Geo-climatic variability and adult asthma hospitalization in Fars, Southwest Iran

Frontiers in Environmental Science(2023)

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摘要
Asthma is a chronic respiratory disease resulting from a complex interaction between genetic and environmental factors. Many environmental factors have been associated with incidence or prevalence of asthma although there is still limited knowledge of major environmental causes of asthma in the general population. This study, for the first time, investigated the effects of climatic and geographical variability on asthma hospitalization among an adult population living in Fars province, southwest Iran. During the study period, the home addresses of patients hospitalized with acute asthma from 2016 to 2019 were mapped. The effects of geo-climatic factors including temperature, rainfall, humidity, evaporation, number of rainy and frosty days, slope, and land covers were assessed on adult asthma hospitalization by Geographical Information System (GIS). Data were analyzed using univariate and multivariate binary logistic regression. A total of 349 patients were recruited, including 157 (44.98%) males and 192 (55%) females. The mean age was 57.77 ± 18.84 years, ranging from 19 to 98 years. Asthmatic patients came from a total of 82 points including villages, towns, and cities. In the univariate analysis, urban setting (OR = 13) and Mean Annual Rainy Days (OR = 1.03) were identified as the factors associated with increased asthma hospitalization, while Mean Annual Temperature (MAT) (OR = 0.927), MinMAT (OR = 0.933), MaxMAT (OR = 0.925), Mean Annual Evaporation (MAE) (OR = 0.999), and slope (OR = 0.925) negatively affected asthma hospitalization. Urban setting was considered the only significant factor in multivariate analysis (OR = 11.026). The major risk zones for adulthood acute asthma in southwest Iran were urban settings and areas with higher numbers of rainy days, lower temperatures, and evaporation at lower slopes.
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关键词
asthma hospitalization,climatic changes,geographical factors,land cover,GIS
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