Using multivariate models to examine the impact of COVID-19 pandemic and gender differences on health and health care
Abstract
Objective
To examine the effect of the COVID-19 pandemic, the effect of sex, and the joint effect of sex and the COVID-19 pandemic in relation to health communication, physical activity, mental health, and behavioral health.
Methods
We drew data from the National Cancer Institute’s 2020 Health Information National Trends Survey (HINTS). We described and compared the characteristics of social determinants of health, physical activity, mental health, alcohol use, patterns of social networking service use, and health information data sharing. Analyses were weighted to provide nationally representative estimates. Multivariate models (multiple linear regression, multiple logistic regression, and multinomial logistic model) were used to assess the sole and joint effect of sex and pandemic. In addition, we applied the Bonferroni correction to adjust p-values to decrease the risks of type I errors when making multiple statistical tests.
Results
Women are more likely to use mobile health and health communication technologies. The effect of sex after the COVID-19 pandemic is significant on mental health, and women are more possible to have depression or anxiety disorders. The effect of sex is also significant before and after the pandemic regarding seeking health or medical information. Women have a smaller quantity and intensity of physical activity, which has a negative effect on health.
Conclusion
Gender differences exist regardless of the COVID-19 pandemic and the pandemic amplifies the differences in some health and health care domains. Intersectional gender analyses are integral to addressing issues that arise and mitigating the exacerbation of inequities. Responses to the pandemic should consider diverse perspectives, including sex and gender.
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