Published online July 2, 2007
PEDIATRICS Vol. 120 No. 1 July 2007, pp. e94-e101 (doi:10.1542/peds.2006-2114)
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ARTICLE

Patterns and Interrelationships of Body-Fat Measures Among Rural Chinese Children Aged 6 to 18 Years

Hongjian Wang, MDa,b, Rachel E. Story, MD, MPHc, Scott A. Venners, PhDd, Binyan Wang, MD, PhDa, Jianhua Yang, MDe, Zhiping Li, MDe, Liuliu Wang, MDe, Xue Liu, MDe, Genfu Tang, MDe, Houxun Xing, MD, MSe, Xiping Xu, MD, PhDd and Xiaobin Wang, MD, ScDa

a Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Children's Memorial Hospital and Children's Memorial Research Center, Chicago, Illinois
c Division of Allergy, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Children's Memorial Hospital, Chicago, Illinois
e Institute for Biomedicine, Anhui Medical University, Hefei, China
d Division of Epidemiology and Biostatistics, University of Illinois School of Public Health, Chicago, Illinois
b Department of Cardiology, Cardiovascular Institute and FuWai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVES. Our goal was to compare BMI and waist circumference with dual-energy radiograph absorptiometry–based measures of adiposity and to describe the pattern and interrelations of these surrogate and direct adiposity measures in prepubertal and pubertal rural Chinese children.

METHODS. This was a cross-sectional study of 2493 children aged 6 to 18 years from a population-based cohort of twin pairs. Dual-energy radiograph absorptiometry–based measurements included total body fat, percentage of body fat, trunk fat, and percentage of trunk fat. Age- and gender-specific patterns and interrelationships among BMI, waist circumference, and dual-energy radiograph absorptiometry–based measurements were described by using smoothing plots and age- and gender-specific correlation analyses.

RESULTS. In girls, BMI, waist circumference, total body fat, percentage of body fat, trunk fat, and percentage of trunk fat all increased linearly with age. In boys, BMI and waist circumference increased linearly with age, but total body fat, percentage of body fat, and trunk fat did not increase significantly with age. In both genders, percentage of trunk fat reached a nadir around 12 years of age and then increased with age. Before puberty (6–11 years), BMI and waist circumference were correlated well with total body fat, percentage of body fat, and trunk fat in both genders. During puberty (12–18 years), the correlations between BMI and each of the dual-energy radiograph absorptiometry–based measurements were higher in girls than in boys. Similar trends were found in the correlations between waist circumference and each of the dual-energy radiograph absorptiometry–based measurements.

CONCLUSIONS. In this relatively lean rural Chinese population, BMI and waist circumference were highly correlated with each other and were good surrogates of total body fat, trunk fat, and percentage of body fat in prepubertal children of both genders and in pubertal girls. However, both BMI and waist circumference overestimated total and trunk fat, especially percentage of body fat in pubertal boys.

Key Words: BMI • waist circumference • dual energy radiograph absorptiometry • obesity • puberty

Abbreviations: WC—waist circumference • DEXA—dual-energy radiograph absorptiometry • TBF—total body fat • %BF—percentage of body fat • TF—trunk fat • %TF—percentage of trunk fat

Childhood and adolescent obesity is increasing worldwide. From 1992 to 2002, the prevalence of overweight and obesity in Chinese people aged 0 to 6 and 7 to 17 years increased by 31.7% and 17.9%, respectively.1,2 Therefore, obesity and its associated cardiovascular disease risk factors are emerging as important public health issues for children and adolescents.3 Exposure to obesity early in life may induce arterial changes contributing to the development of atherosclerosis in adulthood.4 Although there is a lower prevalence of obesity in rural areas of China, the rate of increase in obesity in these areas is outpacing that in urban areas.1,2 Rural residents constitute a large segment of the world's total population, particularly in developing countries. In China, 85% of the population lives in rural, agricultural regions.5 Because of these trends, the prevalence of overweight and obesity in China will likely increase rapidly, as will the illnesses associated with obesity. The public health costs associated with these changes will be immense.

This study simultaneously evaluated surrogate adiposity measurements (BMI, waist circumference [WC]) and direct adiposity measures derived from dual-energy radiograph absorptiometry (DEXA). BMI, based on height and weight measurements, is routinely obtained in clinical settings and used to assess overweight and obesity in children and adults.6 WC is also easily obtained in medical practice as a sign of central obesity and used as a characteristic of the metabolic syndrome. DEXA is one of the best available measures of body fatness.7–10 In this study the body fat measures from DEXA include total body fat (TBF), percentage of body fat (%BF), trunk fat (TF), and percentage of trunk fat (%TF).

This study has 2 aims. First, it compares standard field measures of BMI and WC to laboratory measures of TBF, %BF, TF, and %TF in prepubertal and pubertal rural Chinese children. BMI and WC are often used to identify individuals and populations with increased adiposity to target for public health interventions. Our study will help determine whether these field measures can serve as good surrogates for laboratory measures of adiposity. Second, the study describes the pattern and interrelations of these surrogate and direct adiposity measures in a large sample of rural Chinese children. In particular, this study assesses the differential patterns and interrelationships between prepubertal and pubertal children and between boys and girls, given the known differences in growth, development, and body composition by gender during the pubertal period.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Study Population and Recruitment
This study uses a subset of subjects from a large cohort of twin pairs in Anqing, China, recruited from 1998 to 2000, with the goal to study environmental and genetic determinants of complex human diseases, including obesity and metabolic syndrome. Spanning 80 km along the north bank of the Yangtze River, the area of Anqing has 3 urban areas and 8 rural counties covering 15000 km.2 Medical care in each county of Anqing is administered through a 3-tier (county, township, and village) service network. Twins were identified through a multistage process. First, investigators from Anhui Medical University and the Anqing Hospitals/Research Institutes held a 3-day workshop in each township to train local doctors to participate in subject recruitment. The first day was used to explain the purpose, scope, and procedures of the study. The definition of a twin was introduced, and several examples were presented. Local doctors were requested to go back to their own villages to prepare a list of all of the twins in their practice area. Epidemiologists from Anhui Medical University checked all of the twin lists with the township/village doctors. Twins were chosen on the basis of the following criteria: (1) age of 6 to 60 years, (2) both twins were available for the survey, and (3) both twins (or parents/guardians of children) agreed and consented to participate in the survey. Eligible twins were invited to a central office to complete a questionnaire interview, blood drawing, and physical examination, including anthropometric measurements and DEXA scan. All of the study protocols were approved by the institutional review boards of Children's Memorial Hospital and Anhui Medical University.

Anthropometric Measurements
A detailed description of field-data collection has been described elsewhere.11,12 In brief, height and weight were measured using standard protocols, without shoes or outerwear. Height was measured to the nearest 0.1 cm on a portable stadiometer. Weight was measured to the nearest 0.1 kg with the subjects standing motionless on a scale, and BMI was calculated as weight (kilograms)/height squared (meters squared). A WC measurement was taken at the level of the umbilicus to the nearest millimeter. Each anthropometric measure was taken 3 times and the mean used in all of the analyses.

DEXA
DEXA measures the exponential attenuation of photons emitted at 2 energy levels that are absorbed by various body tissues. This allows for accurate measurements of fat, fat-free, and bone substances.13 A standard whole-body DEXA scan includes total body and 3 regional fat measures: trunk (chest, abdomen, and pelvis), arms, and legs. DEXA measures of body fat have been validated against other estimates, including underwater weighing,9 skinfold measures, bioelectrical impedance analysis, and deuterium oxide dilution.10 A standard software calculation13 was used to calculate TBF measured with a Lunar DPXL instrument (Madison, WI) that was set up in Anqing. %BF is calculated as TBF divided by body weight. %TF is calculated as trunk fat divided by TBF and is a measure of central fat distribution relative to TBF.

Statistical Methods
Our analysis compares BMI and WC to DEXA-based measures of adiposity and describes the interrelations of body mass and fat patterning in prepubertal and pubertal children. Twins were treated as individuals from the general population in our analyses. All of the statistical analyses were conducted using the SAS statistical package (SAS Institute, Inc, Cary, NC).14 Study participants are grouped into 2 age groups: 6 to 11 years (approximating prepubertal) and 12 to 18 years (approximating pubertal). The age of menarche in girls in this population is 13.9 years of age. The onset of puberty is, in general, 2 years before menarche15,16; thus, 12 years of age was chosen as the cutoff in our population.

All of the analyses are gender- and age-group specific and were conducted in several steps. First, the distributions of BMI, WC, TBF, %BF, TF, and %TF in both genders were examined. The relationships between age and body-fat measures are described using smoothing plots to show the changes in average body-fat measures with increasing age and to compare differences between boys and girls. Then, gender and age group-specific relationships among BMI, WC, and body-fat measures from DEXA were plotted to describe the effect of puberty on the interrelationships of body-fat measures. All of the smoothing plots used locally weighted regression as a nonparametric method for smoothing with SAS procedure locally weighted regression.17,18 Furthermore, the interrelationships among body-fat measures were determined using Pearson correlation coefficients. Two methods were used to ensure that correlations between twin pairs did not affect the results. First, generalized estimating equations14 were performed to account for autocorrelations between the twin pairs using data from both twins. Second, the analysis was repeated including only 1 twin per family (the first-born twin). Because results were very similar (data not shown), this report presents results using data from all of the twins.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Epidemiologic Characteristics
The original twin cohort enrolled a total of 3412 children between 6 and 18 years of age. In this report, 919 children were excluded because of missing data for DEXA measures (n = 871), BMI and WC measures (n = 35), reported history of smoking (n = 9), and drinking alcohol (n = 4). Thus, the final analyses included 2493 children. The age and gender distribution and BMI are comparable between the 2493 children included and 919 children excluded from the analyses (data not shown). Table 1 displays gender and age group-specific means and SDs for all of the variables used in the analyses, including age, height, weight, BMI, WC, and DEXA measures of adiposity (TBF, %BF, TF, and %TF).


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  		TABLE 1 Adiposity Characteristics in Chinese Children 6 to 18 Years Old

 
Relationship Between Age and Body-Fat Measures
Figure 1 displays locally weighted regression smoothing plots that show the associations between body-fat measures and age, stratified by gender. BMI and WC increase linearly throughout the age range in both genders but accelerate during puberty. TBF increases in both genders throughout the age range but diverges during puberty when TBF increases more rapidly in girls. Of note, %BF increases in boys from 6 to 12 years of age but decreases during puberty; in girls, %BF increases slowly in prepuberty and accelerates during puberty, which shows remarkable divergence by gender during puberty. Trunk fat increases linearly in boys throughout the age range but accelerates sharply at puberty in girls. In both genders, the %TF has a J-shaped curve, decreasing during prepuberty (to age 10 in girls and to age 11 in boys) and increases sharply in both genders during puberty.


Figure 1
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  		FIGURE 1 The gender-specific relationship between body-fat measures and age. Smoothing plots of BMI, WC, and body-fat measures according to age and gender are shown. The y-axis represents BMI, WC, TBF, %BF, TF, and %TF, respectively, with the x-axis displaying age (6–18 years).

 
Relationship of BMI with WC, %BF, and %TF
Figure 2 depicts gender and age group-specific relationships of BMI with WC, %BF, and %TF. There were few subjects with low BMI (BMI <11 kg/m2 in ages 6–11 years and BMI <13 kg/m2 in ages 12–18 years) or high BMI (BMI >20 kg/m2 in ages 6–11 years and >23 kg/m2 in ages 12–18 years) in this population. Thus, in the analysis of children aged 6 to 11 years, subjects with BMI ≤11 kg/m2 were analyzed as having BMI of 11 kg/m2. Likewise, subjects with BMI ≥20 kg/m2 were analyzed as having BMI of 20 kg/m2. In the analysis of ages 12 to 18, subjects with BMI ≤13 kg/m2 were analyzed as having BMI of 13 kg/m2, and subjects with BMI ≥23 kg/m2 were analyzed as having BMI of 23 kg/m2.


Figure 2
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  		FIGURE 2 The gender-specific relationship between BMI and WC, %BF, and %TF in 2 age groups. Smoothing plots of WC and body fat from DEXA according to gender against BMI in 2 age groups are shown. The y-axis represents WC, %BF, and %TF, respectively; the x-axis displays BMI. Left, 6- to 11-year-olds; right, 12- to 18-year-olds.

 
There is a linear increase in WC with increasing BMI in both age groups and genders. In children aged 6 to 11 years, there is a linear increase in %BF with increasing BMI in both boys and girls. However, there are clear gender differences in the relationship of BMI with %BF in children aged 12 to 18 years. For girls aged 12 to 18 years, there is a linear increase in BMI and %BF. However, in boys there is no apparent increase in %BF with increased BMI until the BMI is ≥20 kg/m2.

%TF in girls aged 6 to 11 years is more or less constant until a BMI ≤16 kg/m2, at which point it increases sharply. In boys, %TF decreases with increasing BMI until a BMI of 16 kg/m2, at which point it increases. In both genders aged 12 to 18 years, there is a linear relationship between BMI (only for BMI >16 kg/m2 in boys) and %TF. Of interest, for both age groups, the %TF of boys is higher than that of girls if BMI is <16 kg/m2 but lower than that of girls if BMI is >16 kg/m2. The relationships between WC and %BF and %TF were similar to those of BMI in both age groups and genders (figures not shown).

Correlation Between Body-Fat Measures
Table 2 demonstrates that in children aged 6 to 11 years, BMI and WC are similarly correlated with the corresponding body fat as measured by DEXA in both genders. The correlation coefficients between BMI and body fat from DEXA (TBF, %BF, and TF) are 0.57, 0.43, and 0.55 in boys and 0.57, 0.40, and 0.54 in girls, respectively. %TF has no correlation with BMI in boys and has mild correlation with BMI in girls 6 to 11 years of age. There is a gender difference in correlation among body-fat measures in children aged 12 to 18 years (P < .05; data not shown). The correlation coefficients between BMI and each of TBF, %BF, TF, and %TF are 0.57, 0.19, 0.63, and 0.49 in boys and 0.88, 0.80, 0.88, and 0.69 in girls, respectively. A similar trend is found in the correlation between WC and these direct body-fat measures by DEXA.


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  		TABLE 2 The Pearson Correlation Coefficients Among BMI, WC, and Body Fat According to Age Groups and Genders

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
This report contributes new information on adiposity and body composition in children and adolescents in several ways. It is one of the first studies to describe gender-specific patterns and interrelationships of body-fat measures in a large rural Chinese population using DEXA-derived measures from childhood through adolescence. It examines the use of BMI and WC, the most commonly used surrogate measures of adiposity, to assess adiposity from prepuberty through puberty in this population. Finally, the results highlight gender and pubertal stage as important determinants in adiposity measurements and their interrelationships.

Our data showed important differences in measures of body fat between boys and girls with the onset of puberty. In girls, BMI, WC, TBF, %BF, and TF all increased linearly with age with a more pronounced increase observed at the onset of puberty (12 years of age). In boys, TBF and TF increased slightly with age. %BF also increased slightly with age during prepuberty, but at 12 years of age and onward, %BF began to decrease with age despite the fact that BMI continued to increase.

During prepuberty, boys had higher BMI, WC, and %TF than girls. After puberty the BMI and WC of boys are only slightly lower than those of girls. In contrast, DEXA measures of body fat in girls (with the exception of %TF) are higher than in boys throughout the entire age range and become more pronounced with the onset of puberty. In adolescence, boys have an increase in muscle mass and central adipose tissue because of testosterone secretion, whereas girls have increased body-fat mass, primarily peripheral adipose tissue, because of estradiol.19,20 The increased adiposity seen in girls that accelerates during puberty is consistent with these changes. These gender differences in fat patterning with puberty result in boys and girls with equivalent BMIs having very different body composition. Thus, it is not surprising that boys and girls in our population have very different levels of adiposity as measured by DEXA when their BMI and WC are very similar.

There was a similar level of central fat distribution in boys and girls from 6 to 18 years of age despite the fact that girls had higher TBF than boys during puberty. These changes are likely because of sexual dimorphism in body-fat distribution mediated by estradiol and testosterone. In boys, there is an accumulation of both subcutaneous and intraabdominal fat in the upper body in an apple-shaped distribution. In contrast, girls have a gluteal accumulation of subcutaneous fat in a pear-shaped distribution. Some studies show that theses changes start in adolescents, whereas others report sexual dimorphism in children as young as 5 years of age.21–23 The cause of prepubertal sexual dimorphism in fat patterning is not known. Garnett et al19 investigated the role of insulin-like growth factor 1, dehydroepiandrosterone sulfate, estradiol, testosterone, and leptin on DEXA-measured %BF and percentage of abdominal fat and found that the hormones examined explained <20% of gender differences in fat patterning. Hormonal regulators of adipose tissue need to be further studied to account for gender differences in body-fat patterning.21 Ethnic differences may also affect fat distribution during puberty.24–26 One study found progression of sexual dimorphism in fat patterning with increasing pubertal maturation in Asian children.24 A study on German children found that the developmental pattern of fat accumulation and distribution during adolescence is highly dynamic and gender specific.27 It is not surprising that studies have differing results, because age, gender, race, study methods, and the relative leanness of a population may play a role.

This study examined the interrelationships of body-fat measures, specifically whether BMI and WC can be used as surrogates of DEXA-based measurements of body fat. Our data demonstrate that, during puberty, there were gender differences in the relationship of BMI and WC to DEXA-based measures of body fat. Among girls, BMI and WC correlate well with DEXA measure of adiposity, and the correlations increase considerably from preadolescents to adolescence. The correlations likely improved because of the higher levels of adiposity in puberty. In contrast, BMI and WC did not accurately reflect adiposity in boys aged ≥12 years in this rural Chinese population. This observation could be explained by differential body composition between boys and girls seen during puberty such that, for a given BMI, boys are likely to have more lean muscle mass than girls, resulting in BMI overestimating adiposity in adolescent boys. However, in studies of American and Italian children and adolescents, BMI was highly correlated with %BF in both genders.28 This Chinese cohort is leaner than the others, and because the correlation between BMI and %BF is stronger in heavier children, the leanness of the population may account for some of the discrepancy. Study methods and genetic differences in the populations may also contribute to the different results.

Our data underscore the notion that, in children, the use of BMI as an indicator of adiposity has an important limitation because of individual variation in growth rates and maturity levels.29 Recent studies report that BMI may not accurately reflect adiposity in children, particularly among male adolescents and children of lower BMI.6,30 In this study, we found that, among boys ≥12 years of age, %BF and %TF remained relatively constant over a range of BMI until a higher BMI (>20 kg/m2 for %BF and >16 kg/m2 for %TF) was reached. A recent study in white males found similar results. It suggested that changes in BMI in males of lower BMI percentiles may occur without appreciable changes in adiposity.30 On the other hand, these observations support the use of high BMI percentile cutoff points (eg, 85th or 95th percentile) to identify children at risk for obesity. Furthermore, the distribution of fat seems to play a central role in the relation between obesity and blood pressure. Individuals with more visceral or android distribution of body fat are at higher risks for diabetes and heart disease.31 Therefore, additional studies are needed to understand the role of BMI as compared with direct measures of body fat in predicting cardiovascular risk in lean and overweight populations.

WC is a measure of central obesity that is easily obtained in medical practice. In addition, it is a characteristic of the metabolic syndrome.32 Lee et al33 reported that WC is significantly associated with total fat and insulin sensitivity and is an independent predictor of insulin resistance in black and white youths aged 8 to 17 years. Al-Sendi et al34 reported that WC is useful in identifying children (12–17 years of age) at risk of developing hypertension. In this study, there were gender differences in the correlations of WC with %BF and %TF in puberty such that WC did not accurately reflect body fat and fat distribution in pubertal boys. This may be because in a lean population of growing children, WC does not reflect changes in central deposition of body fat.

Finally, this is a relatively lean rural Chinese population. Using the growth chart from the Centers for Disease Control and Prevention,35 we plotted the Chinese children's median BMI for specific age and gender (data not shown). We found that, on average, the Chinese children had lower BMI. The average difference in BMI between US and Chinese children is 1.5 kg/m2 (boys) and 1.8 kg/m2 (girls) at 6 to 11 years of age and 2.2 kg/m2 (boys) and 2.0 kg/m2 (girls) at 12 to 18 years of age. Although we are not certain whether the same relationships between BMI and adiposity measures that we found in the Chinese children will hold in US children, especially among overweight and obese children, our study underscored the notion that BMI and WC may not be accurate surrogates for total and trunk fat, especially in adolescent boys. It is important to understand such a relationship in each population so that clinical and research assessment of adiposity and associated health risk could be accurately and efficiently conducted.


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
In this relatively lean rural Chinese population, BMI and WC do not accurately reflect body composition as measured by DEXA in boys ≥12 years of age. In pubertal boys, body fat (except %TF) from DEXA did not show a parallel increase with BMI until the higher end of BMI. In contrast, both BMI and WC correlated well with %BF measured by DEXA in boys 6 to 11 years and in girls 6 to 18 years of age. The results demonstrate that it is essential to consider pubertal stage and gender when using BMI and WC to describe adiposity. These findings are important to consider in both research and clinical settings to accurately identify individuals with increased adiposity who are at risk for cardiovascular diseases or other adiposity-related morbidities.


   ACKNOWLEDGMENTS
 
This study was supported in part by National Institutes of Health grant R01 HD049059 and by the Food Allergy Project.

We thank the team investigators who have provided valuable input into the study, including Drs Katherine Kaufer Christoffel, Wendy Brickman, and Donald Zimmerman.


   FOOTNOTES
 
Accepted Dec 12, 2006.

Address correspondence to Xiaobin Wang, MD, ScD, Mary Ann and J. Milburn Smith Child Health Research Program, Children's Memorial Research Center, 2300 Children's Plaza, Box 157, Chicago, IL 60614. E-mail: xbwang{at}childrensmemorial.org

The authors have indicated they have no financial relationships relevant to this article to disclose.


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 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

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PEDIATRICS (ISSN 1098-4275). ©2007 by the American Academy of Pediatrics




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