Tag Archives: insulin index

energy density, food hyper-palatability and reverse engineering optimal foraging theory

I’m looking forward to Robb Wolf’s new book Wired to Eat in which he talks about the dilemma of optimal foraging theory (OFT) and how it’s a miracle in our modern environment that even more of us aren’t fat, sick and nearly dead.[1]

image26

[yes, I may be a Robb Wolf fan boy.]

But what is  optimal foraging theory[2]?   In essence it is the concept that we’re programmed to hunt and gather and ingest as much energy us we can with the least amount of energy expenditure or order to maximise survival of the species.

In engineering or economics this is akin to a cost : benefit analysis.  Essentially we want maximum benefit for minimum investment.

image13

In a hunter gatherer / paleo / evolutionary context this would mean that we would make an investment (i.e. effort / time / hassle that we could have otherwise spent having fun, procreating or looking after our family) to travel to new places where food was plentiful and easier to obtain.

In these new areas we could spend as little time as possible hunting and gathering and more time relaxing.  Once the food became scarce again we would move on to find another land of plenty.

The people who were good at obtaining the maximum amount of food with the minimum amount of effort survived and thrived and populated the world, and thus became our ancestors.  Those that didnt’ didn’t.

So you can see how the OFT paradigm would be well imprinted on our psyche.

OFT in the wild

In the wild, OFT means that native hunter gatherers would have gone bananas for bananas when they were available…

image28

… gone to extraordinary lengths to obtain energy dense honey …

image16

… and eaten the fattiest cuts of meat and offal, giving the muscle meat to the dogs.

image02

OFT in captivity

But what happens when we translate OFT into a modern context?

image09

Until recently we have never had the situation where nutrition and energy could be separated.

In nature, if something tastes good it is generally good for you.

Our ancestors, at least the ones that survived, grew to understand that as a general rule:

 sweet = good = energy to survive winter

But now we have entered a brave new world.

image19

These days we have are surrounded by energy dense hyperpalatable foods that are designed to taste good without providing substantial levels of nutrients.

image05

When these foods are available our primal programming leaves us defenceless.

Our willpower or our calorie counting apps are no match for engineered foods with an optimised bliss point.

image14

These days diabetes is becoming a bigger problem than starvation in the developing world due to a lack of nutritional value in the the foods they are eating.[3]

The recent industrialisation of the world food system has resulted in a nutritional transition in which developing nations are simultaneously experiencing undernutrition and obesity.

In addition, an abundance of inexpensive, high-density foods laden with sugar and fats is available to a population that expends little energy to obtain such large numbers of calories.

Furthermore, the abundant variety of ultra processed foods overrides the sensory-specific satiety mechanism, thus leading to overconsumption.”[4]

what happens when we go low fat?

So if the problem is simply that we eat too many calories, one solution is to reduce the energy density of our food by avoiding fat, which is the most energy dense of the macronutrients.

Sounds logical, right?

The research into the satiety index demonstrates that there is some basis to the concept that we feel more full with lower energy density, high fibre, high protein foods.[5] [6]   The chart below shows how hungry people report being in the two hours after being fed 1000kJ of different foods (see the low energy density high nutrient density foods for weight loss article for more on this complex and intriguing topic).

image21

However the problem comes when we focus on reducing fat (along with perhaps reduced cost, increased shelf life and palatability combined with an attempt to reach that optimal bliss point[7]), we end up with cheap manufactured food like products that have little nutritional value.

image10

Grain subsidies were brought in to establish and promote cheap ways to feed people to prevent starvation.[8]  It seems now they’ve achieved that goal.[9]

image07

Maybe a little too well.

image01

The foods lowest in fat however are not necessarily the most nutrient dense.     Nutritional excellence and macronutrients are are not necessarily related.

In his blog post Overeating and Brain Evolution: The Omnivore’s REAL Dilemma Robb Wolf says:

I am pretty burned out on the protein, carbs, fat shindig. I’m starting to think that framework creates more confusion than answers.

Thinking about optimum foraging theory, palate novelty and a few related topics will (hopefully) provide a much better framework for folks to affect positive change. 

The chart below shows a comparison of the micronutrients provided by the least nutrient dense 10% of foods versus the most nutrient dense foods compared to the average of all foods available in the USDA foods database.

image18

The quantity of essential nutrients you can get with the same amount of energy is massive!  If eating is about obtaining adequate nutrients then the quality of our food, not just macronutrients or calories matters greatly!

Another problem with simply avoiding fat is that the foods lowest in fat are also the most insulinogenic so we’re left with foods that don’t satiate us with nutrients and also raise our insulin levels.  The chart below shows that the least nutrient dense food are also the most insulinogenic.


what happens when we go low carb?

So the obvious thing to do is to rebel and eliminate all carbohydrates because low fat was such a failure.  Right?

image20

So we swing to the other extreme and avoid all carbohydrates and enjoy fat ad libitum to make up for lost time.

The problem again is that at the other extreme of the macronutrient pendulum we may find that we have limited nutrients.

The chart below shows a comparison of the nutrient density of different dietary approaches showing that a super high fat therapeutic ketogenic approach may not be ideal for everyone, at least in terms of nutrient density.  High fat foods are not always the most nutrient dense and can also, just like low fat foods, be engineered to be hyperpalatable to help us to eat more of them.

image24

The chart below shows the relationship (or lack thereof) between the percentage of fat in our food and the nutrient density.   Simply avoiding or binging on fat does not ensure we are optimising our nutrition.

image12

While many people find that their appetite is normalised whey they reduce the insulin load of their diet high fat foods are more energy dense so it can be easy to overdo the high fat dairy and nuts if you’re one of the unlucky people whose appetite doesn’t disappear.

image08

what happens when we go paleo?

So if ‘paleo foods’ worked so well for paleo peeps then maybe we should retreat back there?  Back to the plantains, the honey and the fattiest cuts of meat?

image27

Well, maybe.  Maybe not.

image06

For some people ‘going paleo’ works really well.  Particularly if you’re really active.

Nutrient dense, energy dense whole foods work really well if you’re also going to the CrossFit Box to hang out with your best buds five times a week.

image11

But for the rest of us that aren’t insanely active, then maybe simply ‘going paleo’ is not the best option…

image25

… particularly if we start tucking into the energy dense ‘paleo comfort foods’.

image03

If we’re not so active, then intentionally limiting our exposure to highly energy dense hyperpalatable foods can be a useful way to manage our OFT programming.

enter nutrient density

A lot of people find that nutrient dense non-starchy veggies, or even simply going “plant based”, works really well, particularly if you have some excess body fat (and maybe even stored protein) that you want to contribute to your daily energy expenditure.

image15

Limiting ourselves to the most nutrient dense foods (in terms of nutrients per calorie) enables us to sidestep the trap of modern foods which have separated nutrients and energy.  Nutrient dense foods also boost our mitochondrial function, and fuel the fat burning Krebs cycle so we can be less dependent on a sugar hit for energy (Cori cycle).

Limiting yourself to nutrient dense foods (i.e. nutrients per calorie) is a great way to reverse engineer optimal foraging theory.

image04

If your problem is that energy dense low nutrient density hyperpalatable foods are just too easy to overeat, then actively constraining your foods to those that have the highest nutrients per calorie could help manage the negative effects of OFT that are engrained in our system by imposing an external constraint.

image22

But if you’re a lean Ironman triathlete these foods are probably not going to get you through.  You will need more energy than you can get from nutrient dense spinach and broccoli.

optimal rehabilitation plan?

So while there is no one size fits all solution, it seems that we have some useful principles that we can use to shortlist our food selection.

  1. We are hardwired to get the maximum amount of energy with the least amount of effort (i.e. optimal foraging theory).
  2. Commercialised manufactured foods have separated nutrients from food and made it very easy to obtain a lot of energy with a small investment.
  3. Eliminating fat can leave us with cheap hyperpalatable grain-based fat free highly insulinogenic foods that will leave us with spiralling insulin and blood glucose levels.
  4. Eating nutrient dense whole foods is a great discipline, but we still need to tailor our energy density to our situation (i.e. weight loss vs athlete).

the solution

So I think we have three useful quantitative parameters with which to optimise our food choices to suit our current situation:

  1. insulin load (which helps as to normalise our blood glucose levels),
  2. nutrient density (which helps us make sure we are getting the most nutrients per calorie possible), and
  3. energy density (helps us to manage the impulses of OFT in the modern world).

image30

I have used a multi criteria analysis to rank the foods for each goal.  The chart below shows the weightings used for each approach.

image23

The lists of optimal foods below have been developed to help you manage your primal impulses.  The table below contains links to seperate blog posts and printable .pdfs for a range of dietary approaches that may be of interest depending on your goals and situation.

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 you identify your optimal dietary approach.

survey

I hope this helps.

Good luck out there!

references

[1] http://ketosummit.com/

[2] https://en.wikipedia.org/wiki/Optimal_foraging_theory

[3] http://www.hoajonline.com/obesity/2052-5966/2/2

[4] https://www.ncbi.nlm.nih.gov/pubmed/24564590

[5] http://nutritiondata.self.com/topics/fullness-factor

[6] https://www.ncbi.nlm.nih.gov/pubmed/7498104

[7] https://www.nextnature.net/2013/02/how-food-scientists-engineer-the-bliss-point-in-junk-food/

[8] https://en.wikipedia.org/wiki/Agricultural_subsidy

[9] http://blog.diabeticcare.com/diabetes-obesity-growth-trend-u-s/

a fresh perspective on nutrition

Warning: This post is a celebration of how data analysis can help us understand how to optimise our nutrition to suit different goals.  It may contain novel ideas based on large amounts of data.   

I was flattered when Chris Green (@heuristics) recently posted a graphical presentation of the food insulin index and my nutrient density data analysis using Tableau.

If you click on the image below you can see where the different foods sit on the plot of nutrient density versus proportion of insulinogenic calories or click on individual data points to learn more about a particular food and find out why it ranks well or poorly.

I think presenting the data in an interactive format using Tableau makes large amounts of data more accessible compared to a static chart or spreadsheet that can be produced in Excel.

image41

Inspired by Chris’s chart, I uploaded the Food Insulin Index data for 147 foods from Kirstine Bell’s thesis Clinical Application of the Food Insulin Index to Diabetes Mellitus.

Click on the chart below to see a larger version or, better yet, open the interactive Tableau version here.   Click on the different tabs to see how your insulin response relates to different parameters such as carbohydrates, fat, protein, glycemic index, glycemic load and sugar.

image12

I think the food insulin index data is exciting because it helps us better understand what drives blood glucose, insulin, Hyperinsulinemia, metabolic syndrome, and the diseases of western civilisation that are sending us to an early grave and bankrupting our western economy.

I’ve included some brief notes on the interactive charts in order to unpack what I think the data is telling us, but if you want a more detailed discussion of the data I encourage you to check out the articles:

investing your insulin budget wisely

I think being able to better understand our insulin response to food is exciting for people with Type 1 diabetes (like my wife) to more accurately calculate their insulin dose or people trying to achieve therapeutic ketosis for the treatment of epilepsy or cancer.

Understanding exactly how fibre and protein affect insulin and glucose demonstrates quantitatively why a low carbohydrate moderate protein approach works so well for people who are insulin resistant.

While lots of people have found the food insulin index data useful, I want to highlight in this article that insulin load is only one factor that should be considered.

image39

If we only consider insulinogenic properties of food there is a risk that we unnecessarily demonise nutrient dense foods that happen to elicit an insulin response.  Rather than avoiding insulin, I think it’s better to think in terms of investing a limited insulin budget.  And just like different people have different levels of income, different people have a different (but still finite) “insulin budget”.  For example…

  • Someone using therapeutic ketogenic approach to battle epilepsy or cancer will want to minimise the insulin load of their diet by eating very high amounts of fat, fasting, and perhaps supplementing with MCTs or exogenous ketones. Someone pursuing therapeutic ketosis will need to pay particular attention to making sure they obtain adequate nutrition within their very small insulin budget.
  • If you have Type 1 Diabetes large doses of insulin will send you on a blood glucose roller coaster that might take a day or two to get under control. Eating a Bernstein-esque low carb diet with moderate to high protein levels and lots of non-starchy veggies will make it possible to manage blood glucose levels with physiologic (normal) amounts of insulin without excessive blood glucose and insulin swings.[1] [2]
  • For a type 2 diabetic who struggles to produce enough insulin to maintain their blood glucose in normal ranges, a lower carb moderate insulin load diet will help their pancreas to keep up and achieve normal blood glucose levels while minimising fat storage.
  • People using a ketogenic approach for weight loss need to keep in mind that reduced insulin levels and ketosis occurs due to a lack of glucose and not higher levels of dietary fat. If your primary goal is weight loss, fat on the plate (or in the coffee cup) should be just enough to stop you from going insane with hunger.  Too much dietary fat will mean that there will be no need to mobilise fat from the body.
  • Athletes and people who are metabolically healthy can be more flexible in their choice of energy source and perhaps focus more on more nutrient dense foods as well as energy dense foods.

insulin is not the bad guy

Humans are great at thinking in absolutes (good/bad; black/white) while ignoring context.  We all like to grab hold of our favourite bit of the elephant of metabolic health and hold on tight.

image02

While many people suffer from hyperinsulinemia and its vast array of associated health consequences we need to remember that insulin is critical to life and growth and is required to metabolise protein for muscle growth/repair as well as all the other important functions of amino acids (neurotransmitters etc).[3]

Ideally we should make every bite count if we want to maximise health and longevity.  Every calorie should contain the maximum amount of nutrients possible.  In a similar way, every unit of insulin that we “invest” should be associated with the maximum amount of nutrition (think of the nutrient density of spinach or liver liver versus than nutrient a soft drink or white bread).

So let’s look at how we can “leverage” our “insulin investment” to maximise our health outcome.

show me the data

In this article I’m going to risk overloading, overwhelming, and confusing you, the reader, with too much data.  But at the same time, with all the data available you won’t have to take my word for it.  You can make your own conclusions.

If the idea is far out, you need to see the data. All the data. Not the hazard ratio, not just the conclusions from the computer.

My new grand principle of doing science: habeas corpus datorum, let’s see the body of the data. If the conclusion is non-intuitive and goes against previous work or common sense, then the data must be strong and all of it must be clearly presented.

So, how should you read a scientific paper? I usually want to see the pictures first.[4]

Richard David Feinman, The World Turned Upside Down

I am trying to draw conclusions from more than 6000 foods in the USDA foods database.  These are hard to present accurately in single charts, so I’ve used a few.  If something that you see doesn’t make sense at first you can drill down into the data to check out the detailed description.  I have also included as much micronutrient and macronutrient as I can.  Just ‘mouse over’ a data point that you’re interested in to see how it compares to another data point.

image30

In the sections below I have given an overview of different ways to look at nutrient density with a more detailed discussion in the appendices at the end of this article.   Unfortunately this post is probably not going to work well on your phone.

You’ll need to view it on big screen for best effect.

Sorry.

My 2c on nutrient density

Lots of people talk about nutrient density, however most of the time this is in relation to a few favourite nutrient(s) rather than a broad range spectrum of essential vitamins, minerals, amino acids and fatty acids.

We hear that butter is high in Vitamin K2 and Vitamin D and hence we should eat more of it[5] or that whey protein is high in essential amino acids (e.g. leucine and lysine) and therefore everyone should be buying tubs of it.[6]

A lot of time these claims are used to advertise a product or to argue a particular philosophical position (e.g. zero carb, vegan, plant based, paleo etc).  The problem here is that many of these so call ‘nutrient dense superfoods’ do not contain a well rounded range of the nutrients that are required for health, but rather a narrow slice of nutrients.

Paleo, Just Eat Real Foods[7] or ‘plant based’ is a good start, however I think there are some foods that are more useful than others.  As detailed in the Building a Better Nutrient Density Index article there are also  some nutrients that are harder to obtain in adequate quantities.

Once we identify the nutrients that are harder to obtain we can focus on the foods that contain the highest amounts of these nutrients.   At the same time it is also useful to think about nutrient density in the context of specific goals, whether that be therapeutic ketosis, weight loss, diabetes or optimal athletic performance.

The more I try to get my head around what it means to optimise nutrition, the more important nutrient density seems to be.  The irony is that many people retreat from insulin to the safe haven of high fat diets that don’t actually have the micronutrients required to optimally power mitochondria, the power plants of our bodies.  Like most things, we need to find the right balance.

Most people now seem to understand that hammering high blood glucose with more insulin is dumb because the problem is insulin resistance and poor glucose disposal, not high blood glucose.

But then the next question is what causes insulin resistance?

It seems to me that part of the answer is sluggish mitochondria that aren’t running at optimal efficiency to burn off the energy we throw at them.  Part of the reason for this is that we’re not powering them with the right nutrients.

To produce ATP efficiently, the mitochondria need particular things.  Glucose or ketone bodies from fat and oxygen are primary.

Your mitochondria can limp along, producing a few ATP on only these three things, but to really do the job right and produce the most ATP, your mitochondria also need thiamine, riboflavin, niacin, pantothenic acid, minerals (especially sulfur, zinc, magnesium, iron and manganese) and antioxidants.

Mitochondria also need plenty of L-carnitine, alpha-lipoic acid, creatine, and ubiquinone (also called coenzyme Q) for peak efficiency.

Dr Terry Wahls

The Wahls Protocol

Terry%20Wahls,%20M.D.%20Photo%20and%20Book%2003272014[1]

This video gives an excellent overview of the role that nutrients play to drive the krebs cycle to enable our mitochondria to produce ATP, the energy currency of our cells.

We can then moderate that using insulin load to  work within the limits of your current metabolic health (i.e. insulin resistance, muscle mass, activity levels, pancreatic function etc).

You need to eat to maintain the blood glucose levels of a metabolically healthy person.

Robb Wolf

robbwolf-468x468[1]

Nutrient density vs proportion of insulinogenic calories

The plot below shows nutrient density versus proportion of insulinogenic calories.   The size of the data points are proportional to the energy density of the foods they represent (e.g. the size of the markers for celery with a low energy density are smaller than for butter which has a high energy density).

image35

There is a lot of data here!  You can click on the image below to see a larger version of the chart or better yet look at the interactive online Tableau version (which I think is pretty cool!).  If you ‘mouse over’ the foods that you’re interested in you can see more details of the foods from the USDA food nutrient database.  Click through the various tabs to see how things look for specific food groups.

The x-axis on these charts is nutrient density / calorie.  You can find out more about how this is calculated in the Building a better nutrient density index article.  Essentially zero is average (or zero standard deviations from the mean) while greater than zero is better than average and less than zero is worse than the average of the 6000 foods analysed.

The nutrient density calculations are based on the USDA database which provides the nutrient content of more than 6000 foods.  It does not account for species specific bioavailability or issues such as fat soluble vitamins.  

I don’t think we can use this to say that plant foods are better or worse than animal foods, but rather it shows us which foods to avoid due and which foods are the best choices within particular categories.  

Personally I think optimal involves getting a balanced range of the most nutrient dense plant and animal based foods. 

So what does this data mean and how could it be practically useful?

  • If you’re metabolically healthy then I think you’d do well eating from the most nutrient dense foods on the right hand side of the chart (i.e. celery, spinach, mushrooms, onions, oranges etc). While many of these nutrient dense foods may have higher proportion of insulinogenic calories I think it’s hard for most people to overeat them.
  • The foods most people should avoid are the highly insulinogenic low nutrient density foods on the top left of this plot (i.e. soft drinks, fruit juice, sport drinks etc).
  • If you’re insulin resistant or aiming for therapeutic ketosis (e.g. as an adjunct treatment for cancer or epilepsy or dementia) you will want to move down the chart to the higher fat low insulinogenic foods while keeping to the right as much as possible.
  • It’s important to note that the high fat foods typically have a lower nutrient density because they do not contain as broad a range of nutrients.

Energy density versus nutrient density

While 60 to 70% of the western population seem to be suffering some level of metabolic syndrome and are insulin resistant[8] some people who are metabolically healthy are still obese.[9]  For these people simply reducing the energy density without consideration of carbs or insulin load (i.e. lowering their fat intake with higher amounts of water and fibre) will help them to consume less calories.

image03

Someone who is metabolically healthy (i.e. excellent blood glucose levels etc) yet still obese would do well to focus on the nutrient dense low energy density vegetables, fruits, seafood and meat in the top right of this chart.

This is basically where I’m at after normalising my glucose and HbA1c but I’d still like to drop some more weight.  I now need to take my own advice and focus on more nutrient dense proteins and vegetables and indulge less on the yummy high fat foods.

The typical problem with a low fat approach typically comes not from eating too much vegetables or fruit (top right of this chart) but rather when your energy comes from highly insulinogenic, energy dense low nutrient density foods (e.g.  processed grains and softdrinks) which end up on the top left of all of these charts.

The only real ‘problem’ with a high nutrient density low energy density approach is that it is physically difficult to get enough food down to achieve an energy surplus.  The benefit is that it typically leads to weight loss while still maintaining very high levels of nutrition.

A high nutrient density low energy density approach could still be ketogenic due to the low level of processed carbohydrates and low insulin load.

Click here to view the interactive Tableau version of nutrient density versus energy density.

Net carbs versus nutrient density

Lots of people like to count carbohydrates or net carbohydrates (i.e. carbohydrates minus the indigestible fibre).  In my view I think it’s better to think in terms of net carbohydrates when eating real foods to make sure you don’t miss out on nutrient dense vegetables.

The chart below shows nutrient density versus net carbohydrates.  Focusing on the foods on the top right and avoiding the soft drinks, cereals and breads at the bottom will be a pretty good strategy.

The limitation of net carbs is that it doesn’t account for the impact of protein which is an important consideration for people with type 1 diabetes or advanced type 2 diabetes.

image28

Click here to view an interactive Tableau version of nutrient density versus net carbs.

Insulin load versus nutrient density

This brings us to my favourite way to look at nutrient density… insulin load.

Thinking in terms of insulin load involves consideration of net carbs plus about half the protein as requiring insulin.  Insulin load per 100g of food is neat because it means that we also end up with lower energy density foods as well which is not a bad thing for most people who often wouldn’t mind losing some weight (note: low energy density foods like celery may not be so great if you’re trying to fuel for a marathon).

I think it’s good to also consider the insulin effect of protein because insulin is a finite resource.   While people who are metabolically healthy will be able to eat high protein foods without seeing a substantial rise in their blood glucose levels, people who are very insulin resistant or have type 1 diabetes will see their  glucose levels rise with protein and may need to inject insulin to cover the protein they eat.  This doesn’t mean though that people who are insulin resistant should avoid high protein foods, because they are typically very nutrient dense.

image33

Again, we can see that it’s the soft drinks, breakfast cereals and breads at the bottom of this chart that we really need to be avoiding!

This thinking seems to align with common sense wisdom.  Tick.

Click here to view an interactive version of insulin load versus nutrient density.

Summary

Hopefully you can see how thinking about nutrient density graphically in combination with other parameters can be useful to refine your food selection for different goals.

The appendices to this article below show more charts for different food groups with a little more discussion of my observations.

Or better yet, why not dive into the interactive data in Tableau and see what you can make of it yourself.

  • Appendix A – Nutrient density vs proportion of insulinogenic calories for therapeutic ketosis
  • Appendix B – Nutrient density vs energy density for weight loss and / or the metabolically healthy
  • Appendix C – Nutrient density vs net carbohydrates for people on a low carb diet
  • Appendix D – Nutrient density vs insulin load for diabetes and therapeutic ketosis

Appendix A – Nutrient density vs proportion of insulinogenic calories for therapeutic ketosis

Foods with a lower proportion of insulinogenic calories can be useful for people trying to achieve therapeutic ketosis, however at the same time we can see at the bottom of this plot that high fat / low insulin load foods are not necessarily the most nutrient dense.

People should ideally choose foods with the highest nutrient density (right hand side) while keeping the proportion of insulinogenic calories in their diet low enough to achieve their goals (e.g. blood glucose, insulin, tumour growth or seizure control).

image35

Click here to view the interactive Tableau version of nutrient density proportion of insulinogenic calories.

Vegetables

Vegetables are typically have high levels of vitamins and minerals as well as some protein but not much fat.

Most people, particularly those who are not severely insulin resistant, will do well to focus on the most nutrient dense vegetables on the right hand side of this chart (i.e. celery, spinach, squash, cabbage, broccoli, mushrooms, artichokes, kale) as their energy density, insulin load and net carbs are also low.

Celery is an example of a food with high amounts of vitamins and minerals with a very low energy density, hence it does really well on the nutrients / calorie scale.

The foods in the chart below with the lowest proportion of insulinogenic calories typically have added fat (e.g. french fries, onion rings which are not ideal) or are very high in fibre (e.g. asparagus, spinach and soybeans which is better).

image49

Seafood

Seafood is really the only substantial source of essential omega 3 fatty acids (i.e. DPA, DHA, EPA, ALA) and hence is an important part of a balanced diet.

The highest nutrient density seafoods are cod, anchovy, salmon, caviar and tuna.  The lowest insulin load fish are mackerel, herring, salmon and caviar.

Again, we should ideally focus on the most nutrient dense foods on the right hand side of the chart, but move down the chart to the least insulinogenic foods depending on our level of metabolic health.

image23

Animal products

Liver is the most nutrient dense of the animal products (right hand side) while processed meats are less nutrient dense (left hand side).  High fat meats are also typically less nutrient dense (bottom of chart).

Non-processed meats are typically well worth the investment of your limited insulin budget.

image32

Nuts seeds

Many nuts and seeds are high fat while also being fairly nutrient dense (i.e. pine nuts, coconut and pecans).  Nuts have a low proportion of insulinogenic calories and hence help to normalise blood glucose levels, but possible to overdo if weight loss is your primary goal.

image10

Dairy and egg

Some dairy products are both high fat and nutritious (e.g. parmesan cheese, egg yolk).

Cream and butter are high fat and energy dense so are useful for managing blood glucose levels but are possible to overdo if weight loss is your primary goal.

Low fat dairy products such as skim milk and whey are typically very nutrient poor overall.

image38

Fruit

Some fruits are nutrient dense, but are typically highly insulinogenic (tangerines, cherries, grapes, apricots, oranges and figs).  Only olives and avocados have a low proportion of insulinogenic calories, however they are not particularly nutrient dense.

image08

Cereals and grains

Unprocessed grains such as oatmeal, teff, spelt, brown rice and quinoa can be nutrient dense but are highly insulinogenic.  Unprocessed grains may be fine if you are metabolically healthy, but choose carefully and don’t go adding sugar, honey or molasses.

However breakfast cereals and most breads are typically highly insulinogenic while also having a poor nutrient density and hence are a poor investment of your limited insulin budget.

This analysis supports the idea that dropping processed grains, packaged breakfast cereals and soft drinks would be a pretty good place to start for most people!

image11

Legumes

Navy beans, lima beans and lentils are nutrient dense but highly insulinogenic.

Peanuts, peanut butter and tofu do OK in terms of both being low insulinogenic as well as nutrient dense.

Processed soy products and meat replacement products are typically highly insulinogenic and have poor nutrient density.

image45

Fats and oils

Fish oil is the most nutritious of the fats.  However as a general rule pure fats are not particularly nutrient dense.  Margarines and salad dressings are very nutrient poor.

image27

Beverages

Soft drinks, sports drinks and sweetened iced teas are bad news and are an extremely bad investment of your limited insulin budget.  Fruit juices are not also not particularly nutrient dense.  Better to eat your fruit whole.

image40

Appendix B – Nutrient density vs energy density

Low energy density, high nutrient density foods are a great way to lose weight, particularly for those who are insulin sensitive.  As we avoid processed carbs as well as high levels of dietary fat while maintaining high levels of nutrition we can allow the fat to come from our belly rather than our plate.

image03

Click here to view the interactive Tableau version of nutrient density versus energy density.

Vegetables

It’s hard to go wrong with the low energy density high nutrient density foods in the top right of this chart (i.e. celery, mushrooms, spinach, onions, broccoli, seaweed, kale etc).

image34

Seafood

Some seafood is nutrient dense and lower in fat (e.g. oysters, tuna, lobster).

Seafood is important because it provides the essential omega 3 fatty acids that are hard to obtain in significant amounts from vegetables and it provides higher levels of protein.

If you are serious about losing weight you’d do pretty well if you limited yourself to the vegetables in the top right of the chart above and the seafood in the top right of the chart below.

Animal products

There are many nutrient dense low energy density animal foods as shown in the chart below.  Liver does pretty well followed by game meat.  Processed meats are not so good.

image24

Nuts seeds

Nut are low insulin but not necessarily low energy density or spectacularly great in terms of nutrients per calories.  Consider limiting your nuts and seeds if your primary goal is weight loss.

image25

Dairy and egg

Whole egg (top right corner) is probably your best option from the dairy and egg category.

Butter and full fat cheese have a high energy density (bottom).

Low fat dairy is nutrient poor (top left corner)!

2016-09-04 (1)

Fruit

If your goal is weight loss then low energy density fruits such as tangerines / mandarins, cherries, apricots and pears will be more helpful than energy dense fruits such as bananas, prunes, raisins and dried fruits.

image09

Cereals and grains

Some unprocessed grains are nutritious and have a low energy density (top right), however as a general rule, breakfast cereals and processed grains are a poor investment of your limited insulin budget (bottom of chart).

image31

Legumes

Lima beans, navy beans, tofu, mung beans and hummus are nutrient dense and low energy density (top right).   Peanuts have a  low insulin load and solid nutrient density but a high energy density (bottom).

image48

Appendix C – Nutrient density vs net carbohydrates for diabetes

Most people keeping track of their carbohydrate intake think in terms of net carbs or total carbohydrates, however this does not consider the insulin demand from protein which is a real consideration if you have diabetes.

Thinking in terms of net carbs will be the best approach for most people; however, if you are highly insulin resistant or have type 1 diabetes you may be better to consider insulin load which considers the effect of protein on insulin.

Choosing foods to the top right of these charts will help you keep nutrition high and net carbohydrates low.

image28

Click here to view an interactive Tableau version of nutrient density versus net carbs.

vegetables

There are plenty of vegetables on the top right of this plot that have minimal net carbs while being very nutrient dense (e.g. celery, spinach, broccoli, asparagus, mushrooms).

Low water foods such as mushrooms, leeks, shallots (at the bottom of the plot) will be hard to eat large quantities of although they have a higher amount of net carbs per 100g.

2016-09-04 (2)

seafood

Most seafood has minimal levels of net carbs, though it’s interesting to note that some seafoods such as oysters have a glycogen pouch depending on what time in the season they are harvested.

image44

animal products

Similar to seafood, most animal products have negligible amounts of net carbs.  The amount that is contained in muscle glycogen is not significant.

Liver and game meats are consistently the most nutrient dense of the animal products.

2016-09-04 (4)

nuts seeds

Nuts and seeds have some non-fibre carbohydrates.  Pine nuts, macadamias and almonds are low in carbs with moderate nutrient density.

image42

dairy and egg

Many dairy and egg products have a high nutrient density as well as being low in net carbs which is why they are popular with low carbers.  Fat free cheeses have more carbohydrates.

2016-09-04 (7)

fruit

There are some lower carb fruits however, it may be wise for people with insulin resistance to avoid many of the higher carbohydrate fruits at the bottom of this chart.

image22

cereals and grains

This chart demonstrates why many breakfast cereals and processed grains (at the bottom of this chart with high levels of carbohydrates and minimal nutrition) are a bad investment of your limited insulin budget.  This style of analysis demonstrates why the common wisdom that soft drinks and breakfast cereals are bad news.

image04

legumes

Not all legumes are created equal.  Choose wisely.  Navy beans, legumes, lima beans and peanuts are probably your safest bet.

image50

beverages

Soft drinks and sports drinks are a very poor investment of your limited insulin budget as they are very low in nutrients.

image29

 

Appendix D – Nutrient density vs insulin load

Thinking in terms of nutrient density versus insulin load enables us to more intelligently consider how we invest our insulin budget.  Again, it’s not that insulin is bad, but rather we should use it wisely for the most nutrient dense foods.

Soft drinks, breakfast cereals and bread at the bottom of this chart are a poor way to invest the limited capacity of your pancreas.

image33

Click here to view an interactive version of insulin load versus nutrient density.

vegetables

Don’t be afraid of vegetables.  Most of them have a very low insulin load.  They should take up a large amount of your plate.  But choose wisely from the top corner (e.g. celery, spinach, squash cabbage, broccoli).

image37

seafood

There are lots of good investments to be made in the top right of this chart of seafood (oyster, salmon, lobster, mackerel).

image51

animal products

Animal products require insulin but they are rich in amino acids which play an important role in the body.   The amount you need will be dependent on your situation and your goals (e.g.  someone aiming for therapeutic ketosis will want less while someone looking to build muscle or retain muscle while dieting will want more protein).

image16

nuts seeds

Looking at nuts in terms of insulin load rather than net carbs enables better differentiation based on how much insulin these foods will demand from your system.   Pine nuts, macadamia nuts and coconut have the lowest insulin load while being nutrient dense.

image43

dairy and egg

Dairy can be insulinogenic, however the higher fat butter, cream and egg still have a fairly low insulin load.

image21

fruit

Grapefruits, cherries, apples, grapes and oranges have a large amount of nutrition with a low insulin load versus more concentrated or dried fruit options.

2016-09-04 (9)

cereals and grains

The breakfast cereals at the bottom of this chart with high amounts of insulin demand and lower levels of nutrients are bad news people who are insulin resistant.

image00

legumes

Lima beans, navy beans, and lentils have a fairly low insulin load and high nutrient density.  However if you are insulin resistant you will need to eat to your metre and make sure your blood glucose levels don’t rise too much if you eat legumes.

image45

fats and oils

Just because it is low insulin doesn’t mean that it is good for you.  Not many very high fat foods have substantial nutrient density.  When it comes to nutrient density, fats in whole foods are a better than trying to consume refined oils.

image47

Beverages

Soft drinks are bad news as they will stimulate large amounts of insulin while providing minimal amounts of nutrition and satiety.

image15

 

references

[1] https://www.youtube.com/channel/UCuJ11OJynsvHMsN48LG18Ag

[2] http://www.diabetes-book.com/

[3] http://www.moodcure.com/

[4] Feinman, Richard David (2014-12-12). The World Turned Upside Down: The Second Low-Carbohydrate Revolution

[5] http://chriskresser.com/vitamin-k2-the-missing-nutrient/

[6] http://www.whfoods.com/genpage.php?tname=foodspice&dbid=38

[7] https://iquitsugar.com/jerf-just-eat-real-food/

[8] https://www.youtube.com/watch?v=horIrfmLvUY

[9] https://en.wikipedia.org/wiki/Metabolically_healthy_obesity

how to make endogenous ketones at home

I’ve spent some time lately analysing these 1100 ketone vs glucose data points looking for the secret to achieving optimal ketone values for weight loss and health.

image23

As you can see from this chart, there is a relationship between ketones and glucose.  As your blood glucose levels decrease your blood ketones rise to compensate.

Different glucose : ketone relationships for different people

It seems that each person has a unique relationship between their blood glucose and ketone values that gives us an insight to understand their insulin resistance status and metabolic health.

image02

Characterisation of different metabolic states

Similar to Dr Kraft’s insulin curves, we can characterise different levels of insulin resistance metabolic health using the relationship between glucose and ketones.

image27

If you want to know why hyperinsulinemia is the “unifying theory of chronic disease” it’s worth taking the time to read up on it to provide some more context for the discussion later in this article. [1] [2] [3] [4] [5]

Type 2 Diabetes

If you have type 2 diabetes and your blood glucose levels are consistently high, you are not metabolising carbohydrates well, and will likely benefit from a lower insulin load dietary approach.

When you go a long time between meals, your ketones don’t kick in because of high insulin levels and / or your mitochondria are not functioning optimally.  You feel tired and hangry.

Particularly in the early stages when someone is still insulin resistant, a lower insulin load dietary approach will help with satiety and carb cravings while keeping blood glucose levels under control.

Hyperinsulinemia and metabolic disorders

If your blood glucose levels are very low and ketone levels are also very low, you may have an infection or a metabolic disorder that is stopping you from producing enough energy.

The yellow line in the chart above is based on an actual person who is suffering from a range of metabolic related issues including obesity, PCOS, depression, etc.  For these people, EXOGENOUS ketones may help to relieve the debilitating symptoms of acute Hyperinsulinemia.

Exciting research is currently underway looking at the use of EXOGENOUS ketones as an adjunct treatment for cancer or to provide energy directly to the mitochondria for people with epilepsy, dementia, Alzheimer’s and the like.[6]  [7]  

2016-08-11.png

Patrick Arnold, who worked with Dr Dominic D’Agostino to develop the first ketone esters and BHB salts, has noted that exogenous ketones may help alleviate the symptoms of the ‘keto flu’ during the transition from a high carb to a low carb dietary approach.


However, as noted by Robb Wolf, once you have successfully transitioned to a lower carb eating style you would need to reduce or eliminate the exogenous ketones to enable your body to fully up-regulate lipolysis (fat burning), maximise ENDOGENOUS ketone production and access your ENDOGENOUS FAT stores.

2016-08-08.png

Insulin resistant

Someone with diabetes who persists with a nutrient dense low insulin load dietary approach may be able to successfully normalise their blood glucose and insulin levels.  When this happens your body will be able to more easily release ENDOGENOUS ketones which will help improve satiety between meals, and decrease appetite which will in turn lead to weight loss.  Exercising to train your body to do more with less is also helpful.

image20

If you are insulin resistant you are probably not able to metabolise carbohydrates, protein or fats very well.  The light blue “mild insulin resistance” line is based on my ketone and glucose values when I started trying to wrap my head around this ketosis thing.

image27

I enthusiastically started adding unrestricted amounts of fat from all the yummy stuff (cheese, butter, cream, peanut butter, BPC etc) in the hope of achieving higher ketone levels and therefore weight loss, but I just got fatter and more inflamed as you can see in the photo on the left.  My blood tests suggested I was developing fatty liver in my mid 30s!  And I thought I was doing it right with the bacon and BPC?!?!?

The photo on the right is after I worked out how to decrease the insulin load of my diet and learning about intermittent fasting from Jason Fung.  I realised that ENDOGENOUS ketosis and weight loss is caused by a lower dietary insulin load, not more EXOGENOUS fat on your plate or in your coffee cup.

image05

I recently had my HbA1c tested at 4.9%.  It’s getting there.  But knowing what I know now about the importance of glucose control,  I would love to lose a bit more weight and see my HbA1c even lower.

I recently purchased a couple of bottles of KetoCaNa from the USA after hearing a number of podcast interviews with Dominic D’Agostino and Patrick Arnold.[8] [9]

This metabolic jet fuel is definitely fascinating stuff!  My experience is that it gives me the buzz like a BPC, but also has an acute diuretic effect (meaning I need to stay close to a toilet and long drives to work in slow traffic were sometimes humiliating).

I had hoped it would have a weight loss effect like some people seemed to be saying it would.

2016-08-10

I did find it had an amazing impact on my appetite.  While it was in my system I didn’t care as much about food.  However once the ketones were used up my appetite came flooding back.  It was like I had ‘bonked’ all of a sudden and needed LOTS OF FOOD NOW!

image17

Unfortunately my hunger and subsequent binge eating seemed to offset the short term appetite suppression.  And it was not going to be financially viable for me to maintain a constant level of artificially elevated ketone levels.

I asked around to see if anyone had come across studies demonstrating long term weight loss effects of exogenous ketones.[11]   It was a VERY enlightening discussion if you want to check it out here.  Wow!

image30

The Pruvit FAQ says that one of the benefits of Keto//OS is weight loss, however no reference to the research studies was provided to Pruve this claim.

AVPageView 11082016 13036 PM.bmp.jpg

Also, the studies that were referenced in the Pruvit FAQ all appear to relate to the benefits of ENDOGENOUS or nutritional ketosis rather than EXOGENOUS ketone supplementation.

Princess_Bride_That_Word

According to a Pruvit tele-seminar the EXOGENOUS ketone salts were not designed to be a weight loss product and hence have not been studied for weight loss.

The only studies that we could find that mentioned EXOGENOUS ketone supplementation and weight loss were on rats an they found that there was no long term effect on weight loss.[12]   

So in spite of my hopeful $250 outlay it seems that exogenous ketones ARE just a fuel source after all.

image06

Even the experts don’t seem to think exogenous ketones help with fat loss.

image25

 

image28

image16 [13]

Confused yet?  I don’t blame you.

Metabolically healthy

The “metabolically healthy” line in the chart above is based on RD Dike man’s ketone and glucose data when he recently did a 21 day fast.

image32

Due to his hard earned metabolic health and improved insulin resistance he has developed the ability to fairly easily release ketones when goes longer periods between meals.

2016-08-10 (2).png

RD has achieved a spectacular HbA1c of 4.4%.  Perhaps a two or three day water only fast testing blood glucose and ketones with no exercise would be a useful test of your insulin status?  You could use RD’s line as the gold standard.

image04

In spite of his improvement in insulin resistance and blood glucose control, he still says the “siren” of hunger is incredibility difficult to resist and mastering appetite is more challenging than particle physics.  As a Chief Scientist at Lockheed Martin, he would know.

RD also told me that when he is not fasting and is eating his regular nutrient dense higher protein meals his ketone levels are not particularly high. While RD fairly easily produces ketones, it seems they are also quickly metabolised so they do not build up in his bloodstream.

I know Luis Villasenor of Ketogains finds the same thing.

image10

Total energy = ketones + glucose

Where this gets even more interesting is when we look at the glucose and ketone data in terms of TOTAL ENERGY.  That is, from both glucose and ketones.

2016-08-12 (11)

The average TOTAL ENERGY of the 1100 data points from these 26 fairly healthy people working hard to achieve nutritional ketosis is 6.1mmol/L. It seems the body works to maintain homeostasis around this level.

When the TOTAL ENERGY in our bloodstream increases outside of the normal range it appears the body raises insulin to store the excess energy.  That is, unless you have untreated Type 1 Diabetes, in which case you end up in diabetic ketoacidosis with high blood glucose and high ketones.

Regardless of whether your energy takes the form of glucose, ketones or free fatty acids they all contribute to acetyl-coA which is oxidized to produce energy.  Forcing excess unused energy to build up in the bloodstream is typically not desirable and can lead to long term issues (gyration, oxidized LDL etc).

I’m not sure if ketones can be converted to glucose or body fat, but it makes sense that excess glucose would be converted to body fat via de novo lip genesis to decrease the TOTAL ENERGY in the blood stream to normal levels.

A number of studies seem to support this view including Roger Unger’s 1964 paper the Hypoglycemic Action of Ketones.  Evidence for a Stimulatory Feedback of Ketones on the Pancreatic Beta Cells.[14]

Ketone bodies have effects on insulin and glucagon secretions that potentially contribute to the control of the rate of their own formation because of antilipolytic and lipolytic hormones, respectively.  Ketones also have a direct inhibitory effect on lipolysis in adipose tissue.[15]

This guy seems to agree too.  But what would he know? [16]  [17] [18]

image26

Looking at the glucose and ketones together in terms of TOTAL ENERGY was a bit of an ‘ah ha’ moment for me.  It helped me to understand why people like Seyfried and D’Agostino always talk about the therapeutic benefits and the insulin lowering effects of a calorie restricted ketogenic diet. [19] [20] [21] [22]

Dealing with high ketones and high glucose typically a concern fro the body because it just doesn’t happen in nature with real whole foods.  But now we have refined grains, HFCS, processed fats and exogenous ketones to ‘bio-hack’ our metabolism and send it into overdrive.

While fat doesn’t normally trigger an insulin response, it seems that excess unused energy in the blood stream, regardless of the source, will trigger an increase in insulin to reduce the TOTAL ENERGY in the blood stream.

I am concerned that if people continue to enthusiastically zealously focus on pursuing higher blood ketones “through whatever means you can”[24] in an  effort to amplify fat loss they will promote excess energy in the bloodstream which will lead to insulin resistance and hyperinsulinemia.

Using multi-level marketing tactics to distribute therapeutic supplements to the uneducated masses who are desperate to lose weight with a ‘more is better’ approach also troubles me deeply.

My heart sank when I saw this video.

MORE investigation required?

There are anecdotal reports that use of exogenous ketones provide mental clarity, enhanced focus and athletic performance benefits.  At the same time there are also people who have been taking these products for a while that don’t appear to be doing so well.

A July 2016 study Ketone Bodies and Exercise Performance: The Next Magic Bullet or Merely Hype? didn’t find that EXOGENOUS ketones were very exciting.

Recently, ketone body supplements (ketone salts and esters) have emerged and may be used to rapidly increase ketone body availability, without the need to first adapt to a ketogenic diet. However, the extent to which ketone bodies regulate skeletal muscle bioenergetics and substrate metabolism during prolonged endurance-type exercise of varying intensity and duration remains unknown. Therefore, at present there are no data available to suggest that ingestion of ketone bodies during exercise improves athletes’ performance under conditions where evidence-based nutritional strategies are applied appropriately.

Another study by Veech et al (who is trying to bring his own ketone ester to market) from August 2016 Nutritional Ketosis Alters Fuel Preference and Thereby Endurance Performance in Athletes found in favour of ketones.

Ketosis decreased muscle glycolysis and plasma lactate concentrations, while providing an alternative substrate for oxidative phosphorylation. Ketosis increased intramuscular triacylglycerol oxidation during exercise, even in the presence of normal muscle glycogen, co-ingested carbohydrate and elevated insulin. These findings may hold clues to greater human potential and a better understanding of fuel metabolism in health and disease.

I can understand how exogenous ketones could be beneficial for someone who is metabolically healthy and consuming a disciplined hypo-caloric nutrient dense diet.  They would likely be able to auto regulate their appetite to easily offset the energy from the EXOGENOUS ketones with less food intake.

While it seems that EXOGENOUS ketones assist in relieving the symptoms of metabolic disorders I’m yet to be convinced that a someone who is obese and / or has Type 2 Diabetes would do as well in the long term, especially if they were hammering MOAR fat and MORE exogenous ketones (along with maybe some sneaky processed carbs on the side) in an effort to get their blood ketones as higher in the hope of losing body fat.

Some questions that I couldn’t find addressed in the Pruvit FAQ that I think would be interesting to study in a long term controlled environment in the in the future are:

  1. What is the a safe dose limit of EXOGENOUS ketones for a young child?  How would you adjust their maximum intake based on age and weight?
  2. IF EXOGENOUS ketones do have a long term weight loss effect what is the upper limit  of intake of EXOGENOUS ketones to avoid stunting a child’s growth?
  3. Is there a difference in the way EXOGENOUS ketones are processed in someone is metabolically healthy versus someone who is very insulin resistant?
  4. Does the affect on appetite continue beyond the point that the ketones are out of your system?
  5. Do you need to take EXOGENOUS ketones continuously to maintain appetite suppression?  Does the effect of ENDOGENOUS wear off as your own ENDOGENOUS ketone production down regulates?  Do you need to keep taking more and more EXOGENOUS ketones to maintain healthy appetite control?
  6. How should someone with Type 2 Diabetes adjust their medication and insulin dose based on their dose of EXOGENOUS ketones?  Should they be under medical supervision during this period?
  7. Is there a difference in health outcome if you are taking EXOGENOUS ketones in the context of a hypo-caloric ketogenic diet versus a hyper-caloric ketogenic diet?  What about a diet high in processed carbs?
  8. Is there a minimum effective dose to achieve optimal long term benefits to your metabolic health or is MORE better?
  9. Are the long term health benefits of EXOGENOUS ketones equivalent to a calorie restricted ketogenic diet?

Unfortunately, I think we will find the answers to these questions sooner rather than later with the large scale experiment that now seems to be well underway.

Perhaps the burden of proof is actually on Pruvit to prove it rather getting their Pruvers to demonstrate that within 59 minutes they are successfully peeing out the product they’ve just paid some serious money for!

The lower the better?

Alessandro Ferretti recently made the observation that metabolically healthy people tend to have lower TOTAL ENERGY levels at rest (and hence have a lower HbA1c), but are able to quickly mobilise glycogen and fat easily when required (e.g. when fasting or a sprint). They are metabolically flexible[25] and metabolically efficient.[26]   

These people would have been able to both conserve energy during a famine and run away from a tiger and live to become our ancestors, while the ones who couldn’t didn’t.

image29

Similar to RD Dikeman, John Halloran is an interesting case.  Recently he has been putting a lot of effort into eating nutrient dense foods, intermittent fasting and high intensity exercise.

image13

He is also committed to improving his metabolic fitness to be more competitive in ice hockey.  His resting heart rate is now a spectacular 45 bpm!

image08

And he’s been able to lose 10kg (22lb) during July 2016!

image12

At 5.2mmol/L (i.e. glucose of 4.0mmol/L plus ketones of 1.2mmol/L) John’s TOTAL ENERGY is lower than the average of the 26 people shown in the glucose + ketone chart above.  Looking good John!

It seems excellent metabolic health is actually characterised by lower TOTAL ENERGY.

MORE is not necessarily BETTER when it comes to health.

Fast well, feed well

To clean up the data a little I removed the ketones vs glucose data points for a couple of people who I thought might be suffering from pancreatic beta cell burnout and one person that was taking exogenous ketones during their fast that had a higher TOTAL ENERGY.  I also removed the top 30% of points that I thought were likely high due to measuring after high fat meals.

So now the chart below represents the glucose and ketone values for a group of reasonably metabolically healthy people following a strict ketogenic dietary approach, excluding for the effect of high fat meals, BPC, fat bombs and the like.

image22

The average ketone value for this group of healthy people trying to live a ketogenic lifestyle is 0.7mmol/L. Their average glucose is 4.8mmol/L (or 87mg/dL). The average TOTAL ENERGY is 5.5mmol/L or 99mg/dL.

ketones (mmol/L)

blood glucose (mmol/L)

total energy (mmol/L)

average

0.7

4.8

5.5

30th percentile

0.4

4.6

5.2

70th percentile

0.9

5.1

5.8

The table below shows this in US units (mg/dL).

ketones
(mmol/L)

blood
glucose (mg/dL)

total
energy (mg/dL)

average

0.7

86

99

30th percentile

0.4

83

94

70th percentile

0.9

92

104

It seems we may not necessarily see really high ketone levels in our blood even if we follow a strict ketogenic diet, particularly if we are metabolically healthy and our body is using to ketones efficiently.

The real ketone magic

When we deplete glucose we train our body to produce ketones.

This is where autophagy, increased NAD+ and SIRT1 kicks in to trigger mitochondrial biogenesis and ENDOGENOUS ketone production (i.e. the free ones).[27]   The REAL magic of ketosis happens when all these things happen and ketones are release as a byproduct.  I do not believe that simply adding EXOGENOUS ketones will have nearly as much benefit to your mitochondria, metabolism and insulin resistance as training your body to produce ENDOGENOUS ketones in a low energy state.

image33

Everything improves when we train our bodies to do more with less (e.g. fasting, high intensity exercise, or even better fasted HIIT).  Resistance to insulin will improve as your insulin receptors are no longer drowning in insulin caused by high TOTAL ENERGY building up in your bloodstream.

image01

Driving up ketones artificially through EXOGENOUS inputs (treating the symptom) does NOT lead to increased metabolic health and mitochondrial biogenesis (cure) particularly if you are driving them higher than normal levels and not using them up with activity.

You may be able to artificially mimic the buzz that you would get when the body produces ketones ENDOGENOUSLY, however it seems you may just be driving insulin resistance and hyperinsulinemia if you follow a “MORE is better” approach.

Simply managing symptoms with patented products for profit without addressing the underlying cause often doesn’t end well.

Just like having low blood glucose is not necessarily good if it is primarily caused by high levels of EXOGENOUS insulin couple with a poor diet, or having lower cholesterol due to statins, having high blood ketone values is not necessarily a good thing if it is achieved it by driving up the TOTAL ENERGY in your blood stream with high levels of purified fat and EXOGENOUS ketones.

Nutrient density

When we feed our body with quality nutrients we maximise ATP production which will make us feel energised and satisfied.  Nutrient dense foods will nourish our mitochondria and reduce our drive to keep on seeking out nutrients from more food.  Greater metabolic efficiency will lead to higher satiety, which leads to less food intake, which leads to a lower TOTAL ENERGY, greater mitochondrial biogenesis, improved insulin sensitivity and lower blood glucose levels.

Prioritising nutrient dense real food is even more important in a ketogenic context.[28]  While we can always take supplements, separating nutrients from our energy source is never a great idea, whether it be soda, processed grains, sugar, glucose gels, HFCS, protein powders, processed oils or exogenous ketones.

Based on my analysis of nutrient density I don’t think you should be trying to avoid protein and carbohydrates in the pursuit of higher ketone levels unless you have a legitimate medical reason for perusing therapeutic ketosis (e.g. cancer, Alzheimer’s, epilepsy, dementia etc).

image09

I believe the best approach is to maximise nutrient density as much as possible while working within the limits of your metabolic health and your pancreas’ ability to maintain normal blood glucose levels.

image14

Intermittent fasting

If your goal is metabolic health, weight loss and improving your ability to produce ENDOGENOUS ketones, then developing a practice of FEASTING and FASTING is important.

To start out, experiment by extending your fasting periods until your TOTAL ENERGY is decreasing over time.  This will cause your circulating insulin levels to decrease which will force your body to produce ENDOGENOUS ketones from your ENDOGENOUS fat stores.

image03

Check out the how to use your glucose meter as a fuel gauge article or Jason Fung’s Intensive Dietary Management blog for some more ideas on how to get started with fasting.   Rebecca Skvorc Latham has also developed a fasting protocol using weight to guide your eating schedule if your primary goal is weight loss rather than blood glucose control.

image24

If you really want to measure something, see how low you can get your glucose levels before your next meal.  Then when you do eat, make sure you choose the most nutrient dense foods you possibly can to build your metabolic machinery and give your mitochondria the best chance of supporting a vibrant, active and happy life.

As my wise friend Raymund Edwards keeps reminding me, FAST WELL, FEED WELL.

 

 

Epilogue

Like most people dabbling in this low carb thing, I’m still on a journey.

I’d love to be able to share shirtless photos like Ted and Dom but I’m still working to overcome my own genetic propensity for diabetes, obesity, Alzheimer’s and Parkinson’s.  I’m still learning and working out how to apply these things in my own life.

Although I do sometimes check blood glucose levels before meals to see how I’m tracking I haven’t been testing ketones much for a year or so after I realised chasing high ketones with more dietary fat wasn’t helping me lose weight.

However after writing this article using other peoples’ data, I was intrigued to see how my ketones were travelling.

This was mid-morning after a kettlebell session.

I was able to get my heart rate up to 190 bpm which is my highest ever!  My daughter joined me today so there was some downtime between sets.  Usually I do an exercise until my heart rate gets up to at least 170 bpm.  I then stop and wait until it drops back down to 140 bpm and then go again.

My aim is to train my mitochondria to pump out more power with less energy (i.e. fasted) to improve insulin sensitivity as well as mitochondrial efficiency and drive  mitochondrial bio-genesis.

You can get a lot of work done in an intense 25 to 30-minute session with these weapons of torture that I keep downstairs in my garage (although I don’t think it really matters what you do as long as you push your body to do more with less).

My appetite today was great so I didn’t feel the need to eat until I had dinner with my family.

Previously I would have not been happy with these ketone readings and would have wanted to drive my ketones higher to get into the ‘optimal ketone zone’.  I would have wondered “Maybe I should have eaten some MORE butter or had a BPC to drive ketones higher to facilitate fat loss?”

But given I’d still like to lose some more body fat I’m pretty happy with these numbers.

  • My total energy is low (4.5mmol/L and 5.1mmol/L).  Check.
  • Ketones are present but not too high which means I’m able to mobilise fat but not building it up in my bloodstream.  Check.
  • Blood glucose is low.  Check.

All good!  Feeling crisp, happy and vibrant thanks to ENDOGENOUS ketones!

(Sorry.   I can’t sell you mine.  You’ll have to make your own.)

 

references

[1] http://www.thefatemperor.com/blog/2015/5/6/the-incredible-dr-joseph-kraft-his-work-on-type-2-diabetes-insulin-reigns-disease

[2] http://www.thefatemperor.com/blog/2015/5/10/lchf-the-genius-of-dr-joseph-r-kraft-exposing-the-true-extent-of-diabetes

[3] https://profgrant.com/2013/08/16/joseph-kraft-why-hyperinsulinemia-matters/

[4] https://www.amazon.com/Diabetes-Epidemic-You-Joseph-Kraft/dp/1425168094

[5] https://www.youtube.com/watch?v=193BP6aORwY

[6] http://fourhourworkweek.com/2016/07/06/dom-dagostino-part-2/

[7] http://www.thelivinlowcarbshow.com/shownotes/10568/848-dr-dominic-dagostino-keto-clarity-expert-interview/

[8] http://superhumanradio.com/579-shr-exclusive-patrick-arnold-back-in-the-supplement-business.html

[9] http://superhumanradio.com/shr-1330-best-practices-for-using-ketone-salts-for-dieting-performance-and-therapeutic-purposes.html

[10] http://docmuscles.shopketo.com/

[11] https://www.facebook.com/groups/optimisingnutrition/permalink/1574631349504574/

[12] https://nutritionandmetabolism.biomedcentral.com/articles/10.1186/s12986-016-0069-y

[13] https://www.facebook.com/groups/optimisingnutrition/permalink/1574631349504574/

[14] https://www.dropbox.com/s/287bftreipfpf29/jcinvest00459-0078.pdf?dl=0

[15] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2129159/

[16] https://www.facebook.com/BurnFatNotSugar/

[17] http://www.dietdoctor.com/obesity-caused-much-insulin

[18] http://www.lowcarbcruiseinfo.com/2016/2016-presentations/Hyperinsulinemia.pptx

[19] http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0115147

[20] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1819381/

[21] http://healthimpactnews.com/2013/ketogenic-diet-in-combination-with-calorie-restriction-and-hyperbaric-treatment-offer-new-hope-in-quest-for-non-toxic-cancer-treatment/

[22] https://www.google.com.au/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjK8Jvku7DOAhUJspQKHS5-DkwQFggbMAA&url=http%3A%2F%2Fwww.rsg1foundation.com%2Fdocs%2Fpatient-resources%2FThe%2520Restricted%2520Ketogenic%2520Diet%2520An%2520Alternative.pdf&usg=AFQjCNFuTA7xmWX1pFr6wBTV_hsS7C5j_w&sig2=pcBN_f_kCLSgFKYUy–uug&bvm=bv.129391328,d.dGo

[23] https://www.facebook.com/DocMuscles/videos/10210426555960535/?comment_id=10210431467003308&comment_tracking=%7B%22tn%22%3A%22R9%22%7D&pnref=story&hc_location=ufi

[24] https://www.facebook.com/DocMuscles/videos/10210426555960535/?comment_id=10210431467003308&comment_tracking=%7B%22tn%22%3A%22R4%22%7D&hc_location=ufi

[25] http://guruperformance.com/episode-3-metabolic-flexibility-with-mike-t-nelson-phd/

[26] http://guruperformance.com/tag/metabolic-efficiency/

[27] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2852209/

[28] http://ketotalk.com/2016/06/23-responding-to-the-paleo-mom-dr-sarah-ballantynes-claims-against-the-ketogenic-diet/

Low Carb Down Under Videos

Back in November 2015 I had the privilege to present at Low Carb Down Under events in Melbourne and Brisbane.  While I was a bit out of my comfort zone stepping out from behind the keyboard, it was a great opportunity to share some thoughts from the blog and meet some amazing people.  

managing insulin to optimise nutrition

The first video, Managing Insulin to Optimise Nutrition, outlines my take on the Food Insulin Index and how we can use it to rank foods based on their insulin demand.  To date the article, the most ketogenic diet foods, has received more than 125,000 views and the video has been viewed more than 3000 times.  I hope the video will help to get the word out there more about what I think is a very useful concept!

engineering the optimal diet

The second video, Engineering the Optimal Diet, outlines how we can quantify nutrient density and combine it with the food insulin index to prioritise foods selections for different goals.   The full article, optimal foods for different goals and the lists of optimal foods for different goals is what I’m most excited about on the blog and hope it will will have the greatest long term impact on what people eat and their health.   

thanks LCDU!

I stayed with Dr Rod Tayler in Melbourne and got to chew Dr Kieron Rooney’s ear for the whole weekend.   Meeting Gary Fettke, Grant Schofield, Peter Bruckner, Ken Sikaris, Shae Wheeler and a whole pile of other wonderful people was a real honour.  

Thanks again to Dr Rod Tayler for the labour of love that is LCDU and to Peter Williams who is a gentleman and the consummate professional with his video production.  Together they have not only facilitated some great events but have also created a massive free resource of online videos.  

the most nutritious low carb meals

If you are struggling with insulin resistance or diabetes you need to reduce the insulin load of your meals to achieve normal blood glucose levels.  But at the same time you also need to maximize the nutrient density of the food you eat.

image0232

After analysing more than 400 meals I have listed below the highest ranking low carb nutrient dense meals.

Click on each of the photos below to see more details for each recipe.

Be sure to subscribe to the blog and / or on Facebook to receive fornightlightly updates.

Also be sure to check out:

Check out this article for more details about basis of the ranking ranking system.

curried egg with cows brains

2016-11-18-copy

eggs benedict

spinach, cheddar and scrambled eggs

20131111_105815 (1)

bacon, eggs, avocado and spinach

spinach-avocado-salad-bacon-egg

low carb breakfast stax

breakfastpizza (1)

steak, broccoli, spinach & halloumi

10974722_10152618347760544_6160378433418389446_o

spinach, egg and avocado

10285383_10152637092785544_6458157593847633736_o

spinach, egg, cheese and cream

IMG_9736

Terry’s Wahls’ lamb skillet meal

10960080_10152573976645544_5136038329487064728_o

Chris Froome’s rest day breakfast

image03[1]

egg, spinach, avocado and tomato

10897970_10152569117015544_5899544708654587592_n

baked creamed spinach

Chrome Legacy Window 17042015 61152 AM.bmp

slow cooked pork with veggies 

image026

spinach, onion and goat cheese omelette

11045461_10152668604940544_3810040701006719940_n

bacon, egg, cheese and cream

IMG_0037

Dom’s breakfast of sardines, oysters, eggs and broccoli

picture_usf_laboratory

asparagus, egg and sauerkraut

Dr Rhonda Patrick’s Ultimate Micronutrient Smoothie vs Zero Carb Gregg

hqdefault1

kale with chorizo and eggs

kale with chorizo and eggs

bulletproof coffee with egg

1512359_10152570446810544_755357712744850191_n

baked eggs with sardines

1_pete_evans_19n80hs-19n80ie

bacon wrapped salmon

10171083_10152582552745544_7436963505230120472_n

Five Sisters Greek omelette

IMG_9072

coffee with cream and stevia

IMG_0150

slow-cooked heart on fire with kale

HeartonFire1

salad and salmon lunch

1512064_10152569146355544_6420556248848115740_o-1

broccoli, cheddar & bacon chowder

broccolicheddarsoup

spicy fish tacos

White Fish Fillets being prepared for Cooking

zucchini and feta fritters

47832cb88a58be1081be243b2656d6e2

cheesy garlic bread with bacon, beans and tomato

IMG_0144-0

chia seed pudding

10923710_10152572380560544_2520892579832977311_o

keto chocolate cake in a mug

lowcarbchocolatecake

optimal foods for different goals

A number of attempts have been made to rank foods based on their nutrient density or some other measure.

Useful parameters that can be used to optimal foods for different goals include:

  • nutrient density / calorie,
  • nutrient density / cost,
  • nutrient density / weight,
  • fibre / calorie,
  • fibre / weight,
  • calorie / weight,
  • cost / calorie, and
  • percentage insulinogenic calories.

This article details a new system that combines these parameters to identify optimal foods for different goals such as:

  • weight loss,
  • diabetes and nutritional ketosis,
  • therapeutic ketosis, and
  • athletes and the metabolically healthy.

My hope is that all this number crunching will help take the some of the guess work and ambiguity out of nutrition.

If we agree that we should focus on nutrient dense foods that don’t overload our pancreas’s ability produce adequate insulin, then we can move closer to agreeing which foods are optimal for an individual’s individual needs.

If you want to skip the detail, the end result of is a number of simple lists of optimal foods for different goals that you can access via the links below. If you want more detail then read on.

goal blog cheat sheet detailed list
therapeutic ketosis visit download download
diabetes and nutritional ketosis visit download download
fat loss visit download download
athletes and metabolically healthy visit download download

Firstly let’s take a look at a number of approaches that have previously been used to rank and prioritise foods.

low carbohydrate diets

As popularized by Dr Robert Atkins, limiting carbohydrates is a simple way to prioritise foods to reduce insulin demand.

By restricting carbohydrates intake, a range of foods are excluded, particularly those that are highly processed and contain added sugars.

While a low carb approach will reduce the insulin load of our food, no specific consideration is given to nutrient density or food quality.

image001

Aggregate Nutrient Density Index (ANDI)

In contrast to Akins’ approach, Joel Fuhrman’s Aggregate Nutrient Density Index (ANDI)[1] ranks foods based on micronutrients per calorie.[2]

I think there is an element of genius to Fuhrman’s nutrient density ranking system.  However when you look in the detail you find it is based on a select range of vitamins and minerals without any consideration of beneficial amino acids or fatty acids.

Fuhrman’s nutritarian approach has come under criticism for excluding a number of essential nutrients and placing extra emphasis on more fringe measures such as “oxygen radical absorbance capacity”.

image002

To determine the ANDI scores, an equal-calorie serving of each food was evaluated. The following nutrients were included in the evaluation: fiber, calcium, iron, magnesium, phosphorus, potassium, zinc, copper, manganese, selenium, vitamin A, beta carotene, alpha carotene, lycopene, lutein and zeaxanthin, vitamin E, vitamin C, thiamin, riboflavin, niacin, pantothenic acid, vitamin B6, folate, vitamin B12, choline, vitamin K, phytosterols, glucosinolates, angiogenesis inhibitors, organosulfides, aromatase inhibitors, resistant starch, resveratrol plus ORAC score.

While claiming to be “evidence driven”, without the inclusion of amino acids or fatty acids Fuhrman’s “nutritarian” approach ends up being heavily biased towards plant based foods.[3]   

Another issue with Furhman’s ANDI is that it can be skewed by a single nutrient present in very high quantities. For example, kale ranks at the top of Furhman’s list primarily due to its massive amount of Vitamin K.  Unfortunately, a mega dose of Vitamin K, which is a fat soluble vitamin, may have limited use by itself.  Rather than finding foods that are high in one nutrient it would be ideal to identify foods that were high in a broad range of nutrients.

Ranking foods in terms of nutrient density per calorie also tends to prioritise leafy veggies, which is great if you are trying to lose weight but not ideal if you’re an athlete trying to fuel up for an intense workout on kale and watercress.

While I think most people would benefit from consuming more green leafy vegetables, in the long term I think they will also benefit from foods with adequate protein protein and beneficial fatty acids.

In the short term someone who is obese has plenty of excess fatty acids and amino acids to spare so they will likely feel great as they are losing weight, however as their weight loss slows and they stop feasting off their own protein and fat the benefits of the a very low fat, very low protein approach may diminish.

NuVal

Professor Dr David Katz and an auspicious group of friends have developed the NuVal[4] food ranking system which uses the following sixteen positive ‘numerator nutrients’ to compare and rank common foods:

  • Fibre
  • Folate
  • Vitamin A
  • Vitamin C
  • Vitamin D
  • Vitamin E
  • Vitamin B12
  • Vitamin B6
  • Potassium
  • Calcium
  • Zinc
  • omega-3 fatty acids
  • total bioflavonoids
  • total carotenoids
  • Magnesium
  • Iron

image003

The sum of the ‘numerator nutrients’ is divided by the sum of the ‘denominator nutrients’ listed below to calculate a score of between one and one hundred:

  • saturated fat
  • trans fat
  • sodium
  • sugar
  • cholesterol

image004

The NuVal system also considers the following ‘additional entries’:

  • protein quality
  • fat quality
  • glycemic load
  • energy density

It’s interesting to note the foods to which it gives a score of 100 including:

  • non-fat skim milk,
  • sweet potato,
  • tomatoes,
  • beans,
  • bananas,
  • blueberries,
  • mango, and
  • wheat bran.

While the stated goal of the NuVal system is to combat diabetes, the food insulin index[5] shows that many of these foods will be problematic for a diabetic trying to maintain normal blood glucose levels.

Some of the more puzzling scores thrown up by the system include:

  • shrimp – 40
  • lobster – 60
  • coconut – 24
  • chicken – 57
  • beef – 46

Other concerns with the NuVal system include:

  • Because it biases heavily against saturated fat, some diabetic friendly foods like beef and coconut are further down the list.
  • The number of foods analysed is fairly limited.
  • Only sixteen vitamins and minerals are included in the analysis.
  • Dietary cholesterol is penalised by the NuVal system although dietary cholesterol does not necessarily lead to cholesterol in the blood or heart disease.
  • The NuVal algorithm has been calibrated to fit the views of the panel of experts, hence it is likely that it will simply reinforce previously held views.
  • Considering added sugar and the glycemic index are a good start, however I think using the food insulin index would be more useful as it is a better measure of the actual amount of glucose being metabolised.

Dave Asprey’s Bulletproof Diet Roadmap

Dave Asprey has developed the Bulletproof Diet Infographic[6] which is a simple ranking of foods to avoid, and preference based on both nutritional density and toxins.

image006

While I think Asprey’s ranking system is excellent, the downside is that it features only a select range of foods and does not explain why each of the foods has been given a particular ranking, although there is a good discussion of the toxins and various other considerations in his Bulletproof Diet Book.[7]

Asprey’s list also doesn’t differentiate between what would be most appropriate for someone with diabetes versus an athlete, or someone aiming for therapeutic ketosis or wanting to lose weight.

Soylent

Another noteworthy foray into the realm of optimising nutrition is Rob Reinhardt’s Soylent.[8]

Reinhardt set out to produce a manufactured food that ticked off all of the micronutrient Recommended Daily Intake (RDI) values, while reducing the cost and the hassle of food preparation.

While Reinhardt notes that his creation would be healthier than the ramen noodles that he was living on before creating Soylent[9], there are a number of downsides to this food replacement which is basically a protein shake on steroids.

Using manufactured foods leaves you exposed to not getting all of the non-essential micronutrients or even the beneficial nutrients that haven’t made it to the current list.  Eating real whole foods seems to be a safer option to ensure you are getting all the nutrients you need.

Mat Lalonde’s nutrient density

After reviewing the various options available and finding them lacking, Dr Mathieu Lalonde developed an excellent ranking of foods based on nutrient density per weight of food using the USDA food database.[11]

Lalonde also included a broader range of nutrients than Fuhrman or Katz by also considering beneficial amino acids and fatty acids.

This analysis identified organ meats as one of the more nutritious foods, followed by herbs and spices, nuts and seeds.

image008

In this video of his AHS2012 presentation Lalonde noted that people wanting to lose weight may wish to prioritise in terms of nutrient density per calorie, however he chose to analyse nutrient density in terms of weight as that might be more relevant for athletes (Lalonde is a CrossFit athlete as well as a biochemist). [12]

After watching this video and hearing about his quantitative approach to nutrient density I was left excited, yet a little unsatisfied, wondering what the ranking might look like in terms of nutrient density / calories.

fibre per calorie

One of the more interesting concepts in the area of nutrition recently is that what you eat could affect your gut bacteria.

Typical daily fibre intake is around 17g for those of us in western civilisation compared to the Recommended Daily Intake (RDI) of 25 to 30g per day.[17]

It is said that African hunter gatherer children obtain more than 150g of fibre per day from eating unprocessed foods in their natural state[18], and before the invention of fire and cooking our ancestors were eating more than 100g of fibre per day.[19]

Fibre is not digestible by the human gut and hence it does not provide energy or cause a rise in blood sugar or insulin.  Fibre in our food neutralises the insulinogenic effect of carbohydrate.[20]

If we rank for fibre per calorie we end up with a few spices such as cinnamon, curry powder, or cocoa at the top of the list along with veggies such as turnip, artichoke, sauerkraut, and cauliflower.

  1. cinnamon
  2. turnip greens
  3. artichoke
  4. curry powder
  5. sauerkraut
  6. cauliflower
  7. raspberries
  8. lettuce
  9. blackberries
  10. lemon peel

Again, this list is interesting, but not something you can live by.  Somehow we need to combine all these approaches to arrive at a more useful list that balances all of these considerations.

what are the “essential nutrients”?

So after reviewing these ranking systems I thought it would be interesting to design my own that would build on these previous approaches as well as considering the insulin response to food to make it more useful for people with diabetes.

The obvious starting point is to agree on the nutrients that should be included.  Listed below are the commonly accepted list of essential amino acids, vitamins and minerals.[21]

vitamins

  1. Choline
  2. Thiamine
  3. Riboflavin
  4. Niacin
  5. Pantothenic acid
  6. Vitamin A
  7. Vitamin B12
  8. Vitamin B6
  9. Vitamin C
  10. Vitamin D
  11. Vitamin E
  12. Vitamin K

minerals

  1. Calcium
  2. Copper
  3. Iron
  4. Magnesium
  5. Manganese
  6. Phosphorus
  7. Potassium
  8. Selenium
  9. Sodium
  10. Zinc

amino acids

  1. Cysteine
  2. Isoleucine
  3. Leucine
  4. Lysine
  5. Phenylalanine
  6. Threonine
  7. Tryptophan
  8. Tyrosine
  9. Valine
  10. Methionine
  11. Histidine

fatty acids

The list of essential and conditionally essential fatty acids is shorter than the other lists and is largely made up of omega 3 fats that the human body cannot manufacture in sufficient quantities. We need to go out of our way to incorporate these into our diet.

  1. Docosahexaenoic acid (DHA) (22:6 n-3)
  2. Eicosapentaenoic acid (EPA) (20:5 n-3)
  3. Docosapentaenoic acid (DPA) (22:5 n-3)
  4. Alpha-linolenic acid (18:3 n-3)

Given that a large part of my focus is to create a system that prioritises diabetic-friendly foods, I thought it would be good to give some more detailed consideration to other ‘good fats’, given that fat typically comprises more than half of the calories for someone following a reduced carbohydrate approach.  Listed below are the additional fatty acids that research shows to be beneficial.

  1. Arachidonic acid (20:4)
  2. Oleic acid (18:1)
  3. Lauric acid (12:0)
  4. Capric acid (10:0)
  5. Pentadecanoic acid (15:0)
  6. Margaric acid (17:0)

You can read more on the reason for inclusion of these additional good fats the Good Fats, Bad Fats article.

nutrient density score

Building on Joel Fuhrman and Matt Lalonde’s nutrient density approach, the nutrient score score is a relative score calculated by comparing the amount of a particular nutrient in each food against all of the foods.

For example, if a particular food has an average amount of Vitamin C compared to the 8,000 other foods in the database it will get a score of zero because it is zero standard deviations from the mean.  If it has a large amount of a certain nutrient then it will receive a high score.

If the amount that a particular nutrient is two standard deviations from the mean then it will get a score of two for that nutrient.  If however it is five standard deviations from the mean it gets a maximum score of three in order to avoid prioritising foods that have massive amounts of one single nutrient versus foods that have solid amounts of a range of essential nutrients.

image011

One example of where this limitation comes into play is kale, which has a massive amount of Vitamin K versus spinach which has a high amount of Vitamin K but also has a range of other nutrients.  Because of the upper limit on the score for a single nutrient the system gives a higher priority to spinach, which has a more well-rounded nutrient profile rather than simply being an overachiever in one or two nutrients.

image013

The nutrient score for a food is the sum of the individual nutrient scores across the forty three nutrients.  The higher the score the more nutritious that food is in comparison to the other foods in the database.

Weighting one nutrient as more important than another could be useful for an individual with a particular goal or health condition (e.g. DHA for someone battling brain cancer).  However I have chosen to keep ‘clean’ to avoid arguments about bias with equal weighting given to each nutrient.[22]  This system will simply highlight foods that have a wide range and a high quantities of nutrients.

weighted multi criteria analyses

Ranking foods by an individual parameter is interesting, however it doesn’t produce a balanced list of foods that you can live by.  Where things start to get interesting is when we combine the different parameters using a multi criteria analysis to suit different goals.

As an engineer I often use a multi criteria analysis (MCA) to analyse a lot of data.  A numerical MCA is a useful way to make sense of a large amount of data and shortlist from a wide range of options.

 

The available parameters from the USDA foods spreadsheet are:

  • nutrient density / calorie,
  • nutrient density / weight,
  • fibre / calorie,
  • fibre / weight,
  • calorie / weight, and
  • percentage insulinogenic calories.

The table below shows the weightings given to each criteria refined to create a shortlist of foods to suit different goals.

goal

ND / cal

ND / weight fibre / cal fibre / weight calories / weight

insulinogenic (%)

fat loss

40%

5% 5% 5% 25%

20%

athlete

5%

30% 10% 5% 5%

45%

diabetes & nutritional ketosis

5%

20% 10% 5% 10%

50%

therapeutic ketosis

5%

20% 5% 5% 0%

65%

  • Someone aiming for therapeutic ketosis will want to minimise their insulin load while maximising nutrition in the context of a very high fat diet.
  • Someone with diabetes or trying to achieve nutritional ketosis will also want to minimise their insulin load, however they should also look to maximise nutrient density and obtain adequate fibre.
  • Someone who has control of their blood glucose levels but is still trying to achieve fat loss will likely benefit from a diet with a reduced calorie density while still maximising fibre and nutrition.
  • An athlete’s primary priority will be to maximise nutrients without as much concern for calorie density or insulin load.

reality check

I have refined these weightings used in the MCA by reviewing the top 500 foods (of the 8000 foods in the USDA foods database) for each scenario.

goal

fibre (g) 

weight (g)  % protein % net carbs % insulinogenic

% fat

fat loss

45

1614 29% 13% 33%

31%

athlete

25

436 26% 12% 31%

56%

diabetes & nutritional ketosis

25

413 30% 4% 21%

58%

therapeutic ketosis

13

357 14% 3% 14%

80%

average all foods

26

899 26% 38% 52%

31%

It’s interesting to see that the net carbohydrates ends up being relatively low for all scenarios when we maximise nutrient density.  It appears that starchy carbs (e.g. grains and sugars) have a relatively low nutrient density compared to other available foods.

image015

The big differentiator across the approaches is calorie density.  If someone has stabilised their blood glucose and insulin levels then the next step in the journey may be to decrease calorie density to naturally manage food intake.  The fat loss approach is slightly more insulinogenic however practically it will be difficult to fit in all the food.

the results

While this process is somewhat convoluted the end result is a fairly simple list of foods that are ideal for different goals.  I have included a shortlist of the highest ranking foods on the blog here along with ‘cheat sheets’ that you can print and stick to your fridge or compile your food lists from.

It’s been great to see many people benefit from focusing these shortlists.  If you’re inquisitive and like to ‘peek under the hood’ I have also included links to a more detailed list that shows the basis of the rankings for each food.

goal blog cheat sheet detailed list
therapeutic ketosis visit download download
diabetes and nutritional ketosis visit download download
fat loss visit download download
athletes and metabolically healthy visit download download

references

[1] http://www.wholefoodsmarket.com/healthy-eating/andi-guide

[2] http://www.wholefoodsmarket.com/healthy-eating/andi-guide

[3] http://www.westonaprice.org/book-reviews/eat-to-live-by-joel-fuhrman/

[4] https://www.nuval.com/

[5] https://optimisingnutrition.wordpress.com/the-insulin-index/

[6] http://www.bulletproofexec.com/wp-content/uploads/2014/01/Bulletproof-Diet-Infographic-Vector.pdf

[7] http://www.amazon.com/The-Bulletproof-Diet-Reclaim-Upgrade/dp/162336518X

[8] https://www.soylent.com/

[9] http://www.newyorker.com/magazine/2014/05/12/the-end-of-food

[10] http://robrhinehart.com/?p=424

[11] http://ketopia.com/nutrient-density-sticking-to-the-essentials-mathieu-lalonde-ahs12/

[12] https://www.youtube.com/watch?v=HwbY12qZcF4

[13] http://solvingnutrition.com/engineering-the-cheapest-and-healthiest-diet-on-a-budget/

[14] http://blog.paleohacks.com/ultimate-guide-paleo-diet-budget/

[15] https://www.youtube.com/watch?v=VvfTV57iPUY

[16] http://perfecthealthdiet.com/

[17] https://www.nrv.gov.au/nutrients/dietary-fibre

[18] http://www.abc.net.au/catalyst/stories/4067184.htm

[19] http://www.gregdavis.ca/share/paleo-articles/academic/The%20Ancestral%20Human%20Diet%20by%20S.%20Boyd%20Eaton.pdf

[20] https://optimisingnutrition.wordpress.com/2015/03/30/what-about-fibre-net-carbs-or-total-carbs/

[21] http://ketopia.com/nutrient-density-sticking-to-the-essentials-mathieu-lalonde-ahs12/

[22] http://www.westonaprice.org/book-reviews/eat-to-live-by-joel-fuhrman/

trends, outliers, insulin and protein

  • The carbohydrate content of a food alone does not accurately predict insulin response.  Protein and fibre content of food also influence in insulin response.
  • The food insulin index data indicates that dietary fat is the one macronutrient that does not does not require a significant amount of insulin.
  • Net carbohydrates plus approximately half protein correlates well with observed insulin response.
  • This knowledge can be used to help select low insulin foods and more accurately calculate insulin doses for diabetics.

background

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

One of the pitfalls for newbies is to design a system with excessive “curve fitting”.  That is, to design a complex system that would work fantastically on a specific set of historical data.  If you ran an overly curve fitted system on another set of data or tried to trade it in real time it would fail because it was too finely tuned to the discrete set of historical data.

“Everything should be as simple as possible, but no simpler.”

Albert Einstein

Another lesson from trading is that you should be able to describe simply why a good system works.  My trading system scanned the market for stocks that were moving up quickly over a number of time periods with minimal volatility so that I could place a close ‘stop loss’ that would take me out of the trade quickly if the trend turned.

When the GFC hit things got too volatile and I got out of the market.  It was no longer fun.  However the skills I learned as an amatuer a quantitative trader (along with my day job running multi criteria analyses to identify motorway alignments, road investments and the like) have given me an interesting angle on nutrition that I hope people find useful.

On the Optimising Nutrition blog I have tried to describe a system to manage nutrition that makes sense to me.  I want to document the things that I wish someone had shown us 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 of the human body, 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 in a moderate amount of detail 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, with a view to better manage blood glucose and insulin demand.  You will see that I have tried to look at the issue from a number of different directions and have also included a more rigorous statistical analysis.

carbohydrate

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

image001

indigestible 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.

image002

The importance of dietary fibre should not be discounted, especially when trying to reduce insulin demand.  Some recommend that diabetics limit total carbohydrates, rather than considering net carbohydrates, or non-fibre carbohydrates.  The danger with a total carbohydrates approach is that people will avoid fibrous non-starchy 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 foods that are largely comprised of fat have a negligible insulin response (R2 = 0.38, r = 0.631, p < 0.001).

image003

To put this another way, the chart below shows the sum of carbohydrate plus protein (i.e. the non-fat content of foods) versus the insulin index (R2 = 0.38, r = 0.62, p < 0.001) indicating that:

  • the greater the proportion of fat in a particular food the less insulin is required; and
  • the more carbohydrates and / or protein ingested the more insulin is required.

image004

Hence, it appears that to reduce insulin demand we need to reduce carbs and / or protein!

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).  Again, this indicates that the 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).

image005

While it appears that insulin demand is triggered by carbohydrates and protein, what is not clear is the relative degree to which carbohydrates and protein contribute to insulin demand.  Are they equivalent or does protein cause a smaller insulin  response?

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.

As shown in this plot, high protein foods are typically lower in carbohydrates which produce the greatest amount of glucose.  Choosing higher protein foods will generally reduce insulin (R2 = 0.10, r = 0.47, p < 0.001).

image006

Increasing protein will also typically lead to a spontaneous reduction in intake due to the thermic and satiety effects of protein. [3] [4]   Protein is critically important for many bodily functions.  It is vital to eat adequate protein.

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 diabetics 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 generally 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.

image007

For most people, transitioning to a reduced carbohydrate whole foods diet will give them most of the results they are after.  However for people with Type 1 Diabetes or people trying to design a therapeutic ketogenic diet, consideration of protein may be important to further refine the process 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.

However for someone struggling to lose weight on a low carb diet, considering the insulinogenic effect of protein might just be what they need to reduce insulin and normalise blood sugars and thus enable them to reach their goals.

glycaemic index

The glycaemic index is a reasonable predictor of insulin demand in terms of correlation (R2 = 0.54, r = 73, p < 0.01), however the ‘elephant in the room’ again is the high protein low carbohydrate foods (e.g. white fish, low fat cheese, lean beef etc).

image009

The other issue is that the glycaemic index is an empirical measurement that has to be measured in humans “in vivo” and can’t easily be calculated based on commonly available food properties.  And again, the glycaemic index does not deal with the insulin response from high protein foods.

glycaemic load

The same issues apply to glycaemic load.  There is a reasonable correlation between glycaemic load and insulin demand.  However it still does not explain the insulin effect of high protein foods (R2 = 0.57, r = 0.75, p < 0.01).  And you have to run these tests in real people “in vivo”.

image010

glucose score

Like the food insulin index, the glucose score is measured “in vivo” based on the area under the curve of a healthy person’s glucose rise due to a particular food.

Glucose score is interesting in that it actually achieves an excellent correlation with insulin demand (R2 = 0.75, r = 0.87, p < 0.001), however there is still a disconnect when it comes to high protein foods.

image010

It seems that some foods that do not raise blood glucose significantly over three hours still elicit an insulin response.  High protein foods digest slowly although they do still require insulin to metabolise.  In a normal healthy person the body’s insulin response to protein is balanced by release of glycogen from the liver, with blood glucose being kept in balance by insulin and glycogen. [5]

In a normal person the insulin keeps up with this slow blood glucose rise and hence we do not see a pronounced blood glucose spike due to high protein foods.

The interesting outliers here are processed low fat milk products that seem to require more insulin than would be anticipated by the blood glucose response.  On the other side of the trend line we have brown rice, pasta and other less processed whole foods which raises the blood glucose but does not require as much insulin as might be expected.

Accounting for fibre (i.e. net carbs rather than total carbs) goes some way to help anticipate the effect of processing.  However the effect of processed foods is an interesting area for future study that is beyond the capacity of this dataset to address.

I ran a number of correlation analysis and could not find an explanation of why a certain food sat above or below the trend line, whether it be carbohydrates, sugar, fibre or protein.

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).  Quitting sugar is only part of the solution.  Most people struggling with diabetes or obesity should ideally consider their total carbohydrate intake.

image011

curve fitting

Kirstine Bells’ Clinical Application of the Food Insulin Index to Diabetes Mellitus[6] documents the development of a number of formula to explain the relationship between food properties and the food insulin index response.  The aim of this her thesis was essentially to build an improved glycemic index to predict insulin response rather than only considering changes in blood glucose.

The chart below shows the best relationship developed using a stepwise multiple linear regression analysis of the various parameters to forecast insulin demand documented in Clinical Application of the Food Insulin Index to Diabetes Mellitus. [7]

The correlation is excellent (R2 = 0.78, r = 0.89, p < 0.001).  However this relationship relies heavily on the glucose score (GS) which has to be tested “in vivo”.

image012

If we strip out the glucose score then the best relationship achieved in the thesis is the one shown below using carbohydrates and protein with a correction factor (R2 = 0.46, r = 0.68, p < 0.001).

The problem with this approach is that it assumes that high fat foods have some insulinogenic effect.  However we have seen above that high fat foods have a negligible insulin response.  This formula also does not account for indigestible fibre which should be subtracted from the total carbohydrate count.  And according to this formula a food with zero carbohydrate and zero protein would still have a significant insulin index response of 10.4, which does not make sense.

image013

simple is true

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).

image014

This approach also does a good job of predicting blood glucose (R2 = 0.59, r = 0.77, p < 0.001) as shown in the chart below.

image015

practical application

Individual foods can be ranked and prioritised based on their proportion of insulinogenic calories using the following formula:

image016

Foods with the lowest proportion of insulinogenic calories will have the gentlest impact on blood glucose and have the lowest insulin demand, a consideration which will be very useful for people who are insulin resistant (i.e. Type 2 Diabetes or Pre-Diabetes) or not able to produce adequate insulin themselves (i.e. Type 1 Diabetes).

You can find a detailed list of foods ranked by their proportion of insulinogenic calories here and with consideration of nutrients and other factors based on different goals here.

Diabetics and people wanting to reduce the insulin demand of their diet can track the total insulin load (as opposed to carbohydrate counting) using the following formula:

image017

The total insulin load can be reduced by decreasing carbohydrates, increasing fibre, moderating protein to the body’s optimum requirement and increasing fat until target blood glucose are achieved.

can we design a “perfect” system?

There is still quite a degree of in this real life data.  This could be due to measurement error in the macronutrients, food quantity, individual characteristics of the people that the food was tested on, or something else.

This approach considering the insulinogenic effect of protein and carbohydrates does however help to better predict insulin demand than carbohydrate alone.

The fact that there is still a high degree of variability in the data and hence limited ability to accurately predict the insulin response to food can be mitigated by keeping the overall insulin load of the diet reasonably low.

Dr Richard Bernstein talks about the ‘law of small numbers’ whereby the compounding errors in the calculation of insulin requirement and the mismatch of insulin response with the rate of digestion misalign means that it is impossible to accurately calculate insulin dose.

The only way to manage the high level of variability is to reduce insulin demand to manageable levels.  This is especially beneficial for people who are injecting insulin, but also relevant for the rest of us.

summary

Building on the analysis of the food insulin index data, the key assumptions that underpin this system are:

  1. carbohydrates require insulin,
  2. indigestible fibre does not require insulin, and
  3. the glucogenic portion of protein that is not used for growth and repair and not lost in digestion also requires insulin.

In order to reduce our insulin load we should do the following, in order of priority:

  1. Reduce insulin load until you normalise blood glucose levels (i.e. reduce digestible carbohydrates and moderate protein if necessary),
  2. Increase nutrient density as much as you can while still maintaining good blood glucose levels (note: this will likely also include fibre from non-starchy veggies which will also increase fibre which reduces insulin and slows digestion),
  3. Reduce dietary fat if you still need to reduce body fat levels, and
  4. Implement an intermittent fasting routine to improve your insulin sensitivity and to kick-start ketosis.

 

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

the Goldilocks glucose zone

  • The body requires somewhere between 160 and 600 calories per day from glucose.
  • This glucose can be sourced both from ingested carbohydrates as well as the glucogenic portion of protein not used for growth and repair.
  • Rather than raising blood glucose immediately, amino acids from protein circulate in the blood until they are required.
  • Excessive glucose from either carbs or protein will lead to increased insulin requirement, insulin resistance, diabetes, obesity and a range of other issues associated with hyperinsulinemia and metabolic syndrome.
  • Someone who is insulin resistant and/or has diminished pancreatic function does not produce adequate insulin to maintain normal blood glucose. Rather than using diabetes medications or exogenous insulin, the alternative option is to decrease one’s dietary insulin load to a point that the body’s natural insulin production can keep up.
  • We can manage our dietary glucose to achieve normal blood sugars by considering the total insulin load from carbohydrate plus the glucogenic portion of protein.

background

Rather than simply focusing on the ideal macronutrient split, this article endeavours to take the discussion one step further to look at how we can optimise the split between dietary glucose and fat given that glucose can be obtained from both carbohydrates, and the glucogenic portion of protein in excess of the body’s requirement for growth and maintenance.

the Goldilocks glucose zone

This article outlines a basis upon which to determine the optimum balance between what are often polar extremes.

On the high glucose end of the argument we are faced with the following issues:

  • high insulin levels,
  • obesity and excess fat accumulation,
  • high blood glucose levels,
  • heart diseases risk, and
  • the plethora of issues that accompany metabolic syndrome and hyperinsulinemia.

At the ketogenic extreme we have concerns about a range of issues including:

  • inadequate fuel for the brain,
  • limited food options,
  • a lack of vitamins and minerals,
  • low fibre,
  • stunted growth,
  • impaired athletic performance, and
  • high cholesterol levels.[1]

Somewhere in the middle there must be an optimal balance of fuel for each individual, a balance between the extremes.

But how do we find this balance point?  Then what do we monitor to ensure we stay there?

Not too hot.  Not too cold.

Not too hard.  Not too soft.

What we are searching for is the “Goldilocks glucose zone”.

the safe starches debate

The ‘safe starches debate’ has been intriguing and has informed my thinking on this controversial issue.

The discussion started at the 2012 Ancestral Health Symposium with a panel hosted by Jimmy Moore. [2]  It continued on the blogs of the two lead representatives of each side of the argument, Paul Jaminet [3] and Ron Rosedale [4].

the case for limiting carbohydrates

On the low carb end of the debate we have Ron Rosedale who argues that:

1. Non-fibre carbohydrates are:

  • detrimental as they lead to increased insulin levels, oxidation and accelerated aging, and
  • unnecessary as we can obtain our glucose needs via gluconeogenesis from protein.

2.  Glucose can be manufactured from glycerol or from lactate and pyruvate recycling.  In some respects this is even better than making glucose from protein. [5]

natural glucose utilisation level

On the not so low carb end of the argument, Paul Jaminet argues that the human body runs on a fuel mix of about 30 to 35% of calories from carbohydrates (say 600 calories per day).  The remaining 70% or so of our fuel comes from fat.

Jaminet recommends that people follow a ‘low carb’ diet, however Jaminet’s version of low carb is a carbohydrate intake somewhere less than the body’s 30% requirement for glucose.  This forces some proportion of the glucose needs to come from gluconeogenesis.

The figure below from The Perfect Health Diet represents this concept graphically. [6]

image001

some perspective

When you look at this in the context of the fact that the typical western diet has 40 to 50% of calories coming from carbohydrates,[8] we are really arguing over whether a low carb diet or a very low carb diet is best for our metabolic health.

Jaminet’s glucose flux has a lot of similarities with Mark Sisson’s Primal Blueprint Carbohydrate Curve. [9]   Jaminet’s 600 calories equates to 150g of carbohydrates which aligns with the top end of Sisson’s ‘effortless weight maintenance zone’.

image003

But what if limiting carbohydrates to less than 150g per day is not working for you (e.g. your blood sugars are not in normal range or you are not achieving weight loss)?

What can we learn from the food insulin index data to help us build on standard carbohydrate counting?

How can we determine the optimum fuel mix for our individual situation, body and goals?

minimum carbohydrate requirement

One of the concerns about a low carbohydrate diet centres on the understanding that the brain needs carbohydrates.

This seems to stem from Institute of Medicine’s advice that the brain needs about 400 calories per day from glucose.  This equates to 100g of carbs which most people wind up to 130g to provide a safety factor.

The IOM however notes that a person who is fat adapted can run on lower amounts of carbohydrates as their brain is fuelled by ketones and there is no minimum requirement for carbohydrates, only glucose which can also be obtained from gluconeogenesis. [10] [11]  In spite of this, nutritionists still recommend a minimum carbohydrate intake.

Jaminet makes a similar differentiation that a typical sedentary person requires about 600 calories for glucose per day, however this may decrease to 300 calories per day for someone on a ketogenic diet.

The understanding of the absolute minimum glucose requirement comes from research by George Cahill who undertook extreme starvation experiments and found that people could survive on as little as 40g of glucose per day (i.e. 160 calories). [12]

In the fed state the body will rely on glucose from ingested carbohydrates.  After a period of fasting it transitions to using glucose form the glycogen stores in the liver and muscles.  Once the glycogen stores are exhausted the body will obtain glucose via gluconeogenesis from cannibalising muscle.

image005

At this point however the brain and the rest of the body have largely transitioned to being fuelled by fat so it only needs to obtain 40g of glucose per day from protein via gluconeogenesis.   This would equate to around 5% of calories from glucose (not necessarily from carbohydrates).

I am not suggesting that starvation ketosis is optimal for most people.  The point is that the body can survive on very little glucose if it needs to for quite a long time.

The longevity crowd will tell you that this is an evolutionary advantage so you can prolong life until a time when there is enough nutrition to reproduce and thrive.  People who could use their fat and muscle for fuel survived to be your ancestors, and those that couldn’t, didn’t.

what is the minimum protein requirement?

According to Nuttall and Gannon [13] the body requires between 32 and 46g of high quality dietary protein to maintain protein balance.

This equates to around 6 to 7% of calories in a 2000 to 2500 calorie diet being taken “off the top” for growth and maintenance, with everything else potentially available as excess.

The same paper notes that the American diet typically consists of between 65 and 100g of protein per day (i.e. 13 to 16% of calories).

three macros or two fuel sources?

Something that has been very interesting to me that I had not understood until recently was that protein is made up of glucogenic and ketogenic amino acids.  Some amino acids can turn into either glucose or fat. [14] [15]

The table below shows the differentiation of amino acids into different categories.

  glycogenic ketogenic both
non-essential Alanine

Arginine

Asparagine

Aspartate

Cysteine

Glutamate

Glutamine

Glycine

Proline

Serine

Tyrosine
essential Histidine

Methionine

Valine

Leucine

Lysine

Isoleucine

Phenylalanine

Tryptophan

Threonine

I will be discussing this concept in more detail in a separate article (The Insulin Index v2), however in essence, what this means is that there are really only two fuel sources for the body, glucose and fat, with “excess” protein being turned into one or the other.

the “well formulated ketogenic diet”

Steve Phinney is probably the most well respected authority on the ketogenic diet.   This figure shows a comparison of what Phinney calls the “well formulated ketogenic diet” (WFKD) as a triangle with a number of possible dietary approaches shown for comparison. [16]

image007

A WKFD can contain 30% protein and 5% carbs or 20% carbs and 10% protein.  A WKFD however cannot however contain 30% protein and 20% carbs because we would get too much glucose which would increase insulin and suppress ketosis.

As shown in the WFKD figure above the protein content of a ketogenic diet can range between 0.8 and 2.4g/kg lean body mass.  However if we are running higher levels of protein we will only achieve ketosis if we also limit carbohydrates.

Listen to Steve Phinney discuss this concept from 2:51 in this video.

Interestingly, the slope of the line along the face of the WKFD triangle corresponds with the assumption that 7% of protein goes off to muscle growth and repair with 75% of the remaining ‘excess’ protein being glucogenic.   This also aligns nicely with the observation from the food insulin index data and the theoretical proportion of glucogenic amino acids in protein.

the Goldilocks glucose zone

Listed below are the various levels of glucose requirement in terms of calories discussed above along with the equivalent carbohydrates and the percent of glucogenic calories in a 2250 calorie diet.

approach glucogenic calories insulin load (g) glucogenic (%)
 glucose utilisation  (Jaminet) 600 150 26.7%
 ketogenic threshold (Phinney) 500 125 22.2%
 ketogenic maintenance (Jaminet) 300 75 13.3%
 starvation (Chaill) 160 40 7.1%
  • The glucose utilisation is Jaminet’s approximation of the glucose calories used by a non-ketogenic person each day. If we run above this level our glycogen stores will become overfull, with excess glucose spilling into the blood, requiring insulin and being stored as fat.  Below this level we need to obtain some of our glucose from protein via gluconeogenesis.
  • The ketogenic threshold represents the theoretical boundary between the WFKD and the rest of the world according to Phinney’s protein vs carbohydrates plot. Below this point our glycogen stores will become depleted to a point that we be forced to rely on our protein and fat stores for energy rather than carbohydrate.  After a period of consuming less carbs than required to keep our glycogen stores topped off we will start to show ketones in our blood and rely on ketones and fat more than glucose.  This level is about 500 calories per day which is about 22% of a 2250 calorie per day diet.
  • The ketogenic maintenance level is based on the 300 calories per day that Jaminet says we need from glucose if we are fat adapted. With a greater proportion of energy coming from fat in the form of ketones we require less glucose for brain function.
  • The starvation level represents what people can survive on as an absolute minimum. In this extreme starvation state the body is cannibalising muscle via gluconeogenesis to convert to glucose to survive.  This is not something I recommend you try at home.  However it is useful to know that the body can survive (but not necessarily thrive) at very low levels of glucose for a significant period of time.

The chart below shows these glucose levels superimposed on a plot of protein versus carbohydrate.  The points on the left hand side of the chart labelled with calorie values represent the point at which all glucogenic calories come from carbohydrates with only the minimum 7% protein for maintenance ingested (i.e. no “excess” protein). Microsoft Word Document 19052015 35145 AM.bmp

As we move to the right we have increasing levels of protein and decreasing levels of carbohydrates to maintain the same total number of glucogenic calories (assuming that 75% of “excess” protein converts to glucose).

The only thing we can be certain of here is that the concepts shown graphically in this figure will not be accurate due to the fact that it is built on a number of layers of theory.  And everyone’s body is different.  However this chart gives us a conceptual framework with which to manipulate our diet to achieve our goals.

The take home message is that, if we are trying to reduce the glucose load of our diet to the point at which our own pancreas can keep up, we need to think, not just in terms of carbohydrates, but in terms of total glucose (or insulin load) from carbohydrates plus excess protein.

I don’t think the body minds that much whether it gets glucose from carbohydrates or protein. [17]  My view is that it is better to maximise vitamins (generally from carbohydrate containing foods) and amino acids (from protein containing foods) as far as possible while at the same time keeping our glucose load within our own pancreas’ ability to keep our blood sugars at normal levels.  What this means is that some people may need to restrict their carbohydrates and their protein more than others to achieve normal blood sugars.

what about the Kitavans?

When faced with the hormonal theory of obesity many people are quick to point to hunter gatherer populations such as the Kitavans that do quite well on high levels of carbohydrates.

Some people seem to tolerate high levels of carbohydrate form whole food sources.  Perhaps they are metabolically flexible such that they can store carbohydrates as fat and quickly use them again, or they are very active and hence using up their glycogen stores regularly, and are very insulin sensitive and adapted to handle significantly more than 600 carbohydrate calories per day from whole food sources.

It may also be that people eating predominantly unprocessed high fibre foods are less likely to be in a caloric excess meaning that they do not have a lot of left over calories to store as fat or to require excess insulin.

Dr Jason Fung points out in this video that in spite of a higher glucose load the Kitavans managed to keep low insulin levels, which seems to be the critical factor.

If you are highly active with great insulin sensitivity and you can consume high levels of carbohydrates while maintaining normal blood glucose and staying lean then good luck to you.  I’m jealous.  Enjoy, at least while it lasts!

It is worth noting that a number of the champions of the low carbohydrate movement such as Tim Noakes, [18] Ben Greenfield [19] and Sami Inkenen [20] found that they had or were becoming diabetic after decades of extreme exercise on a high carbohydrate diet, hence transitioned to a low carbohydrate approach to manage their blood sugars.

comparison of dietary approaches

To help make more sense of this concept I have shown a number of dietary approaches from the article Diet Wars… Which One is Optimal? on the protein vs carbohydrate chart below.

image011

  • Bernstein’s approach is designed to be high protein, low carb, to provide diabetics with their glucose needs from protein which releases glucose more slowly than carbohydrate.
  • This version of the Atkins diet is unlikely to be ketogenic due to the high levels of protein. Reducing carbohydrates and/or protein is likely to be necessary to achieve ketosis, and possibly the weight loss that is typically the aim of the Atkins diet.
  • The Zone and Mediterranean diets, though generally thought to be moderate carbohydrate dietary approaches, are still well above Jaminet’s glucose utilisation threshold.
  • Terry Whals’ Paleo Plus approach achieves a good balance between maximising nutrition through the use of high fibre vegetables and MCT oil without excess protein.
  • The 80% fat diet approach is below the ketogenic maintenance level of 300 glucogenic calories per day but still above starvation ketosis. Personally I think it would be hard for most people to get optimal levels of vitamins, minerals, fibre and possibly protein at these levels without supplementation or focussing on nutrient dense organ meats.  However it may be desirable for someone using ketosis therapeutically for something like cancer or epilepsy.

The typical western diet contains between 40 to 50% carbohydrates, 35 to 40% fat and 15 to 20% protein. [21]  The figure below shows that between 1970 and 2000 carbohydrate intake increased from around 42% to around 49% for men while protein intake has largely stayed constant.  During this period obesity increased from 14.5% to 30.9%. [22]

image014

It’s fair to say that macronutrient composition is only part of the story, but perhaps if we moved the carbohydrate intake back towards the ketogenic corner (along with a shift to more whole unprocessed foods) this trend would turn around again?

what is our light on the horizon?

So how do you decide what dietary approach is optimal for each individual?  What is right for you?  What is the lighthouse on the horizon that you can guide your boat of metabolic health towards?

Back in the Diabetes 102 article we reviewed a number of risk factors that appear to be related to blood sugar control such as the heart disease risks shown in the chart below. [23]

image016

Building on this I developed this table showing the relationship between HbA1c, average blood sugar and ketone values for different heart disease risk categories.

  HbA1c average blood sugar ketones
 (%)  (mmol/L)  (mg/dL)  (mmol/L)
low normal 4.1 3.9 70 4.0
optimal 4.5 4.6 83 2.5
excellent < 5.0 < 5.4 < 97 > 0.3
good < 5.4 < 6 < 108 < 0.3
danger > 6.5 7.8 > 140 < 0.3

Everyone should be striving for optimal blood sugar control in order to manage their overall health and reduce a plethora of risks.

The point where you achieve excellent blood sugar control (i.e. average blood glucose less than 5.4mmol/L) is about where most people will start to show low levels of ketones in their blood.  This is likely to be somewhere around Phinney’s ketogenic threshold (orange line in the protein / carb plot).

People with more severe issues such as extreme insulin resistance, epilepsy, morbid obesity or cancer may choose to push deeper into ketosis beyond the point of simply achieving normal blood sugars and normal HbA1c.  This may require more discipline, intentional supplementation and limitation of food selection than most people are willing to invest.

what gauges do we use to steer the boat?

The most successful diets are the ones that people can stick to.

To this end I have developed a list of optimal foods that prioritises low insulin load, high fibre, nutrient dense foods based on your personal goals (e.g. weight loss, blood sugar control, nutritional ketosis, athletic performance or therapeutic ketosis).  I have also developed this database of optimal meals that will enable you to easily choose simple everyday meals that will provide high levels of nutrition while achieving a low insulin load.

If you have diabetes or insulin resistance then I recommend that you track your blood sugars and ‘eat to your meter’.  You will quickly learn what meals raise your blood sugars and hence what to avoid.

With the understanding that non-fibre carbohydrates plus excess protein raise blood sugar and require insulin you can work to manage your diet until you achieve the excellent blood sugar levels with a reduced or ideally eliminated reliance on medications.

image017

Many people benefit from journaling or tracking food intake on an app such as MyFitnessPal or Cronometre.   Rather than looking at calories or carbohydrates I encourage you to consider insulin load which can be calculated using this formula.

image017

As shown in the table above, you will likely need to get below an insulin load of 150g per day to be under the blue line and under 125g per day to be ketogenic.

While I don’t think it is healthy, natural or normal to consciously monitor everything you eat for extended periods, many people find it useful for a period of time to retrain their habits or to help guide them toward a short term goal.

As a worked example I have calculated the insulin load, % insulinogenic calories as well as the % carbs and % protein for Deshanta from the Optimising Nutrition Facebook group who provided her MyFitnessPal food diary which is summarised in the table below.

carb (g) fat (g) protein (g) fibre (g) insulin load (g) % insulinogenic % carb % pro
143 92 113 42 164 39% 24% 27%
99 99 125 41 128 32% 14% 31%
129 102 134 40 164 36% 20% 30%
50 81 125 17 103 30% 10% 37%
86 88 125 19 137 35% 17% 32%

I’ve also plotted this on the chart below indicating that her diet puts her just outside the realm of a ‘well formulated ketogenic diet’.  If she wanted to improve her blood glucose control further she could consider moving back towards the more ketogenic bottom left of the chart by reducing carbohydrates and / or protein.

image021

If you’re interested in seeing how you can refine your diet to balance your blood sugars with consideration of your blood sugars and glucose load as well as your vitamins and amino acid you could join this closed Facebook group.

what are the levers we can use to steer the boat?

In order to reduce the insulin load of our diet we should do the following:

  1. Increase fibre from non-starchy vegetables (e.g. spinach, mushrooms, peppers, broccoli etc). These will provide vitamins and minerals as well as indigestible fibre that will feed the gut which will also improve insulin resistance. [24]  Increasing fibre in our diet will increase the bulk and the weight of our food without increasing calories or insulin and will tend to decrease our cravings for processed carbohydrates.
  2. Reduce carbohydrates, particularly ones that come in packages with a bar code. Enough said.
  3. If you are not getting the desired results, look to reduce your protein intake until you are achieving excellent blood sugar control and/or your target HbA1c.
  4. If you are still not getting the results you want then look at some form of intermittent fasting to improve your insulin sensitivity and to kick-start ketosis. [25]

Once you are achieving normal blood sugars you may want to occasionally test your blood ketones to confirm you have achieved nutritional ketosis; however tracking your blood sugars will be adequate for most people.

Once you have achieved your desired level of blood sugars, weight and metabolic health you can drop back to monitoring less frequently, just to make sure you are not regressing and then ramp up the efforts again if required.

Then, go outside.  Move.  Have fun.  Find a hobby.  Enjoy life!  And stop thinking so much about food!

[1] http://www.thepaleomom.com/2015/05/adverse-reactions-to-ketogenic-diets-caution-advised.html

[2] https://www.youtube.com/watch?v=XyvlWUQAkxM

[3] http://perfecthealthdiet.com/2012/11/the-safe-starches-panel-from-ahs-2012/

[4] http://drrosedale.com/blog/2011/11/22/is-the-term-safe-starches-an-oxymoron/

[5] http://drrosedale.com/blog/2012/08/18/a-conclusion-to-the-safe-starch-debate-by-answering-four-questions/#ixzz3aDeqQiQ9

[6] http://perfecthealthdiet.com/2011/11/safe-starches-symposium-dr-ron-rosedale/

[7] http://perfecthealthdiet.com/2011/02/ketogenic-diets-i-ways-to-make-a-diet-ketogenic/

[8] http://www.mayoclinic.org/healthy-living/nutrition-and-healthy-eating/in-depth/how-to-eat-healthy/art-20046590

[9] http://www.marksdailyapple.com/press/the-primal-blueprint-diagrams/#axzz3aSDCTDIi

[10] http://lcreview.org/main/130g-carbsday-rda/

[11] See also discussion in Chapter 7 of Richard Feinman’s “The World Turned Upside Down: The Second Low-Carbohydrate Revolution”.

[12] http://www.med.upenn.edu/timm/documents/ReviewArticleTIMM2008-9Lazar-1.pdf

[13] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3636610/

[14] http://en.wikipedia.org/wiki/Glucogenic_amino_acid

[15] https://www.dropbox.com/s/4dkl03mz2fci71v/The%20metabolism%20of%20%E2%80%9Csurplus%E2%80%9D%20amino%20acids.pdf?dl=0

[16] https://youtu.be/8NvFyGGXYiI?list=PLrVWtWmYRR2BlAsGG9tr6T-B4xSum8SCc&t=1234

[17] Though it does take more energy to convert protein to glucose, hence a calorie is not a calories when it comes to protein being converted to glucose via gluconeogenesis.

[18] http://thenoakesfoundation.org

[19] http://www.bengreenfieldfitness.com/2013/05/low-carb-triathlon-training/

[20] http://www.samiinkinen.com/post/86875777832/becoming-a-bonk-proof-triathlete-fat-chance

[21] http://www.ncbi.nlm.nih.gov/pubmed/23324441

[22] http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5304a3.htm

[23] http://www.cardiab.com/content/pdf/1475-2840-12-164.pdf

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

[25] https://intensivedietarymanagement.com/tag/fasting/

latest food insulin index data

After some searching I came across a recent PhD thesis from the University Of Sydney titled Clinical Application of the Food Insulin Index to Diabetes Mellitus (Kirstine Bell, September 2014).

Kirstine Bell’s thesis demonstrated that the food insulin index data had the following practical applications:

  • calculating insulin dose using the food insulin index data provided better blood sugar control for type 1 diabetics compared to normal carbohydrate counting, and
  • type 2 diabetics improved their blood sugar control by choosing foods that caused a lower insulin secretion, independent of calories or carbohydrates.

Appendix 3 of the thesis also contained an extensive food insulin index database of foods that had now been tested.

I have plotted the relationship between carbohydrates and the food insulin index in the chart below.

image003

As you can see from this chart the relationship between carbohydrates and insulin is not straightforward.  Of particular interest is the fact that there are a number of high protein and low fat foods sitting quite high up on the vertical axis while there are a number of high fibre foods with a lower insulin response that you might expect.

However once we account for the effect of protein, fibre and fructose we can achieve a much better prediction of our body’s response to insulin as shown in the revised chart below.

image0232

This understanding of how to calculate our insulin response to food is a useful parameter, along with nutrient density and energy density, which enables us to prioritise our food choices to suit different goals.

image30

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.

image02

the most ketogenic diet foods

  • Ketosis occurs when glucose stores and insulin levels are low which causes the body to switch to the use of fat for fuel.
  • Our insulin response is related not just to carbohydrate, but also the protein and fibre content of our food.
  • This understanding can help us to prioritise foods with a lower insulin load that will help us improve our blood glucose control.

food insulin index

The initial research into the food insulin index was detailed in a 1997 paper An insulin index of foods: the insulin demand generated by 1000-kJ portions of common foods by Susanne Holt, Jennie Brand Miller and Peter Petocz who tested the insulin response to thirty eight different foods.

insulinindex

The food insulin index score of various foods was determined by feeding 1000kJ (or 239 kcal) of different foods to non-diabetic participants and measuring their insulin response over three hours.   This was then compared to the insulin response of pure glucose (which is assigned a value of 100%) to arrive at a “food insulin index” value for each food.

FII versus time chart.jpg

Considering how significant this information could be for people trying to manage their insulin levels (e.g. people with diabetes, “low carbers” or “ketonians”) I was surprised that there hadn’t been much further research or discussion on the topic.  I found a few references and mentions in podcasts, but no one was quite sure what to do with the information, mainly due to the fact that only a small small number of foods been tested.

more food insulin index data

Digging a bit further I came across a recent PhD thesis from the University Of Sydney titled Clinical Application of the Food Insulin Index to Diabetes Mellitus (Kirstine Bell, September 2014) which contained a more extensive list of foods that had been tested since the original study.

With this additional data perhaps we can make more sense of the various factors that affect insulin, the master regulating hormone of our metabolism?

In the chart below I have plotted the carbohydrates versus the insulin response of foods for more than one hundred foods.  Although insulin is loosely correlated with the carbohydrate content of our food, we can see that high protein foods such as steak, tuna and fish still require a significant amount of insulin.

food insulin index - fresh start 9052016 52737 AM.bmp

I ran some analysis on the data and found that we secrete about half as much insulin in response to protein compared to carbohydrate.  And we get the best correlation when we assume that indigestible fibre does not raise insulin.  Interestingly, fructose only requires about a quarter of the insulin as carbohydrate.

Once we account for protein and fibre we get a much better prediction of the insulin response to food compared carbohydrate alone.

food insulin index - fresh start 9052016 52727 AM.bmp

[Check out this cool interactive visualisation of all the FII test data here.]

Using this understanding we can calculate insulin load of our food using the following formula:

insulin load = total carbohydrate – fibre + 0.56 x protein

We can also calculate the proportion of the energy in our food that requires insulin to metabolise (i.e. “the percentage of insulinogenic calories”).

image016

If you have the nutritional properties for a food or a meal you can calculate the percentage  of insulinogenic calories using this calculator created by Dr Ted Naiman.

insulin load, the common denominator

You may have noticed that the internet is full of groups of people passionate about seemingly contradictory dietary approaches that seem to work.

image02

You have the vegans, vegetarians and the longevity crowd who advise that you should minimise animal proteins because they provide excess amino acids which raise IGF-1 and insulin.  People like Joel Fuhrman, T Colin Campbell and Ron Rosedale advise that we should prioritise high fibre unprocessed plant based foods.   This approach, with lower levels of protein, minimal processed carbohydrates and high levels of fibre will have a low insulin load compared to the typical diet.

insulin load = total carbohydrate – fibre + 0.56 x protein

Seemingly on the other end of the spectrum you have the low carbers following an Atkins type diet emphasising higher levels of fat and avoiding carbohydrates.  Similarly, such an approach will also have a relativity low insulin load.

Part of the magic of all of these approaches is that they all manage insulin levels.

possible applications

Insulin is not bad at normal levels, but we are understanding more and more that excess insulin (i.e. hyperinsulinemia) is highly problematic, perhaps as much or more than high blood glucose levels.

Understanding how to calculate our insulin response to food could enable us to better manage our diet to avoid elevated blood glucose and hyperinsulinemia.

The biggest challenge for someone with Type 1 Diabetes (like my wife) occurs when you require a large dose of insulin to address a high blood glucose level that is caused by eating non-fibre carbohydrates and large amounts of protein.  As you can see in continuous glucose monitor plot below, once you’re on the “blood glucose roller-coaster” it’s hard to get off.

It’s much easier to manage your blood glucose levels when the insulin load of your diet is lower (i.e. less non-fibre carbohydrates and moderate protein).

The plot below is from the same person with type 1 diabetes a few weeks later after modifying their diet.  The amplitude of the swings are smaller which makes it easier to manage blood glucose levels with smaller doses of insulin.

A more accurate understanding of insulin load can also help people with diabetes more accurately calculate their insulin dose or people trying to manage conditions like cancer or epilepsy through a therapeutic ketogenic diet.

For the rest of us who are somewhere on the insulin resistance scale, being able to calculate the insulin load of our diet will enable us to design a diet that will enable our pancreas to keep up and maintain normal blood glucose levels.

the most ketogenic foods

Listed below are the foods that will require the least amount of insulin.  I have included a number of other parameters that may be of interest:

  • nutrient density (ND) – high nutrient density foods will help you avoid cravings and achieve satiety with less calories.
  • energy density – foods that contain high levels of fibre and water have a low energy density (i.e. calories per 100g) and will tend to make us full with fewer calories.
  • percentage of insulinogenic calories – this is the proportion of the energy in the food that will require insulin to metabolise.
  • insulin load – foods such as non-starchy vegetables have a higher proportion of insulinogenic calories, but because of their low energy density will have a very low insulin load per 100g of food, meaning that you will need to eat a lot of that particular food for it to affect your blood glucose or insulin significantly.
  • net carbohydrates – these are the digestible carbohydrates that will affect your blood glucose levels and insulin that remain after you account for the indigestible fibre.

The amount you need to prioritise each of these parameters depends on a range of considerations including your blood glucose control and your weight loss goals.   Along with the insulin response to different foods, nutrient density and energy density are other important parameters we can use to optimise our food choices.

2016-07-06 (11)

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.

image02

 

I have sorted the foods below by insulin load which will be useful if you are looking for foods to help you manage the insulin load of your diet.  If you’re interested, the most ketogenic foods article has these foods sorted by their proportion of insulinogenic calories.

Focusing on foods with a low percentage of insulinogenic calories will be useful if you are aiming for a high fat therapeutic ketogenic diet.  Focusing on foods with a low insulin load may be more useful if you want to lose weight and use some of your body fat for fuel.

eggs

Eggs are a staple for low carbers, ketogenic dieters and diabetics.  Not only are they nutritious they are also low in carbohydrates.

 Fried-Egg-Wallpaper-5

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
egg white -0.08 74% 1 9 48
whole egg 0.16 29% 1 10 138
egg yolk 0.17 19% 4 15 317

The egg white is higher in protein and hence more insulinogenic.  At the same time the energy density (calories/100g) of the egg white is lower and hence the insulin load per 100g for the egg white is lower.

dairy

Some people believe that red meat and dairy are uniquely insulinogenic, however my reading of the food insulin index data is that there is nothing special about these foods that isn’t explained by their carbohydrate, protein and fibre content.

Dairy foods typically have a high energy density.  This is great if you’re a growing baby, an athlete trying to replenish energy or a bodybuilder trying to spike insulin for hypertrophy. High palatability and high energy density are not a good combination if you’re trying to lose weight.

cheese

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
cream cheese 0.09 10% 4 8 348
cottage cheese -0.01 38% 3 9 93
ricotta cheese 0.08 25% 3 11 174
feta cheese 0.15 22% 4 14 265
Limburger cheese 0.16 18% 0 15 327
Camembert cheese 0.16 20% 0 15 299
brie cheese 0.14 19% 0 16 334
Muenster cheese 0.15 20% 1 18 368
blue cheese 0.16 20% 2 18 354
mozzarella 0.15 23% 2 18 318
Monterey 0.15 20% 1 19 373
cheddar cheese 0.15 20% 1 20 403
Colby 0.15 20% 3 20 394
Edam cheese 0.17 22% 1 20 356
Gouda cheese 0.17 23% 2 20 356
provolone 0.17 24% 2 21 350
Gruyère cheese 0.17 21% 0 22 412
goat cheese 0.17 22% 2 25 451
Swiss cheese 0.17 26% 5 25 379
parmesan cheese 0.18 30% 3 31 411

milk and cream

Milk has a higher proportion of insulin calories compared to cheese.  Butter and cream have a lower insulin load and proportion of insulinogenic calories.

36959895мляко

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
butter 0.09 0% 0 1 734
cream 0.08 5% 4 5 431
goat milk -0.05 40% 4 7 69
full cream milk -0.10 44% 5 7 65
low fat milk -0.12 58% 5 7 50
human milk -0.14 43% 7 8 71
reduced fat milk -0.13 59% 5 8 51

yoghurt

Full fat plain Greek yoghurt has the lowest percentage of insulinogenic calories while the sweetened and low fat options are extremely insulinogenic.

greek-yogurt

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
Greek Yoghurt 0.01 27% 6 9 130
plain low fat yoghurt -0.02 69% 7 11 63
skim milk yoghurt -0.02 86% 8 12 55
low fat fruit yoghurt -0.00 93% 19 22 95

fruit

It’s interesting to note that there are only a handful of fruits with a low percentage of insulinogenic calories (i.e. olives and avocados).  However some fruits like oranges have a lower insulin load because of their low energy density and therefore may not spike your blood sugar as much as dates or raisins which have a high proportion of insulinogenic calories as well as a high insulin load.  If in doubt, get a blood glucose metre and compare how much your favourite foods raise your blood glucose levels.

spanish-olives

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
olives 0.02 15% 3 3 90
strawberries -0.15 52% 4 5 36
avocado 0.01 18% 5 6 131
raspberries 0.09 42% 6 6 58
watermelon -0.04 88% 7 7 34
nectarines -0.04 68% 8 8 49
limes 0.05 69% 8 8 47
plum -0.06 74% 9 9 51
peaches -0.23 84% 9 9 44
honeydew melon 0.30 88% 8 9 40
apricots -0.21 74% 9 10 54
apples 0.48 77% 10 10 53
blackberries -0.01 79% 8 10 48
grapefruit -0.30 97% 10 10 42
mango 0.10 66% 10 11 67
pear 0.14 69% 11 11 64
orange 0.49 77% 10 11 55
cherries 0.72 84% 10 11 54
apple juice -0.22 95% 11 11 47
pineapple 0.06 84% 12 12 57
mandarin oranges 1.11 85% 11 12 55
kiwifruit -0.02 76% 12 13 67
currants -0.21 83% 12 13 63
apples -0.15 91% 13 13 58
mango nectar -0.20 98% 13 13 53
grape juice -0.06 92% 14 14 62
passion fruit 0.24 54% 13 15 109
guava -0.13 79% 14 15 76
litchis 0.20 80% 14 15 73
grapes 0.45 80% 15 15 77
boysenberries 0.40 66% 15 16 94
blueberries 0.32 72% 16 16 91
figs 0.37 81% 16 17 82
canned peaches -0.14 93% 18 18 77
bananas -0.02 87% 21 21 99
plantains 0.37 79% 25 25 129
dates 0.17 72% 54 56 308
raisins 0.20 84% 68 70 336
prunes 0.11 97% 89 91 378

vegetables

There aren’t many dietary approaches that don’t advise you to eat more vegetables.  It’s also hard to overeat non-starchy veggies because they have a very low calorie density and are high in fibre.  Again, due to the low energy density the net carbohydrates are low in a lot of the non-starchy veggies and hence won’t significant raise your blood glucose levels.

vegetable-03

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
chicory greens -0.25 27% 1 2 28
pickled cucumber -0.99 48% 1 2 13
butter head lettuce -0.98 49% 1 2 16
celery 2.63 49% 1 2 17
radishes 0.70 50% 2 2 19
lettuce 1.34 52% 2 2 17
Chinese cabbage 1.02 60% 1 2 16
chives 0.27 34% 1 3 37
cilantro -0.44 36% 1 3 28
spinach -0.54 41% 1 3 29
mustard greens 0.27 45% 2 3 30
mung beans 0.33 46% 1 3 26
asparagus 1.12 46% 2 3 27
endive -0.60 52% 2 3 20
rhubarb 1.46 57% 3 3 21
summer squash 1.00 65% 2 3 19
artichokes 0.83 33% 3 4 54
turnip greens 1.31 39% 1 4 37
alfalfa (sprouted) -0.54 46% 1 4 31
bamboo shoots 0.90 52% 3 4 28
cabbage 0.81 53% 3 4 30
arugula -0.02 54% 2 4 31
cauliflower -0.60 57% 3 4 28
turnips -0.13 64% 3 4 24
chard (cooked) -0.68 68% 3 4 25
pumpkin -0.04 73% 4 4 23
cucumber -0.03 78% 3 4 18
seaweed (kelp) 0.74 43% 4 5 50
beets 0.34 44% 4 5 48
collards 0.44 46% 2 5 40
snap green beans 0.74 47% 4 5 40
parsley 0.15 49% 3 5 44
jalapeño peppers 0.52 54% 4 5 35
carrots 0.20 55% 5 5 39
okra 0.94 57% 4 5 37
mushrooms 0.65 70% 2 5 30
broccoli 1.21 57% 4 6 42
parsnip 0.73 38% 7 7 76
Brussels sprouts 0.24 54% 5 7 52
peas 0.69 58% 5 7 51
shiitake mushrooms -0.22 60% 5 7 48
bell peppers 0.86 64% 6 7 43
eggplant 0.39 67% 7 7 41
leek 0.13 79% 6 7 36
onions 0.52 77% 7 8 41
winter squash 1.22 80% 7 8 39
kale 0.75 74% 8 10 56

nuts and seeds

Most nuts and seeds have a low percentage of insulinogenic calories though they have a higher energy density are possible to overeat.

food ND % insulinogenic net carbs/100g insulin load  (g/100g) calories/100g
coconut water 1.51 66% 3 3 20
coconut milk 0.03 8% 4 5 246
macadamia nuts 0.12 5% 5 9 769
pecans 0.15 5% 4 9 762
Brazil nuts 0.09 9% 4 15 704
flaxseed 0.08 12% 2 16 568
pine nuts 0.16 11% 9 18 647
coconut meat 0.09 11% 16 20 703
chia seeds 0.10 16% 8 21 511
sunflower seeds 0.18 20% 11 24 491
walnuts 0.10 15% 7 25 683
tahini 0.17 16% 13 26 633
hazel nuts 0.10 16% 15 27 692
almonds 0.11 16% 15 27 652
sesame seeds 0.12 18% 14 27 603
cashew nuts 0.11 22% 24 33 609
pistachio nuts 0.16 23% 19 34 602
pumpkin seeds 0.12 27% 36 53 777

seafood

Seafood is a great source of essential fatty acids which are heard to find in plant based foods.

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

food ND % insulinogenic insulin load  (g/100g) calories/100g
crayfish 0.21 64% 12 78
perch 0.16 59% 13 91
crab 0.26 69% 13 78
oyster 0.31 57% 14 98
lobster 0.30 69% 14 84
sturgeon 0.26 47% 15 129
salmon 0.28 50% 15 122
snapper 0.25 64% 15 94
haddock 0.21 69% 15 85
halibut 0.27 63% 16 105
swordfish 0.28 41% 17 165
rainbow trout 0.28 43% 17 162
mackerel 0.28 45% 17 149
tuna 0.30 50% 17 137
whiting 0.21 63% 17 109
Pollock 0.27 66% 17 105
white fish 0.27 67% 17 102
orange roughy 0.08 67% 17 99
cod 0.17 67% 17 99
herring 0.26 34% 18 210
sardine 0.24 36% 18 202

animal products

7450703_orig

food ND % insulinogenic insulin load  (g/100g) calories/100g
frankfurter 0.10 14% 11 322
bratwurst 0.05 25% 11 171
beef ribs 0.11 13% 12 349
salami 0.12 29% 12 166
foi gras 0.11 11% 13 459
pate 0.13 16% 13 315
turkey heart 0.16 39% 13 130
duck (with skin) 0.12 17% 14 331
pepperoni 0.13 14% 17 487
polish sausage 0.11 26% 17 259
duck (meat only) 0.17 36% 17 195
lamb 0.14 24% 18 308
chorizo 0.15 17% 19 448
ground turkey 0.19 37% 19 203
veal (sirloin) 0.18 38% 19 195
ostrich 0.19 46% 19 168
chicken liver 0.43 48% 20 165
ham 0.26 55% 20 146
sirloin steak 0.16 28% 21 305
goose 0.17 37% 21 230
pork 0.18 46% 21 182
chicken drumstick 0.17 36% 22 238
turkey breast 0.22 70% 22 127
beef liver 0.46 58% 24 169
chuck steak 0.22 50% 25 197
chicken breast 0.22 56% 25 178
veal (leg) 0.25 56% 25 174
emu 0.24 63% 25 159
bacon 0.18 23% 30 522