Muhammad Alsayid1, Mohammed Omer Khan1, Darbaz Adnan1,2, Heather E Rasmussen3, Ali Keshavarzian1,2, Faraz Bishehsari4,5. 1. Department of Internal Medicine, Division of Digestive Diseases and Nutrition, Rush University Medical Center, Chicago, IL, USA. 2. Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Professional Building, 1725 W. Harrison St. Suite 207, Chicago, IL, 60612, USA. 3. Department of Nutrition and Dietetics, University of Nebraska-Lincoln, Lincoln, NE, USA. 4. Department of Internal Medicine, Division of Digestive Diseases and Nutrition, Rush University Medical Center, Chicago, IL, USA. Faraz_Bishehsari@rush.edu. 5. Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Professional Building, 1725 W. Harrison St. Suite 207, Chicago, IL, 60612, USA. Faraz_Bishehsari@rush.edu.
Abstract
BACKGROUND: Metabolic dysfunction and obesity rates are on the rise. Although the central modes of circadian disruption has been studied in relation to the risk of obesity, the role of eating time has remained unclear. Here, we aimed to assess circadian behavioral phenotypes and their association with the risk of elevated body mass index (BMI). METHODS: This was a prospective cross-sectional study of individuals presenting for colorectal cancer screening colonoscopy. Participants completed demographic questionnaires, The Munich ChronoType Questionnaire (MCTQ), and Food Timing Screener (FTS). The primary outcome of the study was the association between circadian phenotypes and elevated BMI. RESULTS: A total of 488 individuals completed the survey, with a mean (SD) age of 57.5 (10.8) years. The mean body mass index (BMI) was 28.8 (6.1) kg/m2, with 72.3% of individuals met criteria for elevated BMI. Four circadian behavioral phenotypes were generated: early chronotype with regular food timing (ER) (34.7%), early chronotype with irregular food timing (EI) (11.7%), intermediate/late chronotype with regular food timing (LR) (33.9%), and intermediate/late chronotype with irregular food timing (LI) (19.7%). In a multivariable regression analysis, LI phenotype had 2.9 times higher odds of elevated BMI as compared to ER phenotype (OR 2.9, 95% CI 1.3-6.7, P = 0.01). CONCLUSION: The combination of late chronotype and irregular food timing, representative of a behavioral circadian rhythm disruption, is associated with higher rates of elevated BMI. The majority of individuals with this abnormal circadian phenotype were younger than 60 years old. This observation is especially relevant because of the ongoing rise in the obesity rates among young adults. LEVEL III: Evidence obtained from well-designed cohort or case-control analytic studies.
BACKGROUND: Metabolic dysfunction and obesity rates are on the rise. Although the central modes of circadian disruption has been studied in relation to the risk of obesity, the role of eating time has remained unclear. Here, we aimed to assess circadian behavioral phenotypes and their association with the risk of elevated body mass index (BMI). METHODS: This was a prospective cross-sectional study of individuals presenting for colorectal cancer screening colonoscopy. Participants completed demographic questionnaires, The Munich ChronoType Questionnaire (MCTQ), and Food Timing Screener (FTS). The primary outcome of the study was the association between circadian phenotypes and elevated BMI. RESULTS: A total of 488 individuals completed the survey, with a mean (SD) age of 57.5 (10.8) years. The mean body mass index (BMI) was 28.8 (6.1) kg/m2, with 72.3% of individuals met criteria for elevated BMI. Four circadian behavioral phenotypes were generated: early chronotype with regular food timing (ER) (34.7%), early chronotype with irregular food timing (EI) (11.7%), intermediate/late chronotype with regular food timing (LR) (33.9%), and intermediate/late chronotype with irregular food timing (LI) (19.7%). In a multivariable regression analysis, LI phenotype had 2.9 times higher odds of elevated BMI as compared to ER phenotype (OR 2.9, 95% CI 1.3-6.7, P = 0.01). CONCLUSION: The combination of late chronotype and irregular food timing, representative of a behavioral circadian rhythm disruption, is associated with higher rates of elevated BMI. The majority of individuals with this abnormal circadian phenotype were younger than 60 years old. This observation is especially relevant because of the ongoing rise in the obesity rates among young adults. LEVEL III: Evidence obtained from well-designed cohort or case-control analytic studies.
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Authors: Marie Ng; Tom Fleming; Margaret Robinson; Blake Thomson; Nicholas Graetz; Christopher Margono; Erin C Mullany; Stan Biryukov; Cristiana Abbafati; Semaw Ferede Abera; Jerry P Abraham; Niveen M E Abu-Rmeileh; Tom Achoki; Fadia S AlBuhairan; Zewdie A Alemu; Rafael Alfonso; Mohammed K Ali; Raghib Ali; Nelson Alvis Guzman; Walid Ammar; Palwasha Anwari; Amitava Banerjee; Simon Barquera; Sanjay Basu; Derrick A Bennett; Zulfiqar Bhutta; Jed Blore; Norberto Cabral; Ismael Campos Nonato; Jung-Chen Chang; Rajiv Chowdhury; Karen J Courville; Michael H Criqui; David K Cundiff; Kaustubh C Dabhadkar; Lalit Dandona; Adrian Davis; Anand Dayama; Samath D Dharmaratne; Eric L Ding; Adnan M Durrani; Alireza Esteghamati; Farshad Farzadfar; Derek F J Fay; Valery L Feigin; Abraham Flaxman; Mohammad H Forouzanfar; Atsushi Goto; Mark A Green; Rajeev Gupta; Nima Hafezi-Nejad; Graeme J Hankey; Heather C Harewood; Rasmus Havmoeller; Simon Hay; Lucia Hernandez; Abdullatif Husseini; Bulat T Idrisov; Nayu Ikeda; Farhad Islami; Eiman Jahangir; Simerjot K Jassal; Sun Ha Jee; Mona Jeffreys; Jost B Jonas; Edmond K Kabagambe; Shams Eldin Ali Hassan Khalifa; Andre Pascal Kengne; Yousef Saleh Khader; Young-Ho Khang; Daniel Kim; Ruth W Kimokoti; Jonas M Kinge; Yoshihiro Kokubo; Soewarta Kosen; Gene Kwan; Taavi Lai; Mall Leinsalu; Yichong Li; Xiaofeng Liang; Shiwei Liu; Giancarlo Logroscino; Paulo A Lotufo; Yuan Lu; Jixiang Ma; Nana Kwaku Mainoo; George A Mensah; Tony R Merriman; Ali H Mokdad; Joanna Moschandreas; Mohsen Naghavi; Aliya Naheed; Devina Nand; K M Venkat Narayan; Erica Leigh Nelson; Marian L Neuhouser; Muhammad Imran Nisar; Takayoshi Ohkubo; Samuel O Oti; Andrea Pedroza; Dorairaj Prabhakaran; Nobhojit Roy; Uchechukwu Sampson; Hyeyoung Seo; Sadaf G Sepanlou; Kenji Shibuya; Rahman Shiri; Ivy Shiue; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Nicolas J C Stapelberg; Lela Sturua; Bryan L Sykes; Martin Tobias; Bach X Tran; Leonardo Trasande; Hideaki Toyoshima; Steven van de Vijver; Tommi J Vasankari; J Lennert Veerman; Gustavo Velasquez-Melendez; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Theo Vos; Claire Wang; XiaoRong Wang; Elisabete Weiderpass; Andrea Werdecker; Jonathan L Wright; Y Claire Yang; Hiroshi Yatsuya; Jihyun Yoon; Seok-Jun Yoon; Yong Zhao; Maigeng Zhou; Shankuan Zhu; Alan D Lopez; Christopher J L Murray; Emmanuela Gakidou Journal: Lancet Date: 2014-05-29 Impact factor: 79.321