water, and bone and reported by Slaughter et al [(1) Table 3, p 715] were compared with the values that resulted from predicting percentage fat determined by DXA in our African sample. In short, we were determining whether the same equations when applied to the best estimate we have of fat in our sample were actually good predictor combinations (Table 4). The skinfold combinations produced higher R2 values and lower SEE values with the US sample than those produced from the BT20 sample. Similarly, Dezenberg's equation 4 produced an R2 = 59% and an SEE = 1.87 on the African sample in comparison to an R2 of 92% on the African American data. Thus, Slaughter's and Dezenberg's predictions apparently related better to body fat when applied to the African American sample than to the African sample.
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TABLE 4. Comparison of prediction quality of percentage body fat using Slaughter's body density, water, and bone mineral calculation on the American sample and dual-energy X-ray absorptiometry (DXA) values from the Birth to Twenty sample1
The new prediction equations and their associated R2 and SEE values separately for boys (n = 78) and girls (n = 56) are shown in Table 5 for each numerical combination of skinfolds (2, 3, ... 6) that produced the best prediction of body fat on the basis of the highest R2 and lowest SEE values. Note that in general the R2 values are not different or are slightly lower than either Slaughter's or Dezenberg's results, but our SEEs are lower, indicating a better estimation. The best-performing combinations of 2 skinfolds were triceps + suprailiac for boys and thigh + suprailiac for girls. These combinations produced lower SEE values (3.2 and 3.7) than those that used the Slaughter combination of triceps + calf (5.2) or triceps + subscapular (4.9) to predict DXA percentage body fat on these African children (Table 4). Indeed, they also produced similar or lower SEE values than the Slaughter combination did in predicting body fat in African American children (Table 4).
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TABLE 5. Prediction equations for percentage body fat from dual-energy X-ray absorptiometry (DXA) for various skinfold-thickness combinations by using the Birth to Twenty sample1
Bland-Altman plots were applied to assess the accuracy of the new prediction equations and the equations of Slaughter for the validation samples of boys and girls (plots not shown here). Plots that used our own equations were restricted to the best-performing equations (defined by the highest R2) for boys (5 skinfolds; triceps, biceps, subscapular, suprailiac, and thigh) and girls (5 skinfolds; biceps, subscapular, suprailiac, thigh, and calf). The limits of agreement (mean difference ± 2 SD) for girls were –7.21% to 8.35%, with a mean difference close to zero (0.57%). For boys the mean difference ± 2 SD was –8.17% to 10.10%, with a mean difference that was, again, close to zero (0.97%). The Slaughter equations for triceps and calf for both boys and girls show mean differences that indicate a bias toward underestimation for the Slaughter equations in comparison to DXA (–6.41% for girls and –5.70% for boys). The limits of the difference for the Slaughter triceps + calf equations ± 2 SD were –17.09% to 4.27% and –17.39% to 6.00% for girls and boys, respectively. The Slaughter equations for triceps and subscapular show mean differences that indicate an even stronger bias toward underestimation for both boys and girls in comparison to DXA than the triceps + calf equations (–11.4% for girls and –9.14% for boys). The limits of the difference for the Slaughter triceps and subscapular equations ± 2 SD were –22.27% to –0.56% and –18.71% to 0.42% for girls and boys, respectively. Pitman test for difference in variance also showed P < 0.01 for comparisons between DXA and the Slaughter equations, indicating significant differences in variance with average percentage body fat. In contrast P > 0.01 was observed from Pitman test for difference in variance for comparisons between our own equations and DXA, indicating no significant difference in variance with average percentage body fat. Regression demonstrated that, for the best combination of each number of skinfolds, the intercept and the slope of the validation sample were not significantly different from the line of identity.
The average percentage of body fat was slightly overpredicted in both boys and girls by <1.0%. There were no significant differences between the means of predicted body fat for any of the combinations of skinfolds and the mean DXA percentage body fat for both sexes. Clearly, in any prediction situation there are going to be individuals who do not predict well. In a fat prediction situation these individuals will typically be the children who are at the extremes of body fat values or who could have subcutaneous fat distributions and patterning that differ from those of the average child. Statistically, they are identified as those children falling outside the ±1.96 SEE values of the prediction equations. In this study 8 boys and 5 girls fell into this category. Six of the 8 boys had DXA fat values greater than (n = 3) or less than (n = 3) the mean DXA values ±2 SD values for boys. The other 2 boys predicted well for combinations of skinfolds <5 and were only identified at the 5 and 6 skinfold combination levels. All 5 girls were greater (n = 2) or less (n = 3) than the DXA mean ± 2 SD values for girls. Of the 13 poor predictors, 8 predicted poorly for all combinations of skinfolds, and all were outside the sex-specific DXA ± 2 SD range. Hence, they were either very fat or thin in comparison to their peers.
DISCUSSION
The prediction of body fat in prepubertal children of black African ancestry (ie, either African Americans or actual African children) has previously only been possible through the use of equations of Slaughter et al (1) to predict percentage fat on the basis of combinations of triceps, calf, and subscapular skinfolds or the equations of Dezenberg et al (2) to predict fat mass. For the first time we were able to test the accuracy of these predictions against DXA-derived values for percentage body fat in African prepubertal children. There is conflicting evidence that DXA can both overestimate and underestimate body fat, depending on the age and sex of the children being assessed. For example, Goran et al (12) found underestimation by DXA in relation to skinfolds in white children aged 5–8 y, whereas Gutin et al (13) recorded a systematic tendency for DXA values to be higher in relation to skinfolds in 9–11-y-old children. In our study it is clear that the Slaughter equations underestimate percentage body fat by 30–50% of the DXA estimate in such children, and Dezenberg equations significantly underestimated fat mass by 15% of the mean values. It is important to try to understand why this is the case.
The current analysis is based on a sample of black African children, whereas Slaughter et al (1, 4) and Dezenberg et al (2) used mixed samples of children of European and African American ancestry and controlled for "race" or ethnicity in their analyses. In addition, the age range of the current sample is narrow (9.1–9.9 y) compared with Slaughter et al's (1, 4) sample (7–11 y) and Dezenberg et al's (2) sample (4–10 y) and strictly prepubertal according to Tanner scaling. Both Slaughter et al (1) and Dezenberg et al (2) chose to use a more liberal interpretation of prepubertal by including children who were already displaying pubertal changes and were rated 2 on the Tanner scales. Finally, the techniques to determine body fat were different between this study and Slaughter's study. DXA was used in Dezenberg's study (2), and the current analysis compared with combinations of body density (hydrodensitometry), body water (deuterium oxide dilution), and bone mineral (photon absorptiometry) in the Slaughter et al (1) study.
The narrow age range and strictly prepubertal nature of the current sample provides a more homogeneous sample from which to investigate body composition. The mixed-pubertal nature of Slaughter's sample is likely to include a large proportion (close to 50%) of children in early pubertal development with consequently greater body fat than strictly prepubertal children. This effect could be balanced by the higher proportion of younger children, but there is no way of knowing how effective this balance was. The use of a multicompartmental model by Slaughter goes some way toward reducing the effect of differing pubertal status by accounting for the chemical changes in the fat-free body known to occur during puberty. In Dezenberg's study it is not possible to determine how many children were actually pubertal, because pubertal assessments were not made in all cases. Clearly, however, Slaughter's and Dezenberg's equations are aimed at samples with a greater range of age and prepubertal development and, in the case of the latter equations, a greater range of ethnicity. However, the African children within this study, although being within a narrow age range and strictly prepubertal, were all within the chronologic and morphologic range of the source samples and, thus, ought not to have produced significantly different results.
There are some interesting implications of the Slaughter and Dezenberg equations that underestimate body fat in African children and in the different combinations of skinfolds that were the best predictor variables. First, it could be that more fat is situated subcutaneously in African American children than in African children. In other words, the same skinfold thickness or combination of predictor variables in African American and African children will reflect less total body fat in African Americans. Second, it would appear that the patterning of fat in African children could be different to that of the African American sample in that particular combinations of skinfolds did not present as best predictor combinations in both samples. Total body fat is apparently better represented by a combination of suprailiac + triceps skinfolds in African boys and subscapular + calf in African girls, compared with triceps + calf or triceps + subscapular in the African American sample.
The current African sample is shorter and lighter than the American sample but appeared to have similar or greater body fat, depending on the method of determination in the American samples. The American boys in Slaughter's study have means of percentage body fat ranging from 19.0% to 23.5% and girls from 23.2% to 27.8% compared with the median African values of 21.8% and 25.8% for boys and girls, respectively. However, the African children tend to deposit less fat in subcutaneous stores, thus justifying the use of ethnic-specific regression equations when calculating body fat. Clearly, there is a need to widen the age range of this prepubertal sample to provide greater applicability, but the current analysis provides a useful check point on body fat at the beginning of adolescence that makes its dissemination desirable at this time.
ACKNOWLEDGMENTS
NC, JMP, and SAN were involved in the initiation of the study, financial support, the logistical organization, and collection of data. NC, PLG, and MMW were responsible for strategies of data analysis. MMW, CB, and NCB were responsible for data analysis and initial drafts of the paper. NC was responsible for the final manuscript and preparation for publication. All authors reviewed and commented on drafts of the paper. None of the authors has any financial or personal interest in any company or organization sponsoring the research, including advisory board affiliations.
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