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基于时间序列模型的中国2020—2029年慢性肾病发病和患病情况预测研究 被引量:3

Prediction of the incidence and morbidity of chronic kidney disease in China from 2020 to 2029 based on the time series model
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摘要 目的了解1990—2019年中国慢性肾病发病和患病情况,并预测2020—2029年的发病率及患病率,为慢性肾病的防控提供参考。方法收集2019年全球疾病负担研究(GBD)数据库中1990—2019年中国慢性肾病发病率和患病率等数据。采用SPSS 25.0分别计算变化率和年估计变化百分比(EAPC)。将1990—2016年数据作为训练集,运用R 4.1.0软件构建自回归移动平均(ARIMA)模型和神经网络自回归(NNAR)模型,并运用MATLAB 7.0软件构建灰色模型(GM)。将2017—2019年数据作为测试集评价模型的预测性能。根据平均绝对误差(MAE)、平均绝对百分误差(MAPE)和误差均方根(RMSE)最小的原则选出最优模型,并预测中国2020—2029年慢性肾病的发病率和患病率。结果2019年中国慢性肾病标化发病率和标化患病率分别为161.52/10万和8124.75/10万,女性标化发病率和标化患病率均高于男性;≥70岁人群发病率和患病率在各年龄组中最高;10~24岁人群发病率、0~9岁人群患病率在各年龄组中分别最低。1990—2019年中国慢性肾病标化发病率和标化患病率均呈上升趋势(EAPC分别为0.61%和0.28%,P<0.05)。其中,女性标化发病率和标化患病率上升幅度(EAPC分别为0.63%、0.30%)明显高于男性(EAPC分别为0.58%、0.24%)。选择预测性能最优的ARIMA模型预测中国2020—2029年慢性肾病发病率,选择NNAR模型预测患病率。结果显示,2020—2029年中国慢性肾病总体发病率和患病率均呈上升趋势,预计到2029年总体发病率和患病率将分别达到294.88/10万和10989.40/10万。结论1990—2019年中国慢性肾病标化发病率和标化患病率总体呈上升趋势。预计到2029年中国慢性肾病发病率和患病率将不断增长,提示政府及相关卫生部门应加强女性、高龄等重点人群的疾病监测及早期筛查。 Objective To understand the situation of incidence and morbidity of chronic kidney disease in China from 1990 to 2019,predict the incidence and morbidity from 2020 to 2029,and provide the reference for the prevention and control of chronic kidney disease.Methods The data of incidence and morbidity of chronic kidney disease from 1990 to 2019 were collected from the Global Burden of Disease Study(GBD)2019.SPSS 25.0 software was used to calculate the change rate and estimated annual percentage change(EAPC).Base on the data from 1990 to 2016,AutoRegressive Integrated Moving Average(ARIMA)model and Neural Network AutoRegression(NNAR)model were established by R 4.1.0 software,and Gray Model(GM)was established by MATLAB 7.0 software.The data from 2017 to 2019 were used as a test set to evaluate predictive performance of models.According to the minimum principle of mean absolute error(MAE),mean absolute percentage error(MAPE)and root mean square error(RMSE),the optimal model was selected to predict the incidences and morbidity rates of chronic kidney disease from 2020 to 2029.Results In 2019,the standardized incidence and standardized morbidity of chronic kidney disease in China were 161.52/105 and 8124.75/105,respectively;the standardized incidence and standardized morbidity of chronic kidney disease in females were significantly higher than those in males;the incidence and morbidity of chronic kidney disease in≥70 years old group were the highest in all age groups;the incidence in 10-24 years old group was the lowest in all age groups;the morbidity in 0-9 years old group was the lowest in all age groups.From 1990 to 2019,the standardized incidence and standardized morbidity of chronic kidney disease showed the upward trend(EAPCs were 0.61%and 0.28%,P<0.05,respectively).The upward trend of standardized incidence and morbidity(EAPCs were 0.63%and 0.30%,respectively)in females were significantly higher than those(EAPCs were 0.58%and 0.24%,respectively)in males.ARIMA model with the best prediction performance was used to predict the incidences of chronic kidney disease from 2020 to 2029 in China,and the NNAR model was used to predict the morbidity rates.The prediction results indicated that the incidence and morbidity from 2020 to 2029 will show the upward trend;the incidence and morbidity will reach 294.88/105 and 10989.40/105 in 2029.Conclusion The standardized incidence and standardized morbidity of chronic kidney disease in China showed the significant upward trend from 1990 to 2019.The incidence and morbidity of chronic kidney disease in China in 2029 will continue to increase,suggesting the government and relevant health departments should strengthen the disease monitoring and early screening of key groups(females,advanced age,etc.).
作者 王仕鸿 令垚 杨子华 彭根祺 曹汝岱 吴树法 陈学琴 孔丹莉 于海兵 丁元林 WANG Shihong;LING Yao;YANG Zihua;PENG Genqi;CAO Rudai;WU Shufa;CHEN Xueqin;KONG Danli;YU Haibing;DING Yuanlin(School of Public Health,Guangdong Medical University,Dongguan,Guangdong Province 523808,China)
出处 《中国慢性病预防与控制》 CAS CSCD 北大核心 2023年第11期801-806,共6页 Chinese Journal of Prevention and Control of Chronic Diseases
基金 广东医科大学学科建设项目(4SG21276P) 广东省基础与应用基础研究基金区域联合基金项目(2020B1515120021) 大学生创新创业训练计划项目(S202210571088,GDMU2021112) 广东省基础与应用基础研究基金自然科学基金项目(2021A1515010061,2022A1515012407) 2022年东莞市社会发展科技项目(20221800905642) 广东省医学科研基金项目(A2021395) 广东医科大学科研基金自然科学类重点培育项目(GDMUZ2020008) 湛江市科技发展专项资金竞争性分配项目(2020A01031) 广东医科大学校级大学生创新创业训练计划项目(GDMU2021138)。
关键词 慢性肾病 疾病预测 时间序列模型 Chronic kidney disease Disease prediction Time series model
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