| Literature DB >> 33725341 |
Kirsty J Elliott-Sale1, Clare L Minahan2, Xanne A K Janse de Jonge3, Kathryn E Ackerman4, Sarianna Sipilä5, Naama W Constantini6, Constance M Lebrun7, Anthony C Hackney8.
Abstract
Until recently, there has been less demand for and interest in female-specific sport and exercise science data. As a result, the vast majority of high-quality sport and exercise science data have been derived from studies with men as participants, which reduces the application of these data due to the known physiological differences between the sexes, specifically with regard to reproductive endocrinology. Furthermore, a shortage of specialist knowledge on female physiology in the sport science community, coupled with a reluctance to effectively adapt experimental designs to incorporate female-specific considerations, such as the menstrual cycle, hormonal contraceptive use, pregnancy and the menopause, has slowed the pursuit of knowledge in this field of research. In addition, a lack of agreement on the terminology and methodological approaches (i.e., gold-standard techniques) used within this research area has further hindered the ability of researchers to adequately develop evidenced-based guidelines for female exercisers. The purpose of this paper was to highlight the specific considerations needed when employing women (i.e., from athletes to non-athletes) as participants in sport and exercise science-based research. These considerations relate to participant selection criteria and adaptations for experimental design and address the diversity and complexities associated with female reproductive endocrinology across the lifespan. This statement intends to promote an increase in the inclusion of women as participants in studies related to sport and exercise science and an enhanced execution of these studies resulting in more high-quality female-specific data.Entities:
Mesh:
Year: 2021 PMID: 33725341 PMCID: PMC8053180 DOI: 10.1007/s40279-021-01435-8
Source DB: PubMed Journal: Sports Med ISSN: 0112-1642 Impact factor: 11.136
Fig. 1Indicative oestrogen and progesterone profiles across the lifespan from childhood to senescence: a oestrogen (pmol∙L−1). With regards to oestrogen, the menstrual cycle has 20 times more oestrogen than pre-puberty and pregnancy 35 times more oestrogen than the menstrual cycle; b progesterone (nmol∙L−1). The menstrual cycle has 35 times more progesterone than pre-puberty and pregnancy almost 7 times more progesterone than during the menstrual cycle. Oral contraceptives users and post-menopausal women have similar levels of endogenous oestrogen and progesterone. Hypothalamic-pituitary forms of amenorrhea (not depicted here) do not show any evidence of oestrogen production based on urinary measurements [1]. In women, “oestrogen” includes the oestrone, oestradiol, oestriol hormones
List of the considerations related to participant characteristics and selection criteria
| Consideration | Rationale (intended to…) | Pros (could…) | Cons (could…) |
|---|---|---|---|
| Define | Increase accuracy and validity of the population definition | Reduce between study variability in describing the population studied | Increase timescale of the study in order to recruit participants who fit the criteria |
| Define | Need to be aware of other physical and endocrine indicators of puberty outside of menarche (e.g. | ||
| Define | Increase homogeneity of hormonal profiles Increase consistency of terminology | Reduce between participant variability in hormone status Reduce between study variability in describing the population studied | Reduce availability of eligible participants Increase timescale of the study if the condition needs to be confirmed prior to the commencement of data collection Increase number of participants who need to be excluded (during or retrospectively) from the study if the condition was not confirmed prior to commencement of the study |
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| Define | Increase accuracy and validity of the population definition | Reduce unfounded assumption that ovulation, and thus eumenorrhea, has been established Reduce between study variability describing the population studied | Increase timescale of the study in order to recruit participants who fit the criteria |
A priori exclusion of participants with self-reported or diagnosed menstrual irregularities for eumenorrheic studies. Menstrual irregularities refer to perturbations of the eumenorrheic menstrual cycle, such as amenorrhea, anovulation, oligomenorrhea etc | Increase homogeneity of hormonal profiles | Reduce between participant variability in hormone status Increase validity of the data | Reduce availability of eligible participants for eumenorrheic studies |
| A posteriori exclusion of participants with observed or implied menstrual irregularities for eumenorrheic studies | Increase number of participants who need to be excluded (during or retrospectively) | ||
| No HC use ≥ 3 months prior to recruitment for study on eumenorrheic participants | Increase likelihood that an eumenorrheic cycle and its typical hormonal profile has been re-established | Reduce occurrence of atypical hormonal profiles not fitting the eumenorrheic definition | Reduce availability of eligible participants for eumenorrheic studies Increase timescale of the study as the condition needs to be met prior to recruitment |
| HC use ≥ 3 months prior to recruitment for HC studies | Increase likelihood that eumenorrheic cycle has been removed and replaced by a hormonal profile indicative of HC use | Reduce occurrence of atypical hormonal profiles not fitting the characterisation of HC users | |
| Define | Increase accuracy and validity of the population definition | Reduce between study variability in describing the population studied | N/A |
| Report the type (e.g., OCPs, implants, injections, intrauterine devices/coils that are hormone releasing and NOT copper-based, vaginal rings, contraceptive transdermal patches) and formulation (e.g., mono, bi or triphasic; combined or progesterone-only; names and concentration of exogenous hormones) of HC used | Increase reliability of studies Increase validity of findings | Reduce between participant variability in hormone status Reduce between study variability in describing the population studied | Increase number of participants who need to be excluded as they do not know the exact type or formulation of HC used |
| One brand/type of OCP per group of participants [ | Increase homogeneity of hormonal profiles (both endogenous and exogenous) | Increase timescale of the study whilst trying to recruit a sufficient sample size on the same brand/type of OCP Reduce generalisability of the findings | |
| Define the | Increase accuracy and validity of the population definition | Increase timescale of the study in order to recruit participants who fit the criteria | |
| Define the | Reduce between participant variability in hormone status Reduce between study variability in describing the population studied | Increase timescale of the study in order to recruit participants who fit the criteria | |
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| Define postpartum as the 12 months following parturition | |||
| State gestation (i.e., the length of time, in days or weeks, that a baby is in the uterus) | Reduce between study variability in describing the population studied | Increase number of participants who need to be excluded as they do not know their exact gestational stage | |
| State gravidity (i.e., number of times that a woman has been pregnant, including miscarriages and abortions) | Increase timescale of the study in order to recruit women willing to state this number (can be a sensitive issue) | ||
| State parity (i.e., number of times that a woman has given birth to a foetus with a gestational age of 24 weeks or more, regardless of whether the child was born alive or was stillborn) | |||
| State singleton or multiple pregnancy | |||
| Define | Increase accuracy and validity of the population definition | Reduce between study variability in describing the population studied | Need to be aware of other physical indicators of menopause (e.g. |
| Define | Increase timescale of the study in order to recruit participants who fit the criteria | ||
| Define | Increase homogeneity of hormonal profiles Increase consistency of terminology | Reduce between participant variability in hormone status Reduce between study variability in describing the population studied | Reduce availability of eligible participants Increase timescale of the study if the condition needs to be confirmed prior to the commencement of data collection Increase number of participants who need to be excluded (during or retrospectively) if the condition was not confirmed prior to commencement of the study |
| Consider menopausal symptoms [ | To limit the effects of menopausal symptoms on outcomes | Reduce the likelihood that effects are indirectly due to symptoms rather than directly due to changes in hormones | Increase the time burden to identify participants with no, or a consistent set of, menopausal symptoms capable of affecting the intended outcome |
| Define | Increase accuracy and validity of the population definition | Reduce between study variability in describing the population studied | N/A |
| Report the type and formulation of HRT used | Increase reliability of studies Increase validity of findings | Reduce between participant variability in hormone status Reduce between study variability in describing the population studied | Increase number of participants who need to be excluded as they do not know the exact type or formulation of HRT used |
Considerations without a reference have been developed by the authors for this statement
HC hormonal contraceptives, HRT hormone replacement therapy, OCP oral contraceptive pill, LH luteinising hormone, NA not applicable
aPlease note that polycystic ovary syndrome affects between 2.2% and 26% of women worldwide, based on data from the World Health Organisation [59]
bPlease note that for women with functional hypothalamic amenorrhea (especially with the female athlete triad), this condition should be immediately corrected
Summary table of the considerations related to experimental design for women’s studies from puberty to post-menopause
| Consideration | Rationale (intended to…) | Pros (could…) | Cons (could…) |
|---|---|---|---|
| Take into account the changes in androstenedione prior to the onset of puberty (e.g., the initial increase in androstenedione has been noted 18 to 12 months prior to the onset of puberty) [ | Increase breadth of data on reproductive ageing by considering the peri-pubertal period | Increase understanding of the peri-pubertal changes in physiological functioning and athletic performance | Increase timescale of the study in order to identify and group participants along these spectrums |
| Take into account the changes in oestrogen prior to the onset of puberty (e.g., the initial increase in oestrogen has been noted 12 and 6 months prior to the onset of puberty) [ | |||
| Take into account the time scale of establishing a eumenorrheic cycle: menarche follows an anovulatory cycle; menstrual cycles during the 1st year after menarche are typically irregular and anovulatory, ranging in duration from 21 to 45 days; by 3 years post-menarche, > 90% of girls have ≥ 10 menstrual cycles per year with an average menstrual interval of 36.5 days; cycles can remain irregular until the 5th year post-menarche [ | Reduce assumption that once menarche has been initiated all girls have fully eumenorrheic cycles | Reduce between participant variability in hormone status | |
| Define menstrual cycle phases based on hormonal profiles (see Table | Increase reliability of studies Increase validity of findings | Reduce likelihood of grouping non-homogenous hormonal profiles Reduce inconsistency in phase definitions between studies | Increase timescale of the study in order to recruit participants who are willing to undertake blood sampling Increase cost of the study |
| Track and establish menstrual cycle characteristics for ≥ 2 months prior to testing. Tracking can be achieved by denoting the first and the last day of menstruation on a calendar for each cycle. Corroboration can be achieved by confirmation of ovulation and hormone concentrations | Reduce within participant variation in menstrual cycle characteristics Reduce likelihood of including participants with menstrual irregularities in eumenorrheic studies Increase ability to accurately predict testing timepoints (i.e., phases) | Increase timescale of the study due to the long lead-in time Increase burden on participants to track their cycles before the experimental aspect of the study | |
| Outcome measures should be repeated in a second cycle | Reduce variability of the data | Increase timescale of the study due to the repeated measures Increase burden on participants to repeat all of the testing sessions | |
| Use urinary ovulation kits to establish the mid-cycle surge in LH; visual confirmation should be provided to the researcher [ | Reduce risk of including anovulatory women in eumenorrheic studies Reduce chance of a false positive result by the participant from an at-home interpretation | Increase chance of missing a positive ovulation result in participants who do not comply or adhere to conducting the test at the same time of day Increase likelihood of overlooking LPD as this method does not exclude LPD cycles | |
| Apply a posteriori exclusion of data from testing timepoints which do not comply with the theoretical (see Fig. | Ensure that the intended reproductive profiles were assessed | Reduce likelihood of grouping non-homogenous hormonal profiles | Increase number of participants who need to be excluded (retrospectively) as a result of not fitting the inclusion criteria |
Stipulate and take into account OCP-taking (i.e., active OCP) days and OCP-free (i.e., inactive/placebo OCP) days: (i) The endogenous concentration of oestrogen and progesterone rises during the OCP free/inactive/placebo days [ (ii) The concentration of exogenous hormones increases during active OCP intake: for example, for a combined monophasic OCP ethinyl estradiol (a type of exogenous oestrogen) increases twofold from day 1 of active OCP to day 21 [ | Increase homogeneity of hormonal profiles | Reduce between participant variability in hormone status | Increase timescale of the study if several conditions need to be assessed |
| Take into account the rising concentrations of oestrogen and progesterone throughout each trimester of pregnancy | Increase timescale of the study in order to identify and group participants along this spectrum | ||
| Take into account the large variation in hormonal profiles associated with the peri-menopause, menopause and post-menopause, thus treating these as separate categories of women based on the criteria outlined in Table |
Considerations without a reference have been developed by the authors for this paper. OCP oral contraceptive pill, LPD luteal phase deficiency, LH luteinising hormone
Fig. 4Visual overlay of the hormonal changes across an idealised 28-day menstrual cycle indicating when each phase begins and ends as described in Table 3. The solid gold line represents oestrogen the short dash purple line represents luteinising hormone and the long dash green line represents progesterone. The black dots represent the mean concentration of oestrogen during each phase and the black diamonds represent the mean concentration of progesterone in each phase
Proposed menstrual cycle phase definitions based on hormonal profiles (see Fig. 4)
| Recommendation | Rationale (intended to…) | Pro | Con |
|---|---|---|---|
Oestrogen and progesterone levels are low | Capture the lowest concentrations of oestrogen and progesterone | Easy to determine due to obvious physical cue (i.e., bloody discharge) | Can be difficult to predict in those with variable cycle length therefore requiring reactive testing sessions (i.e., participant alerting the researcher on day 1 of bleeding and then both parties having availability for testing within the next 4 days) |
Oestrogen higher than during phase 1, 3 and 4 and progesterone higher than during phase 1, but lower than 6.36 nmol·L−1 | Capture the highest oestrogen concentration, while progesterone remains low | Enables the biggest difference between oestrogen and progesterone to be investigated | Difficult to predict without daily blood samples for the determination of oestrogen and progesterone |
Oestrogen higher than phase 1 but lower than phase 2 and 4 and progesterone higher than phase 1 but lower than 6.4 nmol·L−1 | Capture a medium oestrogen concentration, while progesterone remains low | Easy to establish due to the positive LH surge captured by the ovulation kit | Relies on having multiple ovulation kits available for each participant (cost) and requires reactive testing sessions (i.e., participant alerting the researcher to the positive result and then both parties having availability for testing within the next 24–36 h) |
Oestrogen higher than phase 1 and 3 but lower than phase 2 and progesterone > 16 nmol·L−1 | Capture the highest concentration of progesterone and a high concentration of oestrogen | Easy to establish in those with eumenorrheic cycles as it typically occurs within 7 days of confirmed ovulation | Relies on the confirmation of ovulation |
LH luteinising hormone
These recommendations have been developed using information from the following sources: McGovern et al. [69]; Tsampoukos et al. [70]; Janse de Jonge et al. [48]; Elliott-Sale et al. [71]. The phases described in Table 3 are referred to as number (i.e., 1–4), rather than names (i.e., follicular, ovulatory and luteal), to reduce the misidentification or mislabelling of phases. This should ensure that phases are described based on quantifiable metrics rather than ambiguous terms. In order to draw comparisons with previous literature the following matches can be used: phase 1 with the ‘early follicular’ phase; phase 2 with the ‘late follicular’ phase; phase 3 with the ‘ovulatory’ phase; and phase 4 with the ‘mid-luteal’ phase. To date, no consensus has been reached within sport and exercise science on the nomenclature used to describe menstrual cycle phases and their corresponding hormonal profiles
General research considerations
| Consideration | Rationale (intended to…) | Pros (could…) | Cons (could…) |
|---|---|---|---|
| Employ a single-blind design; although participants cannot be blinded, the researcher can be blind to the intended testing timepoint | Protect against bias | Reduce unintentional bias from the researcher to the participant | Increase staffing as an independent person is needed to undertake the blinding process |
| Do not use unclassified (i.e., not stating reproductive status) women as participants even if you are not concerned by the potential influence of reproductive hormones on your outcome measure | Increase homogeneity of hormonal profiles | Reduce between participant variability in hormone status Increase validity of the data | Reduce the availability of eligible participants |
| Standardise, by quantitative means, time of day, prior exercise, caffeine ingestion, dietary intake and nutritional supplementation, alcohol consumption and smoking as these have been shown to affect the concentration of reproductive hormones | Control extraneous variables | Allow the investigation of X on Y, without the influence of Z | Adds more requirements on the participants by asking them to standardise a large number of variables over a set period of time |
| Use the term “withdrawal bleed” rather than “period” when referring to the bleed experienced by OCP users | Stop OCP users misidentifying themselves as eumenorrheic based on bleeding patterns | Education; informing women and researchers about the differences between hormonal contraceptive users and non-users | |
| Do not use the terms “menstrual cycle” and “periods” synonymously | Dispel the myth that they are the same things and that these terms can be used interchangeably | Education; informing women and researchers about menstrual cycles and how periods are just one aspect of that cycle | |
| Do not impose any menstrual cycle language upon HC users ( | Prevent confusion between hormonal contraceptive users and non-users | Allows HC users to describe their own status without adding unnecessary complexity or without misperception | |
| Report gestational age based on ultrasound dating rather than on last menstrual period | Increase the accuracy of reporting of gestational age | Reduce the ambiguity in defining participants in studies involving pregnant women | |
| Consider the timescale for resumption of eumenorrheic cycles following childbirth (i.e., in the postpartum period), given that this varies considerably between women | Reduce the assumption that all postpartum women who do not use hormonal contraceptives have eumenorrheic cycles | Reduce ambiguity in defining participants in studies involving postpartum women | |
| Do not use the term post-menopausal based on participants’ age solely | Protect against including irrelevant participants and to increase the homogeneity of hormonal profiles | Reduce between participant variability in hormone status Increase validity of the data | Increase the time and economic burden to correctly identify and confirm post-menopausal status |
| Do not report gynaecological age (i.e., number of years from menarche to recruitment in the study) as a characteristic of menstrual function (i.e., to illustrate the number of years with eumenorrheic menstrual cycles) | Reduce the assumption that the time between menarche and recruitment is filled with eumenorrheic cycles | Reduce ambiguity in defining participants in studies involving eumenorrheic women | |
| Include an online supplement with additional in-depth information about reproductive status; e.g., data from questionnaires on menstrual cycle status or hormonal contraceptive use, blood marker data, etc | Provide data that can be used for future meta-analyses in studies with women as participants | Quickly increase our understanding of female physiology in relation to sport and exercise science |
The considerations in this table have been developed by the authors for this paper
HC Hormonal contraceptives, OCP oral contraceptive pill OCP
| Not all ‘women’ are the same. Women have a variety of reproductive hormonal profiles that change across the lifespan from puberty to the menopause. |
| The endogenous hormonal profile of women is frequently influenced by exogenous sources, such as hormonal contraceptives (HC) and hormone replacement therapy (HRT). |
| Depending on the research question, women should be recruited on pre-defined, standardised criteria, which, in most cases, should be retrospectively confirmed (i.e., homogenous a priori inclusion and a posteriori exclusion criteria). |
| Depending on the research question, the experimental design needs to be adapted in line with the hormonal milieu (e.g., consideration of menstrual cycle phase, type of HC used, stage of menopause). |