Abstract: 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.
Alex’s Notes: Fat distribution has been known to play a role in various metabolic diseases for a while now. Visceral fat is likely the most common example, with central (abdominal) obesity being a huge risk factor for metabolic syndrome and its complications. This “beer belly” or android fat distribution is commonly associated with men. The opposite, gynoid fat distribution, is characterized with less abdominal fat and more hip/thigh fat. These are the classic apple and pear body shapes of men and women, respectively. The objective of the study at hand was to determine the association of android/gynoid fat ratio with insulin resistance and dyslipidemia in children, regardless of weight status.
Seventy three children aged 7-13 years old (average 9.5-years) were recruited for this study. They were asked to fast overnight and abstain from any medications as appropriate until a serum blood draw the following morning to collect data about insulin, glucose, and lipids. They then ate breakfast while the parents completed additional health and medical history surveys. Afterwards, a DXA scan of the children was performed to determine body composition and fat distribution. 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.
So what did you find so interesting Alex?
As it turns out, the android/gynoid ratio had the strongest relationship with all the tested factors. Notably, it explained almost 46% of the variation of insulin resistance in the children (32% for girls & 52% in boys), while total body fat only accounted for 29% of the variation. After adjustment for both age and BMI, the relationship between the ratio and insulin resistance held strong. Additionally, the ratio explained nearly 27% of the variation in LDL-C + VLDL-C values, 10% of the variation of HDL-C, almost 9% of the total cholesterol variation, and 6% of the triglyceride variation. Total body fat percentage also had a statistically significant association with all these values, albeit to a lesser degree than the android/gynoid ratio.
When we shift focus specifically to the android/gynoid ratio, it becomes evident that there is a significant relationship between it and all tested values in boys, but only insulin resistance in girls. After adjustment for sex and age, it becomes significantly associated with all variables yet again, most strongly with insulin resistance and LDL-C + VLDL-C.
So couldn’t this association be driven by all the fat kids that were tested?
Very good question Billy. The BMI percentiles of the children ranged from 0.1 to 99.6, quite literally providing a sample group that covered nearly all possible weights. And yet, when the data was broken down into BMI tertiles, the association between the ratio and insulin sensitivity remained significant regardless of BMI in males, but not in females.
This means that even if a child is at normal weight, the ratio gives us relationship to disease risk factors and is something that could be targeted. Of course this study didn’t assess the impact of puberty, and I would love to see this repeated in adults. Additionally, it raises one very important question. What is driving what? Are boys more insulin sensitive because they have a gynoid fat distribution? Or do they have that fat distribution because of their insulin sensitivity? Alas, this correlational study cannot tell us.