Abstract
BackgroundFew studies investigated the association between basal metabolic rate (BMR) and indicators of pulmonary function. This study was conducted to estimate BMR in overweight/obese and non-obese healthy subjects using four commonly used predictive equations and to investigate its relation to the indicators of lung function tests (LFT). A cross sectional study was conducted in Tabuk University, Tabuk, Saudi Arabia. A total of 201 students (98 males and 103 females) participated in the study. Four different values of BMR were calculated for each participant using four different predictive equations (Harris-Benedict, Mifflin, FAO/WHO/UNU and Henry-Rees). A portable All-flow spirometer (Clement Clarke International, Harlow, UK) was used for measurements of LFT.ResultsSignificantly higher values of spirometric indicators (p < 0.05) were found in males compared to females, except for FEF75 and FEF75-85. Mean BMR values predicted with the four equations were significantly higher in the males compared to the females and among the overweight/obese compared to the non-obese subjects (p < 0.05). The relation between mean BMR values and the indicators of LFT was statistically insignificant (p > 0.05).ConclusionMean values of LFT indicators are not related to the estimated values of BMR. A practical calculation of BMR based on direct measurement of oxygen consumption is recommended to confirm the absence of this association.
Highlights
Few studies investigated the association between basal metabolic rate (BMR) and indicators of pulmonary function
Lung function test indicators were significantly higher (p < 0.05) among males compared to females, except for FEF75 and FEF75-85
Mean BMR values predicted with the four equations were significantly higher in males compared to females (p < 0.05)
Summary
Few studies investigated the association between basal metabolic rate (BMR) and indicators of pulmonary function. This study was conducted to estimate BMR in overweight/obese and non-obese healthy subjects using four commonly used predictive equations and to investigate its relation to the indicators of lung function tests (LFT). Accurate measurement requires strict laboratory preparations and special equipment. For this reason, predictive equations are increasingly used for its estimation in clinical practice. Several predictive equations, based on body weight, height, and age were used for its estimation. These include equations created by Harris and Benedict [1], Mifflin [2], Food and Agriculture Organization/World Health Organization/
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