TY - JOUR
T1 - Spatial prevalence and associations among respiratory diseases in Maine
AU - Farah, Christopher
AU - Hosgood, H. Dean
AU - Hock, Janet M.
N1 - Funding Information:
This research was funded by US Army Medical Research Command Grant W81XWH-07-02-0102 , PI: J.M. Hock. We thank Shelia Zahm, Sc.D., NCI; N. Anderson, PhD, Maine DEP; and M. Schwenn, MD, Maine Cancer Registry, with much appreciation for their contributions and critical review of the manuscripts. We express our appreciation to Ms. J. Mellett and Mr. D. Fournier at EMHS for facilitating our access to datasets archived by the Maine Hospitals Data Organization.
PY - 2014/10/1
Y1 - 2014/10/1
N2 - 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 (R2=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.
AB - 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 (R2=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.
KW - Environmental health
KW - Health disparities
KW - Respiratory disease
KW - Spatial epidemiology
KW - Spatial statistics
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U2 - 10.1016/j.sste.2014.07.004
DO - 10.1016/j.sste.2014.07.004
M3 - Article
C2 - 25457593
AN - SCOPUS:84907501174
VL - 11
SP - 11
EP - 22
JO - Spatial and Spatio-temporal Epidemiology
JF - Spatial and Spatio-temporal Epidemiology
SN - 1877-5845
ER -