Comparative analysis of nutrition data from national, household, and individual levels: results from a WHO-CINDI collaborative project in Canada, Finland, Poland, and Spain
Bibliographic record
Abstract
STUDY OBJECTIVE: This project determined to what extent data on diet and nutrition, which were collected in a non-uniform manner, could be harmonised and pooled for international and national comparison. DESIGN: Direct comparisons of dietary data between studies were made using food balance sheets (FBS), household budget surveys (HBS), and individual dietary data (IDS); comparisons were also made within countries. Differences in study design and methodological approaches were taken into consideration. Data from research projects from the following four World Health Organisation (WHO) Countrywide Integrated Noncommunicable Disease Intervention (CINDI) countries were included-Canada, Finland, Poland, and Spain. MAIN RESULTS: FBS overestimated food consumption and nutrient intake compared to IDS. Results between HBS and IDS were quite similar, except for fish, meat, pulses and vegetables, which were underestimated by HBS, and sugar and honey and cereals, which were overestimated. Percentages of energy from fat, carbohydrates and proteins were higher when estimated from FBS, HBS, and IDS respectively. CONCLUSIONS: Results suggest that estimations from these three sources of dietary data are difficult to compare because they are measuring different levels of dietary information. The understanding of their relations may be important in formulating and evaluating a nutrition policy.
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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 | 0.032 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.022 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".