Xingjin Yang1, Wencheng Di2, Yunhong Zeng3, Dechen Liu4, Minghui Han1, Ranran Qie1, Shengbing Huang1, Yang Zhao1, Yifei Feng1, Dongsheng Hu5, Liang Sun6. 1. Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. 2. Department of Cardiology, Shenzhen Third People's Hospital, Shenzhen, Guangdong, People's Republic of China. 3. Center for Health Management, Shenzhen Hospital of University of Chinese Academy of Science, Shenzhen, Guangdong, People's Republic of China. 4. Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China; Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China. 5. Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. Electronic address: dongshenghu563@126.com. 6. Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. Electronic address: zzusunl@163.com.
Abstract
AIMS: A comprehensive assessment of the association of shift work with risk of metabolic syndrome (MetS) through a systematic review and meta-analysis has not been reported. We aimed to evaluate the relationship from observational studies. DATA SYNTHESIS: We searched PubMed, Embase, and Web of Science databases from inception to December 16, 2020. Articles were chosen according to established inclusion criteria. Studies with data on men and women and different types of shift work were treated as independent studies. Relative risks (RRs) and 95% confidence intervals (CIs) were pooled by using random-effects models with heterogeneity (I2) > 50%; otherwise, a fixed-effects model was used. A total of 7192 articles was searched from PubMed, Embase and Web of science. Finally, we included 23 articles (38 studies) in this meta-analysis. The pooled RRs and 95% CI of MetS risk with shift work, 1-shift work, 2-shift work, and 3-shift work versus non-shift work were 1.30 (95% CI 1.19-1.41), 0.95 (95% CI 0.82-1.11), 1.19 (95% CI 0.91-1.56) and 1.17 (95% CI 1.00-1.37), respectively. The results from subgroup analyses stratified by sex, age, and region supported our overall findings that shift work is a risk factor for MetS. CONCLUSIONS: This meta-analysis suggests that shift work increases risk of MetS. Higher risk of MetS was found in the shift workers who were 2-shift or 3-shift or women or Asian workers.
AIMS: A comprehensive assessment of the association of shift work with risk of metabolic syndrome (MetS) through a systematic review and meta-analysis has not been reported. We aimed to evaluate the relationship from observational studies. DATA SYNTHESIS: We searched PubMed, Embase, and Web of Science databases from inception to December 16, 2020. Articles were chosen according to established inclusion criteria. Studies with data on men and women and different types of shift work were treated as independent studies. Relative risks (RRs) and 95% confidence intervals (CIs) were pooled by using random-effects models with heterogeneity (I2) > 50%; otherwise, a fixed-effects model was used. A total of 7192 articles was searched from PubMed, Embase and Web of science. Finally, we included 23 articles (38 studies) in this meta-analysis. The pooled RRs and 95% CI of MetS risk with shift work, 1-shift work, 2-shift work, and 3-shift work versus non-shift work were 1.30 (95% CI 1.19-1.41), 0.95 (95% CI 0.82-1.11), 1.19 (95% CI 0.91-1.56) and 1.17 (95% CI 1.00-1.37), respectively. The results from subgroup analyses stratified by sex, age, and region supported our overall findings that shift work is a risk factor for MetS. CONCLUSIONS: This meta-analysis suggests that shift work increases risk of MetS. Higher risk of MetS was found in the shift workers who were 2-shift or 3-shift or women or Asian workers.
Authors: Annina Ropponen; Mo Wang; Auriba Raza; Jurgita Narusyte; Pia Svedberg Journal: Int J Environ Res Public Health Date: 2022-08-31 Impact factor: 4.614