Menstrual Cycle Parameters Are Not Significantly Different After COVID-19 Vaccination

Abstract

Background:

Some studies have suggested minor changes in the menstrual cycle after COVID-19 vaccination, but more detailed analyses of the menstrual cycle are needed to evaluate more specific changes in the menstrual cycle that are not affected by survey-based recall bias.

Materials and Methods:

Using a pretest–post-test quasi-experimental evaluation of menstrual cycle parameters before and after COVID-19 vaccination, we conducted an anonymous online survey of two groups of North American women who prospectively monitor their menstrual cycle parameters daily including bleeding patterns, urinary hormone levels using the ClearBlue Fertility Monitor, or cervical mucus observations. The primary outcome measures were cycle length, length of menses, menstrual volume, estimated day of ovulation (EDO), luteal phase length, and signs of ovulation. Perceived (subjective) menstrual cycle changes and stressors were also evaluated in this study as secondary outcome measures.

Results:

Of the 279 women who initiated the survey, 76 met the inclusion criteria and provided 588 cycles for analysis (227 pre-vaccine cycles, 145 vaccine cycles, 216 post-vaccine cycles). Although 22% of women subjectively identified changes in their menstrual cycle, there were no significant differences in menstrual cycle parameters (cycle length, length of menses, EOD, and luteal phase length) between the pre-vaccine, vaccine, and post-vaccine cycles.

Conclusions:

COVID-19 vaccines were not associated with significant changes in menstrual cycle parameters. Perceived changes by an individual woman must be compared with statistical changes to avoid confirmation bias.

Introduction

Concerns about the safety of the COVID-19 vaccination have led to vaccine hesitancy among some women. These concerns need to be addressed in independent research protocols to educate health care providers and their patients with accurate information about vaccination.¹ Besides vaccination-related concerns, the COVID-19 pandemic itself has been shown to be a source of stress that may affect menstrual cycle parameters and ovarian function.^2,3 A recent population-based study with a large data set of Natural Cycles App users showed no significant changes to menstrual cycles over the course of the COVID-19 pandemic,⁴ and a follow-up study in the same data set recently showed only a slight change (<1 day) in menstrual cycle length post-vaccination.⁵ However, this study only measured menstrual cycle length and length of menses and not other parameters of the menstrual cycle, that is, menstrual volume, day of ovulation, and the luteal phase length.

To date, no studies have investigated menstrual bleeding prospectively, used a menstrual cycle bleeding rating scale, nor looked at days of bleeding; however, a few studies have conducted surveys on womens' perceived menstrual pattern changes before and after COVID-19 vaccination. A Norwegian population-based study⁶ showed heavier bleeding after vaccination, and in an American preprint study, they also observed heavier bleeding and breakthrough bleeding after vaccination.⁷ In two British preprint studies, one observed an increase in menstrual changes post-vaccine for women on hormonal contraception,⁸ but the other found lower odds of menstrual changes for women on hormonal contraception,⁹ one of these studies also found a change in timing of the cycle in women with endometriosis or polycystic ovarian syndrome,⁸ and the other found increased odds of reporting changes in smokers.⁹ Another retrospective survey in the Middle East and North Africa found that two thirds of women reported changes in menstrual symptoms post-vaccination.¹⁰

In women who have had COVID-19 infection, sex hormone concentrations did not change significantly after infection, although there were some women with decreased menstrual volume and cycle prolongation that improved after recovery.¹¹ In the Arizona CoVHORT study, they prospectively collected survey responses regarding menstrual cycle changes after COVID-19 infection, and found more reported changes in those with more severe COVID-19 symptoms, but this was in a minority of patients in their small study.¹²

Survey-based analysis based on recall alone as with the studies described above^6

–10 may not identify the objective changes in the menstrual cycle because of recall bias^2,13 and because of the greater likelihood of women choosing to participate who have experienced menstrual irregularities that may be unrelated to the vaccine. In this study, we recruited participants from two populations of regularly cycling and ovulating women who were already tracking their menstrual cycles and who collected data prospectively both before and after their COVID-19 vaccines. The women were experienced users of the Marquette Method (MM) or the Sympto-Thermal Method (STM), both effective methods of family planning used by thousands of women around the world.^14,15

The purpose of this study was to provide more detailed menstrual cycle parameters for analysis (i.e., cycle length, volume and length of menstrual bleeding, timing and occurrence of ovulation, and the length of the luteal phase) before vaccination, between doses of vaccine, and after vaccination. In addition, perceived menstrual cycle changes were also evaluated to further clarify whether there was a confirmation bias among the women's responses to our survey, compared with the actual objective findings in their cycles before and after vaccine.

Materials and Methods

Population and design

This was a pretest–post-test quasi-experimental evaluation of menstrual cycle parameters in two North American cohorts of women before and after COVID-19 vaccination using an anonymous online survey. Questions about the timing of their COVID-19 vaccination, as well as self-reported menstrual cycle data, were included. Participants were recruited via email among current users of the MM or STM. Women who clicked on the survey link were able to access a Qualtrics survey form (for the MM group) or a Survey Monkey form (for the STM group), which first asked inclusion questions. If all inclusion criteria were met, they were directed to read through an Information and Consent form, which they digitally signed and could download if they agreed.

After the online consent, they were then able to begin the survey which they completed once, entering their information which they had already collected for three cycles before their first vaccination, vaccine cycles between the two vaccines, and post-vaccine cycles after their second vaccination (if applicable). Demographic (non-identifying) information collected included age, ethnicity, years married, and number of children but no digital information (e.g., IP address) nor any other identifying information was collected. Participants were also asked subjective questions regarding whether they perceived any changes after vaccination. STM users provided a unique account identifier, which allowed all captured cycle observations in an App to be accessed anonymously instead of entering their cycle parameters in the survey.

Inclusion criteria were age 18–42 years, menstrual cycles ranging between 21 and 42 days, having at least three cycles after weaning of breastfeeding, and having received the COVID-19 vaccine 3 months ago or longer. Exclusion criteria were currently on medications that affect ovulation during the study and the 3 months prior; currently pregnant or breastfeeding; and previous fertility problems. These criteria were based on a woman's status before entering the study period.

Menstrual bleeding level was identified on each day of the cycle as spotting, light, moderate, or heavy. The MM group used a 1–4 scale (1 = spotting, 2 = light, 3 = moderate, 4 = heavy), and the STM group used a 1–3 scale for these measures (1 = spotting and light, 2 = moderate, 3 = heavy). Consecutive days of bleeding at the beginning of the cycle were summed as a total menses score, and the number of days of menses (length of menses) was also calculated.

Users of the MM reported results from the Clearblue Fertility Monitor (CBFM), a handheld digital monitor with test sticks that measure estrone-3-glucuronide (E3G) and luteinizing hormone (LH) and provides the user with a reading of “low,” “high,” and “peak” fertility.¹⁶ Results from the CBFM (“high” and “peak,” indicating rises in urinary E3G and LH, respectively) were recorded as the first day of each reading on the monitor. STM users recorded the first day of fertile mucus (“high”) and the last day of fertile mucus occurring within a few days of a recognized basal body temperature shift as their indicator of peak fertility using the CycleGoPro App. The estimated day of ovulation (EDO) was based on previous studies indicating that the day after Peak on the CBFM is the most common day of ovulation on ultrasound¹⁷ and the day after peak cervical mucus for STM users.¹⁸ Luteal phase lengths were calculated based on the EDO (luteal phase = cycle length – EDO).

Statistical analysis

Descriptive statistics were used to determine the means, standard deviations, and 95% confidence intervals (CI) of the parameters of the menstrual cycle that is, days of menses, total menses score (menstrual volume), the length of the menstrual cycle, luteal phase lengths, and the EDO. Menstrual cycle parameters were compared over the three time periods (pre-vaccine, vaccine, and post-vaccine cycles) using repeated-measures analysis of variance, and when sphericity was violated, the Huynh–Feldt correction was applied. In cases of significant differences, post hoc tests used the Bonferroni correction for multiple comparisons.

The mean parameters of the three cycles before vaccination were compared with the mean of the same cycle parameters in the vaccine and post-vaccine cycles. The repeated-measures design accounted for age, parity, body mass index, and interval between vaccine doses because data are analyzed within subjects. Chi-square tests were used to compare signs of ovulation between the cycles (i.e., missing peak or not). Analyses were carried out using SPSS version 27 (IBM, Chicago, IL, USA) and Excel (Microsoft, Redmond, WA, USA).

Ethical approval was obtained through the Marquette University Office of Research Compliance Institutional Review Board (HR-3959). The authors did not receive any funding for their work on the study.

Results

Study population

For the 2 groups of women, 5013 emails were sent. In the MM group, 126 emails were sent to method instructors who distributed the invitation to their clients. A more detailed response rate was available for the STM group, where 1725 emails were tracked as opened (35.3% response rate). There were 279 women who initiated the survey, but 203 women were self-excluded by the survey's inclusion criteria parameters (64 of these were either pregnant or breastfeeding, 42 were within 3 cycles of weaning from breastfeeding, 24 were not using the CBFM, 23 did not meet demographic criteria, 19 had not received the vaccine, 16 did not have regular cycles, 9 were on medications that can affect ovulation, and 6 had known fertility problems).

This left 76 women who provided 588 cycles for analysis, 37 in the MM group and 39 in the STM group. The mean age of the participants was 33.3 ± 5.1 years, married an average of 6.9 years (±4.7), with mean pregnancies of 2.2 (±1.8) and mean miscarriages of 0.35 (±0.6), whereas 25% were nulliparous. The majority (99%) were University educated, 93% were Caucasian (two Hispanic, one not stated), with an average body mass index of 25.2 (±5.0) kg/m².

Cycles were classified as “pre-vaccine” cycles (N = 227), “vaccine” cycles (cycles that spanned the first and second doses if applicable, N = 145), or “post-vaccine” cycles (N = 216). Two women received the single-dose Johnson and Johnson vaccine, 73 (96%) received an mRNA vaccine, 48 (63%) received Pfizer, 25 (33%) received Moderna, 1 woman received a mix of Pfizer and Moderna, and 1 woman received AstraZeneca. Two women did not receive their second dose of the mRNA vaccine. The average interval between the two doses of mRNA vaccine was 28.8 days (±13 days, range 14–76 days), and cycles during this time interval between vaccines were considered “vaccine cycles.” There were no differences in demographics between the MM and STM groups in our study aside from the STM group having had slightly more miscarriages than the MM group (p = 0.03).

Menstruation

As shown in Table 1, length of menses was not significantly different between the pre-vaccine, vaccine, and post-vaccine cycles [F(2,71) = 2.69, p = 0.08]. Although there was a significant difference in volume of menses after the Huynh–Feldt correction for sphericity [F(2,144) = 3.702 p = 0.03]. However, the post hoc analysis of this difference with the Bonferroni correction showed no difference between the pre-vaccine, vaccine, and post-vaccine cycles in either group. The slightly higher menstrual scores in the MM group are due to the slightly different bleeding scale used by this group.

Table 1.

Days of Menses and Total Menses Score in the Pre-Vaccine, Vaccine, and Post-Vaccine Cycles

	Days of menses	Total menses score
Pre-vaccine cycle	5.3 ± 0.9 (5.1–5.5)	12.7 ± 2.7 (12.1–13.3)
Vaccine cycle	5.1 ± 1.2 (4.8–5.3)	12.0 ± 2.9 (11.3–12.7)
Post-vaccine cycle	5.2 ± 1.2 (4.9–5.5)	12.0 ± 3.4 (11.2–12.8)

Data are presented as mean ± standard deviation (95% CI).

CI, confidence interval.

Cycle length and EOD

Cycle lengths were not different between the pre-vaccine, vaccine, and post-vaccine cycles [F(2,73) = 2.53, p = 0.09] (Table 2). Similarly, the EDO [F(1.3,134) = 0.4, p = 0.59] and luteal phase length [F(2,122) = 0.10, p = 0.81] were not different between the cycles (Table 2). When evaluating only women who received both vaccines in one cycle (N = 15), there was still no difference in cycle lengths [F(2,28) = 1.5, p = 0.44].

Table 2.

Menstrual Cycle Parameters in the Pre-Vaccine, Vaccine, and Post-Vaccine Cycles

	Cycle length	First high	EDO	Luteal phase length
Pre-vaccine cycle	28.8 ± 2.4 (28.2–29.3)	10.0 ± 2.6 (9.4–10.6)	16.1 ± 3.2 (15.3–16.8)	12.9 ± 2.5 (12.3–13.5)
Vaccine cycle	28.3 ± 2.6 (27.7–28.9)	10.1 ± 3.2 (9.3–10.8)	16.5 ± 5.6 (15.1–17.8)	12.9 ± 2.4 (12.4–13.5)
Post-vaccine cycle	28.3 ± 3.0 (27.6–29.0)	10.1 ± 2.6 (9.5–10.8)	15.9 ± 2.8 (15.3–16.6)	13.3 ± 4.2 (12.3–14.4)

Data are presented as mean ± standard deviation (95% CI).

EDO, estimated day of ovulation.

Hormone changes and signs of fertility

In the MM group, there were no differences in the first High (reflecting the rise in estrogen) on the CBFM [F(1.7,68) = 0.37, p = 0.66] and no differences in the first Peak (reflecting the LH surge) on the CBFM [F(2,34) = 1.67, p = 0.20] between the pre-vaccine, vaccine, and post-vaccine cycles (Table 2). In the STM group, there were no differences in the beginning of fertile cervical mucus [F(1.75,62) = 0.36, p = 0.94] or the peak of cervical mucus [F(2,29) = 0.07, p = 0.93] between the cycles.

Instances of missing signs of ovulation (no peak on CBFM, no peak cervical mucus) were also tabulated between the cycles. There were 23 of 227 pre-vaccine cycles with no Peak on the CBFM (6/104, 5.5%) or peak mucus sign (17/100, 14.5%). In vaccine cycles, there were 12 of 145 with no Peak on the CBFM (3/70, 4.1%) or peak mucus (9/63, 14.3%). In post-vaccine cycles, there were 5 of 97 cycles with no Peak on the CBFM (4.9%) and 23 of 91 with no peak identified by cervical mucus (20.2%). There was no significant difference in the frequency of peaks in the pre-vaccine, vaccine, and post-vaccine cycles (MM group: χ² = 0.17, p = 0.92, STM group: χ² = 2.30, p = 0.32).

Perceived disturbances in the menstrual cycle

Of the 76 women studied, 55 (72%) did not perceive any changes to their menstrual cycle and 17 (22%) felt that there were changes in their menstrual cycle after vaccination. Among the others, one did not provide feedback and three (4%) felt unsure whether there were changes.

Eight of the 17 women in the narrative summaries perceived an increase in their menstrual bleeding (“larger clots than usual,” “clotting in cycle after vaccination, never previously occurred,” “heavier bleeding”), and 4 of 17 perceived a decrease in their bleeding (“period stopped immediately after the vaccine,” “decreased bleeding”). Ovulation changes were perceived in 7 of 17 women (“peak is no longer predictable or consistent,” “ovulation changes”), and 9 of 17 noted changes in cycle length (6 noted longer, 3 noted shorter). Eight of the 17 women had changes in more than one of these categories (bleeding changes, ovulation changes, cycle length changes). When isolating these cases of women perceiving changes, we compared the specific objective menstrual cycle parameters over the three time periods, and due to the size of these subsets of women, we did not have adequate power to detect significant differences (Table 3).

Table 3.

Perceived Versus Actual Menstrual Cycle Parameters (Mean ± Standard Deviation) in the Pre-Vaccine, Vaccine, and Post-Vaccine Cycles

	Total menses score in women with perceived increased bleeding (N = 8)	Total menses score in women with perceived decreased bleeding (N = 4)	EDO in women with perceived ovulatory changes (N = 7)	Cycle length in women with perceived short cycles (N = 3)	Cycle length in women with perceived long cycles (N = 6)
Pre-vaccine cycle	13.1 ± 2.4	13.1 ± 0.4	16.3 ± 3.3	28.8 ± 2.7	28.4 ± 2.4
Vaccine cycle	10.5 ± 3.1	9.8 ± 1.26	22.4 ± 15.5	27.3 ± 1.5	28.1 ± 2.4
Post-vaccine cycle	11.0 ± 3.7	12.4 ± 2.8	15.8 ± 2.6	26.4 ± 8.7	29.2 ± 3.5

Discussion

Knowledge of the menstrual cycle as a vital sign allows women to monitor disturbances in their health that are reflected in the reproductive hormones.¹⁹ While others have noted that stress during the COVID-19 pandemic may affect menstrual cycle parameters,^2,3 it is important to separate subjective perception of change that is susceptible to both recall and confirmation bias. In this study of women who monitored their menstrual cycles daily and prospectively pre- and post-vaccine, we showed that there were no major differences in menstrual bleeding and the parameters of the menstrual cycle after the COVID-19 vaccination, even though 22% of participants had the impression that their cycles had changed. Our findings mainly relate to the mRNA vaccines since 96% of participants received the Pfizer or Moderna mRNA vaccines.

Days of menstrual bleeding were not different pre- and post-vaccine after post hoc Bonferroni correction. Interestingly, a study in women who have had COVID-19 infection¹¹ demonstrated a decreased menstrual volume in 20% of women. Other studies that were based on retrospective surveys did show some menstruation changes,^6

–10 which we did not reproduce in our sample, perhaps because we measured objective rather than perceived changes, or because our sample was not adequately powered to detect very subtle changes.

Other menstrual cycle parameters were not different comparing pre-vaccine baseline averages with the vaccine and post-vaccines cycles. Moreover, these parameters were comparable to the normal ranges and normal variability of cycle lengths (21–35 days) and luteal phase length (9–17 days) found in other studies.²⁰ Even though one study has suggested that cycle length was increased after vaccination,⁵ the small difference of less than 1 day is admittedly not clinically significant. However, it is interesting to note that the same study mentioned above that noted decreased menstrual volume in some women after COVID-19 infection also showed prolonged cycles in 19%¹¹ and may suggest that there is a subset of women who are being identified with the cycle length changes.

In our smaller sample, we did not identify this cycle difference even in women who had both doses of the vaccine in one cycle. Based on these results, these subtle changes may be occurring in a subset of women both with vaccination and with COVID-19 infection that only become obvious in a larger sample size but are likely not substantial enough for the changes to be clinically important.

Anovulation was assumed to have occurred in cycles without an LH surge detected on the CBFM or missed peak on cervical mucus. Given the much higher incidence of missing peak in the cervical mucus cycles (14%–20% for cervical mucus compared with 4%–5% for the CBFM), it is possible that the lower accuracy of cervical mucus overestimated the incidence of assumed anovulation, or, it is possible that some of the missing peak mucus days are due to missing observations not entered by the STM users. Without ultrasound, these signs of fertility remain only an estimate of ovulation, although an accurate one.¹⁷

The rate of missing peak fertility in this study was not different between the pre-vaccine baseline and the vaccine and post-vaccine cycles. The low rates of missing peak on the CBFM (4%–5%) at all three time points are similar to the background rate of sporadic anovulation in this age group of women²¹; therefore, there does not seem to be any definite link between the vaccine and anovulation, but admittedly for the two women who experienced two cycles with no detected LH surge after their second dose of vaccine, it is easy to see how anecdotal connections can be made when data like ours have not yet been readily available.

Our study also shows the importance of avoiding confirmation bias with perceived changes (i.e., 22% of women our study perceived some cycle changes), where one might attribute changes to one intervention (e.g., the vaccine) when the change may be from some other unidentified cause. It is possible that there are other stressors happening at the same time as the vaccine that may account for perceived menstrual cycle changes.^2,3 When comparing perceived and actual changes in cycle parameters, even though the sample size of these subsets were not adequate to detect significant differences, menstrual volume was discrepant between perceived and actual changes for women who perceived heavy bleeding, suggesting that perceived changes in menstruation may not always reflect actual changes, likely because menstrual volume is not always easy to objectively quantify.

However, perceived and actual changes in ovulation and cycle length were consistent, which may be because these changes are more clearly demarcated and more objectively identifiable by women than menstrual volume. This does highlight the fact that studies based only on recall of menstrual volume^6

–10 may not precisely reflect objective changes, and surveys of menstrual bleeding changes should involve prospectively collected data.

Strengths and limitations of this study

In this study, we reported on prospectively collected data on several parameters (bleeding, ovulation day, luteal phase length) that allowed us to study menstrual cycle changes in a population-based sample of women who regularly monitor their cycles. As with the recent study looking at a population using a menstrual cycle App,⁴ evaluating users who collect their own daily data prospectively is a very powerful source of information and this contrasts with other studies that are based on recall where data are not contemporaneous and may lead to recall bias.^13,22

The main weakness of the study was the relatively small sample size with the potential bias of self-selection rather than random selection. Our sample size was over a target of 52 participants to have 80% power to detect effect sizes of 0.4 (i.e., to detect a 1 day difference in cycle length, EDO estimate, luteal phase estimate, or a 1 point difference in menstrual volume scores). Although our study did not have adequate power to detect differences in cycle length of <1 day as was shown in a previous study,⁵ the authors admit, and we agree that this does not seem to reflect a clinically meaningful difference.

The second weakness of our study relates to a lack of population diversity. We specifically wanted to start our analyses looking at women with regular cycles, but women in other circumstances (irregular cycles, breastfeeding, perimenopause, etc.) would also be of interest. Future studies should analyze a larger sample size (a minimum of 150 participants would be required to detect differences of 0.5 days or less in cycle length parameters, i.e., with an effect size of 0.2, alpha 0.05, and power of 80%) of randomly selected women who, like our participants, monitor their cycles prospectively. The CBFM only measures qualitative levels of estrogen and LH (with the CBFM), but future studies could provide more detailed analyses using quantitative fertility monitors.²³

Conclusions

Taken together, with no difference in menstrual bleeding volume, signs of ovulation, and hormone changes in the menstrual cycle, this should provide reassurance to people concerned about the potential effects of the vaccine on the menstrual cycle of reproductive age women. Even though this study did not identify pregnancy and thus whether future pregnancies are impacted, the menstrual cycle as a vital sign²⁴ is the primary mechanism by which fertility can be assessed and so can provide us with reliable information on which to base recommendations regarding COVID-19 vaccines, in particular the mRNA vaccines used by most participants in this study. Moreover, multiple studies have also shown that COVID-19 vaccination does not appear to harm female fertility.^25

–29

Combining participant's perceived changes with the objective findings of the menstrual cycle parameters, we were able to demonstrate that anecdotal associations of menstrual cycle changes did not reflect statistically significant changes in menstrual cycle parameters after COVID-19 mRNA vaccination compared with pre-vaccination baseline cycle averages.

Footnotes

Acknowledgments

The authors thank the Marquette Method and CycleProGo users who contributed data for this study.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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