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Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces

BACKGROUND: Exposure to particulate matter has been associated with increased risk of cardiovascular and respiratory diseases. We evaluated the ecological correlation between standardized hospital discharges with diabetes in Italian provinces and fine particulate matter (PM2.5) adjusting for common...

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Autores principales: Solimini, Angelo G., D’Addario, Maddalena, Villari, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514955/
https://www.ncbi.nlm.nih.gov/pubmed/26208978
http://dx.doi.org/10.1186/s12889-015-2018-5
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author Solimini, Angelo G.
D’Addario, Maddalena
Villari, Paolo
author_facet Solimini, Angelo G.
D’Addario, Maddalena
Villari, Paolo
author_sort Solimini, Angelo G.
collection PubMed
description BACKGROUND: Exposure to particulate matter has been associated with increased risk of cardiovascular and respiratory diseases. We evaluated the ecological correlation between standardized hospital discharges with diabetes in Italian provinces and fine particulate matter (PM2.5) adjusting for common risk factors, socioeconomic factors and differences in hospitalization appropriateness. METHODS: We used cross sectional data aggregated at the province level and available from official institutional databases for years 2008–2010. Covariates included prevalence of adult overweight, obese, smokers, physically inactive, education and income (as average gross domestic product per person, GDP). We reduced the number of covariates to a smaller number of factors for the subsequent statistical model by extracting meaningful components using principal component analysis (PCA). Log-linear multiple regression analysis was used to model diabetes hospital discharges with PCA components and PM2.5 levels and hospitalization appropriateness for men and women. RESULTS: The first PCA components for both men and women were characterized by larger loadings of risk factors (obesity, overweight, physical inactivity, cigarette smoking) and lower socioeconomic factors (educational level and mean GDP). Diabetes hospitalization increases with the first PCA component and decreases with the index of hospitalization appropriateness. In fully adjusted models, diabetes hospitalizations increase with increasing annual PM2.5 concentrations, with a rise of 3.5 % (1.3 %–5.6 %) for men and of 4.0 % (1.5 %-6.4 %) for women per unit of PM2.5 increase. CONCLUSIONS: We found a significant ecological relationship between sex and age standardised hospital discharge with diabetes as principle diagnosis and mean annual PM2.5 concentrations in Italian provinces, once that covariates have been accounted for. The relationship was robust to different means of estimating PM2.5 exposure. A large portion of the variance of diabetes hospitalizations was linked to differences of hospital care appropriateness between Italian regions and this variable should routinely be included in ecological analyses of hospitalizations.
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spelling pubmed-45149552015-07-26 Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces Solimini, Angelo G. D’Addario, Maddalena Villari, Paolo BMC Public Health Research Article BACKGROUND: Exposure to particulate matter has been associated with increased risk of cardiovascular and respiratory diseases. We evaluated the ecological correlation between standardized hospital discharges with diabetes in Italian provinces and fine particulate matter (PM2.5) adjusting for common risk factors, socioeconomic factors and differences in hospitalization appropriateness. METHODS: We used cross sectional data aggregated at the province level and available from official institutional databases for years 2008–2010. Covariates included prevalence of adult overweight, obese, smokers, physically inactive, education and income (as average gross domestic product per person, GDP). We reduced the number of covariates to a smaller number of factors for the subsequent statistical model by extracting meaningful components using principal component analysis (PCA). Log-linear multiple regression analysis was used to model diabetes hospital discharges with PCA components and PM2.5 levels and hospitalization appropriateness for men and women. RESULTS: The first PCA components for both men and women were characterized by larger loadings of risk factors (obesity, overweight, physical inactivity, cigarette smoking) and lower socioeconomic factors (educational level and mean GDP). Diabetes hospitalization increases with the first PCA component and decreases with the index of hospitalization appropriateness. In fully adjusted models, diabetes hospitalizations increase with increasing annual PM2.5 concentrations, with a rise of 3.5 % (1.3 %–5.6 %) for men and of 4.0 % (1.5 %-6.4 %) for women per unit of PM2.5 increase. CONCLUSIONS: We found a significant ecological relationship between sex and age standardised hospital discharge with diabetes as principle diagnosis and mean annual PM2.5 concentrations in Italian provinces, once that covariates have been accounted for. The relationship was robust to different means of estimating PM2.5 exposure. A large portion of the variance of diabetes hospitalizations was linked to differences of hospital care appropriateness between Italian regions and this variable should routinely be included in ecological analyses of hospitalizations. BioMed Central 2015-07-25 /pmc/articles/PMC4514955/ /pubmed/26208978 http://dx.doi.org/10.1186/s12889-015-2018-5 Text en © Solimini et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Solimini, Angelo G.
D’Addario, Maddalena
Villari, Paolo
Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title_full Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title_fullStr Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title_full_unstemmed Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title_short Ecological correlation between diabetes hospitalizations and fine particulate matter in Italian provinces
title_sort ecological correlation between diabetes hospitalizations and fine particulate matter in italian provinces
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514955/
https://www.ncbi.nlm.nih.gov/pubmed/26208978
http://dx.doi.org/10.1186/s12889-015-2018-5
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