Exploring the traditional Chinese diet and its association with health status—a systematic review
Bibliographic record
Abstract
CONTEXT: Increased adherence to a traditional Chinese diet (TCD) could reduce the increasing prevalence of noncommunicable diseases. Currently, there is no consistent definition of the TCD in the literature, and its associations with health outcomes have not yet been identified. OBJECTIVE: This systematic review aimed to assess the definition of the TCD, in the literature, and to evaluate whether the TCD, as described, is associated with health outcomes. DATA SOURCES: Fourteen databases were searched up to April 25, 2022. DATA EXTRACTION: Three reviewers (in pairs) independently screened and extracted data. A modified risk-of-bias tool was used to assess the quality of the studies assessing the TCD definition; the Newcastle-Ottawa Scale and the Cochrane Risk-of-Bias tool were used to assess the quality of the observational studies and randomized controlled trials assessing associations between the TCD and health outcomes. DATA ANALYSIS: Ninety-nine studies were identified that assessed the TCD definition. In at least 75% of the studies, rice and leafy vegetables were consistently reported as food groups that characterize the TCD; the most frequently cited food items were white rice, spinach, bokchoy, and cabbage. Fish and seafood, pork, and pork products were consistently reported in studies exclusively referring to the TCD consumed in southern China (n = 21 studies), whereas wheat and wheat products were commonly reported in studies focusing on northern China (n = 14 studies). Fifteen studies reported on the quantities of food groups that are characteristic of the TCD, but their findings were inconsistent. Of the 99 studies, 54 assessed associations with health outcomes. The TCD was overall inversely associated with obesity risk and weight gain, while relationships between the TCD and other health outcomes were inconsistent. CONCLUSION: Further studies are needed to determine the quantities of foods consumed in the TCD and to establish a consistent definition for further exploration of the TCD's potential role in preventing non-communicable diseases.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".