Prevalence and pattern of abnormal menstruation after COVID-19 infection
Issued Date
2026-01-01
Resource Type
ISSN
07399332
eISSN
10964665
Scopus ID
2-s2.0-105029234710
Journal Title
Health Care for Women International
Rights Holder(s)
SCOPUS
Bibliographic Citation
Health Care for Women International (2026)
Suggested Citation
Tangjitgamol S., Maude R.R., Ativanichayapong N., Walsh R., Beer E., Kaprakhon K., Chaowanklang C. Prevalence and pattern of abnormal menstruation after COVID-19 infection. Health Care for Women International (2026). doi:10.1080/07399332.2026.2617332 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114960
Title
Prevalence and pattern of abnormal menstruation after COVID-19 infection
Corresponding Author(s)
Other Contributor(s)
Abstract
Objective: To evaluate the prevalence of abnormal menstruation after COVID infection as well as the type of abnormality and risk factors. Methods: Data of women who still had menstruation with a history of COVID infection from February 2021 to June 2022 were collected. Clinical features, the presence and pattern of abnormal menstruation post-infection, were obtained through the questionnaire. Results: Of 87 women, the mean age was 33.5 ± 7.2 years. Nine had preexisting menstrual abnormalities (10.3%). The abnormalities were found in 20 women (23.0%), or 2.2-fold higher post-infection. Among these, 17 women (68.0%) had newly developed symptoms. Irregular menstruation was most common in both settings, 33.3% pre-infection and 20.0% post-infection. By univariate analysis, features with higher risk were age ≤ 33 years (crude odds ratio [cOR] 1.61), obesity (cOR 1.74), COVID vaccination > 3 doses (cOR 3.28), > 1 episode of infection (cOR 3.94), contraception use before (OR 1.47) or after infection (cOR 1.92), abnormal menstruation before COVID infection (cOR 44.0), and presence of other long COVID symptoms (cOR 2.09). The differences were statistically significant for vaccination > 3 doses and had abnormal menstruation pre-infection, with the latter as an independent risk by multivariate analysis (adjusted OR 39.58). Conclusion: The prevalence of abnormal menstruation post-COVID infection was 23%. Abnormal menstruation pre-infection was an independent risk factor.