| Title: |
Évaluation des impacts de trois polluants atmosphériques sur la survenue d’une exacerbation de BPCO à Nice |
| Authors: |
Maignant, Gilles; Vanin, Laurence; Awuklu, Yvon, K; Staccini, Pascal |
| Contributors: |
Risques, Epidémiologie, Territoire, INformations, Education et Santé (RETINES); Université Côte d'Azur (UniCA) |
| Source: |
EISSN: 2492-3672 ; Revue francophone sur la santé et les territoires ; https://hal.science/hal-04860155 ; Revue francophone sur la santé et les territoires, 2023, ⟨10.4000/rfst.1834⟩ |
| Publisher Information: |
CCSD; Université d'Angers |
| Publication Year: |
2023 |
| Collection: |
HAL Université Côte d'Azur |
| Subject Terms: |
[SHS.GEO]Humanities and Social Sciences/Geography; [MATH]Mathematics [math] |
| Description: |
International audience ; The environment-health issue is not new. Many authors (Beelen et al., 2014; DGS 2020; Zanobetti et al., 2008) have looked at the effect —in the long term— on the occurrence of pathologies. Very often, these studies work on a national geographical scale. We decided to look at the links between three atmospheric pollutants, namely nitrogen dioxide, ozone, and particulate matter (PM10), on the occurrence of an exacerbation of chronic obstructive pulmonary disease (COPD) in the city of Nice, over the period from January 2012 to December 2018, thus underlining an accentuation of the fragility of humans evolving in these territories. To do this, we relied on the one hand on PMSI data and on the other hand on data collected by the different air quality monitoring stations, from the AtmoSud air quality monitoring network. To study this statistical relationship and its consequences, we used a Poisson regression model based on a generalized linear model. This model was essentially fed by two indicators that we constructed. The regression model thus allows us to estimate the coefficient associated with our explanatory variable and to calculate a relative risk. Thus, we were able to show a significant link between two of our pollutants and our health event, namely the occurrence of a COPD exacerbation. From two databases, we built our statistical model to estimate a possible relationship between exposure to an air pollutant and a COPD exacerbation. The model chosen was a Generalized Linear Model (GLM) of the counting type (Poisson regression), taking into account overdispersion, i.e., when the variance of the observed data is greater than the mean of the variable.) Our unit of observation was the day. With this in mind, we constructed two indicators: - A health indicator: this is our variable to be explained. It corresponds to the number of daily admissions for a COPD exacerbation. The data for its construction were extracted from the PMSI files according to the main cause of hospitalization, ... |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.4000/rfst.1834 |
| Availability: |
https://hal.science/hal-04860155; https://hal.science/hal-04860155v1/document; https://hal.science/hal-04860155v1/file/rfst-1834-3.pdf; https://doi.org/10.4000/rfst.1834 |
| Rights: |
https://creativecommons.org/licenses/by-nc-sa/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.39E8A1A |
| Database: |
BASE |