AN ASSESSMENT OF FRUIT AND VEGETABLE INTAKE, PHYSICAL ACTIVITY, AND SEDENTARY BEHAVIOUR AMONG INDIGENOUS AND NON-INDIGENOUS STUDENTS FROM NORTHERN ONTARIO
Bibliographic record
Abstract
The purpose of this study was to examine fruit and vegetable intake, physical activity (PA), and sedentary behaviour within Indigenous and Non-Indigenous students in grades 5-8 from northern Ontario, Canada. Students (N=872) from 34 schools within the catchment area of Porcupine Health Unit completed the Northern Fruit and Vegetable Program Evaluation survey in May, 2016. The odds of participants having a higher fruit and vegetable intake was lower among (1) those living in remote locations compared to urban locations (OR = -1.299 (95% CI: - 2.336, -0.240), p <0.05) and (2) Indigenous, compared to White, participants (OR = -.674 (95% CI: -1.336, -.0120), p = 0.05); in addition to no associations among ethnicity, location and PA/sedentary behaviour. Among Indigenous participants, those living in remote locations consumed statistically significant less fruit and vegetables (compared to urban and rural; F(2, 128) = 3.780, p = 0.025), and were less physically active (compared to urban and rural; F(2, 121) = 4.724, p = 0.011). There were no statistical differences observed by school location and meeting the sedentary behaviour guidelines for Indigenous populations. Although there were some statistically significant findings pertaining to fruit and vegetable intake among students in northern communities in Ontario, the health behaviours of all participants within this study were concerning. In the future, health interventions are needed to address low fruit and vegetable intake, PA, and sedentary behaviours of children and adolescents. Support through funding opportunities (pertaining to increasing the amount of fruit and vegetables provided to schools) is needed, and it is necessary to advocate for more PA and sedentary behaviour education.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".