Prevalence of Sarcopenia Among Slovenian Older Adults and Associated Risk Factors

Sarcopenia has been shown to affect between 10 and 16% of the global population based on various classification algorithms (1). Multiple research groups have proposed algorithms for sarcopenia classification (2–7), resulting in discrepancies in the reported prevalence which could be attributed to the continuous revisions of the criteria for defining sarcopenia. The algorithms differ in the proposed methods to evaluate domains of strength, muscle mass or physical performance. Despite efforts to compare and reconcile these algorithms, a universal standard for sarcopenia classification has yet to be established, regardless of its recognition as a disease (8). A unified classification algorithm is needed for multiple reasons: diagnosis confirmation, accurate prognosis and effective treatment plans (9). This multifaceted problem has recently been highlighted and points to various contributing factors including limited measurement methods for muscle mass in large cohorts, lack of consensus, inconsistent evaluation of functional status in older adults and lack of public awareness (10). Sarcopenia prevalence has been assessed in different countries, however, there is no data on sarcopenia prevalence in a representative sample of Slovenian older adults.

In addition to the large prevalence variance and weak agreement between classification methods (11), sarcopenia is a complex condition resulting from various contributing factors. For effective prevention, it is imperative to know the factors that can affect sarcopenia development. The natural ageing process is inevitable and associated with a gradual loss of muscle mass and strength (12) and age has been recognised as the most important risk factor of sarcopenia (13, 14). Furthermore, there are lifestyle behavioural factors (physical inactivity or poor dietary habits) that can significantly contribute to the risk of developing sarcopenia and are modifiable through targeted interventions (15, 16). Malnutrition can be frequently associated with a reduction of muscle mass and muscle strength, but their causal relationship is not yet well established (2, 15). However, the risk of malnutrition increases with age due to inadequate nutritional intake and it has major impacts on individuals’ independence and sarcopenia presence (17). Additionally, diminished physical activity with age, especially when coupled with increased physical inactivity, is a first modifiable but still prevalent risk factor of decreased muscle mass and function loss (18). It has been found that low levels of physical activity present a risk factor for sarcopenia onset among community-dwelling adults (19). Beyond physical factors, cognitive decline has been shown to have an association with sarcopenia (20), and the literature highlights the two-way association between cognitive and muscular deterioration, as it has been proposed that cognitive decline and sarcopenia share pathophysiological pathways (21).

This study aims to: a) determine sarcopenia prevalence among Slovenian older adults according to different classification algorithms, b) compare the agreement among the algorithms and c) evaluate the relationship between proposed risk factors and sarcopenia.

This study aimed to determine sarcopenia prevalence among Slovenian older adults according to different classification algorithms and its agreement and we found that sarcopenia is present between 2.1 and 15.3% of participants, while only 0.6% of participants were classified as sarcopenic across all eight used algorithms. The relationship between risk factors has been evaluated and it has been found that adequate nutrition and regular physical activity represent a protective factor, while age, lower cognitive function and sedentary lifestyle represent a risk factor for sarcopenia onset.

Sarcopenia prevalence depends on the classification algorithm being used and was between 2.1% (IWGS) and 15.3% (SDOC) among the general Slovenian population. Our findings are similar to the ones from a Spanish sample of community-dwelling older adults, which reported sarcopenia prevalence between 2.1 and 11.6% according to the EWGSOP2 algorithm, depending on the classification tests being used (30), and to prevalence in other European countries (France, Germany, Switzerland and Portugal) where sarcopenia was found in between 0.7 and 16.8% of older adults using different algorithms (31).

We found sarcopenia prevalence in 15.3% using the SDOC algorithm, which aligns with previous findings from the Hertfordshire cohort study (32,33). However, other population-based cohorts (33) reported lower prevalence for men using this algorithm while omitting the female population. The SDOC algorithm classified only 2% of the sample as sarcopenic among the community-dwelling population from four different European countries, of which there were no sarcopenic participants detected in Germany (31). Importantly, SDOC does not use muscle mass as a classification measure, which could result in higher prevalence in comparison to other classification algorithms.

The focus of the EWGSOP2 algorithm is on inclusion of the muscle strength component at the forefront of the algorithm and introduction to the muscle quality component, however in practice this one is often omitted. Similarly to the findings from Stuck et al. (31) we found that EWGSOP2 classifies less people as sarcopenic compared to other classifications - in our sample, this amounted to 4.1%. Other studies found even lower prevalences: 2.1% among community-dwelling older adults (31) and 1.1% among population-based cohorts (33). EWGSOP2 is relatively new, therefore not many studies have used it compared to the original EWGSOP which includes the muscle strength measure at a confirmatory level. Using EWGSOP, we found 11.8% prevalence of sarcopenia. Van Ancum et al. (34) pooled the data from multiple cohorts across European countries (the Netherlands, Denmark, United Kingdom, Finland, Estonia and France) and one Australian cohort using both the original EWGSOP and revised EWGSOP2, and also found lower sarcopenia prevalence when classified by EWGSOP2, at 16.7% and 11.4%, respectively. Sarcopenia prevalence using EWGSOP from 45 studies was between 20 and 25% (1), from which we can assume that our sample was less sarcopenic than the average of the global population when classified with either EWGSOP or EWGSOP2.

Swapping Sarc-F with Sarc-CalF in EWGSOP2 resulted in a 0.3% increase in sarcopenia prevalence, from 4.1% to 4.4%. Motivation for this was supported with previous findings, where Sarc-CalF showed enhanced sensitivity (35), higher diagnostic accuracy (36) and was able to detect more truly sarcopenic individuals (37) in comparison to Sarc-F.

Another modification in the EWGSOP2 was omitting the screening test - Sarc-F, based on the hypothesis that all of the screened participants are at risk of sarcopenia. This resulted in a 3.6% increase in sarcopenia prevalence to 7.7%. We can assume that Sarc-F excludes sarcopenic individuals due to the subjective observations of the individual’s own physical status. Therefore, Sarc-F might be more suitable to rule out sarcopenia than to detect it (38).

The global prevalence of sarcopenia using FNIH has been reported to be 15 % and for IWGS 20% (1), however, the Slovenian sample showed 7.7% and 2.1%, respectively.

When comparing the agreement among eight classification algorithms, we have found that only 4 (0.6%) participants were consistently classified as sarcopenic. Weak agreement between algorithms has also been found by Bijlsma et al. (11) and recently by Montemurro et al. (30). The discrepancies could be seen due to different assessment methods (i.e. muscle mass can be estimated with BIA or dual-energy x-ray absorptiometry (DXA)) and different sequences of those within the algorithms. Therefore, algorithms for sarcopenia classification still warrant improvements in consistency to be a diagnostic tool. Indeed, the EWGSOP2 algorithm adds a component of muscle quality and points out a need for a valid assessment method (3).

Lastly, we have assessed individual sarcopenia risk factors and preventive factors, as it has been shown that multimorbidity is a risk factor for sarcopenia (39). The first factor we have assessed is age, as it has been previously shown that this is the primary risk factor for sarcopenia onset (14), which our findings have confirmed. We found adequate nutrition to be the most prominent factor in preventing sarcopenia onset, which aligns with SarcoPhAge findings (40). Even though our study did not focus on nutrition quality, these findings show that sufficient macronutrient intake could be important for overall health. A higher amount of MVPA is a protective factor among our sample, similar to the findings from Japan, where higher MVPA was associated with lower functional disability incidence (41). A recent review also found an association between a sedentary lifestyle and sarcopenia onset (16), similar to our findings where a sedentary lifestyle represents a risk factor for sarcopenia. As physical activity decreases among older adults in Europe (42), we can speculate that sarcopenia will become a more prominent challenge in the future mostly due to physical inactivity. Our results indicate that higher BMI is a risk factor for sarcopenia development. The literature suggests that higher BMI values are also associated with adverse outcomes, especially when accompanying already developed sarcopenia, resulting in sarcopenic obesity which has higher mortality rates (43). The relationship between myokines, which regulate brain functions, such as mood, learning, locomotor activity and neuronal injury protection and skeletal muscle, points to the existence of muscle-brain cross-talk (44). Characterised by the progressive degeneration of muscle mass and function, sarcopenia could be conducive to or be associated with impaired cognitive function, as also observed in the present study. However, it is important to note that the relationship between sarcopenia and cognitive function is yet to be determined. Compared to the findings of a recent meta-analysis (45), the odds ratios were lower in our sample, although they still followed a similar trend: malnutrition is the largest behavioural risk factor (hence, adequate nutrition works as a preventive factor), while physical activity has positive effects on sarcopenia presence and aging, physical inactivity and cognitive function decline present a risk factor for sarcopenia.

This study has some limitations - although we aimed to recruit a representative sample of the general Slovenian population, we cannot rule out the possibility that the sample is biased towards the more active older adults who are more likely to respond to invitations to participate. However, we tried to avoid this at the preliminary recruitment phase. Secondly, tests for cognitive decline presented a large amount of missing data, therefore we were not able to use multivariate logistic regression models. Thirdly, our findings could be more conclusive if longitudinal study design were applied.

Sarcopenia prevalence in the Slovenian general population, classified by most algorithms (EWGSOP, EWGSOP2, FNIH, IWGS), is lower than global sarcopenia prevalence and similar to the European countries for which data exists, however prevalence strongly depends upon the classification algorithm being used. Physical activity and adequate nutrition were identified as preventive factors while age, cognitive decline, sedentary lifestyle and BMI are risk factors, pointing to possibilities for effective public health interventions. Addressing these methodological inconsistencies could improve sarcopenia identification, while the promotion of an active lifestyle could improve the quality of life of older adults.