Association between Grain Intake, Nutrient Intake, and Diet Quality of Canadians: Evidence from the Canadian Community Health Survey–Nutrition 2015
Bibliographic record
Abstract
The new Canada's Food Guide (CFG) recommends whole grains foods as the primary choice of grain products in the daily diet. This study examined whether higher shares of whole-grain consumption, beyond the recommended levels (i.e., above half) of the daily grain intake, are linked with optimal diet quality and intakes of some key nutrients, for both children and adolescents and adults in Canada. To meet the objective of this study, we used the Canadian Community Health Survey (CCHS)-Nutrition 2015, which is a nationally representative data. We employed the propensity score matching (PSM) method in this study. PSM estimates the exposure effect when a set of individuals are exposed to a specific treatment (food group intake in this study) in a non-experimental setting. The results of our analyses implied that a high consumption of whole grains is associated with a good diet quality. However, after a certain level of whole-grain consumption, no significant differences can be observed in diet quality scores of children and adolescents and adults. Moreover, it was observed that the proportion of obese and overweight individuals was significantly lower among adults that had balanced intakes of whole and non-whole grains. The results of logistic regression analyses also showed the probability of being obese and overweight is significantly lower in the case of adults with balanced intakes of grains. However, no significant differences were observed in the prevalence of obesity and overweight across whole grains consumption patterns for children and adolescents.
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 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".