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1990-2019年中国痛风疾病负担趋势及未来十年预测研究 被引量:1

Trend Analysis of Gout Burden in China from 1990 to 2019 and Prediction for the Next Ten Years
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摘要 背景痛风是常见的炎症性关节炎之一,对人们的健康造成很大的危害,但目前针对我国痛风疾病负担趋势分析与预测的相关研究有限。目的分析1990—2019年中国痛风疾病负担的变化趋势,并预测未来10年痛风的标化伤残调整寿命年(DALYs)率、标化发病率和标化患病率。方法提取全球疾病负担研究(GBD)2019有关中国痛风DALYs、发病情况和患病情况等疾病负担指标,采用Joinpoint回归模型计算标化DALYs率、标化发病率和标化患病率的年度变化百分比(APC)和平均年度变化百分比(AAPC),采用自回归移动平均模型(ARIMA模型)对2020—2029年的标化DALYs率、标化发病率和标化患病率进行预测。结果1990—2019年,中国痛风DALYs从187436人年增至510485人年,增长了172.35%,发病人数从1181969例增至3041329例,增长了157.31%,患病人数从5864143例增至16161325例,增长了175.60%(对应的标化率分别增长了28.45%、25.92%和28.63%)。Joinpoint回归结果显示,1990—2019年,标化DALYs率、标化发病率、标化患病率整体呈上升趋势(AAPC分别为0.9%、0.8%、0.9%,P<0.05)。痛风疾病负担具有明显的性别和年龄差异,男性疾病负担高于女性,标化DALYs率、标化发病率和标化患病率男女性别比范围分别为3.23~3.51、3.14~3.40和3.17~3.42。女性各指标年龄高峰总体比男性延后,女性在45岁之后疾病负担开始加重,男女性疾病负担均在90岁之后再次增加。ARIMA模型结果显示,预计到2029年,因痛风造成的标化DALYs率和标化发病率分别下降0.33%和0.45%,标化患病率上升0.71%。结论1990—2019年中国痛风疾病负担增长趋势明显,存在明显的性别和年龄差异,且出现年轻化趋势。预计到2029年,因痛风造成的标化患病率略有上升。 Background Gout is the most common inflammatory arthritis,which causes great harm to people's health,however,there are limited studies on the trend analysis and prediction of gout burden in China.Objective To analyze the changing trend of gout in China from 1990 to 2019,and predict the age-standardized disability-adjusted life years(DALYs)rate,incidence rate and prevalence rate of gout in the next 10 years.Methods The indicators of DALYs,incidence,and prevalence of gout in China were extracted from the Global Burden of Disease Study(GBD 2019),the annual percentage change(APC)and annual average percentage change(AAPC)of the age-standardized DALYs rate,age-standardized incidence rate and age-standardized prevalence rate were calculated using the Joinpoint regression model,autoregressive integrated moving average model(ARIMA model)was used to predict the age-standardized DALYs rate,age-standardized incidence rate and age-standardized prevalence rate in 2020-2029.Results In 1990-2019,the DALYs of gout in China increased from 187436 to 510485 person-years,with an increase of 172.35%,the number of cases increased from 1181969 to 3041329,with an increase of 157.31%,the number of patients increased from 5864143 to 16161325,with an increase of 175.60%(the corresponding standardized rates increased by 28.45%,25.92%and 28.63%,respectively).Joinpoint regression results showed an overall increasing trend in the age-standardized DALYs rate,age-standardized incidence rate and age-standardized prevalence rate(AAPC was 0.9%,0.8%,0.9%,respectively,P<0.05)from 1990 to 2019.The gout burden had significant gender and age differences,with men having a higher burden than women,and the range of the male-to-female gender ratios for the standardized DALYs rate,age-standardized incidence rate,and age-standardized prevalence rate was 3.23 to 3.51,3.14 to 3.40,and 3.17 to 3.42,respectively.The age peaks for each indicator were generally delayed in females compared to males,the burden began to increase in females after 45 years of age,and the burden increased again after 90 years of age for both males and females.The ARIMA model results showed that the age-standardized DALYs rate and age-standardized incidence rate due to gout are projected to decrease by 0.33%and 0.45%,respectively,and the age-standardized prevalence rate to increase by 0.71%by 2029.Conclusion From 1990 to 2019,the gout burden in China showed an obvious increasing trend,with significant gender and age differences,and a trend of younger age.The age-standardized prevalence rate due to gout is expected to increase slightly by 2029.
作者 方珈文 冯天元 周志衡 李子悦 颜丹虹 林凯程 FANG Jiawen;FENG Tianyuan;ZHOU Zhiheng;LI Ziyue;YAN Danhong;LIN Kaicheng(School of Health Management,Southern Medical University,Guangzhou 510515,China;Shenzhen Pingshan District People's Hospital,Shenzhen 518118,China;Nanfang Hospital,Southern Medical University,Guangzhou 510515,China)
出处 《中国全科医学》 北大核心 2024年第2期245-252,共8页 Chinese General Practice
基金 国家重点研发计划项目(2020YFC2006401) 广东省哲学社会科学“十三五”规划项目(GD18XGL53) 深圳市科技计划项目(JCYJ20210324135411031) 坪山区卫生健康系统科研项目(202289)。
关键词 痛风 发病率 患病率 疾病负担 趋势分析 ARIMA模型 伤残调整寿命年 Gout Incidence Prevalence Burden of illness Trend analysis ARIMA model DALYs
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