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Record W7036404705

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

2007· dissertation· en· W7036404705 on OpenAlexaboutno aff

Bibliographic record

VenueQueensland's institutional digital repository (The University of Queensland) · 2007
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera: Cerambycidae studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical activityOverweightObesityPublic healthPopulationInjury preventionOccupational safety and healthSedentary lifestyleSuicide preventionQuarter (Canadian coin)
DOInot available

Abstract

fetched live from 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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.203
Teacher spread0.195 · 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 teacher head, 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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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