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Global burden of cancers attributable to tobacco smoking, 1990–2019: an ecological study

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Abstract

Aim and background

Identifying risk factors for cancer initiation and progression is the cornerstone of the preventive approach to cancer management and control (EPMA J. 4(1):6, 2013). Tobacco smoking is a well-recognized risk factor for initiation and spread of several cancers. The predictive, preventive, and personalized medicine (PPPM) approach to cancer management and control focuses on smoking cessation as an essential cancer prevention strategy. Towards this end, this study examines the temporal patterns of cancer burden due to tobacco smoking in the last three decades at global, regional, and national levels.

Data and methods

The data pertaining to the burden of 16 cancers attributable to tobacco smoking at global, regional, and national levels were procured from the Global Burden of Disease 2019 Study. Two main indicators, deaths and disability-adjusted life years (DALYs), were used to describe the burden of cancers attributable to tobacco smoking. The socio-economic development of countries was measured using the socio-demographic index (SDI).

Results

Globally, deaths due to neoplasms caused by tobacco smoking increased from 1.5 million in 1990 to 2.5 million in 2019, whereas the age-standardized mortality rate (ASMR) decreased from 39.8/100,000 to 30.6/100,000 and the age-standardized DALY rate (ASDALR) decreased from 948.9/100,000 to 677.3/100,000 between 1990 and 2019. Males accounted for approximately 80% of global deaths and DALYs in 2019. Populous regions of Asia and a few regions of Europe account for the largest absolute burden, whereas countries in Europe and America have the highest age-standardized rates of cancers due to tobacco smoking. In 8 out of 21 regions, there were more than 100,000 deaths due to cancers attributable to tobacco smoking led by East Asia, followed by Western Europe in 2019. The regions of Sub-Saharan Africa (except southern region) had one of the lowest absolute counts of deaths, DALYs, and age-standardized rates. In 2019, tracheal, bronchus, and lung (TBL), esophageal, stomach, colorectal, and pancreatic cancer were the top 5 neoplasms attributable to tobacco smoking, with different burdens in regions as per their development status. The ASMR and ASDALR of neoplasms due to tobacco smoking were positively correlated with SDI, with pairwise correlation coefficient of 0.55 and 0.52, respectively.

Conclusion

As a preventive tool, tobacco smoking cessation has the biggest potential among all risk factors for preventing millions of cancer deaths every year. Cancer burden due to tobacco smoking is found to be higher in males and is positively associated with socio-economic development of countries. As tobacco smoking begins mostly at younger ages and the epidemic is unfolding in several parts of the world, more accelerated efforts are required towards tobacco cessation and preventing youth from entering this addiction. The PPPM approach to medicine suggests that not only personalized and precision medicine must be provided to cancer patients afflicted by tobacco smoking but personalized and targeted preventive solutions must be provided to prevent initiation and progression of smoking.

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Data availability

All data is procured from GBD Results Tool (https://vizhub.healthdata.org/gbd-results/).

Code availability

Not applicable.

Abbreviations

PPPM:

Predictive, preventive, and personalized medicine

DALYs:

Disability-adjusted life years

SDI:

Socio-demographic index

ASMR:

Age-standardized mortality rate

ASDLAR:

Age-standardized DALY rate

GBD:

Global Burden of Disease

PAF:

Population attributable fraction

RR:

Relative risk

TMREL:

Theoretical minimum risk exposure level

WHO:

World Health Organization

TBL:

Tracheal, bronchus, and lung

SSA:

Sub-Saharan Africa

GWAS:

Genome-wide association studies

GRS:

Genetic risk score

NAT2:

Arylamine N-acetyltransferase 2

SNPs:

Single nucleotide polymorphisms

FCTC:

Framework convention on tobacco control

References

  1. Reitsma MB, Kendrick PJ, Ababneh E, et al. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet. 2021;397(10292):2337–60.

    Article  Google Scholar 

  2. Goodchild M, Nargis N, d’Espaignet ET. Global economic cost of smoking-attributable diseases. Tob Control. 2018;27(1):58–64.

    Article  PubMed  Google Scholar 

  3. Wynder EL, Graham EA. Tobacco smoking as a possible etiologic factor in bronchiogenic carcinoma: a study of six hundred and eighty-four proved cases. JAMA. 1950;143(4):329–36.

    Article  CAS  Google Scholar 

  4. Doll R, Hill AB. The mortality of doctors in relation to their smoking habits. Br Med J. 1954;1(4877):1451.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. United States Public Health Service. Smoking and health: report of the Advisory Committee to the Surgeon General of the Public Health Service. Washington, DC: US Department of Health, Education, and Welfare; 1964.

    Google Scholar 

  6. International Agency for Research on Cancer Monographs 1–132. Last Updated July 1, 2022. Available at https://monographs.iarc.who.int/wp-content/uploads/2019/07/Classifications_by_cancer_site.pdf. (Accessed September 7, 2022).

  7. Golubnitschaja O, Baban B, Boniolo G, Wang W, Bubnov R, Kapalla M, Krapfenbauer K, Mozaffari MS, Costigliola V. Medicine in the early twenty-first century: paradigm and anticipation-EPMA position paper 2016. EPMA J. 2016;7(1):1–3.

    Article  Google Scholar 

  8. Golubnitschaja O, Yeghiazaryan K, Costigliola V, Trog D, Braun M, Debald M, Kuhn W, Schild HH. Risk assessment, disease prevention and personalised treatments in breast cancer: is clinically qualified integrative approach in the horizon? EPMA J. 2013;4(1):1–24.

    Article  Google Scholar 

  9. US FDA. https://www.fda.gov/tobacco-products/products-ingredients-components/chemicals-cigarettes-plant-product-puff (Accessed September 17, 2022)

  10. Rioux N, Castonguay A. 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone modulation of cytokine release in U937 human macrophages. Cancer Immunol Immunother. 2001;49(12):663–70.

    Article  CAS  PubMed  Google Scholar 

  11. Zhou J, Xiong R, Zhou J, Guan X, Jiang G, Chen Y, Yang Q. Involvement of m6A regulatory factor IGF2BP1 in malignant transformation of human bronchial epithelial Beas-2B cells induced by tobacco carcinogen NNK. Toxicol Appl Pharmacol. 2022;1(436):115849.

    Article  Google Scholar 

  12. Qian S, Golubnitschaja O, Zhan X. Chronic inflammation: key player and biomarker-set to predict and prevent cancer development and progression based on individualized patient profiles. EPMA J. 2019;10(4):365–81.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Grech G, Zhan X, Yoo BC, Bubnov R, Hagan S, Danesi R, Vittadini G, Desiderio DM. EPMA position paper in cancer: current overview and future perspectives. EPMA J. 2015;6(1):1–31.

    Article  Google Scholar 

  14. Kucera R, Pecen L, Topolcan O, Dahal AR, Costigliola V, Giordano FA, Golubnitschaja O. Prostate cancer management: long-term beliefs, epidemic developments in the early twenty-first century and 3PM dimensional solutions. EPMA J. 2020;11(3):399–418.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Bizzarri M, Fedeli V, Monti N, Cucina A, Jalouli M, Alwasel SH, Harrath AH. Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes. EPMA J. 2021;12(4):545–58.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Mazurakova A, Koklesova L, Samec M, Kudela E, Kajo K, Skuciova V, Csizmár SH, Mestanova V, Pec M, Adamkov M, Al-Ishaq RK. Anti-breast cancer effects of phytochemicals: primary, secondary, and tertiary care. EPMA J 2022a:1–20.

  17. Mazurakova A, Samec M, Koklesova L, Biringer K, Kudela E, Al-Ishaq RK, Pec M, Giordano FA, Büsselberg D, Kubatka P, Golubnitschaja O. Anti-prostate cancer protection and therapy in the framework of predictive, preventive and personalised medicine—comprehensive effects of phytochemicals in primary, secondary and tertiary care. EPMA J 2022b:1–26.

  18. Zhang S, Wan X, Lv M, Li C, Chu Q, Wang G. TMEM92 acts as an immune-resistance and prognostic marker in pancreatic cancer from the perspective of predictive, preventive, and personalized medicine. EPMA J. 2022;13(3):519–34.

    Article  PubMed  Google Scholar 

  19. Vos T, Lim SS, Abbafati C, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of disease study 2019. Lancet. 2020;396:1204–22.

    Article  Google Scholar 

  20. Wang H, Abbas KM, Abbasifard M, et al. Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the global burden of disease study 2019. Lancet. 2020;396:1160–203.

    Article  Google Scholar 

  21. Murray CJ, Aravkin AY, Zheng P, et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1223–49.

    Article  Google Scholar 

  22. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) results. Seattle: Institute for Health Metrics and Evaluation (IHME). Source: Institute for Health Metrics Evaluation. Used with permission. All rights reserved. Available from https://vizhub.healthdata.org/gbd-results/ (Accessed: September 2022).

  23. Kocarnik JM, Compton K, Dean FE, et al. Cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life years for 29 cancer groups from 2010 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. JAMA oncol. 2022;8(3):420–44.

    Article  PubMed  Google Scholar 

  24. World Health Organisation Global Health Observatory. https://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-tobacco-control-monitor-current-tobaccouse-tobaccosmoking-cigarrettesmoking-agestd-tobagestdcurr (Accessed September 10,2022).

  25. Lee S, Ling PM, Glantz SA. The vector of the tobacco epidemic: tobacco industry practices in low and middle-income countries. Cancer Causes Control. 2012;23(1):117–29.

    Article  PubMed  PubMed Central  Google Scholar 

  26. World Health Organization. WHO report on the global tobacco epidemic, 2015: raising taxes on tobacco. Geneva: World Health Organization; 2015. Available from: http://www.who.int/tobacco/global_report/2015/en

  27. WHO Report on the Global Tobacco Epidemic, 2021: addressing new and emerging products. World Health Organization; 2021.

  28. Portes LH, Machado CV, Turci SR, Figueiredo VC, Cavalcante TM, Silva VL. Tobacco Control Policies in Brazil: a 30-year assessment. Ciencia Saude Coletiva. 2018;23:1837–48.

    Article  PubMed  Google Scholar 

  29. Divino JA, Ehrl P, Candido O, Valadao MA. Extended cost–benefit analysis of tobacco taxation in Brazil. Tobacco Control 2021

  30. Cosgrove KP, Wang S, Kim S-J, et al. Sex differences in the brain’s dopamine signature of cigarette smoking. J Neurosci Off J Soc Neurosci. 2014;34(50):16851–5.

    Article  Google Scholar 

  31. Verick S. Female labor force participation and development. IZA World Labor 2018;87 https://doi.org/10.15185/izawol.87.v2

  32. King TL, Kavanagh A, Scovelle AJ, Milner A. Associations between gender equality and health: a systematic review. Health Promot Int. 2020;35(1):27–41.

    PubMed  Google Scholar 

  33. Bilal U, Beltrán P, Fernández E, Navas-Acien A, Bolumar F, Franco M. Gender equality and smoking: a theory-driven approach to smoking gender differences in Spain. Tob Control. 2016;25(3):295–300.

    Article  PubMed  Google Scholar 

  34. Marcon A, Pesce G, Calciano L, Bellisario V, Dharmage SC, Garcia-Aymerich J, Gislasson T, Heinrich J, Holm M, Janson C, Jarvis D. Trends in smoking initiation in Europe over 40 years: a retrospective cohort study. PLoS One. 2018;13(8):e0201881.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Freedman KS, Nelson NM, Feldman LL. Smoking initiation among young adults in the United States and Canada, 1998–2010: a systematic review. Prev Chronic Dis. 2012;9:E05.

    PubMed  Google Scholar 

  36. United States Public Health Service. Office of the Surgeon General, National Center for Chronic Disease Prevention, Health Promotion (US). Office on Smoking. Preventing tobacco use among youth and young adults: a report of the surgeon general. US Government Printing Office; 2012.

  37. Reitsma MB, Flor LS, Mullany EC, Gupta V, Hay SI, Gakidou E. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and initiation among young people in 204 countries and territories, 1990–2019. Lancet Pub Health. 2021;6(7):e472–81.

    Article  Google Scholar 

  38. United States FDA. Available at https://www.fda.gov/tobacco-products/retail-sales-tobacco-products/tobacco-21 (Accessed September 9, 2022).

  39. Nuyts PA, Kuipers MA, Willemsen MC, Kunst AE. An increase in the tobacco age-of-sale to 21: for debate in Europe. Nicotine Tob Res. 2020;22(7):1247–9.

    Article  PubMed  Google Scholar 

  40. European Union Agency for Fundamental Rights. https://fra.europa.eu/en/publication/2017/mapping-minimum-age-requirements-concerning-rights-child-eu/purchasing-and-consuming-tobacco (Accessed September 10, 2022).

  41. Conrod PJ, Nikolaou K. Annual research review: on the developmental neuropsychology of substance use disorders. J Child Psychol Psychiatry. 2016;57(3):371–94.

    Article  PubMed  Google Scholar 

  42. Debenham J, Grummitt L, Newton NC, Teesson M, Slade T, Conrod P, Kelly EV. Personality-targeted prevention for adolescent tobacco use: three-year outcomes for a randomised trial in Australia. Prev Med. 2021;153:106794.

    Article  PubMed  Google Scholar 

  43. Rebele RW, Koval P, Smillie LD. Personality-informed intervention design: examining how trait regulation can inform efforts to change behavior. Eur J Pers. 2021;35(4):623–45.

    Article  Google Scholar 

  44. Ramsey AT, Bourdon JL, Bray M, Dorsey A, Zalik M, Pietka A, Salyer P, Chen LS, Baker TB, Munafò MR, Bierut LJ. Proof of concept of a personalized genetic risk tool to promote smoking cessation: high acceptability and reduced cigarette smoking. Cancer Prev Res. 2021;14(2):253–62.

    Article  Google Scholar 

  45. Takahashi H, Ogata H, Nishigaki R, Broide DH, Karin M. Tobacco smoke promotes lung tumorigenesis by triggering IKKβ-and JNK1-dependent inflammation. Cancer Cell. 2010;17(1):89–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Greten FR, Grivennikov SI. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity. 2019;51(1):27–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Garcia-Closas M, Rothman N, Figueroa JD, Prokunina-Olsson L, Han SS, Baris D, Jacobs EJ, Malats N, De Vivo I, Albanes D, Purdue MP. Common genetic polymorphisms modify the effect of smoking on absolute risk of bladder cancer. Cancer Res. 2013;73(7):2211–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Figueroa JD, Han SS, Garcia-Closas M, Baris D, Jacobs EJ, Kogevinas M, Schwenn M, Malats N, Johnson A, Purdue MP, Caporaso N. Genome-wide interaction study of smoking and bladder cancer risk. Carcinogenesis. 2014;35(8):1737–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Song N, Shin A, Jung HS, Oh JH, Kim J. Effects of interactions between common genetic variants and smoking on colorectal cancer. BMC Cancer. 2017;17(1):1–9.

    Article  CAS  Google Scholar 

  50. Chen X, Jansen L, Guo F, Hoffmeister M, Chang-Claude J, Brenner H. Smoking, genetic predisposition, and colorectal cancer risk. Clin Transl Gastroenterol 2021;12(3).

  51. Xun WW, Brennan P, Tjonneland A, Vogel U, Overvad K, Kaaks R, Canzian F, Boeing H, Trichopoulou A, Oustoglou E, Giotaki Z. Single-nucleotide polymorphisms (5p15. 33, 15q25. 1, 6p22. 1, 6q27 and 7p15. 3) and lung cancer survival in the European Prospective Investigation into Cancer and Nutrition (EPIC). Mutagenesis. 2011;26(5):657–66.

    Article  CAS  PubMed  Google Scholar 

  52. Amos CI, Wu X, Broderick P, Gorlov IP, Gu J, Eisen T, Dong Q, Zhang Q, Gu X, Vijayakrishnan J, Sullivan K. Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat genet. 2008;40(5):616–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hung RJ, McKay JD, Gaborieau V, Boffetta P, Hashibe M, Zaridze D, Mukeria A, Szeszenia-Dabrowska N, Lissowska J, Rudnai P, Fabianova E. A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25. Nature. 2008;452(7187):633–7.

    Article  CAS  PubMed  Google Scholar 

  54. Thorgeirsson TE, Geller F, Sulem P, Rafnar T, Wiste A, Magnusson KP, Manolescu A, Thorleifsson G, Stefansson H, Ingason A, Stacey SN. A variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature. 2008;452(7187):638–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat Genet. 2010;42:441–7.

    Article  Google Scholar 

  56. Liu JZ, Tozzi F, Waterworth DM, Pillai SG, Muglia P, Middleton L, Berrettini W, Knouff CW, Yuan X, Waeber G, Vollenweider P. Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat genet. 2010;42(5):436–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. VanderWeele TJ, Asomaning K, TchetgenTchetgen EJ, Han Y, Spitz MR, Shete S, Wu X, Gaborieau V, Wang Y, McLaughlin J, Hung RJ. Genetic variants on 15q25. 1, smoking, and lung cancer: an assessment of mediation and interaction. Am J Epidemiol. 2012;175(10):1013–20.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Lan Q, Hsiung CA, Matsuo K, Hong YC, Seow A, Wang Z, Hosgood HD, Chen K, Wang JC, Chatterjee N, Hu W. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat genet. 2012;44(12):1330–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Hung RJ, Spitz MR, Houlston RS, Schwartz AG, Field JK, Ying J, Li Y, Han Y, Ji X, Chen W, Wu X. Lung cancer risk in never-smokers of European descent is associated with genetic variation in the 5p15. 33 TERT-CLPTM1Ll region. J Thorac Oncol. 2019;14(8):1360–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Ji X, Bossé Y, Landi MT, Gui J, Xiao X, Qian D, Joubert P, Lamontagne M, Li Y, Gorlov I, de Biasi M. Identification of susceptibility pathways for the role of chromosome 15q25. 1 in modifying lung cancer risk. Nat Commun. 2018;9(1):1–5.

    Article  Google Scholar 

  61. Hancock DB, Guo Y, Reginsson GW, et al. Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence. Mol Psychiatry. 2018;23:1911–9.

    Article  CAS  PubMed  Google Scholar 

  62. Wang S, Chai P, Jia R. Novel insights on m (6) A RNA methylation in tumorigenesis: a double-edged sword. Mol Cancer. 2018;17:101.

    Article  PubMed  PubMed Central  Google Scholar 

  63. He L, Li J, Wang X, Ying Y, Xie H, Yan H, Zheng X, Xie L. The dual role of N6-methyladenosine modification of RNAs is involved in human cancers. J Cell Mol Med. 2018;22:4630–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. He L, Li H, Wu A, Peng Y, Shu G, Yin G. Functions of N6-methyladenosine and its role in cancer. Mol cancer. 2019;18(1):1–5.

    Article  CAS  Google Scholar 

  65. Li N, Zhan X. Identification of pathology-specific regulators of m6A RNA modification to optimize lung cancer management in the context of predictive, preventive, and personalized medicine. EPMA J. 2020;11(3):485–504.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Xu R, Pang G, Zhao Q, Yang L, Chen S, Jiang L, Shen Y, Shao W. The momentous role of N6-methyladenosine in lung cancer. J Cell Physiol. 2021;236(5):3244–56.

    Article  CAS  PubMed  Google Scholar 

  67. Dong S, Wu Y, Liu Y, Weng H, Huang H. N6-Methyladenosine steers RNA metabolism and regulation in cancer. Cancer Commun. 2021;41(7):538–59.

    Article  Google Scholar 

  68. Lu M, Zhan H, Liu B, et al. N6-methyladenosine-related non-coding RNAs are potential prognostic and immunotherapeutic responsiveness biomarkers for bladder cancer. EPMA J. 2021;12:589–604.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Tuncel G, Kalkan R. Importance of m N6-methyladenosine (m6A) RNA modification in cancer. Medical Oncol. 2019;36(4):1–6.

    Article  Google Scholar 

  70. Balachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015;16(4):e173–80.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Ha YS, Kim TH. The surveillance for muscle-invasive bladder cancer (MIBC). In Bladder Cancer 2018 (pp. 553–597). Academic Press.

  72. Bokhorst LP, Steyerberg EW, Roobol MJ. Decision support for low-risk prostate cancer. In Prostate Cancer (second edition) 2016(pp. 207–213). Academic Press.

  73. McCloskey SA, White J. Radiotherapy and ductal carcinoma in situ. In The Breast (Fifth Edition), Elsevier, 2018;671–676.e2

  74. Guo L. Lung cancer risk prediction nomogram in Chinese female non-smokers. J Thoracic Oncol. 2022;17(9):S35-36. https://doi.org/10.1016/j.jtho.2022.07.066.

    Article  Google Scholar 

  75. Zhu N, Lin S, Cao C, Xu N, Yu X, Chen X. Nomogram to predict successful smoking cessation in a Chinese outpatient population. Tobacco Induced Dis. 2020;18.

  76. Hu N, Yu Z, Du Y, Li J. Risk factors of relapse after smoking cessation: results in China family panel studies from 2010 to 2018. Front Pub Health 2022;10.

  77. World Health Organisation. https://www.who.int/data/gho/data/themes/topics/sdg-target-3_a-tobacco-control (Accessed September 9, 2022).

  78. Boderie NW, van Kippersluis JL, Ceallaigh DT, Radó MK, Burdorf A, van Lenthe FJ, Been JV. PERSonalised Incentives for Supporting Tobacco cessation (PERSIST) among healthcare employees: a randomised controlled trial protocol. BMJ Open. 2020;10(9):e037799.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Kock L, Brown J, Hiscock R, Tattan-Birch H, Smith C, Shahab L. Individual-level behavioural smoking cessation interventions tailored for disadvantaged socioeconomic position: a systematic review and meta-regression. Lancet Pub Health. 2019;4(12):e628–44.

    Article  Google Scholar 

  80. Villanti AC, West JC, Klemperer EM, Graham AL, Mays D, Mermelstein RJ, Higgins ST. Smoking-cessation interventions for US young adults: updated systematic review. Am J Prev Med. 2020;59(1):123–36.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Peretti-Watel P, Constance J, Guilbert P, Gautier A, Beck F, Moatti JP. Smoking too few cigarettes to be at risk? Smokers’ perceptions of risk and risk denial, a French survey. Tob Control. 2007;16(5):351–6.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Heikkinen H, Patja K, Jallinoja P. Smokers’ accounts on the health risks of smoking: why is smoking not dangerous for me? Soc Sci Med. 2010;71(5):877–83.

    Article  PubMed  Google Scholar 

  83. Peretti-Watel P, Seror V, Verger P, Guignard R, Legleye S, Beck F. Smokers’ risk perception, socioeconomic status and source of information on cancer. Addict Behav. 2014;39(9):1304–10.

    Article  PubMed  Google Scholar 

  84. Fanshawe TR, Halliwell W, Lindson N, Aveyard P, Livingstone-Banks J, Hartmann-Boyce J. Tobacco cessation interventions for young people. Cochrane Database Sys Rev 2017(11).

  85. Belsky DW, Moffitt TE, Baker TB, Biddle AK, Evans JP, Harrington H, Houts R, Meier M, Sugden K, Williams B, Poulton R. Polygenic risk and the developmental progression to heavy, persistent smoking and nicotine dependence: evidence from a 4-decade longitudinal study. JAMA Psychiat. 2013;70(5):534–42.

    Article  Google Scholar 

  86. Bizzarri M, Fedeli V, Monti N, et al. Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes. EPMA J. 2021;12:545–58.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Lu M, Zhan X. The crucial role of multiomic approach in cancer research and clinically relevant outcomes. EPMA J. 2018;9:77–102.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the Institute of Health Metrics and Evaluation for providing GBD 2019 estimates in the public domain.

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  1. Humanities and Social Sciences, National Institute of Technology Kurukshetra, Kurukshetra, India

    Rajesh Sharma

  2. Economics and Business Environment, Indian Institute of Management Jammu, Jammu and Kashmir, India

    Bijoy Rakshit

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RS contributed to the design of the study, data collection, analysis and interpretation, writing, and critical revision of the manuscript. BR contributed to writing and critical revision of the manuscript. All authors approved the final version of the manuscript.

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Correspondence to Rajesh Sharma.

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Sharma, R., Rakshit, B. Global burden of cancers attributable to tobacco smoking, 1990–2019: an ecological study. EPMA Journal 14, 167–182 (2023). https://doi.org/10.1007/s13167-022-00308-y

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