Effects of Covid-19 Vaccines on the Menstrual Cycle: A Cross-Sectional Study.

Effects of Covid-19 Vaccines on the Menstrual Cycle: A Cross-Sectional Study. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Covid-19 Vaccines on the Menstrual Cycle: A Cross-Sectional Study. Chavin Gopaul, Bharat Bassaw, Dale Ventour, Davlin Thomas This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2048853/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Prior clinical studies that sought to investigate the safety and efficacy of Covid-19 vaccines did not list menstrual cycle changes as a side-effect. However, following reported cases of menstrual cycle disturbances after vaccination, this study sought to examine the link between Covid-19 vaccination and post-vaccine menstrual cycle abnormalities in pre- and post-menopausal women. Methods: A cross-sectional research design approach using online surveys was employed to investigate the link between vaccination and changes in menstrual cycle. The participants consisted of a cohort of 657 pre- and post-menopausal women with the majority drawn from the reproductive age group (25-44 years). The inclusion criteria was that participants must have received any type of Covid-19 vaccine, not be pregnant and those that did not have a negative diagnosis in any gynecologic condition. Of the eligible sample size, only 344 participants met the inclusion criteria. The sociodemographic and menstrual cycle data was collected from an online survey. Data was analyzed using descriptive, inferential chi-square tests, logistic regression, and correlation. Results: The results partially confirmed the findings from prior studies that Covid-19 vaccination is associated with significant changes in the women’s menstrual cycle flow and menstrual period length even after controlling for age, Body Mass Index, and ethnicity. Other menstrual cycle disturbances such as missed periods, cycle regularity, and spotting/vaginal bleeding were noted to be less significant. However, the extent of menstrual cycle changes was less severe and decreased after the second dose vaccination. It was found that 11.1% and 37.5% of post-menopausal women reported menstrual symptoms after the first and the second dose cycle respectively. Conclusion: The study concludes that although Covid-19 vaccines tend to adversely affect women’s menstrual cycle, these changes are short-lived. The findings have important implications in enhancing the success of Covid-19 vaccination programs by reducing cases of vaccine hesitancy among reproductive-age women. Covid-19 Vaccine Side-Effects Menstrual Cycle Female Reproductive Health Covid-19 Pandemic Vaccine Hesitancy Figures Figure 1 Figure 2 Figure 3 Introduction Covid-19 vaccination is considered the best option for protection against the potentially adverse effects of the SARS-CoV2 infections. 1 Some of the common side-effects associated with Covid-19 vaccines as listed by the UK’s Medicines and Healthcare Products Regulatory Agency (MHRA) as well as the U.S. Vaccine Adverse Reporting System (VAERS) include a sore arm, fever, fatigue, myalgia, and headache. 2 However, in prior clinical studies, changes in menstrual cycles, period flow, menses length, vaginal bleeding were not identified and listed as common side-effects following Covid-19 vaccination. 3 By May 2021, fewer than 200 young vaccinated women had self-reported a menstrual-related disturbance following vaccination to VAERS. 4 However, by September 2021, more women (at least 30,000 reports) had complained of the adverse side-effects related to menstrual cycle abnormalities following vaccination to the UK’s MHRA yellow card surveillance scheme. 2 There were concerns that a possible link between Covid-19 vaccination and menstrual cycle disturbances might lead to vaccine hesitancy, especially among young women. 5 Therefore, clinical studies were needed to evaluate the extent of this relationship in order to assure the public and maintain trust that the vaccines do interfere substantially with fertility. 6 Menstrual cyclicity is an obvious sign of health and fertility in young women and its variation from month to month across a person’s lifespan is considered normal. 7 Specifically, changes in menstrual cycle length, which can be between 24-38 days is considered normal if it falls within 8 days. 3 The normal variation in menstrual cycle can be a concern for young women, especially if it is associated with Covid-19 vaccination exposure. 4 The U.S. National Institute of Health (NIH) had allocated $1.67 million to fund clinical research on the possible association between Covid-19 vaccination and menstrual cycle abnormalities. 2 The findings based on the most recent clinical studies indicate that there is significant evidence that women tend to experience menstrual cycle disturbances following Covid-19 vaccination. 3, 4, 6, 8 A study by the Norwegian Institute of Public Health 9 reported that 13.6% of young women, 18-30 years had experienced heavier periods after the first dose while 15.3% of them experienced heavier menstrual periods after the second dose. A research commissioned by the U.S. National Institute of Health (NIH) further reported 4 that Covid-19 vaccination was associated with less than a day (i.e., 0.71 day) increase in menstrual cycle length for both vaccine-dose cycles compared to the pre-vaccine menstrual cycle. Similarly, using a cohort of 79 spontaneously cycling young women, the study by Woon and Male 3 found that Covid-19 doses were associated with delay in menstrual cycle (2.3 days after the first dose and 1.3 days after the second dose). However, most of these studies found that menstrual changes tend to reverse in subsequent cycles. 4, 6, 8, 10, 11 A study by Muhaidat also found that 66.3% of the participants experienced menstrual symptoms in the period following vaccination. 11 The insight based on clinical studies indicate that the association between Covid-19 vaccination and menstrual cycle changes is linked to the immune activation in response to stimuli. 2 Biologically, it has been noted that the Covid-19 vaccines similar to the human papillomavirus (HPV) vaccines tend to create immune stimulation on the hormones that control the menstrual cycle. 7 The twin island Republic of Trinidad and Tobago has an estimated population of 1.4 million 12 . The country reported its first case of SARS-CoV-2 on March 12, 2020 13 . Since then, public health measures such as border closures, social distancing, and mask-wearing have been implemented to limit the spread of the virus 14 . On February 17th, 2021, Trinidad and Tobago joined the global effort to control the pandemic through vaccination when the Ministry of Health embarked upon the Phase 1 rollout of its National COVID-19 Vaccination Program, with healthcare workers being among the first groups to receive the first doses of the vaccine, along with persons aged 60 years and over and persons with non-communicable diseases. By April 2021, subsequent phases (2 and 3) of the campaign offered frontline essential workers and the eligible public the opportunity to be inoculated. A study investigating the acceptance of the vaccine among healthcare workers in Trinidad and Tobago found that age, profession and trust in international public health organizations and other healthcare professionals predict their vaccine uptake 15 . Researchers in Trinidad and Tobago also reported on the safety of the COVID-19 vaccine by examining the side-effects of the ChAdOx1 nCov-19 (Oxford, AstraZeneca COVID-19 vaccine) among healthcare workers 16 . The study demonstrated that the rate of occurrence of most local and systemic side-effects was less than 50%, corroborating the manufacturer’s claim that the vaccine is safe, with implications to reduce vaccine hesitancy through public health efforts 16 . Other studies in Trinidad and Tobago have been limited to investigating COVID-19 patients’ epidemiological characteristics 17 as well as laboratory predictors of COVID-19 admissions to ICU 18 . The most frequent comorbidities were found to be hypertension and diabetes mellitus, while the most prevalent symptoms were non-productive coughs and fevers 17 . As for laboratory factors, neutrophils, aspartate transaminase (AST), lactate dehydrogenase (LDH) and C-reactive protein (CRP) were suitable predictors of COVID-19 patients in need of ICU care 18 . Both studies allude to the unique characteristics of COVID-19 patients in Trinidad and Tobago and the greater need for research especially in this region. The present study aimed to investigate the association between Covid-19 vaccination and changes in menstrual cycle among young women employed at the North Central Regional Health Authority of Trinidad and Tobago who had been vaccinated between 1 st June 2020 and 18 th March 2022. The study examined whether both the first and second vaccine-dose cycles had a significant effect on variation in the participants’ menstrual cycle. A cross-sectional study design was undertaken using online self-administered surveys, which were employed to collect sociodemographic and menstrual cycle data from the women. The survey was administered from December 2021 to March 2021. The eligible participants consisted of 657 adult healthcare workers who currently menstruate or who have had menstrual cycles in the past and who received at least one dose of the COVID-19 vaccine.. However, of those only 317 women met the inclusion criteria for this study indicated in Figure 1. The data was analyzed using both descriptive and inferential statistical analysis in order to examine the link between Covid-19 vaccination and variation in menstrual cycle. Inferential statistical analysis included logistic regression, correlation analysis, and Chi-square tests of association. Methods Research Design The study employed a cross-sectional research design approach to investigate the effect of Covid-19 vaccines on the menstrual cycle of healthcare workers (HCWs) employed at the North Central Regional Health Authority (NCRHA) of Trinidad and Tobago. The NCRHA was selected as the setting for HCWs as it was the first RHA to distribute COVID-19 vaccines to HCWs at the outset of the country’s national vaccination program. Data capture was conducted via the electronic distribution of a self-administered questionnaire to NCRHA HCWs. The survey remained open for responses from December 18 th 2021 to March 18 th 2022 . Using the stated research design approach, participants who included vaccinated women were required to indicate their sociodemographic information and their corresponding menstrual cycle details before and after vaccination. The anonymous responses were automatically collated via the online platform to which only the principal investigator had access. The collated responses were downloaded as a Microsoft Excel file by the principal investigator, and subsequently coded into an SPSS database and analyzed using IBM SPSS V.21 software. The study protocol was reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. Participants A judgment sampling method was used to obtain the sample of HCWs for this study. The electronic questionnaire was distributed via email to all female NCRHA HCWs. Of the 4,205 NCRHA HCWs to whom the questionnaire was sent, 657 HCWs returned a completed questionnaire during the study period. This cohort of 657 Covid-19 vaccinated women included those who were over 18 years ( Mean age = 36.42 years). Their mean body mass index (BMI) before vaccination was 29.24 (29.24 8.38 kg/m 2 ). The participants consisted of both pre- and post-menopausal women who had either experienced or not experienced a menstrual period in the last 12 months and who had received either the first or second dose vaccine between 1 st June 2020 and 18 th March 2022. Data Collection Instrument Sociodemographic and menstrual cycle data before and after vaccination was collected using a self-administered survey/questionnaire. This data collection instrument was distributed and administered to the email addresses of the female NCRHA HCWs The instrument was modeled on relevant questions selected from a digital survey investigating the impact of COVID-19 on women’s reproductive health in Ireland and the United Kingdom 19 and a digital survey investigating the changes in menstruation as a possible side-effect of COVID-19 vaccines 20 . The online questionnaire consisted of 57 detailed self-report questions that covered two main domains. The first section sought to collect participants’ sociodemographic details, including age, ethnicity, BMI, pregnancy status, breastfeeding status, the date of first vaccination, pre-existing medical diagnosis, and method of contraception. The second section contained questions on the participants’ menstrual cycle regularity, period flow, menstrual period length, and other abnormalities, which were experienced pre- and post-vaccination. The electronic self-administered questionnaire was prefaced with an informed consent form which explained that the survey was anonymous, that participation was voluntary, and explained the purpose of the study. All ethical standards of voluntary participation and confidentiality were maintained. Participation in this study was voluntary and HCWs received no form of financial remuneration in order to reduce the risk of response bias. Due to the anonymous nature of the questionnaire, confirmation of participants’ vaccination could not be verified. Outcome Measures The main outcome measures of this study included the association between the COVID-19 vaccine and participants’ reported menstrual cycle disturbances. Ethics This study was granted ethical approval by The North Central Regional Health Authority Ethics Committee, Trinidad, and The Ministry of Health of Trinidad and Tobago Ethics Committee (3/13/441 Vol. II). Data Analysis The data was analyzed in SPSS v.26 statistical program. To examine the association between Covid-19 vaccination and menstrual cycle changes, both descriptive and inferential statistical analysis was performed. The participants’ sociodemographic details were analyzed using descriptive statistical analysis and presented as frequencies and percentage frequencies. The association between Covid-19 vaccination and menstrual cycle disturbances were analyzed using correlation analysis. Finally, logistic regression and the non-parametric Chi-square test were performed to examine the effect of Covid-19 vaccine-dose on menstrual cycle changes after accounting for participants’ age, ethnicity, and BMI. A parametric paired t -test was used to compare the mean change in menstrual cycle regularity, menstrual cycle length, and period flow between baseline (pre-vaccination) and after vaccination. A statistical significance level of 0.05 was used to conduct the inferential analysis. Results Sociodemographic Data Six hundred and fifty-seven pre- and post-menopausal women participated in the survey . However, three hundred and forty four met the inclusion criteria for this study (see Figure 1). Participants diagnosed with polycystic syndrome ( n = 166), uterine fibroids ( n = 114), had abnormal uterine bleeding ( n = 69), or were pregnant during the period of study ( n = 68), endometriosis ( n = 37) and those breastfeeding ( n = 31) were excluded. The participants’ sociodemographic data (see Table 1) indicated that the mean BMI was 29.24 8.38 kg/m 2 . Most women who participated in the study were between 25-34 years ( n = 135; 42.6%) and 35-44 years ( n = 112; 35.3%). The majority of the women were of the reproductive age group. Approximately forty-four percent of the participants were Africans ( n = 138; 43.5%). In terms of the first dose of Covid-19 vaccine, the majority ( n = 157; 49.5%) had received the Oxford AstraZeneca vaccine while for the second dose of Covid-19 vaccine, the majority ( n = 153; 48.3%) of the women had been injected with Oxford AstraZeneca vaccine and 30.6% of them had received Sinopharm vaccine. The descriptive statistics also indicated that only 16.1% of the participants had reported a positive Covid-19 diagnosis prior to the study, which was conducted between April and June 2022. The majority ( n = 280; 88.3%) of the women who participated in the study reported a regular menstrual cycle. In terms of the menstrual period length, most ( n = 138; 43.5%) of the women reported an average of 3 to 5 days. The majority ( n = 230; 72.6%) had a moderate period flow while only 12.6% of the women reported a heavy period flow. Table 1 Sociodemographic Data Mean Standard Deviation Body Mass Index (BMI) 28.63 8.33 Menstrual cycle length 1.83 0.51 Frequency ( n ) Percentage Frequency (%) Age (Years) : 18-24 15 4.7 25-34 135 42.6 35-44 112 35.3 45-54 46 14.5 55-64 8 2.5 ≥ 65 1 0.3 Ethnicity : African 138 43.5 East Indian 102 32.2 Hispanic, Mixed Races and Others 77 24.3 First Dose Covid-19 Vaccine: Johnson & Johnson 10 3.2 Oxford AstraZeneca 157 49.5 Pfizer-BioNTech 46 14.5 Sinopharm 104 32.8 Second Dose Covid-19 Vaccine: Johnson & Johnson 0 0.0 Oxford AstraZeneca 153 48.3 Pfizer-BioNTech 42 13.2 Sinopharm 97 30.6 Did not receive dose 2 25 7.9 Covid-19 Diagnosis: No 238 75.1 Yes 51 16.1 I think so 12 3.8 Unsure 13 4.1 Other diseases/infections 3 0.9 Menstrual Cycle Regularity: Rarely menstruate 18 5.7 Irregular 19 6.0 Regular 280 88.3 Menstrual Period Length: Rarely menstruate 18 5.7 1-3 days 33 10.4 3-5 days 138 43.5 5-7 days 121 38.2 > 7 days 5 1.6 Other 2 0.6 Menstrual Period Flow: Rarely menstruate 18 5.7 Heavy 40 12.6 Moderate 230 72.6 Light 28 8.8 Other 1 0.3 Menstrual Cycle Disturbances after Covid-19 Vaccination The non-parametric chi-square inferential test was used to compare the extent of menstrual cycle disturbances after the first dose and the second dose cycle. Table 2 shows that there was no statistically significant change in menstrual cycle regularity after the first dose vaccination compared to the second dose vaccination (ρ > 0.05). The chi-square test indicated that exposure to Covid-19 vaccination resulted in a significant change in the women’s menstrual period flow (ρ 0.05). The participants’ menstrual period length was not significantly longer after the first dose compared to the second dose vaccination (ρ > 0.05). The inferential analysis findings based on the Chi-square test also indicated that women experienced other forms of menstrual cycle abnormalities after exposure to the first and the second dose Covid-19 vaccines. The women experienced incidences of late menstrual periods (ρ < 0.001), other menstrual bleeding (ρ < 0.001), severe menstrual symptoms (ρ < 0.001), and other menstrual symptoms (ρ < 0.001). In this case, ‘other menstrual bleeding’ refers to other forms of menstrual bleeding or abnormalities besides those specified in the analysis. However, in the majority of the cases, the variation was not statistically significant. For instance, missed periods (ρ > 0.05) and spotting/vaginal bleeding (ρ > 0.05) were found to be statistically insignificant. Finally, the findings based on the inferential chi-square test indicated that there was a significant change in the number of days before menstrual symptoms started after the first and the second dose Covid-19 vaccination (ρ < 0.001). For those who reported the menstrual symptoms, the majority stated that they tend to occur 14 days after the receiving the first or the second dose of Covid-19 vaccine (ρ < 0.001). Table 2 Menstrual Cycle Disturbances after Covid-19 Vaccination using Chi-Square Tests n (%) First (1 st ) Dose Second (2 nd ) Dose ꭓ 2 -value Change in Cycle Regularity : 165.82 *** No 244 (71.0) 224 (64.7) Yes 100 (29.0) 95 (27.4) Did not receive dose 2 25 (7.9) Change in Period Flow : 387.64*** About the same 216 (62.8) 195 (56.2) Heavier 66 (19.2) 71 (20.5) Lighter 23 (6.6) 22 (6.3) Not applicable 39 (11.4) 32 (9.1) Did not receive dose 2 25 (7.9) Change in Period Length : 402.77 *** About the same 238 (69.1) 225 (65.0) Longer 40 (11.7) 39 (11.4) Shorter 26 (7.6) 21 (6.0) Not applicable 40 (11.7) 34 (9.8) Did not receive dose 2 25 (7.9) Late Period : 156.24*** No 271 (78.9) 261 (75.4) Yes 73 (21.1) 58 (16.7) Did not receive dose 2 25 (7.9) Missed Period : 66.13*** No 323 (94.0) 299 (86.4) Yes 21 (6.0) 20 (5.7) Did not receive dose 2 25 (7.9) Spotting/Vaginal Bleeding : 158.02*** No 310 (90.2) 287 (83.0) Yes 34 (9.8) 32 (9.1) Did not receive dose 2 25 (7.9) Other Menstrual Bleeding : 59.65*** No 322 (93.7) 303 (87.4) Yes 22 (6.3) 16 (4.7) Did not receive dose 2 25 (7.9) Severe Menstrual Symptoms : 200.79*** No 284 (82.6) 272 (78.5) Yes 60 (17.4) 47 (13.6) Did not receive dose 2 25 (7.9) Other Menstrual Symptoms : 96.95*** No 308 (89.6) 289 (83.3) Yes 36 (10.4) 30 (8.8) Did not receive dose 2 25 (7.9) No Menstrual Symptoms : 159.08*** No 168 (48.9) 152 (43.8) Yes 176 (51.1) 167 (48.3) Did not receive dose 2 25 (7.9) Number of Days before Symptoms Started : 278.25*** 1-3 days 16 (4.7) 13 (3.8) 4-7 days 10 (2.8) 8 (2.2) 8-14 days 14 (4.1) 19 (5.4) > 14 days 58 (17.0) 61 (17.7) Menstruating when received vaccine 20 (5.7) 1 (0.3) Not applicable 226 (65.6) 218 (62.8) Blank 2 (0.6) 0 (0.0) Did not receive dose 2 25 (7.9) Notes : ρ-value was calculated using the non-parametric chi-square test and indicates association in menstrual cycle symptoms after the first dose and the second dose cycle. ρ*** (Significance at α = 0.001). Table 3 presents a summary of the chi-square test to assess the difference in menstrual cycle length and period flow before and after the first dose Covid-19 vaccination. The results indicated that there was a significant variation in the women’s menstrual period length before and after the first dose vaccination (ρ < 0.001) (see Figure 2). Similarly, the chi-square test findings presented in Table 3 indicated that exposure to the first dose Covid-19 vaccination resulted in a significant variation in menstrual period flow compared to the situation before vaccination (ρ < 0.001) (see Figure 3). The ( n = 344) represents the women who received first dose vaccination while the ( n = 319) captures the women who received the second dose vaccination. Table 3 Period Length and Flow after First and Second Dose and for Unvaccinated Individuals Period Length Period Flow n Change in Length ( ꭓ 2 ) ρ-value Change in Flow (ꭓ 2 ) ρ-value First dose v. before vaccination : 344 121.15 < 0.001 119.36 < 0.001 Second dose v. before vaccination: 319 402.77 < 0.001 387.64 < 0.001 Notes : ρ-value was calculated using chi-square test and indicates association in menstrual cycle symptoms post-vaccination (after the first and second dose) and before vaccination. Table 3 shows that there were 344 women who participated in the first dose vaccination ( n = 344) compared to 319 who received the second dose ( n = 319). There was a statistically significant association between the respondents who reported ‘no’ to experiencing late period and those who reported ‘yes’ to experiencing late period (ρ < 0.001). Similarly, Table 4 shows that there was a significant difference in the number of respondents who reported ‘no’ to experiencing missed periods and those who reported ‘yes’ to the stated menstrual cycle abnormality (ρ < 0.001). Table 4 Late Period and Missed Period after the First and Second Dose Cycles First Dose Second Dose n Chi-square ( ꭓ 2 ) ρ-value n Chi-square (ꭓ 2 ) ρ-value Late period: No 271 (79%) 261 (82%) Yes 73 (21%) 317.00 < 0.001 58 (18%) 292.00 < 0.001 Missed Period: No 323 (94%) 299 (94%) Yes 19 (6%) 317.00 < 0.001 20 (6%) 292.00 < 0.001 Notes : ρ-value was calculated using chi-square test and indicates association in menstrual cycle abnormalities (late menstrual period and missed menstrual period) after the first and second dose vaccination. The results of the non-parametric chi-square test (see Table 5) indicate that there was a significant association in menstrual symptoms between pre- and post-vaccination period. The frequency of menstrual cycle regularity had changed significantly post-vaccination compared to the cycle regularity before Covid-19 vaccination (ρ < 0.001). The frequency of the period length and period flow as reported by respondents had significantly decreased after the first and second cycle dose vaccination compared to the menstrual period length and period flow before the Covid-19 vaccination (ρ < 0.001). For instance, moderate period flow decreased after the first dose vaccination (65.5%) and the second dose vaccination (61.4%) compared to 72.6% of respondents who had reported moderate period flow prior to the Covid-19 vaccination. Table 5 Chi-squared test: Menstrual Symptoms Post-Vaccination and Pre-Vaccination n (%) Post Vaccination Pre-Vaccination Chi-square (ꭓ 2 ) First Dose Second Dose Regular menstruation 199 (62.8) 189 (59.6) 280 (88.3) 156.14*** Period length 266 (84.0) 248 (78.2) 297 (93.7) 118.23*** Moderate period flow 208 (65.5) 195 (61.4) 230 (72.6) 96.55*** Light period flow 25 (8.0) 24 (7.5) 28 (8.8) 205.13*** Notes : ρ-value was calculated using the non-parametric chi-squared test and indicates variation in menstrual cycle symptoms post-vaccination (after the first and second dose) and menstrual cycle symptoms before Covid-19 vaccination. ρ*** (Significance at α = 0.001). Trends in Women who Experienced Menstrual Changes after Covid-19 Vaccination There are two categories of women who do not menstruate. The first is those that have not yet reached menopause (pre-menopausal) but do not menstruate. The second is those that have reached menopause and were not menstruating prior to receiving Covid-19 vaccines. As shown in Table 6, some of the women in the two categories that were not menstruating previously experienced menstrual cycle after receiving Covid-19 vaccine. A summary of the Chi-squared test in pre- and post-menopausal women who experienced menstrual cycle changes following Covid-19 vaccination is presented in Table 6. The findings show that after the first dose SARS-CoV-2 vaccination, 22 pre- and post-menopausal women (3.3%) reported menstrual cycle abnormalities. However, after the second dose cycle, 28 pre- and post-menopausal women (4.3%) experienced menstrual cycle changes. The increase in the number of women that were not menstruating but reported menstrual cycle abnormalities after the second dose cycle was statistically significant (ρ < 0.001). The results also reveal that among the post-menopausal women (55-64 years and those above 65 years), 37.5% of them reported menstrual cycle abnormalities after the second dose vaccination compared to only 11.1% of the stated group of women that reported menstrual bleeding after the first dose cycle. The change in the proportion of post-menopausal women who reported menstrual cycle changes after the first and the second dose cycle was statistically significant (ρ < 0.001). Table 6 Chi-square test: Trends in Menstrual Cycle Changes after Vaccination n (%) First (1 st ) Dose Second (2 nd ) Dose Chi-square (ꭓ 2 ) Do not menstruate but had menstrual changes after vaccination 22 (3.3) 28 (4.3) 299.01*** Post-menopausal women who reported menstrual symptoms 1 (11.1) 3 (37.5) 46.43*** NB: ρ-value was calculated using chi-squared test and indicates menstrual cycle changes after the first and second dose Covid-19 vaccination. ρ*** (Significance at α = 0.001). Logistic Regression Analysis Logistic regression analysis was conducted to examine the effect of Covid-19 vaccination on the women’s menstrual cycle controlling for the participants’ age, BMI, and ethnicity (see Table 7). The results indicated that after the first dose cycle, none of the variables had a significant effect on likelihood of causing missed period, late period, spotting, and no menstrual cycle symptoms. However, the women’s BMI had a greater odds of contributing to cases of missed period (OR = 1.15; ρ < 0.05) and spotting (OR = 1.55; ρ < 0.05). In addition, the women’s ethnic orientation (OR = 1.87; ρ < 0.05) had a greater likelihood of contributing to ‘no menstrual symptoms’ at 5% significance level. The logistic regression analysis findings indicated that after controlling for the participants’ age, BMI and ethnicity, exposure to the second dose had a significant influence in raising the likelihood (odds) of menstrual cycle abnormalities among the women that participated in the study. Specifically, exposure to the second dose vaccine increased the likelihood of women reporting late period (OR = 2.16; ρ < 0.001), missed period (OR = 2.03; ρ < 0.001), spotting/vaginal bleeding (OR = 2.27; ρ < 0.001) and no menstrual symptoms (OR = 1.23; ρ < 0.001). The implication is that on average, women that had received the second dose Covid-19 vaccine were more likely to report incidences of menstrual cycle abnormalities. Table 7 Logistic Regression: Effect of First and Second Dose Vaccine on Menstrual Cycle Late Period (OR 95% CI) Missed Period (OR 95% CI) Spotting (OR 95% CI) No Menstrual Symptoms (OR 95% CI) First Dose : First dose 0.78 (0.56 1.11) 0.75 (0.45 1.14) 0.66 (0.31 1.08) 0.96 (0.63 1.46) Age 0.91 (0.77 1.03) 0.44 (0.23 0.69) 2.03** (1.33 2.67) 0.64 (0.23 1.28) BMI 0.89 (0.67 1.23) 1.15*** (0.78 1.49) 1.55*** (0.93 2.14) 0.84 (0.54 1.26) Ethnicity 0.67 (0.81 1.01) 1.45 (0.97 1.92) 0.78* (0.42 1.05) 1.87*** (1.11 2.52) Late Period (OR 95% CI) Missed Period (OR 95% CI) Spotting (OR 95% CI) No Menstrual Symptoms (OR 95% CI) Second Dose : Second dose 2.16*** (1.43 3.26) 2.03*** (1.29 3.28) 2.27*** (1.47 3.28) 1.23*** (0.67 1.89) Age 0.56 (0.22 0.93) 0.69 (0.33 1.32) 0.75* (0.47 1.22) 0.77 (0.41 1.13) BMI 0.97 (0.55 1.38) 0.58 (0.38 0.84) 1.68** (0.88 2.61) 0.91 (0.53 1.42) Ethnicity 0.92 (0.58 1.46) 1.55 (0.92 2.01) 0.67 (0.31 1.02) 2.08** (1.312.88) NB: ρ*** (Significance at α = 0.001); ρ** (Significance at α = 0.05); ρ* (Significance at α = 0.10). Correlation Analysis Pearson correlation analysis was undertaken to examine the relationship between Covid-19 vaccination and changes to women’s menstrual cycle. The pearson correlation analysis findings for the first dose cycle (see Table 8) indicate that the first dose vaccination was not significantly associated with any of the participants’ sociodemographic factors such as age, BMI, and ethnicity. The implication is that none of the first dose Covid-19 vaccine types that were given to the women were significantly associated with their sociodemographic profiles. The pearson correlation analysis findings for the second dose vaccination (see Table 9) indicate that there was a significant negative association between the second dose cycle and the ethnic orientation of women ( r = -0.133; ρ < .1). However, the significant relationship between the second dose cycle and ethnicity was only significant at 10% significance level. The other sociodemographic factors (i.e., age and BMI) were not significantly related with exposure to the second dose vaccination. Table 8 Summary of the Pearson Correlation Analysis Results: First Dose Type of Vaccine Age Ethnicity BMI Type of Vaccine 1.000 -0.011 0.004 0.048 Age -0.011 1.000 -0.023 0.084 Ethnicity 0.004 -0.023 1.000 0.026 BMI 0.048 0.084 0.026 1.000 NB: ρ** (Significance at α = 0.001); ρ* (Significance at α = 0.05) Table 9 Summary of the Pearson Correlation Analysis Results: Second Dose Second Dose Age Ethnicity BMI Second Dose 1.000 -0.051 -0.133* -0.086 Age -0.051 1.000 -0.023 0.084 Ethnicity -0.133* -0.023 1.000 0.026 BMI -0.086 0.084 0.026 1.000 NB: ρ** (Significance at α = 0.001); ρ* (Significance at α = 0.05). Discussion Discussion of Findings The results based on the descriptive statistics, inferential chi-square test, and logistic regression found that exposure to Covid-19 vaccination had a significant effect in changing the women’s menstrual cycle although for certain menstrual cycle abnormalities, the effect was not significant. The non-parametric chi-square test findings confirmed that with the exception of late periods, other menstrual bleeding, severe menstrual symptoms, and other menstrual symptoms, participants did not report significant changes to their menstrual cycle. There was evidence that the majority did not experience menstrual cycle disturbances in the form of changes to their cycle regularity, period flow, and period length. In addition, vaccinated women did not experience other menstrual cycle abnormalities, including missed periods, spotting, and no menstruation in the subsequent period after the first and the second dose vaccination. These findings are fairly inconsistent with the outcome of previous studies which noted that exposure to Covid-19 vaccines was associated with delay in menstrual periods 20 , changes in cycle length 21 , late periods 22 , and substantial changes in the menstrual period flow. 23, 24, 25 There are biologically plausible mechanisms that explain the onset of menstrual cycle abnormalities after exposure to the Covid-19 vaccines. 26, 27 According to Male 28 , immunological stimulation of the hormones that control menstrual cycle by Covid-19 vaccines plays an important role in influencing changes to the women’s menstrual cycle after the first and the second dose cycle. In contrast to the findings from previous studies, this research noted that there was no significant variation in the women’s menstrual period length after the first and the second dose cycle vaccination. There was no significant variation in the women who reported to have longer menstrual period length after the first and the second dose cycle compared to the menstrual period length before vaccination. The stated outcome contrasts the insight based on the prior research findings by Edelman et al. who noted that 4 exposure to Covid-19 vaccines was associated with less than 1-day change in the menstrual cycle length. Specifically, Edelman et al. found that pre-menopausal women, 18-45 years who received Covid-19 vaccination experienced a 0.71 day-increase and 0.91 day-increase in period length after the first and the second dose cycle vaccination respectively. The variation could be explained by differences in the sampling and metholodical approach. This study found that the most common form of menstrual cycle abnormalities following Covid-19 vaccination were late period, heavy period, severe menstrual bleeding, and other forms of menstrual symptoms. The significant evidence on late period abnormalities is consistent with the prior findings by Woon and Male 3 , who noted that Covid-19 vaccines were associated with a 2.3-day and a 1.3-day delay after exposure to the first and the second-dose vaccine cycle respectively. The implication is that receiving Covid-19 vaccination is associated with a significant delay in menstrual period. Similarly, the evidence that women experienced heavier period flow after vaccination is consistent with the outcome based on the previous study by the Norwegian Institute of Public Health 9 , who noted that 13.6% and 15.3% of young women, 18-30 years experienced heavier menstrual period flow after the first and the second dose cycle respectively. There was no evidence to confirm that the other common menstrual abnormalities such as cycle irregularity and missed period were significant following Covid-19 vaccination. Consistent with the previous research findings, the results of this study also presented evidence that changes to the women’s menstrual cycle after exposure to the Covid-19 vaccination are short lived. 9, 28, 29, 30 The results of the chi-square test analysis indicated that there were fewer incidences of menstrual disturbances after the second dose cycle compared to the menstrual abnormalities after the first dose cycle. The implication is that the extent of immunological stimulation of the menstrual cycle hormones tends to decrease after the second dose cycle. However, in other studies, 9, 31, 32 there was evidence of adverse post-vaccine menstrual cycle flow after the second dose cycle compared to the first dose cycle. For instance, the study published by the Norwegian Institute of Public Health found that, 9 15.3% of young women, 18-30 years reported heavier periods after the second dose cycle compared to 13.6% of the participants who reported heavier menstrual periods after the first dose vaccination. This trend was also noted based on the outcome of logistics regression analysis for this study. The implication is that the extent of menstrual cycle changes depends on the population group being studied and their age profile. The study findings indicated that among the pre- and post-menopausal women who were not menstruating before vaccination, they reported menstrual cycle changes after receiving the SARS-CoV-2 vaccine. In addition, there was a significant increase in the proportion of post-menopausal women who reported experiencing menstrual symptoms after the second dose vaccination compared to the first dose vaccination. The results indicated that among women who do not menstruate, while 11.1% of post-menopausal women reported menstrual symptoms after the first dose cycle, 37.5% of them experienced menstrual bleeding after the second dose vaccination. These findings are fairly consistent with the outcome of the study by Lee et al. who found that, 33 66% of postmenopausal women had reported breakthrough bleeding after Covid-19 vaccination. Implication of the Findings Although not significant, especially after the first dose cycle, the findings on the link between Covid-19 vaccination and post-vaccine menstrual cycle changes have two major implications. First, the research outcome has considerable implication in enhancing the success of Covid-19 vaccination program, especially among the young reproductive-age women. 28 There are false claims that Covid-19 vaccines could adversely affect women’s fertility and therefore, their ability to conceive. The stated safety concerns related to Covid-19 vaccines increased substantially after reports that young women who had been vaccinated experienced abnormal menstrual cycles. 34 These concerns are likely to increase the level of vaccine hesitancy among young women who fear that taking the jab might adversely affect their ability to conceive. 35 Therefore, the findings from this research are expected to instill trust among young women that the Covid-19 vaccines are safe and do not interfere substantially with their fertility. Specifically, the partial findings in this study that Covid-19 vaccination is not significantly associated with menstrual cycle abnormalities such as late period and other menstrual bleeding is likely to create trust and confidence among the reproductive age women that the Covid-19 vaccines are safe. Second, the research findings on the link between Covid-19 vaccines and post-vaccine menstrual cycle changes are likely to enable young women to effectively plan for potentially altered menstrual cycles in the period after the first and the second dose cycles. The knowledge that Covid-19 vaccination alters the period length and cycle regularity can inform young women to effectively plan for their altered menstrual cycle. 28 This will enable women to avoid unplanned pregnancies that might occur due to changes in their menstrual cycles after vaccination. 28, 34 This is possible given that the young women might need to be careful during the few weeks after the first cycle dose and the second cycle dose. Therefore, the findings would be important in minimizing concerns among women that Covid-19 vaccination might place them at risk of experiencing unplanned pregnancies. Conclusion The findings partially support previous evidence that Covid-19 vaccination is associated with post-vaccine menstrual cycle abnormalities. This study showed that with the exception of late periods, other menstrual bleeding, severe menstrual symptoms, and other menstrual symptoms, the self-reported menstrual cycle disturbances (i.e., missed periods, spotting, change in period length, cycle regularity, and variation in period flow) were not significantly different after the first and the second dose cycle. However, changes in the menstrual cycle were less strong after the second dose compared to the variation after the first dose vaccination. The findings suggest that the menstrual cycle abnormalities that occurred after the Covid-19 vaccination are temporary (short-lived) given that the menstrual cycle reverts to the normal level after a period of time. The research findings have important implications in reducing vaccine hesitancy among young women and therefore, enhancing the success of Covid-19 vaccination program. The knowledge of the link between vaccination and post-vaccine menstrual cycle changes is also expected to help young women to plan for the altered menstrual cycles in order to avoid unintended pregnancies. Declarations Ethics approval and consent to participate: Participant informed consent to participate in this study was sought via an informed consent form that prefaced the survey. The informed consent form explained that the survey was anonymous, that participation was voluntary, and the purpose of the study. All ethical standards of voluntary participation and confidentiality were maintained. Participation in this study was voluntary and HCWs received no form of financial remuneration in order to reduce the risk of response bias. Data was collected in a manner that ensured patient anonymity i.e. no identifiers were recorded. Only de-identified data was recorded. This study was approved by the North Central Regional Health Authority Ethics Committee, Trinidad, and The Ministry of Health of Trinidad and Tobago Ethics Committee (3/13/441 Vol. II) and carried out in accordance with the ethics committees’ guidelines. Consent for publication: Not applicable Availability of data and materials: The data that supports the findings of this study is available from the corresponding author upon reasonable request. Competing interests: The authors declare that there is no conflict of interest regarding the publication of this article. Funding: The authors have not received any funding or benefits from industry or elsewhere to conduct or publish this study. Authors' contributions: CDG and BB were responsible for data analysis, with intellectual contributions from DV. CDG and BB drafted the article. All authors contributed to the conception and design of the paper, interpretation of data, and critical revisions contributing to the intellectual content and approval of the final version of the manuscript. Acknowledgements: Not applicable References 1. Boniface E, Benhar E, Matteson HL, Favaro C, Pearson JT, Darney BJ. COVID-19 vaccines linked to small increase in menstrual cycle length. Obstetrics & Gynecology. 2022; 1(1): 1-5. 2. Male V. Menstrual changes after Covid-19 vaccination. BMJ. 2021; 374. 3. Von Woon E, Male V. Effect of COVID-19 vaccination on menstrual periods in a prospectively recruited cohort. MedRxiv. 2022; 1-5. 4. Edelman A, Boniface ER, Benhar E, Leo H, Matteson KA, Favaro C, Pearson JT, Darney BJ. Association between menstrual cycle length and coronavirus disease 2019 (Covid-19) vaccination. Obstetrics & Gynecology. 2022; 1-5. 5. Li K, Chen G, Hou H. Analysis of sex hormones and menstruation in COVID-19 women of child-bearing age. Reproductive Biomedicine Online. 2021; 42 (1): 260-267. 6. Orvieto R, Noach-Hirsh M, Segev-Zahav A, Haas J, Nahum R, Aizer A. Does mRNA SARS-CoV-2 vaccine influence patients’ performance during IVF-ET cycle? Reproductive Biology and Endocrinology. 2021; 19 (1): 69-70. 7. Suzuki S, Hosono A. No association between HPV vaccine and reported post-vaccination symptoms in Japanese young women: Results of the Nagoya study. Papillomavirus Research. 2018; 5 (1): 96-103. 8. Wang Y-X, Arvizu M, Rich-Edwards JW, et al. Menstrual cycle regularity and length across the reproductive lifespan and risk of premature mortality: Prospective cohort study. BMJ. 2020; 371-372. 9. Norwegian Institute of Public Health. Menstrual changes following COVID-19 vaccination. 2022. https://www.fhi.no/en/news/2022/menstrual-changes-following-covid-19-vaccination/. 10. Kurdoğlu Z. Do the COVID-19 vaccines cause menstrual irregularities? International Journal of Women’s Health Reproductive Science. 2021; 9(3):158-159. 11. Muhaidat N, Alshrouf MA, Azzam MI, Karam AM, Al-Nazer MW, Al-Ani, A. Menstrual symptoms after COVID-19 vaccine: A cross-sectional investigation in the MENA region. International Journal of Women’s Health. 2022; 395-404. 12. Central Statistical Office, 2019. Provisional Mid Year Population Estimate by Age and Sex, 2005–2021. Available at: https://cso.gov.tt/subjects/population-and-vital-statistics/population/. Accessed January 16, 2021. 13. Ministry of Health, Trinidad and Tobago, 2020. Statement from the Honourable Terence Deyalsingh, Minister of Health at the Media Conference to Advise of the First Confirmed (Imported) Case of COVID-19 in Trinidad and Tobago. Available at: http://www.health.gov.tt/sitepages/default.aspx?id=293. Accessed January 16, 2021. 14. Government of the Republic of Trinidad and Tobago Ministry of Health. COVID-19 Novel Coronavirus. Available at: https://health.gov.tt/covid-19/covid-19-guidelines-and-regulations. Accessed January 16, 2021. 15. Gopaul CD, Ventour D, Thomas D. COVID-19 Vaccine Acceptance and Uptake Among Healthcare Workers in Trinidad & Tobago. MedRxiv. 2022. 16. Gopaul CD, Ventour D, Thomas D. ChAdOx1 nCoV-19 Vaccine Side Effects among Healthcare Workers in Trinidad and Tobago. Vaccines 2022;10,466. https://doi.org/10.3390/vaccines10030466. 17. Gopaul CD, Ventour D, Trotman M, Thomas D. The epidemiological characteristics of positive COVID-19 patients in Trinidad and Tobago. Journal of Public Health and Epidemiology. 2022 14(1), 29-34. 18. Gopaul C, Ventour D, Thomas D. Laboratory Predictors for COVID-19 ICU Admissions in Trinidad and Tobago. Research Square, 2020; [Preprint] Available from: https://doi.org/10.21203/rs.3.rs-103394/v1 . 19. Phelan N, Behan LA, Owens L. The impact of the COVID-19 pandemic on women’s reproductive health. Frontiers in Endocrinology. 2021; 191-195. 20. Lee KMN, Junkins EJ, Fatima UA, Cox ML, Clancy KBH. Characterizing menstrual bleeding changes occurring after SARS-CoV-2 vaccination. MedRxiv. 2021; 1-5. 21. Sharp GC, Fraser A, Sawyer G, Kountourides G, Easey KH, Ford G, Olszewska Z, Howe LD, Lawlor DA et al. The COVID-19 pandemic and the menstrual cycle: Research gaps and opportunities. International Journal of Epidemiology. 2022; 51(3): 691-700. 22. Aolymat IA. Cross-sectional study of the impact of COVID-19 on domestic violence, menstruation, genital tract health, and contraception use among women in Jordan. American Journal of Tropical Medicine & Hygiene. 2020; 519-525. 23. Demir O, Sal H, Comba C. Triangle of COVID, anxiety and menstrual cycle. Journal of Obstetrics and Gynaecology. 2021; 1257-1261. 24. Burki T. The indirect impact of COVID-19 on women. Lancet Infectious Diseases. 2020; 20(1): 904-905. 25. Azize DA, Evans E, Richard P. Possible effect of COVID-19 vaccines on menstruation in Cape Coast, Ghana, West Africa: Case series report. Open Journal of Obstetrics and Gynecology. 2021; 11(11): 1650-1656. 26. Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. New England Journal of Medicine. 2020; 383(27): 2603-2615. 27. Lee KM, Junkins EJ, Luo C, Fatima UA, Cox ML, Clancy KB. Investigating trends in those who experience menstrual bleeding changes after SARS-CoV-2 vaccination. MedRxiv. 2022; 10. 28. Male V. Menstruation and Covid-19 vaccination. BMJ. 2022; 376. 29. Sualeh M, Uddin MR, Junaid N, Khan M, Pario A. Impact of COVID-19 vaccination on the menstrual cycle: A cross-sectional study from Karachi, Pakistan. Research Square. 2022; 1-5. 30. Tragostad L. Increased occurrence of menstrual disturbances in 18- to 30-year-old women after covid-19 vaccination. SSRN. 2022; 1-5. 31. Khan SM, Shilen A, Heslin KM, et al. SARS-CoV-2 infection and subsequent changes in the menstrual cycle among participants in the Arizona CoVHORT study. American Journal of Obstetrics and Gynecology. 2021; (21)1: 1044-1049. 32. Safrai M, Rottenstreich A, Herzberg S, Imbar T, Reubinoff B, Ben-Meir A. Stopping the misinformation: BNT162b2 COVID-19 vaccine has no negative effect on women’s fertility. MedRxiv. 2021; 1-10. 33. Lee KMN, Junkins EJ, Luo C, Fatima UA, Cox ML, Clancy KBH. Investigating trends in those who experience menstrual bleeding changes after SARS-CoV-2 vaccination. Sciences Advances. 2022; 8(1): 1-15. 34. Davis HE, Assaf GS, McCorkell L et al. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. E-Clinical Medicine. 2021; 38. 35. World Health Organization. Information for the public: COVID-19 vaccines. 2022. https://www.who.int/westernpacific/emergencies/covid-19/information-vaccines . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2048853","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":136611913,"identity":"f333b392-da9b-4685-8121-8123d94a8cb5","order_by":0,"name":"Chavin Gopaul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYDACCSBOgHEeVAAJZuYGErQknAFpYSRCCxwktoFIAlr4Zzc/k3i4g8GuXxrISJxXG83fDtTyo2IbbkvuHDOTSDzDkDxzDoix7XjujMOMDYw9Z27j1GIgkWBsAHRPssGNBJCWY7kNQC3MjG34tKR/hmpJ/yaROOdY7nzCWnIMHwC12BncyAHa0lCTu4GQFokbOYVALRIJknPOFFskHDuQuxGo5SA+v/DPSN9w8GebjT2/dPvGGx9q6nLnnT988MGPCtxaYJYlNkAi6DCYPEBIPQjYQ+O0jhjFo2AUjIJRMMIAAEtmW934Go/EAAAAAElFTkSuQmCC","orcid":"","institution":"North Central Regional Health Authority","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Chavin","middleName":"","lastName":"Gopaul","suffix":""},{"id":136611914,"identity":"b6e0c2f0-f105-4679-b93a-6638df56538b","order_by":1,"name":"Bharat Bassaw","email":"","orcid":"","institution":"University of the West Indies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bharat","middleName":"","lastName":"Bassaw","suffix":""},{"id":136611915,"identity":"5d29fd53-6548-48f6-8f8b-977e7349c997","order_by":2,"name":"Dale Ventour","email":"","orcid":"","institution":"University of the West Indies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dale","middleName":"","lastName":"Ventour","suffix":""},{"id":136611916,"identity":"c137decb-601c-42d2-af94-b07673ae9551","order_by":3,"name":"Davlin Thomas","email":"","orcid":"","institution":"North Central Regional Health Authority","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Davlin","middleName":"","lastName":"Thomas","suffix":""}],"badges":[],"createdAt":"2022-09-09 11:59:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2048853/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2048853/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":26668331,"identity":"5bc66b1b-2ee3-4a5e-8a81-5b8de2faae72","added_by":"auto","created_at":"2022-09-19 20:11:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60215,"visible":true,"origin":"","legend":"\u003cp\u003eSTROBE Flow Diagram for Included and Excluded Participants\u003c/p\u003e","description":"","filename":"ScreenShot20220919at12.49.56PM.png","url":"https://assets-eu.researchsquare.com/files/rs-2048853/v1/203fa774d422ce0be3199836.png"},{"id":26669040,"identity":"f5365850-0dc1-4aa8-bf94-e12d6154bcff","added_by":"auto","created_at":"2022-09-19 20:16:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44577,"visible":true,"origin":"","legend":"\u003cp\u003eChange in Menstrual Period Length after First and Second Dose\u003c/p\u003e","description":"","filename":"ScreenShot20220919at12.50.12PM.png","url":"https://assets-eu.researchsquare.com/files/rs-2048853/v1/f307541bb80b6044cc94a436.png"},{"id":26668332,"identity":"c0ad7e3a-2a6c-45e6-9440-a427c18756a1","added_by":"auto","created_at":"2022-09-19 20:11:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":43550,"visible":true,"origin":"","legend":"\u003cp\u003eChange in Menstrual Period Flow after First and Second Dose\u003c/p\u003e","description":"","filename":"ScreenShot20220919at12.50.19PM.png","url":"https://assets-eu.researchsquare.com/files/rs-2048853/v1/4ee2bcefc9d7bb9458e6f118.png"},{"id":26669043,"identity":"e158067e-83b3-4d52-8fea-007213daad47","added_by":"auto","created_at":"2022-09-19 20:16:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":696165,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2048853/v1/0c059243-b4df-4378-8261-4561261938db.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffects of Covid-19 Vaccines on the Menstrual Cycle: A Cross-Sectional Study.\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCovid-19 vaccination is considered the best option for protection against the potentially adverse effects of the SARS-CoV2 infections.\u003csup\u003e1\u003c/sup\u003e Some of the common side-effects associated with Covid-19 vaccines as listed by the UK\u0026rsquo;s Medicines and Healthcare Products Regulatory Agency (MHRA) as well as the U.S. Vaccine Adverse Reporting System (VAERS) include a sore arm, fever, fatigue, myalgia, and headache.\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eHowever, in prior clinical studies, changes in menstrual cycles, period flow, menses length, vaginal bleeding were not identified and listed as common side-effects following Covid-19 vaccination.\u003csup\u003e3\u003c/sup\u003e By May 2021, fewer than 200 young vaccinated women had self-reported a menstrual-related disturbance following vaccination to VAERS.\u003csup\u003e4\u0026nbsp;\u003c/sup\u003eHowever, by September 2021, more women (at least 30,000 reports) had complained of the adverse side-effects related to menstrual cycle abnormalities following vaccination to the UK\u0026rsquo;s MHRA yellow card surveillance scheme.\u003csup\u003e\u0026nbsp;2\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThere were concerns that a possible link between Covid-19 vaccination and menstrual cycle disturbances might lead to vaccine hesitancy, especially among young women.\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eTherefore, clinical studies were needed to evaluate the extent of this relationship in order to assure the public and maintain trust that the vaccines do interfere substantially with fertility.\u003csup\u003e6\u0026nbsp;\u003c/sup\u003eMenstrual cyclicity is an obvious sign of health and fertility in young women and its variation from month to month across a person\u0026rsquo;s lifespan is considered normal.\u003csup\u003e7\u0026nbsp;\u003c/sup\u003eSpecifically, changes in menstrual cycle length, which can be between 24-38 days is considered normal if it falls within 8 days.\u003csup\u003e3\u003c/sup\u003e The normal variation in menstrual cycle can be a concern for young women, especially if it is associated with Covid-19 vaccination exposure.\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe U.S. National Institute of Health (NIH) had allocated $1.67 million to fund clinical research on the possible association between Covid-19 vaccination and menstrual cycle abnormalities.\u003csup\u003e2\u003c/sup\u003e The findings based on the most recent clinical studies indicate that there is significant evidence that women tend to experience menstrual cycle disturbances following Covid-19 vaccination.\u003csup\u003e\u0026nbsp;3, 4, 6, 8\u0026nbsp;\u003c/sup\u003eA study by the Norwegian Institute of Public Health\u003csup\u003e9\u003c/sup\u003e reported that 13.6% of young women, 18-30 years had experienced heavier periods after the first dose while 15.3% of them experienced heavier menstrual periods after the second dose. A research commissioned by the U.S. National Institute of Health (NIH) further reported\u003csup\u003e4\u003c/sup\u003e that Covid-19 vaccination was associated with less than a day (i.e., 0.71 day) increase in menstrual cycle length for both vaccine-dose cycles compared to the pre-vaccine menstrual cycle. Similarly, using a cohort of 79 spontaneously cycling young women, the study by Woon and Male\u003csup\u003e3\u0026nbsp;\u003c/sup\u003efound that Covid-19 doses were associated with delay in menstrual cycle (2.3 days after the first dose and 1.3 days after the second dose). However, most of these studies found that menstrual changes tend to reverse in subsequent cycles. \u003csup\u003e4, 6, 8, 10, 11\u0026nbsp;\u003c/sup\u003eA study by Muhaidat also found that 66.3% of the participants experienced menstrual symptoms in the period following vaccination.\u003csup\u003e\u0026nbsp;11\u0026nbsp;\u003c/sup\u003eThe insight based on clinical studies indicate that the association between Covid-19 vaccination and menstrual cycle changes is linked to the immune activation in response to stimuli.\u003csup\u003e\u0026nbsp;2\u0026nbsp;\u003c/sup\u003eBiologically, it has been noted that the Covid-19 vaccines similar to the human papillomavirus (HPV) vaccines tend to create immune stimulation on the hormones that control the menstrual cycle.\u003csup\u003e\u0026nbsp;7\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe twin island Republic of Trinidad and Tobago has an estimated population of 1.4 million\u003csup\u003e\u0026nbsp;12\u003c/sup\u003e. The country reported its first case of SARS-CoV-2 on March 12, 2020\u003csup\u003e13\u003c/sup\u003e. Since then, public health measures such as border closures, social distancing, and mask-wearing have been implemented to limit the spread of the virus\u003csup\u003e14\u003c/sup\u003e. On February 17th, 2021, Trinidad and Tobago joined the global effort to control the pandemic through vaccination when the Ministry of Health embarked upon the Phase 1 rollout of its National COVID-19 Vaccination Program, with healthcare workers being among the first groups to receive the first doses of the vaccine, along with persons aged 60 years and over and persons with non-communicable diseases. By April 2021, subsequent phases (2 and 3) of the campaign offered frontline essential workers and the eligible public the opportunity to be inoculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA study investigating the acceptance of the vaccine among healthcare workers in Trinidad and Tobago found that age, profession and trust in international public health organizations and other healthcare professionals predict their vaccine uptake\u003csup\u003e15\u003c/sup\u003e. Researchers in Trinidad and Tobago also reported on the safety of the COVID-19 vaccine by examining the side-effects of the ChAdOx1 nCov-19 (Oxford, AstraZeneca COVID-19 vaccine) among healthcare workers\u003csup\u003e16\u003c/sup\u003e. The study demonstrated that the rate of occurrence of most local and systemic side-effects was less than 50%, corroborating the manufacturer\u0026rsquo;s claim that the vaccine is safe, with implications to reduce vaccine hesitancy through public health efforts\u003csup\u003e\u0026nbsp;16\u003c/sup\u003e. Other studies in Trinidad and Tobago have been limited to investigating COVID-19 patients\u0026rsquo; epidemiological characteristics\u003csup\u003e17\u003c/sup\u003e as well as laboratory predictors of COVID-19 admissions to ICU\u003csup\u003e\u0026nbsp;18\u003c/sup\u003e. The most frequent comorbidities were found to be hypertension and diabetes mellitus, while the most prevalent symptoms were non-productive coughs and fevers\u003csup\u003e17\u003c/sup\u003e. \u0026nbsp;As for laboratory factors, neutrophils, aspartate transaminase (AST), lactate dehydrogenase (LDH) and C-reactive protein (CRP) were suitable predictors of COVID-19 patients in need of ICU care\u003csup\u003e\u0026nbsp;18\u003c/sup\u003e. Both studies allude to the unique characteristics of COVID-19 patients in Trinidad and Tobago and the greater need for research especially in this region.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The present study aimed to investigate the association between Covid-19 vaccination and changes in menstrual cycle among young women employed at the North Central Regional Health Authority of Trinidad and Tobago who had been vaccinated between 1\u003csup\u003est\u003c/sup\u003e June 2020 and 18\u003csup\u003eth\u003c/sup\u003e March 2022. The study examined whether both the first and second vaccine-dose cycles had a significant effect on variation in the participants\u0026rsquo; menstrual cycle. A cross-sectional study design was undertaken using online self-administered surveys, which were employed to collect sociodemographic and menstrual cycle data from the women. The survey was administered from December 2021 to March 2021. The eligible participants consisted of 657 \u0026nbsp;adult healthcare workers who currently menstruate or who have had menstrual cycles in the past and who received at least one dose of the COVID-19 vaccine.. However, of those only 317 women met the inclusion criteria for this study indicated in Figure 1. The data was analyzed using both descriptive and inferential statistical analysis in order to examine the link between Covid-19 vaccination and variation in menstrual cycle. Inferential statistical analysis included logistic regression, correlation analysis, and Chi-square tests of association. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003e\u003cstrong\u003eResearch Design\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe study employed a cross-sectional research design approach to investigate the effect of Covid-19 vaccines on the menstrual cycle of healthcare workers (HCWs) employed at the North Central Regional Health Authority (NCRHA) of Trinidad and Tobago. The NCRHA was selected as the setting for HCWs as it was the first RHA to distribute COVID-19 vaccines to HCWs at the outset of the country\u0026rsquo;s national vaccination program. Data capture was conducted via the electronic distribution of a self-administered questionnaire to NCRHA HCWs. \u0026nbsp;The survey remained open for responses from December 18\u003csup\u003eth\u003c/sup\u003e 2021 to March 18\u003csup\u003eth\u003c/sup\u003e\u0026nbsp; 2022 . Using the stated research design approach, participants who included vaccinated women were required to indicate their sociodemographic information and their corresponding menstrual cycle details before and after vaccination. The anonymous responses were automatically collated via the online platform to which only the principal investigator had access. The collated responses were downloaded as a Microsoft Excel file by the principal investigator, and subsequently coded into an SPSS database and analyzed using IBM SPSS V.21 software.\u003c/p\u003e\n\u003cp\u003eThe study protocol was reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;\u003cstrong\u003eParticipants\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA judgment sampling method was used to obtain the sample of HCWs for this study. The electronic questionnaire was distributed via email to all female NCRHA HCWs. Of the 4,205 NCRHA HCWs to whom the questionnaire was sent, 657 HCWs returned a completed questionnaire during the study period. \u0026nbsp;This cohort of 657 Covid-19 vaccinated women included those who were over 18 years (\u003cem\u003eMean age\u003c/em\u003e = 36.42 years). Their mean body mass index (BMI) before vaccination was 29.24 (29.24\u0026nbsp;8.38 kg/m\u003csup\u003e2\u003c/sup\u003e). The participants consisted of both pre- and post-menopausal women who had either experienced or not experienced a menstrual period in the last 12 months and who had received either the first or second dose vaccine between 1\u003csup\u003est\u003c/sup\u003e June 2020 and \u0026nbsp;18\u003csup\u003eth\u003c/sup\u003e March 2022. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Instrument\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eSociodemographic and menstrual cycle data before and after vaccination was collected using a self-administered survey/questionnaire. This data collection instrument was distributed and administered to the email addresses of the female NCRHA HCWs\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe instrument was modeled on relevant questions selected from a digital survey investigating the impact of COVID-19 on women\u0026rsquo;s reproductive health in Ireland and the United Kingdom\u003csup\u003e19\u003c/sup\u003e and a digital survey investigating the changes in menstruation as a possible side-effect of COVID-19 vaccines\u003csup\u003e20\u003c/sup\u003e. The online questionnaire consisted of \u0026nbsp;57 detailed self-report questions that covered two main domains. The first section sought to collect participants\u0026rsquo; sociodemographic details, including age, ethnicity, BMI, pregnancy status, breastfeeding status, the date of first vaccination, pre-existing medical diagnosis, and method of contraception. The second section contained questions on the participants\u0026rsquo; menstrual cycle regularity, period flow, menstrual period length, and other abnormalities, which were experienced pre- and post-vaccination. The electronic self-administered questionnaire was prefaced with an informed consent form which explained that the survey was anonymous, that participation was voluntary, and explained the purpose of the study. All ethical standards of voluntary participation and confidentiality were maintained.\u0026nbsp;Participation in this study was voluntary and HCWs received no form of financial remuneration in order to reduce the risk of response bias. \u0026nbsp;Due to the anonymous nature of the questionnaire, confirmation of participants\u0026rsquo; vaccination could not be verified.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main outcome measures of this study included the association between the COVID-19 vaccine and participants\u0026rsquo; reported menstrual cycle disturbances. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was granted ethical approval by The North Central Regional Health Authority Ethics Committee, Trinidad, and The Ministry of Health of Trinidad and Tobago Ethics Committee (3/13/441 Vol. II).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe data was analyzed in SPSS v.26 statistical program. To examine the association between Covid-19 vaccination and menstrual cycle changes, both descriptive and inferential statistical analysis was performed. The participants\u0026rsquo; sociodemographic details were analyzed using descriptive statistical analysis and presented as frequencies and percentage frequencies. The association between Covid-19 vaccination and menstrual cycle disturbances were analyzed using correlation analysis. Finally, logistic regression and the non-parametric Chi-square test were performed to examine the effect of Covid-19 vaccine-dose on menstrual cycle changes after accounting for participants\u0026rsquo; age, ethnicity, and BMI. A parametric paired \u003cem\u003et\u003c/em\u003e-test was used to compare the mean change in menstrual cycle regularity, menstrual cycle length, and period flow between baseline (pre-vaccination) and after vaccination. A statistical significance level of 0.05 was used to conduct the inferential analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eSociodemographic Data\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eSix hundred and fifty-seven pre- and post-menopausal women participated in the survey . However, three hundred and forty four met the inclusion criteria for this study (see Figure 1). Participants diagnosed with polycystic syndrome (\u003cem\u003en\u003c/em\u003e = 166), uterine fibroids (\u003cem\u003en\u003c/em\u003e = 114), had abnormal uterine bleeding (\u003cem\u003en\u003c/em\u003e = 69), or \u0026nbsp;were pregnant during the period of study (\u003cem\u003en\u003c/em\u003e = 68), endometriosis (\u003cem\u003en\u003c/em\u003e = 37) and those breastfeeding (\u003cem\u003en\u003c/em\u003e = 31) were excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe participants\u0026rsquo; sociodemographic data (see Table 1) indicated that the mean BMI was 29.24\u0026nbsp;8.38 kg/m\u003csup\u003e2\u003c/sup\u003e. Most women who participated in the study were between 25-34 years (\u003cem\u003en\u003c/em\u003e = 135; 42.6%) and 35-44 years (\u003cem\u003en\u003c/em\u003e = 112; 35.3%). The majority of the women were of the reproductive age group. Approximately forty-four percent of the participants were Africans (\u003cem\u003en\u003c/em\u003e = 138; 43.5%).\u003c/p\u003e\n\u003cp\u003eIn terms of the first dose of Covid-19 vaccine, the majority (\u003cem\u003en\u003c/em\u003e = 157; 49.5%) had received the Oxford AstraZeneca vaccine while for the second dose of Covid-19 vaccine, the majority (\u003cem\u003en\u003c/em\u003e = 153; 48.3%) of the women had been injected with Oxford AstraZeneca vaccine and 30.6% of them had received Sinopharm vaccine. The descriptive statistics also indicated that only 16.1% of the participants had reported a positive Covid-19 diagnosis prior to the study, which was conducted between April and June 2022.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe majority (\u003cem\u003en\u003c/em\u003e = 280; 88.3%) of the women who participated in the study reported a regular menstrual cycle. In terms of the menstrual period length, most (\u003cem\u003en\u003c/em\u003e = 138; 43.5%) of the women reported an average of 3 to 5 days. The majority (\u003cem\u003en\u003c/em\u003e = 230; 72.6%) had a moderate period flow while only 12.6% of the women reported a heavy period flow.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Sociodemographic Data\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eBody Mass Index (BMI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e28.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eMenstrual cycle length\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003eFrequency (\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003ePercentage Frequency (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (Years)\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e18-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e45-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e55-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eAfrican\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eEast Indian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eHispanic, Mixed Races and Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Dose Covid-19 Vaccine:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eJohnson \u0026amp; Johnson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eOxford AstraZeneca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e49.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003ePfizer-BioNTech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eSinopharm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Dose Covid-19 Vaccine:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eJohnson \u0026amp; Johnson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eOxford AstraZeneca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e48.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003ePfizer-BioNTech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eSinopharm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e30.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCovid-19 Diagnosis:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e75.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eI think so\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eUnsure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eOther diseases/infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual Cycle Regularity:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eRarely menstruate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eIrregular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eRegular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e88.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual Period Length:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eRarely menstruate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e1-3 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e3-5 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e5-7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u0026gt; 7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual Period Flow:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eRarely menstruate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e72.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.401869158878505%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.037383177570092%\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003e\u003cstrong\u003eMenstrual Cycle Disturbances after Covid-19 Vaccination\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe non-parametric chi-square inferential test was used to compare the extent of menstrual cycle disturbances after the first dose and the second dose cycle. Table 2 shows that there was no statistically significant change in menstrual cycle regularity after the first dose vaccination compared to the second dose vaccination (\u0026rho; \u0026gt; 0.05). The chi-square test indicated that exposure to Covid-19 vaccination resulted in a significant change in the women\u0026rsquo;s menstrual period flow (\u0026rho; \u0026lt; 0.001). Exposure to the Covid-19 vaccination also did not have a significant effect on the women\u0026rsquo;s menstrual cycle length (\u0026rho; \u0026gt; 0.05). The participants\u0026rsquo; menstrual period length was not significantly longer after the first dose compared to the second dose vaccination (\u0026rho; \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eThe inferential analysis findings based on the Chi-square test also indicated that women experienced other forms of menstrual cycle abnormalities after exposure to the first and the second dose Covid-19 vaccines. The women experienced incidences of late menstrual periods (\u0026rho; \u0026lt; 0.001), other menstrual bleeding (\u0026rho; \u0026lt; 0.001), severe menstrual symptoms (\u0026rho; \u0026lt; 0.001), and other menstrual symptoms (\u0026rho; \u0026lt; 0.001). In this case, \u0026lsquo;other menstrual bleeding\u0026rsquo; refers to other forms of menstrual bleeding or abnormalities besides those specified in the analysis. However, in the majority of the cases, the variation was not statistically significant. For instance, missed periods (\u0026rho; \u0026gt; 0.05) and spotting/vaginal bleeding (\u0026rho; \u0026gt; 0.05) were found to be statistically insignificant. Finally, the findings based on the inferential chi-square test indicated that there was a significant change in the number of days before menstrual symptoms started after the first and the second dose Covid-19 vaccination (\u0026rho; \u0026lt; 0.001). For those who reported the menstrual symptoms, the majority stated that they tend to occur 14 days after the receiving the first or the second dose of Covid-19 vaccine (\u0026rho; \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Menstrual Cycle Disturbances after Covid-19 Vaccination using Chi-Square Tests n (%)\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"636\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003eFirst (1\u003csup\u003est\u0026nbsp;\u003c/sup\u003e) Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003eSecond (2\u003csup\u003end\u003c/sup\u003e) Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in Cycle Regularity\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e165.82 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e244 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e224 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e100 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e95 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in Period Flow\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e387.64***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eAbout the same\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e216 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e195 (56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eHeavier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e66 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e71 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eLighter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e23 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e22 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e39 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e32 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in Period Length\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e402.77 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eAbout the same\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e238 (69.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e225 (65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eLonger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e40 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e39 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eShorter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e26 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e21 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e40 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e34 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate Period\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e156.24***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e271 (78.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e261 (75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e73 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e58 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissed Period\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e66.13***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e323 (94.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e299 (86.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e21 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e20 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpotting/Vaginal Bleeding\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e158.02***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e310 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e287 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e34 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e32 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Menstrual Bleeding\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e59.65***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e322 (93.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e303 (87.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e22 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e16 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere Menstrual Symptoms\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e200.79***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e284 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e272 (78.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e60 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e47 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther Menstrual Symptoms\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e96.95***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e308 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e289 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e36 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e30 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Menstrual Symptoms\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e159.08***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e168 (48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e152 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e176 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e167 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Days before Symptoms Started\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e278.25***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e1-3 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e16 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e13 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e4-7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e10 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e8 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e8-14 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e14 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e19 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003e\u0026gt; 14 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e58 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e61 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eMenstruating when received vaccine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e20 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e226 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e218 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eBlank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"44.339622641509436%\"\u003e\n \u003cp\u003eDid not receive dose 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.9811320754717%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.81132075471698%\"\u003e\n \u003cp\u003e25 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.867924528301888%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: \u0026rho;-value was calculated using the non-parametric chi-square test and indicates association in menstrual cycle symptoms after the first dose and the second dose cycle. \u0026rho;*** (Significance at \u0026alpha; = 0.001).\u003c/p\u003e\n\u003cp\u003eTable 3 presents a summary of the chi-square test to assess the difference in menstrual cycle length and period flow before and after the first dose Covid-19 vaccination. The results indicated that there was a significant variation in the women\u0026rsquo;s menstrual period length before and after the first dose vaccination (\u0026rho; \u0026lt; 0.001) (see Figure 2). Similarly, the chi-square test findings presented in Table 3 indicated that exposure to the first dose Covid-19 vaccination resulted in a significant variation in menstrual period flow compared to the situation before vaccination (\u0026rho; \u0026lt; 0.001) (see Figure 3). The (\u003cem\u003en\u003c/em\u003e = 344) represents the women who received first dose vaccination while the (\u003cem\u003en\u003c/em\u003e = 319) captures the women who received the second dose vaccination.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003ePeriod Length and Flow after First and Second Dose and for Unvaccinated Individuals\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.17391304347826%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"5.217391304347826%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.608695652173914%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePeriod Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.565217391304348%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePeriod Flow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.434782608695652%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.17391304347826%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"5.217391304347826%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.608695652173914%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in Length (\u003c/strong\u003eꭓ\u003csup\u003e2\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.565217391304348%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026rho;-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in Flow (ꭓ\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.434782608695652%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026rho;-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.17391304347826%\"\u003e\n \u003cp\u003eFirst dose v. before vaccination :\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"5.217391304347826%\"\u003e\n \u003cp\u003e344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.608695652173914%\"\u003e\n \u003cp\u003e121.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.565217391304348%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e119.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.434782608695652%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.17391304347826%\"\u003e\n \u003cp\u003eSecond dose v. before vaccination:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"5.217391304347826%\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.608695652173914%\"\u003e\n \u003cp\u003e402.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.565217391304348%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e387.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.434782608695652%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: \u0026rho;-value was calculated using chi-square test and indicates association in menstrual cycle symptoms post-vaccination (after the first and second dose) and before vaccination. Table 3 shows that there were 344 women who participated in the first dose vaccination (\u003cem\u003en\u003c/em\u003e = 344) compared to 319 who received the second dose (\u003cem\u003en\u003c/em\u003e = 319).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a statistically significant association between the respondents who reported \u0026lsquo;no\u0026rsquo; to experiencing late period and those who reported \u0026lsquo;yes\u0026rsquo; to experiencing late period (\u0026rho; \u0026lt; 0.001). Similarly, Table 4 shows that there was a significant difference in the number of respondents who reported \u0026lsquo;no\u0026rsquo; to experiencing missed periods and those who reported \u0026lsquo;yes\u0026rsquo; to the stated menstrual cycle abnormality (\u0026rho; \u0026lt; 0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eLate Period and Missed Period after the First and Second Dose Cycles\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Dose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Dose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChi-square (\u003c/strong\u003eꭓ\u003csup\u003e2\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026rho;-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003en\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChi-square (ꭓ\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026rho;-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003eLate period:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e271 (79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e261 (82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e73 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e317.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e58 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e292.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003eMissed Period:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e323 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e299 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.822429906542055%\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e19 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e317.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.149532710280374%\"\u003e\n \u003cp\u003e20 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e292.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: \u0026rho;-value was calculated using chi-square test and indicates association in menstrual cycle abnormalities (late menstrual period and missed menstrual period) after the first and second dose vaccination.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results of the non-parametric chi-square test (see Table 5) indicate that there was a significant association in menstrual symptoms between pre- and post-vaccination period. The frequency of menstrual cycle regularity had changed significantly post-vaccination compared to the cycle regularity before Covid-19 vaccination (\u0026rho; \u0026lt; 0.001). The frequency of the period length and period flow as reported by respondents had significantly decreased after the first and second cycle dose vaccination compared to the menstrual period length and period flow before the Covid-19 vaccination (\u0026rho; \u0026lt; 0.001). For instance, moderate period flow decreased after the first dose vaccination (65.5%) and the second dose vaccination (61.4%) compared to 72.6% of respondents who had reported moderate period flow prior to the Covid-19 vaccination. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eChi-squared test: Menstrual Symptoms Post-Vaccination and Pre-Vaccination \u003cem\u003en\u0026nbsp;\u003c/em\u003e(%)\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePost Vaccination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePre-Vaccination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eChi-square (ꭓ\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Dose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Dose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eRegular menstruation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e199 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e189 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e280 (88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e156.14***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003ePeriod length\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e266 (84.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e248 (78.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e297 (93.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e118.23***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eModerate period flow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e208 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e195 (61.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e230 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e96.55***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eLight period flow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.384615384615385%\"\u003e\n \u003cp\u003e25 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.346153846153847%\"\u003e\n \u003cp\u003e24 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.115384615384617%\"\u003e\n \u003cp\u003e28 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.153846153846153%\"\u003e\n \u003cp\u003e205.13***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: \u0026rho;-value was calculated using the non-parametric chi-squared test and indicates variation in menstrual cycle symptoms post-vaccination (after the first and second dose) and menstrual cycle symptoms before Covid-19 vaccination.\u0026nbsp;\u0026rho;*** (Significance at \u0026alpha; = 0.001).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eTrends in Women who Experienced Menstrual Changes after Covid-19 Vaccination\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThere are two categories of women who do not menstruate. The first is those that have not yet reached menopause (pre-menopausal) but do not menstruate. The second is those that have reached menopause and were not menstruating prior to receiving Covid-19 vaccines. As shown in Table 6, some of the women in the two categories that were not menstruating previously experienced menstrual cycle after receiving Covid-19 vaccine.\u003c/p\u003e\n\u003cp\u003eA summary of the Chi-squared test in pre- and post-menopausal women who experienced menstrual cycle changes following Covid-19 vaccination is presented in Table 6. The findings show that after the first dose SARS-CoV-2 vaccination, 22 pre- and post-menopausal women (3.3%) reported menstrual cycle abnormalities. However, after the second dose cycle, 28 pre- and post-menopausal women (4.3%) experienced menstrual cycle changes. The increase in the number of women that were not menstruating but reported menstrual cycle abnormalities after the second dose cycle was statistically significant (\u0026rho; \u0026lt; 0.001). The results also reveal that among the post-menopausal women (55-64 years and those above 65 years), 37.5% of them reported menstrual cycle abnormalities after the second dose vaccination compared to only 11.1% of the stated group of women that reported menstrual bleeding after the first dose cycle. The change in the proportion of post-menopausal women who reported menstrual cycle changes after the first and the second dose cycle was statistically significant (\u0026rho; \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e Chi-square test: Trends in Menstrual Cycle Changes after Vaccination n (%)\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"58.87850467289719%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.214953271028037%\"\u003e\n \u003cp\u003eFirst (1\u003csup\u003est\u0026nbsp;\u003c/sup\u003e) Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.018691588785046%\"\u003e\n \u003cp\u003eSecond (2\u003csup\u003end\u003c/sup\u003e) Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.88785046728972%\"\u003e\n \u003cp\u003eChi-square (ꭓ\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"58.87850467289719%\"\u003e\n \u003cp\u003eDo not menstruate but had menstrual changes after vaccination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.214953271028037%\"\u003e\n \u003cp\u003e22 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.018691588785046%\"\u003e\n \u003cp\u003e28 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.88785046728972%\"\u003e\n \u003cp\u003e\u003cstrong\u003e299.01***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"58.87850467289719%\"\u003e\n \u003cp\u003ePost-menopausal women who reported menstrual symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.214953271028037%\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.018691588785046%\"\u003e\n \u003cp\u003e3 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.88785046728972%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46.43***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: \u0026rho;-value was calculated using chi-squared test and indicates menstrual cycle changes after the first and second dose Covid-19 vaccination. \u0026nbsp;\u0026rho;*** (Significance at \u0026alpha; = 0.001).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eLogistic Regression Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eLogistic regression analysis was conducted to examine the effect of Covid-19 vaccination on the women\u0026rsquo;s menstrual cycle controlling for the participants\u0026rsquo; age, BMI, and ethnicity (see Table 7). The results indicated that after the first dose cycle, none of the variables had a significant effect on likelihood of causing missed period, late period, spotting, and no menstrual cycle symptoms. However, the women\u0026rsquo;s BMI had a greater odds of contributing to cases of missed period (OR = 1.15; \u003cem\u003e\u0026rho;\u003c/em\u003e \u0026lt; 0.05) and spotting (OR = 1.55; \u003cem\u003e\u0026rho;\u003c/em\u003e \u0026lt; 0.05). In addition, the women\u0026rsquo;s ethnic orientation (OR = 1.87; \u003cem\u003e\u0026rho;\u003c/em\u003e \u0026lt; 0.05) had a greater likelihood of contributing to \u0026lsquo;no menstrual symptoms\u0026rsquo; at 5% significance level. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe logistic regression analysis findings indicated that after controlling for the participants\u0026rsquo; age, BMI and ethnicity, exposure to the second dose had a significant influence in raising the likelihood (odds) of menstrual cycle abnormalities among the women that participated in the study. Specifically, exposure to the second dose vaccine increased the likelihood of women reporting late period (OR = 2.16; \u0026rho; \u0026lt; 0.001), missed period (OR = 2.03; \u0026rho; \u0026lt; 0.001), spotting/vaginal bleeding (OR = 2.27; \u0026rho; \u0026lt; 0.001) and no menstrual symptoms (OR = 1.23; \u0026rho; \u0026lt; 0.001). The implication is that on average, women that had received the second dose Covid-19 vaccine were more likely to report incidences of menstrual cycle abnormalities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e Logistic Regression: Effect of First and Second Dose Vaccine on Menstrual Cycle\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"672\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate Period\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissed Period\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpotting\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Menstrual Symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Dose\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eFirst dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003cp\u003e(0.56 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003cp\u003e(0.45 1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003cp\u003e(0.31 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e(0.63 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e(0.77 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003cp\u003e(0.23 0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e2.03**\u003c/p\u003e\n \u003cp\u003e(1.33 2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003cp\u003e(0.23 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003cp\u003e(0.67 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e1.15***\u003c/p\u003e\n \u003cp\u003e(0.78 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e1.55***\u003c/p\u003e\n \u003cp\u003e(0.93 2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003cp\u003e(0.54 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003cp\u003e(0.81 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003cp\u003e(0.97 1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e0.78*\u003c/p\u003e\n \u003cp\u003e(0.42 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e1.87***\u003c/p\u003e\n \u003cp\u003e(1.11 2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate Period\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissed Period\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpotting\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Menstrual Symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(OR 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Dose\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eSecond dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e2.16***\u003c/p\u003e\n \u003cp\u003e(1.43 3.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e2.03***\u003c/p\u003e\n \u003cp\u003e(1.29 3.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e2.27***\u003c/p\u003e\n \u003cp\u003e(1.47 3.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e1.23***\u003c/p\u003e\n \u003cp\u003e(0.67 1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003cp\u003e(0.22 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003cp\u003e(0.33 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e0.75*\u003c/p\u003e\n \u003cp\u003e(0.47 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003cp\u003e(0.41 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003cp\u003e(0.55 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003cp\u003e(0.38 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e1.68**\u003c/p\u003e\n \u003cp\u003e(0.88 2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e(0.53 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.535714285714285%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003cp\u003e(0.58 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.642857142857142%\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003cp\u003e(0.92 2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.75%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003cp\u003e(0.31 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.428571428571427%\"\u003e\n \u003cp\u003e2.08**\u003c/p\u003e\n \u003cp\u003e(1.312.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: \u0026rho;*** (Significance at \u0026alpha; = 0.001); \u0026rho;** (Significance at \u0026alpha; = 0.05); \u0026rho;* (Significance at \u0026alpha; = 0.10).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCorrelation Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePearson correlation analysis was undertaken to examine the relationship between Covid-19 vaccination and changes to women\u0026rsquo;s menstrual cycle. The pearson correlation analysis findings for the first dose cycle (see Table 8) indicate that the first dose vaccination was not significantly associated with any of the participants\u0026rsquo; sociodemographic factors such as age, BMI, and ethnicity. The implication is that none of the first dose Covid-19 vaccine types that were given to the women were significantly associated with their sociodemographic profiles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe pearson correlation analysis findings for the second dose vaccination (see Table 9) indicate that there was a significant negative association between the second dose cycle and the ethnic orientation of women (\u003cem\u003er\u003c/em\u003e = -0.133; \u0026rho; \u0026lt; .1). However, the significant relationship between the second dose cycle and ethnicity was only significant at 10% significance level. The other sociodemographic factors (i.e., age and BMI) were not significantly related with exposure to the second dose vaccination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u003c/strong\u003e Summary of the Pearson Correlation Analysis Results: First Dose\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of Vaccine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.429906542056074%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003eType of Vaccine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.429906542056074%\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.429906542056074%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.429906542056074%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.757009345794394%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: \u0026rho;** (Significance at \u0026alpha; = 0.001); \u0026rho;* (Significance at \u0026alpha; = 0.05)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9\u003c/strong\u003e Summary of the Pearson Correlation Analysis Results: Second Dose\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Dose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003eSecond Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e-0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.133*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e-0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e-0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.133*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.626168224299064%\"\u003e\n \u003cp\u003e-0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.560747663551403%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.69158878504673%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.49532710280374%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: \u0026rho;** (Significance at \u0026alpha; = 0.001); \u0026rho;* (Significance at \u0026alpha; = 0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eDiscussion of Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results based on the descriptive statistics, inferential chi-square test, and logistic regression found that exposure to Covid-19 vaccination had a significant effect in changing the women\u0026rsquo;s menstrual cycle although for certain menstrual cycle abnormalities, the effect was not significant. The non-parametric chi-square test findings confirmed that with the exception of late periods, other menstrual bleeding, severe menstrual symptoms, and other menstrual symptoms, participants did not report significant changes to their menstrual cycle. There was evidence that the majority \u0026nbsp;did not experience menstrual cycle disturbances in the form of changes to their cycle regularity, period flow, and period length. In addition, vaccinated women did not experience other menstrual cycle abnormalities, including missed periods, spotting, and no menstruation in the subsequent period after the first and the second dose vaccination. These findings are fairly inconsistent with the outcome of previous studies which noted that exposure to Covid-19 vaccines was associated with delay in menstrual periods\u003csup\u003e20\u003c/sup\u003e, changes in cycle length\u003csup\u003e21\u0026nbsp;\u003c/sup\u003e, late periods\u003csup\u003e22\u0026nbsp;\u003c/sup\u003e, and substantial changes in the menstrual period flow.\u003csup\u003e23, 24, 25 \u0026nbsp;\u003c/sup\u003eThere are biologically plausible mechanisms that explain the onset of menstrual cycle abnormalities after exposure to the Covid-19 vaccines.\u003csup\u003e\u0026nbsp;26, 27\u0026nbsp;\u003c/sup\u003e According to Male\u003csup\u003e28\u0026nbsp;\u003c/sup\u003e, immunological stimulation of the hormones that control menstrual cycle by Covid-19 vaccines plays an important role in influencing changes to the women\u0026rsquo;s menstrual cycle after the first and the second dose cycle.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn contrast to the findings from previous studies, this research noted that there was no significant variation in the women\u0026rsquo;s menstrual period length after the first and the second dose cycle vaccination. There was no significant variation in the women who reported to have longer menstrual period length after the first and the second dose cycle compared to the menstrual period length before vaccination. The stated outcome contrasts the insight based on the prior research findings by Edelman et al. who noted that\u003csup\u003e4\u0026nbsp;\u003c/sup\u003eexposure to Covid-19 vaccines was associated with less than 1-day change in the menstrual cycle length. Specifically, Edelman et al. found that pre-menopausal women, 18-45 years who received Covid-19 vaccination experienced a 0.71 day-increase and 0.91 day-increase in period length after the first and the second dose cycle vaccination respectively. The variation could be explained by differences in the sampling and metholodical approach.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study found that the most common form of menstrual cycle abnormalities following Covid-19 vaccination were late period, heavy period, severe menstrual bleeding, and other forms of menstrual symptoms. The significant evidence on late period abnormalities is consistent with the prior findings by Woon and Male\u003csup\u003e3\u003c/sup\u003e, who noted that Covid-19 vaccines were associated with a 2.3-day and a 1.3-day delay after exposure to the first and the second-dose vaccine cycle respectively. The implication is that receiving Covid-19 vaccination is associated with a significant delay in menstrual period. Similarly, the evidence that women experienced heavier period flow after vaccination is consistent with the outcome based on the previous study by the Norwegian Institute of Public Health\u003csup\u003e9\u003c/sup\u003e, who noted that 13.6% and 15.3% of young women, 18-30 years experienced heavier menstrual period flow after the first and the second dose cycle respectively. There was no evidence to confirm that the other common menstrual abnormalities such as cycle irregularity and missed period were significant following Covid-19 vaccination.\u003c/p\u003e\n\u003cp\u003eConsistent with the previous research findings, the results of this study also presented evidence that changes to the women\u0026rsquo;s menstrual cycle after exposure to the Covid-19 vaccination are short lived.\u003csup\u003e9, 28, 29, 30\u0026nbsp;\u003c/sup\u003e The results of the chi-square test analysis indicated that there were fewer incidences of menstrual disturbances after the second dose cycle compared to the menstrual abnormalities after the first dose cycle. The implication is that the extent of immunological stimulation of the menstrual cycle hormones tends to decrease after the second dose cycle. However, in other studies, \u003csup\u003e9, 31, 32\u0026nbsp;\u003c/sup\u003e there was evidence of adverse post-vaccine menstrual cycle flow after the second dose cycle compared to the first dose cycle. For instance, the study published by the Norwegian Institute of Public Health found that, \u003csup\u003e9\u0026nbsp;\u003c/sup\u003e15.3% of young women, 18-30 years reported heavier periods after the second dose cycle compared to 13.6% of the participants who reported heavier menstrual periods after the first dose vaccination. This trend was also noted based on the outcome of logistics regression analysis for this study. The implication is that the extent of menstrual cycle changes depends on the population group being studied and their age profile.\u003c/p\u003e\n\u003cp\u003eThe study findings indicated that among the pre- and post-menopausal women who were not menstruating before vaccination, they reported menstrual cycle changes after receiving the SARS-CoV-2 vaccine. In addition, there was a significant increase in the proportion of post-menopausal women who reported experiencing menstrual symptoms after the second dose vaccination compared to the first dose vaccination. The results indicated that among women who do not menstruate, while 11.1% of post-menopausal women reported menstrual symptoms after the first dose cycle, 37.5% of them experienced menstrual bleeding after the second dose vaccination. These findings are fairly consistent with the outcome of the study by Lee et al. who found that, \u003csup\u003e33\u0026nbsp;\u003c/sup\u003e 66% of postmenopausal women had reported breakthrough bleeding after Covid-19 vaccination.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eImplication of the Findings\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAlthough not significant, especially after the first dose cycle, the findings on the link between Covid-19 vaccination and post-vaccine menstrual cycle changes have two major implications. First, the research outcome has considerable implication in enhancing the success of Covid-19 vaccination program, especially among the young reproductive-age women.\u003csup\u003e\u0026nbsp;28 \u0026nbsp;\u003c/sup\u003eThere are false claims that Covid-19 vaccines could adversely affect women\u0026rsquo;s fertility and therefore, their ability to conceive. The stated safety concerns related to Covid-19 vaccines increased substantially after reports that young women who had been vaccinated experienced abnormal menstrual cycles.\u003csup\u003e\u0026nbsp;34\u0026nbsp;\u003c/sup\u003e These concerns are likely to increase the level of vaccine hesitancy among young women who fear that taking the jab might adversely affect their ability to conceive. \u003csup\u003e35 \u0026nbsp;\u003c/sup\u003eTherefore, the findings from this research are expected to instill trust among young women that the Covid-19 vaccines are safe and do not interfere substantially with their fertility. Specifically, the partial findings in this study that Covid-19 vaccination is not significantly associated with menstrual cycle abnormalities such as late period and other menstrual bleeding is likely to create trust and confidence among the reproductive age women that the Covid-19 vaccines are safe.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecond, the research findings on the link between Covid-19 vaccines and post-vaccine menstrual cycle changes are likely to enable young women to effectively plan for potentially altered menstrual cycles in the period after the first and the second dose cycles. The knowledge that Covid-19 vaccination alters the period length and cycle regularity can inform \u0026nbsp; young women to effectively plan for their altered menstrual cycle.\u003csup\u003e\u0026nbsp;28\u0026nbsp;\u003c/sup\u003e This will enable women to avoid unplanned pregnancies that might occur due to changes in their menstrual cycles after vaccination.\u003csup\u003e\u0026nbsp;28, 34\u0026nbsp;\u003c/sup\u003e This is possible given that the young women might need to be careful during the few weeks after the first cycle dose and the second cycle dose. Therefore, the findings would be important in minimizing concerns among women that Covid-19 vaccination might place them at risk of experiencing unplanned pregnancies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings partially support previous evidence that Covid-19 vaccination is associated with post-vaccine menstrual cycle abnormalities. This study showed that with the exception of late periods, other menstrual bleeding, severe menstrual symptoms, and other menstrual symptoms, \u0026nbsp;the self-reported menstrual cycle disturbances (i.e., missed periods, spotting, change in period length, cycle regularity, and variation in period flow) were not significantly different after the first and the second dose cycle. However, changes in the menstrual cycle were less strong after the second dose compared to the variation after the first dose vaccination. The findings suggest that the menstrual cycle abnormalities that occurred after the Covid-19 vaccination are temporary (short-lived) given that the menstrual cycle reverts to the normal level after a period of time. The research findings have important implications in reducing vaccine hesitancy among young women and therefore, enhancing the success of Covid-19 vaccination program. The knowledge of the link between vaccination and post-vaccine menstrual cycle changes is also expected to help young women to plan for the altered menstrual cycles in order to avoid unintended pregnancies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Participant informed consent to participate in this study was sought via an informed consent form that prefaced the survey. The informed consent form explained that the survey was anonymous, that participation was voluntary, and the purpose of the study. All ethical standards of voluntary participation and confidentiality were maintained. Participation in this study was voluntary and HCWs received no form of financial remuneration in order to reduce the risk of response bias. Data was collected in a manner that ensured patient anonymity i.e. no identifiers were recorded. Only de-identified data was recorded. This study was approved by the North Central Regional Health Authority Ethics Committee, Trinidad, and The Ministry of Health of Trinidad and Tobago Ethics Committee (3/13/441 Vol. II) and carried out in accordance with the ethics committees\u0026rsquo; guidelines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The data that supports the findings of this study is available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare that there is no conflict of interest regarding the publication of this article.\u003c/p\u003e\n\u003cp\u003eFunding: The authors have not received any funding or benefits from industry or elsewhere to conduct or publish this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions: CDG and BB were responsible for data analysis, with intellectual contributions from DV. CDG and BB drafted the article. All authors contributed to the conception and design of the paper, interpretation of data, and critical revisions contributing to the intellectual content and approval of the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements: Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Boniface E, Benhar E, Matteson HL, Favaro C, Pearson JT, Darney BJ. COVID-19 vaccines linked to small increase in menstrual cycle length. Obstetrics \u0026amp; Gynecology. 2022; 1(1): 1-5.\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Male V. Menstrual changes after Covid-19 vaccination. BMJ. 2021; 374.\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Von Woon E, Male V. Effect of COVID-19 vaccination on menstrual periods in a prospectively recruited cohort. MedRxiv. 2022; 1-5.\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Edelman A, Boniface ER, Benhar E, Leo H, Matteson KA, Favaro C, Pearson JT, Darney BJ. \u0026nbsp;Association between menstrual cycle length and coronavirus disease 2019 (Covid-19) vaccination. Obstetrics \u0026amp; Gynecology. 2022; 1-5.\u003c/p\u003e\n\u003cp\u003e5.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Li K, Chen G, Hou H. Analysis of sex hormones and menstruation in COVID-19 women of child-bearing age. Reproductive Biomedicine Online. 2021; 42 (1): 260-267.\u003c/p\u003e\n\u003cp\u003e6.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Orvieto R, Noach-Hirsh M, Segev-Zahav A, Haas J, Nahum R, Aizer A. Does mRNA SARS-CoV-2 vaccine influence patients\u0026rsquo; performance during IVF-ET cycle? Reproductive Biology and Endocrinology. 2021; 19 (1): 69-70.\u003c/p\u003e\n\u003cp\u003e7.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Suzuki S, Hosono A. No association between HPV vaccine and reported post-vaccination symptoms in Japanese young women: Results of the Nagoya study. Papillomavirus Research. 2018; 5 (1): 96-103.\u003c/p\u003e\n\u003cp\u003e8.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Wang Y-X, Arvizu M, Rich-Edwards JW, et al. Menstrual cycle regularity and length across the reproductive lifespan and risk of premature mortality: Prospective cohort study. BMJ. 2020; 371-372.\u003c/p\u003e\n\u003cp\u003e9.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Norwegian Institute of Public Health. Menstrual changes following COVID-19 vaccination. 2022. https://www.fhi.no/en/news/2022/menstrual-changes-following-covid-19-vaccination/.\u003c/p\u003e\n\u003cp\u003e10.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Kurdoğlu Z. Do the COVID-19 vaccines cause menstrual irregularities? International Journal of Women\u0026rsquo;s Health Reproductive Science. 2021; 9(3):158-159.\u003c/p\u003e\n\u003cp\u003e11.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Muhaidat N, Alshrouf MA, Azzam MI, Karam AM, Al-Nazer MW, Al-Ani, A. Menstrual symptoms after COVID-19 vaccine: A cross-sectional investigation in the MENA region. International Journal of Women\u0026rsquo;s Health. 2022; 395-404.\u003c/p\u003e\n\u003cp\u003e12.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Central Statistical Office, 2019. Provisional Mid Year Population Estimate by Age and Sex, 2005\u0026ndash;2021. Available at: https://cso.gov.tt/subjects/population-and-vital-statistics/population/. Accessed January 16, 2021.\u003c/p\u003e\n\u003cp\u003e13.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ministry of Health, Trinidad and Tobago, 2020. Statement from the Honourable Terence Deyalsingh, Minister of Health at the Media Conference to Advise of the First Confirmed (Imported) Case of COVID-19 in Trinidad and Tobago. Available at: http://www.health.gov.tt/sitepages/default.aspx?id=293. Accessed January 16, 2021.\u003c/p\u003e\n\u003cp\u003e14.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Government of the Republic of Trinidad and Tobago Ministry of Health. COVID-19 Novel Coronavirus. Available at: https://health.gov.tt/covid-19/covid-19-guidelines-and-regulations. Accessed January 16, 2021.\u003c/p\u003e\n\u003cp\u003e15. Gopaul CD, Ventour D, Thomas D. COVID-19 Vaccine Acceptance and Uptake Among Healthcare Workers in Trinidad \u0026amp; Tobago. MedRxiv. 2022. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e16. Gopaul CD, Ventour D, Thomas D. ChAdOx1 nCoV-19 Vaccine Side Effects among Healthcare Workers in Trinidad and Tobago. Vaccines 2022;10,466. https://doi.org/10.3390/vaccines10030466.\u003c/p\u003e\n\u003cp\u003e17.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Gopaul CD, Ventour D, Trotman M, Thomas D. The epidemiological characteristics of positive COVID-19 patients in Trinidad and Tobago. Journal of Public Health and Epidemiology. 2022 14(1), 29-34.\u003c/p\u003e\n\u003cp\u003e18.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Gopaul C, Ventour D, Thomas D. Laboratory Predictors for COVID-19 ICU Admissions in Trinidad and Tobago. Research Square, 2020; [Preprint] Available from: https://doi.org/10.21203/rs.3.rs-103394/v1 .\u003c/p\u003e\n\u003cp\u003e19.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Phelan N, Behan LA, Owens L. The impact of the COVID-19 pandemic on women\u0026rsquo;s reproductive health. Frontiers in Endocrinology. 2021; 191-195.\u003c/p\u003e\n\u003cp\u003e20.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lee KMN, Junkins EJ, Fatima UA, Cox ML, Clancy KBH. Characterizing menstrual bleeding changes occurring after SARS-CoV-2 vaccination. MedRxiv. 2021; 1-5.\u003c/p\u003e\n\u003cp\u003e21.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sharp GC, Fraser A, Sawyer G, Kountourides G, Easey KH, Ford G, Olszewska Z, Howe LD, Lawlor DA et al. The COVID-19 pandemic and the menstrual cycle: Research gaps and opportunities. International Journal of Epidemiology. 2022; 51(3): 691-700.\u003c/p\u003e\n\u003cp\u003e22.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Aolymat IA. Cross-sectional study of the impact of COVID-19 on domestic violence, menstruation, genital tract health, and contraception use among women in Jordan. American Journal of Tropical Medicine \u0026amp; Hygiene. 2020; 519-525.\u003c/p\u003e\n\u003cp\u003e23.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Demir O, Sal H, Comba C. Triangle of COVID, anxiety and menstrual cycle. Journal of Obstetrics and Gynaecology. 2021; 1257-1261.\u003c/p\u003e\n\u003cp\u003e24.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Burki T. The indirect impact of COVID-19 on women. Lancet Infectious Diseases. 2020; 20(1): 904-905.\u003c/p\u003e\n\u003cp\u003e25.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Azize DA, Evans E, Richard P. Possible effect of COVID-19 vaccines on menstruation in Cape Coast, Ghana, West Africa: Case series report. Open Journal of Obstetrics and Gynecology. 2021; 11(11): 1650-1656.\u003c/p\u003e\n\u003cp\u003e26.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. New England Journal of Medicine. 2020; 383(27): 2603-2615.\u003c/p\u003e\n\u003cp\u003e27.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lee KM, Junkins EJ, Luo C, Fatima UA, Cox ML, Clancy KB. Investigating trends in those who experience menstrual bleeding changes after SARS-CoV-2 vaccination. MedRxiv. 2022; 10.\u003c/p\u003e\n\u003cp\u003e28.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Male V. Menstruation and Covid-19 vaccination. BMJ. 2022; 376.\u003c/p\u003e\n\u003cp\u003e29.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sualeh M, Uddin MR, Junaid N, Khan M, Pario A. Impact of COVID-19 vaccination on the menstrual cycle: A cross-sectional study from Karachi, Pakistan. Research Square. 2022; 1-5.\u003c/p\u003e\n\u003cp\u003e30.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tragostad L. Increased occurrence of menstrual disturbances in 18- to 30-year-old women after covid-19 vaccination. SSRN. 2022; 1-5.\u003c/p\u003e\n\u003cp\u003e31.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Khan SM, Shilen A, Heslin KM, et al. SARS-CoV-2 infection and subsequent changes in the menstrual cycle among participants in the Arizona CoVHORT study. American Journal of Obstetrics and Gynecology. 2021; (21)1: 1044-1049.\u003c/p\u003e\n\u003cp\u003e32.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Safrai M, Rottenstreich A, Herzberg S, Imbar T, Reubinoff B, Ben-Meir A. Stopping the misinformation: BNT162b2 COVID-19 vaccine has no negative effect on women\u0026rsquo;s fertility. MedRxiv. 2021; 1-10.\u003c/p\u003e\n\u003cp\u003e33.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lee KMN, Junkins EJ, Luo C, Fatima UA, Cox ML, Clancy KBH. Investigating trends in those who experience menstrual bleeding changes after SARS-CoV-2 vaccination. Sciences Advances. 2022; 8(1): 1-15.\u003c/p\u003e\n\u003cp\u003e34.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Davis HE, Assaf GS, McCorkell L et al. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. E-Clinical Medicine. 2021; 38.\u003c/p\u003e\n\u003cp\u003e35.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;World Health Organization. Information for the public: COVID-19 vaccines. 2022.\u0026nbsp;\u003ca href=\"https://www.who.int/westernpacific/emergencies/covid-19/information-vaccines\"\u003ehttps://www.who.int/westernpacific/emergencies/covid-19/information-vaccines\u003c/a\u003e.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Covid-19 Vaccine Side-Effects, Menstrual Cycle, Female Reproductive Health, Covid-19 Pandemic, Vaccine Hesitancy","lastPublishedDoi":"10.21203/rs.3.rs-2048853/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2048853/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Prior clinical studies that sought to investigate the safety and efficacy of Covid-19 vaccines did not list \u0026nbsp;menstrual cycle changes as a side-effect. However, following reported cases of menstrual cycle disturbances after vaccination, this study sought to examine the link between Covid-19 vaccination and post-vaccine menstrual cycle abnormalities in pre- and post-menopausal women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional research design approach using online surveys was employed to investigate the link between vaccination and changes in menstrual cycle. The participants consisted of a cohort of 657 pre- and post-menopausal women with the majority drawn from the reproductive age group (25-44 years). The inclusion criteria was that participants must have received any type of Covid-19 vaccine, not be pregnant and those that did not have a negative diagnosis in any gynecologic condition. Of the eligible sample size, only 344 participants met the inclusion criteria. \u0026nbsp;The sociodemographic and menstrual cycle data was collected from an online survey. Data was analyzed using descriptive, inferential chi-square tests, logistic regression, and correlation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The results partially confirmed the findings from prior studies that Covid-19 vaccination is associated with significant changes in the women’s menstrual cycle flow and menstrual period length even after controlling for age, Body Mass Index, and ethnicity. Other menstrual cycle disturbances such as missed periods, cycle regularity, and spotting/vaginal bleeding were noted to be less significant. However, the extent of menstrual cycle changes was less severe and decreased after the second dose vaccination. It was found that 11.1% and 37.5% of post-menopausal women reported menstrual symptoms after the first and the second dose cycle respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The study concludes that although Covid-19 vaccines tend to adversely affect women’s menstrual cycle, these changes are short-lived. The findings have important implications in enhancing the success of Covid-19 vaccination programs by reducing cases of vaccine hesitancy among reproductive-age women.\u003c/p\u003e","manuscriptTitle":"Effects of Covid-19 Vaccines on the Menstrual Cycle: A Cross-Sectional Study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-19 20:11:30","doi":"10.21203/rs.3.rs-2048853/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d4c2fa8-61a5-4a2b-a3a5-5f7fa883fc95","owner":[],"postedDate":"September 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-19T20:11:30+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-19 20:11:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2048853","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2048853","identity":"rs-2048853","version":["v1"]},"buildId":"afDZ1USd8LLqUjqjB8QhT","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}