Sleep debt: the impact of weekday sleep deprivation on cardiovascular health in older women
Bibliographic record
Abstract
STUDY OBJECTIVES: Short sleep duration is associated with increased cardiovascular disease (CVD) risk. However, it is uncertain whether sleep debt, a measure of sleep deficiency during the week compared to the weekend, confers increased cardiovascular risk. Because sleep disturbances increase with age particularly in women, we examined the relationship between sleep debt and ideal cardiovascular health (ICH) in older women. METHODS: Sleep debt is defined as the difference between self-reported total weekday and weekend sleep hours of at least 2 hours among women without apparent CVD and cancer participating in the Women's Health Stress Study follow-up cohort of female health professionals (N = 22 082). The ICH consisted of seven health factors and behaviors as defined by the American Heart Association Strategic 2020 goals including body mass index, smoking, physical activity, diet, blood pressure, total cholesterol, and glucose. RESULTS: Mean age was 72.1 ± 6.0 years. Compared to women with no sleep debt, women with sleep debt were more likely to be obese and have hypertension (pall < .05). Linear regression models adjusted for age and race/ethnicity revealed that sleep debt was significantly associated with poorer ICH (B = -0.13 [95% CI = -0.18 to -0.08]). The relationship was attenuated but remained significant after adjustment for education, income, depression/anxiety, cumulative stress, and snoring. CONCLUSION: Sleep debt was associated with poorer ICH, despite taking into account socioeconomic status and psychosocial factors. These results suggest that weekly sleep duration variation, possibly leading to circadian misalignment, may be associated with cardiovascular risk in older women.
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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 | 0.002 |
| 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) | 0.001 | 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".