Abstract
Background
A universal definition of sarcopenia is still lacking. Since the European criteria have been recently revised, we aimed at studying prevalence of low muscle strength (LMS) and low muscle mass (LMM), as defined according to the European Working Group of Sarcopenia in Older People (EWGSOP) 2 and 1 definitions, and their individual contribution toward mortality and incident mobility disability in a cohort of community-dwelling older people.
Methods
Longitudinal analysis of 535 participants of the InCHIANTI study. LMS and LMM were defined according to the criteria indicated in the EWGSOP2 and 1. Cox and log-binomial regressions were used to examine association with mortality and 3-year mobility disability (inability to walk 400 m).
Results
We observed a lower prevalence of the combination LMM/LMS according to EWGSOP2 compared to EWGSOP1 (3.2% vs 6.2%). Using the new criteria, all sarcopenia components were associated with mortality, although the hazard ratio [HR] for the group LMM/LMS was no longer significant after adjustment for confounders (LMM: HR 2.69, 95% confidence interval [CI] 1.04–6.94; LMS: HR 3.18, 95% CI 1.44–7.01; LMM/LMS: HR 2.95, 95% CI 0.86–10.16). Using EWGSOP1, LMS alone was independently associated with mortality (HR 4.43, 95% CI 1.85–10.57). None of the sarcopenia components conferred a higher risk of mobility disability.
Conclusions
The EWGSOP2 algorithm leads to a reduction in the estimated prevalence of sarcopenia defined as combination of LMM/LMS. The finding that, independent of the adopted criteria, people with LMS and normal mass have a higher mortality risk compared to robust individuals, confirms that evaluation of muscle strength has a central role for prognosis evaluation.
Keywords: Sarcopenia, Community-dwelling, Mortality, Functional performance, Outcomes
Background
Given the current and expected growth in the geriatric population worldwide, the promotion of healthy aging has been set among the priorities of public health authorities. Recently, the World Health Organization introduced the concept of intrinsic capacity (the whole person’s physical and mental capacities) in order to promote an appropriate assessment of the needs of the aging population and the maintenance of an individual’s functional ability (1). Locomotion has been recognized as one of the domains constituting intrinsic capacity (2), which may be affected during aging: poor mobility and muscle dysfunction are commonly observed among older people and contribute to limitations in performing daily tasks. In this scenario, the concept of sarcopenia has gained increasing importance (3). The need of a single and universally shared definition of this condition is even more compelling if we consider that sarcopenia has been recently recognized as a muscle disease codified in the current International Classification of Diseases (ICD-10). European and U.S. experts’ groups agree on the need of simultaneous evaluation of muscle mass and strength for the definition of sarcopenia (4,5), since the trajectories of their decline during aging do not overlap and muscle strength declines much more rapidly than muscle mass (6). Low muscle strength (LMS) depends on several factors beyond loss of muscle mass (6,7) and maintaining or gaining muscle mass has limited value in preventing aging-related decline in muscle strength (8).
According to the updated algorithm proposed by the European Working Group on Sarcopenia in Older People (EWGSOP2) (9), the diagnosis of sarcopenia should be based firstly on the detection of LMS and confirmed by the presence of low muscle mass (LMM), while poor physical performance (eg, low gait speed) identifies people with severe sarcopenia. The 2018 consensus suggests using grip strength and/or chair stand measure to identify LMS and recommends using specific cutoff points for LMS and appendicular lean muscle mass to promote harmonization among sarcopenia studies.
In consequence of the recent change in the proposed cutoffs for muscle mass and strength, data about the prevalence of sarcopenia as defined according to EWGSOP2 in community-dwelling older people are lacking. Moreover, which of the components of sarcopenia (strength and muscle mass loss) is associated to adverse outcomes is still unclear. Although previous studies demonstrated that muscle strength is a better predictor of adverse outcomes than muscle mass (10–12), the latter is per se an independent predictor of survival and disability among older people (13,14). On these assumptions, we aimed to investigate among participants in the InCHIANTI Study (i) the prevalence of LMS and LMM according to EWGSOP2 and EWGSOP1 cutoffs and (ii) the individual contribution of LMS and LMM as defined by EWGSOP2 and EWGSOP1 criteria toward risk of mortality and incident mobility disability.
Methods
Data Source and Sample Selection
For this study, we selected a sample of people 65 years and older from the InCHIANTI Study. As described elsewhere (15), this is an epidemiological, population-based study designed to investigate the factors contributing to late-life disability. The study protocol was approved by the Italian National Institute of Research and Care on Aging ethical committee. The participants were randomly selected from the inhabitants of two town areas in the Chianti region (Greve in Chianti and Bagno a Ripoli, Tuscany, Italy) and provided written consent to participate. The eligible subjects were firstly interviewed at their homes in order to collect data about their health status, physical and cognitive performance, and other factors possibly related to loss of independence in late life; then, the interview was followed by a physical examination at the study clinic. The first wave of the study started in 1998 with 1,453 participants who were followed up with evaluations every 3 years. As baseline, for this analysis, we used data of the second follow-up, when muscle mass was estimated using bioelectrical impedance analysis (BIA). From the original sample, including 1,067 subjects at the second follow-up, we selected 844 participants with age ≥ 65 years. For mortality outcome, we excluded 309 patients who did not undergo performance tests or did not perform BIA examination at baseline, leaving 535 participants available for analysis. Disability outcome was evaluated at the InCHIANTI Study third follow-up. For this analysis, we firstly excluded disabled subjects at baseline (N = 95), then those who had died before the 3-year follow-up (N = 18) or with missing data about functional test at follow-up (N = 53); therefore, we analyzed a cohort of 369 subjects (see Supplementary Figure 1 for the flowchart of the study population selection).
Assessment of Muscle Mass and Muscle Strength
For the purpose of this study, we did not include low physical performance for sarcopenia diagnosis, given that incident mobility disability was the outcome of interest. Muscle mass was estimated through BIA using a Quantum/S Bioelectrical Body Composition Analyzer (Akern Srl, Florence, Italy). BIA measures the opposition of body tissues to the flow of a small (less than 1 mA) alternating current by providing two values (resistance and reactance). According to the EWGSOP2’s recommendations (9), muscle mass was calculated using the Sergi equation: Appendicular skeletal muscle mass (kg) = −3.964 + (0.227 × height2/BIA resistance) + (0.095 × weight) + (1.384 × gender) + (0.064 × BIA reactance), where height is measured in centimeters; BIA resistance and reactance are measured in ohms; weight is measured in kilograms; for gender, men = 1 and women = 0 (16). Using the cut points indicated in the EWGSOP2 consensus, LMM was defined as having appendicular skeletal muscle mass less than 7 kg/m2 in men and 6 kg/m2 in women. For the EWGSOP1’s definition, LMM was identified as having a skeletal muscle index less than 8.87 kg/m2 and 6.42 kg/m2 in men and women, respectively (4,17,18). Skeletal muscle index was obtained from standardization by squared meters of the absolute skeletal muscle mass, calculated through Janssen and colleagues equation (19): Skeletal muscle mass (kg) = ([height2/BIA resistance × 0.401] + [gender × 3.825] + [age × −0.071]) + 5.102, where height is measured in centimeters; BIA resistance is measured in ohms; for gender, men = 1 and women = 0; age is measured in years.
Muscle strength was assessed measuring grip strength (GS) and recording the time to complete repeated chair stand test as a proxy for strength of leg muscles (20,21). GS was measured three times for each hand using a hand-held dynamometer (hydraulic hand BASELINE; Smith and Nephew, Agrate Bianza, Milan, Italy), and the best of the six measurements (usually, the dominant limb) was retained for analyses (22). LMS was defined as (i) a GS less than 27 kg in men and 16 kg in women and/or time > 15 seconds for five rises, as proposed in EWGSOP2 consensus and (ii) a GS less than sex and body mass index (BMI)-specific cut points, as previously reported in EWGSOP1: men: BMI ≤ 24 kg/m2 GS ≤ 29 kg, BMI 24.1–28 kg/m2 GS ≤ 30 kg, BMI > 28 kg/m2 GS ≤ 32 kg; women: BMI ≤ 23 kg/m2 GS ≤ 17 kg, BMI 23.1–26 kg/m2 GS ≤ 17.3 kg, BMI 26.1–29 kg/m2 GS ≤ 18 kg, BMI > 29 kg/m2 GS ≤ 21 kg.
On this basis, as indicated in the EWGSOP2 algorithm (9), probable sarcopenia is defined as the presence of LMS, and the co-occurrence of LMS and LMM confirms the diagnosis of sarcopenia.
Outcome Measures
Vital status was available up to April 2010. Mobility disability was evaluated through a direct measure of physical performance that is the ability to complete a 400-m walk test within 15 minutes without sitting and without the help of another person or walker. Therefore, incident mobility disability was defined as loss of ability to walk 400 m at 3-year follow-up (InCHIANTI third follow-up).
Covariates
At baseline (InCHIANTI second follow-up), data about sociodemographic characteristics (education, marital status) were obtained through interview. Prevalence of specific medical conditions was established through self-reported history, medical records and physical examination. A Mini-Mental State Examination score <24 (corrected for education and age) defined cognitive impairment (23). Adapted Fried et al.’s criteria were measured as previously described (24), and frail individuals were identified as those having three or more positive criteria. Physical performance was evaluated through 400 m walking test. For each participant, we also recorded the SAFE (Survey of Activities and Fear of Falling in the Elderly) score, which investigated fear of falling during performance of 11 activities (25).
Analytic Approach
According to the distribution of LMS and LMM, four groups of people were obtained from the original sample (normal muscle mass and strength, LMM/normal muscle strength, normal muscle mass/LMS, LMM/LMS). The main sociodemographic and clinical characteristics were shown using descriptive statistics. The agreement between EWGSOP2 and 1 definitions of LMM and LMS was evaluated using weighted k coefficient and shown through confusion matrix. To examine the association with mortality and 3-year mobility disability risk, Cox and log-binomial regressions were carried out, respectively.
The proportional hazard assumption of Cox regressions was tested through the inspection of Schoenfeld residuals. Multivariable models were adjusted for age, gender, BMI, marital status, education, and comorbidities. Finally, the predictive capacity of LMM, LMS, or their combination toward mortality was considered and sensitivity, specificity and positive and negative predictive values were calculated. All the analyses were performed using R 3.3 for Mac (R Foundation for Statistical Computing, Vienna, Austria).
Results
The general characteristics of study participants, according to the four groups obtained from the combination of LMM and LMS as defined by EWGSOP2 and EWGSOP1 criteria, are presented in Supplementary Table 1. Overall, the mean age was 77 years (SD 5.5) and 53.6% were women. Only 17 individuals (3.2%) were classified as having LMS/LMM based upon EWGSOP2 criteria. This group included people who were older, less likely to be women and married, and had a higher prevalence of comorbidities and frailty compared to the other groups (people with normal mass and strength and those with either LMM or LMS). When using EWGSOP1 criteria, a higher percentage of people were classified as having LMM/normal strength compared to the new criteria (24.7% vs 8.4%) and LMM/LMS (6.2% vs 3.2%). Conversely, a lower number of people had LMS and normal lean mass according to the EWGSOP1 criteria in respect to EWGSOP2 classification (8.4% vs 15.5%, respectively).
Table 1 displays the agreement between 2010 and 2018 criteria. When EWGSOP2’s definition was applied, the percentage of participants whose classification according to EWGSOP1 did not change were 88%, 30%, 49%, and 24% for normal mass/normal strength, LMM/normal strength, normal mass/LMS, and LMM/LMS, respectively, with a low-moderate overall agreement (weighted Cohen kappa 0.43, 95% CI: 0.23–0.63).
Table 1.
Agreement Between EWGSOP1 and 2 Definitions for LMS and LMM (row percentages)
| EWGSOP1 | EWGSOP2 | |||
|---|---|---|---|---|
| Normal MM and MS | LMM/Normal MS | Normal MM/LMS | LMM/LMS | |
| Normal MM and MS | 285 (88%) | 4 (1%) | 36 (11%) | 0 |
| LMM/Normal MS | 73 (55%) | 39 (30%) | 15 (11%) | 5 (4%) |
| Normal MM/LMS | 19 (42%) | 0 | 22 (49%) | 4 (9%) |
| LMM/LMS | 13 (39%) | 2 (6%) | 10 (30%) | 8 (24%) |
Note: LMM = low muscle mass; LMS = low muscle strength; MM = muscle mass; MS = muscle strength.
Over a mean follow-up of 37 months, 56 participants died. Figure 1 represents Kaplan–Meier curves for mortality for the groups identified using EWGSOP2 (Figure 1A) and EWGSOP1 (Figure 1B) criteria. Association between sarcopenia components defined by EWGSOP2 and adverse outcomes are reported in Table 2. Cox proportional hazard models showed that LMM, LMS, and their combination conferred a higher risk of mortality in comparison to the presence of normal mass and strength (LMM: hazard ratio [HR] 3.95, 95% confidence interval [CI] 1.8–8.65; LMS: HR 2.59, 95% CI 1.29–5.23; LMM/LMS: HR 6.01, 95% CI 2.56–14.15). The result was confirmed also after adjustment for potential confounders (age, sex, BMI, marital status, education, and comorbidities), although HR for the group LMM/LMS was no longer significant (LMM: HR 2.69, 95% CI 1.04–6.94; LMS: HR 3.18, 95% CI 1.44–7.01; LMM/LMS: HR 2.95, 95% CI 0.86–10.16). None of the sarcopenia components conferred a higher risk of mobility disability (relative risk [RR] adjusted for age, sex, and SAFE score: 1.49, 95% CI 0.72–2.79 for LMM; 1.40, 95% CI 0.74–2.48 for LMS; 2.57, 95% CI 0.40–9.06 for LMM/LMS). When exploring the individual contribution of chair rise time and grip strength for adverse outcomes, we obtained inconclusive results given the low number of individuals in each group (eight subjects had LMM and impaired chair rise test and nine subjects had LMM and reduced grip strength (Supplementary Table 2). We also analyzed the association of probable sarcopenia (LMS independent of muscle mass) and sarcopenia (LMS and LMM) with adverse outcomes considering people with normal strength as the reference group (Table 3). The results showed that only probable sarcopenia is independently associated with mortality (probable sarcopenia: HR 2.42, 95% CI 1.21–4.84; sarcopenia: HR 1.96, 95% CI 0.63–6.15). Again, neither probable sarcopenia nor sarcopenia were associated with disability (Table 3).
Figure 1.
Kaplan–Meier curves for mortality in the different groups obtained from the combination of low muscle mass and low muscle strength as defined by EWGSOP2 (panel A) and EWGSOP1 (panel B) criteria
Table 2.
Risk of Mortality and 3-Year Incident Mobility Disability for Individuals with LMM, LMS, and Their Combination According to EWGSOP2 Definition
| Outcomes | Normal MM and MS | LMM/Normal MS | Normal MM/LMS | LMM/LMS |
|---|---|---|---|---|
| Mortality | ||||
| Sample, N | 390 | 45 | 83 | 17 |
| Events, N | 18 | 10 | 19 | 9 |
| Unadjusted HR (95% CI) | Ref | 3.95 (1.8–8.65) | 2.59 (1.29–5.23) | 6.01 (2.56–14.15) |
| Age and sex-adjusted HR (95% CI) | Ref | 3.78 (1.72–8.3) | 2.33 (1.13–4.82) | 3.33 (1.18–9.38) |
| Model Aa HR (95% CI) | Ref | 2.69 (1.04–6.94) | 3.18 (1.44–7.01) | 2.95 (0.86–10.16) |
| Disability | ||||
| Sample, N | 296 | 30 | 40 | 3 |
| Events, N | 58 | 10 | 15 | 2 |
| Unadjusted RR (95% CI) | Ref | 1.7 (0.82–3.18) | 1.91 (1.05–3.28) | 3.4 (0.56–10.88) |
| Model Bb RR (95% CI) | Ref | 1.49 (0.72–2.79) | 1.40 (0.74–2.48) | 2.57 (0.40–9.06) |
Note: CI = confidence interval; HR = hazard ratio; LMM = low muscle mass; LMS = low muscle strength; MM = muscle mass; MS = muscle strength; RR = relative risk.
aAdjusted for age, sex, BMI, marital status, education, and comorbidities.
bAdjusted for age, sex, and SAFE score.
Table 3.
Risk of Mortality and 3-Year Incident Mobility Disability for Probable Sarcopenia and Sarcopenia According to EWGSOP2 Algorithm
| Outcomes | Normal MS | Probable Sarcopenia | Sarcopenia |
|---|---|---|---|
| Mortality | |||
| Sample, N | 435 | 100 | 17 |
| Events, N | 28 | 28 | 9 |
| Unadjusted HR (95% CI) | Ref | 2.29 (1.28–4.11) | 4.32 (1.93–9.69) |
| Age and Sex-Adjusted HR (95% CI) | Ref | 1.74 (0.92–3.30) | 2.30 (0.85–6.18) |
| Model Aa HR (95% CI) | Ref | 2.42 (1.21–4.84) | 1.96 (0.63–6.15) |
| Disability | |||
| Sample, N | 326 | 43 | 3 |
| Events, N | 68 | 17 | 2 |
| Unadjusted RR (95% CI) | Ref | 1.89 (1.08–3.15) | 3.20 (0.52–10.17) |
| Model Bb RR (95% CI) | Ref | 1.39 (0.76–2.39) | 2.43 (0.38–8.53) |
Note: CI = confidence interval; HR = hazard ratio; MS = muscle strength; RR = relative risk.
aAdjusted for age, sex, BMI, marital status, education and comorbidities.
bAdjusted for age, sex and SAFE score.
Using the EWGSOP1 cutoffs, people who had LMM, LMS or both showed higher mortality risk compared to the group with normal mass and strength (HR: 2.85, 95% CI 1.35–6.06; 4.58, 95% CI 2.04–10.24 and 4.63, 95% CI 1.96–10.94, respectively). After adjustment for confounders, people with LMS and normal mass showed a four-time greater probability to die in comparison with people with normal strength and mass (HR 4.43, 95% CI 1.85–10.57; Supplementary Table 3). At variance with the LMS/normal mass combination, neither LMM nor LMS/LMM were independently associated with mortality. Furthermore, none of the sarcopenia components was independently associated with 3-year mobility disability (Supplementary Table 3).
The predictive capacity of LMM, LMS, and their combination for mortality was similar for EWGSOP1 and 2. Both definitions show low sensitivity and positive predictive values and high specificity and negative predictive values toward mortality (Table 4). As expected, we obtained the same results when analyzing the predictive capacity of probable sarcopenia and sarcopenia according to EWGSOP2 algorithm (Table 4).
Table 4.
Predictive Value of LMM, LMS, and Their Combination for Mortality
| Predictors | Sensitivity | Specificity | Positive Predictive Value | Negative Predictive Value |
|---|---|---|---|---|
| EWGSOP2 | ||||
| Normal MM and MS | Ref | Ref | Ref | Ref |
| LMM/Normal MS | 0.33 | 0.89 | 0.12 | 0.97 |
| Normal MM/LMS | 0.44 | 0.84 | 0.13 | 0.97 |
| LMM/LMS | 0.38 | 0.98 | 0.46 | 0.97 |
| Normal MS | Ref | Ref | Ref | Ref |
| Probable sarcopenia | 0.48 | 0.84 | 0.18 | 0.96 |
| Sarcopenia | 0.29 | 0.98 | 0.46 | 0.96 |
| EWGSOP1 | ||||
| Normal MM and MS | Ref | Ref | Ref | Ref |
| LMM/Normal MS | 0.5 | 0.71 | 0.08 | 0.97 |
| Normal MM/ LMS | 0.43 | 0.89 | 0.17 | 0.97 |
| LMM/LMS | 0.47 | 0.93 | 0.28 | 0.97 |
Note: LMM = low muscle mass; LMS = low muscle strength; MM = muscle mass; MS = muscle strength.
Discussion
The identification of universally accepted criteria to diagnose sarcopenia is crucial both in clinical practice and in the research field. The new operational definition of sarcopenia, proposed by the European consensus, led to changes in the cutoff points for muscle strength and appendicular lean mass and proposed alternative tools to assess muscle strength (chair rise time). According to the results of our study, the estimated prevalence of sarcopenia, as combination of LMM and LMS, is lower when using EWGSOP2 algorithm compared to EWGSOP1. Irrespective of the definition used, in our cohort, the combination of LMS and normal muscle mass was independently associated with a higher risk of mortality (in comparison to the presence of normal mass and strength). Nevertheless, none of the sarcopenia parameters was independently associated with mobility disability.
There are few data concerning the prevalence of sarcopenia according to the revised operational definition firstly published in September 2018 (9,26). Locquet and collaborators (27) reported that, in a sample of 501 participants of the Sarcopenia and Physical impairment with advancing Age (SarcoPhAge) study, the prevalence of sarcopenia according to EWGSOP2’s definition was 7.4% (37 of 501 individuals), that is higher than ours (3.2%, 17 of 535 individuals). This discrepancy may be due primarily to different population selection. While we used data from community-dwelling older inhabitants, the SarcoPhAge study enrolled outpatients from different departments (28), including individuals with a higher percentage of comorbidities and frailty compared to the InCHIANTI cohort. Thus, it is not surprising that, despite the small percentage of sarcopenic patients in the SarcoPhAge sample, the prevalence we found in our cohort was even lower. Moreover, literature data published very recently confirm that the estimated prevalence of sarcopenia according to the new algorithm is low (29,30).
Our results showed a low-moderate agreement between the EWGSOP1 and EWGSOP2 definitions for identification of LMS and LMM (Cohen kappa: 0.43). Phu and collaborators published similar results for severe sarcopenia (defined as concomitant presence of poor handgrip strength, low lean mass and low gait speed) (31), although data cannot be directly compared to ours, due to different study design and objectives. The lack of agreement between the two definitions may be explained both by the revised cutoff points for LMS and LMM and by the alternate assessment of low strength according to EWGSOP2. Interestingly, applying the new criteria, we obtained a lower percentage of people with low lean mass but a greater prevalence of LMS, probably because the assessment of strength is based on the evaluation of both grip strength and chair rise time.
According to our results, LMM and LMS alone, diagnosed according to EWGSOP2 criteria, conferred a higher mortality risk (HR 2.69, 95% CI 1.04–6.94; HR 3.18, 95% CI 1.44–7.01, respectively), while the combination LMM/LMS was not independently associated (HR 2.95, 95% CI 0.86–10.16). In addition, probable sarcopenia according to EWGSOP2 (the presence of LMS independent of muscle mass) but not sarcopenia conferred a higher mortality risk (Table 3). These results are similar to those described by Locquet and colleagues (27) and Petermann-Rocha and colleagues (30), reporting no significant association between sarcopenia defined by EWGSOP2 and mortality. Moreover, using FNIH criteria for weakness and low lean mass, McLean and collaborators obtained inconsistent results with regards to mortality risk patterns (32). We cannot rule out that this apparently counterintuitive finding may be explained by the low number of people in the LMM/LMS group as previously discussed; nevertheless, it is also plausible that low lean mass reflects the burden of age and comorbidities rather than being an independent predictor of mortality, while LMS is per se a risk factor for adverse outcomes.
According to our results, the predictive value of EWGSOP2 algorithm toward mortality is similar to that obtained applying the old criteria, resulting in low sensitivity and positive predictive values and high negative predictive values. Therefore, both definitions seem to well discriminate people who would not die rather than identify the individuals at higher mortality risk.
Independently of the definition, in our cohort, sarcopenia components were not associated with incident mobility disability. Although our data are influenced by the low prevalence of LMM and weakness in this sample, they are valuable given that literature data regarding association of EWGSOP2 definition of sarcopenia and mobility disability are lacking. Moreover, the relevance of our findings lies in the definition of the outcome, since the inability to walk 400 m is a direct, not self-reported, measure of mobility disability, leading to major health effects in vulnerable older people. A previous analysis of the InCHIANTI Study (17) reported that the combination of LMS and LMM, defined according to EWGSOP1 thresholds, was associated with functional impairment, but the outcome was incident or worsening IADL disability, instead of inability of walking 400 m, as in our study. In the study by McLean and collaborators (32), low grip strength and low lean mass-to-BMI ratio were associated with mobility disability (4-m gait speed ≤ 0.8 m/s). However, the sample was larger (6,280 individuals) than our cohort, different definitions of the predictors and of the outcome were used and no corrections for confounders were applied. Finally, it should be mentioned that other studies reported that, when examining the individual components of sarcopenia, the presence of low strength predicts the incidence of disability and falls better than the consensus algorithm (12,18), suggesting that the assessment of strength may be preferable, less expensive and time consuming compared to sarcopenia algorithms to predict functional deterioration.
Some limitations of this study should be pointed out. Since data were collected from a population of central Italy, our findings may not be translated to other communities. Secondly, regarding the association between EWGSOP2 LMM/LMS and mortality, we obtained a poor power (66%) for detecting the observed risk estimate as statistically significant; similarly, power calculations for all the comparisons with mobility disability, ranged from 21% to 66%. Accordingly, these results should be interpreted with caution. Moreover, we did not stratify the analyses according to gender since this may further reduce the power. Finally, the choice of excluding physical performance from sarcopenia diagnostic pathway (as explained in the methods section) may have limited the generalizability of our findings.
Despite these limitations, our study has some strengths. Our population of over 65 community-dwelling people is representative of the real world of old outpatients. Moreover, we analyzed the association of sarcopenia with “hard” outcomes, death and ability to walk 400 m. Finally, when analyzing association with the outcomes, we took into account potential confounders, since several factors apart from muscle strength and mass may be responsible for adverse outcomes in an older population.
In conclusion, we obtained a low-to-moderate agreement between old and new criteria for identification of LMM and LMS, due to changed cutoff points and to alternative assessments of muscle strength. The EWGSOP2 algorithm and cutoffs lead to a reduction in the estimated prevalence of sarcopenia defined as combination of LMM and LMS, but this may not translate into a better identification of people at higher risk of adverse outcomes. This finding may be clinically relevant, given that a number of individuals at risk of adverse outcomes could be classified as nonsarcopenic according to EWGSOP2; however, they confirm the pivotal role of muscle strength in sarcopenia diagnostic pathway as suggested in the new algorithm. It is plausible that other factors, instead of LMM itself, could be responsible for reduced grip strength and worse prognosis in our cohort of old individuals. Other studies are needed to confirm these findings and further research is advisable with the aim to identify which factors apart from low lean mass may contribute to reduced strength and may represent the target for interventions.
Supplementary Material
Acknowledgments
The authors are particularly grateful to the InCHIANTI study members who contributed to data collection.
Funding
The InCHIANTI Study was supported by the Italian Ministero della Salute as a “targeted project” (ICS 110.1/RS97.71) and by the U.S. National Institute on Aging (contracts N01-AG-916413, N01-AG-5-0002, N01-AG-821336, grant R01-AG-027012). The study was also supported in part by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
Conflict of Interest
The authors have no potential conflict of interest to declare.
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