{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:29:30Z","timestamp":1784204970031,"version":"3.55.0"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T00:00:00Z","timestamp":1749600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004772","name":"Natural Science Foundation of Ningxia Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004772","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>This study aimed to develop and validate models for identifying individuals at high risk for metabolic syndrome (MetS) and pre-MetS using easily collectible indices.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A cross-sectional analysis was conducted using data from the Ningxia Cardiovascular Disorders Survey (NCDS) in China, collected between January 2020 and December 2021. The study population comprised 10,520 participants with complete demographic, anthropometric, and laboratory data. The diagnostic models for MetS were developed using five easily collectible indicators. The performance of the models was compared with that of Lipid Accumulation Product (LAP), Triglyceride-Glucose (TyG) Index, and Waist-to-Height Ratio (WHtR). These same models were subsequently applied to pre-MetS detection as a secondary analysis. Area under the receiver operating characteristic curve (AUC), Hosmer and Lemeshow test, bootstrap method, Brier score and Decision Curve Analysis were employed to evaluate the performance of the models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Model 1 comprised factors such as WC, SBP, DBP and gender. In contrast, Model 2 included all the variables from Model 1 while additionally incorporating FPG. In the training set, the AUC for Model 1 and Model 2 were 0.914 and 0.924, respectively. The AUC for Model 1 and Model 2 in identifying the presence of pre-MetS and MetS conditions were 0.883 and 0.902, respectively. In the external validation set, the AUC for Model 1 and Model 2 in identifying the presence of MetS were 0.929 and 0.934, respectively. For detecting pre-MetS and MetS conditions, the AUC for Model 1 and Model 2 were 0.885 and 0.902, respectively. Compared to TyG, LAP, and WHtR, model 1 and 2 exhibited a superior ability to identify MetS as well as pre-MetS and MetS conditions in both the training and validation sets.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Our models offered an easy, accurate and efficient tool for identifying MetS and pre-MetS, which might be used in large-scale population screening or self-health management at home.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1587354","type":"journal-article","created":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T05:14:17Z","timestamp":1749618857000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Using easy-to-collect indices to develop and validate models for identifying metabolic syndrome and pre-metabolic syndrome"],"prefix":"10.3389","volume":"16","author":[{"given":"Chao","family":"Shi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yin","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lanqiqi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongjuan","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yining","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinyu","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huitian","family":"Tong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(05)66378-7","article-title":"The metabolic syndrome","volume":"365","author":"Eckel","year":"2005","journal-title":"Lancet"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0199293","article-title":"Metabolic syndrome prevalence and its risk factors among adults in China: A nationally representative cross-sectional study","volume":"13","author":"Li","year":"2018","journal-title":"PLoS One"},{"key":"B3","doi-asserted-by":"publisher","first-page":"6988","DOI":"10.1038\/s41467-023-42423-y","article-title":"Development and validation of an age-sex-ethnicity-specific metabolic syndrome score in the Chinese adults","volume":"14","author":"Yang","year":"2023","journal-title":"Nat Commun"},{"key":"B4","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1016\/j.cmet.2023.02.003","article-title":"The global burden of metabolic disease: Data from 2000 to 2019","volume":"35","author":"Chew","year":"2023","journal-title":"Cell Metab"},{"key":"B5","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s11906-018-0812-z","article-title":"The global epidemic of the metabolic syndrome","volume":"20","author":"Saklayen","year":"2018","journal-title":"Curr Hypertens Rep"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23020786","article-title":"Metabolic syndrome: updates on pathophysiology and management in 2021","volume":"23","author":"Fahed","year":"2022","journal-title":"Int J Mol Sci"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BF02912872","article-title":"Metabolic syndrome: Early identification prevents type II diabetes and cardiovascular disease","volume":"22","author":"Sharma","year":"2007","journal-title":"Indian J Clin Biochem"},{"key":"B8","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1007\/s12020-023-03642-x","article-title":"Mechanisms and risk factors of metabolic syndrome in children and adolescents","volume":"84","author":"Codazzi","year":"2024","journal-title":"Endocrine"},{"key":"B9","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1186\/s12933-024-02379-9","article-title":"Association of metabolic syndrome severity with frailty progression among Chinese middle and old-aged adults: a longitudinal study","volume":"23","author":"Zeng","year":"2024","journal-title":"Cardiovasc Diabetol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.3389\/fnut.2024.1436652","article-title":"Associations between metabolic score for visceral fat and adult lung functions from NHANES 2007-2012","volume":"11","author":"Zhou","year":"2024","journal-title":"Front Nutr"},{"key":"B11","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1038\/s41572-024-00563-5","article-title":"Metabolic syndrome","volume":"10","author":"Neeland","year":"2024","journal-title":"Nat Rev Dis Primers"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S","article-title":"Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation","volume":"15","author":"Alberti","year":"1998","journal-title":"Diabetes Med"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1001\/jama.285.19.2486","article-title":"Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults","volume":"285","year":"2001","journal-title":"JAMA"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1161\/circ.106.25.3143","article-title":"National cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III)","volume":"106","year":"2002","journal-title":"Circulation"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1111\/j.1464-5491.2006.01858.x","article-title":"Metabolic syndrome\u2013a new world-wide definition. A Consensus Statement from the International Diabetes Federation","volume":"23","author":"Alberti","year":"2006","journal-title":"Diabetes Med"},{"key":"B16","doi-asserted-by":"publisher","first-page":"22210","DOI":"10.1038\/srep22210","article-title":"Establishment and application of a new diagnostic definition of metabolic syndrome in the Shantou region of southern China","volume":"6","author":"Ding","year":"2016","journal-title":"Sci Rep"},{"key":"B17","doi-asserted-by":"publisher","first-page":"2598","DOI":"10.3390\/nu11112598","article-title":"The usefulness of anthropometric indices to identify the risk of metabolic syndrome","volume":"11","author":"Suliga","year":"2019","journal-title":"Nutrients"},{"key":"B18","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/s12902-020-0510-0","article-title":"Identification of metabolic syndrome using phenotypes consisting of triglyceride levels with anthropometric indices in Korean adults","volume":"20","author":"Lee","year":"2020","journal-title":"BMC Endocr Disord"},{"key":"B19","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s12986-020-00536-x","article-title":"Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight\/obese adults","volume":"18","author":"Wu","year":"2021","journal-title":"Nutr Metab (Lond)"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.889785","article-title":"Association between four anthropometric indexes and metabolic syndrome in US adults","volume":"13","author":"Li","year":"2022","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B21","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1186\/1471-2261-12-78","article-title":"Lipid accumulation product: a simple and accurate index for predicting metabolic syndrome in Taiwanese people aged 50 and over","volume":"12","author":"Chiang","year":"2012","journal-title":"BMC Cardiovasc Disord"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1016\/j.clnu.2016.12.020","article-title":"The lipid accumulation product is a powerful tool to predict metabolic syndrome in undiagnosed Brazilian adults","volume":"36","author":"Nascimento-Ferreira","year":"2017","journal-title":"Clin Nutr"},{"key":"B23","doi-asserted-by":"publisher","first-page":"101941","DOI":"10.1016\/j.pmedr.2022.101941","article-title":"Triglyceride glucose index: A new biomarker in predicting cardiovascular risk","volume":"29","author":"Ara\u00fajo","year":"2022","journal-title":"Prev Med Rep"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.2196\/57799","article-title":"Utility of anthropometric indexes for detecting metabolic syndrome in resource-limited regions of Northwestern China: cross-sectional study","volume":"10","author":"Yang","year":"2024","journal-title":"JMIR Public Health Surveill"},{"key":"B25","doi-asserted-by":"publisher","first-page":"101109","DOI":"10.1016\/j.xcrm.2023.101109","article-title":"Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome","volume":"4","author":"Chen","year":"2023","journal-title":"Cell Rep Med"},{"key":"B26","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1186\/s12944-024-02138-5","article-title":"Association between metabolic syndrome and kidney cancer risk: a prospective cohort study","volume":"23","author":"Wang","year":"2024","journal-title":"Lipids Health Dis"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1007\/s00592-015-0715-2","article-title":"Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype","volume":"52","author":"Du","year":"2015","journal-title":"Acta Diabetol"},{"key":"B28","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1186\/s12933-022-01511-x","article-title":"Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations","volume":"21","author":"Tao","year":"2022","journal-title":"Cardiovasc Diabetol"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2015-010159","article-title":"Waist-to-height ratio as an indicator of \u2018early health risk\u2019: simpler and more predictive than using a \u2018matrix\u2019 based on BMI and waist circumference","volume":"6","author":"Ashwell","year":"2016","journal-title":"BMJ Open"},{"key":"B30","doi-asserted-by":"publisher","first-page":"1730","DOI":"10.1186\/s12889-022-14122-8","article-title":"Comparison of obesity-related indicators for identifying metabolic syndrome among normal-weight adults in rural Xinjiang, China","volume":"22","author":"Jian","year":"2022","journal-title":"BMC Public Health"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1201132","article-title":"Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study","volume":"14","author":"Li","year":"2023","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.31729\/jnma.4247","article-title":"Accuracy of glucose meter among adults in a semi-urban area in Kathmandu, Nepal","volume":"57","author":"Pokhrel","year":"2019","journal-title":"JNMA J Nepal Med Assoc"},{"key":"B33","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1186\/s12902-022-00948-1","article-title":"Using noninvasive anthropometric indices to develop and validate a predictive model for metabolic syndrome in Chinese adults: a nationwide study","volume":"22","author":"Xu","year":"2022","journal-title":"BMC Endocr Disord"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1038\/s41390-024-03247-8","article-title":"Evaluating eight indicators for identifying metabolic syndrome in Chinese and American adolescents","volume":"96","author":"Hu","year":"2024","journal-title":"Pediatr Res"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13249","article-title":"Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test","volume":"76","author":"Nattino","year":"2020","journal-title":"Biometrics"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13255","article-title":"Discussion of \u201cAssessing the goodness-of-fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test,\u201d by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow","volume":"76","author":"Chen","year":"2020","journal-title":"Biometrics"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.109.192644","article-title":"Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity","volume":"120","author":"Alberti","year":"2009","journal-title":"Circulation"}],"container-title":["Frontiers in Endocrinology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2025.1587354\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T05:14:18Z","timestamp":1749618858000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2025.1587354\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,11]]},"references-count":37,"alternative-id":["10.3389\/fendo.2025.1587354"],"URL":"https:\/\/doi.org\/10.3389\/fendo.2025.1587354","relation":{},"ISSN":["1664-2392"],"issn-type":[{"value":"1664-2392","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,11]]},"article-number":"1587354"}}