Sex Differences in the Association of Tobacco Use with Sleep Patterns in Adults
Bibliographic record
Abstract
ABSTRACT Objectives: We aimed to assess the relationships of sleep duration and trouble sleeping with tobacco use, as well as sex differences in these associations. Methods: Data from the 2005 to 2018 National Health and Nutrition Examination Survey were used. Multinomial logistic regression was used to investigate the relationship between tobacco use and sleep duration, while logistic regression models examined the association between tobacco use and sleep difficulties, with stratification by sex for significant interactions. Results: This study included 33,923 participants, with 8666 (26.41%) reporting trouble sleeping. Individuals who reported smoking cigarettes had increased odds of having shorter [adjusted odds ratio (aOR)=1.63; CI=1.47, 1.80; P <0.001] or longer (aOR=1.53; CI=1.21, 1.93; P <0.001) than average sleep durations, as well as higher odds of experiencing trouble sleeping (aOR=1.41; CI=1.26, 1.58; P <0.001) compared with nontobacco users. In addition, participants who reported smoking other forms of tobacco had increased odds of having shorter-than-average sleep durations (aOR=1.26; CI=1.04, 1.53; P =0.018). There were no significant associations between the use of other tobacco products and trouble sleeping. Female cigarette users had greater odds of having trouble sleeping (aOR=1.58; CI=1.38, 1.81; P <0.001) than males. Conclusion: Cigarette smoking is significantly associated with both long and short sleep durations and trouble sleeping. Future studies should seek to replicate these findings and evaluate the mechanisms underlying this phenomenon. Objectifs: Nous avons cherché à évaluer la durée du sommeil et les troubles du sommeil en relation avec le tabagisme, ainsi que les différences entre les sexes dans ces associations. Méthodes: Nous avons utilisé les données de l’enquête nationale sur la santé et la nutrition en provenance de 2005-2018. La régression logistique multinomiale a été utilisée pour étudier la relation entre le tabagisme et la durée du sommeil, tandis que les modèles de régression logistique ont examiné l’association entre le tabagisme et les troubles du sommeil, avec une stratification par sexe pour les interactions significatives. Résultats: Cette étude a inclus 33 923 participants, dont 8 666 (26,41%) ont signalé des troubles du sommeil. Les personnes ayant déclaré fumer des cigarettes avaient plus de chances d’avoir des durées de sommeil plus courtes (aOR=1,63 ; CI=1,47, 1,80 ; P <0.001)) ou plus longues (aOR=1,53 ; CI=1,21, 1,93 ; P <0,001) que la moyenne, ainsi que plus de chances d’avoir des troubles du sommeil (aOR=1,41 ; CI=1,26, 1,58 ; P <0,001) par rapport aux non-consommateurs de tabac. En outre, les participants ayant déclaré fumer d’autres formes de tabac étaient plus susceptibles d’avoir des durées de sommeil plus courtes que la moyenne (aOR=1,26 ; CI=1,04, 1,53 ; P =0,018). Il n’y avait pas d’association significative entre la consommation d’autres produits du tabac et les troubles du sommeil. Les femmes consommant des cigarettes étaient plus susceptibles d’avoir des troubles du sommeil (aOR=1,58 ; CI=1,38, 1,81 ; P <0,001) que les hommes. Conclusion: Le tabagisme est associé de manière significative à des durées de sommeil longues et courtes et à des troubles du sommeil. Les études futures devraient chercher à reproduire ces résultats et à évaluer les mécanismes sous-jacents à ce phénomène.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".