0894 The Role of Age, Sex, Race/ethnicity, Education, and Marital Status in the Relationship of Chronic Health Conditions and Habitual Sleep Duration
Bibliographic record
Abstract
This study aims to investigate the associations between diagnosis history of chronic conditions and habitual sleep duration, and the role of sociodemographic factors in-between the associations. 2013 Behavioral Risk Factor Surveillance System was used. Multinomial regressions were performed to investigate the risk for extreme sleep durations among those with depression or chronic diseases. Stratified regression analyses were further done to investigate the interactions of sociodemographic variable and depression/chronic diseases on habitual sleep durations. Among 491,773 respondents, most diagnoses were associated with suboptimal sleep durations except skin cancer. In general, the risk for very short sleep duration is higher than that for short and long sleep durations across the diagnoses and groups. Age, sex, education level, race and marital status significantly moderated the relationship between the diagnosis history and extreme sleep durations. Moreover, with depression or arthritis, people in younger age group were more likely to report very short sleep durations than the older group. Men are more likely to report very short sleep duration than women if they had depression. Yet, females are more likely to report very short sleep duration than males if they had the diagnosis of physical diseases. Higher education was associated with lower risk for very short sleep duration in depression, but the trend reversed for heart diseases. For white population, the associations between diagnosis and extreme sleep durations were significant across all chronic conditions. In contrast, black people are less like to have long sleep durations if they had the previous diagnosis of pulmonary diseases, asthma, and arthritis. Sociodemographic factors significantly moderated the relationship between previous chronic illness and sleep duration extremes. Nature of the chronic conditions and social-economic status may account for the discrepancies in medical diagnosis-sleep duration associations. Further study was required to understand sleep duration, as a health behavior, in the context of antecedent chronic conditions. none.
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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 | 0.001 | 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".