Carlos Celis-Morales1, Donald M Lyall2, Yibing Guo1, Lewis Steell1, Daniel Llanas1, Joey Ward2, Daniel F Mackay2, Stephany M Biello3, Mark Es Bailey4, Jill P Pell2, Jason Mr Gill5. 1. BHF Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences. 2. Institute of Health and Wellbeing. 3. Institute of Neuroscience and Psychology, and. 4. School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom. 5. BHF Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, jason.gill@glasgow.ac.uk.
Abstract
Background: Obesity is a multifactorial condition influenced by genetics, lifestyle, and environment.Objective: We investigated whether the association of a validated genetic profile risk score for obesity (GPRS-obesity) with body mass index (BMI) and waist circumference (WC) was modified by sleep characteristics.Design: This study included cross-sectional data from 119,859 white European adults, aged 37-73 y, participating in the UK Biobank. Interactions of GPRS-obesity and sleep characteristics (sleep duration, chronotype, day napping, and shift work) with their effects on BMI and WC were investigated. Results: β Values are expressed as the change in BMI (in kg/m2) or WC per 1-SD increase in GPRS-obesity. The GPRS-obesity was associated with BMI (β: 0.57; 95% CI: 0.55, 0.60; P = 6.3 × 10-207) and WC (1.21 cm; 95% CI: 1.15, 1.28 cm; P = 4.2 × 10-289). There were significant interactions of GPRS-obesity and a variety of sleep characteristics with their relation with BMI (P-interaction < 0.05). In participants who slept <7 or >9 h daily, the effect of GPRS-obesity on BMI was stronger (β: 0.60; 95% CI: 0.54, 0.65 and β: 0.73; 95% CI: 0.49, 0.97, respectively) than in normal-length sleepers (7-9 h; β: 0.52; 95% CI: 0.49, 0.55). A similar pattern was observed for shift workers (β: 0.68; 95% CI: 0.59, 0.77 compared with β: 0.54; 95% CI: 0.51, 0.58 for non-shift workers) and for night-shift workers (β: 0.69; 95% CI: 0.56, 0.82 compared with β: 0.55; 95% CI: 0.51, 0.58 for non-night-shift workers), for those taking naps during the day (β: 0.65; 95% CI: 0.52, 0.78 compared with β: 0.51; 95% CI: 0.48, 0.55 for those who never or rarely had naps), and for those with a self-reported evening chronotype (β: 0.72; 95% CI: 0.61, 0.82 compared with β: 0.52; 95% CI: 0.47, 0.57 for morning chronotype). Similar findings were obtained by using WC as the outcome. Conclusion: This study shows that the association between genetic risk for obesity and phenotypic adiposity measures is exacerbated by adverse sleeping characteristics.
Background: Obesity is a multifactorial condition influenced by genetics, lifestyle, and environment.Objective: We investigated whether the association of a validated genetic profile risk score for obesity (GPRS-obesity) with body mass index (BMI) and waist circumference (WC) was modified by sleep characteristics.Design: This study included cross-sectional data from 119,859 white European adults, aged 37-73 y, participating in the UK Biobank. Interactions of GPRS-obesity and sleep characteristics (sleep duration, chronotype, day napping, and shift work) with their effects on BMI and WC were investigated. Results: β Values are expressed as the change in BMI (in kg/m2) or WC per 1-SD increase in GPRS-obesity. The GPRS-obesity was associated with BMI (β: 0.57; 95% CI: 0.55, 0.60; P = 6.3 × 10-207) and WC (1.21 cm; 95% CI: 1.15, 1.28 cm; P = 4.2 × 10-289). There were significant interactions of GPRS-obesity and a variety of sleep characteristics with their relation with BMI (P-interaction < 0.05). In participants who slept <7 or >9 h daily, the effect of GPRS-obesity on BMI was stronger (β: 0.60; 95% CI: 0.54, 0.65 and β: 0.73; 95% CI: 0.49, 0.97, respectively) than in normal-length sleepers (7-9 h; β: 0.52; 95% CI: 0.49, 0.55). A similar pattern was observed for shift workers (β: 0.68; 95% CI: 0.59, 0.77 compared with β: 0.54; 95% CI: 0.51, 0.58 for non-shift workers) and for night-shift workers (β: 0.69; 95% CI: 0.56, 0.82 compared with β: 0.55; 95% CI: 0.51, 0.58 for non-night-shift workers), for those taking naps during the day (β: 0.65; 95% CI: 0.52, 0.78 compared with β: 0.51; 95% CI: 0.48, 0.55 for those who never or rarely had naps), and for those with a self-reported evening chronotype (β: 0.72; 95% CI: 0.61, 0.82 compared with β: 0.52; 95% CI: 0.47, 0.57 for morning chronotype). Similar findings were obtained by using WC as the outcome. Conclusion: This study shows that the association between genetic risk for obesity and phenotypic adiposity measures is exacerbated by adverse sleeping characteristics.
Authors: C A Celis-Morales; D M Lyall; S R Gray; L Steell; J Anderson; S Iliodromiti; P Welsh; Y Guo; F Petermann; D F Mackay; M E S Bailey; J P Pell; J M R Gill; N Sattar Journal: Int J Obes (Lond) Date: 2017-07-24 Impact factor: 5.095
Authors: Penny Gordon-Larsen; John E French; Naima Moustaid-Moussa; Venkata S Voruganti; Elizabeth J Mayer-Davis; Christopher A Bizon; Zhiyong Cheng; Delisha A Stewart; John W Easterbrook; Saame Raza Shaikh Journal: Adv Nutr Date: 2021-10-01 Impact factor: 11.567