, which have in common that they have been developed in predominantly healthy Asian subjects. Among these are the EU recommended Henry equations, and the equations of Liu et al. Ĭonsequently, improved equations have been developed in an attempt to improve estimates of BMR and reflect racial variations. Likewise, it has been shown that these equations overestimate BMR in overweight and obese populations. This explains the overestimation by the Schofield and HB equations because respectively 87 % and 100 % of the data came from Caucasian men and women. Over the years, several studies have shown that these equations overestimate BMR in tropical populations because in tropical populations BMR is 15–20 % lower compared to Europeans and Americans. Īmong the first widely used prediction equations were the equations developed by Harris and Benedict (HB) in 1918 and the FAO/WHO/UNU recommended prediction equations based on the 1985 Schofield database. Commonly, the prediction equations are based on readily available physical measures such as age, sex, height and weight. Consequently, predictive equations to estimate energy requirements are the order of the day in dietetic practice and for most clinical and inpatient care. Therefore, indirect calorimetry is not feasible in daily practice. Measurement equipment can be costly, is not widely available, requires trained personnel, and can be time consuming. It requires subjects to be at rest while being awake, fasted for at least 10 h, in a supine position, and under thermoneutral conditions. Indirect calorimetry, which is based on the measurement of oxygen consumption and carbon dioxide production, is the preferred method to accurately assess BMR. This approach to estimate energy requirements necessitates the accurate estimation of BMR in populations of different ethnicities and body weight and living under various environmental conditions. In the 1985 FAO/WHO/UNU report on human energy and protein requirements, the use of energy expenditure rather than food intake was proposed to calculate energy requirements and additionally, it was proposed that TDEE can be expressed as multiples of BMR, defined as physical activity level (PAL). Generally, BMR represents 60–80 % of total daily energy expenditure (TDEE). It represents the energy required for maintenance, necessary to sustain and maintain the integrity of vital functions and is mainly determined by the amount of lean tissue. Basal metabolic rate (BMR) was introduced to describe energy expended at rest in contrast to energy expended during physical activity and has been described as the “minimal rate of energy expenditure compatible with life”. Since the classical experiments by Lavoisier and Laplace in 1783, energy metabolism remains the central tenant of human nutrition. To date, the newly developed Singapore equation is the most accurate BMR prediction equation in Chinese and is applicable for use in a large BMI range including those overweight and obese. Cross-validation proved an accuracy rate of 80 %. For a BMI greater than 23, the Singapore equation reached an accuracy rate of 76 %. The accuracy rate (within 10 % accurate) was 78 % which compared well to Owen (70 %), Henry (67 %), Mifflin (67 %), Liu (58 %), Harris-Benedict (45 %) and Yang (37 %) for the whole range of BMI. Additionally, the newly derived equation was cross-validated in a separate group of 70 Chinese subjects (26 men and 44 women, age: 21–69 years, BMI: 17–39 kg/m 2). A regression equation was derived using stepwise regression and accuracy was compared to 6 existing equations (Harris-Benedict, Henry, Liu, Yang, Owen and Mifflin).
Continuous open-circuit indirect calorimetry using a ventilated hood system for 30 min was used to measure BMR. The aim of this study was to develop a new BMR prediction equation for Chinese adults applicable for a large BMI range and compare it with commonly used prediction equations. However, there is a paucity of data on BMR measured in overweight and obese adults living in Asia and equations developed for this group of interest. Therefore, BMR prediction equations have been developed in multiple populations because indirect calorimetry is not always feasible. Measurement of basal metabolic rate (BMR) is suggested as a tool to estimate energy requirements.
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