摘要
目的 探索不同阶段日本婴儿死亡率（IMR）的影响因素，分析人均GDP的作用。方法 分别以1970-2000年、2000-2018年的IMR为因变量、相关经济社会因素为自变量进行阶段性岭回归分析，回归系数t检验差异有统计学意义的自变量为婴儿死亡率的影响因素，比较标准化回归系数绝对值大小判断对因变量的影响程度。结果 两个阶段的岭回归方程F检验差异均有统计学意义（P<0.05）。1970-2000年各回归系数的t检验差异均有统计学意义（P<0.05）。2000-2018年人均GDP、人口密度的回归系数t检验差异均无统计学意义（P>0.05），其他的均有统计学意义（P<0.05）。按标准化回归系数绝对值大小排序，有统计学意义的自变量1970-2000年依次为人口密度、城镇人口增长率、人均GDP、超百万城市群的人口、CO2排放量、人均居民最终消费支出、总生育率、人口增长率、耗电量，2000-2018年依次为人均居民最终消费支出、超百万城市群的人口、护士和助产士数、人均当前卫生支出、CO2排放量。结论 日本IMR影响因素动态变化，人均GDP不是关键性影响因素，出现了对婴儿死亡率从有影响向无影响的关系转变，不能过度放大经济发展对IMR的作用。
关键词： 婴儿死亡率；人均GDP；岭回归；日本
Abstract
Objective To search the influencing factors of infant mortality rate (IMR) in Japan at different stages, and analyze the role of per capita GDP. Methods IMR from 1970 to 2000 and from 2000 to 2018 were identified as dependent variable, and relevant economic and social factors were identified as independent variables for staged ridge regression analysis. The independent variables with statistically significant difference in regression coefficient t-test were identified as influencing factors of IMR, and the absolute value of standardized regression coefficient was compared to judge the degree of influence on dependent variables. Results The difference of ridge regression equation F test between the two stages was statistically significant (P<0.05). There were significant difference in t-test of each regression coefficient from 1970 to 2000(P<0.05). There were no significant difference in the t-test of the regression coefficients of per capita GDP and population density from 2000 to 2018(P>0.05), and the others were statistically significant (P<0.05). Conclusion The impact factors of IMR are dynamic, and the per capita GDP is not a key factor. There is indeed a shift in the relationship between per capita GDP and IMR from impact to non impact. The role of economic growth in IMR should not be exaggerated.
Key words： infant mortality rate; Per capita GDP; Ridge regression; Japan
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