Coronavirus disease 2019 (COVID-19) is a novel infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (1). Since the first cluster of its disease in Wuhan, China, was reported in December 2019, the infection has rapidly expanded worldwide, making World Health Organization (WHO) to declare this as a pandemic on March 11, 2020 (2). The clinical manifestation of the disease varies from fever, myalgia, nonproductive cough to acute respiratory distress syndrome, fulminant myocarditis, and death (3,4). Recognition of the clinical risk factors of severe COVID-19 infection is a high priority to effectively manage this emerging threat of the new virus. Reports have consistently shown that the older age and comorbidities such as hypertension, respiratory system disease and, cardiovascular disease are associated with worse outcomes of COVID-19 (5,6). Gender difference in its association with susceptibility and severity of infectious disease is reported in the past for several other infectious organisms (7). However, the gender difference in regards to the severity of COVID-19 infection has not well been delineated thus far. Therefore, the aim of this study was to investigate how gender difference can affect the disease severity of COVID-19 infection.
MATERIALS AND METHODS
This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (8).
Data Sources and Search
We performed a comprehensive literature search of PubMed and Embase databases from December 1, 2019, to March 26, 2020. The following search terms were applied to include all relevant studies documenting gender information on COVID-19 infection and its association with outcomes: “coronavirus 2019 or 2019-nCoV or sars cov 2 or COVID-19 or COVID; sex or gender or male or female or clinical characteristic or clinical features of clinical course or risk factor.” We conducted an additional manual search of secondary sources, including commentaries and citations of initially identified articles to minimize the risk of missing relevant studies.
Studies were included in our meta-analysis when it was: 1) published in peer-reviewed journals and 2) study that recorded patient characteristics of severe versus nonsevere or survivor versus nonsurvivor in COVID-19 infection. There was no restriction on publication language. Duplicate reports from the same study population were excluded. No contact was made to the authors since there were no missing outcomes for the analysis.
Data Extraction and Quality Assessment
The search was screened by two investigators (H.U., T.K.) independently to assess the eligibility of each study. After the initial screen through titles and abstracts, the full-texts of articles were retrieved and assessed if there were any potential correlations. Any disagreement in the process of study selection and data extraction were resolved by input from the third author (H.T.) (9).
For each eligible study, we extracted the study characteristics (author name, study design, location of the study), patient characteristics (number of patients, age, gender, and comorbidities), and outcome measures.
The Newcastle-Ottawa Assessment Scale was used for each study to assess the quality of the studies (10).
Data Synthesis and Analysis
The endpoints were the rate of severe COVID-19 infection and death. Severe COVID-19 infection was defined by each study. For each included study, the total number and event number for each gender were extracted in regard to each outcome. The pooled results were presented as odds ratios (ORs) and 95% CI. Review Manager Version 5.3 (The Cochrane Collaboration, Copenhagen, Denmark) was used to conduct statistical analysis. A random-effect model was used for the analysis. Mantel-Haenszel effect model was used to calculate the pooled OR and 95% CI of categorical variables.
Literature Search and Study Characteristics
A total of 403 articles were identified after initial database searching and additional records review. After title and abstract screening, 39 articles were extracted for full-text article assessment. Two studies were excluded due to reporting duplicate of the same population (1,11), two were excluded due to the meta-analysis nature of the original article, four were excluded due to lack of information on gender, and 16 were excluded due to the lack of comparison between severity of the infection. Finally, our search identified 15 observational studies (12–26) to be included in our meta-analysis (Fig. 1). Eleven studies compared characteristics of severe versus nonsevere and four compared survivors versus nonsurvivors of COVID-19 infection. The analysis included a total of 3,494 patients with 1,935 (55.4%) males and 1,559 (44.6%) females. The details of the study and patient characteristics are summarized in Table 1. All except one report were from China. The median age ranged from 42.0 to 60.0. The definition of severe COVID-19 infection for each included study is summarized in Table S1 (Supplemental Digital Content 1, http://links.lww.com/CCX/A208). The result of quality assessment by the Newcastle-Ottawa Assessment Scale is summarized in Table S2 (Supplemental Digital Content 1, http://links.lww.com/CCX/A208).
Males were more likely to develop severe COVID-19 infection compared with females (OR, 1.31; 95% CI, 1.07–1.60). There was no significant heterogeneity (I2 = 12%) among the studies (Fig. 2). There was no significant difference in mortality between males and females (OR, 1.53; 95% CI, 0.87–2.69) without significant heterogeneity (I2 = 17%) among studies (Fig. 3).
The salient findings of this meta-analysis are that males were more likely to develop severe COVID-19 infections compared with females, while there was no significant difference in mortality between gender.
Studies have reported significant differences between men and women in regards to prevalence, severity, and even response to vaccination to several other viral illnesses, partially explained by the biological difference in antiviral, inflammatory, and cellular immune response to viruses (27,28). These differences are not only limited to virus but also seen in certain bacteria and parasites (29). Understanding the epidemiology of gender difference in susceptibility and vulnerability to a certain outbreak of infection may be important to effectively respond to or prepare for the public health crisis by minimizing the health, economic and social impact of the emerging outbreak (7,30).
Reports from WHO Europe and Chinese Centers for Disease Control and Prevention widely agree that the COVID-19 infections are seen more frequently in males compared with females (53.6% vs 46.4% and 51.4% vs 48.6%, respectively) (31,32). However, the gender difference on the impact of disease severity of COVID-19 infection is not as well understood due to relatively small study size of each study. Although Guan et al (13) have shown no significant gender difference in requirements of ICU care, Shi et al (15) have found males to be associated with refractoriness of COVID-19 infection. By performing a meta-analysis of studies comparing severe versus nonsevere COVID-19 infection, we were able to provide the largest scale of evidence on gender disparity of severity of COVID-19 infection, concluding that males were more likely to develop severe COVID-19 infection compared with females. In our analysis, mortality was not significantly different between the gender; however, it is likely that the study population was small to exhibit significant differences.
Interestingly, similar findings of males being more susceptible and mounting more severe reaction to virus have been reported in severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), an infection caused by a similar yet different stream of coronavirus. A report from Hong Kong investigating characteristic of SARS have documented males to have significantly higher case fatality rate compared with females (33). Furthermore, MERS has been reported to have a significantly higher incidence in males compared with females (7,34).
The observed findings of gender difference in susceptibility and vulnerability to COVID-19 infection may be multifactorial. Gender differences in behavior may contribute to our findings of males being more susceptible to severe COVID-19 infection. For instance, in the Chinese population, men are reported to have a higher prevalence of smoking compared with women (35). Since all except one of the studies included in the present analysis are reported from China, this could have affected our result. However, to date, there is no firm evidence that smoking is the risk factor of severe COVID-19 infection. Furthermore, underlying differences in gene expression may be associated with different rates of severe COVID-19 infection between gender. For instance, an expression of angiotensin-converting enzyme 2 (ACE2) may also have a significant role in the observed gender difference in COVID-19 infection outcomes. Emerging evidence has suggested that ACE2 is a co-receptor for SARS-CoV-2 viral entry into the human cell that plays a significant role of the pathogenesis of this virus (36). The recent study has suggested that ACE2 expression was higher in Asian males (37), which may have potentially contributed to the findings of this analysis. Other explanations to why men were associated with severe outcomes compared with women in response to COVID-19 infection may involve differences in immunologic reaction and the lack of protective effect of estrogen signaling seen in females; an insight derived from a study of MERS and SARS (38).
The present analysis has several limitations. First, the included studies were retrospective observational studies, and the pooled OR are unadjusted. Furthermore, the lack of individual patient-level data limits our ability to adjust for potential confounders. However, our meta-analysis is valuable since previous studies have shown conflicting results of gender difference in the severity of COVID-19. Second, the definition of severe illness was variable among the studies. Therefore, the results must be cautiously interpreted in regard to potential heterogeneity. Finally, all but one of the included studies were reported from China, potentially limiting its applicability to other countries and races. Nonetheless, this report is thus far the largest study comparing gender difference of vulnerability to this emerging COVID-19 infection.
This meta-analysis suggests that the male gender may be a predictor of more severe COVID-19 infection but does not predict mortality. Further accumulation of evidence from around the world is warranted to confirm our findings.
1. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395:497–506
2. World Health Organization: Rolling Updates on Coronavirus Disease (COVID-19). 2020. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen
. Accessed March 28, 2020
3. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet. 2020; 395:507–513
4. Hu H, Ma F, Wei X, et al. Coronavirus fulminant myocarditis saved with glucocorticoid and human immunoglobulin. Eur Heart J. 2020;ehaa190
5. CDC COVID-19 Response Team: Severe outcomes among patients with coronavirus disease 2019 (COVID-19) — United States FM, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:343–346
6. Yang J, Zheng Y, Gou X, et al. Prevalence of comorbidities in the novel Wuhan coronavirus (COVID-19) infection: A systematic review and meta-analysis. Int J Infect Dis. 2020; 94:91–95
7. Jansen A, Chiew M, Konings F, et al. on behalf the World Health Organization Regional Office for the Western Pacific MERS Event Management Team. Sex matters - a preliminary analysis of Middle East respiratory syndrome in the Republic of Korea, 2015. Western Pac Surveill Response J. 2015; 6:68–71
8. Liberati A, Altman DG, Tetzlaff J. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. J Clin Epidemiol. 2009; 62:e1–e34
9. Takagi H, Kuno T, Hari Y, et al. ALICE (All-Literature Investigation of Cardiovascular Evidence) Group. Prognostic impact of baseline C-reactive protein levels on mortality after transcatheter aortic valve implantation. J Card Surg. 2020; 35:974–980
10. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010; 25:603–605
11. Mo P, Xing Y, Xiao Y, et al. Clinical characteristics of refractory COVID-19 pneumonia in Wuhan, China. Clin Infect Dis. 2020;ciaa270
12. Gao Y, Li T, Han M, et al. Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol. 2020; 92:791–796
13. Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020; 382:1708–1720
14. Qin C, Zhou L, Hu Z, et al. Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin Infect Dis. 2020ciaa248
15. Shi Y, Yu X, Zhao H, et al. Host susceptibility to severe COVID-19 and establishment of a host risk score: Findings of 487 cases outside Wuhan. Crit Care. 2020; 24:108
16. Tian S, Hu N, Lou J, et al. Characteristics of COVID-19 infection in Beijing. J Infect. 2020; 80:401–406
17. Wan S, Xiang Y, Fang W, et al. Clinical features and treatment of COVID-19 patients in Northeast Chongqing. J Med Virol. 2020; 92:797–806
18. Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020; 323:1061–1069
19. Wang Z, Yang B, Li Q, et al. Clinical features of 69 cases with coronavirus disease 2019 in Wuhan, China. Clin Infect Dis. 2020ciaa272
20. Wu C, Chen X, Cai Y, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020e200994
21. Young BE, Ong SWX, Kalimuddin S, et al. Epidemiologic features and clinical course of patients infected with sARS-CoV-2 in Singapore. JAMA. 2020; 323:1488–1494
22. Zhang JJ, Dong X, Cao YY, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy. 2020 Feb 19. [online ahead of print]
23. Tang N, Li D, Wang X, et al. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020; 18:844–847
24. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: A single-centered, retrospective, observational study. Lancet Respir Med. 2020; 8:475–481
25. Yuan M, Yin W, Tao Z, et al. Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China. PLoS One. 2020; 15:e0230548
26. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet. 2020; 395:1054–1062
27. Klein SL, Jedlicka A, Pekosz A. The Xs and Y of immune responses to viral vaccines. Lancet Infect Dis. 2010; 10:338–349
28. Theiler RN, Rasmussen SA, Treadwell TA, et al. Emerging and zoonotic infections in women. Infect Dis Clin North Am. 2008; 22:755–772
29. van Lunzen J, Altfeld M. Sex differences in infectious diseases-common but neglected. J Infect Dis. 2014; 209Suppl 3S79–S80
30. Smith J. Overcoming the ‘tyranny of the urgent’: Integrating gender into disease outbreak preparedness and response. Gend Dev. 2019; 27:355–369
31. The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19). Zhonghua Liu Xing Bing Xue Za Zhi. 2020; 41:145–151
32. World Health Organization: COVID-19 situation update for the WHO European Region: Data for the week of 16-22 March 2020 (Epi week 12). 2020. Available at: http://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/weekly-surveillance-report
. Accessed March 27, 2020
33. Karlberg J, Chong DS, Lai WY. Do men have a higher case fatality rate of severe acute respiratory syndrome than women do? Am J Epidemiol. 2004; 159:229–231
34. Oboho IK, Tomczyk SM, Al-Asmari AM, et al. 2014 MERS-CoV outbreak in Jeddah–a link to health care facilities. N Engl J Med. 2015; 372:846–854
35. Liu S, Zhang M, Yang L, et al. Prevalence and patterns of tobacco smoking among Chinese adult men and women: Findings of the 2010 national smoking survey. J Epidemiol Community Health. 2017; 71:154–161
36. Zhou P, Yang XL, Wang XG, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020; 579:270–273
37. Zhao Y, Zhao Z, Wang Y, et al. Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov. bioRxiv. 2020.01.26.919985
38. Channappanavar R, Fett C, Mack M, et al. Sex-based differences in susceptibility to severe acute respiratory syndrome coronavirus infection. J Immunol. 2017; 198:4046–4053