title: Fine particulate matter components and emergency department visits among a privately insured population in Greater Houston.
abstract: Although adverse health effects of PM2.5 (particulate matter with aerodynamic diameter less than 2.5μm) mass have been extensively studied, it remains unclear regarding which PM2.5 components are most harmful. No studies have reported the associations between PM2.5 components and adverse health effects among a privately insured population. In our study, we estimated the short-term associations between exposure to PM2.5 components and emergency department (ED) visits for all-cause and cause-specific diseases in Greater Houston, Texas, during 2008-2013 using ED visit data extracted from a private insurance company (Blue Cross Blue Shield Texas [BCBSTX]). A total of 526,453 ED visits were included in our assessment, with an average of 236 (±63) visits per day. We selected 20 PM2.5 components from the U.S. Environmental Protection Agency's Chemical Speciation Network site located in Houston, and then applied Poisson regression models to assess the previously mentioned associations. Interquartile range increases in bromine (0.003μg/m(3)), potassium (0.048μg/m(3)), sodium ion (0.306μg/m(3)), and sulfate (1.648μg/m(3)) were statistically significantly associated with the increased risks in total ED of 0.71% (95% confidence interval (CI): 0.06, 1.37%), 0.71% (95% CI: 0.21, 1.22%), 1.28% (95% CI: 0.34, 2.24%), and 1.22% (95% CI: 0.23, 2.23%), respectively. Seasonal analysis suggested strongest associations occurred during the warm season. Our findings suggest that a privately insured population, presumably healthier than the general population, may be still at risk of adverse health effects due to exposure to ambient PM2.5 components.
authors.affiliation: Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA.
authors.forename: Suyang
authors.initials: S
authors.lastname: Liu
authors.affiliation: Department of Management, Policy and Community, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA.
authors.forename: Cecilia M
authors.initials: CM
authors.lastname: Ganduglia
authors.affiliation: Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, TX, USA 77030.
authors.forename: Xiao
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA.
authors.forename: George L
authors.initials: GL
authors.lastname: Delclos
authors.affiliation: Department of Management, Policy and Community, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA; Department of Health Services Administration, School of Public Health, University of Maryland, College Park, MD 20742, USA.
authors.forename: Luisa
authors.initials: L
authors.lastname: Franzini
authors.affiliation: Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA; Southwest Center for Occupational and Environmental Health, School of Public Health, University of Texas Health Science Center at Houston, TX 77030, USA. Electronic address: kai.zhang@uth.tmc.edu.
authors.forename: Kai
authors.initials: K
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000368:Aged; D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis; D002947:Cities; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D004781:Environmental Exposure; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D012306:Risk; D012621:Seasons; D013781:Texas; D055815:Young Adult
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Components; Emergency department visits; Fine particulate matter; Poisson regression; Species; Time series