3.7.7: Gender and COVID-19 Outcomes
- Page ID
- 59216
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)In the early stages of the COVID-19 pandemic, researchers noted a pattern of much higher mortality among men when compared to women (Grasselli et al. 2020; Jin et al. 2020). This trend led researchers to hypothesize the existence of biological sex-related factors in susceptibility to the virus. These results suggested the possibility of sex-specific clinical and public health interventions (Gebhard 2020; Peckham et al. 2020; Pivonello et al. 2021; Scully et al. 2020; Bunders and Altfeld 2020; Hussain et al. 2020; Klein et al. 2020; Takahashi et al. 2020; Wolfe et al. 2021).
However, a later study argued that the variation that was attributed to sex observed in COVID-19 data is rather likely explained by variations in data collection practices, gender- (not sex) based patterns in health behaviors, occupational exposures, and health conditions. Further, the gender-based effect may vary according to other issues such as socioeconomic status, geography, and race or ethnicity (Danielsen et al. 2022). This is of interest to researchers because the shift of the focus from sex to gender implies that there may not necessarily be biological factors involved in the difference.
The study analyzed weekly data from April 27, 2020, through the week of May 10, 2021, of sex categorized COVID-19 cases and mortality for the United States. The data were collected from state public health websites. The data suggested moderately higher COVID-19 mortality rates for men. It should first be noted that in the United States men had higher mortality rates than women before the pandemic. Interestingly, the data provided little evidence that COVID-19 changed this dynamic. The authors of the study argued that this could indicate that the disparity in COVID-19 outcomes between men and women did not have to do with a specific, sex-linked male vulnerability to COVID-19, but reflects a set of complex biosocial factors as well as the systemic health and social inequities of men and women in different socioeconomic groups.
The conclusions of this study were based on an observational study as the researchers did not control any of the factors associated with sex or COVID-19. The authors of the study pointed out that the problem was essentially confounding because of the unequal rates of preexisting health conditions between women and men across various social groups. For example, heart conditions are associated with poorer COVID-19 outcomes and mortality (Bae et al. 2021; Madjid et al. 2020). At the same time the prevalence is not evenly distributed across age and sex, and in fact older men tend to have higher rates of cardiovascular disease (James et al. 2018; Mosca et al. 2011). This means that the higher COVID-19 mortality rates may reflect the fact that these preexisting health conditions vary across sex, and the high prevalence of the preexisting health conditions for men drove up the mortality rate from COVID-19. In the observed data, this effect could not be distinguished from a sex-specific biological effect on COVID-19 mortality.