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Analysis of symptoms and their potential associations with e-liquids’ components: a social media study

Overview of attention for article published in BMC Public Health, July 2016
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Mentioned by

twitter
2 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
98 Mendeley
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Title
Analysis of symptoms and their potential associations with e-liquids’ components: a social media study
Published in
BMC Public Health, July 2016
DOI 10.1186/s12889-016-3326-0
Pubmed ID
Authors

Qiudan Li, Yongcheng Zhan, Lei Wang, Scott J. Leischow, Daniel Dajun Zeng

Abstract

The electronic cigarette (e-cigarette) market has grown rapidly in recent years. However, causes of e-cigarette related symptoms among users and their impact on health remain uncertain. This research aims to mine the potential relationships between symptoms and e-liquid components, such as propylene glycol (PG), vegetable glycerine (VG), flavor extracts, and nicotine, using user-generated data collected from Reddit. A total of 3605 e-liquid related posts from January 1st, 2011 to June 30th, 2015 were collected from Reddit. Then the patterns of VG/PG distribution among different flavors were analyzed. Next, the relationship between throat hit, which was a typical symptom of e-cigarette use, and e-liquid components was studied. Finally, other symptoms were examined based on e-liquid components and user sentiment. We discovered 3 main sets of findings: 1) We identified three groups of flavors in terms of VG/PG ratios. Fruits, cream, and nuts flavors were similar. Sweet, menthol, and seasonings flavors were classified into one group. Tobacco and beverages flavors were the third group. 2) Throat hit was analyzed and we found that menthol and tobacco flavors, as well as high ratios of PG and nicotine level, could produce more throat hit. 3) A total of 9 systems of 25 symptoms were identified and analyzed. Components including VG/PG ratio, flavor, and nicotine could be possible reasons for these symptoms. E-liquid components shown to be associated with e-cigarette use symptomology were VG/PG ratios, flavors, and nicotine levels. Future analysis could be conducted based on the structure of e-liquid components categories built in this study. Information revealed in this study could be utilized by e-cigarette users to understand the relationship between e-liquid type and symptoms experienced, by vendors to choose appropriate recipes of e-liquid, and by policy makers to develop new regulations.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 97 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 21 21%
Student > Master 15 15%
Researcher 13 13%
Student > Ph. D. Student 8 8%
Student > Postgraduate 6 6%
Other 14 14%
Unknown 21 21%
Readers by discipline Count As %
Medicine and Dentistry 18 18%
Social Sciences 8 8%
Environmental Science 7 7%
Nursing and Health Professions 6 6%
Pharmacology, Toxicology and Pharmaceutical Science 5 5%
Other 27 28%
Unknown 27 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 August 2017.
All research outputs
#6,951,042
of 11,623,235 outputs
Outputs from BMC Public Health
#5,651
of 7,995 outputs
Outputs of similar age
#134,766
of 264,911 outputs
Outputs of similar age from BMC Public Health
#256
of 361 outputs
Altmetric has tracked 11,623,235 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,995 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 264,911 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 361 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.