Bibliographic record
Abstract
BACKGROUND: In addition to recommendations about the consumption of specific foods and nutriens, a measure of overall diet quality is useful. Over the years, a number of countries, but not Canada, have developed indexes to evaluate diet quality. DATA AND METHODS: The American Healthy Eating Index was adapted to conform to recommendations in Canada's Food Guide. Data from 33,664 respondents to the 2004 Canadian Community Health Survey-Nutrition were used. Usual index scores were calculated with the Software for Intake Distribution Estimation program. Multiple linear regression models were used to examine associations between index scores and various characteristics, particularly the frequency of vegetable and fruit consumption. RESULTS: For the population aged 2 or older, the average score on the Canadian adaptation of the Healthy Eating Index in 2004 was 58.8 out of a possible 100 points. Children aged 2 to 8 had the highest average scores (65 or more). Average scores tended to fall into early adolescence, stabiilizing around 55 at ages 14 to 30. A gradual upturn thereafter brought the average score to around 60 at age 71 or older. At all ages, women's scores exceeded those of men. The frequency of vegetable and fruit consumption was linked to index scores. INTERPRETATION: The American Healthy Eating Index can be adapted to Canadian food intake recommendations. Canadian Community Health Survey questions about the frequency of vegetable and fruit consumption can be used as an approximation of diet quality.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".