{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T20:35:24Z","timestamp":1773693324734,"version":"3.50.1"},"reference-count":62,"publisher":"Walter de Gruyter GmbH","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,1,28]]},"abstract":"Abstract<\/jats:title>Background<\/jats:title>Anthropometric indicators are associated with cardiometabolic risk factors (CMRF), but there is no consensus as to which indicator is the most suitable to screen for clustered CMRF. This study aimed to evaluate the utility of five anthropometric indicators to screen for clustered CMRF in children and adolescents.<\/jats:p><\/jats:sec>Methods<\/jats:title>A cross-sectional study was conducted in 1139 schoolchildren aged 6\u201317 years from Northeastern Brazil. Body weight, height, waist circumference (WC) and subscapular (SSF) and triceps skinfold thickness (TSF) were measured. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated. The following CMRF were evaluated: elevated total cholesterol, low high-density lipoprotein-cholesterol (HDL-C), elevated low-density lipoprotein-cholesterol (LDL-C), high triglyceride concentration, hyperglycemia and high blood pressure. The participants were categorized into no CMRF, 1 CMRF, 2 CMRF and \u22653 CMRF. Receiver operating characteristic (ROC) curves were constructed to assess the accuracy of the anthropometric indicators in predicting CMRF for age group and sex.<\/jats:p><\/jats:sec>Results<\/jats:title>Poor associations were observed between the anthropometric indicators and 1 CMRF (accuracy of 0.49\u20130.64). The indicators showed moderate associations with 2 CMRF (accuracy of 0.57\u20130.75) and \u22653 CMRF (accuracy of 0.59\u20130.79). In general, TSF exhibited the worst performance in predicting CMRF, followed by WHtR. The highest accuracies were observed for BMI, WC and SSF, with no significant difference between these indicators.<\/jats:p><\/jats:sec>Conclusions<\/jats:title>The routine use of BMI, WC and SSF as epidemiological screening tools for clustered CMRF in childhood and adolescence should be encouraged.<\/jats:p><\/jats:sec>","DOI":"10.1515\/jpem-2018-0217","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T09:03:07Z","timestamp":1544432587000},"page":"49-55","source":"Crossref","is-referenced-by-count":23,"title":["Utility of anthropometric indicators to screen for clustered cardiometabolic risk factors in children and adolescents"],"prefix":"10.1515","volume":"32","author":[{"given":"Teresa Maria Bianchini","family":"de Quadros","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex Pinheiro","family":"Gordia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alynne Christian Ribeiro","family":"Andaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edmar Lacerda","family":"Mendes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jorge","family":"Mota","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luciana Rodrigues","family":"Silva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","reference":[{"key":"ref401","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1056\/NEJMra1514009","article-title":"Mechanisms, pathophysiology, and management of obesity","volume":"376","year":"2017","journal-title":"N Engl J Med"},{"key":"ref181","first-page":"77","volume-title":"Anthropometrica: a textbook of body measurement for sports and health courses","year":"1996"},{"key":"ref411","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1017\/S0954422410000144","article-title":"A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value","volume":"23","year":"2010","journal-title":"Nutr Res Rev"},{"key":"ref551","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1093\/clinchem\/18.6.499","article-title":"Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge","volume":"18","year":"1972","journal-title":"Clin Chem"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1056\/NEJMra1514009","article-title":"Mechanisms, pathophysiology, and management of obesity","volume":"376","year":"2017","journal-title":"N Engl J Med"},{"key":"ref191","first-page":"53","article-title":"7th Brazilian Guideline of Arterial Hypertension: Chapter 10 - 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