1990-2019年中国归因于高体质指数的2型糖尿病疾病负担分析与预测研究  

Analysis and Prediction of the Disease Burden of Type 2 Diabetes Attributable to High Body Mass Index in China from 1990 to 2019

作　　者：李子悦 方珈文 林凯程[2] LI Ziyue;FANG Jiawen;LIN Kaicheng(School of Health Management,Southern Medical University,Guangzhou 510515,China;Nanfang Hospital,Southern Medical University,Guangzhou 510515,China)

机构地区：[1]南方医科大学卫生管理学院,广东省广州市510515 [2]南方医科大学南方医院,广东省广州市510515

出　　处：《中国全科医学》2024年第9期1126-1133,1148,共9页Chinese General Practice

基　　金：广东省哲学社会科学“十三五”规划课题(GD18XGL53)。

摘　　要：背景中国的糖尿病患者数位居全球首位。近年来糖尿病患病率和死亡率不断上升,威胁人们健康水平,给我国人民群众带来沉重负担。随着肥胖患病率不断上升,预计糖尿病疾病负担将持续上升,糖尿病已成为我国不容忽视的公共卫生问题。目的描述和分析1990—2019年中国归因于高BMI的2型糖尿病疾病负担状况及其变化趋势,预测2020—2024年中国归因于高BMI的2型糖尿病疾病负担状况,旨在为中国2型糖尿病科学防控提供依据。方法于2023年5月,从2019年全球疾病负担(GBD 2019)中提取1990—2019年中国2型糖尿病伤残调整寿命年(DALYs)、DALYs率、标化DALYs率、死亡人数、死亡率及标化死亡率等疾病负担指标的数据,采用联结点回归模型通过年度变化百分比(APC)和平均年度变化百分比(AAPC)分析其变化趋势。基于1990—2016年数据(训练集),构建归因于高BMI的2型糖尿病DALYs率和死亡率的自回归移动平均(ARIMA)模型,利用2017—2019年数据(测试集)进行模型评价。用预测值与实际值得到的相对误差、模型的平均绝对误差(MAE)、平均绝对百分比误差(MAPE)、均方误差(MASE)及均方根误差(RMSE)判断模型预测效果,选择最佳模型预测2020—2024年中国归因于高BMI的2型糖尿病疾病负担。结果1990—2019年:疾病负担整体呈上升趋势(标化DALYs率AAPC=2.85%,标化死亡率AAPC=2.32%,均P<0.05),标化DALYs率从80.21/10万增至181.54/10万,标化死亡率从1.25/10万增至2.39/10万;男性和女性的标化DALYs率和标化死亡率均呈快速上升趋势,与1990年相比,2019年男性标化DALYs率增长了173%,女性增长了89%,男性标化死亡率增长了146%,女性增长了58%;DALYs率和死亡率随年龄增加明显增加,DALYs率在30岁后迅速增加,高峰基本维持在65~69岁(1990年337.47/10万,2019年711.09/10万)和70~74岁年龄组(1990年323.64/10万,2019年730.47/10万),人群死亡率在45岁后迅速增加,高峰维持�Background China ranks first in the world in terms of the number of diabetes patients.In recent years,the prevalence and mortality of diabetes have been rising,threatening people's health and placing a heavy burden on the people of China.As the prevalence of obesity continues to rise,the burden of diabetes is expected to continue to rise,and diabetes has become a public health problem that cannot be ignored in China.Objective To describe and analyze the disease burden of type 2 diabetes attributable to high BMI and its trend in China from 1990 to 2019,and predict the disease burden of type 2 diabetes attributable to high BMI in China from 2020 to 2024,so as to provide a basis for the scientific prevention and control of type 2 diabetes in China.Methods In May 2023,data on the burden of disease indicators of type 2 diabetes such as disability-adjusted life years(DALYs),DALYs rate,standardized DALYs rate,death toll,mortality rate and standardized mortality rate of type 2 diabetes in China from 1990 to 2019 were extracted from the Global Burden of Disease 2019(GBD 2019),and the trend was analyzed by annual percentage change(APC)and average annual percentage change(AAPC)using the Joinpoint Regression Model.An autoregressive moving average(ARIMA)model of DALYs rate and mortality rate of type 2 diabetes attributable to high BMI was constructed based on the data from 1990 to 2016(training set),and evaluated using the data from 2017 to 2019(test set).The relative error between the predicted value and the actual value,the mean absolute error(MAE),mean absolute percentage error(MAPE),mean square error(MSE)and root mean square error(RMSE)of the model were used to determine the model prediction effect,and the optimal model was selected to predict the burden of type 2 diabetes attributable to high BMI in China from 2020 to 2024.Results From 1990 to 2019,the burden of disease showed an overall upward trend(AAPC of standardized DALYs rate=2.85%,AAPC of standardized mortality=2.32%,both P<0.05),the standardized DALYs rate increa

关 键 词：糖尿病 2型 人体质量指数 超重 疾病负担 联结点回归模型 ARIMA模型 预测 伤残调整寿命年 

分 类 号：R587.1[医药卫生—内分泌] R197.1[医药卫生—内科学]