Household and housing determinants of sleep duration during the COVID-19 pandemic: Results from the COHESION Study
Bibliographic record
Abstract
BACKGROUND: Public health measures in response to the COVID-19 pandemic forced individuals to spend more time at home. We sought to investigate the relationship between housing characteristics and sleep duration in the context of COVID-19. METHODS: Our exploratory study was part of the COvid-19: Health and Social Inequities across Neighborhoods (COHESION) Study Phase-1, a pan-Canadian population-based cohort involving nearly 1300 participants, launched in May 2020. Sociodemographic, household and housing characteristics (dwelling type, dissatisfaction, access to outdoor space, family composition, etc.), and self-reported sleep were prospectively collected through COHESION Study follow-ups. We explored the associations between housing and household characteristics and sleep duration using linear regressions, as well as testing for effect modification by income satisfaction and gender. RESULTS: Our study sample involved 624 COHESION Study participants aged 50 ± 16years (mean±SD), mainly women (78%), White (86%), and university graduates (64%). The average sleep duration was 7.8 (1.4) hours. Sleep duration was shorter according to the number of children in the household, income dissatisfaction, and type of dwelling in multivariable models. Sleep was short in those without access to a private outdoor space, or only having a balcony/terrace. In stratified analyses, sleep duration was associated with housing conditions dissatisfaction only in those dissatisfied with their income. CONCLUSION: Our exploratory study highlights the relationship between housing quality and access to outdoor space, family composition and sleep duration in the context of COVID-19. Our findings also highlight the importance of housing characteristics as sources of observed differences in sleep duration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".