Factors associated with fruit and vegetable consumption among adults
Bibliographic record
Abstract
BACKGROUND: The higher consumption of fruit and vegetables is considered to be an indicator of healthy eating and the protective effects of fruit and vegetable (FV) consumption for noncommunicable diseases have been investigated extensively. The present study aimed to investigate the association between fruit and vegetable intake (FVI), health behaviours and socio-demographic factors among adult Canadians. METHODS: This analysis was based on the information from the Canadian Community Health Survey, Cycle 3.1. Daily intake of fruit and vegetables from a total number of 15,512 apparently healthy individuals, aged 18-64 years, were assessed using a structured questionnaire, which included 20 questions on the frequency of consumption of different types of fruit and vegetables. Multiple logistic regression models were used to determine the association between FVI and some socio-economic factors and lifestyle behaviour among adult Canadians. RESULTS: In total 77% of Canadian adults consumed fruit and vegetables less than five times per day. Females were more likely to consume more fruit [odds ratio (OR) 2.05; 95% confidence interval (CI) 1.75-2.4], vegetables (OR 1.95; 95% CI 1.65-2.29) and FV (OR 2.52; 95% CI 2.20-2.90) than males. Single/never married individuals, individuals with higher levels of education, never smokers, former drinkers and older people reported more consumption of fruit and vegetables than others. CONCLUSIONS: The results obtained in the present study indicate an association between FVI and some socio-economic and healthy lifestyle behaviours, and that a substantial gap exists between the recommended level and the actual intake of the FV among the Canadian population. Because a higher intake of FV improves public health, it is imperative to tailor nutrition education at the individual and community levels in Canadian populations.
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".