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亚洲和西方国家主要国家哮喘发病率的模式、趋势及其对2030年的预测。

Patterns and trends in asthma incidence rates in main Asian and Western countries and their prediction to 2030.

作者信息

Zheng Yang, Lan Lei, Lu Gan, Gao Ya-Dong

机构信息

Department of Allergy, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China.

State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China.

出版信息

Chin Med J Pulm Crit Care Med. 2024 Sep 17;2(3):188-196. doi: 10.1016/j.pccm.2024.08.004. eCollection 2024 Sep.

DOI:10.1016/j.pccm.2024.08.004
PMID:39403411
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11471091/
Abstract

BACKGROUND

The urbanization and industrialization of East and Southeast Asia in decades past has significantly altered living environment and lifestyles, which may have complicated effects on the burden of asthma. We aim to examine the patterns and trends of asthma incidence rates in six major East and Southeast Asian countries as well as five major Western countries, and predict the numbers of new cases attributed to various factors.

METHODS

Data on annual asthma incident cases and corresponding population by age group were drawn from 6 major selected East and Southeast Asian countries available in the Global Burden of Disease database, including China, Japan, Korea, Singapore, Philippines, and Thailand. We also collected data of five major high-income Western countries for comparative purposes. Two separate Bayesian age-period-cohort models, representing pre-COVID (model 1) and post-COVID (model 2) scenarios, were constructed to predict the asthma incidence until 2030.

RESULTS

In model 1, the age-standardized incidence rate of asthma will be the highest in the US (1970.07 per 100,000, 95% confidence interval [CI] 533.05-4455.03), while the lowest incidence rate will be found in Singapore (296.72 per 100,000, 95% CI 135.16-899.55) in 2030. Between 1990 and 2030, the incidence of asthma is projected to increase in China and Thailand, with average annual percentages changes (AAPC) ranging from 0.70% to 1.80%. The remaining four Asian countries show a declining trend, with AAPC ranging from -0.51% to -2.00%. In model 2, the US is estimated to have the highest age-standardized incidence rate (902.71 per 100,000, 95% CI 375.44-2277.24), while Korea will have the lowest incidence rate (176.46 per 100,000, 95% CI 58.77-512.09) in 2030. A decrease in asthma incidence was observed in all countries with the overall AAPC ranging from -3.42% to -0.42%. Notably, a turning point was found around 2020, after which the incidence rates dropped significantly.

CONCLUSIONS

Pandemic-related factors may temporarily lower the incidence of asthma. The expected increasing asthma incidence in pre-COVID scenario (model 1) should still warrant attention from public health practitioners and call for efforts to reduce the burden of asthma.

摘要

背景

过去几十年里,东亚和东南亚地区的城市化和工业化显著改变了生活环境和生活方式,这可能对哮喘负担产生复杂影响。我们旨在研究东亚和东南亚六个主要国家以及五个主要西方国家哮喘发病率的模式和趋势,并预测归因于各种因素的新发病例数。

方法

从全球疾病负担数据库中选取的6个东亚和东南亚主要国家,包括中国、日本、韩国、新加坡、菲律宾和泰国,获取按年龄组划分的年度哮喘发病病例和相应人口的数据。为作比较,我们还收集了五个主要西方高收入国家的数据。构建了两个独立的贝叶斯年龄-时期-队列模型,分别代表新冠疫情前(模型1)和新冠疫情后(模型2)的情景,以预测到2030年的哮喘发病率。

结果

在模型1中,预计到2030年,美国的哮喘年龄标准化发病率最高(每10万人中1970.07例,95%置信区间[CI]为533.05 - 4455.03),而新加坡的发病率最低(每10万人中296.72例,95%CI为135.16 - 899.55)。1990年至2030年期间,预计中国和泰国的哮喘发病率将上升,年均变化百分比(AAPC)在0.70%至1.80%之间。其余四个亚洲国家呈下降趋势,AAPC在 - 0.51%至 - 2.00%之间。在模型2中,预计到2030年,美国的哮喘年龄标准化发病率最高(每10万人中902.71例),95%CI为375.44 - 2277.24),而韩国的发病率最低(每10万人中176.46例,95%CI为58.77 - 512.09)。所有国家的哮喘发病率均下降,总体AAPC在 - 3.42%至 - 0.42%之间。值得注意的是,在2020年左右发现了一个转折点,此后发病率大幅下降。

结论

与大流行相关的因素可能会暂时降低哮喘的发病率。在新冠疫情前情景(模型1)中预计哮喘发病率上升,这仍应引起公共卫生从业者的关注,并呼吁努力减轻哮喘负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/5a6dc9329052/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/81c8fa8c9478/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/812256deb939/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/5a6dc9329052/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/81c8fa8c9478/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/812256deb939/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29f7/11471091/5a6dc9329052/gr3.jpg

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