Abstract

To evaluate predictors of resting energy expenditure (REE) in older people which are more comfortable for them than indirect calorimetry and which are suitable for field studies. Cross-sectional study. Department of Human Biology, Kiel University. 100 (51 males, 49 females) healthy independently-living normal-weight (BMI, males 26.0±2.67 kg/m², females 25.0±3.29 kg/m²) Germans, aged 60-83 years. REE, body composition, anthropometry, peak expiratory flow rate (PEF), and physical activity level were determined using indirect calorimetry, bioimpedance analysis, anthropometrics, peak-flow-meter, and standardized questionnaire, respectively. Stepwise linear multiple regression analysis was performed with REE or weight adjusted REE as dependent variables. Independent variables were body height, weight, body mass index (BMI), waist circumference, abdomen circumference, hip circumference, waist-to-hip ratio (WHR), lean body mass (LBM), PEF, and physical activity level. The only significant predictor of REE was LBM in males and BMI in females. Trunk circumferences emerged as strong predictors of weight adjusted REE. Abdomen circumference and hip circumference explained in males and females 69% and 70% of variation in adjusted REE, respectively. Weaker predictors were LBM in males (R² increased from 0.69 to 0.80) as well as body height and BMI in females (R² increased from 0.70 to 0.91). Waist circumference, WHR, physical activity level, and PEF were no significant determinants of adjusted REE. These findings demonstrate that trunk circumferences, but not WHR, are very strong predictors of weight adjusted REE in non-geriatric older people. This implies that the sex-specific use of abdomen or hip circumference in combination with LBM or body height and BMI seems to be well sufficient to predict weight adjusted REE in the aged. These measures might also be of clinical relevance, because they are more comfortable for older sick people than indirect calorimetry. Further studies are needed to test the applicability of the prediction equations to frail older populations.

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