基本信息来源于合作网站,原文需代理用户跳转至来源网站获取       
摘要:
Aims: Establish profiles of young “at risk” of injuries, first, on an overall point of view and, secondly, for some types of injuries (sport, home, road traffic, school and work injuries). Methods: We have taken nearly 50 variables into consideration: 17 variables for construction of the socioeconomic status, 9 variables for the investigation of symptoms, 11 concerning drugs, 5 for healthy habits, 3 for investigating the violence behavior, 4 concerning the school, 3 for subjective health and finally 3 for social network. We have used the principal component analysis, the multiple correspondence analysis and the weighted-frequency score for reducing the number of them. After these reductions, 15 variables were available for analyses. The relationship between injuries and investigated factors was assessed using the Pearson’s chi-square test. We also calculated odds ratio (OR) with their 95% confidence intervals (95%CI) to estimate the strengths of the associations. To further assess these relationships but also for taking into account the potentials confounding effects of some variables, logistic regression model and multinomial logistic regression model were applied. Results: The whole injury prevalence was equal to 45.6% and among the injured, the proportion of the several types was equal to 33.8% for sport injuries, 32.2% for home injuries, 16.6% for traffic injuries, 11.6% for school injuries and 5.7% for work injuries. We can say that, in light of the variables studied, the “at risk” profile for having reported an injury is being a boy, being younger, having drug experiences, with the violent profile, and declaring several symptoms. There are no consistent and marked deviations in this study from the findings obtained in previous studies. Conclusion: Analyzing injuries in general is interesting but for preventing them it is important to know in which activities children and students are engaged when they are injured.
推荐文章
Spatial prediction of landslide susceptibility using GIS-based statistical and machine learning mode
Landslide susceptibility mapping
Statistical model
Machine learning model
Four cases
Behavior of rare earth elements in granitic profiles, eastern Tibetan Plateau, China
Chemical weathering
Eu anomaly
Critical zone
Soil weathering
Forest carbon storage in Guizhou Province based on field measurement dataset
Forest carbon storage
Field measurement dataset
Karst landform
矩阵Young不等式
半正定矩阵
Young不等式
酉不变范数
内容分析
关键词云
关键词热度
相关文献总数  
(/次)
(/年)
文献信息
篇名 Injury-Related Profiles among School-Aged Children in Cameroon: Analysis Based on the “First Survey—Health Young People”
来源期刊 流行病学期刊(英文) 学科 医学
关键词 INJURIES HEALTH Behavior YOUTH EPIDEMIOLOGY Cameroon
年,卷(期) 2014,(2) 所属期刊栏目
研究方向 页码范围 89-114
页数 26页 分类号 R73
字数 语种
DOI
五维指标
传播情况
(/次)
(/年)
引文网络
引文网络
二级参考文献  (0)
共引文献  (0)
参考文献  (0)
节点文献
引证文献  (0)
同被引文献  (0)
二级引证文献  (0)
2014(0)
  • 参考文献(0)
  • 二级参考文献(0)
  • 引证文献(0)
  • 二级引证文献(0)
研究主题发展历程
节点文献
INJURIES
HEALTH
Behavior
YOUTH
EPIDEMIOLOGY
Cameroon
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
流行病学期刊(英文)
季刊
2165-7459
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
221
总下载数(次)
0
总被引数(次)
0
论文1v1指导