The sex and gender dimensions of COVID-19: A narrative review of the potential underlying factors

Abstract

Multiple lines of evidence indicate that the male sex is a significant risk factor for severe disease and mortality due to coronavirus disease 2019 (COVID-19). However, the precise explanation for the discrepancy is currently unclear. Immunologically, the female-biased protection against COVID-19 could presumably be due to a more rapid and robust immune response to viruses exhibited by males. The female hormones, e.g., estrogens and progesterone, may have protective roles against viral infections. In contrast, male hormones, e.g., testosterone, can act oppositely. Besides, the expression of the ACE-2 receptor in the lung and airway lining, which the SARS-CoV-2 uses to enter cells, is more pronounced in males. Estrogen potentially plays a role in downregulating the expression of ACE-2, which could be a plausible biological explanation for the reduced severity of COVID-19 in females. Comorbidities, e.g., cardiovascular diseases, diabetes, and kidney disorders, are considered significant risk factors for severe outcomes in COVID-19. Age-adjusted data shows that males are statistically more predisposed to these morbidities-amplifying risks for males with COVID-19. In addition, many sociocultural factors and gender-constructed behavior of men and women impact exposure to infections and outcomes. In many parts of the world, women are more likely to abide by health regulations, e.g., mask-wearing and handwashing, than men. In contrast, men, in general, are more involved with high-risk behaviors, e.g., smoking and alcohol consumption, and high-risk jobs that require admixing with people, which increases their risk of exposure to the infection. Overall, males and females suffer differently from COVID-19 due to a complex interplay between many biological and sociocultural factors.

Keywords: Biological difference; COVID-19; Gender disparities; Risk factors; Sociocultural effects.

Graphical abstract

Fig. 1

Age, sex, existing conditions of COVID-19 cases and deaths. (a) Percent probability of dying for a patient with a given pre-existing condition. (b) Percent probability of dying depending on the age group. (c) In 10-year age bands by sex, deaths per 100,000 population and sex ratio. (d) Percent probability of dying for a patient by sex. $\mathit{Death}\mathit{rate}=\frac{\mathit{No}.\mathit{of}\mathit{deaths}}{\mathit{No}.\mathit{of}\mathit{cases}}=\mathit{probability}\mathit{of}\mathit{dying}when\mathit{infected}\mathit{by}\mathit{the}\mathit{virus}\left(\%\right)$. The percentages shown in panels a, b, and d do not add up to 100%, as they do not represent share of deaths by condition. CRD = chronic respiratory diseases, HTN = hypertension, DM = diabetes, CVD = cardiovascular disorders.

Fig. 2

A partial overview of the immune system. Left panel: innate immune cells, middle: dendritic cell (DC) as a sensor cell, it recognizes virus RNA through PRR and DC act as antigen-presenting cell, found higher in the females, right panel: Cytotoxic T cell (CTL), Th1 can kill virus-infected cells present higher in female and basal antibody is also higher.

Fig. 3

Testosterone promotes viral entry via upregulating TMPRSS2 transcription (Gebhard et al., 2020). The entry of androgen (a) stimulates heat shock protein (HSP) to activates androgen receptor (AR) (b), and phosphorylated AR homodimer translocate to the nucleus to (c) bind to androgen response element (ARE). This (d) upregulates the transcription of TMPRSS2. Upregulation of TMPRSS2 protein (f) promotes virus entry (g) to the cells.

Fig. 4

Sex disaggregated data on identified cases and deaths due to COVID-19 across countries included in the Global Health 50/50 tracker (as of 30 Nov 2020) (Global Health 50/50, 2022). (a) Male to female case identification rate in countries reporting >10,000 identified cases (N = 41,840,331) where the sex-disaggregated data is available. (b) Male to female death rate among male and female in countries reporting >1000 COVID-19 related death incidences (N = 1,155,509) where the sex-disaggregated data is available. The name of the countries is ordered alphabetically. (c) The proportion of death in male and female confirmed cases.