Hormonal reductionism is as myopic as biochemical reductionism

Biochemistry-based arguments can be very misleading. Yet, biochemistry can be extremely useful in the elucidation of diet and lifestyle effects that are suggested by well-designed studies of humans. If you start with a biochemistry-based argument though, and ignore actual studies of humans, you can easily convince someone that glycogen-depleting exercise (e.g., weight training) is unhealthy, because many health markers change for the worse after that type of exercise. But it is the damage caused by glycogen-depleting exercise that leads to health improvements, via short- and long-term compensatory adaptations ().

Biochemistry is very helpful in terms of providing “pieces for the puzzle”, but biochemical reductionism is a problem. Analogous to biochemical reductionism, and perhaps one example of it, is hormonal reductionism – trying to argue that all diet and lifestyle effects are mediated by a single hormone. A less extreme position, but still myopic, is to argue that all diet and lifestyle effects are mostly mediated by a single hormone.

One of my own “favorite” hormones is adiponectin, which I have been discussing for years in this blog (). Increased serum adiponectin has been found to be significantly associated with: decreased body fat (particularly decreased visceral fat), decreased risk of developing diabetes type 2, and decreased blood pressure. Adiponectin appears to also have anti-inflammatory and athero-protective properties.

As a side note, typically women have higher levels of serum adiponectin than men, particularly young women. Culturally we have a tendency to see young women as “delicate” and “vulnerable”. Guess what? Young women are the closest we get to “indestructible” in the human species. And there is an evolutionary reason for that, which is that fertile women have been in our evolutionary past, and still are, the bottleneck of any population. A population of 100 individuals, where 99 are men and 1 is a woman, will quickly disappear. If it is 99 women and 1 fertile man, the population will grow; but there will also be some problems due to inbreeding. Even if the guy is ugly the population will grow; without competition, he will look very cute.

Jung and colleagues measured various hormone levels in 78 obese people who had visited obesity clinics at five university hospitals (Ajou, Ulsan, Catholic, Hanyang and Yonsei) in Korea (). Those folks restricted their caloric intake to 500 calories less than their usual intake, and exercised, for 12 weeks. Below are the measured changes in tumor necrosis factor α (TNF-α, now called only TNF), interleukin-6 (IL-6), resistin, leptin, adiponectin, and interleukin-10 (IL-10).

We see from the table above that the hormonal changes were all significant (all at the P equal to or lower than 0.001 level except one, at the P lower than 0.05 level), and all indicative of health improvements. The serum concentrations of all hormones decreased, with two exceptions – adiponectin and interleukin-10, which increased. Interleukin-10 is an anti-inflammatory hormone produced by white blood cells. The most significant increase of the two was by far in adiponectin (P = .001, versus P = .041 for interleukin-10).

Now, should we try to find a way of producing synthetic adiponectin then? My guess is that doing that will not lead to very positive results in human trials; because, as you can see from the table, hormones vary in concert. At the moment, the only way to “supplement” adiponectin is to lose body fat, and that leads to concurrent changes in many other hormones (e.g., TNF decreases).

Trying to manipulate one single hormone, or build an entire health-improvement approach based on its effects, is myopic. But that is what often happens. Leptin is a relatively recent example.

One reason why biochemistry is so complex, with so many convoluted processes, is that evolution is a tinkerer that is “blind” to complexity. Traits appear at random in populations and spread if they increase reproductive success; even if they decrease survival success, by the way ().

Evolution is not an engineer, and is not even our “friend” (). To optimize our health, we need to “hack” evolution.

Refined carbohydrate-rich foods, palatability, glycemic load, and the Paleo movement

A great deal of discussion has been going on recently revolving around the so-called “carbohydrate hypothesis of obesity”. I will use the acronym CHO to refer to this hypothesis. This acronym is often used to refer to carbohydrates in nutrition research; I hope this will not cause confusion.

The CHO could be summarized as this: a person consumes foods with “easily digestible” carbohydrates, those carbohydrates raise insulin levels abnormally, the abnormally high insulin levels drive too much fat into body fat cells and keep it there, this causes hunger as not enough fat is released from fat cells for use as energy, this hunger drives the consumption of more foods with “easily digestible” carbohydrates, and so on.

It is posited as a feedback-loop process that causes serious problems over a period of years. The term “easily digestible” is within quotes for emphasis. If it is taken to mean “refined”, which is still a bit vague, there is a good amount of epidemiological evidence in support of the CHO. If it is taken to mean simply “easily digestible”, as in potatoes and rice (which is technically a refined food, but a rather benign one), there is a lot of evidence against it. Even from an unbiased (hopefully) look at county-level data in the China Study.

Another hypothesis that has been around for a long time and that has been revived recently, which we could call the “palatability hypothesis”, is a competing hypothesis. It is an interesting and intriguing hypothesis, at least at first glance. There seems to be some truth to this hypothesis. The idea here is that we have not evolved mechanisms to deal with highly palatable foods, and thus end up overeating them.  Therefore we should go in the opposite direction, and place emphasis on foods that are not very palatable to reach our optimal weight. You might think that to test this hypothesis it would be enough to find out if this diet works: “Eat something … if it tastes good, spit it out!”

But it is not so simple. To test this palatability hypothesis one could try to measure the palatability of foods, and see if it is correlated with consumption. The problem is that the formulations I have seen of the palatability hypothesis treat the palatability construct as static, when in fact it is dynamic – very dynamic. The perception of the reward associated with a specific food changes depending on a number of factors.

For example, we cannot assign a palatability score to a food without considering the particular state in which the individual who eats the food is. That state is defined by a number of factors, including physiological and psychological ones, which vary a lot across individuals and even across different points in time for the same individual. For someone who is hungry after a 20 h fast, for instance, the perceived reward associated with a food will go up significantly compared to the same person in the fed state.

Regarding the CHO, it seems very clear that refined carbohydrate-rich foods in general, particularly the highly modified ones, disrupt normal biological mechanisms that regulate hunger. Perceived food reward, or palatability, is a function of hunger. Abnormal glucose and insulin responses appear to be at the core of this phenomenon. There are undoubtedly many other factors at play as well. But, as you can see, there is a major overlap between the CHO and the palatability hypothesis. Refined carbohydrate-rich foods generally have higher palatability than natural foods in general. Humans are good engineers.

One meme that seems to be forming recently on the Internetz is that the CHO is incompatible with data from healthy isolated groups that consume a lot of carbohydrates, which are sometimes presented as alternative models of life in the Paleolithic. But in fact among influential proponents of the CHO are the intellectual founders of the Paleolithic dieting movement. Including folks who studied native diets high in carbohydrates, and found their users to be very healthy (e.g., the Kitavans). One thing that these intellectual founders did though was to clearly frame the CHO in terms of refined carbohydrate-rich foods.

Natural carbohydrate-rich foods are clearly distinguished from refined ones based on one key attribute; not the only one, but a very important one nonetheless. That attribute is their glycemic load (GL). I am using the term “natural” here as roughly synonymous with “unrefined” or “whole”. Although they are often confused, the GL is not the same as the glycemic index (GI). The GI is a measure of the effect of carbohydrate intake on blood sugar levels. Glucose is the reference; it has a GI of 100.

The GL provides a better way of predicting total blood sugar response, in terms of “area under the curve”, based on both the type and quantity of carbohydrate in a specific food. Area under the curve is ultimately what really matters; a pointed but brief spike may not have much of a metabolic effect. Insulin response is highly correlated with blood sugar response in terms of area under the curve. The GL is calculated through the following formula:

GL = (GI x the amount of available carbohydrate in grams) / 100

The GL of a food is also dynamic, but its range of variation is small enough in normoglycemic individuals so that it can be treated as a relatively static number. (Still, the reference are normoglycemic individuals.) One of the main differences between refined and natural carbohydrate-rich foods is the much higher GL of industrial carbohydrate-rich foods, and this is not affected by slight variations in GL and GI depending on an individual’s state. The table below illustrates this difference.

Looking back at the environment of our evolutionary adaptation (EEA), which was not static either, this situation becomes analogous to that of vitamin D deficiency today. A few minutes of sun exposure stimulate the production of 10,000 IU of vitamin D, whereas food fortification in the standard American diet normally provides less than 500 IU. The difference is large. So is the difference in GL of natural and refined carbohydrate-rich foods.

And what are the immediate consequences of that difference in GL values? They are abnormally elevated blood sugar and insulin levels after meals containing refined carbohydrate-rich foods. (Incidentally, the GL  happens to be relatively low for the rice preparations consumed by Asian populations who seem to do well on rice-based diets.)  Abnormal levels of other hormones, in a chronic fashion, come later, after many years consuming those foods. These hormones include adiponectin, leptin, and tumor necrosis factor. The authors of the article from which the table above was taken note that:

Within the past 20 y, substantial evidence has accumulated showing that long term consumption of high glycemic load carbohydrates can adversely affect metabolism and health. Specifically, chronic hyperglycemia and hyperinsulinemia induced by high glycemic load carbohydrates may elicit a number of hormonal and physiologic changes that promote insulin resistance. Chronic hyperinsulinemia represents the primary metabolic defect in the metabolic syndrome.

Who are the authors of this article? They are Loren Cordain, S. Boyd Eaton, Anthony Sebastian, Neil Mann, Staffan Lindeberg, Bruce A. Watkins, James H O’Keefe, and Janette Brand-Miller. The paper is titled “Origins and evolution of the Western diet: Health implications for the 21st century”. A full-text PDF is available here. For most of these authors, this article is their most widely cited publication so far, and it is piling up citations as I write. This means that not only members of the general public have been reading it, but that professional researchers have been reading it as well, and citing it in their own research publications.

In summary, the CHO and the palatability hypothesis overlap, and the overlap is not trivial. But the palatability hypothesis is more difficult to test. As Karl Popper noted, a good hypothesis is a testable hypothesis. Eating natural foods will make an enormous difference for the better in your health if you are coming from the standard American diet, and you can justify this statement based on the CHO, the palatability hypothesis, or even a few others – e.g., a nutrient density hypothesis, which would be closer to Weston Price's views. Even if you eat only plant-based natural foods, which I cannot fully recommend based on data I’ve reviewed on this blog, you will be better off.

There is no doubt that abnormally elevated insulin is associated with body fat accumulation

For as long as diets existed there have been influential proponents, or believers, who at some point had what they thought were epiphanies. From that point forward, they disavowed the diets that they formally endorsed. Low carbohydrate dieting seems to be in this situation now. Among other things, it has been recently “discovered” that the idea that insulin drives fat into body fat cells is “wrong”.

Based on some of the comments I have been receiving lately, apparently a few readers think that I am one of those “enlightened”. If you are interested in what I have been eating, for quite some time now, just click on the link at the top of this blog that refers to my transformation. It is essentially high in all macronutrients on days that I exercise, and low in carbohydrates and calories on days that I don’t. It is a cyclic approach that works for me; calorie surpluses on some days and calorie deficits on other days.

But let me set the record straight regarding what I think: there is no doubt that insulin is associated with body fat accumulation. I was told that an influential health blogger (whom I respect a lot) denied this recently, going to the extreme of saying that no professional metabolism or endocrinology researcher believes in it, but I couldn’t find any evidence of that statement. It is not hard at all to find professional metabolism and endocrinology researchers who have asserted that insulin is associated with body fat accumulation, based on very reliable evidence. Actually, this is Biochemistry 101.

What I think is truly unclear is whether insulin spikes associated with carbohydrate-rich foods in general are the cause of obesity. This idea is, indeed, probably wrong given the evidence we have from various human populations whose members consume plenty of non-industrialized carbohydrate-rich foods. On a related note, I particularly disagree with the notion that the pancreas gets tired over time due to having to secrete insulin in bursts, which seems to also be one of the foundations on which many low carbohydrate diet varieties rest.

As with almost everything related to health, the role of insulin in body fat gain is complex, and part of that complexity is due to the nonlinear relationship between body fat gain and postprandial insulin release. Industrial carbohydrate-rich foods have a much higher glycemic load than natural carbohydrate-rich foods, even though their glycemic index may be the same in some cases. In other words, the quantity of easily digestible carbohydrates per gram is much higher in industrial carbohydrate-rich foods.

In normoglycemic folks, this leads to an abnormally elevated insulin response, among other hormonal responses. For example, circulating growth hormone, which promotes body fat loss, is inversely correlated with circulating insulin. Insulin drives fat, typically from dietary sources of fat, into adipocytes. That fat may also come from excess carbohydrates, packaged into VLDL particles.

Under normal circumstances, that would be fine, since our body is designed to store fat and release it as needed. But the abnormal insulin response elicited by industrial carbohydrate-rich foods, together with other hormonal responses, leads to a little more body fat accumulation, and for longer, than it should. And I’m talking here about people without any metabolic damage. Saturated and monounsaturated fats are healthy when eaten, but when they are stored as excess body fat, they become pro-inflammatory.

Body fat is like an organ, secreting many hormones into the bloodstream, several of which are pro-inflammatory. One of those pro-inflammatory hormones, which I believe is closely linked with many diseases of civilization, is tumor necrosis factor. (The acronym is now TNF. Apparently the “-alpha” after its name and acronym has been dropped recently.) Dietary fat, particularly saturated fat, seems to be anti-inflammatory. In other words, body fat accumulation is the problem. You only need 30 g/d of excess body fat accumulation to gain around 24 lbs of fat per year. Over three years, that will add up to over 70 lbs of body fat.

In my view, ultimately it is excess inflammation (which is, in essence, a vascular response) that is at the source of most of the diseases of civilization.

That is where the nonlinearity comes in. Insulin is healthy up to a point. Beyond that, it starts causing health problems, over time. And one of the main mechanisms by which it does so is via excessive body fat accumulation, with different damage threshold levels for different people. Insulin may decrease appetite as it goes up, but it increases it if goes down too much. If it goes up abnormally, typically it will go down too much. As it reaches a trough it induces hypoglycemia, even if mildly.

Take a look at the graph below, from this post showing the glucose variations in normoglycemic individuals. There is a lot of variation among different individuals, but it is clear that the magnitude of the hypoglycemic dips is inversely correlated with the magnitude of the glucose spikes. That inverse correlation is due primarily to the effect of insulin. Under normal circumstances, a decrease in circulating insulin would promote an increase in free fatty acids in circulation, which would normally have a suppressing effect on hunger in the hours after a meal. But industrial carbohydrate-rich foods lead to increases and decreases in glucose and insulin that are too steep, causing the opposite effect.

You may ask: why do you keep talking about industrial carbohydrate-rich foods? Why not talk about industrial protein- or fat-rich foods as well? The reason is that the food industry has not been very successful at producing industrial protein- or fat-rich foods that are palatable without adding a lot of carbohydrate to them.

More often than not they need enough carbohydrate added in the form of sugar to become truly addictive.

Subcutaneous versus visceral fat: How to tell the difference?

The photos below, from Wikipedia, show two patterns of abdominal fat deposition. The one on the left is predominantly of subcutaneous abdominal fat deposition. The one on the right is an example of visceral abdominal fat deposition, around internal organs, together with a significant amount of subcutaneous fat deposition as well.

Body fat is not an inert mass used only to store energy. Body fat can be seen as a “distributed organ”, as it secretes a number of hormones into the bloodstream. For example, it secretes leptin, which regulates hunger. It secretes adiponectin, which has many health-promoting properties. It also secretes tumor necrosis factor-alpha (more recently referred to as simply “tumor necrosis factor” in the medical literature), which promotes inflammation. Inflammation is necessary to repair damaged tissue and deal with pathogens, but too much of it does more harm than good.

How does one differentiate subcutaneous from visceral abdominal fat?

Subcutaneous abdominal fat shifts position more easily as one’s body moves. When one is standing, subcutaneous fat often tends to fold around the navel, creating a “mouth” shape. Subcutaneous fat is easier to hold in one’s hand, as shown on the left photo above. Because subcutaneous fat tends to “shift” more easily as one changes the position of the body, if you measure your waist circumference lying down and standing up, and the difference is large (a one-inch difference can be considered large), you probably have a significant amount of subcutaneous fat.

Waist circumference is a variable that reflects individual changes in body fat percentage fairly well. This is especially true as one becomes lean (e.g., around 14-17 percent or less of body fat for men, and 21-24 for women), because as that happens abdominal fat contributes to an increasingly higher proportion of total body fat. For people who are lean, a 1-inch reduction in waist circumference will frequently translate into a 2-3 percent reduction in body fat percentage. Having said that, waist circumference comparisons between individuals are often misleading. Waist-to-fat ratios tend to vary a lot among different individuals (like almost any trait). This means that someone with a 34-inch waist (measured at the navel) may have a lower body fat percentage than someone with a 33-inch waist.

Subcutaneous abdominal fat is hard to mobilize; that is, it is hard to burn through diet and exercise. This is why it is often called the “stubborn” abdominal fat. One reason for the difficulty in mobilizing subcutaneous abdominal fat is that the network of blood vessels is not as dense in the area where this type of fat occurs, as it is with visceral fat. Another reason, which is related to degree of vascularization, is that subcutaneous fat is farther away from the portal vein than visceral fat. As such, it has to travel a longer distance to reach the main “highway” that will take it to other tissues (e.g., muscle) for use as energy.

In terms of health, excess subcutaneous fat is not nearly as detrimental as excess visceral fat. Excess visceral fat typically happens together with excess subcutaneous fat; but not necessarily the other way around. For instance, sumo wrestlers frequently have excess subcutaneous fat, but little or no visceral fat. The more health-detrimental effect of excess visceral fat is probably related to its proximity to the portal vein, which amplifies the negative health effects of excessive pro-inflammatory hormone secretion. Those hormones reach a major transport “highway” rather quickly.

Even though excess subcutaneous body fat is more benign than excess visceral fat, excess body fat of any kind is unlikely to be health-promoting. From an evolutionary perspective, excess body fat impaired agile movement and decreased circulating adiponectin levels; the latter leading to a host of negative health effects. In modern humans, negative health effects may be much less pronounced with subcutaneous than visceral fat, but they will still occur.

Based on studies of isolated hunger-gatherers, it is reasonable to estimate “natural” body fat levels among our Stone Age ancestors, and thus optimal body fat levels in modern humans, to be around 6-13 percent in men and 14–20 percent in women.

If you think that being overweight probably protected some of our Stone Age ancestors during times of famine, here is one interesting factoid to consider. It will take over a month for a man weighing 150 lbs and with 10 percent body fat to die from starvation, and death will not be typically caused by too little body fat being left for use as a source of energy. In starvation, normally death will be caused by heart failure, as the body slowly breaks down muscle tissue (including heart muscle) to maintain blood glucose levels.

References:

Arner, P. (2005). Site differences in human subcutaneous adipose tissue metabolism in obesity. Aesthetic Plastic Surgery, 8(1), 13-17.

Brooks, G.A., Fahey, T.D., & Baldwin, K.M. (2005). Exercise physiology: Human bioenergetics and its applications. Boston, MA: McGraw-Hill.

Fleck, S.J., & Kraemer, W.J. (2004). Designing resistance training programs. Champaign, IL: Human Kinetics.

Taubes, G. (2007). Good calories, bad calories: Challenging the conventional wisdom on diet, weight control, and disease. New York, NY: Alfred A. Knopf.

Body mass index and cancer deaths in various US states

Ancel Keys is often heavily criticized for allegedly originating the fat phobia that we see today in the US and other countries, perhaps with good reason. But he has also made many important contributions to the health sciences.

One of them was the index known as body mass index (BMI), calculated based on a person's weight and height. Unlike other measures, such as body fat percentage and body fat mass, BMI is very easy to calculate; divide your weight (kg) by your height (m) squared.

BMI is strongly correlated with body fat percentage, and body fat mass. Very muscular people are exceptions; they may have a high BMI and yet reduced body fat.

Excessive body fat mass leads to chronic inflammation, due in part to elevated circulating levels of pro-inflammatory hormones such as tumor necrosis factor-alpha (cute name eh?).

Chronic inflammation, in turn, leads to increased incidence of cancer.

Thus it should be no surprise that having a BMI above 30 (obesity level) is strongly correlated with cancer death rates; see graph below (click on it to enlarge), from: Florida, 2009 (full reference at the end of this post).

The correlation for the graph above is a high 0.702, calculated as the square-root of the R-squared value shown at the bottom-right. The R-squared is the percentage of explained variance for cancer deaths, meaning that nearly 50 percent of the cancer deaths are "explained", or caused, by the BMI percentages.

One more reason to bring body fat down to healthy levels.

How do you do that? A good way to start is to replace refined carbohydrates and sugars with natural sources of protein and fat in your diet; eggs included, no need to worry about dietary cholesterol.

Reference:

Florida, R. (2009). The geography of obesity. Creative Class, Nov. 25.

Adiponectin and tumor necrosis factor-alpha levels after a high saturated fat meal

This is one of those interesting studies where the authors start with some pre-conceived assumptions and end up concluding something else, some way toward the opposite of what they assumed.

My final interpretation of the study results is a bit different though. It suggests that the results are actually the opposite of what the authors originally assumed.

The authors of the study (Poppitt et al., 2008; full reference at the end of this post) start by stating that since “… dietary fat is associated with increased lipid storage, weight gain, and obesity …” it is important to study the effect of dietary fat intake on the blood levels of certain substances that are associated with lipid disorders, weight gain and obesity.

In short, the authors start from the assumption that dietary fat is bad. By the way, this type of indictment of all fats is not very common these days. Usually saturated fat is the target.

Since dietary fat is assumed to be bad for us, that justifies the authors’ goal of studying the effect of dietary fat on certain hormones associated with bad health, including the body fat-secreted hormones adiponectin and tumor necrosis factor-alpha. Low levels of serum adiponectin, and elevated levels of tumor necrosis factor-alpha, are associated with various health complications.

In the study, a high-fat test meal with approximately 59 g of fat (71% of energy as fat) was given at breakfast on two occasions to 18 healthy and lean men. These men had, on average, 23 years of age, a 31-inch waist, and a body mass index of 22.9. In other words, they were young and fit.

Two fatty meal variations were used, one with a lot more saturated fat than the other. Their ratio of saturated:unsaturated fatty acids was 71:29 for the high saturated fat meal, and 55:45 for the other. The table below provides a more detailed picture of the fat composition of the meals. The authors refer to these meals as instances of “acute intake of dietary lipid”.

Lunch, snack and dinner meals were also served to the participants. Those meals were nearly fat-free, with 1 to 3 g of fat only; apparently to help the participants “recover” from the high fat meal. They included plenty of refined grains (e.g., pasta) and fruit juices. Way to go; give these folks refined carbohydrates and sugars galore to help them recover from the “damage” done by the high fat meal!

Blood samples were collected at 0 (baseline), 1, 3, and 6 h for the measurement of various substances, including the body fat hormones adiponectin and tumor necrosis factor-alpha levels.

The figure below shows the variation in adiponectin levels at several times after the meal. The black circles are for the high saturated fat group, and the white circles for the other group. Adiponectin levels do not really start at the same level for both groups, which makes the graph a bit unclear; to better interpret the graph it may be a good idea to simply ignore the first (white) circle at the zero mark on the vertical axis. Also, no hormone levels were negative, of course; the zero on the vertical axis represents a reference value.

As we can see from the figure above, adiponectin levels go up for both groups after the fatty meal, and end up higher than they started for both groups; more for the high saturated fat than for the low saturated fat group. They are at very similar levels at the 24 h mark, but the levels at 24 h for the high saturated fat group appear to be a lot higher than they were right after the fatty meal. (The start point for the high saturated fat group being the first black circle from the left on the graph.) None of the differences are reported as significant. This is not surprising, given the small sample.

The figure below shows the variation in tumor necrosis factor-alpha levels at several times after the meal. This is an even more interesting one, because it suggests a possible negative effect of the low fat meals.

In terms of tumor necrosis factor-alpha levels, the figure above suggests that both groups end up higher than they started, by about the same amount, which is not very good. (With tumor necrosis factor-alpha, unlike adiponectin, the less you have the better - so to speak, the hormone has important functions.) Again, none of the differences, with the exception of one, are reported as significant. The exception is the tumor necrosis factor-alpha level at 6 h for the low saturated fat group, which is significantly lower. But that difference disappears at the 10 h mark, never to be seen again.

Interestingly, note that tumor necrosis factor-alpha levels go up very clearly after the additional meals, which were low fat meals rich in refined carbohydrate and sugars. The variation in adiponectin is not as clearly associated with the additional meals. The points at which those meals were served are indicated by the arrows at the top of the graph; first arrow from left for lunch, second for a snack, and third arrow for dinner.

The conclusion by the authors of the study was that there is “… no evidence from this study of lean, healthy male subjects that the adipose hormone adiponectin is sensitive to acute intake of dietary lipid or to an increase in fatty acid saturation.” They do acknowledge the reduction in tumor necrosis factor-alpha up until the start of the low fat meals, and say that the “mechanism leading to the decrease in TNF-alpha on the high SFA:USFA treatment in our trial is unknown to us.”

My interpretation of this study is that, at least for young and lean men:

- There is some evidence that dietary saturated fat intake leads to increased levels of circulating adiponectin and decreased levels of tumor necrosis factor-alpha in the first few hours after a meal rich in saturated fat; with plenty of palmitic acid in it, by the way, of which animal fat is a great source. These are desirable and health-promoting hormonal responses.

- These is some evidence that meals high in refined carbohydrates and sugars increase levels of circulating tumor necrosis factor-alpha in the hours following the meals. Elevated levels of tumor necrosis factor-alpha are not good news; something that I guess is implied by the name of the hormone.

- There is some evidence that dietary saturated fat intake leads to an increase in adiponectin levels 24 h after a high fat meal, even when it is followed by low fat meals high in refined carbohydrates and sugars. This suggests a protective effect, which is in line with the hypothesis that adiponectin is not only a health marker by also a health-promoting hormone.

Due to the small sample used, none of the conclusions above is based on statistically significant results. More research is needed in the future, with larger samples. I am not sure it will happen though. This study’s findings were obviously accidental, and saturated fat phobia is still widespread.

Adiponectin is highly correlated with body weight, particularly weight associated with body fat mass. So, if you were able to achieve weight loss through a low carbohydrate diet involving a high consumption of saturated fat, there is absolutely no need to change that based on the results of this study.

Plus, saturated fat has the added benefit that it increases HDL cholesterol, the “good” cholesterol.

Reference:

Poppitt, S.D. et al. (2008). Postprandial response of adiponectin, interleukin-6, tumor necrosis factor-α, and C-reactive protein to a high-fat dietary load. Nutrition, 24(4), 322-329.