Secondary Logo

Journal Logo

Original Studies

Effect of sex hormones on coronavirus disease 2019: an analysis of 5,061 laboratory-confirmed cases in South Korea

Lee, Jae Hoon MD1; Kim, Yong Chan MD2; Cho, Si Hyun MD, PhD1; Lee, Jinae PhD3; You, Seng Chan MD4; Song, Young Goo MD, PhD2; Won, Young Bin MD5; Choi, Young Sik MD, PhD5; Park, Yun Soo MD, PhD6

Author Information
doi: 10.1097/GME.0000000000001657


In South Korea, since the identification of the first confirmed case on January 20, 2020, coronavirus disease 2019 (COVID-19) cases have been identified sporadically in the early stages of the outbreak. After February 19, several patients were identified from religious groups and long-term care facilities. Subsequently, an exponential rise in the number of confirmed cases nationwide was observed.1 Infection spread has been mitigated by adherence to social-distancing measures, mask-wearing, contact-tracing, and isolation of confirmed cases. Although the number of confirmed cases reached 10,752 with 244 deaths as of April 28, the acute upward slope seems to have been flattened.2

Sex has been observed to be a factor of marked importance in the short history of the COVID-19 pandemic. According to several studies, men have higher rates of COVID-19-related morbidity and mortality than women.3,4 Some studies have suggested that sex hormones may affect the susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent mortality.3-6 Based on these findings, a clinical trial is recruiting COVID-19 patients to evaluate the effect of female sex hormones on the clinical outcomes of patients by administering estrogen to adult men or postmenopausal women with low levels of female sex hormones ( Identifier: NCT04359329). Presently, only a few published studies on the effects of sex hormones on the morbidity and mortality of COVID-19 are available. Understanding the effects of sex hormones on SARS-CoV-2 infection may assist in the identification of high-risk patients, prognosis prediction, and triage of patients for hospitalization during the current pandemic. The sex-specific disparities in morbidity and mortality of COVID-19 observed in several countries may be considered as indirect evidence of the effects of sex hormones on SARS-CoV-2 infection. However, these findings have not been reported in all countries, and sex-specific morbidity and mortality vary significantly by region. Moreover, only a few studies have reported a female-dominant sex ratio for COVID-19 morbidity. In South Korea, confirmed cases were more common in women, and COVID-19 was the most prevalent in young adults.7 For understanding this disease better, it is worthwhile to examine the epidemiological findings in South Korea, which are different than those in other countries. In this study, we evaluated the sex-specific characteristics of patients with laboratory-confirmed COVID-19 in an epidemiologic setting in South Korea using nationwide claims data and investigated the effects of female sex hormones on the clinical course and disease severity of COVID-19.


Patient data

We performed a retrospective cohort study using the Health Insurance Review and Assessment (HIRA) dataset, consisting of data from adult patients (age ≥20 y) with laboratory-confirmed COVID-19 between January 20, 2020, and April 8, 2020, in South Korea. The South Korean government operates a mandatory nationwide insurance system (National Health Insurance), which covers all forms of health services including hospitalization, ambulatory care, and pharmaceutical services. All healthcare utilization information is registered under a comprehensive database operated by the HIRA. Medical institutions submit the healthcare utilization information via electronic forms for reimbursement purposes, and this information is integrated into the HIRA claims database, which covers the entire population of South Korea (approximately 51 million). Thus, the database contains information on most patients, including data on ambulatory care histories, principal diagnoses, prescriptions, procedures, and comorbidities, based on the Korean Standard Classification of Diseases and Causes of Death, 7th edition (KCD-7), a modified version of the International Classification of Disease 10th revision. Details of the HIRA database are described elsewhere.8

The KCD-7 codes for the diagnosis of COVID-19 and patients’ comorbidities are described in the supplementary table (Supplemental Table 1, Underlying comorbidities were defined as the reimbursement of the KCD-7 code of study diseases within 5 years prior to the diagnosis of COVID-19. Drug codes for estrogen therapy, estrogen plus progestogen therapy, and tibolone were used for identifying the use of hormone therapy (HT) in female patients. Recent use of HT was defined as the prescription of HT drug codes for more than 1 month after January 2019. Nonuse of HT was defined as no prescription of HT drug codes for the 5 years covered by the database.

Diagnosis and treatment

During the study period, all patients with COVID-19 were diagnosed and treated according to the guidelines published by the Korea Centers for Disease Control.2 The reverse-transcription polymerase chain reaction test was used for detecting SARS-CoV-2. Sputum, nasal, and oropharyngeal samples were collected from the individuals. Clinical specimens were tested with reagents, authorized for emergency use, in public facilities, medical institutions, or entrusted facilities. A person who tested positive was confirmed to be infected with SARS-CoV-2, regardless of the presence of any clinical symptoms. After confirming the diagnosis, patients were classified based on their condition. Patients with mild disease with no need for hospitalization or special treatments were monitored at residential treatment centers. Meanwhile, those with moderate-to-severe disease were admitted to medical institutions. At medical institutions in South Korea, several patients were treated according to the management protocol issued by the Korean Society of Infectious Diseases, Korean Society for Antimicrobial Therapy, and Korean Society for AIDS. The treatment guidelines have been revised and updated during the outbreak. The latest guidelines on antiviral therapy for COVID-19 were issued on May 19, 2020.9 When antiviral therapy was considered for patients with laboratory-confirmed COVID-19, the majority were treated with hydroxychloroquine or lopinavir/ritonavir as soon as possible. Combination therapy with type I interferon or ribavirin was initiated in patients showing an inadequate clinical response despite hydroxychloroquine or lopinavir/ritonavir administration.

Statistical analysis

Comparisons between male and female COVID-19 patients were performed using descriptive statistics. The results were presented as numbers (percentages) for categorical variables and means ± standard deviations for continuous variables. Continuous variables were compared using an independent t test, and categorical variables were compared using the chi-squared test or Fisher exact test. Cox proportional hazard regression analysis was performed for identifying the risk factors of mortality among the covariate variables of sex, age ≥65 years, and seven comorbidities (cardiovascular disease, cerebrovascular disease, hypertension, diabetes, pulmonary disease, malignancy, and chronic kidney disease).

HT was usually prescribed for women in their 40s-60s. To attenuate the age effect for evaluating the association of HT with the clinical outcomes of female patients, a propensity score matching technique was adopted. The propensity score was calculated using a logit model for matching recent HT female patients in the treatment group and never HT female patients in the control group according to age and predicting probabilities within a caliper of 0.25. A 1:3 propensity score matching was fulfilled to match the recent HT patients with non-HT patients and confirmed the age balanced between the recent HT and non-HT patients. All statistical analyses were performed using SAS Enterprise Guide (SAS Institute Inc., Cary, NC). Results with a P value of < 0.05 were considered statistically significant. The study protocol was approved by the institutional review board (3-2020-0072) of Yonsei University College of Medicine, Gangnam Severance Hospital (Seoul, Republic of Korea), and the protocol adhered to the tenets of the Declaration of Helsinki. Since the study was retrospective and the study participants were anonymized, the institutional review board waived the requirement for written consent from the patients.


Figure 1 shows the trend of patients with laboratory-confirmed COVID-19 between January 20, 2020, and April 8, 2020, in South Korea. During the period, a total of 10,384 patients infected with SARS-CoV-2 were reported to the Korea Center for Disease Control and Prevention. Of those, 5,061 adult patients with confirmed COVID-19 were included in our study. The clinical characteristics and outcomes of the patients are reported in Table 1. Confirmed cases were more common in women (2,832 [56%]) than in men (2,229 [44%]). The mean age was 45.62 ± 18.05 years in men and 44.88 ± 17.49 years in women. There were sex- and age-specific disparities in the number of confirmed COVID-19 cases (Fig. 2A). COVID-19 was the most prevalent in the 20-39 years age group for both sexes (993 [44.55%] in men and 1,250 [44.14%] in women). Additionally, the number of patients was higher among women than among men in all age groups. The most common comorbidity was hypertension (296 [13.3%] men and 316 [11.2%] women, P = 0.022), followed by diabetes (234 [10.5%]) in men and chronic pulmonary disease (241 [8.51%]) in women. The rates of oxygen therapy administration (144 [6.46%] vs 131 [4.63%], P = 0.004) and intensive care unit (ICU) admission (60 [2.69%] vs 53 [1.87%], P = 0.049) were higher in men than in women. The length of stay after admission to the ICU was longer in men than in women (19.7 ± 11.80 vs 14.75 ± 9.23, P = 0.016); however, the length of stay in hospitalized patients in general was longer in women than in men (6.0 ± 8.03 vs 5.02 ± 7.40, P < 0.001). There was no significant difference in the mortality rate between men (n = 42, 1.88%) and women (n = 42, 1.48%) (P = 0.267) (Table 1). The mortality increased with age, and the largest number was observed in the >70 years age group (28 men [9.69%] and 31 women [10.65%]) (Fig. 2B). The multivariable Cox analysis revealed that age >65 years (hazard ratio [HR], 14.335; 95% confidence interval [CI], 8.239-24.942), cardiovascular disease (HR, 2.316; 95% CI, 1.053-5.094), and malignancy (HR, 4.332; 95% CI, 1.533-12.242) were the risk factors for mortality (Table 2).

FIG. 1
FIG. 1:
Trend of confirmed coronavirus disease cases over time between January 20, 2020, and April 8, 2020, in South Korea.

TABLE 1 - Clinical characteristics and outcomes of 5,061 adult patients with confirmed COVID-19 in South Korea
Variables Male (n = 2,229) Female (n = 2,832) P value
Age, y 45.62 ± 18.05 44.88 ± 17.49 0.140
Comorbidities, no. (%)
 Cardiovascular disease 18 (0.81) 31 (1.09) 0.994
 Cerebrovascular disease 13 (0.58) 6 (0.21) 0.032
 Hypertension 296 (13.28) 316 (11.16) 0.022
 Heart failure 51 (2.29) 82 (2.90) 0.18
 Diabetes 234 (10.50) 185 (6.53) 0.079
 Pulmonary disease 188 (8.43) 241 (8.51) 0.924
 Malignancy 21 (0.94) 18 (0.64) 0.216
 Chronic kidney disease 15 (0.67) 10 (0.35) 0.107
 Chronic liver disease 2 (0.09) 3 (0.11) >0.999
Treatments, no. (%)
 Oxygen therapy 144 (6.46) 131 (4.63) 0.004
 Invasive mechanical ventilation 7 (0.31) 3 (0.11) 0.098
 Extracorporeal membrane oxygenation 1 (0.04) 1 (0.04) 0.865
 Renal replacement therapy 7 (0.31) 6 (0.21) 0.476
Clinical outcomes
 ICU admission, no. (%) 60 (2.69) 53 (1.87) 0.049
 Length of ICU stay, d 19.7 ± 11.80 14.75 ± 9.23 0.016
 Length of hospital stay for admitted patients, d 5.02 ± 7.40 6.0 ± 8.03 <0.001
Mortality, no. (%) 42 (1.88) 42 (1.48) 0.267
COVID-19, coronavirus disease 2019; ICU, intensive care unit.

FIG. 2
FIG. 2:
Sex- and age-specific disparities in coronavirus disease cases. (A) Confirmed cases; (B) mortality cases.

TABLE 2 - Multivariable Cox proportional hazard model for mortality of patients with confirmed COVID-19
Variables Hazard ratio 95% Confidence interval P value
Sex (female vs male)
 Male (reference) Reference
 Female 0.854 0.549-1.327 0.482
Age (≥65 vs <65)
 <65 (reference) Reference
 ≥65 14.335 8.239-24.942 <0.001
 Cardiovascular disease 2.316 1.053-5.094 0.037
 Cerebrovascular disease 0.471 0.065-3.435 0.458
 Hypertension 1.238 0.758-2.021 0.691
 Diabetes 1.524 0.909-2.553 0.110
 Pulmonary disease 0.586 0.265-1.296 0.187
 Malignancy 4.332 1.533-12.242 0.006
 Chronic kidney disease 1.256 0.305-5.179 0.752
COVID-19, coronavirus disease 2019.

In the subgroup analysis, the clinical characteristics of 53 recent HT users and 159 non-HT users were compared (Table 3). The mean ages were 49.40 ± 11.04 and 49.40 ± 10.97 years in the corresponding groups, respectively. Hypertension was the most common comorbidity in recent HT users (5 [9.43%]) and in non-HT users (17 [10.69%]). Although statistical significance was not observed, non-HT users were more likely to receive oxygen therapy (10 [6.29%] vs 1 [1.89%], P = 0.211), whereas recent HT users were likely to have a longer length of stay after admission to the ICU (19.0 ± 15.56 vs 15.67 ± 7.87 d, P = 0.210). In these groups, only one death was reported in the non-HT user group during the follow-up period.

TABLE 3 - Clinical characteristics and outcomes of women who have been prescribed HT for the past year compared with those who did not using age-matched case-control data with a 1:3 ratio
Variables HT recent users (n = 53) HT never users (n = 159) P value
Age, y 49.40 ± 11.04 49.40 ± 10.97 0.925
Comorbidities, no. (%)
 Cardiovascular disease . . NA
 Cerebrovascular disease . . NA
 Hypertension 5 (9.43) 17 (10.69) 0.795
 Heart failure 0 6 (3.77) 0.151
 Diabetes 4 (7.55) 11 (6.92) 0.877
 Pulmonary disease 5 (9.43) 15 (9.43) >0.999
 Malignancy 1 (1.89) 0 0.250
 Chronic kidney disease 0 3 (1.89) 0.314
 Chronic liver disease . . NA
Treatments, no. (%)
 Oxygen therapy 1 (1.89) 10 (6.29) 0.211
 Invasive mechanical ventilation 0 2 (1.26) 0.412
 Extracorporeal membrane oxygenation 0 1 (0.63) 0.563
 Renal replacement therapy 0 1 (0.63) 0.563
Clinical outcomes
 ICU admission, no. (%) 2 (3.77) 6 (3.77) >0.999
 Length of ICU stay, d 19.0 ± 15.56 15.67 ± 7.87 0.210
 Length of hospital stay for admitted patients, d 6.89 ± 8.65 6.91 ± 9.11 0.677
Mortality 0 1 (0.63) 0.563
HT, hormone therapy; ICU, intensive care unit.


To our knowledge, this is the first study to include a large number of confirmed cases that evaluated the effect of sex hormones on clinical outcomes of COVID-19. In this study, confirmed cases were the most prevalent in young women. Older age and underlying comorbidities, but not sex, had strong associations with mortality. HT use did not have a significant association with clinical outcomes in peri- and postmenopausal women. These findings suggest that female sex hormones may not have a protective role against COVID-19-related morbidity and mortality.

Male-dominant susceptibility to viral respiratory infections has been previously suggested.10,11 Several studies have reported a male-biased sex ratio in confirmed COVID-19 cases.12-14 In the Middle East respiratory syndrome coronavirus outbreak in South Korea, the number of cases was higher in men than in women (59.7% vs 40.3%).15 However, epidemiologic studies on SARS-CoV infection have shown that the proportions of female patients were higher in several countries and regions (55.7% in Hong Kong, 61.0% in Toronto, 66.0% in Singapore, and 63.2% in Guangzhou).16 Similarly, we demonstrated that the number of female patients infected with SARS-CoV-2 was higher. In South Korea, specific religious groups were associated with the largest number of COVID-19 cases.1 The predominance of women in those religious groups could be reflected in the female-biased sex ratio in our domestic COVID-19 outbreak. Additionally, the occupational hazards of a crowded workplace could be a risk factor for SARS-CoV-2 infection. In South Korea, the COVID-19 outbreak emerged at a call center, where the workers were at a high risk of coming in contact with each other.17 At this call center, the affected individuals were predominantly female. We believe that these social and cultural factors could have led to sex-specific disparities in COVID-19 morbidity in South Korea.

In contrast to the studies conducted in other countries, our study showed that COVID-19 was the most prevalent in women in the 20-39 years age group. This finding was also observed in another study using data reported to the Korea Centers for Disease Control and Prevention.8,18 In 2015, the Middle East respiratory syndrome coronavirus outbreak in South Korea spread through in-hospital infections.15,19 Hence, during the COVID-19 outbreak, clinicians actively performed diagnostic tests for preventing in-hospital transmissions. Additionally, the Korean government established a wide range of indications for diagnostic testing such that any individual could get tested, even if the symptoms were not severe. Therefore, many healthy young adults with mild or no symptoms could get tested and diagnosed. Our results may represent the real epidemiology of COVID-19, encompassing asymptomatic to severe cases.

Data from several countries have shown a male-biased sex ratio in COVID-19 mortality.12,14,20 In previous mice models, female hormones had a protective effect on mortality related to SARS-CoV infection.4 McCoy et al suggested that androgens, which may play an important role in SARS-CoV-2 entry into the host cell, were implicated in COVID-19 mortality.5 However, in our study, male sex was not an independent risk factor for mortality, and there was no significant association between HT use and the clinical outcomes of peri- and postmenopausal women. Although our study did not corroborate the protective role of female hormones against SARS-CoV-2 infection, further studies including emerging cases across several countries are required for determining the effects of sex hormones on SARS-CoV-2 infection.

This study has several limitations. First, owing to the nature of HIRA data, it was impossible to investigate detailed patient information, such as smoking history, viral loads, laboratory results, and radiologic findings, which could influence the clinical outcomes. In addition, we could not evaluate the exact interaction between female sex hormone levels and clinical outcomes because of the limited laboratory data available. Second, we cannot rule out the possibility of the underestimation of the number of male patients owing to asymptomatic or mild infections. A cohort study of patients with subclinical manifestations is needed for determining the sex ratio of the overall SARS-CoV-2 infections. Third, because of the limited number of women who received HT, we could not fully evaluate the effect of sex hormones on the clinical outcomes of COVID-19. Moreover, it is difficult to determine whether the patient was using the prescribed medications using claims data, and thus, HT use was evaluated based on drug codes for HT. Fourth, the menopausal status of female patients could not be evaluated. However, considering that the mean age at menopause (49.3 ± 0.1 y) is relatively lower in Korea than in other countries,21 the patients included in the subgroup analysis may represent peri- and postmenopausal women.


This study provides indirect epidemiologic evidence on the effects of female sex hormones on the prevalence and clinical outcomes of COVID-19. Female sex hormones were not associated with the morbidity and mortality of COVID-19 in South Korea. Furthermore, we showed that HT use was not associated with the clinical outcomes. Our findings could assist in the effective allocation of valuable health care resources and patient management during the current pandemic.


1. Korean Society of Infectious Diseases; Korean Society of Pediatric Infectious Diseases; Korean Society of Epidemiology; Korean Society for Antimicrobial Therapy; Korean Society for Healthcare-associated Infection Control and Prevention; Korea Centers for Disease Control and Prevention. Report on the Epidemiological Features of Coronavirus Disease 2019 (COVID-19) Outbreak in the Republic of Korea from January 19 to March 2, 2020. J Korean Med Sci 2020;35:e112.
2. Korea Centers for Disease Control and Prevention Coronavirus Disease-19, Republic of Korea. 2020. Available at: http://ncov.mohw.gokr/en/. Accessed April 28, 2020.
3. Channappanavar R, Fett C, Mack M, Ten Eyck PP, Meyerholz DK, Perlman S. Sex-based differences in susceptibility to severe acute respiratory syndrome coronavirus infection. J Immunol 2017; 198:4046–4053.
4. McCoy J, Wambier CG, Vano-Galvan S, et al. Racial variations in COVID-19 deaths may be due to androgen receptor genetic variants associated with prostate cancer and androgenetic alopecia. Are anti-androgens a potential treatment for COVID-19? J Cosmet Dermatol 2020; 19:1542–1543.
5. La Vignera S, Cannarella R, Condorelli RA, Torre F, Aversa A, Calogero AE. Sex-specific SARS-CoV-2 mortality: among hormone-modulated ACE2 expression, risk of venous thromboembolism and hypovitaminosis D. Int J Mol Sci 2020; 21:2948.
6. Walter LA, McGregor AJ. Sex- and gender-specific observations and implications for COVID-19. West J Emerg Med 2020; 21:507–509.
7. COVID-19 National Emergency Response Center, Epidemiology and Case Management Team, Korea Centers for Disease Control and Prevention. Coronavirus Disease-19: The First 7,755 Cases in the Republic of Korea [published correction appears in Osong Public Health Res Perspect. 2020 Jun;11(3):146]. Osong Public Health Res Perspect 2020;11:85-90.
8. Kim L, Kim JA, Kim S. A guide for the utilization of health insurance review and assessment service national patient samples. Epidemiol Health 2014; 36:e2014008.
9. Kim SB, Huh K, Heo JY, et al. Interim guidelines on antiviral therapy for COVID-19. Infect Chemother 2020; 52:281–304.
10. Sue K. The science behind “man flu”. BMJ 2017; 359:j5560.
11. Bouman A, Heineman MJ, Faas MM. Sex hormones and the immune response in humans. Hum Reprod Update 2005; 11:411–423.
12. Guan W-J, Ni Z-Y, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382:1708–1720.
13. Livingston E, Bucher K. Coronavirus disease 2019 (COVID-19) in Italy [published online ahead of print March 17, 2020]. JAMA.
14. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052–2059.
15. Kim KH, Tandi TE, Choi JW, Moon JM, Kim MS. Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea 2015: epidemiology, characteristics and public health implications. J Hosp Infect 2017; 95:207–213.
16. Chan-Yeung M, Xu RH. SARS: epidemiology. Respirology 2003; 8: (suppl): S9–14.
17. Park SY, Kim YM, Yi S, et al. Coronavirus disease outbreak in call center, South Korea. Emerg Infect Dis 2020; 26:1666–1670.
18. Dudley JP, Lee NT. Disparities in age-specific morbidity and mortality from SARS-CoV-2 in China and the Republic of Korea. Clin Infect Dis 2020; 71:863–865.
19. Cho SY, Kang JM, Ha YE, et al. MERS-CoV outbreak following a single patient exposure in an emergency room in South Korea: an epidemiological outbreak study. Lancet 2016; 388:994–1001.
20. Assessment RR. Coronavirus disease 2019 (COVID-19) in the EU/EEA and the UK-ninth update. European Centre for Disease Prevention and Control: Stockholm 2020.
21. Park Y, Gu BS, Kang HC, Chun SH. The menopausal age and climacteric symptoms, and the related factors of Korean women. Korean J Women Health Nurs 2001; 7:473–485.

Big data; COVID-19; Hormone therapy; SARS-CoV-2; Sex characteristics

Supplemental Digital Content

Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The North American Menopause Society.