中国血吸虫病防治杂志(中英文) ›› 2025, Vol. 37 ›› Issue (3): 255-267, 283.

• 论著 • 上一篇    下一篇

1990—2035年全球细粒棘球蚴病疾病负担分析及预测

赖祯1,刘刚2,赵海利1,邱妙妙1,陈建1,罗恩3,辛军国1*,杨晓虹1*   

  1. 1 成都医学院公共卫生学院(四川 成都 610500);2 厦门大学公共卫生学院;3 四川省成都市第五人民医院肝胆胰外科
  • 出版日期:2025-06-25 发布日期:2025-07-14
  • 通讯作者: 杨晓虹 21376686@qq.com 辛军国 junguoxin@163.com
  • 作者简介:赖祯,女,硕士研究生。研究方向:流行病学与统计学方法与应用
  • 基金资助:
    国家自然科学基金(81925019,U22A20333);厦门大学-成都医学院开放课题(XMU-CMC202402)

Analysis and prediction of global burden due to cystic echinococcosis from 1990 to 2035

LAI Zhen1, LIU Gang2, ZHAO Haili1, QIU Miaomiao1, CHEN Jian1, LUO En3, XIN Junguo1*, YANG Xiaohong1*   

  1. 1 School of Public Health, Chengdu Medical College, Chengdu, Sichuan 610500, China; 2 School of Public Health, Xiamen University, China; 3 Department of Hepatobiliary and Pancreatic Surgery, Chengdu Fifth People's Hospital, Sichuan Province, China
  • Online:2025-06-25 Published:2025-07-14

摘要: 目的 分析1990—2021年全球细粒棘球蚴病疾病负担变化趋势、预测2022—2035年全球细粒棘球蚴病疾病负担,为制定细粒棘球蚴病防治策略提供参考。方法 从2021年全球疾病负担研究(Global Burden of Disease Study 2021)数据库中获取1990—2021年全球细粒棘球蚴病年龄标化患病率、死亡率和伤残调整寿命年(disability⁃adjusted life years,DALYs)率及其95%不确定性区间(uncertainty interval,UI)等数据,采用Joinpoint回归模型分析1990—2021年全球细粒棘球蚴病疾病负担变化趋势,采用平滑样条模型和前沿分析探索全球细粒棘球蚴病疾病负担与社会人口学指数(socio⁃demographic index,SDI)间的关联,采用贝叶斯年龄⁃时期⁃队列(Bayesian age⁃period⁃cohort,BAPC)模型预测2022—2035年全球细粒棘球蚴病疾病负担流行趋势。结果 2021年,全球细粒棘球蚴病年龄标化患病率为7.69/105[95% UI:(6.27/105,9.51/105)]、年龄标化死亡率为0.02/105[95% UI:(0.01/105,0.02/105)]、年龄标化DALYs率为1.32/105[95% UI:(0.99/105,1.69/105)]。1990—2021年,全球细粒棘球蚴病年龄标化患病率呈年均增长0.14%的上升趋势、年龄标化死亡率和DALYs率分别呈年均减少4.68%和4.01%的下降趋势。Joinpoint回归分析显示,全球细粒棘球蚴病年龄标化患病率在1990—2000年[年度变化百分比(annual percent change,APC)= -0.66%,95%可信区间(confidence interval,CI):  (-0.70%,-0.61%)]和2005—2015年[APC = -0.88%,95% CI:(-0.93%,-0.82%)]呈下降趋势、在2000—2005年[APC = 3.68%,95% CI:(3.49%,3.87%)]和2015—2021年[APC = 0.30%,95% CI:(0.19%,0.40%)] 呈上升趋势。1990—2021年,全球21个地区细粒棘球蚴病年龄标化患病率(r = -0.17,P < 0.05)、年龄标化死亡率(r = -0.67,P < 0.05)、年龄标化DALYs率(r = -0.60,P < 0.05)均与SDI呈负相关;2021年,全球204个国家和地区细粒棘球蚴病年龄标化死亡率(r = -0.61,P < 0.05)和年龄标化DALYs率(r = -0.44,P < 0.05)均与SDI呈负相关。前沿分析显示,部分SDI较高的国家和地区细粒棘球蚴病年龄标化DALYs率仍与“前沿”有一定差距。BAPC模型预测结果显示,2022—2035年全球男[估计年度变化百分比(estimated annual percentage change,EAPC)= 0.18%,95% CI:(0.13%,0.23%)]、女性细粒棘球蚴病年龄标化患病率有所上升[EAPC = 0.29%,95% CI:(0.24%,0.34%)],而年龄标化死亡率[男性:EAPC = -4.71%,95% CI:(-4.71%,-4.37%);女性:EAPC = -4.74%,95% CI:(-4.74%,-4.74%)]和年龄标化DALYs率[男性:EAPC = -3.35%,95% CI:(-3.36%,-3.34%);女性:EAPC = -3.17%,95% CI:(-3.18%,-3.16%)]有所下降。结论 1990—2021年全球细粒棘球蚴病疾病负担总体呈下降趋势,但预测2022—2035年全球细粒棘球蚴病患病率呈上升趋势;建议加大细粒棘球蚴病防控力度。

关键词: 细粒棘球蚴病, 疾病负担, Joinpoint回归模型, 前沿分析, 贝叶斯年龄?时期?队列模型

Abstract: Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age⁃standardized prevalence, mortality, disability⁃adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio⁃demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age⁃period⁃cohort (BAPC) model.  Results The global age⁃standardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/105 [95% UI: (6.27/105, 9.51/105)], 0.02/105 [95% UI: (0.01/105, 0.02/105)], and 1.32/105 [95% UI: (0.99/105, 1.69/105)] in 2021. The global age⁃standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age⁃standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age⁃standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = -0.66%, 95% confidence interval (CI): (-0.70%, -0.61%)] and from 2005 to 2015 [APC = -0.88%, 95% CI: (-0.93%, -0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC = 0.30%, 95% CI: (0.19%, 0.40%)]. The age⁃standardized prevalence (r = -0.17, P < 0.05), mortality (r = -0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = -0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age⁃standardized mortality (r = -0.61, P < 0.05) and DALYs rates (r = -0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age⁃standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high⁃SDI countries or territories. In addition, the global age⁃standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age⁃standardized mortality [men: EAPC = -4.71%, 95% CI: (-4.37%, -4.71%); women: EAPC = -4.74%, 95% CI: (-4.74%, -4.74%)] and DALYs rates [men: EAPC = -3.35%, 95% CI: (-3.36%, -3.34%); women: EAPC = -3.17%, 95% CI: (-3.18%, -3.16%)] were projected to appear a tendency towards a decline among both men and women.  Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended. 

Key words: Cystic echinococcosis, Burden of disease, Joinpoint regression model, Frontier analysis, Bayesian?age?period?cohort analysis

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