Utility of three anthropometric indices in assessing the cardiometabolic risk profile in children. Issue 3 (1st November 2016)

• Record Type: Journal Article
• Authors: Buchan, Duncan S.; Boddy, Lynne M.; Grace, Fergal M.; Brown, Elise; Sculthorpe, Nicholas; Cunningham, Conor; Murphy, Marie H.; Dagger, Rebecca; Foweather, Lawrence; Graves, Lee E. F.; Hopkins, Nicola D.; Stratton, Gareth; Baker, Julien S.
• Is Part Of: American journal of human biology. Volume 29:Issue 3(2017:May/Jun.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-11-01
• Subjects: adiposity -- cardiometabolic risk -- screening -- waist‐to‐height ratio -- youth; Human biology -- Periodicals; Physical anthropology -- Periodicals; Biologie humaine -- Périodiques; Anthropologie physique -- Périodiques; 612
• DOI: 10.1002/ajhb.22934
• Languages: English
• ISSNs: 1042-0533

Abstract

Abstract: Objectives: To evaluate the ability of BMI, WC, and WHtR to identify increased cardiometabolic risk in pre‐adolescents. Methods: This is a cross‐sectional study involving 192 children (10.92 ± 0.58 years, 56% female) from the United Kingdom between 2010 and 2013. Receiver operating characteristic curves determined the discriminatory ability of BMI, WC and WHtR to identify individuals with increased cardiometabolic risk (increased clustered triglycerides, HDL‐cholesterol, systolic blood pressure, cardiorespiratory fitness, and glucose). Results: A WHtR ≥ 0.5 increased the odds by 5.2 (95% confidence interval 2.6 ‐ 10.3) of having increased cardiometabolic risk. Similar associations were observed for BMI and WC. Both BMI‐z and WHtR were fair predictors of increased cardiometabolic risk, although BMI‐z demonstrated the best trade‐off between sensitivity and specificity, 76.1% and 63.6%, compared with 68.1% and 65.5% for WHtR. Cross‐validation analysis revealed that BMI‐z and WHtR correctly classified 84% of individuals (kappa score = 0.671, 95% CI 0.55, 0.79). The sensitivity of the cut‐points suggests that 89.3% of individuals were correctly classified as being at risk with only 10.7% misdiagnosed whereas the specificity of the cut‐points indicated that 77.8% of individuals were correctly identified as being healthy with 22.2% of individuals incorrectly diagnosed as being at risk. Conclusions: Findings suggest that WHtR provides similar cardiometabolic risk estimates to age and sex adjusted BMI.