Influence of neighbourhood‐level crowding on sleep‐disordered breathing severity: mediation by body size
Bibliographic record
Abstract
Neighbourhood-level crowding, a measure of the percentage of households with more than one person per room, may impact the severity of sleep-disordered breathing. This study examined the association of neighbourhood-level crowding with apnoea-hypopnoea index in a large clinical sample of diverse adults with sleep-disordered breathing. Sleep-disordered breathing severity was quantified as the apnoea-hypopnoea index calculated from overnight polysomnogram; analyses were restricted to those with apnoea-hypopnoea index ≥5. Neighbourhood-level crowding was defined using 2000 US Census tract data as percentage of households in a census tract with >1 person per room. Multivariable linear mixed models were fit to examine the associations between the percentage of neighbourhood-level crowding and apnoea-hypopnoea index, and a causal mediation analysis was conducted to determine if body mass index acted as a mediator between neighbourhood-level crowding and apnoea-hypopnoea index. Among 1789 patients (43% African American; 68% male; 80% obese), the mean apnoea-hypopnoea index was 29.0 ± 25.3. After adjusting for race, age, marital status and gender, neighbourhood-level crowding was associated with apnoea-hypopnoea index; for every one-unit increase in percentage of neighbourhood-level crowding mean, the apnoea-hypopnoea index increased by 0.40 ± 0.20 (P = 0.04). There was a statistically significant indirect effect of neighbourhood-level crowding through body mass index on the apnoea-hypopnoea index (P < 0.001). Neighbourhood-level crowding is associated with severity of sleep-disordered breathing. Body mass index partially mediated the association between neighbourhood-level crowding and sleep-disordered breathing. Investigating prevalent neighbourhood conditions impacting breathing in urban settings may be promising.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".