Impaired sleep quality is associated with concurrent elevations in inflammatory markers: are post-menopausal women at greater risk?
Bibliographic record
Abstract
BACKGROUND: Chronic inflammation and impaired sleep increase the risk for cardiovascular disease. Menopausal women may be particularly at risk as a result of impaired sleep. The objective of the current investigation was to assess the relationship between poor sleep and C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and myeloperoxidase (MPO) in healthy non- and postmenopausal women and men. METHODS: A fasting blood draw was obtained from 122 healthy men and women (31 were postmenopausal). Higher scores on the Pittsburgh Sleep Quality Index (PSQI) were used to define poor sleep. Given the sample size and healthy nature of the sample, hierarchical linear regression analyses were performed on a composite inflammatory score involving CRP, IL-6, and TNF-α. Sex/menopausal group and PSQI were entered as predictors, and the interaction of the group by PSQI was entered stepwise. Analyses on MPO were performed separately. RESULTS: Sleep quality was associated with higher inflammatory activity (β = 0.272, P = 0.003), which remained significant (P = 0.046) after controlling for age, waist circumference, exercise times per week, and depressive symptoms. While in the same direction, sleep quality was not significantly associated with MPO. Dichotomizing sleep quality led to similar results. CONCLUSION: Impaired sleep quality is independently associated with greater inflammation in healthy adult men and women. Despite an overall less favorable metabolic and inflammatory profile in postmenopausal women, impaired sleep did not emerge as differentially related to inflammatory activity in this group.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".