Exploring heterogeneity in the associations between menopausal status and depression: a cross-sectional study with a unique analytical approach
Bibliographic record
Abstract
OBJECTIVES: The extent to which menopause status contributes to depressive symptoms remains controversial. This study aimed to examine associations between menopausal status and depressive symptoms and the heterogeneity in these associations. METHODS: We conducted three consecutive national surveys of community-dwelling Australian women aged 18-79 years between October 2013 and July 2017. Depressive symptoms were measured by Beck Depression Inventory II (BDI-II) score (range 0-63). Symptoms were classified into a binary outcome of minimal to mild (BDI-II score <20) and moderate to severe (MS) (BDI-II score ≥20). The average effect (average treatment effect [ATE]) and conditional average effect of the menopausal status on depressive symptoms were investigated by causal forest method. RESULTS: The prevalence of MS depressive symptoms in 10,351 participants was 23.7% (95% CI: 22.9-24.5). Compared with premenopause, the BDI-II score was higher for the menopause transition (ATE = 2.43 units, 95% CI: 1.20-3.65) and postmenopause (ATE = 3.03 units, 95% CI: 1.25-4.81). Compared with premenopause, the menopause transition was associated with an average increase in the prevalence of MS depressive symptoms by 6 percentage points (ATE = 0.06, 95% CI: 0.01-0.12). There were no differences in depressive symptoms between the menopause transition and postmenopause.In menopause transition, the BDI-II score was -1.22 units lower and the prevalence of MS depressive symptoms was 5 percentage points lower among employed women compared with unemployed women. In postmenopause, the BDI-II score was 1.75 units higher for unpartnered women compared with partnered women. CONCLUSIONS: The menopause transition and postmenopause are associated with a higher BDI-II score and an increased prevalence of MS depressive symptoms compared with premenopause. These associations are favorably modified by paid employment in the menopause transition and unfavorably by being unpartnered postmenopause.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".