PMID- 31634664
OWN - NLM
STAT- MEDLINE
DCOM- 20200211
LR  - 20200211
IS  - 1873-6750 (Electronic)
IS  - 0160-4120 (Linking)
VI  - 133
IP  - Pt A
DP  - 2019 Dec
TI  - Source apportionment of primary and secondary PM(2.5): Associations with 
      pediatric respiratory disease emergency department visits in the U.S. State of 
      Georgia.
PG  - 105167
LID - S0160-4120(19)31893-8 [pii]
LID - 10.1016/j.envint.2019.105167 [doi]
AB  - We developed a hybrid chemical transport model and receptor model (CTM-RM) to 
      conduct source apportionment of both primary and secondary PM(2.5) (particulate 
      matter </=2.5 mum in diameter) at 36 km resolution throughout the U.S. State of 
      Georgia for the years 2005 and 2007. This novel source apportionment model 
      enabled us to estimate and compare associations of short-term changes in 
      12 PM(2.5) source concentrations (agriculture, biogenic, coal, dust, fuel oil, 
      metals, natural gas, non-road mobile diesel, non-road mobile gasoline, on-road 
      mobile diesel, on-road mobile gasoline, and all other sources) with emergency 
      department (ED) visits for pediatric respiratory diseases. ED visits for asthma 
      (N = 49,651), pneumonia (N = 25,558), and acute upper respiratory infections 
      (acute URI, N = 235,343) among patients aged </=18 years were obtained from patient 
      claims records. Using a case-crossover study, we estimated odds ratios per 
      interquartile range (IQR) increase for 3-day moving average PM(2.5) source 
      concentrations using conditional logistic regression, matching on day-of-week, 
      month, and year, and adjusting for average temperature, humidity, and holidays. 
      We fit both single-source and multi-source models. We observed positive 
      associations between several PM(2.5) sources and ED visits for asthma, pneumonia, 
      and acute URI. For example, for asthma, per IQR increase in the source 
      contribution in the single-source model, odds ratios were 1.022 (95% CI: 1.013, 
      1.031) for dust; 1.050 (95% CI: 1.036, 1.063) for metals, and 1.091 (95% CI: 
      1.064, 1.119) for natural gas. These sources comprised 5.7%, 2.2%, and 6.3% of 
      total PM(2.5) mass, respectively. PM(2.5) from metals and natural gas were 
      positively associated with all three respiratory outcomes. In addition, non-road 
      mobile diesel was positively associated with pneumonia and acute URI.
CI  - Copyright (c) 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.
FAU - Huang, Mengjiao
AU  - Huang M
AD  - School of Community Health Sciences, University of Nevada, Reno, NV, USA. 
      Electronic address: mengjiaoh@nevada.unr.edu.
FAU - Ivey, Cesunica
AU  - Ivey C
AD  - Department of Chemical and Environmental Engineering, University of California, 
      Riverside, CA, USA. Electronic address: cesunica@ucr.edu.
FAU - Hu, Yongtao
AU  - Hu Y
AD  - School of Civil and Environmental Engineering, Georgia Institute of Technology, 
      Atlanta, GA, USA. Electronic address: yh29@mail.gatech.edu.
FAU - Holmes, Heather A
AU  - Holmes HA
AD  - Atmospheric Sciences Program, Department of Physics, University of Nevada, Reno, 
      NV, USA. Electronic address: hholmes@unr.edu.
FAU - Strickland, Matthew J
AU  - Strickland MJ
AD  - School of Community Health Sciences, University of Nevada, Reno, NV, USA. 
      Electronic address: mstrickland@unr.edu.
LA  - eng
PT  - Journal Article
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20191018
PL  - Netherlands
TA  - Environ Int
JT  - Environment international
JID - 7807270
RN  - 0 (Air Pollutants)
RN  - 0 (Coal)
RN  - 0 (Dust)
RN  - 0 (Gasoline)
RN  - 0 (Particulate Matter)
SB  - IM
MH  - Adolescent
MH  - Air Pollutants/analysis/*toxicity
MH  - Child
MH  - Coal
MH  - Cross-Over Studies
MH  - Dust
MH  - Emergency Service, Hospital/*statistics & numerical data
MH  - Female
MH  - Gasoline
MH  - Georgia
MH  - Humans
MH  - Logistic Models
MH  - Male
MH  - Odds Ratio
MH  - Particulate Matter/analysis/*toxicity
MH  - Respiration Disorders/*etiology
OTO - NOTNLM
OT  - Epidemiologic model
OT  - Hybrid chemical transport-receptor model
OT  - PM(2.5)
OT  - Pediatric respiratory ED visits
OT  - Source apportionment
EDAT- 2019/10/22 06:00
MHDA- 2020/02/12 06:00
CRDT- 2019/10/22 06:00
PHST- 2019/06/07 00:00 [received]
PHST- 2019/09/03 00:00 [revised]
PHST- 2019/09/06 00:00 [accepted]
PHST- 2019/10/22 06:00 [pubmed]
PHST- 2020/02/12 06:00 [medline]
PHST- 2019/10/22 06:00 [entrez]
AID - S0160-4120(19)31893-8 [pii]
AID - 10.1016/j.envint.2019.105167 [doi]
PST - ppublish
SO  - Environ Int. 2019 Dec;133(Pt A):105167. doi: 10.1016/j.envint.2019.105167. Epub 
      2019 Oct 18.