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Humans Use Less Energy While Resting Compared to 30 Years Ago

A person laid down, resting.
Credit: Katie Moum on Unsplash.
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Over 1 billion people worldwide are classified as obese, according to the World Health Organization. While a myriad of genetic and lifestyle factors can contribute to obesity risk, a long-standing debate has questioned whether the primary contributor to increasing obesity levels is an increase in food consumption, or a reduced energy expenditure.

A new study, led by Professor John Speakman at the University of Aberdeen, provides new evidence in this debate. Speakman is a renowned British biologist and is one of the world’s leading experts on metabolism and energy expenditure.

The researchers used the International Atomic Energy Agency Doubly Labeled Water database, which includes energy expenditure data of adults in the United States and Europe, to explore patterns in total energy expenditure (TEE), basal energy expenditure (BEE) and physical activity energy expenditure (also called activity energy expenditure) over time. 


What is the doubly-labeled water technique?

The doubly-labeled water technique is regarded by Speakman as the “gold standard” approach for measuring energy expenditure. Individuals are asked to drink water in which the oxygen and hydrogen molecules have been subsidized with heavy forms – 18O and 2H, respectively. Analyzing how quickly these molecules are “flushed” from the body indicates energy expenditure rates.

Using the database – and adjusting for the effects of age and body composition – the researchers discovered that the TEE in this population has declined by 7.7% in males and 4.8% in females since the early 1990s. Through combining the TEE and BEE measurements, Speakman and colleagues established that the biggest contributor to this decline was changes in resting and activity expenditure. The amount of energy expended through physical activity has increased, but BEE has declined. Why? The answer isn’t clear right now, but Speakman suggests a few hypotheses.

Technology Networks interviewed Speakman to learn more about the inspiration behind the study, the methods adopted and the potential implications of the research findings.

Molly Campbell (MC): What inspired you to conduct this research study?

John Speakman (JS): I have been interested in the causes of obesity for a long time. It is one of the world’s major health issues and it is important that we understand why increasing numbers of people across the whole world are becoming more obese.

Obesity is due to a problem of energy imbalance – we consume more energy in food than we expend – so the drivers of obesity must cause one or other of those factors to change. They have to cause us to eat more food, or they have to cause us to expend less energy. Generally, it has been presumed that both are potentially important.

We are immersed in a society where high-fat, high-sugar foods are readily available. Plus, we have become very sedentary, meaning our activity expenditure has likely declined. In 2008, myself and a colleague (Dr. Klaas Westerterp) summarized some data from the Netherlands that questioned whether there has been a decline in expenditure. We found that between 1985 and 2005 there was no evidence that expenditure had fallen, but that data pertained to just one town in the Netherlands where obesity levels were quite low. I always had an ambition to pull together a larger dataset from a broader range of countries to see if the absence of a decline in total expenditure was really true. That motivated the current analysis.

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MC: Can you explain what TEE is, and how this differs from BEE?

JS: TEE is the total number of calories you burn in a day for all purposes. It is a critical value because it is that total that needs to be balanced by our intake. It has three main components: basal or resting expenditure, which is our expenditure when we are at rest in a warm comfortable environment and not digesting food. If we eat food, then our metabolism goes up. The difference between the metabolic rate after feeding and the non-feeding resting rate is called several names – like diet-induced thermogenesis, or the thermic effect of food. The third component of our TEE is the energy we spend on activity. That isn’t just exercise expenditure, like going for a run or to the gym, but everything we do, such as moving around, typing, going for a walk, playing with our kids and so on. This is all activity energy expenditure.

MC: Your study relied on the doubly-labeled water technique for measuring energy expenditure. For readers that may be unfamiliar, how has this method been developed and used previously? Is it a reliable method?

JS: The classic way to measure energy expenditure is to measure gas exchange in our breath, i.e., how much oxygen is consumed and how much CO2 is produced. The problem is that, to measure this, you need to have a hood on your head or be permanently confined in a small room.

In the 1950s, a scientist called Professor Nathan Lifson in the United States invented a new method that was based on the elimination of stable isotopes. This was great because you could use it without putting people inside hoods and chambers. The problem was that it was super expensive, so people could only afford to use it on rats,mice and small birds. The cost of doing the analysis declined over time and with improved technology.

The first human measures were done in 1982 by a scientist, also from the United States, called Professor Dale Schoeller. I was part of a group of scientists that developed and improved protocols for the method in the late 1980s and 1990s, which culminated in a book that I wrote in 1997. At the individual level, the error of a single measure compared to the chamber method averages at about 7%. For group measures, it is accurate to about 0.5%, so it’s a good technique and indeed the only available method for directly measuring free-living energy demands. In that sense it is regarded as the gold standard measurement.

Speakman’s 1997 book, titled Doubly Labelled Water: Theory and Practice, is published by Springer New York.

MC: You analyzed data from over 4,000 measurements of adults living in Europe and the USA. Can you discuss this sample in terms of representation?

JS: These measures were submitted to a database of measurements that I and several other key users of the method have compiled over the last five years or so. In total, the database now has more than 10,000 measures submitted by over 130 researchers. I am super-grateful to all these contributors without whom the paper would never have happened. It is a great resource and shows the power of scientists coming together to share data to answer questions that can’t be answered in individual studies. The data generally includes people recruited into studies in control groups that are not manipulated. These are a pretty representative group. Their body mass index (BMI) distribution can be accessed in Figure 1 of the supplementary materials in the paper.  

MC: You found that activity expenditure has increased and that the decline in overall energy expenditure is due to a reduction in the energy expenditure we spend at rest. Can you explain how you formed this conclusion?

JS: For approximately 1,500 of the subjects, we not only had TEE data but also BEE data, and so by making an assumption about diet-induced thermogenesis we could calculate activity energy expenditure. We then adjusted these measurements for differences in body weight and age and looked at how the adjusted values changed over time. We found that TEE has declined by ~6% over the last 30 years or so. That would be consistent with the idea that activity energy expenditure has fallen, but the big surprise was that, actually, this went up, and it was BEE that had declined.

MC: It isn’t clear why the amount of energy we use while resting has declined. Do you have any hypotheses that you can share?

JS: Nobody had previously suggested that changes in BEE would be important, so it is understudied. There are several potential causes. First, we know that people who smoke have greater BEE, so maybe the reduction in smoking is important. Second, there may have been an increase in climate control in our living spaces that buffers us from any environmental effects. In mice, for example, it is known that if you keep them in the cold their BEE measured in the warm is higher than those kept always in the warm. Maybe then reduced exposure to cold is a factor.

Third, some studies suggest that high disease burdens also elevate BEE, so maybe a reduced risk of infectious disease has been a factor (all the measures were obtained pre-COVID-19). Finally, there are many dietary factors that may be important. In the paper we included a mouse study conducted by colleagues at Yale University, which suggested that intake of saturated fats could be an important driver of adjusted BEE. But basically, we don’t know what the cause is at the moment.

MC: What potential impacts do you believe this research could have? Do you have plans to conduct further studies?

JS: The magnitude of the effect of BEE is sufficient in mathematical models to explain the obesity increase. That doesn’t prove it was responsible, only that it could have been. It also suggests then that if we can reverse the fall, maybe that will contribute to reversing the epidemic. First, however, we have to find out what caused the fall. We have lots of studies planned that have come out of this work.

MC: Are there any limitations to this study that you wish to highlight? If so, how would you look to improve on these?

JS: The main limits are that we don’t have enough data on the individuals to reconstruct what may have been the causal factors. For example, we have no data on their diets, smoking status or infectious disease status, etc. Second, we can only speculate if this change is a driver of the epidemic. The data are cross-sectional and the link to expanding obesity levels is only a correlation.

Reference: Speakman JR, de Jong JMA, Sinha S, et al. Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure. Nat Metab. 2023;5(4):579-588. doi:10.1038/s42255-023-00782-2

Professor John Speakman was speaking to Molly Campbell, Senior Science Writer for Technology Networks.