raphaels7

Hi, the insulin index Nutrita uses is a better predictor of the metabolic impact a food is likely to have because predictions based on blood sugar increases (GI) or the total carb load (GL) have many more false positive and false negative errors.

Nutrita's Insulin index has been extensively refined to minimize these errors.

The problems with GI and GL:

For example, 100g of carbs from a potatoe increases blood glucose less than 100g of carbs from potatoe flour. the Glycemic Load cannot distinguish that.

The Glycemic index looks at rises in blood sugar and suffers another problem, in that it can't tell you how much insulin it 'cost you' to maintain blood sugars. so you could be thinking "hey my blood sugars are normal this food is fine for me!" but in fact you're producing a tsunami of insulin to keep stable blood sugars. So the GI will miss prediabetes, basically.

Check out these podcasts and studies which go through the science papers demonstrating this https://www.breaknutrition.com/episode-8-starch-digestibilit... and https://www.breaknutrition.com/episode-7-processed-starches-...

Hi foxyv, I'm the co-founder of Nutrita and wanted to say your comment is spot on. Dr.Fung and his IDM clinic are getting amazing results. We're big fans of theirs

you can do so much more for diabetics and the obese by telling them to little foods high on the insulin index than you can by telling them to avoid "calorie rich" foods that are "hyperpalatable"

the insulin index is a good estimate of how your metabolism will react to a food, much more so than it being "calorie rich" (which calories?) or "hyperpalatable" (to whom?)

Hi, are you familiar with type of content Break Nutrition puts out? I think you'll see it's very science heavy and not geared towards ye' old food tracking app.

First, this app doesn't actually use the glycemic index (GI) of foods because the GI has an excessively high false negative rate (type 2 error), meaning that a 'normal' blood glucose response will often be given in the context of a hyperinsulinemic response.

So we're definitely not "a GI list in an app that monetizes your data".

Second, how many grams of ketones you produce shortly after being ketotic vs long-term ketosis is not at all clear and still an empirically open question - the downward trend is still just a guess based on anecdotes (nothing wrong with that).

Third, your comment about IF and carb loading being necessary to keep ketosis going is simply incorrect. You can stay ketogenic without carb-loading, since this will acutely increase the oxaloacetate-to-aceteyl-CoA ratio, thus diverting fatty acids away from ketogenesis. I think your comment may be in reference to staying 'healthy' in ketosis? Like not tanking your thyroid hormones? Thyroid hormones don't tank because of ketones, they often tank because of chronic caloric restriction - a common scenario in a fat-loss scenario.

Lastly, you're right that many factors keep you in or out of ketosis. You seem to know more than the average person yet even you are not entirely up to date on the clinical side of it, and this is precisely why our app would be of great use to you and other less knowledgeable users: you'd have somewhere to share your metrics, meals and see how it all compares with others if you have a blood glucose readings for instance, or your fasting triglycerides and insulin values. All nicely organized and presented from within the comfort of 1 app.

I wouldn't write it off until you've tried it ;)

Thanks.

When I was 15 I remember seeing my grandmother's glucose monitor values scribbled on her little notepad, their were big swings. I didn't know what I know now and I'm that, had she access to better information than what her doctors gave her, she could have better managed diabetes.

I hope this app helps diabetics do what I regret not having been able to for my (type 2) diabetic grandmother - reverse diabetes.

Hi Hurundo thanks for your insightful comment.

You're quite right that there are a myriad of identified and yet unidentified affecting an individual's Kraft Pattern of insulin release to a particular food. For example,it's becoming clearer that foods like flours with disrupted macromolecular starch network can negatively sway the insulin incretin and subsequent insulin response; 2 foods with identical glycemic responses can stimulate GIP and insulin to significantly different degrees https://breaknutrition.com/episode-8-starch-digestibility-li... The point being though we're saying "you're insulin is going to be X in 10min after this slice of pizza", what we're doing is using empirical averages with all their limitations to teach people how pizza, donuts and fruit juices all cause you to hypersecrete insulin, and that's very very bad. Of course, the more advanced users will still be able to track useful dietary, exercise, timing and other metrics for their N = 1's.

You mention implantable insulin monitoring, and that's of great interest to us. I'm a molecular biologist by training and would've loved to work on bringing that device to market. Until we have that though, there are other metrics that are pretty informative. For example, our app is going to have a McAuley Index calculator which plugs fasting insulin and triglycerides into a formula giving a pretty decent index compared to the clinical SSPG 2-hour test https://breaknutrition.com/episode-34-metabolic-syndrome-ser....

Blood marker tracking is also going to be a part of our app but we're not going to introduce quite yet.

Thanks,

Raphael Sirtoli