{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T11:06:47Z","timestamp":1779188807377,"version":"3.51.4"},"reference-count":49,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Therapeutic Advances in Endocrinology"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Metabolic syndrome (MetS) is a common condition marked by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. It has significant health and economic impacts, highlighting the need for early predictive markers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To compare the prognostic performance of various obesity indices in the 1-year incidence of MetS among adult employees of a private educational institution.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design:<\/jats:title>\n                    <jats:p>Cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A prospective cohort study was conducted using data from adults employed at a private educational institution in Lima, Peru. Participants were enrolled in 2019 and followed for 1\u2009year to monitor anthropometric and biochemical parameters. The outcome was the development of MetS at the end of follow-up, defined according to the criteria of the Latin American Diabetes Association. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) with 95% confidence intervals (CI) was calculated to assess the predictive utility of each index for MetS after 1\u2009year.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Of the 792 adults initially enrolled, 475 were included in the final analysis after exclusions and loss to follow-up. Their average age was 38.4\u2009years, and 54.3% were women. The overall incidence of MetS was 7.4%, with 12% for males and 4% for females. The highest AUC values for predicting MetS were observed for the body mass index (AUC: 0.88; 95% CI: 0.84\u20130.92), waist-to-height ratio (WHtR; AUC: 0.89; 95% CI: 0.85\u20130.92), abdominal volume index (AVI; AUC: 0.89; 95% CI: 0.86\u20130.92), and body roundness index (BRI; AUC: 0.89; 95% CI: 0.85\u20130.92). In sex-stratified analyses, results were consistent for males. Among females, the body adiposity index also showed good discrimination (AUC: 0.91; 95% CI: 0.83\u20131.00). The wide 95% CI reflects the small number of incident MetS cases among women (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      \u2009=\u200910) and should be interpreted with caution.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>In conclusion, the incidence of MetS after 1\u2009year of follow-up was 7.4%, with a higher rate among males. The WHtR, BRI, and AVI were the most useful anthropometric indices for predicting MetS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20420188261428781","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T14:25:22Z","timestamp":1773239122000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Obesity indices as predictors of metabolic syndrome: 1-year findings from a Peruvian cohort of private educational institution workers"],"prefix":"10.1177","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9158-1108","authenticated-orcid":false,"given":"Vicente A.","family":"Benites-Zapata","sequence":"first","affiliation":[{"name":"Unidad de Investigaci\u00f3n para la Generaci\u00f3n de Evidencias en Salud, Universidad San Ignacio de Loyola, Av. la Fontana 750, La Molina, Lima 15024, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9441-1067","authenticated-orcid":false,"given":"Daniel","family":"Fernandez-Guzman","sequence":"additional","affiliation":[{"name":"Carrera de Medicina Humana, Universidad Cient\u00edfica del Sur, Lima, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0282-6634","authenticated-orcid":false,"given":"Percy","family":"Herrera-A\u00f1azco","sequence":"additional","affiliation":[{"name":"Carrera de Medicina Humana, Universidad Cient\u00edfica del Sur, Lima, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2297-0695","authenticated-orcid":false,"given":"Enrique","family":"Moncada-Mapelli","sequence":"additional","affiliation":[{"name":"Carrera de Medicina Humana, Universidad Cient\u00edfica del Sur, Lima, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8339-162X","authenticated-orcid":false,"given":"Diego","family":"Urrunaga-Pastor","sequence":"additional","affiliation":[{"name":"School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4664-2856","authenticated-orcid":false,"given":"Carlos J.","family":"Toro-Huamanchumo","sequence":"additional","affiliation":[{"name":"Unidad de Investigaci\u00f3n para la Generaci\u00f3n de Evidencias en Salud, Universidad San Ignacio de Loyola, Lima, Peru"},{"name":"OBEMET Center for Obesity and Metabolic Health, Lima, Peru"},{"name":"Nutrition and Health Innovation Research Institute, Edith Cowan University, Joondalup, WA, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,3,6]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11906-018-0812-z"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.5603\/AH.a2022.0012"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12877-022-03672-6"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.21149\/12835"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.21149\/spm.v56i2.7330"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmet.2023.02.003"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsx.2020.05.043"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsx.2020.07.018"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1590\/S1135-57272009000200009"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.35434\/rcmhnaaa.2024.172.2245"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2018.02.055"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-1079"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000012415"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10654-010-9459-z"},{"key":"e_1_3_4_16_2","article-title":"Economic impact of overweight and obesity to surpass $4 trillion by 2035","author":"World Obesity Federation","unstructured":"World Obesity Federation. 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