, Volume 47, Issue 2, pp 421–427 | Cite as

Passive smoke exposure and risk of diabetes: a meta-analysis of prospective studies

  • Kan Sun
  • Dan Liu
  • Chuan Wang
  • Men Ren
  • Chuan Yang
  • Li Yan


Epidemiological evidence suggests that passive smoke exposure is related to the development of diabetes. However, data on this issue are controversial. We conducted a meta-analysis to provide a quantitative assessment of the association between passive smoking and the risk of diabetes. We searched the Medline and Embase databases up to October 2013 to identify prospective cohort studies related to passive smoke exposure and incident diabetes. Summary effect estimates with 95 % confidence intervals (CI) were derived using a fixed or random effects model, depending on the heterogeneity of the included studies. Six prospective studies that span three continents involving 154,406 participants (ages 18–74) with 7,116 new diabetes cases were included in the meta-analysis. On the basis of the Newcastle Ottawa Scale system, five studies were identified as relatively high-quality. In our primary analysis, compared to never smokers without passive smoke exposure, never smokers reporting passive smoke exposure was associated with increased risk of diabetes (pooled relative risk 1.21, 95 % CI 1.07–1.38). Such association persisted in the dose–response analysis. No indications of significant heterogeneity and publication bias were detected. Estimates of total effects were generally consistent in the sensitivity and subgroup analyses. Findings of the present meta-analysis suggest that passive smoke exposure is independently associated with the risk of diabetes. The conclusion may have a far-reaching significance for public health in countries of high smoking intensity and high incident diabetes.


Passive smoke exposure Diabetes Prospective cohort study Meta-analysis 



This work was supported by Grants from the National Natural Science Foundation of China (81270916, 81000317 and 81170766). The funders were not involved in study design, data collection, data analysis, manuscript preparation and/or publication decisions.

Conflict of interest

All of the authors have no relevant conflict of interests.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Kan Sun
    • 1
  • Dan Liu
    • 1
  • Chuan Wang
    • 1
  • Men Ren
    • 1
  • Chuan Yang
    • 1
  • Li Yan
    • 1
  1. 1.Department of EndocrinologySun Yat-sen Memorial Hospital, Sun Yat-sen UniversityGuangzhouPeople’s Republic of China

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