Covid-19 vaccination and menstrual cycle length in the Apple Women's Health Study.
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ABSTRACT:
SUBMITTER: Gibson EA
PROVIDER: S-EPMC9628464 | biostudies-literature | 2022 Nov
REPOSITORIES: biostudies-literature
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Covid-19 vaccination and menstrual cycle length in the Apple Women's Health Study.
Gibson Elizabeth A EA Li Huichu H Fruh Victoria V Gabra Malaika M Asokan Gowtham G Jukic Anne Marie Z AMZ Baird Donna D DD Curry Christine L CL Fischer-Colbrie Tyler T Onnela Jukka-Pekka JP Williams Michelle A MA Hauser Russ R Coull Brent A BA Mahalingaiah Shruthi S
NPJ digital medicine 20221102 1
COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination. We estimated covariate-adjusted differences in mean cycle length (MCL), measured in days, between pre-vaccination cycles, vaccination cycles, and post-vaccination cycles within vaccinated participants who met eligibility criteria in the Apple Women's Health Study, a longitudinal mobile-application-based cohort of people in the U.S. with manually logged menstrual cycles. A total of 9652 participant ...[more]
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Project description:BackgroundCOVID-19 vaccination may be associated with change in menstrual cycle length following vaccination.MethodsWe conducted a longitudinal analysis within a subgroup of 14,915 participants in the Apple Women's Health Study (AWHS) who enrolled between November 2019 and December 2021 and met the following eligibility criteria: were living in the U.S., met minimum age requirements for consent, were English speaking, actively tracked their menstrual cycles, and responded to the COVID-19 Vaccine Update survey. In the main analysis, we included tracked cycles recorded when premenopausal participants were not pregnant, lactating, or using hormonal contraceptives. We used conditional linear regression and multivariable linear mixed-effects models with random intercepts to estimate the covariate-adjusted difference in mean cycle length, measured in days, between pre-vaccination cycles, cycles in which a vaccine was administered, and post-vaccination cycles within vaccinated participants, and between vaccinated and unvaccinated participants. We further compared associations between vaccination and menstrual cycle length by the timing of vaccine dose within a menstrual cycle (i.e., in follicular or luteal phase). We present Bonferroni-adjusted 95% confidence intervals to account for multiple comparisons.ResultsA total of 128,094 cycles (median = 10 cycles per participant; interquartile range: 4-22) from 9,652 participants (8,486 vaccinated; 1,166 unvaccinated) were included. The average within-individual standard deviation in cycle length was 4.2 days. Fifty-five percent of vaccinated participants received Pfizer-BioNTech's mRNA vaccine, 37% received Moderna's mRNA vaccine, and 7% received the Johnson & Johnson/Janssen vaccine (J&J). We found no evidence of a difference between mean menstrual cycle length in the unvaccinated and vaccinated participants prior to vaccination (0.24 days, 95% CI: -0.34, 0.82).Among vaccinated participants, COVID-19 vaccination was associated with a small increase in mean cycle length (MCL) for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimates for pre vs post cycle lengths were 0.14 days (95% CI: -0.13, 0.40) in the first cycle following vaccination, 0.13 days (95% CI: -0.14, 0.40) in the second, -0.17 days (95% CI: -0.43, 0.10) in the third, and -0.25 days (95% CI: -0.52, 0.01) in the fourth cycle post-vaccination. Follicular phase vaccination was associated with an increase in MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles.ConclusionsCOVID-19 vaccination was associated with an immediate short-term increase in menstrual cycle length overall, which appeared to be driven by doses received in the follicular phase. However, the magnitude of this increase was small and diminished in each cycle following vaccination. No association with cycle length persisted over time. The magnitude of change associated with vaccination was well within the natural variability in the study population. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.
| S-EPMC9298140 | biostudies-literature
Project description:Menstrual characteristics are important signs of women's health. Here we examine the variation of menstrual cycle length by age, ethnicity, and body weight using 165,668 cycles from 12,608 participants in the US using mobile menstrual tracking apps. After adjusting for all covariates, mean menstrual cycle length is shorter with older age across all age groups until age 50 and then became longer for those age 50 and older. Menstrual cycles are on average 1.6 (95%CI: 1.2, 2.0) days longer for Asian and 0.7 (95%CI: 0.4, 1.0) days longer for Hispanic participants compared to white non-Hispanic participants. Participants with BMI ≥ 40 kg/m2 have 1.5 (95%CI: 1.2, 1.8) days longer cycles compared to those with BMI between 18.5 and 25 kg/m2. Cycle variability is the lowest among participants aged 35-39 but are considerably higher by 46% (95%CI: 43%, 48%) and 45% (95%CI: 41%, 49%) among those aged under 20 and between 45-49. Cycle variability increase by 200% (95%CI: 191%, 210%) among those aged above 50 compared to those in the 35-39 age group. Compared to white participants, those who are Asian and Hispanic have larger cycle variability. Participants with obesity also have higher cycle variability. Here we confirm previous observations of changes in menstrual cycle pattern with age across reproductive life span and report new evidence on the differences of menstrual variation by ethnicity and obesity status. Future studies should explore the underlying determinants of the variation in menstrual characteristics.
| S-EPMC10226714 | biostudies-literature
Project description:IntroductionAfter COVID-19 vaccination, women of reproductive age reported changes in their menstrual cycle.Materials and methodsA retrospective study was carried out after a survey on social networks that included women aged 18-41 years with normal cycles according to International Federation of Gynecology and Obstetrics and who were vaccinated (complete schedule for two doses, except J&J/Janssen or incomplete with a single dose). Women with following conditions were excluded: pregnant or lactating women; history of diseases that cause menstrual irregularities or early menopause: anorexia, bulimia, polycystic ovary syndrome, hypothyroidism, obesity, or low weight; hysterectomized or oophorectomized patients; and high performance athletes.ResultsOverall, 950 women completed the survey between July and September 2021. In total, 408 women met the inclusion criteria, and 184 reported the following characteristics: frequency (normal 43.47%, infrequent 25%, and frequent 31.53%), regularity (regular 51.08%, irregular 42.93%, and absent/amenorrhea 5.97%), duration (normal 65.21%, prolonged 26.08%, absent/amenorrhea 8.69%), and volume (heavy 41.84%, light 20.65%, and absent/amenorrhea 6.52%).ConclusionsSARS-CoV-2 infection and COVID-19 vaccination can influence the menstrual cycle and cause alterations.
| S-EPMC9295013 | biostudies-literature
Project description:We prospectively examined the association between COVID-19 vaccination and menstrual cycle characteristics in an internet-based prospective cohort study. We included a sample of 1,137 participants who enrolled in Pregnancy Study Online (PRESTO), a preconception cohort study of couples trying to conceive, during January 2021-August 2022. Eligible participants were aged 21-45 years, United States or Canadian residents, and trying to conceive without fertility treatment. At baseline and every 8 weeks for up to 12 months, participants completed questionnaires on which they provided information on COVID-19 vaccination and menstrual cycle characteristics, including cycle regularity, cycle length, bleed length, heaviness of bleed, and menstrual pain. We fit generalized estimating equation (GEE) models with a log link function and Poisson distribution to estimate the adjusted risk ratio (RR) for irregular cycles associated with COVID-19 vaccination. We used linear regression with GEE to estimate adjusted mean differences in menstrual cycle length associated with COVID-19 vaccination. We adjusted for sociodemographic, lifestyle, medical and reproductive factors. Participants had 1.1 day longer menstrual cycles after receiving the first dose of COVID-19 vaccine (95 % CI: 0.4, 1.9) and 1.3 day longer cycles after receiving the second dose (95 % CI: 0.2, 2.5). Associations were attenuated at the second cycle post-vaccination. We did not observe strong associations between COVID-19 vaccination and cycle regularity, bleed length, heaviness of bleed, or menstrual pain. In conclusion, COVID-19 vaccination was associated with a ∼1 day temporary increase in menstrual cycle length, but was not appreciably associated with other menstrual cycle characteristics.
| S-EPMC10239900 | biostudies-literature
Project description:Numerous anecdotal accounts and qualitative research studies have reported on post-vaccination menstrual irregularities in women of reproductive age. However, none have quantified the impact. This is the first systematic review and meta-analysis to quantify and characterize the menstrual irregularities associated with vaccination for women of reproductive age. A search on July 20, 2022, retrieved articles published between December 1, 2019, and July 1, 2022, from MEDLINE, Embase, and Web of Science. The included articles were studies with full texts written in English that reported on menstrual irregularities for vaccinated vs. unvaccinated women of reproductive age. The quality of the studies was evaluated using the Study Quality Assessment Tool for Observation Cohort and Cross-Sectional Studies. Four observational studies were included. Review Manager was used to generating a forest plot with odds ratios (ORs) at the 95% confidence interval (CI), finding statistically significant associations between vaccination and menstrual irregularities for 25,054 women of reproductive age (OR = 1.91, CI: 1.76-2.07) with a significant overall effect of the mean (Z = 16.01, p < 0.0001). The studies were heterogeneous with significant dispersion of values (χ2 = 195.10 at df = 3, p < 0.00001, I 2 = 98%). The findings of this systematic review and meta-analysis are limited by the availability of quantitative data. The results have implications for treating women of reproductive age with menstrual irregularities and informing them about the potential side effects of vaccinations.
| S-EPMC9802578 | biostudies-literature
Project description:Air pollution can influence women's reproductive health, specifically menstrual cycle characteristics, oocyte quality, and risk of miscarriage. The aim of the study was to assess whether air pollution can affect the length of the overall menstrual cycle and the length of its phases (follicular and luteal). Municipal ecological monitoring data was used to assess the air pollution exposure during the monitored menstrual cycle of each of 133 woman of reproductive age. Principal component analyses were used to group pollutants (PM10, SO₂, CO, and NOx) to represent a source-related mixture. PM10 and SO₂ assessed separately negatively affected the length of the luteal phase after standardization (b = -0.02; p = 0.03; b = -0.06; p = 0.02, respectively). Representing a fossil fuel combustion emission, they were also associated with luteal phase shortening (b = -0.32; p = 0.02). These pollutants did not affect the follicular phase length and overall cycle length, neither in single- nor in multi-pollutant models. CO and NOx assessed either separately or together as a traffic emission were not associated with overall cycle length or the length of cycle phases. Luteal phase shortening, a possible manifestation of luteal phase deficiency, can result from fossil fuel combustion. This suggests that air pollution may contribute to fertility problems in women.
| S-EPMC5551254 | biostudies-other
Project description:There has been increasing public concern that COVID-19 vaccination causes menstrual disturbance regarding the relative effect of vaccination compared to SARS-CoV-2 infection. Our objectives were to test potential risk factors for reporting menstrual cycle changes following COVID-19 vaccination and to compare menstrual parameters following COVID-19 vaccination and COVID-19 disease. We performed a secondary analysis of a retrospective online survey conducted in the UK in March 2021. In pre-menopausal vaccinated participants (n = 4,989), 18% reported menstrual cycle changes after their first COVID-19 vaccine injection. The prevalence of reporting any menstrual changes was higher for women who smoke, have a history of COVID-19 disease, or are not using estradiol-containing contraceptives. In a second sample including both vaccinated and unvaccinated participants (n = 12,579), COVID-19 vaccination alone was not associated with abnormal menstrual cycle parameters, while a history of COVID-19 disease was associated with an increased risk of reporting heavier bleeding, "missed" periods, and inter-menstrual bleeding.
| S-EPMC10015085 | biostudies-literature
Project description:ObjectiveTo describe the characteristics of people who experience changes to their menstrual cycle after COVID-19 vaccination.DesignLongitudinal study.Patient(s)We recruited a volunteer sample with and without a history of SARS-CoV-2 infection who enrolled in the Arizona COVID-19 Cohort (CoVHORT) study and participated in a reproductive sub-cohort who were pre-menopausal, not pregnant, and had received a COVID-19 vaccine in 2021 (n = 545).Exposure(s)Demographic and reproductive characteristics were collected via self-reports.Main outcome measure(s)Information on self-reported changes in the menstrual cycle after COVID-19 vaccination was collected from May 2021 to December 2021. We looked at demographic and reproductive characteristics as predictors of menstrual cycle change.Result(s)The majority of our vaccinated sample received the Pfizer-BioNTech vaccine (58%), and were 26-35 years old (51%), non-Hispanic (84%), and White (88%). Approximately 25% of vaccinated participants reported a change in their menstrual cycle after vaccination; the majority reported changes after their second dose (56%) as compared with their first (18%) and third (14%) doses. The most commonly reported changes were irregular menstruation (43%), increased premenstrual symptoms (34%), increased menstrual pain or cramps (30%), and abnormally heavy or prolonged bleeding (31%). High self-reported perceived stress levels compared with low perceived stress (OR, 2.22; 95% CI 1.12-4.37) and greater body mass index (OR, 1.04; 95% CI 1.00-1.07) were associated with greater odds of experiencing the menstrual cycle changes after the vaccination. Participants having a history of SARS-CoV-2 infection were less likely to report changes in their menstrual cycle after vaccination compared with the participants with no history of SARS-CoV-2 infection (OR, 0.58; 95% CI 0.32-1.04).Conclusion(s)Among vaccinated participants, approximately 25% of them reported predominantly temporary changes in the menstrual cycle, however, we are unable to determine whether these changes are due to normal cycle variability. The COVID-19 vaccines are safe and effective for everyone, including pregnant people and people trying to conceive; hence, these findings should not discourage vaccination.
| S-EPMC9758067 | biostudies-literature
Project description:BackgroundPrevious studies have suggested that emergent events may affect pregnancy planning decisions. However, few have investigated the effect of factors related to the COVID-19 pandemic on pregnancy planning, measured by attempting conception, and how attempting conception status may differ by individual-level factors, such as social status or educational level.ObjectiveThis study aimed to examine the effects of factors related to the COVID-19 pandemic, until March 2021, on attempting conception status and to assess the effect measure modification by educational level and subjective social status.Study designWe conducted a longitudinal analysis within a subgroup of 21,616 participants in the Apple Women's Health Study who enrolled from November 2019 to March 2021, who met the inclusion criteria, and who responded to the monthly status menstrual update question on attempting conception status (yes or no). Participants reporting hysterectomy, pregnancy, lactation, or menopause were excluded. We used generalized estimating equation methodology to fit logistic regression models that estimate odds ratios and 95% confidence intervals for the association between the proportion of participants attempting conception and the month of response (compared with a prepandemic reference month of February 2020) while accounting for longitudinal correlation and adjusting for age, race and ethnicity, and marital status. We stratified the analysis by social status and educational level.ResultsWe observed a trend of reduced odds of attempting conception, with an 18% reduction in the odds of attempting conception in August 2020 and October 2020 compared with the prepandemic month of February 2020 (August odds ratio: 0.82 [95% confidence interval, 0.70-0.97]; October odds ratio: 0.82 [95% confidence interval, 0.69-0.97). The participants with lower educational level (no college education) experienced a sustained reduction in the odds of attempting to conceive from June 2020 to March 2021 compared with February 2020, with up to a 24% reduction in the odds of attempting to conceive in October 2020 (odds ratio, 0.76; 95% confidence interval, 0.59-0.96). Among participants that were college educated, we observed an initial reduction in the odds of attempting to conceive starting in July 2020 (odds ratio 0.73; 95% confidence interval, 0.54-0.99) that returned near prepandemic odds. Moreover, we observed a reduction in the odds of attempting to conceive among those with low subjective social status, with a decline in the odds of attempting to conceive beginning in July 2020 (odds ratio, 0.83; 95% confidence interval, 0.63-1.10) and continuing until March 2021 (odds ratio, 0.79; 95% confidence interval, 0.59-1.06), with the greatest reduction in odds in October 2020 (odds ratio, 0.67; 95% confidence interval, 0.50-0.91).ConclusionAmong women in the Apple Women's Health Study cohort, our findings suggested a reduction in the odds of attempting to conceive during the COVID-19 pandemic, until March 2021, particularly among women of lower educational level and lower perceived social status.
| S-EPMC9093060 | biostudies-literature
Project description:BackgroundUse of menstrual tracking data to understand abnormal bleeding patterns has been limited because of lack of incorporation of key demographic and health characteristics and confirmation of menstrual tracking accuracy.ObjectiveThis study aimed to identify abnormal uterine bleeding patterns and their prevalence and confirm existing and expected associations between abnormal uterine bleeding patterns, demographics, and medical conditions.Study designApple Women's Health Study participants from November 2019 through July 2021 who contributed menstrual tracking data and did not report pregnancy, lactation, use of hormones, or menopause were included in the analysis. Four abnormal uterine bleeding patterns were evaluated: irregular menses, infrequent menses, prolonged menses, and irregular intermenstrual bleeding (spotting). Monthly tracking confirmation using survey responses was used to exclude inaccurate or incomplete digital records. We investigated the prevalence of abnormal uterine bleeding stratified by demographic characteristics and used logistic regression to evaluate the relationship of abnormal uterine bleeding to a number of self-reported medical conditions.ResultsThere were 18,875 participants who met inclusion criteria, with a mean age of 33 (standard deviation, 8.2) years, mean body mass index of 29.3 (standard deviation, 8.0), and with 68.9% (95% confidence interval, 68.2-69.5) identifying as White, non-Hispanic. Abnormal uterine bleeding was found in 16.4% of participants (n=3103; 95% confidence interval, 15.9-17.0) after accurate tracking was confirmed; 2.9% had irregular menses (95% confidence interval, 2.7-3.1), 8.4% had infrequent menses (95% confidence interval, 8.0-8.8), 2.3% had prolonged menses (95% confidence interval, 2.1-2.5), and 6.1% had spotting (95% confidence interval, 5.7-6.4). Black participants had 33% higher prevalence (prevalence ratio, 1.33; 95% confidence interval, 1.09-1.61) of infrequent menses compared with White, non-Hispanic participants after controlling for age and body mass index. The prevalence of infrequent menses was increased in class 1, 2, and 3 obesity (class 1: body mass index, 30-34.9; prevalence ratio, 1.31; 95% confidence interval, 1.13-1.52; class 2: body mass index, 35-39.9; prevalence ratio, 1.25; 95% confidence interval, 1.05-1.49; class 3: body mass index, >40; prevalence ratio, 1.51; 95% confidence interval, 1.21-1.88) after controlling for age and race/ethnicity. Those with class 3 obesity had 18% higher prevalence of abnormal uterine bleeding compared with healthy-weight participants (prevalence ratio, 1.18; 95% confidence interval, 1.02-1.38). Participants with polycystic ovary syndrome had 19% higher prevalence of abnormal uterine bleeding compared with participants without this condition (prevalence ratio, 1.19; 95% confidence interval, 1.08-1.31). Participants with hyperthyroidism (prevalence ratio, 1.34; 95% confidence interval, 1.13-1.59) and hypothyroidism (prevalence ratio, 1.17; 95% confidence interval, 1.05-1.31) had a higher prevalence of abnormal uterine bleeding, as did those reporting endometriosis (prevalence ratio, 1.28; 95% confidence interval, 1.12-1.45), cervical dysplasia (prevalence ratio, 1.20; 95% confidence interval, 1.03-1.39), and fibroids (prevalence ratio, 1.14; 95% confidence interval, 1.00-1.30).ConclusionIn this cohort, abnormal uterine bleeding was present in 16.4% of those with confirmed menstrual tracking. Black or obese participants had increased prevalence of abnormal uterine bleeding. Participants reporting conditions such as polycystic ovary syndrome, thyroid disease, endometriosis, and cervical dysplasia had a higher prevalence of abnormal uterine bleeding.
| S-EPMC9877138 | biostudies-literature