Methods & limitations.

The "what you have saved" numbers compare your logged daily sugar intake against an assumed pre-quit baseline of 50g/day.

That number sits roughly between the WHO conditional target (25g/day) and the UK National Diet and Nutrition Survey average for adults (60–80g/day depending on age and gender). It is the shape of a person who has been moderately conscious of sugar but has not made a deliberate effort to cut it. If your real baseline was 100g/day (one daily cola plus regular sweet snacks), the savings figures shown understate the impact materially.

Source: UK NDNS 2019–2024 rolling averages; WHO sugars guideline 2015.

Sugar provides 4 kilocalories per gram, the canonical Atwater factor for digestible carbohydrate. Your "calories not consumed" figure is simply (baseline grams minus your logged average) × 4 × days.

This is an over-estimate of "fat not gained" because not all consumed calories become fat — some are oxidised, some are excreted, some are diverted into glycogen replenishment. But as a measure of "calories not consumed", 4 kcal/g is exact.

We assume a pre-quit habit cost of £2/day — the UK retail price of one can of cola plus one chocolate biscuit, or roughly one daily flavoured coffee. Your figure scales linearly with how much of the time you log under target.

This is the assumption you are most likely to disagree with. A heavy daily Starbucks habit at £4.50 doubles the savings. Someone who only had occasional sweets pre-quit will see lower savings than the figure suggests. Treat it as an order-of- magnitude estimate, not a personal financial statement.

The "X% lower decay risk" figure draws on the Sheiham & James 2014 systematic review and dose-response analysis published in BMC Public Health. Their finding: dental caries risk responds linearly to dietary free-sugar intake across the full range from 0% to 15% of total energy.

We use a simplified linear model: each percentage-point reduction in daily added-sugar-as-energy reduces caries risk by approximately 2 percentage points (doubled to reflect the cumulative compounding effect across months). The model caps at 50% to avoid implying impossible risk reductions.

Sheiham, A., & James, W. P. T. (2014). A reappraisal of the quantitative relationship between sugar intake and dental caries. BMC Public Health, 14:863.

The GL number on the Dashboard SugarBudgetBar is a rough proxy (approximately 0.25 × total grams of added sugar) intended only to give a relative sense of the day. Accurate GL calculation requires a per-food lookup against the Foster-Powell GI tables multiplied by the actual carb content per serving — which requires either a food database query or AI estimation (the v0.8+ sugar_log_ai job will use the GI table approach).

Until then, treat the GL number as ordinal (higher = worse) rather than absolute.

The day-by-day withdrawal-intensity curve shown in modules and on the Dashboard is drawn from clinical-observation literature (Avena, Rada & Hoebel 2008; Colantuoni et al. 2001; clinical review at Recovered.org). Individual variation is substantial — we present the modal experience, not yours specifically.

If your day 3 is fine and your day 10 is the worst, you are not doing it wrong. The curve is a guide, not a prediction.

The "Lally automaticity" milestone at day 66 references Lally et al. 2010 (European Journal of Social Psychology), the only real-world habit formation study cited widely. The reported median was 66 days, range 18–254 days. Your habit may form much faster (a simple swap like cola-to-water) or much slower (an embedded substance-like dependency).

We use day 66 as the milestone because it is the most-cited and most-defensible single number — not because it is a guarantee.

We do not show estimated weight loss, blood pressure change, HbA1c projection, fatty liver regression, or any other clinical outcome metric. Those depend on too many individual variables (age, sex, BMI, baseline insulin sensitivity, exercise patterns, sleep, genetics) to estimate without doing actual harm with bad numbers.

If your GP or dentist measures something and it improves, that is the right way to learn whether your quit is working clinically. We measure the behaviour; they measure the body.

If any of the above feels wrong, mis-cited, or out of date, email methods@sugarquit.app. We update this page when the underlying assumptions change, with the date of last update at the top.