What is already known about this topic? The psychological impact of the large-scale infection of the population resulting from the end of lockdown measures in China during the coronavirus disease 2019 (COVID-19) pandemic is unknown. What is added by this report? Among all participants, 55.7% had depression symptoms, with a significant difference between the infected and non-infected groups, and 30.1% had anxiety. Those who were young, unvaccinated, had lower incomes, and experienced chronic diseases were more likely to experience negative emotions. What are the implications for public health practice? Government officials should take into account the effect of policies on public sentiment during similar public health events and implement tailored community interventions to address any negative sentiment.

BackgroundThe prevalence of cigarette smoking in China is high and the utilization of smoking cessation clinics is very low. Multicomponent smoking cessation interventions involving community and hospital collaboration have the potential to increase the smoking cessation rate. However, the cost-effectiveness of this intervention model is unknown.MethodsWe conducted a smoking cessation intervention trial in 19 community health service centers in Beijing, China. A cost-effectiveness analysis was performed from a societal perspective to compare three strategies of smoking cessation: no intervention (NI), pharmacological intervention (PI), and comprehensive intervention (CI) (PI plus online health promotion). A Markov model, with a time horizon of 20 years, was used to simulate the natural progression of estimated 10,000 male smokers. A cross-sectional survey was conducted to obtain data on costs and quality-adjusted life years (QALYs) by using the five-level EuroQol-5-dimension (EQ-5D-5L) questionnaire. Probabilistic sensitivity analysis was performed to explore parameters of uncertainty in the model.ResultsA total of 680 participants were included in this study, including 283 in the PI group and 397 in the CI group. After 6 months of follow-up, the smoking cessation rate reached 30.0% in the CI group and 21.2% in the PI group. Using the Markov model, compared with the NI group, the intervention strategies of the PI group and the CI group were found to be cost-effective, with an incremental cost-effectiveness ratio (ICER) of $535.62/QALY and $366.19/QALY, respectively. The probabilistic sensitivity analysis indicated that the CI strategy was always the most cost-effective intervention.ConclusionCI for smoking cessation, based in hospital and community in China, is more cost-effective than PI alone. Therefore, this smoking cessation model should be considered to be implemented in healthcare settings.

Background and purposeThe relationship between sleep duration and stroke are inconclusive in China, especially in those individuals with metabolic syndrome. We aimed to investigate the association between sleep duration and incident stroke in participants with metabolic syndrome or its specific components in China.Materials and methodsData were taken from the 2011 and 2015 waves of China Health and Retirement Longitudinal Study (CHARLS). Habitual sleep duration (≤6, 6∼8 [reference], >8 h), daytime napping (0, 1∼60 [reference], and >60 min) were determined by self-reported questionnaires. Metabolic syndrome was defined by blood assessment and biomarkers combined with self-reported doctors’ diagnosis. Incident stroke was determined by reported stroke from 2011 to 2015 wave. Cross-sectional and longitudinal associations between sleep and (incident) stroke at baseline and 4-year follow-up period were tested among the population with metabolic syndrome and its components.ResultsA U-shaped relationship was observed between sleep duration and stroke in cross-sectional analysis. Sleep ≤ 6 h/night had a greater risk of incident stroke (hazard ratio [HR] 1.65; 95% confidence interval [CI] 1.04–2.61) compared with sleep 6∼8 h/night. And the HR of stroke was 1.62 (95%CI, 1.03–2.53) for sleep < 7 h/day compared to 7∼9 h/day. These associations were more evident in the female and individuals aged 45–65 years. Furthermore, the effect of short sleep duration on incident stroke was different in each component of metabolic syndrome, which was more pronounced in participants with elevated blood pressure. And a significant joint effect of sleeping ≤ 6 h/night and no napping on risk of stroke was observed (HR 1.82, 95%CI 1.06–3.12).ConclusionShort sleep duration was an independent risk factor for incident stroke, especially among females, individuals aged 45–65 years, or those with some components of metabolic syndrome, such as hypertension. Napping could buffer the risk of short sleep duration on incident stroke.

Objective To study the effect of social support on quit smoking, to provide theoretical reference and suggestions for the construction of social support for tobacco control. Methods Based on the design idea of case-control study, adult smokers who participated in the community smoking cessation intervention project in Beijing were selected as the study objects, and they were divided into successful quit smoking group and unsuccessful quit smoking group. The status of the public tobacco control policy, community tobacco exposure, and the environment of household tobacco control were compared between groups, and a structural equation modeling was established for ConfirmatoryFactorAnalysis. Results Our descriptive results showed that there were statistical differences in quit smoking results among smokers with different household tobacco control regulations, workplace tobacco control regulations and the number of smokers in the family, meanwhile there were differences in the 6-month smoking reduction with different levels of tobacco harm knowledge promotion and the interval between smoking behaviors at home. And the multivariate analysis indicated that household tobacco control regulations (OR = 1.302, 95%CI: 1.003 ~ 1.690), workplace tobacco control regulations (OR = 1.273, 95%CI: 1.052 ~ 1.540), the interval between smoking behaviors at home (OR = 1.145, 95%CI: 1.019 ~ 1.287) have statistical association with quit smoking. while the results of structural equation modeling found that public tobacco control policy (β = 0.388, P = 0.026) and the environment of household tobacco control (β = 0.368, P = 0.022) had statistical influence on quit smoking. Conclusion Public tobacco control policies and the environment of household tobacco control have substantial impact on the quit smoking. Specifically, household tobacco control regulations, workplace tobacco control regulations, tobacco harm knowledge publicity and the interval between smoking behaviors at home have a positive impact on the quit smoking effect of smokers, and the number of smokers in the family has a negative impact on the quit smoking.