Characteristics and Predictors of Abstinence Among Smokers of a Smoking Cessation Clinic in Hunan China

Abstract

Background: More than 300 million smokers make China the largest cigarette consumer globally, which is a huge economic burden. Smoking cessation (SC) clinics can offer counseling and follow-up services. The operational experience of SC clinics in China needs to be summarized and improved based on research evidence. Purpose: The objectives of this study were to describe quit rates among attendees of SC clinics in Hunan and assess predictors of successful SC. Methods: The participants in this study were smokers who visited the SC clinic of Hunan Cancer Hospital from February 1, 2015 to September 30, 2018. Individuals who received individual counseling and assessment from the SC clinic staff and were willing to quit smoking were eligible for inclusion. Those with critical illness or cancer were excluded. Application of smoking cessation clinic registration form (unified by Chinese Center for Disease Control and Prevention) was used to assess participants at the consultation. Follow-ups and counseling were performed over telephone at 1 week, 1 month, and 3 months after the initial cessation consultation or in times of need. Successful SC was checked for at 3 months after the start of SC. Results: A total of 328 smokers (mean age 45.67 ± 12.38 years) had participated. The abstinence rate at 3 months was 28.4%. Binary regression analysis revealed significant independent predictors to be the total numbers of SC follow up sessions, previous SC attempts, and participants' decision on when to quit smoking (The relative to quit immediately group, quit within 30 days, quit after 30 days, and undecided quit were less likely to succeed in quitting. while quit within seven days had no statistical significance. Conclusion: SC clinics can achieve a desirably high quit rate. Participant's previous attempts at quitting, three or more follow-ups, and the decision to quit immediately or within seven days were factors helpful in predicting the success of SC.

Keywords: abstinence rates; multivariate binary regression; quitting predictor; smoker characteristic; smoking; smoking cessation; smoking cessation clinic; smoking quit rate.

Figure 1

(A) Health assessment represents the proportion of the subjective assessment of physical condition grade of 328 patients; (B) Fagerstrom score represents the proportion of Fagerstrom Test for Nicotine dependence among 328 patients. (C) Date of SC represents the proportional distribution characteristics of the expected start time of smoking cessation between the successful and unsuccessful smoking cessation groups; (D) Follow ups represents the proportional distribution characteristics of the number of follow-up visits between the successful group and the failed group. SC, smoking cessation.