Prediction of basal metabolic rate in patients with Prader-Willi syndrome

Stefano Lazzer, G Grugni, G Tringali, A Sartorio

Research output: Contribution to journalArticle

Abstract

BACKGROUND/OBJECTIVES: The objective of this study was to develop new equations for predicting basal metabolic rate (BMR) in Prader-Willi syndrome (PWS) subjects and to compare their accuracy with commonly used equations developed by Lazzer (2007), Livingston (2005), Huang (2004), Nelson (1992), Mifflin (1990), Owen (1987), WHO (1985), Bernstein (1983) and Harris-Benedict (1919), using the Bland-Altman method.

SUBJECTS/METHODS: BMR was measured by indirect calorimetry and fat-free mass (FFM) and fat mass (FM) by a tetrapolar impedancemeter in 80 Caucasian PWS patients (mean body mass index: 39.1 kg/m(2); 17-50 years). Equations were derived by stepwise multiple regression analysis using a calibration group (n:50) and tested against the validation group (n:30).

RESULTS: Two new equations, based on anthropometric (BMR=body mass × 0.052+sex × 0.778-age × 0.033+2.839 (R(2)adj=0.61, s.e.=0.89 MJ per day)) or body composition (BMR=FFMx0.074+FMx0.042+sexx0.636-agex0.037+2.515 (R(2)adj=0.69, s.e.=0.82 MJ per day)), were generated. Predicted BMR (PBMR) was not significantly different from the measured BMR (<3.3%), and was accurate in 59% and 62% of patients, respectively. Nevertheless, significant magnitude bias was found for both equations (P<0.001, R(2)=0.36). The Owen (1987), Mifflin (1990), Huang (2004) and Lazzer (2007) equations showed mean differences <5% and PBMR was accurate in ~50% of patients. The Livingston (2005), WHO (1985) and Harris-Benedict (1919) equations showed a PBMR overestimation >7% and were accurate in <50% of patients. The Nelson (1992) and Bernstein (1983) equations showed a greater PBMR underestimation in >60% of subjects.

CONCLUSIONS: The new prediction equations showed significantly higher accuracy compared with equations tested, with exception of Lazzer (2007) and Livingston (2005) equations, and result in lower mean differences and lower limits of agreement compared with the equations tested.

Original languageEnglish
Pages (from-to)494-8
Number of pages5
JournalEuropean Journal of Clinical Nutrition
Volume70
Issue number4
DOIs
Publication statusPublished - Apr 2016

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Prader-Willi Syndrome
Basal Metabolism
Fats
Indirect Calorimetry
Body Composition
Calibration
Body Mass Index
Regression Analysis

Keywords

  • Adolescent
  • Adult
  • Basal Metabolism
  • Body Composition
  • Body Mass Index
  • Calorimetry, Indirect
  • Electric Impedance
  • Female
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Models, Theoretical
  • Prader-Willi Syndrome
  • Predictive Value of Tests
  • Young Adult
  • Journal Article
  • Research Support, Non-U.S. Gov't

Cite this

Prediction of basal metabolic rate in patients with Prader-Willi syndrome. / Lazzer, Stefano; Grugni, G; Tringali, G; Sartorio, A.

In: European Journal of Clinical Nutrition, Vol. 70, No. 4, 04.2016, p. 494-8.

Research output: Contribution to journalArticle

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T1 - Prediction of basal metabolic rate in patients with Prader-Willi syndrome

AU - Lazzer, Stefano

AU - Grugni, G

AU - Tringali, G

AU - Sartorio, A

PY - 2016/4

Y1 - 2016/4

N2 - BACKGROUND/OBJECTIVES: The objective of this study was to develop new equations for predicting basal metabolic rate (BMR) in Prader-Willi syndrome (PWS) subjects and to compare their accuracy with commonly used equations developed by Lazzer (2007), Livingston (2005), Huang (2004), Nelson (1992), Mifflin (1990), Owen (1987), WHO (1985), Bernstein (1983) and Harris-Benedict (1919), using the Bland-Altman method.SUBJECTS/METHODS: BMR was measured by indirect calorimetry and fat-free mass (FFM) and fat mass (FM) by a tetrapolar impedancemeter in 80 Caucasian PWS patients (mean body mass index: 39.1 kg/m(2); 17-50 years). Equations were derived by stepwise multiple regression analysis using a calibration group (n:50) and tested against the validation group (n:30).RESULTS: Two new equations, based on anthropometric (BMR=body mass × 0.052+sex × 0.778-age × 0.033+2.839 (R(2)adj=0.61, s.e.=0.89 MJ per day)) or body composition (BMR=FFMx0.074+FMx0.042+sexx0.636-agex0.037+2.515 (R(2)adj=0.69, s.e.=0.82 MJ per day)), were generated. Predicted BMR (PBMR) was not significantly different from the measured BMR (<3.3%), and was accurate in 59% and 62% of patients, respectively. Nevertheless, significant magnitude bias was found for both equations (P<0.001, R(2)=0.36). The Owen (1987), Mifflin (1990), Huang (2004) and Lazzer (2007) equations showed mean differences <5% and PBMR was accurate in ~50% of patients. The Livingston (2005), WHO (1985) and Harris-Benedict (1919) equations showed a PBMR overestimation >7% and were accurate in <50% of patients. The Nelson (1992) and Bernstein (1983) equations showed a greater PBMR underestimation in >60% of subjects.CONCLUSIONS: The new prediction equations showed significantly higher accuracy compared with equations tested, with exception of Lazzer (2007) and Livingston (2005) equations, and result in lower mean differences and lower limits of agreement compared with the equations tested.

AB - BACKGROUND/OBJECTIVES: The objective of this study was to develop new equations for predicting basal metabolic rate (BMR) in Prader-Willi syndrome (PWS) subjects and to compare their accuracy with commonly used equations developed by Lazzer (2007), Livingston (2005), Huang (2004), Nelson (1992), Mifflin (1990), Owen (1987), WHO (1985), Bernstein (1983) and Harris-Benedict (1919), using the Bland-Altman method.SUBJECTS/METHODS: BMR was measured by indirect calorimetry and fat-free mass (FFM) and fat mass (FM) by a tetrapolar impedancemeter in 80 Caucasian PWS patients (mean body mass index: 39.1 kg/m(2); 17-50 years). Equations were derived by stepwise multiple regression analysis using a calibration group (n:50) and tested against the validation group (n:30).RESULTS: Two new equations, based on anthropometric (BMR=body mass × 0.052+sex × 0.778-age × 0.033+2.839 (R(2)adj=0.61, s.e.=0.89 MJ per day)) or body composition (BMR=FFMx0.074+FMx0.042+sexx0.636-agex0.037+2.515 (R(2)adj=0.69, s.e.=0.82 MJ per day)), were generated. Predicted BMR (PBMR) was not significantly different from the measured BMR (<3.3%), and was accurate in 59% and 62% of patients, respectively. Nevertheless, significant magnitude bias was found for both equations (P<0.001, R(2)=0.36). The Owen (1987), Mifflin (1990), Huang (2004) and Lazzer (2007) equations showed mean differences <5% and PBMR was accurate in ~50% of patients. The Livingston (2005), WHO (1985) and Harris-Benedict (1919) equations showed a PBMR overestimation >7% and were accurate in <50% of patients. The Nelson (1992) and Bernstein (1983) equations showed a greater PBMR underestimation in >60% of subjects.CONCLUSIONS: The new prediction equations showed significantly higher accuracy compared with equations tested, with exception of Lazzer (2007) and Livingston (2005) equations, and result in lower mean differences and lower limits of agreement compared with the equations tested.

KW - Adolescent

KW - Adult

KW - Basal Metabolism

KW - Body Composition

KW - Body Mass Index

KW - Calorimetry, Indirect

KW - Electric Impedance

KW - Female

KW - Humans

KW - Linear Models

KW - Male

KW - Middle Aged

KW - Models, Theoretical

KW - Prader-Willi Syndrome

KW - Predictive Value of Tests

KW - Young Adult

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1038/ejcn.2015.161

DO - 10.1038/ejcn.2015.161

M3 - Article

C2 - 26395435

VL - 70

SP - 494

EP - 498

JO - European Journal of Clinical Nutrition

JF - European Journal of Clinical Nutrition

SN - 0954-3007

IS - 4

ER -