ObjectivesTo assess if nutritional interventions informed by indirect calorimetry (IC), compared to predictive equations, show greater improvements in achieving weight goals, muscle mass, strength, physical and functional performance.DesignQuasi-experimental study.Setting and ParticipantsGeriatric rehabilitation inpatients referred to dietitian.Intervention and MeasurementsPatients were allocated based on admission ward to either the IC or equation (EQ) group. Measured resting metabolic rate (RMR) by IC was communicated to the treating dietitian for the IC group but concealed for the EQ group. Achieving weight goals was determined by comparing individualised weight goals with weight changes from inclusion to discharge (weight gain/loss: >2% change, maintenance: ≤2%). Muscle mass, strength, physical and functional performance were assessed at admission and discharge. Food intake was assessed twice over three-days at inclusion and before discharge using plate waste observation.ResultsFifty-three patients were included (IC n=22; EQ n=31; age: 84.3±8.4 years). The measured RMR was lower than the estimated RMR within both groups [mean difference IC −282 (95%CI −490;−203), EQ −273 (−381;−42) kcal/day)] and comparable between-groups (median IC 1271 [interquartile range 1111;1446] versus EQ 1302 [1135;1397] kcal/day, p=0.800). Energy targets in the IC group were lower than the EQ group [mean difference −317 (95%CI −479;−155) kcal/day]. There were no between-group differences in energy intake, achieving weight goals, changes in muscle mass, strength, physical and functional performance.ConclusionsIn geriatric rehabilitation inpatients, nutritional interventions informed by IC compared to predictive equations showed no greater improvement in achieving weight goals, muscle mass, strength, physical and functional performance. IC facilitates more accurate determination of energy targets in this population. However, evidence for the potential benefits of its use in nutrition interventions was limited by a lack of agreement between patients’ energy intake and energy targets.
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Rationale: It is well established that resting energy expenditure (REE) decreases with age. Data derived from indirect calorimetry (IC) are still limited with respect to the number of high aged individuals, BMI groups and health conditions. Therefore, IC generated REE of the BASAROT sample and those calculated according to the Harris-Benedict (HB) equation were used to re-evaluate the proposed association between REE and age. Methods: The IC-BASAROT sample combines the result of IC performed in 2622 individuals from 10 centers (7 Germany, 2 Italy, 1 Netherlands) done under strictly standardized conditions (e.g. at least 8h of fasting) in free-living, mostly healthy adults aged 18 to 100 years including all BMI ranges. IC was performed by canopy technique (Cosmed Quark RMR/Sensor Medics Vmax29) in 96.5% of cases and by face mask (Cosmed Fitmate) in 3.5%. Weight was measured by calibrated scales and height was determined to the nearest of 1mm. Results: REE in the total sample (BMI: 26.9±9.1 kg/m², 43.7±17.6 y) correlated more positively with body weight than with BMI (r=0.768; p<0.001 vs. r=0.571; p<0.001). Gender+body weight explained 75% of REE variance, gender+BMI 69% and gender+age only 28%. To reduce confounding by body weight we performed age-related analysis in the subgroup of women weighing 50-79 kg (n=780, BMI: 23.4±3.4 kg/m², 41.4±18.5 y) and men weighing 60-89 kg (n=500, BMI: 24.9±3.0 kg/m², 47.5±19.3 y) and compared results with REEHB (tab. 1). IC results from 18 to 100 y showed an approximately 50% lower decrease in REE than HB in women (-129 kcal/d vs. - 257 kcal/d) and in men (-200 kcal/d vs. -406 kcal/d, tab. 1). REEIC (n=1280) did not correlate with age (r=-0.042; p=0.132). In line, we observed a significant overestimation of REE by HB up to 39 y in both sexes and an underestimation in men 60 y of age and older. Conclusion: Age-related decline in REE appears to be lower than expected and might due to changes in body composition both in the younger and older generation. No indication of the often proposed systematic overestimation of HB in women was seen. Overall, findings should be considered in future models for estimating REE.
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Background & aims: Individual energy requirements of overweight and obese adults can often not be measured by indirect calorimetry, mainly due to the time-consuming procedure and the high costs. To analyze which resting energy expenditure (REE) predictive equation is the best alternative for indirect calorimetry in Belgian normal weight to morbid obese women.Methods: Predictive equations were included when based on weight, height, gender, age, fat free mass and fat mass. REE was measured with indirect calorimetry. Accuracy of equations was evaluated by the percentage of subjects predicted within 10% of REE measured, the root mean squared prediction error (RMSE) and the mean percentage difference (bias) between predicted and measured REE.Results: Twenty-seven predictive equations (of which 9 based on FFM) were included. Validation was based on 536 F (18–71 year). Most accurate and precise for the Belgian women were the Huang, Siervo, Muller (FFM), Harris–Benedict (HB), and the Mifflin equation with 71%, 71%, 70%, 69%, and 68% accurate predictions, respectively; bias −1.7, −0.5, +1.1, +2.2, and −1.8%, RMSE 168, 170, 163, 167, and 173 kcal/d. The equations of HB and Mifflin are most widely used in clinical practice and both provide accurate predictions across a wide range of BMI groups. In an already overweight group the underpredicting Mifflin equation might be preferred. Above BMI 45 kg/m2, the Siervo equation performed best, while the FAO/WHO/UNU or Schofield equation should not be used in this extremely obese group.Conclusions: In Belgian women, the original Harris–Benedict or the Mifflin equation is a reliable tool to predict REE across a wide variety of body weight (BMI 18.5–50). Estimations for the BMI range between 30 and 40 kg/m2, however, should be improved.
