Literature DB >> 25545928

Geographic disparities of asthma prevalence in south-western United States of America.

Lung-Chang Chien1, Hasanat Alamgir2.   

Abstract

Asthma is one of the most prevalent chronic diseases in the United States of America (USA), and many of its risk factors have so far been investigated and identified; however, evidence is limited on how spatial disparities impact the disease. The purpose of this study was to provide scientific evidence on the location influence on asthma in the four states of southwestern USA (California, Arizona, New Mexico and Texas) which, together, include 360 counties. The Behavioral Risk Factor Surveillance System database for these four states covering the period of 2000 to 2011 was used in this analysis, and a Bayesian structured additive regression model was applied to analyse by a geographical information system. After adjusting for individual characteristics, socioeconomic status and health behaviour, this study found higher odds associated with asthma and a likely cluster around the Bay Area in California, while lower odds appeared in several counties around the larger cities of Texas, such as Dallas, Houston and San Antonio. The significance map shows 43 of 360 counties (11.9%) to be high-risk areas for asthma. The level of geographical disparities demonstrates that the county risk of asthma prevalence varies significantly and can be about 19.9% (95% confidence interval: 15.3-25.8) higher or lower than the overall asthma prevalence. We provide an efficient method to utilise and interpret the existing surveillance data on asthma. Visualisation by maps may help deliver future interventions on targeted areas and vulnerable populations to reduce geographical disparities in the burden of asthma.

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Mesh:

Year:  2014        PMID: 25545928     DOI: 10.4081/gh.2014.8

Source DB:  PubMed          Journal:  Geospat Health        ISSN: 1827-1987            Impact factor:   1.212


  3 in total

1.  Spatiotemporal patterns of childhood asthma hospitalization and utilization in Memphis Metropolitan Area from 2005 to 2015.

Authors:  Tonny J Oyana; Pradeep Podila; Jagila Minso Wesley; Slawo Lomnicki; Stephania Cormier
Journal:  J Asthma       Date:  2017-01-05       Impact factor: 2.515

2.  Prevalence and Occupational and Environmental Risk Factors of Self-Reported Asthma: Evidence from a Cross-Sectional Survey in Seven Chinese Cities.

Authors:  Qing-Ling Fu; Yue Du; Geng Xu; Hua Zhang; Lei Cheng; Yan-Jun Wang; Dong-Dong Zhu; Wei Lv; Shi-Xi Liu; Pei-Zhong Li; Jian-Bo Shi; Chun-Quan Ou
Journal:  Int J Environ Res Public Health       Date:  2016-11-04       Impact factor: 3.390

3.  A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma.

Authors:  Matthew Bozigar; Andrew Lawson; John Pearce; Kathryn King; Erik Svendsen
Journal:  Int J Health Geogr       Date:  2020-03-18       Impact factor: 3.918

  3 in total

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