The DOI matches its Crossref record.
Global epidemiology of areca nut usage
Abstract
Abstract A substantial proportion of the world's population is engaged in chewing areca nut and the habit is endemic throughout the Indian subcontinent, large parts of south Asia and Melanesia. A large variety of ingredients, including tobacco, may be used along with areca nut constituting a betel quid. The composition and method of chewing can vary widely from country to country and these population variations are described in this review. Some populations are known to use areca nut without tobacco providing good opportunities to further research the carcinogenecity of areca nut. Some interesting trends on chewing patterns have emerged from recent data, suggesting a decline in the habit in some countries such as Thailand while the prevalence of areca nut use is rising in India and Taiwan.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Epidemiology of Betel Quid Usage
Gupta, P., & Ray, C. (2004) · Annals of the Academy of Medicine, Singapore · doi:10.47102/annals-acadmedsg.v33n4p31s · Cited by 333
Self-citationDefining a global research and policy agenda for betel quid and areca nut
Mehrtash, H., Duncan, K., Parascandola, M., David, A., Gritz, E. R., Gupta, P. C., Mehrotra, R., Amer Nordin, A. S., Pearlman, P. C., Warnakulasuriya, S., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30460-6 · Cited by 221
Petti, S., Masood, M., & Scully, C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0078999 · Cited by 144
Tetrameric acetyl-CoA acetyltransferase 1 is important for tumor growth
Fan, J., Lin, R., Xia, S., Chen, D., Elf, S. E., Liu, S., Pan, Y., Xu, H., Qian, Z., Wang, M., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.10.014 · Cited by 106
Metadata
- Authors
- Gupta, P. C., & Warnakulasuriya, S.
- Venue
- Addiction Biology
- Publisher
- Wiley
- Published
- 2002-01
- Volume
- 7
- Issue
- 1
- Pages
- 77-83
- ISSN
- 1355-6215 (ISSN-L)
- 1369-1600
- OpenAlex
- W2083157947
- Cited by
- 643
- References
- 0
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Global epidemiology of areca nut usage. https://app.cochat.ai/papers/10.1080/13556210020091437
- The paper
- Gupta, P. C., & Warnakulasuriya, S. (2002). Global epidemiology of areca nut usage. Addiction Biology. https://doi.org/10.1080/13556210020091437
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.