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SchoepME, etal. BMJ Open 2019;9:e026186. doi:10.1136/bmjopen-2018-026186
Open access
Productivity loss due to menstruation-
related symptoms: a nationwide cross-
sectional survey among 32 748 women
Mark E Schoep,1,2 Eddy M M Adang,3 Jacques W M Maas,4 Bianca De Bie,5
Johanna W M Aarts,1 Theodoor E Nieboer1
To cite: SchoepME,
AdangEMM, MaasJWM,
etal. Productivity loss due
to menstruation-related
symptoms: a nationwide
cross-sectional survey among
32 748 women. BMJ Open
2019;9:e026186. doi:10.1136/
bmjopen-2018-026186
►Prepublication history and
additional material for this paper
are available online. To view
please visit the journal (http://
dx. doi. org/ 10. 1136/ bmjopen-
2018- 026186).
Received 22 August 2018
Revised 8 March 2019
Accepted 12 March 2019
1Department of Obstetrics and
Gynaecology, Radboudumc,
Nijmegen, The Netherlands
2Department of Obstetrics and
Gynaecology, Hospital Rijnstate,
Arnhem, The Netherlands
3Department of Health Evidence,
Radboudumc, Nijmegen, The
Netherlands
4Obstetrics & Gynaecology,
Maxima Medical Centre locatie
Veldhoven, Veldhoven, The
Netherlands
5Dutch Patient Endometriosis
Foundation, Numansdorp, The
Netherlands
Correspondence to
DrTheodoor ENieboer;
bertho. nieboer@ radboudumc. nl
Research
© Author(s) (or their
employer(s)) 2019. Re-use
permitted under CC BY-NC. No
commercial re-use. See rights
and permissions. Published by
BMJ.
ABSTRACT
Objective To evaluate age-dependent productivity loss
caused by menstruation-related symptoms, measured
in absenteeism (time away from work or school) and
presenteeism (productivity loss while present at work or
school).
Methods Design/setting: internet-based, cross-sectional
survey conducted in the Netherlands from July to October
2017. Participants: 32 748 women aged 15–45 years,
recruited through social media. Outcome measures: self-
reported lost productivity in days, divided into absenteeism
and presenteeism; impact of menstrual symptoms;
reasons women give when calling in sick; and women’s
preferences regarding the implications of menstruation-
related symptoms for schools and workplaces.
Results A total of 13.8% (n=4514) of all women reported
absenteeism during their menstrual periods with 3.4%
(n=1108) reporting absenteeism every or almost every
menstrual cycle. The mean absenteeism related to a
woman’s period was 1.3 days per year. A total of 80.7%
(n=26 438) of the respondents reported presenteeism
and decreased productivity a mean of 23.2 days per
year. An average productivity loss of 33% resulted in a
mean of 8.9 days of total lost productivity per year due
to presenteeism. Women under 21 years were more
likely to report absenteeism due to menstruation-related
symptoms (OR 3.3, 95% CI 3.1 to 3.6). When women
called in sick due to their periods, only 20.1% (n=908)
told their employer or school that their absence was due
to menstrual complaints. Notably, 67.7% (n=22 154) of
the participants wished they had greater exibility in their
tasks and working hours at work or school during their
periods.
Conclusions Menstruation-related symptoms cause a
great deal of lost productivity, and presenteeism is a bigger
contributor to this than absenteeism. There is an urgent
need for more focus on the impact of these symptoms,
especially in women aged under 21 years, for discussions
of treatment options with women of all ages and, ideally,
more exibility for women who work or go to school.
BACKGROUND
Menstruation-related symptoms (MRSs)
are diverse and widespread among women.
Symptoms include dysmenorrhoea, heavy
menstrual bleeding and premenstrual mood
disturbances with reported prevalence of
45%–90%, 14%–25% and 20%–29%, respec-
tively.1–3 Studies show that women with MRSs
have lower scores on several domains of quality
of life such as general health and physical,
mental, social and occupational functioning
during their periods.1 4–7 Furthermore, these
symptoms may create considerable financial
burdens on patients and their families as well
as on society.5 6 8–12 Such financial burdens are
related to the costs of visits to the doctor, over-
the-counter drugs and medical or surgical
treatment. However, costs related to produc-
tivity loss could be the largest cost driver.
Productivity costs are defined as costs asso-
ciated with paid and unpaid production loss
and the replacement of productive people
due to illness or disability.13 Productivity costs
can be divided into costs related to absen-
teeism and costs related to presenteeism.
Absenteeism represents the total amount
of time off work or away from school, and
presenteeism represents the loss of produc-
tivity while present at a job or school.
Although the literature is scarce and the
results are variable, studies on specific patient
groups generally show that MRSs can cause
absenteeism.14–16 Research on the association
between MRSs and presenteeism is even more
Strengths and limitations of this study
►This is the largest cohort study to analyse the im-
pact of menstruation-related symptoms on work
and school productivity.
►The survey was performed among the general fe-
male population and is consequently not per se re-
lated to one specic gynaecological condition.
►Due to the way of recruitment of participants, there
may have been some degree of selection bias.
►Outcomes are based on self-reported data and
consequently lack objectivity regarding productivity
loss.
►The generalisability of the study may be limited to
employment and school systems comparable with
the Dutch.
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limited. It has been suggested that research into possible
impairments in quality of life caused by menstrual symp-
toms should not focus on single symptoms but rather on
a complex of symptoms that vary widely but that are all
related to the menstrual cycle. This complex includes
both standard symptoms, like heavy menstrual bleeding
and abdominal cramps, and also less common symptoms,
like nausea and cold sweats.17 18
Taking all symptoms into account, it seems likely that
the real impact of MRSs is underestimated in the general
population. Despite being almost two decades into the
21st century, discussions about MRSs may still be rather
taboo. This survey-based exploratory study aimed to
quantify the burden of MRSs in the general female popu-
lation, with burden defined as the number of lost days
at work or school due to absenteeism and presenteeism.
Furthermore, it was aimed to study the impact of specific
symptoms on absenteeism and presenteeism.
METHODS
This cross-sectional study consisted of an online survey
that was distributed from 12 July to 11 October 2017. All
data were anonymously collected and stored under the
privacy rules of the Radboud University Medical Center.
Patients gave informed consent when they initiated the
questionnaire.
Patient and public involvement
A group of women, among which were several members
of the Dutch Patient Endometriosis Foundation, women
with a linguistic education and women with a medical
origin, was involved in the conduct of this study at several
stages, that is, in the development and dissemination of
the questionnaire and in the analysis and interpretation
of the results. One of the authors of this manuscript, BDB,
is the chair of the Dutch Patient Endometriosis Founda-
tion. Additional contributions are noted in the Acknowl-
edgements section.
Questionnaire development
The questionnaire had several parts, and online supple-
mentary appendix 1 provides details about the questions.
Part 1 consisted of questions about each woman’s basic
characteristics. Part 2 had questions about menstrual
symptoms, and part 3 had questions related to absen-
teeism and presenteeism. Adaptive questioning was used
with a maximum of six questions per page. Participants
were asked in a lay manner how long their menstrual
cycle was and what the exact meaning of a menstrual cycle
was. The duration of the cycle was divided in five catego-
ries (25 days or less, 26–30 days, 31–35 days, 36–40 days
and 41 days or more). Furthermore, participants could
indicate if they had an irregular cycle, meaning more
than 10 days difference per cycle, if they were amenor-
rhoeic due to the use of an intrauterine device (IUD) or
the continuous use of oral contraceptives, or the option
‘I do not know’. Additional questions about absenteeism
and presenteeism were included that were based on
the Productivity Cost Questionnaire from the Institute
for Medical Technology Assessment (iMTA-PCQ).19 We
modified the iMTA-PCQ-recommended recall period of
4 weeks to 3 months so that it was in line with the rele-
vant time period for this study and so we could include
multiple menstrual periods. We assumed the amount
of presenteeism to be larger than the amount of absen-
teeism. Therefore, the recall period for absenteeism
was extended to 6 months to maintain accuracy. Visual
analogue scales (VAS) were used to quantify the amount
of pain, or the intensity of the symptom, and the impair-
ment due to pain or the other symptom. Presenteeism
was measured by asking women to what extent they were
able to be as productive as possible compared with a day
without MRSs. This was scored on a scale from 0 to 10,
with 0 being totally unproductive and 10 fully productive.
In separate questions, participants were asked to quantify
their absenteeism that was related to MRSs and absen-
teeism for any other reason than MRSs. For the latter, we
did not specifically ask the underlying reason.
Target population and recruitment
The study population comprised women between 15 and
45 years old. The upper age limit was chosen to avoid
interference from menopausal symptoms; the lower
to have a time margin after the average menarche age,
since it is known that the first periods are irregular and
often accompanied with discomfort and uncertainty.
A large number of women were approached with the
aim of obtaining a cohort that was representative of the
general female population in terms of level of education,
medical history and/or gynaecological diagnosis. Women
were invited to complete a survey using an online ques-
tionnaire tool20 through a campaign on social media
platforms Facebook and Twitter. Patient organisations,
colleagues and visitors of the Facebook page of one of the
authors (TN) were asked to share the link to the ques-
tionnaire in order to reach the widest possible audience.
On 12 July 2017, a link to the questionnaire was posted
on Facebook and Twitter through the account of one
of the authors (TN). In the post, both women with and
without MRSs were encouraged to fill in the question-
naire. Within 24 hours of the first posting on social media,
over 6000 respondents had filled in the questionnaire,
and by July 18, there were 15 000 respondents, which
was announced by a repost of the link to the question-
naire. A third post was made on Facebook and Twitter on
16 September 2017, to reach women who may have been
on holiday when the first posts were created.
Data analysis
The outcome measures were presented in a descriptive
way; we used valid percentages in case of missing values
where necessary. We distinguished between women who
were mainly working or mainly studying. Therefore, we
present these data for two groups, that is, for women who
worked more than 5 hours per week (‘working group’)
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and for women who studied more than 5 hours per week
(‘studying group’).
We used binary logistic regression to calculate ORs.
Absenteeism and presenteeism were used as dependant
variables. As independent variables, we used the following
parameters: women younger than 21 versus women aged
21 and older, smoking yes or no, reports of absenteeism
not related to MRSs, educational level, the use of oral
contraception and the use of an levonorgestrel-releasing
IUD. All independent variables were used in an univariate
as well as a multivariate analysis. We also studied the asso-
ciation between pain scores and both absenteeism and
presenteeism, given that the literature shows that pain
scores of 0–4, 5–6 and 7 or higher have a different impact
on activity, mood and sleep.21 22 Analyses were performed
using IBM SPSS Statistics V.22.00.
Assumptions and transformation of the original data
To present data on level of education in an international
format, we had to transform the original data, which was
based on the Dutch school system.23 The categorical data
of participants’ length of menstrual cycle were trans-
formed into averages.
With regard to the evaluation of absenteeism and
presenteeism, ‘the guideline for economic evaluations
in healthcare in the Netherlands’ was used.24 A work day
accounts for 8 hours. For most sectors in the Netherlands,
a full-time work-week is 36 hours. The maximum amount
of working hours per year was set at 1558 when they were
working full time. We asked women to report their absen-
teeism due to MRSs per cycle and used a recall period of
6 months.
To calculate the percentages for absenteeism, 1 day of
absenteeism accounted for 8 hours of lost productivity.
When a woman reported to study or work more than
40 hours per week, we transformed these hours to 40 for
reasons of clarity in the calculations and comparability
with the data of the Dutch Central Bureau of Statistics
(CBS). We made a few other transformations for cate-
gorical data. For absenteeism related to MRSs, the cate-
gory ‘more than three days per cycle’ was considered to
be 4 days per cycle. For absenteeism that was not related
to MRSs, the category ‘more than ten days in the past
six months’ was considered to be 11 days in the past
6 months.
To present yearly data, we multiplied some of these data
based on the original recall period. The number of days
for absenteeism related to MRSs was based on days per
cycle, which were therefore multiplied by 12.7 based on
the reported average menstrual cycle of 28.8 days (see
table 1). These values were then multiplied by one if the
woman reported that she called in sick ‘every period’, 0.75
if she reported ‘almost every period’, 0.5 if she reported
‘half of all periods’ and 0.25 if she reported calling in sick
‘only once in a while’. Values for absenteeism that was not
related to MRS were based on a recall period of 6 months
and were therefore multiplied by two in order to obtain
the number of days per year. The values for presenteeism
Table 1 Basic characteristics of study participants
(n=32 748)
Number
(percentage) Mean±SD Median
Age, years 28.6±8.6 28
15–19 6141 (18.8)
20–24 6118 (18.7)
25–29 5825 (17.8)
30–34 5483 (16.7)
35–40 4687 (14.3)
41–45 4494 (13.7)
Level of education
Low 4020 (12.3)
Medium 12 335 (37.9)
High 16 229 (49.8)
Hours/week
Paid work 21.7±14.7 24
Study 7.4±13.6 0
Voluntary work 0.8±3.1 0
Menstrual cycle
Regular cycle 25 717 (78.5)
Duration 28.8±3.0 28
Amenorrhoea due
to LG-IUD/OC
3675 (11.2)
Irregular,
variation>10 days
per cycle
2495 (7.6)
Do not know 861 (2.6)
Days with blood
loss per cycle
5.4±1.6 5
Visited a doctor for
MRSs
No 17 873 (54.6)
Yes, general
practitioner
10 141 (31.0)
Yes, gynaecologist 4698 (14.4)
Diagnosis for MRSs*
No 29 731 (90.8)
Yes 3017 (9.2)
Endometriosis 1120 (3.4)
PCOS 588 (1.8)
Adenomyosis 103 (0.3)
Fibroids 275 (0.8)
Other 1901 (5.8)
Contraception*
Hormonal
contraception
11 993 (36.6)
OC 8650 (26.4)
LG-IUD 2752 (8.4)
Continued
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were based on a recall period of 3 months and were there-
fore multiplied by four.
RESULTS
A total of 44 173 women initiated the questionnaire. We
excluded participants who did not report a date of birth
or whose age did not fulfil the inclusion criteria (figure 1).
There were no duplicates of IP addresses. Women who
did not answer questions related to absenteeism and
presenteeism were excluded. Furthermore, cases with
impossible results (eg, 10 000 000 days of presenteeism
in 3 months or 140 changes of sanitary pads a day) were
excluded. This resulted in a total of 32 748 women in the
final analysis.
Table 1 summarises the basic characteristics of the
participants. We found that 45.4% (n=14 839) had visited
a doctor for menstrual complaints in the past, with a
total of 3017 (9.2%) women reporting a diagnosis of a
menstrual disorder, such as endometriosis or fibroids.
The mean age of women in the working group was
higher than the mean ager of women in the studying
group. The mean number of working hours per week
in the working group was 27.0 (SD 11.4), and the mean
number of study hours in the studying group was 27.4
(SD 12.1). A total of 7335 women (22.4%) reported both
working and studying more than 5 hours per week. In this
group, 3001 women were working more than 16 hours a
week, and 5284 women in the study group were studying
more than 16 hours a week.
Absenteeism
Table 2 shows the results on absenteeism due to MRSs.
Although 13.8% of the women (n=4514) reported absen-
teeism due to MRSs, only 1108 women (3.4%) reported
absenteeism every cycle or almost every cycle. The
percentage of absenteeism in every cycle or almost every
cycle was 2.4% in the working group and 4.5% in the
studying group. The mean absenteeism due to MRSs was
Number
(percentage) Mean±SD Median
Other hormonal:
injection,
transdermal and
so on
882 (2.7)
No hormonal
contraception
20 755 (63.4)
Cu-IUD 771 (2.4)
Female
sterilisation
423 (1.3)
No female
contraception
19 639 (60.0)
Nulliparous 21 585 (66.0)
Paid work>5 hours
a week
26 104 (79.7)
Age 29.7±8.3 29
Hours of paid
work/week
27.0±11.4 28
Hours spent on
study/week
7.5±13.4 0
>40 hours of paid
work/week
1047 (3.2)
Study>5 hours a
week
8764 (26.8)
Age 22.0±6.2 20
Hours spent on
study/week
27.4±12.1 30
Hours of paid
work/week
15.5±11.3 12
>40 hours spent
on study/week
322 (1.0)
Mean duration of cycle based on women with a regular cycle.
*More than one answer possible.
Cu-IUD, copper intrauterine device; LG-IUD, levonorgestrel-
releasing intrauterine device; MRSs, menstruation-related
symptoms; PCOS, polycystic ovary syndrome; OC, oral
contraceptive.
Table 1 Continued
Figure 1 Flow chart for the respondents.
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0.9 days per year for the working group and 1.6 day per
year for the study group.
We also calculated the mean total absenteeism that was
not related to MRSs. For the entire group, this was 3.3 days
per year; for the working group, it was 3.5 days, and for
the studying group, it was 4.3 days. The mean percentage
of absenteeism that was not related to MRSs was 3.5%
in the working group and 3.7% in the studying group.
Consequently, absenteeism due to MRSs in our cohort
accounted for, on average, 22% of the total absenteeism
in the working group and 24% in the studying group.
Presenteeism
Table 3 shows the numbers reported for presenteeism.
Over 80 % of all women reported presenteeism during
their periods. The differences between the working group
and the study group were not large in terms of prevalence
and lost productivity. The mean number of lost produc-
tive days per year due to presenteeism was more than
sevenfold greater than the mean number of lost produc-
tive days due to absenteeism.
Factors associated with absenteeism and presenteeism
Figure 2 shows the association between reported pain
or discomfort scores and both absenteeism and presen-
teeism. As seen in detail in table 4, high VAS scores were
significantly associated with higher levels of absenteeism
and presenteeism. The strongest relationship was found
for abdominal pain scores that were seven or higher on
Table 2 Reported absenteeism caused by menstruation-
related symptoms
Number
(percentage) Mean±SD
All (n=32 748)
Absenteeism 4514 (13.8)
≤0.5 day 538 (1.6)
1 day 2259 (6.9)
2 days 1171 (3.6)
3 days 349 (1.1)
>3 days 184 (0.6)
Total days of
absenteeism per year
1.3±5.9
Work (n=26 104)
Absenteeism 2926 (11.2)
≤0.5 day 374 (1.4)
1 day 1476 (5.7)
2 days 757 (2.9)
3 days 211 (0.8)
>3 days 98 (0.4)
Total days of
absenteeism per year
0.9±3.9
Study (n=8764)
Absenteeism 1715 (19.6)
≤0.5 day 234 (2.7)
1 day 921 (10.5)
2 days 423 (4.8)
3 days 92 (1.0)
>3 days 41 (0.5)
Total days of
absenteeism per year
1.6±5.0
Women were asked to report the average amount of days on which
they were absent due to menstruation-related symptoms per cycle.
The total days of absenteeism per year was calculated. The added
numbers of women in the work and study group exceed the total
amount of participants, since 2120 women reported to both study
and work more than 5 hours/week.
Table 3 Reported presenteeism caused by menstruation-
related symptoms
Number
(percentage) Mean±SD Median
All (n=32 748)
Presenteeism 26 438 (80.7)
Number of days in
the past 3 months
5.8±5.3 5.0
Percentage of
productivity loss
per day
33.0±24.8 30.0
Days/year of lost
productivity
8.9±11.0 5.6
Work (n=26 104)
Presenteeism 21 252 (81.4)
Number of days in
the past 3 months
5.7±5.2 5.0
Percentage of
productivity loss
per day
31.7±24.7 30.0
Days/year of lost
productivity
8.4±10.6 4.8
Study (n=8764)
Presenteeism 7385 (84.3)
Number of days in
the past 3 months
6.3±5.3 5.0
Percentage of
productivity loss
per day
36.8±24.2 40.0
Days/year of lost
productivity
10.5±11.8 7.2
Women were asked to report the amount of days on which they
were less productive and to what extent. The total days of lost
productivity per year was calculated. The added numbers of
women in the work and study group exceed the total amount of
participants, since 2120 women reported to both study and work
more than 5hours/week.
Note that the values presented in days/year of lost productivity
do not add up exactly, since these data were calculated on an
individual basis and are not the result of merely multiplying the two
averages.
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a scale from 0 to 10. ORs were 5.6 for absenteeism (95%
CI 5.0 to 6.2) and 8.8 for presenteeism (95% CI 8.1 to
9.5). Figure 3 shows the association between age and both
presenteeism and absenteeism. As shown in both figure 3
and table 4, we found that younger women showed signifi-
cantly higher rates of absenteeism and presenteeism. A
levonorgestrel-releasing IUD is associated with especially
less presenteeism.
Menstruation and suggested implications for schools and
workplaces
From the respondent who had been calling in sick due
to MRSs, 20.1% (n=908) told their employer or school
menstrual symptoms were the reason, 46.4% (n=2092)
only mentioned the presenting symptom. No reason was
given by 27.7% (n=1250), while 5.8% (n=260) made up
another reason. Comparing women aged below 21 years
with women aged 21 years and above, we found that
younger women were less open about their MRSs being
the reason for calling in sick (12.0%) versus women
older than 21 (27.0%). Women were asked to report
suggestions on how work places and conditions could
be changed in order for them to function better during
their menstrual periods. There were 32 708 responses
to this multiple-choice question, to which each woman
could give more than one answer. The majority of women
(67.7%, n=22 154) preferred more flexibility during their
periods, such as the possibility of doing less physical work
(32.1%, n=10 499), the ability to work from home (39.5%,
n=12 917), more time for personal care (28.3%, n=9241)
or the ability to take a day off and make up for it later
(11.5%, n=3756). In addition, 32.9% wished they could
take a complete day off without any consequences. A
percentage of 27.2 (n=8890) did not wish for any changes
in policy. Many women (79.7%, n=26 072) were open to
discussing MRSs with their company doctor, and 56.7%
(n=18 579) thought that doing so would draw more atten-
tion to MRS-related matters.
DISCUSSION
This survey-based study showed that menstruation-re-
lated absenteeism and, to a greater extent, presenteeism
are widespread in the general female population. In our
cohort, MRSs accounted for up to 24% of total absen-
teeism for women who were working and studying. The
annual productivity loss due to presenteeism was seven-
fold times more than the annual productivity loss due to
absenteeism, and women younger than 21 years experi-
ence the largest burden. Symptom severity scores showed
significant and strong associations with both absenteeism
and presenteeism. When women called in sick due to
MRSs, only one in five stated openly that menstrual symp-
toms were the main reason. A majority of women prefers
more flexibility during their periods when it comes to
work or school.
There have been few studies on absenteeism and presen-
teeism related to MRSs in the general female population.
To our knowledge, Tanaka’s study25 is the only other
published study on absenteeism and presenteeism due to
MRSs in the general female population. In a cohort of
19 254 Japanese women, a total of 3311 (17.2%) reported
work productivity lost in the prior 3 months, mostly in the
form of decreased efficiency (62.0%, n=2052). Of these
2052 subjects, the mean number of workdays lost due to
decreased efficiency was 5.7 days in 3 months. After recal-
culation, this accounts for 2.4 days per year for the entire
population. This is fewer days than the 8.9 days per year
in our cohort. However, the numbers for absenteeism
were more similar, with a mean of 1.0 day of absenteeism
per year in the entire Japanese cohort compared with 1.3
days in our cohort. Differences in regulations of social
services, a difference in attitude towards sick leave and a
different method of data collection might explain these
differences. It has been suggested in research on muscu-
loskeletal symptoms that rates of absenteeism might be
lower in Japan compared with European countries and
the USA. Consequently, presenteeism might therefore be
a more representative variable.26 27
More data are available regarding the impact of dysmen-
orrhoea on quality of life and absenteeism. De Sanctis
et al reviewed studies on dysmenorrhoea in multiple
countries, some of which included menstruation-related
absenteeism data.14 They found that the prevalence of
school absences in adolescents that was due to dysmenor-
rhoea varied between 7.7% and 57.8%. Since the review
included 41 140 women in 27 countries, and there was a
high degree of heterogeneity in the outcome measures,
no firm conclusions could be drawn. Hailemeskel et al
evaluated 440 female university students in Ethiopia.28
Figure 2 The relationship between pain and intensity
scores, related to absenteeism and presenteeism, in lost
days per year.
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Table 4 ORs and 95% CIs for factors related to absenteeism and presenteeism
Absenteeism Presenteeism
OR (95% CI)
OR after correction
(95% CI) OR (95% CI)
OR after correction
(95% CI)
Age<21 years* 3.7 (3.4 to 3.9) 3.3 (3.1 to 3.6) 1.4 (1.3 to 1.5) 1.3 (1.2 to 1.4)
Smoking† 1.3 (1.2 to 1.5) 1.3 (1.2 to 1.4) 1.5 (1.3 to 1.6) 1.4 (1.3 to 1.6)
Absenteeism not related
to MRSs in the past
6 months‡
2.2 (2.1 to 2.4) 1.7 (1.6 to 1.9) 1.4 (1.3 to 1.5) 1.3 (1.2 to 1.4)
Level of education§
Low 4.5 (4.1 to 4.9) 2.7 (2.4 to 3.0) 1.3 (1.2 to 1.4) 1.1 (1.0 to 1.2)**
Medium 2.2 (2.1 to 2.4) 1.7 (1.5 to 1.8) 1.3 (1.2 to 1.4) 1.2 (1.1 to 1.2)
High 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
Oral contraception¶
No 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
Yes 1.2 (1.1 to 1.3) 1.0 (0.9 to 1.1)†† 0.9 (0.9 to 1.0) 0.9 (0.8 to 0.9)
LG-IUD¶
No 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
Yes 0.7 (0.6 to 0.8) 0.9 (0.8 to 1.0) 0.5 (0.5 to 0.6) 0.5 (0.5 to 0.6)
Abdominal pain score¶
0–4 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
5–6 2.6 (2.3 to 2.9) 2.2 (1.9 to 2.4) 5.2 (4.8 to 5.7) 5.3 (4.9 to 5.7)
>7 7.0 (6.4 to 7.8) 5.6 (5.0 to 6.2) 8.7 (8.0 to 9.4) 8.8 (8.1 to 9.5)
Headache pain score¶
0–4 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
5–6 1.5 (1.3 to 1.6) 1.5 (1.4 to 1.6) 3.0 (2.7 to 3.3) 3.1 (2.8 to 3.4)
>7 2.0 (1.8 to 2.1) 2.3 (2.1 to 2.5) 3.5 (3.2 to 3.9) 3.7 (3.4 to 4.1)
Backache pain score¶
0–4 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
5–6 1.6 (1.5 to 1.7) 1.4 (1.3 to 1.5) 3.5 (3.2 to 3.9) 3.5 (3.2 to 3.8)
>7 2.7 (2.5 to 2.9) 2.2 (2.1 to 2.4) 4.7 (4.2 to 5.2) 4.5 (4.0 to 5.0)
Tiredness intensity
score¶
0–4 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
5–6 1.8 (1.7 to 2.0) 1.8 (1.6 to 2.0) 3.3 (3.1 to 3.6) 3.3 (3.1 to 3.6)
>7 3.0 (2.8 to 3.2) 2.8 (2.6 to 3.1) 5.1 (4.7 to 5.6) 5.2 (4.7 to 5.7)
Psychological
complaints intensity
score¶
0–4 1.0 (n/a) 1.0 (n/a) 1.0 (n/a) 1.0 (n/a)
5–6 1.6 (1.5 to 1.7) 1.5 (1.4 to 1.7) 2.7 (2.5 to 2.9) 2.6 (2,5 to 2.9)
>7 2.2 (2.0 to 2.4) 2.1 (2.0 to 2.3) 4.4 (4.0 to 4.7) 4.3 (4.0 to 4.7)
ORs>1 correlate with a higher prevalence of absenteeism or presenteeism. ORs<1 correlate with a lower prevalence of absenteeism or
presenteeism.
*Correction for smoking and absenteeism that was not related to menstruation-related symptoms (MRSs).
†Correction for age, absenteeism that was not related to MRSs and level of education.
‡Correction for age, smoking and level of education.
§Correction for age, smoking and absenteeism that was not related to MRSs.
¶Correction for age, smoking, absenteeism that was not related to MRSs and level of education.
**P=0.26, ††p=0.73 for all other ORs, p<0.05.
LG-IUD, levonorgestrel-releasing intrauterine device.
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Among students with dysmenorrhoea, 66.8% reported a
loss of concentration in class, and 56.3% reported class
absences during the last month. In a questionnaire-based
study of 706 Hispanic female adolescents, 38% reported
missing school due to dysmenorrhoea during the 3
months prior to the survey, and 59% reported a decrease
in concentration in class due to dysmenorrhoea.29
Absenteeism and presenteeism due to endometriosis
in other studies was greater than in our study, which was
not surprising.9 14 30 However, some interesting parallels
can be drawn to findings from a recent study by Soliman
et al.14 They found that the average number of hours of
presenteeism, 5.3 hours per week, was far greater than
the number of hours of absenteeism, which was 1.1 hours
per week. Furthermore, younger women had significantly
higher levels of lost productivity than their older coun-
terparts, and more severe symptoms were associated with
more absenteeism and presenteeism. This was in line with
our findings, since we also found higher rates of both
absenteeism and presenteeism in younger women. A
taboo on talking openly about MRS, undertreatment and
less flexibility at school might be possible explanations for
these differences. Comparing our outcomes with studies
on other non-gynaecological conditions is hard due to
differences in methods and presentation of findings and
the cyclic character of MRSs. However, the incidence of
presenteeism seems to be as high as it is in patients with
inflammatory bowel disease.31 Moreover, the amount of
impairment is comparable with severe gastro-oesopha-
geal reflux (31.9%), moderate irritable bowel syndrome
(36.6%) and allergic rhinitis (33.4%–39.8%)%).32
Our finding that only 20.1% of women were open
about their menstrual symptoms as a reason for calling
in sick may confirm the general idea that women tend
not to speak openly about MRSs. Wong et al found that
in a cohort of schoolgirls in Malaysia, 76.1% considered
dysmenorrhoea a normal part of the menstrual cycle.15
In the context of the findings noted above, our study
also suggests there is a taboo for women in terms of
discussing menstrual problems with their employers. The
latter may therefore conclude that the impact of MRSs
on their employees is negligible. Considering the fact
that we also found that 68% of women wish that they had
greater flexibility during their periods, either at school
or at work, more openness about MRSs in the employ-
ment setting seems desirable. The reasons underlying
this taboo are likely to have a historical basis; indeed,
since ancient times, menstruation has been surrounded
with mythical stories and has not been well understood.
However, in recent years, the lay literature in developed
countries has focused more attention on MRSs.33–35 The
prevalence and the impact of MRSs on the general popu-
lation and the number of women who are asking for a
different approach all reflect the need to change the view
of menstrual symptoms and the way they are addressed
in society.
This study consisted of a large cohort, and it reached
a large number of women within the age range that was
aimed for. The questionnaire was developed in collabora-
tion with patient representatives to make it understand-
able by and relevant to most women. The cohort appeared
to be a representative sample of the general female popu-
lation based on the number of working hours.33 When
we compare our data with the national registries, the
total amount of absenteeism is found to be comparable,
regardless of whether it was related to MRSs.36 37 It is
difficult to compare our numbers on women with a diag-
nosis explaining their MRSs with numbers found in other
studies. We found that only 9% of the participants had
such a diagnosis, which seems about as expected or even
somewhat low.3 38–40 In contrast, 45% of the women in the
study reported consulting a physician for their MRSs. This
number was relatively high compared with other studies
in which, for example, the percentage of women with
dysmenorrhoea who sought medical advice was approxi-
mately 15%.15 16 An important factor might be the Dutch
health system in which general practitioners are available
free of charge. Women with a low level of education were
relatively under-represented.41 As our results show, espe-
cially absenteeism related to MRSs is associated with a low
level of education, and this might have biased our results.
We expect women with lower educational levels to do
more physical jobs or jobs with less flexibility. Therefore,
our findings on work productivity loss might be under-
estimated. However, our finding could be overestimated
due to the possibility that women with more MRSs might
be more likely to respond to a questionnaire, as it may
seem more relevant to them. Moreover, we were not able
to provide data on presenteeism not related to MRSs nor
were we able to correct for comorbid health conditions.
Thus, these results must be interpreted with caution. Due
to the way that the questionnaire was distributed through
Figure 3 The relationship between age and average
absenteeism and presenteeism.
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social media, there may have been some selection bias.
However, a recent review stated that Facebook is a useful
recruitment tool for healthcare research.42 Although we
did not use a validated questionnaire, our most important
outcomes were based on questions derived from the PCQ,
which itself is based on validated questions and which is
recommended by guidelines for cost research.24 Self-re-
ported absenteeism generally shows a good correlation
with official records, although accuracy decreases with
increasing recall period.43 This might have initiated a
recall bias in our cohort. It is unknown to what extend
recall bias affects reports on presenteeism.44 In general,
although results vary among studies on premenstrual
complaints, a prospective collection of data on symp-
toms is advisable.45 46 Furthermore, an extrapolation
of a 3-month and 6-month timeframe to a yearly basis
may intrinsically imply some degree of uncertainty, for
example, when the influenza season is not included
in the original analysis. Finally, these results may not
be generalised internationally due to variability in the
regulation of social services in different countries, and
this is also a limitation of our study. In he Netherlands,
wages are paid during sick leave that has duration of less
than 1 year, but women in other countries may not have
this benefit. Since we know that many factors influence
menstrual symptoms, including biological, cultural, and
environmental factors, these differences might well influ-
ence both absenteeism and presenteeism.6 14 47
In conclusion, we have found that the impact of MRSs
on work and school productivity is considerable and that
presenteeism contributes significantly more to the matter
than absenteeism. Future research should identify how
women affected by MRSs could be helped best and how
their productivity can be improved in order to reduce the
societal impact regarding absenteeism and presenteeism.
Acknowledgements The authors would like to thank Reinoud Oomen, Peter de
Vroed, Steven Giesbers, Elsbeth Teeling, Paula Kragten and Annemarie Haverkamp
for their valuable contributions in the development and dispersion of the
questionnaire.
Contributors TEN, BDB and JWMA conceived the study. MES wrote the rst and
successive drafts of the manuscript. MES, TEN and EMMA modelled and analysed
the data. TEN, EMMA, JWMM, BDB and JWMA contributed to study conception and
design. MES and TEN collected the data. All authors revised the manuscript for
important intellectual content. MES and TEN had full access to the data and take
responsibility for the integrity of the data and the accuracy of the data analysis. TEN
is the guarantor.
Funding The authors have not declared a specic grant for this research from any
funding agency in the public, commercial or not-for-prot sectors.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval Approval for this study was obtained from the local medical
ethics committee ‘Commissie Mensgebonden Onderzoek (CMO)’ under number le
number 2017–3387 on 12 July 2017.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement No additional data from this study are available from a
repository. Data are available on request from the corresponding author.
Open access This is an open access article distributed in accordance with the
Creative 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, appropriate credit is given, any changes made indicated, and the use
is non-commercial. See: http:// creativecommons. org/ licenses/ by- nc/ 4. 0/.
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