A retrospective case-control study on menstrual cycle changes following COVID-19 vaccination and disease

Abstract

There has been increasing public concern that COVID-19 vaccination causes menstrual disturbance regarding the relative effect of vaccination compared to SARS-CoV-2 infection. Our objectives were to test potential risk factors for reporting menstrual cycle changes following COVID-19 vaccination and to compare menstrual parameters following COVID-19 vaccination and COVID-19 disease. We performed a secondary analysis of a retrospective online survey conducted in the UK in March 2021. In pre-menopausal vaccinated participants (n = 4,989), 18% reported menstrual cycle changes after their first COVID-19 vaccine injection. The prevalence of reporting any menstrual changes was higher for women who smoke, have a history of COVID-19 disease, or are not using estradiol-containing contraceptives. In a second sample including both vaccinated and unvaccinated participants (n = 12,579), COVID-19 vaccination alone was not associated with abnormal menstrual cycle parameters, while a history of COVID-19 disease was associated with an increased risk of reporting heavier bleeding, "missed" periods, and inter-menstrual bleeding.

Keywords: Health sciences; Immunology; Public health; Women's health.

Graphical abstract

Figure 1

Flowchart of the sample selection for vaccinated individuals

Figure 2

Prevalence ratios from univariable analyses of the relationship between multiple characteristics and menstrual cycle changes following COVID-19 vaccination The figure depicts prevalence ratios and 99%CI for 33 variables. ∗∗: FDR p-value <0.01; ∗∗∗ FDR p-value <0.001.

Figure 3

Predicted probability of reporting any menstrual changes following COVID-19 vaccination Predicted values and 99% confidence intervals given contraceptive use, COVID-19 disease (based on type and certainty of diagnosis), and menstrual cycle changes over the last year. Most individuals (82%) reported no menstrual disturbances following COVID-19 vaccination. This probability was lower for users of combined contraceptives and higher for current smokers and those who had a history of COVID-19 disease.

Figure 4

Flowchart of the sample selection for vaccinated and unvaccinated individuals

Figure 5

Predicted probabilities and 95% confidence intervals for cycle characteristics “during the pandemic” given self-reported COVID-19 vaccination and disease history. Discrete predictors (cycle characteristics before the pandemic, contraceptive use, BMI, and reproductive disease at baseline) are held constant at their proportions (not their reference level). Vax: participants vaccinated with 1 or 2 doses but without a history of COVID-19 disease; Covax: participants diagnosed with SARS-CoV-2 infection and vaccinated; Cov: unvaccinated participants diagnosed with a history of COVID-19 disease; None: participants neither vaccinated nor diagnosed with SARS-CoV-2 infection. (A) Cycle Frequency: Normal: between 24 and 38 days; Frequent: <24 days; Infrequent: >38 days. The probability of reporting frequent cycle vs. normal cycles is higher in the Cov and Covax groups than in the Vax group (+30%). (B) Cycle Regularity. Regular (less than 10 days difference between the lengths of two cycles). Cycle regularity does not vary across groups. (C) Period Flow. The probability of reporting heavier flow is higher in the Cov and Covax groups than the Vax group (+38%), while the probability of reporting lighter vs. normal flow is higher in the Covax compared to the Vax group (+29%). (D) IMB. The predicted probability of reporting more IMB is higher in the Cov and Covax groups than the Vax group (+31%). (E) Period Duration. A prolonged period is defined as >8 days. The predicted probability to report long periods is higher in the Cov group than the Vax group (+65%). (F) Period “missed”. Participants were asked whether they perceived having missed a period or whether their periods had stopped. The probability of reporting periods “stopping” or “missed” is higher in the Cov group compared to the Vax group (+31%).

Figure 6

Most common words (unigrams) and pairs of adjacent words (bigrams) used to describe menstrual cycle changes following COVID-19 vaccination (n = 574)

Figure 7

Correlation matrix between key words within sentences describing menstrual cycle changes following COVID-19 vaccination Numbers indicate the strength of the correlation (phi coefficient) between words. Colors indicate the direction (red: positive, blue: negative).

Figure 8

Network of words describing menstrual cycle changes following vaccination with COVID-19 Words have been lemmatized to the root of their words, for example “light” can represent both “lighter” and “light". Node size represents degree centrality (the commonality of words, only words with more than 5 occurrences are included). Edge thickness is a measure of correlation between words. When only correlations >0.20 were considered, 4 clusters emerged (circled in colors).