Literature DB >> 25457593

Spatial prevalence and associations among respiratory diseases in Maine.

Christopher Farah1, H Dean Hosgood2, Janet M Hock3.   

Abstract

Chronic respiratory diseases rank among the leading global disease burdens. Maine's respiratory disease prevalence exceeds the US average, despite limited urbanization/industrialization. To provide insight into potential etiologic factors among this unique, rural population, we analyzed the spatial distributions of, and potential associations among asthma, COPD, pneumonia, and URI adult outpatient data (n=47,099) from all outpatient transactions (n=5,052,900) in 2009 for Maine hospitals and affiliate clinics, using spatial scan statistic, geographic weighted regression (GWR), and a Delaunay graph algorithm. Non-random high prevalence regions were identified, the majority of which (84% of the population underlying all regions) exhibited clusters for all four respiratory diseases. GWR provided further evidence of spatial correlation (R(2)=0.991) between the communicable and noncommunicable diseases under investigation, suggesting spatial interdependence in risk. Sensitivity analyses of known respiratory disease risks did not fully explain our results. Prospective epidemiology studies are needed to clarify all contributors to risk.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Environmental health; Health disparities; Respiratory disease; Spatial epidemiology; Spatial statistics

Mesh:

Year:  2014        PMID: 25457593     DOI: 10.1016/j.sste.2014.07.004

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN: 1877-5845


  4 in total

1.  Practical utility of general practice data capture and spatial analysis for understanding COPD and asthma.

Authors:  T Niyonsenga; N T Coffee; P Del Fante; S B Høj; M Daniel
Journal:  BMC Health Serv Res       Date:  2018-11-26       Impact factor: 2.655

2.  Brief adult respiratory system health status scale-community version (BARSHSS-CV): developing and evaluating the reliability and validity.

Authors:  Hongzhe Dou; Yuejia Zhao; Yanhong Chen; Qingchun Zhao; Bo Xiao; Yan Wang; Yonghe Zhang; Zhiguo Chen; Jie Guo; Lingwei Tao
Journal:  BMC Health Serv Res       Date:  2018-09-03       Impact factor: 2.655

3.  Trends and area variations in Potentially Preventable Admissions for COPD in Spain (2002-2013): a significant decline and convergence between areas.

Authors:  Julián Librero; Berta Ibañez-Beroiz; Salvador Peiró; M Ridao-López; Clara L Rodríguez-Bernal; Francisco J Gómez-Romero; Enrique Bernal-Delgado
Journal:  BMC Health Serv Res       Date:  2016-08-09       Impact factor: 2.655

4.  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

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.