Insulin responses to foods rich in carbohydrates and protein

Insulin is often presented as a hormone that is at the core of the diseases of civilization, particularly because of the insulin response elicited by foods rich in refined carbohydrates and sugars. What is often not mentioned is that protein also elicits an insulin response and so do foods where carbohydrates are mixed with fat. Sometimes the insulin responses are way more than one would expect based on the macronutrient compositions of the foods.

Holt et al. (1997; full reference at the end of this post) conducted a classic study of insulin responses. This study has been widely cited, and paints an interesting picture of differences in insulin responses to various foods. But you have to be careful where you look. There has been some confusion about the results because of the way they are often reported in places like Wikipedia and on various Internet sites that refer to the study.

The key thing to bear in mind when reviewing this study is that the amounts of food used were designed to have the same calorie content: 1000 kJ or 240 kcal (i.e., 240 calories). This led to wild variations in the size of the portions that are compared and their weight in grams. Also, some of the food portions are probably not what people usually eat in one sitting.

In Holt et al.’s (1997) study the participants were 41 lean and healthy university students. They were fed 1000 kJ (240 kcal) portions of the test foods on separate mornings after a 10-hour fast overnight. Blood insulin levels were measured at different times within a 120-minute period after each meal. An insulin score was then calculated from the area under the insulin response curve for each food; white bread was used as the reference food.

Part of Table 2 on page 1267 is shown below (the full text version of the paper is linked at the end of this post), just to illustrate the types and amounts of food served, and the macronutrient breakdown for each food. I hope you can see what I meant when I said that some of the food portions are probably not what people usually eat in one sitting. I don’t think it would be hard to find someone who would eat 158 g of beef steak in one sitting, but 333 g of fish is a little more difficult. Fish has a higher proportion of protein than beef steak, and thus is more satiating. The same goes for 625 g of orange, about 6 oranges. Foods that have more fat have more calories per gram; hence the smaller portions served for high-fat foods.

Table 4 of the article is a bit long, so I am providing it in two parts below. AUC stands for “area under the curve”. As you can see, for isocaloric portions of different foods (i.e., with the same amount of calories), there is a huge variation in insulin response. The insulin AUCs are shown on the second numeric column from the left. Also note that the insulin responses (AUC) for white bread varied in different meals. This complicates things a bit, but at least provides a more realistic view of the responses since each participant served as his or her own control.

Look at the third column from the right, which shows the insulin responses per gram of each food, compared with the response to white bread, always shown at the top for each group of related foods (e.g., protein-rich foods). The gram-adjusted response for whole-meal bread is rather high, and so is the glucose response. The gram-adjusted insulin response to potatoes is less than one-third of the response to white bread, even though the non-gram-adjusted glucose response is higher. The insulin response to beef is also less than one-third of the response to white bread, gram-for-gram. Even cheese leads to a gram-adjusted response that is about half the one for white bread, and I don’t think many people will eat the same amount of cheese in one sitting as they would do with white bread.

In summary, insulin responses to protein-rich foods are often 50 to 70 percent lower than responses to equivalent amounts of refined carbohydrate-rich foods. Also, insulin responses to unrefined carbohydrate-rich foods (e.g., potato, fruits) are often 70 to 90 percent lower than responses to equivalent amounts of refined carbohydrate-rich foods.

Why do insulin levels go up in response to dietary protein?

One of the reasons is that insulin is needed for tissue protein synthesis. That is, increased circulating protein (as amino acids) and insulin have a net anabolic effect, promoting muscle growth and inhibiting muscle breakdown. (Muscle protein synthesis and breakdown happen all the time; the net effect defines whether muscle grows or shrinks.) In this respect, insulin acts in conjunction with other hormones, such as growth hormone and insulin-like growth factor 1.

Reference:

Holt, S.H., Miller, J.C., & Petocz, P. (1997). An insulin index of foods: The insulin demand generated by 1000-kJ portions of common foods. American Journal of Clinical Nutrition, 66, 1264-1276.

The 2013 PLoS ONE sugar and diabetes study: Sugar from fruits is harmless

A new study linking sugar consumption with diabetes prevalence has gained significant media attention recently. The study was published in February 2013 in the journal PLoS ONE (). The authors are Sanjay Basu, Paula Yoffe, Nancy Hills and Robert H. Lustig.

Among the claims made by the media is that “… sugar consumption — independent of obesity — is a major factor behind the recent global pandemic of type 2 diabetes” (). As it turns out, the effects revealed by the study seem to be very small, which may actually be a side effect of data aggregation; I will discuss this further below.

Fruits are exonerated

Let me start by saying that this study also included in the analysis the main natural source of sugar, fruit, as a competing variable (competing with the effects of sugar itself), and found it to be unrelated to diabetes. As the authors note: “None of the other food categories — including fiber-containing foods (pulses, nuts, vegetables, roots, tubers), fruits, meats, cereals, and oils — had a significant association with diabetes prevalence rates”.

This should not surprise anyone who has actually met and talked with Dr. Lustig, the senior author of the study and a very accessible man who has been reaching out to the public in a way that few in his position do. He is a clinician and senior researcher affiliated with a major university; public outreach, in the highly visible way that he does it, is probably something that he does primarily (if not solely) to help people. Dr. Lustig was at the 2012 Ancestral Health Symposium, and he told me, and anyone who asked him, that sugar in industrialized foods was his target, not sugar in fruits.

As I noted here before, the sugar combination of fruits, in their natural package, may in fact be health-promoting (). The natural package probably promotes enough satiety to prevent overconsumption.

Both (unnatural) sugar and obesity have effects, but they are tiny in this study

The Diabetes Report Card 2012 () provides a wealth of information that can be useful as a background for our discussion here.

In the USA, general diabetes prevalence varies depending on state, with some states having higher prevalence than others. The vast majority of diabetes cases are of type 2 diabetes, which is widely believed to be strongly associated with obesity.

In 2012, the diabetes prevalence among adults (aged 20 years or older) in Texas was 9.8 percent. This rate is relatively high compared to other states, although lower than in some. So, among a random group of 1,000 adult Texans, you would find approximately 98 with diabetes.

Prevalence increases with age. Among USA adults in general, prevalence of diabetes is 2.6 percent within ages 20–44, 11.7 percent within ages 45–64, and 18.9 percent at age 64 or older. So the numbers above for Texas, and prevalence in almost any population, are also a reflection of age distribution in the population.

According to the 2013 study published in PLoS ONE, a 1 percent increase in obesity prevalence is associated with a 0.081 percent increase in diabetes prevalence. This comes directly from the table below, fifth column on the right. That is the column for the model that includes all of the variables listed on the left.



We can translate the findings above in more meaningful terms by referring to hypothetical groups of 1,000 people. Let us say we have two groups of 1,000 people. In one of them we have 200 obese people (20 percent); and no obese person in the other. We would find only between 1 and 2 people with diabetes in the group with 200 obese people.

The authors also considered overweight prevalence as a cause of diabetes prevalence. A section of the table with the corresponding results in included below. They also found a significant effect, of smaller size than for obesity – which itself is a small effect.



The study also suggests that consumption of the sugar equivalent of a 12 oz. can of regular soft drink per person per day was associated with a 1.1 percent rise in diabetes prevalence. The effect here is about the same as that of a 1 percent increase in obesity.

That is, let us say we have two groups of 1,000 people. In one of them we have 200 people (20 percent) consuming one 12 oz. can of soft drink per day; and no one consuming sugar in the other. (Sugar from fruits is not considered here.) We would find only about 2 people with diabetes in the group with 200 sugary soda drinkers.

In other words, the effects revealed by this study are very small. They are so small that their corresponding effect sizes make them borderline irrelevant for predictions at the individual level. Based on this study, obesity and sugar consumption combined would account for no more than 5 out of each 100 cases of diabetes (a generous estimate, based on the results discussed above).

Even being weak, the effects revealed by this study are not irrelevant for policy-making, because policies tend to influence the behavior of very large numbers of people. For example, if the number of people that could be influenced by policies to curb consumption of refined sugar were 100 million, the number of cases of diabetes that could be prevented would be 200 thousand, notwithstanding the weak effects revealed by this study.

Why are the effects so small?

The effects in this study are based on data aggregated by country. When data is aggregated by population, the level of variation in the data is reduced; sometimes dramatically, a problem that is proportional to the level of aggregation (e.g., the problem is greater for country aggregation than for city aggregation).

Because there can be no association without correlation, and no correlation without variation, coefficients of association tend to be reduced when data aggregation occurs. This is, in my view, the real problem behind what statisticians often refer to, in “statospeech”, as “ecological fallacy”. The effects in aggregated data are weaker than the effects one would get without aggregation.

So, I suspect that the effects in this study, which are fairly weak at the level of aggregation used (the country level), reflect much stronger effects at the individual level of analysis.

Bottom line

Should you avoid getting obese? Should you avoid consuming industrialized products with added sugar? I think so, and I would still have recommended these without this study. There seems to be no problem with natural foods containing sugar, such as fruits.

This study shows evidence that sugar in industrialized foods is associated with diabetes, independently from obesity, but it does not provide evidence that obesity doesn’t matter. It shows that both matter, independently of one another, which is an interesting finding that backs up Dr. Lustig’s calls for policies to specifically curb refined sugar consumption.

Again, what the study refers to as sugar, as availability but implying consumption, seems to refer mostly to industrialized foods where sugar was added to make them more enticing. Fruit consumption was also included in the study, and found to have no significant effect on diabetes prevalence.

Here is a more interesting question. If a group of people have a predisposition toward developing diabetes, due to any reason (genetic, epigenetic, environmental), what would be the probability that they would develop diabetes if they became obese and/or consumed unnatural sugar-added foods?

This type of question can be answered with a moderating effects analysis, but as I noted here before (), moderating effects analyses are not conducted in health research.

How to make white rice nutritious

One of the problems often pointed out about rice, and particularly about white rice, is that its nutrition content is fairly low. It is basically carbohydrates with some trace amounts of protein. A 100-g portion of cooked white rice will typically deliver 28 g of carbohydrates, with zero fiber, and 3 g of protein. The micronutrient content of such a portion leaves a lot to be desired when compared with fruits and vegetables, as you can see below (from Nutritiondata.com). Keep in mind that this is for 100 g of “enriched” white rice; the nutrients you see there, such as manganese, are added.

White rice is rice that has had its husk, bran, and germ removed. This prevents spoilage and thus significantly increases its shelf life. As it happens, it also significantly reduces both its nutrition and toxin content. White rice is one of the refined foods with the lowest toxin content.

Another interesting property of white rice is that it absorbs moisture to the tune of about 2.5 times its weight. That is, a 100-g portion of dry white rice will lead to a 250-g portion of edible white rice after cooking. This does not only dramatically decrease white rice’s glycemic load () compared with wheat-based products in general (with some exceptions, such as pasta), but also allows for white rice to be made into a highly nutritious dish.

If you slow cook almost anything in water, many of its nutrients will seep into the water. All you have to do is to then use that water (often called broth) to cook white rice in it, and you will end up with highly nutritious rice. Typically you will need twice as much broth as rice, cooked for about 15 minutes – e.g., 2 cups of broth for 1 cup of rice.

You can add meats to the white rice, such as pulled chicken or shrimp; add some tomato sauce to that and you’ll make it a chicken or shrimp risotto. You can also add vegetables to the rice. If you want your rice to have something like an al dente consistency, I recommend doing these after the rice is ready; i.e., after you cooked it in the broth.

For the white rice-based dish below I used a broth from about two hours of slow cooking of diced vegetables; namely red bell peppers, carrots, celery, onions, and cabbage. After cooking the rice for 15 minutes, and letting it "sit" for a while (another 15 minutes with the pan covered), I also added the vegetables to it.

As a side note, the cabbage and onion tend to completely dissolve after 1 h or so of slow cooking. The added vegetables give the dish quite a nutritional punch. For example, the cabbage alone seems to be a great source of vitamin C (which is not completely destroyed by the slow cooking), the anti-inflammatory amino acid glutamine, and the DNA repair-promoting substance known as indole-3-carbinol ().

The good folks over at the Highbrow Paleo group on Facebook () had a few other great ideas posted in response to my previous post on the low glycemic load of white rice (), such as cooking white rice in bone broth (thanks Derrick!).

Rice consumption and health

Carbohydrate-rich foods lead to the formation of blood sugars after digestion (e.g., glucose, fructose), which are then used by the liver to synthesize liver glycogen. Liver glycogen is essentially liver-stored sugar, which is in turn used to meet the glucose needs of the human brain – about 5 g/h for the average person.

(Source: Wikipedia)

When one thinks of the carbohydrate content of foods, there are two measures that often come to mind: the glycemic index and the glycemic load. Of these two, the first, the glycemic index, tends to get a lot more attention. Some would argue that the glycemic load is a lot more important, and that rice, as consumed in Asia, may provide a good illustration of that importance.

A 100-g portion of cooked rice will typically deliver 28 g of carbohydrates, with zero fiber, and 3 g of protein. By comparison, a 100-g portion of white Italian bread will contain 54 g of carbohydrates, with 4 g of fiber, and 10 g of protein – the latter in the form of gluten. A 100-g portion of baked white potato will have 21 g of carbohydrates, with 2 g of fiber, and 2 g of protein.

As you can see above, the amount of carbohydrate per gram in white rice is about half that of white bread. One of the reasons is that the water content in rice, as usually consumed, is comparable to that in fruits. Not surprisingly, rice’s glycemic load is 15 (medium), which is half the glycemic load of 30 (high) of white Italian bread. These refer to 100-g portions. The glycemic load of 100 g of baked white potato is 10 (low).

The glycemic load of a portion of food allows for the estimation of how much that portion of food raises a person's blood glucose level; with one unit of glycemic load being equivalent to the blood glucose effect of consumption of one gram of glucose.

Two common denominators between hunter-gatherer groups that consume a lot of carbohydrates and Asian populations that also consume a lot of carbohydrates are that: (a) their carbohydrate consumption apparently has no negative health effects; and (b) they consume carbohydrates from relatively low glycemic load sources.

The carbohydrate-rich foods consumed by hunter-gatherers are predominantly fruits and starchy tubers. For various Asian populations, it is predominantly white rice. As noted above, the water content of white rice, as usually consumed by Asian populations, is comparable to that of fruits. It also happens to be similar to that of cooked starchy tubers.

An analysis of the China Study II dataset, previously discussed here, suggests that widespread replacement of rice with wheat flour may have been a major source of problems in China during the 1980s and beyond ().

Even though rice is an industrialized seed-based food, the difference between its glycemic load and those of most industrialized carbohydrate-rich foods is large (). This applies to rice as usually consumed – as a vehicle for moisture or sauces that would otherwise remain on the plate. White rice combines this utilitarian purpose with a very low anti-nutrient content.

It is often said that white rice’s nutrient content is very low, but this problem can be easily overcome – a topic for the next post.

Hunger is your best friend: It makes natural foods taste delicious and promotes optimal nutrient partitioning

One of the biggest problems with modern diets rich in industrial foods is that they promote unnatural hunger patterns. For example, hunger can be caused by hypoglycemic dips, coupled with force-storage of fat in adipocytes, after meals rich in refined carbohydrates. This is a double-edged post-meal pattern that is induced by, among other things, abnormally elevated insulin levels. The resulting hunger is a rather unnatural type of hunger.

By the way, I often read here and there, mostly in blogs, that “insulin suppresses hunger”. I frankly don’t know where this idea comes from. What actually happens is that insulin is co-secreted with a number of other hormones. One of those, like insulin also secreted by the beta-cells in the pancreas, is amylin – a powerful appetite suppressor. Amylin deficiency leads to hunger even after a large carbohydrate-rich meal, when insulin levels are elevated.

Abnormally high insulin levels – like those after a “healthy” breakfast of carbohydrate-rich cereals, pancakes etc. – lead to abnormal blood glucose dips soon after the meal. What I am talking about here is a fall in glucose levels that is considerable, and that also happens very fast – illustrated by the ratio between the lengths of the vertical and horizontal black lines on the figure below, from a previous post ().

Those hypoglycemic dips induce hunger, because the hormonal changes necessary to apply a break to the fall in glucose levels (which left unchecked would lead to death) leave us with a hormonal mix that ends up stimulating hunger, in an unnatural way. At the bottom of those dips, insulin levels are much lower than before. I am not talking about diabetics here. I am talking about normoglycemic folks, like the ones whose glucose levels are show on the figure above.

On a diet primarily of natural foods, or foods that are not heavily modified from their natural state, hunger patterns tend to be better synchronized with nutrient deficiencies. This is one of the main advantages of a natural foods diet. By nutrients, I do not mean only micronutrients such as vitamins and minerals, but also macronutrients such as amino and fatty acids.

On a natural diet, nutrient deficiencies should happen regularly. Our bodies are designed for sporadic nutrient intake, remaining most of the time in the fasted state. Human beings are unique in that they have very large brains in proportion to their overall body size, brains that run primarily on glucose – the average person’s brain consumes about 5 g/h of glucose. This latter characteristic makes it very difficult to extrapolate diet-based results based on other species to humans.

As hunger becomes better synchronized with nutrient deficiencies, it should promote optimal nutrient partitioning. This means that, among other things: (a) you should periodically feel hungry for different types of food, depending on your nutrient needs at that point in time; (b) if you do weight training, and fell hungry, some muscle gain should follow; and (c) if you let hunger drive food consumption, on a diet of predominantly natural foods, body fat levels should remain relatively low.

In this sense, hunger becomes your friend – and the best spice!

Laser surgery for myopia early in life may create reading problems after 40

Shortsightedness, or myopia, seems to be endemic in urban populations. The National Institutes of Health suggests that myopia cannot be prevented, and that neither reading nor watching television causes myopia. I find that doubtful, as reading is a rather unnatural activity, and there is evidence that myopia is significantly associated with amount of reading at early ages.

(Source: WebMD.com)

Trying to avoid reading early in life would not be a highly recommended Paleolithic-mimicking choice, except for those who later decide to live among hunter-gatherers. (In spite of our romantic views of hunter-gatherer life, it is very rare to see an urbanite do this outside the context of anthropological studies.) Education requires a lot of reading, and without education in urban environments one is likely to end up suffering from other diseases of civilization. Diabetes, for example, is strongly and inversely associated with education level in urban environments.

Also, keeping up with friends on Facebook, without which life as we know it now could go on, requires a lot of reading and writing.

A different theory, often associated with Cordain, is that myopia is due to consumption of industrial carbohydrate-rich foods. Interestingly, according to Cordain and colleagues, myopia is typically accompanied by higher stature, a finding that is supported by empirical evidence. The idea here is that industrial carbohydrate-rich foods promote abnormal growth patterns during developmental stages, which arguably include abnormal growth of the human eye and its various structures.

Avoiding industrial carbohydrate-rich foods during developmental stages is feasible, but currently very difficult given public health policies that strongly promote the consumption of some of those foods, during development stages, as healthy choices (e.g., cereals). In part as a result of those policies, and also due to budget constraints (those foods tend to be generally cheap), industrial carbohydrate-rich foods are frequently served as meals in schools.

Okay, now to the main topic of this post. Let us say a person has myopia, should he or she fix it surgically?

As one ages, the ability to read at a short-distance (as in reading from books, or from a computer screen) goes down, because the ability to focus on short-distance objects becomes impaired. This phenomenon is called presbyopia, and is also associated with excessive reading. Therefore it could be called a disease of civilization as well. Most college professors at the level of Associate Professor and higher I know (that is, older folks, like me) have developed it, sometimes as early as in their late 30s.

In the general population, normally presbyopia sets in between 40 and 50 years of age, requiring the use of "reading glasses" afterwards … except for those with myopia. This is sometimes called the “myopia payoff of presbyopia”. People with myopia are often able to read well, without the help of glasses, after presbyopia sets in. The reason is that myopia essentially opposes presbyopia at short distances.

Someone with myopia will still have it after presbyopia sets in, and thus will have difficulty seeing at long distances, but will frequently be able to read well at short distances.

So, if you undergo eye laser surgery (the most common type) to correct myopia early in life, you may create reading problems after 40.

P.S.: A friend of mine who has been studying this tells me that eye problems in general are caused by avoidance of indirect sunlight. I am planning on looking into this more deeply in the future.