The (Surprisingly Wide) Range of BMRs in Adults

Now that we’ve completed our BMR series, culminating in the release of our new BMR calculator, I think it’s time to zoom out and address a big-picture question: just how variable are human BMRs?

Based on my time in the fitness industry talking with other professionals, working with clients, and generally monitoring the chatter of people online, I think most people tacitly think that human BMRs fall within a relatively narrow range. Very frequently, I’ll see the idea floated that the average female BMR is around 1400 Calories, the average male BMR is around 1800 Calories, and it’s very rare for BMRs to fall outside the range of 1,200-2,200 Calories per day.

There’s a bit of truth to that idea … but only a bit. It is true that most BMRs fall between 1200 and 2200 Calories per day, but it’s not particularly uncommon for BMRs to fall outside of that range. And, at the extremes, BMRs can be much lower than 1,200 Calories per day, and much higher than 2,200 Calories per day.

Starting with the extremes, you can find published instances of BMRs below 800 Calories per day (in the case of patients with anorexia), or exceeding 3700 Calories per day (in the case of extremely muscular athletes).

But, we don’t even need to look at the extremes to see BMRs that fall below 1,200 Calories per day, or that exceed 2,200 Calories per day. For this point, let’s turn our attention to two large, high-quality studies by Mifflin et al and Pavlidou et al. Both of these studies assessed BMR in large samples of people who were more-or-less representative of people in the general population. The subjects in the Mifflin study were a little lighter, on average, than people today (since the study was from 1990), and the subjects in the Pavlidou study were a little heavier, on average, than most folks, so blending these two studies should give us a pretty good overview of the “normal” range of BMR values.

In the Mifflin study, the lowest female BMR was 927 Calories, and the lowest male BMR was 1030 Calories. In the Pavlidou study, the lowest female BMR was 908 Calories, and the lowest male BMR was 1039 Calories.

Similarly, the highest female BMR in the Mifflin study was 2216 Calories, and the highest male BMR was 2849 Calories. In the Pavlidou study, the highest female BMR was 2492 Calories, and the highest male BMR was 2595 Calories.

So, even within the general population, it’s not unheard of for women to have BMRs below 1000 Calories per day, and for men to have BMRs below 1100 Calories per day, nor is it unheard of for women to have BMRs exceeding 2200 Calories per day, and for men to have BMRs exceeding 2500 Calories per day.

But, even then, you could say that we’re no longer dealing with the extremes of extreme populations, but we are still focusing on extremes (the highest and lowest values) within more “normal” populations. So, let’s go one step further.

We can estimate how common or how rare an observation should be if we know the statistical distribution describing those observations. In other words, for data that’s roughly normally distributed (which BMR data is), if we know the mean and standard deviation describing the data, we can estimate how common or uncommon an occurrence should be, using the normal probability density function.

In the Mifflin study, women had BMRs of 1348 ± 214 Calories (mean ± standard deviation), and men had BMRs of 1776 ± 297 Calories. In the Pavlidou study, women had BMRs of 1533 ± 308 Calories, and men had BMRs of 2006 ± 346 Calories. When we pool the results of these two studies, we get the following distributions: for women, 1440 ± 280 Calories; for men, 1890 ± 340 Calories; and for both sexes combined, 1665 ± 380 Calories.

With that information, we can estimate how frequently we should observe various high or low BMR values. Of note, we shouldn’t extrapolate too far since we don’t know the precise skewness and kurtosis values for these samples, but any values within 1.5-2 standard deviations from the mean should be relatively common. Since these are likely skew right distributions (there’s simply a lot more room for BMR values to be very high than very low, because there’s a much larger size difference between the largest people and average-sized people than between the very smallest people and average-sized people), I’ll roughly define the “normal” range as values between 1.5 standard deviations below the mean, and 2 standard deviations above the mean. In other words, if you were in a room with 100 people, you should expect to find a handful people with BMRs below the bottom end of these ranges, or above the top end of these ranges.

So, even when conservatively describing the range of normal BMR values, it becomes clear that BMRs below 1200 Calories or above 2200 Calories per day aren’t terribly uncommon. A BMR of 1200 Calories per day is a little less than 1 standard deviation below the mean for women, and a BMR above 2200 calories per day is a little less than 1 standard deviation above the mean for men. Stated another way, you should expect approximately 1 in 5 women to have a BMR below 1200 Calories per day, you should expect about 1 in 5 men to have a BMR above 2200 Calories per day, and you should expect about 1 in 5 people to have a BMR below 1200 Calories per day or above 2200 Calories per day.

Of course, this is all still one step removed from being useful and applicable for you. It might be nice to learn about the range of human BMRs generally, but you’re probably a bit more interested in the likelihood that you have a particularly high or low BMR. Clearly, BMRs below 1200 Calories per day are going to be more common for smaller people, and BMRs above 2200 Calories per day are going to be more common for larger people.

Thankfully, we can model that easily enough. For the charts below, I used the weight-based version of the Oxford/Henry BMR formula to model average BMR as a function of weight. From there, based on the data discussed in this article, I assumed that the distribution of differences between actual and predicted BMR values has a standard deviation of 200 Calories. Finally, all that was left to do was calculate the probability of having a BMR below 1200 Calories, above 2200 Calories, or between 1200 and 2200 Calories per day at each body weight using normal probability density functions.

I realize these graphs are a bit busy, but these are some key points and landmarks:

1. It’s very uncommon for women to have BMRs above 2200 Calories per day, but BMRs below 1200 should be relatively common at lower body weights.
2. Women who weigh 65kg have a ~1-in-5 chance of having a BMR below 1200, with the likelihood increasing at even lower body weights. Other landmarks: at 80kg, there’s only a ~1-in-20 chance, but at 50kg, it’s closer to a 50/50 proposition (i.e., 1200 Calories is an average BMR for 50kg women).
3. BMRs below 1200 Calories are considerably less common for men, but also aren’t terribly uncommon at body weights below 60kg.
4. BMRs above 2200 Calories are considerably more common for men. 100kg men have a ~1-in-5 chance of having a BMR above 2200 Calories per day, and above 115kg, most men should expect to have BMRs above 2200 Calories per day.
5. The body weights at which you’re the least likely to have a BMR below 1200 or above 2200 Calories per day: about 100kg for women and about 75kg for men.

To wrap this article up, I wanted to state my main reason for writing it: I think a lot of people wind up confused, frustrated, and disappointed because they underestimate the variability of human physiology. If you think that we’re all extremely similar, then it’s easy to spin your wheels trying to follow standard advice and heuristics that don’t apply quite as broadly as most people assume. And, if you fall outside the “normal” range, it’s easy to think that there’s something wrong with you, especially if you’ve been led to believe that the “normal” range describes >99% of individuals. But in this case, the “norms” don’t describe >99% of individuals – they apply to about 80%. It’s not at all uncommon to have a BMR below 1200 calories per day, or above 2200. About 1 in 5 people fall outside that range (especially women who are a bit smaller than average, or men who are a bit larger than average). So, standard weight loss or weight gain advice and heuristics tailored to the “average” person frequently don’t apply to a lot of people. Understand it, embrace it, and don’t be afraid of a bit of self-experimentation.