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. 2025 Mar 1;36(2):245-252.
doi: 10.1097/EDE.0000000000001807. Epub 2023 Oct 22.

Socioeconomic Status, Smoking, and Lung Cancer: Mediation and Bias Analysis in the SYNERGY Study

Jan Hovanec  1 , Benjamin Kendzia  1 , Ann Olsson  2 , Joachim Schüz  2 , Hans Kromhout  3 , Roel Vermeulen  3 , Susan Peters  3 , Per Gustavsson  4 , Enrica Migliore  5 , Loredana Radoi  6 , Christine Barul  7 , Dario Consonni  8 , Neil E Caporaso  9 , Maria Teresa Landi  9 , John K Field  10 , Stefan Karrasch  11   12 , Heinz-Erich Wichmann  11 , Jack Siemiatycki  13 , Marie-Elise Parent  14 , Lorenzo Richiardi  5 , Lorenzo Simonato  15 , Karl-Heinz Jöckel  16 , Wolfgang Ahrens  17 , Hermann Pohlabeln  17 , Guillermo Fernández-Tardón  18 , David Zaridze  19 , John R McLaughlin  20 , Paul A Demers  21 , Beata Świątkowska  22 , Jolanta Lissowska  23 , Tamás Pándics  24 , Eleonora Fabianova  25 , Dana Mates  26 , Miriam Schejbalova  27 , Lenka Foretova  28 , Vladimír Janout  29 , Paolo Boffetta  30   31   32 , Francesco Forastiere  33   34 , Kurt Straif  35   36 , Thomas Brüning  1 , Thomas Behrens  1
Affiliations

Socioeconomic Status, Smoking, and Lung Cancer: Mediation and Bias Analysis in the SYNERGY Study

Jan Hovanec et al. Epidemiology. .

Abstract

Background: Increased lung cancer risks for low socioeconomic status (SES) groups are only partially attributable to smoking habits. Little effort has been made to investigate the persistent risks related to low SES by quantification of potential biases.

Methods: Based on 12 case-control studies, including 18 centers of the international SYNERGY project (16,550 cases, 20,147 controls), we estimated controlled direct effects (CDE) of SES on lung cancer via multiple logistic regression, adjusted for age, study center, and smoking habits and stratified by sex. We conducted mediation analysis by inverse odds ratio weighting to estimate natural direct effects and natural indirect effects via smoking habits. We considered misclassification of smoking status, selection bias, and unmeasured mediator-outcome confounding by genetic risk, both separately and by multiple quantitative bias analyses, using bootstrap to create 95% simulation intervals (SI).

Results: Mediation analysis of lung cancer risks for SES estimated mean proportions of 43% in men and 33% in women attributable to smoking. Bias analyses decreased the direct effects of SES on lung cancer, with selection bias showing the strongest reduction in lung cancer risk in the multiple bias analysis. Lung cancer risks remained increased for lower SES groups, with higher risks in men (fourth vs. first [highest] SES quartile: CDE, 1.50 [SI, 1.32, 1.69]) than women (CDE: 1.20 [SI: 1.01, 1.45]). Natural direct effects were similar to CDE, particularly in men.

Conclusions: Bias adjustment lowered direct lung cancer risk estimates of lower SES groups. However, risks for low SES remained elevated, likely attributable to occupational hazards or other environmental exposures.

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Conflict of interest statement

Disclosure: The authors do not declare any conflict of interest. J.H., B.K., T. Brüning, and T. Behrens, as staff of the Institute for Prevention and Occupational Medicine (IPA), are employed by the study’s main financing body, the German Social Accident Insurance. IPA is an independent research institute of the Ruhr-University Bochum. The authors are independent of the German Social Accident Insurance in study design, access to the collected data, responsibility for data analysis and interpretation, and the right to publish. The views expressed in this article are those of the authors and not necessarily those of the sponsor. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policies, or views of the International Agency for Research on Cancer/World Health Organization.

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