RESEARCH

Rickard Ljung,1,2 YiYi Xu,3 Anders Sundström,1 Susannah Leach,4,5 Ebba Hallberg,1Maria Bygdell,6 Maria Larsson,1 Veronica Arthurson,1 Magnus Gisslén,7,8 Rolf Gedeborg,9,10
Fredrik Nyberg3
For numbered affiliations see
end of the article
Correspondence to: R Ljung
rickard.ljung@lakemedelsverket.
se(ORCID 0000-0002-0654-4530)
Additional material is published
online only. To view please visit
the journal online.
Cite this as: BMJ 2023;381:e074778
http://dx.doi.org/10.1136/
bmj‑2023‑074778

Accepted: 27 March 2023

Abstract
Objectives
To evaluate the risks of any menstrual disturbance andbleeding following SARS-CoV-2 vaccination in women
who are premenopausal or postmenopausal.
DesignA 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 menstruationor 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 sevendays, considered the control period, and 8-90 days).
Main outcome measures
Healthcare contact (admission to hospital or visit)
for menstrual disturbance or bleeding before orafter menopause (diagnosed with the International
Statistical Classification of Diseases and Related

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 andhealthcare 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
the bmj | BMJ 2023;381:e074778 | doi: 10.1136/bmj-2023-074778

Health Problems, Tenth Revision codes N91, N92,
N93, N95).
Results
2 580 007 (87.6%) of 2 946 448 women received atleast 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. Riskof postmenopausal bleeding suggested a 23-33%
increased risk after 8-90 days with BNT162b2 andmRNA-1273 after the third dose, but the association
with ChAdOx1 nCoV-19 was less clear. For menstrual
disturbance or bleeding in women who werepremenopausal, adjustment for covariates almost
completely removed the weak associations noted in
the crude analyses.
Conclusions
Weak and inconsistent associations wereobserved between SARS-CoV-2 vaccination andhealthcare contacts for bleeding in women who
are postmenopausal, and even less evidence wasrecorded of an association for menstrual disturbanceor bleeding in women who were premenopausal.
These findings do not provide substantial support fora causal association between SARS-CoV-2 vaccinationand 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 disturbanceafter SARS-CoV-2 vaccination via their respective
pharmacovigilance systems.1-3
Several studies on self-reported menstruation cycles
after SARS-CoV-2 vaccination, from survey data anda menstrual cycle tracking app, indicate changes inmenstruation cycles.4-9 A link between SARS-CoV-2
vaccination and menstrual disturbance has also
1

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Association between SARS-CoV-2 vaccination and healthcare
contacts for menstrual disturbance and bleeding in women
before and after menopause: nationwide, register based cohort
study

RESEARCH

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 thelarger 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 fromthe national patient register and drug history forprescription drugs from 1 January2018 from thenational 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 patientsliving at special care facilities or receiving home careservices 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 from2

the national vaccination register.23 Positive resultsfrom 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 asrisk of menstruation disorders. In Sweden, womenwith gynaecological issues will often, especially inurban areas, turn directly to gynaecological specialistcare. 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 Götalandregion), diagnoses were additionally obtained fromregional primary healthcare registers. The date andcause of death were obtained from the register of
the total population and the national cause of deathregister.25 26

Study population
The study included all women aged 12-74 years
who were residing in Sweden on 1 January 2018 (toensure previous comorbidities are accounted for), andstill 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 1274)) until 31 December 2020, and individuals who
were pregnant or had a history of any menstruation
disorders, breast cancer, cancer of the female genitalorgans, 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 ofany vaccine, and several different risk periods wereapplied. 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 themprovides 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 anacute 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 thedoi: 10.1136/bmj-2023-074778 | BMJ 2023;381:e074778 | the bmj

BMJ: first published as 10.1136/bmj-2023-074778 on 3 May 2023. Downloaded from http://www.bmj.com/ on 28 May 2023 by guest. Protected by copyright.

been widely discussed on social media.10 However,
menstrual cycles vary naturally and minor menstrual
disturbances are generally not considered to be ofclinical importance. Changes can, however, generateconsiderable distress in the affected women, especiallyduring 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 inthe 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 othervaccines (eg, against human papillomavirus), but nosuch association was established.13-15
Pharmacovigilance systems relying on self-reportingare 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 whatis detected in clinical trials, individual level data fromlarge observational studies are needed.16
In a nationwide cohort study in Sweden, we
evaluated the risks of menstrual disturbance andbleeding after SARS-CoV-2 vaccination in women who
were before or after menopause. High quality data fromnationwide registers enabled us to evaluate the risk by
vaccine product and vaccination dose number.

RESEARCH

Covariates
Age, median (IQR)
Employed as a healthcare worker:
No
YesCountry of birth:
SwedenOutside Sweden
Education:
Primary
Secondary
Tertiary
Unknown
Cardiovascular disease:No
Yes
Stroke or transient ischaemic attack:No
Yes
Diabetes (type 1 and 2):
No
Yes
Chronic pulmonary disease:
No
Yes
Asthma:No
Yes
Chronic kidney disease:
No
Yes
Cancer:No
Yes
Coagulation disorders:No
Yes
Polycystic ovary syndrome:No
Yes
Thyroid diseases:
No
Yes
Pituitary disorders:No
Yes
Uterine polyps or fibroids:
No
Yes
Endometriosis:
No
Yes
Pelvic inflammatory diseases:
No
Yes
Obesity:No
Yes
Autoimmune diseases:
No
Yes
Menopausal hormone:No
Yes
Contraception:No

Baseline (all unvaccinated)(n=2 946 448)
44 (24-58)

At least one dose
(n=2 580 007)
46 (25-59)

At least two doses(n=2 515 868)
46 (26-59)

Three doses and more
(n=1 652 472)
53 (41-63)

2 018 128 (68.5)
928 320 (31.5)

1 740 484 (67.5)
839 523 (32.5)

1 690 984 (67.2)
824 884 (32.8)

1 057 348 (64.0)
595 124 (36.0)

2 383 529 (80.9)
562 919 (19.1)

2 153 373 (83.5)
426 634 (16.5)

2 107 976 (83.8)
407 892 (16.2)

1 432 112 (86.7)
220 360 (13.3)

416 303 (14.1)
1 076 764 (36.5)
1 077 071 (36.6)
376 310 (12.8)

354 647 (13.7)
957 364 (37.1)
989 890 (38.4)
278 106 (10.8)

342 635 (13.6)
940 376 (37.4)
978 262 (38.9)
254 595 (10.1)

204 655 (12.4)
689 049 (41.7)
743 930 (45)14 838 (0.9)

2 850 349 (96.7)
96 099 (3.3)

2 491 633 (96.6)
88 374 (3.4)

2 428 912 (96.5)
86 956 (3.5)

1 580 841 (95.7)
71 631 (4.3)

2 927 167 (99.3)
19 281 (0.7)

2 562 162 (99.3)
17 845 (0.7)

2 498 227 (99.3)
17 641 (0.7)

1 637 146 (99.1)
15 326 (0.9)

2 835 636 (96.2)
110 812 (3.8)

2 477 521 (96.0)
102 486 (4.0)

2 414 737 (96.0)
101 131 (4.0)

1 568 459 (94.9)
84 013 (5.1)

2 928 408 (99.4)
18 040 (0.6)

2 563 464 (99.4)
16 543 (0.6)

2 499 620 (99.4)
16 248 (0.6)

1 638 670 (99.2)
13 802 (0.8)

2 877 204 (97.6)
69 244 (2.4)

2 518 549 (97.6)
61 458 (2.4)

2 456 384 (97.6)
59 484 (2.4)

1 615 853 (97.8)
36 619 (2.2)

2 908 552 (98.7)
37 896 (1.3)

2 546 491 (98.7)
33 516 (1.3)

2 483 198 (98.7)
32 670 (1.3)

1 629 523 (98.6)
22 949 (1.4)

2 886 227 (98.0)
60 221 (2.0)

2 523 106 (97.8)
56 901 (2.2)

2 459 511 (97.8)
56 357 (2.2)

1 602 926 (97.0)
49 546 (3.0)

1 139 856 (99.2)
8821 (0.8)

1 038 321 (99.2)
7890 (0.8)

1 018 983 (99.2)
7717 (0.8)

702 468 (99.2)
5634 (0.8)

1 139 698 (99.2)
8979 (0.8)

1 038 724 (99.3)
7487 (0.7)

1 019 459 (99.3)
7241 (0.7)

704 123 (99.4)
3979 (0.6)

2 728 628 (92.6)
217 820 (7.4)

2 380 747 (92.3)
199 260 (7.7)

2 319 269 (92.2)
196 599 (7.8)

1 494 707 (90.5)
157 765 (9.5)

1 142 025 (99.4)
6652 (0.6)

1 040 378 (99.4)
5833 (0.6)

1 020 982 (99.4)
5718 (0.6)

704 115 (99.4)
3987 (0.6)

1 119 516 (97.5)
29 161 (2.5)

1 020 167 (97.5)
26 044 (2.5)

1 001 063 (97.5)
25 637 (2.5)

688 302 (97.2)
19 800 (2.8)

913 984 (79.6)
234 693 (20.4)

837 134 (80.0)
209 077 (20.0)

821 956 (80.1)
204 744 (19.9)

566 195 (80.0)
141 907 (20.0)

1 052 420 (91.6)
96 257 (8.4)

963 202 (92.1)
83 009 (7.9)

946 222 (92.2)
80 478 (7.8)

658 303 (93.0)
49 799 (7.0)

2 898 410 (98.4)
48 038 (1.6)

2 537 952 (98.4)
42 055 (1.6)

2 475 086 (98.4)
40 782 (1.6)

1 624 829 (98.3)
27 643 (1.7)

2 883 402 (97.9)
63 046 (2.1)

2 522 085 (97.8)
57 922 (2.2)

2 458 815 (97.7)
57 053 (2.3)

1 606 176 (97.2)
46 296 (2.8)

910 720 (79.3)
237 957 (20.7)

820 835 (78.5)
225 376 (21.5)

803 415 (78.3)
223 285 (21.7)

518 113 (73.2)
189 989 (26.8)

673 527 (58.6)

611 978 (58.5)

601 640 (58.6)

465 248 (65.7)

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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(Continued)

the bmj | BMJ 2023;381:e074778 | doi: 10.1136/bmj-2023-074778

3

RESEARCH

Table 1 | Continued
Baseline (all unvaccinated)(n=2 946 448)
475 150 (41.4)

At least one dose
(n=2 580 007)
434 233 (41.5)

At least two doses(n=2 515 868)
425 060 (41.4)

Three doses and more
(n=1 652 472)
242 854 (34.3)

2 813 692 (95.5)
132 756 (4.5)

2 455 434 (95.2)
124 573 (4.8)

2 392 597 (95.1)
123 271 (4.9)

1 544 641 (93.5)
107 831 (6.5)

2 556 629 (86.8)
389 819 (13.2)

2 222 691 (86.2)
357 316 (13.8)

2 165 607 (86.1)
350 261 (13.9)

1 397 733 (84.6)
254 739 (15.4)

1 137 176 (99.0)
11 501 (1.0)

1 035 938 (99.0)
10 273 (1.0)

1 016 703 (99.0)
9997 (1.0)

701 847 (99.1)
6255 (0.9)

2 810 256 (95.4)
136 192 (4.6)

2 455 195 (95.2)
124 812 (4.8)

2 393 249 (95.1)
122 619 (4.9)

1 556 863 (94.2)
95 609 (5.8)

1 063 528 (92.6)
85 149 (7.4)

969 199 (92.6)
77 012 (7.4)

951 321 (92.7)
75 379 (7.3)

651 465 (92.0)
56 637 (8.0)

801 144 (69.7)
347 533 (30.3)
1 (0-3)0 (0-0)4 (1-12)729 467 (69.7)
316 744 (30.3)
1 (0-3)0 (0-0)4 (1-12)715 586 (69.7)
311 114 (30.3)
1 (0-3)0 (0-0)4 (1-13)475 232 (67.1)
232 870 (32.9)
1 (0-3)0 (0-0)5 (1-14)

Data are number (percentage), unless otherwise stated. IQR=interquartile range; NSAIDs=Non-steroidal anti-inflammatory drugs.

Cumulative proportion

individual to get an appointment, including a potential
additional interval in getting an appointment with agynaecologist. 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 specificvaccine brands used in Sweden, BNT162b2 (Pfizer-

1.0

12-24 years

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

25-49 years

One dose
Two doses
Three doses
Four doses

0.8
0.6
0.4
0.2

Cumulative proportion0
1.0

50-64 years

65-74 years

0.8
0.6
0.4
0.2
0
Jan
2021

Apr
2021

Jul
2021

Oct
2021

Jan
2022

Apr
2022
Time (years)

Jan
2021

Apr
2021

Jul
2021

Oct
2021

Jan
2022

Apr
2022
Time (years)

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 risk4

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Covariates
Yes
Anticoagulants:
No
Yes
Antidepressant treatment:
No
Yes
Tranexamic acid:No
Yes
Oral corticosteroids:
No
Yes
Epilepsy medication:No
Yes
NSAIDs:No
Yes
Numbers of specialist outpatient visits, median (IQR)
Days of inpatient stay, median (IQR)
Number of primary care visits, median (IQR)

RESEARCH

Risk windows
Person-years
Cases
Postmenopausal bleeding (45-74 years, n=1 561 429)
Unvaccinated646 1333144
Any dose:
1-7 days
77 501416
8-90 days
665 572
3401
Dose 1:27 379166
1-7 days
8-90 days
159 069
844
Dose 2:
1-7 days
27 216122
8-90 days
320 329
1561
Dose 3:
1-7 days
22 907128
186 174996
8-90 days
Menstrual disturbance (12-49 years, n=1 634 294)
Unvaccinated
1 067 762
9615
Any dose:
62 278674
1-7 days
8-90 days
480 493
4970
Dose 1:
1-7 days
26 034288
8-90 days
147 296
1364
Dose 2:
1-7 days
24 969250
8-90 days
281 999
2981
Dose 3:
1-7 days
11 274136
8-90 days
51 198625
Premenopausal bleeding (12-49 years, n=1 634 294)
Unvaccinated1 070 500
1865
Any dose:
1-7 days
62 625133
8-90 days
484 600
1002
Dose 1:
1-7 days
26 14454
8-90 days
148 118
273
Dose 2:
1-7 days
25 09646
8-90 days
284 736
608
Dose 3:
1-7 days
11 38533
8-90 days
51 745
121

Incidence rate (per
100 000 person-years)

Crude model,* HR(95% CI)

Full model,†HR (95% CI)

486.6

ref

ref

536.8
511.0

1.19 (1.06 to 1.33)
1.21 (1.13 to 1.29)

1.12 (1.00 to 1.25)
1.14 (1.06 to 1.23)

606.3
530.6

1.20 (1.02 to 1.41)
1.14 (1.04 to 1.25)

1.15 (0.98 to 1.35)
1.08 (0.98 to 1.19)

448.3
487.3

1.06 (0.88 to 1.29)
1.22 (1.11 to 1.34)

0.98 (0.81 to 1.19)
1.14 (1.03 to 1.25)

558.8
535.0

1.45 (1.14 to 1.84)
1.40 (1.17 to 1.67)

1.28 (1.01 to 1.62)
1.25 (1.04 to 1.50)

900.5

ref

ref

1082.21034.4

1.41 (1.29 to 1.52)
1.38 (1.32 to 1.44)

1.13 (1.04 to 1.23)
1.06 (1.01 to 1.11)

1106.2926.0

1.49 (1.32 to 1.68)
1.29 (1.21 to 1.37)

1.26 (1.11 to 1.42)
1.07 (1.00 to 1.14)

1001.21057.1

1.21 (1.06 to 1.37)
1.33 (1.26 to 1.40)

1.04 (0.91 to 1.18)
1.04 (0.98 to 1.10)

1206.31220.81.34 (1.11 to 1.62)
1.43 (1.27 to 1.62)

1.02 (0.84 to 1.23)
1.00 (0.89 to 1.13)

174.2

ref

ref

212.4
206.8

1.44 (1.2 to 1.74)
1.43 (1.3 to 1.58)

1.08 (0.90 to 1.30)
1.01 (0.91 to 1.12)

206.6
184.3

1.40 (1.06 to 1.85)
1.32 (1.14 to 1.51)

1.14 (0.86 to 1.50)
1.01 (0.88 to 1.16)

183.3
213.5

1.22 (0.90 to 1.65)
1.45 (1.29 to 1.63)

0.96 (0.71 to 1.30)
1.03 (0.92 to 1.17)

289.9
233.8

1.67 (1.13 to 2.49)
1.32 (1.00 to 1.75)

1.14 (0.77 to 1.70)
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 201819 (ie, no. of primary care visits, number of specialist outpatient visits, and days of inpatient stay), and prior comorbidities and treatments listed insupplement table S1.

region and Västra Götaland region), where regional
primary healthcare data were also available.
To contextualise the results, we also estimated therisk 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, anddid not have the previously mentioned comorbidities
within five years before August 2020. We also studied
the risk of menstruation disorders during follow-up atdays seven, 28, and 90 after the first positive test resultof SARS-CoV-2 infection.
the bmj | BMJ 2023;381:e074778 | doi: 10.1136/bmj-2023-074778

Outcomes
We studied three different menstruation disorders
in different restricted age ranges (defined to include
premenopausal or postmenopausal women whenrelevant for the respective outcomes). We identified
only incident cases by using the first recording of a
primary diagnosis, according to the Swedish clinicalmodification of the 10th revision of the International
Statistical Classification of Diseases and Related
Health Problems (ICD-10-SE), in one of the registers todefine the outcome. Hence, outcomes were based ona healthcare contact (admission to hospital or visit)
where a physician registered any of the diagnoses
under study. All healthcare contacts with any of thediagnoses under study were included in the analyses
including primary care, regardless of whether thesecontacts were related to a physician or other healthcare
5

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Table 2 | Hazard ratios (HR) with 95% confidence interval (CI) for menstruation disorders after each dose in one to sevendays and 8-90 days risk windows, among women in a Swedish population cohort

RESEARCH

Risk windows
Person-years
Postmenopausal bleeding (45-74 years, n=590 271)
Unvaccinated
252 977
Any dose:
1-7 days
28 6238-90 days
243 943
Dose 1:
10 281
1-7 days
8-90 days
60 233
Dose 2:
1-7 days
10 1348-90 days
119 097
Dose 3:
1-7 days
8209
64 6138-90 days
Menstrual disturbance (12-49 years, n=664 201)
Unvaccinated446 270
Any dose:
24 260
1-7 days
8-90 days
188 275
Dose 1:
1-7 days
10 3318-90 days
61 602
Dose 2:
1-7 days9776
8-90 days
109 514
Dose 3:
1-7 days4153
8-90 days
17 159Premenopausal bleeding (12-49 years, n=664 201)
Unvaccinated449 008
Any dose:
1-7 days
24 4598-90 days
190 173
Dose 1:
1-7 days
10 3988-90 days
62 149Dose 2:
1-7 days9852
8-90 days
110 609
Dose 3:
1-7 days4209
8-90 days
17 414

Cases

Incidence rate
(per 100 000 person-years)

Crude model,* HR (95% CI)

Full model,† HR (95% CI)

1345

531.7

ref

ref

175
1287

611.4
527.6

1.26 (1.06 to 1.49)
1.15 (1.03 to 1.28)

1.16 (0.97 to 1.37)
1.05 (0.94 to 1.17)

75
311

729.5
516.3

1.30 (1.02 to 1.66)
1.04 (0.89 to 1.21)

1.23 (0.96 to 1.57)
0.95 (0.81 to 1.11)

50
597

493.4
501.3

1.15 (0.85 to 1.56)
1.21 (1.04 to 1.40)

1.02 (0.75 to 1.39)
1.08 (0.93 to 1.25)

50
379

609.1
586.6

1.41 (0.98 to 2.02)
1.34 (1.03 to 1.74)

1.18 (0.82 to 1.69)
1.13 (0.86 to 1.49)

6092

1365.1

ref

ref

374
2802

1 541.6
1 488.2

1.28 (1.15 to 1.43)
1.27 (1.20 to 1.34)

1.11 (0.99 to 1.23)
1.06 (1.00 to 1.12)

169
813

1635.91319.81.41 (1.21 to 1.65)
1.16 (1.07 to 1.26)

1.25 (1.07 to 1.46)
1.03 (0.95 to 1.12)

144
1701

1473.01553.2

1.15 (0.97 to 1.37)
1.26 (1.18 to 1.35)

1.05 (0.88 to 1.24)
1.07 (0.99 to 1.14)

61
288

1468.71678.41.03 (0.78 to 1.35)
1.28 (1.08 to 1.51)

0.87 (0.66 to 1.15)
1.00 (0.85 to 1.19)

1210

269.5

ref

ref

75
603

306.6
317.1

1.33 (1.04 to 1.69)
1.39 (1.23 to 1.57)

1.00 (0.78 to 1.28)
0.99 (0.87 to 1.13)

32
162

307.8
260.7

1.37 (0.96 to 1.96)
1.21 (1.01 to 1.45)

1.13 (0.79 to 1.61)
0.95 (0.79 to 1.14)

22
371

223.3
335.4

0.92 (0.60 to 1.42)
1.44 (1.24 to 1.67)

0.73 (0.47 to 1.13)
1.04 (0.89 to 1.22)

21
70

498.9
402.0

1.62 (0.99 to 2.66)
1.27 (0.90 to 1.80)

1.15 (0.70 to 1.88)
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.

worker visit. The date of diagnosis was regarded as aproxy 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/other6

countries), employed as a healthcare worker (yes/no), marital status (married/not married), education(primary, secondary, tertiary, undetermined), numberof 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).

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 thirddose), and then at each risk window (one to seven days
doi: 10.1136/bmj-2023-074778 | BMJ 2023;381:e074778 | the bmj

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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

RESEARCH

Risk windows
Person-years
BNT162b2 (Pfizer-BioNTech)
Unvaccinated646 760
Dose 1:
1-7 days
20 4668-90 days
103 775
Dose 2:
1-7 days
21 0068-90 days
247 223
Dose 3:15 6681-7 days
8-90 days
138 714mRNA-1273 (Moderna)
Unvaccinated646 760
Dose 1:
1-7 days
2612
8-90 days
13 911
Dose 2:
1-7 days2691
8-90 days
31 409Dose 3:
1-7 days7238
8-90 days
47 539ChAdOx1 nCoV-19 (AstraZeneca)
Unvaccinated646 760
Dose 1:
1-7 days4429
8-90 days
41 414
Dose 2:
1-7 days3518
8-90 days
41 671

Cases

Incidence rate
(per 100 000 person-years)

Crude model,* HR (95% CI)

Full model,† HR (95% CI)

3144

486.1

ref

ref

120
532

586.3
512.6

1.16 (0.96 to 1.40)
1.11 (0.99 to 1.24)

1.09 (0.90 to 1.32)
1.01 (0.90 to 1.14)

101
1240

480.8
501.6

1.13 (0.92 to 1.40)
1.24 (1.13 to 1.37)

1.02 (0.83 to 1.26)
1.14 (1.04 to 1.26)

95
724

606.3
521.9

1.59 (1.23 to 2.06)
1.36 (1.13 to 1.63)

1.41 (1.09 to 1.83)
1.23 (1.02 to 1.49)

3144

486.1

ref

ref

18
73

689.2
524.8

1.44 (0.90 to 2.03)
1.24 (0.97 to 1.58)

1.33 (0.84 to 2.13)
1.13 (0.88 to 1.44)

5
150

185.8
477.6

0.45 (0.19 to 1.08)
1.23 (1.02 to 1.48)

0.41 (0.17 to 0.99)
1.12 (0.92 to 1.35)

33
272

455.9
572.2

1.17 (0.80 to 1.72)
1.53 (1.22 to 1.91)

1.04 (0.71 to 1.53)
1.33 (1.06 to 1.67)

3144

486.1

ref

ref

28
239

632.2
577.1

1.14 (0.78 to 1.66)
1.16 (1.01 to 1.34)

1.24 (0.85 to 1.81)
1.17 (1.01 to 1.35)

16
171

454.8
410.4

1.27 (0.76 to 2.11)
1.17 (0.95 to 1.43)

1.21 (0.73 to 2.02)
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.

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 ofinterest, end of each risk window, or a censoring event(defined as receiving a second, third, or fourth doseof any vaccine, emigration, death, or end of study on
28 February 2022). An individual contributed persontime as unvaccinated until the first vaccination. Aftereach vaccination dose, individuals contributed persontime in each corresponding risk window of interest (ie,exposed risk time). We also restricted analyses to thesubpopulation where primary care data were available.
Additionally, we performed sensitivity analyses limited
to women without previous hormone treatment, andin women without a prior diagnosis of coagulationdisease 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 andperiod after first positive SARS-CoV-2 test) and thenat 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 ofinterest, end of each risk window, or a censoring eventthe bmj | BMJ 2023;381:e074778 | doi: 10.1136/bmj-2023-074778

(ie, emigration, death, or end of study on 26 December2020).
Hazard ratios with 95% confidence intervals were
estimated from Cox models. We report results from acrude 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 werereported 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 SARSCoV-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
7

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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

RESEARCH

Menstrual disturbance and bleeding disorders after
vaccination
Postmenopausal bleeding
Adjusted hazard ratio comparing the risk forpostmenopausal bleeding after vaccination with any
dose compared with unvaccinated periods was 1.12
(95% confidence interval 1.00 to 1.25) in the one toseven 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 withprimary 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 wereobserved 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 toseven days risk window (1.48 (1.12 to 1.94)); similarrisks were also observed in the subpopulation withprimary care data, most obviously for the second dosein the 8-90 days risk window (supplement table S4).
Exclusion of women with prior coagulation disorders
did not change the results notably compared with themain analyses (table 2, supplement table S5).

Product specific risk estimates for postmenopausal
bleeding

Analyses of associations from the full model withindividual 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 after8

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).

Menstrual disturbance

The adjusted hazard ratio for menstrual disturbanceafter 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 weakassociations 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 ofthese 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 theother outcomes because of fewer observed events.
The strongest associations observed, although notsignificant, 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 to1.70)). 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 evenwider confidence intervals (table 3, supplement figureS4). 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
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table 1 and table S2 by vaccine status. Women cancontribute with person-time to more than one vaccine
status group.
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 primarycare 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 thestudy 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 SARSCoV-2 during the study period of 1 August 2020 to 26
December 2020.

RESEARCH

Discussion
In this large population-based study of nearly three
million women, we observed weak but reasonably
precise associations between SARS-CoV-2 vaccinationand 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, butsuggest a less clear association with ChAdOx1 nCoV19.
For menstrual disturbance, adjustment for covariates
almost completely removed the associations foundafter vaccination in the crude estimates, and only aweak association remained after the first dose, limited
to the one to seven days risk window. Considering thecharacteristics of this condition, and that the change
is measured based on encounters with specialist
healthcare in this study, a causal effect limited to thisrisk window is unlikely.
The number of healthcare contacts for the outcome ofpremenstrual bleeding were fewer, and risk estimates
after vaccination consequently more imprecise. The
risk was also notably attenuated by adjustment forcovariates 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 forpostmenopausal bleeding were increased in the 90 day
risk window after infection.
Strengths and weaknesses
The main strengths of our study include the populationbased 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 specificmedical conditions, including diagnosis of obesityand chronic obstructive pulmonary disease. We haveno 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 amodest sensitivity. Also, we have no information onwhether the healthcare contact was a planned or anacute visit. Time from first symptoms to healthcare
the bmj | BMJ 2023;381:e074778 | doi: 10.1136/bmj-2023-074778

contact is probably longer for women with menstrual
disturbances and bleeding before menopause thanfor 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 thecondition is analysed. The time between onset, startof symptoms, and date of healthcare contact mightthus be considerable, making the interpretation ofeffect of different risk windows challenging. Hence,
we might also, especially for menstrual disturbancesand premenopausal bleeding, catch some prevalent(before exposure) cases, especially in the one to sevenday 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 correctcodes from the International Statistical Classificationof Diseases and Related Health Problems for defining
premenopausal bleeding or postmenopausal bleeding.
Reverse causation, where women get vaccinatedbefore a planned healthcare contact, is also an issue.
Also, women with an ongoing covid-19 infection willprobably cancel or postpone planned or semi-acutehealthcare contacts.

Other studies and supportive data
The concern for an association between SARSCoV-2 vaccination and menstrual or bleeding
disturbances in women has been triggered by thelarge number of spontaneous case reports related tosuch conditions.1-3, 10 Also, several studies on selfreported menstruation cycles changes after SARSCoV-2 vaccination have been published.4-9 27 28 The
European Medicines Agency has recommended thatheavy menstrual bleeding should be acknowledged
as a side effect of both SARS-CoV-2 mRNA vaccines.12
However, European Medicines Agency considered thatthe available data do not support causal association
between SARS-CoV-2 mRNA vaccines and absence ofmenstruation.12 The results from the present study are
not necessarily contradictive of this labelling, which
was mainly based on self-reported survey data andspontaneous case reports. This type of data can beprone 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 vaccinationand 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 activationof the immune system might trigger menstruation
effects.11 Two studies based on self-reported data
have reported some associations between humanpapillomavirus vaccines and menstruation effects.13
14
However, a large population-based study found
9

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(hazard ratio 1.28 (95% confidence interval 0.88 to1.86)) and premenopausal bleeding (1.45 (0.91 to2.32)). Of note, the number of cases of premenopausal
bleeding was very low. A similar pattern was observedin the subpopulation with primary care data, withslightly higher point estimates for postmenopausal
bleeding (supplement table S10).

RESEARCH

Conclusions
We observed weak and inconsistent associations
between SARS-CoV-2 vaccination and healthcare
contacts for postmenopausal bleeding, and evenless consistent for menstrual disturbance, andpremenstrual 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 SARSCoV-2 vaccination and healthcare contacts related to
menstrual or bleeding disorders.
Author affiliations

1

Division of Use and Information, Swedish Medical Products Agency,
Uppsala, Sweden
2
Institute of Environmental Medicine, Karolinska Institutet,
Stockholm, Sweden
3

School of Public Health and Community Medicine, Instituteof Medicine, Sahlgrenska Academy, University of Gothenburg,
Gothenburg, Sweden
4
Department of Microbiology and Immunology, Institute of
Biomedicine, Sahlgrenska Academy, University of Gothenburg,
Gothenburg, Sweden
5
Department of Clinical Pharmacology, Sahlgrenska University
Hospital, Gothenburg, Sweden
6
Department of Internal Medicine and Clinical Nutrition, Instituteof Medicine, The Sahlgrenska Academy, University of Gothenburg,
Gothenburg, Sweden
7
Department of Infectious Diseases, Institute of Biomedicine,
Sahlgrenska Academy, University of Gothenburg, Gothenburg,
Sweden8
Region Västra Götaland, Department of Infectious Diseases,
Sahlgrenska University Hospital, Gothenburg, Sweden
9
Division of Licensing, Swedish Medical Products Agency, PO Box
26, 751 03 Uppsala, Sweden
10
Department of Surgical Sciences, Uppsala University, Uppsala,SwedenContributors: FN had full access to all the data in the study andtakes responsibility for the integrity of the data and the accuracy ofthe data analysis. RL and YX contributed equally to this study andare considered joint first authors. FN and RL act as guarantors. RL,
YX, AS, RG, and FN contributed to concept and design. All authors
contributed to acquisition, analysis, or interpretation of data. RL,
YX, RG, and FN drafted the manuscript. All authors critically revised
the manuscript for important intellectual content. YX conducted
the statistical analysis. FN, and MG obtained funding. FN provided
administrative, technical, or material support. FN and RL supervised
the study. The corresponding author (RL) attests that all listed authors
meet authorship criteria and that no others meeting the criteria havebeen omitted.
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 theagreement 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 thedecision to submit the article for publication. The researchers are10

independent from the funders. All authors had full access to all thedata, including statistical reports and tables, in the study and takeresponsibility 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 employeeof AstraZeneca since 16 January 2023. The work in this article was
performed before this employment commenced. FN reports prioremployment 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.
Ethical approval: The study obtained ethics approval from theSwedish Ethical Review Authority (2020-01800, 2020-05829, 202100267, 2021-00829, 2021-02106, 2021-04098, 2022-00500-02,
2022-01207-02, 2022-03323-02). Consent to participate is notapplicable because this study is register based.
Data sharing: Access to similar data requires permission. Apartfrom ethical approval from the Swedish Ethical Review Authority,
researchers will also need approval from each register holder.
FN, the lead author, affirms that the manuscript is an honest,
accurate, and transparent account of the study being reported; thatno important aspects of the study have been omitted; and thatany 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 andinternational public health and regulatory agencies. Additionally weplan on making press releases to national and international media, as
well as making plain language summaries available on the homepagesof the Swedish Medical Products Agency and Gothenburg University.
Provenance and peer review: Not commissioned, externally peer
reviewed.
This is an Open Access article distributed in accordance with theCreative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work
non-commercially, and license their derivative works on different
terms, provided the original work is properly cited and the use is noncommercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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no association between human papillomavirus
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