Tag Archives: glycemic load

the intimate relationship between carbohydrates, protein, insulin, fibre, fat, sugar and nutrient density exposed!

  • The food insulin index data demonstrates that the carbohydrate content of your food does not accurately predict insulin response.
  • Protein requires about half as much insulin as carbohydrate.
  • Indigestible fibre from whole foods tends to have a minimal influence on our glucose and insulin response.
  • Dietary fat does not require a significant amount of insulin.
  • Net carbohydrates plus approximately half protein correlates well with our insulin response.
  • This understanding can help select foods that will cause a lower insulin response and enable more accurate calculation of insulin dosing for people with diabetes.

background

I used to dabble in share trading.  I don’t know much about financial systems, but I spent a lot of time designing and testing “trend following” trading systems.

When the Global Financial Crisis hit in 2009 things got too volatile, and I got out of the market.  It was no longer fun.  However, the skills I learned as a quantitative trader, along with my day job as an engineering running multi-criteria analyses to identify motorway alignments and prioritise road investments and the like have given me a unique perspective on nutrition that people seem to have found useful.

On the Optimising Nutrition blog, I have tried to describe a system to manage nutrition that makes sense to me.  In these articles, I try to document the things that I wish someone had shown to Monica and me when we started out trying to understand diabetes and nutrition.

If we want to understand and predict the behaviour of insulin, the master regulator hormone, we need to first determine what we know that is accurate, significant and useful that we can use.

Kirstine Bell’s PhD thesis Clinical Application of the Food Insulin Index to Diabetes Mellitus[1] (Sept 2014) details the results of the latest food insulin test data for more than one hundred foods.  It also evaluates the relationship between insulin demand and protein, fat, carbohydrates, glycaemic index, glycaemic load, indigestible fibre, individual amino acids and blood glucose.

Previously I have discussed how to calculate how much insulin may be required based on the carbohydrate, protein and fibre ingested.  Given the importance of this issue, this article looks in more detail at what can be learned from the test data included in this thesis about the relationship between these parameters, to better manage blood glucose and insulin demand.

carbohydrate

The amount of carbohydrate does an excellent job of explaining the amount our glucose levels increase.

Most people know that carbohydrates require insulin.  As shown in the chart below, the quantity of carbohydrate goes some way to explaining insulin response.  However it is far from a perfect relationship (R2 = 0.44, r = 0.67, p < 0.05).

fibre

Taking indigestible fibre into account (i.e. net carbohydrates) improves the relationship (R2 = 0.48, r = 0.69, p < 0.05).  The best correlation is achieved when we subtract all the indigestible fibre from the total carbohydrate value.  However, we can see from the cluster of data points on the vertical axis there is something going on that is not explained by carbohydrates alone.

The importance of dietary fibre should not be discounted, especially when trying to reduce insulin demand.  Some recommend that people with diabetes limit total carbohydrates, rather than considering net carbohydrates, or non-fibre carbohydrates.  The danger with a total carbohydrates approach is that people will avoid non-starchy fibrous vegetables that provide vitamins and minerals that cannot be obtained from other foods (unless you’re consuming a significant amount of organ meats), as well as feeding the gut bacteria which is also important to help improve insulin sensitivity and the body’s ability to digest fats. [2]

fat

The food insulin index data indicates that the highest fat foods have the lowest insulin response (R2 = 0.38, r = 0.631, p < 0.001).

 

The figure below shows a similar chart for the glucose score (i.e. the area under the curve of the blood glucose rise over three hours after ingestion of the food).  Blood glucose response is lowest for foods that contain a higher proportion of calories from fat (R2 = 0.45, r = 0.68, p < 0.001).

Now, while getting more of your energy from fat will help to reduce your insulin requirements and stabilise your blood sugar, you should keep in mind:

  1.  The glycerol backbone in fat can be converted to glucose if necessary via gluconeogenesis, so there can still be some insulin and glucose response to refined fat.
  2. Refined fat typically does not contain a broad spectrum of micronutrients.
  3. While type 2 diabetes appears on the surface to be a condition of glucose intolerance, it is fundamentally an issue with your adipose tissue being full.  Once you exceed your personal fat threshold your body fat is no longer able to hold excess energy and it spills over into the bloodstream.  Reducing the carbohydrates in your diet will stabilise the blood glucose swings, however, you will need to reduce your overall energy intake to enable the excess energy to flow from your body fat stores before you become truly insulin sensitive and lower your blood glucose levels.

protein

Another observation from trading is that you can learn a lot by considering outliers.  You have to decide whether the data points that don’t quite fit the trend are garbage or ‘black swans’ need to be accounted for in the system.

In the carbohydrate vs insulin relationship, the outliers are the high protein foods that trigger a higher insulin response than can be explained by considering carbohydrates alone.  When we zoom in on the bottom left corner of the carbohydrate vs insulin response chart we see that high-fat foods such as butter, bacon, avocado, olive oil and walnuts do not have a significant insulin response.  However, high protein foods such as fish, steak and tuna still have a significant insulin response.

As a general rule, as we increase the protein content of our food our insulin requirements come down.  High protein foods force out the processed carbohydrates which require the greatest amount of insulin.  Choosing higher protein foods will generally reduce insulin (R2 = 0.10, r = 0.47, p < 0.001).

Increasing protein will also typically lead to a spontaneous reduction in intake due to the thermic and satiety effects of protein. [3] [4]   It is vital to eat adequate protein, but it is hard to overeat protein due to the strong satiety response.

However, protein in excess of the body’s needs for growth and repair can be converted to glucose.  The fact that protein can turn to glucose represents a potential ‘hack’ for people with diabetes trying to manage their blood glucose as they can get the glucose required for brain function without spiking blood glucose as much as carbohydrates.

Choosing higher protein foods will lead to better blood glucose control.  Although high protein foods still raise the blood glucose somewhat, particularly if you are not insulin sensitive, however, the blood glucose response is gentler, and hence the pancreas can secrete enough insulin to balance blood glucose.

For most people, transitioning to a reduced carbohydrate whole foods diet will give them most of the results they are after.  However, for people who require a therapeutic ketogenic diet, consideration of protein may be necessary to achieve the desired outcomes.

For a healthy bodybuilder, the glucogenic and insulinogenic effect of protein might be an anabolic advantage, with the post-workout protein shake providing an insulin spike to help build muscle.

sugar

The sugar content of a food is not a particularly useful predictor of insulin demand (R2 = 0.10, r = 0.32, p = 0.001) compared with net carbohydrates (R2 = 0.48, r = 0.69, p < 0.05). Most people struggling with diabetes will need to consider the total sugar in their diet to optimise blood.

insulin load vs food insulin index

If we, take out indigestible fibre (net carbs), assume that fat has a negligible insulin response and refine the protein factor to maximise the correlation with the test data, we end up with this chart which has an improved correlation compared to the model above (R2 = 0.49, r = 0.70, p < 0.001).

nutrient density

One of the shortcomings of the insulin load concept is that extremes of insulin load can lead to a nutrient-poor outcome.  As shown in the chart below, nutrient density seems to peak at about 40% insulinogenic calories.  If you are insulin resistant, you will want to choose food that has less than 40% insulinogenic calories.

If you have diabetes, you may want to tweak your diet to less than 25% insulinogenic calories.  Meanwhile, if you are chasing therapeutic keto, then you will want less than 15% insulinogenic calories.  But keep in mind that this will have negative impacts on your ability to get the essential nutrients you need.

the Nutrient Optimiser

We’ve been working hard to build a tool that will make all this info easier to understand and apply.    If you head on over to NutrientOptimiser.com and tell us some details about yourself this exciting new free tool will give you target macronutrient ranges, optimal food choices and suggested meals that will help you reach your goals.

We’re very excited to have this tool now available for you to use.  We’d love your feedback on how we can improve it to help more people.

 

last updated January 2018

references

[1] http://ses.library.usyd.edu.au/handle/2123/11945

[2] http://www.amazon.com/Brain-Maker-Power-Microbes-Protect/dp/0316380105

[3] http://wholehealthsource.blogspot.com.au/2013/04/glucagon-dietary-protein-and-low.html

[4] http://www.ncbi.nlm.nih.gov/pubmed/16002798

[5] http://wholehealthsource.blogspot.com.au/2013/04/glucagon-dietary-protein-and-low.html

[6] http://ses.library.usyd.edu.au/handle/2123/11945

[7] http://ses.library.usyd.edu.au/handle/2123/11945

[8] http://www.amazon.com/Brain-Maker-Power-Microbes-Protect-ebook/dp/B00MEMMS9I

proportion of insulinogenic calories

Someone looking to “go low carb” will typically try to make a decision on whether a food meets their goals simply based on the number of carbohydrates per serving or per 100g shown on the label.

This approach has limited benefit though, as the food may or may not contain a lot of water which makes it hard to compare in terms of carbohydrates per calorie.

Another way is to look at the amount of protein and fat in relation to the carbohydrates, but again this is a difficult calculation to make when you’re looking at the nutritional label in the shopping isle.

If we take the concept of “net carbs” and the idea that protein has some insulinogenic effect we can calculate the proportion of insulinogenic calories using the following formula:

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This calculation could be useful to determine whether one food is better than another if you’re trying to reduce your insulin load to the point that your pancreas can keep up.

As demonstrated by the chart below, the lower the proportion of insulinogenic calories in your food the less likely your meal is going to require large amounts of insulin, raise your blood glucose or cause you to store fat.

food insulin index table - correlation analysis 26052015 53725 AM.bmp

Sure, this is not a simple calculation we can quickly while we’re out shopping.  However using readily available nutritional data we can compare and rank a wide range of foods, making us better informed when we prepare our shopping list.

An extensive list of the foods with the lowest proportion of insulinogenic calories can be in this list of the most ketogenic diet foods.

Or we can combine it with other nutritional parameters to highlight ideal foods for weight loss, diabetes, therapeutic ketosis or athletic performance.

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[next article…  application of insulin load for type 1 diabetics]

[this post is part of the insulin index series]

[Like what you’re reading?  Skip to the full story here.]

glycemic load versus insulin load

The glycemic index (GI) compares the rise in blood sugar for a particular food relative to glucose.  The theory goes that it is better to eat low glycemic index carbohydrates that will not raise our blood sugar too much and will take longer to digest.

Building on the glycemic index is the concept of glycemic load which is the GI of a food multiplied by the grams of carbohydrate eaten.  Watermelon has a very high GI value, however because watermelon only contains a small quantity of carbohydrates (watermelon is mostly water) the overall glycemic load is small.  A large glycemic load occurs when you eat a large quantity of a high glycemic index carbohydrate.

The limitation of the GI approach is that we can eat a diet full of low glycemic index carbohydrates and protein while still producing a large amount of insulin.  Even though they are slow to digest and do not raise blood sugar significantly, a low GI moderate GL diet will still require substantial amounts of insulin.  It’s the amount of insulin, not the grams of carbohydrates or even the rise in blood sugar that’s really at the nub of the problem.

AVPageView 23042015 33836 AM.bmp

The chart below shows the relationship between the glycemic load and insulin index.  Reducing the glycemic load does not guarantee a low insulin response, particularly when it comes to high protein foods.

food insulin index table - correlation analysis 13052015 54118 AM.bmp

Even if you’re eating low GI foods that don’t spike your blood sugars you may still be generating a sustained requirement for insulin.  Maintaining reasonable blood sugars in spite of a moderate glycemic load is just an indication that your pancreas is still keeping up, for now.

Various studies have shown that eating a low GI diet doesn’t help with weight loss. [4] [5]  We also now know that high insulin levels are also a massive health risk as well as high blood sugars. [6]

Rather than focusing on the glycemic load or the glycemic index, I believe it is more important to manage the overall insulin load of the diet, particularly if your aim is to achieve optimal blood sugars or reduce excess body fat.

 

references

[1] http://www.glycemicindex.com/

[2] http://sydney.edu.au/science/people/jennie.brandmiller.php

[3] https://www.diabetesaustralia.com.au/Living-with-Diabetes/Eating-Well/Glycaemic-Index-GI/

[4] http://www.ncbi.nlm.nih.gov/pubmed/17823436

[5] http://chriskresser.com/is-the-glycemic-index-useful

[6] http://high-fat-nutrition.blogspot.com.au/2014/12/accord-and-musings-on-insulin.html

superfoods for diabetes & nutritional ketosis

These foods will help you to maintain excellent blood glucose levels by reducing the insulin load of your diet while at the same time maximising nutrient density to minimise cravings and allow you to get the nutrients you need with less food.

More than carbohydrates or the glycemic index, the food insulin index data suggests that our blood glucose and insulin response to food is better predicted by net carbohydrates plus about half the protein we eat.

There is a relationship between carbohydrate and our insulin response to the food we eat, but it is not that strong, particularly when it comes to high protein foods or high fibre foods.

insulin response to carbohydrate from the food insulin index testing

Accounting for fibre and protein enables us to more accurately predict the amount of insulin that will be required to metabolise a particular food.  This knowledge can be useful for someone with diabetes and/or a person who is insulin resistant to help them calculate their insulin dosage or to choose foods that will require less insulin.  People wanting to follow a ketogenic diet will want to select foods towards the bottom corner of this chart.

insulin response to food = net carbs + 0.56 * protein

If your blood glucose levels are high you are likely insulin resistant (e.g.  type 2 diabetes) or not able to produce enough insulin (e.g. type 1 diabetes) it makes sense to reduce the insulin load of your food so your pancreas can keep up.

This list of foods has been optimised to reduce the insulin load while also maximising nutrient density.  These low insulin load, high nutrient density foods will lead to improved blood sugar control and normalised insulin levels.  Reduced insulin levels will allow body fat to be released and be used for energy to improve body composition and insulin resistance.

As shown in the chart below this selection of foods is also nutrient dense and provides a substantially greater amount of nutrients compared to the average of all foods available.

2017-02-27 (2).png

From a macronutrient perspective, these foods have a similar protein content to the rest of the foods in the USDA database, more fibre but much less digestible non-fibre carbohydrate.  And the carbohydrates that are there come from nutrient dense veggies that are hard to overconsume compared to the processed nutrient poor carbs that are typically causing the issues for people.

2017-02-27 (3).png

Included in the tables are the nutrient density score, percentage of insulinogenic calories, insulin load, energy density and the multicriteria analysis score (MCA) that combines all these factors.  Why not use these lists to inspire your next trip to the grocery store?

vegetables and fruit

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food ND % insulinogenic insulin load (g/100g) calories/100g MCA
endive 17 23% 1 17 1.9
chicory greens 15 23% 2 23 1.8
alfalfa 12 19% 1 23 1.7
escarole 14 24% 1 19 1.7
coriander 14 30% 2 23 1.6
spinach 19 49% 4 23 1.3
curry powder 5 13% 14 325 1.3
beet greens 12 35% 2 22 1.3
basil 18 47% 3 23 1.3
zucchini 14 40% 2 17 1.3
asparagus 17 50% 3 22 1.2
paprika 8 27% 26 282 1.2
mustard greens 8 36% 3 27 1.1
parsley 14 48% 5 36 1.1
turnip greens 12 44% 4 29 1.1
banana pepper 7 36% 3 27 1.0
collards 8 37% 4 33 1.0
arugula 12 45% 3 25 1.0
lettuce 14 50% 2 15 1.0
chard 14 51% 3 19 1.0
eggplant 5 35% 3 25 1.0
pickles 8 39% 1 12 1.0
cucumber 8 39% 1 12 1.0
okra 13 50% 3 22 1.0
summer squash 10 45% 2 19 1.0
sage 4 26% 26 315 0.9
poppy seeds 1 17% 23 525 0.9
Chinese cabbage 14 54% 2 12 0.9
watercress 20 65% 2 11 0.9
chives 12 48% 4 30 0.9
broccoli 13 50% 5 35 0.9
edamame 8 41% 13 121 0.9
sauerkraut 6 39% 2 19 0.9
jalapeno peppers 4 37% 3 27 0.9
cloves 6 35% 35 274 0.9
cauliflower 11 50% 4 25 0.9
marjoram 4 31% 27 271 0.9
caraway seed 3 27% 28 333 0.8
thyme 5 34% 31 276 0.8
red peppers 6 40% 3 31 0.8
radishes 7 43% 2 16 0.8
celery 10 50% 3 18 0.8
portabella mushrooms 12 55% 5 29 0.8

eggs and dairy

dairy20and20eggs

food ND % insulinogenic insulin load (g/100g) calories/100g MCA
egg yolk 5 18% 12 275 1.2
whole egg 6 30% 10 143 1.1
cream -6 6% 5 340 1.0
sour cream -5 13% 6 198 0.9
limburger cheese -1 19% 15 327 0.9
cream cheese -5 11% 10 350 0.9
camembert -1 21% 16 300 0.8
feta cheese -1 22% 15 264 0.8
Swiss cheese -0 22% 22 393 0.8
butter -7 2% 3 718 0.8
blue cheese -1 21% 19 353 0.8
gruyere cheese -0 22% 23 413 0.8
edam cheese -1 23% 21 357 0.8
cheddar cheese -2 20% 20 410 0.8
brie -3 19% 16 334 0.8
Monterey cheese -2 20% 19 373 0.8
goat cheese -3 21% 14 264 0.8
muenster cheese -2 21% 19 368 0.8
gouda cheese -1 24% 21 356 0.8
Colby -2 21% 20 394 0.7
ricotta -2 27% 12 174 0.7

nuts, seeds and legumes

image10

food ND % insulinogenic insulin load (g/100g) calories/100g MCA
sunflower seeds 3 15% 22 546 1.0
flax seed 0 11% 16 534 1.0
coconut milk -6 8% 5 230 1.0
sesame seeds -2 10% 17 631 0.9
brazil nuts -2 9% 16 659 0.9
coconut cream -7 8% 7 330 0.9
pumpkin seeds 1 19% 29 559 0.9
hazelnuts -2 10% 17 629 0.9
coconut meat -6 10% 9 354 0.8
walnuts -1 13% 22 619 0.8
almonds -1 15% 25 607 0.8
pine nuts -3 11% 21 673 0.8
almond butter -1 16% 26 614 0.8
pecans -5 6% 12 691 0.8
macadamia nuts -6 6% 12 718 0.7

seafood

seafood-salad-5616x3744-shrimp-scallop-greens-738

food ND % insulinogenic insulin load (g/100g) calories/100g MCA
mackerel 0 14% 10 305 1.1
fish roe 15 47% 18 143 1.1
caviar 9 33% 23 264 1.1
cisco 5 29% 13 177 1.0
trout 13 45% 18 168 1.0
sardine 9 37% 19 208 1.0
sturgeon 14 49% 16 135 0.9
salmon 15 52% 20 156 0.9
anchovy 11 44% 22 210 0.9
herring 7 36% 19 217 0.9

offal

food ND % insulinogenic insulin load (g/100g) calories/100g MCA
beef brains 3 22% 8 151 1.1
lamb brains 5 27% 10 154 1.1
sweetbread -3 12% 9 318 1.0
lamb liver 14 48% 20 168 1.0
turkey liver 13 47% 21 189 1.0
chicken liver 14 50% 20 172 0.9
liver sausage -4 13% 10 331 0.9
chicken liver pate 5 34% 17 201 0.9
lamb kidney 14 52% 15 112 0.9
veal liver 15 55% 26 192 0.8
liver pate -4 16% 13 319 0.8
lamb sweetbread 7 43% 15 144 0.8
beef kidney 11 52% 20 157 0.7

animal products

7450703_orig

food ND % insulinogenic insulin load (g/100g) calories/100g MCA
bratwurst 0 16% 13 333 1.0
ground turkey 5 30% 19 258 0.9
bacon -4 11% 11 417 0.9
pork sausage 1 25% 13 217 0.9
salami -1 18% 17 378 0.9
pork ribs -1 18% 16 361 0.9
kielbasa -3 15% 12 325 0.9
turkey bacon -3 19% 11 226 0.8
pork sausage -2 20% 16 325 0.8
knackwurst -4 16% 12 307 0.8
roast pork 8 41% 20 199 0.8
bologna -7 11% 9 310 0.8
pepperoni -4 13% 16 504 0.8
beef sausage -3 18% 15 332 0.8
lamb rib -2 19% 17 361 0.8
duck -3 18% 15 337 0.8
pork ribs 6 39% 21 216 0.8
blood sausage -5 14% 13 379 0.8
pork loin 7 41% 19 193 0.8
frankfurter -5 17% 12 290 0.8
meatballs -3 19% 14 286 0.8
headcheese -5 20% 8 157 0.8
roast ham 6 41% 18 178 0.8
chorizo -3 17% 19 455 0.8
roast beef 5 38% 21 219 0.7
turkey -2 20% 21 414 0.7
chicken (leg with skin) 6 42% 18 184 0.7
T-bone steak -1 26% 19 294 0.7
ground beef 1 30% 18 248 0.7

other dietary approaches

The table below contains links to separate blog posts and printable .pdfs detailing optimal foods for a range of dietary approaches (sorted from most to least nutrient dense) that may be of interest depending on your situation and goals.   You can print them out to stick to your fridge or take on your next shopping expedition for some inspiration.

dietary approach printable .pdf
weight loss (insulin sensitive) download
autoimmune (nutrient dense) download
alkaline foods download
nutrient dense bulking download
nutrient dense (maintenance) download
weight loss (insulin resistant) download
autoimmune (diabetes friendly) download
zero carb download
diabetes and nutritional ketosis download
vegan (nutrient dense) download
vegan (diabetic friendly) download
therapeutic ketosis download
avoid download

If you’re not sure which approach is right for you and whether you are insulin resistant, this survey may help identify the optimal dietary approach for you.

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