This page explains exactly how the score works and what data goes into it.
NYAM score bands
Every product and every basket maps to one of five levels. The same scale applies whether you're looking at a single product or your weekly shop, so "Moderate" always means the same thing.
The four signals NYAM uses
Nutri-Score — nutritional quality
Nutri-Score is a five-grade system (A through E) developed by Santé Publique France and adopted across multiple European countries. It evaluates products against energy, sugar, saturated fat, sodium, fibre, protein, and fruits/vegetables/legumes content.
NYAM uses the Nutri-Score 2023 algorithm — the most current version with improved handling of beverages, fats, and red meat.
When Open Food Facts has already computed a grade for a product, we use it directly. When OFF has the underlying nutrient data but no computed grade, NYAM computes it locally using the same publicly-published algorithm. Either way, the grade you see follows the official Nutri-Score logic — we don't invent our own variations.
NOVA — processing classification
NOVA is a four-tier framework developed by Carlos Monteiro and the University of São Paulo team. It classifies foods by how processed they are:
- NOVA 1 — Unprocessed or minimally processed (whole foods)
- NOVA 2 — Processed culinary ingredients (oils, butter, sugar)
- NOVA 3 — Processed foods (cheese, bread, canned vegetables)
- NOVA 4 — Ultra-processed (ready meals, soft drinks, most snack foods)
NOVA 4 ultra-processed foods are linked to a wide range of negative health outcomes in observational research, even when their nutrient profile looks acceptable. NYAM treats NOVA 4 as significant: any NOVA 4 product has a score floor of 61 — they can't be classified better than "Room to Improve" no matter what other factors look like.
Additive risk
NYAM evaluates additives based on independent risk assessments rather than just counting how many a product contains. Additives are categorised into:
- Low risk — no meaningful evidence of harm at typical exposure
- Moderate risk — emerging concerns or specific population sensitivities
- Under-review risk — additives where current evidence is being re-evaluated; treated conservatively pending review
- High risk — clear evidence linking to adverse outcomes
- Combination risk — pairs of additives that interact harmfully (e.g. E211 + E300 forming benzene under certain conditions)
A product with one high-risk additive scores worse than a product with five low-risk ones. We think this matches reality better than a flat count.
Pesticide risk
For fresh produce, NYAM flags items more likely to carry pesticide residues, based on PAN UK's analysis of UK Government PRiF (Pesticide Residues in Food) testing — measured by the percentage of samples found to carry multiple residues. Higher-risk produce raises the score.
How NYAM combines the signals
Most scoring apps use a weighted-sum formula (e.g. "Nutri-Score is 40% of the total, NOVA is 30%..."). NYAM doesn't. Weighted sums struggle with edge cases: they can give a high score to a product with great nutrients but ultra-processed status, or punish a whole food because its sodium happens to be high.
Instead, NYAM uses an anchor and modifier model:
When NYAM can't score a product
If a product doesn't have a published Nutri-Score and Open Food Facts doesn't have enough underlying nutrient data for NYAM to calculate one (proteins, sugars, saturated fat, salt, and energy per 100g), we show "Insufficient Data" rather than estimate.
When you scan a product like this, NYAM fetches the latest information from Open Food Facts in the background. As OFF's volunteer community adds data and as more people use NYAM, coverage improves automatically.
Data sources and credits
NYAM is built on the foundation of work done by hundreds of thousands of volunteers and researchers across multiple organisations. We owe them — explicitly:
Open Food Facts
Open Food Facts is the foundational data source for NYAM. It's a volunteer-driven, free, open database of food products worldwide — over 3 million products with nutrition information, ingredients, labels, and processing data. The organisation runs on donations and grants, maintained by a small team and a global volunteer community.
Without OFF, NYAM doesn't exist. We use their product database, their Nutri-Score computations, their NOVA classifications, their additives taxonomy, and their ingredient analysis. Where we compute Nutri-Score ourselves, we use their publicly-published 2023 algorithm.
NYAM is committed to supporting Open Food Facts financially — through donations now and a percentage of post-tax profits if NYAM becomes sustainable. Open data deserves to be sustained by the businesses that benefit from it. We're also building the technical foundation to contribute data back to OFF when our users help fill gaps — closing the loop on the open-data ecosystem we depend on.
Nutri-Score
Developed by Santé Publique France and the team at EREN (Equipe de Recherche en Epidémiologie Nutritionnelle). The 2023 algorithm update was based on the 2024 Nature Food paper by Galan, Kesse-Guyot et al.
NOVA classification
Developed by Carlos Monteiro and colleagues at the Universidade de São Paulo Centre for Epidemiological Studies in Health and Nutrition (NUPENS).
Additive risk assessments
Risk classifications draw from peer-reviewed research, EFSA (European Food Safety Authority) evaluations, and the work of independent food safety researchers.
Pesticide flags
Pesticide residue data from PAN UK's analysis of UK Government PRiF (Pesticide Residues in Food) testing.
NYAM is built by NYAM App Ltd in the UK. We're a small team committed to helping people make better food choices honestly — using the best science available, presented clearly, without sponsorship from food brands.