Epidemiology of sarcopenia: A narrative review

Abstract

Sarcopenia is a progressive loss of skeletal muscle mass and strength that contributes to adverse outcomes such as falls, fractures, and mortality in aging populations. Its prevalence varies widely across studies, influenced by intrinsic factors (eg, age, comorbidities, lifestyle), environmental conditions (eg, urban–rural differences, institutionalization), and the diagnostic criteria applied. This review synthesizes evidence mainly from systematic reviews and meta-analyses to examine how these factors shape the epidemiology of sarcopenia. The use of different definitions, such as EWGSOP 1/2, AWGS 2014/2019, IWGS, and FNIH, leads to large variations in prevalence estimates. This limits regional comparisons and hampers surveillance. The review also highlights key risk factors such as physical inactivity, malnutrition, smoking, irregular sleep, and cognitive impairment, although the overall certainty of evidence remains low to moderate. These findings emphasize the need for harmonized diagnostic standards and greater methodological consistency in future studies. Clinically, integrating sarcopenia screening into routine care and implementing targeted lifestyle interventions may help reduce disease burden. Future longitudinal and interventional research is essential to clarify causal pathways and guide effective public health strategies for sarcopenia prevention and management.

1. Introduction

Sarcopenia is characterized by a progressive decline in skeletal muscle mass and strength. While it has traditionally been linked to advanced age, recent evidence suggests that it can develop as early as in midlife, before the age of 60 years [1]. The pathophysiology of sarcopenia is complex and may be influenced by intrinsic factors such as age, comorbidities, ethnicity, and lifestyle, as well as extrinsic environmental factors, including country of residence and living conditions [2]. As a result, the prevalence of sarcopenia may vary across different clinical settings and populations.

Common comorbidities associated with a higher prevalence of sarcopenia include diabetes mellitus (DM), cardiovascular diseases (CVD), heart failure (HF), cognitive impairment (MCI), and Alzheimer's disease (AD). Lifestyle-related factors—physical activity, sleep patterns, and nutritional status—also play important roles. In addition, environmental influences like continent or country of residence, urban–rural disparities, and living arrangements (eg, community versus institutional settings) may further contribute to the variability in prevalence. Sarcopenia contributes to adverse outcomes in older adults, including functional decline, increased care needs, and mortality. Many of these associated risk factors represent modifiable targets for intervention, offering opportunities to reduce disease burden and improve patient outcomes [2].

Another key factor influencing prevalence is the definition of sarcopenia itself. Commonly used diagnostic criteria include the European Working Group on Sarcopenia in Older People (EWGSOP1) [3], its revised version EWGSOP2 [4], the Asian Working Group for Sarcopenia 2014 (AWGS 2014) [5] and 2019 (AWGS 2019) [6], the International Working Group on Sarcopenia (IWGS) [7], the Foundation for the National Institutes of Health (FNIH) [8], and definitions based solely on low muscle mass [9]. These criteria differ in tools and cut-offs, which greatly influence reported prevalence.

This narrative review summarizes the influence of intrinsic factors, environmental conditions, and diagnostic criteria on the epidemiology of sarcopenia, drawing on evidence from published meta-analyses and systematic reviews. We conducted a literature search on PubMed and selected representative studies, primarily from the past ten years, based on relevance and methodological quality as assessed by the authors.

2. Prevalence of sarcopenia in different continents and ethnic groups

The prevalence of sarcopenia across different continents is theoretically influenced by various factors, including ethnicity, physical activity levels, dietary habits, economic status, and the prevalence of certain diseases [2]. Additionally, regional differences in the choice of diagnostic criteria can contribute to discrepancies in reported prevalence rates in the literature.

In this section, we summarize the prevalence data for each continent on the basis of existing meta-analyses. An extensive meta-analysis conducted by Petermann-Rocha et al. [9], encompassing 151 studies and 692,056 individuals, provided a comprehensive overview of the prevalence of sarcopenia on different continents; however, data from Africa are relatively limited. Therefore, prevalence estimates for Africa were drawn primarily from systematic reviews conducted by Mballa et al. [10] and Veronese et al. [11], who focused specifically on the African population. Table 1 summarizes the prevalence reported in existing meta-analyses, with continent-specific findings discussed in the following subsections.

Table 1.

Prevalence of sarcopenia in different continents.

	Prevalence defined by different criteria (95% CI) (number of studies)
	AWGS 2014	EWGSOP1	EWGSOP2	IWGS	FNIH	Muscle mass	Handgrip strength
Europe [9]	33% (29%–37%)(1)	22% (19%–26%) (27)	1% (1%–1%)(2)	7% (2%–13%)(4)	11% (5%–17%)(7)	29% (22%–37%) (17)	–
Asia [9]	15% (12%–17%) (45)	21% (14%–29%)(8)	9% (8%–11%)(1)	17% (10%–25%)(6)	10% (7%–12%)(8)	27% (20%–33%) (13)	–
North America [9]	–	14% (10%–18%)(2)	–	17% (11%–23%)(1)	9% (8%–10%)(1)	18% (15%–20%) (12)	–
South America [9]	–	21% (15%–27%)(9)	–	18% (13%–23%)(1)	29% (20%–39%)(1)	35% (15%–56%) (9)	–
Africa [10,11]	–	17% (12%–22%)(7)	29% (15%–73%)(2)	–	28% (12%–45%)(6)	SA ASMI 9% (6%–12%)(2) ASM/SMI 49% (36–62%)(2)	53% (43%–63%)(1)
Oceania [9]	–	40% (33%–47%)(2)	–	–	5% (4%–6%)(1)	23% (19%–27%)	–

AWGS, Asian Working Group for Sarcopenia; EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; FNIH, The Foundation for the National Institutes of Health; SA ASMI, South African appendicular skeletal muscle mass index; ASM, appendicular skeletal muscle mass; SMI, skeletal mass index.

Europe: The prevalence in different continents is shown in Table 1. Europe has the second-highest number of studies on the prevalence of sarcopenia [9]. Among these studies, the reported prevalence ranged from 1% (95% CI: 1%–1%, EWGSOP2 criteria) to 33% (data from only one study, AWGS2014 criteria). Although the pooled prevalence based on the EWGSOP2 criteria is low at 1%, this estimate is derived from only two studies. In contrast, the prevalence based on the AWGS 2014 criteria is high at 33%, but this is based on data from only one study. Therefore, these extreme values require further research to determine whether they accurately reflect the true prevalence. The three most commonly used diagnostic criteria in European studies are the EWGSOP1 criteria (22% prevalence, 95% CI: 19%–26%), the muscle mass definition (29% prevalence, 95% CI: 22%–37%), and the FNIH criteria (11% prevalence, 95% CI: 5%–17%).

2.1. Asia

Asia has the highest number of studies reporting the prevalence of sarcopenia [9], with prevalence estimates ranging from 9% (data from only one study, EWGSOP2 criteria) to 27% (95% CI: 20%–33%, muscle mass definition). Unlike Europe, most Asian studies adopt the AWGS 2014 criteria (15% prevalence, 95% CI: 12%–17%), followed by the muscle mass definition (27% prevalence, 95% CI: 20%–33%), the EWGSOP1 criteria (21% prevalence, 95% CI: 14%–29%), and the FNIH criteria (10% prevalence, 95% CI: 7%–12%). Since data from Asia and Europe are abundant, a comparison was made between the two regions for the criteria that were used in at least five studies. The findings suggest that the pooled prevalence is similar between Asia and Europe when the same diagnostic criteria are applied. The comparative prevalence values for each criterion are as follows: EWGSOP1: 22% (Europe) vs 21% (Asia); FNIH: 11% (Europe) vs 10% (Asia); and muscle mass definitions: 29% (Europe) vs 27% (Asia).

2.2. America

America is further divided into North America and South America [9]. In North America, the reported prevalence of sarcopenia ranges from 9% (data from only one study, FNIH criteria) to 18% (95% CI: 15%–20%, muscle mass definition). The muscle mass definition is the most commonly used criterion, whereas other diagnostic criteria have been applied in only one or two studies. In South America, the prevalence ranges from 18% (data from only one study, IWGS criteria) to 35% (95% CI: 15%–56%, muscle mass definition), with the muscle mass definition also being the most frequently used. The prevalence of sarcopenia in South America is generally higher than that in North America across different diagnostic criteria. For instance, the prevalence using the EWGSOP1 criteria is 21% in South America and 14% in North America. When defined by low muscle mass alone, the prevalence is 35% in South America and 18% in North America.

2.3. Africa

A recent systematic review [10] reported that the prevalence of sarcopenia in Africa ranges from 9% (95% CI: 6%–12%, defined by South African appendicular skeletal mass index) to 53% (95% CI: 43%–63%, defined by handgrip strength). The most commonly used diagnostic criteria are the EWGSOP1 criteria (17% prevalence, 95% CI: 12%–22%) and the FNIH criteria (28% prevalence, 95% CI: 12%–45%) in African studies. When the prevalence was compared using the same diagnostic criteria, Africa had a higher prevalence than what was reported in the preceding subsections for Asia, Europe, or North America [[9], [10], [11]]. However, this may be because most African studies are hospital-based [10], whereas previous research has indicated that the prevalence of sarcopenia in hospital patients is significantly higher than that in community-dwelling residents [12]. Therefore, whether Africa truly has a higher prevalence remains uncertain, and further objective comparisons in future studies are needed.

2.4. Oceania

Research on sarcopenia in Oceania is relatively limited [9], with reported prevalence ranging from 5% (data from only one study, FNIH criteria) to 40% (95% CI: 33%–47%, EWGSOP1 criteria). Owing to the small number of studies and the fact that each diagnostic criterion has been used in only one or two studies, the available data are insufficient to draw meaningful comparisons with other regions.

As the above results suggest, there are considerable differences among continents in terms of the number of studies, diagnostic criteria employed, and characteristics of study populations. These variations make it difficult to directly compare the prevalence of sarcopenia across regions. Asia and Europe are the most extensively studied continents, and the pooled prevalence rates reported using various diagnostic criteria in these two regions are generally comparable [9].

Importantly, the meta-analyses cited here include relatively few studies that use newer criteria, such as EWGSOP2 [4] and AWGS 2019 [6]. Consequently, prevalence data derived from these updated definitions are still limited across continents, and further meta-analyses are needed to provide more comprehensive and up-to-date estimates. The prevalence based on AWGS 2019 in Asian countries will be discussed in the following section, and the influence of different diagnostic criteria on prevalence will also be explored later in this article.

Another important aspect is the difference in the prevalence of sarcopenia among ethnic groups. Today, each continent is inhabited by a mix of ethnicities, and individuals of the same ethnicity may adopt different lifestyles depending on the continent in which they reside. These factors can influence our understanding of the role that ethnicity plays in the prevalence of sarcopenia. To our knowledge, no meta-analysis has focused specifically on ethnic differences in the prevalence of sarcopenia. However, a review by Jung et al. [13] summarized findings from a study using data from the National Health and Nutrition Examination Survey (NHANES) in the United States (1999–2004). This study revealed that, in general, the Hispanic population had the highest prevalence, whereas the non-Hispanic Black population had the lowest prevalence, and the prevalence of non-Hispanic White individuals and other individuals (including Asian, Native American, and multiracial individuals) fell in between that of the other populations (Table 3). Despite using outdated definitions, the study offers insight into how ethnicity may influence sarcopenia, as the data came from a single country and time period.

Table 3.

Prevalence of sarcopenia in different age groups [13].

	Number of participants	Prevalence (age group)
NHANES study (1999–2004) [22]	4367	NH white	NH black	Hispanic	Other
		M: 2.5% (18–39), 10.1% (40–64), 15.5% (≥65) W: 3.9% (18–39), 8.8% (40–64), 15.1% (≥65)	M: 0.0% (18–39), 0.2% (40–64), 8.6% (≥65) W: 0.0% (18–39), 0.4% (40–64), 1.6% (≥65)	M: 7.2% (18–39), 11.4% (40–64), 26.8% (≥65) W: 18.9% (18–39), 16.8% (40–64), 27.2% (≥65)	M: 10.6% (18–39), 12.1% (40–64), 16.5% (≥65) W: 0.0% (18–39), 6.2% (40–64), 23.2% (≥65)
NHANES study (1999–2006) [21]	14448	Year 1999–2000	Year 2001–2002	Year 2003–2004	Year 2005–2006
		11.3% (18–39), 15.1% (40–59), 22.3% (60–79), 45.1% (≥80)	13.5% (18–39), 12.1% (40–59), 23.7% (60–79), 40.1% (≥80)	14.9% (18–39), 14.2% (40–59), 23.6% (60–79), 42.0% (≥80)	14.1% (18–39), 12.9% (40–59), 17.7% (60–79), NR (≥80)
KNHANES study (2008–2009) [24]	10485	M: 13.3% (40–49), 20.6% (50–59), 32.6% (60–69), 47.8% (70–79), 59.0% (≥80)
		W: 4.8% (40–49), 4.8% (50–59), 4.1% (60–69), 14.0% (70–79), 12.7% (≥80)
KNHANES study [23] (2008–2011) [23]	17968	M: 20.5% (20–39), 27.5% (40–64), 42.9% (≥65)
		W: 17.7% (20–39), 30.8% (40–64), 41.8% (≥65)
Single center study (Korea) [25]	300090	M: 13.0% (20–29), 15.9% (30–39), 13.9% (40–49), 13.9% (50–59), 20.4% (60–69), 32.7% (70–79), 44.2% (80–89)
		W: 17.0% (20–29), 15.1% (30–39), 18.8% (40–49), 32.4% (50–59), 45.2% (60–69), 58.1% (70–79), 66.7% (80–89)

NHANES, National Health and Nutrition Examination Survey; KNHANES, Korea National Health and Nutrition Examination Survey; NH, Non-Hispanic; M, men, W, women.

To address the methodological quality of the meta-analyses cited in this review, we conducted an evaluation using the AMSTAR 2 tool and assessed the reporting completeness based on PRISMA guidelines. The global meta-analysis by Petermann-Rocha et al. [9] adheres closely to the PRISMA 2020 guidelines, with a registered protocol, comprehensive database search, clear inclusion criteria, and appropriate meta-analytic methods. According to AMSTAR 2, the review demonstrates moderate methodological quality, with strengths in duplicate screening, risk of bias assessment, and heterogeneity exploration. However, limitations include lack of sensitivity analyses, no formal publication bias assessment, and incomplete reporting of reasons for study exclusion at full-text screening. Despite these gaps, the review provides a valuable synthesis of sarcopenia prevalence, highlighting the need for more population-representative and methodologically rigorous studies.

Two systematic reviews on sarcopenia in Africa showed differing methodological quality. Mballa Yene et al. [10] followed PRISMA guidelines and registered in PROSPERO, with clear objectives, comprehensive search strategies, and bias assessment via Hoy's tool. It was rated moderate in AMSTAR 2, with strengths including protocol registration and subgroup analysis, but lacked detailed exclusion reasons and discussion on bias impact. In contrast, Veronese et al. [11] adhered well to PRISMA guidelines, used the Newcastle–Ottawa Scale for bias assessment, involved independent reviewers, and conducted appropriate statistical synthesis, achieving high AMSTAR 2 quality despite some unaddressed confounding factors and a limited number of included studies.

These methodological differences should be considered when interpreting the reported prevalence estimates, particularly in regions with limited data or high heterogeneity.

3. Prevalence of sarcopenia in different countries in Asia

As mentioned earlier, most studies in Asia adopt the AWGS criteria. According to earlier meta-analyses, the prevalence of sarcopenia in Asia according to the AWGS 2014 [5] criteria was approximately 15% [9]. Compared with the AWGS 2014 criteria, the AWGS 2019 criteria adopt more lenient cutoff values for handgrip strength and gait speed and introduce the concept of possible sarcopenia, allowing at-risk individuals to receive timely lifestyle modifications. The lower threshold for diagnosis also contributes to a higher prevalence of sarcopenia.

The most recent meta-analysis and systematic review by Weng et al. analyzed studies that applied the AWGS 2019 criteria to assess the prevalence of sarcopenia in Asian countries [14]. In the meta-analysis, data from 74 studies involving 91878 community-dwelling older adults aged 60 years and above in various Asian countries were analyzed. The pooled prevalence of sarcopenia was 16.5% (95% CI: 14.7%–18.4%), that of severe sarcopenia was 4.4% (95% CI: 3.3%–5.8%), and that of possible sarcopenia was 28.7% (95% CI: 22.0%–36.5%).

The prevalence rates in different Asian countries are shown in Table 2. Across Asian countries, the prevalence of sarcopenia generally falls between 10% and 20%. The reported prevalence rates in China, Japan, Korea, Taiwan, Thailand, Singapore, and Malaysia are 18.4% (95% CI: 18.4%), 13.2% (95% CI: 10.4%–16.6%), 19.9% (95% CI: 16.8%–23.3%), 17.6% (95% CI: 10.9%–27.2%), 13.6% (95% CI: 7.5%–23.5%), 16.0% (95% CI: 9.3%–26.1%), and 8.6% (95% CI: 7.6%–9.1%), respectively. Notably, although Malaysia's prevalence appears significantly lower, this estimate is currently based on only one study, and further research is needed to confirm whether this trend holds true.

Table 2.

Prevalence of sarcopenia in different Asian countries (AWGS 2019) [14].

	Number of studies	Number of older patients	Prevalence (95% CI)
China	24	27221	18.4% (15.0%–22.3%)
Japan	22	33396	13.2% (10.4%–16.6%)
Korea	15	23652	19.9% (16.8%–23.3%)
Taiwan	7	3272	17.6% (10.9%–27.2%)
Thailand	4	1858	13.6% (7.5%–23.5%)
Singapore	1	75	16.0% (9.3%–26.1%)
Malaysia	1	2404	8.6% (7.6%–9.8%)

Previous research has shown that updated cutoff values in AWGS 2019 offer better accuracy in predicting sarcopenia-related outcomes [15]. On the basis of these results, when AWGS 2019 is used as the diagnostic standard, the prevalence of sarcopenia in Asian countries generally ranges from 10% to 20%, whereas the overall prevalence of possible sarcopenia approaches 30%. This finding indicates that a substantial proportion of the Asian population is at risk of sarcopenia, and these individuals could benefit from early lifestyle modifications in diet and exercise, highlighting sarcopenia as a significant public health issue that should not be overlooked.

This systematic review and meta-analysis [14] shows good adherence to PRISMA and moderate-to-high quality by AMSTAR 2. It followed PRISMA guidelines with a registered protocol (INPLASY202450095), comprehensive search strategies, clear inclusion criteria, dual-reviewer screening, and appropriate risk-of-bias tools. Subgroup and publication bias analyses were also conducted, with results clearly presented. According to AMSTAR 2, strengths include protocol registration, duplicate processes, and thorough methodological assessment. Minor limitations include limited detail on excluded studies and minimal discussion on bias impact. Overall, the review is methodologically sound and provides a reliable synthesis of sarcopenia data in Asia.

4. Prevalence of sarcopenia in different age groups

Muscle mass and strength decrease with age. The combined effects of progressive muscle fiber atrophy with a preferential decrease in fast units, neural degeneration, and disruptions in protein homeostasis are the primary causes of primary sarcopenia [16]. Most studies on sarcopenia in the current literature focus on older adults, typically those aged 60 and above. With respect to studies focusing on older populations, a meta-analysis of community-dwelling older adults identified age as an associated factor for sarcopenia [17], indicating that the risk increases progressively with advancing age. However, another meta-analysis of nursing home residents revealed that age was not an associated factor and suggested that even relatively younger individuals in nursing homes should be actively screened for sarcopenia [18]. These findings highlight that the impact of age on the prevalence of sarcopenia may vary across different elderly populations, emphasizing the need for careful interpretation of study results.

Compared with the elderly population, where well-established criteria for diagnosing sarcopenia exist, the definition of sarcopenia in younger populations varies across studies. Most studies define sarcopenia on the basis of muscle mass measured by BIA, DXA, or CT, normalized by height squared, body weight, or fat mass. A few studies have used muscle strength, adjusting for BMI or leg length [13,19]. However, there is no standardized cutoff value among studies, and this lack of uniformity makes it difficult to directly compare the prevalence in different age groups. Therefore, comparing the prevalence of sarcopenia between age groups is best performed within a single large-scale study. Currently, the most extensive studies are NHANES [20,21], the Korea National Health and Nutrition Examination Survey (KNHANES) nationwide cohort studies [22,23], and studies from a single healthcare center in South Korea [24]. These datasets have been thoroughly summarized in the review article by Jung et al. [13].

The prevalence in different age groups is shown in Table 3. NHANES studies generally show an increasing prevalence of sarcopenia with age [20,21]. For example, a study by Li et al. (1999–2004) reported that the average prevalence was 10%–15% in individuals aged 18–39 and 40–59, increasing to 20%–30% in those aged 60–80, and exceeding 40% in those over 80 [20]. Similarly, KNHANES studies revealed comparable findings. Bae et al. (2008–2011) reported that in men, the prevalence was 20.5% for those aged 20–39 years, 27.5% for those aged 40–64 years, and 42.9% for those aged ≥ 65 years. In women, the prevalence in corresponding age groups was 17.7%, 30.8%, 41.8%, and 41.8%, respectively [22]. A recent large-scale study from a single healthcare center in South Korea (2012–2018, 300090 participants) further confirmed this trend [24]. In men, the prevalence was 10%–20% for those < 60 years, increasing to 20.4% at 60–69 years, 32.7% at 70–79 years, and 44.2% at 80–89 years. Women exhibited a similar trend but with an earlier and steeper increase. The prevalence was 10%–20% for those < 50 years, increasing to 32.4% at 50–59 years, 45.2% at 60–69 years, 58.1% at 70–79 years, and 66.7% at 80–89 years.

On the basis of the above findings, a general summary can be drawn: under the same assessment methods, the prevalence of sarcopenia in general population tends to increase with age. This trend becomes particularly evident after 60 years of age, when a significant increase in prevalence is observed. Among the general population over 60, the prevalence continues to increase with advancing age. Although these conclusions are primarily drawn from cross-sectional observational studies, the consistency across large-scale population-based datasets and the presence of a dose-response relationship support a moderate quality of evidence according to the GRADE approach. Nevertheless, the observational nature of the data and the lack of longitudinal confirmation suggest that further high-quality prospective studies are warranted to strengthen this conclusion.

5. Prevalence of sarcopenia using different diagnostic criteria

Different diagnostic criteria for sarcopenia vary in the assessment tools and cutoff values used (Table 4). Even within the same working group, updated versions are released over time on the basis of evolving consensus. Therefore, when comparing the prevalence of sarcopenia, it is essential to consider which definition is being applied. Ideally, the impact of different criteria on prevalence should be evaluated by applying multiple definitions within the same population. However, in practice, studies from different regions tend to favor different criteria, and studies conducted at different time points often adopt different versions of the definitions. As a result, the number of studies that can directly assess the influence of diagnostic criteria on prevalence is limited. This section is primarily based on the review by Voulgaridou et al. [25], which provides a comprehensive discussion on this topic. We focus on the six most commonly used definitions in the literature: AWGS 2014, AWGS 2019, EWGSOP1, EWGSOP2, IWGS, and the FNIH criteria [9].

Table 4.

Diagnostic algorithm and cutoff points for confirmation of sarcopenia.

		AWGS 2014 [5]	AWGS 2019 [6]	EWGSOP1 [3]	EWGSOP2 [4]	IWGS [7]	FNIH [8]
Evaluation	handgrip strength	M < 26 kg	M < 28 kg	M < 30 kg	M < 27 kg	–	M < 26 kg
		F < 18 kg	F < 18 kg	F < 20 kg	F < 16 kg		F < 16 kg
	Walking speed	< 0.8 m/s	< 1.0 m/s	< 0.8 m/s	–	<1.0 m/s	–
	5-time chair stand	–	t ≥ 12 s	–	t > 15 s	–	–
	SPBB	–	≤ 9	–	–	–	–
Muscle mass	ASM	–	–	–	M < 20 kg F < 15 kg	–	–
	ASM/height2	DXA	DXA	DXA or BIA two standard deviations below the mean reference value (healthy young adult)	DXA or BIA M < 7 kg/m2, F < 5.5 kg/m2	DXA M ≤ 7.23 kg/m2 F ≤ 5.67 kg/m2	–
		M < 7 kg/m2	M < 7 kg/m2
		F < 5.4 kg/m2	F < 5.4 kg/m2
		BIA	BIA
		M < 7 kg/m2	M < 7 kg/m2
		F < 5.7 kg/m2	F < 5.7 kg/m2
	ASM/BMI	-	-	-	-	-	M < 0.789 F < 0.512
Confirmation of diagnosis		↓handgrip strength or	↓handgrip strength or	↓handgrip strength or	↓handgrip strength or	↓ walking speed	↓ Grip strength
		↓walking speed +	↓physical performance+	↓walking speed +	⇧chair-stand +	+	+
		ASM/height2	ASM/height2	ASM/height2	ASM/height2	ASM/height2	ASM/BMI

AWGS, Asian Working Group for Sarcopenia; EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; FNIH, The Foundation for the National Institutes of Health.

5.1. AWGS 2014 vs AWGS 2019

Compared with the AWGS 2014 criteria, the AWGS 2019 criteria raised the grip strength cutoff for men from 26 kg to 28 kg and increased the gait speed cutoff for both sexes from 0.8 m/s to 1.0 m/s. For the assessment of physical performance, in addition to gait speed, the Five-Times Sit-to-Stand Test and the Short Physical Performance Battery (SPPB) were introduced as alternative tools.

These changes have contributed to an increased prevalence of sarcopenia. The results of studies that compared the prevalence according to different criteria are shown in Table 5. A study from Korea by Kim et al. [26], which included 2123 community-dwelling individuals aged 70 years or older, assessed the prevalence using different diagnostic criteria. The results showed that when the AWGS 2014 criteria were used, the average prevalence was 9.2% (10.3% in men and 8.1% in women). However, when the AWGS 2019 criteria were applied, the prevalence increased to 22.8% (26.8% in men and 18.8% in women). Similar findings have been confirmed by other studies [27,28]. Another study conducted by Pang et al. [28], which included 542 community-dwelling Singaporeans aged 21–90 years, also demonstrated an increase in prevalence—from 6.7% according to the AWGS 2014 criteria to 13.6% according to the AWGS 2019 criteria.

Table 5.

Studies comparing prevalence of sarcopenia defined by different criteria.

		Criteria	Prevalence
Kim et al. [26]	≥70-year-old, 2123 community-dwelling individuals in Korea	AWGS 2014	9.2%
		AWGS 2019	22.8%
		EWGSOP1	21%
		EWGSOP2	11.2%
		IWGS	15.6%
		FNIH	6.6%
Pang et al. [28]	≥60-year-old, 542 community-dwelling individuals from Singapore	AWGS 2014	6.7%
		AWGS 2019	13.6%
		EWGSOP2	7.1%
Yang et al. [27]	≥60-year-old, 483 community-dwelling individuals from China	AWGS 2014	9.1%
		EWGSOP1	15.7%
		EWGSOP2	4.6%
		IWGS	16.1%
		FNIH	3.3%
Yang et al. [29]	≥60-year-old, 384 community-dwelling individuals from China	EWGSOP1	27.3%
		EWGSOP2	26.8%
Wallengren et al. [30]	Two cohorts (one ≥70-year-old and the other ≥85-year-old), totally 1041 participants from Sweeden	EWGSOP1	11%
		EWGSOP2	10%
Shafiee et al. [31]	≥60-year-old, 2426 community-dwelling individuals from Iran	EWGSOP1 (Iranian cutoff)	Men: 19.7%
			Women: 13.6%
		EWGSOP2 (Iranian cutoff)	Men: 10.5%
			Women: 7.13%
		EWGSOP2 (European cutoff)	Men: 12.7%
			Women: 5.42%
Bachettini et al. [32]	≥60-year-old, 1291 community-dwelling individuals from Brazil	EWGSOP1	8.8%
		EWGSOP2	3.4%
Lee et al. [33]	≥50-year-old, 408 community-dwelling individuals from Taiwan	IWGS	7.8% (RASM)
			16.6% (SMI)
		EWGSOP1	4.1% (RSAM))
			11.1% (SMI)
Sim et al. [34]	≥70-year-old, 903 community-dwelling Caucasian-Australian women	FNIH	9.4%
		EWGSOP1	24.1%

AWGS, Asian Working Group for Sarcopenia; EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; FNIH, The Foundation for the National Institutes of Health.

5.2. EWGSOP1 vs EWGSOP2

In contrast to the direction of adjustment seen in the AWGS criteria, the EWGSOP2 criteria [4] revised the cutoff values downward compared with the EWGSOP1 criteria [3]. Specifically, the grip strength threshold was reduced from 30 kg to 27 kg for men and from 20 kg to 16 kg for women. The cutoff values for muscle mass were also adjusted. Current studies consistently show that the prevalence of sarcopenia diagnosed via the EWGSOP2 is lower than that diagnosed via the EWGSOP1 (Table 5) [27,[29], [30], [31], [32]].

5.3. EWGSOP vs AWGS

On the basis of current evidence [26,28], it can be inferred that the prevalence estimated via AWGS 2019 is comparable to that estimated via EWGSOP1, whereas the prevalence estimated via AWGS 2014 is closer to that estimated via EWGSOP2 (Table 5). For example, a study by Kim et al. [26] reported sarcopenia prevalence rates of 21% (EWGSOP1), 11.2% (EWGSOP2), 9.2% (AWGS 2014), and 22.8% (AWGS 2019). Similarly, Pang et al. [28] reported prevalence rates of 7.1% (EWGSOP2), 6.7% (AWGS 2014), and 13.6% (AWGS 2019). Another study involving 483 community-dwelling older adults also found higher prevalence using EWGSOP1 (15.7 %), and lower rates with EWGSOP2 (4.7%) and AWGS 2014 (9.1%), confirming this trend [27].

5.4. IWGS or FNIH vs other criteria

Studies directly comparing the IWGS [7] and FNIH [8] criteria with other definitions within the same population are relatively limited (Table 5). Previous research has shown that the prevalence of IWGS can be either higher or lower than that of EWGSOP1, depending on the population studied [27,33]. In contrast, the FNIH definition consistently yields a lower prevalence than EWGSOP1 does. In a study of 903 community-dwelling Australian women aged 70 years or older, the prevalence of sarcopenia was 9.4% according to the FNIH and 24.1% according to the EWGSOP1 [34]. Similarly, in the study by Yang et al. [27], the reported prevalence was 3.3% with FNIH and 15.7% with EWGSOP1.

In summary, diagnostic criteria greatly influence the reported prevalence of sarcopenia. Overall, AWGS 2019 and EWGSOP1 yield higher estimates, while AWGS 2014 and EWGSOP2 report lower ones. FNIH consistently reports the lowest prevalence, and IWGS results vary by population.

5.5. Clinical and policy implications of divergent sarcopenia definitions

From a clinical perspective, broader definitions like AWGS 2019 and EWGSOP1 identify more individuals as sarcopenic, expanding the at-risk population eligible for intervention. This may improve early detection and timely initiation of resistance training or nutritional support. In contrast, Stricter definitions like AWGS 2014 and EWGSOP2 may underestimate cases and delay treatment.

At the public health level, these discrepancies can cause inconsistent estimates of disease burden across regions. For example, applying AWGS 2019 instead of AWGS 2014 in the same population can more than double the prevalence. This shift may affect funding priorities, screening strategies, and geriatric care planning.

In epidemiological monitoring, varying diagnostic criteria make cross-national comparisons and trend analyses difficult. Global aging initiatives, such as those led by the WHO, depend on consistent definitions to track sarcopenia accurately. Without harmonized criteria or clear reporting, it remains challenging to compare data over time or across regions.

To facilitate a clearer comparison, Table 6 summarizes the diagnostic tendencies of the most commonly used criteria.

Table 6.

Prevalence tendency of diagnostic criteria.

Prevalence tendency	Diagnostic Criteria
Higher prevalence	AWGS 2019, EWGSOP1
Lower prevalence	AWGS 2014, EWGSOP2
Lowest prevalence	FNIH
Variable prevalence	IWGS

AWGS, Asian Working Group for Sarcopenia; EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; FNIH, The Foundation for the National Institutes of Health.

6. Prevalence of sarcopenia in communities, hospitals, or nursing homes

Regardless of whether we conduct sarcopenia screening or prevention in the community, institutions, or hospitals, understanding its prevalence in these settings is crucial. The significant variations in the prevalence of sarcopenia across these environments make it challenging to establish standardized preventive strategies and therapeutic protocols.

A meta-analysis by Papadopoulou et al. [12] summarized the prevalence of sarcopenia among adults aged 60 years and older in these settings. A total of 34,955 individuals aged 60 years and older from the general population were examined, including 15,599 men (45%) and 19,347 women (55%). Among them, 30,287 were community-dwelling individuals, 3802 were hospitalized patients, and 886 were nursing home residents (Table 7).

Table 7.

Prevalence of sarcopenia in community, hospital, or nursing home [12].

Study population (N = 34,955)	Prevalence (95% CI)
Total	13% (11%–15%)
Community-dwelling individuals (N = 30287)
Total	10% (8%–12%)
Men	11% (8%–13%)
Women	9% (7%–11%)
Hospital patients (N = 3802)
Total	23% (15%–32%)
Men	23% (15%–30%)
Women	24% (14%–35%)
Nursing home residents (N = 886)
Total	38% (34%–41%)
Men	51% (37%–66%)
Women	31% (22%–42%)

The prevalence of sarcopenia among community-dwelling individuals was 10% (95% CI: 8%–12%), with 11% (95% CI: 8%–13%) in men and 9% (95% CI: 7%–11%) in women. Among nursing home residents, the prevalence was 38% (95% CI: 34%–41%), with 51% (95% CI: 37%–66%) in men and 31% (95% CI: 22%–42%) in women. Among hospitalized patients, the prevalence was 23% (95% CI: 15%–32%), with 23% (95% CI: 15%–30%) in men and 24% (95% CI: 14%–35%) in women (Table 7).

In summary, the prevalence of sarcopenia is greater in nursing home residents and hospitalized patients than in community-dwelling individuals. Malnutrition and low physical activity may be key contributing factors to these findings. Sarcopenic residents in nursing homes tend to be sedentary and are more likely to experience malnutrition [35,36]. In hospitalized patients, additional risk factors for sarcopenia may include acute or chronic diseases, reduced energy intake, low physical activity, prolonged bed rest, depressed mood, and social isolation [37,38].

This systematic review and meta-analysis by Papadopoulou et al. [12] registered with PROSPERO and adhering to several PRISMA guidelines, provides a comprehensive overview of sarcopenia prevalence across different populations. The study features a robust search strategy, appropriate meta-analytic techniques, and subgroup analyses. However, the absence of individual study risk of bias assessments and limited evaluation of study-level quality restrict the confidence in its conclusions. According to the AMSTAR 2 tool, the review demonstrates moderate methodological quality, suggesting that the evidence is reasonably reliable, though future reviews would benefit from a more rigorous appraisal of bias and its implications on pooled estimates.

7. Prevalence of sarcopenia in urban, rural-urban, or rural areas

The built environment has a significant effect on the prevalence of sarcopenia. Factors such as food accessibility, availability, and affordability, as well as the presence and proximity of opportunities for leisure-time physical activity, can be directly or indirectly influenced by the built environment [[39], [40], [41]]. Therefore, the built environment may be a key determinant of sarcopenia incidence.

A meta-analysis by Li et al. [42] examined the prevalence of sarcopenia among individuals in urban, urban‒rural, and rural areas. A total of 433091 individuals were examined, with an overall sarcopenia incidence of 18% (95% CI: 14%–22%). The prevalence of sarcopenia was lower in urban areas, at 16% (95% CI: 10%–22%), than in rural areas, at 20% (95% CI: 16%–25%), and in urban‒rural areas, at 21% (95% CI: 16%–25%) (Table 8).

Table 8.

Prevalence of sarcopenia in urban, rural‒urban, or rural area [42].

Study population (N = 433,091)	Prevalence (95 % CI)
Total	18 % (14 %–22 %)
Urban	16 % (10 %–22 %)
Urban‒rural	21 % (16 %–25 %)
Rural	20 % (16 %–25 %)

In summary, the prevalence of sarcopenia is greater among individuals in rural areas than among those in urban areas, which may be attributed to several factors, including lower socioeconomic status, poor nutritional status, reduced physical activity, and underlying health conditions. Urban areas are typically characterized by greater material abundance and better access to adequate nutritional supplements, whereas a greater proportion of older adults in rural areas experience malnutrition, potentially leading to lower muscle mass and strength [42]. Additionally, fewer older adults in rural areas engage in physical activity than their urban counterparts do, which may contribute to lower gait speed and handgrip strength [43]. Furthermore, osteoarthritis is more prevalent among the rural elderly population and significantly affects gait speed, which is a key component in the diagnosis of sarcopenia [43].

The urban–rural meta-analysis [42] was rated as moderate in quality based on AMSTAR 2 and PRISMA criteria. Strengths included protocol registration, detailed subgroup and sensitivity analyses, and assessment of publication bias using Egger's and Begg's tests. However, the study did not apply GRADE to evaluate evidence certainty and failed to explain how study-level biases may have affected the results. These limitations should be considered when interpreting urban–rural differences in sarcopenia prevalence.

8. Prevalence of sarcopenia among different diseases

Sarcopenia has been linked to various physical and mental health conditions, particularly in individuals with chronic diseases, such as diabetes [14], cardiovascular disease [44], renal dysfunction [45], and cognitive impairment [46], that are common in the aging population [2]. These conditions often interact, contributing to a downward spiral in overall health status among older adults.

Table 9 presents the results of current systematic reviews and meta-analyses on the prevalence of sarcopenia across different disease states. The prevalence varied depending on age groups and diagnostic criteria, demonstrating significant heterogeneity. However, in general, individuals with these chronic conditions presented a greater prevalence of sarcopenia than did the general population, particularly those hospitalized for acute decompensated heart failure or undergoing dialysis.

Table 9.

Prevalence of sarcopenia across different disease states.

Disease	population/subgroups	Prevalence
DM [14]	8 studies focusing on people with Type 2 DM, 3261 patients	20.5%
CVD [44]	14 studies with 3697 patients HF with reduced ejection fraction and HF with preserved ejection fraction	34%–66%
	Hospitalized for acute decompensated HF	66%
CKD [45]	A total of 140 studies (42041 patients) across 25 countries were included in this systematic review and meta-analyses	24.5 % and did not differ among stages (P = 0.33).
	Patient on Dialysis	50.0%
Dementia [46]	77 studies consisting of 92058 subjects >50 years old in MCI, AD or other types of dementia	Not reported
	MCI	2.8%–73.9%
	AD	4.2%–86.6%
	Other types of dementia	15.4%–61.3%

DM, diabetes mellitus; CVD, cardiovascular diseases; HF, Heart Failure; MCI, mild cognitive impairment; AD, Alzheimer's disease.

These consistent findings underscore the critical importance of early evaluation and intervention for sarcopenia in older adults with multiple comorbidities, particularly those at high risk. Furthermore, the results highlight that sarcopenia is not solely a concern within geriatrics but is also relevant across a broad spectrum of internal medicine specialties.

Overall, the meta-analyses examining sarcopenia in chronic disease populations were of moderate quality. Most applied clear inclusion criteria, appropriate statistical methods, and risk-of-bias assessments. However, common limitations included the lack of protocol registration, limited assessment of publication bias, and absence of GRADE-based evidence grading. These methodological issues should be considered when interpreting the pooled prevalence estimates.

9. Incidence of sarcopenia

Few studies have assessed the incidence of sarcopenia. In the Korean Frailty and Aging Cohort Study (KFACS), which included 1636 participants (54.4% women; mean age 75.9 ± 3.7 years), sarcopenia developed in 101 men (13.5%) and 104 women (11.7%) over a two-year follow-up period [47]. A meta-analysis by Weng et al. [14], which included eight studies with a total of 8173 patients, reported an overall incidence of 11.5%. The incidence of sarcopenia varies by sex and country and is influenced by factors such as sleep duration [48,49]. Differences in diagnostic criteria and study quality significantly impact the reported incidence rates.

Compared to prevalence studies, research on incidence provides deeper insights into the risk factors for sarcopenia and helps evaluate which interventions may be more effective in reducing or preventing its onset. However, such studies remain limited, representing a significant unmet need. Therefore, Future prospective longitudinal studies are essential to determine whether specific populations, behaviors, environments, or time periods are associated with an increased risk of developing sarcopenia.

10. Risk factors and consequences associated with the prevalence of sarcopenia

Sarcopenia is characterized by the progressive loss of muscle mass and strength and is influenced by various lifestyle factors and health-related factors. Research has revealed a strong association between sarcopenia and the following five key risk factors: physical inactivity, smoking, irregular sleep duration (both short and long), malnutrition and cognitive impairment. These factors not only increase the risk of sarcopenia but also pose a serious threat to the health and well-being of older adults. However, by addressing these modifiable risk factors, older adults can preserve muscle and enhance their overall quality of life in later years.

10.1. Physical activity

Physical activity (PA) can prevent several chronic diseases, such as heart disease, obesity, and hypertension. It also significantly affects muscle strength and mass, making it an essential factor in reducing the risk of sarcopenia. Research has shown a strong association between PA and a lower incidence of sarcopenia. Meta-analysis results consistently indicate that physically inactive older adults have a significantly greater risk of sarcopenia, ranging from 1.73 to 2.8 times higher than that of active individuals [17,50,51].

One large meta-analysis involving 40,007 participants with a mean age of 71.7 (SD = 4.9) years revealed that PA significantly reduced the likelihood of sarcopenia (OR = 0.45, 95% CI: 0.37–0.55) [51]. Another meta-analysis reported an increased risk of sarcopenia among physically inactive individuals (OR = 1.73, 95% CI: 1.48–2.01), indicating that physical inactivity is a key behavioral risk factor for sarcopenia in community-dwelling older adults.

Maintaining regular PA is essential for overall health and well-being. Among various types of PA, resistance training has been particularly effective in preserving muscle mass and preventing sarcopenia [17,51]. Moreover, studies suggest that physical inactivity not only contributes to sarcopenia but is also linked to cognitive decline. Cognitive impairment usually leads to long bed rest times or a sedentary lifestyle and inadequate dietary intake, which could contribute to sarcopenia [52,53].

Given these findings, promoting regular physical activity should be a key strategy in public health efforts to prevent sarcopenia among older adults, along with routine screening for early detection [50].

10.2. Smoking

Smoking is a well-known risk factor for various chronic diseases, and emerging evidence suggests that it may also contribute to the development of sarcopenia. A meta-analysis of 29 studies revealed that smoking was significantly associated with an increased risk of sarcopenia (OR = 1.20, 95% CI: 1.10–1.21) [17]. Similarly, another meta-analysis of 12 studies (22,515 participants) reported an OR of 1.12 (95% CI: 1.03–1.21) [54], reinforcing the link between smoking and sarcopenia. However, high heterogeneity among studies remains a challenge. A smaller study, the São Paulo Aging & Health Study (SPAH), revealed a significantly high OR for sarcopenia in smoking males in the community (OR = 4.62; 95% CI 2.42–8.80), but its small sample size limits its impact on the overall estimate [55].

Although existing evidence suggests a potential link between smoking and sarcopenia, the certainty of evidence is rated as very low according to the GRADE approach. This is primarily due to the observational study design, high heterogeneity in results, and inconsistent definitions of smoking exposure. Most studies relied on self-reported smoking status without standardized measures such as pack-years, reducing the reliability of exposure classification. Furthermore, many studies were not specifically designed to evaluate the association between smoking and sarcopenia, and differences in population characteristics and diagnostic criteria limit generalizability. Given these limitations, a clear causal relationship cannot be established, and higher-quality prospective studies are warranted.

Evidence on whether smoking cessation can reduce the risk of sarcopenia remains limited. A cross-sectional study by Nogami et al. [56] found that among former smokers, those who had quit smoking for ≥ 20 years had significantly higher appendicular skeletal muscle (ASM) index and handgrip strength (HGS) compared to those who had quit for < 10 years. The duration of smoking cessation was positively associated with both ASM index and HGS. Similarly, a retrospective cohort study by Zheng et al. [57] reported that current smokers had a higher risk of sarcopenia, particularly those with a longer smoking history. Former smokers had a significantly lower risk of sarcopenia than current smokers (HR: 0.67, 95% CI: 0.47–0.97), and those who had quit smoking for more than four years showed an even greater reduction in risk (HR: 0.43, 95% CI: 0.24–0.78). Although the GRADE level of evidence remains low, these findings support the notion that promoting smoking cessation may be a feasible strategy to reduce the risk and burden of sarcopenia among smokers.

10.3. Short and long sleep durations

Both short (< 6 h) and long (≥ 8 h) sleep durations have been associated with an increased risk of sarcopenia. Inadequate sleep may contribute to muscle loss through increased inflammation, hormonal dysregulation, and reduced physical activity levels [17,58].

A meta-analysis including 18 studies with 82,359 participants aged between 35 and 85 years revealed a significant association between sleep duration and sarcopenia, particularly among older adults. Most studies have been conducted in Asia, specifically in China, Korea, and Japan. Individuals sleeping less than 6 h per night had a 3.32-fold greater risk of sarcopenia (OR = 3.32, 95% CI: 1.86–5.93), whereas those sleeping more than 8 h had a 2.30-fold greater risk (OR = 2.30, 95% CI: 1.37–3.86) [17]. A U-shaped relationship between sleep duration and sarcopenia was observed, suggesting that insufficient and excessive sleep are detrimental to older adults’ health [17,58]. A subgroup analysis from the second study examined sex differences and revealed that both short and long sleep durations negatively impacted women, whereas men were primarily affected by prolonged sleep [58].

Maintaining an appropriate sleep duration may help reduce the risk of sarcopenia, but the certainty of evidence remains low according to the GRADE framework. This is mainly due to the cross-sectional nature of all included studies, which limits causal interpretation. The small sample of studies, along with moderate to high heterogeneity and unmeasured confounders (such as physical activity or nutritional status), further weakens the strength of the conclusions [58,59]. The U-shaped trend supports biological plausibility, but it remains unclear whether adjusting sleep habits can effectively prevent or reverse muscle decline. Future research with stronger study designs, such as prospective cohorts or randomized trials, is needed to clarify the impact of sleep patterns on muscle health.

A lack of sufficient sleep may lead to elevated cortisol levels, contributing to muscle loss. Sleep plays a critical role in the body's repair processes, including protein synthesis, tissue regeneration, muscle recovery, and hormone regulation. Sleep deprivation can impair these functions, leading to insulin resistance, suppressed protein synthesis, and increased muscle breakdown. Additionally, short sleep duration has been associated with chronic low-grade inflammation and unhealthy lifestyles, such as smoking, excessive alcohol consumption, and reduced physical activity. Conversely, excessive sleep may cause daytime fatigue and fragmented sleep patterns, which are also linked to inflammation and elevated cortisol levels [60].

10.4. Malnutrition

Malnutrition results from a lack of nutrients such as protein, vitamin, and mineral intake and causes body composition changes, including decreased muscle mass. Poor nutritional status is closely associated with sarcopenia. An observational study by Calcaterra et al. recruited 809 older adults aged above 65 years and reported that a Mini Nutritional Assessment (MNA) score below 24, which indicates a risk of malnutrition, was significantly correlated with almost all definitions of sarcopenia on the basis of reduced muscle mass, except the Foundation for the National Institutes of Health (FNIH) criteria. Furthermore, individuals in the lowest quartile of lean mass had a significantly greater risk of malnutrition than those in the highest quartile did (OR = 9.55) [61].

One meta-analysis conducted by Gao et al. analyzing ten studies also supported this association, and the results revealed that older adults with malnutrition or who were at risk of malnutrition had an almost 3-fold increased risk of developing sarcopenia (OR: 2.99, 95% CI: 2.40–3.72) [17].

Current evidence suggests a significant association between malnutrition and sarcopenia; however, the quality of evidence remains low according to the GRADE framework. This is mainly because most of the included studies were cross-sectional in nature, which limits the ability to infer causal relationships. Furthermore, the presence of heterogeneity among studies and the lack of temporal sequence further undermine the strength of evidence. High-quality prospective studies are needed to clarify whether improving nutritional status can effectively reduce the risk or progression of sarcopenia.

According to previous research, aging and frailty are significant contributors to malnutrition [62,63]. Older frail adults with malnutrition often experience weight loss, insufficient protein intake, and muscle weakness. Individuals with malnutrition may experience reduced energy levels, leading to decreased physical activity, further exacerbating muscle loss. Conversely, those with insufficient physical activity may develop sarcopenia even if their nutrient intake is adequate due to a lack of muscle stimulation.

Although nutritional interventions such as protein, creatine, β-Hydroxy β-Methylbutyrate, and vitamin D supplementation have been widely studied for the prevention and treatment of sarcopenia [64], the current GRADE level of evidence remains low to moderate. This is primarily due to methodological limitations, including small sample sizes, short follow-up durations, and inconsistent results across studies. In many trials, the beneficial effects of nutritional supplementation were either modest or only evident when combined with resistance exercise. Furthermore, most study populations consisted of relatively healthy older adults, limiting the generalizability of findings to sarcopenic or malnourished individuals. Given these limitations, routine supplementation is not recommended for all older adults. Instead, public health strategies should prioritize exercise-based interventions, while reserving nutritional support for targeted subgroups identified as high-risk through nutritional screening or clinical assessment. Future research with well-designed, large-scale RCTs in sarcopenic populations is needed to establish clearer causal relationships and refine clinical recommendations. For health promotion programs in the community, health professionals could formulate appropriate exercise and nutritional interventions depending on the specific health requirements of individuals and reinforce that proper nutritional intake is fundamental for sarcopenia prevention, such as maintaining an adequate nutritional status [61].

10.5. Cognitive impairment

Sarcopenia has been linked to an increased risk of cognitive impairment, regardless of the study population, the specific definitions of sarcopenia, or the cognitive impairment criteria. A meta-analysis of six studies revealed that individuals with sarcopenia had a 62% greater risk of cognitive impairment (OR = 1.62, 95% CI: 1.05–2.51), suggesting that sarcopenia is a potential risk factor for cognitive decline [17].

Another meta-analysis conducted in Taiwan, which included 15 studies with 10,410 participants aged over 70, further supported this association. Most of the studies were based on community-dwelling populations. The pooled OR was 2.85 (95% CI: 2.19–3.72) for cognitive impairment among individuals with sarcopenia [52]. In this study, most of the included research indicated a higher prevalence of sarcopenia among individuals with cognitive impairment than among those without. However, the prevalence of sarcopenia was lower in community-dwelling older adults than in hospital-dwelling patients or those with comorbidities such as diabetes or end-stage renal disease (ESRD) and other comorbidities. These differences may be attributed to patients having complex health conditions and being older [17,52,53].

Evidence supports a link between sarcopenia and cognitive impairment, though the GRADE rating indicates low certainty. This is mainly due to the cross-sectional design of all included studies, the risk of residual confounding, and evidence of publication bias. Despite consistent findings across subgroups, the lack of longitudinal data limits conclusions about causality. From a public health perspective, these results highlight the potential value of early sarcopenia screening in older adults as a strategy to identify those at risk of cognitive decline. However, further prospective studies are needed to clarify whether treating sarcopenia can help prevent or slow cognitive impairment.

Emerging evidence suggests a potential link between sarcopenia and cognitive impairment. For example, elevated levels of inflammatory markers such as interleukin-6 (IL-6) and C-reactive protein (CRP) have been associated with skeletal muscle loss, reduced muscle strength, and an increased risk of dementia. Hormonal pathways may also influence the potential mechanisms linking sarcopenia and cognitive impairment. Additionally, lower serum testosterone levels have been linked to decreased muscle mass and strength and are independent predictors of cognitive decline [52].

In terms of muscle strength, physical performance and muscle mass may have several impacts on cognitive impairment. This highlights the need for early recognition and management of sarcopenia as a potential strategy to prevent cognitive decline in older adults. Maintaining muscle strength and function may be important in preserving cognitive health and reducing the burden of dementia-related conditions.

11. Consequences of sarcopenia – falls, fractures and mortality

11.1. Falls and fractures

Sarcopenia is a known risk factor for functional decline and disability in older adults. It is linked to impaired balance, slower gait speed, and reduced mobility, all of which contribute to a higher risk of falls and fractures [[65], [66], [67], [68]]. Previous studies have shown that sarcopenia is strongly associated with an elevated risk of falls and subsequent fractures in older people [9,[67], [68], [69]]. A systematic review and meta-analysis by Yeung et al. showed that sarcopenic individuals had an increased risk of falls (OR 1.89; 95% CI: 1.33–2.68) and fractures (OR 1.71; 95% CI: 1.44–2.03) [68]. These associations remained consistent across study designs, populations, sexes, and regions [68]. In a Chinese cohort of 2000 community-dwelling older men, sarcopenia independently predicted fracture risk even after adjusting for osteoporosis (HR 1.87; 95% CI: 1.26–2.79) [70]. These findings highlight the importance of early detection and intervention to mitigate fall-related injuries in older adults.

11.2. Mortality

Sarcopenia is associated with increased mortality rates [2,66,71,72]. A Japanese study involving 720 community-dwelling older adults revealed that the risk for all-cause mortality significantly increased in men (OR 1.95; 95% CI 1.04–3.67) but not in women (OR 0.77; 95% CI 0.29–2.22) with sarcopenia [71]. Beaudart et al. [64] reported that subjects with sarcopenia have an approximately 4-fold greater mortality risk than nonsarcopenic subjects do (pooled OR of 3.60, 95% CI 2.96–4.37), especially in people above the age of 79 years. Although the impacts of sarcopenia on mortality vary among patient populations, a pooled analysis of the results from 109 studies concluded that sarcopenia is associated with a poor survival rate and/or a high risk of all-cause mortality [2]. The highest risk was observed in patients who underwent emergency laparotomy (OR 3.50, 95% CI 2.54–4.81), whereas the lowest risk was observed in those who underwent radical cystectomy (HR 1.41, 95% CI 1.22–1.62). Lung cancer patients with sarcopenia had the highest risk of poor survival (OR 3.07, 95% CI 2.45–3.85). Esophageal cancer patients had the lowest risk (HR 1.12, 95% CI 1.04–1.20) [2]. Nevertheless, some studies have indicated that muscle strength has a greater impact on mortality rates in older adults than muscle mass does [73,74]. This finding is consistent with a national study comprising 4449 U S. adults aged 50 years and older, which revealed that low muscle strength was significantly associated with a higher all-cause mortality rate (OR 2.34; 95% CI 1.71–3.20) regardless of muscle mass [66]. All of these studies consistently demonstrate that sarcopenia is significantly associated with increased mortality among older adults and may serve as an important predictor of mortality.

12. Conclusions

Reported sarcopenia prevalence varies widely across populations due to intrinsic factors (eg, age, comorbidities), environmental conditions (eg, urban–rural differences), and inconsistent diagnostic criteria. Definitions such as AWGS 2014/2019, EWGSOP1/2, IWGS, and FNIH yield differing prevalence estimates, limiting comparability. Broader criteria like AWGS 2019 may improve early detection but risk overestimating disease burden and affecting healthcare planning.

These findings have important implications for clinical and public health practice. Clinicians should consider integrating sarcopenia screening into routine care for older adults, particularly in high-risk settings or among individuals with diabetes, cardiovascular disease, or cognitive impairment. Evidence-based interventions such as resistance training, protein supplementation, smoking cessation, and sleep hygiene promotion should be prioritized. At the public health level, targeted campaigns and programs tailored to at-risk groups—such as nursing home residents and rural populations—are warranted to reduce disease burden and promote healthy aging.

However, the certainty of evidence for most risk factors remains low to moderate under GRADE, mainly due to reliance on observational studies, inconsistent definitions, and limited longitudinal data. High-quality prospective studies and RCTs are needed to clarify causality, guide clinical practice, and support prevention efforts. A global consensus on diagnostic criteria is essential for consistent surveillance and policy planning.

CRediT author statement

Tzu-Hao Tseng: Validation, Writing- Original draft. Shau-Huai Fu: Validation, Writing- Original draft. Ning-Huei Sie: Validation, Writing- Original draft. Yi-Chien Lu: Validation, Writing- Original draft. Chen-Yu Wang: Validation, Visualization, Writing- Reviewing and editing. Chih-Hsing Wu: Validation, Visualization, Writing- Reviewing and editing.

Conflicts of interest

The authors declare no competing interests.