Abstract
Objectives
To evaluate the risks of any menstrual disturbance and bleeding following SARS-CoV-2 vaccination in women who are premenopausal or postmenopausal.
Design
A nationwide, register based cohort study.
Setting
All inpatient and specialised outpatient care in Sweden from 27 December 2020 to 28 February 2022. A subset covering primary care for 40% of the Swedish female population was also included.
Participants
2 946 448 Swedish women aged 12-74 years were included. Pregnant women, women living in nursing homes, and women with history of any menstruation or bleeding disorders, breast cancer, cancer of female genital organs, or who underwent a hysterectomy between 1 January 2015 and 26 December 2020 were excluded.
Interventions
SARS-CoV-2 vaccination, by vaccine product (BNT162b2, mRNA-1273, or ChAdOx1 nCoV-19 (AZD1222)) and dose (unvaccinated and first, second, and third dose) over two time windows (one to seven days, considered the control period, and 8-90 days).
Main outcome measures
Healthcare contact (admission to hospital or visit) for menstrual disturbance or bleeding before or after menopause (diagnosed with the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes N91, N92, N93, N95).
Results
2 580 007 (87.6%) of 2 946 448 women received at least one SARS-CoV-2 vaccination and 1 652 472 (64.0%) 2 580 007 of vaccinated women received three doses before the end of follow-up. The highest risks for bleeding in women who were postmenopausal were observed after the third dose, in the one to seven days risk window (hazard ratio 1.28 (95% confidence interval 1.01 to 1.62)) and in the 8-90 days risk window (1.25 (1.04 to 1.50)). The impact of adjustment for covariates was modest. Risk of postmenopausal bleeding suggested a 23-33% increased risk after 8-90 days with BNT162b2 and mRNA-1273 after the third dose, but the association with ChAdOx1 nCoV-19 was less clear. For menstrual disturbance or bleeding in women who were premenopausal, adjustment for covariates almost completely removed the weak associations noted in the crude analyses.
Conclusions
Weak and inconsistent associations were observed between SARS-CoV-2 vaccination and healthcare contacts for bleeding in women who are postmenopausal, and even less evidence was recorded of an association for menstrual disturbance or bleeding in women who were premenopausal. These findings do not provide substantial support for a causal association between SARS-CoV-2 vaccination and healthcare contacts related to menstrual or bleeding disorders.
Introduction
Menstrual disturbances such as excessive, frequent, and irregular menstruation or absent, scant, and rare menstruation have been reported in association with SARS-CoV-2 vaccines. The US Vaccine Adverse Event Reporting System, the UK Medicines and Healthcare Products Regulatory Agency’s Yellow Card surveillance scheme, and the Swedish Medical Products Agency have received many reports of menstrual disturbance after SARS-CoV-2 vaccination via their respective pharmacovigilance systems.1 2 3
Several studies on self-reported menstruation cycles after SARS-CoV-2 vaccination, from survey data and a menstrual cycle tracking app, indicate changes in menstruation cycles.4 5 6 7 8 9 A link between SARS-CoV-2 vaccination and menstrual disturbance has also been widely discussed on social media.10 However, menstrual cycles vary naturally and minor menstrual disturbances are generally not considered to be of clinical importance. Changes can, however, generate considerable distress in the affected women, especially during a mass vaccination campaign when concerns are raised about adverse reactions that might not yet be well characterised.11 The Pharmacovigilance Risk Assessment Committee of the European Medicines Agency has recommended listing heavy menstrual bleeding as a side effect of unknown frequency in the product information for the SARS-CoV-2 mRNA vaccines. The recommendation follows a review of the available evidence, including cases reported during clinical trials, cases spontaneously reported in Eudravigilance, and findings from the medical literature.12 Previously, investigations researched concerns about menstrual disturbances from other vaccines (eg, against human papillomavirus), but no such association was established.13 14 15
Pharmacovigilance systems relying on self-reporting are useful for identifying potential safety signals but not suited for quantifying the frequency of health event occurrence or estimating the strength of the potential association. To characterise and quantify suspected adverse effects of SARS-CoV-2 vaccines, outside what is detected in clinical trials, individual level data from large observational studies are needed.16
In a nationwide cohort study in Sweden, we evaluated the risks of menstrual disturbance and bleeding after SARS-CoV-2 vaccination in women who were before or after menopause. High quality data from nationwide registers enabled us to evaluate the risk by vaccine product and vaccination dose number.
Material and methods
Data sources
For all individuals, we linked data from Swedish national and regional registers as an analysis within the RECOVAC (register-based large-scale national population study to monitor SARS-CoV-2 vaccination effectiveness and safety) study, which is within the larger project of SCIFI-PEARL (Swedish Covid-19 Investigation for Future Insights—a Population Epidemiology Approach using Register Linkage), described in detail elsewhere.17 A complete medical history from 1 January 2015 was obtained from the national patient register and drug history for prescription drugs from 1 January2018 from the national prescribed drug register.18 19 History of cancer was obtained from the national cancer register.20 Sociodemographic data including education, family situation, income, and occupation data from 2015 were obtained from Statistics Sweden.21 Information about pregnancy was obtained from the national medical birth register. Information about older patients living at special care facilities or receiving home care services was obtained from the register of social service interventions for the elderly and the disabled.22
Vaccination data, including vaccine product, dose number, and date of vaccination, were obtained from the national vaccination register.23 Positive results from SARS-CoV-2 polymerase chain reaction tests were identified from SmiNet, the national register of notifiable communicable diseases.24 We obtained diagnoses of menstrual disturbance and bleeding in women before or after menopause from healthcare contacts registered as outpatient specialist visits or inpatient stays from the national patient register. The risk of having any diagnosis of menstrual disturbance, bleeding before and after menopause after contact with a healthcare service is hereafter referred to as risk of menstruation disorders. In Sweden, women with gynaecological issues will often, especially in urban areas, turn directly to gynaecological specialist care. However, in a subpopulation, we were also able to include information on primary care visits. Thus, for women living in the two largest metropolitan areas (Stockholm region and Västra Götaland region), diagnoses were additionally obtained from regional primary healthcare registers. The date and cause of death were obtained from the register of the total population and the national cause of death register.25 26
Study population
The study included all women aged 12-74 years who were residing in Sweden on 1 January 2018 (to ensure previous comorbidities are accounted for), and still resident in the country on 27 December 2020, when the SARS-CoV-2 vaccine campaign started in Sweden. Data for sex was taken from information in the registry rather than from patient reported gender. The exclusion criteria were women living at special care facilities (5927 women (0.15% of those aged 12-74)) until 31 December 2020, and individuals who were pregnant or had a history of any menstruation disorders, breast cancer, cancer of the female genital organs, or who underwent a hysterectomy between 1 January 2015 (the maximum period of stored history from the register data) and 26 December 2020.
Study period, exposures, and risk windows
The study period was from 27 December 2020 to 28 February 2022. Exposure variables were each dose of any vaccine, and several different risk periods were applied. In the main analyses, we used two mutually exclusive risk periods, one to seven days and 8-90 days after vaccination. The first seven days were deemed to be a negative control period. The time needed for an unknown pathological mechanism to manifest need to be considered, the symptoms then develop to become sufficiently worrying for the woman to seek medical attention, and the healthcare system them provides an appointment or admission, which results in a diagnosis. For menstrual disturbances, a woman is unlikely to notice any effects and be able to get an acute appointment within the first week. As menstrual cycles are around 28 days, we anticipated that a women would be delayed in deciding to seek medical attention for any disturbances. Hence, the 90 day window allows for two cycles and an additional month for the individual to get an appointment, including a potential additional interval in getting an appointment with a gynaecologist. We assessed the risk of menstruation disorders in each risk period after the administration date of the first, second, and third dose with any vaccine. Stratified analyses were performed for three specific vaccine brands used in Sweden, BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and ChAdOx1 nCoV-19 (AZD1222) (AstraZeneca). In sensitivity analyses, we also estimated risk with follow-ups at days seven, 28, and 90 starting the day after exposure date. We performed our main analyses for the whole study population and additional analyses in a subpopulation living in the two largest metropolitan areas (Stockholm region and Västra Götaland region), where regional primary healthcare data were also available.
To contextualise the results, we also estimated the risk for menstruation disorders after a SARS-CoV-2 infection in women who were not vaccinated. The study period for this analysis was from 1 August 2020 (when full-scale testing was implemented in Sweden) to 26 December 2020 (when vaccinations started). In this analysis, we included all female individuals aged 12-74 years who were residing in Sweden on 1 January 2018 and 1 August 2020, who were not pregnant, did not live in nursing home on 1 August 2020, and did not have the previously mentioned comorbidities within five years before August 2020. We also studied the risk of menstruation disorders during follow-up at days seven, 28, and 90 after the first positive test result of SARS-CoV-2 infection.
Outcomes
We studied three different menstruation disorders in different restricted age ranges (defined to include premenopausal or postmenopausal women when relevant for the respective outcomes). We identified only incident cases by using the first recording of a primary diagnosis, according to the Swedish clinical modification of the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10-SE), in one of the registers to define the outcome. Hence, outcomes were based on a healthcare contact (admission to hospital or visit) where a physician registered any of the diagnoses under study. All healthcare contacts with any of the diagnoses under study were included in the analyses including primary care, regardless of whether these contacts were related to a physician or other healthcare worker visit. The date of diagnosis was regarded as a proxy for date of onset because we have no means to assess the true start of symptoms. We studied postmenopausal bleeding in women of 45-74 years, using ICD-10-SE code N95.0.
We also studied menstrual disturbance in women aged 12-49 years, using ICD-10-SE codes N91 and N92.
Additionally, we studied premenopausal bleeding in women aged 12-49 years, using ICD-10-SE codes N93.8 and N93.9. For the Stockholm region and Västra Götaland region, the ICD-10-SE-P (for primary care) code N93 was additionally used.
Covariates
Covariates included in the full models were age (cubic spline with four knots), country of birth (Sweden/other countries), employed as a healthcare worker (yes/no), marital status (married/not married), education (primary, secondary, tertiary, undetermined), number of primary care visits, number of specialist outpatient visits, and days of inpatient stay, during 2018-19, as well as prior comorbidities and treatments (each yes/no; listed in supplement table S1, directed acyclic graphs, supplement DAG S1, and supplement DAG S2) (table 1, supplement table S2).
Table 1.
Distribution of characteristics related to demographics and medical history, by vaccine status. All women were unvaccinated at the baseline, and they can contribute with person-time to more than one vaccine status group
| Covariates | Baseline (all unvaccinated) (n=2 946 448) |
At least one dose (n=2 580 007) | At least two doses (n=2 515 868) | Three doses and more (n=1 652 472) |
|---|---|---|---|---|
| Age, median (IQR) | 44 (24-58) | 46 (25-59) | 46 (26-59) | 53 (41-63) |
| Employed as a healthcare worker: | ||||
| No | 2 018 128 (68.5) | 1 740 484 (67.5) | 1 690 984 (67.2) | 1 057 348 (64.0) |
| Yes | 928 320 (31.5) | 839 523 (32.5) | 824 884 (32.8) | 595 124 (36.0) |
| Country of birth: | ||||
| Sweden | 2 383 529 (80.9) | 2 153 373 (83.5) | 2 107 976 (83.8) | 1 432 112 (86.7) |
| Outside Sweden | 562 919 (19.1) | 426 634 (16.5) | 407 892 (16.2) | 220 360 (13.3) |
| Education: | ||||
| Primary | 416 303 (14.1) | 354 647 (13.7) | 342 635 (13.6) | 204 655 (12.4) |
| Secondary | 1 076 764 (36.5) | 957 364 (37.1) | 940 376 (37.4) | 689 049 (41.7) |
| Tertiary | 1 077 071 (36.6) | 989 890 (38.4) | 978 262 (38.9) | 743 930 (45) |
| Unknown | 376 310 (12.8) | 278 106 (10.8) | 254 595 (10.1) | 14 838 (0.9) |
| Cardiovascular disease: | ||||
| No | 2 850 349 (96.7) | 2 491 633 (96.6) | 2 428 912 (96.5) | 1 580 841 (95.7) |
| Yes | 96 099 (3.3) | 88 374 (3.4) | 86 956 (3.5) | 71 631 (4.3) |
| Stroke or transient ischaemic attack: | ||||
| No | 2 927 167 (99.3) | 2 562 162 (99.3) | 2 498 227 (99.3) | 1 637 146 (99.1) |
| Yes | 19 281 (0.7) | 17 845 (0.7) | 17 641 (0.7) | 15 326 (0.9) |
| Diabetes (type 1 and 2): | ||||
| No | 2 835 636 (96.2) | 2 477 521 (96.0) | 2 414 737 (96.0) | 1 568 459 (94.9) |
| Yes | 110 812 (3.8) | 102 486 (4.0) | 101 131 (4.0) | 84 013 (5.1) |
| Chronic pulmonary disease: | ||||
| No | 2 928 408 (99.4) | 2 563 464 (99.4) | 2 499 620 (99.4) | 1 638 670 (99.2) |
| Yes | 18 040 (0.6) | 16 543 (0.6) | 16 248 (0.6) | 13 802 (0.8) |
| Asthma: | ||||
| No | 2 877 204 (97.6) | 2 518 549 (97.6) | 2 456 384 (97.6) | 1 615 853 (97.8) |
| Yes | 69 244 (2.4) | 61 458 (2.4) | 59 484 (2.4) | 36 619 (2.2) |
| Chronic kidney disease: | ||||
| No | 2 908 552 (98.7) | 2 546 491 (98.7) | 2 483 198 (98.7) | 1 629 523 (98.6) |
| Yes | 37 896 (1.3) | 33 516 (1.3) | 32 670 (1.3) | 22 949 (1.4) |
| Cancer: | ||||
| No | 2 886 227 (98.0) | 2 523 106 (97.8) | 2 459 511 (97.8) | 1 602 926 (97.0) |
| Yes | 60 221 (2.0) | 56 901 (2.2) | 56 357 (2.2) | 49 546 (3.0) |
| Coagulation disorders: | ||||
| No | 1 139 856 (99.2) | 1 038 321 (99.2) | 1 018 983 (99.2) | 702 468 (99.2) |
| Yes | 8821 (0.8) | 7890 (0.8) | 7717 (0.8) | 5634 (0.8) |
| Polycystic ovary syndrome: | ||||
| No | 1 139 698 (99.2) | 1 038 724 (99.3) | 1 019 459 (99.3) | 704 123 (99.4) |
| Yes | 8979 (0.8) | 7487 (0.7) | 7241 (0.7) | 3979 (0.6) |
| Thyroid diseases: | ||||
| No | 2 728 628 (92.6) | 2 380 747 (92.3) | 2 319 269 (92.2) | 1 494 707 (90.5) |
| Yes | 217 820 (7.4) | 199 260 (7.7) | 196 599 (7.8) | 157 765 (9.5) |
| Pituitary disorders: | ||||
| No | 1 142 025 (99.4) | 1 040 378 (99.4) | 1 020 982 (99.4) | 704 115 (99.4) |
| Yes | 6652 (0.6) | 5833 (0.6) | 5718 (0.6) | 3987 (0.6) |
| Uterine polyps or fibroids: | ||||
| No | 1 119 516 (97.5) | 1 020 167 (97.5) | 1 001 063 (97.5) | 688 302 (97.2) |
| Yes | 29 161 (2.5) | 26 044 (2.5) | 25 637 (2.5) | 19 800 (2.8) |
| Endometriosis: | ||||
| No | 913 984 (79.6) | 837 134 (80.0) | 821 956 (80.1) | 566 195 (80.0) |
| Yes | 234 693 (20.4) | 209 077 (20.0) | 204 744 (19.9) | 141 907 (20.0) |
| Pelvic inflammatory diseases: | ||||
| No | 1 052 420 (91.6) | 963 202 (92.1) | 946 222 (92.2) | 658 303 (93.0) |
| Yes | 96 257 (8.4) | 83 009 (7.9) | 80 478 (7.8) | 49 799 (7.0) |
| Obesity: | ||||
| No | 2 898 410 (98.4) | 2 537 952 (98.4) | 2 475 086 (98.4) | 1 624 829 (98.3) |
| Yes | 48 038 (1.6) | 42 055 (1.6) | 40 782 (1.6) | 27 643 (1.7) |
| Autoimmune diseases: | ||||
| No | 2 883 402 (97.9) | 2 522 085 (97.8) | 2 458 815 (97.7) | 1 606 176 (97.2) |
| Yes | 63 046 (2.1) | 57 922 (2.2) | 57 053 (2.3) | 46 296 (2.8) |
| Menopausal hormone: | ||||
| No | 910 720 (79.3) | 820 835 (78.5) | 803 415 (78.3) | 518 113 (73.2) |
| Yes | 237 957 (20.7) | 225 376 (21.5) | 223 285 (21.7) | 189 989 (26.8) |
| Contraception: | ||||
| No | 673 527 (58.6) | 611 978 (58.5) | 601 640 (58.6) | 465 248 (65.7) |
| Yes | 475 150 (41.4) | 434 233 (41.5) | 425 060 (41.4) | 242 854 (34.3) |
| Anticoagulants: | ||||
| No | 2 813 692 (95.5) | 2 455 434 (95.2) | 2 392 597 (95.1) | 1 544 641 (93.5) |
| Yes | 132 756 (4.5) | 124 573 (4.8) | 123 271 (4.9) | 107 831 (6.5) |
| Antidepressant treatment: | ||||
| No | 2 556 629 (86.8) | 2 222 691 (86.2) | 2 165 607 (86.1) | 1 397 733 (84.6) |
| Yes | 389 819 (13.2) | 357 316 (13.8) | 350 261 (13.9) | 254 739 (15.4) |
| Tranexamic acid: | ||||
| No | 1 137 176 (99.0) | 1 035 938 (99.0) | 1 016 703 (99.0) | 701 847 (99.1) |
| Yes | 11 501 (1.0) | 10 273 (1.0) | 9997 (1.0) | 6255 (0.9) |
| Oral corticosteroids: | ||||
| No | 2 810 256 (95.4) | 2 455 195 (95.2) | 2 393 249 (95.1) | 1 556 863 (94.2) |
| Yes | 136 192 (4.6) | 124 812 (4.8) | 122 619 (4.9) | 95 609 (5.8) |
| Epilepsy medication: | ||||
| No | 1 063 528 (92.6) | 969 199 (92.6) | 951 321 (92.7) | 651 465 (92.0) |
| Yes | 85 149 (7.4) | 77 012 (7.4) | 75 379 (7.3) | 56 637 (8.0) |
| NSAIDs: | ||||
| No | 801 144 (69.7) | 729 467 (69.7) | 715 586 (69.7) | 475 232 (67.1) |
| Yes | 347 533 (30.3) | 316 744 (30.3) | 311 114 (30.3) | 232 870 (32.9) |
| Numbers of specialist outpatient visits, median (IQR) | 1 (0-3) | 1 (0-3) | 1 (0-3) | 1 (0-3) |
| Days of inpatient stay, median (IQR) | 0 (0-0) | 0 (0-0) | 0 (0-0) | 0 (0-0) |
| Number of primary care visits, median (IQR) | 4 (1-12) | 4 (1-12) | 4 (1-13) | 5 (1-14) |
Data are number (percentage), unless otherwise stated. IQR=interquartile range; NSAIDs=Non-steroidal anti-inflammatory drugs.
Statistical analysis
Cox proportional hazards models with time varying exposure were used, where each woman’s follow-up time was divided according to her vaccination status (unvaccinated, first dose, second dose, and third dose), and then at each risk window (one to seven days and 8-90 days after each dose in the main analyses, and within days seven, 28, or 90 in the sensitivity analyses). Each individual was followed up from 27 December 2020 until the earliest of the outcome of interest, end of each risk window, or a censoring event (defined as receiving a second, third, or fourth dose of any vaccine, emigration, death, or end of study on 28 February 2022). An individual contributed person-time as unvaccinated until the first vaccination. After each vaccination dose, individuals contributed person-time in each corresponding risk window of interest (ie, exposed risk time). We also restricted analyses to the subpopulation where primary care data were available. Additionally, we performed sensitivity analyses limited to women without previous hormone treatment, and in women without a prior diagnosis of coagulation disease or a filled prescription for anticoagulants.
In the complementary analyses, to assess the risk for menstruation disorders at days seven, 28, or 90 after a covid-19 infection in unvaccinated women, each woman’s follow-up time was divided according to covid-19 infection status (no infection period and period after first positive SARS-CoV-2 test) and then at each risk window (within days 7, 28, or 90 after first positive test). Each woman was followed up from 1 August 2020 until the earliest of the outcome of interest, end of each risk window, or a censoring event (ie, emigration, death, or end of study on 26 December 2020).
Hazard ratios with 95% confidence intervals were estimated from Cox models. We report results from a crude model without any adjustment for covariates, and a full model adjusted for all covariates listed previously.
Patient and public involvement
Patients were not directly involved in the study. However, the rationale for the study was around 8000 (November 2022) reports of suspected adverse drug reactions regarding menstrual disturbances that were reported to the Swedish Medical Products Agency. Approximately 90% of the suspected adverse drug reactions were reported by consumers.
Results
Descriptive analyses
In total, 2 946 448 girls and women aged 12-74 years were included in the vaccination analyses. Of these, 2 580 007 (87.6%) received at least one SARS-CoV-2 vaccination before the end of follow-up on 28 February 2022. Among the vaccinated, 1 652 472 (64.0%) of 2 580 007 women received three doses, but this proportion varied by age (fig 1). Participants’ demographics and medical history are presented in table 1 and table S2 by vaccine status. Women can contribute with person-time to more than one vaccine status group.
Fig 1.
Cumulative proportion of vaccine uptake (up to four doses) in different age groups, between 1 January 2020 and 28 February 2022, among women in a Swedish population cohort. Vaccination started on 27 December 2020 for the oldest age group and patients at highest risk
More than 99% of menstrual disturbance (19 329/19 443 cases in the National Patient Register) or bleeding disorder diagnoses (9370/9407 cases) in the overall study population were from specialist outpatient care. In the subpopulation where primary care data were available (n=1 156 260, approximately 40% of the Swedish female population), about 11% (666/6207 cases) of the diagnoses reflecting premenopausal and postmenopausal bleeding, and 19% (2119/11 344 cases) of diagnoses of menstrual disturbance were recorded in primary healthcare. Crude annual rates of the outcomes during the study period of 2015-22 were of similar magnitude (supplement table S3).
For the analyses of menstruation or bleeding disorders after a positive SARS-CoV-2 test, 754 991 (25.7%) of 2 942 544 women tested positive for SARS-CoV-2 during the study period of 1 August 2020 to 26 December 2020.
Menstrual disturbance and bleeding disorders after vaccination
Postmenopausal bleeding
Adjusted hazard ratio comparing the risk for postmenopausal bleeding after vaccination with any dose compared with unvaccinated periods was 1.12 (95% confidence interval 1.00 to 1.25) in the one to seven days risk window and 1.14 (1.06 to 1.23) in the 8-90 days risk window (table 2, supplement figure S1). The impact of adjustment for covariates was modest. The highest risks were observed after the third dose, both in the one to seven days risk window (1.28 (1.01 to 1.62)) and the 8-90 days risk window (1.25 (1.04 to 1.50)). The precision of these estimates was overall good. The results from the subpopulation with primary care data showed similar pattern to the main analyses, but with generally lower risk estimates (table 3, supplement figure S2). After restriction to women without prior hormone treatment, increased risks were observed after the third dose in both risk windows, with slightly higher estimates than in the main analyses (table 2, supplement table S4). The strongest association was reported in the third dose in the one to seven days risk window (1.48 (1.12 to 1.94)); similar risks were also observed in the subpopulation with primary care data, most obviously for the second dose in the 8-90 days risk window (supplement table S4). Exclusion of women with prior coagulation disorders did not change the results notably compared with the main analyses (table 2, supplement table S5).
Table 2.
Hazard ratios (HR) with 95% confidence interval (CI) for menstruation disorders after each dose in one to seven days and 8-90 days risk windows, among women in a Swedish population cohort
| Risk windows | Person-years | Cases | Incidence rate (per 100 000 person-years) |
Crude model,* HR (95% CI) | Full model,†
HR (95% CI) |
|---|---|---|---|---|---|
| Postmenopausal bleeding (45-74 years, n=1 561 429) | |||||
| Unvaccinated | 646 133 | 3144 | 486.6 | ref | ref |
| Any dose: | |||||
| 1-7 days | 77 501 | 416 | 536.8 | 1.19 (1.06 to 1.33) | 1.12 (1.00 to 1.25) |
| 8-90 days | 665 572 | 3401 | 511.0 | 1.21 (1.13 to 1.29) | 1.14 (1.06 to 1.23) |
| Dose 1: | |||||
| 1-7 days | 27 379 | 166 | 606.3 | 1.20 (1.02 to 1.41) | 1.15 (0.98 to 1.35) |
| 8-90 days | 159 069 | 844 | 530.6 | 1.14 (1.04 to 1.25) | 1.08 (0.98 to 1.19) |
| Dose 2: | |||||
| 1-7 days | 27 216 | 122 | 448.3 | 1.06 (0.88 to 1.29) | 0.98 (0.81 to 1.19) |
| 8-90 days | 320 329 | 1561 | 487.3 | 1.22 (1.11 to 1.34) | 1.14 (1.03 to 1.25) |
| Dose 3: | |||||
| 1-7 days | 22 907 | 128 | 558.8 | 1.45 (1.14 to 1.84) | 1.28 (1.01 to 1.62) |
| 8-90 days | 186 174 | 996 | 535.0 | 1.40 (1.17 to 1.67) | 1.25 (1.04 to 1.50) |
| Menstrual disturbance (12-49 years, n=1 634 294) | |||||
| Unvaccinated | 1 067 762 | 9615 | 900.5 | ref | ref |
| Any dose: | |||||
| 1-7 days | 62 278 | 674 | 1082.2 | 1.41 (1.29 to 1.52) | 1.13 (1.04 to 1.23) |
| 8-90 days | 480 493 | 4970 | 1034.4 | 1.38 (1.32 to 1.44) | 1.06 (1.01 to 1.11) |
| Dose 1: | |||||
| 1-7 days | 26 034 | 288 | 1106.2 | 1.49 (1.32 to 1.68) | 1.26 (1.11 to 1.42) |
| 8-90 days | 147 296 | 1364 | 926.0 | 1.29 (1.21 to 1.37) | 1.07 (1.00 to 1.14) |
| Dose 2: | |||||
| 1-7 days | 24 969 | 250 | 1001.2 | 1.21 (1.06 to 1.37) | 1.04 (0.91 to 1.18) |
| 8-90 days | 281 999 | 2981 | 1057.1 | 1.33 (1.26 to 1.40) | 1.04 (0.98 to 1.10) |
| Dose 3: | |||||
| 1-7 days | 11 274 | 136 | 1206.3 | 1.34 (1.11 to 1.62) | 1.02 (0.84 to 1.23) |
| 8-90 days | 51 198 | 625 | 1220.8 | 1.43 (1.27 to 1.62) | 1.00 (0.89 to 1.13) |
| Premenopausal bleeding (12-49 years, n=1 634 294) | |||||
| Unvaccinated | 1 070 500 | 1865 | 174.2 | ref | ref |
| Any dose: | |||||
| 1-7 days | 62 625 | 133 | 212.4 | 1.44 (1.2 to 1.74) | 1.08 (0.90 to 1.30) |
| 8-90 days | 484 600 | 1002 | 206.8 | 1.43 (1.3 to 1.58) | 1.01 (0.91 to 1.12) |
| Dose 1: | |||||
| 1-7 days | 26 144 | 54 | 206.6 | 1.40 (1.06 to 1.85) | 1.14 (0.86 to 1.50) |
| 8-90 days | 148 118 | 273 | 184.3 | 1.32 (1.14 to 1.51) | 1.01 (0.88 to 1.16) |
| Dose 2: | |||||
| 1-7 days | 25 096 | 46 | 183.3 | 1.22 (0.90 to 1.65) | 0.96 (0.71 to 1.30) |
| 8-90 days | 284 736 | 608 | 213.5 | 1.45 (1.29 to 1.63) | 1.03 (0.92 to 1.17) |
| Dose 3: | |||||
| 1-7 days | 11 385 | 33 | 289.9 | 1.67 (1.13 to 2.49) | 1.14 (0.77 to 1.70) |
| 8-90 days | 51 745 | 121 | 233.8 | 1.32 (1.00 to 1.75) | 0.83 (0.63 to 1.10) |
Crude model included no covariates.
Full model included age, country of birth, employed as a healthcare worker, marital status, education, and health seeking behaviours during 2018-19 (ie, no. of primary care visits, number of specialist outpatient visits, and days of inpatient stay), and prior comorbidities and treatments listed in supplement table S1.
Table 3.
Hazard ratios (HR) with 95% confidence interval (CI) for menstrual disturbance and bleeding after each dose in one to seven days and 8-90 days risk windows in the subpopulation with primary care data (Stockholm region and Västra Götaland region, approximately 40% of total population), among women in a Swedish population cohort
| Risk windows | Person-years | Cases | Incidence rate (per 100 000 person-years) |
Crude model,* HR (95% CI) | Full model,† HR (95% CI) |
|---|---|---|---|---|---|
| Postmenopausal bleeding (45-74 years, n=590 271) | |||||
| Unvaccinated | 252 977 | 1345 | 531.7 | ref | ref |
| Any dose: | |||||
| 1-7 days | 28 623 | 175 | 611.4 | 1.26 (1.06 to 1.49) | 1.16 (0.97 to 1.37) |
| 8-90 days | 243 943 | 1287 | 527.6 | 1.15 (1.03 to 1.28) | 1.05 (0.94 to 1.17) |
| Dose 1: | |||||
| 1-7 days | 10 281 | 75 | 729.5 | 1.30 (1.02 to 1.66) | 1.23 (0.96 to 1.57) |
| 8-90 days | 60 233 | 311 | 516.3 | 1.04 (0.89 to 1.21) | 0.95 (0.81 to 1.11) |
| Dose 2: | |||||
| 1-7 days | 10 134 | 50 | 493.4 | 1.15 (0.85 to 1.56) | 1.02 (0.75 to 1.39) |
| 8-90 days | 119 097 | 597 | 501.3 | 1.21 (1.04 to 1.40) | 1.08 (0.93 to 1.25) |
| Dose 3: | |||||
| 1-7 days | 8209 | 50 | 609.1 | 1.41 (0.98 to 2.02) | 1.18 (0.82 to 1.69) |
| 8-90 days | 64 613 | 379 | 586.6 | 1.34 (1.03 to 1.74) | 1.13 (0.86 to 1.49) |
| Menstrual disturbance (12-49 years, n=664 201) | |||||
| Unvaccinated | 446 270 | 6092 | 1365.1 | ref | ref |
| Any dose: | |||||
| 1-7 days | 24 260 | 374 | 1 541.6 | 1.28 (1.15 to 1.43) | 1.11 (0.99 to 1.23) |
| 8-90 days | 188 275 | 2802 | 1 488.2 | 1.27 (1.20 to 1.34) | 1.06 (1.00 to 1.12) |
| Dose 1: | |||||
| 1-7 days | 10 331 | 169 | 1635.9 | 1.41 (1.21 to 1.65) | 1.25 (1.07 to 1.46) |
| 8-90 days | 61 602 | 813 | 1319.8 | 1.16 (1.07 to 1.26) | 1.03 (0.95 to 1.12) |
| Dose 2: | |||||
| 1-7 days | 9776 | 144 | 1473.0 | 1.15 (0.97 to 1.37) | 1.05 (0.88 to 1.24) |
| 8-90 days | 109 514 | 1701 | 1553.2 | 1.26 (1.18 to 1.35) | 1.07 (0.99 to 1.14) |
| Dose 3: | |||||
| 1-7 days | 4153 | 61 | 1468.7 | 1.03 (0.78 to 1.35) | 0.87 (0.66 to 1.15) |
| 8-90 days | 17 159 | 288 | 1678.4 | 1.28 (1.08 to 1.51) | 1.00 (0.85 to 1.19) |
| Premenopausal bleeding (12-49 years, n=664 201) | |||||
| Unvaccinated | 449 008 | 1210 | 269.5 | ref | ref |
| Any dose: | |||||
| 1-7 days | 24 459 | 75 | 306.6 | 1.33 (1.04 to 1.69) | 1.00 (0.78 to 1.28) |
| 8-90 days | 190 173 | 603 | 317.1 | 1.39 (1.23 to 1.57) | 0.99 (0.87 to 1.13) |
| Dose 1: | |||||
| 1-7 days | 10 398 | 32 | 307.8 | 1.37 (0.96 to 1.96) | 1.13 (0.79 to 1.61) |
| 8-90 days | 62 149 | 162 | 260.7 | 1.21 (1.01 to 1.45) | 0.95 (0.79 to 1.14) |
| Dose 2: | |||||
| 1-7 days | 9852 | 22 | 223.3 | 0.92 (0.60 to 1.42) | 0.73 (0.47 to 1.13) |
| 8-90 days | 110 609 | 371 | 335.4 | 1.44 (1.24 to 1.67) | 1.04 (0.89 to 1.22) |
| Dose 3: | |||||
| 1-7 days | 4209 | 21 | 498.9 | 1.62 (0.99 to 2.66) | 1.15 (0.70 to 1.88) |
| 8-90 days | 17 414 | 70 | 402.0 | 1.27 (0.90 to 1.80) | 0.83 (0.59 to 1.17) |
Crude model included no covariates.
Full model included age, country of birth, employed as a healthcare worker, marital status, education, and health seeking behaviours during 2018-19 (ie, no. of primary care visits, no. of specialist outpatient visits, and days of inpatient stay), and prior comorbidities and treatments listed in supplement table S1.
Product specific risk estimates for postmenopausal bleeding
Analyses of associations from the full model with individual vaccine products suggested an increased risk of 41% (one to seven days) and 23% (8-90 days) with BNT162b2 after the third dose, as well as 14% increased risk during the 8-90 days risk window after the second dose (table 4, supplement figure S3). No increased risk was observed after the first dose with BNT162b2. For mRNA-1273, risk increased by 33% after the third dose in the 8-90 days risk window. The risk estimates for mRNA-1273 and ChAdOx1 nCoV-19 were overall imprecise (table 4, supplement figure S3).
Table 4.
Hazard ratios (HR) with 95% confidence interval (CI) for postmenopausal bleeding after each dose in one to seven days and 8-90 days risk windows, stratified by vaccine product, among women in a Swedish population cohort
| Risk windows | Person-years | Cases | Incidence rate (per 100 000 person-years) |
Crude model,* HR (95% CI) | Full model,† HR (95% CI) |
|---|---|---|---|---|---|
| BNT162b2 (Pfizer-BioNTech) | |||||
| Unvaccinated | 646 760 | 3144 | 486.1 | ref | ref |
| Dose 1: | |||||
| 1-7 days | 20 466 | 120 | 586.3 | 1.16 (0.96 to 1.40) | 1.09 (0.90 to 1.32) |
| 8-90 days | 103 775 | 532 | 512.6 | 1.11 (0.99 to 1.24) | 1.01 (0.90 to 1.14) |
| Dose 2: | |||||
| 1-7 days | 21 006 | 101 | 480.8 | 1.13 (0.92 to 1.40) | 1.02 (0.83 to 1.26) |
| 8-90 days | 247 223 | 1240 | 501.6 | 1.24 (1.13 to 1.37) | 1.14 (1.04 to 1.26) |
| Dose 3: | |||||
| 1-7 days | 15 668 | 95 | 606.3 | 1.59 (1.23 to 2.06) | 1.41 (1.09 to 1.83) |
| 8-90 days | 138 714 | 724 | 521.9 | 1.36 (1.13 to 1.63) | 1.23 (1.02 to 1.49) |
| mRNA-1273 (Moderna) | |||||
| Unvaccinated | 646 760 | 3144 | 486.1 | ref | ref |
| Dose 1: | |||||
| 1-7 days | 2612 | 18 | 689.2 | 1.44 (0.90 to 2.03) | 1.33 (0.84 to 2.13) |
| 8-90 days | 13 911 | 73 | 524.8 | 1.24 (0.97 to 1.58) | 1.13 (0.88 to 1.44) |
| Dose 2: | |||||
| 1-7 days | 2691 | 5 | 185.8 | 0.45 (0.19 to 1.08) | 0.41 (0.17 to 0.99) |
| 8-90 days | 31 409 | 150 | 477.6 | 1.23 (1.02 to 1.48) | 1.12 (0.92 to 1.35) |
| Dose 3: | |||||
| 1-7 days | 7238 | 33 | 455.9 | 1.17 (0.80 to 1.72) | 1.04 (0.71 to 1.53) |
| 8-90 days | 47 539 | 272 | 572.2 | 1.53 (1.22 to 1.91) | 1.33 (1.06 to 1.67) |
| ChAdOx1 nCoV-19 (AstraZeneca) | |||||
| Unvaccinated | 646 760 | 3144 | 486.1 | ref | ref |
| Dose 1: | |||||
| 1-7 days | 4429 | 28 | 632.2 | 1.14 (0.78 to 1.66) | 1.24 (0.85 to 1.81) |
| 8-90 days | 41 414 | 239 | 577.1 | 1.16 (1.01 to 1.34) | 1.17 (1.01 to 1.35) |
| Dose 2: | |||||
| 1-7 days | 3518 | 16 | 454.8 | 1.27 (0.76 to 2.11) | 1.21 (0.73 to 2.02) |
| 8-90 days | 41 671 | 171 | 410.4 | 1.17 (0.95 to 1.43) | 1.14 (0.92 to 1.40) |
Crude model included no covariates.
Full model included age, country of birth, employed as a healthcare worker, marital status, education, and health seeking behaviours during 2018-19 (ie, no. of primary care visits, no. of specialist outpatient visits, and days of inpatient stay), and prior comorbidities and treatments listed in supplement table S1.
Menstrual disturbance
The adjusted hazard ratio for menstrual disturbance after vaccination with any dose compared with unvaccinated periods was 1.13 (95% confidence interval 1.04 to 1.23) in the one to seven days risk window and 1.06 (1.01 to 1.11) in the 8-90 days risk window. Adjustment for covariates strongly attenuated or almost completely removed the weak associations noted in the dose specific crude analyses (table 2, supplement figure S1). The strongest adjusted association observed was a 26% increased risk of menstrual disturbance among women aged 12-49 years in the one to seven days risk window (1.26 (1.11 to 1.42)) after the first dose. The precision of these estimates was good overall. The results from the subpopulation with primary care data were largely similar to the main analyses (table 3, supplement figure S2). Similarly, product specific risk estimates were largely consistent with the overall risk estimates (table S6, supplement figure S3).
Premenopausal bleeding
The adjusted hazard ratio for premenopausal bleeding after vaccination with any dose compared with unvaccinated periods was 1.08 (95% confidence interval 0.90 to 1.30) in the one to seven days risk windows and 1.01 (0.91 to 1.12) for the 8-90 days risk windows. Adjustment for covariates almost completely removed the associations reported in the crude analyses (table 2, supplement figure S1). The estimates were more imprecise compared with the other outcomes because of fewer observed events. The strongest associations observed, although not significant, were a 14% increased risk in the one to seven days risk window both after the first dose (1.14 (0.86 to 1.50)) and the third dose (1.14 (0.77 to 1.70)). No increased risk was observed after the second dose (0.96 (0.71 to 1.30)) in the corresponding risk window. Again, similar results were observed in the subpopulation with primary care data but with even wider confidence intervals (table 3, supplement figure S4). Product specific risk estimates did not show any clearly increased risks and were very imprecise (table S7, supplement figure S3). In supplement table S8, we show menstruation disorders in the subpopulation with primary care data after each dose within the risk window at days seven, 28, or 90.
Menstruation and bleeding disorders after a positive SARS-CoV-2 test
The risk for the three outcomes was reduced during the first seven days after a positive test (supplement table S9). However, within 90 days, the risk weakly increased, most notably for postmenopausal bleeding (hazard ratio 1.28 (95% confidence interval 0.88 to 1.86)) and premenopausal bleeding (1.45 (0.91 to 2.32)). Of note, the number of cases of premenopausal bleeding was very low. A similar pattern was observed in the subpopulation with primary care data, with slightly higher point estimates for postmenopausal bleeding (supplement table S10).
Discussion
In this large population-based study of nearly three million women, we observed weak but reasonably precise associations between SARS-CoV-2 vaccination and healthcare contacts for postmenopausal bleeding. Increased risk was observed after the second and third dose in the 8-90 days risk window and was of similar size in the one to seven days risk window after a third dose. This pattern is somewhat unexpected for a causal association. Analyses of associations with individual vaccine products and risk of postmenopausal bleeding provided results that suggest an increased risk with BNT162b2 and mRNA-1273 after the third dose, but suggest a less clear association with ChAdOx1 nCoV-19.
For menstrual disturbance, adjustment for covariates almost completely removed the associations found after vaccination in the crude estimates, and only a weak association remained after the first dose, limited to the one to seven days risk window. Considering the characteristics of this condition, and that the change is measured based on encounters with specialist healthcare in this study, a causal effect limited to this risk window is unlikely.
The number of healthcare contacts for the outcome of premenstrual bleeding were fewer, and risk estimates after vaccination consequently more imprecise. The risk was also notably attenuated by adjustment for covariates and overall did not support an association with SARS-CoV-2 vaccination.
The risk of the three outcomes did not substantially increase after covid-19, although point estimates for postmenopausal bleeding were increased in the 90 day risk window after infection.
Strengths and weaknesses
The main strengths of our study include the population-based cohort design, large sample size, near complete follow-up, and independent ascertainment of data for SARS-CoV-2 vaccinations and healthcare contacts from nationwide registers with mandatory reporting, in a setting with a universal, tax financed healthcare system. We have adjusted for socioeconomic factors, previous healthcare use, and for several specific medical conditions, including diagnosis of obesity and chronic obstructive pulmonary disease. We have no direct information on ease of access to healthcare, body mass index, or smoking. With a possible exception for postmenopausal bleeding, healthcare contacts for menstrual disorders might have a modest sensitivity. Also, we have no information on whether the healthcare contact was a planned or an acute visit. Time from first symptoms to healthcare contact is probably longer for women with menstrual disturbances and bleeding before menopause than for women after menopausal who have bleeding. Use of the date of healthcare contact for these conditions does not mean that the date of onset of the condition is analysed. The time between onset, start of symptoms, and date of healthcare contact might thus be considerable, making the interpretation of effect of different risk windows challenging. Hence, we might also, especially for menstrual disturbances and premenopausal bleeding, catch some prevalent (before exposure) cases, especially in the one to seven day time window analysed. We are unable to acquire the point in time when a woman enters menopause. Hence, we rely on the physician using the correct codes from the International Statistical Classification of Diseases and Related Health Problems for defining premenopausal bleeding or postmenopausal bleeding. Reverse causation, where women get vaccinated before a planned healthcare contact, is also an issue. Also, women with an ongoing covid-19 infection will probably cancel or postpone planned or semi-acute healthcare contacts.
Other studies and supportive data
The concern for an association between SARS-CoV-2 vaccination and menstrual or bleeding disturbances in women has been triggered by the large number of spontaneous case reports related to such conditions.1 2 3 10 Also, several studies on self-reported menstruation cycles changes after SARS-CoV-2 vaccination have been published.4 5 6 7 8 9 27 28 The European Medicines Agency has recommended that heavy menstrual bleeding should be acknowledged as a side effect of both SARS-CoV-2 mRNA vaccines.12 However, European Medicines Agency considered that the available data do not support causal association between SARS-CoV-2 mRNA vaccines and absence of menstruation.12 The results from the present study are not necessarily contradictive of this labelling, which was mainly based on self-reported survey data and spontaneous case reports. This type of data can be prone to recall bias. Self-reporting might also obtain events that normally would not result in a healthcare contact but might still be sufficiently disturbing to be relevant for the affected women. Self-reporting, as well as health seeking behaviour, can be stimulated by media attention.10 29 To the best of our knowledge, no previous large observational study has assessed an association between SARS-CoV-2 vaccination and healthcare contacts for menstrual or bleeding disorders using independent ascertainment of both exposure and outcome.
No clear and specific mechanistic explanation allows for this type of association or supports a general such association with vaccines. 30 31 An unspecific activation of the immune system might trigger menstruation effects.11 Two studies based on self-reported data have reported some associations between human papillomavirus vaccines and menstruation effects.13 14 However, a large population-based study found no association between human papillomavirus vaccination and primary ovarian insufficiency.15 Menstrual effects are not labelled in any of the influenza vaccines or hepatitis A or B vaccines used in the European Union at present.13 14 15
Conclusions
We observed weak and inconsistent associations between SARS-CoV-2 vaccination and healthcare contacts for postmenopausal bleeding, and even less consistent for menstrual disturbance, and premenstrual bleeding. Extensive adjustment for confounding attenuated most risk estimates. The patterns of association are not consistent with a causal effect. These findings do not provide any substantial support for a causal association between SARS-CoV-2 vaccination and healthcare contacts related to menstrual or bleeding disorders.
What is already known?
Large numbers of spontaneous case reports report menstrual disturbance after SARS-CoV-2 vaccination
Studies that used self-reported data indicate menstrual cycle changes after SARS-CoV-2 vaccination
What this study adds
No evidence of an increased risk of healthcare contacts for menstrual disturbances or before menopausal bleeding in a cohort of nearly three million women using independent ascertainment of both SARS-CoV-2 vaccination and healthcare contacts
Postmenopausal bleeding and contacts with healthcare had a weak association, but with a pattern that is not expected for a hypothesised underlying causal association between vaccines and postmenopausal bleeding
Web extra.
Extra material supplied by authors
Web appendix: Online appendix
Funding: This study was funded by the SciLifeLab National Covid-19 Research Program, financed by the Knut and Alice Wallenberg Foundation (grants KAW 2021-0010/VC2021.0018 and KAW 2020.0299/VC 2022.0008), and the Swedish Research Council (grants 2021-05045 and 2021-05450). The SCIFI-PEARL study also has basic funding from grants given by the Swedish state under the agreement between the Swedish government and the county councils, the ALF agreement (grants ALFGBG-938453, ALFGBG-971130, ALFGBG-978954,), and from FORMAS (Research Council for Environment, Agricultural Sciences and Spatial Planning), a Swedish Research Council for Sustainable Development (grant 2020-02828). The funders had no role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the article for publication. The researchers are independent from the funders. All authors had full access to all the data, including statistical reports and tables, in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: MG reports personal fees from AstraZeneca, Gilead, GSK/ViiV, MSD, Biogen, Novocure, Amgen, Novo Nordisk, outside the submitted work. SL reports consulting for Scandinavian Biopharma and is an employee of AstraZeneca since 16 January 2023. The work in this article was performed before this employment commenced. FN reports prior employment at AstraZeneca until 2019, and ownership of some AstraZeneca shares. MB and YX declare no competing interests. AS reported participating in research funded by governmental agencies, universities, Astellas Pharma, Janssen Biotech, AstraZeneca, Pfizer, Roche, (then) Abbott Laboratories, (then) Schering-Plough, UCB Nordic, and Sobi, with all funds paid to Karolinska Institutet, outside of the submitted work. RL reported receiving grants from Sanofi Aventis paid to his institution outside the submitted work; and receiving personal fees from Pfizer outside of the submitted work.
FN, the lead author, affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned have been explained.
Dissemination to participants and related patient and public communities: We plan to disseminate these research findings to relevant stakeholders by presenting our findings at relevant conferences, by sharing the findings with the European Medicines Agency, the Public Health Agency of Sweden, and other national and international public health and regulatory agencies. Additionally we plan on making press releases to national and international media, as well as making plain language summaries available on the homepages of the Swedish Medical Products Agency and Gothenburg University.
Provenance and peer review: Not commissioned, externally peer reviewed.
Ethics statements
Ethical approval
The study obtained ethics approval from the Swedish Ethical Review Authority (2020-01800, 2020-05829, 2021-00267, 2021-00829, 2021-02106, 2021-04098, 2022-00500-02, 2022-01207-02, 2022-03323-02). Consent to participate is not applicable because this study is register based.
Data availability statement
Access to similar data requires permission. Apart from ethical approval from the Swedish Ethical Review Authority, researchers will also need approval from each register holder.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Web appendix: Online appendix
Data Availability Statement
Access to similar data requires permission. Apart from ethical approval from the Swedish Ethical Review Authority, researchers will also need approval from each register holder.