Literature DB >> 29587829

How do we define and measure sarcopenia? Protocol for a systematic review.

Paulo Roberto Carvalho do Nascimento1,2, Stéphane Poitras3, Martin Bilodeau3,4,5.   

Abstract

BACKGROUND: The loss of muscle mass is a natural aging consequence. A reduction of muscle mass that surpasses the physiological rate is considered the key factor responsible for the development of a geriatric syndrome called sarcopenia. However, a new understanding of the importance of muscle quality over quantity is rising; as a result, different definitions for sarcopenia has been used. Due to the negative impact on elder's health and quality of life, the number of research investigating the causes, prevalence, and management of sarcopenia is increasing, although a consensus on sarcopenia definition is still missing. This systematic review will assess observational studies reporting the presence of sarcopenia aiming to verify how sarcopenia is defined, the diagnosis criteria, and the tools used for assessment. In addition, we will investigate the influence of the definition and diagnostic tools on the prevalence rate.
METHODS: Keywords related to the condition, population, and type of study will be combined to build a search strategy for each of the following databases MEDLINE, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and Google Scholar. Two independent reviewers will analyze the retrieved papers for eligibility and the methodological quality of eligible studies. The definition of sarcopenia and diagnostic tools used in each study and the prevalence estimates will be extracted. Descriptive statistics will be used to report the definitions of sarcopenia, diagnostic tools, and whether these influence or not, the prevalence rates. DISCUSSION: Sarcopenia is receiving greater attention in geriatrics research in recent years. Therefore, it is important to investigate how this condition is defined in the literature and whether these definitions can interfere with the reported estimates devoting more efforts on the topic. The results of this study can help to determine the most used definitions of sarcopenia reported in the literature, its strengths and limitations, and open a discussion about a need for a more valid, easy, and suitable one. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015020832.

Entities:  

Keywords:  Aged; Aging; Bias; Epidemiology; Sarcopenia

Mesh:

Year:  2018        PMID: 29587829      PMCID: PMC5870090          DOI: 10.1186/s13643-018-0712-y

Source DB:  PubMed          Journal:  Syst Rev        ISSN: 2046-4053


Background

Sarcopenia is a geriatric syndrome affecting older adults, which was firstly described by Rosenberg [1] as the loss of muscle mass in seniors. In addition to the loss of muscle mass [2, 3], aging is also accompanied by a reduction in muscle strength [4, 5] and decline in physical function [6, 7], which are combined to define sarcopenia according to a contemporary definition [8]. These alterations may be associated with changes in muscular quality [3, 9] due to the reduction in the size [10-12], number [10, 12], and contractility of the muscle fiber [13, 14], as well as fat tissue infiltration in the muscle [15, 16]. Prevalence of sarcopenia increases with age advance [17, 18]. However, it is not possible to rely on this estimates due to the lack of a universal definition of sarcopenia. Despite the effort from the European Working Group on Sarcopenia in Older People (EWGSOP) [8] to diagnose sarcopenia, results from two recent systematic reviews [19, 20] pooling the prevalence estimates for sarcopenia presented discrepant values of 10 and 29%, respectively. The difference in the results of these reviews seems to be due to the lack of similarity in defining sarcopenia. A clear definition of sarcopenia is important since the number of publications on this syndrome is increasing [19, 21–24], and especially due to the fact that sarcopenia is associated with an increased risk for all-cause of mortality (OR = 3.64, 95% CI = 2.94 to 4.51) and functional decline (OR = 2.58, 95% CI = 1.33 to 4.99) [24], summed to a high economic cost [25]. Considering that older adults are a growing population group around the world [26], the burden due sarcopenia tends to be higher. The negative consequences resulted from sarcopenia have stimulated the development of studies about its prevalence [19, 20] and management [20]. However, to date, no study has comprehensively evaluated the definitions and tools used in the literature to define and determine the presence of sarcopenia. The lack of a consensus on defining sarcopenia prevents estimating the prevalence and prognosis and comparing the effectiveness of interventions between clinical trials. The EWGSOP [8] was the first group attempting to provide a consensus definition for sarcopenia followed by the International Working Group on Sarcopenia (IWGS) [27], and by the Asian Working Group for Sarcopenia (AWGS) [28], respectively. These groups defined sarcopenia based on the appendicular muscle mass adjusted by the height squared, the handgrip strength, and/or gait speed presenting a certain variation from each other. Further, an initiative from the Foundation for the National Institutes of Health (FNIH) proposed that sarcopenia should be defined based on muscle mass adjusted by the body mass index (BMI) with cutoff values of (< 0.789 kg/m2 men and < 0.512 kg/m2 women) and grip strength (< 26 kg men and < 16 kg women) [29]. Although the definitions provided by the EWGSOP, IWGS, AWGS, and FNIH use different strategies and cutoff points to normalize and define loss of muscle mass, reduction in muscle strength, and low gait speed, the loss of muscle mass is considered the starting point for the development of sarcopenia. However, recent studies provided information that reduction in muscle quality surpass the loss of muscle mass and that the aging decline is respectively greater in muscle power, strength, and mass [30-32]. Furthermore, in a recent study, dos Santos et al. [33] observed that in a population of older adults (+ 90 years old), participants with low muscle mass had 1.65 (95% CI 1.27–2.31) increased odds for being at risk for losing physical independence and participants with low muscle force had 6.19 (95% CI 5.08–7.53) increased odds for being at risk of losing physical independence. As a result, new views on the criterion to define sarcopenia are emerging, not limiting sarcopenia to loss of muscle mass but, instead, as a loss of muscle strength due to alterations in the muscle quality related to the age advance [34]. Nevertheless, it is unclear whether these definitions are used in research reporting sarcopenia estimates and how they influence the results. Thus, the primary aim of this systematic review will be to identify how sarcopenia is defined and measured in the literature reporting its prevalence. Secondly, we will evaluate how different definitions can affect prevalence estimates.

Methods

Protocol and registration

This protocol is reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P checklist) [35] according to the elaboration and explanation guideline [36]. The PRISMA-P checklist is included as an additional file [see Additional file 1]. This protocol is registered with PROSPERO no. CRD42015020832.

Selection criteria

All indexed observational population-based studies published, in which the prevalence of sarcopenia in community-dwelling older adults was reported, will be considered for review independent of the language of publication and publication date.

Exclusion criteria

We will exclude articles reporting on the prevalence of sarcopenia in participants with specific health issues (e.g., diabetes, cancer, and organ transplantation). Furthermore, we will not include articles written in languages other than English, French, or Portuguese, which could not be translated by the authors.

Search strategy

An electronic search will be conducted using the databases MEDLINE, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science (Core Collection), and Google Scholar. A search strategy was built for each database (Appendix 1) using a combination of specific terms for (a) target population—“elderly,” “older adults,” “older people,” “older person,” and “community-dwelling;” (b) condition—“sarcopenia,” “aging,” and “muscular atrophy;” and (c) type of study—“prevalence,” “incidence,” “epidemiology,” “cross-sectional,” and “cohort studies.” We will include studies that analyzed prevalence of sarcopenia published in peer-reviewed journals through February 2018. Additionally, we will perform a comprehensive examination of reference lists from eligible studies. Data pertaining to individuals under 60 years old will not be considered. All retrieved papers will be exported to a reference manager software (Endnote®), then examined by two independent researchers (PN an MB), through the readings of the title, abstract, and full text. In each stage, studies that do not fulfill eligibility criteria will be excluded. In cases of disagreements between reviewers that cannot be resolved by consensus, a third opinion will be consulted for final arbitration.

Quality appraisal

Two independent researchers (PN and MB) will critically appraise the quality of each eligible study using the quality assessment tool for observational cohort and cross-sectional studies proposed by the National Heart, Lung and Blood Institute (Appendix 2). The quality will be based on the following items: (1) clear question and objective, (2) target population, (3) participation rate, (4) sample selection, (5) sample size justification, (6) temporal relationship for exposure/outcome, (7) length of the timeframe, (8) levels of the exposure of interest, (9) exposure measure details, (10) number of exposure measurements, (11) outcome measures, (12) blinding of outcome assessors, (13) follow-up rate, and (14) statistical analyses.

Data extraction and analysis

The information about the articles (author, type of study, data collection strategy, sample size, age, gender, definition of sarcopenia, measurement tools, and prevalence rate) will be extracted independently by two researchers (PN and MB) using an electronic sheet. Frequency distribution will be used to present the definitions and tools used to diagnose sarcopenia through the studies. We will analyze the influence of the definitions of sarcopenia on prevalence estimates according to mean age or age strata (i.e., 60–70 years, 71–80 years, > 80 years), presenting results using descriptive statistics.

Discussion

To our knowledge, this will be the first systematic review analyzing the definitions and tools used to diagnose sarcopenia. This review will provide a summary of the sarcopenia definitions currently used to diagnose sarcopenia and implications in terms of estimates. Further, it provides evidence for discussion on how to best define sarcopenia. A standard definition and screening tools for sarcopenia are important to provide valid and reproducible values allowing reliable measures and comparison between estimates. Considering the amount of time and resources expended recently with research on sarcopenia, maybe it is time to take a step back and analyze how well this condition is being diagnosed, the validity and probabilities of false positive or false negative cases provided by the current definitions before applying more efforts with new researches. The results of the systematic review will be presented in scientific events and published in a peer-reviewed journal.

Additional file

PRISMA-P checklist. (DOCX 30 kb)
Table 1

Search strategy

Web of ScienceGoogle ScholarMEDLINEEMBASECINAHL
# 1 TS = (sarcopen* OR aging OR muscle atrophy)# 2 TI = (prevalence OR incidence OR cross-sectional OR cohort)# 3 TI = (older adults OR elder* OR seniors OR community-dwelling)(#3 AND #2 AND #1)Sarcopenia prevalencePrevalence of sarcopenia1. Sarcopenia/2. sarcopenia.ti,ab.3. 1 or 24. Muscular Atrophy/5. (musc* adj1 atrophy).ti,ab.6. 4 or 57. aging.ti,ab.8. Aging/9. 7 or 810. 6 and 911. “Aged, 80 and over”/ or Aged/12. Prevalence/13. Cross-Sectional Studies/14. 12 or 1315. 3 or 1016. 11 and 14 and 151. Sarcopenia/2. sarcopenia.ti,ab.3. 1 or 24. Muscular Atrophy/5. (musc* adj1 atrophy).ti,ab.6. 4 or 57. Aging/8. aged.ti,ab.9. 7 or 810. 6 and 911. Aged/12. “Aged, 80 and over”/13. 11 or 1214. Prevalence/15. Incidence/16. Cohort Studies/17. Cross-Sectional Studies/18. 3 or 1019. 14 or 15 or 16 or 1720. 13 and 18 and 19S1. TI Sarcopenia OR AB SarcopeniaS2. TI (MH “Muscular Atrophy”)S3. S1 OR S2S4. TI Aged OR AB AgedS5. (MH “Aged, 80 and Over”)S6. S4 OR S5S7. (MH “Prevalence”) OR (MH “Cross Sectional Studies”) OR (MH “Surveys”) OR (MH “Epidemiological Research”)S8. S3 AND S6 AND S7
CriteriaYesNoOther (CD, NR, NA)
1. Was the research question or objective in this paper clearly stated?
2. Was the study population clearly specified and defined?
3. Was the participation rate of eligible persons at least 50%?
4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study prespecified and applied uniformly to all participants?
5. Was a sample size justification, power description, or variance and effect estimates provided?
6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured?
7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed?
8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g., categories of exposure, or exposure measured as continuous variable)?
9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?
10. Was the exposure(s) assessed more than once over time?
11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?
12. Were the outcome assessors blinded to the exposure status of participants?
13. Was loss to follow-up after baseline 20% or less?
14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)?
Quality rating (Good, Fair, or Poor) (see guidance)
 Rater #1 initials:
 Rater #2 initials:
 Additional comments (If Poor, please state why):

CD cannot determine, NA not applicable, NR not reported

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