The influence of social determinants of health on child physical health in Greater Sudbury neighbourhoods
Notice bibliographique
Résumé
There is increasing awareness that social determinants of health are associated with growing health inequities, or avoidable differences, among many populations. The City of Greater Sudbury is experiencing these health inequities, including inequities in child physical health and wellbeing. This study will examine the relationship between specific social determinants of health and child physical health and wellbeing in Greater Sudbury neighbourhoods. The goals of this research are 1) to explore the relationships between specific social determinants of health and child physical health and wellbeing in Greater Sudbury neighbourhoods, 2) explore the collective influence of social determinants of health on child physical health and wellbeing, and 3) examine unique relationships that may exist between the social determinants of health and children physical health in neighbourhoods for the City of Greater Sudbury. The complexity, nature, and interactions of the social determinants of health within society makes observing them quantitatively difficult. This requires many different social determinants of health to be studied separately from one another, as well as together, in order to understand how they influence child physical health and wellbeing. In order to better understand these interactions, the social ecological model of health promotion presents an ideal theoretical framework for examining multiple variables and their correlations and, therefore, is used in this study. This study is an ecological crosssectional study using secondary data analysis of the 2011 National Household Survey (Statistics Canada) and the Early Development Instrument which was developed by the Offord Centre for Child Studies. This study involves a multi-variate analysis with the dependent variable of child physical health being represented by a composite measure of child physical health and wellbeing, and multiple independent variables including different measures of neighbourhood income, education, unemployment, lone-parent families and poverty. Child physical health and wellbeing is represented by the Early Development Instrument (EDI) - a questionnaire completed by the teacher or an Early Child Educator (ECE) when the child is in senior kindergarten. The EDI is a comprehensive measure of child physical health and wellbeing because it includes gross/fine motor skills, physical readiness for the school day, and physical independence. The social determinants of health are represented by the National Household Survey – a voluntary sample survey using a random sample collected by Statistics Canada, which the federal government uses to collect social and economic data about the Canadian population (Statistics Canada, 2011). IV Descriptive statistics address the assumptions of linear regression as well as examine the nature and normalcy of the independent and dependent variables. Then the presence of outliers are tested using univariate, bivariate, and multivariate detection methods. Linear and multiple regression tests are then used to analyze the influences of the social determinants of health on child physical health and wellbeing. The results of this study demonstrate the challenges of exploring geographical differences in the health of a population, and how those differences in health may be socially produced. Furthermore, this study provides insight into better understanding how child physical health and wellbeing in Greater Sudbury neighbourhoods may be influenced by socially produced health disparities.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».