Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/10236
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dc.contributor.authorZong, Xin’nanen_US
dc.contributor.authorKelishadi, Royaen_US
dc.contributor.authorKim, Hae Soonen_US
dc.contributor.authorSchwandt, Peteren_US
dc.contributor.authorMatsha, Tandi Edithen_US
dc.contributor.authorMill, Jose G.en_US
dc.contributor.authorWhincup, Peter H.en_US
dc.contributor.authorPacifico, Luciaen_US
dc.contributor.authorLópez‑Bermejo, Abelen_US
dc.contributor.authorCaserta, Carmelo Antonioen_US
dc.contributor.authorMedeiros, Carla Campos Munizen_US
dc.contributor.authorYan, Weilien_US
dc.contributor.authorKollias, Anastasiosen_US
dc.contributor.authorSkidmore, Paulaen_US
dc.contributor.authorCorreia-Costa, Lianeen_US
dc.contributor.authorKhadilkar, Anuradha Vamanen_US
dc.contributor.authorJazi, Fariborz Sharifianen_US
dc.contributor.authorGong, Zhuoen_US
dc.contributor.authorZhang, Chengen_US
dc.contributor.authorMagnussen, Costan G.en_US
dc.contributor.authorZhao, Minen_US
dc.contributor.authorXi, Boen_US
dc.date.accessioned2025-10-27T08:17:22Z-
dc.date.available2025-10-27T08:17:22Z-
dc.date.issued2024-
dc.identifier.citationZong, X. et al. 2022. Utility of waist-to-height ratio, waist circumference and body mass index in predicting clustered cardiometabolic risk factors and subclinical vascular phenotypes in children and adolescents: A pooled analysis of individual data from 14 countries. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 18(5): 1-9, [https://doi.org/10.1016/j.dsx.2024.103042]en_US
dc.identifier.issn1871-4021-
dc.identifier.issn1878-0334 (Online)-
dc.identifier.urihttp://hdl.handle.net/11189/10236-
dc.description.abstractAims: The clinical utility of waist-to-height ratio (WHtR) in predicting cardiometabolic risk factors (CMRFs) and subclinical markers of cardiovascular disease remains controversial. We aimed to compare the utility of WHtR with waist circumference (WC) and body mass index (BMI) in identifying children and adolescents (youths) at risk for cardiometabolic outcomes, including clustered CMRFs, high carotid intima-media thickness (cIMT), and arterial stiffness (assessed as high pulse wave velocity, PWV). Methods: We analyzed data from 34,224 youths (51.0 % boys, aged 6–18 years) with CMRFs, 5004 (49.5 % boys, aged 6–18 years) with cIMT measurement, and 3100 (56.4 % boys, aged 6–17 years) with PWV measurement from 20 pediatric samples across 14 countries. Results: WHtR, WC, and BMI z-scores had similar performance in discriminating youths with ≥3 CMRFs, with the area under the curve (AUC) (95 % confidence interval, CI)) ranging from 0.77 (0.75–0.78) to 0.78 (0.76–0.80) using the modified National Cholesterol Education Program (NCEP) definition, and from 0.77 (0.74–0.79) to 0.77 (0.74–0.80) using the International Diabetes Federation (IDF) definition. Similarly, all three measures showed similar performance in discriminating youths with subclinical vascular outcomes, with AUC (95 % CI) ranging from 0.67 (0.64–0.71) to 0.70 (0.66–0.73) for high cIMT (≥P95 values) and from 0.60 (0.58–0.66) to 0.62 (0.58–0.66) for high PWV (≥P95 values). Conclusions: Our findings suggest that WHtR, WC, and BMI are equally effective in identifying at-risk youths across diverse pediatric populations worldwide. Given its simplicity and ease of use, WHtR could be a preferable option for quickly screening youths with increased cardiometabolic risk in clinical settings.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofDiabetes and Metabolic Syndrome: Clinical Research and Reviewsen_US
dc.subjectWaist-to-height ratioen_US
dc.subjectWaist circumferenceen_US
dc.subjectBody mass indexen_US
dc.subjectObesityen_US
dc.subjectCardiometabolic risk factorsen_US
dc.subjectCarotid intima-media thicknessen_US
dc.subjectPulse wave velocityen_US
dc.subjectChilden_US
dc.subjectAdolescenten_US
dc.titleUtility of waist-to-height ratio, waist circumference and body mass index in predicting clustered cardiometabolic risk factors and subclinical vascular phenotypes in children and adolescents: A pooled analysis of individual data from 14 countriesen_US
dc.identifier.doihttps://doi.org/10.1016/j.dsx.2024.103042-
dc.typeArticleen_US
Appears in Collections:HWSci - Journal Articles (DHET subsidised)
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