Predictive equation of resting energy expenditure in obese adult Taiwanese

Chung Kang Tseng, Hua-Shai Hsu, Chih-Te Ho, Hui Ying Huang, Chiu Shong Liu, Cheng-Chieh Lin, Wen-Yuan Lin

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Objective: To examine the accuracy of present resting energy expenditure (REE) predictive equations among obese adult Taiwanese, and obtain new predictive equations for this population. Method: A total of 80 participants (men = 42, women = 38) aged 18-64 years (mean 41.5 ± 13.1 years) with body mass index (BMI) ≥30 kg/m 2 were recruited from obesity clinic of a tertiary hospital. Anthropometric data including weight, height, waist circumference (WC), hip circumference (HipC) were collected. Body fat and fat free mass (FFM) were measured using bioelectric impedance analysis. Indirect calorimeter (Vmax 29n) was used for measurement of REE. The commonly used predictive equations (Harris-Benedict equation, Bernstein equation, Mifflin equation, Owen equation, Schofield equation, Cunningham equation, Wang equation, and Liu equation) were tested for group means and individual prediction accuracy for our target population. New predictive equations were formulated using multiple linear regression analyses. Result: The mean BMI was 34.3 ± 4.6 kg/m 2. All of the commonly used predictive equations showed statistically significant differences with the measured REE values. As for individual prediction accuracy, these predictive equations showed poor performance and only Mifflin equation provided an individual accuracy over 40%. The new predictive equation recommended for obese adult Taiwanese is below: REE (kcal/d) = 11.6 × weight (kg) - 204.84 × gender - 4.8 × height (cm) + 1594.6 (gender: men = 1; women = 2). Conclusion: The previous commonly used predictive equations were less accurate in obese Taiwanese. For this specific population, the newly developed equation should be applied for better prediction of REE.

Original languageEnglish (US)
JournalObesity Research and Clinical Practice
Volume5
Issue number4
DOIs
StatePublished - Oct 1 2011

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Energy Metabolism
Body Mass Index
Weights and Measures
Health Services Needs and Demand
Waist Circumference
Electric Impedance
Tertiary Care Centers
Population
Adipose Tissue
Hip
Linear Models
Obesity
Fats
Regression Analysis

Keywords

  • Indirect calorimeter
  • Predictive equation
  • Resting energy expenditure

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics

Cite this

Predictive equation of resting energy expenditure in obese adult Taiwanese. / Tseng, Chung Kang; Hsu, Hua-Shai; Ho, Chih-Te; Huang, Hui Ying; Liu, Chiu Shong; Lin, Cheng-Chieh; Lin, Wen-Yuan.

In: Obesity Research and Clinical Practice, Vol. 5, No. 4, 01.10.2011.

Research output: Contribution to journalArticle

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abstract = "Objective: To examine the accuracy of present resting energy expenditure (REE) predictive equations among obese adult Taiwanese, and obtain new predictive equations for this population. Method: A total of 80 participants (men = 42, women = 38) aged 18-64 years (mean 41.5 ± 13.1 years) with body mass index (BMI) ≥30 kg/m 2 were recruited from obesity clinic of a tertiary hospital. Anthropometric data including weight, height, waist circumference (WC), hip circumference (HipC) were collected. Body fat and fat free mass (FFM) were measured using bioelectric impedance analysis. Indirect calorimeter (Vmax 29n) was used for measurement of REE. The commonly used predictive equations (Harris-Benedict equation, Bernstein equation, Mifflin equation, Owen equation, Schofield equation, Cunningham equation, Wang equation, and Liu equation) were tested for group means and individual prediction accuracy for our target population. New predictive equations were formulated using multiple linear regression analyses. Result: The mean BMI was 34.3 ± 4.6 kg/m 2. All of the commonly used predictive equations showed statistically significant differences with the measured REE values. As for individual prediction accuracy, these predictive equations showed poor performance and only Mifflin equation provided an individual accuracy over 40{\%}. The new predictive equation recommended for obese adult Taiwanese is below: REE (kcal/d) = 11.6 × weight (kg) - 204.84 × gender - 4.8 × height (cm) + 1594.6 (gender: men = 1; women = 2). Conclusion: The previous commonly used predictive equations were less accurate in obese Taiwanese. For this specific population, the newly developed equation should be applied for better prediction of REE.",
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AB - Objective: To examine the accuracy of present resting energy expenditure (REE) predictive equations among obese adult Taiwanese, and obtain new predictive equations for this population. Method: A total of 80 participants (men = 42, women = 38) aged 18-64 years (mean 41.5 ± 13.1 years) with body mass index (BMI) ≥30 kg/m 2 were recruited from obesity clinic of a tertiary hospital. Anthropometric data including weight, height, waist circumference (WC), hip circumference (HipC) were collected. Body fat and fat free mass (FFM) were measured using bioelectric impedance analysis. Indirect calorimeter (Vmax 29n) was used for measurement of REE. The commonly used predictive equations (Harris-Benedict equation, Bernstein equation, Mifflin equation, Owen equation, Schofield equation, Cunningham equation, Wang equation, and Liu equation) were tested for group means and individual prediction accuracy for our target population. New predictive equations were formulated using multiple linear regression analyses. Result: The mean BMI was 34.3 ± 4.6 kg/m 2. All of the commonly used predictive equations showed statistically significant differences with the measured REE values. As for individual prediction accuracy, these predictive equations showed poor performance and only Mifflin equation provided an individual accuracy over 40%. The new predictive equation recommended for obese adult Taiwanese is below: REE (kcal/d) = 11.6 × weight (kg) - 204.84 × gender - 4.8 × height (cm) + 1594.6 (gender: men = 1; women = 2). Conclusion: The previous commonly used predictive equations were less accurate in obese Taiwanese. For this specific population, the newly developed equation should be applied for better prediction of REE.

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