I have been diabetic for 20 years. I have tried every method, app, plan, and tool, including systems falsely marketed as "smart." No method works or delivers decent results except for using a scale and weighing ALL the ingredients. For a diabetic, eating "out" is always a roll of the dice. The "fun" feedback from post-meal blood sugar is always a reminder of how "eyeballing a plate" is utterly useless.

At Bitesnap we were surprised at how much interest there was from researchers to use our app for diet tracking. It turns out giving people a piece of paper to write “grilled cheese sandwich for lunch” is not a scalable and reliable way to collect research quality data.

We even worked with USDA on putting together a food logging dataset: https://agdatacommons.nal.usda.gov/articles/dataset/SNAPMe_A...

I highly recommend people get a food scale/measuring cups and weighing everything single thing they eat (even small things like nuts and cooking oil) for at least two weeks. After that I think you have a much better appreciation for how many calories your regular meals and snacks have.

>people are on average off by 53% and even trained professionals are still off by 40%. Basically if you want to have a higher level of accuracy you need to use a food scale or something that measure the volume of food, people just can't estimate portion sizes visually.

I can typically estimate them accurately without direct measurement, and with feedback that will tend to make errors cancel out over time. My trick is to note package weights, and divide containers into N equal portions. That is: I decide a target portion size first, and then portion it out.

If the task is "measure out an ounce of butter" I realistically won't be 40% off - because I can very accurately divide a rectangular solid in half repeatedly, and the butter comes in a one-pound package. Similarly, I have a pretty good idea how much grilled chicken is on my plate, because I know how much raw chicken I cooked, because I made a whole piece from a pack of N roughly-equal pieces weighing X (values which I noted when I bought it).

There is actually an elegant _mathematical_ solution to this problem using sensor fusion and a differential equation model of the science: if you weigh your food almost all of the time at home, and only make portion and ingredient guesses when infrequently eating out, we can actually estimate your personal rate of underestimation and correct for it.

Our startup (BODYSIM.com) has also been doing research on this a long time. As founders, we all have >16 months of daily food logging mostly by kitchen scale weights, aligned to daily BIA-scale weigh-ins, fitness tracker calories, bi-weekly blood tests, monthly DEXAs, 3D scans, etc etc. We also have a science-based structural model of macronutrient balance and muscle hypertrophy. Given all that, we can VERY confidently estimate your TDEE (total daily energy expenditure) and its components, and predict how your fat and muscle mass will change on a daily basis. This is real math/science so you can also run it in reverse. This ("simultaneity constraint") provides enough constraints we can estimate users' individual underestimating/over-indulgence when eating out. In fact, it's better to just NOT log those days AT ALL and we can fill them in. I think this solution isn't more widely used b/c you need all this other "quantified self" type data at the same time.

This goes a long way to further convince me that it is portion sizes in the US. Having traveled, it is quite absurd to see the difference in standard order sizes.

Even for zero calorie things like water and unsweetened teas/coffees. You just get smaller cups. I'm not even sure you can get a US large in Japan for most drinks?

>and even trained professionals are still off by 40%

I find this very hard to believe, unless the term “trained professional” is quite broad. When I was much more into fitness and weighed every meal to the gram, I could tell if a bowl of cereal was a serving to within a gram or two.

I downloaded SnapCalorie to try it out on Android. I went all the way through the sign-up phase, only to discovery that I would need to activate subscription in order to have the 7-day trial. Ended up uninstalling the app :(

From the paper (https://openaccess.thecvf.com/content/CVPR2021/papers/Thames...):

> We asked them to estimate the mass of each ingredient present on the plate and subsequently converted these values into nutrition estimates using the same USDA [9] values we used to create our dataset

I get that there's a linear relationship between the mass of a food and its calories, but I'd expect that nutritionists would be better at estimating the calories in a plate of food than the mass of a food item. Most people aren't doing the math in their heads, they're using a frame of reference that recognizes calories. Did you have this in mind? Is there any research on this?

Not too shocking really:

https://pmc.ncbi.nlm.nih.gov/articles/PMC1322248/

> Aiming to pour a “shot” of alcohol (1.5 ounces, 44.3 ml), both students and bartenders poured more into short, wide glasses than into tall slender glasses (46.1 ml v 44.7 ml and 54.6 ml v 46.4 ml, respectively). Practice reduced the tendency to overpour, but not for short, wide glasses. Despite an average of six years of experience, bartenders poured 20.5% more into short, wide glasses than tall, slender ones; paying careful attention reduced but did not eliminate the effect.

A plate is a very wide 'glass'.

I'm currently dieting again, and the only way that I've been able to properly portion calories is to weigh nearly everything I eat and then add the numbers together in Google Sheets.

Eyeballing a portion of a lot of food can be nearly impossible to determine how much food you actually got, but weight is fairly straightforward and objective (at least to an ounce or so of granularity for most kitchen scales, which is good enough for dieting).

Fats are definitely the easiest way to mess up counting, especially when a lot of people can't compute not cooking without oil/butter.

If the goal is losing weight, I found that maximising volume (e.g. Minimising calory density) works wonders for me. I am used to being full before feeling satiated (mostly upbringing I guess), so this is my trick.

As someone who takes a photo of every single meal I eat, I was very excited to try out Snapcalorie but it was completely wrong for all the pictures I tried giving it. I uploaded a picture of a recent meal of tomato egg, baked octopus tentacles, and shrimp, and it identified it as pasta, mushrooms, and chicken. Also, it doesn't work for typical home meals that are eaten family-style.

I was part of a project that did some work in this area also, we developed a machine learning based wearable to detect chewing:

https://www.ah-lab.cs.dartmouth.edu/publications/detecting-e...

Even when you weight, the weight needs to be on cooked food, otherwise it's useless. I'm not going to cook a separate meal for every member of a family

This should be an indication that tracking as a personal health methodology is inherently flawed. Your body is your most accurate measurement system, both in terms of precision and accuracy but also in its multidimensional, intersectional measurement apparatus that completely demolishes the poor substitutes found in personal nutrition, which are continuously shown to be either flawed in theory or in practice.

Tracking takes more work and is less accurate. Bad trade.

The only use I see in tracking is to perhaps help one inform one's intuition. But that's as far as I'll go.

> you need to use a food scale or something that measure the volume of food

Isn't that obvious? Basic high school science projects would have students using measuring devices. Are you saying that it's common for nutritional studies to tell people to eyeball their portions and that is then used as actual data?

I see from the article "Nutritional epidemiology studies typically ask people to keep a food diary or complete questionnaires about their intake over the past 24 hours, a week, or even several months." I find that hard to believe. How could any study like that be taken seriously? That's like having someone stand at a street corner for an hour and observe the population to then come up with an average BMI for the neighbourhood.