Verena Friedrich1, Adrian Brügger, Georg Bauer. 1. Division of Public and Organizational Health, Institute of Social and Preventive Medicine, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland. verena.friedrich@ifspm.unizh.ch
Abstract
OBJECTIVES: This study provides information about the prevalence of tobacco prevention (TP) and the stages of change with respect to the introduction of TP among companies in the Canton of Zurich (n = 1,648). It explores the factors that predict restrictiveness of smoking policies, number of individual support measures, interest in services to promote TP, and the relationship between TP and health outcomes. METHODS: Data were gathered by means of a written questionnaire and analysed using ordinal regression models. RESULTS: Whereas many companies maintain smoke-free policies, only few provide cessation-courses. Health and welfare organisations have strictest, and building and hospitality companies have least strict policies. Company size predicts number of individual support measures but not policy restrictiveness. Both measures are predicted by personal concern of the representative. Interest in services is predicted by tobacco-related problems and medium stages of change. Finally, stricter policies are associated with lower proportion of smokers and less tobacco-related problems. CONCLUSIONS: Health professionals should support less advanced companies in their endeavour to implement TP. The findings provide a baseline to evaluate the implementation of the forthcoming smoke-free legislation.
OBJECTIVES: This study provides information about the prevalence of tobacco prevention (TP) and the stages of change with respect to the introduction of TP among companies in the Canton of Zurich (n = 1,648). It explores the factors that predict restrictiveness of smoking policies, number of individual support measures, interest in services to promote TP, and the relationship between TP and health outcomes. METHODS: Data were gathered by means of a written questionnaire and analysed using ordinal regression models. RESULTS: Whereas many companies maintain smoke-free policies, only few provide cessation-courses. Health and welfare organisations have strictest, and building and hospitality companies have least strict policies. Company size predicts number of individual support measures but not policy restrictiveness. Both measures are predicted by personal concern of the representative. Interest in services is predicted by tobacco-related problems and medium stages of change. Finally, stricter policies are associated with lower proportion of smokers and less tobacco-related problems. CONCLUSIONS: Health professionals should support less advanced companies in their endeavour to implement TP. The findings provide a baseline to evaluate the implementation of the forthcoming smoke-free legislation.
Authors: Dariush Mozaffarian; Ashkan Afshin; Neal L Benowitz; Vera Bittner; Stephen R Daniels; Harold A Franch; David R Jacobs; William E Kraus; Penny M Kris-Etherton; Debra A Krummel; Barry M Popkin; Laurie P Whitsel; Neil A Zakai Journal: Circulation Date: 2012-08-20 Impact factor: 29.690
Authors: Luke Wolfenden; Sharni Goldman; Fiona G Stacey; Alice Grady; Melanie Kingsland; Christopher M Williams; John Wiggers; Andrew Milat; Chris Rissel; Adrian Bauman; Margaret M Farrell; France Légaré; Ali Ben Charif; Hervé Tchala Vignon Zomahoun; Rebecca K Hodder; Jannah Jones; Debbie Booth; Benjamin Parmenter; Tim Regan; Sze Lin Yoong Journal: Cochrane Database Syst Rev Date: 2018-11-14