predictors of smoking cessation among adult smokers in six cities in china lin li, hua-hie yong, ron...

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Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong Corresponding author: Lin Li, PhD; E-mail: lin.li@ cancervic .org.au The authors would like to thank other members of the ITC China team for their support. Poster Presentation at the 2010 SRNT Annual Meeting, Baltimore, Maryland, February 2010

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Page 1: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Predictors of smoking cessation among adult smokers in six cities in China

Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Corresponding author: Lin Li, PhD; E-mail: [email protected]

The authors would like to thank other members of the ITC China team for their support.

Poster Presentation at the 2010 SRNT Annual Meeting, Baltimore, Maryland, February 2010

Page 2: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Background and objective

• Few longitudinal studies on smoking cessation have been reported in China, and it remains unclear whether determinants of quitting are similar to those found in Western countries.

• This paper uses longitudinal data from the first two waves of the International Tobacco Control Policy Evaluation (ITC) China Survey to examine predictors of cessation behaviours among adult smokers in 6 cities in China, in light of existing knowledge from previous research (Hyland et al) in 4 Western countries (Australia, Canada, the UK and USA) that are also part of the broader ITC Project.

Page 3: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Methods

• The ITC China Survey is a prospective face-to-face cohort survey. It employs a stratified multi-stage cluster sampling design.

• Between April and August 2006, 4,732 adult smokers were first surveyed in Beijing, Shenyang, Shanghai, Changsha, Guangzhou and Yinchuan. Of these, 3,863 were successfully followed up in the second Wave in late 2007, with a gap of 16 months.

• Baseline measures of sociodemographics, dependence and interest in quitting were used prospectively to predict both making quit attempts and quit success among those who tried.

Page 4: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Results Overall, 979 out of 3863 (25%) Chinese smokers reported having made at least one quit attempt between Waves 1 and 2. Compared to ITC-4 Western countries, fewer smokers in China made quit attempts.

Reported quit attempt rate between Waves 1 & 2

25%

36%

0%5%

10%15%20%25%30%35%40%

China ITC-4 countries

Perc

en

t

Inter Survey Interval: China=16 months, ITC-4 countries=8 months.

Page 5: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Results (cont’) Of those attempted, 212 (21.7%) were still stopped smoking at Wave 2, which is close to the success rates (25%) in ITC-4 western countries.

Successful quitting among those who made a quit attempt between Waves 1 and 2

0%

5%

10%

15%

20%

25%

30%

China ITC-4 countries

Perc

en

t

Page 6: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Quit attempt – Predictors

Multivariate analyses showed that independent predictors of making quit attempts in Chinese smokers included:

• Higher quitting self-efficacy; • Previous quit attempts;

• Having at least some intention to quit;

• Disagreeing that s/he enjoyed smoking too much to quit;

• Having very negative opinion of smoking ; and

• (longer) Time to first cigarette upon waking.

Note: Underlined factors differ to ITC-4 Western countries.

Page 7: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Quit success – Predictors

Independent predictors of quit success among those who made attempts included:

• Older age (40+)

• Having longer previous abstinence from smoking (>=7 months);

• Having more immediate quitting intentions (ie, planning to quit within 1 month)

Note: Underlined factors differ to ITC-4 Western countries.

Page 8: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Discussion

• Chinese smokers less likely to make quit attempts.

– Need for more programs to motivate.

• Predictors of attempts differ.

– May be because smoking is more normative.

• Quit attempts rates among Chinese smokers is indicative of the need for tobacco control efforts in China to increase the need/demand for quitting.

– Anti-smoking campaigns/health education can play an important

role in motivating people to quit smoking.

Page 9: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

Discussion (cont’)

• Percentages staying quit similar.

• Predictors of success differ.

– Intentions predictive in China.

– Those trying to quit may be less addicted.

– Need to understand this better.

Page 10: Predictors of smoking cessation among adult smokers in six cities in China Lin Li, Hua-Hie Yong, Ron Borland, Guoze Feng, Yuan Jiang, Geoffrey T. Fong

• Existing knowledge from Western countries about cessation is not necessarily generalizable to China, which has different social-economic conditions and tobacco control environment.

• Progress may be made by motivating more Chinese smokers to quit.

– Mass public information campaigns are needed.

– Provision of expensive cessation services may not be

as important at least in the short term.

Conclusions