Betel nuts (areca nuts) are the seeds of the areca palm, widely chewed across South and Southeast Asia, often wrapped in betel leaf with lime paste. They contain arecoline, a stimulant compound, and are classified as a Group 1 carcinogen by the IARC — regular chewing is strongly linked to oral cancer, oral submucous fibrosis, and cardiovascular disease. They have no place in a healthy diet.
Betel nut chewing is not recommended. If used in cultural contexts, awareness of the significant oral cancer and cardiovascular risks is essential. Cessation support is available through healthcare providers.
Where Betel nuts Stands Out
Macronutrients per 100g
Vitamins & Minerals
| Nutrient | Per 100g | % Daily Value* | Level |
|---|---|---|---|
| Potassium | 450 mg | 23% | |
| Calcium | 400 mg | 50% | |
| Phosphorus | 89.0 mg | 13% | |
| Iron | 4.90 mg | 35% | |
| Niacin (B3) | 1.10 mg | 7% | |
| Riboflavin (B2) | 0.520 mg | 37% | |
| Thiamin (B1) | 0.190 mg | 17% | |
| Vitamin B12 | 0.000 µg | 0% | |
| Vitamin D | 0.000 µg | 0% | |
| Vitamin A (RE) | 0.000 µg | 0% | |
| Vitamin C | 0.000 mg | 0% | |
| Maltose | 0.000 g | — | |
| Glucose (dextrose) | 0.000 g | — | |
| Fructose | 0.000 g | — | |
| Cholesterol | 0.000 mg | — | |
| Beta-carotene | 0.000 µg | — | |
| Retinol (vitamin A) | 0.000 µg | 0% |
* % Daily Value is the proportion of an adult
EU Nutrient Reference Value (NRV) supplied by 100g of this food.
NRVs are the labelling standard — the same basis as the “%RI” figures printed on
food packaging — so these percentages are directly comparable with a shop label.
They are a single adult figure and do not vary by age or sex, which is why they
sometimes differ from UK dietary reference values: the NRV for vitamin C is 80mg
where the UK RNI is 40mg. When Nutriofia assesses your own intake in the
reports and trackers, it uses the age- and sex-specific UK values instead.
Fibre is shown without a percentage. Our fibre values use the UK
Englyst NSP method, while the published 30g daily goal is an AOAC figure — the two
are measured differently and a single percentage would mislead.
How we source and normalise our data →