Short sleep duration and its association with energy metabolism
Bibliographic record
Abstract
A growing body of observational evidence suggests that short sleep duration is a risk factor for the development of obesity. Although increased energy intake is the most prevailing causal explanation for this association, we should also consider possible effects on energy metabolism to understand fully the potential impact of short sleep duration on the regulation of energy balance. We performed a search of the literature from 1970 to 2011, including original papers, investigating the relation between short sleep and energy metabolism in animals and humans. Although the limited number of experimental studies in humans precludes any definitive conclusions about causality, short sleep duration does not seem to substantially affect total daily energy expenditure, nor is there sufficient evidence in support of any meaningful effect of restricted sleep on the specific components of energy metabolism (i.e. resting metabolic rate, intentional as well as unintentional physical activity, diet-induced thermogenesis, and substrate utilization). As studies on rats suggest that other factors that can potentially influence energy metabolism could be affected (i.e. hormonal systems and thermoregulation), we included these factors in our literature search and found some indications in support of an up-regulation of thyroid hormones and glucocorticoids as well as increased heat dissipation following total or severe sleep deficit. Although we found some evidence also in humans that suggests a possible effect on energy metabolism, the limitations of the studies make it difficult to draw conclusions on the effect of short sleep on energy metabolism under relevant free living conditions. To explore this area further, more studies using suitable methodology under relevant conditions to mimic real-life situations are needed.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".