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Enregistrement 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 sur OpenAlex

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Notice bibliographique

RevueUniversity of Alberta Library · 2022
Typedissertation
Langueen
DomaineComputer Science
ThématiqueEducational Robotics and Engineering
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOverweightResidenceBuilt environmentSocial determinants of healthObesityCohortChildhood obesityCohort studySocial deprivation

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,896
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,006
Tête enseignante GPT0,198
Écart entre enseignants0,191 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle