Development and validation of an equation to predict total energy expenditure in a sample of Mexican adults

Authors

  • Luis Ortiz-Hernandez Universidad
  • César Iván Ayala-Guzmán
  • Lic.
  • Ricardo López Solís
  • Mariana Tejeda Espinosa

DOI:

https://doi.org/10.12873/413ortiz

Keywords:

total energy expenditure, adults, physical activity, resting energy expenditure, indirect calorimetry, heart rate

Abstract

Our aim was to develop and validate an equation to predict total energy expenditure (TEE) based on anthropometric measurements and physical activity questionnaires that can be applied among non-institutionalized Mexican adults. To meet this aim, a validation study was conducted with a sample of Mexican adults (n=115, 37% men) that were randomly divided into two groups to develop and validate new equations to estimate TEE. TEE was measured by indirect calorimetry and heart rate monitoring for at least three days. These measurements were considered as the reference method. The predictors of TEE were age, sex, fat and fat-free mass, body weight and physical activity level (PAL), which was assessed with two questions. The accuracy of factorial methods (e.g. FAO/WHO or Ainsworth’s metabolic equivalents list) and empirical equations to estimate TEE was compared. Multiple linear regression and Intra-class correlation coefficients were estimate as agreement measurement. The equation developed is as follows: TEE (kcal / d) = 1331.712 - (686.344 x sex, men: 1, women: 2) + (18,051 x body weight, kg) - (16.020 x age, years) + (894.007 x PAL). The accuracy of the equation was modest in the development (R2 = 54.4, standard error = 511.3) and validation (R2 = 59.2, standard error = 372.8) samples. However, this equation had higher accuracy than factorial methods or empirical equations. The equation was developed to estimate the TEE of Mexican adults, which can be used as a general guide to provide nutritional counselling.

Author Biographies

César Iván Ayala-Guzmán

Doctorate in Biological and Health Sciences, Universidad Autónoma Metropolitana.

Lic.

Health Care Department. Universidad Autónoma Metropolitana Unidad Xochimilco

Ricardo López Solís

Health Care Department, Universidad Autónoma Metropolitana Xochimilco

Mariana Tejeda Espinosa

Health Care Department, Universidad Autónoma Metropolitana Xochimilco

References

American College of Cardiology/American Heart Association Task Force on Practice Guidelines OEP, 2013. Executive summary: Guidelines (2013) for the management of overweight and obesity in adults. Obesity. 2014;22 Suppl 2:S5-39.

Academy of Nutrition and Dietetics (2015) Adult Weight Management: Executive Summary of Recommendations (2014). [Available from: https://www.andeal.org/vault/pq130.pdf]

Pinheiro Volp AC, Esteves de Oliveira FC, Duarte Moreira Alves R, Esteves EA, Bressan J. Energy expenditure: components and evaluation methods. Nutr Hosp. 2011;26(3):430-40.

Chung N, Park MY, Kim J, Park HY, Hwang H, Lee CH, et al. Non-exercise activity thermogenesis (NEAT): a component of total daily energy expenditure. J Exerc Nutr & Biochemistry. 2018;22(2):23-30.

Melby C, Paris HL, Foright R. Chapter 10. Energy balance. In: Karpinski C, Rosenbloom CA, eds. Sports nutrition. A handbook for professionals. Sports, cardiovascular, and wellness nutrition dietetics practice group. Chicago, IL: Academy of Nutrition and Dietetics; 2017:191-217.

Redondo RB. Gasto energético en reposo. Métodos de evaluación y aplicaciones. Rev Esp Nutr Comunitaria. 2015;21(1):243-251.

Hasson RE, Howe CA, Jones BL, Freedson PS. Accuracy of four resting metabolic rate prediction equations: effects of sex, body mass index, age, and race/ethnicity. J Sci Med Sport. 2011;14(4):344-351.

Orozco-Ruiz X, Pichardo`-Ontiveros E, Tovar AR, Torres N, Medina-Vera I, Prinelli F, et al. Development and validation of new predictive equation for resting energy expenditure in adults with overweight and obesity. Clin Nutr. 2018;37(6 Pt A):2198-205.

Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51(2):241-247.

Food and Agriculture Organization. Human energy requirements. Rome, Italy: FAO/WHO/UNU; 2001.

Institute of Medicine. Dietary Reference Intakes. Washington, DC: The National Academies Press; 2005.

Harris JA, Benedict FG. A biometric study of human basal metabolism. PNAS. 1918;4(12):370-373.

Ainsworth BE, Haskell WL, Herrmann SD, et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011;43(8):1575-1581.

Haneda M, Noda M, Origasa H, Noto H, Yabe D, Fujita Y, et al. Japanese Clinical Practice Guideline for Diabetes 2016. J Diabetes Investig. 2018.

Algina J, Moulder BC, Moser BK. Sample Size Requirements for Accurate Estimation of Squared Semi-Partial Correlation Coefficients. Multivariate Behav Res. 2002;37(1):37-57.

Johansson G, Westerterp KR. Assessment of the physical activity level with two questions: validation with doubly labeled water. Int J Obes. 2005. 2008;32(6):1031-1033.

Compher C, Frankenfield D, Keim N, Roth-Yousey L. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc. 2006;106(6):881-903.

Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol. 1949;109(1-2):1-9.

Livingstone MB, Prentice AM, Coward WA, et al. Simultaneous measurement of free-living energy expenditure by the doubly labeled water method and heart-rate monitoring. Am J Clin Nutr. 1990;52(1):59-65.

Fletcher GF, Ades PA, Kligfield P, et al. Exercise standards for testing and training: a scientific statement from the American Heart Association. Circulation. 2013;128(8):873-934.

Myers J, Forman DE, Balady GJ, et al. Supervision of exercise testing by nonphysicians: a scientific statement from the American Heart Association. Circulation. 2014;130(12):1014-1027.

Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153-156.

Lohmann TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics Books; 1988.

Habicht J. Estandarización de métodos epidemiológicos cuantitativos sobre el terreno. Bol Of Sanit Panam. 1974;75(5):375-384.

Heymsfield SB, Harp JB, Rowell PN, Nguyen AM, Pietrobelli A. How much may I eat? Calorie estimates based upon energy expenditure prediction equations. Obes Rev. 2006;7(4):361-370.

Ocobock C. The allocation and interaction model: A new model for predicting total energy expenditure of highly active humans in natural environments. Am J Human Biol. 2016;28(3):372-380.

Leonard WR, Katzmarzyk PT, Stephen MA, Ross AG. Comparison of the heart rate-monitoring and factorial methods: assessment of energy expenditure in highland and coastal Ecuadoreans. Am J Clin Nutr. 1995;61(5):1146-1152.

Alfonzo-Gonzalez G, Doucet E, Almeras N, Bouchard C, Tremblay A. Estimation of daily energy needs with the FAO/WHO/UNU 1985 procedures in adults: comparison to whole-body indirect calorimetry measurements. Eur J Clin Nutr. 2004;58(8):1125-1131.

Rennie KL, Hennings SJ, Mitchell J, Wareham NJ. Estimating energy expenditure by heart-rate monitoring without individual calibration. Med Sci Sports Exerc. 2001;33(6):939-945.

Ceesay SM, Prentice AM, Day KC, et al. The use of heart rate monitoring in the estimation of energy expenditure: a validation study using indirect whole-body calorimetry. Br J Nutr. 1989;61(2):175-186.

Published

2021-09-01

How to Cite

Ortiz-Hernandez, L., Ayala-Guzmán , C. I. ., Martínez Bolaños , R. A. ., López Solís , R. ., & Tejeda Espinosa , M. . (2021). Development and validation of an equation to predict total energy expenditure in a sample of Mexican adults. Nutrición Clínica Y Dietética Hospitalaria, 41(3). https://doi.org/10.12873/413ortiz

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Research articles

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