Associations Between Secondhand Smoke Exposure and Sleep Patterns in Children
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to investigate the relationship between exposure to secondhand smoke (SHS) and child sleep patterns among a group of children with asthma who were exposed regularly to tobacco smoke at home. METHODS: We studied 219 children who were enrolled in an asthma intervention trial and were exposed regularly to SHS. Serum cotinine levels were used to measure exposure to tobacco smoke, and sleep patterns were assessed through parent reports using the Children's Sleep Habits Questionnaire. Covariates in adjusted analyses included gender, age, race, maternal marital status, education, and income, prenatal tobacco exposure, maternal depression, Home Observation for Measurement of the Environment total score, household density, asthma severity, and use of asthma medications. RESULTS: Exposure to SHS was associated with sleep problems, including longer sleep-onset delay (P = .004), sleep-disordered breathing (P = .02), parasomnias (P = .002), daytime sleepiness (P = .022), and overall sleep disturbance (P = .0002). CONCLUSIONS: We conclude that exposure to SHS is associated with increased sleep problems among children with asthma.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".