REFINING OF ASTHMA PREVALENCE SPATIAL DISTRIBUTION AND VISUALIZATION OF OUTDOOR ENVIRONMENT FACTORS USING GIS AND ITS APPLICATION FOR IDENTIFICATION OF MUTUAL ASSOCIATIONS
Language English Country Czech Republic Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
26615660
DOI
10.21101/cejph.a4193
Knihovny.cz E-resources
- MeSH
- Asthma epidemiology MeSH
- Residence Characteristics * MeSH
- Child MeSH
- Geographic Information Systems MeSH
- Air Pollutants analysis MeSH
- Humans MeSH
- Linear Models MeSH
- Adolescent MeSH
- Child, Preschool MeSH
- Prevalence MeSH
- Spatial Analysis MeSH
- Environment * MeSH
- Air Pollution analysis MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Child, Preschool MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic epidemiology MeSH
- Names of Substances
- Air Pollutants MeSH
AIM: This study presents a procedure of complex assessment of the environment impact on asthma prevalence. This approach is also applicable for any other disease which is supposed to be associated with the quality of the outdoor environment. METHODS: The input data included asthma prevalence values from the National Institute of Public Health (NIPH) cross-section questionnaire survey (13,456 children) and annual reports on activities of all paediatricians in the Czech Republic (2,072 surgeries); concentrations of PM10, PM2.5, NO2, SO2, O3, benzene, benzo(a)pyrene, As, Cd, Pb and Ni; emissions of total suspended particles, SO2, NOx, CO, VOC, NH3; traffic intensity; land cover (anthropogenic area, urban greenery, arable land, grassland, other agricultural land, forests); proportion of cultivation of individual agricultural crops (17 categories); and proportion of individual woods (15 categories). Using the Geographical Information Systems (GIS) analysis the integration of all source data through one spatial unit was achieved and complete data sets were compiled to be subjected to statistical analysis (combination of factor analysis with logistic/linear regression). RESULTS: In this study, the approach of combined use of GIS analyses and statistical evaluation of large input data sets was tested. The asthma prevalence demonstrated positive associations with the air pollution (PM10, PM2.5, benzene, benzo(a)pyren, SO2, Pb, Cd) and the rate of agricultural use of land (growing oats, rye, arable fodder crops). Conversely, there was a negative association with the occurrence of natural forests (ash, poplar, fir, beech, spruce, pine). No significant associations were observed with the distance from the road, traffic intensity and NO2 concentration. CONCLUSIONS: These findings suggest that the outdoor quality may be one of the crucial factors for asthma prevalence.
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