Waist circumference percentiles in 2-18 year old Indian children

Anuradha Khadilkar1, Veena Ekbote1, Shashi Chiplonkar1

  • 1Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.

Insights

This study created waist circumference (WC) percentile curves for Indian children. A 70th WC percentile cutoff effectively identifies children at risk for metabolic syndrome (MS).

Area of Science:

  • Pediatric Endocrinology
  • Public Health Nutrition
  • Growth Monitoring

Background:

  • Metabolic syndrome (MS) is a growing concern in children, necessitating reliable screening tools.
  • Waist circumference (WC) is a key indicator of central obesity and a predictor of MS risk.
  • Lack of established reference data for WC in Indian children hinders accurate risk assessment.

Purpose of the Study:

  • To establish age- and sex-specific reference percentile curves for waist circumference (WC) in Indian children.
  • To determine an optimal WC percentile cutoff for identifying children at risk for metabolic syndrome (MS).

Main Methods:

  • A multicenter, cross-sectional study involving 10,842 Indian children (aged [age range not specified]) from 5 major cities.
  • Waist circumference (WC) measurements were taken using standardized techniques.
  • The LMS method was used to compute sex-specific reference percentiles, and Receiver Operating Characteristic (ROC) curve analysis identified the optimal MS risk cutoff.

Main Results:

  • Age- and sex-specific WC percentile curves (5th to 95th) were generated, showing increased WC with age in both genders.
  • Median WC was higher in boys than girls after 15 years of age.
  • The 70th WC percentile demonstrated high sensitivity (0.82-0.84) and specificity (0.85) for identifying MS risk, with significant Area Under the ROC Curve (0.88-0.92).

Conclusions:

  • The study provides valuable age- and sex-specific reference curves for WC in Indian children.
  • A cutoff of the 70th WC percentile is recommended for effectively screening Indian children for metabolic syndrome (MS) risk.
Abstract

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