![]() The Henry Oxford equation is among the ‘newer’ equations and uses weight as the primary predictor of RMR. Therefore, when deciding on which is most fit for your client, it is worthwhile to consider the researchers’ initial objectives while developing the equation, and the profile of the original study cohort. Most formulas have used large cohorts of people as the basis of their predictive analyses. What do their age, weight, height and BMI look like? Our client summary tool will give you a nice overview of the aforementioned. While it quickly becomes clear that there are multiple factors you’ll need to consider when choosing an energy calculation formula, let’s start with the basics for now.įirstly, you’ll want to determine who your client is. Some studies have also suggested that hormones such as leptin, triiodothyronine and thyroxine may also play a significant role.An accurate assessment of RMR and EER should never be conducted without the consideration of all relevant conditions. ![]() Chronic health conditions are known to increase a patient’s energy requirements. If available, utilisation of your client’s fat free mass in your RMR calculations is highly advisable. Physical activity can greatly influence body composition and weight and thus, RMR. Research has suggested that RMR drops approximately 2% per decade. On average, men have a greater lean mass than women. Genetics, particularly race or ethnicity.Previous research has shown that RMR can vary significantly between individuals.
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