Demographic and social correlates and indicators for behavioural compliance with personal protection among Chinese community-dwellers during COVID-19: a cross-sectional study.

ABSTRACT

OBJECTIVES: Examine compliance with personal protective measures in communities for the prevention and control of local transmission of the COVID-19, and explore indicators for such behavioural compliance. DESIGN: Cross-sectional design with a self-selecting sample. Data collected in February 2020. SETTING: Community dwellers in China. PARTICIPANTS: 2956 participants aged 16 and above completed the study and were included in the analysis. OUTCOME MEASURES: Nationwide COVID-19 survey. Demographics and self-reported compliance with four personal protective measures-home quarantine, mask-wearing, temperature-taking and hand-sanitising were collected. Outbreak severity and timeliness of personal protection order were obtained from the China Center for Disease Control and Prevention website. Logistic regression models were employed to examine the association between demographic and social indicators and behavioural compliance. RESULTS: Compliance with home quarantine was only associated with gender (men, OR=0.61 (0.51-0.73), inverse association) but no other indicators. In contrast, men had higher compliance with mask-wearing (OR=1.79 (1.49-2.16)) and temperature-taking (OR=1.27 (1.05-1.53)). Compared with younger adults (≤20 years), the middle-age groups (31-40 and 41-50 years of age) were more compliant with all protective behaviours, except for home quarantine (OR=0.71 (0.54-0.93) and 0.67 (0.46-0.97), respectively). CONCLUSION: Male gender was associated with lower compliance with home quarantine yet higher compliance with mask-wearing and temperature-taking. The middle-age participants (31-50 years) had lower compliance with home quarantine but higher with other measures. These findings may be supported by the economic considerations and the long-inherited Confucian values among Chinese. In light of the ongoing COVID-19 pandemic, public health authorities should tailor policy implementation to disparities in psychosocial indicators.