Sleep quality and associated factors during the COVID-19 epidemic among community non-medical anti-epidemic Workers of Wuhan, China.

BACKGROUND: Since the outbreak of Coronavirus Disease 2019 (COVID-19) in December 2019, community non-medical anti-epidemic workers have played an important role in the prevention of COVID-19 in China. The present study aimed to assess sleep quality and its associated factors among community non-medical anti-epidemic workers. METHOD: A survey was conducted using anonymous online questionnaire to collect information from 16 March 2020 to 24 March 2020. A total of 474 participants were included, with a 94.23% completion rate. The questionnaire contained demographic data, physical symptoms, and contact history with COVID-19. The researchers assessed perceived social support by the Multidimensional Scale of Perceived Social Support (MSPSS), assessed perceived stress by the Perceived Stress Scale (PSS), and measured sleep quality by the Pittsburgh Sleep Quality Index (PSQI) questionnaire. RESULTS: Among the participants, 46.20% reported poor sleep quality. A binary logistic regression revealed that having educational background of junior college or above, being a member of the police force, having contacted individuals with confirmed or suspected COVID-19 infection, having chronic disease(s), having illness within 2 weeks, and having high or moderate perceived stress were significant factors associated with an increased risk of poor sleep quality. CONCLUSION: Demographic factors, physical symptoms, history of contact with COVID-19, and perceived stress are significantly associated with poor sleep quality of community non-medical anti-epidemic workers. Thus, targeting these factors might be helpful in enhancing sleep quality of community workers.

Study on Factors of People's Wearing Masks Based on Two Online Surveys: Cross-Sectional Evidence from China.

(1) Background: To analyze factors of people's wearing masks based on two online surveys, and to explore whether living area factor or quarantine status could have an impact on mask-wearing. (2) Methods: Chi-square test and logistic regression analysis were used to explore the influence of different factors on people's behavior of mask-wearing in the present study. R3.6.2 was used for data cleaning, SPSS 26.0 was used to conduct corresponding statistical analysis, and a two-sided p-value less than 0.05 was considered to be statistically significant. (3) Results: According to our study, the proportion of participants who wore face masks was higher than 90.0% in both surveys. Single factor analysis showed that the proportion of people wearing face masks raised with the increase of people's education, age, and monthly income (Yuan) in both surveys. People who lived in rural areas were less likely to wear masks. Mask-wearing rate was lower in the isolated individuals than in the non-isolated ones. (4) Conclusions: Masks-wearing is one of the effective measures for COVID-19 pandemic prevention and control. After the Chinese government made wearing face masks mandatory in public places, most residents in China had developed the habit of wearing masks, contributing to the high rate of masks-wearing in China. However, people in rural areas need to raise their awareness of wearing masks. Meanwhile, the mask-wearing of the isolated individuals needs to be enhanced.