Gerben Hulsegge1,2, H Susan J Picavet2, Allard J van der Beek1, W M Monique Verschuren2,3, Jos W Twisk4, Karin I Proper2. 1. Department of Public and Occupational Health, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands. 2. Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. 3. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. 4. Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
Abstract
Background: The relation between shift work and a large variety of cardiometabolic risk factors is unclear. Also, the role of chronotype is understudied. We examined relations between shift work and cardiometabolic risk factors, and explored these relations in different chronotypes. Methods: Cardiometabolic risk factors (anthropometry, blood pressure, lipids, diabetes, γ-glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate) were assessed among 1334 adults in 1987-91, with repeated measurements every 5 years. Using shift work history data collected in 2013-15, we identified shift work status 1 year prior to all six waves. Linear mixed models and logistic generalized estimating equations were used to estimate the longitudinal relations between shift work and risk factors 1 year later. Results: Shift work was not significantly related with cardiometabolic risk factors (P ≥ 0.05), except for overweight/body mass index. Shift workers had more often overweight (OR: 1.44, 95% CI 1.06-1.95) and a higher body mass index (BMI) (β: 0.56 kg m-2, 95% CI 0.10-1.03) than day workers. A significant difference in BMI between day and shift workers was observed among evening chronotypes (β: 0.97 kg m-2, 95% CI 0.21-1.73), but not among morning chronotypes (β: 0.04 kg m-2, 95% CI -0.85 to 0.93). No differences by frequency of night shifts and duration of shift work were observed. Conclusion: Shift workers did not have an increased risk of cardiometabolic risk factors compared with day workers, but, in particular shift working evening chronotypes, had an increased risk of overweight. More research is needed to verify our results, and establish whether tailored interventions by chronotype are wanted.
Background: The relation between shift work and a large variety of cardiometabolic risk factors is unclear. Also, the role of chronotype is understudied. We examined relations between shift work and cardiometabolic risk factors, and explored these relations in different chronotypes. Methods: Cardiometabolic risk factors (anthropometry, blood pressure, lipids, diabetes, γ-glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate) were assessed among 1334 adults in 1987-91, with repeated measurements every 5 years. Using shift work history data collected in 2013-15, we identified shift work status 1 year prior to all six waves. Linear mixed models and logistic generalized estimating equations were used to estimate the longitudinal relations between shift work and risk factors 1 year later. Results: Shift work was not significantly related with cardiometabolic risk factors (P ≥ 0.05), except for overweight/body mass index. Shift workers had more often overweight (OR: 1.44, 95% CI 1.06-1.95) and a higher body mass index (BMI) (β: 0.56 kg m-2, 95% CI 0.10-1.03) than day workers. A significant difference in BMI between day and shift workers was observed among evening chronotypes (β: 0.97 kg m-2, 95% CI 0.21-1.73), but not among morning chronotypes (β: 0.04 kg m-2, 95% CI -0.85 to 0.93). No differences by frequency of night shifts and duration of shift work were observed. Conclusion: Shift workers did not have an increased risk of cardiometabolic risk factors compared with day workers, but, in particular shift working evening chronotypes, had an increased risk of overweight. More research is needed to verify our results, and establish whether tailored interventions by chronotype are wanted.
Authors: Christian Moretti Anfossi; Magdalena Ahumada Muñoz; Christian Tobar Fredes; Felipe Pérez Rojas; Jamie Ross; Jenny Head; Annie Britton Journal: Ann Work Expo Health Date: 2022-07-02 Impact factor: 2.779
Authors: Maaike Schilperoort; Rosa van den Berg; Martijn E T Dollé; Conny T M van Oostrom; Karina Wagner; Lauren L Tambyrajah; Paul Wackers; Tom Deboer; Gerben Hulsegge; Karin I Proper; Harry van Steeg; Till Roenneberg; Nienke R Biermasz; Patrick C N Rensen; Sander Kooijman; Linda W M van Kerkhof Journal: Sci Rep Date: 2019-05-27 Impact factor: 4.379
Authors: Alexandra Hemmer; Julie Mareschal; Charna Dibner; Jacques A Pralong; Victor Dorribo; Stephen Perrig; Laurence Genton; Claude Pichard; Tinh-Hai Collet Journal: Nutrients Date: 2021-11-22 Impact factor: 5.717
Authors: Karin I Proper; Eva Jaarsma; Suzan J W Robroek; Jolinda L D Schram; Hendriek Boshuizen; H Susan J Picavet; W M Monique Verschuren; Sandra H van Oostrom Journal: BMC Public Health Date: 2021-07-02 Impact factor: 3.295
Authors: Jennifer Cable; Eva Schernhammer; Erin C Hanlon; Céline Vetter; Jonathan Cedernaes; Nour Makarem; Hassan S Dashti; Ari Shechter; Christopher Depner; Ashley Ingiosi; Christine Blume; Xiao Tan; Elie Gottlieb; Christian Benedict; Eve Van Cauter; Marie-Pierre St-Onge Journal: Ann N Y Acad Sci Date: 2021-08-02 Impact factor: 6.499