a 9-year trend in the prevalence of allergic disease based on national health insurance data
Clicks: 266
ID: 137374
2015
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Steady Performance
67.8
/100
264 views
215 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Objectives: To investigate trends in the prevalence of allergic disease over a 9-year period. Methods: Using National Health Insurance Service (NHIS) data, the annual number of patients with allergic disease was obtained for each regional subdivisions (small cities, counties, and districts) from 2003 to 2011. Annual populations for each sub-region were obtained and used to calculate the standardized prevalence. To compare prevalence within the study period, data was standardized spatially and temporally. For standardization, demographic data was used to obtain the registered population and demographic structure for 2010, which was used to perform direct standardization of previous years. In addition, a geographic information system (GIS) was used to visualize prevalence for individual sub-regions, and allergic diseases were categorized into five groups according to prevalence. Results: The nationwide outpatient prevalence of allergic rhinitis increased approximately 2.3-fold, from 1.27% in 2003 to 2.97% in 2013, while inpatient prevalence also increased approximately 2.4-fold,. The outpatient prevalence of asthma increased 1.2-fold, and inpatient prevalence increased 1.3-fold. The outpatient prevalence of atopic dermatitis decreased approximately 12%, and inpatient prevalence decreased 5%. Conclusions: There was a large difference between prevalence estimated from actual treatment data and prevalence based on patients’ self-reported data, particularly for allergic rhinitis. Prevalence must continually be calculated and trends should be analyzed for the efficient management of allergic diseases. To this end, prevalence studies using NHIS claims data may be useful.
| Reference Key |
yoo2015journala
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Byoungin Yoo;Yoonhyung Park;Kwanjun Park;Hoseob Kim |
| Journal | Biodiversity data journal |
| Year | 2015 |
| DOI |
10.3961/jpmph.15.011
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.