I just finished reading Herman Pontzer’s book Burn. It’s good, I recommend it! I don’t agree with everything, though. Pontzer is the metabolic researcher who went to Africa to study the metabolic rates of Hadza hunter gatherers. To his surprise he discovered that hunter gatherers burn the same number of calories per day as sedentary office workers despite the fact that they spend their days walking and doing hard work like climbing trees to collect honey and digging up tubers with wooden sticks.
The idea that people who have a very active lifestyle burn more calories than other people simply seems to be incorrect, as counter-intuitive as that sounds. The body compensates. Pontzer calls this the constrained energy model. He supports this with the research of his colleagues, citing studies of the Shuar of Ecuador and a study of black women living in Illinois versus a more active population of women in Nigeria.
He concludes: people who work harder don’t necessarily burn more calories. On this I agree.
This is a brave conclusion. I’ve now read a lot of metabolic research papers. The metabolic research field is oddly obsessed with movement. Researchers will follow people around for days on end marking down the amount of time spent walking, cooking, hoeing a row of corn, sleeping, etc. They use metabolic machines to calculate the exact amount of energy all of these activities require. It is difficult to swim against the current of your own field.
Pontzer also cites a large body of evidence that starting an exercise regimen won’t increase your caloric burn as much as you think. He cites a study from the Netherlands where people who had never exercised before were trained to run a marathon over a period of a year. By the end they were running 25 miles per week. Pontzer says this amount of running plus the additional muscle mass should have increased daily burn by 390 calories, but in fact it only increased burn by 120 calories. So if you train to run a marathon, you can eat an extra one of those little 100 calorie snack packs a day and a handful of peanuts. I’m guessing that’s not the return on investment you were hoping for.
Basal Metabolic Rate
In fact, your total caloric burn seems to be tied quite closely to your Basal Metabolic Rate (BMR, this is very similar to the Resting Metabolic Rate – RMR – which I’ll use interchangeably). BMR is tested in the morning after an overnight fast. The subject lies on a couch or bed in a reclined position while breathing into an apparatus that measures Oxygen consumed and carbon dioxide exhaled. From this we can measure BMR. For most people most of the time your total calories burned will be 1.5-2 times your BMR.
Pontzer is very clear that you cannot increase your BMR. Nor does he think you can change your total calories out without training like an Olympic athlete, who can increase their caloric burn to around 2.5 times BMR.
He DOES think you can permanently lower your BMR through prolonged caloric restriction, however. He cites Kevin Hall’s research of contestants on The Biggest Loser TV show, where obese people reduce their caloric consumption by half while training inttensely. Even 6 years after the show ended, Hall found that the contestants had a lower BMR than expected.
Then he talks about Ancel Keys 1945 starvation experiment where Keys fed conscious objectors half of their daily caloric needs for 6 months. Upon refeeding Pontzer says, “As their weight came back their bodies called off the alarm. Unlike the Biggest Loser contestants, their BMRs returned to normal”.
What’s The Difference?
I found that to be the single most interesting line in the book. For some reason, the metabolism of Biggest Loser contestants was permanently damaged through caloric restriction but the metabolisms of the men in Keys’ study were not! Pontzer is completely incurious about this. He just states it as fact and moves on.
Surely something is different about the two groups. Perhaps the difference is because one group was obese at the start of the study and the other group was not. Perhaps there was a dietary change between 1945 and 2016 such as the rapid increase in polyunsaturated fat in the US diet that was responsible for the change. Perhaps both are in play.
Pontzer also acknowledges that there are wide variations between BMRs both between and within populations. He cites the Tsimane farmer-foragers of Bolivia, stating, “Tsimane adults have elevated BMR because of their high levels of parasitic and bacterial infection”. He states it as a certainty, although in his peer-reviewed paper1 there is more room for interpretation.
“Tsimane RMR is 18 to 47% (women) and 22 to 40% (men) higher than expected using six standard prediction equations. … An adult diagnosed with helminths and marked WBC elevation (additional 3.0 3 106 cell/lL) can expect to have excess RMR of 143 to 168 kcals/day, depending on the prediction equation used. This amount reflects increases of 10 to 12% and 11 to 15% above predicted mean RMR in men and women, respectively … Despite the size and number of significant effects, our best-fit models explain only 9 to 19% of the variance in excess RMR”.Pontzer et al., “High resting metabolic rate among Amazonian forager-horticulturalists experiencing high pathogen burden“
I have argued on this blog that pure starch eating cultures have very saturated body fat and this gives them a high metabolic rate when food is plentiful. The largest study on obese caucasians found an average BMR of 28.6 kcal/kg of fat free mass (FFM) amongst men2. The Biggest Loser contestants had a BMR of 27.1 kcal/kg FFM 6 years after the contest, although they had a quite respectable 34.5 at the beginning3. The Harris-Benedict equation, developed in the US in 1919 predicts “normal” BMR to be 30-31 kcal/kg FFM by my calculation. Male rice farmers in Korea were reported to have a BMR of 36.3 kcal/kg of FFM in the off-harvest season4. Male Lao rice farmers were reported to have a BMR of 39.9 kcal/kg FFM. Thai male rice farmers, averaging 46 years of age, had a BMR of 37.8 kcal/kg FFM at harvest season5. Their wives (same age) registered an eye-popping 40.8 kcal/kg FFM. By comparison, the Tsimane men who Pontzer says have an elevated BMR due to pathogen burden have a BMR of 38.0 kcal/kg FFM. In this context, the Tsimane BMR are not exceptional, they are normal for a starch eating culture.
The Thailand study also includes a dietary analysis. The macros that produced the female BMR of 40.8 kcal/kg FFM was 84% carbohydrate (as rice), 11% protein and 5% fat. This is what I mean when I say “starch eating cultures”.
This can be seen globally. Female Mossi farmers growing sorghum and millet in Upper Volta (West Africa) were found to have a resting metabolic rate of 41.3 kcal/kg FFM. This paper has its problems – RMR was not measured first thing in the morning and it’s unclear if any of the women were lactating – but it is still another piece of evidence that metabolic rate isn’t set in stone.
Conversely, there are studies that show quite low metabolic rates, all the way down to 23.9 kcal/kg FFM among male farmers in Tanzania6. I suspect metabolic rates that low are due to long term food shortage, but that data is not presented.
|Population||BMR (kcal/kg Fat Free Mass)|
|Male Farmer Tanzania||23.9|
|Obese White Males||28.6|
|Biggest Loser Contestant Before||34.5|
|Biggest Loser Contestant 6 Years After||27.1|
|Harris-Benedict Equation Prediction||30-31|
|Male Tsimane farmer-forager||38.0|
|Male Korean Rice Farmer||36.3|
|Lao Male Rice Farmer||39.9|
|Female Thai Rice Farmer Pre-harvest||32.4|
|Female Thai Rice Farmer Harvest||40.8|
Given the massive variation in BMR measured around the world, I would expect more curiosity from Pontzer about the mechanisms that control BMR. Instead his position seems to be that your BMR is your BMR and there is nothing you can do about it, not even exercise will help. To suggest that BMR can be changed only opens the door to hucksters and charlatans.
Yet in addition to seeing variations in BMR between cultures and individuals there are also large differences WITHIN individuals. The BMR in the Biggest loser competition varied from 34.6 kcal/kg FFM before the contest to 27.1 kcal/kg FFM 6 years after. The female Thai rice farmers BMR varied from 32.4 kcal/kg FFM in the pre-harvest season to 40.8 during harvest season. If the Biggest Loser contestants had a BMR of 40.8 kcal/kg FFM and a typical total energy expenditure of 1.7 times that, they’d burn 4900 calories a day, which Pontzer argues is at the top end of how much the human digestive system can absorb in a day. What causes the variation? Why did the metabolic rates of the conscientious objectors bounce back in the Keys study but not in the Biggest Loser contestants?
I am fat and I’m a molecular biologist, so I think about the mechanisms of obesity. I know that mice lacking SCD1 have very saturated fat, extraordinarily high metabolic rates, are protected from obesity and have a high ratio of NAD+/NADH. I presume that the mechanism by which saturated fat regenerates NAD+ is by generating mitochondrial ROS, of which glutathione is oxidized in the process of scavenging. Oxidized gluathione is recycled by glutathione reductase which generates NADP+, which the mitochondrial enzyme NNT uses to regenerate NAD+.
The NAD+ allows the citric acid cycle to continue spinning and activates the sirtuins to keep our mitochondrial enzymes deacetylated. In other words, NAD+ keeps our metabolisms humming. Knowing this, my prediction was that I would find the highest metabolic rates in the world in rice eating cultures, and I did. Rice is incredibly low in fat (and therefore PUFA) and it is easily stored so that rice-growing cultures don’t have as much of a metabolism depressing “hunger season” as some other farming cultures. Eating mostly (almost entirely based on the macros given in the Thai study) white rice will make your fat very saturated, just like the SCD1 deficient mice.
When you’re interested in biological mechanisms, it is easy to come up with testable hypotheses. Here’s one: within a given population, BMR should be correlated with the lactate/pyruvate ratio in the blood. Blood lactate and pyruvate are easy and cheap to test and give an indirect indication of NAD+/NADH ratio.7
When you’re not interested in them I suspect it is easy to get caught in a loop of measuring activity levels and white blood cells and immune markers forever and winding up at “our best-fit models explain only 9 to 19% of the variance in excess RMR”.
ASIDE: If you grew up eating oils, switching to an all-rice diet will probably not work the same for you as it does in Thailand.
- 1.Gurven MD, Trumble BC, Stieglitz J, et al. High resting metabolic rate among Amazonian forager-horticulturalists experiencing high pathogen burden. Am J Phys Anthropol. Published online July 4, 2016:414-425. doi:10.1002/ajpa.23040
- 2.Lazzer S, Bedogni G, Lafortuna CL, et al. Relationship Between Basal Metabolic Rate, Gender, Age, and Body Composition in 8,780 White Obese Subjects. Obesity. Published online January 2010:71-78. doi:10.1038/oby.2009.162
- 3.Fothergill E, Guo J, Howard L, et al. Persistent metabolic adaptation 6 years after “The Biggest Loser” competition. Obesity. Published online May 2, 2016:1612-1619. doi:10.1002/oby.21538
- 4.Kim EK, Yeon SE, Lee SH, Choe JS. Comparison of total energy expenditure between the farming season and off farming season and accuracy assessment of estimated energy requirement prediction equation of Korean farmers. Nutr Res Pract. Published online 2015:71. doi:10.4162/nrp.2015.9.1.71
- 5.Murayama N, Ohtsuka R. Seasonal fluctuation in energy balance among farmers in Northeast Thailand: The lack of response of energy intake to the change of energy expenditure. Eur J Clin Nutr. Published online January 1999:39-49. doi:10.1038/sj.ejcn.1600675
- 6.NDANGUZI OCAN H. BASAL METABOLIC RATE AND ENERGY COST OF PERFORMING FARM ACTIVITIES IN MAGUBIKE VILLAGE, KILOSA DISTRICT, MOROGORO, TANZANIA. Published online 2008.
- 7.Istfan N, Hasson B, Apovian C, et al. Acute carbohydrate overfeeding: a redox model of insulin action and its impact on metabolic dysfunction in humans. American Journal of Physiology-Endocrinology and Metabolism. Published online November 1, 2021:E636-E651. doi:10.1152/ajpendo.00094.2021