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Estimation of the effects of heavy Asian dust on respiratory function by definition type

Overview of attention for article published in Genes and Environment, November 2017
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Title
Estimation of the effects of heavy Asian dust on respiratory function by definition type
Published in
Genes and Environment, November 2017
DOI 10.1186/s41021-017-0085-9
Pubmed ID
Authors

Jun Kurai, Masanari Watanabe, Hisashi Noma, Kyoko Iwata, Jumpei Taniguchi, Hiroyuki Sano, Yuji Tohda, Eiji Shimizu

Abstract

The adverse effects of Asian dust (AD) on health have been demonstrated in earlier studies, but there is no standardized definition for heavy-AD. This study aimed to examine which definition of heavy-AD has the most adverse effect on respiratory function. One-hundred-and-thirty-seven adults with asthma, and 384 school children self-measured their morning peak expiratory flow (PEF). The four definitions of heavy-AD are: (1) the definition provided by the Japan Meteorological Agency (JMA), (2) daily median AD particle level ≥ 0.07 km(-1), obtained through light detection and ranging (LIDAR) (3) hourly AD particle level ≥ 0.1 km(-1), and (4) hourly level ≥ 0.07 km(-1). Linear mixed models were used to estimate the effects of heavy-AD, by definition type, on daily PEF values. In adults with asthma, as per the JMA's definition, significantly reduced PEF were observed on heavy-AD days (lag 0), lag 0-1, and lag 0-3. In school children, after a heavy-AD event, as defined by the JMA, PEF significantly decreased on lag 0-1, lag 0-2, and lag 0-3. However, as per the other definitions, there was no significant decrease in the PEF in the adults and children. The associations between heavy-AD and respiratory function differed between these definitions.

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Postgraduate 1 13%
Lecturer 1 13%
Student > Master 1 13%
Unknown 3 38%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 13%
Environmental Science 1 13%
Nursing and Health Professions 1 13%
Agricultural and Biological Sciences 1 13%
Engineering 1 13%
Other 0 0%
Unknown 3 38%