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Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
Spatial patterns of lower respiratory tract infections and their association with fine particulate matter
Aji Kusumaning Asri1, Wen-Chi Pan2, Hsiao-Yun Lee3
1Department of Geomatics, National Cheng Kung University, Tainan, 70101, Taiwan.
Abstract:
This study aimed to identify the spatial patterns of lower respiratory tract infections (LRIs) and their association with fine particulate matter (PM2.5). The disability-adjusted life year (DALY) database was used to represent the burden each country experiences as a result of LRIs. PM2.5 data obtained from the Atmosphere Composition Analysis Group was assessed as the source for main exposure. Global Moran's I and Getis-Ord Gi* were applied to identify the spatial patterns and for hotspots analysis of LRIs. A generalized linear mixed model was coupled with a sensitivity test after controlling for covariates to estimate the association between LRIs and PM2.5. Subgroup analyses were performed to determine whether LRIs and PM2.5 are correlated for various ages and geographic regions. A significant spatial auto-correlated pattern was identified for global LRIs with Moran's Index 0.79, and the hotspots of LRIs were clustered in 35 African and 4 Eastern Mediterranean countries. A consistent significant positive association between LRIs and PM2.5 with a coefficient of 0.21 (95% CI 0.06-0.36) was identified. Furthermore, subgroup analysis revealed a significant effect of PM2.5 on LRI for children (0-14 years) and the elderly (≥ 70 years), and this effect was confirmed to be significant in all regions except for those comprised of Eastern Mediterranean countries.
Insights
Fine particulate matter (PM2.5) exposure is linked to increased lower respiratory tract infections (LRIs) globally. Hotspots for LRIs are concentrated in Africa and the Eastern Mediterranean, particularly affecting children and the elderly.
Area of Science:
- Environmental Health
- Epidemiology
- Spatial Analysis
Background:
- Lower respiratory tract infections (LRIs) represent a significant global health burden.
- Fine particulate matter (PM2.5) is a major air pollutant with suspected links to respiratory diseases.
- Understanding the spatial distribution of LRIs and their environmental determinants is crucial for public health interventions.
Purpose of the Study:
- To investigate the global spatial patterns of lower respiratory tract infections (LRIs).
- To examine the association between LRI burden and exposure to fine particulate matter (PM2.5).
- To identify geographical hotspots of LRIs and analyze demographic-specific risks.
Main Methods:
- Utilized disability-adjusted life year (DALY) data for LRI burden and PM2.5 data from the Atmosphere Composition Analysis Group.
- Applied spatial statistics including Global Moran's I and Getis-Ord Gi* for pattern and hotspot analysis.
- Employed a generalized linear mixed model with covariate control and subgroup analyses for age and region.
Main Results:
- Identified significant global spatial autocorrelation of LRIs (Moran's Index = 0.79).
- Pinpointed LRI hotspots in 35 African and 4 Eastern Mediterranean countries.
- Found a consistent positive association between PM2.5 exposure and LRIs (coefficient = 0.21, 95% CI: 0.06-0.36), especially in children and the elderly across most regions.
Conclusions:
- LRIs exhibit distinct spatial clustering, with significant hotspots in specific African and Eastern Mediterranean regions.
- PM2.5 exposure is a significant risk factor for LRIs, with heightened vulnerability observed in pediatric and elderly populations.
- Targeted air quality management and public health strategies are warranted in identified high-risk areas and for vulnerable age groups.
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