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Unduly influenced by any overrepresented subpopulations. This is a much larger population than the samples used to develop other popular BMR equations using height, weight, and age, such as the Harris-Benedict equation (239 subjects), the revised Harris-Benedict equation (337 subjects), and the Mifflin-St Jeor equations (498 subjects).Since the Oxford/Henry equations were developed, a meta study found that the Oxford/Henry equations had the best combination of low error (small average deviations between measured and predicted BMRs) and low bias (not systematically over- or under-estimating BMR in particularly large or particularly small people) across both sexes. Similarly, another huge study with nearly 17,000 subjects found that the Oxford/Henry equations were among the best-performing equations for people in all BMI categories. Finally, a 2022 meta-analysis found that the FAO/WHO/UNU equations performed best in people with overweight and obesity, but that review included relatively few studies that used the Oxford/Henry equations. However, BMR estimates provided by the FAO/WHO/UNU equations and the Oxford/Henry equations tend to converge at higher body weights and BMIs (in other words, if the FAO/WHO/UNU equations perform well in people with obesity, the Oxford/Henry equations do too).Overall, in most populations, the Oxford/Henry equations are the best BMR equations based on height, weight, age, and sex.Cunningham, 1991Much like the Oxford/Henry equations, the 1991 version of the Cunningham equation is the result of synthesizing data from multiple other studies. Cunningham had first developed an equation for estimating BMR from fat-free mass in 1980. In the intervening decade, more research groups investigated the relationship between fat-free mass (FFM) and BMR, allowing Cunningham to systematically analyze the results from a total population of 1482 subjects. The studies included both males and females, with a pretty even mix of lean and obese subjects.Subsequent research has supported the validity of the 1991 Cunningham equations. For instance, a decade after Cunningham’s study, Wang and colleagues analyzed the FFM/BMR relationship in the published research (which included another seven studies that came out after Cunningham’s equation was published). It was a somewhat less rigorous analysis – I don’t believe they applied weightings based on the number of subjects in each study – but it found that the “average” equation to predict BMR from FFM was BMR = 21.5 * FFM + 407, which is practically indistinguishable from Cunningham’s equation.Furthermore, they modeled the theoretical relationship between FFM and BMR that was revealed from animal research spanning a range of 7 orders

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Of magnitude; when scaled to body size, metabolic rates are shockingly consistent and predictable between species. Wang and colleagues found that the theoretical relationship between FFM and BMR in animals of all sizes could be modeled with this equation: BMR = 21.7 * FFM + 3742. Again, that’s virtually indistinguishable from the 1991 Cunningham equation.Finally, to lend support to both the 1991 Cunningham equation and the Oxford/Henry equations, both equations produce comparable BMR estimates. Essentially, if the Oxford/Henry equations are good, and the 1991 Cunningham equation produces similar estimates, that suggests that the 1991 Cunningham equation is also pretty good (and vice versa). Using the NHANES body composition cohort, I calculated the estimated BMR for all participants using both the Oxford/Henry equations and the 1991 Cunningham equation. They produced estimates that differed by less than 100 Calories, on average.Which equation should you use?If both the Oxford/Henry and the 1991 Cunningham equation are generally good, and typically produce similar BMR estimates, which one should you use?If you don’t have a decent idea of your body composition, the Oxford/Henry equations are probably the way to go. However, if you do have a pretty good idea of your body composition, the 1991 Cunningham equation is likely the better option. Fat-free mass is by far the most important predictor of BMR. Equations like the Oxford/Henry equations work well because sex, height, and weight are reliably associated with fat-free mass. So, in essence, the Oxford/Henry equation is tacitly predicting your fat-free mass to then predict your BMR. But, if you think you can estimate your body-fat percentage with a reasonable degree of accuracy (within about 5% or so), using the 1991 Cunningham equation essentially lets you go “straight to the source,” and estimate BMR directly from FFM.Ultimately, the choice of equation shouldn’t make that large of a difference for most people, most of the time. There are a few exceptions, however.First, if you think your body-fat percentage is considerably higher or considerably lower than average for people of your age, height, weight, and sex, the 1991 Cunningham equation is likely a much better option than the Oxford/Henry equations. If you’re 15% body fat, and the average person of your height, weight, age, and sex is 30% body fat, the Oxford/Henry equations would likely underestimate your BMR.Second, if you’re over 60 years old, the Oxford/Henry equation corresponding to your age and sex is probably the better