{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T15:39:36Z","timestamp":1770046776686,"version":"3.49.0"},"reference-count":18,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2015,12,26]],"date-time":"2015-12-26T00:00:00Z","timestamp":1451088000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"National Science and Technology Support Programme of China","award":["2012BAJ18B02"],"award-info":[{"award-number":["2012BAJ18B02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Diabetes Invest"],"published-print":{"date-parts":[[2016,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Aims\/Introduction<\/jats:title><jats:p>Obesity plays a central role in metabolic syndrome. Obesity indexes are important in clinical work. In the present study, we sought to determine the relationships between obesity indexes and metabolic risk factors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>We studied 11,568 participants over 35 years. Body mass index, waist circumference (<jats:styled-content style=\"fixed-case\">WC<\/jats:styled-content>), waist\u2010to\u2010height ratio (<jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR) and waist\u2010to\u2010hip ratio were measured and calculated. To compare the predictive ability of the obesity indexes in diagnosing multiple metabolic risk factors, the areas under receiver operating characteristic curves were calculated, and cut\u2010off values were determined. A partial correlation coefficient was used to assess the intercorrelations between the obesity indexes, and to evaluate the correlations between each index and each metabolic risk factor.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The partial correlation coefficient for <jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR and <jats:styled-content style=\"fixed-case\">WC<\/jats:styled-content> was 0.947. In diagnosing multiple metabolic risk factors, the <jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR areas under receiver operating characteristic curves was greater than that for the other obesity indexes in both sexes. The cut\u2010off point for the <jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR was 0.50 in men and 0.52 in women. The cut\u2010off point for <jats:styled-content style=\"fixed-case\">WC<\/jats:styled-content> was 85 cm in men and 80 cm in women.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p><jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR strongly correlates with <jats:styled-content style=\"fixed-case\">WC<\/jats:styled-content>. The <jats:styled-content style=\"fixed-case\">WH<\/jats:styled-content>tR might show the same predictive ability as the <jats:styled-content style=\"fixed-case\">WC<\/jats:styled-content> in diagnosing multiple metabolic risk factors.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jdi.12442","type":"journal-article","created":{"date-parts":[[2015,11,12]],"date-time":"2015-11-12T13:00:38Z","timestamp":1447333238000},"page":"601-606","source":"Crossref","is-referenced-by-count":33,"title":["Associations between metabolic risk factors and body mass index, waist circumference, waist\u2010to\u2010height ratio and waist\u2010to\u2010hip ratio in a Chinese rural population"],"prefix":"10.1111","volume":"7","author":[{"given":"Xin","family":"Guan","sequence":"first","affiliation":[{"name":"Department of Cardiology The First Hospital of China Medical University Shenyang 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