Zone Diet Paradigm Difference

The ketogenic diet (for the control/reversal of diabetes) is based on the notion that excessive consumption of carbs leads to Insulin Resistance which is the basis of diabetes. Thus, reducing carbohydrates results in a reversal of diabetes because it improves Insulin Sensitivity (ie, it decreases Insulin Resistance).

The author of the Zone Diet agrees that Insulin Resistance is the core issue in weight loss but disagrees with the cause of Insulin Resistance. From (Insulin Resistance and Weight Loss. Dr. Sears. Apr 6, 2018):

It is constantly elevated insulin levels that makes you gain weight, and keep the weight on. The reason is that if the muscle cells are not taking in enough glucose from the blood, the increased insulin levels drive that glucose into the fat cells instead and that accelerates the storage of dietary excess calories as stored fat. This makes you gain weight. Furthermore, these increased insulin levels prevent your fat cells from releasing stored fat to be used as energy for the body. This keeps the weight on.

Agreed. And, that is the premise of the ketogenic diet as well.

Insulin is a hormone that helps regulate the amount of glucose, a breakdown product of carbohydrates, in our blood required for optimal brain function as well controlling enzyme activities, gene expression and the distribution and storage of energy.

Here Dr Sears shows a common but fundamental misconception about the role of dietary carbohydrates. Carbohydrates are not required to produce glucose. The liver can produce more than enough glucose in the liver though Gluconeogenesis (GNG) from other substrates such as body fat. If dietary carbohydrates were required then the blood sugar during fasting would not level out – which it does.

To be fair, I assume Dr Sears knows better.

So What’s the Difference of Keto vs Zone?

The Zone Diet has a different diagnosis to the cause of Insulin Resistance. With the Zone Diet, it’s not carb intolerance that is postulated to be the core issue, it’s inflammation that causes Insulin Resistance. From Dr Sears:

insulin resistance … is caused by increased cellular inflammation.

There are several factors that play a role in insulin resistance, but cellular inflammation is the biggest culprit.

Dr Sears explains his view of cellular inflammation in this article (What is Cellular Inflammation? Dr. Barry Sears. Jan 10, 2012). In the article he cites quite a few papers but many of these are his own papers.

Back to the original article:

Cellular inflammation results from an imbalance of two key fatty acids in our blood, Arachidonic Acid (AA) and Eicosapentaenoic Acid (EPA). When the levels of arachidonic acid are in excess it leads to the generation of hormones known to be pro-inflammatory. This inflammation makes it difficult for insulin to communicate with our cells in the liver, muscle, and adipose tissue.

Let’s check out Dr. Sears assertions. From (Essential fatty acids in health and chronic disease. Artemis P Simopoulos. The American Journal of Clinical Nutrition, Volume 70, Issue 3, 1 September 1999, Pages 560s–569s):

Human beings evolved consuming a diet that contained about equal amounts of n−3 and n−6 essential fatty acids. Over the past 100–150 y there has been an enormous increase in the consumption of n−6 fatty acids due to the increased intake of vegetable oils from corn, sunflower seeds, safflower seeds, cottonseed, and soybeans.

n−3 Fatty acids, however, have antiinflammatory, antithrombotic, antiarrhythmic, hypolipidemic, and vasodilatory properties. These beneficial effects of n−3 fatty acids have been shown in the secondary prevention of coronary heart disease, hypertension, type 2 diabetes, and, in some patients with renal disease, rheumatoid arthritis, ulcerative colitis, Crohn disease, and chronic obstructive pulmonary disease.

Most of the studies were carried out with fish oils [eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)]. However, α-linolenic acid, found in green leafy vegetables, flaxseed, rapeseed, and walnuts, desaturates and elongates in the human body to EPA and DHA and by itself may have beneficial effects in health and in the control of chronic diseases.

This particular paper, at least, supports Dr Sears’ position on dietary causes other than high carbohydrates being the source of hyperinsulinemia and Type 2 Diabetes. However, one of the referenced papers sheds light on this as a diabetic therapy.

In a randomized, double-blind, placebo-controlled, crossover trial, patients with type 2 diabetes consumed 6 g n−3 fatty acids (EPA and DHA)/d for 6 mo in addition to their usual oral therapy (14). Fasting serum glucose concentrations increased by 11% during the n−3 fatty acid phase and by 8% during the placebo phase (olive oil), showing a nonsignificant net increase of 3%.

Similarly, there was no significant change in glycated hemoglobin concentrations.

However, fasting triacylglycerol concentrations decreased by 43%, which is a highly significant change. This study is the largest and longest reported placebo-controlled trial of the effect of n−3 fatty acids on type 2 diabetes. It showed convincingly that n−3 fatty acid intake, along with oral therapy for diabetes, can lower triacylglycerol concentrations with no adverse effects on glycemic control.

This was more than enough time for an improvement in HbA1C values, but there was no improvement on blood sugar control. There was an improvement in triaglycerol concentrations (Connor WE, Prince MJ, Ullmann D, et al. The hypotriglyceridemic effect of fish oil in adult-onset diabetes without adverse glucose control. Ann N Y Acad Sci 1993;683:337–40.)

Diabetic control as judged by five criteria did not deteriorate after 6 months of fish oil compared to 6 months of olive oil supplementation in 16 patients with NIDDM who were eating a low fat, high complex carbohydrate diet.

Plasma total and VLDL triglyceride and cholesterol decreased significantly after fish oil supplementation; plasma total and HDL cholesterol concentrations did not change.

The LDL cholesterol level was significantly increased with fish oil supplementation, suggesting that patients with NIDDM who are given a fish oil supplement to decrease the plasma total and VLDL triglyceride levels may also need further dietary and/or pharmaceutical therapy to maintain an LDL cholesterol level compatible with a low risk of coronary disease. The study emphasizes the safe use of fish oil over a 6-month period in diabetic patients.

Here’s a metastudy that looked at 26 studies on the subject (Fish Oil and Glycemic Control in Diabetes. DIABETES CARE, VOLUME 21, NUMBER 4, APRIL 1998. Frieberg,

The use of fish oil has no adverse affects on HbA1 c in diabetic subjects and lowers triglyceride levels effectively by almost 30%. However, this may be accompanied by a slight increase in LDL cholesterol concentration. Fish oil may be useful in treating dyslipidemia in diabetes.

Fish oil administration resulted in a tendency for fasting blood glucose levels to be higher in NIDDM subjects (0.43 mmol/l [95% CI, 0.00–0.87], P = 0.06) and to be significantly lower in IDDM patients (-1 . 86 mmol/l [95% CI, -3.1 to -0.61], P = 0.05). This difference in fasting blood glucose responses to fish oil between NIDDM and IDDM subjects was significant (P = 0.01).

Fish oil consumption lowered serum triglycerides significantly by 25–30% in both types of subjects and resulted in a slight but significant increase in LDL cholesterol levels in NIDDM subjects only.

So it sounds to me like fish oil has no real/consistent effect on blood sugars and they raise LDL levels a bit. They do lower serum triglycerides which is a good thing. Makes me glad I take them.

So Dr Sears’ argument that Diabetes is ultimately caused by incorrect amounts of Omega-3 to Omega-6 ratios is demonstrably refuted by the actual evidence that supplementation doesn’t improve HbA1C. This may also be the reason that people on the Zone diet don’t get cured from Diabetes – except to the extent that their weight drops.


Insulin Load in Diabetics

High Fasting Insulin levels are the lock that prevents a person from using body fat.

Of the three macros (fat, carbs and protein) only carbs have a significant impact on blood sugar and as a result can raise insulin levels. Clearly, if you reduce the carb load you also reduce the area under the curve for Insulin while digesting food. But does lower carb consumption at meals impact fasting (basal) insulin levels?

From (Insulin Response to Glucose in Diabetic and Nondiabetic Subjects. John D. Bagdade, Edwin L. Bierman, and Daniel Porte Jr. Journal of Clinical Investigation. October 1, 1967):

Obesity, but not diabetes, was associated with an elevation of this basal insulin level.

Thus obesity predicted with the magnitude of the insulin response to glucose ingestion.

Thus increasing degrees of carbohydrate intolerance were associated with decreasing insulin responses. Elevated levels of insulin, in both the basal state and in response to glucose, were related to obesity.

More specifically from the text of the study:

Fasting insulin levels of obese subjects (36 uU +/- 17.6) were significantly higher (P < 0.001) than those of the thin subjects (14 uU +/- 4.8). … Thus the degree of obesity, and not the carbohydrate intolerance, was associated with the insulin levels maintained after an overnight fast.

So it’s not so much the carb intolerance but the obesity itself which raised fasting insulin levels. The next observation was:

…there was a highly significant linear correlation between fasting insulin and insulin response to glucose in both nondiabetic and diabetic subjects. This demonstrates a tendency for subjects with higher fasting levels to demonstrate greater insulin responses to glucose.

The initial insulin response to glucose in diabetics is attenuated and the total insulin response is also less at the same weight. However, obese diabetics produce a significantly larger amount of Insulin than thin diabetics or non-diabetics.

It is interesting how much of a driving force that obesity is. Fasting Insulin levels were not related to a diabetic response to glucose as much as whether or not a person is obese.

No matter what the cause, the prescription is the same – weight loss.

Explains Some Low Carb Folks

This does explain people who are on low carb and still have high fasting levels of Insulin and are obese. Low carb alone won’t solve the fasting levels of Insulin but loss of weight will.

This goes a long way to explaining why some low carb individuals can’t seem to lose much weight and are still obese even after a long time on Low Carb (Two Keto Dudes, Jimmy Moore come to mind). One of the Two Keto Dudes Richard (I believe it was) commented that he has a high fasting insulin even after years on keto.


IIFYM Keto Style

Keto isn’t necessarily contrary to IIFYM. It’s really just a different set of macros. If you are switching from IIFYM you can track the same way. You just get to have a low carb number and a higher fat number. Plus, you lose your cravings for sweets (after a few days).

I have a macros calculator. It is here. Let’s plug in my current numbers.

Macro Levels to Maintain Current Weight

Protein: 112 grams, 448 calories, 19.9% of calories (minimum)
Net Carbs: 20 grams, 80 calories, 3.6% of calories (maximum)
Fat: 191 grams, 1719 calories, 76.5% of calories (maximum, less if you exceed protein)

There’s no pizza, tacos, ice cream or gummy bears on this diet. But you will get used to eating real food. It might take a while but the desire for junk goes away with the cravings. This is pretty much all that there is to it.


You can safely go under on carbs. You can safely go over on protein. If you go over on protein just ease up on your fats.

If you want to lose weight, you just need to eat less fat. If you want to gain weight, you eat more fat.

Flexible Dieting and IIFYM

There’s a concept out there that is termed Flexible Dieting or IIFYM (If it fits your macros). It promises no limits to the types of food you can eat.

Nuts and Bolts of Flexible Dieting

The system is basically this.

  • Calculate TDEE
  • Determine macro ratios (typically from Zone 30/30/40 ratios)
  • Eat to your macros every day (no more, no less)

“Positives” of IIFYM

IIFYM has some obvious benefits. With it you can  “eat whatever you want”. If you want pizza, as long as it fits your macros you can eat it. Same goes for ice cream, etc. Anything you want just not in quantities which will push you past your macros.

Although there is no calorie counting but you weigh/count the surrogates of protein/fat/carb macros. IIFYM macros are typically higher protein than the Standard American Diet (SAD) so they tend to produce good results.

They also tend to be lower than the SAD in carbohydrates which has a positive benefit. And they limit the carbohydrates in quantity which may be the first time someone who tries the diet has ever limited their carbs. This is a way to learn portion control perhaps without feeling like you are not getting something you really want (like cake, ice cream or pasta).

IIFYM requires measurement and recording of food and tracking macros daily. It emphasizes day-to-day consistency in eating which may (or may not) be beneficial. You can use tools like MyFitnessPal or Cronometer to track your macros.

IIFYM Macro Selections

My primary concern about IIFYM is that while the initial selection of macros is great compared to the Standard American Diet (SAD) it’s only so good for someone with Metabolic Syndrome/Insulin Resistance. Setting the protein macro to 30% of calories is going to be a good thing in nearly every case (except in rare cases like kidney failure).

Dropping carb consumption is going to be good for otherwise healthy people. For the 40% of the population with Metabolic Syndrome, eating 30% of their calories from carbohydrates may lead to worsening blood sugar control and hasten the complications from diabetes.

In my case, before LCHF I was eating 200 grams a day of carbs which is about 800 calories a day. That was around 33% of my approximately 2400 calories I ate a day. Increasing my carbohydrate intake to 40% would have been 140 additional calories from carbohydrates or an addition 40 grams of carbohydrates (from 200 to 240g) that my already overloaded system would have pushed into my bloodstream.  That would have meant I would have had to take an additional 10 units of Insulin (at a minimum) and maybe more to cover the carbohydrates. Not the recipe for reducing Insulin Resistance.

Another concern is the idea that the 30/30/40 ratio is somehow a “balanced” ratio. I haven’t seen any evidence in the literature establishing this ratio as ideal in any sense of the word. In particular, the studies on diabetics I have seen show this balance is a bad balance compared to ketogenic ratios.

Fitness World and IIFYM

This approach seems to have gained traction in the fitness community where glycogen stores are important for high intensity work (CrossFit and Nutrition – Part 3). And someone who works out intensely every day can probably tolerate a higher level of carbohydrates than someone who works out much less frequently.

Micro-nutrients and IIFYM

There seems to be a de-emphasis on micronutrients/vitamins/minerals in IIFYML. For instance this article claims that there’s no such thing as clean eating (What is Flexible Dieting? Here’s How to Get Started). A gram of carbs from a twinkie and a gram of carbs from broccoli work just the same in your body. And that’s just simply false. Some carbs are slowly digested and raise blood sugar by a small amount and others send blood sugar up sky high.

Equally there are some IIFYM/Flexible Dieting sources out there who are concerned about micronutrients and vitamins. For instance, this YouTube guy who expresses the idea that micronutrients matter (Flexible Dieting 101: The Simple Facts).

This may be made more difficult to track with MyFitnessPal (MFP). I don’t use MFP but reading the process to see your micronutrients with MFP seems clumsy (Where can I find my micronutrients?).

With Cronometer I see the micronutrients every single day and know exactly where I am at for each micronutrient/vitamin/mineral.

Here are my micro nutrients (averaged for this past week although it’s the same data day-by-day).

And here are my vitamins and minerals for the week (same for the day).

Higher Carb Diets Have Lower Compliance

One thing I have observed is that higher carb level diets don’t produce good compliance beyond a very short term. That is because they really don’t blunt carb cravings like a low carb diet does. This means they still have the potential roller coaster of blood sugar spikes.

Eating Carb Macros

Trying a theoretical case with someone who weighs 200 lbs and wants to maintain their weight. That is:

  • Protein = 2000 * 30% = 600 calories or 150 g
  • Fat = 2000 * 30% = 600 calories or 67g
  • Carbs = 2000 * 40% = 800 calories or 200g

Reduced to familiar food, 150g of protein is 26 ozs of boneless, skinless chicken breast. I picked that because it is low fat and there’s no much fat on IIFYM macros. That very low fat option takes up 16 of the 67 g of fat leaving around 51g of fat for the rest of the day.

So we have 200g of protein and only 51g of fat left. If we pick a “healthy” carbohydrate like a potato.

To get to 200g of “healthy” carb choices we would need to eat almost 8 potatoes. If we put a bit of butter or olive oil on the potatoes:

We only get less than 4 tablespoons worth of olive oil and we are out of fat, carbs and protein. This might be where fruit comes in handy since fruit has a lot of carbs and little fat/protein.

Using Healthier Vegetable Choices

Let’s try replacing the potato with a low carb vegetable like broccoli:

At 6g a cup to get 200g of broccoli we’d need to eat 33 cups of broccoli. This demonstrates the difficulty of getting a lot of carbs and doing it with low carb vegetables.

Unhealthier Choices

But none of this matches the promise of IIFYM which is that you can eat whatever you want as long as it fits your macros. And today let’s say I want to eat ice cream, tacos and pizza.

My pizza Choice will be a moderate 2 slices of Little Caesar’s pizza. MFP has lower macros than Cronometer so let’s go with MFP:

What do I have left?

  • Protein = 150 – 28g = 122g
  • Fat = 67 – 22g = 45g
  • Carbs = 200 – 64g = 136g

Now I get my Ben and Jerry’s:

  • Protein = 122 – 8g = 114g
  • Fat = 45 – 25g = 20g
  • Carbs = 136 – 49g = 87g

Still a fair amount left but I haven’t had my four tacos yet.

This is where MFP numbers don’t match the company website. The Taco Bell site has:

  • Protein = 114 – (8*4) 32g = 82g
  • Fat = 20 – (9*4) 36g = -16g <<< OOPS, I’ve already gone over for fat
  • Carbs = 87 – (13*4) 52 g = 35g

This is where the rubber meets the road. I’ve not gone crazy this day. Nothing that I don’t feel like I deserve to eat. But they don’t fit my macros. So I need to only have 2 tacos. It’s lunch time and I feel pretty deprived.

  • Protein = 114 – (8*2) 16g = 98g
  • Fat = 20 – (9*2) 18g = 2g
  • Carbs = 87 – (13*2) 16 g = 16g

So I can have some carbs but I’ve got not much fat so no chips, etc. And I’ve got a whole lot of protein I still need to get in. Sounds like I will be eating two protein shakes that day. So how did I do?

  • Protein = 2000 * 30% = 600 calories or 150 g (I went over by 3g)
  • Fat = 2000 * 30% = 600 calories or 67g (I went over by 15g)
  • Carbs = 2000 * 40% = 800 calories or 200g (I ended up 75g under)

Time for a handful of jelly beans or gummy bears. Trouble is I only have 80 calories and I need to get in 75*4 = 300 calories to hit my carb number. Still not horrible for my first day.

No, don’t worry. I’m not going to do it. Just wanted to demonstrate what I see with people who eat this way. Perhaps they get better at planning and meal prep. Some of them do. And they probably have better compliance.


Which Fat Matters and in What Sense Does it Matter?

From this study (Proc Natl Acad Sci U S A. 2009 Sep 8; 106(36): 15430–15435. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. Elisa Fabbrini,

Visceral adipose tissue (VAT) is an important risk factor for obesity-related metabolic disorders. Therefore, a reduction in VAT has become a key goal in obesity management. However, VAT is correlated with intrahepatic triglyceride (IHTG) content, so it is possible that IHTG, not VAT, is a better marker of metabolic disease. We determined the independent association of IHTG and VAT to metabolic function, by evaluating groups of obese subjects, who differed in IHTG content (high or normal) but matched on VAT volume or differed in VAT volume (high or low) but matched on IHTG content.

Hepatic, adipose tissue and muscle insulin sensitivity were 41, 13, and 36% lower (P < 0.01), whereas VLDL-triglyceride secretion rate was almost double (P < 0.001), in subjects with higher than normal IHTG content, matched on VAT. No differences in insulin sensitivity or VLDL-TG secretion were observed between subjects with different VAT volumes, matched on IHTG content. Adipose tissue CD36 expression was lower (P < 0.05), whereas skeletal muscle CD36 expression was higher (P < 0.05), in subjects with higher than normal IHTG.

These data demonstrate that IHTG, not VAT, is a better marker of the metabolic derangements associated with obesity.

Furthermore, alterations in tissue fatty acid transport could be involved in the pathogenesis of ectopic triglyceride accumulation by redirecting plasma fatty acid uptake from adipose tissue toward other tissues.


Coronary artery calcium score

From this paper (Radiol Bras. 2017 May-Jun; 50(3): 182–189. doi: 10.1590/0100-3984.2015.0235. Coronary artery calcium score: current status. Priscilla Ornellas Neves, Joalbo Andrade, and Henry Monção):

The CAC score is an independent marker of risk for cardiac events, cardiac mortality, and all-cause mortality. In addition, it provides additional prognostic information to other cardiovascular risk markers.

The well-established indications for the use of the CAC score include stratification of global cardiovascular risk for asymptomatic patients: intermediate risk based on the Framingham risk score (class I); low risk based on a family history of early CAD (class IIa); and low-risk patients with diabetes (class IIa).

In symptomatic patients, the pre-test probability should always be given weight in the interpretation of the CAC score as a filter or tool to indicate the best method to facilitate the diagnosis. Therefore, the use of the CAC score alone is limited in symptomatic patients.

In patients with diabetes, the CAC score helps identify the individuals most at risk, who could benefit from screening for silent ischemia and from more aggressive clinical treatment.

See also (J Am Coll Cardiol. 2009 Jan 27; 53(4): 345–352. Coronary calcium predicts events better with absolute calcium scores than age-gender-race percentiles – The Multi-Ethnic Study of Atherosclerosis (MESA).
Matthew J Budoff,

Expressing CAC in terms of age and gender specific percentiles had significantly lower area under the ROC curve(AUC) than using absolute scores (women: AUC 0.73 versus 0.76,p=0.044; men: AUC 0.73 versus 0.77,p<0.001). Akaike’s information criterion (AIC) indicated better model fit using the overall score. Both methods robustly predicted events(>90th percentile associated with a hazard ratio(HR) of 16.4(95% c.i. 9.30,28.9), and score >400 associated with HR of 20.6(95% c.i. 11.8, 36.0).

Within groups based on age/gender/race/ethnicity specific percentiles there remains a clear trend of increasing risk across levels of the absolute CAC groups.

In contrast, once absolute CAC category is fixed, there is no increasing trend across levels of age/gender/race/ethnicity specific categories.

Patients with low absolute scores are low risk, regardless of age-gender-ethnicity percentile rank.

Persons with an absolute CAC score of >400 are high risk, regardless of percentile rank.

I am interested in getting my CAC score to see what damage years of diabetes and hypertension may have done to me.


Weight to Height Ratio = Predictor of Mortality

From this study (Ashwell M, Mayhew L, Richardson J, Rickayzen B (2014) Waist-to-Height Ratio Is More Predictive of Years of Life Lost than Body Mass Index. PLoS ONE 9(9): e103483.

Mortality risk associated with BMI in the British HALS survey was similar to that found in US studies. However, Waist to Height Ratio (WHtR) was a better predictor of mortality risk. For the first time, Years of Life Lost (YLL) have been quantified for different values of WHtR. This has been done for both sexes separately and for three representative ages.


Hypertension and meds

I was on diuretics for my hypertension for years before I was diagnosed as a diabetic.

From (CARDIOLOGY, May 23, 2012, Effects of Thiazide Diuretics on Glucose Metabolism. Joel M. Gore, MD reviewing Stears AJ et al. Hypertension 2012 May).

In the first trial, 41 patients had a significant increase in blood glucose during a 2-hour oral glucose tolerance test (OGTT) after 4 weeks of bendroflumethiazide treatment, but not after 4 weeks of atenolol treatment.

Things that make me go — Hmmm.


Hypertension and Hyper-Insulinemia

From this study (J Clin Invest. 1985 Mar; 75(3): 809–817. Hyperinsulinemia. A link between hypertension obesity and glucose intolerance. M Modan, H Halkin, S Almog, A Lusky, A Eshkol, M Shefi, A Shitrit, and Z Fuchs):

83.4% of the hypertensives were either glucose-intolerant or obese–both established insulin-resistant conditions.

We conclude that insulin resistance and/or hyperinsulinemia
(a) are present in the majority of hypertensives, (b) constitute
a common pathophysiologic feature of obesity, glucose intolerance, and hypertension, possibly explaining their ubiquitous association, and (c) may be linked to the increased peripheral vascular resistance of hypertension, which is putatively related to elevated intracellular sodium concentration.

Hypertension? Cause may be elevated Insulin levels.


Glycemic Index/Glycemic Load Variability

There’s an interesting look at the use of Glycemic Index and Glycemic Load as a means for diabetics to control blood sugar (Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. Nirupa R Matthan Lynne M Ausman Huicui Meng Hocine Tighiouart Alice H Lichtenstein. The American Journal of Clinical Nutrition, Volume 104, Issue 4, 1 . October 2016, Pages 1004–1013).

These data indicate that there is substantial variability in individual responses to GI value determinations, demonstrating that it is unlikely to be a good approach to guiding food choices. Additionally, even in healthy individuals, glycemic status significantly contributes to the variability in GI value estimates.

Here’s where I think there’s a point but it may not be relevant. Sure the numbers are not absolute for all individuals. It shouldn’t be a surprise to anyone that some people are more tolerant of carbohydrates than others. In fact, that’s part of the very reason that Low Carb works so well for those of us that are more sensitive to carbohydrates than others.

I have no doubt that the area under the curve for my blood sugar response when I was a diabetic was much higher than most healthy people. That explains some of the variability. However, this study used subjects who were all pretty healthy. Interestingly, the HbA1C average of this group was between 5.5% and 5.6% with a range plus/minus 0.5%. Some of these may be pre-diabetic and unaware of it.

What would be more interesting than person to person variability in the absolute value of the GI number would be the relative numbers for each of the groups.

Variability – Width of the Standard Deviation

There was a pretty wide standard deviation in the number reported:

The mean ± Standard Deviation (SD) Glycemic Index (GI) value for white bread was 62 ± 15 when calculated by using the recommended method.

Yes, that’s around 25% variability which is fairly wide. As the study stated:

… we documented substantial variability in the mean intra-individual (20%) and inter-individual (25%) CVs for a single food, white bread.

So not only were differences noted in the values between different people but even the same person had different responses to the same load.

Here’s the 2002 Standard table for GI/GL (International table of glycemic index and glycemic load values: 2002. Kaye Foster-Powell, Susanna HA Holt, and Janette C Brand-Miller).

Here’s a shorter table listing the GI for various foods (Glycemic Index Chart: GI Ratings for Hundreds of Foods).  Foods listed as “Low Glycemic Index” as not necessarily low carb. For instance, broccoli (GI=15) and cranberries (GI=45) are both Low Glycemic Index since they are less than GI=55 but there’s three times the GI represented in cranberries compared to broccoli.

The American Diabetics Association states (Glycemic Index and Diabetes):

Studies also show that the total amount of carbohydrate in food, in general, is a stronger predictor of blood glucose response than the GI.

… for most people with diabetes, the first tool for managing blood glucose is some type of carbohydrate counting.

Because the type of carbohydrate can affect blood glucose, using the GI may be helpful in “fine-tuning” blood glucose management. In other words, combined with carbohydrate counting, it may provide an additional benefit for achieving blood glucose goals for individuals who can and want to put extra effort into monitoring their food choices

Good points. But why not mention just limiting carbohydrates altogether?