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Effect of gargling with tea and ingredients of tea on the prevention of influenza infection: a meta-analysis

Overview of attention for article published in BMC Public Health, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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28 news outlets
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273 X users
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4 Facebook pages

Citations

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31 Dimensions

Readers on

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51 Mendeley
Title
Effect of gargling with tea and ingredients of tea on the prevention of influenza infection: a meta-analysis
Published in
BMC Public Health, May 2016
DOI 10.1186/s12889-016-3083-0
Pubmed ID
Authors

Kazuki Ide, Hiroshi Yamada, Yohei Kawasaki

Abstract

Influenza viruses can spread easily from person to person, and annual influenza epidemics are serious public health issues worldwide. Non-pharmaceutical public health interventions could potentially be effective for combatting influenza epidemics, but combined interventions and/or interventions with greater effectiveness are needed. Experimental studies have reported that tea and its ingredients (especially catechins) have antiviral activities. Although several clinical studies have investigated the use of tea or its ingredients to prevent influenza infections, the effect of gargling these substances has remained uncertain. We conducted a meta-analysis of randomized controlled studies and prospective cohort studies to assess the effect of gargling with tea and its ingredients on the prevention of influenza infection. The published literature was searched using the Cochrane Library, PubMed/MEDLINE (1966 to September 2015), Web of Science (1981 to September 2015), and Ichu-shi Web (1983 to September 2015). The extracted studies were read by two reviewers independently, and their overall scientific quality was evaluated. Studies meeting our inclusion criteria were pooled using the Mantel-Haenszel method in a fixed effects model and were also analyzed in a random effects model. The qualities of the model fits were assessed using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The literature search and review identified 5 studies that met the inclusion criteria for the meta-analysis (total number of participants, 1890; mean age range, 16-83 years). The participants who gargled with tea or its ingredients showed a lower risk of influenza infection than did participants who gargled with placebo/water or who did not gargle (fixed effects model, Mantel-Haenszel method: relative risk [RR] = 0.70, 95 % confidence interval [CI] = 0.54-0.89; random effects model: RR = 0.71, 95 % CI = 0.56-0.91). The fixed effects model had a better quality of fit than the random effects model (fixed effects model: AIC = 6.04, BIC = 5.65; random effects model: AIC = 8.74, BIC = 7.52). Gargling with tea and its ingredients may have a preventative effect for influenza infection. However, additional large-scale studies in different populations and a pooled analysis of these studies are needed to confirm the effect.

X Demographics

X Demographics

The data shown below were collected from the profiles of 273 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 4%
Unknown 49 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 18%
Student > Bachelor 7 14%
Student > Ph. D. Student 6 12%
Student > Master 6 12%
Other 2 4%
Other 6 12%
Unknown 15 29%
Readers by discipline Count As %
Medicine and Dentistry 12 24%
Biochemistry, Genetics and Molecular Biology 6 12%
Nursing and Health Professions 4 8%
Agricultural and Biological Sciences 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 7 14%
Unknown 17 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 420. 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 15 November 2023.
All research outputs
#70,602
of 25,793,330 outputs
Outputs from BMC Public Health
#66
of 17,846 outputs
Outputs of similar age
#1,435
of 327,218 outputs
Outputs of similar age from BMC Public Health
#2
of 189 outputs
Altmetric has tracked 25,793,330 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,846 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done particularly well, scoring higher than 99% 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 327,218 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 99% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.