﻿ 基于路径模型的肺癌死亡率影响因素研究

# 基于路径模型的肺癌死亡率影响因素研究Study on Influencing Factors of Lung Cancer Mortality Based on Path Model

Abstract: In order to study the factors affecting lung cancer mortality, this paper selected relevant DATA from Data USA as samples to establish a path model based on dependent variables of lung cancer mortality. Firstly, the explanatory variables included in the model were determined by correlation analysis, and the sample data obtained were analyzed by SPSS software. The regression equation was established by step-by-step regression method, and the correlation coefficient and regression coefficient were obtained, and the path diagram was drawn. The analysis results show that smoking is one of the main causes of lung cancer. In addition, benzene and other harmful substances produced by the combustion of petroleum, coal, internal combustion engines and asphalt road dust are also important factors of lung cancer. Therefore, we should advocate non-smoking and strengthen the urban environmental health work.

1. 引言

2. 理论依据

2.1. 相关分析

2.2. 路径分析

2.3. 逐步回归

3. 模型构建与结果分析

3.1. 研究假设

1) 空气污染指数(AQI)、人均工业烟尘(吨/人)、人均工业废水排放总量(吨/人)、烟民数量与肺癌死亡率呈正相关，森林覆盖率与肺癌死亡率呈负相关；

2) 以在职医生数量和政府医疗资金为指标刻画一个时期的医疗水平，与肺癌死亡率呈负相关；

3) 空气污染指数(AQI)与人均工业烟尘(吨/人)呈正相关；

4) 烟民数量增加，一定程度上会增加酸性气体污染，空气污染指数越高，表示空气污染越严重,故烟民数量与空气污染指数呈正相关；

5) 绿色植被有助于改善空气，吸附大气中的烟尘，故空气污染指数(AQI)、人均工业烟尘(吨/人)与森林覆盖率呈负相关。

Figure 1. Initial path diagram

3.2. 符号规定

3.3. 数据预处理

Table 1. The symbol table

3.4. 数据预处理

3.4.1. 相关分析

3.4.2. 建立各相关因素间的回归方程

Table 2. Regression analysis results using lung cancer mortality as the dependent variable

*因变量：Zscane (肺癌死亡率)。

Table 3. Summary table of regression analysis results

3.4.3. 修改并完成路径图的绘制

Table 4. Table of coefficients after normalization of data

Figure 2. Path diagram

4. 模型的评价与改进

Table 5. Table of coefficients with unstandardized data

Figure 3. Modified path diagram

5. 结果与讨论

5.1. 结构与建议

5.2. 不足与展望

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