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Impact of ambient fine particulate matter (PM2.5) exposure on the risk of influenza-like-illness: a time-series analysis in Beijing, China

Overview of attention for article published in Environmental Health, February 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)

Mentioned by

news
6 news outlets
blogs
2 blogs
policy
1 policy source
twitter
43 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
121 Dimensions

Readers on

mendeley
117 Mendeley
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Title
Impact of ambient fine particulate matter (PM2.5) exposure on the risk of influenza-like-illness: a time-series analysis in Beijing, China
Published in
Environmental Health, February 2016
DOI 10.1186/s12940-016-0115-2
Pubmed ID
Authors

Cindy Feng, Jian Li, Wenjie Sun, Yi Zhang, Quanyi Wang

Abstract

Air pollution in Beijing, especially PM2.5, has received increasing attention in the past years. Although exposure to PM2.5 has been linked to many health issues, few studies have quantified the impact of PM2.5 on the risk of influenza-like illness (ILI). The aim of our study is to investigate the association between daily PM2.5 and ILI risk in Beijing, by means of a generalized additive model. Daily PM2.5, meteorological factors, and influenza-like illness (ILI) counts during January 1, 2008 to December 31, 2014 were retrieved. An inverse Gaussian generalized additive model with log link function was used to flexibly model the nonlinear relationship between the PM2.5 (single- and multiday lagged exposure) and ILI risk, adjusted for the weather conditions, seasonal and year trends. We also assessed if the effect of PM2.5 differs during flu season versus non-flu season by including the interaction term between PM2.5 and flu season in the model. Furthermore, a stratified analysis by age groups was conducted to investigate how the effect of PM2.5 differs across age groups. Our findings suggested a strong positive relationships between PM2.5 and ILI risk at the flu season (October-April) (p-value < 0.001), after adjusting for the effects of ambient daily temperature and humidity, month and year; whereas no significant association was identified at the non-flu season (May-September) (p-value = 0.174). A short term delayed effect of PM2.5 was also identified with 2-day moving average (current day to the previous day) of PM2.5 yielding the best predictive power. Furthermore, PM2.5 was strongly associated with ILI risk across all age groups (p-value < 0.001) at the flu season, but the effect was the most pronounced among adults (age 25-59), followed by young adults (age 15-24), school children (age 5-14) and the elderly (age 60+) and the effect of PM2.5 was the least pronounced for children under 5 years of age (age < 5). Ambient PM2.5 concentrations were significantly associated with ILI risk in Beijing at the flu season and the effect of PM2.5 differed across age groups, in Beijing, China.

Twitter Demographics

The data shown below were collected from the profiles of 43 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Taiwan 1 <1%
Unknown 116 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 18%
Researcher 17 15%
Student > Ph. D. Student 13 11%
Student > Bachelor 12 10%
Professor 7 6%
Other 16 14%
Unknown 31 26%
Readers by discipline Count As %
Environmental Science 23 20%
Medicine and Dentistry 18 15%
Engineering 12 10%
Social Sciences 4 3%
Agricultural and Biological Sciences 3 3%
Other 22 19%
Unknown 35 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 102. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 November 2021.
All research outputs
#320,992
of 21,770,930 outputs
Outputs from Environmental Health
#89
of 1,441 outputs
Outputs of similar age
#6,809
of 379,387 outputs
Outputs of similar age from Environmental Health
#1
of 1 outputs
Altmetric has tracked 21,770,930 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,441 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.2. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 379,387 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them