Healthy food intentions and higher socioeconomic status are associated with healthier food choices in an Inuit population
Bibliographic record
Abstract
BACKGROUND: Changing food behaviours amongst Canadian Inuit may contribute to rising chronic disease prevalence, and research is needed to develop nutritional behaviour change programmes. The present study examined patterns of food acquisition and preparation behaviours amongst Inuit adults in Nunavut and associations with psychosocial and socioeconomic factors. METHODS: Developed from behavioural theories and community workshops, Adult Impact Questionnaires were conducted with adult Inuit (≥19 years) from randomly selected households in three remote communities in Nunavut, Canada, to determine patterns of healthy food knowledge, self-efficacy and intentions, frequencies of healthy and unhealthy food acquisition and healthiness of preparation methods. Associations between these constructs with demographic and socioeconomic factors were analysed using multivariate linear regressions. RESULTS: Amongst 266 participants [mean (SD) age 41.2 (13.6) years; response rates 69-93%], non-nutrient-dense foods were acquired a mean (SD) of 2.9 (2.3) times more frequently than nutrient-dense, and/or low sugar/fat foods. Participants tended to use preparation methods that add fat. Intentions to perform healthy dietary behaviours was inversely correlated with unhealthy food acquisition (β=-0.25, P<0.001), and positively associated with healthy food acquisition (β=0.22, P<0.001) and healthiness of preparation methods (β=0.15, P=0.012). Greater healthy food knowledge and self-efficacy were associated with intentions (β=0.21, P=0.003 and β=0.55, P<0.001, respectively). Self-efficacy was associated with healthier preparation (β=0.14, P=0.025) and less unhealthy food acquisition (β=-0.27, P<0.001), whilst knowledge was associated with acquiring healthy foods (β=0.13, P=0.035). Socioeconomic status was positively associated with healthy preparation and food acquisition behaviours. CONCLUSIONS: Interventions to improve diet in Nunavut Inuit should target healthy food intentions, knowledge and self-efficacy. Behaviour change strategies emphasising economic benefits of a healthy diet should be employed to target individuals of low socioeconomic status.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".