IC-BASAROTs: New Practice Method for More Accurate Bed-side Assessment of Individual Energy Expenditure

IC-BASAROTs: Verification of a New Practice Method for More Accurate Bed-side Assessment of Individual Energy Expenditure

Assessment of resting energy expenditure (REE) by indirect calorimetry (IC) in 1400 healthy individuals for arithmetical transformation into an bedside tool to estimate energy requirements in dietary practice (BASAROTs). A multinational, multicenter, prospective cross-sectional study.

Study Overview

• Status: Unknown
• Conditions: Healthy; Overweight; Body Weight; Thinness

Detailed Description

The assessment of energy expenditure is the basic requirement for any nutritional therapy. Nevertheless, there is still no accurate, scientifically validated and practical bedside tool.

The reference method for energy expenditure measurement is indirect calorimetry (IC). High costs, time requirements and the need for trained personal are main reasons for its limited use in clinical practice. Also arithmetical calculations, such as the Harris-Benedict equation, are not widely accepted.

In general energy expenditure is often estimated by so called rules of thumbs, a method requiring only one multiplication with body weight (for example: 25 kcal/kg body weight). Sex, age and BMI are usually not considered, although they are independent predictors of energy expenditure. Thus, energy expenditure estimations are often inaccurate, especially in older and overweight/obese persons.

Therefore, it is important to develop a bedside tool that is more accurate but simple enough to be accepted by practitioners. In 2004, the Austrian Society of Clinical Nutrition published the first BMI, aged and sex adapted rule of thumbs, called BASAROTs (BMI Age Sex Adjusted Rule Of Thumbs). Those were, however, based on results of the Harris Benedict equation.

The main objective of the present study is, therefore, to replace the existing BASAROTs by BASAROTs based on actual measurements of resting energy expenditure by indirect calorimetry (IC-BASAROTs).

• Study Type: Observational
• Enrollment (Anticipated): 1400

Contacts and Locations

Study Locations

• Germany
  • Bavaria
    • Munich, Bavaria, Germany, 80992
      • Recruiting
      • Technical University of Munich
      • Contact: Christina Holzapfel, Dr.; Email: christina.holzapfel@tum.de
  • Hesse
    • Fulda, Hesse, Germany, 36030
      • Recruiting
      • Fulda University of Applied Sciences
      • Contact: Kathrin Kohlenberg-Müller, Prof. Dr.; Phone Number: +49 661 9649 378; Email: kathrin.kohlenberg-mueller@he.hs-fulda.de
  • Mecklenburg-Western Pomerania
    • Neubrandenburg, Mecklenburg-Western Pomerania, Germany, 17033
      • Recruiting
      • Dietrich Bonheoffer Hospital of Neubrandenburg
      • Contact: Peter Keil, Dr. med.; Phone Number: +49 0375 775 3700; Email: keiljp@dbknb.de
    • Neubrandenburg, Mecklenburg-Western Pomerania, Germany, 17033
      • Recruiting
      • University of Applied Sciences Neubrandenburg
      • Contact: Luzia Valentini, Prof. Dr.; Phone Number: +49 395 5693 2512; Email: valentini@hs-nb.de
      • Contact: Sara Ramminger, M. Sc.; Phone Number: +49 395 5693 1507; Email: ramminger@hs-nb.de
  • Rhineland-Palatinate
    • Mainz, Rhineland-Palatinate, Germany, 55116
      • Recruiting
      • Profil Institut for Metabolic Research
      • Contact: Leona Plum-Mörschel, Dr; Email: leona.plum-moerschel@profil.com
  • Saxony
    • Leipzig, Saxony, Germany, 04103
      • Recruiting
      • Leipzig University - Medical Center IFB AdiposityDiseases
      • Contact: Tanja Schütz, Dr.; Phone Number: +49 341 97 15 957; Email: tatjana.schuetz@medizin.uni-leipzig.de

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 100 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Minimum sample size of n = 1400: 700 mostly healthy people (50% women, aged 18-100 years, BMI 16.5 to 39.9 kg / m²), 420 underweight individuals (50% women, 18 years to 100 years, BMI from 14.0 to 16.4 kg/m²), 280 morbidly obese (50% women,18 years to 100 years, BMI 40.0-49,9 kg/m²).

Recruitment of volunteers is performed in the local trial centers.

Description

Inclusion Criteria:

• female, male
• 18 years to 85 years
• Body Mass Index: 14,0 - 49,9 kg/m²
• Eastern Cooperative Oncology Group (ECOG) Performance Status (Grade 0 or 1)
• normal thyroid function
• subjective health in dependence of BMI (underweight, normal weight, obesity, morbid obesity)

Exclusion Criteria:

• implanted pacemaker
• amputations
• paresis (mono- and diparesis)
• Asian or African descent
• above-average physical activity (competitive sport)
• present or suspicion of malignant neoplasms (tumors, metastases, hemato-oncological diseases)
• severe diseases (organ diseases, neurological diseases)
• severe dementia (MMSE < 20 points)
• pregnancy
• participation in other trials
• subjects with expect non-compliance to protocol guidelines
• intake of:
• lithium compound
• neuroleptics: Olanzapine (Zyprexa ®), Clozapine, Sertindole, Ziprasidone, Haloperidol, Thioridazine
• anticonvulsant (Carbamazepin, Valproic Acid, Topiramate)
• noradrenalin-reuptake-inhibitor (NARI): Reboxetine , Atomoxetine
• tricyclic antidepressants (Amitryptiline, Clomipramine, Doxepin, Imipramine, Trimipramin)
• Lorcaserin
• interferon-alfa, interferon-beta
• Baclofen
• Orciprenaline
• Amiodarona
• Insulin
• corticoid therapy (oral)

Study Plan

How is the study designed?

Number of groups / cohorts

18

Cohorts and Interventions

Group / Cohort
Female, BMI: 14,00-16,49 kg/m²; Age: 18 - 100 Years
Female, BMI: 16,50-18,49 kg/m²; Age: 18 - 100 years
Female, BMI: 18,50-19,99 kg/m²; Age: 18 - 100 years
Female, BMI: 20,00-24,99 kg/m²; Age: 18 - 100 years
Female, BMI: 25,00-29,99 kg/m²; Age: 18 - 100 years
Female, BMI: 30,00-34,99 kg/m²; Age: 18 - 100 years
Female, BMI: 35,00-39,99 kg/m²; Age: 18 - 100 years
Female, BMI: 40,00-44,99 kg/m²; Age: 18 - 100 years
Female, BMI: 45,00-49,99 kg/m²; Age: 18 - 100 years
Male, BMI: 14,00-16,49 kg/m²; Age: 18 - 100 years
Male, BMI: 16,50-18,49 kg/m²; Age: 18 - 100 years
Male, BMI: 18,50-19,99 kg/m²; Age: 18 - 100 years
Male, BMI: 20,00-24,99 kg/m²; Age: 18 - 100 years
Male, BMI: 25,00-29,99 kg/m²; Age: 18 - 100 years
Male, BMI: 30,00-34,99 kg/m²; Age: 18 - 100 years
Male, BMI: 35,00-39,99 kg/m²; Age: 18 - 100 years
Male, BMI: 40,00-44,99 kg/m²; Age: 18 - 100 years
Male, BMI: 45,00-49,99 kg/m²; Age: 18 - 100 years

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
resting energy expenditure (REE) (kcal)	Assessed by indirect calorimetry	15 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
blood pressure (mm Hg)	upper arm measurement by certified medical device	one single (baseline) measurement under standardized conditions
Body temperature (°C)	measured axillar, by infra-red ear thermometer and non-contact thermoscan	one single (baseline) measurement under standardized conditions
Heart rate (bpm)	measured by heart rate band and blood pressure device	one single (baseline) measurement under standardized conditions
Body weight (kg)	measured by electronic scale integrated in BIA device	one single (baseline) measurement under standardized conditions
Body height (m)	measured by digital stationary stadiometer	one single (baseline) measurement under standardized conditions
Fat mass (FM) (kg)	measured by bioelectrical impedance analysis (BIA)	one single (baseline) measurement under standardized conditions
Fat-free mass (FFM) (kg)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Fat-free mass index (FFMI) (kg/m²)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Fat mass index (FMI) (kg/m²)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Skeletal muscle mass (SMM) (kg)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Total body water (TBW) (l)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Extracellular water (ECW) (l)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Resistance (R) (Ω)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Reactance (Xc) (Ω)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Phase angle (°)	measured by bioelectrical impedance Analysis (BIA)	one single (baseline) measurement under standardized conditions
Waist circumference (cm)	measured by measuring tape	one single (baseline) measurement under standardized conditions
International Physical Activity Questionnaire (IPAQ) short form		one single (baseline) interview

Collaborators and Investigators

• Sponsor: University of Applied Sciences Neubrandenburg
• Investigators: Principal Investigator: Luzia Valentini, Prof. Dr., Neubrandenburg University of Applied Sciences

Publications and helpful links

General Publications

• Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381-95. doi: 10.1249/01.MSS.0000078924.61453.FB.
• Elizabeth Weekes C. Controversies in the determination of energy requirements. Proc Nutr Soc. 2007 Aug;66(3):367-77. doi: 10.1017/S0029665107005630.
• Schoeller DA. Making indirect calorimetry a gold standard for predicting energy requirements for institutionalized patients. J Am Diet Assoc. 2007 Mar;107(3):390-2. doi: 10.1016/j.jada.2007.01.030. No abstract available.
• Valentini L, Roth E, Jadrna K, Postrach E, Schulzke JD. The BASA-ROT table: an arithmetic-hypothetical concept for easy BMI-, age-, and sex-adjusted bedside estimation of energy expenditure. Nutrition. 2012 Jul;28(7-8):773-8. doi: 10.1016/j.nut.2011.11.020.
• Lawrence M. Predicting energy requirements: is energy expenditure proportional to the BMR or to body weight? An analysis of data collected in rural Gambian women. Eur J Clin Nutr. 1988 Nov;42(11):919-27.
• Piers LS, Soares MJ, McCormack LM, O'Dea K. Is there evidence for an age-related reduction in metabolic rate? J Appl Physiol (1985). 1998 Dec;85(6):2196-204. doi: 10.1152/jappl.1998.85.6.2196.
• Muller MJ, Bosy-Westphal A, Kutzner D, Heller M. Metabolically active components of fat-free mass and resting energy expenditure in humans: recent lessons from imaging technologies. Obes Rev. 2002 May;3(2):113-22. doi: 10.1046/j.1467-789x.2002.00057.x.
• Dickerson RN. Optimal caloric intake for critically ill patients: first, do no harm. Nutr Clin Pract. 2011 Feb;26(1):48-54. doi: 10.1177/0884533610393254.
• Berger MM, Pichard C. Development and current use of parenteral nutrition in critical care - an opinion paper. Crit Care. 2014 Aug 8;18(4):478. doi: 10.1186/s13054-014-0478-0.
• Heidegger CP, Berger MM, Graf S, Zingg W, Darmon P, Costanza MC, Thibault R, Pichard C. Optimisation of energy provision with supplemental parenteral nutrition in critically ill patients: a randomised controlled clinical trial. Lancet. 2013 Feb 2;381(9864):385-93. doi: 10.1016/S0140-6736(12)61351-8. Epub 2012 Dec 3.
• Bader N, Bosy-Westphal A, Dilba B, Muller MJ. Intra- and interindividual variability of resting energy expenditure in healthy male subjects -- biological and methodological variability of resting energy expenditure. Br J Nutr. 2005 Nov;94(5):843-9. doi: 10.1079/bjn20051551.
• Bosy-Westphal A, Eichhorn C, Kutzner D, Illner K, Heller M, Muller MJ. The age-related decline in resting energy expenditure in humans is due to the loss of fat-free mass and to alterations in its metabolically active components. J Nutr. 2003 Jul;133(7):2356-62. doi: 10.1093/jn/133.7.2356.
• Gonnissen HK, Adam TC, Hursel R, Rutters F, Verhoef SP, Westerterp-Plantenga MS. Sleep duration, sleep quality and body weight: parallel developments. Physiol Behav. 2013 Sep 10;121:112-6. doi: 10.1016/j.physbeh.2013.04.007. Epub 2013 May 3.
• Chaput JP, St-Onge MP. Increased food intake by insufficient sleep in humans: are we jumping the gun on the hormonal explanation? Front Endocrinol (Lausanne). 2014 Jul 15;5:116. doi: 10.3389/fendo.2014.00116. eCollection 2014. No abstract available.
• Rutten A, Abu-Omar K. Prevalence of physical activity in the European Union. Soz Praventivmed. 2004;49(4):281-9. doi: 10.1007/s00038-004-3100-4.
• Bosy-Westphal A, Schautz B, Later W, Kehayias JJ, Gallagher D, Muller MJ. What makes a BIA equation unique? Validity of eight-electrode multifrequency BIA to estimate body composition in a healthy adult population. Eur J Clin Nutr. 2013 Jan;67 Suppl 1:S14-21. doi: 10.1038/ejcn.2012.160.

Study record dates

Study Major Dates

• Study Start: March 1, 2015
• Primary Completion (ANTICIPATED): December 1, 2019
• Study Completion (ANTICIPATED): December 1, 2020

Study Registration Dates

• First Submitted: February 8, 2016
• First Submitted That Met QC Criteria: February 12, 2016
• First Posted (ESTIMATE): February 15, 2016

Study Record Updates

• Last Update Posted (ACTUAL): April 11, 2018
• Last Update Submitted That Met QC Criteria: April 9, 2018
• Last Verified: April 1, 2018

More Information

Terms related to this study

• Keywords: Resting energy expenditure; Indirect Calorimetry; Calorie requirements
• Additional Relevant MeSH Terms: Overweight; Body Weight; Thinness
• Other Study ID Numbers: BB023/15

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: The other study centers forward us pseudonymised participant data for evaluation. It might also be possible that we share selected pseudonymised participant data with the other study centers.