BMJ Open (Jun 2020)

Waist-to-height ratio as a screening tool for cardiometabolic risk in children and adolescents: a nationwide cross-sectional study in China

  • Yin Wang,
  • Yuan Jiang,
  • Weili Yan,
  • Jie Mi,
  • Yalan Dou,
  • Xiaotian Chen,
  • Yinkun Yan,
  • Xiaoyuan Zhao,
  • Hong Cheng,
  • Dongqing Hou,
  • Hongyan Chen

DOI
https://doi.org/10.1136/bmjopen-2020-037040
Journal volume & issue
Vol. 10, no. 6

Abstract

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Objectives To demonstrate the accuracy and flexibility of using waist-to-height ratio (WHtR) as a screening tool for identifying children and adolescents with cardiometabolic risk (CMR) across a wide range of prevalence levels among general paediatric populations.Design A nationwide population-based cross-sectional study with all data collected at school settings in six cities of China.Participants A total of 8130 children and adolescents aged 7–18 years with complete anthropometric and CMR measurements based on blood tests were recruited.Outcome measures Elevated blood pressure, dyslipidaemia, elevated fasting blood glucose and central obesity were measured. The primary outcome, CMRs, was defined as meeting three or more of the above risk factors. The accuracy of WHtR for identifying CMRs was evaluated using areas under the curves (AUCs) with 95% CI of the receiver operating characteristic curve. The predictability of WHtR at given CMRs prevalence levels was estimated by positive predictive value (PPV) and negative predictive value.Results Overall, 6.1% of study participants were presented with CMRs. WHtR had high AUCs ranging from 0.84 (95% CI 0.81 to 0.88) to 0.88 (95% CI 0.86 to 0.90) in the total population and age-subgroup and gender-subgroup. The overall optimal WHtR cut-off value was 0.467, with boys having a higher cut-off than girls (0.481 vs 0.456). WHtR achieved an overall sensitivity of 0.89 and PPV of 18.8% at a specificity of 0.75. The screening performance of WHtR remained satisfactory across a wide range of given CMRs prevalence levels (5%, 10% and 20%).Conclusion WHtR as a screening tool could accurately and flexibly identify children affected with the clusters of three or more of CMR factors from the general paediatric population with various CMR prevalence levels. Our findings provide support for policy-making on early CMR identification and management in the high-risk group of children.