ABSTRACT BACKGROUND/OBJECTIVES Resting energy expenditure (REE) constitutes the largest component of total energy expenditure and undergoes an age-related decline that is unexplained by

decreased fat-free mass. Phase angle (PhA) is a cellular health indicator that is possibly associated with REE. We investigated the association of REE and PhA in hospitalized older adults.

SUBJECTS/METHODS This single-center, cross-sectional analysis utilized the baseline data from a prospective longitudinal study and included 131 eligible patients aged ≥70 years. The REE was

measured using indirect calorimetry, and PhA and body composition were assessed using bioelectrical impedance. The association between REE, PhA, and body composition was examined, and REE

association between REE and PhA and skeletal muscle mass (standardized _β_ [95% CI]; 28.072 [2.188–53.956], _p_ = 0.035) without any significant interaction between PhA and age on REE. The

low PhA group had a significantly lower REE (kcal/day; 890 [856–925] vs. 1077 [1033–1122], _p_ < 0.001), and this remained significant after adjusting for age, sex, and skeletal muscle

mass index. CONCLUSIONS PhA is associated with REE in older adults. Adjusting REE calculation algorithms based on PhA values and correcting predicted REE according to PhA may aid in

determining more accurate energy requirements. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access

through your institution Subscribe to this journal Receive 12 print issues and online access $259.00 per year only $21.58 per issue Learn more Buy this article * Purchase on SpringerLink *

Instant access to full article PDF Buy now Prices may be subject to local taxes which are calculated during checkout ADDITIONAL ACCESS OPTIONS: * Log in * Learn about institutional

subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS THE EFFECT OF AGE AND BODY MASS INDEX ON ENERGY EXPENDITURE OF CRITICALLY ILL MEDICAL PATIENTS

Article Open access 16 September 2020 24-H ENERGY EXPENDITURE IN PEOPLE WITH TYPE 1 DIABETES: IMPACT ON EQUATIONS FOR CLINICAL ESTIMATION OF ENERGY EXPENDITURE Article 14 May 2024 MEASURED

VS ESTIMATED RESTING ENERGY EXPENDITURE IN CHILDREN AND ADOLESCENTS WITH OBESITY Article Open access 14 August 2023 DATA AVAILABILITY The datasets generated during and/or analyzed during the

current study are not publicly available due to privacy reasons and ethical restrictions related to patient data but are available from the corresponding author upon reasonable request.

REFERENCES * Kyu HH, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy

life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1859–922. Article  Google Scholar  *

Maeda K, Ishida Y, Nonogaki T, Mori N. Reference body mass index values and the prevalence of malnutrition according to the Global Leadership Initiative on Malnutrition criteria. Clin Nutr.

2020;39:180–4. Article  PubMed  Google Scholar  * Leij-Halfwerk S, Verwijs MH, van Houdt S, Borkent JW, Guaitoli PR, Pelgrim T, et al. Prevalence of protein-energy malnutrition risk in

European older adults in community, residential and hospital settings, according to 22 malnutrition screening tools validated for use in adults ≥65 years: a systematic review and

meta-analysis. Maturitas. 2019;126:80–9. Article  PubMed  Google Scholar  * Schuetz P, Fehr R, Baechli V, Geiser M, Deiss M, Gomes F, et al. Individualised nutritional support in medical

inpatients at nutritional risk: a randomised clinical trial. Lancet. 2019;393:2312–21. Article  PubMed  Google Scholar  * Bendavid I, Lobo DN, Barazzoni R, Cederholm T, Coëffier M, De Van

Der Schueren M, et al. The centenary of the Harris–Benedict equations: How to assess energy requirements best? Recommendations from the ESPEN expert group. Clinical Nutrition.

2021;40:690–701. Article  PubMed  Google Scholar  * Zusman O, Theilla M, Cohen J, Kagan I, Bendavid I, Singer P. Resting energy expenditure, calorie and protein consumption in critically ill

patients: a retrospective cohort study. Crit Care. 2016;20:367. Article  PubMed  PubMed Central  Google Scholar  * Omura T, Tamura Y, Yamaoka T, Yoshimura Y, Sakurai T, Umegaki H, et al.

Assessing the association between optimal energy intake and all‐cause mortality in older patients with diabetes mellitus using the Japanese Elderly Diabetes Intervention Trial. Geriatr

Gerontol Int. 2020;20:59–65. Article  PubMed  Google Scholar  * Soares MJ, Müller MJ. Resting energy expenditure and body composition: critical aspects for clinical nutrition. Eur J Clin

Nutr. 2018;72:1208–14. Article  CAS  PubMed  Google Scholar  * Achamrah N, Delsoglio M, De Waele E, Berger MM, Pichard C. Indirect calorimetry: the 6 main issues. Clin Nutr. 2021;40:4–14.

Article  PubMed  Google Scholar  * Pontzer H, Yamada Y, Sagayama H, Ainslie PN, Andersen LF, Anderson LJ, et al. Daily energy expenditure through the human life course. Science.

2021;373:808–12. Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Manini TM. Energy expenditure and aging. Ageing Res Rev. 2010;9:1–11. Article  CAS  PubMed  Google Scholar  *

Ward LC, Brantlov S. Bioimpedance basics and phase angle fundamentals. Rev Endocr Metab Disord. 2023;24:381–91. Article  PubMed  PubMed Central  Google Scholar  * Norman K, Stobäus N,

Pirlich M, Bosy-Westphal A. Bioelectrical phase angle and impedance vector analysis–clinical relevance and applicability of impedance parameters. Clin Nutr. 2012;31:854–61. Article  PubMed 

Google Scholar  * Slee A, Birc D, Stokoe D. Bioelectrical impedance vector analysis, phase-angle assessment and relationship with malnutrition risk in a cohort of frail older hospital

patients in the United Kingdom. Nutrition. 2015;31:132–7. Article  PubMed  Google Scholar  * Yamada Y, Yoshida T, Murakami H, Kawakami R, Gando Y, Ohno H. et al. Phase angle obtained via

bioelectrical impedance analysis and objectively measured physical activity or exercise habits. Sci Rep. 2022;12:17274. Article  ADS  PubMed  PubMed Central  Google Scholar  * Norman K,

Herpich C, Müller-Werdan U. Role of phase angle in older adults with focus on the geriatric syndromes sarcopenia and frailty. Rev Endocr Metab Disord. 2023;24:429–37. Article  PubMed  Google

Scholar  * Martins PC, Alves Junior CAS, Silva AM, Silva DAS. Phase angle and body composition: a scoping review. Clin Nutr ESPEN. 2023;56:237–50. Article  PubMed  Google Scholar  * Garlini

LM, Alves FD, Ceretta LB, Perry IS, Souza GC, Clausell NO. Phase angle and mortality: a systematic review. Eur J Clin Nutr. 2019;73:495–508. Article  PubMed  Google Scholar  * Marra M, Di

Vincenzo O, Cioffi I, Sammarco R, Morlino D, Scalfi L. Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and

bioelectrical impedance analysis derived phase angle. J Int Soc Sports Nutr. 2021;18:68. Article  PubMed  PubMed Central  Google Scholar  * Marra M, Cioffi I, Sammarco R, Santarpia L,

Contaldo F, Scalfi L, et al. Are raw BIA variables useful for predicting resting energy expenditure in adults with obesity? Nutrients. 2019;11:216. Article  CAS  PubMed  PubMed Central 

Google Scholar  * Marra M, Sammarco R, Cioffi I, Morlino D, Di Vincenzo O, Speranza E, et al. New predictive equations for estimating resting energy expenditure in subjects with normal

weight and overweight. Nutrition. 2021;84:111105. Article  PubMed  Google Scholar  * Kojima G, Iliffe S, Taniguchi Y, Shimada H, Rakugi H, Walters K. Prevalence of frailty in Japan: a

systematic review and meta-analysis. J Epidemiol. 2017;27:347–53. Article  PubMed  Google Scholar  * Weir JB. New methods for calculating metabolic rate with special reference to protein

metabolism. J Physiol. 1949;109:1–9. Article  PubMed  PubMed Central  Google Scholar  * Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in

longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83. Article  CAS  PubMed  Google Scholar  * Rubenstein LZ, Harker JO, Salvà A, Guigoz Y, Vellas B. Screening for

undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci. 2001;56:M366–72. Article  CAS  PubMed  Google Scholar  *

Prados-Torres A, Calderón-Larrañaga A, Hancco-Saavedra J, Poblador-Plou B, van den Akker M. Multimorbidity patterns: a systematic review. J Clin Epidemiol. 2014;67:254–66. Article  PubMed 

Google Scholar  * Yamada M, Kimura Y, Ishiyama D, Nishio N, Otobe Y, Tanaka T, et al. Phase angle is a useful indicator for muscle function in older adults. J Nutr Health Aging.

2019;23:251–5. Article  CAS  PubMed  Google Scholar  * Cederholm T, Jensen GL, Correia M, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition—a

consensus report from the global clinical nutrition community. Clin Nutr. 2019;38:1–9. Article  CAS  PubMed  Google Scholar  * Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K,

et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21:300–7.e2. Article  PubMed  Google Scholar  * Mukaka MM.

Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24:69–71. CAS  PubMed  PubMed Central  Google Scholar  * Iacobucci D,

Schneider MJ, Popovich DL, Bakamitsos GA. Mean centering, multicollinearity, and moderators in multiple regression: the reconciliation redux. Behav Res Methods. 2017;49:403–4. Article 

PubMed  Google Scholar  * R Core Team. R: A Language and Environment for Etatistical Computing. Vienna, Austria: R Foundation for Statistical Computing. 2023. https://R-project.org/. *

Austin PC, Steyerberg EW. The number of subjects per variable required in linear regression analyses. J Clin Epidemiol. 2015;68:627–36. Article  PubMed  Google Scholar  * Harrell FE Jr., Lee

KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87. Article  PubMed

  Google Scholar  * Marra M, Cioffi I, Morlino D, Vincenzo OD, Pagano MC, Imperatore N, et al. New predictive equations for estimating resting energy expenditure in adults with Crohn’s

disease. J Parenter Enteral Nutr. 2020;44:1021–8. Article  Google Scholar  * Müller MJ, Geisler C, Hübers M, Pourhassan M, Braun W, Bosy-Westphal A. Normalizing resting energy expenditure

across the life course in humans: challenges and hopes. Eur J Clin Nutr. 2018;72:628–37. Article  PubMed  Google Scholar  * Neelemaat F, van Bokhorst-de van der Schueren MA, Thijs A, Seidell

JC, Weijs PJ. Resting energy expenditure in malnourished older patients at hospital admission and three months after discharge: predictive equations versus measurements. Clin Nutr.

2012;31:958–66. Article  PubMed  Google Scholar  * Kawase F, Masaki Y, Ozawa H, Imanaka M, Sugiyama A, Wada H, et al. Resting energy expenditure in older inpatients: a comparison of

prediction equations and measurements. Nutrients. 2022;14:5210. Article  PubMed  PubMed Central  Google Scholar  * Itoi A, Yamada Y, Yokoyama K, Adachi T, Kimura M. Validity of predictive

equations for resting metabolic rate in healthy older adults. Clin Nutr ESPEN. 2017;22:64–70. Article  PubMed  Google Scholar  * Visser M, van Venrooij LM, Wanders DC, de Vos R, Wisselink W,

van Leeuwen PA, et al. The bioelectrical impedance phase angle as an indicator of undernutrition and adverse clinical outcome in cardiac surgical patients. Clin Nutr. 2012;31:981–6. Article

  PubMed  Google Scholar  * Lahaye C, Derumeaux-Burel H, Guillet C, Pereira B, Boirie Y. Determinants of resting energy expenditure in very old nursing home residents. J Nutr Health Aging.

2022;26:872–8. Article  CAS  PubMed  Google Scholar  * Pourhassan M, Daubert D, Wirth R. Measured and predicted resting energy expenditure in malnourished older hospitalized patients: a

cross-sectional and longitudinal comparison. Nutrients. 2020;12:2240. Article  PubMed  PubMed Central  Google Scholar  * Del Giorno R, Quarenghi M, Stefanelli K, Rigamonti A, Stanglini C, De

Vecchi V, et al. Phase angle is associated with length of hospital stay, readmissions, mortality, and falls in patients hospitalized in internal-medicine wards: a retrospective cohort

study. Nutrition. 2021;85:111068. Article  PubMed  Google Scholar  * Genton L, Herrmann FR, Spörri A, Graf CE. Association of mortality and phase angle measured by different bioelectrical

impedance analysis (BIA) devices. Clin Nutr. 2018;37:1066–9. Article  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS We would like to thank the medical staff at Asuke Hospital

for their support and assistance with data collection. We would also like to thank Editage (http://www.editage.jp) for English language editing. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS *

Department of Nutrition, Asuke Hospital Aichi Prefectural Welfare Federation of Agricultural Cooperatives, Toyota, Aichi, Japan Fumiya Kawase * Graduate School of Nutritional Science,

Nagoya University of Arts and Sciences, Nisshin, Aichi, Japan Fumiya Kawase & Takayoshi Tsukahara * Department of Internal Medicine, Asuke Hospital Aichi Prefectural Welfare Federation

of Agricultural Cooperatives, Toyota, Aichi, Japan Yoshiyuki Masaki & Shinya Kobayashi * Department of Community-Based Medical Education, Nagoya City University Graduate School of

Medical Sciences, Nagoya, Japan Yoshiyuki Masaki * Department of Nursing, Asuke Hospital Aichi Prefectural Welfare Federation of Agricultural Cooperatives, Toyota, Aichi, Japan Hiroko Ozawa,

 Manami Imanaka & Aoi Sugiyama * Department of Rehabilitation Therapy, Asuke Hospital Aichi Prefectural Welfare Federation of Agricultural Cooperatives, Toyota, Aichi, Japan Hironari

Wada Authors * Fumiya Kawase View author publications You can also search for this author inPubMed Google Scholar * Yoshiyuki Masaki View author publications You can also search for this

author inPubMed Google Scholar * Hiroko Ozawa View author publications You can also search for this author inPubMed Google Scholar * Manami Imanaka View author publications You can also

search for this author inPubMed Google Scholar * Aoi Sugiyama View author publications You can also search for this author inPubMed Google Scholar * Hironari Wada View author publications

You can also search for this author inPubMed Google Scholar * Shinya Kobayashi View author publications You can also search for this author inPubMed Google Scholar * Takayoshi Tsukahara View

author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Conceptualization: FK, YM, HO, MI, AS, HW, SK, and TT; Data curation: FK, HO, HW, MI, and AS;

Formal analysis: FK; Investigation: FK, HO, HW, MI, AS, and HW; Methodology: FK, YM, and TT; Project administration: FK, YM, SK, and TT; Roles/Writing—original draft: FK; Writing—review and

editing: FK, YM, HO, MI, AS, HW, SK, and TT. All the authors have read and approved the final version of the manuscript. CORRESPONDING AUTHOR Correspondence to Fumiya Kawase. ETHICS

DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in

published maps and institutional affiliations. RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a

publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing

agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Kawase, F., Masaki, Y., Ozawa, H. _et al._ Association of resting energy expenditure with phase

angle in hospitalized older patients: a cross-sectional analysis. _Eur J Clin Nutr_ 78, 187–192 (2024). https://doi.org/10.1038/s41430-023-01370-z Download citation * Received: 30 July 2023

* Revised: 01 November 2023 * Accepted: 09 November 2023 * Published: 21 November 2023 * Issue Date: March 2024 * DOI: https://doi.org/10.1038/s41430-023-01370-z SHARE THIS ARTICLE Anyone

you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the

Springer Nature SharedIt content-sharing initiative