Four major dietary patterns identified for a target-population of adults residing in Newfoundland and Labrador, Canada
Bibliographic record
Abstract
BACKGROUND: Very limited nutritional epidemiological studies conducted to explore the unique dietary exposure in Newfoundland and Labrador (NL). This study aims to identify and characterize major dietary patterns in the target-population from general adult NL residents and assess the associations with selected demographic factors. METHODS: A total of 192 participants, aged 35-70 years, completed and returned a food-frequency questionnaire (FFQ) and participated in a telephone interview to collect demographic information. Dietary patterns were identified by common factor analysis. Univariate and multivariate linear regression analyses were used to assess determinants of the different food consumption patterns. Pearson's correlation coefficients were calculated for food scores of each pattern, total energy, and energy-adjusted nutrient intakes. RESULTS: Factor analyses identified four dietary patterns, which were labeled as "Meat", "Vegetable/fruit", "Fish", and "Grain" patterns. In combination, the four dietary patterns explained 63% of the variance in dietary habits of the study population. Multivariate linear regression analysis indicated an increasing trend of factor scores for Meat and Grain pattern with age. Male participants were found to be more likely to choose the Meat and Fish patterns. Current smokers and those married/living together tend to choose the Grain pattern. Pearson's correlation coefficients showed positive correlations between fat and cholesterol and the Meat pattern, fiber and the Vegetable/fruits pattern, protein and the Fish pattern, and carbohydrates and the Grain pattern. CONCLUSION: This study derived four dietary patterns and obtained their significant associations with specific demographic characteristics in this population. It identified one dietary consumption pattern (Fish) not yet seen in other studied populations. These findings will update the current dietary-health information published in this province, and contribute to further research into the association between dietary practices and health.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".