Comprehensive overview of common e-liquid ingredients and how they can be used to predict an e-liquid's flavour category.

electronic nicotine delivery devices public policy surveillance and monitoring tobacco industry

Journal

Tobacco control
ISSN: 1468-3318
Titre abrégé: Tob Control
Pays: England
ID NLM: 9209612

Informations de publication

Date de publication:
03 2021
Historique:
received: 10 10 2019
revised: 10 01 2020
accepted: 19 01 2020
pubmed: 12 2 2020
medline: 16 10 2021
entrez: 12 2 2020
Statut: ppublish

Résumé

Flavours increase e-cigarette attractiveness and use and thereby exposure to potentially toxic ingredients. An overview of e-liquid ingredients is needed to select target ingredients for chemical analytical and toxicological research and for regulatory approaches aimed at reducing e-cigarette attractiveness. Using information from e-cigarette manufacturers, we aim to identify the flavouring ingredients most frequently added to e-liquids on the Dutch market. Additionally, we used flavouring compositions to automatically classify e-liquids into flavour categories, thereby generating an overview that can facilitate market surveillance. We used a dataset containing 16 839 e-liquids that were manually classified into 16 flavour categories in our previous study. For the overall set and each flavour category, we identified flavourings present in more than 10% of the products and their median quantities. Next, quantitative and qualitative ingredient information was used to predict e-liquid flavour categories using a random forest algorithm. We identified 219 unique ingredients that were added to more than 100 e-liquids, of which 213 were flavourings. The mean number of flavourings per e-liquid was 10±15. The most frequently used flavourings were vanillin (present in 35% of all liquids), ethyl maltol (32%) and ethyl butyrate (28%). In addition, we identified 29 category-specific flavourings. Moreover, e-liquids' flavour categories were predicted with an overall accuracy of 70%. Information from manufacturers can be used to identify frequently used and category-specific flavourings. Qualitative and quantitative ingredient information can be used to successfully predict an e-liquid's flavour category, serving as an example for regulators that have similar datasets available.

Identifiants

pubmed: 32041831
pii: tobaccocontrol-2019-055447
doi: 10.1136/tobaccocontrol-2019-055447
pmc: PMC7907577
doi:

Substances chimiques

Flavoring Agents 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

185-191

Informations de copyright

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Erna J Z Krüsemann (EJZ)

Centre for Health Protection, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, The Netherlands erna.krusemann@rivm.nl.
Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands.

Anne Havermans (A)

Centre for Health Protection, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, The Netherlands.

Jeroen L A Pennings (JLA)

Centre for Health Protection, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, The Netherlands.

Kees de Graaf (K)

Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands.

Sanne Boesveldt (S)

Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands.

Reinskje Talhout (R)

Centre for Health Protection, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, The Netherlands.

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Classifications MeSH