the food insulin index list

the latest food insulin index data

Understanding the various factors that affect your insulin requirement is critical to diabetes management and optimal health.

Living with someone who has Type 1 Diabetes for seventeen years I’ve gained a deep appreciation of how different foods affect your blood glucose levels.  Poor food choices can send you on a blood glucose rollercoaster that can affect your appetite, mood and energy levels.

Luckily, the latest insulin index testing data can help us to better manage our food choices to manage our blood sugars and insulin levels.

In this article, I will share my analysis, experience and insights about how we can use the insights from insulin index testing to optimise your metabolic health.

The blood glucose roller coaster

Since she was ten, my wife Monica has had to manually manage her blood sugars as they swing up with food and then drop again when she injects insulin.

The continuous glucose monitor chart below shows a typical daily experience for someone with Type 1 Diabetes.

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High blood glucose levels make her feel “yucky”.  Then, plummeting blood glucose levels due to the mega doses of insulin don’t feel good either.

Low blood glucose levels drive you to eat until you feel good again.  This wild blood glucose roller coaster ride leaves you feeling exhausted.

These days Monica has an insulin pump which means she doesn’t have to insert a needle six times or more a day.  But we’ve found that good blood glucose control still comes down to managing the food you eat.  To stabilise the massive swings in blood sugars you need to make intelligent food choices to reduce the amount of insulin you need.

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The dietary advice that Monica has received over the past three decades living with Type 1 has been sketchy at best.  When she was first diagnosed with Type 1, Monica tells the story of being told to eat so much high carb food that she hid it in the pot plants in her hospital room.

These days the story is pretty much the same.  The photo below is of the daughter of some friends of ours, Lucy Smith, in the hospital just after she was diagnosed with Type 1 Diabetes.

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When we decided we wanted to have kids, we found a great doctor who helped us to understand how to match insulin with carbs.  However, no one told us how to make better food choices to reduce the amount of insulin required, including physicians, endocrinologists or diabetes educators.

We eventually stumbled across the low carb, and Monica has been able to significantly improve her blood glucose control.  This has enabled her to have a lot more energy to invest in to being a mother as well as going back to work as a teacher which she is loving.

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So, low carb produces great results for people trying to stabilise their blood sugars.  But there is still more to the story for people who need to actively manage insulin.

The latest food insulin index data

In early 2014, I came across Jason Fung’s Aetiology of Obesity series on YouTube where he discussed the food insulin index research that had been carried out at predominantly the University of Sydney which seemed to provide more insight into our insulin response to food.

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I hoped that by gaining a better understanding how different foods affect our requirement for insulin, I might be able to help further optimise our food to normalise Monica’s blood glucose swings.

However, unfortunately, while the concept of insulin index testing is exciting, the data that is commonly available is hard to make sense of.  The initial research into the food insulin index was detailed in a 1997 paper An insulin index of foods: the insulin demand generated by 1000-kJ portions of common foods by Susanne Holt, Jennie Brand-Miller and Peter Petocz who tested the insulin response to thirty-eight different foods.  The insulin score of the various foods tested is shown in the image below.

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The food insulin index score of various foods was determined by feeding 1000kJ (or 239 kcal) of a range of foods to non-diabetic participants and measuring their insulin response over three hours.  Some example insulin responses to different foods are shown in the chart below

FII versus time chart

This value is then compared to the insulin response to pure glucose (which is assigned a value of 100%) to arrive at a “food insulin index” value for each food.  All foods tested were then ranked relative to pure glucose.

Considering how significant this information could be for people trying to manage their insulin levels I was surprised that there hadn’t been a lot of further research or discussion on the topic.  I found a few references and mentions in podcasts, but no one was quite sure what to do with the information.  The chart showing the insulin index of the original 38 foods tested was really more confusing than useful for most people.

But then I found the mother load of data!

But then, after searching some more, I came across a PhD thesis Clinical Application of the Food Insulin Index to Diabetes Mellitus (Kirstine Bell, September 2014).   Appendix 3 of the thesis contained an extensive food insulin index database of foods that had now been tested.  The figure below shows all the foods tested plotted from smallest to largest insulin response.

[I know this is a bit hard to read.  You can click on the image to expand it.  I’ve uploaded these charts to Tableau online here so you can make more sense of the data.]

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The chart below shows the relationship between carbohydrates and insulin response for all the foods tested to date.

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As you can see, the relationship between the carbohydrates we eat and the insulin we require to metabolise our food is not straightforward.

Some high protein and low-fat foods (e.g. fish and steak) are sitting quite high up on the vertical axis while there are some high fibre foods (e.g. all bran and navy beans) and high fructose foods (e.g. raisins and apples) with a lower insulin response than you might expect.

However, once we account for the effect of protein, fibre we are able to more accurately predict our body’s insulin response to food.  The foods in the bottom left corner of this chart will require the least insulin (e.g. butter, olive oil and avocado) while the foods in the top right will require the most insulin (e.g. rice bubbles, cornflakes and jellybeans)

carbohydrates fibre protein and vs food insulin index.png

It’s also interesting to note that fructose (a form of sugar found in fruit) requires only about 25% as much insulin as glucose.  The glycerol backbone in fat can also be converted to glucose via gluconeogenesis if there is no other glucose availabe from glucose or protien in the diet.  However, neither of these have a massive influence compared to carbohydrates, protein and fibre.

How is this useful?

This improved ability to quantify our insulin response to food enables us to precisely identify foods that require less insulin and reduce the amplitude of our blood sugar swings in response to food.

Many people trying to follow a therapeutic ketogenic diet (for the management of cancer, epilepsy, Alzheimers, dementia etc.) have found it very useful to reduce their insulin requirements and increase their ketone levels.

Similarly, people with diabetes who are injecting insulin have also found it be invaluable to help them more accurately.

Calculating the proportion of insulinogenic calories is useful for people who require a very low insulin therapeutic ketogenic diet while insulin load is useful for people managing hyperinsulinemia, insulin resistance or diabetes (see Insulin dosing for Type 1 Diabetes article)

Monica’s daily insulin dose has dropped from more than fifty units a day to closer to 20 units of insulin per day, and the amplitude of her blood glucose swings is much smaller.  The improvement in the quality of life, energy levels and mood for someone with diabetes when they stabilise their blood sugars is massive.  I’ve seen and experience this first hand, hence my passion to get this message out!

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The problem with the food insulin index

The problem with looking at things purely from a food insulin index perspective is that the resultant high-fat foods do not provide a broad range of micronutrients.

A diet with a low proportion of insulinogenic calories also tends to be very energy dense which can make portion control more challenging for people wanting to lose weight.

While stabilise the glucose swings is related mainly to the quality of the food we eat, bringing down the overall blood sugar levels is mostly about weight loss and the quantity of food we eat.

Once we stabilise blood sugars with a lower insulin load diet, we then need to focus on reducing the energy density of your food to enable you to lose weight and allow then fat stores to function optimally.

Diabetes occurs when our fat stores become too full, and they can no longer expand and contract to absorb and release the food from our meals, and the excess energy spills into the bloodstream.  Increasing the nutrient:energy ratio of our food will allow us to get the nutrients we need with less energy which will, in turn, help us to achieve and maintain an optimal body fat level.

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optimal foods for different goals

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

Building on the ability to quantify insulin load, nutrient density and energy density, more recently I have been developing an exciting new tool.

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The Nutrient Optimiser reviews your food log diet and helps you to normalise your blood glucose and insulin levels by gradually retraining your eating habits by eliminating foods that boost your insulin level and blood glucose levels using our ability to calculate the insulin load.

As shown in the chart below, some nutrients are easy to find.  However, most of us have a large number of micronutrient gaps and need to prioritise the foods and meals that will provide those harder to find nutrients.  Once your glucose levels are normalised, the Nutrient Optimiser starts to focus more on providing you with the nutrients you need with less energy.

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Then, if you still have weight to lose, the Nutrient Optimiser will focus on the energy density of your diet until you have achieved your desired level of weight loss.

It’s early days for the Nutrient Optimiser, but the initial results are very promising.   I’d love it if you’d head over to NutrientOptimiser.com to get your free report to find your optimal dietary approach and which foods, meals will be ideal for you.

 

 

Post last updated January 2018

37 thoughts on “the latest food insulin index data”

  1. But the foods which cause the least insulin secretion, according to the above graph, are low carb. So, “independent of calories or carbohydrates” seems a little misleading.

  2. I had the same question Alec. But if you read the actual thesis and the associated papers you’ll see that they actually kept the calories and carbohydrates consistent. They weren’t really testing a low carb approach. The only variable was the insulin index of the foods. In effect they would have been choosing foods with more fibre and less protein. A much better improvement would be achieved by adopting a low insulin load approach. Hopefully they can repeat a similar study in the future with this approach.

    1. Has anyone yet come up with an
      Insulin Index that tested isolated
      foods? I haven’t found one. It’s
      prohibitive to test insulin on one’s
      own, since the testing process is
      expensive and not universally
      available.

      1. Marty:

        No “reply” button on your last post.
        Are you referring to the 38 “foods”
        that they tested? “Jellybeans” are
        food? “Mars Bars”, “donuts” “ice cream”
        “Cake”? Well, okay if they say so.
        Why not some real food? Tallow? Butter?
        Nuts? Not on the list. “Fish”? What
        kind of fish? There are many kinds
        of marine foods. Do they all fall under
        the heading “fish”? Are all meats “beef”?
        The paper was behind a paywall. Maybe
        it’s all explained there.
        I’m talking about an insulin test for isolated
        foods. This one isn’t it.

  3. Great information ! I would have liked to see “lite” or skim milk included. The Swedish “Keyhole marking” requires less than 0.7% fat and in my opinion it is a pure early disease and widow maker! A 12 year study of 1600 men showed that those with lowest intake of milk fat compared to those with most high fat dairy had 3x = 300% higher incidence of central obesity = lots higher risk for diabetes, heart disease and risk for death of all causes. The study is here: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3656401/
    As also well known, skim milk was used to fatten pigs when pig fat was more important than lean pork. It would not surprise me if skim milk was also given to geese with grain to speed up fois gras. But for now its insulin index is most interesting!

  4. Thanks for reply!
    Full cream milk comes out at insulin index 25% from the diagram in your “The most ketogenic foods”. What am I missing to arrive at 40% ?

    One more thing to address is probably the carbohydrate fructose as has a very low insulin response but produces liver fat and leads to insulin resistance in a different pathway than through (over-) exposure to insulin. It may deserve an exclusion and a special goodbye? Is it one reason raisins are coming out good in the insulinogenic index, its 28% fructose? Looking forward to your analysis!

  5. Found it interesting that in the study, the Australian version of Kellogg’s Special K has an FII of 48, while the U.S. version has an FII of 86. And there’s not much difference in the macros. Be interesting to find out why such a huge difference.

  6. Hey Marty

    Excellent information.

    One major premise of a low carb diet is that carbs increases insulin.

    So instead of looking at how many carbs foods contain, and draw a correlation, its even better to look simply at how much insulin foods raises.

    Your table list of foods is particularly useful to diabetics.

    p.s. low fat yogurt could be renamed high insulin yogurt.

  7. Thanks Marty,
    Do you have list the new Food Insulin Demand (FID) not the Food Insulin Index (FII) ? Which Do you think the most accurate to determine insulin shots? GI, GL, FII, FID, or Carb content?

    Thanks

  8. Hi Marty, have been on a low carb, high fat diet now for 4 weeks, but am flying by the seat of my pants re insulin dosing. I’ve printed out the superfoods table, but have no idea how to translate this info into insulin requirements. Also,blackberries seem the only fruit on the list, unless I’m missing something. Can you clarify?

  9. Hai Marty, I have read Bell Thesis 1,page 214, how to count FID of the white bread of 26 (1 slice white bread has FII of 73 and contains 310 kj so 73 times 310/1000 is 22.63)? FID, Food Insulin Demand. (FID = FII x kJ in food portion /1000) scaled using the FID and carbohydrate content of 1000 kJ of glucose powder (100/59)).

  10. How do substances that trigger insulin, but which don’t contain any calories, factor in? How do you calculate the insulin load of an artificial sweetener like Aspartame that has an insulin response? Is there a way?

    1. From The book Brain Maker: David Perlmutter.

      “We used to think that sugar substitutes like saccharin, sucralose, and aspartame didn’t have a metabolic impact because they don’t raise insulin, it turns out that they can indeed wreak tremendous metabolic havoc and cause the same metabolic disorders as real sugar. How so? They do this by changing the microbiome in ways that favor dysbiosis, blood sugar imbalances, and an overall unhealthy metabolism. And yes, the food and beverage industry has a splitting headache over this latest study, which was published in 2014 in the journal Nature.
      https://www.nature.com/news/sugar-substitutes-linked-to-obesity-1.15938
      Just forget Coke’s Zero. It is like drugs. Always side effects.

  11. The research out of Israel and Stanford on personalised diets and gut micro biome see eran Segal’s ted talk one published research should help one size does not fit all.
    Eric

  12. Hi
    Okay, I’m sorry if I sound stupid but I’m not getting it. According to the graphs withe pasta has a lower insulin response than beef. But that goes against everything everybody is saying. What am I missing? Why does it matter how far to the right the foods are on the x-axis? Surley the insulin response (y-axis) is the more important factor, which would mean all the foods towards the bottom of the graph are the ones to dig into. I’m completely confused. Can somebody please explain? I’d really appreciate it.
    Isabella

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