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Associations of PM2.5 and Black Carbon with Hospital Emergency Room Visits during Heavy Haze Events

A Case Study in Beijing, China

Bibliographic Data

ID17801117
AuthorsFengchao Liang (0000-0003-2088-0722, Peking University), Lin Tian (0000-0003-1503-0918, Peking University), Linwei Tian (0000-0003-2240-8886, Peking University), Qun Guo (0000-0002-1472-7679, Peking University), Dane Westerdahl (City University of Hong Kong), Yang Liu (0000-0003-1220-7044, Emory University), Xiaobin Jin (0000-0003-1862-5837, Peking University), Guoxing Li (0000-0002-4384-7063, Peking University), Xiaochuan Pan (0000-0002-3074-9771, Peking University, corresponding author)
Year2017
Volume14
Issue7
Pages725-725
Publication date2017-07-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph14070725
PMID28678202
OpenAlexW2733809319
LanguageEN
Citations received3
References cited31

In January 2013, severe haze events over northeastern China sparked substantial health concerns. This study explores the associations of fine particulate matter less than 2.5 μm (PM 2.5 ) and black carbon (BC) with hospital emergency room visits (ERVs) during a haze season in Beijing. During that period, daily counts of ERVs for respiratory, cardiovascular and ocular diseases were obtained from a Level-3A hospital in Beijing from 1 December 2012 to 28 February 2013, and associations of which with PM 2.5 and BC were estimated by time-stratified case-crossover analysis in single- and two-pollutant models. We found a 27.5% (95% confidence interval (CI): 13.0, 43.9%) increase in respiratory ERV (lag02), a 19.4% (95% CI: 2.5, 39.0%) increase in cardiovascular ERV (lag0), and a 12.6% (95% CI: 0.0, 26.7%) increase in ocular ERV (lag0) along with an interquartile range (IQR) increase in the PM 2.5 . An IQR increase of BC was associated with 27.6% (95% CI: 9.6, 48.6%) (lag02), 18.8% (95% CI: 1.4, 39.2%) (lag0) and 11.8% (95% CI: -1.4, 26.8%) (lag0) increases for changes in these same health outcomes respectively. Estimated associations were consistent after adjusting SO2 or NO2 in two-pollutant models. This study provides evidence that improving air quality and reducing haze days would greatly benefit the population health

Beijing · China · Confidence interval · Environmental health · Geography · Haze · Interquartile range · Meteorology · Air Quality and Health Impacts · Climate Change and Health Impacts · COVID-19 impact on air quality · Demography · Environmental Science · Medicine · Internal Medicine

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Unique citing works3
Citations per year0,43
Citation span2019 - 2021 (3)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 3

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