Abstract: Objective To compare and analyze the current burden status of autism spectrum disorders (ASD) in China and globally, to extract the epidemiological characteristics and to predict the burden in 2030, based on the analysis of the global burden of disease (GBD) database, so as to provide reference for the prevention and control of the disease burden caused by ASD. Methods Prevalence and disability-adjusted life years (DALYs) data from 1990 to 2019 for ASD in China and globally were retrieved from the GBD database. Joinpoint regression model was used to analyze the changes in ASD disease burden and calculate average annual percentage change (AAPC) over time. Auto regressive integrated moving average model(ARIMA) was constructed to predict the trend of ASD disease burden in China and globally from 2020 to 2030. Results The age standardized prevalence rate and age standardized DALYs rate in China showed an upward trend from 1990 to 2019, with an average annual increase of 0.14% and 0.15%, respectively, and the increase was higher than the global average level (AAPC=-0.03%, P<0.001, AAPC=-0.03%, P<0.001). It is predicted that the age standardized prevalence rate and age standardized DALYs rate of ASD in China will both show an upward trend by 2030, reaching 376.08/10⁵ and 57.90/10⁵, respectively. In comparison, the global age standardized prevalence rate and age standardized DALYs rate of ASD, which are 369.47/10⁵ and 56.28/10⁵, respectively, and the trend is relatively stable. The burden of ASD is biggest for male children under the age of 5 in China and globally. Conclusion Over the past three decades, the burden of ASD in China has persistently escalated and may exceed the global average in the future, making it particularly urgent to implement targeted prevention and control measures.

Key words: autism spectrum disorder, global burden of disease, disability-adjusted life years, Joinpoint regression model, auto regressive integrated moving average model

摘要： 目的 通过对全球疾病负担(GBD)数据库的分析,了解中国与全球孤独症谱系障碍(ASD)的疾病负担现状及流行特征,并对2030年疾病负担进行预测,为预防和控制因ASD导致的疾病负担提供参考依据。方法 收集全球疾病负担数据库中1990—2019中国及全球ASD患病及伤残调整生命年(DALYs)数据,运用Joinpoint回归模型分析ASD疾病负担随时间的变化并计算平均年度变化百分比(AAPC),构建自回归移动平均模型(ARIMA)预测2020—2030年中国与全球ASD疾病负担趋势。结果 中国1990—2019年中国年龄标化患病率和年龄标化DALYs率均呈上升趋势,平均每年分别上升0.14%和0.15%,且上升幅度高于全球平均水平(AAPC=-0.03%,P<0.001,AAPC=-0.03%,P<0.001)。预测至2030年中国ASD年龄标化患病率和年龄标化DALYs率均呈上升趋势,分别为376.08/10⁵和57.90/10⁵,相比全球ASD年龄标化患病率和年龄标化DALYs率分别为369.47/10⁵和56.28/10⁵,呈较平稳趋势。中国及全球5岁以下年龄组的男童ASD疾病负担最大。结论 中国ASD疾病负担在过去三十年持续上升,并且在未来可能超过全球平均水平,实施有针对性的应对措施显得尤为紧迫。

关键词: 孤独症谱系障碍, 全球疾病负担, 伤残调整生命年, Joinpoint回归模型, 自回归移动平均模型