What Determines Your Basal Metabolic Rate?

Your basal metabolic rate (BMR) tells you how much energy your body burns to just “keep the lights on” – it’s the energy used to power the basic functions of your vital organs, to accomplish sufficient protein and cell turnover to keep your tissues functioning properly, etc. If you didn’t leave your bed all day and didn’t move a muscle, your basal metabolic rate is the amount of energy you’d still burn in a day.

When you look at the equations used to estimate BMR (you can read more about the best BMR equations here), you’ll find that almost all of them predict your BMR based on either 1) your age, height, weight, and sex, or 2) the amount of fat-free mass you have. But, those factors are merely associated with basal metabolic rate. They’re used to estimate BMR because they’re characteristics that are relatively easy to measure or estimate, and they’re predictive of the actual determinants of BMR.

So, what are the actual determinants of BMR?

1. Body composition (but not in the way you’d probably expect)
2. The specific metabolic rates of your body’s various tissues

Each tissue in your body has its own basal metabolic rate. Some tissues require a lot of energy to function normally, while others require very little. You’ve probably heard that “muscle burns more calories than fat,” and that’s technically true, but it matters less than you likely expect.

Your muscles have a tissue-specific BMR of about 13 Calories per kilogram, and your fat tissue has a BMR of about 4.5 Calories per kilogram. So, if you lost 10kg of fat and gained 10kg of muscle, you’d experience an enormous change in “big picture” body composition, but your BMR would only be expected to increase by about 85 Calories per day. That’s not nothing, but it’s also not a dramatic change.

The real metabolic heavy hitters are your heart, kidneys, brain, and liver.

In contrast to your muscle and fat tissue, your heart and kidneys have a BMR of about 440 Calories per kilogram, your brain has a BMR of about 240 Calories per kilogram, and your liver has a BMR of about 200 Calories per kilogram. Collectively, they generally account for less than 5% of total body mass, while typically accounting for more than 50% of your total BMR. 

So, when I say that body composition is one of the determinants of BMR, I don’t just mean that body-fat percentage or total fat-free mass are direct determinants of BMR. Rather, I mean that the actual granular composition of your body determines your BMR. If two people weigh 75kg and have 60kg of fat-free mass, but one of them has kidneys, a liver, and a heart that are 20% larger than average, and the other has kidneys, a liver, and a heart that are 20% smaller than average (comfortably within the range of normal inter-individual variability), their “big-picture” body composition would be the same, but a granular assessment of the tissues composing their body would reveal considerable differences in body composition. As a result, these two people would be expected to have BMRs that differed by about 230 Calories per day. In other words, slight variations in organ mass can have almost a 3-times larger impact on BMR than losing 10kg of fat and gaining 10kg of muscle. 

As mentioned in a previous article, even the best BMR prediction equations using factors like age, sex, height, weight, age, and fat-free mass have the potential to under- or over-estimate BMR by at least 300-400 Calories per day. These equations work as well as they do (producing reasonable ballpark estimates for most people) because age, sex, height, weight, age, and/or fat-free mass are associated with granular body composition – males, younger people, larger people, and people with more fat-free mass have more total tissue, and they also tend to have more “high metabolic rate” tissue.

But, on the flip side, these equations can sometimes significantly over- or under-estimate BMR because all of those factors are more strongly predictive of low-metabolic-rate tissue mass than high-metabolic-rate tissue mass. In other words, if I know your body mass and have a rough idea of your body-fat percentage, I can estimate how much fat mass you have with reasonable accuracy, and I can predict how much muscle mass you have with a high degree of accuracy. And, since those tissues don’t burn very much energy at rest, any errors in my ability to estimate your total fat mass and total muscle mass would have a relatively small impact on my ability to estimate your basal metabolic rate. But, I wouldn’t be able to predict your heart, brain, kidney, and liver mass with nearly as much accuracy. Since those tissues do burn a ton of energy at rest, any errors in my ability to estimate your organ masses would have a relatively large impact on my ability to estimate your basal metabolic rate.

However, in studies where researchers perform MRIs to estimate organ volume and organ mass, they can estimate BMR far more accurately. Instead of having a typical error of about 150-200 Calories, with the largest errors exceeding 400 Calories, the typical error shrinks to 60-100 Calories, and the largest errors rarely exceed 150-200 Calories. In other words, by more precisely estimating organ masses using MRI, instead of (tacitly) very roughly estimating organ masses using factors like height, weight, age, sex, and total fat-free mass, you can predict BMR with about 2-2.5-times more accuracy. This same general principle applies to estimating changes in BMR with weight loss.

From there, the remaining errors are primarily due to differences in organ-specific BMRs (your kidneys may burn 5% more energy per unit of mass than someone else’s kidneys, for instance), and errors in estimating organ masses from MRIs, but there’s not THAT much error left to account for.

So, here are the basic takeaways:

1. Your BMR is determined by your granular body composition, and the specific metabolic rates of the tissues composing your body.
2. So, by estimating someone’s BMR, you’re functionally making predictions about their granular body composition.
3. Variance in the size of high-metabolic-rate tissues, like the brain, liver, kidneys, and heart, has a much larger impact on BMR than variance in low-metabolic-rate tissues like muscle, fat, and bone.
4. Factors like age, sex, height, weight, and total fat-free mass are more predictive of low-metabolic-rate tissue mass than high-metabolic-rate tissue mass. So, it should be unsurprising that even the best BMR equations can sometimes significantly under- or overestimate BMR.

Before wrapping up, I’d like to point out a fun fact about body size and granular body composition that’s baked into BMR prediction equations.

As you’ll recall from from a previous article, the 1991 Cunningham equation predicts BMR using this formula:

BMR = 21.6 × Fat-Free Mass (kg) + 370

So, you might ask, “where does the  ‘+ 370’ come from?” Literally, it would imply that someone with 0kg of fat-free mass would still have a BMR of 370 Calories per day. Obviously that’s not the case – a prediction equation really only needs to “work” within a range of reasonable values, and most adults have at least 30-35kg of fat-free mass. But, it also (and much more reasonably) implies that BMR per unit of fat-free mass decreases as fat-free mass increases.

To illustrate, this formula would predict that someone with 40kg of fat-free mass would have a BMR of 1234 Calories per day: 30.85 Calories per kilogram of fat-free mass. Similarly, it would predict that someone with 80kg of fat-free mass would have a BMR of 2098 Calories per day: 26.23 Calories per kilogram of fat-free mass.

So, is that actually true? Does this formula accurately reflect reality?

Yep! A 2002 study by Heymsfield and colleagues illustrates this well. In a sample of 289 subjects, BMR was positively associated with fat-free mass (more fat-free mass = higher BMR), but BMR per kilogram of fat-free mass was negatively associated with fat-free mass (more fat-free mass = lower BMR per unit of fat-free mass).

Furthermore, they found that as fat-free mass increased, more and more fat-free mass came from low-metabolic-rate tissues (muscle, bone, and the lean component of adipose tissue).

A 2011 study by Müller and colleagues lets us extend these findings further. The researchers used MRI to assess the granular body composition of 262 subjects, allowing us to model out how high-metabolic-rate tissue mass changes as fat-free mass changes. The findings illustrate that the percentage of your fat-free mass comprised of high-metabolic-rate tissues (brain, heart, liver, and kidneys) is expected to decrease as total fat-free mass increases, primarily due to the brain and liver accounting for smaller percentages of total fat-free mass.

So, you now know what actually determines your basal metabolic rate: your granular body composition, and the specific metabolic rates of the individual tissues composing your body. You also now know why BMR per unit of fat-free mass generally decreases as fat-free mass increases, and you know what accounts for most of the potential for error in standard BMR equations: ultimately, it mostly comes down to your high-metabolic-rate organs. Factors like height, weight, age, sex, and fat-free mass can’t predict the masses of high-metabolic-rate tissues as accurately as they can predict the masses of low-metabolic-rate tissues, but those high-metabolic rate tissues account for most of your BMR. Furthermore, high-metabolic-rate tissues account for less and less of your total fat-free mass as fat-free mass increases.

Other articles in this series will dig deeper into this topic, discussing how factors like age and sex impact BMR, why athletes have higher BMRs (it’s not just a matter of having more muscle mass!), and how weight gain and weight loss affect your BMR. After that, we’ll explore how we can use all of this information to improve on the (current) best BMR prediction equations. You can also try our BMR calculator, which incorporates all of the information covered in this series, in order to estimate your BMR as accurately as possible.