The camera · Decision 3 of 14

Why we track added sugar, and what we mean by it

Snapkin says “added sugar” everywhere, because that is the phrase people use. Underneath, it uses the World Health Organization's definition of free sugars. That covers more.

Last updated .

What the app does
Counts WHO free sugars, and counts fruit purées too. The daily limit is roughly 10% of your calorie target. No streak on it, no reward for staying under.
How sure we are Thin , One small study, or an engineering choice.
Less than anything else the app shows. It is a rough budget, not a measurement. That is why it has no confidence badge.

The evidence for it, and there is little of it

This is the weakest evidence on any of these pages, and the page says so throughout. Here is what there is.

10% of energy is the WHO’s limit on free sugars, and where the app’s daily limit comes from WHO guideline (2015) · below 10%: strong recommendation; below 5%: conditional
0.98 agreement score (ICC) for experts estimating added sugar in packaged foods; this does not test Snapkin or photo estimates Scapin et al. (2021) · 930 products, ICC
−0.80 kg weight change from eating less free sugar, in adults eating freely Te Morenga et al. (BMJ 2013) · and no effect once calories are matched

What “added sugar” means here

The definition underneath is the World Health Organization's free sugars: sugar added by a manufacturer, a cook or the person eating, plus honey, syrups, and fruit juice and juice concentrates. It does not include the sugar in whole fruit, in vegetables, or in plain milk and yoghurt. The app also counts fruit purées and smoothies. That follows the wider 2018 UK definition, which looks at how much the fruit was processed. The WHO’s wording does not list all of these processed-fruit cases. Plain stewed or canned fruit that still has pieces in it is not automatically free sugar. Any sweetener added to it still counts.

The “Added Sugars” line on a US nutrition label (21 CFR 101.9) is not the same thing. Total sugars, the figure on a European label, is a third thing again. The three definitions differ on juice, and on the sugar that is naturally in whole foods.

Three definitions of sugar, and where they differ What each one counts, for the same food.
Counted as sugar? Snapkin
(WHO free sugars)
US label
“Added Sugars”
EU label
“of which sugars”
Sugar stirred in, or added by a manufacturerYesYesYes
Honey, syrups, molassesYesYesYes
100% fruit juice, including correctly reconstituted juiceYesNoYes
Concentrated juice used as a sweetenerYesYes*Yes
Sugar in whole fruit and vegetablesNoNoYes
Lactose in plain milk and yoghurtNoNoYes

*US rules contain specific concentrate exceptions. See FDA guidance and the regulation linked above.

Unsweetened 100% orange juice can say zero added sugars on a US label. Its natural sugars still count as WHO free sugars. The grams depend on the serving. Concentrated juice used to sweeten other foods can count as added sugar under FDA rules. Adding water back to 100% juice is a different case.

The WHO guideline recommends keeping free sugars below 10% of energy, and suggests going below 5% if possible. Snapkin takes 10% of your target calories and turns it into grams at 4 kcal/g. Then it rounds to the nearest 5 g. So the budget you see can be a little above or below 10%. It is a rough budget for tracking, not an exact WHO limit.

How the number is worked out

Snapkin gives the analyser this definition and a step-by-step guide for estimating. The definition decides which sugars count. The guide decides what to do when a label or recipe is incomplete. Knowing the definition does not tell it the ingredients or the portion size of a photographed meal.

Free sugars are not printed on any European label, so they have to be estimated. Experts have published methods for estimating added and free sugars from food tables and ingredient lists. The instructions we give the analyser borrow their order of steps. But an AI following instructions is not the tested expert method. Louie et al. (2015) set out ten steps, starting from hard evidence and ending with guesses by food category. Kibblewhite et al. (2017) restated them for WHO free sugars. Scapin et al. (2021) adapted them for a country whose labels show neither total nor added sugars.

Scapin checked the method against the values on US labels for 930 products. The agreement score (ICC) was 0.98. Davies et al., 2022 tested Louie's method on their own. They found R² 0.97 and a mean absolute error of 1.26 g per 100 g. Davies used a made-up test set of 500 Australian products to compare the manual method with a machine-learning method. Both tests are about packaged food information, not photographs.

0.98 ICC against US label-declared values, 930 products One specialist, ingredient lists in hand
1.26 g manual-method MAE per 100 g or 100 mL; 500 synthetic test products Davies et al. 2022, R² 0.97
4.6 g standard deviation between two trained researchers, per 100 g Louie, Lei & Rangan 2016, the same 5,740 foods

The repeat study asks a different question. Two people followed the same written steps for the same 5,740 foods. Their answers differed with a standard deviation of 4.6 g per 100 g. You cannot divide that number by another study’s mean error and call the result “so many times less accurate”. The measures, the samples and the comparisons are all different.

The evidence against, and there is a lot of it

The weight effect is mostly about calories

Te Morenga et al. (BMJ 2013): eating less sugar changed weight by −0.80 kg (95% CI −1.21 to −0.39). Eating more changed it by +0.75 kg (0.30 to 1.19). But there was no significant weight difference when sugar replaced other carbohydrates at the same calories. This is a finding about body weight. It is not proof that sugar has no other health effects. The WHO’s guideline also looks at tooth decay.

Estimating sugar from a photograph is the weakest thing this app does

One peer-reviewed photo study reports total sugar: O'Hara et al. (2025), 114 photographs of weighed meals, judged by ChatGPT-4. It measured total sugar, not free sugar. We have no test showing that Snapkin can tell the two apart from photographs. Hidden ingredients make that a very uncertain estimate.

Similar median calories do not mean accurate individual meals The difference between the estimated median and the true median across 114 meals. Not the mean error per meal.
Sugar 32% low

Total sugar; this is not a free-sugar accuracy result

Protein 2.7% low

Same photographs, ChatGPT-4

Energy 0.1% high

Median-to-median difference; individual errors can cancel

0 35% difference between medians
O’Hara et al. compared a median calorie estimate of 525 kcal with a true median of 524.5 kcal. That is a 0.1% difference between medians. The error on single meals was much larger: the paper reports an average relative error of 27.3%. The total-sugar medians differed by −32%. Similar medians do not mean the amount for one particular meal is right.

“Carbs that turn into sugar” is a different thing, and we do not track it

Carbohydrate your body can digest, including starch, can raise your blood sugar. Glycaemic load combines a food’s glycaemic index with how much carbohydrate it has. It is not the same thing as free sugar. Zeevi et al. (Cell 2015) gave 800 people continuous glucose monitors across 46,898 meals. Different people responded very differently to the same meal. Published glycaemic index and load tables exist, but they do not predict every person’s response. Snapkin does not estimate your personal blood sugar response.

So the sugar limit is a rough budget, not a measurement. It carries no confidence badge. The eating disorders page has the other half of this decision: there is no streak on the sugar limit, and no celebration for staying under it.