Objective Evaluate the risk of pre-existing comorbidities on COVID-19 mortality, and provide clinical suggestions accordingly. Setting A nested case–control design using confirmed case reports released from the news or the national/provincial/municipal health commissions of China between 18 December 2019 and 8 March 2020. Participants Patients with confirmed SARS-CoV-2 infection, excluding asymptomatic patients, in mainland China outside of Hubei Province. Outcome measures Patient demographics, survival time and status, and history of comorbidities. Method A total of 94 publicly reported deaths in locations outside of Hubei Province, mainland China, were included as cases. Each case was matched with up to three controls, based on gender and age ±1 year old (94 cases and 181 controls). The inverse probability-weighted Cox proportional hazard model was performed, controlling for age, gender and the early period of the outbreak. Results Of the 94 cases, the median age was 72.5 years old (IQR=16), and 59.6% were men, while in the control group the median age was 67 years old (IQR=22), and 64.6% were men. Adjusting for age, gender and the early period of the outbreak, poor health conditions were associated with a higher risk of COVID-19 mortality (HR of comorbidity score, 1.31 [95% CI 1.11 to 1.54]; p=0.001). The estimated mortality risk in patients with pre-existing coronary heart disease (CHD) was three times that of those without CHD (p<0.001). The estimated 30-day survival probability for a profile patient with pre-existing CHD (65-year-old woman with no other comorbidities) was 0.53 (95% CI 0.34 to 0.82), while it was 0.85 (95% CI 0.79 to 0.91) for those without CHD. Older age was also associated with increased mortality risk: every 1-year increase in age was associated with a 4% increased risk of mortality (p<0.001). Conclusion Extra care and early medical interventions are needed for patients with pre-existing comorbidities, especially CHD.

The study was designed to examine the relationships between sleep disturbance, negative affect and quality of life among patients with maintenance hemodialysis. A total of 118 patients in Shanghai, China, with maintenance hemodialysis (>40 years old) participated in the study. They completed three questionnaires: the Positive and Negative Affect Scale (PANAS), the Pittsburgh Sleep Quality Index (PSQI) and the European Quality of 5-Dimensions (EQ-5D-5L). Results showed that male participants’ negative affect scored significantly higher than female participants’.The mean global PSQI score was 8.64 (poor sleepers score 6 or more); sleep disturbance affected 63.6% of the patients, which indicated that in general the participants’ sleep quality was relatively poor.The patients with worse sleep quality and negative affect were more likely to have a lower quality of life. In addition, the effect of the sleep disturbance on quality of life was mediated by negative affect (The Z value of Sobel test was -3.18, p< .01).These findings suggest sleep disturbance and negative affect were common among patients with maintenance hemodialysis and had a negative impact on their quality of life; negative affect may mediate the relationship between sleep disturbance and quality of life.

E-cigarettes are widely advertised, while the potential risks of e-cigarette use have been reported among adolescents. This study assessed online e-cigarette information exposure and its association with adolescents’ e-cigarette use in Shanghai, China. A total of 12,470 students aged 13–18 years participated. A questionnaire collected information on students’ sociodemographic factors, e-cigarette information exposure, cigarette use, e-cigarette use, and e-cigarette use intention. A multivariate logistic regression was performed to assess correlates of exposure to e-cigarette information and the association between e-cigarette information exposure and e-cigarette use. Overall, 73.9% of students knew about e-cigarettes and the primary sources of information were the internet (42.4%), movies/TV (36.4%), bulletin boards in retail stores or supermarkets (34.9%), advertising flyers (33.9%), and friends (13.8%). Students who had friends using e-cigarettes were curious about e-cigarettes and showed a greater monthly allowance; smokers and females were at a higher risk of social media and website exposure. Moreover, online information exposure (social media exposure, website exposure, and total internet exposure) was significantly associated with the intention to use e-cigarettes. The enforcement of regulations on online e-cigarette content should be implemented. Moreover, efforts to prevent young people from using e-cigarettes may benefit from targeting students at a higher risk of online e-cigarette information exposure.