Wu C, Wang S
Preventive Medicine Department of Medical College of Jinan University, Guangzhou.
Zhonghua Liu Xing Bing Xue Za Zhi. 1998 Aug;19(4):227-30.
In order to expound the impact of traffic condition to road injury, the relations of road injury with motorization, road situation e and highway capacity were studied, using Canonical Correlation analysis method. Results showed that the Canonical Correlation Coefficient A(0.9486) was representing the direct correlation of the motorization with the injury and death rates, referring the higher the motorization, the greater the death and injury rates. The Canonical Correlation Coefficient B(0.9220) indicated the direct correlation between the highway capacity and the frequency of road injury, as well as the larger the highway capacity, the more frequency of road injury occurrance. The Canonical Correlation Coefficient C(0.6446) revealed the relations between levels of road situation and the accident rates per 10,000 vehicles. Results showed that the higher the quality of roadway, the lower was the accident rate. In view of this, traffic condition was closely related to road injury. Thus, the frequency of accident, death rate and injury rate could be reduced through improving the road quality and traffic conditions. Relations between two sets of random variables, the ties of the canonical variables and the original variables could all be well analysed with Canonical Correlation analysis. Canonical Correlation is useful to analyse two sets of random variables in epidemiological studies since it provides a great amount of information to be applied and operated widely and easily.
为阐述交通状况对道路伤害的影响，采用典型相关分析方法，研究了道路伤害与机动化、道路状况及公路通行能力之间的关系。结果表明，典型相关系数A（0.9486）表示机动化与伤亡率之间的直接相关性，即机动化程度越高，伤亡率越高。典型相关系数B（0.9220）表明公路通行能力与道路伤害发生频率之间的直接相关性，即公路通行能力越大，道路伤害发生频率越高。典型相关系数C（0.6446）揭示了道路状况水平与每万辆车事故率之间的关系。结果表明，道路质量越高，事故率越低。鉴于此，交通状况与道路伤害密切相关。因此，通过改善道路质量和交通状况，可以降低事故发生频率、死亡率和伤害率。典型相关分析可以很好地分析两组随机变量之间的关系、典型变量与原始变量之间的联系。典型相关在流行病学研究中分析两组随机变量很有用，因为它提供了大量易于广泛应用和操作的信息。
