Title: Menstrual characteristics and associations with sociodemographic factors and self-rated
health in Spain: a cross-sectional study
Version: 2 Date: 03 Oct 2023
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
No - there are minor issues
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
No - there are major issues
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
Not sure - key details are missing from the manuscript
STATISTICS - Is the use of statistics in the manuscript appropriate?
No - there are issues with the statistics in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
No - there are major issues
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Maybe - with major revisions
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: This study looks at the associations between sociodemographic
characteristics, with a focus on disadvantage, and menstrual characteristics (such as menstrual
blood flow, cycle duration).
There is limited research understanding inequalities in menstrual health, and the extent of
menstrual health challenges across different populations. The survey undertaken by the authors
is a great contribution to research evidence on these issues.
However, the hypothesis and the rationale for the hypothesis underlying this paper is not clearly
articulated. Authors state that socioeconomic status and other dimensions of disadvantage
impact health more broadly, but it is not clear why they hypothesise that these characteristics
are associated with menstrual characteristics. That is, what are the plausible causal pathways
between income or lower educational attainment and menstrual blood flow, or cycle regularity?
Diet? Lifestyle? Stress? What are the pathways through which we think this is a relationship
we would expect to exist, and what is the existing evidence for these relationships? There
is little past literature cited in the background linkages between menstrual characteristics and
sociodemographics. There is more attention to these pathways in the discussion - but this is
needed in the backgroudn to JUSTIFY doing the study in the first place, and to set in place the
hypotheses (and thus inform analyses) for this work.
There is no past literature given or rationale for the menstrual characteristics given and why
understanding variation of these is an important research question.
There are many analyses presented in the paper that I feel have alternative explanations.
The authors collected information on menstrual blood flow by asking about the quantity of
products used - but this is likely heavily influenced by how frequently users change their
products (perhaps not full) and what they perceive as a 'full' product. Its very plausible this varies
with socioeconomic status given those conserving products may change less often (this is then
observed later in the paper where lighter menstruation more common with lower education - the
reverse seems to be observed with heavier bleeding among greater disadvantage). Authors have
defined 'menstrual bleeding abundance' as 25-80mL (no citation on guidelines is given) - but
reports this a 62.4% - if over half of the sample is reporting this it suggests to me this is 'average'
for the population - and may suggest the measure is overly sensitive.
Given clots can be a normal part of menstrual discharge, I don't see any rationale for the
paper as to why these are included as 'menstrual characteristics' or why they would vary by
sociodemographics.
I am particularly struggling with why we would hypothesise that self-rated health would
PREDICT menstrual characteristics - and not the other way around. Wouldn't greater difficulties
with menstruation make PWM perceive themselves to have poorer health (particularly in a
survey asking about these characteristics)? Or if they have a diagnosed menstrual disorder like
heavy bleeding or disorder like Endometriosis or PCOS which might be associated with many
of the characteristics stated - then they may well rate their health worse. Why would this then
be a risk or protective factor for menstrual characteristics?
It appears there is new data on menstrual pain management presented in the discussion that isn't
in the results. Only the results should present new information like this.
It wasn't clear to me what was included as 'premenstural symptoms' - i'm not surprised that most
participants reported experiencing symptoms - without a measure of the extent to which these
impact life these don't necessarily indicate any kind of premenstrual syndrome. - This comes up
for the first time in the discussion, and again should have been foregrounded in the introduction,
and with clear citations and rationale given in introduction and methods as to why things were
measured in a particular way and why we would assume they are problematic. This verges on
problematising usual menstrual cycling experiences.
The discussion does not explore the alternative explanations for relationships among the
variables. Most of the discussion focuses on social and political implications of the findings or
menstrual health challenges - but this paper reports on biological differences.  The authors need
to engage more with the literature on menstrual biology and plausible causal mechanisms.
TABLES and ANALYSES
Particularly given the large proportions in the outcomes being assessed - the odds ratios aren't
very meaningful. The tables shoudl also present % differences between the groups/categories to
give an indication of how meaningful the differences are.
All of the analyses say 'aOR' ie. adjusted Odds Ratio - but its not clear what variables were
used in adjustment. Given the interrelationships between different socio-demographics, I would
assume (and hope) that the adjustment was including all sociodemographics as predictors. But
its not clear in the analysis section or in the tables. If not, then there are significant issues here
with multiple testing and adjustment.
Throughout the paper, the authors refer to 'higher risk' among different groups. But ODDS
ratios are presented, not risk ratios. Throughout this needs to be reported accurately - there is
significantly higher odds - but not risk. These are different.
MINOR COMMENTS
The total sample size should be presented in the abstract.
The authors often use 'Besides,' to connect sentences. This doesn't read well - and almost in
every instance this word could simply be removed to improve readability of the paper.
REQUESTED REVISIONS:
I have provided my reviewer comments in the box above.