The folly of the mean – Why do they differ so?

A few years ago I did a small study where we combined a ketogenic diet with resistance exercise [1]. After 10 weeks the 8 women in the diet group experienced a mean weight loss of 5,6kg. DEXA-scanning (Dual Energy X-ray Absorptiometry) showed that the mean fat mass loss was 5,6kg and that the fat free mass was unchanged. But, it would be wrong of me to say that this strategy conserves lean body mass, because the truth of the matter is that it all depends. Because 4 of the women in the diet group increased lean body mass, while 4 lost some despite the 10 weeks of resistance exercise. The individual results from the study are illustrated below.

As you can see, there are large individual variations. But individual variations are often not presented in scientific articles. Instead we are given results as means, and the means do not tell us what happens at the individual level. Of course, results also commonly include a measure of variation such as standard deviation (SD) or confidence interval (CI), but that still does not tell us what the true variation was and exactly how the different individuals responded. And this is the trouble with presenting study results as means; there are always individual variations and the funny thing is that it is usually these very variations we really want to understand.

Exercise studies are good examples of how misleading averages and means can be. Generally speaking we have to say that exercise at best is a very poor weight loss strategy. The reason is that exercise studies rarely yield weight loss of any significance. Even if we didn’t have exercise studies we would still know that exercise does not make us lean, because we all know that our body weight does not change with changes in exercise volume. My body weight is practically constant, no matter how much or how little I exercise, and most people seem to be like me. Of course, if we do resistance or strength training we will build muscles, and often gain weight, but there is just no obvious link between energy expended during exercise and concomitant weight loss.

However, if we look closer at exercise studies it may seem that it is possible to lose weight from exercising, but that it doesn’t happen to all of us. Take for example a study lead by Neil A. King at Queensland University of Technology [2]. Fifty-eight overweight and obese men and women completed 12 weeks of supervised exercise in a laboratory. The exercise sessions were designed to expend 2500 kcal/week and involved exercising at 70% of each individual’s maximum heart rate for 5 days a week. The aim of the study was to assess the effects of 12 weeks of mandatory exercise on appetite control.

After the 12 weeks of exercise the mean weight loss was 3,6kg. Now, we cannot conclude that this loss was caused by the exercise itself. Usually when people are recruited to studies such as these, they tend to change their behavior towards a more healthy lifestyle. Unless we can control for eating behavior, stress, alcohol intake or any other factor known to influence weight loss we cannot say that exercise is a causal factor. Anyway these are the individual results from the study:

About 22 of the participants, or roughly half, lost more weight than the mean. And 10 participants gained weight. So the really interesting question is; what is the cause of the difference in the individual responses? Although the mean weight loss was small and likely affected by non-exercise factors the above results do not exclude the possibility that some of these people lost weight simply by exercising and without significant changes in other lifestyle factors. In fact the very statement that I usually make, that exercise does not cause significant weight loss, is based on results given as means. But what if there’s always responders and non-responders equaling each other out?

Still, we need to remember that if exercise by itself caused some of the people in the King study to lose weight, it is more likely because of factors such as reduced insulin resistance, reduced glycogen stores or improved fat metabolism, than because of increased energy expenditure.

Diet studies are also hard to interpret based on results presented as means. The Look AHEAD (Action for Health in Diabetes) [3,4] documented the effect of a traditional lifestyle intervention on overweight and type 2 diabetics. More than 5000 overweight men and women were randomized into an intensive lifestyle intervention group (ILI) or a control group that only received information and support. The study lasted 4 years (this is a gigantic study and one of very few randomized controlled trials of this size) and the goal of the ILI group was to achieve a 7% weight loss and to maintain the loss throughout the 4 years. The participants in the ILI group were asked to eat 1200-1800 kcal per day of which less than 30% was to come from fat. In addition the goal was to exercise 175 minutes per week, and they participated in regular group and individual counseling. All in all, the researchers did all they could to make sure the participants lost weight.

After 4 years of dieting the mean weight loss in the ILI group was 4,9kg or 4,7% of baseline body weight. The below graph illustrates that many achieved a great weight loss after 1 year, but as the study progressed, the participants gradually regained their lost weight, and if the study had lasted any longer the mean weight loss would probably have been even smaller.

But once again the mean results don’t really tell us much. Wadden and coworkers reveals that only 74% of the participants lost weight and that the remaining 26% gained weight. Only 46% lost more than 5% of initial body weight (which was 95kg in women and 109 in men, so roughly 5kg), and only 35% lost more than 7% of initial weight. With so much effort in so heavy people these results are a strong indication that traditional dieting simply does not work. But once again we need to ask what the difference between the participants who lost a lot of weight and those who lost little was. This is the really important question, and a question that is asked to rarely. Those who continue to cling to the old dogma might say that those who lost the most weight probably were those who followed the given advice the most and that those who lost little did not do as told.

And they might be right. But we need to know. We can be pretty sure that many of the participants did not do as told and that many did more. That’s just how people are and had this been a smaller and more tightly controlled study, anyone who did more or less than asked would have been excluded from the analysis. But there might also be large individual variations in response to the same intervention, and once again it is these variations – the reason we respond differently to the same stimuli – we truly want to understand.

One way we sometimes try to shed light on some of the individual variations is to do correlation analyses. For example, if in the above study, there was a strong correlation between protein intake and weight loss, then differences in protein intake was probably an important reason for the individual variations. But the ting is that we rarely find such strong correlations in weight loss studies and so we are left in the dark when it comes to understanding what biological mechanisms are hidden in the mean.

Even though studies fail to elucidate the reason for individual variations, I would still like the individual results to be presented more often, because this acts as a strong reminder that we cannot truly understand the world if we cannot understand why we differ so.

References

1. Jabekk PT, Moe IA, Meen HD, Tomten SE, Hostmark AT: Resistance training in overweight women on a ketogenic diet conserved lean body mass while reducing body fat. Nutr Metab (Lond) 2010, 7: 17.

2. King NA, Caudwell PP, Hopkins M, Stubbs JR, Naslund E, Blundell JE: Dual-process action of exercise on appetite control: increase in orexigenic drive but improvement in meal-induced satiety. Am J Clin Nutr 2009, 90: 921-927.

3. Wing RR: Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes mellitus: four-year results of the Look AHEAD trial. Arch Intern Med 2010, 170: 1566-1575.

4. Wadden TA, Neiberg RH, Wing RR, Clark JM, Delahanty LM, Hill JO, Krakoff J, Otto A, Ryan DH, Vitolins MZ: Four-year weight losses in the Look AHEAD study: factors associated with long-term success. Obesity (Silver Spring) 2011, 19: 1987-1998.

Overfeeding – Calories count, but don’t bother counting them

«The upper two sets of figures show Mr. A. Levanzin of Malta, Dr. Benedict’s celebrated subject, before and at the completion of his fast. ‘About two and a half years ago, while I was over-eating, obese, neurasthenic, pessimistic and with a shattered nervous system, I chanced to read. . . an article about fasting. It was a flash of light that struck me vividly. It indicated to rue the right path to health and happiness. . . Today is the 31st and last day of it. . . I am feeling very well, very uplifted, and. . . do not feel yet any trace of hunger. I did not feel the least uncomfortable sensation except the bad taste of my coated tongue. I hope that a great benefit to my health shall accrue from it’. The lower two sets of figures show Mr. Winston Morris, one of the subjects of the University of Vermont study of experimental obesity before and after gain in weight. For the initial 75 days his average calorie intake was 6,700 (5,400 kcal/70 kg body wt) and for the following 60 days 10,200 kcal (8,300 kcal/70 kg). During both periods the composition of the diet by weight was approximately: protein, 17%, fat, 28% and carbohydrate, 52%. In contrast to Mr. Levanzin, he does not recommend his regimen as the right path to health and happiness.» [1]

Even among individuals who appear to combine dietary and lifestyle habits believed to promote the development of obesity, weight gain over the years is much slower than one would expect considering the pleasure associated with eating, the loose regulation of daily food intake, and the great tolerance for excessive intakes. [2]

It is not strange that the matter of overfeeding has lodged itself at the core of many nutrition debates. Overfeeding address the very question of what makes us fat and how we fatten.

But overfeeding studies do not fit nicely into the «calories inn – calories out» dogma. In fact, the finding that overfeeding does not generally cause long term overweight, is used to argue that it is what we eat, as opposed to how much, that determines how much weight we gain. The logic is that what we eat affects how much we eat, how much we burn and how we feel and so on. If different types of food affect how energetic we feel, as we know they can, and this effect is independent of energy content, then calories do not seem worth counting.

Because changes in RMR and thermic effect of food were small, the resistance to weight and fat gain with overfeeding was attributed to changes in spontaneous physical activity… [3]

The whole subject of overfeeding is extremely interesting, but it requires some careful tongue in cheek navigation through a minefield of twisted logic and rhetoric traps. For example, is overfeeding even relevant to the normal physiology of overweight and obesity? And even if subjects in studies are not «force fed» but rather make a small effort to overeat, can it tell us what causes obesity? And if we accept that dietary composition matter in a normal diet, then composition matters in overfeeding as well. Do we then know what component of the diet is responsible for weight gain?

Energy
Body weight is definitely regulated, and as it seems, quite tightly so. Most people are relatively weight stable most of the time, despite large variations in day to day energy expenditure and energy intake. An age-related drift in body weight has been estimated to about half a pound per year. David Weigle calculates that if the cost of depositing this ½ pound is 1560 kcal and that the caloric intake of an average individual is approximately 900,000 kcal per year, this weight gain represents an excess energy consumption of less than 0.2% [4]. This number is simply too small to conclude that body weight is something we are in control of. Counting calories just does not make any sense, because our body is in charge, not our mind.

Individuals who gain the less body weight during overfeeding are those who experience a greater increase in total energy expenditure. [5]

But the fact that body weight is tightly regulated does not mean it is unchangeable. We know it’s not. Losing weight can be quite easy. This means that the mechanisms that regulate body weight (or rather fatness) are the very mechanisms we alter when we lose weight and so those mechanisms are easily manipulated.

Gaining weight, at least in a speed equaling the speed at which we can lose weight, is close to impossible. The main reason is that overfeeding makes us full. A near complete suppression of appetite has been observed in both human and animal subjects [1,4,6,7]. For example, in one study, normal weight men were overfed by 1000 kcal per day for 21 days. This produced a mean fat gain of 79 grams per day. The voluntary caloric intake over the first 10 days after the end of the overfeeding, was reduced by 476 kcal per day relative to baseline.

In one study where rats were overfed to achieve twice the body weight of control animals, two obese rats were kept at a temperature of 5 degrees Celsius (which is a temperature that requires the rats to burn more energy for heat production), and yet did not consume food for 11 and 16 days. The animals started eating again once they were down to their original weight.

This graph shows the feeding and weight response in three tube overfed macaques. Overfeeding is during the solid bar. Food intake goes down during overfeeding and increases once the animals approach baseline weight

Extra energy ingested during overfeeding does not simply become stored. That is, some does. But one common consequence of overfeeding is increased energy expenditure. In a study by Leibel and coworkers, both obese and lean subjects were overfed and kept at 10% increased bodyweight compared to normal. This caused an increase in energy expenditure of 9kcal per kilo fat free mass in the lean and 8kcal in the obese [8].

Hence, the hypothesis that higher food intake may be the cause rather than the consequence of higher 24-h carbohydrate oxidation rates cannot be positively ruled out. [9]

Because not all extra energy is stored, weight changes in response to overfeeding are generally small. Still, large individual variation is common [10-12] and this variation is important to consider. There are many proposed mechanisms for the individual variation, such as different mitochondrial efficiency, compliance to diet and differences in digestion. Of course, the amount of overfeeding is often calculated based on self-reported food intake prior to overfeeding. This may also be a source of error and underreporting may explain some of the individual differences. People with a family history of diabetes experience larger detrimental effects from overfeeding than people without [13], which illustrates how our genes determine our potential for disease and weight gain.

One of the more famous of overfeeding studies, which resulted in a pile of articles, was conducted by Claude Bouchard in 1990 [14]. To see if there really were differences in how individuals responded to overfeeding and to see if this difference was due to different genotypes, he used 12 pairs of monozygotic twins. They were overfed by 1000 kcal, six days a week for 84 days. On average this resulted in 8.1kg (2,7kg of which was lean body mass) gained weight. But the range was from 4,3kg to 13,3kg. The twins gained the same amount of weight, in the same way, and thus showed the importance of genes. But the large variation between twin pairs in response to overfeeding is interesting.

The Bouchard study also found that the twins with the most type 1 muscle fibers, the slow fat burning type, gained the least fat. It might seem that skeletal muscle oxidative capacity in part predicts weight gain [15]. 4 months after the overfeeding, the twins had lost 7 of the 8 kilos gained, but at a 5 year follow-up mean weight had increased by 5kg. This was however likely the result of the younger twins (youngest pairs were 19y) adding some normal late pubertal weight.

And, although Bouchard and coworkers seemed somewhat surprised by it, the study found that there was no correlation between the total energy ingested and weight gained.

No current treatment for obesity reliably sustains weight loss, perhaps because compensatory metabolic processes resist the maintenance of the altered body weight. [8]

Diet composition
In overfeeding, as in normal feeding, results depend on the type of nutrient consumed. Overfeeding on carbohydrate affects the body differently from overfeeding on fat and different fats and carbohydrates will, theoretically, affect us differently.

One of the most extreme overfeeding rituals is that of the Cameroonian Guru Walla. In the Guru Walla, young men consume a diet made of red sorghum and cow milk (makes up over 95% of calories). The young men isolate themselves in different houses with a female attendant devoted exclusively to the preparation of Guru Walla meals. The diet and exclusion is supposed to lead to a certain level of purity. The men eat every 3 hour for 60 days, during which time body-weight can increase by an average of 17kg [16]. The ritual food is truly a high carb diet, with 70% CHO, 15% fat and 15% protein. Despite their large weight gain, the excess weight is lost after the ritual ends.

Patrick Pasquet writes about the long term effects of the Guru Walla: «Thus, 2.5 y after cessation of fattening there was a spontaneous return to initial body weight and body composition of the overfed subjects.» Pasquet almost had his nice stats ruined by one Cameroonian getting married and not losing as much weight as the other subjects: «Eight of them did not change daily life patterns and food habits in relation to the pre overfeeding period. One subject got married in the meantime; interestingly, for this subject some persistent overweight was left (6.7 of a 19.7kg gain).» [17] Marriage is of course a common accelerator of weight gain.

In a crossover study from 1995, led by Tracy Horton [18], lean and obese subjects were overfed on either fat or carbohydrate for 2 weeks. All subjects gained a similar amount of weight on both overfeeding strategies, and post overfeeding body weight gradually came back to baseline in both groups. But measurements showed that energy expenditure was increased more with carbohydrates than fat. This is likely because the body tries to burn off as much glucose as possible to keep from getting dangerously high blood glucose, while increased fat intake is not as dangerous, and there is thus less need for increasing oxidation of it. There were also indications of more energy being stored with fat overfeeding than with carb overfeeding. Lean and obese subjects responded similarly to overfeeding, although not surprisingly, the obese had a higher proportional oxidization of carbohydrate on both strategies.

The obese are commonly recognized by the fact that they are carbohydrate burners rather than fat burners [19]. Although the researchers does not mention it, table 3 shows that carbohydrate overfeeding caused greatly increased fasting insulin concentration in both lean and obese subjects. But fat overfeeding halved insulin in the lean and doubled it in the obese. It is also strange that the lean subjects had much higher insulin before fat overfeeding than before carbohydrate overfeeding. As this was a crossover study the results should be interpreted with caution.

Danish researcher Ole Lammert, and colleagues, also compared carbohydrate and fat overfeeding [12]. No significant difference in carbohydrate (78% carbohydrates, 11% protein, 11% fat) and fat 58% fat, 11% protein, 31% carbohydrate) were found after 21 days overfeeding. Both groups gained 1,5kg of weight.

When we eat carbohydrates, much can be stored in muscles and liver as glycogen, but as soon as these stores are saturated, carbohydrate oxidation increases and de novo lipogenesis (conversion of carbohydrates to fat) increases [20]. In one study, extreme carbohydrate overfeeding caused subjects to burn 400g of carbs per day, without exercising. And resting energy expenditure increased by 35%. Fasting glucose levels did not increase, which shows the body’s great ability (in lean subjects) to convert glucose to fat so as to keep blood glucose low. In addition, the study showed that going from a low fat diet to eating a high carb (86%) overfeeding diet, can bring your triglycerides from 0,8 mmol/l to a whopping 8,6 mmol/l, which is an astonishing feat.

Body weight change in both lean and obese subjects in the Horton study. As usual, once overfeeding is finished, food intake and body weight goes down. You could theorize that the reduction in body weight post overfeeding is caused by the subjects wanting to lose the newly gained weight. But as the reaction is the same in many other animal species, it is likely a natural physiologic response.

Body composition
It is interesting that overfeeding also can cause quite an increase in lean body mass, sometimes half the weight gained [11,12]. Only 64-75% of the 17 kg weight gained during the Guru Walla is fat mass [16]. In the Vermont prison overfeeding study, inmates increased their body weight by 16,2kg of which 10.4kg was determined to be fat. This does not mean that overeating is a good or way to build muscles, but there is much indication that if you want optimal muscle growth, you shouldn’t hold back on food intake.

Weight gained as fat can be either hyperplasia (new cells) or hypertrophy (increased cell size). A 2010 study found that 8 weeks overfeeding in 28 healthy normal weight adults led to an obvious increase in fat cell size, but also an increase in fat cell number [21].

Conclusion
Weight gain from overfeeding is not large. In fact, we could say that overfeeding works about as well at increasing body weight as energy restriction works at decreasing it. People do gain weight by voluntary overfeeding themselves or being force fed, but as soon as subjects return to their regular diet, the newly gained weight is quickly lost. This finding is one important reason the set point hypothesis emerged. What part of the diet is mostly responsible for the weight gain is difficult to say, but it is not likely easy to overeat on a low carbohydrate diet. Overfeeding is not healthy, and one important reason for the observed increased energy expenditure, is likely the body desperately trying to keep blood glucose down.

Overfeeding pushes the body’s equilibrium towards increased fat storage, but in animals and humans alike, once normal feeding commences, the equilibrium is once again restored at the original body weight. It is also clear that although most of the surplus energy is stored, quite a large part is used to increase energy expenditure, and so it is difficult to calculate weight gain or fat gain from calories consumed as food. In other words, more energy (calories) increases body weight, but the processes of energy storage and expenditure are too complex for it to make any sense to count calories.

References

1. Sims EA, Danforth E Jr, Horton ES, Bray GA, Glennon JA, Salans LB: Endocrine and metabolic effects of experimental obesity in man. Recent Prog Horm Res 1973, 29: 457-496.

2. Flatt JP: Issues and misconceptions about obesity. Obesity (Silver Spring) 2011, 19: 676-686.

3. Galgani J, Ravussin E: Energy metabolism, fuel selection and body weight regulation. Int J Obes (Lond) 2008, 32 Suppl 7: S109-S119.

4. Weigle DS: Appetite and the regulation of body composition. FASEB J 1994, 8: 302-310.

5. Tappy L: Metabolic consequences of overfeeding in humans. Curr Opin Clin Nutr Metab Care 2004, 7: 623-628.

6. Roberts SB, Young VR, Fuss P, Fiatarone MA, Richard B, Rasmussen H, Wagner D, Joseph L, Holehouse E, Evans WJ: Energy expenditure and subsequent nutrient intakes in overfed young men. Am J Physiol 1990, 259: R461-R469.

7. Bessesen DH, Bull S, Cornier MA: Trafficking of dietary fat and resistance to obesity. Physiol Behav 2008, 94: 681-688.

8. Leibel RL, Rosenbaum M, Hirsch J: Changes in energy expenditure resulting from altered body weight. N Engl J Med 1995, 332: 621-628.

9. Pannacciulli N, Salbe AD, Ortega E, Venti CA, Bogardus C, Krakoff J: The 24-h carbohydrate oxidation rate in a human respiratory chamber predicts ad libitum food intake. Am J Clin Nutr 2007, 86: 625-632.

10. Stock MJ: Gluttony and thermogenesis revisited. Int J Obes Relat Metab Disord 1999, 23: 1105-1117.

11. Forbes GB, Brown MR, Welle SL, Lipinski BA: Deliberate overfeeding in women and men: energy cost and composition of the weight gain. Br J Nutr 1986, 56: 1-9.

12. Lammert O, Grunnet N, Faber P, Bjornsbo KS, Dich J, Larsen LO, Neese RA, Hellerstein MK, Quistorff B: Effects of isoenergetic overfeeding of either carbohydrate or fat in young men. Br J Nutr 2000, 84: 233-245.

13. Samocha-Bonet D, Campbell LV, Viardot A, Freund J, Tam CS, Greenfield JR, Heilbronn LK: A family history of type 2 diabetes increases risk factors associated with overfeeding. Diabetologia 2010, 53: 1700-1708.

14. Bouchard C, Tremblay A, Despres JP, Nadeau A, Lupien PJ, Theriault G, Dussault J, Moorjani S, Pinault S, Fournier G: The response to long-term overfeeding in identical twins. N Engl J Med 1990, 322: 1477-1482.

15. Sun G, Ukkola O, Rankinen T, Joanisse DR, Bouchard C: Skeletal muscle characteristics predict body fat gain in response to overfeeding in never-obese young men. Metabolism 2002, 51: 451-456.

16. Pasquet P, Brigant L, Froment A, Koppert GA, Bard D, de G, I, Apfelbaum M: Massive overfeeding and energy balance in men: the Guru Walla model. Am J Clin Nutr 1992, 56: 483-490.

17. Pasquet P, Apfelbaum M: Recovery of initial body weight and composition after long-term massive overfeeding in men. Am J Clin Nutr 1994, 60: 861-863.

18. Horton TJ, Drougas H, Brachey A, Reed GW, Peters JC, Hill JO: Fat and carbohydrate overfeeding in humans: different effects on energy storage. Am J Clin Nutr 1995, 62: 19-29.

19. Zurlo F, Lillioja S, Esposito-Del Puente A, Nyomba BL, Raz I, Saad MF, Swinburn BA, Knowler WC, Bogardus C, Ravussin E: Low ratio of fat to carbohydrate oxidation as predictor of weight gain: study of 24-h RQ. Am J Physiol 1990, 259: E650-E657.

20. Acheson KJ, Schutz Y, Bessard T, Anantharaman K, Flatt JP, Jequier E: Glycogen storage capacity and de novo lipogenesis during massive carbohydrate overfeeding in man. Am J Clin Nutr 1988, 48: 240-247.

21. Tchoukalova YD, Votruba SB, Tchkonia T, Giorgadze N, Kirkland JL, Jensen MD: Regional differences in cellular mechanisms of adipose tissue gain with overfeeding. Proc Natl Acad Sci U S A 2010, 107: 18226-18231.

Fat people are liars

Obviously! Obesity is a remarkably simple problem to solve. Eat less and move more. When energy expenditure exceeds energy intake, you lose weight. Many people claim to have tried eating less and exercising more and claim that it does not work. As this would be a violation of the laws of thermodynamics it is quite unlikely.

Not only do overweight people claim to break the fundamental laws of nature they also constantly lie about how much they actually eat.

Elaine Prewitt and coworkers examined the effect of a 37%-fat (HF) diet for 4 weeks followed by a 20%-fat diet (LF) for 20 weeks on body composition and weight in 18 premenopausal women with body mass index (BMI) of 18-44. They found that

Despite adjustments in energy intake to maintain weight throughout the study, by the end of the LF period, energy intake had increased significantly in comparison with the HF diet (119% of the HF intake, P < 0.0001). 

The authors knew what kind of people they were dealing with and wrote

We have no means of assessing the degree of food waste by subjects when meals were taken out but there was no reason to attribute the magnitude of energy increase we observed to overreporting of dietary infractions. By contrast, one would expect the subjects, particularly obese subjects, to underreport extra foods eaten.

W. Daniel Schmidt and coworkers exercised overweight women. All study groups were put on an energy restricted diet. The control group only dieted without changing exercise routines, but somehow they didn’t lose any weight. The authors write:

The fact that the control subjects in our study did not lose weight is perplexing and conflicts with other research that generally supports weight loss with caloric restriction [17, 18]. One explanation may be that subjects simply underreported the amount of calories consumed, thus making this an issue of noncompliance. 

Not only are fat people liars, but fat people on low fat diets are the worst. James Krieger, everyone’s favorite researcher, suggests that:

…subjects on low-fat diets systematically underreport energy intake compared with subjects on low carbohydrate diets.

In support of his theory he cites a study where weight loss from a low fat diet did not turn out as predicted.

Fat people on low fat diets are not only the worst liars around, they are also not very smart. Kelly A. Meckling and coworkers compared a low fat diet to a low carbohydrate diet in overweight men and women. They write:

Energy restriction alone predicted a weight loss of 5.5. and 6.9 kg, respectively, in the LF and LC groups, which was close to the observed values of 6.8 and 7 kg for the same groups. Slight differences, particularly for LF subjects might be explained by underreporting of habitual diets, as the subjects became better able to estimate their intakes and keep better food records as the trial proceeded. 

Those put i a low carb group obviously nailed the food reporting task right away, even before they actually were put on the diet, and missed the predicted weight loss by a mere 100 grams.

Everyone knows low fat fatties are the worst. Thermodynamics applied to food and the body is very simple, yet predicted weight loss are often not achieved by low fat fatties.

Writes Jennifer B Keogh and colleagues (when a low carb group lost more weight than a low fat group in their study):

Greater weight loss with a low-carbohydrate diet than with a conventional low-fat diet has been reported previously (2– 4, 57). Subjects in these studies reported similar energy intakes despite differences in weight loss, which suggests that the conventional diet group underreported their intake (3, 4, 57).

A group of Dutch researchers set out to test the extent of underreporting in 30 obese men. Their conclusion:

Total underreporting by the obese men was explained by underrecording and undereating. The obese men selectively underreported fat intake.

Not only did these men lie about how much they were eating, they didn’t even eat as much as they should have. They underrate. Those bastards!

If by chance you are wondering if the methods of the Dutch researchers were bulletproof, they weren’t. Still…

It is possible that overweight people under report more than lean people. But people seem to think that the under reporting somehow is the reason they are fat. They don’t know how much they eat and so they stuff themselves and grow fat. It is also possible that low fat diets does not work very well and that the human body is more metabolically complex than the simple energy calculations used predict.

But if overweight people do really under report more than «normal» weight people, are they then fat because they under report and lie, or are they perhaps under reporting because they are fat and afraid of being stigmatized as gluttonous and desperately trying to keep some of their dignity?

A closer look at adiponectin

Whether insulin or leptin or adiponectin or PPAR gamma or NF KB or a bajillion cytokines are the proximate mediators of obesity or atherosclerosis is hardly the point, is it?

Kurt G. Harris MD

Although biochemistry can be marvelously exiting we must not lose sight of the bigger picture. It is increasingly unlikely that any one tiny substance is going to be our savior.

Still, adiponectin would be a good candidate. Adiponectin is indeed popular these days. If you type it in Pubmed you get about 7150 hits of which a whopping 4800 of these are from after 2006

Leptin is adiponectins evil twin brother 
Whereas leptin is considered a pro inflammatory substance which may contribute to the development and progression of autoimmune responses, adiponectin seem to act as an anti-inflammatory factor. If your adiponectin level is low, you want to increase it. Leptin is generally high in obesity and lifestyle diseases while adiponectin is low. In vitro studies indicate that leptin promotes human breast cancer cell proliferation while adiponectin exhibits anti-proliferative actions.

Despite being produced almost exclusively by the fat tissue (lymphocytes also produce it) obese persons usually have low adiponectin levels. Expression of the mRNA responsible for the production of adiponectin is significantly decreased in the adipose tissue of obese mice and humans, which may explain why this occurs.

Adiponectin has showed numerous inverse correlations with weight, BMI, insulin, glucose, HOMA, atherogenic lipid profiles, cancers, liver disease, and dementia and so on. In short, adiponectin seems to positively correlate with anything positive.

Adiponectin itself may be antiatherosclerotic, as it acts as an endogenous antithrombotic factor and inhibits macrophage activation and foam cell accumulation, both being critical cytologic elements of atheromas. Stroke, coronary heart disease, steatohepatitis, insulin resistance, nonalcoholic fatty liver disease, and a wide array of cancers have been associated with decreased adiponectin levels. 

Wozniak et al 2009 

Serum adiponectin concentrations are inversely associated with obesity, insulin resistance and type 2 diabetes in rodents and humans, whereas increased serum adiponectin concentrations are associated with improved insulin sensitivity.

If you are overweight with good insulin sensitivity it means your fat tissue is doing its job, that there is minimal endoplasmatic reticulum stress, minimal inflammation and that you probably have a high adiponectin level.

Morrison et al (2010) examined 108 obese girls of who 31 was identified with having paradoxically high adiponectin levels. In these 108 obese girls, adiponectin levels at age 16 years independently predicted HDL level (positive) and waist circumference (negative), insulin level (negative), and glucose (negative) at age 23. Paradoxically high adiponectin levels at age 16 was a negative independent predictor for waist circumference, HOMA-IR and for the components of the metabolic syndrome at age 23.

Adiponectin and rodents
Most of what we know about adiponectin is from rodent studies. T. Yamauchi and colleagues showed that decreased expression of adiponectin correlates with insulin resistance in mouse models of altered insulin sensitivity. They propose that adiponectin decreases insulin resistance by increasing fatty acid oxidation and thus decreasing triglyceride content in muscle and liver in the obese mice. In lipoatrophic insulin resistant mice the resistance was completely reversed by administering a combination of physiological doses of adiponectin and leptin. When administered separately the resistance was only partially improved. The results from these trials are of course interesting and important, but the authors naturally concluded that “…adiponectin might provide a novel treatment modality for insulin resistance and type 2 diabetes,” thus missing the bigger picture by a mile.

In normal mice adiponectin administration has been shown to improve insulin sensitivity and lower glucose levels.

The insulin sensitizer agonist with the marvelous name of peroxisome proliferator-activated receptor-gamma (PPARg) stimulates adiponectin production in fat tissue. Adiponectin is thought to be part of this agonist’s mechanism for lowering circulating fatty acids and increasing fat oxidation. The increase in insulin sensitivity by adiponectin might be simply from the increased fatty acid oxidation ameliorating fat cell overload.

Additionally, adiponectin has a direct effect on glucose uptake in skeletal muscle and adipose tissue and may increase the glucose transporter (GLUT4) translocation to the plasma membrane. Interestingly, pro-inflammatory cytokines, such as TNF-α and IL-6 are potent inhibitors of adiponectin gene expression or protein secretion.

In the early 2000 Matthias Blüher and colleagues produced a strain of the genetically engineered FIRKO mouse. This mouse lacks insulin receptors in the fat tissue. An inability to store energy in fat tissue and especially to take up glucose is normally very harmful. The FIRKO mice are immune to the dietary induced obesity used in other mice. However they live quite a lot longer than normal mice. Due to its genetic defect the FIRKO mouse have normal insulin sensitivity and normal glucose homeostasis. Despite its lean shape the FIRKO mouse also over express adiponectin. Transgenic mice lacking adiponectin on the other hand show impaired insulin sensitivity and an abnormal glucose homeostasis.

The over expression of adiponectin could be what saves the FIRKO mouse from the normally observed ill effects of adipocyte insulin resistance.

Intravenous injections of adiponectin in rodents have increased adiponectin in the cerebrospinal fluid which indicates brain transport. When injected directly into the brain adiponectin decrease body weight in rodents mainly by increasing energy expenditure.

The leptin deficient ob/ob mice respond particularly well to adiponectin injections both in brain and serum and shows increased thermogenesis, weight loss and reduction in serum glucose and lipid levels after injections.

One proposed mechanism for the coexistence of obesity and insulin resistance is endoplasmatic reticulum stress caused by the growing adipocytes. Obesity induces ER stress in mouse adipose tissue, which also correlates with reduced adiponectin levels. Suppressing ER stress increases adiponectin levels in 3T3-L1 adipocytes in vitro and alleviates diet induced adiponectin downregulation in mice.

Adiponectin, diet and weight loss
The best way to increase adiponectin is to lose weight as adiponectin increases in plasma with fat loss. Shai et al fond a significant increase in adiponectin level during both weight-loss and maintenance phases despite dissimilar macronutrient intakes.

Severely obese women has significant less fasting and postprandial (medium carb diet) adiponectin compared to lean women.

Sidika E Kasim-Karakas gave 22 healthy postmenopausal women a eucaloric low fat – high carb diet for 4 months followed by the same diet (15%fat) only energy restricted for 8 months. The researchers wondered whether energy restriction would modulate the inflammatory response to a high carb diet. The eucaloric diet decreased adiponectin from 16.3 to 14.2mg/L (P<0.05). The energy restricted diet increased adiponectin from 14.2 back to 16.3.

During the eucaloric phase, the low-fat – high carbohydrate diet exerted unfavorable effects on several inflammatory markers. The energy restricted low-fat – high-carbohydrate diet caused weight loss and affected inflammatory markers favorably thus indicating a protective role of energy restriction on the inflammatory effect of high carbohydrate feeding.

Pischon et al recently reported that in the 532 male participants of the Health Professionals Follow-Up Study, serum adiponectin concentrations correlated inversely with the glycemic load and positively with the total fat content of the diet.

Hypoadiponectinemia is as mentioned associated which the metabolic syndrome with all its components and also correlate with non alcoholic fatty liver disease (NAFLD). There is however much indicating that low GI diet in these conditions increases adiponectin level.

Keogh et al (2008) explains that adiponectin seem to only increase in the face of substantial but not moderate weight loss. Keogh et al found no effect of weight loss on adiponectin level either by a low carbohydrate or low fat diet. The weight loss was 6-7kg in 8 weeks. However Keogh had previously found an improvement in adiponectin after 12 months but not after 3 months, which suggests a delayed weight loss response on adiponectin.

Hivert et al looked at blood samples from the Nurses’ Health Study. They found that in the women who did not develop diabetes, baseline levels of adiponectin were associated with significantly greater weight gain after adjusting for age, BMI, physical activity, diet, and other factors. The women in the highest quintile of adiponectin gained 3.18 kg compared to women in the lowest quintile who gained 0.80 kg over 4 years. There was no such association in the women who did develop diabetes. The finding might indicate that higher adiponectin production by adipocytes might be a sign of healthier adipose tissue with further capacity to store fat. This is supported by the finding that a good fat storing ability seems to protect against insulin resistance.

Weight reduction has been found to increase plasma adiponectin in both obese and diabetic patients. Exercise interventions of short duration that does not alter body weight or body fat does not change adiponectin levels. Layman et al (2005) found that an exercise regimen that reduced body fat increased adiponectin levels. The positive changes in adiponectin remained even when controlling for changes in body fat.

Other effects
In vitro studies suggest that adiponectin plays an important role in nitric oxide (NO) generation which is an important function for arterial elasticity. Impaired NO generation plays a role in endothelial dysfunction and atherosclerosis. Decreased plasma adiponectin correlates with impaired insulin-stimulated nitric oxide synthase activity in skeletal muscles and also severity of insulin resistance in people with type 2 diabetes. This finding may provide one link between reduced plasma adiponectin levels and accelerated atherosclerosis in type 2 diabetes.

Adiponectin also affects endothelial progenitor cells which play an important part in repairing damages to the vasculature. Adiponectin seem to inhibit EPC apoptosis in vitro.

A Japanese study found a correlation between cognitive impairment and adiponectin. Plasma adiponectin was significantly higher in people with mild cognitive impairment and people with Alzheimer’s disease compared to normal controls.

Smoking lowers adiponectin

As with many other biological substances adiponectin level varies with day and night and feeding/fasting. This lends caution to interpretation of adiponectin results.

Leptin and local cellular hunger – uniting the theories

Leptin

About 15 years ago the 167 amino acid peptide hormone leptin was discovered by Jeffrey M. Friedman and colleagues through work with genetic mouse models. It is primarily expressed in adipose tissue and there is thus a close correlation between the blood level of leptin and the size of the fat tissue. A small fat tissue size, as in anorexia nervosa, correlates with low leptin levels. Since its discovery leptin has commonly been known as an appetite hormone. Because of its correlation with fat tissue size it was considered an important step in obesity research from the very beginning.

The ob/ob mice strain (the very strain that helped us isolate leptin) produce no leptin. They are extremely fat and have a voracious appetite. If injected with leptin, they eat less and loose weight. The initial results from mouse trials created an air of optimism in the obesity research area. Leptin was thought to stimulate satiety. Imagine a substance that when injected would simply turn you off food. But, as always, the human body proved more complex than first assumed. It turned out that unlike the ob/ob mouse, overweight humans often had high leptin levels. Consequently leptin injections in overweight humans, not surprisingly proved a poor treatment.

4deaf-leanobese_mice400
Leptin deficient mouse to the right with normal mouse to the left. From: www.ohsu.edu/Bouret/ images/leanobese_mice400.jpg

Leptin circulates in a free form and binds to leptin-binding proteins. It’s secreted in a pulsatile fashion and secretion varies with night and day. The main regulating factors for serum leptin concentration seem to be short-term food intake and the amount of energy stored in adipocytes. Although leptin correlates positively with body fat size and supposedly down regulates hunger, the overweight and obese humans still experience strong hunger. This apparent paradox sparked the term “leptin resistance”.

Leptin resistance was thought to be much like insulin resistance and thus caused by long term high levels of serum leptin. Despite high serum leptin levels, the cerebrospinal fluid/serum leptin ratio is lower in obese compared to lean individuals, suggesting that a lower central nervous system leptin transport may explain part of the supposed leptin resistance in obesity (Eckert 1998).

Local cellular hunger

Before I delve deeper into the world of leptin I need to do a quick recap. I’ve written more substantially about this before here and here, but will try to summarize the most important points (Alternatively read thisthis and this).

Our sense of hunger is strongly dependant upon the state of our metabolism. For example, if we manipulate the fat tissue (by drugs or low carbohydrate diets or even exercise) into releasing larger amounts of fatty acids (energy), we don’t feel very hungry. Even more so if in addition glucose production is up regulated and glycogen breakdown is on. We also know that in most animal models, an increase in fat storage occurs prior to increases in food intake. It is thus more likely that we feel hungry and eat because we are storing fat, than it is that we are storing fat because we feel hungry and subsequently eat more.

Of course we don’t feel very hungry when we have a high fat oxidation. As humans we get the energy we need to sustain life and locomotion from two sources; food or stores in our body. When the stores provide a larger part of the energy needed the need for acquiring it from food declines. Hunger declines, metabolism is turned up and energy stores in our body shrink.

If, we on the other hand manipulate the fat tissue in the direction of storage, for example through increasing insulin levels we shut down fat release from adipose tissue. This effect takes place whether the insulin comes from injections or your own pancreas. The energy provided by the body stores is no longer enough to sustain high metabolism. The result is increased hunger, lower body temperature and no drive to exercise (fatigue). Many overweight people recognize these symptoms and meet them at a daily basis. These are the symptoms of a hungry body in a storage mode. It is hungry because much of the energy it needs is stored away. In this mode, if we don’t eat and don’t fill the energy gap with energy from food, the body will starve. It will starve no matter how much energy we’ve got stored as fat. What matters is if or how much of the energy stores are available for use.

Starving the body (even if you are overweight) will cause a great deal of things. In females, amenorrhea or loss of menses, the shutting down fertility is common. Fertility (and sex drive) is one of the first things to go when the body feel its starving. The simple explanation for why an energy deficit causes disruption of the reproductive function is that reproductive function has a low priority in the survival of mammals. Functions essential for survival are those of basic cellular maintenance, keeping correct body temperature and locomotion to obtain food. These functions are maintained at the expense of other functions (e.g. reproduction).

In the words of George Wade et al (1996):

” …it is worth noting that the low priorities of both reproduction and fat storage vis-a-vis processes necessary for survival could account for their habitual association. Exercise, exposure to low temperatures, excessive fat storage, or poorly controlled diabetes mellitus illustrate this second point.”

Take a strong note of the “excessive fat storage” part. Fat storing is from the body’s view not necessarily considered a state of energy surplus, but often that of energy deprivation. What is deprived, are all the tissues of the body, and even fat tissue itself. For as long as energy is being locked into the form of triacylglycerols and the hormonal environment hinder its release, no tissues can use it.

In animal studies, feeding a high-fat diet (which increases the energy flow from fat tissue to other tissues) may ameliorate reproductive deficits. Energy deficits resulting from inadequate energy intake are also more extreme when consuming a high carbohydrate diet.

Decreased reproductive function is but one symptom of starvation. When deprived of energy, even muscles may brake down to a larger extent to supply glucose for fuel. Supporting this theory are observations of sudden increases in muscle mass in ketogenic diet studies, and findings that the muscles in obese woman act very much like muscles in a starving person (Hittel 2009).

The major point here is that energy availability of the whole body does not reflect the energy availability of specific tissue cells. And hunger is largely the result of our metabolism, the regulatory point seem to be the production of ATP in liver cells (Friedman 1999).

Uniting the theories

Now for how leptin relates to hunger and our metabolism.

Leptin as an energy flux indicator

Leptin was thought to be a satiety signal. But, according to resent research, leptin’s main function is not simply to directly regulate hunger and satiety, but to inform the organism that there is enough energy to sustain life. The major physiologic role of leptin seems to be to signal available energy to the hypothalamus.

Increasing leptin increases fat oxidation. The finding is of great importance because increasing fat oxidation by any means, reduce hunger. Arch et al probably hit the nail on its head when they proposed that leptin is not raised in obese individuals because of leptin resistance, but because leptin is opposing other forces that promote obesity. Because of the opposing forces that drive fat storage, leptin is desperately trying to get the energy stored as fat transported to other tissues.

In anorexia nervosa leptin levels are low, very low (Eckert 1998). The oxidation of stored fuels is kept at a minimum and consequently the body is no longer signaling that it has energy surplus, which it hasn’t. It needs energy from food.

When fasting, leptin levels decrease rapidly before and out of proportion to any changes in fat mass, thus likely signaling an energy gap. A gap existing because the oxidation of stored fuels is not in itself enough to keep metabolism high. Consequently the body need energy from food and lack of leptin is signaling just that.

Expression of leptin from adipocytes is directly related to the glucose uptake by adipocytes. Glucose uptake is directly related to insulin level, and glucose level is directly related to fat oxidation. When fat oxidation is low, as with a high carbohydrate diet, the body relies heavily on glucose for fuel. The strong reliance on glucose increase the probability of low glucose levels with consequent decreased leptin secretion and increased hunger.

Ketones are produced to spare glucose. Most of the cells that can metabolize glucose can also metabolize ketone bodies. When people are fasting they commonly experience a great hunger the first days, but as glucose level drops, fat metabolism is turned up and keton production is increased. When ketone body production is increased, hunger declines, even though a person is still fasting. Thus hunger is controlled by the total rate of oxidation of fuels and not by the amount of energy ingested.

The same mechanism comes into play on a low carbohydrate diet when insulin is decreased and ketone body production is increased (Johnstone 2008Boden 2005).

When fat oxidation increases, whether it is by eating less (calorie restriction) or specifically reducing glucose and insulin load (low carbohydrate diet), leptin decreases. But this may not mean increased hunger. There may no longer be a need to overpower other fat storing effects. A decreased sensation of hunger may actually appear simultaneously with decreased leptin levels, further supporting the notion that leptin is not simply a hunger signal.

Leptin is decreased with dieting also because total fat mass is decreased. But, leptin concentration decrease after weight loss has been found to be disproportionate to changes in adiposity. These observations suggest that other factors in addition to adipose mass modulate leptin secretion. On low calorie diets, the individuals who experience the greatest increase in hunger, and therefore those who probably have the lowest fat oxidation rates, are also those who have the larges decrease in leptin (Keim 1998).

When the overweight person is hungry, this seems a paradox to those only preoccupied with total body energy expenditure and intake. It is not a paradox. It is a completely natural response to specific tissues starving because too much of the energy ingested is stored in the adipose tissue. The overweight person may also have a high level of leptin in combination with high level of hunger, because some tissues are in fact starving. Leptin is perhaps increased in this condition to increase energy availability, but does not in itself down regulate hunger. Hunger is reduced only if fat oxidation is properly increased.

In one study (Cooling 1998) the researchers found that subjects habitually consuming a high-fat diet had raised leptin concentrations and a higher basal metabolic rate (BMR) than subjects with the same BMI and adiposity habitually consuming a low-fat diet. In this case leptin seem to be high in the individuals on the high fat diet because it signals an energy surplus. A high fat intake leads to less fat storage than do high carbohydrate intake. The finding also shows how diet and thus metabolism influences leptin secretion independent of fat tissue size.

Leptin resistance

Evidence for leptin resistance was first based solely on the finding that obese humans generally have elevated serum or plasma leptin concentrations compared to lean subjects (arch 1998). Because the theory was not supported by experimental data, Arch et al (1998) proposed that that leptin concentrations are not raised in obese individuals because of leptin resistance, but because leptin is opposing other forces that promote obesity.

But does leptin resistance really exist? Or can the findings which lead to the theory perhaps be explained through the local cellular hunger – energy oxidation hypothesis? The question proves difficult to answer.  In 1998, roughly two years after the discovery that overweight individuals had high levels of leptin, some researchers already considered this hypothetical resistance to be nonexistent.

There still are several indications that a form of leptin resistance might exist. For one there is the fact that cerebrospinal fluid/serum leptin ratio is lower in obese compared to lean individuals. Although, this may just be a transport problem not related to an actual resistance. Several rat studies have shown increased fat oxidation rates by skeletal muscles when exposed to leptin. In humans however it is not quite that easy. One study (Steinberg 2002) showed a greatly increased fatty acid oxidation in muscles from lean individuals in vitro. Muscles tissue from overweight individuals however, did not show an increase when exposed to leptin. The finding is of course considered to be an indication of leptin resistance in the overweight, but remember these cautioning word from the authors;  “it should also be noted that the non physiological conditions imposed in such a preparation (i.e., high leptin, absence of insulin and other hormonal factors) make it difficult to extrapolate our findings to the in vivo condition.”

Also, animal studies have demonstrated that 4 weeks of high fat feeding can induce leptin resistance in skeletal muscle, as demonstrated by the elimination of leptin’s stimulatory effect on fat metabolism. If the stimulatory effect is gone we do indeed need to call it a resistance.

Leptin may be increased in obese individuals and so representing an attempt to overpower fat storing processes as well as possibly representing a leptin resistance. When weight is lost there seem to be a decrease in leptin either because of a reduced need for its effect on fat metabolism or because of an increase in leptin sensitivity. In any case, a high level of leptin in overweight do not likely cause overweight. It is there to reduce fat storage rather than to drive it.

Blüher et al (2009) argues that leptin resistance or hyperleptinemia causes not only an increasing degree of obesity, but is also associated with increased lipid storage in muscle, liver, and other tissues, dysfunction of several neuroendocrine axes, including the reproductive, thyroid, and adrenal axes, as well as abnormal function of the immune and autonomic system i.e. thermoregulation, energy expenditure, and others. Looking at this cluster of symptoms, we are looking at any metabolic resistant overweight person. All symptoms can be easily explained without leptin and it is thus unlikely that leptin play the causal role.

Uniting

Leptin was originally believed to control hunger, although it was never actually clear if it “controlled” it, or was simply a part of the intricate physiological interaction that is hunger. Leptin was later discovered to also be a part of the regulation of reproduction and the hypothalamic-pituitary-gonadal (HPG) axis. Animals that lack leptin (ob/ob mice) or have obvious leptin resistance (db/db mice and fa/fa rats) fail to achieve puberty and are infertile.

This is where we most easily see the theories unite. Reproduction is, as Wade shows us, highly sensitive to fluctuations in energy as is leptin. Leptin acts as a signal informing the different tissues of the energy state of the body, rather than itself controlling the energy metabolism.

The features of hypothalamic hypogonadism in women (low levels of sex hormones) and it’s associated disturbances can be restored by leptin administration. The question is, do we simply trick the body into believing there is more energy than there actually is, or do we actually increase energy availability?

Amenorrhea, the lack of menses, may also be induced by exercise. Endurance trained athletes have a higher prevalence of amenorrhea or dysmenorrhea than non exercising controls. It is normalized with leptin injections. Administering leptin may increase fat oxidation and thus, as Friedman et al has reported, also increase hepatic ATP levels and by doing so may restore fertility function.

Both increased levels of leptin, as in obesity, but also low levels act inhibitory in the HPG axis. Blüher el al claims that: “These results underline a pivotal role of leptin in regulating reproductive function and strengthen the hypothesis that leptin is one of the factors mediating reproductive abnormalities in several disease states.” But it may not be this way. Leptin is not necessarily “controlling” fertility. It may simply be the messenger informing the body of its energy status. Reproduction is regulated in accordance with energy status.

Blüher et al continues: “We have shown that leptin may serve as a signal to convey information to the reproductive system that the amount of energy stored in the body as fat is adequate not only for the survival of the person but also for carrying a pregnancy to term.”

This claim however, rests on the assumption that the energy stored as fat is available for use. This is not always the case.

When leptin resistance seem to be causing obesity in rodent models and the rare cases in humans, it is likely because the different body tissues and the hypothalamus constantly experience an energy shortage. Metabolism with all its manifestations, fertility included, is adapted. The body does what it can when it senses energy to be in short supply. It increases hunger, decreases the metabolic rate and effectively shuts down unnecessary processes.

 

32729-leptintreatment

Effects of recombinant human leptin treatment in a patient with congenital leptin deficiency. (A) Before treatment. (B) After treatment. From: Leptin: a pivotal regulator of human energy homeostasis, Farooqi 2009.

States of congenital leptin deficiency because of mutations of the leptin gene have been associated with severe obesity, glucose intolerance, and insulin resistance in humans. All expected symptoms if fat oxidation is low.

Despite the initial hopes, placebo-controlled trials in obese persons over periods of several weeks with leptin-treated subjects have not shown impressive results on weight loss. This is not surprising, considering that many obese persons have high leptin levels, high glucose level and high insulin resistance, and thus a fat tissue which reluctantly gives away energy. A slight increase in fat oxidation with leptin replacement therapy is expected to reveal nothing but small decreases in fat tissue, as long as nothing else is done with the fact that the tissue is in a storage mode.

Even in patients with severe lipodystrophy (inability to store fat/loss of fat tissue) leptin replacement decreases fat mass. The decrease in fat mass is an indicator that fat oxidation is increased and in accordance symptoms of starvation are improved (Oral 2002). At least in the short run. Women with anorexia nervosa and with cachexia resulting from cancer or severe chronic infections also show many of the symptoms of a starving body, including low leptin levels. Despite the fact that leptin would have the highly undesirable effect of inducing weight loss in these patients leptin treatment is still recommended (Friedman 2009). It is another example of a treatment aimed at ameliorating symptoms, without positively (probably negatively) effecting the underlying cause.

Control by food intake

Seen together the current data point to leptin as a signal informing the hypothalamus of the availability of oxidizable fuels.

If leptin is secreted in response to the energy metabolism, we would expect macronutrient intake to influence leptin level. Several studies have found such an effect, while others have not.

An increase in dietary protein from 15% to 30% of energy at a constant carbohydrate intake has produced sustained decreases in caloric intake, hunger and leptin levels (Weigle2005).

60315-leptin
Concentrations of circulating leptin (adjusted for adiposity) in 12 women during a prolonged energy deficit. Means with different superscript letters are significantly different, P < 0.05. From Relation between circulating leptin concentrations and appetite during a prolonged, moderate energy deficit in women, Keim et al 1998.

Havel et al (1999) reported acutely decreased leptin concentration after ingestion of a high fat, low-carbohydrate diet. Jensen et al (2006) found that persons in the highest quintile for whole-grain intake in a prospective study had 11% lower circulating leptin compared to those in the lowest quintile. It is intriguing to think that lower in this case could mean increased hunger response due to lower fat oxidation, but we must consider the possibility that it simply reflects and reduced leptin resistance. Volek et al reported a 42% decrease in leptin with a low carbohydrate diet (12%CHO) and 18% decrease in leptin with low-fat diet (24% fat) for 12 weeks in overweight subjects. Once again, the results could indicate a lack of energy availability or improvement in leptin resistance.

But, because we know that carbohydrate restriction greatly increases fat oxidation, reduces hunger and may even increase heat production and locomotion, it seem most likely that the larger decrease in leptin on a low carbohydrate compared to a high carbohydrate diet represents a decreased need to overpower fat storing mechanisms. The significant decrease in leptin found by Volek et al persisted after normalization of body and fat mass.

Expression of leptin from adipocytes is directly related to the glucose uptake by adipocytes. This could in itself explain why leptin is reduced more with carbohydrate restriction. Leptin also decreases with decreasing weight, because fat tissue is the main secreting organ. This means that in an overweight person with hyperleptinemia a reduction in leptin level is expected with weight loss and is not negative just because high leptin may reduce hunger.

It seems that increases in leptin usually signal a surplus of energy, but not in the obese. In the obese the high levels seem to be caused by the body’s desperate attempt to increase fat oxidation.

In support of this are the findings that injections of leptin increase fat oxidation in combination with reduced food intake. That dieting which increase fat oxidation cause reduced levels of leptin in the overweight.

Summing it up

Believing that leptin may prove to be an important treatment for obesity, trough down regulating hunger, is nothing short of crazy. There is little doubt left in the literature that the hunger experienced by an overweight person, stems from the unavailability of oxidizable fuels. Hunger is not what must be improved, rather we must increase the release and oxidation of the fat situated in adipose tissue stores, and hunger will decrease.

Although leptin is expressed in relation to adipose tissue mass, its main function is not so signal adipose tissue size, but fluctuations in available oxidizable fuels. When leptin treatment ameliorates adverse symptoms related to conditions of low fat mass, i.e. anorexia nervosa or lipodystrophies, the mechanism is likely an increase in fat oxidation and thus a small increase in oxidizable fuels. Treating these conditions with leptin is counterintuitive and may even cause adverse effects over time. Blaming leptin is equivalent to killing the messenger.

Local cellular hunger

I once wrote a short paper about menstrual disturbances in female athletes. Menstrual disorders seem to be more prevalent in athletes than sedentary controls and more prevalent in sports emphasizing leanness. Elite athletes also have higher menarche age compared to non elite athlete controls. Menstrual disorders increase the risk of low bone mineral density, stress fractures and infertility. One hypothesis put forth to explain the apparent increased risk of menstrual disturbances was “the body fat hypothesis.”

The body fat hypothesis originates from observations showing that females with extremely low body fat where amenorrheic (absence of menstrual cycles for more than 90 d) and that amenorrheic athletes had lower body fat percentages than eumenorrheic (normal menstrual cycles) athletes. But, when simply matching eumenorrheic and amenorrheic athletes for body fat, it was found that the body fat hypothesis could not explain the prevalence of menstrual dysfunction in athletes. Amenorrhea often occurs in the general adolescent female population, even in the absence of substantial undernutrition or underweight, and there are many underweight and lean athletes who still maintain their menstrual function.

Sudden strenuous exercise induces amenorrhea in humans and more so if the exercise is compounded by weight loss. This caused scientists to speculate if a negative energy balance is a causal factor in menstrual disturbances. It was in researching this I stumbled over the work of George Wade, and he really opened my eyes. Starving an animal will cause it to lose its reproductive function. The simple explanation of why an energy deficit causes disruption of the reproductive function is that reproductive function has a low priority in the survival of mammals. Functions essential for survival are those of basic cellular maintenance, keeping correct body temperature and locomotion to obtain food. These functions are maintained at the expense of other functions (e.g. reproduction, storage of energy as fat and growth).


Wade et al. points out that;” …it is worth noting that the low priorities of both reproduction and fat storage vis-a-vis processes necessary for survival could account for their habitual association. Exercise, exposure to low temperatures, excessive fat storage, or poorly controlled diabetes mellitus illustrate this second point.

When energy balance is discussed, it is implicit that we are discussing the whole body. But the theory of energy balance is inaccurate when simply defined as “energy intake minus energy expenditure.” It is inaccurate simply because the energy availability of the whole body does not necessarily reflect the energy availability of specific cells (e.g. the ovarian cells). So the important question is not necessarily if the body is in a negative energy balance, but rather what factors may cause a local energy deficit independent of total energy balance?

In a study by Tomten and Høstmark, 20 long distance runners were compared. 10 of the athletes had regular menses (control) and the other 10 athletes reported irregular menses. In the latter group a statistically significant negative energy balance was found. But the energy deficit was primarily because of a lower intake of dietary fat. Tomten and Høstmark conclude; “Present results might indicate that a high CHO/low fat diet could promote an inadequate EI (Energy Intake; my explanation) in recreational or sub-elite athletes and could cause energy deficit and endocrine disturbances.

Although a restriction in dietary fat intake is often found in athletes, it is not often referred to as an independent hypothesis. This might seem odd, given that there do exist a perfectly reasonable physiologic explanation for the link between dietary fat and menstrual disorders.

A diet comprising of mostly carbohydrates is more likely to give higher insulin load than diets with more fat and protein.

Injected insulin disrupts reproductive function in animals. In the words of Wade et al. “When food intake is limited or when an inordinate fraction of the available energy is diverted to other uses such as exercise or fattening [my bold], reproductive attempts are suspended in favor of processes necessary for individual survival”. In animal studies, feeding a high-fat diet may ameliorate reproductive deficits. Energy deficits resulting from inadequate energy intake are also more extreme when consuming a high carbohydrate diet.

Obese women also seem predisposed of menstrual disturbances. Many women get pregnant only after loosing weight. This may seem counterintuitive. Wouldn’t nature prefer a mother with large energy stores and thus a grater chance of caring for her young through hard times? Well, as it seems, nature would prefer a certain amount of extra available energy, as illustrated by the loss of menses with extreme leanness. But, in the case of overweight and obesity we are fooled by an apparent surplus of energy. To be more precise, the fat cells have a surplus of energy, but that tells us nothing of the energy available for other tissues. The menstrual disturbances in athletes are in part likely caused by low energy availability for the ovarian cells, and when we are talking reproduction, these are the cells that count.

Yet another indication that a local starvation may exist is a finding that myostatin secretion is may be close to 3 times higher in insulin resistant obese subjects than in lean controls. Myostatin is a natural regulator of muscle tissue growth. Removing myostatin will make you look like a human version of the Belgian blue (just type myostatin in Google). Increased myostatin secretion is seen with fasting, hunger and very low energy intakes. This might be an important evolutionary adaptation by which our body breaks down superfluous muscle protein for glucose production.

When muscles are insulin resistant, they cannot take up sufficient glucose. In addition a high insulin level may make stored fat unavailable. So from the muscles point of view the body is starving independent of the amount of stored energy in the body. For an overweight insulin resistant person this may become a downward spiral with a gradual decreased ratio of muscle mass to fat mass.

Insulin resistance and polycystic ovarian syndrome are commonly associated. PCOS is a condition characterized by excessive cyst growth on the ovaries and will often cause infertility. Funny thing is that this condition is best improved by carbohydrate restriction. One explanation is an improved energy flow to the ovaries.

As a final closing argument several studies of carbohydrate restriction have reported muscle growth without increases in exercise level. It is as if the muscles are finally given the energy they need to respond and grow to mechanic stimuli.

A scale model of obesity


Whatever the individual cause of obesity is, in the absolute majority of cases, carbohydrate restriction works effectively at reducing adipose tissue weight. This is a common observation in most human and animal studies. Carbohydrate restriction for the most part works because it influences insulin and glucose. In addition it affects our sensations of hunger and satiety and affects the energy flow to the individual tissues. This might be a simplification, but it’s a fair simplification. The increased fat storage and insufficient fat release apparent in overweight must in most cases be explained by the specific disease or condition’s influence on insulin and glucose metabolism, simply because insulin and glucose are the main regulators of fat metabolism.


I’ve often pictured the adipose tissue as a scale. All the factors that influence energy release from this tissue rest in one cup and all the factors influencing storage of energy rest in the other. Tipping the scale to one side symbolizes fat storage, tipping to the other symbolizes fat release. If the scale is in perfect equilibrium, the storage of energy matches the release of energy and the fat tissue remains roughly the same size.



Most people are more or less weight stable most of the time. The behavior of our fat tissue is, like most other physiological processes, a process seeking equilibrium (although not likely due to a set-point). Imagine any factor that is known to influence fat metabolism. Take dietary carbohydrates. Let us ad an increased intake of dietary carbohydrates as a factor on one side.


The factors contributing to the storage of energy now overpower the factors contributing the release of energy. Increasing carbohydrate intake will cause a decrease in lipolysis (fat release), mainly through the increased insulin release and increased glucose levels. Tipping the scale in this way (provided all other factors remain constant) will cause a net storage and we will gain weight in the form of fat. A larger fat storage in relation to the fat release will cause a more rapid weight gain. Of course, the scale that is our fat tissue goes up and down during the day and night. It does not remain in a fixed position for any amount of time, but the more time spent below horizontal position on one side in relation to the other, the larger the effect.

Adding an increase in exercise level to the scale will once again tip it towards equilibrium. 

Exercise improves the glucose tolerance of our skeletal muscles. Exercise might increase the level of LPL (lipoprotein lipase) in muscles and reduce the level in fat tissue. It might increase glucose uptake in muscles both by reducing glycogen stores, increasing glucose transporters or simply increasing muscle size. The net effect of exercise is that blood glucose and insulin levels are kept at a lower level and the scale is tipped in favor of fat release. Although exercise very often does not make us leaner, it may also do so and the above-mentioned mechanisms are likely explanations.


Exercise and diet are two lifestyle factors with large impact on our imaginary scale. Lifestyle factors do however affect us differently because of our different genetic heritage. Genetic factors may also more easily be understood using a scale model. Looking at fat storage this way, might give us a simple way of explaining many of the often-cited paradoxes of overweight.

Imagine for example that you are overweight while your brother is not, despite having an apparently similar lifestyle. It seems that your scale is tipping in the opposite direction of that of your brother (or sister, friend or whoever). As fat storage most often must be explained through insulin and /or glucose metabolism and not through energy intake or energy expenditure, we can imagine several scenarios that could explain the brotherly differences. Perhaps your brother has been genetically equipped with a more effective glucose uptake in skeletal muscles or that he needs a smaller stimulus (physical activity) in order to improve glucose uptake. A better glucose uptake would mean smaller increase in blood glucose after ingestion of dietary carbohydrate, a smaller insulin release and thus a smaller fat storage with an ensuing better fat release. This small difference would mean that your brother could consume more dietary carbohydrate without tipping the scale too far in direction of fat storage. It might also make your brother more physically active. It is not fair, but it is how it is. We are not all equipped with the same physiology or the same potential for changing our physiology.

I don’t suspect my scale contributes to the knowledge and understanding of health and nutrition, but it has helped me picture how our body works and it reminds me that overweight is about fat tissue size and not body size or body weight. When faced with a non responder (e.g. a person not losing much weight with carbohydrate restriction) we know the factors working against fat storage overpower the factors working for fat release. Knowing the effect of different factors on our physiology we can easily investigate the less common factors like cortisol, thyroid hormones or perhaps myostatin for that matter. The scale may help remind us that we are built differently and respond differently to any external factors.

I am still surprised by the way people often talk about overweight as if we were all physiologically identical. Most people will for example have no difficulty admitting that we tan differently and have different skin complexions from birth, but somehow when it comes to weight it is often expected that we are all created equal. Well, we’re not. Although the underlying cause of overweight and obesity are pretty much the same in all of us, we all have different potential to gain weight both locally and systemic. The scale model may illustrate our genetic differences and answer the poor, but often encountered argument «If carbohydrates make us fat, why isn’t everybody consuming carbohydrates fat?» Our scales are loaded differently from birth. Carbohydrates in a certain amount definitely do have the potential to make most of us fatter, but from a physiological point of view, we are not created equal.