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  1. Our take

    This preprint, which has yet to undergo peer-review, examined changes in menstrual period timing and flow after COVID-19 vaccination in 1,273 adults in the United Kingdom. About half of the surveyed individuals reported changes in period timing (earlier or later than expected) and flow (lighter or heavier than expected) in their subsequent period after COVID-19 vaccination, though the study population is self-selected and the author notes that the frequency of menstrual changes after COVID-19 vaccination is likely overreported and does not represent the prevalence of menstrual changes after vaccination. Vaccine type did not impact menstrual changes, but participants on hormonal contraceptives were more likely to report changes in menstrual flow. Prospective studies with control groups are needed to estimate the frequency of menstrual changes following COVID-19 vaccination compared to baseline changes over time, and future vaccine trials should incorporate menstrual changes as a reportable side effect.

    Study design


    Study population and setting

    This study described menstrual changes in a self-selected sample of adults (18+ years) in the United Kingdom (UK) who had received vaccination against SARS-CoV-2. A total of 2,241 participants reported their age, length of their normal menstrual cycle, contraceptive use, breastfeeding status, history of gynecologic conditions, vaccine type, vaccine date during their menstrual cycle, and the timing and flow of their subsequent period after each vaccination dose (doses were administered approximately 8 weeks apart in the UK regardless of vaccine type) on an online form. Among these respondents 1,273 (57%) provided complete data and were included in the analysis. The study assessed the timing and flow of each participant's next period after vaccination based on the following variables: vaccine brand (Pfizer, Moderna, AstraZeneca); use of hormonal contraceptives; and vaccination timing during each participant’s menstrual period using Chi squared tests. It also assessed how subsequent period changes after the first vaccine dose related to period changes after the second vaccine dose. In a post-hoc analysis, it assessed differences in period timing and flow in participants with several gynecologic conditions. All analyses were unadjusted for potential confounders.

    Summary of main findings

    The participants’ median age was 33 years old (interquartile range [IQR] 29-39), the median cycle length was 28 days (IQR: 27-30), and the majority (1,117, 87.6%) were not using hormonal contraception. Among the participants who were vaccinated with Pfizer (n = 778, 61%), AstraZeneca (346, 27.1%), or Moderna (n = 136, 10.7%) there were no significant differences between subsequent period timing (late 29-35%, on time 40-47%, early 24-27%) or flow (heavier 31-35%, the same 49-55%, lighter 13-17%). While there were no statistically significant changes in subsequent period timing by hormonal contraceptive use (23-28% early, 43-45% on time, 29-32% heavier), participants on hormonal contraceptives were more likely to report lighter (19% vs. 14%) or heavier (42% vs. 32%) flow compared to participants not on hormonal contraceptives (p-value = 0.001). Vaccination timing during the menstrual cycle (relative to predicted ovulation dates among participants not on hormonal contraception) did not have a clear effect on subsequent period timing or flow. Among the subset of 813 respondents who had completed both vaccine doses, menstrual changes following vaccine dose one were very similar to changes following the second vaccine dose. Finally, among the small subset of individuals with endometriosis (n = 60, 4.7%) and polycystic ovarian syndrome (n = 87, 6.8%), vaccination was statistically significantly associated with earlier (38% vs. 23%) and later (41% vs. 31%) periods respectively, compared to participants with no history of gynecologic conditions.

    Study strengths

    This study provided thoughtful explanations for who was included (and why they were included) in each analysis. It also provided a link to a pre-specified analysis plan and a de-identified dataset.


    This study notes that it likely overestimates menstrual changes after COVID-19 vaccination given that people who experienced changes were more likely to respond to the survey. It therefore cannot be used to estimate the prevalence of menstrual changes following COVID-19 vaccination. This bias may also influence why participants using hormonal contraception reported more menstrual changes than non-users. There is also insufficient detail about participant recruitment to determine the temporal period of data collection or how representative the study population is of people who are menstruating. For example, 87.6% were not using hormonal contraception, which may reflect that this study population is actively attempting pregnancy. Despite providing reasoned explanations of which characteristics qualified participants for each analysis, this study does not provide information on how many participants were included in each analysis. Finally, each factor was evaluated without adjusting for factors which may confound their association with menstrual cycle timing and flow.

    Value added

    This study addresses an underreported side effect of COVID-19 vaccination, temporary changes in menstrual timing and flow.

  2. SciScore for 10.1101/2021.11.15.21266317: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableRespondents who did not have a period after the vaccine, but the reason is specified (eg. became pregnant in the same cycle that they were vaccinated, opted not to have a withdrawal bleed if taking a contraceptive pill; n = 28). 8.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The study has a number of limitations. First, because the participants were recruited retrospectively, the data is likely to be enriched for those who noticed a change, who might be more motivated to participate in the study. Therefore, we cannot use this data to determine the frequency with which people experience menstrual changes following COVID-19 vaccination or, directly, to confirm or disprove any link between vaccination and menstrual changes. Approaches in which participants are recruited prospectively or using menstrual cycle data collected for other reasons, for example, datasets from menstrual cycle tracking apps with linked data about dates of vaccination, are better equipped to answer these questions. Approaches using menstrual cycle tracking apps are likely to be particularly powerful because the large number of cycles logged and the granularity of the data will allow detection of small and rare changes to post-vaccination menstrual cycles. Further, where the app uses user data to predict the day of ovulation, the date of vaccination relative to ovulation can be determined with greater accuracy than the crude estimate used here. It is also important to note that the majority of the participants in this study were from the UK, so our findings here might not be applicable to other countries. In particular, we did not examine any potential associations with vaccines that are not approved for use in the UK, such as Sinovac, Sinopharm or Sputnik V. In the UK, we use ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.