You can measure your resting metabolic rate (RMR) in two main ways: a clinical breath test called indirect calorimetry, which is the gold standard, or a predictive equation that estimates RMR from your age, weight, and height. The clinical test is more accurate, but a well-chosen equation gets within 10% of the measured value for most people.
What RMR Actually Measures
Your resting metabolic rate is the number of calories your body burns just to keep you alive while you’re awake and at rest. That includes breathing, circulating blood, maintaining body temperature, and running your brain. For most people, RMR accounts for the largest chunk of total daily calorie needs, often 60% to 75%, which is why it matters so much for anyone trying to manage their weight or fuel their training.
RMR is sometimes used interchangeably with basal metabolic rate (BMR), but they’re slightly different. BMR has stricter testing conditions: it’s measured first thing in the morning after an overnight fast, 24 hours without exercise, and complete rest. RMR allows a bit more flexibility, requiring only about 12 hours without exercise and a minimum of 15 minutes of quiet rest before the test begins. In practice, the two numbers are very close, and RMR is far more commonly tested because the conditions are easier to meet.
The Clinical Breath Test (Indirect Calorimetry)
Indirect calorimetry measures how much oxygen you breathe in and how much carbon dioxide you breathe out. The ratio between those two gases reveals which fuels your body is burning (carbohydrate vs. fat) and how many calories it takes to keep you running at rest. A device then converts those gas measurements into a daily calorie number using a standard formula. This is the most accurate way to determine your personal RMR.
During the test, you typically lie down or sit in a comfortable chair while breathing into a mouthpiece or under a clear plastic canopy (hood) that covers your head. The test lasts about 15 to 30 minutes. It’s painless and passive. You just breathe normally while the machine does the work.
You can find indirect calorimetry testing at university sports performance labs, dietitian offices, some hospitals, and metabolic testing clinics. Prices generally range from $75 to $250 depending on the facility and location.
How to Prepare for the Test
Preparation matters. If you show up after a workout or a large meal, the results won’t reflect your true resting rate. UC Davis Health recommends these guidelines:
- Fasting: No food, caloric beverages, or caffeine for at least 6 hours before the test. Water is fine.
- Don’t over-fast: Going longer than 16 hours without eating can actually raise your metabolic rate by triggering a stress response.
- No exercise: Skip your workout the morning of your appointment.
- Minimize stress: Avoid intense physical or mental stress the day before testing, including heavy training sessions.
The room should also be at a comfortable, neutral temperature. For a lightly clothed person, the thermoneutral zone where your body doesn’t have to work extra to stay warm or cool itself falls roughly between 25°C and 33°C (about 78°F to 91°F). Most testing facilities control for this, but it’s worth knowing that being cold or overheated during the test will skew results upward.
Estimating RMR With Predictive Equations
If clinical testing isn’t accessible or affordable, predictive equations offer a reasonable alternative. These formulas use some combination of your age, sex, weight, and height to estimate RMR. Several have been developed over the past century, and they vary in accuracy.
The Mifflin-St Jeor equation is the most commonly recommended for the general population. In a validation study of women across a range of body sizes, it predicted RMR within 10% of the measured value in about 71% of participants, with an average group-level error of essentially zero. That makes it the best general-purpose option, though it still produces clinically meaningful errors in roughly one out of three people.
The formulas look like this:
- Men: (10 × weight in kg) + (6.25 × height in cm) − (5 × age in years) + 5
- Women: (10 × weight in kg) + (6.25 × height in cm) − (5 × age in years) − 161
The result is your estimated RMR in calories per day. For a 35-year-old woman who is 165 cm tall and weighs 65 kg, that comes out to about 1,354 calories per day.
Which Equation Works Best for Athletes
Athletes and highly muscular individuals are a special case because standard equations don’t account for the extra calorie-burning tissue they carry. A systematic review with meta-analysis in Sports Medicine found that no single equation is universally best for athletes, but the Ten-Haaf equation (which uses age, weight, and height) was the most accurate and precise overall. It predicted RMR within 10% of measured values for about 80% of athletes, compared to 41% to 64% for other common equations.
Five equations performed without statistically significant bias in athletes: the Cunningham equation (which requires knowing your lean body mass), the Harris-Benedict equation, two versions of the Cunningham formula, and the Ten-Haaf equation. However, the Harris-Benedict equation showed a tendency to underestimate RMR in heavier male athletes, so it should be used cautiously in that group.
If you know your body fat percentage, the Cunningham equation is worth considering because it’s built around lean mass rather than total body weight. But if you don’t have that data, the Ten-Haaf equation using basic measurements appears to be the most reliable choice for active people.
Consumer Devices and Wearables
Fitness wearables like Apple Watch, Garmin, and Polar watches estimate daily calorie burn, but their accuracy for resting metabolic rate specifically is limited. A systematic review found that Apple and Polar wearables overestimated energy expenditure the majority of the time (58% and 69% of measurements, respectively), while Garmin and Withings devices underestimated it in about 69% to 74% of cases. These devices rely on algorithms built from heart rate, movement data, and user-entered profile information rather than direct metabolic measurement, so their estimates are best treated as rough ballparks.
A newer category of home-use metabolic devices has emerged, including products like Lumen, which measures the carbon dioxide concentration in your breath. Research published in the Journal of the International Society of Sports Nutrition found that the Lumen device could detect changes in fuel use after high-carbohydrate meals and track weekly shifts in response to dietary changes. These portable devices offer more metabolic insight than a wristband, but they remain limited compared to full indirect calorimetry systems that measure both oxygen consumption and carbon dioxide output simultaneously. They’re currently better suited for tracking trends in fuel use (fat vs. carbohydrate burning) than for providing a precise RMR number.
Why Your RMR Might Differ From Predictions
Body composition is the biggest variable that equations can’t fully capture. Skeletal muscle burns roughly 10 to 15 calories per kilogram per day at rest, while fat tissue burns much less. Muscle contributes about 20% of your total daily energy expenditure compared to just 5% from fat tissue (in someone with around 20% body fat). Two people who weigh the same but carry different amounts of muscle will have meaningfully different resting metabolic rates, and weight-based equations can’t distinguish between them.
Other factors that shift RMR include thyroid function, recent weight loss (which can temporarily suppress metabolic rate), chronic stress, sleep quality, and certain medications. Age plays a role too, partly because people tend to lose muscle as they get older. If you suspect your metabolism is unusually slow or fast, a clinical test is the only way to get a definitive answer rather than relying on a population average.
Choosing the Right Method
For most people trying to set a calorie target for weight loss or gain, the Mifflin-St Jeor equation is a solid starting point. It’s free, takes 30 seconds, and is accurate enough to guide initial decisions. If you’re an athlete or have an unusually high or low body fat percentage, the Ten-Haaf or Cunningham equations will likely give you a better estimate.
If you’ve been eating at what should be a deficit and not losing weight, or if you’re an athlete trying to optimize performance nutrition, investing in a clinical indirect calorimetry test is worth it. Having a measured number removes the guesswork and gives you a reliable baseline to build your nutrition plan around. One test is usually enough unless your body composition changes significantly.