Chinese General Practice ›› 2024, Vol. 27 ›› Issue (09): 1126-1133.DOI: 10.12114/j.issn.1007-9572.2023.0504

Special Issue: 内分泌代谢性疾病最新文章合集

• Original Research • Previous Articles     Next Articles

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

  

  1. 1. School of Health Management, Southern Medical University, Guangzhou 510515, China
    2. Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
  • Received:2023-08-10 Revised:2023-10-20 Published:2024-03-20 Online:2023-12-19
  • Contact: LIN Kaicheng

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

  

  1. 1.510515 广东省广州市,南方医科大学卫生管理学院
    2.510515 广东省广州市,南方医科大学南方医院
  • 通讯作者: 林凯程
  • 作者简介:
    作者贡献:李子悦负责研究的整体构思与设计、数据收集整理、论文撰写与修订;方珈文负责数据分析、图表制作、文献整理;林凯程负责文章的修订、文章的质量控制与审查,并提供资金资助。
  • 基金资助:
    广东省哲学社会科学"十三五"规划课题(GD18XGL53)

Abstract:

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 increased from 80.21/100 000 to 181.54/100 000, and the standardized mortality rate increased from 1.25/100 000 to 2.39/100 000. The standardized DALYs rate and standardized mortality rate of both men and women showed a rapid upward trend, with standardized DALYs rate increasing by 173% for males and 89% for females compared to 2019, as well as the standardized mortality rate increasing by 146% for males and 58% for females. The DALYs rate and mortality rate increased significantly with age, with DALYs rates increasing rapidly after age 30 years, with peaks basically maintained in the 65-69 (337.47/100 000 in 1990, 711.09/100 000 in 2019) and 70-74 age groups (323.64/100 000 in 1990, 730.47/100 000 in 2019) , and the population mortality rate increased rapidly after the age of 45 years and the peak was maintained above the age of 95 years (12.78/100 000 in 1990 and 33.29/100 000 in 2019) . The DALYs and mortality rates of type 2 diabetes attributable to high BMI in China was increasing at a higher rate compared to the world. There were four inflection points in 1990-2019, the standardized DALYs rate and standardized mortality rate increased the fastest in 2000-2004 and 1996-2004, respectively. The ARIMA model predicted that the standardized DALYs rate and standardized mortality rate of type 2 diabetes attributable to high BMI in China would continue to increase from 2020 to 2024, reaching 205.142/100 000 (95%CI=189.775/100 000-220.508/100 000) and 2.621/100 000 (95%CI=2.343/100 000-2.900/100 000) by 2024, respectively.

Conclusion

The disease burden of type 2 diabetes attributable to high BMI in China is generally on the rise, manifested by an increase in the disease burden and number of deaths attributable to DALYs, and the growth rate is higher than globally. The disease burden of type 2 diabetes attributable to high BMI in men was progressively higher than that in women. The DALYs rate and mortality rate of type 2 diabetes attributable to high BMI were trending towards younger age groups. The ARIMA model indicated that the disease burden of type 2 diabetes attributable to high BMI was expected to continue to rise. In order to reduce the disease burden of type 2 diabetes, health education should be strengthened for the key populations (male, middle-aged and elderly people) to improve the awareness of diabetes prevention and control, and weight management can be strengthened by promoting healthy diet and lifestyle habits.

Key words: Diabetes mellitus, type 2, Body mass index, Overweight, Burden of illness, Joinpoint regression model, ARIMA model, Forecasting, Disability-adjusted life years

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,高峰维持在95岁以上(1990年12.78/10万,2019年33.29/10万);与全球相比,我国归因于高BMI的2型糖尿病的DALYs率和死亡率整体增速均较高。在1990—2019年中均有4个时间拐点,标化DALYs率和标化死亡率分别在2000—2004年和1996—2004年增速最快。经ARIMA模型预测得到2020—2024年中国归因于高BMI的2型糖尿病标化DALYs率和标化死亡率均呈持续上升趋势,到2024年分别达到205.142/10万(95%CI=189.775/10万~220.508/10万)和2.621/10万(95%CI=2.343/10万~2.900/10万)。

结论

我国归因于高BMI的2型糖尿病的疾病负担总体呈上升趋势,表现为由伤残导致的疾病负担与死亡人数升高,且增速高于全球。我国男性归因于高BMI的2型糖尿病的疾病负担逐渐高于女性,归因于高BMI的2型糖尿病的DALYs率和死亡率有年轻化趋势,ARIMA模型显示归因于高BMI的2型糖尿病的疾病负担预计将持续上升。为减轻2型糖尿病疾病负担,应该对重点人群(男性、中老年人群)加强健康教育,以提高对糖尿病防治的知晓度,可以通过提倡健康饮食和生活习惯加强体质量管理。

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