BMR Calculator

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What BMR is, and what it is not

Basal metabolic rate is the energy cost of staying alive with nothing else going on: heart, lungs, kidneys, liver, the constant chemical housekeeping of every cell, and a brain that alone accounts for a fifth of the total in an adult. A true basal measurement has strict conditions: an overnight fast, no exercise the day before, lying still and awake in a thermoneutral room, measured on waking. Almost nobody's BMR has ever been measured that way, including yours.

What is usually measured instead is resting metabolic rate: the same idea under practical conditions, seated or lying quietly after a short rest, not necessarily fasted overnight in a laboratory bed. RMR typically runs about 10 per cent above true BMR, which is the main reason two sources can quote the same body two different 'metabolisms' and both be right. Several of the equations on this page were published as RMR equations for exactly this reason, and the labels have been used loosely in the literature for fifty years.

BMR is also not a fixed personal constant that you can be assigned once. It tracks your fat-free mass closely (that is the single strongest predictor, better than weight, height or age individually), so it moves as your body composition moves. And crucially, it is not a target: the FAO/WHO/UNU consultation puts basal rate at 45 to 70 per cent of total daily expenditure depending on age and lifestyle, so eating at BMR means eating a long way below what you actually spend.

The five equations and where each came from

Harris and Benedict came first. Their preliminary communication appeared in the Proceedings of the National Academy of Sciences in 1918, and the full Carnegie Institution monograph the following year, built on 239 subjects (136 men and 103 women) measured by respiration calorimetry. Roza and Shizgal refitted those equations in 1984 against an expanded series of 337 measurements, and it is that revised form, not the 1919 original, that this page computes and that most calculators quietly use.

Mifflin and St Jeor published theirs in 1990 from indirect calorimetry in 498 healthy adults aged 19 to 78, roughly half of them normal weight and half obese: a deliberately modern, deliberately mixed sample, because the older equations had been fitted on a population that ate and moved differently. The simplified coefficients on this page (10 × kg, 6.25 × cm, 5 × age) are the form the authors themselves printed alongside the full regression.

Katch–McArdle and Cunningham both abandon weight in favour of fat-free mass, on the reasoning that fat tissue is close to metabolically inert while muscle and organs are not. Cunningham's 1980 paper was a reanalysis of 223 subjects drawn from the Harris and Benedict data, and concluded that lean body mass alone explained the variance that the older equations had been splitting across weight, height and age. Its form is the plainest of the set: 500 plus 22 for every kilogram of lean tissue.

Owen came last and argues the opposite case. Two papers (women in 1986, men in 1987, 44 and 60 subjects respectively) found that once you measure carefully, weight alone predicts resting metabolism about as well as more elaborate models, and produced two equations with no height or age term at all. Owen's numbers run lower than everyone else's, which is a feature rather than a fault: the authors argued the older equations systematically overestimated. The women's equation quoted here applies to the 36 non-athletes in that sample; the eight trained athletes needed a different one entirely.

Which one to trust, and when

Mifflin–St Jeor (1990) was derived from indirect calorimetry in several hundred adults and validates best across general populations; it is the default here and in most dietetic practice. The revised Harris–Benedict (Roza & Shizgal, 1984) is a modernised version of the century-old original; it remains reasonable but drifts high at higher body fat. Katch–McArdle works from lean mass instead of total weight, which makes it the sharpest choice when you actually know your body fat percentage from a decent measurement, and no better than a guess when you're guessing.

The 2005 systematic review that settled the question for most dietitians compared the published equations against measured resting metabolic rate and found Mifflin–St Jeor the most reliable, predicting within 10 per cent of measured values in more non-obese and obese individuals than any other equation, with the narrowest error range. That is the evidence behind making it the headline here, and behind the fact that almost every clinical protocol written since names it first.

The lean-mass equations earn their place in a narrower window. If your body fat percentage came from a DEXA scan, a competent multi-site skinfold or at minimum a careful tape estimate, Cunningham and Katch–McArdle correct the main blind spot of weight-based formulas: they stop treating twelve kilograms of fat and twelve kilograms of muscle as the same twelve kilograms. Cunningham reads a little above Katch–McArdle at any realistic lean mass, and is the one sports dietitians tend to prefer for lean, trained athletes. Feed either a guessed body fat figure and the apparent precision is fiction: the error of your guess passes straight through, amplified by a coefficient of about 22.

Owen is worth reading as a sanity check rather than a headline. When every other equation agrees and Owen sits 150 kcal below them, that gap is telling you how much of the other estimates rests on height and age terms fitted to a particular population. If your measured weight trend suggests your real maintenance is lower than the calculators say (which happens), Owen is often the equation that was closest all along.

What actually changes your BMR, and by how much

Fat-free mass is the dominant term, and it is why the lean-mass equations exist. Muscle costs roughly 13 kcal per kilogram per day at rest in the standard organ-and-tissue estimates, while stored fat costs around 4.5: real, but a fraction of it. Organs are the expensive part: the brain, liver, heart and kidneys together make up a small share of body weight and a large share of basal expenditure, which is why very small adults have a higher BMR per kilogram than very large ones.

Age lowers the number in every equation, but the mechanism matters more than the coefficient. Most of the decline is lost muscle and reduced activity rather than an intrinsic metabolic slowdown, which is why a 60-year-old who has kept their lean mass reads much closer to their younger self than the age term alone predicts.

Illness and hormones move it in both directions and sometimes sharply. An overactive thyroid can raise resting expenditure substantially, an underactive one lowers it; fever raises it; major burns, sepsis and trauma raise it enough that clinical practice applies explicit stress factors on top of a predicted BMR. Some psychiatric and hormonal medications lower it. None of these are captured by a formula that sees only height, weight, age and sex.

Extreme dieting lowers it too, though less than folklore claims. Sustained severe restriction produces a measurable drop beyond what the loss of body mass alone predicts (typically in the range of 5 to 15 per cent, through reduced sympathetic tone and improved muscular efficiency), and it largely recovers when energy intake returns to maintenance. What it does not do is permanently break your metabolism. The far bigger and more permanent effect is losing lean mass, which is the argument for protein and resistance training during any cut.

• A kilogram of skeletal muscle: about 13 kcal a day at rest. A kilogram of fat: about 4.5.
• Ageing: most of the fall is lost lean mass and lost movement, not an intrinsic slowdown.
• Thyroid disease, fever, burns, sepsis and some medications: real shifts a formula cannot see.
• Severe dieting: a 5–15% adaptive drop that largely reverses; lost muscle is the lasting cost.

What the 2021 doubly-labelled-water study found about metabolism across life

The best evidence we have on how energy expenditure really behaves over a lifetime came in 2021, when a consortium pooled doubly-labelled-water measurements (the gold standard for total energy expenditure in free-living people) on 6,421 individuals from 29 countries, aged from eight days to 95 years. Doubly-labelled water is expensive enough that no single study could ever assemble that sample; the database was built by combining decades of them.

The findings rearranged a lot of received wisdom. Expenditure per kilogram of fat-free mass climbs rapidly after birth to peak at roughly 50 per cent above adult values at about one year of age, then declines slowly through childhood and adolescence. From about age 20 it is essentially flat: adjusted total energy expenditure holds steady through the twenties, thirties, forties and fifties, and the analysis found it stable even during pregnancy. Only after about 60 does it fall, and then by roughly 0.7 per cent a year.

That matters for how you read a BMR result. The 'metabolism collapses at 40' story does not survive the data: what collapses is usually lean mass and daily movement, both of which are partly under your control and both of which the equations see only indirectly, through weight and an age coefficient. It also means an age term in a prediction equation is doing something slightly dishonest (encoding a population trend that is largely a composition trend), which is one more reason the lean-mass equations are worth running when you have a real body fat figure to feed them.

Why eating at your BMR is not a plan

This is the single most common misuse of the number on this page. BMR is the floor of what your body spends, not a budget for what you should eat. Basal rate is 45 to 70 per cent of total daily expenditure depending on age and lifestyle, so eating at BMR means running a deficit of anywhere from a third to a half of your intake, far past the point where the losses stop being mostly fat.

What that produces is predictable: fatigue, poor training quality, disproportionate loss of lean tissue, disrupted sleep and hormones, and an adherence failure that arrives faster than the weight loss does. It is also unnecessary. A cut planned at 10 to 20 per cent below total expenditure produces fat loss at a rate that can be sustained for months, and this site refuses to plan anything deeper: the deficit calculator holds every target at 80 per cent of your own expenditure and at absolute floors of 1,500 kcal for men and 1,200 kcal for women, with the rails written into the calculation code rather than into a warning nobody reads.

The right use of a BMR figure is as an input. Multiply it by an activity factor to get total daily expenditure, take a percentage off that for a cut or add a percentage for a gain, then let three or four weeks of honest weight data tell you how wrong the estimate was. The table under your result does the first step for you at all five activity factors, and links through with your numbers already filled in.

Where BMR is used clinically

In hospitals, a predicted basal rate is the starting point for prescribing nutrition support. Enteral and parenteral feeding regimens are written in kilocalories per day, and in the absence of a metabolic cart the number comes from an equation plus an adjustment for illness: stress factors for burns, sepsis, trauma and major surgery, and a downward eye on patients at risk of refeeding syndrome, where feeding too fast after prolonged starvation is dangerous in its own right. Critical care is also where prediction equations perform worst, which is why guidelines push for measured calorimetry when a ventilated patient's requirements really matter.

Outside intensive care the same arithmetic appears in bariatric surgery follow-up, in the management of eating disorders where an energy prescription is part of a supervised treatment plan, in oncology and cystic fibrosis where maintaining weight is a clinical goal in itself, and in endocrinology as a sanity check when a patient's weight trajectory and reported intake do not reconcile. In each case the predicted figure is a starting hypothesis that gets corrected by measured weight change, the same discipline this page recommends for a person at home with a set of scales.

It also shows up in research and in policy: energy intakes reported in dietary surveys are routinely checked against predicted basal rate to detect implausible under-reporting, which is endemic in self-reported food diaries and is the reason nutrition researchers treat an intake below about 1.35 times predicted BMR with suspicion. When a calculator tells you that your logged intake is below your basal rate and you are not losing weight, that same arithmetic is quietly pointing at the food diary.

How it's calculated

Worked example: a man of 42, 180 cm and 85 kg, with a measured 22% body fat

1. Mifflin–St Jeor for men: 10 × 85 = 850, plus 6.25 × 180 = 1,125, minus 5 × 42 = 210, plus 5 → 1,770 kcal per day. That is the headline, about 7,406 kJ.
2. Revised Harris–Benedict: 88.362 + 13.397 × 85 (= 1,138.7) + 4.799 × 180 (= 863.8) − 5.677 × 42 (= 238.4) → 1,852 kcal, which the page rounds to 1,850.
3. Work out lean mass for the two lean-mass equations: 85 kg × (1 − 0.22) = 66.3 kg of lean tissue, and 18.7 kg of fat.
4. Katch–McArdle: 370 + 21.6 × 66.3 = 370 + 1,432 → 1,802 kcal, shown as 1,800.
5. Cunningham: 500 + 22 × 66.3 = 500 + 1,459 → 1,959 kcal, shown as 1,960, the highest of the five, as it usually is.
6. Owen for men: 879 + 10.2 × 85 = 879 + 867 → 1,746 kcal, shown as 1,750, the lowest, as it usually is.
7. Read the spread: the three BMR equations span 1,770 to 1,850 kcal, about 80 kcal apart; across all five the range widens to 1,750–1,960, a spread of roughly 210 kcal. That range is the honest answer, not any one number in it.
8. Turn the headline into a daily total: 1,770 × 1.2 = 2,120 kcal sedentary, × 1.375 = 2,430 lightly active, × 1.55 = 2,740 moderately active, × 1.725 = 3,050 very active, × 1.9 = 3,360 extra active.
9. Note what eating at BMR would mean: at a moderately active 2,740 kcal, eating 1,770 is a 35% deficit, roughly twice the deepest cut this site will plan.

Where this number is used in the real world

• Hospital nutrition support, where a predicted basal rate plus a stress factor sets the energy in an enteral or parenteral feeding regimen.
• Critical care, as a fallback when indirect calorimetry is unavailable, with the explicit caveat that this is the population in whom prediction equations perform worst.
• Refeeding after prolonged undernutrition, where the risk runs in the opposite direction and energy is introduced cautiously under supervision.
• Bariatric surgery follow-up and supervised weight management, to track whether measured requirements are falling faster than body mass alone would predict.
• Sports nutrition, where Cunningham on measured lean mass is the usual starting point for setting an athlete's maintenance intake.
• Dietary survey research, where reported energy intakes below about 1.35 times predicted BMR are flagged as implausible under-reporting.
• Everyday self-tracking, as the first term in a calorie target that then gets calibrated against three or four weeks of real weight data.

Frequently asked questions

Keep going

A single number rarely tells the whole story. Alongside the BMR result, the TDEE calculator, the lean body mass calculator, the calorie deficit calculator, the macros calculator and the FFMI calculator each add a different angle on the same measurements. For the reasoning behind the numbers, read TDEE explained, Track without DEXA and BMI vs body fat vs waist.

Sources

1. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr 1990;51:241–7. doi.org/10.1093/ajcn/51.2.241
2. Roza AM, Shizgal HM. The Harris Benedict equation reevaluated: resting energy requirements and the body cell mass. Am J Clin Nutr 1984;40:168–82. doi.org/10.1093/ajcn/40.1.168
3. Harris JA, Benedict FG. A biometric study of human basal metabolism. Proc Natl Acad Sci USA 1918;4:370–3 (preliminary communication; the full data appeared in the 1919 Carnegie Institution monograph). doi.org/10.1073/pnas.4.12.370
4. Cunningham JJ. A reanalysis of the factors influencing basal metabolic rate in normal adults. Am J Clin Nutr 1980;33:2372–4. doi.org/10.1093/ajcn/33.11.2372
5. Owen OE, Kavle E, Owen RS, et al. A reappraisal of caloric requirements in healthy women. Am J Clin Nutr 1986;44:1–19. doi.org/10.1093/ajcn/44.1.1
6. Owen OE, Holup JL, D'Alessio DA, et al. A reappraisal of the caloric requirements of men. Am J Clin Nutr 1987;46:875–85. doi.org/10.1093/ajcn/46.6.875
7. Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc 2005;105:775–89. doi.org/10.1016/j.jada.2005.02.005
8. Pontzer H, Yamada Y, Sagayama H, et al. Daily energy expenditure through the human life course. Science 2021;373:808–12. doi.org/10.1126/science.abe5017
9. FAO/WHO/UNU. Human energy requirements: report of a joint FAO/WHO/UNU expert consultation. Rome, 2004. www.fao.org/4/y5686e/y5686e00.htm