A comprehensive environmental exposure indicator and respiratory health in asthmatic children: a case study

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Environmental and Ecological Statistics Pub Date : 2024-03-23 DOI:10.1007/s10651-024-00610-0
Giovanna Cilluffo, Gianluca Sottile, Giuliana Ferrante, Salvatore Fasola, Velia Malizia, Laura Montalbano, Andrea Ranzi, Chiara Badaloni, Giovanni Viegi, Stefania La Grutta
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Abstract

The primary goal of asthma management is to achieve and maintain asthma control, which can be influenced by environmental factors. This longitudinal study aimed to construct a comprehensive environmental indicator to predict asthma control in children with asthma in Palermo, Italy. The study included 179 asthmatic children aged 5–16 years. The Normalized Difference Vegetation Index (NDVI) was used to measure green cover, and the Coordination of Information on the Environment (CORINE) framework was used to assess land use based on each home address. A land use regression (LUR) model centered on the home address estimated NO2 exposure for each child using GIS. An environmental indicator, including environmental and personal exposure, was formulated using an additive value model approach. A logistic regression mixed model assessed the association between the environmental indicator and uncontrolled asthma. A probability map of uncontrolled asthma was constructed. In conclusion, a comprehensive environmental indicator proved effective in identifying areas at higher and lower risk of uncontrolled asthma.

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综合环境暴露指标与哮喘儿童的呼吸健康:一项案例研究
哮喘管理的首要目标是实现并保持哮喘控制,而环境因素会对哮喘控制产生影响。这项纵向研究旨在构建一个综合环境指标,以预测意大利巴勒莫哮喘儿童的哮喘控制情况。研究对象包括 179 名 5-16 岁的哮喘儿童。归一化差异植被指数(NDVI)用于测量绿化覆盖率,环境信息协调(CORINE)框架用于根据每个家庭地址评估土地使用情况。以家庭住址为中心的土地利用回归(LUR)模型利用地理信息系统估算了每个儿童的二氧化氮暴露量。使用加值模型方法制定了一个环境指标,包括环境和个人暴露量。逻辑回归混合模型评估了环境指标与不受控制的哮喘之间的关系。绘制了哮喘失控的概率图。总之,综合环境指标证明可以有效识别哮喘失控风险较高和较低的地区。
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来源期刊
Environmental and Ecological Statistics
Environmental and Ecological Statistics 环境科学-环境科学
CiteScore
5.90
自引率
2.60%
发文量
27
审稿时长
>36 weeks
期刊介绍: Environmental and Ecological Statistics publishes papers on practical applications of statistics and related quantitative methods to environmental science addressing contemporary issues. Emphasis is on applied mathematical statistics, statistical methodology, and data interpretation and improvement for future use, with a view to advance statistics for environment, ecology and environmental health, and to advance environmental theory and practice using valid statistics. Besides clarity of exposition, a single most important criterion for publication is the appropriateness of the statistical method to the particular environmental problem. The Journal covers all aspects of the collection, analysis, presentation and interpretation of environmental data for research, policy and regulation. The Journal is cross-disciplinary within the context of contemporary environmental issues and the associated statistical tools, concepts and methods. The Journal broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas. Special features include invited discussion papers; research communications; technical notes and consultation corner; mini-reviews; letters to the Editor; news, views and announcements; hardware and software reviews; data management etc.
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