The influence of social determinants of health and the built environment on the weight status of preschoolers in Alberta
Bibliographic record
Abstract
Background Underweight, overweight, and obesity in early childhood can compromise health over the life course. Underweight, an indicator of undernutrition, can lead to higher morbidity, restricted growth, and delayed development. Overweight and obesity can lead to health conditions such as cardiovascular stress, skeletal stress, and asthma at an early age. Contextual factors in a child’s upbringing, such as social determinants of health (SDH) and the built environment, impact health inequities and may have protective or harmful effects towards developing underweight, overweight and obesity in early childhood. My thesis has two objectives: (a) to examine associations between social determinants of health and weight status in preschool children in Edmonton and Calgary, Canada and (b) to examine relationships between built environment variables related to physical activity and excess weight status in preschoolers in Edmonton and Calgary, Canada. Methods In Chapter 2, I conducted a retrospective cohort study to examine associations between social determinants of health, including ethnicity, maternal immigration status, neighborhood-level income, urban versus rural residence, and material and social deprivation on weight status in preschool children in Edmonton and Calgary. I ran three multinomial regression models, where the outcome variable was child weight status. The first model studied associations between child ethnicity, maternal immigration status, neighborhood-level income, and residence with child weight status. The second and third models individually estimated associations 3 between material and social deprivation and child weight status. In Chapter 3, I conducted a retrospective cohort study to examine associations between the distance to nearest playground, distance to nearest major park, distance to nearest school, number of street intersections, number of major parks, number of major playgrounds, and weight status in preschoolers in Edmonton and Calgary. I ran three binomial logistic regression models, where the outcome variable was child weight status examined in 2 categories (normal weight and excess weight[overweight and obesity]). The first model examined individual associations between each of the built environment variables and the likelihood of excess weight. The second model examined combined associations between all built environment variables and the likelihood of having excess weight. The third model examined combined associations between all built environment variables and odds of having excess weight, while additionally adjusting for child sex, age at BMI measurement, ethnicity, annual neighborhood-level income, and city. Results In Chapter 2(n=169,465), I found that children with Chinese ethnicity were less likely to have overweight (Relative Risk Ratio[RRR]: 0.63) and obesity (RRR: 0.47) and children with South Asian ethnicity were more likely to have underweight (RRR: 3.95) and obesity (RRR: 1.38). Children with mothers who immigrated to Canada were less likely to have underweight (RRR: 0.70) and obesity (RRR: 0.70). Every $10,000 increase in income was associated with a decrease in the likelihood of children having overweight (RRR: 0.94) and obesity (RRR: 0.87). Relative to the least deprived quintile, children in the most materially deprived quintile were more likely to have underweight (RRR: 1.98), overweight (RRR: 1.56) and obesity (RRR: 3.32). Children in the most socially deprived quintile were more likely to have overweight (RRR: 1.25) and obesity 4 (RRR: 1.40) (all p<0.0001). In Chapter 3(n=121,692), I found that distance to nearest school was related to children’s weight status, whereby every 100m increase in distance to nearest school resulted in lower odds of excess weight (Odds Ratio: 0.996; p<0.05). None of the other built environment measures that were considered had any impact on preschool children’s weight status. Conclusion My findings highlight SDH-based differences in underweight, overweight and obesity prevalence in preschoolers and suggest that SDH exert a greater influence on weight status in preschoolers than the built environment. Public health efforts to prevent or manage underweight, overweight and obesity in early childhood should emphasize social determinant of health assessments in the clinical setting and target vulnerable populations based on inequities in social determinants of health to promote healthy living and manage weight status. To help explain my findings, several research avenues are suggested, including examination of (a) the link between high-quality playground and major park accessibility and weight status in preschoolers and (b) modifying effects of climate and neighborhood safety on the link between built environment and weight status in preschoolers. Further SDH research targeting underweight in Canadian preschool populations is also needed.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".