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Poster presentation
0147 Meta-analysis on night shift work and risk of metabolic syndrome
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  1. Feng Wang1,2,
  2. Liuzhuo Zhang3,
  3. Yanfang Zhang3,
  4. Bo Zhang1,
  5. Yonghua He1,
  6. Shaohua Xie1,
  7. Mengjie Li1,
  8. Xiaoping Miao4,
  9. Zhimin Li3,
  10. Ignatius Tak-sun Yu1,
  11. Lap Ah Tse1,2
  1. 1JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Sha Tin, Hong Kong
  2. 2Shenzhen Municipal Key Laboratory for Health Risk Analysis, Shenzhen Research Institute of the Chinese University of Hong Kong, Shenzhen, China
  3. 3Shenzhen Prevention and Treatment Center for Occupational Diseases, Shenzhen, China
  4. 4Department of Epidemiology and Biostatistics, Tongji School of Public Health, Huazhong University of Science and Technology, Wuhan, China

Abstract

Objectives This study aims to quantitatively summarise the association between night shift work and the risk of metabolic syndrome (MetS).

Method We systematically searched all observational studies published in English on Pubmed and Embase from 1971 to 2013. We extracted effect measures (relative risk, RR; or odd ratio, OR) with 95% confidence interval (CI) from individual studies to generate pooled results using meta-analysis approach. Pooled RR was calculated using random- or fixed effect model. Downs and Black scale was applied to assess the methodological quality of included studies.

Results A total of 13 studies were included in the meta-analysis. The pooled adjusted RR for the association between “ever exposed to night shift work” and MetS risk was 1.57 (95% CI = 1.24–1.98, pheterogeneity = 0.001). Further stratification analysis for gender, MetS definition and study population demonstrated similar trends. The sensitivity analysis confirmed the stability of the results and no publication bias was detected.

Conclusions The present meta-analysis suggests that night shift work is significantly associated with the risk of MetS, showing a positive dose-response relationship with the intensity of night shifts. Large-scale well-design prospective studies are required to further investigate the association, especially in Asia countries.[National Natural Science Foundation of China (Project number 81273172 and 81372964), Shelly@cuhk.edu.hk (Lap Ah Tse)]

https://doi.org/10.1136/oemed-2014-102362.244

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