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Association between respiratory hospital admissions and air quality in Portugal: A count time series approach
- Source :
- PLoS ONE, Vol 16, Iss 7, p e0253455 (2021), PLoS ONE
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.
- Subjects :
- Atmospheric Science
Respiratory Tract Diseases
Air pollution
Social Sciences
010501 environmental sciences
medicine.disease_cause
01 natural sciences
Geographical locations
Urban Environments
0302 clinical medicine
Statistics
Medicine and Health Sciences
030212 general & internal medicine
Geographic Areas
media_common
Air Pollutants
Multidisciplinary
Geography
Applied Mathematics
Simulation and Modeling
Pollution
Terrestrial Environments
Hospitals
Europe
Hospitalization
Chemistry
Physical Sciences
Medicine
Seasons
Algorithms
Count data
Research Article
Urban Areas
Heteroscedasticity
Science
Geometry
Human Geography
Research and Analysis Methods
Air Quality
Urban Geography
03 medical and health sciences
Clustering Algorithms
Air Pollution
Covariate
medicine
media_common.cataloged_instance
Environmental Chemistry
Humans
European Union
European union
Air quality index
0105 earth and related environmental sciences
Portugal
Time series approach
Ecology and Environmental Sciences
Metropolitan area
Health Care
Radii
Health Care Facilities
Atmospheric Chemistry
Earth Sciences
Particulate Matter
People and places
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....303ae38de9807c137dad36c6c643e192