Spatial vulnerability of fine particulate matter relative to the prevalence of diabetes in the United States
Journal
Science of the Total Environment
Journal Volume
508
Pages
136-144
Date Issued
2015
Author(s)
Abstract
Recent research supports a link between diabetes and fine particulate matter (?2.5μg in diameter; PM2.5) in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004 to 2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM2.5 concentrations. When PM2.5 concentrations increased 1μg/m3, the increase in the relative risk percentage for diabetes ranged from -5.47% (95% credible interval=-6.14, -4.77) to 2.34% (95% CI=2.01, 2.70), where 1323 of 3109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM2.5, and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM2.5 pollution. ? 2014 Elsevier B.V.
Subjects
Diabetes prevalence; PM2.5; Spatial vulnerability; Spatiotemporal model
SDGs
Other Subjects
Environmental Protection Agency; 95% credible intervals; Enhanced surveillance; Fine particulate matter; PM2.5; Socio-economic status; Spatial vulnerability; Spatio-temporal models; Surveillance systems; Particles (particulate matter); atmospheric pollution; Bayesian analysis; diabetes; disease prevalence; particulate matter; socioeconomic status; spatiotemporal analysis; vulnerability; Article; Bayes theorem; concentration (parameters); controlled study; diabetes mellitus; female; geographic and geological phenomena; geographic disparity; geographic distribution; human; long term exposure; male; particulate matter; physical inactivity; prevalence; risk assessment; risk factor; social status; United States; vulnerable population; air pollutant; air pollution; analysis; diabetes mellitus; environmental exposure; particulate matter; statistics and numerical data; United States; air pollutant; particulate matter; Air Pollutants; Air Pollution; Diabetes Mellitus; Environmental Exposure; Humans; Particulate Matter; United States
Type
journal article