自回归移动平均模型在心血管疾病死亡预测中的应用  

Application of an autoregressive integrated moving average model in prediction of cardiovascular disease mortality

作　　者：郭亮 赖佳伟 周小军[1] 罗蝶 陈家言 李佳俊妮 GUO Liang;LAI Jia-wei;ZHOU Xiao-jun;LUO Die;CHEN Jia-yan;LI Jia-jun-ni(School of Public Health,Jiangxi Provincial Key Laboratory of Preventive Medicine,Nanchang University,Nanchang,Jiangxi 330006,China)

机构地区：[1]南昌大学公共卫生学院,江西省预防医学重点实验室,江西南昌330006

出　　处：《上海预防医学》2021年第9期807-812,共6页Shanghai Journal of Preventive Medicine

摘　　要：【目的】基于自回归移动平均(ARIMA)模型,构建江西省渝水区居民心血管疾病死亡时间序列模型,为该地区心血管疾病防治工作提供数学模型支撑。【方法】基于江西省渝水区居民2014—2018年心血管疾病死亡的时序资料,使用Econometrics View 9.0软件构建ARIMA季节调整模型预测该地区居民2019—2021年心血管疾病死亡情况。【结果】江西省渝水区居民2014—2018年心血管疾病月度死亡数呈现长期上升趋势,季节规律明显,每年春季和冬季为心血管病死亡高峰期。将原始序列N1经一阶差分及一阶季节性差分后,序列n1表现出良好平稳性(P<0.05)。列出所有的理论模型并分别计算其模型参数,经统计学检验后,筛选出7个ARIMA季节调整备选模型,其中ARIMA(1,1,1)(1,1,1)12为最优模型,R^(2)=0.749,调整R^(2)=0.724,赤池信息准则(AIC)=8.454,施瓦兹准则(SC)=8.633,汉南-奎因准则(HQ)=8.515。ARIMA(1,1,1)(1,1,1)12模型的残差序列通过白噪声检验(P>0.05),预测效果良好。【结论】ARIMA(1,1,1)(1,1,1)12模型可以较准确地模拟江西省渝水区心血管疾病死亡的长期趋势及季节规律,并对其年度变化趋势及月度分布做出科学的预测。[Objective]To use autoregressive integrated moving average(ARIMA)model for predicting the mortality of cardiovascular diseases in residents in Yushui District,Jiangxi Province,and to provide basis for developing the prevention and control strategies as well as to promote the continuous optimization of chronic disease prevention and treatment demonstration area.[Methods]Based on the cardiovascular death monitoring data of residents in Yushui District,Jiangxi Province from 2014 to 2018,Econometrics View 9.0 software was used to construct the ARIMA seasonal adjustment model to predict the monthly cardiovascular death in this area.[Results]The monthly death rate of cardiovascular diseases in Yushui showed a long-term rising trend,with an apparent seasonal pattern(a peak of cardiovascular death from December to January each year).After the original sequence was subjected to first-order difference and first-order seasonal difference,the difference sequence showed good stationarity(P<0.05).All the theoretical models were listed and their model parameters were calculated respectively.After statistical test(P<0.05),7 alternative models for seasonal adjustment of ARIMA were selected.Among them,ARIMA(1,1,1)(1,1,1)_(12) is the optimal model selected in this study(R^(2)=0.749,Adjustment R^(2)=0.724,AIC=8.454,SC=8.633,HQ=8.515).And its residual sequence was tested by white noise test(P>0.05),indicating that the prediction effect was good.[Conclusion]ARIMA(1,1,1)(1,1,1)_(12) model can accurately simulate the long-term trend and seasonal pattern of cardiovascular disease death in Yushui,and make a scientific prediction of the trend and monthly distribution of cardiovascular disease death in the next three years.

关 键 词：自回归移动平均模型 心血管疾病 死亡 居民 渝水区 江西省 

分 类 号：R135[医药卫生—劳动卫生]