Associations between changes in habitual sleep duration and lower self-rated health among COVID-19 survivors: findings from a survey across 16 countries/regions
Bibliographic record
Abstract
Abstract Background Self-rated health (SRH) is widely recognized as a clinically significant predictor of subsequent mortality risk. Although COVID-19 may impair SRH, this relationship has not been extensively examined. The present study aimed to examine the correlation between habitual sleep duration, changes in sleep duration after infection, and SRH in subjects who have experienced SARS-CoV-2 infection. Methods Participants from 16 countries participated in the International COVID Sleep Study-II (ICOSS-II) online survey in 2021. A total of 10,794 of these participants were included in the analysis, including 1,509 COVID-19 individuals (who reported that they had tested positive for COVID-19). SRH was evaluated using a 0-100 linear visual analog scale. Habitual sleep durations of < 6 h and > 9 h were defined as short and long habitual sleep duration, respectively. Changes in habitual sleep duration after infection of ≤ -2 h and ≥ 1 h were defined as decreased or increased, respectively. Results Participants with COVID-19 had lower SRH scores than non-infected participants, and those with more severe COVID-19 had a tendency towards even lower SRH scores. In a multivariate regression analysis of participants who had experienced COVID-19, both decreased and increased habitual sleep duration after infection were significantly associated with lower SRH after controlling for sleep quality (β = −0.056 and −0.058, respectively, both p < 0.05); however, associations between current short or long habitual sleep duration and SRH were negligible. Multinomial logistic regression analysis showed that decreased habitual sleep duration was significantly related to increased fatigue (odds ratio [OR] = 1.824, p < 0.01), shortness of breath (OR = 1.725, p < 0.05), diarrhea/nausea/vomiting (OR = 2.636, p < 0.01), and hallucinations (OR = 5.091, p < 0.05), while increased habitual sleep duration was significantly related to increased fatigue (OR = 1.900, p < 0.01). Conclusions Changes in habitual sleep duration following SARS-CoV-2 infection were associated with lower SRH. Decreased or increased habitual sleep duration might have a bidirectional relation with post-COVID-19 symptoms. Further research is needed to better understand the mechanisms underlying these relationships for in order to improve SRH in individuals with COVID-19.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".