Sarcopenia is associated with a greater risk of polypharmacy and number of medications: a systematic review and meta‐analysis

Konstantinos Prokopidis; Panagiotis Giannos; Jean Yves Reginster; Olivier Bruyere; Mirko Petrovic; Antonio Cherubini; Konstantinos K Triantafyllidis; Konstantinos S Kechagias; Yannis Dionyssiotis; Matteo Cesari; Kinda Ibrahim; David Scott; Mario Barbagallo; Nicola Veronese; Special interest group in Systematic Reviews and Meta‐analyses and the Task Force on Pharmaceutical Strategy of the European Geriatric Medicine Society (EuGMS)

doi:10.1002/jcsm.13190

. 2023 Feb 13;14(2):671–683. doi: 10.1002/jcsm.13190

Sarcopenia is associated with a greater risk of polypharmacy and number of medications: a systematic review and meta‐analysis

Konstantinos Prokopidis ^1,^2,^✉, Panagiotis Giannos ^2,³, Jean Yves Reginster ^4,⁵, Olivier Bruyere ⁶, Mirko Petrovic ⁷, Antonio Cherubini ⁸, Konstantinos K Triantafyllidis ^2,⁹, Konstantinos S Kechagias ^2,¹⁰, Yannis Dionyssiotis ¹¹, Matteo Cesari ^12,¹³, Kinda Ibrahim ^14,¹⁵, David Scott ^16,¹⁷, Mario Barbagallo ¹⁸, Nicola Veronese ¹⁸; Special interest group in Systematic Reviews and Meta‐analyses and the Task Force on Pharmaceutical Strategy of the European Geriatric Medicine Society (EuGMS)

^¹Department of Musculoskeletal Biology, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK

^²Society of Meta‐research and Biomedical Innovation, London, UK

^³Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK

^⁴WHO Collaborating Center for Epidemiology of Musculoskeletal Health and Aging, Liège, Belgium

^⁵Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium

^⁶Division of Public Health, Epidemiology and Health Economics, WHO Collaborating Center for Public Health Aspects of Musculo‐Skeletal Health and Ageing, University of Liège, Liège, Belgium

^⁷Section of Geriatrics, Department of Internal Medicine and Paediatrics, Ghent University, Ghent, Belgium

^⁸Geriatria, Accettazione Geriatrica e Centro di Ricerca per l'Invecchiamento, IRCCS INRCA, Ancona, Italy

^⁹Department of Nutrition and Dietetics, Homerton University Hospital Foundation Trust, London, UK

^¹⁰Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK

^¹¹Medical School, Spinal Cord Injury Rehabilitation Clinic, General University Hospital Patras, University of Patras, Patras, Greece

^¹²Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy

^¹³Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, Milan, Italy

^¹⁴Academic Geriatric Medicine, Faculty of Medicine, University Hospital Southampton, University of Southampton, Southampton, UK

^¹⁵Applied Research Collaboration Wessex, The National Institute of Health and Care Research (NIHR), University of Southampton, Southampton, UK

^¹⁶Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia

^¹⁷Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia

^¹⁸Department of Internal Medicine and Geriatrics, University of Palermo, Palermo, Italy

Correspondence to: Konstantinos Prokopidis, Society of Meta‐research and Biomedical Innovation, London, UK. Email: k.prokopidis@liverpool.ac.uk

^✉

Corresponding author.

PMCID: PMC10067503 PMID: 36781175

Abstract

Polypharmacy in older adults is associated with multiple negative consequences that may affect muscular function, independently from the presence of medical conditions. The aim of this systematic review and meta‐analysis was to investigate the association of sarcopenia with polypharmacy and higher number of medications. A systematic literature search of observational studies using PubMed, Web of Science, Scopus and Cochrane Library databases was conducted from inception until June 2022. To determine if sarcopenia is associated with a higher risk of polypharmacy and increased number of medications, a meta‐analysis using a random‐effects model was used to calculate the pooled effects (CRD42022337539). Twenty‐nine studies were included in the systematic review and meta‐analysis. Sarcopenia was associated with a higher prevalence of polypharmacy (odds ratio [OR]: 1.65, 95% confidence interval [CI] [1.23, 2.20], I ² = 84%, P < 0.01) and higher number of medications (mean difference: 1.39, 95% CI [0.59, 2.19], I ² = 95%, P < 0.01) compared with individuals without sarcopenia. Using meta‐regression, a high variance was observed due to different populations (i.e., community‐dwelling, nursing home residents, inpatients, outpatients) for both outcomes of polypharmacy (r = −0.338, SE = 0.1669, 95% CI [−0.67, −0.01], z = −2.03, P = 0.04) and number of medications (r = 0.589, SE = 0.2615, 95% CI [0.08, 1.10], z = 2.25, P = 0.02). This systematic review and meta‐analysis reported a significantly increased risk of polypharmacy and higher number of medications in people with sarcopenia compared with individuals without this condition. Future research should clarify whether the specificity and number of medications is a direct contributor in accelerating the progression of muscle wasting and dysfunction contributing to sarcopenia in older adults.

Keywords: polypharmacy, medications, sarcopenia, physical function, ageing

Introduction

Polypharmacy is defined as the use of multiple concurrent medications or the simultaneous long‐term use of different drugs by the same individual. ¹ Despite that a univocal consensus has not yet established regarding the numerical definition of polypharmacy, several studies have reported that the concurrent use of five or more medications is usually sufficient for the definition of this condition. ¹

The prevalence of polypharmacy in older people is extremely wide ranging, due to differences in age, current health condition, health care setting and geographic location. ² Epidemiological data suggest that polypharmacy may affect more than one third of older people worldwide, ³ , ⁴ , ⁵ making this phenomenon of great relevance in geriatric medicine. It is widely known that polypharmacy in older populations has been associated with several negative healthcare outcomes, independent from the presence of medical conditions. For example, a large umbrella review found that, among 26 meta‐analyses, polypharmacy was associated with multiple detrimental outcomes, including adverse drug reactions, adverse drug events, disability and hospitalizations. ⁶ Interestingly, frailty is associated with less polypharmacy and higher prevalence of symptomatic drugs (i.e., laxatives, paracetamol and opioids) use among nursing home residents compared with non‐frail individuals that were prescribed primarily preventive drugs such as bisphosphonates and acetylsalicylic acid. ⁷ However, there is a growing concern about the clinical management of comorbidities and the impact of polypharmacy that could result in potentially inappropriate prescribing. ⁸ , ⁹ , ¹⁰

There has been an increasing interest in understanding the association between polypharmacy and sarcopenia—the pathological loss of muscle mass, strength and function in older people. ¹¹ Sarcopenia is associated with an increased risk of impaired physical function, ¹² hospitalization and mortality. ¹³ Polypharmacy, particularly specific drugs such as corticosteroids, ¹⁴ has shown to be associated with muscle weakness and low appendicular lean mass in older age. ¹⁵ , ¹⁶ On the other hand, there is some evidence that changes in body weight and composition as well as protein synthesis affect drug distribution and metabolism. ¹⁷ A recent scoping review of the literature found an association between sarcopenia and risk of sarcopenia and polypharmacy or the number of medications in community‐dwelling older people, but not among residents of nursing homes or hospital inpatients. ⁹ The results of that review were based on cross‐sectional data, identifying only an association rather than a causal relationship between sarcopenia and polypharmacy or number of medications. Nevertheless, the different existing definitions of sarcopenia and polypharmacy, the wide‐ranging methods of sarcopenia assessment, and the health care setting of older populations have hindered the appropriate evaluation of the relationship between polypharmacy and sarcopenia. ⁹ Specifically, antidiabetic drugs may induce transcription factors of myostatin ¹⁸ and blunt hypertrophic responses following exercise, ¹⁹ while beta‐blockers could impair muscular adaptation to exercise, reducing endurance exercise capacity. ²⁰ In addition, glucocorticoids and anti‐proliferative drugs for cancer treatment could upregulate E3 ubiquitin ligases such as atrogin1, MuRF1, and MUSA1 ¹⁴ and reduce the expression of mediators involved in mitochondrial function. ²¹ Finally, considering the association between polypharmacy and malnutrition ²² , ²³ due to potential changes in gastrointestinal microenvironment and the gut microbiota, ²⁴ deprescribing, that is, judiciously decreasing or stopping a number of medications, may improve nutritional status, ²⁵ a key contributor in improving sarcopenia status.

There is currently no systematic review and meta‐analysis exploring the quantitative differences regarding the prevalence of polypharmacy and number of medications between older adults with sarcopenia compared with those without sarcopenia. Therefore, in this meta‐analysis, we aimed to investigate the extent at which sarcopenia may amplify the risk of polypharmacy and be associated with higher number of medications. Our analyses might shed light on how multiple variables, such as different definitions of sarcopenia and polypharmacy, body composition assessment tools, geographical location, study population, health status and different age groups among older populations, could impact a polypharmacy/sarcopenia relationship.

Methods

This systematic review and meta‐analysis was conducted in accordance with the updated 2020 Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. ²⁶ The protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD: 42022337539).

Search strategy

Two independent reviewers (K. P. and K. K. T.) searched PubMed, Scopus, Web of Science and Cochrane Library from inception until June 2022. The full search strategy and the search terms used are described in the Supporting information, Table S1 ). The searches were re‐run before submission to retrieve any additional studies that met our inclusion criteria. Discrepancies in the literature search process were resolved by a third and fourth investigator (P. G. and K. S. K.).

Inclusion and exclusion criteria

Studies were included based on the following criteria: (i) baseline data from observational studies (i.e., cross‐sectional, longitudinal and case–control); (ii) adults irrespective of health status; (iii) adults aged ≥60 years; (iv) clear diagnostic criteria for sarcopenia (i.e., EWGSOP 1 and 2, AWGS, FNIH, CHS); (v) clear criteria for polypharmacy (i.e., ≥5 medications); and (vi) studies had to include both adults with and without sarcopenia. Published articles were excluded if they (i) were reviews, letters, in vivo or in vitro experiments, commentaries or posters; (ii) were not published as a full text and in English; it appears to have little impact on the effect estimates and conclusions of systematic reviews ²⁷ ; and (iii) included participants were below 60 years old.

Data extraction and risk of bias

Two authors (K. P. and K. K. T.) extracted data independently, which included the name of first author, date of publication, country of origin, participant age, study design, population studied, number of participants, health status, prevalence of polypharmacy, number of medications, and definition of polypharmacy and sarcopenia. Disagreements between authors were resolved by two independent reviewers (P. G. and K. S. K.). The quality of the included studies was evaluated using the Methodological index for non‐randomized studies (MINORS) tool ²⁸ and performed by three independent reviewers (K. P., K. K. T. and K. S. K.). MINORS is a comprehensive tool used to assess bias in nonrandomized controlled trials based on the following items: a clearly stated aim; inclusion of consecutive patients; prospective data collection; endpoints appropriate to study aim; unbiased assessment of study endpoint; follow‐up period appropriate to study aim; <5% lost to follow‐up; prospective calculation of study size; adequate control group; contemporary groups; baseline equivalence of groups; and adequate statistical analyses. According to the scoring system, MINORS' domains are scored as 0 if they are not reported, 1 when they have been reported but with inadequate details, and 2 when they have been reported while providing adequate information. The global ideal score is 16 for noncomparative studies, and a score below 8 was deemed as a high risk of bias and of some concerns, respectively.

Statistical analysis

Quantitative data were treated as continuous measurements, and changes in outcomes from sarcopenic and non‐sarcopenic individuals were compared between groups to calculate mean differences (MDs) in number of medications and the odds ratio (OR) regarding the prevalence of polypharmacy. When studies provided interquartile ranges (IQR), the formula ‘standard deviation (SD) = width of IQR/1.35’ was used to approximately calculate the missing SDs. ²⁹ Statistical significance was assessed using the random‐effects model and inverse‐variance method.

Statistical heterogeneity of outcome measurements between different studies was assessed using the overlap of their confidence interval (95% CI) and expressed as measurements of Cochran's Q (Chi‐square test) and I ². The classification of data as having low heterogeneity were based on I ² from 30% to 49%, moderate heterogeneity from 50% to 74% and high heterogeneity from 75% and above. ³⁰ In case of high heterogeneity, a random‐effects meta‐regression was conducted to explore potential sources of variability that could affect estimate rates among studies. ³¹ Subgroup analyses based on age, population studied, similar health status, definition of polypharmacy, definition of sarcopenia and geographical location were performed. Moreover, sensitivity analyses were performed to evaluate the robustness of reported statistical results by discounting the effect of existing comorbidities and risk of malnutrition that would differ between sarcopenic and non‐sarcopenic groups on outcome measurements and according to risk of bias of the included cohort studies. Further sensitivity analysis was intended to improve the accuracy of our findings by excluding studies conducted in populations with additional comorbidities in the sarcopenic compared with the group without sarcopenia that could interfere with the number of medications and/or prevalence of polypharmacy. The meta‐analysis was synthesized using Review Manager (RevMan 5.4.1) software. A P value of <0.05 was considered statistically significant.

For the evaluation of unexplained variance among studies with substantial heterogeneity, meta‐regressions were performed on the number of medications and prevalence of polypharmacy using a random‐effects model. Six and seven covariates were included in the meta‐regression related to the number of medications and prevalence of polypharmacy, respectively. Particularly, age, population of study, geographical area, risk of bias, muscle mass assessment tool, definition of sarcopenia and definition of polypharmacy were all used as individual covariates using STATA/MP 13.0.

Results

Literature search

The initial literature search provided 7426 publications. Following the exclusion of duplicates and abstracts, 43 full texts were identified as eligible for inclusion in the systematic review and meta‐analysis. Of these 43 studies, two studies were dismissed due to missing data ³² , ³³ and five studies because of usage of a screening tool for the diagnosis of sarcopenia. ³⁴ , ³⁵ , ³⁶ , ³⁷ , ³⁸ Additionally, three studies were excluded due to lack of polypharmacy definition ³⁹ , ⁴⁰ , ⁴¹ and another two ⁴² , ⁴³ due to being part of other studies, albeit one measured the number of medications ⁴⁴ while the other polypharmacy prevalence. ⁴⁵ In total, 29 studies were included in the systematic review and meta‐analysis exploring the prevalence of polypharmacy and number of medications in people with sarcopenia compared with those without sarcopenia (Figure 1 ).

Descriptive results

Seventeen studies assessed the prevalence of polypharmacy ²⁵ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ and 13 studies assessed the number of medications received. ⁴⁴ , ⁴⁶ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁷ , ⁶⁸ , ⁶⁹ , ⁷⁰ , ⁷¹ The study by Suzan et al. was included in the analysis of both groups (prevalence of polypharmacy and number of medications). ⁴⁶ Detailed characteristics of the included studies are outlined in Tables 1 and 2 .

Table 1.

Study and participant characteristics of the included studies measuring prevalence of polypharmacy.

				Sarcopenic		Non‐sarcopenic
Study, year	Country	Study design	Total n	n (M/F)	Age	n (M/F)	Age	Prevalence of Polypharmacy	Polypharmacy Definition	Sarcopenia Definition	Population
Okayama et al. 2022	Japan	Cross‐sectional	61	24 (0/24)	81.5 (8.7)	37 (0/37)	75.1 (6.7)	Sarcopenic: 18% Non‐sarcopenic: 16%	≥4 medications	AWGS	Community dwelling
Matsumoto et al. 2022	Japan	Retrospective cohort	361	196 (−/−)	78.3 (7.7) All	165 (−/−)	78.3 (7.7) All	Sarcopenic: 58.5% Non‐sarcopenic: 41.5%	≥5 medications	AWGS	Inpatients
Suzan et al. 2022	Turkey	Cross‐sectional	258	77 (23/54)	75.7 (8.0)	181 (52/129)	78.4 (7.6)	Sarcopenic: 77% Non‐sarcopenic: 61%	≥5 medications	EWGSOP 2	Community dwelling
Hsu et al. 2021	Taiwan	Cross‐sectional	102	47 (40/7)	85.1 (6.2)	55 (38/17)	78.3 (8.5)	Sarcopenic: 36.2% Non‐sarcopenic: 30.9%	≥5 medications	AWGS	Community dwelling
Jang et al. 2020	Korea	Longitudinal	1281	370	81.2 (6.6)	911	74.1 (5.7)	Sarcopenic: 29.7% Non‐sarcopenic: 19.4%	≥5 medications	EWGSOP 1 and 2	Community dwelling
Dodds et al. 2020	United Kingdom	Cross‐sectional ^c	1686	328 (147/181)	69–70	1358 (677/681)	69–70	Sarcopenic: 40.3% Non‐sarcopenic: 16.2%	≥5 medications	EWGSOP 2 ^a	Community dwelling
Sazlina et al. 2020	Malaysia	Cross‐sectional ^c	506	144 (69/75)	Multiples ages; most below 80 years	363 (133/229)	Multiple Ages; most below 80 years	Sarcopenic: 25% Non‐sarcopenic: 75%	≥5 medications	AWGS	Community dwelling
Su et al. 2019	Japan	Cross‐sectional	310	25 (9/16)	77.8 (5.5)	285 (143/142)	76.0 (5.8) ^d	Sarcopenic: 29.1% Non‐sarcopenic: 52%	≥5 medications	EWGSOP 2	Community dwelling
Agosta et al. 2019	Italy	Cross‐sectional	655	227 (115/112)	81–85	428 (200/228)	79–81	Sarcopenic: 59.9% Non‐sarcopenic: 53%	≥5 medications	EWGSOP 1	Inpatients
Kimura et al. 2018	Japan	Cross‐sectional	205	30 (8/22)	79.4 (5.0)	175 (67/108)	76.9 (5.1)	Sarcopenic: 63.3% Non‐sarcopenic: 33.7%	≥5 medications	AWGS	Outpatients
Jang et al. 2018	Korea	Longitudinal	1343	215 (82/133)	80.8 (6.3)	1128 (520/608)	75.1 (6.1)	Sarcopenic: 34.4% Non‐sarcopenic: 20.1%	≥5 medications	AWGS	Community dwelling
Hao et al. 2018	China	Cross‐sectional	407	127 (77/50)	82.0 (8.0)	280 (215/65)	81.0 (8.8)	Sarcopenic: 45% Non‐sarcopenic: 42%	≥5 medications	AWGS	Inpatients
Pérez‐Zepeda et al. 2017	Australia	Longitudinal	172	69 (−/−)	85.5 (6.8)	103 (−/−)	85.0 (6.2)	Sarcopenic: 85.5% Non‐sarcopenic: 85.4%	≥6 medications	EWGSOP 1	Inpatients
Yang et al. 2017	China	Longitudinal	288	49 (38/11)	83.7 (5.9)	239 (187/52)	80.5 (6.6)	Sarcopenic: 34.7% Non‐sarcopenic: 47.3%	≥5 medications	AWGS	Inpatients
König et al. 2017	Germany	Cross‐sectional	1502	127 (78/49)	60–84 ^e	1375 (663/712)	60–84 ^e	Sarcopenic: 16.3% Non‐sarcopenic: 6.9%	≥5 medications	FNIH Sarcopenia Project ^b	Community dwelling
Yalcin et al. 2016	Turkey	Cross‐sectional	141	41 (17/24)	82.6 (7.3)	100 (62/38)	78.0 (7.4)	Sarcopenic: 61% Non‐sarcopenic: 65%	≥5 medications	EWGSOP 1	Nursing home
Hirani et al. 2015	Australia	Longitudinal	1496	57 (57/0)	83.5 (6.1)	1439 (1439/0)	76.4 (5.2)	Sarcopenic: 52.6% Non‐sarcopenic: 36.3%	≥5 medications	FNIH Sarcopenic Project	Community dwelling

Open in a new tab

Note: Data are expressed as mean (standard deviation).

Abbreviations: AWGS, Asian Working Group for Sarcopenia; CC, calf circumference; EWGSOP, European Working Group on Sarcopenia in Older People; FNIH, Foundation for the National Institutes of Health Biomarkers Consortium; SARC‐F, strength, assistance with walking, rising from a chair, climbing stairs, and falls.

^{^a}

Assessed low handgrip strength and chair‐rising test and not muscle mass, indicating probable sarcopenia.

^{^b}

Assessed low ALM/BMI as part of sarcopenia definition.

^{^c}

Cross‐sectional data from longitudinal study.

^{^d}

Mean age of the whole cohort.

^{^e}

Mean age of the whole cohort (68.7 ± 3.7).

Table 2.

Study and participant characteristics of the included studies assessing number of medications.

			Total	Sarcopenic		Non‐sarcopenic
Study, year	Country	Study design	n	n (M/F)	Age	n (M/F)	Age	No of medications	Sarcopenia definition	Population
Formiga et al. 2022	Austria, Germany, Israel, Italy, The Netherlands, Poland and Spain	Cross‐sectional	315	41 (23/18)	83.0 (7.0)	274 (146/128)	79.0 (6.0)	Sarcopenic: 9 (4) Non‐sarcopenic: 8 (4.3)	EWGSOP 2	Community dwelling with type 2 diabetes
Remelli et al. 2022	Italy	Cross‐sectional	610	139 (89/50)	82.4 (6.8)	471 (208/263)	80.2 (6.5)	Sarcopenic: 6.1 (2.7) Non‐sarcopenic: 6.1 (2.9)	EWGSOP 2	Inpatients
Suzan et al. 2022	Turkey	Cross‐sectional	258	77 (23/54)	75.7 (8.0)	181 (52/129)	78.4 (7.6)	Sarcopenic: 77% Non‐sarcopenic: 61%	EWGSOP 2	Community dwelling
Cebria et al. 2020	Spain	Cross‐sectional	114	28 (6/22)	>65 ^≠	86 (34/52)	>65 ^c	Sarcopenic: 8.82 (3.94) Non‐sarcopenic: 0.17 (0.47)	EWGSOP 2	Institutionalized
Curcio et al. 2019	Italy	Cross‐sectional	420	55 (−/−)	80.2 (7.3)	365 (79/286)	74.7 (8.2)	Sarcopenic: 4 (1) Non‐sarcopenic: 2 (1)	EWGSOP 1	Inpatients
Pourhassan et al. 2018	Germany	Longitudinal	198	50 (20/30)	82.5 (5.7)	148 (39/109)	82.9 (6.0)	Sarcopenic: 8 [5–9] ^a Non‐sarcopenic: 9 [6–11] ^a	EWGSOP 1	Inpatients
Takahashi et al. 2018	Japan	Cross‐sectional	279	86 (23/63)	81.2 (7.4)	193 (83/110)	73.9 (6.4)	Sarcopenic: 6.0 [3.0–7.0] ^a Non‐sarcopenic: 3.0 [1.0–5.0] ^a	AWGS	Outpatients
Öztürk et al. 2018	Turkey	Cross‐sectional	230	61 (40/21)	73.3 (7.2)	169 (92/77)	72.7 (5.9)	Sarcopenic: 3.4 (3.32) Non‐sarcopenic: 3.7 (2.81)	EWGSOP 1	Outpatients
Yalcin et al. 2017	Turkey	Cross‐sectional	241	93 (52/41)	83.3 (5.7)	148 (65/83)	79.9 (6.6)	Sarcopenic: 7 [0–13] ^a Non‐sarcopenic: 6 [0–11] ^a	EWGSOP 1	Nursing home
Beaudart et al. 2015	Belgium	Longitudinal	534	73 (25/48)	77.1 (7.0)	461 (187/274)	72.9 (5.8)	Sarcopenic: 6.79 (3.14) Non‐sarcopenic: 5.66 (3.50)	EWGSOP 1	Community dwelling
Gao et al. 2015	China	Cross‐sectional	612	60 (7/53)	76.8 (6.7)	552 (247/305)	71.3 (6.4)	Sarcopenic: 2.8 (3.0) Non‐sarcopenic: 2.0 (2.1)	AWGS	Community dwelling
Halil et al. 2014	Turkey	Cross‐sectional	711	483 (257/226)	78.5 (7.4)	228 (100/128)	76.3 (7.7)	Sarcopenic: 4.8 (3.0) Non‐sarcopenic: 3.9 (2.3)	Cardiovascular Health Study ^b	Nursing home
Landi et al. 2012	Italy	Longitudinal	260	66 (45/21)	86.7 (5.4)	194 (132/62)	84.7 (4.3)	Sarcopenic: 3.1 (1.8) Non‐sarcopenic: 3.0 (2.0)	EWGSOP 1	Community dwelling

Open in a new tab

Note: Data are expressed as mean (standard deviation).

Abbreviations: AWGS, Asian Working Group for Sarcopenia; EWGSOP, European Working Group on Sarcopenia in Older People.

^{^a}

Median [interquartile range].

^{^b}

Sarcopenia was defined as low handgrip strength or low calf circumference.

^{^c}

Mean age of the whole cohort (82.03 ± 8.25).

Five studies were conducted in Japan, ²⁵ , ⁴⁷ , ⁵⁰ , ⁵⁷ , ⁶⁹ five in Turkey, ⁴⁶ , ⁵⁵ , ⁶⁶ , ⁶⁸ , ⁷⁰ four in Italy, ⁴⁴ , ⁴⁵ , ⁶³ , ⁶⁷ three in China, ⁵² , ⁵³ , ⁶⁵ two in Germany, ⁵⁴ , ⁷¹ two in Australia, ⁵⁶ , ⁶⁰ two in South Korea, ⁴⁸ , ⁵¹ one in Spain, ⁶² one in United Kingdom, ⁴⁹ one in Belgium, ⁶¹ one in Taiwan, ⁵⁹ one in Malaysia ⁵⁸ and one in multiple European countries. ⁶⁴

Eighteen studies were cross‐sectional ⁴⁴ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁵⁰ , ⁵² , ⁵⁴ , ⁵⁵ , ⁵⁷ , ⁵⁹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁸ , ⁶⁹ , ⁷⁰ and six longitudinal, ⁴⁸ , ⁵¹ , ⁵³ , ⁵⁶ , ⁶¹ , ⁶⁷ four studies utilized data from longitudinal studies ⁴⁹ , ⁵⁸ , ⁶⁰ , ⁷¹ and one was a retrospective cohort study. ²⁵ Cross‐sectional information was collected from all observational studies.

Eighteen studies included subjects with sarcopenia with mean age 80 years and above, ⁴⁴ , ⁴⁵ , ⁴⁷ , ⁴⁸ , ⁵¹ , ⁵² , ⁵³ , ⁵⁵ , ⁵⁶ , ⁵⁹ , ⁶⁰ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁷ , ⁶⁹ , ⁷⁰ , ⁷¹ while 11 studies included subjects with sarcopenia with mean age below 80 years. ²⁵ , ⁴⁶ , ⁴⁹ , ⁵⁰ , ⁵⁴ , ⁵⁷ , ⁵⁸ , ⁶¹ , ⁶⁵ , ⁶⁶ , ⁶⁸

Subjects with sarcopenia had a greater prevalence of malnutrition in eight studies as opposed to subjects without sarcopenia ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁵³ , ⁵⁵ , ⁶¹ , ⁶⁹ , ⁷¹ ; in three studies, they had greater prevalence of general comorbidities ⁴⁹ , ⁵⁶ , ⁶² ; in two studies, they had a greater prevalence of depression, ⁴⁸ , ⁶⁷ a higher prevalence of dementia ⁴⁵ , ⁴⁶ and type 2 diabetes ⁴⁶ , ⁵⁰ ; and in one study, they had higher prevalence of osteoporosis ⁶⁹ and respiratory disease. ⁵² Nevertheless, nine studies displayed similar rates of general comorbidities between subjects with sarcopenia compared with those without sarcopenia, ⁴⁴ , ⁵⁵ , ⁵⁷ , ⁵⁹ , ⁶⁰ , ⁶³ , ⁶⁵ , ⁶⁶ , ⁷¹ while in four studies, subjects without sarcopenia had a higher prevalence of hypertension ⁵² , ⁵³ , ⁵⁸ , ⁶⁴ ; in one study, they had a higher prevalence of type 2 diabetes ⁵⁸ ; and in one study, they had a higher prevalence of chronic kidney disease ⁵² compared with subjects with sarcopenia.

Finally, in three studies, there was no report of general comorbidities ²⁵ , ⁵⁴ , ⁶⁸ while in two studies, participants with comorbidities were excluded. ⁴⁷ , ⁵⁸ In 13 studies, subjects were community dwelling ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵⁴ , ⁵⁶ , ⁵⁸ , ⁵⁹ , ⁶¹ , ⁶⁴ , ⁶⁵ , ⁶⁷ ; in nine studies, subjects were inpatients ²⁵ , ⁴⁴ , ⁴⁵ , ⁵² , ⁵³ , ⁶⁰ , ⁶² , ⁶³ , ⁷¹ ; in four studies, subjects were outpatients ⁴⁶ , ⁵⁷ , ⁶⁸ , ⁶⁹ ; and in three studies, were nursing home residents. ⁵⁵ , ⁶⁶ , ⁷⁰

Definition of sarcopenia and polypharmacy

To define sarcopenia, nine studies used the EWGSOP 1 criteria, ⁴⁵ , ⁵⁵ , ⁶⁰ , ⁶¹ , ⁶³ , ⁶⁷ , ⁶⁸ , ⁷⁰ , ⁷¹ and seven studies used the EWGSOP 2 criteria ⁴⁴ , ⁴⁶ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁶² , ⁶⁴ of which one used low handgrip strength and chair‐rising test performance as a surrogate for probable sarcopenia. ⁴⁹ Furthermore, 10 studies used the AWGS criteria, ²⁵ , ⁴⁷ , ⁵¹ , ⁵² , ⁵³ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁵ , ⁶⁹ 2 studies used the FNIH Sarcopenia Project ⁵⁴ , ⁵⁶ of which one used only appendicular lean mass (ALM) to body mass index (BMI) cut‐off values, ⁵⁴ and 1 study used the Cardiovascular Health Study criteria. ⁶⁶ Details regarding the diagnostic criteria for sarcopenia in each study are described in Table 3 . Polypharmacy was defined as the use of five or more daily medications in 15 studies, ²⁵ , ⁴⁵ , ⁴⁶ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ six or more in 1 study ⁶⁰ and four or more in 1 study. ⁴⁷

Table 3.

Diagnostic criteria of sarcopenia in the included studies.

	Criteria	Studies
EWGSOP 1	Grip strength: men, <30 kg; women, <20 kg ASM (BIA): men, <8.87 kg/m²; women, <6.42 kg/m² Gait speed: ≤0.8 m/s	⁴⁵ , ⁵⁵ , ⁶³ , ⁶⁸ , ⁷⁰
	Grip strength: men, <30 kg; women, <20 kg ASM (BIA): men, <8.87 kg/m²; women, <6.42 kg/m² SPPB: ≤8 point score	⁷¹
	Grip strength: Lowest quintile adjusted for BMI & sex ASM (BIA): men, <10.76 kg/m²; women, <6.76 kg/m²	⁶⁰
	Grip strength: men, <30 kg; women, <20 kg ASM (DXA): men, <7.26 kg/m²; women, <5.5 kg/m² SPPB: ≤8 point score	⁶¹
	Grip strength: men, <30 kg; women, <20 kg Gait speed: ≤0.8 m/s Mid‐arm circumference: men, <21.1 cm; women, <19.2 cm	⁶⁷
EWGSOP 2	Grip strength: men, <27 kg; women, <16 kg ASM (BIA): men, <20 kg; women, <15 kg	⁴⁶
	Grip strength: men, <27 kg; women, <16 kg ASM (BIA): men, <20 kg; women, <15 kg SPPB: ≤8 point score	⁶⁴
	Grip strength: men, <27 kg; women, <16 kg ASM (BIA)/height²: men <7.0 kg/m²; women, <6.0 kg/m² SPPB: ≤8 point score	⁶²
	Grip strength: men, <27 kg; women, <16 kg ASM (BIA): men, <20 kg; women, <15 kg SPPB: ≤8 point score Gait speed: ≤0.8 m/s	⁴⁸
	Grip strength: men, <27 kg; women, <16 kg Chair stand; >15 sec for five rises	⁴⁹
	Grip strength: men, <27 kg; women, <16 kg ASM (BIA)/height²: men <7.0 kg/m²; women, 5.5 kg/m²	⁴⁴ , ⁵⁰
AWGS	Grip strength: women, <18 kg ASM (BIA): women, <5.7 kg/m² 5‐m chair stand test: ≥12 s	⁴⁷
	Grip strength: men, <26 kg; women, <18 kg ASM (BIA): men, <7.0 kg/m²; women, <5.7 kg/m² Gait speed: ≤0.8 m/s	⁵⁷ , ⁵⁸ , ⁵⁹
	Grip strength: men, <26 kg; women, <18 kg CC: men, <34 cm; women, <33 cm Gait speed: ≤0.8 m/s	⁶⁹
	ASM (BIA)/BMI: men, <0.789; women, <0.512 Grip strength: men, <26 kg; women, <18 kg Gait speed: ≤0.8 m/s	⁵¹
	CC: <31 cm Grip strength: men, <26 kg; women, <18 kg Gait speed: ≤0.8 m/s	⁵² , ⁶⁵
	Grip strength: men, <26 kg; women, <18 kg ASM (BIA): men, <6.7 kg/m²; women, <4.75 kg/m² Gait speed: ≤0.8 m/s	⁵³
	Grip strength: men, <26 kg; women, <18 kg ASM (BIA): men, <7.0 kg/m²; women, <5.7 kg/m²	²⁵
FNIH	ASM (DXA)/BMI: men, <0.789; women, <0.512	⁵⁴
FNIH	ASM (DXA): men, 19.75 kg Grip strength: men, <26 kg Gait speed: ≤0.8 m/s	⁵⁶
CHS	CC: <31 cm Grip strength: men (BMI ≤ 24 → ≤29 kg; BMI 24.1–28 → ≤30 kg; BMI > 28; ≤32 kg) women (BMI ≤ 23 → ≤17 kg; BMI 23.1–26 → ≤17.3 kg; BMI 26.1–29 → ≤18 kg; BMI > 29; ≤21 kg)	⁶⁶

Open in a new tab

Abbreviations: ASM, appendicular skeletal muscle; AWGS, Asian Working Group for Sarcopenia; BIA, bioelectrical impedance; BMI, body mass index; CC, calf circumference; CHS, Cardiovascular Health Study; DXA, dual‐energy x‐ray absorptiometry; EWGSOP, European Working Group on Sarcopenia in Older People; FNIH, Foundation for the National Institutes of Health Biomarkers Consortium Sarcopenia Project; SPPB, short physical performance battery.

Polypharmacy in older subjects with sarcopenia versus without sarcopenia

Our main analysis (k = 17, 2153 subjects with sarcopenia and 8861 subjects without sarcopenia) showed that sarcopenia was associated with a higher prevalence of polypharmacy (OR: 1.65, 95% CI [1.23, 2.20], I ² = 84%, P < 0.01) (Figure 2 ).

Association of polypharmacy in subjects with sarcopenia versus without sarcopenia.

Based on age, we observed a significant risk of having polypharmacy in subjects with sarcopenia below 80 years of age (k = 9, OR: 2.02, 95% CI [1.36, 3.01], I ² = 86%, P < 0.01), although no changes were observed in subjects 80 years and above (k = 8, OR: 1.27, 95% CI [0.82, 1.97], I ² = 80%, P = 0.28) (Figure S1 ).

According to similar health status, we did not find a greater risk of polypharmacy in sarcopenic versus non‐sarcopenic groups (k = 4, OR: 1.38, 95% CI [0.74, 2.56], I ² = 57%, P = 0.31) (Figure S2 ).

In addition, a significant risk in having polypharmacy was observed in community‐dwelling subjects with sarcopenia (k = 9, OR: 2.00, 95% CI [1.35, 2.97], I ² = 86%, P < 0.01) and outpatients (k = 2, OR: 2.51, 95% CI [1.55, 4.07], I ² = 0%, P < 0.01), but not in hospital inpatients (k = 5; OR: 1.11, 95% CI [0.65, 1.89], I ² = 83%, P = 0.70) (Figure S3 ).

In Europe, a significant higher risk of having polypharmacy in subjects with sarcopenia was found (k = 5, OR: 2.23, 95% CI [1.52, 3.27], I ² = 73%, P < 0.01), but not in Asia (k = 10, OR: 1.42, 95% CI [0.97, 2.07], I ² = 83%, P = 0.07) (Figure S4 ).

In terms of sarcopenia definition, a significant risk in having polypharmacy was found in older adults with sarcopenia following the EWGSOP criteria (k = 7, OR: 1.95, 95% CI [1.38, 2.76], I ² = 75%, P < 0.01); however, this risk between sarcopenic and non‐sarcopenic groups was not displayed in studies that used the AWGS criteria (k = 8, OR: 1.30, 95% CI [0.81, 2.08], I ² = 84%, P = 0.28) (Figure S5 ).

Furthermore, based on muscle mass assessment tool, a significant difference was depicted between groups evaluated via both bioelectrical impedance (BIA) (k = 12, OR: 1.54, 95% CI [1.13, 2.11], I ² = 78%, P < 0.01) and dual‐energy x‐ray absorptiometry (DXA) (k = 3, OR: 2.25, 95% CI [1.55, 3.27], I ² = 17%, P < 0.01) (Figure S6 ).

Finally, based on the polypharmacy definition, five or more medications posed a significant risk in having polypharmacy in older adults with sarcopenia versus without sarcopenia (k = 15, OR: 1.63, 95% CI [1.20, 2.21], I ² = 85%, P < 0.01) (Figure S7 ). Details of subgroup analysis are found in Table S2 .

Following multiple sensitivity analyses, no changes from the main analysis were detected following the deletion of studies including no report of fully appropriate criteria for sarcopenia definition (OR: 1.49, 95% CI [1.12, 1.98], I ² = 79%, P < 0.01) (Figure S8 ), dementia (OR: 1.58, 95% CI [1.13, 2.21], I ² = 86%, P < 0.01) (Figure S9 ), depression (OR: 1.64, 95% CI [1.18, 2.27], I ² = 85%, P < 0.01) (Figure S10 ), type 2 diabetes (OR: 1.58, 95% CI [1.15, 2.17], I ² = 86%, P < 0.01) (Figure S11 ), respiratory disease (OR: 1.75, 95% CI [1.32, 2.32], I ² = 81%, P < 0.01) (Figure S12 ), prevalence of malnutrition (OR: 1.74, 95% CI [1.21, 2.50], I ² = 87%, P < 0.01) (Figure S13 ), and high risk of bias (OR: 1.61, 95% CI [1.18, 2.21], I ² = 85%, P < 0.01) (Figure S14 ).

Number of medications in older subjects with sarcopenia versus those without sarcopenia

Our main analysis (k = 13; 1312 subjects with sarcopenia and 3470 subjects without sarcopenia) showed that the number of medications was significantly higher in older subjects with sarcopenia compared with those without sarcopenia (MD: 1.39, 95% CI [0.59, 2.19], I ² = 95%, P < 0.01) (Figure 3 ).

Association of number of medications in subjects with sarcopenia versus without sarcopenia.

Based on subgroup analyses, we observed a significantly higher number of medications in both subjects with sarcopenia and without sarcopenia below 80 years of age (k = 5, MD: 0.85, 95% CI [0.34, 1.35], I ² = 56%, P < 0.01) and 80 years and above (k = 8, MD: 1.79, 95% CI [0.49, 3.09], I ² = 97%, P < 0.01) (Figure S15 ).

In subjects with similar health status, no differences regarding the number of medications were observed between individuals with versus without sarcopenia (k = 5, MD: 0.60, 95% CI [−0.35, 1.55], I ² = 94%, P = 0.22) (Figure S16 ).

In addition, a significantly greater number of medications was found in community‐dwelling (k = 4, MD: 0.66, 95% CI [0.11, 1.21], I ² = 48%, P = 0.02) and nursing home residents (k = 2, MD: 0.90, 95% CI [0.51, 1.30], I ² = 0%, P < 0.01), but not in inpatients (k = 4, MD: 2.31, 95% CI [0.04, 4.57], I ² = 98%, P = 0.05) and outpatients (k = 3, MD: 1.49, 95% CI [−0.51, 3.48], I ² = 93%, P = 0.14) (Figure S17 ).

In Europe, a significant difference in number of medications was detected in subjects with sarcopenia (k = 11, MD: 1.30, 95% CI [0.41, 2.19], I ² = 95%, P < 0.01); however, a significant difference between groups was not established in Asia (k = 2, MD: 1.90, 95% CI [−0.25, 4.06], I ² = 94%, P = 0.08) (Figure S18 ).

Moreover, based on muscle mass assessment tool, significant differences were observed between groups via both BIA (k = 8, MD: 1.58, 95% CI [0.19, 2.98], I ² = 96%, P = 0.03) and following measurements of calf circumference (k = 3, MD: 1.55, 95% CI [0.26, 2.84], I ² = 92%, P = 0.02) (Figure S19 ).

In terms of sarcopenia definition, a significant difference was found in subjects with sarcopenia versus without sarcopenia following the EWGSOP criteria (k = 11, MD: 1.36, 95% CI [0.29, 2.43], I ² = 95%, P = 0.01); however, no changes were observed when the AWGS criteria were used (k = 2, MD: 1.90, 95% CI [−0.25, 4.06], I ² = 94%, P = 0.08) (Figure S20 ). Details of subgroup analysis are found in Table S3 .

Following multiple sensitivity analyses, no changes from the main analysis were detected following the deletion of studies that included subjects with osteoporosis (MD: 1.25, 95% CI [0.43, 2.07], I ² = 95%, P < 0.01) (Figure S21 ), depression (MD: 1.51, 95% CI [0.66, 2.37], I ² = 95%, P < 0.01) (Figure S22 ), dementia and type 2 diabetes (MD: 1.37, 95% CI [0.52, 2.21], I ² = 95%, P < 0.01) (Figure S23 ), sarcopenia definition (MD: 1.45, 95% CI [0.52, 2.38], I ² = 95%, P < 0.01) (Figure S24 ), prevalence of malnutrition (MD: 1.47, 95% CI [0.48, 2.45], I ² = 96%, P < 0.01) (Figure S25 ) and high risk of bias (MD: 1.41, 95% CI [0.59, 2.24], I ² = 95%, P < 0.01) (Figure S26 ).

Meta‐regression analyses

The increased heterogeneity observed for the prevalence of polypharmacy and number of medications in individuals with vs. without sarcopenia was further investigated via meta‐regression analyses. Differences in study population, age, risk of bias, geographical location, sarcopenia and polypharmacy definition, and muscle mass assessment tool did not explain the potentially high heterogeneity among studies in individuals with and without sarcopenia.

Regarding the prevalence of polypharmacy between individuals with and without sarcopenia, variance among studies was observed due to different populations (i.e., community dwelling, nursing home residents, inpatients and outpatients) (r = −0.338, SE = 0.1669, 95% CI [−0.67, −0.01], z = −2.03, P = 0.04), while no other covariates (i.e., age, risk of bias, geographical location, sarcopenia definition and muscle mass assessment tool) were considered potential sources of variance among included studies. Similarly, in studies measuring the number of medications, variance was explained due to different population groups (r = 0.589, SE = 0.2615, 95% CI [0.08, 1.10], z = 2.25, P = 0.02). Meta‐regression analysis according to participant health status was not feasible, considering the heterogeneity of different comorbidities assessed in multiple studies.

Risk of bias of included studies

The overall quality of the included studies was considered high (Table S4 ), although two studies were considered having a high risk of bias. ⁴⁵ , ⁷⁰

Discussion

In this systematic review with meta‐analysis, including 29 studies, we found that older subjects with sarcopenia had an increased prevalence of polypharmacy and a mean higher number of medications compared with those without sarcopenia. The meta‐regression analysis explained only a limited part of the heterogeneity found.

Both polypharmacy and sarcopenia are very common conditions among older adults. ⁹ Overall, the findings of the present study suggest that among sarcopenic older adults, the number of medications is, in mean, 1.39 higher and the prevalence of polypharmacy is 65% higher, compared with their counterparts without sarcopenia. Of importance, the association between sarcopenia and polypharmacy seems to be significant among outpatients and community dwellers, but not in hospitalized people and nursing home patients. Moreover, the diagnostic criteria used seem another important factor to consider because the association with sarcopenia was observed when this condition was diagnosed using EWGSOP criteria, but not those proposed by AWGS underlining new potential areas of research. However, it is worth noting that this observation may also be attributed to differences in populations due to variety of ethnicities and geographical areas.

Ageing itself may increase the vulnerability to a variety of adverse effects, ⁷² further complicating the importance of polypharmacy in older people having sarcopenia. In this regard, even if the studies included did not report detailed information regarding the categories of medications used, we can argue that certain medications may influence body composition, whereas other drugs may have negative effects on muscles mainly leading to malnutrition (e.g., increasing nausea or diarrhoea). ⁹ Traditionally, some medications commonly used in older people, such as glucocorticoids and antidepressants are associated with muscle toxicity, whereas others (e.g., beta blockers or non‐steroidal anti‐inflammatory drugs [NSAIDS]) might cause detrimental metabolic effects, such as mitochondrial dysfunction, diminished blood flow and electrolyte, hormonal or acid–base alterations. ⁵⁴ Further, they may also suppress acute exercise‐induced responses via reduction of gene transcription regulators such as mitogen‐activated protein kinases (MAPKs) and nuclear factor‐kappa beta (NF‐κB), ⁷³ necessary for exercise‐stimulated adaptations of the skeletal muscle. ⁷⁴ These chronic alterations may lead to blunted strength and muscle hypertrophic adaptations, ⁷⁵ although research in this area is inconclusive. ⁷⁶

Generally, polypharmacy can only be considered as an indicator for several adverse clinical outcomes, ⁶ even if a direct relationship with these outcomes has not been yet established. ⁹ It is therefore imperative to assess whether polypharmacy may play a causative role in the occurrence of sarcopenia since sarcopenia itself is associated with an increased risk of several devastating health outcomes, including disability, higher rate of surgical complications and increased mortality. ⁷⁷ At present, we can hypothesize that the association between polypharmacy and sarcopenia might be mediated by other conditions, in particular malnutrition. ²⁶

Strengths and limitations

This is the first study assessing quantitatively the relationship of polypharmacy in people living with sarcopenia and those without. We could not reliably assess publication bias because observational studies that report prevalence rates do not indicate positive or negative results, and there is currently no established method to test for publication bias. In addition, publication bias could not have been established also due to the small number of studies per definition of sarcopenia classification (i.e., EWGSOP 1 and 2) and the high heterogeneity among studies. Based on current recommendations, if the heterogeneity is high, at least 10 studies are needed to examine reporting bias using funnel plots. ⁷⁸ Furthermore, we found that those with sarcopenia below 80 years old were at an increased risk of polypharmacy versus those without sarcopenia, albeit no significant differences were found among individuals aged 80 years and above. These results raise questions in relation to the confounding factors that could have mediated this relationship between the two ageing groups; however, these covariates were not available to be accounted for in the analyses. Accordingly, a critical limitation is the lack of information on medications compiling polypharmacy in the studies included in our analysis. For example, certain medications may improve an individual's condition that may (in)directly reduce the risk of sarcopenia; hence, attention should be raised regarding appropriate versus inappropriate drug prescription. Finally, it is worth stating the possible inflation pertaining to the number of medications, which could overestimate polypharmacy status, considering the errors that may emerge by inaccurate coding of drug prescription and/or incorrect tabulations conducted electronically.

Conclusions

This systematic review and meta‐analysis clearly reported that the problem of polypharmacy in people with sarcopenia may be critical, considering its significantly increased prevalence compared with populations without sarcopenia. Polypharmacy is associated with several negative clinical outcomes in older people, including sarcopenia, raising critical questions regarding appropriate versus inappropriate drug prescription. Future research should clarify if polypharmacy is a direct contributor in accelerating the progression of sarcopenia and if inappropriate deprescribing could decelerate its progression.

Conflict of interest

The authors declare no conflicts of interest.

Supporting information

Figure S1. Supporting information

Click here for additional data file.^{(999.2KB, pdf)}

Figure S2. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S3. Supporting information

Click here for additional data file.^{(1.2MB, pdf)}

Figure S4. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S5. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S6. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S7. Supporting information

Click here for additional data file.^{(995KB, pdf)}

Figure S8. Supporting information

Click here for additional data file.^{(725.3KB, pdf)}

Figure S9. Supporting information

Click here for additional data file.^{(722.8KB, pdf)}

Figure S10. Supporting information

Click here for additional data file.^{(729.2KB, pdf)}

Figure S11. Supporting information

Click here for additional data file.^{(728.5KB, pdf)}

Figure S12. Supporting information

Click here for additional data file.^{(733.3KB, pdf)}

Figure S13. Supporting information

Click here for additional data file.^{(721KB, pdf)}

Figure S14. Supporting information

Click here for additional data file.^{(730.5KB, pdf)}

Figure S15. Supporting information

Click here for additional data file.^{(911.4KB, pdf)}

Figure S16. Supporting information

Click here for additional data file.^{(897.2KB, pdf)}

Figure S17. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S18. Supporting information

Click here for additional data file.^{(894.6KB, pdf)}

Figure S19. Supporting information

Click here for additional data file.^{(1MB, pdf)}

Figure S20. Supporting information

Click here for additional data file.^{(972.1KB, pdf)}

Figure S21. Supporting information

Click here for additional data file.^{(678.3KB, pdf)}

Figure S22. Supporting information

Click here for additional data file.^{(679KB, pdf)}

Figure S23. Supporting information

Click here for additional data file.^{(673.6KB, pdf)}

Figure S24. Supporting information

Click here for additional data file.^{(676.3KB, pdf)}

Figure S25. Supporting information

Click here for additional data file.^{(663.6KB, pdf)}

Figure S26. Supporting information

Click here for additional data file.^{(676.6KB, pdf)}

Table S1. Supporting information

Click here for additional data file.^{(13.8KB, docx)}

Table S2 and Table S3. Supporting information

Click here for additional data file.^{(24.4KB, docx)}

Table S4. Supporting information

Click here for additional data file.^{(25.1KB, docx)}

Acknowledgements

The authors of this manuscript certify that they comply with the ethical guidelines for authorship and publishing in the Journal of Cachexia, Sarcopenia and Muscle. ⁷⁹

Prokopidis K., Giannos P., Reginster J. Y., Bruyere O., Petrovic M., Cherubini A., Triantafyllidis K. K., Kechagias K. S., Dionyssiotis Y., Cesari M., Ibrahim K., Scott D., Barbagallo M., Veronese N., and Special interest group in Systematic Reviews and Meta‐analyses and the Task Force on Pharmaceutical Strategy of the European Geriatric Medicine Society (EuGMS) (2023) Sarcopenia is associated with a greater risk of polypharmacy and number of medications: a systematic review and meta‐analysis, Journal of Cachexia, Sarcopenia and Muscle, 14, 671–683, 10.1002/jcsm.13190

References

1. Masnoon N, Shakib S, Kalisch‐Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr 2017;17:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
2. Khezrian M, McNeil CJ, Murray AD, Myint PK. An overview of prevalence, determinants and health outcomes of polypharmacy. Ther Adv Drug Saf 2020;11:2042098620933741. [DOI] [PMC free article] [PubMed] [Google Scholar]
3. Midão L, Giardini A, Menditto E, Kardas P, Costa E. Polypharmacy prevalence among older adults based on the survey of health, ageing and retirement in Europe. Arch Gerontol Geriatr 2018;78:213–220. [DOI] [PubMed] [Google Scholar]
4. Pazan F, Wehling M. Polypharmacy in older adults: a narrative review of definitions, epidemiology and consequences. Eur Geriatr Med 2021;12:443–452. [DOI] [PMC free article] [PubMed] [Google Scholar]
5. Badawy NA, Labeeb SA, Alsamdan MF, Alazemi BF. Prevalence and risk of polypharmacy among community‐dwelling, elderly Kuwaiti patients. Med Princ Pract 2020;29:166–173. [DOI] [PMC free article] [PubMed] [Google Scholar]
6. Davies LE, Spiers G, Kingston A, Todd A, Adamson J, Hanratty B. Adverse outcomes of polypharmacy in plder people: systematic review of reviews. J Am Med Dir Assoc 2020;21:181–187. [DOI] [PubMed] [Google Scholar]
7. Villani ER, Vetrano DL, Liperoti R, Palmer K, Denkinger M, van der Roest HG, et al. Relationship between frailty and drug use among nursing homes residents: results from the SHELTER study. Aging Clin Exp Res 2021;33:2839–2847. [DOI] [PubMed] [Google Scholar]
8. Achterhof AB, Rozsnyai Z, Reeve E, Jungo KT, Floriani C, Poortvliet RKE, et al. Potentially inappropriate medication and attitudes of older adults towards deprescribing. PLoS ONE 2020;15:e0240463. [DOI] [PMC free article] [PubMed] [Google Scholar]
9. Pana A, Sourtzi P, Kalokairinou A, Velonaki VS. Sarcopenia and polypharmacy among older adults: a scoping review of the literature. Arch Gerontol Geriatr 2022;98:104520. [DOI] [PubMed] [Google Scholar]
10. Onder G, Vetrano DL, Palmer K, Trevisan C, Amato L, Berti F, et al. Italian guidelines on management of persons with multimorbidity and polypharmacy. Aging Clin Exp Res 2022;34:989–996. [DOI] [PMC free article] [PubMed] [Google Scholar]
11. Cruz‐Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019;48:16–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
12. Bertschi D, Kiss CM, Beerli N, Mauthner O, Kressig RW. Impact of sarcopenia on daily functioning: a cross‐sectional study among older inpatients. Aging Clin Exp Res 2022;34:2041–2046. [DOI] [PMC free article] [PubMed] [Google Scholar]
13. Fernandes LV, Paiva AEG, Silva ACB, de Castro IC, Santiago AF, de Oliveira EP, et al. Prevalence of sarcopenia according to EWGSOP1 and EWGSOP2 in older adults and their associations with unfavorable health outcomes: a systematic review. Aging Clin Exp Res 2022;34:505–514. [DOI] [PubMed] [Google Scholar]
14. Klein GL. The effect of glucocorticoids on bone and muscle. Osteoporos Sarcopenia 2015;1:39–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
15. Jensen LD, Andersen O, Hallin M, Petersen J. Potentially inappropriate medication related to weakness in older acute medical patients. Int J Clin Pharmacol 2014;36:570–580. [DOI] [PubMed] [Google Scholar]
16. Pasco JA, Mohebbi M, Holloway KL, Brennan‐Olsen SL, Hyde NK, Kotowicz MA. Musculoskeletal decline and mortality: prospective data from the Geelong Osteoporosis Study. J Cachexia Sarcopenia Muscle 2017;8:482–489. [DOI] [PMC free article] [PubMed] [Google Scholar]
17. Maher D, Ailabouni N, Mangoni AA, Wiese MD, Reeve E. Alterations in drug disposition in older adults: a focus on geriatric syndromes. Expert Opin Drug Metab Toxicol 2021;17:41–52. [DOI] [PubMed] [Google Scholar]
18. Kang MJ, Moon JW, Lee JO, Kim JH, Jung EJ, Kim SJ, et al. Metformin induces muscle atrophy by transcriptional regulation of myostatin via HDAC6 and FoxO3a. J Cachexia Sarcopenia Muscle 2022;13:605–620. [DOI] [PMC free article] [PubMed] [Google Scholar]
19. Walton RG, Dungan CM, Long DE, Tuggle SC, Kosmac K, Peck BD, et al. Metformin blunts muscle hypertrophy in response to progressive resistance exercise training in older adults: a randomized, double‐blind, placebo‐controlled, multicenter trial: The MASTERS trial. Aging Cell 2019;18:e13039. [DOI] [PMC free article] [PubMed] [Google Scholar]
20. Ladage D, Schwinger RHG, Brixius K. Cardio‐selective beta‐blocker: pharmacological evidence and their influence on exercise capacity. Cardiovasc Ther 2013;31:76–83. [DOI] [PubMed] [Google Scholar]
21. Barreto R, Mandili G, Witzmann FA, Novelli F, Zimmers TA, Bonetto A. Cancer and chemotherapy contribute to muscle loss by activating common signaling pathways. Front Physiol 2016;7:472. [DOI] [PMC free article] [PubMed] [Google Scholar]
22. Landi F, Calvani R, Tosato M, Martone AM, Ortolani E, Savera G, et al. Anorexia of aging: risk factors, consequences, and potential treatments. Nutrients 2016;8:69. [DOI] [PMC free article] [PubMed] [Google Scholar]
23. Onder G, Landi F, Fusco D, Corsonello A, Tosato M, Battaglia M, et al. Recommendations to prescribe in complex older adults: results of the CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) project. Drugs Aging 2014;31:33–45. [DOI] [PubMed] [Google Scholar]
24. Wang X, Wu M. Research progress of gut microbiota and frailty syndrome. Open Med (Wars) 2021;16:1525–1536. [DOI] [PMC free article] [PubMed] [Google Scholar]
25. Matsumoto A, Yoshimura Y, Wakabayashi H, Kose E, Nagano F, Bise T, et al. Deprescribing leads to improved energy intake among hospitalized older sarcopenic adults with polypharmacy after stroke. Nutrients 2022;14:443. [DOI] [PMC free article] [PubMed] [Google Scholar]
26. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 2021;88:105906. [DOI] [PubMed] [Google Scholar]
27. Dobrescu AI, Nussbaumer‐Streit B, Klerings I, Wagner G, Persad E, Sommer I, et al. Restricting evidence syntheses of interventions to English‐language publications is a viable methodological shortcut for most medical topics: a systematic review. J Clin Epidemiol 2021;137:209–217. [DOI] [PubMed] [Google Scholar]
28. Slim K, Nini E, Forestier D, Kwiatkowski F, Panis Y, Chipponi J. Methodological index for non‐randomized studies (MINORS): development and validation of a new instrument. ANZ J Surg 2003;73:712–716. [DOI] [PubMed] [Google Scholar]
29. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005;5:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
30. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta‐analyses. BMJ 2003;327:557–560. [DOI] [PMC free article] [PubMed] [Google Scholar]
31. Cumpston M, Li T, Page MJ, Chandler J, Welch VA, Higgins JP, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev 2019;10:ED000142. [DOI] [PMC free article] [PubMed] [Google Scholar]
32. Kuyumcu ME, Halil M, Kara O, Cuni B, Caglayan G, Guven S, et al. Ultrasonographic evaluation of the calf muscle mass and architecture in elderly patients with and without sarcopenia. Arch Gerontol Geriatr 2016;65:218–224. [DOI] [PubMed] [Google Scholar]
33. Siegert E, March C, Otten L, Makowka A, Preis E, Buttgereit F, et al. Prevalence of sarcopenia in systemic sclerosis: assessing body composition and functional disability in patients with systemic sclerosis. Nutrition 2018;55‐56:51–55. [DOI] [PubMed] [Google Scholar]
34. Wu TY, Liaw CK, Chen FC, Kuo KL, Chie WC, Yang RS. Sarcopenia screened with SARC‐F questionnaire is associated with quality of life and 4‐year mortality. J Am Med Dir Assoc 2016;17:1129–1135. [DOI] [PubMed] [Google Scholar]
35. Essomba MJN, Atsa D, Noah DZ, Zingui‐Ottou M, Paula G, Nkeck JR, et al. Geriatric syndromes in an urban elderly population in Cameroon: a focus on disability, sarcopenia and cognitive impairment. Pan Afr Med J 2020;37:229. [DOI] [PMC free article] [PubMed] [Google Scholar]
36. Tan LF, Lim ZY, Choe R, Seetharaman S, Merchant R. Screening for frailty and sarcopenia among older persons in medical outpatient clinics and its associations with healthcare burden. J Am Med Dir Assoc 2017;18:583–587. [DOI] [PubMed] [Google Scholar]
37. Sato PHR, Ferreira AA, Rosado EL. The prevalence and risk factors for sarcopenia in older adults and long‐living older adults. Arch Gerontol Geriatr 2020;89:104089. [DOI] [PubMed] [Google Scholar]
38. Tang T, Wu L, Yang L, Jiang J, Hao Q, Dong B, et al. A sarcopenia screening test predicts mortality in hospitalized older adults. Sci Rep 2018;8:2923. [DOI] [PMC free article] [PubMed] [Google Scholar]
39. Park H, Jang IY, Han M, Lee H, Jung HW, Lee E, et al. Sarcopenia is associated with severe erectile dysfunction in older adults: a population‐based cohort study. Korean J Intern Med 2020;35:1245–1253. [DOI] [PMC free article] [PubMed] [Google Scholar]
40. Vetrano DL, Landi F, Volpato S, Corsonello A, Meloni E, Bernabei R, et al. Association of sarcopenia with short‐ and long‐term mortality in older adults admitted to acute care wards: results from the CRIME study. J Gerontol A Biol Sci Med Sci 2014;69:1154–1161. [DOI] [PubMed] [Google Scholar]
41. Darroch P, O'Brien WJ, Mazahery H, Wham C. Sarcopenia prevalence and risk factors among residents in aged care. Nutrients 2022;14:1837. [DOI] [PMC free article] [PubMed] [Google Scholar]
42. Martone AM, Bianchi L, Abete P, Bellelli G, Bo M, Cherubini A, et al. The incidence of sarcopenia among hospitalized older patients: results from the Glisten study. J Cachexia Sarcopenia Muscle 2017;8:907–914. [DOI] [PMC free article] [PubMed] [Google Scholar]
43. Bianchi L, Maietti E, Abete P, Bellelli G, Bo M, Cherubini A, et al. Comparing EWGSOP2 and FNIH sarcopenia definitions: agreement and 3‐year survival prognostic value in older hospitalized adults: the GLISTEN study. J Gerontol A Biol Sci Med Sci 2020;75:1331–1337. [DOI] [PubMed] [Google Scholar]
44. Remelli F, Maietti E, Abete P, Bellelli G, Bo M, Cherubini A, et al. Prevalence of obesity and diabetes in older people with sarcopenia defined according to EWGSOP2 and FNHI criteria. Aging Clin Exp Res 2022;34:113–120. [DOI] [PMC free article] [PubMed] [Google Scholar]
45. Agosta L, Bo M, Bianchi L, Abete P, Belelli G, Cherubini A, et al. Polypharmacy and sarcopenia in hospitalized older patients: results of the GLISTEN study. Aging Clin Exp Res 2019;31:557–559. [DOI] [PubMed] [Google Scholar]
46. Suzan V, Kanat BB, Yavuzer H. Association of sarcopenia with geriatric syndromes and neutrophil/lymphocyte ratio. Medicine 2022;11:645–650. [Google Scholar]
47. Okayama A, Nakayama N, Kashiwa K, Horinouchi Y, Fukusaki H, Nakamura H, et al. Prevalence of Sarcopenia and Its Association with Quality of Life, Postural Stability, and Past Incidence of Falls in Postmenopausal Women with Osteoporosis: A Cross‐Sectional Study. Multidisciplinary Digital Publishing Institute; 2022. p 192. [DOI] [PMC free article] [PubMed] [Google Scholar]
48. Jang IY, Lee E, Lee H, Park H, Kim S, Kim KI, et al. Characteristics of sarcopenia by European consensuses and a phenotype score. J Cachexia Sarcopenia Muscle 2020;11:497–504. [DOI] [PMC free article] [PubMed] [Google Scholar]
49. Dodds RM, Murray JC, Robinson SM, Sayer AA. The identification of probable sarcopenia in early old age based on the SARC‐F tool and clinical suspicion: findings from the 1946 British birth cohort. Eur Geriatr Med 2020;11:433–441. [DOI] [PMC free article] [PubMed] [Google Scholar]
50. Su Y, Hirayama K, Han TF, Izutsu M, Yuki M. Sarcopenia prevalence and risk factors among Japanese community dwelling older adults living in a snow‐covered city according to EWGSOP2. J Clin Med 2019;8:291. [DOI] [PMC free article] [PubMed] [Google Scholar]
51. Jang IY, Jung HW, Lee CK, Yu SS, Lee YS, Lee E. Comparisons of predictive values of sarcopenia with different muscle mass indices in Korean rural older adults: a longitudinal analysis of the Aging Study of PyeongChang Rural Area. Clin Interv Aging 2018;13:91–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
52. Hao Q, Hu X, Xie L, Chen J, Jiang J, Dong B, et al. Prevalence of sarcopenia and associated factors in hospitalised older patients: a cross‐sectional study. Australas J Ageing 2018;37:62–67. [DOI] [PubMed] [Google Scholar]
53. Yang M, Hu X, Wang H, Zhang L, Hao Q, Dong B. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study. J Cachexia Sarcopenia Muscle 2017;8:251–258. [DOI] [PMC free article] [PubMed] [Google Scholar]
54. König M, Spira D, Demuth I, Steinhagen‐Thiessen E, Norman K. Polypharmacy as a risk factor for clinically relevant sarcopenia: results from the Berlin Aging Study II. J Gerontol A 2018;73:117–122. [DOI] [PubMed] [Google Scholar]
55. Yalcin A, Aras S, Atmis V, Cengiz OK, Varli M, Cinar E, et al. Sarcopenia prevalence and factors associated with sarcopenia in older people living in a nursing home in A nkara Turkey. Geriatr Gerontol Int 2016;16:903–910. [DOI] [PubMed] [Google Scholar]
56. Hirani V, Blyth F, Naganathan V, Le Couteur DG, Seibel MJ, Waite LM, et al. Sarcopenia is associated with incident disability, institutionalization, and mortality in community‐dwelling older men: the Concord Health and Ageing in Men Project. J Am Med Dir Assoc 2015;16:607–613. [DOI] [PubMed] [Google Scholar]
57. Kimura A, Sugimoto T, Niida S, Toba K, Sakurai T. Association between appetite and sarcopenia in patients with mild cognitive impairment and early‐stage Alzheimer's disease: a case‐control study. Front Nutr 2018;5:128. [DOI] [PMC free article] [PubMed] [Google Scholar]
58. Sazlina SG, Lee PY, Chan YM, Hamid MSA, Tan NC. The prevalence and factors associated with sarcopenia among community living elderly with type 2 diabetes mellitus in primary care clinics in Malaysia. Plos One 2020;15:e0233299. [DOI] [PMC free article] [PubMed] [Google Scholar]
59. Hsu YH, Liang CK, Chou MY, Wang YC, Liao MC, Chang WC, et al. Sarcopenia is independently associated with parietal atrophy in older adults. Exp Gerontol 2021;151:111402. [DOI] [PubMed] [Google Scholar]
60. Perez‐Zepeda MU, Sgaravatti A, Dent E. Sarcopenia and post‐hospital outcomes in older adults: a longitudinal study. Arch Gerontol Geriatr 2017;69:105–109. [DOI] [PubMed] [Google Scholar]
61. Beaudart C, Reginster JY, Petermans J, Gillain S, Quabron A, Locquet M, et al. Quality of life and physical components linked to sarcopenia: the SarcoPhAge study. Exp Gerontol 2015;69:103–110. [DOI] [PubMed] [Google Scholar]
62. Cebria IIMA, Arnal‐Gomez A, Tortosa‐Chulia MA, Balasch‐Bernat M, Forcano S, Sentandreu‐Mano T, et al. Functional and clinical characteristics for predicting sarcopenia in institutionalised older adults: identifying tools for clinical screening. Int J Environ Res Public Health 2020;17:4483. [DOI] [PMC free article] [PubMed] [Google Scholar]
63. Curcio F, Liguori I, Cellulare M, Sasso G, Della‐Morte D, Gargiulo G, et al. Physical Activity Scale for the Elderly (PASE) score is related to sarcopenia in noninstitutionalized older adults. J Geriatr Phys Ther 2019;42:130–135. [DOI] [PubMed] [Google Scholar]
64. Formiga F, Moreno‐Gonzalez R, Corsonello A, Carlsson A, Arnlov J, Mattace‐Raso F, et al. Diabetes, sarcopenia and chronic kidney disease; the Screening for CKD among Older People across Europe (SCOPE) study. BMC Geriatr 2022;22:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
65. Gao LL, Jiang JJ, Yang M, Hao QK, Luo L, Dong BR. Prevalence of sarcopenia and associated factors in chinese community‐dwelling elderly: comparison between rural and urban areas. J Am Med Dir Assoc 2015;16:1003.e1–1003.e6. [DOI] [PubMed] [Google Scholar]
66. Halil M, Ulger Z, Varli M, Doventas A, Ozturk GB, Kuyumcu ME, et al. Sarcopenia assessment project in the nursing homes in Turkey. Eur J Clin Nutr 2014;68:690–694. [DOI] [PubMed] [Google Scholar]
67. Landi F, Liperoti R, Russo A, Giovannini S, Tosato M, Capoluongo E, et al. Sarcopenia as a risk factor for falls in elderly individuals: results from the ilSIRENTE study. Clin Nutr 2012;31:652–658. [DOI] [PubMed] [Google Scholar]
68. Ozturk ZA, Turkbeyler IH, Abiyev A, Kul S, Edizer B, Yakaryilmaz FD, et al. Health‐related quality of life and fall risk associated with age‐related body composition changes; sarcopenia, obesity and sarcopenic obesity. Intern Med J 2018;48:973–981. [DOI] [PubMed] [Google Scholar]
69. Takahashi M, Maeda K, Wakabayashi H. Prevalence of sarcopenia and association with oral health‐related quality of life and oral health status in older dental clinic outpatients. Geriatr Gerontol Int 2018;18:915–921. [DOI] [PubMed] [Google Scholar]
70. Yalcin A, Silay K. Sarcopenia and health‐related quality of life in Turkish nursing home residents: a cross‐sectional study. Asian J Gerontol Geriatr 2017;12:42–46. [Google Scholar]
71. Pourhassan M, Norman K, Muller MJ, Dziewas R, Wirth R. Impact of sarcopenia on one‐year mortality among older hospitalized patients with impaired mobility. J Frailty Aging 2018;7:40–46. [DOI] [PubMed] [Google Scholar]
72. Baruth JM, Gentry MT, Rummans TA, Miller DM, Burton MC. Polypharmacy in older adults: the role of the multidisciplinary team. Hosp Pract (1995) 2020;48:56–62. [DOI] [PubMed] [Google Scholar]
73. Markworth JF, Vella LD, Figueiredo VC, Cameron‐Smith D. Ibuprofen treatment blunts early translational signaling responses in human skeletal muscle following resistance exercise. J Appl Physiol 2014;117:20–28. [DOI] [PubMed] [Google Scholar]
74. Kramer HF, Goodyear LJ. Exercise, MAPK, and NF‐κB signaling in skeletal muscle. J Appl Physiol 2007;103:388–395. [DOI] [PubMed] [Google Scholar]
75. Lilja M, Mandić M, Apró W, Melin M, Olsson K, Rosenborg S, et al. High doses of anti‐inflammatory drugs compromise muscle strength and hypertrophic adaptations to resistance training in young adults. Acta Physiologica 2018;222:e12948. [DOI] [PubMed] [Google Scholar]
76. Trappe TA, Carroll CC, Dickinson JM, LeMoine JK, Haus JM, Sullivan BE, et al. Influence of acetaminophen and ibuprofen on skeletal muscle adaptations to resistance exercise in older adults. Am J Physiol Regul Integr Comp Physiol 2011;300:R655–R662. [DOI] [PMC free article] [PubMed] [Google Scholar]
77. Veronese N, Demurtas J, Soysal P, Smith L, Torbahn G, Schoene D, et al. Sarcopenia and health‐related outcomes: an umbrella review of observational studies. Eur Geriatr Med 2019;10:853–862. [DOI] [PubMed] [Google Scholar]
78. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta‐analyses of randomised controlled trials. BMJ 2011;343:d4002. [DOI] [PubMed] [Google Scholar]
79. von Haehling S, Morley JE, Coats AJ, Anker SD. Ethical guidelines for publishing in the Journal of Cachexia, Sarcopenia and Muscle: update 2021. J Cachexia Sarcopenia Muscle 2021;12:2259–2261. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1. Supporting information

Click here for additional data file.^{(999.2KB, pdf)}

Figure S2. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S3. Supporting information

Click here for additional data file.^{(1.2MB, pdf)}

Figure S4. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S5. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S6. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S7. Supporting information

Click here for additional data file.^{(995KB, pdf)}

Figure S8. Supporting information

Click here for additional data file.^{(725.3KB, pdf)}

Figure S9. Supporting information

Click here for additional data file.^{(722.8KB, pdf)}

Figure S10. Supporting information

Click here for additional data file.^{(729.2KB, pdf)}

Figure S11. Supporting information

Click here for additional data file.^{(728.5KB, pdf)}

Figure S12. Supporting information

Click here for additional data file.^{(733.3KB, pdf)}

Figure S13. Supporting information

Click here for additional data file.^{(721KB, pdf)}

Figure S14. Supporting information

Click here for additional data file.^{(730.5KB, pdf)}

Figure S15. Supporting information

Click here for additional data file.^{(911.4KB, pdf)}

Figure S16. Supporting information

Click here for additional data file.^{(897.2KB, pdf)}

Figure S17. Supporting information

Click here for additional data file.^{(1.1MB, pdf)}

Figure S18. Supporting information

Click here for additional data file.^{(894.6KB, pdf)}

Figure S19. Supporting information

Click here for additional data file.^{(1MB, pdf)}

Figure S20. Supporting information

Click here for additional data file.^{(972.1KB, pdf)}

Figure S21. Supporting information

Click here for additional data file.^{(678.3KB, pdf)}

Figure S22. Supporting information

Click here for additional data file.^{(679KB, pdf)}

Figure S23. Supporting information

Click here for additional data file.^{(673.6KB, pdf)}

Figure S24. Supporting information

Click here for additional data file.^{(676.3KB, pdf)}

Figure S25. Supporting information

Click here for additional data file.^{(663.6KB, pdf)}

Figure S26. Supporting information

Click here for additional data file.^{(676.6KB, pdf)}

Table S1. Supporting information

Click here for additional data file.^{(13.8KB, docx)}

Table S2 and Table S3. Supporting information

Click here for additional data file.^{(24.4KB, docx)}

Table S4. Supporting information

Click here for additional data file.^{(25.1KB, docx)}

[jcsm13190-bib-0001] 1. Masnoon N, Shakib S, Kalisch‐Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr 2017;17:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0002] 2. Khezrian M, McNeil CJ, Murray AD, Myint PK. An overview of prevalence, determinants and health outcomes of polypharmacy. Ther Adv Drug Saf 2020;11:2042098620933741. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0003] 3. Midão L, Giardini A, Menditto E, Kardas P, Costa E. Polypharmacy prevalence among older adults based on the survey of health, ageing and retirement in Europe. Arch Gerontol Geriatr 2018;78:213–220. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0004] 4. Pazan F, Wehling M. Polypharmacy in older adults: a narrative review of definitions, epidemiology and consequences. Eur Geriatr Med 2021;12:443–452. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0005] 5. Badawy NA, Labeeb SA, Alsamdan MF, Alazemi BF. Prevalence and risk of polypharmacy among community‐dwelling, elderly Kuwaiti patients. Med Princ Pract 2020;29:166–173. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0006] 6. Davies LE, Spiers G, Kingston A, Todd A, Adamson J, Hanratty B. Adverse outcomes of polypharmacy in plder people: systematic review of reviews. J Am Med Dir Assoc 2020;21:181–187. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0007] 7. Villani ER, Vetrano DL, Liperoti R, Palmer K, Denkinger M, van der Roest HG, et al. Relationship between frailty and drug use among nursing homes residents: results from the SHELTER study. Aging Clin Exp Res 2021;33:2839–2847. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0008] 8. Achterhof AB, Rozsnyai Z, Reeve E, Jungo KT, Floriani C, Poortvliet RKE, et al. Potentially inappropriate medication and attitudes of older adults towards deprescribing. PLoS ONE 2020;15:e0240463. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0009] 9. Pana A, Sourtzi P, Kalokairinou A, Velonaki VS. Sarcopenia and polypharmacy among older adults: a scoping review of the literature. Arch Gerontol Geriatr 2022;98:104520. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0010] 10. Onder G, Vetrano DL, Palmer K, Trevisan C, Amato L, Berti F, et al. Italian guidelines on management of persons with multimorbidity and polypharmacy. Aging Clin Exp Res 2022;34:989–996. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0011] 11. Cruz‐Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019;48:16–31. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0012] 12. Bertschi D, Kiss CM, Beerli N, Mauthner O, Kressig RW. Impact of sarcopenia on daily functioning: a cross‐sectional study among older inpatients. Aging Clin Exp Res 2022;34:2041–2046. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0013] 13. Fernandes LV, Paiva AEG, Silva ACB, de Castro IC, Santiago AF, de Oliveira EP, et al. Prevalence of sarcopenia according to EWGSOP1 and EWGSOP2 in older adults and their associations with unfavorable health outcomes: a systematic review. Aging Clin Exp Res 2022;34:505–514. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0014] 14. Klein GL. The effect of glucocorticoids on bone and muscle. Osteoporos Sarcopenia 2015;1:39–45. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0015] 15. Jensen LD, Andersen O, Hallin M, Petersen J. Potentially inappropriate medication related to weakness in older acute medical patients. Int J Clin Pharmacol 2014;36:570–580. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0016] 16. Pasco JA, Mohebbi M, Holloway KL, Brennan‐Olsen SL, Hyde NK, Kotowicz MA. Musculoskeletal decline and mortality: prospective data from the Geelong Osteoporosis Study. J Cachexia Sarcopenia Muscle 2017;8:482–489. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0017] 17. Maher D, Ailabouni N, Mangoni AA, Wiese MD, Reeve E. Alterations in drug disposition in older adults: a focus on geriatric syndromes. Expert Opin Drug Metab Toxicol 2021;17:41–52. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0018] 18. Kang MJ, Moon JW, Lee JO, Kim JH, Jung EJ, Kim SJ, et al. Metformin induces muscle atrophy by transcriptional regulation of myostatin via HDAC6 and FoxO3a. J Cachexia Sarcopenia Muscle 2022;13:605–620. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0019] 19. Walton RG, Dungan CM, Long DE, Tuggle SC, Kosmac K, Peck BD, et al. Metformin blunts muscle hypertrophy in response to progressive resistance exercise training in older adults: a randomized, double‐blind, placebo‐controlled, multicenter trial: The MASTERS trial. Aging Cell 2019;18:e13039. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0020] 20. Ladage D, Schwinger RHG, Brixius K. Cardio‐selective beta‐blocker: pharmacological evidence and their influence on exercise capacity. Cardiovasc Ther 2013;31:76–83. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0021] 21. Barreto R, Mandili G, Witzmann FA, Novelli F, Zimmers TA, Bonetto A. Cancer and chemotherapy contribute to muscle loss by activating common signaling pathways. Front Physiol 2016;7:472. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0022] 22. Landi F, Calvani R, Tosato M, Martone AM, Ortolani E, Savera G, et al. Anorexia of aging: risk factors, consequences, and potential treatments. Nutrients 2016;8:69. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0023] 23. Onder G, Landi F, Fusco D, Corsonello A, Tosato M, Battaglia M, et al. Recommendations to prescribe in complex older adults: results of the CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) project. Drugs Aging 2014;31:33–45. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0024] 24. Wang X, Wu M. Research progress of gut microbiota and frailty syndrome. Open Med (Wars) 2021;16:1525–1536. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0025] 25. Matsumoto A, Yoshimura Y, Wakabayashi H, Kose E, Nagano F, Bise T, et al. Deprescribing leads to improved energy intake among hospitalized older sarcopenic adults with polypharmacy after stroke. Nutrients 2022;14:443. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0026] 26. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 2021;88:105906. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0027] 27. Dobrescu AI, Nussbaumer‐Streit B, Klerings I, Wagner G, Persad E, Sommer I, et al. Restricting evidence syntheses of interventions to English‐language publications is a viable methodological shortcut for most medical topics: a systematic review. J Clin Epidemiol 2021;137:209–217. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0028] 28. Slim K, Nini E, Forestier D, Kwiatkowski F, Panis Y, Chipponi J. Methodological index for non‐randomized studies (MINORS): development and validation of a new instrument. ANZ J Surg 2003;73:712–716. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0029] 29. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005;5:13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0030] 30. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta‐analyses. BMJ 2003;327:557–560. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0031] 31. Cumpston M, Li T, Page MJ, Chandler J, Welch VA, Higgins JP, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev 2019;10:ED000142. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0032] 32. Kuyumcu ME, Halil M, Kara O, Cuni B, Caglayan G, Guven S, et al. Ultrasonographic evaluation of the calf muscle mass and architecture in elderly patients with and without sarcopenia. Arch Gerontol Geriatr 2016;65:218–224. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0033] 33. Siegert E, March C, Otten L, Makowka A, Preis E, Buttgereit F, et al. Prevalence of sarcopenia in systemic sclerosis: assessing body composition and functional disability in patients with systemic sclerosis. Nutrition 2018;55‐56:51–55. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0034] 34. Wu TY, Liaw CK, Chen FC, Kuo KL, Chie WC, Yang RS. Sarcopenia screened with SARC‐F questionnaire is associated with quality of life and 4‐year mortality. J Am Med Dir Assoc 2016;17:1129–1135. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0035] 35. Essomba MJN, Atsa D, Noah DZ, Zingui‐Ottou M, Paula G, Nkeck JR, et al. Geriatric syndromes in an urban elderly population in Cameroon: a focus on disability, sarcopenia and cognitive impairment. Pan Afr Med J 2020;37:229. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0036] 36. Tan LF, Lim ZY, Choe R, Seetharaman S, Merchant R. Screening for frailty and sarcopenia among older persons in medical outpatient clinics and its associations with healthcare burden. J Am Med Dir Assoc 2017;18:583–587. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0037] 37. Sato PHR, Ferreira AA, Rosado EL. The prevalence and risk factors for sarcopenia in older adults and long‐living older adults. Arch Gerontol Geriatr 2020;89:104089. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0038] 38. Tang T, Wu L, Yang L, Jiang J, Hao Q, Dong B, et al. A sarcopenia screening test predicts mortality in hospitalized older adults. Sci Rep 2018;8:2923. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0039] 39. Park H, Jang IY, Han M, Lee H, Jung HW, Lee E, et al. Sarcopenia is associated with severe erectile dysfunction in older adults: a population‐based cohort study. Korean J Intern Med 2020;35:1245–1253. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0040] 40. Vetrano DL, Landi F, Volpato S, Corsonello A, Meloni E, Bernabei R, et al. Association of sarcopenia with short‐ and long‐term mortality in older adults admitted to acute care wards: results from the CRIME study. J Gerontol A Biol Sci Med Sci 2014;69:1154–1161. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0041] 41. Darroch P, O'Brien WJ, Mazahery H, Wham C. Sarcopenia prevalence and risk factors among residents in aged care. Nutrients 2022;14:1837. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0042] 42. Martone AM, Bianchi L, Abete P, Bellelli G, Bo M, Cherubini A, et al. The incidence of sarcopenia among hospitalized older patients: results from the Glisten study. J Cachexia Sarcopenia Muscle 2017;8:907–914. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0043] 43. Bianchi L, Maietti E, Abete P, Bellelli G, Bo M, Cherubini A, et al. Comparing EWGSOP2 and FNIH sarcopenia definitions: agreement and 3‐year survival prognostic value in older hospitalized adults: the GLISTEN study. J Gerontol A Biol Sci Med Sci 2020;75:1331–1337. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0044] 44. Remelli F, Maietti E, Abete P, Bellelli G, Bo M, Cherubini A, et al. Prevalence of obesity and diabetes in older people with sarcopenia defined according to EWGSOP2 and FNHI criteria. Aging Clin Exp Res 2022;34:113–120. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0045] 45. Agosta L, Bo M, Bianchi L, Abete P, Belelli G, Cherubini A, et al. Polypharmacy and sarcopenia in hospitalized older patients: results of the GLISTEN study. Aging Clin Exp Res 2019;31:557–559. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0046] 46. Suzan V, Kanat BB, Yavuzer H. Association of sarcopenia with geriatric syndromes and neutrophil/lymphocyte ratio. Medicine 2022;11:645–650. [Google Scholar]

[jcsm13190-bib-0047] 47. Okayama A, Nakayama N, Kashiwa K, Horinouchi Y, Fukusaki H, Nakamura H, et al. Prevalence of Sarcopenia and Its Association with Quality of Life, Postural Stability, and Past Incidence of Falls in Postmenopausal Women with Osteoporosis: A Cross‐Sectional Study. Multidisciplinary Digital Publishing Institute; 2022. p 192. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0048] 48. Jang IY, Lee E, Lee H, Park H, Kim S, Kim KI, et al. Characteristics of sarcopenia by European consensuses and a phenotype score. J Cachexia Sarcopenia Muscle 2020;11:497–504. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0049] 49. Dodds RM, Murray JC, Robinson SM, Sayer AA. The identification of probable sarcopenia in early old age based on the SARC‐F tool and clinical suspicion: findings from the 1946 British birth cohort. Eur Geriatr Med 2020;11:433–441. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0050] 50. Su Y, Hirayama K, Han TF, Izutsu M, Yuki M. Sarcopenia prevalence and risk factors among Japanese community dwelling older adults living in a snow‐covered city according to EWGSOP2. J Clin Med 2019;8:291. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0051] 51. Jang IY, Jung HW, Lee CK, Yu SS, Lee YS, Lee E. Comparisons of predictive values of sarcopenia with different muscle mass indices in Korean rural older adults: a longitudinal analysis of the Aging Study of PyeongChang Rural Area. Clin Interv Aging 2018;13:91–99. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0052] 52. Hao Q, Hu X, Xie L, Chen J, Jiang J, Dong B, et al. Prevalence of sarcopenia and associated factors in hospitalised older patients: a cross‐sectional study. Australas J Ageing 2018;37:62–67. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0053] 53. Yang M, Hu X, Wang H, Zhang L, Hao Q, Dong B. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study. J Cachexia Sarcopenia Muscle 2017;8:251–258. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0054] 54. König M, Spira D, Demuth I, Steinhagen‐Thiessen E, Norman K. Polypharmacy as a risk factor for clinically relevant sarcopenia: results from the Berlin Aging Study II. J Gerontol A 2018;73:117–122. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0055] 55. Yalcin A, Aras S, Atmis V, Cengiz OK, Varli M, Cinar E, et al. Sarcopenia prevalence and factors associated with sarcopenia in older people living in a nursing home in A nkara Turkey. Geriatr Gerontol Int 2016;16:903–910. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0056] 56. Hirani V, Blyth F, Naganathan V, Le Couteur DG, Seibel MJ, Waite LM, et al. Sarcopenia is associated with incident disability, institutionalization, and mortality in community‐dwelling older men: the Concord Health and Ageing in Men Project. J Am Med Dir Assoc 2015;16:607–613. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0057] 57. Kimura A, Sugimoto T, Niida S, Toba K, Sakurai T. Association between appetite and sarcopenia in patients with mild cognitive impairment and early‐stage Alzheimer's disease: a case‐control study. Front Nutr 2018;5:128. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0058] 58. Sazlina SG, Lee PY, Chan YM, Hamid MSA, Tan NC. The prevalence and factors associated with sarcopenia among community living elderly with type 2 diabetes mellitus in primary care clinics in Malaysia. Plos One 2020;15:e0233299. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0059] 59. Hsu YH, Liang CK, Chou MY, Wang YC, Liao MC, Chang WC, et al. Sarcopenia is independently associated with parietal atrophy in older adults. Exp Gerontol 2021;151:111402. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0060] 60. Perez‐Zepeda MU, Sgaravatti A, Dent E. Sarcopenia and post‐hospital outcomes in older adults: a longitudinal study. Arch Gerontol Geriatr 2017;69:105–109. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0061] 61. Beaudart C, Reginster JY, Petermans J, Gillain S, Quabron A, Locquet M, et al. Quality of life and physical components linked to sarcopenia: the SarcoPhAge study. Exp Gerontol 2015;69:103–110. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0062] 62. Cebria IIMA, Arnal‐Gomez A, Tortosa‐Chulia MA, Balasch‐Bernat M, Forcano S, Sentandreu‐Mano T, et al. Functional and clinical characteristics for predicting sarcopenia in institutionalised older adults: identifying tools for clinical screening. Int J Environ Res Public Health 2020;17:4483. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0063] 63. Curcio F, Liguori I, Cellulare M, Sasso G, Della‐Morte D, Gargiulo G, et al. Physical Activity Scale for the Elderly (PASE) score is related to sarcopenia in noninstitutionalized older adults. J Geriatr Phys Ther 2019;42:130–135. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0064] 64. Formiga F, Moreno‐Gonzalez R, Corsonello A, Carlsson A, Arnlov J, Mattace‐Raso F, et al. Diabetes, sarcopenia and chronic kidney disease; the Screening for CKD among Older People across Europe (SCOPE) study. BMC Geriatr 2022;22:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0065] 65. Gao LL, Jiang JJ, Yang M, Hao QK, Luo L, Dong BR. Prevalence of sarcopenia and associated factors in chinese community‐dwelling elderly: comparison between rural and urban areas. J Am Med Dir Assoc 2015;16:1003.e1–1003.e6. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0066] 66. Halil M, Ulger Z, Varli M, Doventas A, Ozturk GB, Kuyumcu ME, et al. Sarcopenia assessment project in the nursing homes in Turkey. Eur J Clin Nutr 2014;68:690–694. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0067] 67. Landi F, Liperoti R, Russo A, Giovannini S, Tosato M, Capoluongo E, et al. Sarcopenia as a risk factor for falls in elderly individuals: results from the ilSIRENTE study. Clin Nutr 2012;31:652–658. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0068] 68. Ozturk ZA, Turkbeyler IH, Abiyev A, Kul S, Edizer B, Yakaryilmaz FD, et al. Health‐related quality of life and fall risk associated with age‐related body composition changes; sarcopenia, obesity and sarcopenic obesity. Intern Med J 2018;48:973–981. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0069] 69. Takahashi M, Maeda K, Wakabayashi H. Prevalence of sarcopenia and association with oral health‐related quality of life and oral health status in older dental clinic outpatients. Geriatr Gerontol Int 2018;18:915–921. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0070] 70. Yalcin A, Silay K. Sarcopenia and health‐related quality of life in Turkish nursing home residents: a cross‐sectional study. Asian J Gerontol Geriatr 2017;12:42–46. [Google Scholar]

[jcsm13190-bib-0071] 71. Pourhassan M, Norman K, Muller MJ, Dziewas R, Wirth R. Impact of sarcopenia on one‐year mortality among older hospitalized patients with impaired mobility. J Frailty Aging 2018;7:40–46. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0072] 72. Baruth JM, Gentry MT, Rummans TA, Miller DM, Burton MC. Polypharmacy in older adults: the role of the multidisciplinary team. Hosp Pract (1995) 2020;48:56–62. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0073] 73. Markworth JF, Vella LD, Figueiredo VC, Cameron‐Smith D. Ibuprofen treatment blunts early translational signaling responses in human skeletal muscle following resistance exercise. J Appl Physiol 2014;117:20–28. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0074] 74. Kramer HF, Goodyear LJ. Exercise, MAPK, and NF‐κB signaling in skeletal muscle. J Appl Physiol 2007;103:388–395. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0075] 75. Lilja M, Mandić M, Apró W, Melin M, Olsson K, Rosenborg S, et al. High doses of anti‐inflammatory drugs compromise muscle strength and hypertrophic adaptations to resistance training in young adults. Acta Physiologica 2018;222:e12948. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0076] 76. Trappe TA, Carroll CC, Dickinson JM, LeMoine JK, Haus JM, Sullivan BE, et al. Influence of acetaminophen and ibuprofen on skeletal muscle adaptations to resistance exercise in older adults. Am J Physiol Regul Integr Comp Physiol 2011;300:R655–R662. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcsm13190-bib-0077] 77. Veronese N, Demurtas J, Soysal P, Smith L, Torbahn G, Schoene D, et al. Sarcopenia and health‐related outcomes: an umbrella review of observational studies. Eur Geriatr Med 2019;10:853–862. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0078] 78. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta‐analyses of randomised controlled trials. BMJ 2011;343:d4002. [DOI] [PubMed] [Google Scholar]

[jcsm13190-bib-0079] 79. von Haehling S, Morley JE, Coats AJ, Anker SD. Ethical guidelines for publishing in the Journal of Cachexia, Sarcopenia and Muscle: update 2021. J Cachexia Sarcopenia Muscle 2021;12:2259–2261. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Sarcopenia is associated with a greater risk of polypharmacy and number of medications: a systematic review and meta‐analysis

Konstantinos Prokopidis

Panagiotis Giannos

Jean Yves Reginster

Olivier Bruyere

Mirko Petrovic

Antonio Cherubini

Konstantinos K Triantafyllidis

Konstantinos S Kechagias

Yannis Dionyssiotis

Matteo Cesari

Kinda Ibrahim

David Scott

Mario Barbagallo

Nicola Veronese

Abstract

Introduction

Methods

Search strategy

Inclusion and exclusion criteria

Data extraction and risk of bias

Statistical analysis

Results

Literature search

Figure 1.

Descriptive results

Table 1.

Table 2.

Definition of sarcopenia and polypharmacy

Table 3.

Polypharmacy in older subjects with sarcopenia versus without sarcopenia

Figure 2.

Number of medications in older subjects with sarcopenia versus those without sarcopenia

Figure 3.

Meta‐regression analyses

Risk of bias of included studies

Discussion

Strengths and limitations

Conclusions

Conflict of interest

Supporting information

Acknowledgements

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases