They also found that visiting a doctor or health professional is enough to increase third the odds of making a quit attempt as well as quitting successfully, which is encouraging. However, strangely they also found that those who used any NRT or Zyban for quitting were also more likely to relapse compared with those who quit without any assistance, perhaps due to differential memory effects, something recently demonstrated in Western smokers (Borland, Partos, & Cummings, 2011). Nevertheless, the social variations in nicotine dependence, self-efficacy, and quit interest also suggest that any population-level intervention for smoking cessation may be less effective for those from lower SES groups and specific targeting may be necessary to reach this group to ensure effectiveness and to help reduce the disparity in cessation rates across socio-economic groups.

China ratified the Framework Convention on Tobacco Control in 2005 and it is obliged, under article 14, to assist Chinese smokers to quit. This is also consistent with one of its major goals under the 12th five-year plan, endorsed by the National People��s Congress in March, 2011, to improve the life expectancy of Chinese population by 1 year (Zhu, Young-soo, & Beaglehole, 2012). This study has several limitations that warrant mention. First, the use of self-report data particularly for quitting activity may lead to either under-reporting of brief attempts and those that occur long time ago (Borland et al., 2011) or over-reporting of quit success because of social desirability bias, both of which could artificially inflate the quitting success rate.

Second, because of attrition, respondents Cilengitide from higher socio-economic background were under-represented in our longitudinal sample, and although attempts were made in all our models to control for any baseline differences between those included/retained and those excluded/lost to the study, caution should be exercised when generalizing our findings as there may be other unmeasured differences between the two groups, which, if present, could result in some confounding of effect found. Third, our findings were based on sample from seven cities and thus, may not generalize to the rest of China especially to those who live in the vast rural regions. However, a major strength of this study is its longitudinal design. The use of GEE models for analysis also helps to maximize the cases available for analyses, thus, increasing the power of detection of effects. The use of multiple indicators of SES is another strength as the consistency of the findings across measures suggests that any effect found is not idiosyncratic to a particular measure.