In Robb Wolf’s new book Wired to Eat 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]
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.
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.
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…
… gone to extraordinary lengths to obtain energy dense honey …
… and eaten the fattiest cuts of meat and offal, giving the muscle meat to the dogs.
OFT in captivity
But what happens when we translate OFT into a modern context?
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.
We are now surrounded by energy dense hyperpalatable foods that are designed to taste good without providing substantial levels of nutrients.
Our primal programming is defenceless to these foods. Our willpower or our calorie counting apps are no match for engineered foods optimised for bliss point.
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 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 1000 kJ of different foods (see the low energy density high nutrient density foods for weight loss article for more on this complex and intriguing topic).
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.
Grain subsidies were brought in to establish and promote cheap ways to feed people to prevent starvation with cheap calories.[8] It seems now they’ve achieved that goal.[9]
Maybe a little too well.
The foods lowest in fat however are not necessarily the most nutrient dense. Nutritional excellence and macronutrients are are not necessarily related.
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.
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 eliminate all carbohydrates because low fat was such a failure. Right?
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.
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.
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.
what happens when we go paleo?
So if the ‘paleo diet’ 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?
Well, maybe. Maybe not.
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.
But for the rest of us that aren’t insanely active, then maybe simply ‘going paleo’ is not the best option…
… particularly if we start tucking into the energy dense ‘paleo comfort foods’.
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.
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 regular sugar hit to make us feel good (Cori cycle).
Limiting yourself to nutrient dense foods (i.e. nutrients per calorie) is a great way to reverse engineer optimal foraging theory.
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.
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 easily obtain 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.
We are hardwired to get the maximum amount of energy with the least amount of effort (i.e. optimal foraging theory).
Commercialised manufactured foods have separated nutrients from food and made it very easy to obtain a lot of energy with a small investment.
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.
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:
insulin load (which helps as to normalise our blood glucose levels),
nutrient density (which helps us make sure we are getting the most nutrients per calorie possible), and
energy density (helps us to manage the impulses of OFT in the modern world).
I have used a multi criteria analysis to rank the foods for each goal. The chart below shows the weightings used for each approach.
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.
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.
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.
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.
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.
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:
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.
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 within 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 occur 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.
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 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 macro nutrient as I can. Just ‘mouse over’ a data point that you’re interested in to see how it compares to another data point.
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 a 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 micro nutrients 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 mitochondrial 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
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
Nutrient density vs proportion of insulinogenic calories
The plot below shows nutrient density versus proportion of insulinogenic calories. The size of the data points is 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).
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 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 a 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.
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.
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.
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.
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.
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.
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).
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).
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.
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.
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.
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.
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.
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!
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.
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.
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.
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.
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).
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.
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.
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)!
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.
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).
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).
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.
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.
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.
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.
nuts seeds
Nuts and seeds have some non-fibre carbohydrates. Pine nuts, macadamias and almonds are low in carbs with moderate nutrient density.
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.
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.
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.
legumes
Not all legumes are created equal. Choose wisely. Navy beans, legumes, lima beans and peanuts are probably your safest bet.
beverages
Soft drinks and sports drinks are a very poor investment of your limited insulin budget as they are very low in nutrients.
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.
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).
seafood
There are lots of good investments to be made in the top right of this chart of seafood (oyster, salmon, lobster, mackerel).
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).
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.
dairy and egg
Dairy can be insulinogenic, however the higher fat butter, cream and egg still have a fairly low insulin load.
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.
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.
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.
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.
Beverages
Soft drinks are bad news as they will stimulate large amounts of insulin while providing minimal amounts of nutrition and satiety.
In this article, I share my insights and learnings on the benefits, side effects and risks of endogenous and endogenous ketosis.
Exogenous vs. endogenous ketosis
But first, I think it’s important to understand the difference between exogenous and endogenous ketosis:
Endogenous ketosis occurs when we go without food for a significant period. Our insulin levels drop, and we transition to burning body fat and ketones in our blood rise.
Exogenous ketosisoccurs when we drink exogenous ketonesor consume a ketogenic diet.
Ketones vs glucose
Ketones are important. As blood glucose decreases, the ketones in your blood increase to keep our energy levels stable.
The chart below shows three thousand blood glucose vs ketone values measured at the same time from a range of people following a low carbohydrate or ketogenic diet.
Some people produce more ketones than others. Some people have higher blood glucose levels.
What our ketone and glucose values tell us about our metabolic health
Hyperinsulinemia has been called as the “unifying theory of chronic disease” [1] [2] [3] [4] [5]. It’s beneficial to understand where you stand on the spectrum of metabolic health and insulin sensitivity.
The chart below shows the typical relationship between blood glucose and blood ketone for a range of different degrees of insulin resistance/sensitivity.
If your blood glucose levels are consistently high it’s likely you are not metabolising carbohydrate well. When you go without food, endogenous ketones are slow to kick in because your insulin levels are also high. You feel tired and hungry, and you are likely to eat again sooner and not stop until you feel good.
By contrast, if you are insulin sensitive you may be able to go longer between meals naturally and you will not feel as compelled to eat as much or as often. If someone is insulin resistant, a lower insulin load dietary approach will help with satiety and carb cravings while keeping blood glucose levels and insulin under control.
hyperinsulinemia and metabolic disorders
Exciting research is coming out 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]
EXOGENOUS ketones may help to relieve the debilitating symptoms and side effects of acute hyperinsulinemia, Alzheimer’s, dementia, epilepsy or other conditions where glucose is not used well.
exogenous ketones and the low carb flu
Patrick Arnold, who worked with Dr Dominic D’Agostino to develop the first ketone esters and ketone 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, once you have successfully transitioned to a lower carb eating style it may be wise 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 body fat stores.
As discussed in the article Are ketones insulinogenic and does it matter? it exogenous ketones require about half as much insulin as carbohydrate to metabolise (or about the same amount as protein). Hence the continual use of exogenous ketones will limit how much our insulin levels are able to decrease.
Someone with diabetes who follows 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 liver will be able to more easily produce 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.
my experience with exogenous ketones
The light blue “mild insulin resistance” line is based on my ketone and glucose tests when I started trying to wrap my head around low carb/keto.
I enthusiastically started adding generous 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 lots of 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. 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.
I initially purchased a couple of bottles of KetoCaNa after hearing a number of podcast interviews with Dominic D’Agostino and Patrick Arnold.[8][9]
Part of the reasons shelling out the money for the exogenous ketones was to see if it would provide a fuel source that didn’t need insulin for my wife Monica who has Type 1 Diabetes.
This metabolic jet fuel is definitely fascinating stuff! My experience is that it gave me a buzz like a BPC but also has an acute diuretic effect.
I had hoped it would have a weight loss effect like some people seemed to be saying it would.
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.
Unfortunately, my hunger and subsequent binge eating seemed to more than offset the short term appetite suppression that had occurred while the exogenous ketones were in my system. And it was not going to be financially viable for me to maintain a constant level of artificially elevated ketone levels which return to normal levels after a couple of hours.
do exogenous ketones help with weight loss?
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.
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 prove his claim.
Also, the studies that were referenced in the Pruvit FAQ all appeared to relate to the benefits of ENDOGENOUS or nutritional ketosis rather than EXOGENOUS ketone supplementation.
According to Dominic D’Agostino in a Pruvit teleseminar, the EXOGENOUS ketone salts were not designed to be a weight loss product and hence have not been studied for weight loss after all!
The only studies that we could find that mentioned EXOGENOUS ketone supplementation and weight loss were on rats and 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.
Even the experts don’t seem to think exogenous ketones help with fat loss.
The “metabolically healthy” line in the chart above is based on RD Dikeman’s ketone and glucose data when he fasted for 21 days.
Due to his hard-earned metabolic health and improved insulin resistance RD has developed the ability to fairly easily release ketones when he doesn’t eat for a while. RD still doesn’t find going without food effortless, but it is easier than when his insulin levels were much higher which prevented his body from accessing his body fat stores.
Through a disciplined diet and exercise habits 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 glucose : ketone gradient as the gold standard.
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 when fasting, it seems they are also quickly metabolised so they do not build up in his bloodstream.
Where this gets even more interesting is when we look at the glucose and ketone data in terms of TOTAL ENERGY. That is, the energy coming from both glucose and ketones.
The average TOTAL ENERGY of the three thousand data points from these healthy people working hard to achieve nutritional ketosis is around 6.0mmol/L. It seems the body works to maintain homoeostasis around this level.
When the TOTAL ENERGY in our bloodstream increases outside of the normal range it 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 due to the lack of insulin available to keep your energy in storage.
Regardless of whether your energy takes the form of glucose, ketones or free fatty acids, they all contribute to acetyl-coA which is oxidised to produce energy. Forcing excess unused energy to build up in the bloodstream is typically desirable and can lead to long term issues (e.g. glycation, oxidised 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 lipogenesis to decrease the TOTAL ENERGY in the blood stream to normal levels.
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]
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 Thomas Seyfried and Dominic 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 is typically not a concern because it doesn’t happen in nature or when eating 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, 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 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.
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.
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 both more fat and 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 answer through a controlled study in the future are:
What is the safe dose limit of EXOGENOUS ketones for a young child? How would you adjust their maximum intake based on age and weight?
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?
Is there a difference in the way EXOGENOUS ketones are processed in someone is metabolically healthy versus someone who is very insulin resistant?
Does the effect on appetite continue beyond the point that the ketones are out of your system?
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?
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?
Is there a difference in health outcome if you are taking EXOGENOUS ketones in the context of a hypocaloric ketogenic diet versus a hypercaloric ketogenic diet? What about a diet high in processed carbs?
Is there a minimum effective dose to achieve optimal long term benefits to your metabolic health or is MORE better?
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.
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 mobilize glycogen and fat easily when required (e.g. when fasting or a sprint).
Metabolically healthy people are both 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.
Similar to RD Dikeman, John Halloran is an interesting case. He has been putting a lot of effort into eating nutrient dense foods, intermittent fasting and high-intensity exercise.
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!
And he’s been able to lose 10kg (22lb) in one month!
At 5.2mmol/L (i.e. glucose of 4.0mmol/L plus ketones of 1.2mmol/L) John’s TOTAL ENERGY is well below the average of the 26 people shown in the glucose + ketone chart above. 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 or coffee.
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.
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 magic of ketones
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 released 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.
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 flooded with insulin caused by high TOTAL ENERGY building up in your bloodstream (i.e. from glucose, ketones and even free fatty acids).
Driving up ketones artificially through EXOGENOUS inputs (treating the symptom) does NOT lead to increased metabolic health or 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.
Perhaps as more exogenous products come to market without the marketing hype that that comes with multi level marketing (e.g. Julian Baker’s Insta Ketone which are a sixth of the price of the Pruvit products) people will get to see if they really do anything useful.
Just like having low blood glucose is not necessarily good if it is primarily caused by high levels of EXOGENOUS insulin coupled 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/or 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, increased 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.
the best exogenous ketone supplement
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.
If you 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.
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 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.
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 maximise the nutrient density of the food you eat.
After analysing more than 400 meals I have listed below the highest ranking nutrient dense low carb and keto recipes.
Click on each of the photos below to see more details for each recipe.
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.
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.
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”.
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
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
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.
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.
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.
cinnamon
turnip greens
artichoke
curry powder
sauerkraut
cauliflower
raspberries
lettuce
blackberries
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
Choline
Thiamine
Riboflavin
Niacin
Pantothenic acid
Vitamin A
Vitamin B12
Vitamin B6
Vitamin C
Vitamin D
Vitamin E
Vitamin K
minerals
Calcium
Copper
Iron
Magnesium
Manganese
Phosphorus
Potassium
Selenium
Sodium
Zinc
amino acids
Cysteine
Isoleucine
Leucine
Lysine
Phenylalanine
Threonine
Tryptophan
Tyrosine
Valine
Methionine
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.
Docosahexaenoic acid (DHA) (22:6 n-3)
Eicosapentaenoic acid (EPA) (20:5 n-3)
Docosapentaenoic acid (DPA) (22:5 n-3)
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.
Arachidonic acid (20:4)
Oleic acid (18:1)
Lauric acid (12:0)
Capric acid (10:0)
Pentadecanoic acid (15:0)
Margaric acid (17:0)
You can read more on the reason for inclusion of these additional good fats the Good Fats, Bad Fatsarticle.
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.
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.
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.
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.
It’s generally difficult for healthy people to eat too much protein. However the fact that protein requires some insulin to metabolise is an important consideration for people who need to inject extra to keep their blood glucose levels stable.
A better understanding of the insulin response to various foods would be useful for diabetics calculating their insulin dose or even to help refine food choices to manage insulin load.
Since launching the optimising nutrition blog I have had many interesting discussions and learned a lot about protein and how it affects insulin and blood glucose.
The Most Ketogenic Diet Foods article which reviews the food insulin index data and what we can learn about our food choices has received almost 200,000 view. Given the level of interest, I thought it would be useful to review this topic in more detail.
the food insulin index… a quick refresher
If you’ve been reading Optimising Nutrition blog you would have come across discussion of the recent food insulin index testing undertaken at the University of Sydney as detailed in Kirstine Bell’s PhD thesis Clinical Application of the Food Insulin Indexto Diabetes Mellitus [1] (Sept 2014).
The primary learning from the recently expanded food insulin index data is that the carbohydrate content of a food only partially explains the insulin response. The protein, fibre and fructose also affect our insulin response to our food.
The cluster of data points on the left-hand side of the figure below shows that:
low carbohydrate, high fat foods trigger a negligible insulin response, while
low carbohydrate high protein foods cause a significant insulin response.
When we assume that fibre is indigestible and protein has about half the insulinogenic effect of carbohydrates we get a much better prediction of insulin response.
The insulin requirement of a particular food is described better by the following formula:
insulin load = total carbohydrates – fibre + 0.56 * protein
digestion time for protein versus carbohydrates
One of the limitations of the food insulin index data is that the insulin area under the curve was measured over only three hours. This is not a big deal for foods that are high in carbohydrates as they are generally fully digested within three hours.
However protein can take much longer to digest. In the article The Blood Glucose, Glucagon and Insulin Response to Protein we saw that the insulin response to protein in diabetics can be even greater and over a longer period than for people who do not have diabetes.
If we were to repeat the food insulin index testing over a longer period it is likely that the measured insulin response would be significantly greater and even more-so in people with diabetes. That is, the insulin response to protein may be greater than the 56% of the insulin response to carbohydrate indicated by the analysis of the food insulin index data if we were to measure the insulin response over a longer period.
Wilder’s ketogenic formula
Dr Russell Wilder of the Mayo Clinic was the first to coin the term ‘ketogenic diet’. [2] Wilder developed the diet as an alternative to fasting in the treatment of epilepsy in the 1920s.
Wilder also developed the formula shown below to determine whether a diet would be ketogenic. If the number from this calculation was greater than 1.5 (ideally greater than 2.0) then the diet would be considered to be ketogenic and appropriate for the treatment of epileptics. [3]
This formula is based on the understanding that:
100% of carbohydrate is glucogenic (i.e. converts to glucose),
54% of protein is glucogenic,
46% of protein is ketogenic, and
10% of fat is glucogenic.
I had previously searched for detail of how Wilder had arrived at the 56% / 46% split for protein and only found references suggesting that the 56% glucogenic potential of protein comes from the analysis of nitrogen in the urine of dogs. [4] However I recently came across this paper which details Wilder’s thinking in more detail.
Wilder’s conclusion that a diet needs to have more than two times the ketogenic precursors compared to glucogenic precursors is still the basis of the formulation of diets used to treat epilepsy.
According to George Cahill, Krebs also found that 57g of glucose may be derived from 100g of protein. [5] Again, this is similar to the insulin demand for protein observed in the food insulin index tests.
carbohydrate counting
The most straight forward approach is to assume that protein has no impact on insulin or blood sugars.
Dr Richard Berstein and Dr Robert Atkins pioneered the concept of carbohydrate counting for weight loss and diabetes management in the 70s and 80s. There have been various waves of popularity of low carbohydrate diets with many people finding success.
Carbohydrate counting alone is a reasonable approach that is likely to work for most people, particularly if they are not highly insulin resistant.
However, there are some people that reducing carbohydrates alone doesn’t work for. The fact that protein also generates insulin suggests that managing protein as well as carbohydrates may be necessary to manage insulin levels.
thermic effect of food
You may have heard of the concept of the thermic effect of food where different foods require different amounts of energy for the digestion process. For example, a mushroom, which has a very low calorie density and a lot of fibre and protein, may require more energy to digest than is obtained from the digestion of the mushroom.
The maximum and minimum thermic effect (also known as the specific dynamic action) for each macronutrient is shown below. [6]
Compared to carbohydrates and fat, protein only yields between 76% and 84% of the energy per calorie ingested because of losses in digestion. This is useful to know if you’re trying to minimise calorie intake.
As discussed in the Why We Get Fat V2 article, part of this thermic effect of food is also likely to be due to the fact that there is a significant loss of energy when we convert protein to glucose to be used as energy. The body doesn’t like to do this other than in an emergency.
Steve Phinney’s “well formulated ketogenic diet”
One of the key observations from Steve Phinney’s well formulated ketogenic diet (WKFD) chart is that we need to strike a balance between carbohydrates and protein in order to maximise the ketogenic potential of our diet.
You can have 30% protein and 5% carbs or 20% carbs and 10% protein and still be within the bounds of a ketogenic diet. However if you have 30% protein and 20% carbs you will be outside the realms of a ketogenic diet because you will be producing too much glucose.
According to Nuttall and Gannon [7] the body requires between 32 and 46g per day 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’ protein for gluconeogenesis. This should not be considered optimal, but simply a minimum reference point for the absolute minimum amount of protein.
Interestingly, the slope of the line along the face of Phinney’s WFKD triangle corresponds with the assumption that 7% of protein goes to muscle growth and repair (protein synthesis) with 75% of the remaining ‘excess’ protein being glucogenic. This 75% value is in the “ball park” (although a little higher) of our previous estimate of the glucogenic potential of protein based on the analysis of the food insulin index data.
amino acid potential
We also have an understanding of which amino acids are glucogenic, which are ketogenic and which are a bit of both. [8][9][10] The table below shows the various amino acids divided up on the basis of their ketogenic versus glucogenic potential and also which are essential versus non-essential. [11]
Only two amino acids are exclusively ketogenic. There is a handful that are both glucogenic and ketogenic. However most of the amino acids are glycogenic, meaning that they will most likely turn into glucose if not required for protein synthesis.
According to David Bender“In fasting and on a low carbohydrate diet as much of the amino acid carbon as possible will be used for gluconeogenesis, an ATP-expensive, and hence thermogenic process.”
Hence it appears likely that in a low carbohydrate diet situation excess amino acids that fit under the “both” classification will be turned to glucose rather than ketones because the body needs the extra glucose which it is not getting from ingested carbohydrates.
Conversely, if someone is consuming a high carbohydrate diet the excess amino acids that fit into the “both” category will be converted to ketones rather than glucose because the body is getting more than enough glucose from the diet.
So, to some extent, protein is versatile depending on the body’s need. But at the same time, it is only a small portion of the amino acids that are able to do this. The fate of the majority of the amino acids is pre-destined.
the krebs cycle
The figure below shows the process of catabolism of amino acids. [12]
I am not an organic chemist, but from what I understand this means that:
The amino acids Leucine and Lysine cannot be converted back to glucose as they are ketogenic;
Isoleucine, Tyrosine, Phenylalanine, Tryptophan, Threonine all enter into the amino acid catabolism cycle and can be used for various functions, such as muscle repair and growth, but can also be converted back into glucose if required (glucogenic) or turned into fatty acids (ketogenic); and
The remaining amino acids enter the cycle and can be used for a variety of functions in the body, but cannot be converted into fatty acids. If they are not required they can be turned into glucose and potentially stored as body fat.
The majority of the amino acids obtained from the digestion of protein have the potential to be turned into glucose through gluconeogenesis.
The reason that we don’t see a sharp rise in blood glucose is partly because amino acids from digestion circulate in the blood until they are required. Gluconeogenesis is a demand driven process. Glucose is pulled from amino acids when there is no other source rather than pushed into the bloodstream due to ingestion of excess protein.
By contrast, glucose from carbohydrates will be used to refill glycogen stores (liver and muscle) and then find their way quickly into the bloodstream. In most people, the amino acid stores in the blood are not saturated and hence there is plenty of capacity to store amino acids until they are required, at least if you have good insulin sensitivity and are not diabetic.
The body does need glucose, and it is fine to get it from carbohydrates or protein via gluconeogenesis. However many people struggle to produce enough insulin and / or are insulin resistant and hence struggle to keep their blood sugars in normal range. For these people it makes sense to reduce the insulin load their diet (the portion that requires insulin) to a point that they can maintain normal blood glucose levels.
tallying up the amino acids
I figured I could use this knowledge of the categorisations of the various amino acids to better understand how much of the proteins in the 8000 foods listed in the USDA food database are glucogenic versus ketogenic.
For each food in the USDA database I tallied up the weight of the glucogenic and ketogenic amino acids and the amino acids that fell onto the ‘both’ category and found that:
ketogenic amino acids make up only 12% by weight of the total protein across the 8000 foods in the database,
glucogenic amino acids comprise 74% of the foods, and
amino acids that fit in the “both” comprise 14% of the total weight of amino acids.
This means that somewhere between 78% and 89.5% of protein has the potential to turn into glucose, depending on whether you considered the amino acids in the ‘both’ column to be glucogenic or ketogenic, or somewhere in between.
For someone eating a low carbohydrate diet nearly 90% of ‘excess’ protein could be turned to glucose in the blood stream.
Why is this different to the observation from the food insulin index testing that approximately 56% of protein raises insulin? Perhaps the following factors come into play:
When we consider the glucogenic potential of the individual amino acids we are considering the maximum potential of protein if it is not first used for protein synthesis. The amount of protein synthesis will be greater for say an athlete or a body builder, with less protein remaining for gluconeogenesis.
Converting protein to glucose requires energy and hence some of the energy from ingested protein is lost in the process and hence is not converted to glucose.
The insulin index testing is undertaken over only three hours. Protein takes much longer to digest and be metabolised into glucose hence the insulin index testing may underestimate the full glucogenic potential of protein.
which foods have the most ketogenic protein?
So I bet you are wondering which forms of protein have the highest amount of ketogenic protein. Maybe not? Well, I was, and I am going to share it with you.
The table below shows the foods from the USDA database that have the most ketogenic protein (assuming the ‘both’ amino acids are split 50/50 glucogenic / ketogenic) in terms of grams of ketogenic amino acids per 100 grams of the food.
Food
ketogenic aminos ( per 100g)
% ketogenic protein
% insulinogenic
Seal, Bearded Alaskan
19.4g
23%
72%
Whale, Beluga
17.6g
25%
64%
Cod
16.3g
26%
68%
Seaweed, spirulina
14.2g
25%
64%
White fish
13.6g
22%
53%
Parmesan cheese
12.3g
32%
28%
Beef, sirloin
10.0g
33%
50%
Beef, ribeye
9.7g
33%
44%
Bacon
9.3g
25%
22%
Egg yolk
9.2g
27%
18%
Lamb
9.0g
25%
39%
Chicken, breast with skin
7.8g
24%
48%
Salmon
7.0g
28%
45%
Egg, whole
3.3g
26%
29%
Milk
0.9g
29%
43%
It is hard to know what to make of this list other than noting that the seal, whale and cod have the highest amounts of ketogenic protein. Perhaps there is something about cold water animals that cause them to store more ketogenic amino acids? This seems to align with what we see in the traditional diets of humans who may eat more fat if they are living further away from the equator but eat more carbohydrates from fruits if they live closer to the equator.
Although seal, whale and cod have high amounts of ketogenic amino acids, overall they are still quite insulinogenic. In view of the high proportion of insulinogenic properties of some meats it is not surprising that people can thrive on a 100% meat zero carb diet because the body can get as much glucose they need from the meat.[13] At the same time though, I’m not sure that an all meat diet can provide an optimal array of vitamins and minerals unless you are emphasising organ meats.
In view of the fact that a large amount of protein can be converted to glucose through gluconeogenesis, it seems better to focus on foods that have a lower percentage of insulinogenic calories if you are insulin resistant or do not have a fully functioning pancreas.
Rather than worrying about whether you’re eating too much protein, most people will do fine if they limit their processed grains and sugars and eating as much protein as their appetite directs them to. If you are aiming for a therapeutic ketogenic diet to manage chronic conditions such as cancer, epilepsy or dementia, then you may want to consider moderating your protein intake to drive ketosis.
The table below shows a comparison of a range of glucogenic factors for protein relative to carbohydrate, summarising the discussion above. Most of the approaches to understanding the insulinogenic portion of protein give an even higher value than suggested by the analysis of the food insulin index data.
Basis
% insulinogenic
Comment
Carbohydrates only
0%
A lower end sensitivity assuming that no protein is converted to glucose (i.e. as per standard carbohydrate counting).
Food insulin index
56%
Based on testing of > 100 foods in healthy individuals
Thermic effect of food
77%
Average of additional in digestion losses minus 7%.
Wilder’s formula
54%
Used in initial ketogenic formula
Krebs / Janney
57%
Based on nitrogen excretion in dogs
Glucogenic potential (min)
78%
Based on summing amino acids in USDA foods database, excluding “both” aminos.
Glucogenic potential (max)
89.5%
Based on summing amino acids in USDA foods database, including “both” aminos.
Steve Phinney WFKD
75%
Assuming that the first 7% of calories goes to growth and repair with 75% of the remaining amino acids being glucogenic.
the most ketogenic foods… updated
I have calculated the insulinogenic potential of the foods shown in this previous article (The Most Ketogenic Diet Foods) using the following approaches:
carbohydrates only;
food insulin index data (i.e. protein is 56% insulinogenic);
thermic effect (i.e. protein is 77% insulinogenic); and
maximum glucogenic potential of the amino acids for each food (varies for each food based on data in USDA foods database).
This updated data illustrates the difference in standard carbohydrate counting and the full insulinogenic potential of the food. While there is a range of values due to the varying amounts and types of protein overall, there is a reasonable alignment between the food insulin index (56%), thermic effect of food (77%) and maximum glucogenic potential values, particularly when we compare it to the carbohydrate only approach for the lowest carbohydrate foods.
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 Indexto 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).
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.
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).
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.
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).
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).
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.
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).
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”.
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.
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.
curve fitting
Kirstine Bells’ Clinical Application of the Food Insulin Indexto 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 Indexto 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”.
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.
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).
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.
practical application
Individual foods can be ranked and prioritised based on their proportion of insulinogenic calories using the following formula:
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:
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:
carbohydrates require insulin,
indigestible fibre does not require insulin, and
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:
Reduce insulin load until you normalise blood glucose levels (i.e. reduce digestible carbohydrates and moderate protein if necessary),
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),
Reduce dietary fat if you still need to reduce body fat levels, and
Implement an intermittent fasting routine to improve your insulin sensitivity and to kick-start ketosis.
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:
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 ageing, 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.
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’.
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 from the glycogen stores in the liver and muscles. Once the glycogen stores are exhausted the body will obtain glucose via gluconeogenesis from cannibalising muscle.
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]
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 fewer 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).
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 from 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.
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]
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]
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.
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.
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.
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:
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.
Reduce carbohydrates, particularly ones that come in packages with a bar code. Enough said.
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.
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!
[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.
The glycemic index (GI) compares the rise in blood sugar for a particular food relative to glucose. The theory goes that it is better to eat low glycemic index carbohydrates that will not raise our blood sugar too much and will take longer to digest.
Building on the glycemic index is the concept of glycemic load which is the GI of a food multiplied by the grams of carbohydrate eaten. Watermelon has a very high GI value, however because watermelon only contains a small quantity of carbohydrates (watermelon is mostly water) the overall glycemic load is small. A large glycemic load occurs when you eat a large quantity of a high glycemic index carbohydrate.
The limitation of the GI approach is that we can eat a diet full of low glycemic index carbohydrates and protein while still producing a large amount of insulin. Even though they are slow to digest and do not raise blood sugar significantly, a low GI moderate GL diet will still require substantial amounts of insulin. It’s the amount of insulin, not the grams of carbohydrates or even the rise in blood sugar that’s really at the nub of the problem.
The chart below shows the relationship between the glycemic load and insulin index. Reducing the glycemic load does not guarantee a low insulin response, particularly when it comes to high protein foods.
Even if you’re eating low GI foods that don’t spike your blood sugars you may still be generating a sustained requirement for insulin. Maintaining reasonable blood sugars in spite of a moderate glycemic load is just an indication that your pancreas is still keeping up, for now.
Various studies have shown that eating a low GI diet doesn’t help with weight loss. [4][5] We also now know that high insulin levels are also a massive health risk as well as high blood sugars. [6]
Rather than focusing on the glycemic load or the glycemic index, I believe it is more important to manage the overall insulin load of the diet, particularly if your aim is to achieve optimal blood sugars or reduce excess body fat.
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