Effect of passive smoking exposure on risk of type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies

Front Endocrinol (Lausanne). 2023 Jul 31:14:1195354. doi: 10.3389/fendo.2023.1195354. eCollection 2023.

Abstract

Objective: The effect of passive smoking exposure on the risk of type 2 diabetes has not been systematically studied. A meta-analysis was conducted to assess the association between passive smoking exposure and the risk of diabetes.

Methods: We searched three major databases up to 31 October 2022 to identify relevant prospective cohort studies on the association between passive smoking and the risk of type 2 diabetes. The pooled relative risk (RR) and 95% confidence interval (CI) for the association between passive smoking exposure and the risk of type 2 diabetes were analyzed using a fixed-effect model.

Results: Ten prospective cohort studies were included in this meta-analysis, with a total of 251,620 participants involved. The pooled RR showed a significantly positive association between nonsmokers exposed to passive smoking and type 2 diabetes as compared to non-smokers who were not exposed to passive smoking [RR = 1.27; 95% CI (1.19, 1.36); p < 0.001]. Sensitivity analysis indicated that the pooled RR was not substantially affected by any of the individual studies.

Conclusion: Exposure to passive smoking increases the risk of type 2 diabetes. This study may have a positive effect on the prevention of type 2 diabetes.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023372532.

Keywords: meta-analysis; passive smoking; prospective cohort studies; relative risk; type 2 diabetes.

Publication types

  • Meta-Analysis
  • Systematic Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Factual
  • Diabetes Mellitus, Type 2* / epidemiology
  • Diabetes Mellitus, Type 2* / etiology
  • Humans
  • Prospective Studies
  • Tobacco Smoke Pollution* / adverse effects

Substances

  • Tobacco Smoke Pollution

Grants and funding

This work was supported by the National Key Research and Development Program of China (2021YFA1301202), National Natural Science Foundation of China (82273676), Liaoning Province Scientific and Technological Project (2021JH2/10300039). Major Research Plan of National Natural Science Foundation of China (Grant No.92163213) and General Program of National Natural Science Foundation of China (Grant No. 81970085).