Abstract
Background: Exposure to air pollution aggravates symptoms of atopic dermatitis (AD) in children in the population studies. Variability in individual patient's response from individual susceptibility is needed to be explored. Objective: This study aimed to investigate spectrum of individual variability in the associations between AD symptoms and air quality. Methods: We enrolled 89 children aged 0-6 years with AD (22 890 person-days). Daily manifestation of symptoms was recorded for an average of 257 days (range 100-499). Both an individual analysis using logistic regression models and an overall analysis using a generalized estimating equation were performed. Results: The odds ratios of an individual ranged 0.24-8.11 for particulate matter <10 μm in diameter (PM 10 ), 0.09-101.92 for nitrogen oxide (NO 2 ), 0.03-44.00 for ozone (O 3 ), 0.11-58.30 for sulfur dioxide (SO 2 ), 0.00-15.83 for carbon monoxide (CO), 0.00-39 446.94 for temperature, and 0.03-5.18 for relative humidity, demonstrating a wide individual variability. In the overall analysis, PM 10 , NO 2 , SO 2 , and CO had a significantly positive association, whereas temperature and relative humidity were negatively associated with AD symptoms. Air pollution was responsible for aggravation of symptoms from 24.7% (O 3 ) to 39.3% (SO 2 ) of AD children. Overall, 71.9% of the AD children responded to at least one or more air pollution and weather variable. Conclusion: Responses of AD children to air pollution and weather variable were considerably variable among individuals. An individualized model would be useful to forecast and manage AD symptoms in patients.
| Original language | English |
|---|---|
| Pages (from-to) | 179-187 |
| Number of pages | 9 |
| Journal | Pediatric Allergy and Immunology |
| Volume | 30 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- air quality
- atopic dermatitis
- epidemiology
- forecast
- individualized model
- susceptibility
- time series data analysis
- weather
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