Tag: self-experiments

Does Vinegar Really Lower Blood Glucose? If so, how? – Literature Survey & Pre-registration for an N=3 Community Experiment

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Summary

About a week ago a reader, /u/genetastic, reached out about collaborating on experiments to determine the effect of vinegar on blood glucose after meal consumption.

Like most of you, I had heard all the nigh-magical, pseudoscience claims about using apple cider vinegar to treat diabetes. However, when you dig into the literature, there’s a sizable number of peer-reviewed studies, including several decent meta-analyses, showing that consumption of vinegar with a meal can reduce the blood glucose impact in both diabetic and non-diabetic subjects (see background below for details). There’s also a lot of open questions, including:

  • Is the effect large enough to matter for practical meals?
  • What types of meals does vinegar affect?
  • What is the best protocol to get a large effect without unpleasant side effects?
  • What’s the underlying mechanism?
  • Is the effect specific to vinegar or do other acids work?

/u/genetastic, a third collaborator /u/kabong, and I decided to answer these questions with community self-experiment.

Below, I give more details on the background literature and pre-register our protocol and analyses.

It would significantly improve the study to have a larger number of participants. If you’re interested in collaborating on this or other scientifically rigorous self-experiments with low-carb foods, supplements, or other health interventions, please let me know in the comments or via the contact form on the right.

Details

Purpose

  • To replicate (or fail to replicate) the existing literature and quantify the effect of vinegar on blood glucose level after consumption of complex carbohydrates.
  • To better understand the underlying mechanism by determining how this effect varies with person/metabolic status, dose, source of calories, and type of acid.

Background

Link to list and summaries of literature reviewed

Over the past 20 years, several clinical trials have shown that consumption of vinegar with a meal can reduce the post-meal blood glucose concentration on both non-diabetic and diabetic patients. A meta-analysis of 11 high-quality studies showed a significant and systematic reduction in glucose and insulin area under the curve (see Figures 1 & 2).

Figure 1. Forest plot showing individual and pooled random effect standard mean difference (95% CI) of trials testing the effect of vinegar on glucose area under the curve. Test of overall effect: z = 2.42, p = 0.01.
Figure 2. Forest plot showing individual and pooled random effect standard mean difference (95% CI) of trials testing the effect of vinegar on insulin area under the curve. Test of overall effect: z = 3.73, p < 0.001.

Based on this, I believe that vinegar has an effect. However, there’s no clear consensus on how or why vinegar lowers blood glucose. Various mechanisms have been proposed, including:

  • Delayed gastric emptying
  • Increased glucose uptake by muscles
  • Inhibition of alpha-amylase, leading to slower breakdown of starches

I’m particularly intrigued by the work of the Le Feunteun group, that argues that the effect is not due to vinegar specifically, but rather reduced pH slowing the breakdown of starch by inhibiting the enzyme alpha-amylase. Supporting this claim:

One of the biggest challenges in the vinegar/acid literature is that all of the experiments were done with different meals, protocols, and doses, making it difficult to integrate data from multiple studies. To address this issue and answer some of the open questions about this effect, /u/genetastic, /u/kabong, and I decided to do a series of community self-experiments.

While we each have different motivations and interests, overall, the questions we’re looking to answer are:

  • Is the effect large enough to matter for practical meals?
  • What types of meals does vinegar affect?
  • What is the best protocol to get a large effect without unpleasant side effects?
  • What’s the underlying mechanism?
  • Is the effect specific to vinegar or do other acids work?

To answer these questions, we will be conducting experiments using the protocol below.

Methods

Materials

  • Meals:
    • white bread (starch)
    • dried dates (simple sugars)
    • tortilla with beans, salsa, & avocado (starch, fat, and protein)
  • Vinegar:
    • Apple cider or white vinegar
    • As large a quantity as comfortable, not to exceed 30g
    • Diluted in as little water as tolerable

Blinding

  • Vinegar supplementation will not be blinded
  • However, the protocol was established in advance and adhered to without modification once experiments started.

Procedure

  • Each participant is using a slightly different procedure
  • QD (u/sskaye):
    • Meals are eaten contemporaneously with vinegar or an equal amount of water at ~10:30a.
    • Blood sugar is monitored for 5h using a Dexcom G6, with calibration performed 15-30 min. before the start of each experiments.
    • Treatments are alternated daily V-/V+/W (V-: meal with no vinegar; V+: meal with vinegar; W: wash/no experiment.
  • u/genetastic:
    • Meals are eaten contemporaneously with vinegar between breakfast/lunch. CGM data is checked to make sure that BG is at baseline before a test.
    • Treatments are alternated daily with no wash period.
  • u/kabong:
    • Meals are eaten contemporaneously with vinegar.
    • Blood sugar is monitored for 3h using a Freestyle Libre, with calibration using a fingerstick meter.
    • Treatments are 3x per week, each at the end of a >24h fast.

Measurements

Analysis

  • Peak blood glucose, iAuC, and time to peak blood glucose will be calculated for each experiment
  • Student’s t-test will be used to test if the values for any of the above metrics were different with and without consumption of vinegar.
  • Additional exploratory analysis may be done based on the data, but will be noted as such

Data Processing & Visualization

iAUC will be calculated using the trapezoid method. Data will be visualized using Tableau.

Data

All data will be posted after analysis.

Results & Discussion

Results will be posted and discussed after the data is analyzed.

Conclusions & Next Experiments

Conclusions & next experiments will be posted after the data is analyzed.


– QD

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Weekly Update & Health Statistics: 9/12/21

I’m always looking for collaborators for future experiments. If you’re interested in collaborating on scientifically rigorous self-experiments with low-carb foods, supplements, or other health interventions, please let me know in the comments or via the contact form on the right.

I finally posted the results for low-carb breads this week. This was the most interesting of my prepared food studies so far. There was a huge variation in taste, texture, and BG impact and some mysteries that I’ll need to unravel (specifically, what’s going on with the resistant starches?).

Experiments this week focused on reader requests from the last few posts, including adding “control” foods for each category (regular, non-low carb versions). Some of the best tasting and lowest BG impact foods have come from comments, so please keep them coming!

Lastly, I’ll be kicking off a new study next week looking at the effect of acid on metabolism of macronutrients. Most readers have probably heard the BS around apple cider vinegar, but there’s a fair amount of peer-reviewed literature showing an effect of acids on blood glucose and metabolism (nothing magical, but measureable). There’s a fair amount of dispute around the mechanism, what types of macronutrients are affected, and whether it affects both diabetics and non-diabetics. A reader reached out to me about collaborating to test the effect, so we’re going to try to sort it out (keeping anonymous until/unless I’m given permission to name). We’re finalizing the protocol, after which I’ll post on our literature review, pre-registration of protocol and analysis, and then results when we have them.

Active & Planned Experiments

  • Blood Glucose Impact of Low-Carb Foods
    • Goal: Determine blood glucose impact of low-carb foods and ingredients
    • Approach: Protocol
    • Status:
      • This week: 4 commenter requests (Two Good yogurt, Julian Bakery bread, and “control” tortillas & ice cream (non-low carb, for comparison)) and 3 chocolates.
      • Reported:
      • Up next:
        • Commenter requests (9/18)
        • Chocolate (9/25)
  • Blood Glucose Impact of Supplements
    • Goal: Determine blood glucose impact and mechanism of promising supplements
    • Approach: tbd
    • Status:
      • This week: literature review, determining protocol
      • Reported:
        • Nothing yet
      • Up next:
        • Literature review (9/18)
        • Pre-registration of protocol and analyses (9/18)
  • Methods of Sleeping Longer

Let me know in the comments if there’s any other experiments you’d like to see.


– QD

Observations & Data

Continue reading “Weekly Update & Health Statistics: 9/12/21” →

Weekly Health Statistics: 7/11 – 7/17/21

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For those checking the dates, I post these with a 1-week lag. 

Summary:

What I’m tracking

  • Sleep: 
    • Metrics: total time, heart rate variability, pulse (sleeping vs. waking)
    • Method: Apple watch + Autosleep app
    • Frequency: daily
  • Blood glucose:
    • Metrics: fasting BG, Avg. BG, coefficient of variation, time 70-140 mg/dL, time <60 mg/dL
    • Method: Dexcom G6 CGM
    • Frequency: continuous
  • Body:
    • Metrics: weight, waist circumference, BMI, waist/height
    • Method: scale + Renpho tape measure
    • Frequency: weekly
  • Other blood:
    • Metrics: hemoglobin, cholesterol, blood pressure, pulse
    • Method: Hemocue 801, Cardiocheck PA, Omron 10
    • Frequency: weekly for blood pressure & pulse, every 2 weeks for hemoglobin & cholesterol

Observations

  • Sleep:
    • This was the first week of my sleep experiment, so in addition to the metrics automatically tracked by my watch, I’m noting down any time I wake up in the middle of the night.
    • Despite the fact that all the auto-tracked metrics looked good, I was waking up much more frequently in the middle of the night and feeling more tired. This suggests the auto-tracked metrics are not a great measure of overall sleep quality.
    • I need to do a more detailed analysis to figure out what’s going on here…
  • Blood glucose:
    • All stats back to normal after last week’s travel. 
    • Time 70-140 mg/dL still could be a bit better. Will continue to cut back on insulin at meals.
  • Body:
    • Still seeing steady drop in weight and waistline. I’m very happy with my progress here. 
  • Blood:
    • Switching to every other week measurement for cholesterol and hemoglobin to reduce tracking burden. Will increase frequency if I’m doing any experiments that might cause them to change.
    • Blood pressure was much higher than normal this week. I ate an unusual dinner last night and had higher than normal BG, so might just be an outlier. Will keep an eye on this and see if it persists.

Active & Planned Experiments

  • Comprehensive bloodwork:
    • Goal: Establish baseline for a broad range of biomarkers and check overall health
    • Approach: WellnessFX Premium panel
    • Status: Got the results, need to analyze and write up.
  • Testing methods of sleeping longer:
    • Goals:
      • To determine if taking melatonin supplements in the evening extends the duration of my time asleep and subjective fatigue given a consistent bedtime.
      • To determine if taking melatonin supplement and/or sleeping longer affects subjective fatigue, blood glucose, heart rate variability, or pulse
    • Approach: here
    • Status: Week 1 complete

Data:

Blood

Body

Sleep

Methods:

Measurements: See summary section above

Data Processing & Visualization. Data was visualized using Tableau.

Data: here


– QD

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Weekly Health Statistics: 7/4 – 7/10/21

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For those checking the dates, I’m posting these with a 1-week lag. 

Summary:

What I’m tracking

  • Sleep: 
    • Method: Apple watch + Autosleep app
    • Metrics: total time, heart rate variability, pulse (sleeping vs. waking)
  • Blood glucose:
    • Method: Dexcom G6 CGM
    • Metrics: fasting BG, Avg. BG, coefficient of variation, time 70-140 mg/dL, time <60 mg/dL
  • Body:
  • Other blood:
  • Urine:
    • Method: Vessel
    • Metrics: biotin, ketones, pH, vitamin C, magnesium, hydration, & cortisol

Observations

  • Sleep:
    • Sleep improved again this week, despite traveling Monday-Wednesday and I continue to feel much better/less tired than before I started going to bed at a consistent time.
    • Still noticing that I’m waking up earlier than preferred, though it’s not always showing up in the data (probably b/c I stay in bed trying to go back to sleep). I’m starting an experiment this week to test ways to stay asleep longer, so I’ll need to make sure I measure wake-up time correctly.
  • Blood glucose:
    • Fasting BG spiked up this week, likely due to travel Monday-Wednesday. I ate much later those days (8p vs. normally 5p), which led to a higher fasting BG. 
    • Rest of BG stats were ok, but not great, again likely related to traveling and less controlled meals.
  • Body:
    • Still seeing steady drop in weight and waistline. I’m very happy with my progress here. 
  • Blood:
    • Hemoglobin in dead center of normal. Starting to look like those high points were anomalies.
    • Cholesterol (total, LDL, and HDL) looks like it’s holding steady. Numbers are decent, but could be better. I may target this for intervention after my sleep study.
    • Blood pressure seems to be trending down. Will keep an eye on.
  • Urine:
    • Nothing interesting in this data. My values for biotin, pH, & Vitamin C are outside of the “normal” range, but I haven’t been able to find any literature indicating that this is even correlated with medical issues I would be concerned about.
    • In 6 tests, I’ve only gotten a reading on cortisol three times. That measurements seems to be extremely unreliable.
    • All-in-all, I’m not getting much value out of the vessel tests. I’ve finished out the pack I bought and won’t be continuing these stop.

Active & Planned Experiments

  • Comprehensive bloodwork:
    • Goal: Establish baseline for a broad range of biomarkers and check overall health
    • Approach: WellnessFX Premium panel
    • Status: Got the results, need to analyze and write up.
  • Testing methods of sleeping longer:
    • Goal: Determine interventions that will enable me to stay asleep longer
    • Approach: Melatonin?, will ask in several forums to get suggestions
    • Status: posting in forums this week

Data:

Urine

Blood

Body

Sleep

Methods:

Measurements: 

Data Processing & Visualization. Data was visualized using Tableau.

Data: here


– QD

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Melatonin to Stay Asleep Longer: Protocol & Pre-registered Analyses

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Summary

I’m trying to sleep longer, but am waking up too early in the morning. I’m going to test if melatonin can help me sleep longer. Based on suggestions solicited from the ACX open thread, I’m going to try a 30 day, blinded, randomized trial of 0.3 & 3 mg melatonin, both regular and extended release. If I see anything promising from this initial test, I’ll repeat the trial with the best condition to confirm and get a better measure of effect size.

Details

Purpose

  • To determine if taking melatonin supplements in the evening extends the duration of my time asleep and subjective fatigue given a consistent bedtime.
  • To determine if taking melatonin supplement and/or sleeping longer affects subjective fatigue, blood glucose, heart rate variability, or pulse

Background

Over the past 5 weeks, I’ve been making an effort to get more sleep. I’ve been able to hit an average time asleep of ~7h and, qualitatively, I’ve been feeling a lot less tired and have been able to concentrate better in the afternoons.  

I’d like to see if sleeping even longer will result in further improvement. However, over the last week I’ve noticed that I’ve been waking up earlier and earlier (before my morning alarm). I stay in bed (eyes closed) until the alarm, but can’t go back to sleep.

Based on my data so far, there’s no clear correlation with time I fell asleep or total time asleep. Might be a correlation with heart rate variability, but I need more data to be sure.

I’d like to test some interventions to sleep longer. I already exercise in the evenings and for as long as I’m willing to do (~30 min. high intensity, 5-10 min. stretching), my last meal is 4h before going to bed, and my CGM does not show a consistent rise in blood sugar before waking up.

Given that, my next thought was to try melatonin. It’s typically used to control when you go to sleep, but it last long enough in the bloodstream that it might impact time asleep as well. Based on suggestions solicited from the ACX open thread, I’m going to try a 30 day, blinded, randomized trial of 0.3 & 3 mg melatonin, both regular and extended release. If I see anything promising from this initial test, I’ll repeat the trial with the best condition to confirm and get a better measure of effect size.

Methods

Materials

Blinding

  • Melatonin was placed in opaque, size 000 gel capsules (6 per type).
  • Dosages were randomly assigned to days using the excel random number generator and placed into a coded pill container by a second person (not me). 
  • Data will be unblinded after the completion of the experiment.

Procedure

  • At 9pm, I will take that days gel capsule with minimal water.
  • At 9:30pm, I will turn lights off and attempt to go to sleep.
  • I will record:
    • If I wake up during the night
    • Subjective tiredness (1-3 scale) upon arising and at 3p
    • If any other unusual events occur

Measurements

Analysis

  • Sleep time, wake time, total time asleep, number of times waking up before alarm, fasting blood glucose, time of morning blood glucose rise, pulse, and HRV will be plotted vs. dose and release type. 
  • p-values will be calculated for each comparison and corrected for multiple-comparison
  • Additional exploratory analysis may be done based on the data, but will be noted as such

Data Processing & Visualization

Data was exported from Autosleep, reformatted using a custom python script, and visualized using Tableau. Wake times were corrected manually using contemporaneous notes (see measurements, above).

Data

All data will be posted after it is unblinded.

Results & Discussion

Results will be posted and discussed after the data is unblinded and analyzed.

Conclusions & Next Experiments

Conclusions & next experiments will be posted after the data is unblinded and analyzed.


– QD

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