OBJECTIVE: We evaluated the impact of demographic factors, smoking patterns, and the occurrence of smoking-related diseases on smoking cessation, with a particular emphasis on the temporal relationship between diagnosis of smoking-related diseases and cessation. STUDY DESIGN AND SETTING: A cohort was assembled of participants of a general health screening examination aged 50-74 years. Lifetime smoking habits and medical history were obtained by a self-administered questionnaire. In a retrospective cohort study approach, predictors of cessation among ever-smokers (n = 4,575) were identified using the extended proportional hazards model. RESULTS: Male gender, late onset of smoking, and higher educational level were predictive of cessation. However, the by far strongest predictors of cessation were diagnoses of smoking-related diseases: relative cessation rates in the year of disease occurrence were 11.2 for myocardial infarction (95% confidence interval CI = 8.9-14.0), 7.2 for stroke (95% CI = 5.1-11.6), 2.5 for diabetes mellitus (95% CI = 1.6-4.0) and 4.8 for cancer (95% CI = 3.1-7.4) relative to years before diagnosis of the respective diseases. CONCLUSION: Our results underline the key role of perceived detrimental effects of smoking for cessation. When smokers personally experience the health consequences of smoking, many permanently quit.
OBJECTIVE: We evaluated the impact of demographic factors, smoking patterns, and the occurrence of smoking-related diseases on smoking cessation, with a particular emphasis on the temporal relationship between diagnosis of smoking-related diseases and cessation. STUDY DESIGN AND SETTING: A cohort was assembled of participants of a general health screening examination aged 50-74 years. Lifetime smoking habits and medical history were obtained by a self-administered questionnaire. In a retrospective cohort study approach, predictors of cessation among ever-smokers (n = 4,575) were identified using the extended proportional hazards model. RESULTS: Male gender, late onset of smoking, and higher educational level were predictive of cessation. However, the by far strongest predictors of cessation were diagnoses of smoking-related diseases: relative cessation rates in the year of disease occurrence were 11.2 for myocardial infarction (95% confidence interval CI = 8.9-14.0), 7.2 for stroke (95% CI = 5.1-11.6), 2.5 for diabetes mellitus (95% CI = 1.6-4.0) and 4.8 for cancer (95% CI = 3.1-7.4) relative to years before diagnosis of the respective diseases. CONCLUSION: Our results underline the key role of perceived detrimental effects of smoking for cessation. When smokers personally experience the health consequences of smoking, many permanently quit.
Authors: Gioia Di Credico; Valeria Edefonti; Jerry Polesel; Francesco Pauli; Nicola Torelli; Diego Serraino; Eva Negri; Daniele Luce; Isabelle Stucker; Keitaro Matsuo; Paul Brennan; Marta Vilensky; Leticia Fernandez; Maria Paula Curado; Ana Menezes; Alexander W Daudt; Rosalina Koifman; Victor Wunsch-Filho; Ivana Holcatova; Wolfgang Ahrens; Pagona Lagiou; Lorenzo Simonato; Lorenzo Richiardi; Claire Healy; Kristina Kjaerheim; David I Conway; Tatiana V Macfarlane; Peter Thomson; Antonio Agudo; Ariana Znaor; Leonardo F Boaventura Rios; Tatiana N Toporcov; Silvia Franceschi; Rolando Herrero; Joshua Muscat; Andrew F Olshan; Jose P Zevallos; Carlo La Vecchia; Deborah M Winn; Erich M Sturgis; Guojun Li; Eleonora Fabianova; Jolanda Lissowska; Dana Mates; Peter Rudnai; Oxana Shangina; Beata Swiatkowska; Kirsten Moysich; Zuo-Feng Zhang; Hal Morgenstern; Fabio Levi; Elaine Smith; Philip Lazarus; Cristina Bosetti; Werner Garavello; Karl Kelsey; Michael McClean; Heribert Ramroth; Chu Chen; Stephen M Schwartz; Thomas L Vaughan; Tongzhang Zheng; Gwenn Menvielle; Stefania Boccia; Gabriella Cadoni; Richard B Hayes; Mark Purdue; Maura Gillison; Stimson Schantz; Guo-Pei Yu; Hermann Brenner; Gypsyamber D'Souza; Neil D Gross; Shu-Chun Chuang; Paolo Boffetta; Mia Hashibe; Yuan-Chin Amy Lee; Luigino Dal Maso Journal: Oral Oncol Date: 2019-05-17 Impact factor: 5.337
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Authors: Andrew Rundle; John Richie; Karen Steindorf; Marco Peluso; Kim Overvad; Ole Raaschou-Nielsen; Francoise Clavel-Chapelon; Jacob P Linseisen; Heiner Boeing; Antonia Trichopoulou; Domenico Palli; Vittorio Krogh; Rosario Tumino; Salvatore Panico; Hendrik B Bueno-De-Mesquita; Petra H Peeters; Eiliv Lund; Carlos A Gonzalez; Carmen Martinez; Miren Dorronsoro; Aurelio Barricarte; M Jose Tormo; Josèr Quiros; Antonio Agudo; Goran Berglund; Bengt Jarvholm; Sheila Bingham; Timothy J Key; Emmanuelle Gormally; Rodolfo Saracci; Rudolf Kaaks; Elio Riboli; Paolo Vineis Journal: Biomarkers Date: 2010-02 Impact factor: 2.658