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Enregistrement W7036404705

THE BENEFITS AND INJURY RELATED HARMS OF PHYSICAL ACTIVITY IN CHILDREN AGED 5-12 YEARS

2007· dissertation· en· W7036404705 sur OpenAlexaboutno aff

Notice bibliographique

RevueQueensland's institutional digital repository (The University of Queensland) · 2007
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueColeoptera: Cerambycidae studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPhysical activityOverweightObesityPublic healthPopulationInjury preventionOccupational safety and healthSedentary lifestyleSuicide preventionQuarter (Canadian coin)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: The prevalence of overweight status amongst Australian children has increased substantially and now approximates one quarter of the paediatric population. Proponents of physical activity have argued that this increase in partly due to decreasing activity levels, coinciding with an increase in sedentary behaviour. Consequently, a public health agenda to increase physical activity participation has emerged and Australian guidelines were published in 2004, recommending that children aged 5-12 years participate in a minimum of 60 minutes of physical activity daily and spend no more than two hours a day using electronic media for entertainment. However, an unintended consequence of physical activity is exposure to the risk of injury. To date, these risks have not been quantified in primary school aged children despite injury being a leading cause for hospitalisation and death in this population. Furthermore, the protective effect of ‘sufficient’ physical activity against obesity remains uncertain, with a lack of consensus of an independent relationship between activity and weight status. A clearer understanding of the relationship between physical activity and the positive and negative outcomes is therefore warranted to inform public health policy and ensure that the potential benefits of increased activity participation amongst the paediatric population will not be outweighed by the risks and costs of injury. Aims: There were five main aims of the thesis: 1. To describe the distribution of BMI in children 5-12 years by age, sex and SES 2. To quantify the association between physical activity and obesity in children 5-12 years 3. to describe the distribution of physical activity participation in children 5- 12 years by age, sex and SES. 4. To describe the physical activity specific incidence of injury in children 5- 12 years, by age, sex and SES 5. To quantify the association between categories of physical activity and injury type sustained. Method: The Childhood Injury Prevention Study (CHIPS) was a prospective cohort study that collected data from a randomly selected sample of Brisbane primary and pre-school children aged 5 to 12 years. Data for each participating child were available for the following variables: age, gender, body mass index (BMI), socioeconomic status (SES) indicators (household income, maternal education, school area SES), family size, home play equipment availability, transport method to school, estimated time per week in various types of physical activity and sedentary leisure activities, and incidence of injury recorded prospectively over 12 months. Analytic strategies Logistic regression analysis was performed to 1) determine the protective effect of compliance with the Australian guidelines against obesity. 2) identify variables that were associated with insufficient (< 60 minutes) daily activity. The age and gender distribution of injury rates per hourly exposure were calculated for all activity and for organized, non-organised and common specific activities occurring outside school hours. Additionally, child-based injury rates were calculated for physical activity related injuries both in and out of the school setting. Results: Compliance with physical activity guidelines and protection against overweight status Approximately 20% of the cohort was considered overweight according to international age standardised BMI charts. Non-compliance with activity guidelines was 15% for out of school physical activity participation, and 31% for excessive electronic media entertainment use. Non-compliance with the minimal physical activity guideline increased the odds of being overweight by 28%, however this difference was not statistically significant. There was, however a significant 63% increase in the odds of overweight status amongst children who overused electronic media for entertainment. Children failing the minimum activity participation recommendation were less likely to walk or cycle to school (adjusted odds ratio (OR) 0.43; 95% CI = 0.24 – 0.77) or participate in organised sports or activity (OR 0.42; 95% CI = 0.28 – 0.64) and were more likely to spend in excess of 2 hours a day watching television of using a computer for entertainment (OR 2.10 (1.16 – 3.78). Harms of physical activity: exposure to injury risk A high number of injuries (89%) sustained by the cohort were directly related to physical activity and 34% of physical activity related injuries required professional medical treatment. Analysis of injuries occurring outside of school revealed an overall injury rate of 5.7 injuries per 10 000 hours of exposure to physical activity and a medically treated injury rate of 1.7 per 10 000 hours. The highest injury risks per exposure time occurred for tackle-style football, wheeled activities and tennis. Conclusion: One in seven children from the Greater Brisbane area are at risk for being insufficiently active according to Australian national guidelines whilst a third overuse electronic media. Given that overuse of electronic entertainment was positively associated with childhood obesity, these children should be the target of public health campaigns to promote alternative leisure time activities. Injury rates per hours of exposure to physical activity were low with less than 2 injuries requiring medical treatment occurring for every 10 000 hours of activity participation outside of school.

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 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 enseignants0,653
Score d'incertitude au seuil0,441

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 technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,007
Tête enseignante GPT0,203
Écart entre enseignants0,195 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

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Même revueQueensland's institutional digital repository (The University of Queensland)Même sujetColeoptera: Cerambycidae studiesTravaux en français237 207