Sleep health among preconception women: Findings from the PREGO study
Bibliographic record
Abstract
Sleep is particularly critical during the preconception period, as it can impact the health of both women and their potential offspring, but data specifically on preconception sleep health are scarce. The study objective was to document sleep health and its correlates among preconception women. Females (18-45 years) from Canada and who are trying to conceive were recruited to participate in the PREGO Study. Sleep health (duration, quality, and disorders) was measured using the Sleep Health Index. Sociodemographic (age, marital status, level of education, income, ethnic or cultural origins, weight and height), pregnancy-related (gravidity), behavioral (physical activity level, alcohol and caffeine intake, nicotine and cannabis use) and psychological (marital happiness, life satisfaction, depressive and anxiety symptoms, stress, psychological distress) data were self-reported using validated questionnaires. Multivariable linear regression analyses were used to identify correlates of preconception sleep health. Preconception sleep health data were available for 620 women (mean age: 29.9 ± 3.5 years; 67.6% nulligravid). Participants' global sleep health score was 71.5 ± 14.4 (out of 100, with higher scores indicating better sleep health) and 81.3% had sleep duration variability between weekdays and weekends. Depression (β = -1.60; 95% CI: -1.99, -1.22) and life satisfaction (β = 0.39; 95% CI: 0.11, 0.67) were significant correlates and explained 16% of the variance in sleep health. Preconception women appear to have good overall sleep health, but for many their sleep duration varies between weekdays and weekends. Having higher levels of depressive symptoms was associated with worse sleep health, while good sleep health was associated with higher life satisfaction. It may be worthwhile to ask women wishing to conceive - especially those with depressive symptoms - about their sleep health. These results can be useful for healthcare providers with female patients planning a pregnancy and preconception women who wish to optimize their sleep health as it may benefit both women and their future offspring.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".