Examining Associations of Community Food Environments with Individual Diet Quality and Body Weight Status of Canadian Children
Bibliographic record
Abstract
Reducing the prevalence of unhealthy eating is an important challenge to address in order to reduce the burden of obesity and chronic disease. Approximately 1.6 million or one-third of Canadian children and youth are overweight or obese, and about 70% of children and youth consume less than five servings of vegetables and fruit daily. It is being increasingly recognized that food environments in which children live influence their diets and body weights. However, study findings are inconsistent, partly due to different approaches to measure the food environment. In addition, no study has examined the combined effect of the absolute and relative densities of unhealthy food outlets on diet quality and body weight status in Canadian children. The objective of this thesis was to examine the associations of community food environments with individual diet quality and body weight status in a sample of Canadian school-aged children. The specific objectives were to: 1) assess which food environment indicator and geographic area is better able to capture associations with individual diet quality and body weight status, and 2) use the better performing indicator and geographic area to assess whether the community food environment affects individual diet quality and body weight status. These objectives were addressed using data from Raising healthy Eating and Active Living Kids in Alberta (REAL Kids Alberta), a population-based survey of grade 5 students in Alberta, in addition to food retailer data provided by the Environmental Public Health Department of Alberta Health Services. In the first study of this thesis, comparison of two food environment indicators revealed that the novel indicator, which considers the types of foods sold or served at an establishment, was better able to capture associations with diet and weight status compared to the indicator based on store type. When geographic areas were compared, 1600m buffers around schools were better able to capture associations compared to smaller geographic areas. In the second study of this thesis, attending a school in an area with a higher relative density (proportion) of unhealthy food outlets was associated with lower diet quality, predominantly in areas where the absolute density (number) of unhealthy food outlets was also high. These findings provide evidence that the community food environment plays a role in the development of unhealthy eating and increased body weights of school-aged children. Interventions to reduce unhealthy eating and excess weights may be most effective in areas with a higher number of unhealthy food outlets, specifically where there are few alternative healthy options available. The present findings also support the need for more precise assessment of the community food environment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".