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BackgroundTobacco use is still highly prevalent globally in spite of the tobacco control efforts made by the governments. In view of the harm of smoking and relapse after smoking cessation, the purpose of this study is to establish a competitive risk model to determine potential risk factors for smoking relapse.MethodsThe population-based cohort of ex-smokers over the age of 18 years was obtained from the China Family Panel Studies (CFPS) database from 2010 to 2018. Competing risk models were conducted to identify the risk factors for relapse.ResultsA total of 1,019 subjects were included in this study, of which 311 (30.52%) subjects relapsed during the follow-up period. A multivariate analysis indicated that age < 40 years [hazard ratio (HR) 19.142; 95% CI: 10.641–34.434, p < 0.01], cohabitation (HR: 1.422; 95% CI: 1.081–1.87, p = 0.01), and often depression [HR 1.422; 95% CI, (1.081–1.87), p = 0.01] were associated with a great risk of relapse while the age of quitting smoking < 60 years (HR: 0. 436; 95% CI: 0.229–0.831, p < 0.01) and joining the Chinese Communist Party (CCP) (HR 0.611; 95% CI: 0.397–0.939, p = 0.03) were reduced risk factors for relapse.ConclusionsApproximately 3 in 10 ex-smokers were observed to relapse. There are various risk factors for relapse as well. In the face of such a serious situation, it is urgent to take action to control smoking.

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Background The mental well-being of older people has become social concern under aging times in China. Social capital has been linked to mental well-being. Our aims were to explore how social capital and the state of mental well-being of older people were changing and what the relationship between them was. Methods Data were from six waves of the China Family Panel Studies that were conducted between 2010 and 2020, and a total of 1,055 participants aged 60 and over were included in the analysis. The Generalized Estimated Equation model (GEE) was used to clarify the long-term relationship, and to use GEE we first defined how time points were related, in other words, an appropriate working correlation structure was supposed to choose. Therefore, correlation coefficient between measurements at two time points was calculated to choose the exchange structure. All the analyses were performed in the statistical software Stata 15.0. Results The mental well-being of older people has deteriorated over time, especially we found that between 2014 and 2016, the mental well-being of older people plummeted. In addition, cognitive social capital was positively correlated with mental well-being, while structural social capital was inverse. Conclusions Policymakers are supposed to take into account the long-term impact of cognitive and structural social capital on the mental well-being of older people and to provide them with projects aimed at increasing cognitive social capital and turning the pressure of structural social capital into a source of happiness in life.

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