Objective This study aimed to assess household preparedness for emergency events and its determinants in China. Design A cross-sectional questionnaire survey was conducted on 3541 households in China in 2015. Participants Households were selected using a stratified cluster sampling strategy, representing central, eastern, western and southern regions of China. The designed questionnaires were administered through face-to-face interviews. Outcome measures Household emergency preparedness was measured with 14 indicators, tapping into the supply of nine emergency necessities (food and water, extra batteries, battery-powered radio, battery-operated torch, first-aid kit, gas mask, fire extinguisher, escape ropes, whistle), coverage of accident insurance, knowledge of local emergency response systems (emergency numbers, exit routes and shelters) and availability of a household evacuation plan. If an individual acted on 9 of the 14 indicators, they were deemed well prepared. Logistic regression models were established to identify predictors of well preparedness based on 3541 returned questionnaires containing no missing values. Results Only 9.9% of households were well prepared for emergencies: 53.6% did not know what to do and 31.6% did not want to think about it. A higher level of preparedness was found in the respondents who have attained higher education (adjusted OR=0.826 compared with the higher level), participated in emergency training activities (adjusted OR=2.299), had better emergency knowledge (adjusted OR=2.043), reported less fate-submissiveness (adjusted OR=1.385) and more self-reliance (adjusted OR=1.349), prior exposure to emergency events (adjusted OR=1.280) and held more positive attitudes towards preparedness (adjusted OR=1.286). Conclusion Household preparedness for emergency events is poor in China. Lack of motivation, negative attitude to preparedness and knowledge shortfall are major but remediable barriers for household preparedness.

This study seeks to measure the efficiency disparity and productivity change of tertiary general public hospitals in Wuhan city, central China from the perspective of administrative affiliations by using panel data from 2013 to 2017. Sample hospitals were divided into three categories, namely provincial hospitals, municipal hospitals, and other levels of hospitals. Data envelopment analysis with bootstrapping technique was used to estimate efficiency scores, and a sensitive analysis was performed by varying the specification of model by considering undesirable outputs to test robustness of estimation, and efficiency evolution analysis was carried out by using the Malmquist index. The results indicated that the average values of provincial hospitals and municipal hospitals have experienced efficiency improvement over the period, especially after the initiation of Pilot Public Hospital Reform, but hospitals under other affiliations showed an opposite trend. Meanwhile, differences of administrative subordination in technical efficiency of public hospitals emerged, and the disparity was likely to grow over time. The higher efficiency of hospitals affiliated with municipality, as compared with those governed by province and under other administrative affiliations, may be attributed to better governance and organization structure.

Background: Insufficient and poor-quality sleep have significant negative health consequences for university students in China. In this study, we aimed to assess the subjective sleep quality of university students during the normalisation of COVID-19 epidemic prevention and control in China and to identify key factors affecting their sleep quality. Materials and Methods: A cross-sectional survey was conducted among 1326 university students from Hubei Province, China. Latent profile analysis was conducted on the results of class-difference tests of sleep patterns. Multinomial logistic regression was used to explore the relationship between the influencing factors and three classes of sleep quality. Results: The overall score of sleep quality (9.18 ± 3.22) among university students was assessed by using the PSQI scale, and 427 (32.20%) students reported poor sleep quality. Three distinct classes of sleep patterns were identified, namely, good sleepers (Class 1, 70.44%), poor sleep quality with less medication use (Class 2, 26.55%) and poor sleepers (Class 3, 3.01%). Conclusions: Compared with ‘good sleepers’, students having ‘poor sleep quality with less hypnotic drug use’ were influenced by their education stage, smoking habits, physical activity, depression and anxiety. Meanwhile, ‘poor sleepers’ may be affected by their age, origins, smoking habits, mental stress, depression and anxiety. Significant heterogeneity was confirmed in the sleep patterns of university students. Their behavioural lifestyles and mental health-related factors demonstrated different relationship patterns with sleep quality. Multiple sleep promotion interventions, including moderate aerobic exercises, psychological counselling and mindfulness training, should be regularly performed in groups to improve their sleep quality.