Predictors of smoking relapse among adult in smoking cessation

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Published Mar 27, 2015
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Vol. 93 No. 1 (2015): Issue Jan 2015

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Sriha Belguith Asma
Elmhamdi Sana
Bouanene Iness
Harizi Chahida
Ben Salah Aroua
Ben Salem Kamel
Soltani Essoussi Mohamed

Abstract

Background: Smoking is a public health problem in Tunisia. The smoking cessation assistance is one of means against this epidemic. Few smokers require this need to quit. Purpose: this study aimed at identifying the predictive factors associated to the smoking relapse at the adult.

Method: We carried out a prospective cohort study, during a period of 18 months, at the smoking cessation center of the University hospital of Monastir (Tunisia). The population study consisted of adult abstinent in smoking cessation interventions. Baseline contained a questionnaire investigating the smoking history, the nicotine dependence and the anxiety / depression state and information of the medical examination at follow-up visits. A phone survey was realized, 21 months after the inclusion beginning, to estimate the rate of smoking abstinence, the deadline average of relapse and these predictors. A multivariate Cox regression was used to identify predictors of smoking relapses.

Results: A total of 143 adults were included in our study with a mean age of 44 ± 14 years. The median consumption was 30 cigarettes/ day. The median of initial carbon monoxide expired was 13 ppm. The median period of the medical treatment was 4 weeks. In the survey 74 patients relapse (51,7%) : IC95% [44 -60], with a median deadline of relapse of 11 weeks IC95% [9,1-12,9]. In the multivariate analysis, smoking relapse was associated with a period of treatment less than 4 weeks OR: 2,53: IC95 [1,48-4,32], and with a perception, less than 2 benefits, at the medical examination at follow-up visits OR: 1,54: IC95 [1,02-2,66].

Conclusion: The results of this study give us important clarifications, on profits offered by the adult smoking cessation interventions.

Keywords:

Smokers; Help to quit; Tobacco cessation rate; Relapse, Predictors

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