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Record W6942312955 · doi:10.14288/1.0449527

The relationships of menopause and hormone replacement therapy on modifiable health behaviours

2025· article· en· W6942312955 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2025
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMenopauseHormone replacement therapy (female-to-male)Body mass indexLogistic regressionPhysical activityAlcohol intakePhysical fitnessPhysical exerciseGuideline

Abstract

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Background: Menopause and hormone replacement therapy (HRT) may be associated with changes in modifiable health behaviours (MHBs). However, their independent and synergistic role on MHBs and national health guideline adherence is unclear. This study characterized MHBs (dietary intake, physical activity, and sleep) in general and in relation to guidelines among females based on menopause/HRT status. Methods: Females from the Canadian Longitudinal Study on Aging were classified into four groups: 1) pre/perimenopausal, 2) post-menopausal and have never used HRT, 3) post-menopausal with past HRT use, or 4) post-menopausal with current/recent HRT use. MHBs were collected via questionnaires. Dietary intake was categorized into five groups: grains, fruit/vegetables, dairy, proteins, fats, or processed foods. Physical activity was classified into walking/light, moderate-vigorous, and strength-based activities (minutes/week). Sleep was expressed as mean sleep duration over the past month (hours/night). Linear mixed models compared MHBs across four groups (reference: pre/perimenopausal females), and binary logistic regressions assessed adherence to physical activity and sleep guidelines, adjusting for age, body mass index (BMI), race, marital status, income, education, alcohol intake, and smoking status. Results: A total of 10,381 females were included (median [IQR] age: 60 [15] years; BMI: 27 [7] kg/m²). Fruit/vegetables, fats, and processed foods were lower in post-menopausal females who have never used HRT (β=-0.058±0.140, β=-0.086±0.026, β=-0.118±0.026; all p≤0.001) and past HRT users (β=-0.038±0.017, p=0.002; β=-0.075±0.018, p=0.021; β=-0.116±0.031; all p<0.001). Proteins intake was higher in post-menopausal current HRT users (β=0.058±0.018, p=0.002). Walking/light and moderate-vigorous activity were higher in post-menopausal females who have never used HRT (β=0.103±0.032, p=0.001; β=0.095±0.041, p=0.019) and current HRT users (β=0.108±0.047, p=0.021; β=0.130±0.061, p=0.032). The overall model intercept was significant for strength-based physical activity (p=0.037), with no post hoc differences across menopause/HRT groups. Sleep duration was shorter in post-menopausal females who have never used HRT (Mean±SD: 6.8±1.2); β=-0.093±0.036, p=0.010), but was longer in post-menopausal current HRT users (7.0±1.3; β=0.123±0.054, p=0.023). The model intercept for meeting sleep guidelines was significant; post-menopausal current and past HRT users met 22% and 20% less, respectively (β=-0.248±0.094, p=0.009; β=-0.223±0.078, p=0.004). Conclusion: Menopause and HRT status may influence MHBs, highlighting the need for future research on interventions addressing these factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.259
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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