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This is a cross\u2010sectional study that enrolled secondary data of 937 men and women \u2265\u200918\u2009years assisted at Secondary Healthcare. Traditional markers of adiposity and cardiometabolic risk were waist circumference, body mass index, triglycerides, glucose, glycated hemoglobin, systolic (SBP) and diastolic (DBP) blood pressure, while the non\u2010traditional were deep\u2010abdominal\u2010adipose\u2010tissue index, visceral adiposity index (VAI), lipid accumulation product index, Castelli risk index 1 and 2, TG\/HDL\u2010c ratio, atherogenic index of plasma, and triglyceride\u2010glucose index (TyG index). Self\u2010reported habitual sleep durations were classified as short, recommended, or long according to the National Sleep Foundation. The prevalence ratios (PRs) were estimated by Poisson regression models, adjusted for potential confounders (\n                    <jats:italic>\u03b1<\/jats:italic>\n                    \u2009=\u20090.05). The prevalence of short and long sleep was 9.8% (5.9\u2009\u00b1\u20090.7\u2009h\/night) and 36.7% (10.5\u2009\u00b1\u20091.3\u2009h\/night), respectively. Short sleep was positively associated with abdominal obesity (PR: 1.15; 95% CI: 1.01\u20131.23), overweight (PR: 1.11; 95% CI: 1.00\u20131.24), high VAI (PR: 1.36; 95% CI: 1.04\u20131.77), high TyG index (PR: 1.44; 95% CI: 1.09\u20131.89), and high DBP (PR: 1.35; 95% CI: 1.07\u20131.72), regardless of confounders. No association between long sleep and cardiometabolic risk was found. In conclusion, individuals at high cardiovascular risk with short sleep duration are more likely to have adiposity\u2010related risk, insulin resistance, and diastolic blood pressure imbalance.\n                  <\/jats:p>","DOI":"10.1096\/fj.202602078rr","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T15:21:15Z","timestamp":1787930475000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Short Sleep Duration Is Positively Associated With Traditional and Non\u2010Traditional Markers of Adiposity and Cardiometabolic Risk in Individuals at Secondary Healthcare: A Cross\u2010Sectional Study"],"prefix":"10.1096","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4083-4400","authenticated-orcid":false,"given":"Nathallia Maria Cotta","family":"e Oliveira","sequence":"first","affiliation":[{"name":"Laboratory of Clinical Analysis and Genomics (LACEG); Laboratory of Energy Metabolism and Body Composition (LAMECC), Department of Nutrition and Health Universidade Federal de Vi\u00e7osa  Vi\u00e7osa Minas Gerais Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1932-6126","authenticated-orcid":false,"given":"Mariana De Santis","family":"Filgueiras","sequence":"additional","affiliation":[{"name":"Department of Nutrition and Health Universidade Federal de Vi\u00e7osa  Vi\u00e7osa Minas Gerais Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0363-0572","authenticated-orcid":false,"given":"Gilmara Alves","family":"Zanirate","sequence":"additional","affiliation":[{"name":"Laboratory of Clinical Analysis and Genomics (LACEG); 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