Advertisement

Decreased Basal Metabolic Rate Can Be an Objective Marker for Sarcopenia and Frailty in Older Males

Published:August 16, 2018DOI:https://doi.org/10.1016/j.jamda.2018.07.001

      Abstract

      Objectives

      The aim of this study is to demonstrate the ability of the basal metabolic rate (BMR) to detect frailty and sarcopenia in older males.

      Setting and Participants

      A total of 305 male patients undergoing comprehensive geriatric assessment were included in the study.

      Measures

      The frailty status was assessed with the Fried criteria. Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People criteria. BMR is calculated by bioimpedance analysis. Areas under the curves (AUCs) of receiver operating characteristic analyses were used to test the predictive accuracy of BMR in detecting sarcopenia.

      Results

      The mean age was 74.52 ± 7.51 years. Among the patients in the sample, 95 (31.1%) had sarcopenia and 55 (18%) had frailty. Patients who had a BMR <1612 kcal/d had a higher frequency of frailty than those who had a BMR ≥1612 kcal/d (67.3 vs 32.7, P < .001). Results were similar for sarcopenia (77.9 vs 22.1, P < .001). When BMR was divided by body surface area (BSA), BMR/BSA with a cut-off of 874 kcal/m2 had a sensitivity of 80% and a specificity of 68%, and the AUC was 0.82 for BMR/BSA, in diagnosing sarcopenia (P < .01). The participants without sarcopenia had a higher BMR/BSA for the unadjusted (OR = 8.00, 95% CI 4.52-14.19, P < .001) and adjusted analyses (OR = 6.60, 95% CI 3.52-12.38, P < .001).

      Conclusions

      Older male patients with sarcopenia and frailty have a higher BMR reduction. Therefore, it should be kept in mind that patients with low BMR should alert us to screen sarcopenia and frailty. BMR/BSA may play a role in objective screening to detect sarcopenia in older males.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of the American Medical Directors Association
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Kalyani R.R.
        • Corriere M.
        • Ferrucci L.
        Age-related and disease-related muscle loss: The effect of diabetes, obesity, and other diseases.
        Lancet Diabetes Endocrinol. 2014; 2: 819-829
        • Soysal P.
        • Stubbs B.
        • Lucato P.
        • et al.
        Inflammation and frailty in the elderly: A systematic review and meta-analysis.
        Ageing Res Rev. 2016; 31: 1-8
        • Cruz-Jentoft A.J.
        • Baeyens J.P.
        • Bauer J.M.
        • et al.
        Sarcopenia: European consensus on definition and diagnosis: Report of the European working group on sarcopenia in older people.
        Age Ageing. 2010; 39: 412-423
        • Fried L.P.
        • Tangen C.M.
        • Walston J.
        • et al.
        Frailty in older adults: Evidence for a phenotype.
        J Gerontol A Biol Sci Med Sci. 2001; 56: M146-M156
        • Abizanda P.
        • Romero L.
        • Sanchez-Jurado P.M.
        • et al.
        Energetics of aging and frailty: The FRADEA Study.
        J Gerontol A Biol Sci Med Sci. 2016; 71: 787-796
        • Sabounchi N.S.
        • Rahmandad H.
        • Ammerman A.
        Best-fitting prediction equations for basal metabolic rate: Informing obesity interventions in diverse populations.
        Int J Obes (Lond). 2013; 37: 1364-1370
        • Chau D.
        • Cho L.M.
        • Jani P.
        • St Jeor S.T.
        Individualizing recommendations for weight management in the elderly.
        Curr Opin Clin Nutr Metab Care. 2008; 11: 27-31
        • Elia M.
        • Ritz P.
        • Stubbs R.J.
        Total energy expenditure in the elderly.
        Eur J Clin Nutr. 2000; 54: S92-S103
        • Schrack J.A.
        • Knuth N.D.
        • Simonsick E.M.
        • Ferrucci L.
        “IDEAL” aging is associated with lower resting metabolic rate: The Baltimore Longitudinal Study of Aging.
        J Am Geriatr Soc. 2014; 62: 667-672
        • Ruggiero C.
        • Metter E.J.
        • Melenovsky V.
        • et al.
        High basal metabolic rate is a risk factor for mortality: The Baltimore Longitudinal Study of Aging.
        J Gerontol A Biol Sci Med Sci. 2008; 63: 698-706
        • Unutmaz G.D.
        • Soysal P.
        • Tuven B.
        • Isik A.T.
        Costs of medication in older patients: Before and after comprehensive geriatric assessment.
        Clin Interv Aging. 2018; 13: 607-613
        • Selekler K.C.B.
        • Uluc S.
        Power of Discrimination of Montreal cognitive assessment (MOCA) scale in Turkish patients with mild cognitive impairment and Alzheimer's disease.
        Turk J Geriatr. 2010; 13: 166-171
        • Gungen C.
        • Ertan T.
        • Eker E.
        • et al.
        Reliability and validity of the standardized Mini Mental State Examination in the diagnosis of mild dementia in Turkish population [in Turkish].
        Turk J Psychiatry. 2002; 13: 273-281
        • Durmaz B.
        • Soysal P.
        • Ellidokuz H.
        • Isik A.T.
        Validity and reliability of geriatric depression Scale–15 (short Form) in Turkish older adults.
        North Clin Istanb. 2018; 5: 216-220
        • Lawton M.P.
        • Brody E.M.
        Assessment of older people: Self-maintaining and instrumental activities of daily living.
        Gerontologist. 1969; 9: 179-186
        • Tinetti M.E.
        Performance-oriented assessment of mobility problems in elderly patients.
        J Am Geriatr Soc. 1986; 34: 119-126
        • Guigoz Y.
        The Mini Nutritional Assessment (MNA) review of the literature—what does it tell us?.
        J Nutr Health Aging. 2006; 10 (discussion 485–487): 466-485
        • Janssen I.
        • Heymsfield S.B.
        • Baumgartner R.N.
        • Ross R.
        Estimation of skeletal muscle mass by bioelectrical impedance analysis.
        J Appl Physiol (1985). 2000; 89: 465-471
        • Cesari M.
        • Leeuwenburgh C.
        • Lauretani F.
        • et al.
        Frailty syndrome and skeletal muscle: Results from the Invecchiare in Chianti study.
        Am J Clin Nutr. 2006; 83: 1142-1148
        • Sakamoto Y.
        • Nishizawa M.
        • Sato H.
        • et al.
        International comparison: Resting energy expenditure prediction models.
        Am J Clin Nutr. 2002; 75: 358S-359S
        • Mosteller R.D.
        Simplified calculation of body-surface area.
        N Engl J Med. 1987; 317: 1098
        • Santilli V.
        • Bernetti A.
        • Mangone M.
        • Paoloni M.
        Clinical definition of sarcopenia.
        Clin Cases Miner Bone Metab. 2014; 11: 177-180
        • Janssen I.
        • Shepard D.S.
        • Katzmarzyk P.T.
        • Roubenoff R.
        The healthcare costs of sarcopenia in the United States.
        J Am Geriatr Soc. 2004; 52: 80-85
        • Gallagher D.
        • Belmonte D.
        • Deurenberg P.
        • et al.
        Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass.
        Am J Physiol. 1998; 275: E249-E258
        • Malmstrom T.K.
        • Morley J.E.
        • SARC-F
        A simple questionnaire to rapidly diagnose sarcopenia.
        J Am Med Dir Assoc. 2013; 14: 531-532
        • Goodman M.J.
        • Ghate S.R.
        • Mavros P.
        • et al.
        Development of a practical screening tool to predict low muscle mass using NHANES 1999-2004.
        J Cachexia Sarcopenia Muscle. 2013; 4: 187-197
        • Ishii S.
        • Tanaka T.
        • Shibasaki K.
        • et al.
        Development of a simple screening test for sarcopenia in older adults.
        Geriatr Gerontol Int. 2014; 14: 93-101
        • Locquet M.
        • Beaudart C.
        • Reginster J.Y.
        • et al.
        Comparison of the performance of five screening methods for sarcopenia.
        Clin Epidemiol. 2018; 10: 71-82
        • Alencar M.A.
        • Dias J.M.
        • Figueiredo L.C.
        • Dias R.C.
        Handgrip strength in elderly with dementia: Study of reliability.
        Rev Bras Fisioter. 2012; 16: 510-514
        • Rolland Y.
        • Lauwers-Cances V.
        • Cournot M.
        • et al.
        Sarcopenia, calf circumference, and physical function of elderly women: A cross-sectional study.
        J Am Geriatr Soc. 2003; 51: 1120-1124
        • Kamiya K.
        • Masuda T.
        • Matsue Y.
        • et al.
        Prognostic usefulness of arm and calf circumference in patients >/=65 years of age with cardiovascular disease.
        Am J Cardiol. 2017; 119: 186-191
        • Marra M.
        • Pasanisi F.
        • Scalfi L.
        • et al.
        The prediction of basal metabolic rate in young adult, severely obese patients using single-frequency bioimpedance analysis.
        Acta Diabetol. 2003; 40: S139-S141
        • Altay M.A.
        • Erturk C.
        • Sert C.
        • et al.
        Bioelectrical impedance analysis of basal metabolic rate and body composition of patients with femoral neck fractures versus controls.
        Eklem Hastalik Cerrahisi. 2012; 23: 77-81
        • Sert C.
        • Altindag O.
        • Sirmatel F.
        Determination of basal metabolic rate and body composition with bioelectrical impedance method in children with cerebral palsy.
        J Child Neurol. 2009; 24: 237-240
        • Utaka S.
        • Avesani C.M.
        • Draibe S.A.
        • et al.
        Inflammation is associated with increased energy expenditure in patients with chronic kidney disease.
        Am J Clin Nutr. 2005; 82: 801-805
        • Aversa Z.
        • Costelli P.
        • Muscaritoli M.
        Cancer-induced muscle wasting: Latest findings in prevention and treatment.
        Ther Adv Med Oncol. 2017; 9: 369-382
        • Kim S.
        • Welsh D.A.
        • Ravussin E.
        • et al.
        An elevation of resting metabolic rate with declining health in nonagenarians may be associated with decreased muscle mass and function in women and men, respectively.
        J Gerontol A Biol Sci Med Sci. 2014; 69: 650-656
        • Wilson M.M.
        • Morley J.E.
        Invited review: Aging and energy balance.
        J Appl Physiol (1985). 2003; 95: 1728-1736
        • Cesari M.
        • Landi F.
        • Vellas B.
        • et al.
        Sarcopenia and physical frailty: Two sides of the same coin.
        Front Aging Neurosci. 2014; 6: 192
        • Yeolekar M.E.
        • Sukumaran S.
        Frailty syndrome: A review.
        J Assoc Physicians India. 2014; 62: 34-38
        • Boirie Y.
        Physiopathological mechanism of sarcopenia.
        J Nutr Health Aging. 2009; 13: 717-723
        • Campbell W.W.
        • Leidy H.J.
        Dietary protein and resistance training effects on muscle and body composition in older persons.
        J Am Coll Nutr. 2007; 26: 696s-703s
        • Baumgartner R.N.
        • Waters D.L.
        • Gallagher D.
        • et al.
        Predictors of skeletal muscle mass in elderly men and women.
        Mech Ageing Dev. 1999; 107: 123-136
        • Juul A.
        • Skakkebaek N.E.
        Androgens and the ageing male.
        Hum Reprod Update. 2002; 8: 423-433

      Linked Article

      • Basal Metabolic Rate Parameters, Sarcopenia, and Frailty in Older Males
        Journal of the American Medical Directors AssociationVol. 20Issue 7
        • Preview
          I read the recent article published in this journal by Soysal et al1 with interest. The authors conducted a cross-sectional study to evaluate the association between the basal metabolic rate (BMR) with several adjustments, frailty, and sarcopenia in 305 older males. Several comprehensive geriatric assessment (CGA) parameters were also used for the analysis, and the predictive ability of BMR parameters was evaluated for detecting sarcopenia, frailty, and CGA status. The adjusted odds ratio (95% confidence interval) of subjects without sarcopenia for higher BMR per body surface area (BSA) was 6.60 (3.52-12.38).
        • Full-Text
        • PDF