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

. 2025 Mar 01 ; 36 (2) : 245-252. [epub] 20231022

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid39435907

Grantová podpora
001 World Health Organization - International
N02 CP001006 NCI NIH HHS - United States

Odkazy

PubMed 39435907
PubMed Central PMC12684412
DOI 10.1097/ede.0000000000001807
PII: 00001648-990000000-00308
Knihovny.cz E-zdroje

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.

Boston College Chestnut Hill MA

Cancer Epidemiology Unit Department of Medical Sciences University of Turin Turin Italy

Center for Research in Epidemiology and Population Health Team Exposome and Heredity U1018 Inserm University Paris Saclay University Paris Cité Villejuif France

Dalla Lana School of Public Health University of Toronto Toronto Canada

Department of Cancer Epidemiology and Prevention Maria Sklodowska Curie National Research Institute of Oncology Warsaw Poland

Department of Cardiovascular Sciences and Public Health University of Padova Padova Italy

Department of Epidemiology and Prevention N N Blokhin National Medical Research Centre of Oncology Moscow Russia

Department of Family Population and Preventive Medicine Renaissance School of Medicine Stony Brook University Stony Brook NY

Department of Medical and Surgical Sciences University of Bologna Bologna Italy

Environmental Research Group School of Public Health Imperial College London United Kingdom

Epidemiology and Biostatistics Unit Centre Armand Frappier Santé Biotechnologie Institut national de la recherche scientifique Laval Quebec Canada

Epidemiology Unit Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Milan Italy

Faculty of Medicine Palacky University Olomouc Czech Republic

From the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance Institute of the Ruhr University Bochum Bochum Germany

Health Research Institute of Asturias University of Oviedo ISPA and CIBERESP Spain

Institute and Clinic for Occupational Social and Environmental Medicine University Hospital LMU Munich; Comprehensive Pneumology Center Munich Munich Germany

Institute for Medical Informatics Biometry and Epidemiology University of Duisburg Essen Essen Germany

Institute for Risk Assessment Sciences Utrecht University Utrecht The Netherlands

Institute of Epidemiology Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany

Institute of Hygiene and Epidemiology 1 Faculty of Medicine Charles University Prague Czech Republic

International Agency for Research on Cancer Lyon France

ISGlobal Barcelona Spain

Leibniz Institute for Prevention Research and Epidemiology BIPS Bremen Germany

Masaryk Memorial Cancer Institute Brno Czech Republic

National Cancer Institute Bethesda MD

National Institute of Public Health Bucharest Romania

National Public Health Center Budapest Hungary

National Research Council Palermo Italy

Occupational Cancer Research Centre Ontario Health Toronto Canada

Regional Authority of Public Health Banska Bystrica Slovakia

Roy Castle Lung Cancer Research Programme Department of Molecular and Clinical Cancer Medicine The University of Liverpool Liverpool United Kingdom

Stony Brook Cancer Center Stony Brook University Stony Brook NY

The Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden

The Nofer Institute of Occupational Medicine Lodz Poland

Université Rennes Inserm EHESP Irset UMR_S 1085 Pointe à Pitre France

University of Montreal Hospital Research Center Montreal Canada

Zobrazit více v PubMed

Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA. Cancer J. Clin 2021;71(3):209–249. PubMed

GBD 2016 Occupational Carcinogens Collaborators. Global and regional burden of cancer in 2016 arising from occupational exposure to selected carcinogens: a systematic analysis for the Global Burden of Disease Study 2016. Occup. Environ. Med 2020;77(3):151–159. PubMed PMC

Hovanec J, Siemiatycki J, Conway DI, et al. Lung cancer and socioeconomic status in a pooled analysis of case-control studies. PLoS ONE. 2018;13(2):e0192999. PubMed PMC

Menvielle G, Franck J, Radoï L, et al. Quantifying the mediating effects of smoking and occupational exposures in the relation between education and lung cancer: the ICARE study. Eur. J. Epidemiol 2016:1–9. PubMed

Blakely T, Barendregt JJ, Foster RH, et al. The association of active smoking with multiple cancers: national census-cancer registry cohorts with quantitative bias analysis. Cancer causes & control : CCC. 2013;24(6):1243–1255. PubMed

Fox MP, MacLehose RF, Lash TL. Applying Quantitative Bias Analysis to Epidemiologic Data. Cham: Springer; 2021.

Greenland S, Lash TL. Bias Analysis. In: Rothman KJ, Greenland S, Lash TL, eds. Modern epidemiology. Third edition. Philadelphia: Wolters Kluwer Health / Lippincott Williams & Wilkins; 2008:345–380.

Jiang Z, VanderWeele TJ. When is the difference method conservative for assessing mediation? Am. J. Epidemiol 2015;182(2):105–108. PubMed PMC

Kaufman JS, MacLehose RF, Kaufman S. A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiologic perspectives & innovations : EP+I. 2004;1(1):4. PubMed PMC

Richiardi L, Bellocco R, Zugna D. Mediation analysis in epidemiology: methods, interpretation and bias. Int. J. Epidemiol 2013;42(5):1511–1519. PubMed

Pearl J. Direct and Indirect Effects. In: Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc; 2001:411–420.

Naimi AI, Kaufman JS, MacLehose RF. Mediation misgivings: ambiguous clinical and public health interpretations of natural direct and indirect effects. Int J Epidemiol. 2014;43(5):1656–1661. PubMed

Olsson AC, Vermeulen R, Schüz J, et al. Exposure-Response Analyses of Asbestos and Lung Cancer Subtypes in a Pooled Analysis of Case-Control Studies. Epidemiology. 2017;28(2):288–299. PubMed PMC

Ganzeboom HB, Treiman DJ. International Stratification and Mobility File: Conversion Tools. http://www.harryganzeboom.nl/ismf/index.htm. Updated May 10, 2019. Accessed February 27, 2023.

Leffondre K, Abrahamowicz M, Xiao Y, Siemiatycki J. Modelling smoking history using a comprehensive smoking index: application to lung cancer. Stat. Med 2006;25(24):4132–4146. PubMed

Ahrens W, Merletti F. A standard tool for the analysis of occupational lung cancer in epidemiologic studies. Int. J. Occup. Environ. Health 1998;4(4):236–240. PubMed

Mirabelli D, Chiusolo M, Calisti R, et al. Database of occupations and industrial activities that involve the risk of pulmonary tumors. Epidemiol. Prev 2001;25(4–5):215–221. PubMed

Tchetgen Tchetgen EJ. Inverse odds ratio-weighted estimation for causal mediation analysis. Stat. Med 2013;32(26):4567–4580. PubMed PMC

Nguyen QC, Osypuk TL, Schmidt NM, Glymour MM, Tchetgen Tchetgen EJ. Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting. Am. J. Epidemiol 2015;181(5):349–356. PubMed PMC

Steen J, Loeys T, Moerkerke B, Vansteelandt S. Flexible Mediation Analysis With Multiple Mediators. Am. J. Epidemiol 2017;186(2):184–193. PubMed

VanderWeele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. Am. J. Epidemiol 2010;172(12):1339–1348. PubMed PMC

Petersen ML, Sinisi SE, van der Laan MJ. Estimation of direct causal effects. Epidemiology. 2006;17(3):276–284. PubMed

Valeri L, VanderWeele TJ. Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. Psychol. Methods 2013;18(2):137–150. PubMed PMC

Vartiainen E, Seppälä T, Lillsunde P, Puska P. Validation of self reported smoking by serum cotinine measurement in a community-based study. Journal of Epidemiology and Community Health. 2002;56(3):167–170. PubMed PMC

Wong SL, Shields M, Leatherdale S, Malaison E, Hammond D. Assessment of validity of self-reported smoking status. Health Rep. 2012;23(1):47–53. PubMed

Hovanec J, Weiß T, Koch H, et al. Smoking and urinary cotinine by socioeconomic status in the Heinz Nixdorf Recall Study. J Epidemiol Community Health. 2019;73(6):489–495. PubMed

Richiardi L, Boffetta P, Merletti F. Analysis of nonresponse bias in a population-based case–control study on lung cancer. J Clin Epidemiol. 2002;55(10):1033–1040. PubMed

Minematsu N, Nakamura H, Furuuchi M, et al. Limitation of cigarette consumption by CYP2A6*4, *7 and *9 polymorphisms. Eur Respir J. 2006;27(2):289–292. PubMed

Wassenaar CA, Dong Q, Wei Q, Amos CI, Spitz MR, Tyndale RF. Relationship between CYP2A6 and CHRNA5-CHRNA3-CHRNB4 variation and smoking behaviors and lung cancer risk. J Natl Cancer Inst. 2011;103(17):1342–1346. PubMed PMC

Thorgeirsson TE, Gudbjartsson DF, Surakka I, et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat. Genet 2010;42(5):448–453. PubMed PMC

VanderWeele TJ. Bias formulas for sensitivity analysis for direct and indirect effects. Epidemiology. 2010;21(4):540–551. PubMed PMC

Smith LH, VanderWeele TJ. Mediational E-values: Approximate sensitivity analysis for unmeasured mediator-outcome confounding. Epidemiology. 2019. PubMed PMC

Ben-Shlomo Y A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol. 2002;31(2):285–293. PubMed

Power C, Graham H, Due P, et al. The contribution of childhood and adult socioeconomic position to adult obesity and smoking behaviour: an international comparison. Int J Epidemiol. 2005;34(2):335–344. PubMed

Alberg AJ, Worley ML, Tooze JA, et al. The Validity of Self-reported Recent Smoking in Head and Neck Cancer Surgical Patients. Otolaryngology—head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery. 2015;153(6):990–995. PubMed PMC

Blakely T, McKenzie S, Carter K. Misclassification of the mediator matters when estimating indirect effects. Journal of Epidemiology and Community Health. 2013;67(5):458–466. PubMed

Corbin M, Haslett S, Pearce N, Maule M, Greenland S. A comparison of sensitivity-specificity imputation, direct imputation and fully Bayesian analysis to adjust for exposure misclassification when validation data are unavailable. Int. J. Epidemiol 2017;46(3):1063–1072. PubMed

Martikainen P, Valkonen T. Bias related to the exclusion of the economically inactive in studies on social class differences in mortality. Int. J. Epidemiol 1999;28(5):899–904. PubMed

VanderWeele TJ, Asomaning K, Tchetgen Tchetgen EJ, et al. Genetic variants on 15q25.1, smoking, and lung cancer: an assessment of mediation and interaction. Am. J. Epidemiol 2012;175(10):1013–1020. PubMed PMC

Zhang P, Chen P-L, Li Z-H, et al. Association of smoking and polygenic risk with the incidence of lung cancer: a prospective cohort study. Br J Cancer. 2022;126(11):1637–1646. PubMed PMC

Qin X, Yang F. Simulation-based sensitivity analysis for causal mediation studies. Psychol. Methods 2021. Published December 16, 2021. PubMed

Behrens T, Ge C, Vermeulen R, et al. Occupational exposure to nickel and hexavalent chromium and the risk of lung cancer in a pooled analysis of case-control studies (SYNERGY). Int. J. Cancer 2023;152(4):645–660. PubMed

Olsson A, Guha N, Bouaoun L, et al. Occupational Exposure to Polycyclic Aromatic Hydrocarbons and Lung Cancer Risk: Results from a Pooled Analysis of Case-Control Studies (SYNERGY). Cancer Epidemiol Biomarkers Prev. 2022;31(7):1433–1441. PubMed PMC

Taylor R, Najafi F, Dobson A. Meta-analysis of studies of passive smoking and lung cancer: effects of study type and continent. Int J Epidemiol. 2007;36(5):1048–1059. PubMed

Raaschou-Nielsen O, Andersen ZJ, Beelen R, et al. Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE). Lancet Oncol. 2013;14(9):813–822. PubMed

Chen T-Y, Fang Y-H, Chen H-L, et al. Impact of cooking oil fume exposure and fume extractor use on lung cancer risk in non-smoking Han Chinese women. Sci Rep. 2020;10(1):6774. PubMed PMC

Petrovic D, de Mestral C, Bochud M, et al. The contribution of health behaviors to socioeconomic inequalities in health: A systematic review. Preventive Medicine. 2018;113:15–31. PubMed

Louwman WJ, van Lenthe FJ, Coebergh JWW, Mackenbach JP. Behaviour partly explains educational differences in cancer incidence in the south-eastern Netherlands: the longitudinal GLOBE study. Eur J Cancer Prev. 2004;13(2):119–125. PubMed

Menvielle G, Boshuizen H, Kunst AE, et al. The role of smoking and diet in explaining educational inequalities in lung cancer incidence. J Natl Cancer Inst. 2009;101(5):321–330. PubMed PMC

Lash TL, Ahern TP, Collin LJ, Fox MP, MacLehose RF. Bias Analysis Gone Bad. Am. J. Epidemiol 2021;190(8):1604–1612. PubMed PMC

Najít záznam

Citační ukazatele

Pouze přihlášení uživatelé

Možnosti archivace

Nahrávání dat ...