|Year : 2019 | Volume
| Issue : 3 | Page : 103-108
Association between the muscle mass index and physical frailty in geriatric outpatients
Purwita Wijaya Laksmi1, Nur Ainun2, Bambang Setyohadi3, Siti Setiati1, Anna Ariane3, Gunawan Tirtarahardja4
1 Division of Geriatric, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo General Hospital, Jakarta-, Indonesia
2 Department of Internal Medicine, Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo General Hospital, Jakarta-, Indonesia
3 Division of Rheumatology, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia-Dr. Cipto Mangunkusumo General Hospital, Jakarta-, Indonesia
4 Osteoporosis Center, Medistra Hospital, Jakarta-, Indonesia
|Date of Web Publication||14-Jan-2020|
Purwita Wijaya Laksmi
Division of Geriatric, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia, Dr. Cipto Mangunkusumo General Hospital, Jakarta
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Objective: Frailty syndrome is commonly seen in geriatric patients. In this study, we investigated the association between the muscle mass index and physical frailty in elderly outpatients. Materials and Methods: A cross-sectional study was conducted among elderly patients (≥60 years old) from the Geriatric Clinic of the Dr. Cipto Mangunkusumo Hospital in Jakarta, Indonesia, from April to June 2018. Each subject underwent anthropometric measurements, a frailty evaluation using the Cardiovascular Health Study questionnaire, and lean mass measurements using dual-energy X-ray absorptiometry. The appendicular lean mass (ALM) measurement was adjusted by the height squared (ALM/ht2) and by the body mass index (ALM/BMI) to indicate the muscle mass index. Results: The proportions of the frail, prefrail, and robust patients were 29.17%, 58.33%, and 12.5%, respectively. There was a significant difference in the ALM/ht2 values between the frail and nonfrail (prefrail and robust) patients (6.54 [1.01] kg/m2 vs. 7.03 [0.91] kg/m2, P = 0.01), but not in the ALM/BMI values. No significant association was observed between frailty and the muscle mass index. Multivariate analysis indicated that the frailty status was significantly associated with the nutritional status (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.59–8.49) and functional status (OR = 4.94, 95% CI = 2.01–11.75). Conclusion: Physical frailty was not significantly associated with the muscle mass index, but it was associated with the nutritional and functional statuses.
Keywords: Appendicular lean mass, elderly, muscle mass index, physical frailty
|How to cite this article:|
Laksmi PW, Ainun N, Setyohadi B, Setiati S, Ariane A, Tirtarahardja G. Association between the muscle mass index and physical frailty in geriatric outpatients. J Nat Sc Biol Med 2019;10, Suppl S1:103-8
|How to cite this URL:|
Laksmi PW, Ainun N, Setyohadi B, Setiati S, Ariane A, Tirtarahardja G. Association between the muscle mass index and physical frailty in geriatric outpatients. J Nat Sc Biol Med [serial online] 2019 [cited 2020 Oct 29];10, Suppl S1:103-8. Available from: http://www.jnsbm.org/text.asp?2019/10/3/103/275587
| Introduction|| |
Frailty syndrome describes a state of diminishing physiological reserves caused by the accumulation of multidimensional deficits due to aging, and it is inversely related to the quality of life of elderly patients. Frailty syndrome in geriatric patients makes them more susceptible to health problems, such as falls and disabilities, thereby increasing their morbidity and mortality risks.,, Various sociodemographic, biological, lifestyle, and psychological factors are related to the occurrence of frailty syndrome. In addition, sarcopenia, which describes decreases in muscle mass and function, often overlaps with frailty syndrome, or more specifically, physical frailty. The muscle weakness that precedes physical frailty can occur in middle-aged individuals. According to the frailty phenotype described by Fried et al., low muscle mass is an essential component of physical frailty;,, however, some previous studies have shown inconclusive results.,, Therefore, the aim of this study was to determine the associations between the muscle mass index and physical frailty in elderly outpatients.
| Materials and Methods|| |
This was a cross-sectional study based on the use of primary data, which received ethical clearance from the Ethical Committee of the Faculty of Medicine, Universitas Indonesia–Dr. Cipto Mangunkusumo Hospital in Jakarta, Indonesia (No. 0137/UN2.F1/ETIK/2018). All of the study patients provided written informed consent.
The study patients consisted of elderly outpatients 60 years old or older who were consecutively recruited from April to June 2018 at the Geriatric Outpatient Clinic of the Dr. Cipto Mangunkusumo Hospital in Jakarta, Indonesia. The exclusion criteria were as follows: amputated limb(s), inability to ambulate, inability to comprehend instructions, the use of artificial implants, Parkinson's or other tremor disease diagnosis, in an acute disease phase, and a bodyweight of more than 100 kg, which can affect a dual-energy X-ray absorptiometry (DXA) examination.
The frailty status of each study patient was assessed using the frailty phenotype criteria described by Fried et al. based on the Cardiovascular Health Study (CHS): Unintentional weight loss, self-reported exhaustion, weakness, a slow walking speed, and a low physical activity level. The patients were categorized as robust when they did not exhibit any of the aforementioned criteria, prefrail if they exhibited 1–2 criteria, and frail if they exhibited three or more criteria. For the statistical analysis, the prefrail and robust patients were categorized as not frail.
A 15-foot walking test at the usual pace was used to measure the walking time of each study subject. The handgrip strength of each subject's dominant hand was measured while he/she was in a sitting position using a JAMAR hydraulic handheld dynamometer (Jamar J00105; Jamar, Indiana, [Indiana], USA), which corresponded with the procedure recommended by the American Society of Hand Therapists. The highest value out of three attempts was recorded. In addition, the appendicular lean mass (ALM) was calculated for each subject as the sum of the regional lean masses of the four limbs as assessed using DXA (conducted at the Osteoporosis Centre at the Medistra Hospital in Jakarta, Indonesia). The ALM measurement then was adjusted by the height squared (ALM/ht2) and the body mass index (ALM/BMI) to indicate the muscle mass index. The low lean mass classification for the ALM/ht 2 values was based on the Asian Working Group for Sarcopenia (AWGS) criteria, and the classification for the ALM/BMI values was based on the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project criteria., The BMI was classified according to the Asia-Pacific criteria, and the nutritional status was assessed using the long form of the Mini Nutritional Assessment (MNA). The functional status was assessed using Barthel's Activities of Daily Living (ADL) index, with a maximum score of 20, which describes an individual's independence with regard to daily life activities. The patients' comorbidities were assessed using the cumulative illness rating scale (CIRS).
The data were analyzed using IBM SPSS Statistics for Windows version 20.0 (IBM Corp., Armonk, NY, USA). The α value and statistical power were set at 5% and 80%, respectively. The minimum sample size was 106 patients. The Kolmogorov–Smirnov test was used to determine the data normality. The numerical data were presented as a mean (standard deviation) if the data had a normal distribution or a median (minimum–maximum) if it did not. The categorical data were presented as a percentage. The means of the muscle mass index values of the two groups were compared using an independent t-test if the data were normally distributed or a Mann–Whitney U-test if the data were not normally distributed. A correlation test was used to determine the correlations between the walking time and handgrip strength using both muscle mass index parameters (ALM/ht 2 and ALM/BMI). The relationship between a low muscle mass and the frailty status was analyzed by using a Chi-squared test, or by using Fisher's exact test if applying an approximation method was inadequate. Bivariate logistic regression analyses were carried out for the gender, age group (≤75 years old and >75 years old), CIRS category (scores of ≤5 and >5), ADL category (independent and dependent), and MNA category (scores of ≤23.5 [malnourished and at risk of malnourishment] and >23.5 [good/normal nutritional status]), with frailty as the dependent variable. A multivariate logistic regression analysis was performed using those variables with P < 0.25 based on the bivariate analysis. For the multivariate logistic regression analysis, we used a backward elimination procedure until the model contained only those variables that contributed significantly to the model.
| Results|| |
A total of 120 patients participated in this study, and 61.7% of them were females. Based on the MNA values, more than half of the patients had normal nutritional statuses (66.67%). Based on the BMI values, almost one-third of the patients were obese and 20.8% were underweight. None of the patients had moderate to total dependency with regard to their daily life activities, and 39.17% of the patients had CIRS scores of ≤5 [Table 1].
The proportions of the frail, prefrail, and robust patients based on the CHS criteria were 29.17%, 58.33%, and 12.5%, respectively. The ALM/ht 2 values for the robust, prefrail, and frail patients were 7.17 (1.14) kg/m 2, 6.99 (0.86) kg/m 2, and 6.54 (1.01) kg/m 2, respectively. [Table 2] shows that there was a significant difference in the muscle mass index adjusted by the height squared (ALM/ht 2) values between the frail and nonfrail patients (6.54 [1.01] kg/m 2 vs. 7.03 [0.91] kg/m 2, P < 0.05). However, there was a nonsignificant result for the ALM/BMI values (P > 0.05).
There were no associations between the frailty status and the muscle mass index based on the ALM/ht 2 values (prevalence ratio [PR] = 2.03, 95% confidence interval [CI] = 0.80–5.15, P > 0.05) and the ALM/BMI values (PR = 5.09, 95% CI = 0.45–58.06, P > 0.05), as shown in [Table 3].
|Table 3: Associations between the muscle mass index and the frailty status|
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Based on the bivariate analysis [Table 4], the comorbid, nutritional, and functional statuses were the variables that had P < 0.25. The multivariate analysis revealed significant associations between the nutritional status (odds ratio [OR] = 3.67, 95% CI = 1.59–8.49, P < 0.05), the functional status (OR = 4.94, 95% CI = 2.01–11.75, P < 0.05), and the frailty status.
|Table 4: Bivariate analysis of the frailty status and the confounding factors|
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| Discussion|| |
Almost one-third of the study patients were obese, and 20.8% were underweight. More than half of the patients had normal nutritional statuses (66.67%), only 2 out of the 120 patients were malnourished and almost one-third of the patients were at risk for malnourishment. The proportion of frail patients in this study was 29.17%, while the prefrail and robust proportions were 58.33% and 12.5%, respectively. Using the same criteria [Table 5], Seto et al. found a much lower proportion (14.1%) for the frail patients. The difference between these values may be due to the higher proportion of underweight patients (20.8% vs. 4.9%, respectively) in the current study. Similar results were also seen when comparing the proportions of the patients at risk for malnourishment (31.67% vs. 18.2%, respectively). These outcomes are parallel to those of a previous study conducted by Setiati et al., wherein the nutritional status was significantly associated with the frailty status (OR = 3.75, 95%CI = 2.29–6.13).
The ALM results obtained in our study were lower than those from the study by Buckinx et al. This difference may have occurred because the study by Buckinx et al. was conducted in a Western community composed mostly of Caucasians, who tend to have greater statures than Asians. However, there was no statistically significant difference between the muscle mass index means based on the ALM/BMI values, which may be explained by the fat mass that contributes to the bodyweight included in the BMI calculation. Therefore, BMI does not fully reflect the muscle mass. In addition, the ALM/ht 2 used in this study refers to the AWGS consensus, which was intended for the Asian population, while the ALM/BMI refers to the FNIH criteria, which used data from Western Caucasians. This made it less representative when applied to Indonesia or an Asian population because the muscle mass is strongly influenced by the body size characteristics of the different races.,
The muscle mass index using the ALM/ht 2 values showed significantly stronger correlations with the handgrip strength (r = 0.543, P < 0.05) and walking time (r = −0.266, P < 0.05), when compared to the muscle mass index using the ALM/BMI values (r = 0.399, P < 0.05 and r = −0.001, P > 0.05, respectively). Similarly, in a study conducted by Han et al., the ALM/ht 2 values showed slightly stronger correlations with the handgrip strength (r = 0.171, P < 0.05) and the gait speed (in m/s; r = 0.109, P < 0.05), when compared to the ALM/BMI values (r = 0.098, P < 0.05 and r = 0.105, P < 0.05, respectively). Thus, the results of the current study support the use of the ALM/ht 2 for the muscle mass index.
There was no significant association between a low muscle mass index value and frailty syndrome based on the ALM/ht 2 values (PR = 52.03, 95% CI = 0.80–5.15, P > 0.05) or the ALM/BMI values (PR = 5.09, 95% CI = 0.45–58.06, P > 0.05). These results showed that the physical frailty was not caused by low muscle mass alone (i.e., muscle quantity), but that it was also due to decreases in the quality and function of the muscles. Several studies have suggested that muscle mass alone cannot explain the declines in muscle strength and physical function in elderly patients. For example, the Health ABC Study (The Dynamics of Health, Aging, and Body Composition) found that the age-related deterioration in the muscle strength occurs 2–5 times faster than the muscle mass deterioration. Similar studies have also reported that an increase in muscle mass did not prevent frailty and muscle strength deterioration., In addition to muscle quantity, muscle quality is one of the factors contributing to the age-related deterioration in muscle strength. Our findings corresponded to those from the European Working Group on Sarcopenia in Older People, which reported that a reduction in muscle mass does not always show a linear relationship with a decline in muscle function. We also found that the nutritional and functional statuses were significantly associated with physical frailty. Kurkcu et al. reported that malnutrition was independently associated with frailty syndrome. Thus, this study, including ours, reported results contradictory to those of Fried et al., which suggested a shift in prevention and therapy from a focus on muscle mass to a focus on muscle function by maintaining good nutrition and an active lifestyle.
This was the first study that addressed the association between the muscle mass index and physical frailty among elderly outpatients in Indonesia. Nevertheless, due to its cross-sectional design, this study was not able to draw a causal relationship between the two variables. The number of patients in this study was considered to be enough to sufficiently represent the elderly population in Indonesia, and the findings are valid. However, further analyses using other parameters, such as the muscle quality or function, nutritional status, and functional status, are needed.
| Conclusion|| |
A low lean mass cannot be used as the only predictive factor for physical frailty. Further analyses using other parameters, such as the muscle quality or function, nutritional status, and functional status, are needed. Moreover, the results of this study support the use of ALM/ht 2 values as the preferred muscle mass index values.
The authors would like to thank all the participants and the Geriatric Outpatient Clinic of Dr. Cipto Mangunkusumo Hospital, who provided immense support for our study. We are also indebted to the staff at the Osteoporosis Center at the Medistra Hospital for their kind cooperation. This study was partially funded by Publikasi Terindeks Internasional untuk Tugas Akhir Mahasiswa Universitas Indonesia Grant.
Financial support and sponsorship
The 3rd ICE on the IMERI committee supported the peer review and manuscript preparation of this article.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Morley JE, Vellas B, van Kan GA, Anker SD, Bauer JM, Bernabei R, et al.
Frailty consensus: A call to action. J Am Med Dir Assoc 2013;14:392-7.
Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet 2013;381:752-62.
Kojima G, Iliffe S, Jivraj S, Walters K. Association between frailty and quality of life among community-dwelling older people: A systematic review and meta-analysis. J Epidemiol Community Health 2016;70:716-21.
Feng Z, Lugtenberg M, Franse C, Fang X, Hu S, Jin C, et al.
Risk factors and protective factors associated with incident or increase of frailty among community-dwelling older adults: A systematic review of longitudinal studies. PLoS One 2017;12:e0178383.
Theou O, Jones GR, Overend TJ, Kloseck M, Vandervoort AA. An exploration of the association between frailty and muscle fatigue. Appl Physiol Nutr Metab 2008;33:651-65.
Evans WJ, Paolisso G, Abbatecola AM, Corsonello A, Bustacchini S, Strollo F, et al.
Frailty and muscle metabolism dysregulation in the elderly. Biogerontology 2010;11:527-36.
Limpawattana P, Kotruchin P, Pongchaiyakul C. Sarcopenia in Asia. Osteoporos Sarcopenia 2015;1:92-7.
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al.
Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146-56.
Buckinx F, Reginster JY, Brunois T, Lenaerts C, Beaudart C, Croisier JL, et al.
Prevalence of sarcopenia in a population of nursing home residents according to their frailty status: Results of the SENIOR cohort. J Musculoskelet Neuronal Interact 2017;17:209-17.
Spira D, Buchmann N, Nikolov J, Demuth I, Steinhagen-Thiessen E, Eckardt R, et al.
Association of low lean mass with frailty and physical performance: A comparison between two operational definitions of sarcopenia-data from the berlin aging study II (BASE-II). J Gerontol A Biol Sci Med Sci 2015;70:779-84.
Frisoli A Jr., Chaves PH, Ingham SJ, Fried LP. Severe osteopenia and osteoporosis, sarcopenia, and frailty status in community-dwelling older women: Results from the women's health and aging study (WHAS) II. Bone 2011;48:952-7.
Fried LP, Borhani NO, Enright P, Furberg CD, Gardin JM, Kronmal RA, et al.
The cardiovascular health study: Design and rationale. Ann Epidemiol 1991;1:263-76.
Robert HC, Denison HJ, Martin HJ, Patel HP, Syddal H, Copper C, et al
. A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardized approach. Age Ageing 2011;40:423-9.
Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al.
Sarcopenia in Asia: Consensus report of the Asian working group for sarcopenia. J Am Med Dir Assoc 2014;15:95-101.
Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, et al.
The FNIH sarcopenia project: Rationale, study description, conference recommendations, and final estimates. J Gerontol A Biol Sci Med Sci 2014;69:547-58.
World Health Organization/International Association for the Study of Obesity/International Obesity Task Force. The Asia-Pacific perspective: redefining obesity and its treatment. Melbourne: Health Communication Australia; 2000.
Guigoz Y. The mini nutritional assessment (MNA) review of the literature – What does it tell us? J Nutr Health Aging 2006;10:466-85.
Mahoney FI, Barthel DW. Functional evaluation: The barthel index. Md State Med J 1965;14:61-5.
Salvi F, Miller MD, Grilli A, Giorgi R, Towers AL, Morichi V, et al.
A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. J Am Geriatr Soc 2008;56:1926-31.
Seto E, Setiati S, Laksmi PW, Tamin TZ. Diagnostic test of a scoring system for frailty syndrome in the elderly according to cardiovascular health study, study of osteoporotic fracture and comprehensive geriatric assessment based frailty index compared with frailty index 40 items. Acta Med Indones 2015;47:183-7.
Setiati S, Laksmi PW, Aryana IGPS, Sunarti S, Widajanti N, Dwipa L, et al
. Frailty state among Indonesian elderly: Prevalence, associated factors, and frailty state transition. BMC Geriatrics. 2019;19:182.
Patrick JM, Bassey EJ, Fentem PH. Changes in body fat and muscle in manual workers at and after retirement. Eur J Appl Physiol Occup Physiol 1982;49:187-96.
Han DS, Chang KV, Li CM, Lin YH, Kao TW, Tsai KS, et al.
Skeletal muscle mass adjusted by height correlated better with muscular functions than that adjusted by body weight in defining sarcopenia. Sci Rep 2016;6:19457.
McGregor RA, Cameron-Smith D, Poppitt SD. It is not just muscle mass: A review of muscle quality, composition and metabolism during ageing as determinants of muscle function and mobility in later life. Longev Healthspan 2014;3:9.
Goodpaster BH, Park SW, Harris TB, Kritchevsky SB, Nevitt M, Schwartz AV, et al.
The loss of skeletal muscle strength, mass, and quality in older adults: The health, aging and body composition study. J Gerontol A Biol Sci Med Sci 2006;61:1059-64.
Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al.
Sarcopenia: European consensus on definition and diagnosis: Report of the European working group on sarcopenia in older people. Age Ageing 2010;39:412-23.
Kurkcu M, Meijer RI, Lonterman S, Muller M, de van der Schueren MA. The association between nutritional status and frailty characteristics among geriatric outpatients. Clin Nutr ESPEN 2018;23:112-6.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]