Trends in Diet, Nutritional Status, and Diet-related Noncommunicable Diseases in China and India: The Economic Costs of the Nutrition Transition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Undernutrition is being rapidly reduced in India and China. In both countries the diet is shifting toward higher fat and lower carbohydrate content. Distinct features are high intakes of foods from animal sources and edible oils in China, and high intakes of dairy and added sugar in India. The proportion of overweight is increasing very rapidly in China among all adults; in India the shift is most pronounced among urban residents and high-income rural residents. Hypertension and stroke are relatively higher in China and adult-onset diabetes is relatively higher in India. Established economic techniques were used to measure and project the costs of undernutrition and diet-related noncommunicable diseases in 1995 and 2025. Current WHO mortality projections of diet-related noncommunicable diseases, dietary and body composition survey data, and national data sets of hospital costs for healthcare, are used for the economic analyses. In 1995, China's costs of undernutrition and costs of diet-related noncommunicable diseases were of similar magnitude, but there will be a rapid increase in the costs and prevalence of diet-related noncommunicable diseases by 2025. By contrast with China, India's costs of undernutrition will continue to decline, but undernutrition costs did surpass overnutrition diet-related noncommunicable disease costs in 1995. India's rapid increase in diet-related noncommunicable diseases and their costs projects similar economic costs of undernutrition and overnutrition by 2025.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it