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Importance of android/gynoid fat ratio in predicting metabolic and cardiovascular disease risk in normal weight as well as overweight and obese children.

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.
AuthorsLennie Samsell, Michael Regier, Cheryl Walton, Lesley Cottrell
JournalJournal of obesity (J Obes) Vol. 2014 Pg. 846578 ( 2014) ISSN: 2090-0716 [Electronic] United States
PMID25302115 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
Topics
  • Absorptiometry, Photon
  • Adolescent
  • Body Composition
  • Body Fat Distribution
  • Cardiovascular Diseases (blood, epidemiology, prevention & control)
  • Child
  • Female
  • Humans
  • Insulin Resistance
  • Male
  • Metabolic Syndrome (blood, epidemiology, prevention & control)
  • Pediatric Obesity (epidemiology, pathology, prevention & control)
  • Predictive Value of Tests
  • Severity of Illness Index
  • Thinness

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