Are Body Composition Parameters Better than Conventional Anthropometric Measures in Predicting Pediatric Hypertension?

Int J Environ Res Public Health. 2020 Aug 10;17(16):5771. doi: 10.3390/ijerph17165771.

Abstract

Body composition (BC) parameters are associated with cardiometabolic diseases in children; however, the importance of BC parameters for predicting pediatric hypertension is inconclusive. This cross-sectional study aimed to compare the difference in predictive values of BC parameters and conventional anthropometric measures for pediatric hypertension in school-aged children. A total of 340 children (177 girls and 163 boys) with a mean age of 8.8 ± 1.7 years and mean body mass index (BMI) z-score of 0.50 ± 1.24 were enrolled (102 hypertensive children and 238 normotensive children). Significantly higher values of anthropometric measures (BMI, BMI z-score, BMI percentile, waist-to-height ratio) and BC parameters (body-fat percentage, muscle weight, fat mass, fat-free mass) were observed among the hypertensive subgroup compared to their normotensive counterparts. A prediction model combining fat mass ≥ 3.65 kg and fat-free mass ≥ 34.65 kg (area under the receiver operating characteristic curve = 0.688; sensitivity = 66.7%; specificity = 89.9%) performed better than BMI alone (area under the receiver operating characteristic curve = 0.649; sensitivity = 55.9%; specificity = 73.9%) in predicting hypertension. In conclusion, BC parameters are better than anthropometric measures in predicting pediatric hypertension. BC measuring is a reasonable approach for risk stratification in pediatric hypertension.

Keywords: body mass index; body-fat percentage; children; fat mass; fat-free mass; hypertension; muscle weight; waist-to-height ratio.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Composition*
  • Body Mass Index
  • Child
  • Cross-Sectional Studies
  • Female
  • Forecasting
  • Humans
  • Hypertension* / diagnosis
  • Hypertension* / epidemiology
  • Male
  • Prognosis
  • ROC Curve
  • Risk Factors
  • Waist Circumference
  • Waist-Height Ratio*