The Effect of Patient Neighborhood Income Level on the Purchase of Continuous Positive Airway Pressure Treatment among Patients with Sleep Apnea
Bibliographic record
Abstract
RATIONALE: The cost of continuous positive airway pressure (CPAP) treatment for patients with low socioeconomic status may be an important barrier to successful treatment of obstructive sleep apnea under a copayment health care system. OBJECTIVES: We evaluated an association between patient neighborhood income level and the purchase of a CPAP device under a cost-sharing health care insurance system. METHODS: All adults who underwent a first diagnostic sleep study at St. Michael's Hospital (Toronto, ON, Canada) between 2004 and 2010 were included. Severity of obstructive sleep apnea was determined by the apnea-hypopnea index (AHI) and level of daytime sleepiness (by the Epworth Sleepiness Scale). Patient data were linked to provincial health administrative data from 1991 to 2013 to determine the purchase of CPAP equipment, comorbidities, neighborhood income, and rural status at baseline. Neighborhood income was categorized into quintiles, ranked from poorest (Q1) to wealthiest (Q5). Assuming that the majority of participants with severe obstructive sleep apnea (AHI > 30 events/h) and excessive daytime sleepiness (Epworth Sleepiness Scale ≥ 10) would have been strongly recommended CPAP, we evaluated the association between patient neighborhood income and purchase of a CPAP device in this group via multivariable Cox regressions. MEASUREMENTS AND MAIN RESULTS: Of the 695 participants with severe obstructive sleep apnea and excessive daytime sleepiness, 400 (58%) purchased a CPAP device. Patients who accepted CPAP were more likely to live in a higher-income neighborhood. Cumulative incidence of CPAP acceptance at 6 months was 43% for individuals in a low-income neighborhood (Q1) and 52% in combined higher-income neighborhoods (Q2-5) (P = 0.05). Controlling for sex and age, living in higher-income neighborhoods was associated with a 27% increased chance of accepting CPAP compared with the lowest-income neighborhood (hazard ratio Q2-5 vs. Q1, 1.27; 95% confidence interval, 0.98-1.64; P = 0.07). CONCLUSIONS: Living in an unfavorable neighborhood is not an obstacle to CPAP treatment among symptomatic patients with severe obstructive sleep apnea under a copayment health care system. However, a potential 27% improvement in CPAP acceptance associated with higher neighborhood income is not inconsequential. Also, the overall CPAP acceptance rate was relatively low, suggesting that obstacles other than finances are primarily responsible.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".