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Record W6921781571 · doi:10.7939/r3-g1qe-ac94

The influence of social determinants of health and the built environment on the weight status of preschoolers in Alberta

2022· dissertation· en· W6921781571 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightResidenceBuilt environmentSocial determinants of healthObesityCohortChildhood obesityCohort studySocial deprivation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.006
GPT teacher head0.198
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
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