{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T12:43:44Z","timestamp":1775479424389,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background\/Objectives: Obesity is a major contributor to cardiovascular disease, yet traditional risk assessment methods may overlook behavioral and circadian influences that modulate metabolic health. Chronotype, physical activity, sleep quality, eating speed, and breakfast habits have been increasingly associated with cardiometabolic outcomes. This study aims to evaluate the associations between these behavioral factors and both anthropometric and biochemical markers of cardiovascular risk among obese candidates for bariatric surgery. Methods: A cross-sectional study was conducted in a sample of 286 obese adults (78.3% females, mean 44.3 years, SD = 10.8, mean BMI = 42.5 kg\/m2, SD = 6.2) followed at a central Portuguese hospital. Chronotype (reduced Morningness\u2013Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), physical activity (Godin\u2013Shephard Questionnaire), eating speed, and breakfast skipping were assessed. Cardiovascular risk markers included waist-to-hip ratio (WHR), waist-to-height ratio, A Body Shape Index (ABSI), Body Roundness Index, atherogenic index of plasma (AIP), triglyceride\u2013glucose index (TyG), and homeostatic model assessment for insulin resistance (HOMA-IR). Results: Men exhibited significantly higher WHR, ABSI, HOMA-IR, TyG, and AIP. Eveningness was associated with higher insulin (r = \u22120.168, p = 0.006) and HOMA-IR (r = \u22120.156, p = 0.011). Poor sleep quality was associated with higher body fat mass (r = 0.151, p = 0.013), total cholesterol (r = 0.169, p = 0.005) and LDL cholesterol (r = 0.132, p = 0.030). Faster eating speed was associated with a higher waist circumference (r = 0.123, p = 0.038) and skeletal muscle mass (r = 0.160, p = 0.009). Conclusions: Male sex, evening chronotype, and poor sleep quality were associated with more adverse cardiometabolic profiles in individuals with severe obesity. These findings support the integration of behavioral and circadian factors into cardiovascular risk assessment strategies.<\/jats:p>","DOI":"10.3390\/nu17111858","type":"journal-article","created":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T07:46:26Z","timestamp":1748504786000},"page":"1858","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Chronotype, Lifestyles, and Anthropometric and Biochemical Indices for Cardiovascular Risk Assessment Among Obese Individuals"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-0834-2828","authenticated-orcid":false,"given":"Margarida","family":"Raba\u00e7a Alexandre","sequence":"first","affiliation":[{"name":"Faculty of Nutrition and Food Sciences, University of Porto, 4150-180 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9177-6423","authenticated-orcid":false,"given":"Rui","family":"Po\u00ednhos","sequence":"additional","affiliation":[{"name":"Faculty of Nutrition and Food Sciences, University of Porto, 4150-180 Porto, Portugal"},{"name":"Department of Biology and Environment, School of Life and Environmental Sciences, University of Tr\u00e1s-os-Montes e Alto Douro (ECVA, UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal"}]},{"name":"CRI-O Group","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7710-4284","authenticated-orcid":false,"given":"Bruno M. P. M.","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Faculty of Nutrition and Food Sciences, University of Porto, 4150-180 Porto, Portugal"},{"name":"Laboratory of Artificial Intelligence and Decision Support, Institute for Systems and Computer Engineering, Technology and Science (LIAAD, INESC-TEC), 4200-465 Porto, Portugal"}]},{"given":"Flora","family":"Correia","sequence":"additional","affiliation":[{"name":"Universidade Lus\u00f3fona\u2019s Research Center for Biosciences & Health Technologies (CBIOS), Campo Grande 376, 1749-024 Lisboa, Portugal"},{"name":"Portuguese Society of Nutrition and Food Sciences (SPCNA), 4200-401 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,29]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (WHO) (2025, April 11). Obesity and Overweight. Fact Sheets. 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