{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:56:32Z","timestamp":1785419792174,"version":"3.56.0"},"reference-count":33,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:bold>Background.<\/jats:bold>\n                    The prevalence of obesity and metabolic syndrome (MetS) is increasing, worldwide. Using a simple, efficient and reliable tool for predicting MetS is an essential approach in preventive health programs. The aim of this study was to compare the different anthropometric indices in predicting metabolic syndrome in older adults.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Methods.<\/jats:bold>\n                    This cross-sectional study is a part of the Amirkola Health and Ageing cohort Project (2011\u20132016). Of total, 1,488 older people aged 60\u201392 years were entered to the study. Medical and personal information of participants were collected by a questionnaire. After measuring the height, weight, waist circumference, hip circumference and neck circumference, body mass index, waist to hip ratio, waist to height ratio, abdominal volume index and conicity index were calculated. Independent t-test, chi-square and ROC curve were used to analyze the data.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Results.<\/jats:bold>\n                    Based on ATPIII-2005 diagnostic criteria, the prevalence of metabolic syndrome was 71.57%.The prevalence in female was higher than male. All of examined anthropometric indices, except neck circumference (p = 0.10), showed a significant difference in people with MetS compared to the individuals without metabolic syndrome (p&lt;0.001). Waist to height ratio showed the largest area under the curve for predicting MetS (0.786; 95% CI: 0.76\u20130.81) followed by BMI (0.746; 95% CI: 0.71\u20130.77), AVI (0.745; 95% CI: 0.71\u20130.77), and waist circumference (0.743; 95% CI: 0.71\u20130.77).\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Conclusion.<\/jats:bold>\n                    Waist to height ratio was the best predictor of MetS in older adults.\n                  <\/jats:p>","DOI":"10.2478\/rjim-2020-0026","type":"journal-article","created":{"date-parts":[[2020,9,7]],"date-time":"2020-09-07T09:07:02Z","timestamp":1599469622000},"page":"43-49","source":"Crossref","is-referenced-by-count":12,"title":["Comparison of anthropometric indices for predicting the risk of metabolic syndrome in older adults"],"prefix":"10.2478","volume":"59","author":[{"given":"Sara","family":"Khosravian","sequence":"first","affiliation":[{"name":"Student Research Committee , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Ali","family":"Bayani","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Reza","family":"Hosseini","sequence":"additional","affiliation":[{"name":"Social Determinants of Health Research Center, Health Research Institute , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Bijani","sequence":"additional","affiliation":[{"name":"Non-Communicable Pediatric Research Center, Health Research Institute , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simin","family":"Mouodi","sequence":"additional","affiliation":[{"name":"Social Determinants of Health Research Center, Health Research Institute , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reza","family":"Ghadimi","sequence":"additional","affiliation":[{"name":"Social Determinants of Health Research Center, Health Research Institute , Babol University of Medical Sciences , Babol , Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2021,3,5]]},"reference":[{"key":"2026042915193610678_j_rjim-2020-0026_ref_001_w2aab3b7b2b1b6b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"1. 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