Estimating age of menopause in mothers in the ALSPAC Study: A data note.

The UK Biobank asked women to report their age at menopause during the baseline assessment and the mean reported age was 49.8 years (median 50, SD = 5.1). The Study of Women’s Health Across the Nation (SWAN Study), a longitudinal study in the US, found a median age at natural menopause of 51.4 years in its cross-sectional screener data (n = 14,620) 31 and slightly higher at 52.5 years among longitudinal cohort participants (n = 1,483). 32 The higher estimate in the longitudinal cohort likely reflects selection factors: women who had already reached menopause before age 42 were excluded from follow-up, and attrition over time disproportionately affected women with characteristics linked to earlier menopause (e.g., smokers, lower education, poorer health). Other studies report a median self-reported age at menopause among White women from industrialized countries ranging between 50 and 52 years. 33 – 37 In our sample, the mean age at menopause was 49.4 years (median 50 years), slightly lower than in other studies but still comparable. This discrepancy may be partly due to the mean age at several timepoints falling below the typical menopausal age range. As a result, women who experienced menopause earlier may have been more likely to be captured, while those who reached menopause at older ages may have been underrepresented. This could have biased the estimated distribution of menopausal age toward younger ages, potentially explaining the lower age at menopause in our sample compared to other studies. When further data is available from more recent follow-ups, this estimation should be re-calculated.

Women were asked a set of detailed questions about their menstrual cycles including when they last had a menstrual period (LMP), reasons for period cessation if relevant, and their use of contraception and hormone replacement therapy (HRT), at eight timepoints, via postal questionnaires or in-person clinic assessments. Table 1 summarises the data collection timepoints, the number of questionnaire responses or clinic attendees, the year of completion, and the mean age at each timepoint. The average age at completion ranged from 47.4 (standard deviation [SD] 4.5) to 57.7 years (SD 4.5). A complete list of the questions and response options used to determine women’s date of LMP at each timepoint, i.e. their most recent menstrual period, is presented in Table 2 . Despite minor differences in wording and response options, the questions were comparable across timepoints. Table 3 provides the corresponding ALSPAC variable names and source file locations. All questionnaires and clinic assessments used in ALSPAC are publicly available to view on the study website . The specific questionnaires used in this analysis have also been uploaded to our project’s GitHub repository [ https://github.com/RochelleKnight/Estimating-age-of-menopause-in-mothers-in-the-ALSPAC-Study ]. Questionnaire MB followed a different structure for the reproductive health questions than the other questionnaires/clinics. It was therefore not used to assign dates of LMP as described under the section “ Assigning date of LMP when self-reported date of LMP has been reported (completely or incompletely)” however is included in the above table for completeness. See Extended Material for details on how data from Questionnaire MB were incorporated. If a participant answered ‘No’ to ‘In the last 12 months have you had a period or menstrual bleeding?’, they were then asked the question ‘Were your periods stopped by:’ More than one response was allowed to be marked. Questioned asked as ‘Currently using contraceptive injection or implant’. Split into three questions each asking about tablets, patches or creams. In brief, information was obtained on the day, month and year of reported date of LMP, whether a period occurred in the last 12 months (yes/no), whether a period occurred in the last 3 months (yes/no), what caused menstruation to stop if relevant, occurrence of any surgical operations relating to reproductive organs, and if the women were taking hormonal contraceptives or HRT.

Rochelle Knight: Conceptualization, Methodology, Software, Data Curation, Writing – Original Draft. Abigail Fraser: Conceptualization, Methodology, Writing – Review & Editing, Supervision. Carol Joinson: Conceptualization, Methodology, Writing – Review & Editing, Supervision. Ana Gonçalves Soares: Conceptualization, Methodology, Software, Writing – Review & Editing, Supervision.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a longitudinal birth cohort that recruited pregnant women with an expected date of delivery between April 1991 and December 1992 residing in Avon, UK. The initial ALSPAC sample consisted of 14,541 pregnancies, from 14,203 unique mothers (338 mothers having two enrolled pregnancies), which resulted in 14,062 live births. As a result of the additional phases of recruitment, a further 630 mothers who did not enrol originally have provided data since their child was 7 years of age. This provides a total of 14,833 unique mothers (known as the Generation 0 or G0) enrolled in ALSPAC. Since recruitment, mothers, their children and partners have been followed-up through questionnaires, research clinic assessments and data linkage. Since 2014, study data have been collected and managed using REDCap (Research Electronic Data Capture), a secure, web-based platform hosted at the University of Bristol. 26 REDCap is specifically designed to support data capture and management in research studies. Details on the representativeness, cohort profiles and recruitment have been extensively described in previous publications. 27 – 30 The ALSPAC study website contains details of all data available through a fully searchable data dictionary and variable search tool ( http://www.bristol.ac.uk/alspac/researchers/our-data ). In this study prospective data from ALSPAC G0 mothers was used. Ethical approval for the ALSPAC study was obtained from the ALSPAC Law and Ethics Committee and local research ethics committees. These approvals cover all core study data collection, including the questionnaires and clinic data that are used in the present analysis. All questionnaire content was reviewed and approved by the ALSPAC Ethics and Law Committee. Initial approvals for the establishment of the cohort were granted by: Bristol and Weston Health Authority (E1808, Children of the Nineties: Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC)) , approved 28th November 1989; Southmead Health Authority (49/89, Children of the Nineties – “ALSPAC” ), approved 5th April 1990; and Frenchay Health Authority (90/8, Children of the Nineties ), approved 28th June 1990. Approval details for all subsequent clinics (committee, approval number, dates) are available here: https://www.bristol.ac.uk/media-library/sites/alspac/documents/governance/Research_Ethics_Committee_approval_references.pdf Informed consent for the use of all data was obtained from participants in accordance with the recommendations of the Ethics and Law Committee at the time. The completion of a questionnaire, either on paper or online, was considered to be written consent from participants to use their data for research purposes. Participants can contact the study team at any time to retrospectively withdraw consent for their data to be used. Study participation is voluntary and during all data collection sweeps, information was provided on the intended use of data. Full details of the ALSPAC consent procedure are available on the study website . In addition to these study-level approvals, researchers are required to submit individual level project proposals for consideration by the ALSPAC Executive Committee. The present project received such approval before data access was granted.

In ALSPAC, women in the mothers cohort were asked their age at menopause in one questionnaire (Questionnaire U). This questionnaire was completed by 4,423 women at a mean age of 49.7 (SD 4.5). Of these, 1,616 reported their age of menopause (mean 48.65, SD 4.0), 2,536 women reported that they had not yet been through the menopause, and the remaining responses were missing. Previous studies have derived the timing of the final menstrual period (FMP) in ALSPAC 23 – 25 ; however, detailed descriptions of the derivation methods have generally not been reported. These studies excluded women who reported hormonal medication use at any time, rather than excluding only the specific timepoints where use was reported. They also did not incorporate the self-reported age at menopause variable. In addition, earlier approaches relied primarily on clinic data, as these were linked to the outcomes being analysed, despite questionnaire data also collecting information on menstrual bleeding history. The method presented here was developed to provide a transparent and reproducible approach to estimating the FMP in ALSPAC. Our approach builds on previous work but refines the derivation by incorporating information from both questionnaires and clinic assessments and by making use of multiple questions relating to menstrual bleeding history. The approach also draws on guidance from the Stages of Reproductive Aging Workshop (STRAW) framework to inform the classification of menopausal status. We explicitly consider inconsistencies between responses and outline a systematic approach to handling missing data. By documenting this approach, we aim to provide a consistent FMP variable that can be used by future researchers working with ALSPAC data. The approach is designed to be flexible: it can be extended as additional data becomes available. This approach can also be useful for other studies with prospective information on menstrual bleeding history, which may encounter similar challenges.

One of the key strengths of the ALSPAC dataset is the availability of repeated data on menstrual cycles. This longitudinal information provides a detailed view of menstrual changes over time, capturing the often-irregular patterns characteristic of the menopause transition. As a result, it allows for more accurate estimation of age at menopause compared to relying solely on retrospective self-reports, which are prone to recall error. 21 , 22 Additionally, the repeated data support future work to classify woman into menopausal stages - premenopause, perimenopause and postmenopause - using the Stages of Reproductive Aging Workshop (STRAW) + 10 38 criteria. A broad challenge was the potential for incorrect estimation of age at menopause due to missing, incomplete, or inconsistent reporting of menstrual history. Responses to “ In the last 12 months have you had a period or menstrual bleeding? ”, “ In the last 3 months have you had a period or menstrual bleeding? ” and “ When was your last period? ” did not always align. Although consistency checks were performed to reconcile discrepancies, misreporting of LMP may still have affected the estimation of age at menopause. In some cases, we identified likely misclassification. For example, 80 women reported a period of amenorrhea lasting more than 12 months at one timepoint, suggesting menopause, but subsequently reported menstruating within the last year at a later timepoint. This highlights the limitations of relying on self-reported data to determine menopausal status. Ultimately, we used the most recent plausible reported LMP to define age at menopause. In longitudinal data with repeated and occasionally conflicting reports, a single LMP must be selected to estimate age at menopause, and we considered the most recent plausible report to provide the most reliable representation of menstrual status across follow-up. As a result, 37 of these women do not have an estimated age at menopause, despite previously indicating a period of amenorrhea consistent with menopause. Another limitation is the lack of information on when women discontinued hormonal contraceptives or HRT. While current use was recorded, there was no data on the timing of discontinuation. Because hormonal medications can obscure natural bleeding patterns, menopausal status—and particularly the timing of the final menstrual period—cannot be reliably determined while a woman is using them. We therefore excluded timepoints where hormone use was reported. However, if a woman reported hormone use at one timepoint but not at a later timepoint, we lacked information on how long had elapsed since discontinuation, and could not determine natural menstrual cycles had resumed. Consequently, a reported LMP could reflect bleeding prior to starting hormones, a withdrawal bleed, or a natural period. Some women may have also reached menopause while still using hormonal medications, meaning the menopausal transition was not captured, and their age at menopause could not be estimated. These limitations may have affected the accuracy of LMP reporting and, consequently, the estimation of menopausal age. While the exclusion of timepoints where hormonal medications were reported was necessary, it may have introduced bias into the age at natural menopause. Overall, 35% of women ever reported the use of hormonal medications. Of these, 25% had a derived age at natural menopause, compared with 39% of women who never reported hormonal medication use. Women who used hormonal medications may therefore be underrepresented among those with a derived age at natural menopause. If women experiencing more severe menopausal symptoms were more likely to initiate HRT before their final menstrual period, this could lead to underrepresentation of women with more symptomatic menopausal transitions. Researchers using this variable should therefore consider the potential for selection bias and assess the impact of hormonal medication use where possible. The often large gaps between attended timepoints also posed challenges. While the average interval between attended timepoints was 2.1 years, some exceeded 10 years. In such cases, when the only available information was a report of no menstruation in the last 12 months, menopause likely occurred sometime during the intervening years. However, without more precise or frequent data, age at menopause could not be reliably assigned, contributing to potential misclassification and underestimation of menopausal age. Finally, the structure of Questionnaire Y limited our ability to assign LMP dates at that timepoint. Whereas most questionnaires asked all women about menstruation in the last 12 and 3 months and to report the date of their LMP, Questionnaire Y only asked for an LMP date if the woman reported menstruating in the last 12 months. As a result, we could only assign an LMP date for a subset of women at this timepoint—those still menstruating—limiting the usefulness of these data for estimating age at menopause and adding to the broader challenges described above.

Menopause is defined as the permanent cessation of menstruation, marking the loss of ovarian follicular activity. 1 , 2 It occurs with the final menstrual period (FMP) and is typically diagnosed retrospectively after 12 months of amenorrhoea. 1 , 3 Age at menopause is a marker of aging and overall health. A later age at menopause has been associated with increased life expectancy 4 and reduced all-cause mortality, 5 as well as a lower risk of cardiovascular disease 4 , 6 – 12 and osteoporosis. 13 , 14 It is also linked to a higher risk of breast, 15 , 16 endometrial, and ovarian cancers. 4 , 17 – 20 Previous studies have mostly relied on retrospective self-reports of age at FMP, which are susceptible to recall error, particularly when many years have passed since the menopause. 21 , 22 While prospective data on menstrual cycles can help capture the variability in menstrual patterns and reduce recall error, accurately identifying the age at menopause using repeated, prospective data can pose challenges. In this data note, we describe our approach to estimating the age at natural menopause using repeated menstrual cycle data from participants in a UK birth cohort.

Age at natural menopause was determined using both a derived measure based on menstrual bleeding history data and self-reported age at menopause, whenever available. Having assigned LMP dates as described above, we defined the final menstrual period (menopause) as occurring if a woman’s most recent LMP was more than 365 days before the date of attendance at her last assessment. Age at menopause was then defined as age at FMP. Self-reported age at menopause was derived from multiple questionnaires. Questionnaires T, V, and Y asked, “What was your age at your last menstrual period?”. If the reported age was at least one year prior to the respondent’s current age, it was assigned as self-reported age at menopause. Questionnaire U (completed in 2011–2012 by 4,423 women) directly asked, “What was your age at menopause?”. The maximum self-reported age at menopause across Questionnaires U, T, V, and Y was assigned as each woman’s self-reported age at menopause. To ensure consistency between sources, we applied a validity check: self-reported age at menopause had to be no more than two years earlier than the age at the most recent LMP, otherwise it was excluded. This helped reduce instances where self-report and LMP data conflicted in implausible ways. For example, consider a woman who reported a LMP within the last 12 months at age 52, meaning she was not yet classified as postmenopausal. At a later timepoint, aged 54, she reported her last menstrual period occurred at age 50 via the question “What was your age at your last menstrual period?”. If taken at face value, this would suggest she was already postmenopausal by age 52, contradicting her earlier LMP report. To allow for some inconsistency in recall or reporting, we accepted self-reported ages at menopause only if they were after the most recent LMP, or within two years prior to it. This threshold provided a balance between data inclusion and plausibility. If a woman only had self-reported age at menopause, this value was used. Otherwise, we prioritised the menopause age derived from longitudinal menstrual reports, as it is less likely to be affected by recall bias.

As age of menopause is estimated based on menstrual bleeding patterns, we also considered factors that affect menstrual bleeding and therefore could result in an inaccurate assessment of menopausal status. These include surgery of reproductive organs, use of contraceptives and HRT, and other reasons such as chemotherapy or radiation therapy, ablation/resection, pregnancy, or breastfeeding. All women were asked in questionnaires and clinics whether they had undergone any surgeries to remove their reproductive organs (see Table 2 for full list of options). Response options that would result in the cessation of menstruation were as follows: • Hysterectomy with bilateral oophorectomy (removal of uterus and both ovaries) • Bilateral oophorectomy (removal of both ovaries) • Hysterectomy (removal of uterus) • Hysterectomy with unilateral oophorectomy (removal of uterus and one ovary) Hysterectomy with bilateral oophorectomy (removal of uterus and both ovaries) Bilateral oophorectomy (removal of both ovaries) Hysterectomy (removal of uterus) Hysterectomy with unilateral oophorectomy (removal of uterus and one ovary) Women who reported any of these surgeries were asked to provide the date and age at which the procedure was performed. If a woman did not explicitly report undergoing surgery but provided either an age or a date of surgery, it was assumed that she had the procedure. Conversely, women who reported surgery but did not provide a date or age were excluded. As a separate question, women who reported no menstrual bleeding in the last 12 months were asked to indicate the reason for cessation (see Table 2 for full list of options). Surgical reasons included: Surgery, Hysterectomy and Oophorectomy, without further detail. We assumed that reports of ‘Surgery’ and ‘Oophorectomy’ would result in the cessation of all subsequent menstruation. The women were not asked to report the date of surgery, hence the date and age at questionnaire completion or clinic attendance were used as proxies. The overall date and age at surgery were taken as the earliest reported values. Any timepoints following surgery were excluded. Estimations of date of LMP were made for timepoints preceding surgery. If self-reported age at menopause age derived from Questionnaires T, U, V and Y was greater than or equal to the surgery age, it was set to missing. At all eight timepoints, women were asked whether they were currently using hormonal contraceptives or HRT. Table 2 summarises the specific questions and response options related to contraceptive and HRT use for all for all questionnaires and clinic assessments. Because hormonal medications can affect menstrual bleeding patterns, menopausal status cannot be determined when these medications are being used. Therefore, any timepoints at which current use of hormonal contraceptives or HRT was reported were excluded. Women who reported no menstrual bleeding in the last 12 months were asked to indicate the reason for cessation (see Table 2 for full list of options). Timepoints were excluded if the reported cause was chemotherapy or radiation therapy; ablation/resection; pregnancy, or breastfeeding; or other reason/other medical reason.

Figure 6 shows participant flow from recruitment through to analysis. After accounting for withdrawal of consent, 14,833 unique G0 women were enrolled in the ALSPAC study, of whom 7,197 responded to at least one relevant timepoint. Thirty-five women were excluded due to reporting a surgical procedure that would have ceased menstruation without providing the date or age at surgery. After applying exclusion criteria, 5,949 women remained, contributing an average of 3.6 responses each. We were able to assign at least one LMP date for 5,339 of these women. We derived an age at natural menopause - using both age derived from menstrual bleeding history and self-reported age - for 2,422 women. The overall average age at menopause was 49.4 years (SD = 4.1, range: 30–63 years, median = 50 years). Of these, 2,111 women had an age derived from menstrual history data (mean = 49.6 years, SD = 4.1, range: 30–63), and 311 based on self-reported age at menopause (mean = 48.2 years, SD = 4.0, range: 34–61). A total of 1,322 women had both a derived and self-reported age at menopause, with a correlation 0.75 between the two measures. We were unable to derive an age at natural menopause for 3,588 women. At their final attended timepoint, these women had a mean age of 51.5 years (SD: 5.9, range: 34–68). Of them, 1,982 had experienced an LMP within the last 12 months. An additional 1,483 women (mean age = 56.9 years, SD = 3.1) reported that they had not had a period in the last 12 months, likely indicating they were postmenopause, however lacked sufficient data to estimate a final menstrual period. Figure 7 displays the distribution of age at menopause within the sample.

Access to ALSPAC data is available through a system of managed open access. Application steps to request access to ALSPAC data are highlighted below. 1. Please read the ALSPAC access policy (PDF, 621kB ) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse our fully searchable research proposals database , which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. Please read the ALSPAC access policy (PDF, 621kB ) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. You may also find it useful to browse our fully searchable research proposals database , which lists all research projects that have been approved since April 2011. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. Any questions regarding data or sample access should be directed to [email protected] (data) or [email protected] (samples). The final derived ‘Age at Menopause’ variable will returned to ALSPAC and made available to other researchers as part of the ALSPAC data resource. Extended Materials and source code are available on GitHub: https://github.com/RochelleKnight/Estimating-age-of-menopause-in-mothers-in-the-ALSPAC-Study Archived software available from: https://doi.org/10.5281/zenodo.17236215 License: MIT License.