New predictive model may be suitable for predicting RMR in Singaporeans

A new equation developed by a team of researchers to accurately predict resting metabolic rate (RMR) in Singaporeans outperformed the Harris-Benedict equation (HBE).

“Prediction equations for RMR are valuable in managing patients’ weight; however, no accurate equation exists for Singaporeans … The new regression model we have formulated appears to be well-suited for use in healthy adults, primarily Chinese Singaporean women, as it offers several advantages over the HBE,” said the investigators.

“Specifically, it comprises easy-to-calculate variables that have a strong physiological link to RMR, has a sound statistical basis, and is free of the substantial fixed error inherent in the classical HBE,” they added.

Using indirect calorimetry (IC) as reference method, the team aimed to develop and cross-validate a predictive regression equation for RMR in Singaporeans. Its performance was assessed using OLP* regression and Bland-Altman analysis. Internal cross-validation was done using PRESS* statistics. To compare this new model with existing equations, the performance of the HBE was also assessed. A total of 104 healthy Singaporeans participated (67 percent female), 93 of whom were Chinese. [Proceedings of Singapore Healthcare 2023;doi:10.1177/20101058231156628]

For the new equation, OLP regression showed no fixed (intercept=-122 kcal) or proportional bias (slope=1.09). Total (systematic and random) error was 212 kcal as per Bland-Altman analysis.

For HBE, OLP regression showed a significant pattern of overprediction (y-intercept=-280 kcal). “[This translates to an overprediction of] RMR by 9.9 percent in Asian Singaporean adults, specifically by 7.0 percent in men and 11.8 percent in women,” the investigators explained. “[T]herefore, it may not be suitable for use in our local clinical dietetics practice.”

Internal model validation revealed minimal reduction in the new equation’s predictive accuracy (R²=0.83 vs 0.82; SEE*_p=106.4 vs 109.8 kcal). “PRESS statistics usually generate less promising estimates of an equation’s capability, which highlights the reliability of the newly developed equation,” they noted.

Rationale for RMR prediction equations

“In the teeth of an emerging epidemic of diabetes, obesity, and other weight-related morbidities, a weight management plan that is individualized for patients is a crucial tool in the hands of the clinician,” said the researchers.

Albeit accurate, IC is costly, has stringent conditions, and requires technical knowhow to use. Also, cheaper portable IC machines have a larger margin of error. Moreover, most of the established equations today are reportedly inaccurate in an ethnically diverse population. [Curr Opin Clin Nutr Metab Care 2005;8:319-328; J Am Diet Assoc 2005;105:775-789] “Hence, there is a need for population-specific RMR prediction equations,” the researchers stressed.

“This new equation provides a practical and convenient method for accurately predicting RMR in Singaporean patients, mainly Chinese females, [to aid] their weight and nutrition management with the inclusion of novel predictors,” they said.

New predictors

One of the novel predictors of RMR in the equation is WSR**. “[T]here is growing evidence that waist circumference is a better predictor of chronic diseases in Asians. WSR is a surrogate measure of visceral adipose tissue that accounts for stature … [U]nlike previous predictive equations, including WSR (along with body mass) in the new equation provides greater accuracy as the equation considers body composition – an important determinant of RMR,” the researchers noted.

Another new predictor is the IPAQ** score, which reflects an individual’s physical activity level. “As physical activity has such a strong bearing on RMR, the new equation has the advantage over other equations of incorporating the IPAQ score,” they added.

“[With] easily obtained anthropometric and self-reported measures, we envisage its potential relevance in clinical and epidemiological settings,” they concluded.

Future research should evaluate the new equation’s performance in other ethnicities (ie, Malays, Indians), as well as among critically ill, elderly, or obese individuals. It would also be worth looking into the ability of direct body composition measures to predict RMR in Asian Singaporeans, they added.