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Temporal analysis of determinants for respiratory emergency department visits in a large German hospital
INTRODUCTION: Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241969/ https://www.ncbi.nlm.nih.gov/pubmed/30487970 http://dx.doi.org/10.1136/bmjresp-2018-000338 |
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author | Krefis, Anne Caroline Fischereit, Jana Hoffmann, Peter Pinnschmidt, Hans Sorbe, Christina Augustin, Matthias Augustin, Jobst |
author_facet | Krefis, Anne Caroline Fischereit, Jana Hoffmann, Peter Pinnschmidt, Hans Sorbe, Christina Augustin, Matthias Augustin, Jobst |
author_sort | Krefis, Anne Caroline |
collection | PubMed |
description | INTRODUCTION: Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day of the week, season and year (study period from 2013 to 2015). METHODS: Highly correlated environmental data entered a categorical principal components analysis (CATPCA). We analysed cross-correlation functions between the time series of the respective daily environmental factors and daily ED visits. Time lags with peak correlations of environmental variables obtained by the CATPCA on ED visits together with day of the week, year, running day (linear, quadratic and cubic), season and interaction terms entered the univariate analysis of variance (UNIANOVA) model. RESULTS: The analyses demonstrated main effects on ED visits for the day of the week with highest admission rates on Mondays (B=10.69; ƞ(2)=0.333; p<0.001). A significant time trend could be observed showing increasing numbers of ED visits per each year (p<0.001). The variable ‘running day’ (linear, quadratic and cubic) indicated a significant non-linear effect over time. The variable season showed significant results with winter, spring and summer recording fewer ED visits compared with the reference season autumn. Environmental variables showed no direct associations with respiratory ED visits. DISCUSSION: ED visits were significantly associated with temporal variables. Our data did not show direct associations between environmental variables and ED visits. In times of rapid urbanisation, increases in respiratory diseases, temperature and air pollution, our analyses can help focus future studies and enhance strategies to reduce increasing numbers of respiratory diseases and ED visits. Because the potential costs of medical care in hospitals can be high compared with physicians, public health recommendations for reducing the increasing ED visits should be promoted and evaluated. |
format | Online Article Text |
id | pubmed-6241969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62419692018-11-28 Temporal analysis of determinants for respiratory emergency department visits in a large German hospital Krefis, Anne Caroline Fischereit, Jana Hoffmann, Peter Pinnschmidt, Hans Sorbe, Christina Augustin, Matthias Augustin, Jobst BMJ Open Respir Res Respiratory Epidemiology INTRODUCTION: Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day of the week, season and year (study period from 2013 to 2015). METHODS: Highly correlated environmental data entered a categorical principal components analysis (CATPCA). We analysed cross-correlation functions between the time series of the respective daily environmental factors and daily ED visits. Time lags with peak correlations of environmental variables obtained by the CATPCA on ED visits together with day of the week, year, running day (linear, quadratic and cubic), season and interaction terms entered the univariate analysis of variance (UNIANOVA) model. RESULTS: The analyses demonstrated main effects on ED visits for the day of the week with highest admission rates on Mondays (B=10.69; ƞ(2)=0.333; p<0.001). A significant time trend could be observed showing increasing numbers of ED visits per each year (p<0.001). The variable ‘running day’ (linear, quadratic and cubic) indicated a significant non-linear effect over time. The variable season showed significant results with winter, spring and summer recording fewer ED visits compared with the reference season autumn. Environmental variables showed no direct associations with respiratory ED visits. DISCUSSION: ED visits were significantly associated with temporal variables. Our data did not show direct associations between environmental variables and ED visits. In times of rapid urbanisation, increases in respiratory diseases, temperature and air pollution, our analyses can help focus future studies and enhance strategies to reduce increasing numbers of respiratory diseases and ED visits. Because the potential costs of medical care in hospitals can be high compared with physicians, public health recommendations for reducing the increasing ED visits should be promoted and evaluated. BMJ Publishing Group 2018-11-01 /pmc/articles/PMC6241969/ /pubmed/30487970 http://dx.doi.org/10.1136/bmjresp-2018-000338 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Respiratory Epidemiology Krefis, Anne Caroline Fischereit, Jana Hoffmann, Peter Pinnschmidt, Hans Sorbe, Christina Augustin, Matthias Augustin, Jobst Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title | Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title_full | Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title_fullStr | Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title_full_unstemmed | Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title_short | Temporal analysis of determinants for respiratory emergency department visits in a large German hospital |
title_sort | temporal analysis of determinants for respiratory emergency department visits in a large german hospital |
topic | Respiratory Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241969/ https://www.ncbi.nlm.nih.gov/pubmed/30487970 http://dx.doi.org/10.1136/bmjresp-2018-000338 |
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