Evidence map›Paper›PMID 39403411›Full record

ArticleChinese medical journal pulmonary and critical care medicine2024

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

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

Abstract read
In one paragraph

Article in Chinese medical journal pulmonary and critical care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Recent advances in allergen immunotherapy.Chinese medical journal · 2026
    Review
  5. Article
  6. Lp-PLA2-derived LysoPC drives dendritic cell immunogenic activation and Th17 inflammation in severe asthma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Skin-lung axis in the atopic march: The immune link from skin to lungs.Chinese medical journal pulmonary and critical care medicine · 2025
    Review
  12. Review
  13. The value of treatable traits across the spectrum of adult asthma severity.Chinese medical journal pulmonary and critical care medicine · 2025
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yang ZhengDepartment of Allergy, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China.
Lei LanState 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.
Gan LuDepartment of Allergy, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China.
Ya-Dong GaoDepartment of Allergy, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AsthmaBayesian age–period–cohort modelCoronavirus disease 2019 (COVID-19)East and Southeast AsiaPrediction

Identifiers

PMID39403411
PMCPMC11471091

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.