Cardiometabolic health impacts of time-restricted eating: implications for type 2 diabetes, cancer and cardiovascular diseases
Bibliographic record
Abstract
PURPOSE OF REVIEW: Time-restricted eating (TRE) entails consuming energy intake within a 4- to 10-h window, with the remaining time spent fasting. Although studies have reported health benefits from TRE, little is known about the impact of TRE on common chronic diseases such as type 2 diabetes, cancer and cardiovascular disease. This review summarizes and critically evaluates the most recent TRE research findings relevant to managing and treating these chronic diseases. RECENT FINDINGS: Most recent TRE studies have been in populations with overweight/obesity or metabolic syndrome; two have been in populations with diabetes, three in cancer survivors and none in populations with cardiovascular disease. Collectively, these studies showed that participants could adhere to TRE and TRE is well tolerated. These studies also showed preliminary efficacy for improved glucose regulation and insulin sensitivity, a reduction in body fat and blood pressure, reduced cardiovascular risk scores and increased quality of life. More research is required to define the most effective TRE protocol (i.e. length and timing of eating window, intervention duration). SUMMARY: TRE has demonstrated benefits on cardiovascular, metabolic and clinical outcomes relevant to the underlying pathophysiology, but there are limited data on TRE implemented specifically within populations with diabetes, cancer or cardiovascular disease.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".