Giishpin Nonagzwaat Binoojiinyik Kanim Na Majiishkaami: determinants of obesity among indigenous children in six First Nations Communities in Northeastern Ontario
Bibliographic record
Abstract
Background: Worldwide, childhood obesity rates are high and even higher among Indigenous children. Childhood obesity is of concern as it can result in metabolic conditions. Much has been written about the causes of obesity, usually focusing on individual behaviours, but a gap exists in understanding the social determinants of obesity in Indigenous populations. Methods: Survey data was collected from First Nations students in grades 6 to 8 through a diet and health behavior survey. Measurements including height, weight and waist circumference were taken. Focus groups with 33 caregivers were conducted to explore the determinants of physical activity and nutrition. Results: The prevalence of overweight/obesity in children was 65.8%. The prevalence central obesity was 37.7%. There was a strong positive correlation between waist circumference (cm) and BMI z scores (rs = 0.84, p>0). Daily physical activity (DPA) of 60 minutes per day was associated with a BMI ≤85th percentile and a waist circumference ≤90th percentile. Girls consumed 3.5 servings of fruits and vegetables and boys consumed 2.5 servings. Consuming fruit juice was directly associated with central obesity. Normal weight was associated with participation in at least four types of cultural activities. Caregivers identified impediments to physical activity as financial, recreational technology, safety concerns, and community activation. Changes in lifestyles, influenced by the consequences of colonization, have resulted in reduced physical activity. Colonial policies result in funding challenges for children’s recreation programs and a reliance on government develops. Safety concerns stem from intergenerational trauma created by colonial policies. Dietary decisions were influenced by the availability of fish and game, hunting and fishing regulations, food insecurity and the proliferation of processed foods. Dietary decisions are influenced by the contamination of traditional territories, the marginalization of culture, participation in the economy and issues of poverty. Conclusions: Waist circumference is an effective indicator of obesity along with BMI and should be used in public health screening of Indigenous children. Low fruit and vegetable consumption is of concern as is the consumption of fruit juice. Protective factors against obesity are 60 minutes of DPA and participation in at least four types of cultural activities. Colonialism is a determinant of physical activity, nutrition, and obesity in this population.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".