Abstract:

Objective　To understand the current situation of neurological disease burden in China, to analyze the changing trend of neurological disease burden in China from 1990 to 2019, and to explore the influence of age, period, and cohort on neurological disease burden. Methods　The burden of neurological diseases in China and the whole world from 1990 to 2019 based on data from the Global Burden of Disease Study 2019 (GBD 2019) was descripted. The changing trends of neurological disease burden were analyzed by the Joinpoint regression model. The endogenous factor estimation method and age-period-cohort (APC) model were used to fit the Chinese and global disability-adjusted life year (DALY) rates of neurological diseases, so as to further analyze the age effect, period effect, and cohort effect. The R language software was used to build ARIMA models to predict the age-standardized incidence rate, age-standardized mortality rate, and age-standardized DALY rate of neurological diseases in China and the whole world from 2020 to 2024. Results　The Joinpoint regression model results showed that the age-standardized DALY rates of neurological diseases in China and the whole world from 1990 to 2019 both showed a decreasing trend, from 1 097.64/100 000 and 1 264.17/100 000 in 1990 to 1 076.59/100 000 and 1 253.56/100 000 in 2019, with a greater decrease in China (1.92%) than the whole world (0.84%); there were statistical differences in the decreasing trends (all P<0.05). The APC model showed that the age effect of neurological disease burden in China and the whole world showed a "J" shaped distribution. The risk of neurological disease burden increased with age after 50; disease burden increased with period effect, but decreased with cohort effect, with the late birth cohort having smaller risk of neurological disease burden than the earlier birth cohort. The ARIMA model results showed that the age-standardized DALY rates for neurological diseases in China and the whole world were roughly on the rise from 2020 to 2024. Conclusions　Strengthening the screening and prevention of neurological diseases, focusing on the elderly, and reducing behavioral risk factors such as smoking and improving irrational dietary habits are priority measures for the prevention and control of neurological diseases.

Key words:

Nurden of disease, Neurological diseases, Trend analysis, Joinpoint regression model, Age-period-cohort model, ARIMA model

摘要：

目的　了解中国神经系统疾病负担现状，分析中国1990—2019年神经系统疾病负担变化趋势，探讨年龄、时期、队列3个因素对神经系统疾病负担的影响。方法　基于2019年全球疾病负担研究数据（GBD 2019），对1990—2019年中国与全球神经系统疾病负担进行描述，采用Joinpoint回归模型分析神经系统疾病负担的变化趋势；利用内生因子估（IE）算法和年龄-时期-队列（APC）模型对中国与全球神经系统疾病伤残调整损失寿命年率（DALY）进行拟合，进一步分析神经系统疾病的年龄效应、时期效应和队列效应；运用R语言软件建立ARIMA模型预测2020—2024年中国与全球神经系统疾病的标化发病率、死亡率和DALY率。结果　Joinpoint回归模型结果显示，1990—2019年，中国与全球神经系统疾病标化DALY率均呈下降趋势，由1990年的1 097.64/10万、1 264.17/10万下降至2019年的1 076.59/10万、1 253.56/10万，中国下降幅度（1.92%）较全球（0.84%）大，且下降趋势差异均有统计学意义（均P<0.05）。APC模型显示，中国与全球的神经系统疾病负担的年龄效应呈现“J”型分布，50岁之后神经系统疾病负担风险随年龄增加而增大，疾病负担随时期效应增加而增大，但随队列效应增加而减小，即晚出生队列的神经系统疾病负担风险小于较早出生队列。ARIMA模型预测结果显示，中国与全球神经系统疾病的标化DALY率在2020—2024年大致呈上升趋势。结论　加强神经系统疾病的筛查及防治工作，重点关注老年人群的防治，减少吸烟、改善不合理膳食习惯等行为是防控神经系统疾病的优先措施。

关键词:

疾病负担, 神经系统疾病, 趋势分析, Joinpoint回归模型, 年龄-时期-队列模型, ARIMA模型