I use stevia as a replacement for sugar. This research is difficult to understand for a layperson like me (I'm too thick). Is anyone able to answer the questions below?
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Extract: "non-nutritive sweeteners (NNS), such as saccharin, sucralose, aspartame, acesulfame-K, and stevia, that do not contain calories and are thereby presumed to be inert and not elicit a postprandial glycemic response."
Question: Does this research confirm that stevia elicits a postprandial glycemic response? (Does stevia stimulate insulin?).
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Extract: "Notably, all four tested NNS (saccharin, sucralose, aspartame, and stevia) significantly and distinctly altered the human intestinal and oral microbiome, as would be expected for these chemically diverse compounds."
Extract: "Degradation of steviol glycosides by gut bacteria is an established component of their metabolism although some species may be more proficient than others in performing this task and thus, pre-exposure microbiome heterogeneity may conduce to differential responses to stevia."
Question: So stevia alters the human intestinal and oral microbiome. Are these changes a negative outcome and thus a concern for anyone using stevia?
From what I've read about postprandial glucose levels, the question seems less about whether or not something elicits a glycemic response, but by how much and how that compares to glucose/fructose.
Another useful measure would be comparing satiation after consumption of sugar vs non-caloric sweeteners, to determine if the significant drop in calories leads to more food ingested overall.
Stevia in particular seems to be one of the lesser studied sweeteners, based on a handful of papers postprandial glucose levels doesn't seem to differ a lot compared to sugar. But there seem to be somewhat consistent findings that satiety levels remain largely the same given the same mass of ingested food ( e.g. [0][1]).
To your second question, from my view the understanding of the human microbiome is still rather poor, especially in terms of health implications on various physiological systems (including neurological), optimal composition and applicable ways to maintain it. Although the last time I checked was probably 1-2 years ago, if anyone is aware of useful new data here I would welcome a link.
You can go down a rabbit hole with the references in this paper - I think a generally interested layperson is definitely capable of understanding papers like this. My instinct is that the hardest to understand papers are often actually so special-area related that those papers don't contain useful information except for researchers. So you can skip them.
Don't know about the second question and suspect no one else does either.
As an aside - how did you manage that transition to stevia? I despise non-sugar sweeteners and can detect them in very small amounts. For "reasons" I don't eat meat and I supplement protein intake with whey. If it wasn't for a small number of high-quality unflavored (and thus lacking artificial sweeteners) whey isolates I would probably re-introduce meat into my diet.
Not answering your questions directly, but it has been known for decades that fake sugars (NNS in the abstract) cause weight gain.
Since you asked about insulin response; (some?) artificial sweeteners seem to be safe for diabetics. There is no other group of people I can think of that should consider using these products.
On a somewhat related note, the soft drink industry has replaced some "diet" drinks with "light" versions that contain sugar and NNS.
I've found that this causes (intentional?) confusion, especially at restaurants, and multiple servers have inadvertently tried to serve our kids that stuff when we ordered things like "lemonade".
In addition to all the above, consuming NNS causes migraines for some people, and they interact badly with some medications. I disagree with the abstract's use of the term "presumed inert", but I suppose they are trying to be diplomatic.
While it does not address the root question, one benefit of sugar substitutes is that they are many times sweeter than sugar: stevia is 200-300x sweeter, resulting in less total mass consumed. My hopelessly-naive-because-biology thought is that each molecule would be metabolized a single time (by your own liver or your microbiome), resulting in less total impact on your body.
> Notably, all four tested NNS (saccharin, sucralose, aspartame, and stevia) significantly and distinctly altered the human intestinal and oral microbiome, as would be expected for these chemically diverse compounds.
But also:
> Non-nutritive sweeteners (NNS) are commonly integrated into human diet and presumed to be inert
So they are presumed to be inert, but also significantly alter microbiome, as would be expected since they are chemically diverse compounds.
They indicate it should be obvious that they are not inert at the same time as they are presumed to be inert? And if it's obvious that they are not inert then why are there so many unanswered questions while they're still allowed into our food system? Is it unreasonable to expect that some newly popular food additive is properly studied before it stats to gain massive adoption in prepared foods?
The assertion of them being "inert" is probably in terms of interaction with the human metabolism. That is likely what is studied when deciding if a compound is safe for ingestion.
What you are calling out is the wider impact to our internal ecology and that is s much more complex thing to measure and something that we are only beginning to understand. There are no regulatory frameworks that take that into account.
A glance suggests that Saccharine and Sucralose may be problematic. The others may be “complicated” but the effect also looks close to noise. They should have included some non-sweetener molecules of a similar nature as controls.
Sucralose was an instant no to me when I saw the molecule. “Here let’s hang a chlorine off this here sugar.” Nope. I recall seeing similar sentiments in a thread over at Reddit where a biochemist remarked that it looked like a pesticide.
The weird complicated molecules in Stevia and Monk Fruit seem safe precisely because they look like something the body is going to hack apart right away and look like all the other complicated molecules found in plants that the body is used to dealing with. Things like blueberries and onions are just loaded with random baroque carbon sculptures like this.
> Sucralose was an instant no to me when I saw the molecule. “Here let’s hang a chlorine off this here sugar.” Nope. I recall seeing similar sentiments in a thread over at Reddit where a biochemist remarked that it looked like a pesticide.
If you could infer the properties of a compound by making vague analogies to other similar looking molecules, chemistry would be easy. Changing a single atom can completely change the safety properties of a compound, ie. H2O->H2O2, Hg2Cl2->HgCl2.
> The weird complicated molecules in Stevia and Monk Fruit seem safe precisely because they look like something the body is going to hack apart right away and look like all the other complicated molecules found in plants that the body is used to dealing with.
Yeah, like the atropa belladonna, the deadly nightshade? I'm sure that's chock full of "baroque carbon sculptures". Maybe biochemistry just isn't so easy.
As someone that is relying on a single high school chemistry class as a base of knowledge, why would Cl here give you pause? In other words why is the Cl here bad, but ok in say salt?
you can't just read a molecule and say "oh it looks like something safe". Digitalin and the cardiac glycosides [1a,1b] may look like completely innocuous compounds (just have to remove a group and they are inactive). Some hormones look like cholesterol. Some steroisomers [2] (think of it as just changing the order atoms are connected in space but not what they are connected to) of molecules kill you while some other forms are safe and that's even harder to grasp on a 2d representation of the structure.
Isn’t bleach just a water molecule with an extra oxygen atom? I’m not a chemist but I didn’t think you could make assumptions about the effect of a substance in the way you describe. Am I missing something?
Everyone always with this "noise"! Of course there is noise! They are looking at the "noise" and telling you what it is from! Genetics!
If you average any trial out in a large population there will be "noise", but these people who live with the "noise" are the ones affected and suffering.
Does everyone have microbiome-driven effects of non-nutritive sweeteners? Probably not, but what about the ones that do?
By messing with part of the fructose transport mechanisms sugar alcohols are messing with the microbiome so likely would have stood out. There is a reason at least here there are labels warning of too much consumption.
Microbiome researcher here - I feel like this is the time I get to shine in HN threads.
The Segal and Elinav labs are powerhouses in computational and gnotobiotic microbiome study. They've published several highly cited papers around interactions between diet, the microbiome, and various host parameters. A couple highlights include this [1] 2015 Cell paper predicting host glycemic response from microbial and dietary information, and this [2] 2014 Nature paper identifying artificial sweeteners as a source of glucose intolerance (mediated through the microbiome).
In the current work, they show that two non-nutritive sweeteners (NNS, saccharin and sucralose) impair glucose tolerance, and that the microbiome of individuals most susceptible to NNS-induced glucose-intolerance can transmit some of the phenotype to mice. These data are generated with human cohorts of good size (n=20 per sweetener) over a reasonable time frame (2 weeks of daily NNS administration). Importantly, the levels of NNS that are administered are well below the acceptable daily intake (ADI). For example, sucralose is given at 102 mg/day, about 34% of the ADI of 5 mg/kg, and reasonably close to an estimate of 1.6 mg/kg as average daily consumption in humans (reference in [3]). The strongest data for the paper is with sucralose (and saccharin). The researchers show that consumption of sucralose causes a shift in glycemic response: participants consuming sucralose had higher glucose excursion in a glucose tolerance test (GTT) than those consuming either control diet (Fig 2A, E, F). In addition to GTT changes, sucralose-consuming participants had altered level of 9 identified metabolites (Fig 4B-D).
After establishing these baseline results, the researchers search for mechanism by stratifying the sucralose cohort in the top and bottom responders. These are, respectively, the individuals who show most change from baseline in GTT at the end of intervention (2 weeks) and those that show the least. There are differences in metabolites, as well as the biochemical pathways those metabolites come from (TCA cycle) in these two groups (Fig 4E, F). There are correlations between changes in the microbiome (both specific taxa and functional gene categories) and the changes in measured metabolite levels as well (Fig 5).
In figure 6, the researchers present their strongest data. The researchers inoculate groups of germ-free mice with fecal samples from the sucralose participants from either the baseline or end of intervention. 4 groups of mice receive the feces of the top 1-4 responders (most perturbed GTT), 3 groups receive feces from the bottom 1-3 responders, and each of these is compared to a group receiving baseline feces. The purpose of this test is to see if the microbiome, altered by sucralose administration, can cause impaired glucose tolerance in mice that have never been exposed to sucralose. The researchers show that indeed there is significant glucose-tolerance impairment in mice that receive post-sucralose feeding feces, though interetingly they show that both bottom- and top-responder feces causes this (Fig 6A, G). They show that baseline samples from bottom- and top-responders do not cause differences in glucose tolerance (Fig 8C), showing that something about the sucralose treatment changes microbial composition to promote glucose intolerance. The researchers attempt to find a mechanistic explanation for the differences by comparing groups of mice colonized with top- and bottom-responder (grouped by baseline or end of intervention) feces.
Ultimately, this is an extremely impressive paper representing a lot of work (and many storied I haven't recapped). Like many microbiome papers, I think it oversells the mechanistic and physiologically relevant aspects of the research.
1. The data is presented in ways that maximize statistical significance with very little reference to the scale of the actual change.
a. Fig 4 B-D and Fig 5 B, D, F show significant metabolite differences but give no reference to actual changes in blood concentration (also Fig 5 metabolites not significant after FDR correction). Without isotope-dilution mass spectrometry (which this is not), it's hard to tell how large the changes are in the blood metabolites. The relationship between concentration of a metabolite and measured area on a mass spec is a power function (for different metabolites exponents can be less or greater than 1), and so this data may represent a lot of change in concentration or very little. In addition, the authors rely on GTT differences to tell the story, but what is the scale of these changes? It is not clear that there is physiological relevance to this scale of change.
b. Many of the metrics used are hard to relate to physiologically relevant quantities and allow researcher degrees of freedom. As an example Fig 3 ordinates the participant samples using a principal components projection of the microbial gene annotations. The loadings determining the ordination - and selected for highlight are shown in Fig 3 G-J. The researchers group several of these loadings into super pathways (e.g. purine metabolism) but it's very hard to tell if this kind of difference reflects a functional capacity change in the microbiome (and certainly gives no data about the actual transcription of these genes). Any of these groupings could be highlighted, allowing a lot of flexibility in the storytelling with no penalization for multiple hypotheses.
c. Fig 8J "Spearman correlation of sucrose degradation pathway fold change abundance (day 21/baseline) with fold difference in GTT-AUC of each of the conventionalized mouse groups." This is so far away from physiology it's hard to say what it means.
2. Both Eran Segal and Eran Elinav are co-founders of the company DayTwo - a personalized microbiome company that helps diabetics manage their symptoms with microbiome based analytics and treatments. The paper feels like it explores the 'personalization angle' and the expense of other mechanistic studies. For example, the importance of osmolarity on the microbiome and how phenotypes around osmostress might be contributing to the resulting host phenotypes.
Anecdotally, as a type 1 diabetic it’s very interesting to observe different effects of sugars and sweeteners on my continuous blood glucose sensor over time.
For example DASH is a zero-calorie but sweet drink I have tried a couple of times and it makes my body chart a course for the moon.
Another drink called Gusto seems to have replaced sugars with Agave syrup, which works well at first but after several days builds up intolerance or something.
Modern regular orange juice is like a load of TNT with a 4 minute fuse.
Recently white wine and sparkling white wine instantly start making my sugar readings hop around erratically, moment by moment. (Not something I saw before about 4 months ago - before that it would be more like a steady incline.
The disruptors have made their way over to food and drink, it seems.
Somewhat unrelated to the article: I am a LADA diabetic (Latent Autoimmune Diabetes in Adults, sometimes referred to as Type 1.5). I am insulin dependent, but I didn't become symptomatic until my early 40s.
Lately, I have been experimenting with the "grazing diet". Instead of eating three meals a day one would eat a dozen or more really small meals; basically snacks.
The motivation was that the glucose response profile of my insulin was poorly matched with the glucose response profile of the foods I eat. My insulin (Humalog), has a profile lasting three to four hours, while most of my foods have a much shorter profile, some with a profile of an hour or less. By spreading my carbohydrate intake over more time I get a better match to my insulin response. For example, I spend two or more hours eating lunch. So far, it seems to be helping noticeably.
have you ever tested diet soda with the various artificial sweeteners? I've tried it personally and never seen the slightest notch above what would random noise whereas sugar is "straight to the moon, lois" a half hour to hour later.
vanilla-almond|3 years ago
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Extract: "non-nutritive sweeteners (NNS), such as saccharin, sucralose, aspartame, acesulfame-K, and stevia, that do not contain calories and are thereby presumed to be inert and not elicit a postprandial glycemic response."
Question: Does this research confirm that stevia elicits a postprandial glycemic response? (Does stevia stimulate insulin?).
---
Extract: "Notably, all four tested NNS (saccharin, sucralose, aspartame, and stevia) significantly and distinctly altered the human intestinal and oral microbiome, as would be expected for these chemically diverse compounds."
Extract: "Degradation of steviol glycosides by gut bacteria is an established component of their metabolism although some species may be more proficient than others in performing this task and thus, pre-exposure microbiome heterogeneity may conduce to differential responses to stevia."
Question: So stevia alters the human intestinal and oral microbiome. Are these changes a negative outcome and thus a concern for anyone using stevia?
kekebo|3 years ago
From what I've read about postprandial glucose levels, the question seems less about whether or not something elicits a glycemic response, but by how much and how that compares to glucose/fructose.
Another useful measure would be comparing satiation after consumption of sugar vs non-caloric sweeteners, to determine if the significant drop in calories leads to more food ingested overall.
Stevia in particular seems to be one of the lesser studied sweeteners, based on a handful of papers postprandial glucose levels doesn't seem to differ a lot compared to sugar. But there seem to be somewhat consistent findings that satiety levels remain largely the same given the same mass of ingested food ( e.g. [0][1]).
To your second question, from my view the understanding of the human microbiome is still rather poor, especially in terms of health implications on various physiological systems (including neurological), optimal composition and applicable ways to maintain it. Although the last time I checked was probably 1-2 years ago, if anyone is aware of useful new data here I would welcome a link.
[0] https://sci-hub.ee/10.3390/nu11123036
[1] https://sci-hub.ee/https://www.sciencedirect.com/science/art...
clusterhacks|3 years ago
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7103435/#:~:tex....
You can go down a rabbit hole with the references in this paper - I think a generally interested layperson is definitely capable of understanding papers like this. My instinct is that the hardest to understand papers are often actually so special-area related that those papers don't contain useful information except for researchers. So you can skip them.
Don't know about the second question and suspect no one else does either.
As an aside - how did you manage that transition to stevia? I despise non-sugar sweeteners and can detect them in very small amounts. For "reasons" I don't eat meat and I supplement protein intake with whey. If it wasn't for a small number of high-quality unflavored (and thus lacking artificial sweeteners) whey isolates I would probably re-introduce meat into my diet.
hedora|3 years ago
Since you asked about insulin response; (some?) artificial sweeteners seem to be safe for diabetics. There is no other group of people I can think of that should consider using these products.
On a somewhat related note, the soft drink industry has replaced some "diet" drinks with "light" versions that contain sugar and NNS.
I've found that this causes (intentional?) confusion, especially at restaurants, and multiple servers have inadvertently tried to serve our kids that stuff when we ordered things like "lemonade".
In addition to all the above, consuming NNS causes migraines for some people, and they interact badly with some medications. I disagree with the abstract's use of the term "presumed inert", but I suppose they are trying to be diplomatic.
41b696ef1113|3 years ago
tejohnso|3 years ago
> Notably, all four tested NNS (saccharin, sucralose, aspartame, and stevia) significantly and distinctly altered the human intestinal and oral microbiome, as would be expected for these chemically diverse compounds.
But also:
> Non-nutritive sweeteners (NNS) are commonly integrated into human diet and presumed to be inert
So they are presumed to be inert, but also significantly alter microbiome, as would be expected since they are chemically diverse compounds.
They indicate it should be obvious that they are not inert at the same time as they are presumed to be inert? And if it's obvious that they are not inert then why are there so many unanswered questions while they're still allowed into our food system? Is it unreasonable to expect that some newly popular food additive is properly studied before it stats to gain massive adoption in prepared foods?
Tagbert|3 years ago
What you are calling out is the wider impact to our internal ecology and that is s much more complex thing to measure and something that we are only beginning to understand. There are no regulatory frameworks that take that into account.
api|3 years ago
Sucralose was an instant no to me when I saw the molecule. “Here let’s hang a chlorine off this here sugar.” Nope. I recall seeing similar sentiments in a thread over at Reddit where a biochemist remarked that it looked like a pesticide.
The weird complicated molecules in Stevia and Monk Fruit seem safe precisely because they look like something the body is going to hack apart right away and look like all the other complicated molecules found in plants that the body is used to dealing with. Things like blueberries and onions are just loaded with random baroque carbon sculptures like this.
naasking|3 years ago
If you could infer the properties of a compound by making vague analogies to other similar looking molecules, chemistry would be easy. Changing a single atom can completely change the safety properties of a compound, ie. H2O->H2O2, Hg2Cl2->HgCl2.
> The weird complicated molecules in Stevia and Monk Fruit seem safe precisely because they look like something the body is going to hack apart right away and look like all the other complicated molecules found in plants that the body is used to dealing with.
Yeah, like the atropa belladonna, the deadly nightshade? I'm sure that's chock full of "baroque carbon sculptures". Maybe biochemistry just isn't so easy.
balderdash|3 years ago
ta988|3 years ago
[1a] https://en.m.wikipedia.org/wiki/Cardiac_glycoside
[1b] https://en.m.wikipedia.org/wiki/Steroid
[2] https://en.m.wikipedia.org/wiki/Enantiopure_drug
seanhandley|3 years ago
GekkePrutser|3 years ago
matheusmoreira|3 years ago
FollowingTheDao|3 years ago
If you average any trial out in a large population there will be "noise", but these people who live with the "noise" are the ones affected and suffering.
Does everyone have microbiome-driven effects of non-nutritive sweeteners? Probably not, but what about the ones that do?
hombre_fatal|3 years ago
stjohnswarts|3 years ago
anjel|3 years ago
heisenbit|3 years ago
bloaf|3 years ago
[1] https://en.wikipedia.org/wiki/Psicose
https://pubmed.ncbi.nlm.nih.gov/32708827/
mirekrusin|3 years ago
wdwvt1|3 years ago
The Segal and Elinav labs are powerhouses in computational and gnotobiotic microbiome study. They've published several highly cited papers around interactions between diet, the microbiome, and various host parameters. A couple highlights include this [1] 2015 Cell paper predicting host glycemic response from microbial and dietary information, and this [2] 2014 Nature paper identifying artificial sweeteners as a source of glucose intolerance (mediated through the microbiome).
In the current work, they show that two non-nutritive sweeteners (NNS, saccharin and sucralose) impair glucose tolerance, and that the microbiome of individuals most susceptible to NNS-induced glucose-intolerance can transmit some of the phenotype to mice. These data are generated with human cohorts of good size (n=20 per sweetener) over a reasonable time frame (2 weeks of daily NNS administration). Importantly, the levels of NNS that are administered are well below the acceptable daily intake (ADI). For example, sucralose is given at 102 mg/day, about 34% of the ADI of 5 mg/kg, and reasonably close to an estimate of 1.6 mg/kg as average daily consumption in humans (reference in [3]). The strongest data for the paper is with sucralose (and saccharin). The researchers show that consumption of sucralose causes a shift in glycemic response: participants consuming sucralose had higher glucose excursion in a glucose tolerance test (GTT) than those consuming either control diet (Fig 2A, E, F). In addition to GTT changes, sucralose-consuming participants had altered level of 9 identified metabolites (Fig 4B-D).
After establishing these baseline results, the researchers search for mechanism by stratifying the sucralose cohort in the top and bottom responders. These are, respectively, the individuals who show most change from baseline in GTT at the end of intervention (2 weeks) and those that show the least. There are differences in metabolites, as well as the biochemical pathways those metabolites come from (TCA cycle) in these two groups (Fig 4E, F). There are correlations between changes in the microbiome (both specific taxa and functional gene categories) and the changes in measured metabolite levels as well (Fig 5).
In figure 6, the researchers present their strongest data. The researchers inoculate groups of germ-free mice with fecal samples from the sucralose participants from either the baseline or end of intervention. 4 groups of mice receive the feces of the top 1-4 responders (most perturbed GTT), 3 groups receive feces from the bottom 1-3 responders, and each of these is compared to a group receiving baseline feces. The purpose of this test is to see if the microbiome, altered by sucralose administration, can cause impaired glucose tolerance in mice that have never been exposed to sucralose. The researchers show that indeed there is significant glucose-tolerance impairment in mice that receive post-sucralose feeding feces, though interetingly they show that both bottom- and top-responder feces causes this (Fig 6A, G). They show that baseline samples from bottom- and top-responders do not cause differences in glucose tolerance (Fig 8C), showing that something about the sucralose treatment changes microbial composition to promote glucose intolerance. The researchers attempt to find a mechanistic explanation for the differences by comparing groups of mice colonized with top- and bottom-responder (grouped by baseline or end of intervention) feces.
Ultimately, this is an extremely impressive paper representing a lot of work (and many storied I haven't recapped). Like many microbiome papers, I think it oversells the mechanistic and physiologically relevant aspects of the research.
1. The data is presented in ways that maximize statistical significance with very little reference to the scale of the actual change. a. Fig 4 B-D and Fig 5 B, D, F show significant metabolite differences but give no reference to actual changes in blood concentration (also Fig 5 metabolites not significant after FDR correction). Without isotope-dilution mass spectrometry (which this is not), it's hard to tell how large the changes are in the blood metabolites. The relationship between concentration of a metabolite and measured area on a mass spec is a power function (for different metabolites exponents can be less or greater than 1), and so this data may represent a lot of change in concentration or very little. In addition, the authors rely on GTT differences to tell the story, but what is the scale of these changes? It is not clear that there is physiological relevance to this scale of change. b. Many of the metrics used are hard to relate to physiologically relevant quantities and allow researcher degrees of freedom. As an example Fig 3 ordinates the participant samples using a principal components projection of the microbial gene annotations. The loadings determining the ordination - and selected for highlight are shown in Fig 3 G-J. The researchers group several of these loadings into super pathways (e.g. purine metabolism) but it's very hard to tell if this kind of difference reflects a functional capacity change in the microbiome (and certainly gives no data about the actual transcription of these genes). Any of these groupings could be highlighted, allowing a lot of flexibility in the storytelling with no penalization for multiple hypotheses. c. Fig 8J "Spearman correlation of sucrose degradation pathway fold change abundance (day 21/baseline) with fold difference in GTT-AUC of each of the conventionalized mouse groups." This is so far away from physiology it's hard to say what it means.
2. Both Eran Segal and Eran Elinav are co-founders of the company DayTwo - a personalized microbiome company that helps diabetics manage their symptoms with microbiome based analytics and treatments. The paper feels like it explores the 'personalization angle' and the expense of other mechanistic studies. For example, the importance of osmolarity on the microbiome and how phenotypes around osmostress might be contributing to the resulting host phenotypes.
[1] https://www.sciencedirect.com/science/article/pii/S009286741... [2] https://www.nature.com/articles/nature13793?tdc_uid=921043 [3] https://foodinsight.org/everything-you-need-to-know-about-su...
clearwind|3 years ago
For example DASH is a zero-calorie but sweet drink I have tried a couple of times and it makes my body chart a course for the moon.
Another drink called Gusto seems to have replaced sugars with Agave syrup, which works well at first but after several days builds up intolerance or something.
Modern regular orange juice is like a load of TNT with a 4 minute fuse.
Recently white wine and sparkling white wine instantly start making my sugar readings hop around erratically, moment by moment. (Not something I saw before about 4 months ago - before that it would be more like a steady incline.
The disruptors have made their way over to food and drink, it seems.
inetsee|3 years ago
Lately, I have been experimenting with the "grazing diet". Instead of eating three meals a day one would eat a dozen or more really small meals; basically snacks.
The motivation was that the glucose response profile of my insulin was poorly matched with the glucose response profile of the foods I eat. My insulin (Humalog), has a profile lasting three to four hours, while most of my foods have a much shorter profile, some with a profile of an hour or less. By spreading my carbohydrate intake over more time I get a better match to my insulin response. For example, I spend two or more hours eating lunch. So far, it seems to be helping noticeably.
stjohnswarts|3 years ago
ohiovr|3 years ago
edwnj|3 years ago