Community perspectives on food insecurity and obesity: Focus groups with caregivers of Métis and Off-reserve First Nations children
Bibliographic record
Abstract
INTRODUCTION: Aboriginal children in Canada are at a higher risk for overweight and obesity than other Canadian children. In Northern and remote areas, this has been linked to a lack of affordable nutritious food. However, the majority of Aboriginal children live in urban areas where food choices are more plentiful. This study aimed to explore the experiences of food insecurity among Métis and First Nations parents living in urban areas, including the predictors and perceived connections between food insecurity and obesity among Aboriginal children. METHODS: Factors influencing children's diets, families' experiences with food insecurity, and coping strategies were explored using focus group discussions with 32 parents and caregivers of Métis and off-reserve First Nations children from Midland-Penetanguishene and London, Ontario. Four focus groups were conducted and transcribed verbatim between July 2011 and March 2013. A thematic analysis was conducted using NVivo software, and second coders ensured reliability of the results. RESULTS: Caregivers identified low income as an underlying cause of food insecurity within their communities and as contributing to poor nutrition among their children. Families reported a reliance on energy-dense, nutrient-poor foods, as these tended to be more affordable and lasted longer than more nutritious, fresh food options. A lack of transportation also compromised families' ability to purchase healthful food. Aboriginal caregivers also mentioned a lack of access to traditional foods. Coping strategies such as food banks and community programming were not always seen as effective. In fact, some were reported as potentially exacerbating the problem of overweight and obesity among First Nations and Métis children. CONCLUSION: Food insecurity manifested itself in different ways, and coping strategies were often insufficient for addressing the lack of fruit and vegetable consumption in Aboriginal children's diets. Results suggest that obesity prevention strategies should take a family-targeted approach that considers the unique barriers facing urban Aboriginal populations. This study also reinforces the importance of low income as an important risk factor for obesity among Aboriginal peoples.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".