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Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City

The percentage of the world's population living in urban areas is projected to increase in the next decades. Big cities are heterogeneous environments in which socioeconomic and environmental differences among the neighborhoods are often very pronounced. Each individual, during his/her life, is...

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Autores principales: Pala, Daniele, Pagán, José, Parimbelli, Enea, Rocca, Marica Teresa, Bellazzi, Riccardo, Casella, Vittorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499162/
https://www.ncbi.nlm.nih.gov/pubmed/31106206
http://dx.doi.org/10.3389/fmed.2019.00084
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author Pala, Daniele
Pagán, José
Parimbelli, Enea
Rocca, Marica Teresa
Bellazzi, Riccardo
Casella, Vittorio
author_facet Pala, Daniele
Pagán, José
Parimbelli, Enea
Rocca, Marica Teresa
Bellazzi, Riccardo
Casella, Vittorio
author_sort Pala, Daniele
collection PubMed
description The percentage of the world's population living in urban areas is projected to increase in the next decades. Big cities are heterogeneous environments in which socioeconomic and environmental differences among the neighborhoods are often very pronounced. Each individual, during his/her life, is constantly subject to a mix of exposures that have an effect on their phenotype but are frequently difficult to identify, especially in an urban environment. Studying how the combination of environmental and socioeconomic factors which the population is exposed to influences pathological outcomes can help transforming public health from a reactive to a predictive system. Thanks to the application of state-of-the-art spatially enabled methods, patients can be stratified according to their characteristics and the geographical context they live in, optimizing healthcare processes and the reducing its costs. Some public health studies focusing specifically on urban areas have been conducted, but they usually consider a coarse spatial subdivision, as a consequence of scarce availability of well-integrated data regarding health and environmental exposure at a sufficient level of granularity to enable meaningful statistical analyses. In this paper, we present an application of highly fine-grained spatial resolution methods to New York City data. We investigated the link between asthma hospitalizations and a combination of air pollution and other environmental and socioeconomic factors. We first performed an explorative analysis using spatial clustering methods that shows that asthma is related to numerous factors whose level of influence varies considerably among neighborhoods. We then performed a Geographically Weighted Regression with different covariates and determined which environmental and socioeconomic factors can predict hospitalizations and how they vary throughout the city. These methods showed to be promising both for visualization and analysis of demographic and epidemiological urban dynamics, that can be used to organize targeted intervention and treatment policies to address the single citizens considering the factors he/she is exposed to. We found a link between asthma and several factors such as PM2.5, age, health insurance coverage, race, poverty, obesity, industrial areas, and recycling. This study has been conducted within the PULSE project, funded by the European Commission, briefly presented in this paper.
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spelling pubmed-64991622019-05-17 Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City Pala, Daniele Pagán, José Parimbelli, Enea Rocca, Marica Teresa Bellazzi, Riccardo Casella, Vittorio Front Med (Lausanne) Medicine The percentage of the world's population living in urban areas is projected to increase in the next decades. Big cities are heterogeneous environments in which socioeconomic and environmental differences among the neighborhoods are often very pronounced. Each individual, during his/her life, is constantly subject to a mix of exposures that have an effect on their phenotype but are frequently difficult to identify, especially in an urban environment. Studying how the combination of environmental and socioeconomic factors which the population is exposed to influences pathological outcomes can help transforming public health from a reactive to a predictive system. Thanks to the application of state-of-the-art spatially enabled methods, patients can be stratified according to their characteristics and the geographical context they live in, optimizing healthcare processes and the reducing its costs. Some public health studies focusing specifically on urban areas have been conducted, but they usually consider a coarse spatial subdivision, as a consequence of scarce availability of well-integrated data regarding health and environmental exposure at a sufficient level of granularity to enable meaningful statistical analyses. In this paper, we present an application of highly fine-grained spatial resolution methods to New York City data. We investigated the link between asthma hospitalizations and a combination of air pollution and other environmental and socioeconomic factors. We first performed an explorative analysis using spatial clustering methods that shows that asthma is related to numerous factors whose level of influence varies considerably among neighborhoods. We then performed a Geographically Weighted Regression with different covariates and determined which environmental and socioeconomic factors can predict hospitalizations and how they vary throughout the city. These methods showed to be promising both for visualization and analysis of demographic and epidemiological urban dynamics, that can be used to organize targeted intervention and treatment policies to address the single citizens considering the factors he/she is exposed to. We found a link between asthma and several factors such as PM2.5, age, health insurance coverage, race, poverty, obesity, industrial areas, and recycling. This study has been conducted within the PULSE project, funded by the European Commission, briefly presented in this paper. Frontiers Media S.A. 2019-04-24 /pmc/articles/PMC6499162/ /pubmed/31106206 http://dx.doi.org/10.3389/fmed.2019.00084 Text en Copyright © 2019 Pala, Pagán, Parimbelli, Rocca, Bellazzi and Casella. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Pala, Daniele
Pagán, José
Parimbelli, Enea
Rocca, Marica Teresa
Bellazzi, Riccardo
Casella, Vittorio
Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title_full Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title_fullStr Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title_full_unstemmed Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title_short Spatial Enablement to Support Environmental, Demographic, Socioeconomics, and Health Data Integration and Analysis for Big Cities: A Case Study With Asthma Hospitalizations in New York City
title_sort spatial enablement to support environmental, demographic, socioeconomics, and health data integration and analysis for big cities: a case study with asthma hospitalizations in new york city
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499162/
https://www.ncbi.nlm.nih.gov/pubmed/31106206
http://dx.doi.org/10.3389/fmed.2019.00084
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