combinations of ingredients (e.g. how much does indigestible fiber, fat, or protein slow carb absorption
When I tried this before, I added ingredients to my normal meals measured the change in my normal BG trends (see Next Experiments). This proved too noisy and I couldn’t get a clean measure of the effect of even pure glucose in a reasonable number of measurements (see Next Experiments).
This time, I have a continuous glucose monitor (Freestyle Libre, post coming soon on accuracy vs. fingerstick and attempts to calibrate it) and am going to try to more carefully isolate the effects of the ingredient being tested.
This is going to be a lot of work and take many weeks, so I was hoping to get some feedback on my experimental design before I start. If you’re interested, please take a look and leave your feedback/critique in the comments.
It’d really improve the experiment to have more people participating. Let me know in the comments or by e-mail if you want to join in (see sidebar).
Proposed Experiment
Note: I put some specific questions at the end
Goals:
Determine effect of individual ingredients on the blood sugar of person with Type 2 diabetes
Determine effect of combining ingredients on same.
Develop model to predict the effect on blood sugar of meals that’s more accurate than standard carb+protein counting
Approach:
Calibrate Instruments: Over several days, measure blood sugar by both CGM (Freestyle Libre) and BGM (Freestyle Lite). Develop a calibration curve to increase accuracy of CGM data
Note: I’m already doing this and initial indication is that ~75% of the discrepancy between the two meters can be accounted for by a simple linear gain + offset error
Establish Baseline: Monitor blood sugar while skipping breakfast & lunch (both food & insulin) to identify a period of time where my blood sugar is stable for a long enough (need at least 2-4 hours).
Will collect data on at least 3 days in which I’m not exercising in the morning (M, W, F)
To reduce potential noise, need to be careful not to overeat or eat late the night before.
Measure Food Effects: For each ingredient or combination of interest, follow the same procedure as in the baseline, but at the selected time, consume a fixed, measured quantity of the ingredient and monitor blood sugar by CGM and BGM (every 30 min.) for 2 hours or until my blood sugar is stable for at least 1 h.
Initial quantity will be selected based on my previous experience of what will raise my blood sugar by ~20 mg/dL.
Based on the initial results, I will test different quantities of the ingredients until I have a dose-response curve with BG increases from 0 to 40 mg/dL or the quantity exceeds what I would reasonably consume in a sitting, whichever is smaller.
Number experiments will be at least 3 per ingredient or combination.
Initial Ingredients to Test:
Glucose tablet – baseline to which everything else will be compared
Dissolved glucose – effect of dissolving an ingredient
Whey protein – effect of protein
Casein protein – effect of protein type
Allulose – my favorite “indigestible” sweetener for baking & ice-cream
Oat-fiber – low-calorie, low-carb flour replacement I use for muffins and cookies
Inulin – used in a lot of low-carb foods
Questions
Current design tests one ingredient at a time. This is a lot simpler and lets me get results for the first ingredients sooner, but does introduce a systematic variation between ingredients (the week). My thought was to mitigate this by re-testing glucose at some frequency to measure week-to-week variation. Do you think this is sufficient or is there a better design?
I’m not planning to repeat quantities of a given ingredient multiple times, but instead vary the quantity. Since the end result of interest is change in BG as a function of quantity, I figured this would be more experimentally efficient. Are there any problems with this approach?
Since experiments will be done on M, W, F, there will be a 1-2 day washout period between ingredients. Is this sufficient or do I need to separate ingredients by week to ensure a two day washout?
Are there any other ingredients you’d like to see me test?
Preheat oven to 275 °F and spray 9″ springform pan with oil of choice.
Combine chocolate and butter in a bowl. Melt in a microwave at 50% power, stirring occasionally, ~4 min. Let cool for 5 min.
Whisk together eggs, erythritol, water, glucomannan, vanilla, and espresso powder. Whisk in in chocolate mixture until smooth and slightly thickened. Filter through fine-mesh strainer into pan, then gently tap pan on counter to remove air bubbles.
Let cake mixture sit for 10 min. to let air bubbles rise to the top. Pop bubbles with a fork, then bake for 45-50 min., until edges are set and center jiggles slightly when shaken.
Let cool for 5 min., then run a paring knife around the sides of the pan. Let cool on a wire rack until barely warm, ~30 min., then cover, poke holes in top, and refrigerate for at least 6 h.
Remove sides of pan and use an offset spatula to separate cake from bottom tray. Let stand at room temperature for 30 min., then serve with whipped cream.
Whipped Cream
Whisk together all ingredients in a stand mixer on medium low for 1 min, then high until stiff peaks form, 1-3 min.
Tried this recipe?Let us know how it was in the comments
Also posted to Reddit in r/diabetes and r/QuantifiedSelf. Check those out if you want to see/participate in the discussion.
A couple weeks ago, u/NeutyBooty posted on how hot showers caused their blood glucose to rise. Lot’s of commenters confirmed the general observation, but for some it appeared to be a CGM artifact, for some it matched their finger-stick meter, and others they see a BG drop.
To figure out what’s really going on, we decided to do a communal self-experiment. Over the past two weeks, 8 Redditor with diabetes have been measuring their blood glucose before and after showering. So far, we have 22 measurements, so I thought it would be useful to post an initial exploratory analysis of the data to see if the wider community had an insights or suggestions.
In the comments, please chime in with any thoughts, additional analyses, or questions. If there’s any graph, calculation, etc. you’d like to see, let me know and I’ll add it. We also need more experimenters, so if your interested, let me know.
Highlights:
Initial indications are that we are seeing a real and consistent increase in BG from hot showers, not a sensor artifact.
So far, we are not seeing a clear person-to-person variation in the effect (more data needed).
There’s some very tentative but interesting trends in the data:
The effect is stronger with lower initial BG
The effect varies with time of day (could easily be a confounding variable here)
In order to get a clear answer on person-to-person variation and to better pull out any correlations, we need more data, especially repeat data from more people. If you’re interested in joining the experiment, let me know.
Details:
Design/Methods
Protocol here. All data was converted into consistent units and put into an excel spreadsheet. From the raw data, I calculated change in BG from start of shower, as well as the largest relative change, and the time until largest relative change (see spreadsheet for calculation details). Visualization was done using Tableau.
First, let’s look at the big question: are we seeing an effect? For this question, I plotted largest observed change over the 1 hour monitoring period for each shower as measured by both BGM and CGM.
Max ΔBGM & ΔCGM for each shower, colored by experimenter.
Looking at the graphs you can see the following:
We are seeing a measurable rise in blood sugar from a hot shower.
The effect is approximately the same size when measured by BGM vs. CGM, suggesting it’s not a sensor artifact
BIG CAVEAT: We don’t have much data from people with both BGM and CGM, and the majority of data is coming from two experimenters, so this conclusion is very tentative.
We’re not (yet) seeing a clear person-to-person variation. For both BGM and CGM, with the exception of 1 outlier in each case, there’s a pretty consistent increase in BG after a shower.
Interestingly, while we consistently see an increase in BG after showering, the timing of that increase is much more variable. If instead of looking at Max ΔBG over the monitoring period, you look at ΔBG 15 minutes after the shower, you get:
ΔBGM & ΔCGM@15 min. for each shower, colored by experimenter.
While we still see the effect, it’s a a lot more variable, especially in the BGM measurements.
Next, even though there’s not enough data for solid conclusions, I thought it’d be interesting to see if there was any interesting patterns/correlations in the data. I looked at:
ΔCGM@15 min. vs. ΔBGM@15 min. – only three data points, so can’t really say anything
Max ΔCGM vs. Max ΔBGM – two data points, can’t say anything
Max ΔBGM vs. hour of the day – no trend across the whole data set, but within Experimenter H’s, there’s an indication of a greater rise later in the day (R2 = 0.40, p = 0.08)
Max ΔCGM vs. hour of the day – no clear trend across the whole data set, nor within experimenters
Max ΔBGM vs. starting BGM – no trend across the whole data set, but within Experimenter H’s data, there’s an indication of a strong negative correlation (R2 = 0.57, p = 0.03).
Max ΔCGM vs. starting CGM – no clear trend across the whole data set, nor within experimenters.
Max ΔBGM vs. hour of the day, colored by experimenter. Data from Experimenter H highlighted, showing a clearing increasing trend (R2 = 0.4, p = 0.08)Max ΔBGM vs. initial BGM, colored by experimenter. Data from Experimenter H highlighted, showing a clearing decreasing trend (R2 = 0.57, p = 0.03)
Note: This is an updated version of my previous post on this recipe. Since my first attempts, I’ve tried out 10 new batches, with big improvements in taste and texture. I also worked out a low-calorie version with shredded coconut instead of chocolate.
I’ve been trying to work out a low-carb chocolate chip-cookie dough ice cream to go along with my other ice cream recipes, but I haven’t liked any of the low-carb cookie dough recipes I’ve found on-line. All of them either didn’t really taste like a traditional chocolate chip cookie dough or were too soft even when frozen.
Since the oat-fiber muffins turned out so good, I decided to see if I could use an oat-fiber/whey protein base to make a cookie dough. The results turned out surprisingly good for a first attempt. Still needs some work, but I thought I’d share now to get some advice before I keep developing.
Flour → 80g oat-fiber + 44g whey protein + 16g gluten (same ratio as my oat-fiber muffins)
White sugar → allulose (1:1 by weight)
Brown sugar → allulose (1:1 by weight) + molasses (10% of sugar by weight, adapted from here)
Chocolate chips → 1 cup shredded coconut (I didn’t have any sugar-free chocolate chips, wouldn’t have done this otherwise.
Added 50% more egg to get to the right dough consistency.
Added a sprinkle of flaky sea salt to the top of the cookie before baking.
This was a pretty good start:
Good:
They tasted very similar to chocolate chip cookie dough (minus the chocolate)
They froze to a good texture.
While not as good as chocolate chips, the shredded coconut gave a nice flavor and texture to the dough.
Con:
When baked, the cookies puffed up and had more of a bread/muffin texture than a cookie texture.
The amount of coconut was more than I’d like.
First attempt at oat-fiber cookies. Taste was good, but they puffed up and had more of a bread than cookie texture.
To fix the texture problem, I made the following changes:
Removed gluten (it prevented the muffins from deflating, so removing it should reducing “puffing”)
Went from 2 eggs to 1 egg + 1 yolk (less egg white should give a less stable structure)
Halved the amount of coconut.
This was a big improvement. The taste of the dough stayed the same, but the cookies spread and gave a texture very similar to a chewy chocolate chip cookie.
Second attempt, with gluten and half of egg white removed. Taste, texture, and appearance of a chewy chocolate chip cookie (without the chocolate for now).
Reduce the molasses content (would help the carbs count, but probably make it taste worse. Could try substituting some “brown sugar” erythritol instead?)
Lower the temperature to let the cookies spread more before setting
Reduce the amount of egg white (hard to do as I’m already at 1 egg, but I could add yolks and whites separately).
At this point, I posted the recipe to r/ketorecipes on Reddit and got additional suggestion to try a blend of erythritol and allulose (erythritol for crispier texture, but keep some allulose to mitigate “cooling effect”).
Round 1: Optimizing Texture
Based on the ideas above, I tried the following experiments:
All: I bought some Montezuma 100% cocoa chocolate from Trader Joe’s (surprisingly not bitter!) and used that in all recipes. I really l like the taste and texture it adds, particularly the contrast with the sweet taste of the cookie.
Reduced baking temperature and increased time (375 °F/11 min., 350 °F/13 min., 325 °F/15 min., 325 °F/16 min.)
Taste: no change
Texture: no significant change, maybe slightly less chewy…
Spread: no change
Conclusion: Original time/temp (375 °F/11 min.) is best
Went from 1 egg + 1 yolk to 2 yolk, plus added 10 g almond milk (needed to get dough to correct consistency)
Taste: creamier, less drying
Texture: slightly crispier
Spread: Much more spread during baking, similar to a regular cookie
Conclusion: Definite improvement in taste and I prefer the more spread out/thinner shape
Replace 50% of allulose with erythritol
Taste: no change (no perceptible cooling effect)
Texture: much crispier
Spread: no change
Conclusion: Much closer to my preferred texture
This was a big improvement in just a few tries and pretty close to what I wanted. I had originally planned to try out a bunch more variations (flour:fat & flour:protein ratio, amount of molasses, type of protein, etc.), but these were so good I decided to just combine the improvements and see if that did the trick.
Replaced whole egg with egg yolk and added almond milk. Improved taste and spread like a regular cookie. Still too chewy, thought.
Replaced half of allulose with erythritol. Crispier on the outside, but still chewy in the middle.
Round 2: Combining Changes & Low-Calorie Version
Based on the success of round 1, I made a batch combining all the improvements together. I also made a couple batches using yogurt and shredded coconut in place of the butter and chocolate to reduce calories.
2 egg yolk + 30 g almond milk + 50% erythritol
Taste: Fantastic, really tastes like a Nestle’s toll house cookie.
Texture: crispy on the edges, soft/chewy on the inside. I’d prefer a little crispier, but this is great.
Spread: Just like a regular chocolate chip cookie
Conclusion: Got the combined improvements from Round 1. While it could always improve, this was almost exactly what I was looking for.
Replace butter with yogurt & chocolate with shredded coconut. Removed almond milk (dough was already too “wet” before adding)
Calories: Drops from 106 to 36 calories/cookie
Taste: Not as good as the butter/chocolate version, but pretty good. Much “lighter”.
Texture: Way too “bready.” Must be an effect of the yogurt.
Spread: Much less
Conclusion: Ok for a first try, but the “bready” texture is a real problem. Will try less yogurt.
Same as above except half as much yogurt + 10g almond milk
Calories: Drops from 106 to 36 calories/cookie
Taste: Same. Not as good as the butter/chocolate version, but pretty good. Much “lighter”.
Texture: Back to normal. Crispy on the outside, chewy on the inside.
Spread: Still didn’t spread as much as the butter/chocolate cookie, but not a big deal.
Conclusion: This was great. I prefer the taste of the chocolate/butter based cookie, but I can eat a lot more of these. Will definitely make again.
All improvements combined (no egg whites, 50% erythritol, added almond milk). Taste, texture, and spread exactly how I want!Cross-section so you can see the crispier outside and chewy center.Goes great with almond milk!Low-calorie version with yogurt instead of butter and shredded coconut instead of chocolate. Almost as good and 1/3rd the calories.
My original plan was to do a whole bunch more batches with different substitutions and varying ratios, but I’m really happy with how these turned out. I might come back to this recipe in the future if I want to really dial it in or get a different effect, but for now I think I’ll leave it as is and start working on something else.
Hope you enjoy it,
– QD
Low-carb Adaptation of Nestle Toll House Cookies
QD
A low-carb adaptation of Nestle Toll House Cookies
Whisk together oat fiber, whey protein, baking soda, and salt.
Cream butter, allulose, erythritol, molasses, and vanilla with a stand or electric mixer.
Beat in egg yolk and almond milk, then slowly beat in oat fiber mixture, then fold in chopped chocolate.
Transfer to a lined baking sheet (I use a 1″ cookie scoop) and bake for 11 min.
Let cool on a wire rack, then serve.
Notes
0.9g net carbs per cookie.Nutrition information calculated by adding up macros of the individual ingredients. Allulose not included in the Total or Net carbs.Cookie dough can be frozen and stored for at least 1 month before baking.Unlike regular cookie recipes, this does not benefit from letting the dough rest in the refrigerator before baking (spreads less and doesn’t taste quite as good). If you don’t want to bake immediately, put the dough in the freezer.
Whisk together oat fiber, whey protein, baking soda, and salt.
Cream yogurt, allulose, erythritol, molasses, and vanilla with a stand or electric mixer.
Beat in egg yolk and almond milk, then slowly beat in oat fiber mixture and shredded coconut.
Transfer to a lined baking sheet (I use a 1″ cookie scoop) and bake for 11 min.
Let cool on a wire rack, then serve.
Notes
0.7g net carbs per cookie.
Nutrition information calculated by adding up macros of the individual ingredients. Allulose not included in the Total or Net carbs.
Cookie dough can be frozen and stored for at least 1 month before baking.Unlike regular cookie recipes, this does not benefit from letting the dough rest in the refrigerator before baking (spreads less and doesn’t taste quite as good). If you don’t want to bake immediately, put the dough in the freezer.
