Epidemiological and nutritional research on prevention of cardiovascular disease in China
Bibliographic record
Abstract
Anthropological evidence suggests that regional differences in eating practices may be characterized by sub-ethnicity. Hakka is one sub-ethnicity who still retain a unique way of life in China. A field survey on diet and health among the Hakka people was undertaken in 1994. Approximately 200 participants were interviewed for their medical history, life-style and food habits. Blood pressure, body mass index, blood sample, 24 h urine and electrocardiogram were collected. The food samples taken from one tenth of the participants were analyzed for the ingredients in their daily meals. From this survey the prevalence of hypertension in Hakka was approximately 10 %. The sodium/potassium ratio was lower than that in Guangzhou and comparable with that in Okinawa, the island of longevity in Japan. For men, taurine level was found to be close to that in Mediterranean countries, where there is low mortality from cardiovascular diseases. For women, the taurine level was even higher, approximating that of Japanese women, who show the greatest longevity and lowest cardiac mortality worldwide. Less obesity was found in Hakka people than that in the US, Canada or Japan. These findings suggest that the following are the major reasons for these positive findings: the Hakka people maintain traditional food habits and maintain active awareness of their health; the major foods are rice, fish, vegetables and fruits; wide use of soybeans; extensive consumption of visceral organs which have rich source of trace elements. These eating practices and nutritional patterns may be beneficial factors for preventing atherosclerosis and hypertension.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".