Background
Health behaviours are influenced by individual characteristics including age, gender, education and economic level. This study aimed to assess the associations between individual-level determinants and adherence to COVID-19 preventive measures.
Methods
We performed secondary analyses of international data collected using an online survey during the first wave of the COVID-19 pandemic between June and December 2020. The dependent variables were self-reported adherence to COVID-19 preventive measures (wearing of face masks, frequent washing/sanitizing of hands, physical distancing, working remotely). The independent variables were age, sex at birth (female vs male), having a chronic disease related elevated risk for severe COVID-19 (none/little, might be at increased risk, at increased risk), educational level completed (no formal education, primary, secondary vs college/university) and employment status (retiree, students, not employed vs employed). Four multivariate logistic regression analyses were conducted to determine the associations between the dependent variables and independent variables. Interaction terms with country-income level were tested in regressions to explore its moderating effect.
Results
Out of 16,866 respondents, 12,634 (74.9%) wore masks or face coverings, 12,336 (73.1%) washed or sanitized their hands frequently, 11,464 (68.0%) reported adherence to physical distancing and 5,646 (33.5%) worked remotely. In adjusted analyses, increased age, college/university education, employment, and having risks for severe COVID-19 were associated with significantly higher odds of adhering to COVID-19 preventive measures. Retirees and students had lower odds of adhering to COVID-19 prevention measures than employed individuals. Males had significantly lower odds of wearing face masks (AOR: 0.901), frequent washing/sanitizing hands (AOR: 0.774) and working remotely (AOR: 0.875) compared to females. Country-income level generally moderated the above relationships such that the associations disappeared in lower income countries.
Conclusion
The study findings suggest that the individual socio-demographic factors—age, sex, employment status, education status and having a chronic disease – influence adherence to COVID-19 preventive measures. Findings further reiterate the need for health education and health promotion campaigns on preventive health measures to focus on subpopulations, such as younger males, students and retirees, that require targeted or unique messaging.