Novel gender-specific visceral adiposity index for Mexican pediatric population

Abstract

BackgroundVisceral Adiposity Index (VAI) has been strongly associated with adipocytokine synthesis, proinflammatory activity, insulin resistance, dyslipidemia, hypertension and atherosclerosis. VAI is a model that includes and correlates anthropometric and metabolic markers and has been proposed as a risk factor index associated with cardiovascular risk in adults. Some studies conducted in pediatric population have extrapolated VAI calculation in order to predict these abnormalities; nonetheless, no adjustment has been done for pediatric ranges in any of the variables included in the formula. The aim of this study was to design a new sex-specific VAI model adjusted for pediatric population. Subjects and methodsCross-sectional study, 548 children (290 males and 258 females) aged 3-17 years were included for analysis. Eutrophic, apparently healthy children (n=223) were recruited from 3 public schools located nearby the hospital. Overweight (n=89) and obese subjects (n=236) were patients that regularly attend at the Pediatric Obesity Clinic from “Hospital General de México”. Anthropometric evaluation included weight, height, waist circumference (WC). Body mass index (BMI) was calculated and Tg and HDL measured in a 12hour fasting condition (mMol/L). ResultsA non-lineal quadratic regression model accurately explained the relationship between WC and BMI in pediatric population (coefficient of determination R2=0.938; p<0.001 for males and R2=0.907; p<0.001 for females). Medians of triglycerides and HDL-cholesterol values of 223 healthy children were used to calculate the second formula component (Males: median Tg=0.76mmol/l, median HDL-cholesterol=1.37mmol/l; Females: median Tg=0.91mml/l, median HDL-chloesterol=1.42mmol/l). ConclusionsVAI formula construction seemed to be different in children compared to adults. In the present study we propose a new gender-specific visceral adipose index for pediatric Mexican population living in urban areas that could be further used to predict abnormal cardiometabolic outcomes.