Numerous studies have shown that android or truncal obesity is associated with a risk for metabolic and cardiovascular disease, yet there is evidence that gynoid fat distribution may be protective. However, these studies have focused on adults and obese children. The purpose of our study was to determine if the android/gynoid fat ratio is positively correlated with insulin resistance, HOMA2-IR, and dislipidemia in a child sample of varying body sizes. In 7–13-year-old children with BMI percentiles ranging from 0.1 to 99.6, the android/gynoid ratio was closely associated with insulin resistance and combined LDL + VLDL-cholesterol. When separated by sex, it became clear that these relationships were stronger in boys than in girls. Subjects were stratified into BMI percentile based tertiles. For boys, the android/gynoid ratio was significantly related to insulin resistance regardless of BMI tertile with and LDL + VLDL in tertiles 1 and 3. For girls, only LDL + VLDL showed any significance with android/gynoid ratio and only in tertile 2. We conclude that the android/gynoid fat ratio is closely associated with insulin resistance and LDL + VLDL-, “bad,” cholesterol in normal weight boys and may provide a measurement of metabolic and cardiovascular disease risk in that population.
Childhood obesity is a common health problem in the United States and despite public focus addressing the problem, obesity rates among school-age children (6–19 years old) remain high at 19%. An additional 25% of children are overweight, increasing the concern and need to continue obesity prevention and treatment efforts nationwide [
Childhood and adult obesity can come in many different forms that are not inherently equal in terms of their health impact. The existing literature reflects that truncal adiposity, or the android body type, is a strong indicator of risk for disease [
Insulin plays a crucial role in metabolism, and insulin resistance may be the underlying linkage between obesity, type 2 diabetes, and cardiovascular disease [
Studies have shown important relationships between the android/gynoid ratio and metabolic [
All study protocols were reviewed and approved by the West Virginia University Institutional Review Board prior to any research activity. Signed parental consents and child assents were obtained from all participants before collecting any surveys or performing any examination of the subjects.
Children aged 7 to 13 years were either recruited from outpatient pediatric clinics or as a follow-up to their participation in an annual school screening program in a rural, Eastern United States setting. Study flyers were posted within the clinics and throughout the communities (e.g., grocery stores and schools) and were sent home with the screening program participants. The cross-sectional study design using the aforementioned recruitment strategy over the study period, 24 months, enrolled 73 children participants.
Families who contacted the research team with an interest to participate in the study scheduled a clinic visit in the Physician Office Center—Pediatric and Adolescent Group Practice (PAGP) in Morgantown, West Virginia. Basic contact information was collected so that a series of surveys for one parent or legal guardian and the child could be mailed prior to the scheduled visit. Families were instructed to return completed surveys on the day of their appointment. Children were also asked to fast overnight before the visit and to abstain from any medications as appropriate.
Upon arriving at the clinic visit, anthropometrics were obtained and recorded for the child without shoes. Because the child was fasting, up to 15 cc of serum was drawn from each participant. Once the child was able to eat a breakfast, which was provided, a urine sample was collected and a pulmonary function test and allergy testing were completed. Parents were asked to complete additional surveys related to their child’s health and medical history while the clinical assessments were being conducted. The clinic visit took an average of three hours to complete. Families were reimbursed for their travel and time.
Total body, android, and gynoid fats were measured using an iDXA X-ray bone densitometer (GE Healthcare) with software designed for a pediatric population. Android was measured with the lower boundary at the pelvis cut with the upper boundary above the pelvis cut by 20% of the distance between the pelvis and neck cuts. Gynoid upper boundary was below the pelvis cut line by 1.5 times the android space and gynoid space was equal to 2 times the android space [
Blood samples were collected in a Red/Black SST tube and a K2 EDTA tube using standard venipuncture practices. The SST tube sat at room temperature for 30 minutes followed by centrifugation at 1000 rcf for 10 minutes at room temperature. The samples were taken to LabCorp. for testing of insulin, glucose, total cholesterol, HDL-cholesterol, LDL-cholesterol, VLDL-cholesterol, and triglycerides.
HOMA2-IR was used to assess insulin resistance from fasting glucose and insulin levels, (
Means, standard errors, and
We assessed the associations using the adjusted coefficient of multiple determination which adjusts for the number of variables in the model and ameliorates problems with artificial inflation of the
Table
Characteristics, anthropometrics, and biochemistries of participants, stratified by sex and combined (mean ± SE).
Variable | Girls |
Boys |
Total |
---|---|---|---|
Anthropometrics and age | |||
Age (years) | 9.5 ± 0.3 | 9.6 ± 0.3 | 9.5 ± 0.2 |
BMI |
0.43 ± 0.19 | 0.47 ± 0.21 | 0.46 ± 0.14 |
BMI percentile | 63 ± 5 | 61 ± 5 | 62 ± 3 |
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BMI tertiles (percentiles) | |||
1 mean ± SE | 28 ± 4 | 24 ± 4 | 26 ± 3 |
(min–max) | (0–44) | (0–43) | (0–44) |
2 mean ± SE | 66 ± 3 | 66 ± 4 | 66 ± 2 |
(min–max) | (45–82) | (47–83) | (45–83) |
3 mean ± SE | 93 ± 1 | 95 ± 2 | 94 ± 1 |
(min–max) | (85–98) | (85–100) | (85–100) |
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DXA measurements | |||
Total body fat (%) | 31.9 ± 1.4 | 29.6 ± 1.6 | 30.5 ± 1.1 |
Android body fat (% of total) | 27.5 ± 2.2 | 24.9 ± 2.2 | 25.9 ± 1.7 |
Gynoid body fat (% of total) | 37.0 ± 1.4 | 32.7 ± 1.4 | 34.6 ± 1.0 |
Android/gynoid ratio | 0.71 ± 0.04 | 0.70 ± 0.04 | 0.70 ± 0.03 |
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Blood constituents | |||
Glucose (mmol/L) | 4.66 ± 0.07 | 4.80 ± 0.05 | 4.73 ± 0.04 |
Insulin (pmol/L) | 53.2 ± 4.6 | 51.1 ± 5.2 | 52.0 ± 3.52 |
HOMA2-IR | 1.13 ± 0.10 | 1.09 ± 0.11 | 1.11 ± 0.07 |
Triglycerides (mmol/L) | 1.17 ± 0.23 | 0.90 ± 0.10 | 1.00 ± 0.12 |
Total cholesterol (mmol/L) | 4.04 ± 0.09 | 4.27 ± 0.11 | 4.17 ± 0.07 |
HDL-cholesterol (mmol/L) | 1.38 ± 0.06 | 1.51 ± 0.06 | 1.45 ± 0.04 |
LDL + VLDL-cholesterol (mmol/L) | 2.56 ± 0.10 | 2.76 ± 0.12 | 2.67 ± 0.08 |
We used simple linear regression to assess the relationship between three different covariates of obesity (BMI Z score, percentage of total body fat and android/gynoid ratio) and the outcomes of cardiovascular and metabolic risk factors (Table
Regression based correlation analyses adjusted
Outcome | Covariate | ||
---|---|---|---|
BMI |
Percent of total body fat | Android/gynoid | |
|
|
|
|
HOMA2-IR | 0.276 (<0.001) | 0.293 (<0.001) | 0.459 (<0.001) |
Triglycerides | 0.039 (0.050) | 0.039 (0.052) | 0.063 (0.018) |
Total cholesterol | 0.055 (0.026) | 0.085 (0.007) | 0.088 (0.006) |
HDL-cholesterol | 0.079 (0.009) | 0.044 (0.041) | 0.103 (0.003) |
LDL + VLDL-cholesterol | 0.185 (<0.0001) | 0.199 (<0.001) | 0.268 (<0.001) |
Our emphasis on the android/gynoid ratio (Table
Regression based correlation analyses adjusted
Outcome | Android/gynoid | |||
---|---|---|---|---|
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Girls | Boys | Sex adjusted model | Sex and age adjusted model | |
HOMA2-IR | 0.322 (<0.001) | 0.523 (<0.001) | 0.452 (<0.001) | 0.508 (<0.001) |
Triglycerides | 0.009 (0.267) | 0.195 (0.003) | 0.060 (0.018) | 0.068 (0.018) |
Total cholesterol | <0.001 (0.817) | 0.223 (0.001) | 0.113 (0.006) | 0.121 (0.005) |
HDL-cholesterol | 0.002 (0.311) | 0.156 (0.007) | 0.114 (0.003) | 0.124 (0.003) |
LDL + VLDL-cholesterol | <0.001 (0.761) | 0.438 (<0.001) | 0.270 (<0.001) | 0.261 (<0.001) |
The coefficient of partial determination measures the marginal contribution of one covariate when others are already in the model. We observed that when the android/gynoid ratio is already in the model, the addition of the child’s sex only reduced residual sum of squares by 0.02%. In contrast, when the android/gynoid ratio is already in the model, the addition of the child’s age provided an 11.54% reduction in the residual sum of squares. We noted that if both the android/gynoid ratio and age are already in the model, the addition of sex decreased the residual sum of squares by only 0.09%. We noted that, in all our sex adjusted regression models, the model coefficient for the sex covariate was not statistically significant, despite the differences in significance of
Finally, we assessed if the relationships between the outcomes and the android/gynoid ratio were being driven by the most obese of our subjects, by considering the android/gynoid ratio relationships within tertiles based on BMI percentile. We observed that there is a 5.9% reduction in the residual sum of squares with the addition of BMI tertiles to the regression model when the android/gynoid ratio is already in the model. Furthermore, we had an 11.9% reduction in the residual sum of squares with the addition of age when the BMI tertiles are already in the model. Finally, we observed that there was a 6.3% reduction in the residual sum of squares with the addition of BMI tertiles to the regression model when the android/gynoid ratio and age were already in the model. Based on these results, we explored both within BMI tertile strata correlations and adjusted correlations (Table
Regression based correlation analyses adjusted
Android/gynoid ratio |
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---|---|---|---|---|
BMI 1st tertile | BMI 2nd tertile | BMI 3rd tertile | BMI and age adjusted | |
Both sexes | ||||
HOMA2-IR | 0.307 (0.003) | 0.111 (0.057) | 0.386 (0.001) | 0.532 (<0.001) |
Triglycerides | 0.053 (0.144) | <0.001 (0.439) | <0.001 (0.464) | 0.060 (0.018) |
Total cholesterol | 0.095 (0.078) | <0.001 (0.544) | 0.100 (0.073) | 0.107 (0.006) |
HDL-cholesterol | <0.001 (0.564) | <0.001 (0.545) | 0.079 (0.099) | 0.087 (0.004) |
LDL + VLDL-cholesterol | 0.146 (0.037) | 0.034 (0.187) | 0.266 (0.007) | 0.268 (<0.001) |
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Femalea | ||||
HOMA2-IR | 0.330 (0.082) | 0.065 (0.400) | 0.261 (0.131) | 0.555 (<0.001) |
Triglycerides | 0.010 (0.785) | 0.060 (0.421) | 0.001 (0.924) | 0.086 (0.280) |
Total cholesterol | 0.047 (0.549) | 0.097 (0.301) | 0.303 (0.099) | 0.028 (0.824) |
HDL-cholesterol | 0.106 (0.359) | 0.034 (0.544) | 0.032 (0.622) | 0.053 (0.331) |
LDL + VLDL-cholesterol | 0.006 (0.836) | 0.335 (0.038) | 0.268 (0.153) | 0.039 (0.769) |
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Maleb | ||||
HOMA2-IR | 0.256 (0.037) | 0.449 (0.017) | 0.402 (0.009) | 0.538 (<0.001) |
Triglycerides | 0.225 (0.049) | 0.002 (0.894) | 0.200 (0.062) | 0.197 (0.003) |
Total cholesterol | 0.174 (0.077) | 0.004 (0.842) | 0.362 (0.014) | 0.254 (0.001) |
HDL-cholesterol | 0.028 (0.264) | 0.000 (0.958) | 0.118 (0.123) | 0.246 (0.005) |
LDL + VLDL-cholesterol | 0.281 (0.030) | 0.011 (0.751) | 0.563 (0.002) | 0.408 (<0.001) |
The differences between sexes became more apparent in these analyses. For girls, we observed a statistically significant association between VLDL + LDL-cholesterol and the android/gynoid ratio within BMI tertile 2 (
For boys, we observed that, across all three tertiles, the android/gynoid ratio was significantly associated with HOMA2-IR (Table
In our population of 7–13-year-old boys and girls, the android/gynoid ratio proved to be the obesity measure most closely related to both insulin resistance and dislipidemia. An important and unique observation was that the relationship between both metabolic and cardiovascular disease risk and android/gynoid ratio was strong in normal weight boys as well as the overweight or obese. These relationships did not hold true for girls.
When compared to BMI Z score and percent of total body fat, we found that the android/gynoid ratio was clearly the most closely related to all disease risk factors. However, the effects of android/gynoid ratio on HOMA2-IR did differ by age. In boys, all risk factors showed a significant relationship with the android/gynoid ratio, and HOMA2-IR and LDL + VLDL-cholesterol had very high correlations, while, in girls, only HOMA2-IR was significantly related to the android/gynoid ratio. Also, of note, the effect of age as a covariate was lost in males but not females.
In 1996, Vague [
In our subjects, the android/gynoid ratio was a good predictor of both insulin resistance and the cardiovascular risk factor, LDL + VLDL-cholesterol, in normal as well as overweight or obese boys. The BMI percentile of our population ranged from 0.1 to 99.6 percentile, providing us with an opportunity to assess the relationship between android/gynoid ratio and disease risk in normal weight children as well as overweight and obese. When we broke our subjects into tertiles of BMI percentile, the android/gynoid ratio in boys was significantly correlated with HOMA2-IR regardless of BMI tertile and with LDL + VLDL-cholesterol in both the low and high tertiles. However, the effect of android/gynoid ratio on HOMA2-IR in girls was lost.
Various anthropometric measurements have been used to assess metabolic and cardiovascular risk, including BMI and percent body fat, as well as site specific measurements, such as abdominal or android fat and waist circumference. A number of studies have shown that high levels of central or truncal obesity carry risks for both metabolic and cardiovascular diseases in adults [
The fact that the android/gynoid ratio is related to disease risk, even if a child is at normal weight, gives us a target area for changes in body fat. Interventions in both children and adults have been shown to decrease android fat and improve insulin resistance. Tang et al. [
Our study was cross-sectional rather than longitudinal, limiting what can be said about cause and effect between the android/gynoid ratio and disease risk. Also, we made no measures of Tanner stages and cannot assess the impact that puberty may be having on our findings, particularly those of sex and age. The sample size restricted our ability to explore more complex relationships such as covariate interactions.
The finding that the android/gynoid ratio is highly correlated to risk factors for both metabolic and cardiovascular diseases in normal weight boys is important. It is impractical to expect that DXA scans will become a part of routine screenings in apparently healthy children. However, Arnberg et al. [
The authors declare that there is no conflict of interests regarding the publication of this paper.
This project was funded through an internal grant mechanism, no. 2R335 from the West Virginia University Department of Pediatrics. The authors would like to thank the research team members and specifically acknowledge the efforts of Jan Rapp, Michelle Sanders, Barbara Menear, Dr. Rafka Chaiban, Dr. Silvia Cardenas, and Dr. Yesim Demirdag.