Yuan Jiang1,2, Yalan Dou1, Hongyan Chen1, Yi Zhang1,2, Xiaotian Chen1,2, Yin Wang1,2, Myanca Rodrigues3, Weili Yan4,5. 1. Department of Clinical Epidemiology and Clinical Trial Unit, National Children's Medical Center, Children's Hospital of Fudan University, Shanghai, 201102, People's Republic of China. 2. Research Unit of Early Intervention of Genetically Related Childhood Cardiovascular Diseases (2018RU002), Chinese Academy of Medical Sciences, Shanghai, China. 3. Health Research Methodology Graduate Program, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada. 4. Department of Clinical Epidemiology and Clinical Trial Unit, National Children's Medical Center, Children's Hospital of Fudan University, Shanghai, 201102, People's Republic of China. yanwl@fudan.edu.cn. 5. Research Unit of Early Intervention of Genetically Related Childhood Cardiovascular Diseases (2018RU002), Chinese Academy of Medical Sciences, Shanghai, China. yanwl@fudan.edu.cn.
Abstract
OBJECTIVE: To provide the latest evidence of performance and robustness of waist-to-height ratio (WHtR) in discriminating clusters of cardiometabolic risk factors (CMRs) and promote WHtR in routine primary health care practice in children, a meta-analysis was used. METHODS: Searches was performed in eight databases from inception to July 03, 2020. Inclusion criteria were: (1) observational study, (2) children and adolescents, (3) provided WHtR measurements, (4) had CMRs as outcomes, and (5) diagnostic studies. Exclusion criteria were: (1) non-original articles, (2) unable to extract 2 × 2 contingency tables, (3) not in English or Chinese language, (4) populations comprising clinical patients, or (5) duplicate articles. WHtR cutoff points, 2 × 2 contingency tables were extracted from published reports. Outcomes included: CMR clusters of at least three CMRs (CMR3), two (CMR2), one (CMR1), and CMR components. Bivariate mixed-effects models were performed to estimate the summarised area under the curves (AUSROC) with 95% CIs and related indexes. We conducted subgroup analyses by sex and East Asian ethnicity. RESULTS: Fifty-three observational studies were included. The AUSROC reached 0.91 (95% CI: 0.88-0.93), 0.85 (95% CI: 0.81, 0.88) and 0.75 (95% CI: 0.71, 0.79) for CMR3, CMR2, and CMR1, respectively. The pooled sensitivity and specificity for CMR3 reached 0.84 and exceeded 0.75 for CMR2. For CMR1, the sensitivity achieved 0.55 with 0.84 for specificity. We had similar findings for our subgroup and sensitivity analyses. CONCLUSIONS: WHtR shows good and robust performance in identifying CMRs clustering across racial populations, suggesting its promising utility in public health practice globally.
OBJECTIVE: To provide the latest evidence of performance and robustness of waist-to-height ratio (WHtR) in discriminating clusters of cardiometabolic risk factors (CMRs) and promote WHtR in routine primary health care practice in children, a meta-analysis was used. METHODS: Searches was performed in eight databases from inception to July 03, 2020. Inclusion criteria were: (1) observational study, (2) children and adolescents, (3) provided WHtR measurements, (4) had CMRs as outcomes, and (5) diagnostic studies. Exclusion criteria were: (1) non-original articles, (2) unable to extract 2 × 2 contingency tables, (3) not in English or Chinese language, (4) populations comprising clinical patients, or (5) duplicate articles. WHtR cutoff points, 2 × 2 contingency tables were extracted from published reports. Outcomes included: CMR clusters of at least three CMRs (CMR3), two (CMR2), one (CMR1), and CMR components. Bivariate mixed-effects models were performed to estimate the summarised area under the curves (AUSROC) with 95% CIs and related indexes. We conducted subgroup analyses by sex and East Asian ethnicity. RESULTS: Fifty-three observational studies were included. The AUSROC reached 0.91 (95% CI: 0.88-0.93), 0.85 (95% CI: 0.81, 0.88) and 0.75 (95% CI: 0.71, 0.79) for CMR3, CMR2, and CMR1, respectively. The pooled sensitivity and specificity for CMR3 reached 0.84 and exceeded 0.75 for CMR2. For CMR1, the sensitivity achieved 0.55 with 0.84 for specificity. We had similar findings for our subgroup and sensitivity analyses. CONCLUSIONS: WHtR shows good and robust performance in identifying CMRs clustering across racial populations, suggesting its promising utility in public health practice globally.
Entities:
Keywords:
Cardiometabolic risk; Diagnostic test; Meta-analysis; Paediatric population; Waist-to-height ratio
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