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Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population
Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479348/ https://www.ncbi.nlm.nih.gov/pubmed/30934853 http://dx.doi.org/10.3390/ijerph16071133 |
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author | Humphrey, Jamie L. Lindstrom, Megan Barton, Kelsey E. Shrestha, Prateek Man Carlton, Elizabeth J. Adgate, John L. Miller, Shelly L. Root, Elisabeth Dowling |
author_facet | Humphrey, Jamie L. Lindstrom, Megan Barton, Kelsey E. Shrestha, Prateek Man Carlton, Elizabeth J. Adgate, John L. Miller, Shelly L. Root, Elisabeth Dowling |
author_sort | Humphrey, Jamie L. |
collection | PubMed |
description | Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and environmental hazards, and to examine whether those subtypes are associated with lung function. The study included 182 low-income participants who were enrolled in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study during the years 2015–2017. Distinct neighborhood typologies were identified based on analyses of 632 census tracts in the Denver-Metro and Front Range area of Colorado; neighborhood characteristics used to identify typologies included green space, traffic-related air pollution, violent and property crime, racial/ethnic composition, and socioeconomic status (SES). Generalized estimating equations were used to examine the association between neighborhood typology and lung function. We found four distinct neighborhood typologies and provide evidence that these social and environmental aspects of neighborhoods cluster along lines of advantage/disadvantage. We provide suggestive evidence of a double jeopardy situation where low-income populations living in disadvantaged neighborhoods may have decreased lung function. Using LPA with social and environmental characteristics may help to identify meaningful neighborhood subtypes and inform research on the mechanisms by which neighborhoods influence health. |
format | Online Article Text |
id | pubmed-6479348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64793482019-04-29 Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population Humphrey, Jamie L. Lindstrom, Megan Barton, Kelsey E. Shrestha, Prateek Man Carlton, Elizabeth J. Adgate, John L. Miller, Shelly L. Root, Elisabeth Dowling Int J Environ Res Public Health Article Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and environmental hazards, and to examine whether those subtypes are associated with lung function. The study included 182 low-income participants who were enrolled in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study during the years 2015–2017. Distinct neighborhood typologies were identified based on analyses of 632 census tracts in the Denver-Metro and Front Range area of Colorado; neighborhood characteristics used to identify typologies included green space, traffic-related air pollution, violent and property crime, racial/ethnic composition, and socioeconomic status (SES). Generalized estimating equations were used to examine the association between neighborhood typology and lung function. We found four distinct neighborhood typologies and provide evidence that these social and environmental aspects of neighborhoods cluster along lines of advantage/disadvantage. We provide suggestive evidence of a double jeopardy situation where low-income populations living in disadvantaged neighborhoods may have decreased lung function. Using LPA with social and environmental characteristics may help to identify meaningful neighborhood subtypes and inform research on the mechanisms by which neighborhoods influence health. MDPI 2019-03-29 2019-04 /pmc/articles/PMC6479348/ /pubmed/30934853 http://dx.doi.org/10.3390/ijerph16071133 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Humphrey, Jamie L. Lindstrom, Megan Barton, Kelsey E. Shrestha, Prateek Man Carlton, Elizabeth J. Adgate, John L. Miller, Shelly L. Root, Elisabeth Dowling Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title | Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title_full | Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title_fullStr | Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title_full_unstemmed | Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title_short | Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population |
title_sort | social and environmental neighborhood typologies and lung function in a low-income, urban population |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479348/ https://www.ncbi.nlm.nih.gov/pubmed/30934853 http://dx.doi.org/10.3390/ijerph16071133 |
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