Background

The COVID-19 pandemic, which emerged in Wuhan, China, in December 2019, created a global health crisis. In response, researchers and public health officials have made substantial efforts to develop vaccines aimed at mitigating the impact of the virus [1]. By late 2020, several vaccines had been successfully developed and authorized for emergency use, resulting in their widespread distribution in early 2021 [2]. Vaccines have become the most effective method to curb the pandemic, leading to notable reductions in both the incidence of COVID-19 and associated mortality rates [3, 4]. Despite their effectiveness, vaccine uptake has been impeded by concerns regarding their efficacy, potential adverse effects, and safety, and the expedited nature of their development [5, 6].

Many studies have been conducted to assess the safety, efficacy, and potential adverse effects of COVID-19 vaccines [7, 8]. Among the observed adverse effects, menstrual cycle changes have emerged as a significant concern [9, 10]. This issue has been substantiated by reports from numerous women who experienced unexpected alterations in their menstrual cycles through the Vaccine Adverse Event Reporting System (VAERS) and social media [11, 12]. Furthermore, observational studies commonly reported longer or shorter menstrual cycles, increased irregularity, and heavier bleeding after COVID-19 vaccination [13, 14]. However, these changes were typically short-term and resolved spontaneously in approximately half of the cases [15, 16].

The National Institutes of Health (NIH) agreed to fund five institutes to explore a potential link between COVID-19 vaccination and menstrual cycle changes, including the underlying mechanisms [17]. This could have lead to greater interest from researchers in investigating the prevalence of menstrual changes following COVID-19 vaccination, but few studies have investigated the underlying mechanisms [18]. Thus, it is important to consolidate these diverse findings for a more comprehensive understanding of the impact of COVID-19 vaccination on the menstrual cycle [19]. Therefore, we performed this systematic review and meta-analysis to summarize the available qualitative and quantitative data from observational studies that investigated menstrual cycle changes associated with COVID-19 vaccination in adult women.

Objective

This systematic review was carried out to answer the following research question:

In adult women, is the use of the COVID-19 vaccine associated with menstrual cycle changes compared with no vaccination?

Methods

This review adhered to the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) statement [20].

Eligibility criteria

The criteria for considering relevant studies for this review were as follows:

  1. 1.

    Types of studies

We included observational studies on humans that investigated the association of the COVID-19 vaccine with menstrual changes, including cross-sectional, prospective or retrospective case‒control, or cohort studies. We excluded experimental in vitro studies, case reports, review articles, editorials, expert opinions, and preprinted articles. Randomized controlled trials (RCTs) were excluded because our study aimed to determine the pooled prevalence of menstrual changes caused by the COVID-19 vaccine. Additionally, vaccine trials did not prospectively collect data on menstrual health outcomes [21].

  1. 2.

    Types of participants

We included human studies in which participants were adult women aged 18–55 years who were otherwise healthy. We excluded studies with the following participant criteria: aged less than 18 years or more than 55 years; pregnant or lactating participants; participants with hormonal or other pathologies that might cause menstrual changes other than the potential effect of the COVID-19 vaccine.

  1. 3.

    Types of interventions

We sought studies in which participants received at least two doses of COVID-19 vaccines of any type.

  1. 4.

    Outcomes

We included studies examining a range of menstrual abnormalities, which included flow (heavy, light, normal), regularity (regular or irregular), duration of cycle (normal or abnormal), and presence of painful menstruation (dysmenorrhea), regardless of whether these changes were self-reported or clinically measured. We excluded studies that investigated the side effects of the COVID-19 vaccine in general and surveillance reports.

Information sources and search strategy

We systematically searched the PubMed, Science Direct, and Web of Science databases for articles published until July 2023. Moreover, we examined the references of the selected articles to find additional relevant articles. Three authors conducted an independent search via the following search terms: (“COVID-19 vaccine” AND “menstrual cycle” OR, “menstrual irregularities”); we also searched for the most widely used vaccine trade names (“Pfizer” OR “Janssen” OR “AstraZeneca” OR “Moderna”, AND “menstrual cycle” OR, “menstrual irregularities”). We also used the truncation (*) with the same root word (vaccine) to find additional research articles. We used truncation to ensure that all potential variants of the search term were found. No limits were applied to the search results except for studies in humans, publication type, or duration filters (2020–July 2023); however, no language restriction was used.

Selection and data collection process

The citations were retrieved via reference management software (Mendeley). Duplicate citations were removed. All the remaining studies underwent a thorough review process. Two authors independently assessed each study, and a third author reviewed all discrepancies to resolve any disagreements during the initial screening. The initial screening involved scrutinizing titles and abstracts against the predefined eligibility criteria. A structured data collection approach was adopted via a Google Excel spreadsheet (Supplementary Tables 1–4). This sheet included essential study information such as the author’s name, year of publication, country of origin, study design, sample size, participant age, inclusion criteria, exclusion criteria, administered vaccine, reported outcomes and results. This methodical process ensured the systematic compilation of relevant data from the selected studies.

Data items

All outcomes for which data were obtained were self-reported menstrual changes in terms of flow (heavy, normal, light), which was normal between 20 and 90 mL, approximately 1 and 5 tablespoons; regularity (interval variations between cycles, where the average is to have periods every 28 days); duration of menstruation (number of bleeding days, where normal is between 2 and 7 days); and duration of cycle (first day of period to the day before the next one, where normal is from 23 to 35 days). Studies have reported menstrual changes via different measurements, such as frequency and the risk ratio. Therefore, we have entered data on positive events to calculate individual and pooled event rates to ensure consistency.

Study risk of bias assessment

In this review, the methodological quality of various types of studies, including cohort and case‒control studies, was evaluated via the Newcastle–Ottawa scale [22]. For cross-sectional studies, a modified version of the Newcastle–Ottawa scale was used as suggested in a previous systematic review [23]. Two independent reviewers conducted the assessments, and a third reviewer resolved any disagreements through mutual consensus. Notably, the overall quality of the studies was not used as a basis for exclusion in this review. Instead, the primary focus was on conducting a comprehensive assessment of postvaccination menstrual changes across the selected studies.

Synthesis methods

All the data were analyzed via Comprehensive Meta-Analysis Software Version 4.0. Forest plots were created to calculate the individual and pooled prevalence of different types of menstrual disorders, 95% confidence intervals (CIs) were calculated for both fixed effects and random effects, and heterogeneity was assessed with Q statistics and the I2 test. The cutoff values for the I2 statistic were used to classify heterogeneity as very low (0–25%), low (25–50%), moderate (50–75%), or high (> 75%). Publication bias was assessed via funnel plots and Begg’s adjusted rank correlation test. A P value < 0.10 was considered to indicate publication bias.

Results

Study selection

The PubMed search produced 65 articles, the Web of Science search yielded 54 articles, and ScienceDirect provided 330 articles. A manual search for relevant articles resulted in the identification of 14 articles. After excluding articles that did not meet the inclusion criteria and removing duplicate citations, 83 articles were identified for thorough retrieval and examination. At this stage, three articles were excluded because they were preprints [24,25,26]. Among the remaining 80 articles, 69 were excluded for several reasons related to participants, interventions, study design, and scope of the studies. These included studies that involved adolescents, peri/postmenopausal, breastfeeding, and pregnant women; studies with unclear pregnancy and/or lactation status; studies that involved women with known hormonal or pathological conditions that affect menstruation; studies with unspecified menstrual changes; studies with unstated COVID-19 vaccine types; studies that reported COVID-19-related adverse events, including menstrual changes, without specifying the type of change; and other reasons, such as study design (experimental, quasiexperimental, mixed-method) or studies of menstrual changes with different scopes, such as fertility and endometriosis. Thus, 11 studies were included for the final review, synthesis of evidence, and assessment of the risk of bias [27,28,29,30,31,32,33,34,35,36,37]. The process of selection and exclusion is shown in the PRISMA flow chart (Fig. 1).

Fig. 1
figure 1

PRISMA flowchart

Full size image

Study characteristics

The 11 studies that were selected included 26,283 participants. Among the selected studies, diverse research designs were used. Specifically, five studies adopted a cohort design; one study employed a case‒control approach. Additionally, five studies utilized a cross-sectional design. For details of the study design, participant demographics, type of vaccine administered, and specific outcomes, please refer to Table 1 for a comprehensive overview.

Table 1 Study characteristics
Full size table

Risk of bias in studies

Assessment of quality for the five cohort studies revealed one study of good quality (7 points), whereas the remaining studies were of fair quality (3–4 points) owing to a lack of unexposed controls, ascertainment of exposure, and adequate follow-up. On the other hand, one cross-sectional study was of fair quality (5 points), whereas four studies were of poor methodological quality (2–4 points) owing to the lack of information on nonrespondents, ascertainment of exposure to the COVID-19 vaccine, and assessment of outcomes via self-reports. The details are shown in Tables 2, 3, and 4.

Table 2 Quality assessment of studies using the Newcastle‒Ottawa scale for assessing cohort studies
Full size table
Table 3 Quality assessment of studies using the Newcastle‒Ottawa scale for assessing case‒control studies
Full size table
Table 4 Quality assessment of studies using a modified Newcastle‒Ottawa scale for assessing cross-sectional studies
Full size table

Key findings on menstrual cycle changes associated with COVID-19 vaccination

The studies included in our analysis did not provide data on the overall prevalence of menstrual cycle changes. Instead, they provide information specific to various types of menstrual alterations. Therefore, we generated multiple forest plots categorizing menstrual cycle changes into irregular cycles, abnormal cycle duration, abnormal menstrual flow, and dysmenorrhea.

Prevalence of irregular cycles after COVID-19 vaccination

Seven studies were included in the analysis of the incidence of irregular circulation cycles after COVID-19 vaccination. Overall, the pooled prevalence was 16% (95% CI: 5.8–37.2%). There was high heterogeneity among the included studies (I2 = 100%; Q = 2576; P value < 0.001), as shown in the forest plot (Fig. 2). However, no publication bias was found in any of the studies (p = 0.440) according to Begg’s adjusted rank correlation test.

Fig. 2
figure 2

Forest plot of irregular cycles after COVID-19 vaccination

Full size image

Prevalence of abnormal cycle duration after COVID-19 vaccination

Figure 3 shows the forest plot for the pooled prevalence of abnormal cycle duration after COVID-19 vaccination. Four studies were included in the analysis of the prevalence of abnormal cycle duration after COVID-19 vaccination. Overall, the pooled prevalence was 27.3% (95% CI: 7.2–64.6%). There was highly significant heterogeneity among the included studies (I2 = 100%; Q = 2658; P value < 0.001). No publication bias was found in any of the studies (p = 0.248) via Begg’s adjusted rank correlation test.

Fig. 3
figure 3

Forest plot of abnormal cycle duration after COVID-19 vaccination

Full size image

Prevalence of abnormal menstrual flow after COVID-19 vaccination

Figure 4 shows the forest plot for the pooled prevalence of heavy flow after COVID-19 vaccination, in which seven studies were included. Overall, the pooled incidence was 11.7% (95% CI: 5.8–22%), and there was highly significant heterogeneity among the included studies (I2 = 100%; Q = 1116; P value < 0.001). No publication bias was found in any of the studies (p = 0.326) via Begg’s adjusted rank correlation test. Furthermore, five studies were included in the analysis of the prevalence of light menstrual flow after COVID-19 vaccination. Overall, the pooled prevalence was 5.5% (95% CI: 2.3–12.5%). There was highly significant heterogeneity among the included studies (I2 = 99%; Q = 317; P value < 0.001). No publication bias was found in any of the studies (p = 0.312) via Begg’s adjusted rank correlation test.

Fig. 4
figure 4

Forest plot of heavy menstrual flow after COVID-19 vaccination

Full size image

Prevalence of dysmenorrhea after COVID-19 vaccination

Figure 5 shows the forest plot for the pooled prevalence of painful menstruation (dysmenorrhea) after COVID-19 vaccination, in which five studies were included for data analysis. Overall, the pooled prevalence was 22.1% (95% CI: 5.2–59.4%). There was highly significant heterogeneity among the included studies (I2 = 100%; Q = 3764; P value < 0.001). No publication bias was found in any of the studies (p = 0.164) via Begg’s adjusted rank correlation test.

Fig. 5
figure 5

Forest plot of dysmenorrhea after COVID-19 vaccination

Full size image

Discussion

The results of our systematic review and meta-analysis highlight the potential association of COVID-19 vaccination with menstrual cycle changes among adult women. We observed that more than one quarter of women experienced abnormal cycle duration, followed by dysmenorrhea in approximately 22% of women, while abnormal menstrual cycle length and flow were less common. When these findings are compared with the literature on menstrual alterations related to COVID-19 vaccination, our results align with and add context to previous observations [38]. One large prospective study indicated that women who received the COVID-19 vaccine experienced a slight increase in the menstrual cycle length of less than one day after both the first and second doses [21]. Individuals who received the vaccine during the follicular phase of their menstrual cycle were more likely to experience cycle length disturbances than those who received it during the luteal phase [39].

The current review revealed a lower prevalence of heavy menstrual flow than did another meta-analysis, which reported that menorrhagia was the most frequently observed menstrual change, with a pooled prevalence of 24.24% [40]. However, our findings might be explained by novel data suggesting that decreased menstrual volume and a prolonged cycle are consequences of SARS-CoV-2 infection independent of its severity [41], and four of our included studies involved patients with prior COVID-19 disease [27, 31, 34, 35]. In contrast, a recently published systematic review and meta-analysis did not find a significant difference in the risk of adverse menstrual events between women who received the COVID-19 vaccine and those who did not, but the evidence is limited by significant heterogeneity and a high risk of bias in the included studies [42].

Moreover, the reporting in this SR was limited to certain outcomes; for example, the duration of menstrual changes and linked vaccine type were reported in three prospective cohort studies that followed participants for sufficient periods. Overall, menstrual changes are temporary and typically last for one to two menstrual cycles postvaccination [31, 33, 36]. One recent study revealed that participants who received the booster vaccine dose had an average cycle duration of 1.20 days longer (95% CI: 1.00–1.40), which persisted from the second to the fourth cycle after receiving the mRNA vaccine [43]. When the vaccination types were compared, the group that received only CoronaVac reported a higher rate of menstrual irregularities than did the groups that received both CoronaVac and BioNTech, with 32.2% and 19.1%, respectively (p = 0.033) [36]. Sensitivity analyses comparing menstrual cycle changes by vaccine brand did not significantly vary among the vaccinated cohorts that received the Pfizer-BioNTech vaccine (55%), the Moderna vaccine (35%), or the Johnson & Johnson/Janssen vaccine (7%) [33].

Although the current review did not explore potential causal relationships, it is important to note that various pandemic-related factors can lead to temporary changes in the menstrual cycle [44]. Several intrinsic mechanisms have been proposed to clarify the link between significant immune challenges, such as vaccination, and the menstrual cycle [45, 46]. These mechanisms involve immune activation in response to diverse stimuli, including immunological influences on the hormones that regulate the menstrual cycle [47, 48]. Furthermore, immune cells in the uterine lining play crucial roles in the build-up and breakdown of this tissue during each menstrual process [49]. Other extrinsic factors that could contribute to menstrual changes include stress related to the pandemic, lifestyle changes due to the pandemic, and infection with SARS-CoV-2 [18, 50]. Reaching a definitive conclusion regarding the direct link between these changes and a specific type of COVID-19 vaccine presents a significant challenge. This challenge arises from various factors, including differences in study designs, research methods, and subjectivity in reporting these outcomes. Moreover, early assessments of adverse events in COVID-19 vaccine trials were focused primarily on systemic and major adverse events [51, 52].

This review was based on an extensive search, pooling data from studies with different populations, and applying strict eligibility criteria to eliminate studies with potential confounding factors. We calculated both individual event rates and combined event rates via appropriate statistical methods. These qualities can be considered strengths of the analysis. Thus, this study may provide valuable insights into menstrual alterations in adult women after COVID-19 vaccination. Nevertheless, it is essential to interpret the results cautiously due to certain limitations. First, there was a moderate to high risk of bias for some of the included studies, owing to the study design, reliance on self-reported outcomes, short follow-up periods, and lack of control groups. Second, we observed significant heterogeneity in our findings, likely stemming from several factors, including variations in sample size, differences in sampling methods, the diverse nature of the populations studied, and variations in settings and vaccine administration.

Currently, we have sufficient evidence from studies over the past three years indicating the association of the COVID-19 vaccine with temporary menstrual cycle alterations in adult women. However, the exact mechanisms remain unclear; therefore, experimental studies are warranted to determine the temporal link between the COVID-19 vaccine and menstrual cycle changes. The following criteria might optimize the study design and strengthen outcomes: (1) recruitment of unvaccinated controls; (2) inclusion of different age categories, e.g., adolescents and perimenopausal women; (3) the establishment of clinical measures for menstrual characteristics; (4) adequate follow-up of not less than one year after exposure to the COVID-19 vaccine series/booster dose; (4) adjustment for other factors that contribute to menstrual changes.

Finally, it is important to consider the menstrual cycle as a crucial indicator of women’s health and not merely fertility/pregnancy-related health. Thus, efforts should be made to increase the awareness of health care providers regarding the latest evidence of the impact of the COVID-19 pandemic on women’s health. Moreover, women’s concerns about vaccination should be addressed, and proper counseling based on the available evidence should be provided. With respect to public health considerations, although menstrual cycle changes are potential side effects of COVID-19 vaccination, they should not discourage vaccination. Additionally, mechanisms of reporting and monitoring of menstrual health outcomes for future COVID-19 vaccination programs should be strengthened.

Conclusions

This systematic review consolidates the growing body of evidence regarding the potential association of COVID-19 vaccination with menstrual cycle alterations, highlighting abnormal cycle duration and dysmenorrhea as more commonly reported than other menstrual cycle characteristics. However, the evidence is limited by a moderate risk of bias and heterogeneity among the included studies. Thus, further trials are needed to explore causal relationships. While these observed menstrual variations prompt significant considerations for women’s health and health care practices, vaccination continues to be advised for women of reproductive age.