The habit · Decision 9 of 14

Why track anything at all

Logging is usually studied as part of a wider programme. The results below do not show the effect of Snapkin, photo logging, or logging on its own.

Last updated .

What the app does
Asks for a photograph rather than a database search, because the biggest problem in this category is how few people are still logging after a month.
How sure we are Fair , Real, but small, indirect, or thinly measured.
Regular logging goes together with more weight loss, and some digital programmes help. Installing an app alone does not guarantee a benefit. Motivation and the support around the app matter.

The evidence for it

Three results about the same behaviour: a pooled estimate from randomised trials, a comparison of behaviour-change techniques, and a study of how often people log.

−2.87 kg more weight lost than a control group, pooled across 12 randomized trials of programmes where people tracked their diet and activity Berry et al. (2021) · 95% CI −3.78 to −1.96 · intake down 182 kcal/d
13% of the difference in results between studies was explained by self-monitoring; not 13% extra weight loss Michie et al. (2009) · 122 studies, 44,747 people
2.7 × a day how often people who lost 10% or more of their weight logged, compared with 1.7 times a day for those who lost less Harvey et al. (2019) · 142 participants; a link at month six, not proof of cause

What exists compares ways of logging, or compares whole programmes that happen to include logging. The best of it: Berry et al. (2021) pooled 12 randomised trials of digital self-monitoring and found −2.87 kg (95% CI −3.78, −1.96), with calorie intake down 182 kcal a day. Michie et al. (2009) looked across 122 studies and 44,747 people. Of the 26 behaviour-change techniques they examined, self-monitoring explained more of the difference between studies than any other. Harvey et al. (2019) found that people who lost 10% or more logged 2.7 times a day, against 1.7 times for those who lost less than 10%. Among those still logging at month six, the time they spent logging did not differ significantly between the groups. This does not mean logging time does not matter. It does not prove that logging more often causes weight loss either.

Different programmes gave different weight-loss results Weight difference against a control group, with 95% confidence intervals, on one axis.
no difference
Diet-and-activity programmes, 12 trials −2.87 kg

Berry et al. 2021. Calorie intake down 182 kcal a day alongside it

Being handed MyFitnessPal, 212 patients −0.30 kg

Laing et al. 2014, primary care, six months, p = 0.63. The interval crosses zero

−4.2 kg +1.4 kg
Berry pooled diet-and-activity programmes, often with advice made for each person. Laing tested handing out MyFitnessPal at the family doctor and did not find a significant weight benefit. These findings do not single out food logging. They do not predict the effect of Snapkin.

And the usual warning from the same research: Burke et al. (2011) found the link every time, and then said plainly that “the level of evidence was weak because of methodologic limitations.”

Prediabetes is where the evidence is strongest, and it is not about the app

The Diabetes Prevention Program (3,234 people, followed for 2.8 years on average) is the best-known study. An intensive lifestyle programme, aiming for 7% weight loss and 150 minutes of activity a week, cut the rate of new type 2 diabetes by 58% compared with placebo (95% CI 48–66). That is 4.8 versus 11.0 new cases per 100 person-years. Metformin, a drug, cut them by 31% (17–43). Average weight loss was 5.6 kg. The Finnish Diabetes Prevention Study (522 people) found the same 58% reduction on its own.

Writing down what you eat was part of both. In the American programme, Wing et al. (2004) reported that “dietary self-monitoring was positively related to meeting both weight loss and activity goals.” In the Finnish study, dietary advice was based on three-day food records.

How much weight loss is enough? The usual “5 to 7%” figure is a programme target. It is what those two trials aimed for and reached. It did not come from a study designed to find the right amount. The real relationship is gradual, with no cut-off point. Hamman et al. (2006) found 16% lower diabetes risk for each kilogram lost (HR 0.42, 95% CI 0.35–0.51 per 5 kg). Weight loss was the strongest predictor. This is a link seen inside the trial, not a guaranteed risk cut from each kilogram. Magkos et al. (2016) showed that 5% weight loss on its own made fat, liver and muscle respond better to insulin.

Diabetes fifteen years after the DPP groups were assigned Share of each group that had developed type 2 diabetes at the 15-year follow-up.
Intensive lifestyle programme 55%

The group that lost 5.6 kg and reached its activity target

Metformin 56%

The group that started on metformin

Placebo 62%

The group that started on placebo; later offered lifestyle training

0 70% of the group
At 2.8 years the lifestyle group’s risk was 58% lower. At the 15-year follow-up, more than half of every group has developed diabetes. The gap is seven percentage points. The long-term follow-up includes changes in treatment: all groups were offered lifestyle training after the randomized part ended. These are totals by the group people started in. They are not fifteen years of an unchanged placebo comparison. They show a lot of risk remains. They do not prove that everyone will get diabetes in the end.

The evidence against, and the two numbers we like least

Almost nobody keeps logging

Helander et al. (2014) followed 189,770 people who downloaded and opened a free photo food-logging app at least once.

Active use in one free photo-logging app The Eatery: 189,770 people who opened the app at least once in 2011–2012.

2.58% used it actively did not

Active meant at least ten photographs over at least one week: 4,895 people (2.58%). This is not a standard measure of how many people still use an app after 30 days. The app already used photographs. So the result cannot show that photos stop people giving up, or that the effort of tapping caused it.

Apps in general do very little

Chew et al. (2022) put the pooled effect of apps at 2.18 kg at three months, falling to 1.63 kg at twelve. They called the effects “minimal in their current states.” A separate review studied apps combined with a human coach (Chew et al., 2023). It found −2.15 kg against a mix of control groups. It asked for research on what a coach adds over an app alone. Comparing pooled numbers from two reviews cannot show that coaching doubles the effect. Snapkin has no human coach.

Self-reported calories barely match real calories

Freedman et al. (2014) pooled five studies with 2,265 people in total. Each compared what people reported eating with doubly labelled water, the most accurate way to measure how much energy a person really uses. Under-reporting gets worse with body weight, by a further 5 to 7 percentage points at a BMI of 30 compared with 25. The correlation between reported and true calorie intake was r = 0.21 to 0.31.

How much of what people eat never makes it into the log Calories left out, measured against doubly labelled water, the most accurate method.
A single 24-hour recall 15%

Freedman et al. 2014, pooled over five validation studies, 2,265 people

A food frequency questionnaire 28%

The same pooling. The more the method asks you to remember, the worse it gets

0 35% under-reported
Photo-based methods have the same problem: Ho et al. (2020) found photo logging came up 448 kcal a day short against doubly labelled water. That pooled shortfall does not say how much came from food that was never logged and how much from wrong estimates. Both can play a part.