Skeletal muscle comprises about 40% of the body weight and is important for performing daily physical activity (Sherwood, 2008). A good muscle strength and flexibility may help to reduce the risk of injury and fall which could lead to physical disabilities, poor quality of life and mortality. Muscle function is also related with muscle mass (Reed et al., 1991). Muscle receives about 15% of cardiac output at rest, and the need for blood supply increases during exercise (Sherwood, 2008). Thus, a good blood supply is important for muscle to function efficiently. The role of vascular function in the development of muscle mass was addressed in a recent study by Jeon et al. (2021). It was observed that poor vascular function may impair oxygen and nutrient delivery to the muscles, hence causing impairment of muscle protein synthesis and alteration in mitochondrial function (Groen et al., 2014; Jeon et al., 2021).

In human research, one of the non-invasive methods to assess vascular function is by measuring arterial stiffness (AS). AS is described as an elastic resistance to deformation that involves complex interactions between the extracellular matrix components such as elastin, collagen, glycoproteins and proteoglycans, and vascular smooth muscle cells in the arterial wall (Safar et al., 2003). AS is accelerated by aging and classic CVD risk factor such as atherosclerosis, thus reducing the normal arterial compliance. Stiffness of the aorta is frequently studied and the gold standard measurement of aortic stiffness is carotid-femoral pulse wave velocity (cfPWV), which measures the speed of the pressure wave that travels from the aorta to the femoral artery (Laurent et al., 2006). Another marker of AS is brachial-ankle PWV (baPWV) which indicates central and peripheral arterial stiffness (Katakami et al., 2014). PWV was independently associated with cardiovascular events as highlighted by the European Society of Cardiology/European Society of Hypertension Guidelines (Mancia et al., 2013).

Previous studies have investigated the association between PWV and muscle indices (Watson et al., 2011; van Dijk et al., 2015; Lima-Junior et al., 2019). A prospective study showed that increased PWV was associated with poor muscular function in people with altered blood flow (Watson et al., 2011). It was also revealed that reduction in muscle flexibility and strength was an indicator of increased arterial stiffness (AS) (Yamamoto et al., 2009; Fahs et al., 2010). However, several studies showed no significant association (van Dijk et al., 2015; Lima-Junior et al., 2019). This might be contributed by different methods of measurements and low sample sizes. Hence, the objective of this study was to investigate the relationship between AS and muscle indices by systematically reviewing the relevant studies involving healthy adults and those with established CVD or CVD risk factors, which were known to affect vascular function.

From the three databases, a total of 2295 articles were obtained. These included 561 articles from PubMed, 1089 articles from Scopus, and 645 articles from Web of Science. The articles were published between the years 1971 and June 2021. A total of 56 articles written in languages other than English were omitted. After reading the titles or abstracts, 2204 articles were further omitted. The remaining 35 articles were obtained and reviewed thoroughly by fully reading the whole text. Out of these 35 articles, only 17 articles fulfilled the selection criteria, hence included in this review. The process of article selection is shown in Figure 1.

Table 1 summarized the two studies related to the association between muscle strength and AS in healthy subjects, while Table 2 summarized the seven studies related to the association between muscle strength and AS in subjects with established CVD and CVD risk factors. Table 3 summarized 11 studies related to the association between muscle mass and AS in subjects with CVD risk factors. There were no studies related to the association between muscle mass and AS in healthy subjects. The details of the parameters measured in each study were included in Tables 4, 5, respectively.

For the association between muscle strength and AS in healthy subjects (Table 1), all studies found that muscle strength was inversely correlated with arterial stiffness as measured by cfPWV (Fahs et al., 2010; Gonzales, 2013). A cross-sectional study showed that increased muscle strength was associated with lower prevalence of high cfPWV in young healthy men (odds ratio = 0.14, 95% confidence interval = 0.02–0.92, P = 0.04) (Fahs et al., 2010). Another study by Gonzales (2013) demonstrated that cfPWV was associated with the gait distance in healthy, older subjects (r = −0.51; P < 0.05) (Gonzales, 2013).

In subjects with CVD or CVD risk factors (Table 2), five out of seven studies found significant associations (Watson et al., 2011; Ohara et al., 2015; Yamanashi et al., 2018; Rong et al., 2020; Zhang et al., 2021). For example, the study by Rong et al. (2020) found that muscle strength as measured by handgrip dynamometer was negatively associated with baPWV in elderly subjects (Rong et al., 2020). Whereas the study by Ohara et al. (2015) found that muscle strength as measured by handgrip dynamometer was negatively associated with baPWV in middle-aged and older subjects (Ohara et al., 2015). A prospective study found a significant association between aortic PWV and gait speed in peripheral arterial disease (PAD) patients (OR = −0.028, CI (−0.047, −0.010), P < 0.01), but the association was not significant in total cohort population (Watson et al., 2011). Similarly, the study by Yamanashi et al. (2018) found an inverse association between handgrip strength and PWV in non-hypertensive adults [men (β = −0.97; P = 0.001), women (β = −0.44; P = 0.020)], but not in the hypertensive group and the total cohort (Yamanashi et al., 2018). Another two studies did not observe any significant association between AS and muscle strength (van Dijk et al., 2015; Lima-Junior et al., 2019).

As for the association between muscle mass and PWV, all 11 relevant studies involved subjects with CVD or CVD risk factors. Most of the studies were cross-sectional studies. All the eleven studies found a negative association between muscle mass and PWV (Ochi et al., 2010; Kim et al., 2011; Ohara et al., 2015; Tanaka et al., 2016; Zhang et al., 2019, 2021; Rong et al., 2020; Yang et al., 2020; Yoon et al., 2020; Fischer et al., 2021; Inomoto et al., 2021). Five studies that measured the appendicular skeletal muscle index (ASMI) as the muscle mass marker showed a negative association between ASMI and baPWV (Zhang et al., 2019, 2021; Rong et al., 2020; Yang et al., 2020; Fischer et al., 2021). For example, the study by Rong et al. (2020) found that ASMI was negatively associated with baPWV in elderly Chinese after adjustment of potential confounders [(β = −32.752; P < 0.0001 (men); β = −39.783; P < 0.0001) (women)] (Rong et al., 2020).

Yang et al. (2020) found that low muscle mass was associated with increased risk of AS in Chinese nationals aged 45 years old and older (men, P ≤ 0.0001, β = −0.208, women, P ≤ 0.0001, β = −0.245) (Yang et al., 2020). In Japan, subjects older than 65 years old showed a negative association between baPWV and ASMI (β = −0.27; P < 0.001) (Zhang et al., 2021). A study on post-menopausal women also revealed similar finding whereby ASMI and arm leg mass (armLM) were negatively associated with baPWV with β = −0.23 (P = 0.043) and β = −0.23 (P = 0.045), respectively (Fischer et al., 2021). A cross-sectional study by Kim et al. (2011) observed that appendicular skeletal muscle mass (ASM) was not associated with baPWV. However, there was a significant association between ASM and visceral fat area ratio (MFR) (β = −59.505, P = 0.002) (Kim et al., 2011).

Relative skeletal muscle mass (calculated using the formula ASM/height²) had a negative association with baPWV in Japanese postmenopausal women with type 2 diabetes mellitus (T2DM) (Tanaka et al., 2016). Ohara et al. (2015) also found that skeletal muscle mass was inversely associated with baPWV in male (β = −0.18; P = 0.0002) and female subjects (β = −0.11; P = 0.0017) (Ohara et al., 2015). Skeletal muscle index is another measurement of muscle mass used in two studies. South Korean men and women showed a negative association between their skeletal muscle index and baPWV [(β = −0.188; P < 0.001 (men); β = −0.136; P = 0.011) (women)], whereas working men with low muscle mass in Japan (aged 35–44 and 45–54 years old) had a higher risk of AS (Yoon et al., 2020; Inomoto et al., 2021).

Arterial compliance represents the capacity of the artery to expand and recoil following heart contraction and relaxation, which permits blood flow from pulsatile and intermittent form to a steadier, laminar flow (Sherwood, 2008). Increased AS give more resistant to the blood flow and higher workload for the left ventricle. This led to increased blood pressure and enhanced atherosclerosis development (Oren et al., 2003; Mitchell et al., 2005).

The main factors contributing to AS are aging and atherosclerosis (Greenland et al., 2010). The artery becomes stiff when the collagen in the arterial wall increased and the elastin tissue decreased (Zieman et al., 2005). Besides structural changes, increase in local vasoconstrictor such as endothelin-1 (ET-1) or reduction in vasodilator such as nitric oxide (NO) may contribute to AS (Bellien et al., 2010; Guo et al., 2018). These modulators are released from vascular endothelial cells and has a significant role in the control of vascular activity (Santos-Parker et al., 2017; Trindade et al., 2017). Poor NO production is a cardinal feature of endothelial dysfunction (ED) (Sun et al., 2020). Several CAD risk factors such as hypertension, dyslipidemia and diabetes mellitus were known to increase AS through underlying ED (Rider et al., 2012; Aminuddin et al., 2020; Ji et al., 2020). Thus, having CAD risk factors would accelerate AS on top of the aging process.

In our review, it was found that in most of the studies, muscle indices had negative association with AS as measured by PWV. This association is evident in both healthy subjects and subjects with CVD or CVD risk factors. However, most of the studies are cross-sectional studies, hence the studies were unable to determine the cause-effect association between muscular functions and AS. There were only two prospective studies that determined the direct relationship between AS and muscle indices (Watson et al., 2011; van Dijk et al., 2015). Watson et al. (2011) showed that in PAD patients, higher PWV was independently associated with slower gait speed, thus suggesting that increased PWV leads to reduction in muscle strength. In contrast, van Dijk et al. (2015) showed that hand-grip strength was not associated with AS after a follow-up duration of 2 years. The author proposed that the lack of an association might be due to the difference between short- and long-term alteration of the arteries. It has been shown that structural adaptations of the artery such as changes in elastin and collagen need a longer time to develop (van Dijk et al., 2015). Another cross-sectional study by Lima-Junior et al. (2019) also showed no significant association between PWV and muscle indices. Small sample size might account for such discrepancy (Lima-Junior et al., 2019).

Regular exercise is an important modality in improving cardiovascular health and endothelial function (Francescomarino et al., 2009; Aminuddin et al., 2011), thus improving AS (Kollet et al., 2021). Exercise also increases muscle strength (Chen et al., 2017; Sanian et al., 2019; Otsuki et al., 2020). Increased muscle strength and reduced AS were inversely related with CVD risk factors such as increased levels of low-density lipoprotein, body fat and inflammation, decreased lean tissue mass and insulin resistance (Fahs et al., 2010; Nishitani et al., 2011; Rider et al., 2012; Farias et al., 2013; Aminuddin et al., 2020; Ji et al., 2020).

In terms of the association between AS and muscle mass, previous studies showed that there were negative association between low muscle mass and AS. There are several mechanisms that can explain such relationship. Firstly, an increase in AS may reduce basal limb blood flow, leading to decreased delivery of nutrients and oxygen to the muscle tissues and lower muscle mass (Suzuki et al., 2001; Abbatecola et al., 2012; Rong et al., 2020). AS is also associated with increased reflected wave, systolic blood pressure and pulse pressure along the arterial system that cause small vessel injury (Safar et al., 2003). Secondly, the muscle mass itself may exert an effect on AS. When there is muscle death due to muscle disuse or aging, maladaptive muscle remodeling may occur if there is impaired removal of the apoptotic cells (Siu et al., 2005; Sciorati et al., 2016). This includes fatty infiltration within the muscles that leads to the release of inflammatory cytokines (Sciorati et al., 2016). Inflammatory cytokines such as tumor necrosis factor-α, interleukin (IL)-1β and IL-6 activate several inflammatory signaling pathways that promote insulin resistance (Chen et al., 2015). Inflammation also causes proteolysis which leads to reduced muscle mass (Goodman, 1991). In addition, reduced muscle mass is also associated with insulin resistance, since skeletal muscle is the major site of glucose utilization (Yamanashi et al., 2018). Insulin resistance has been linked to AS (Ikonomidis et al., 2015), which could be explained by the underlying reduction in NO bioavailability (Sonne et al., 2009), increased endothelin levels and increased proliferation of vascular smooth muscle cells (Trovati and Anfossi, 2002).

Another dynamic that links muscle mass and AS is through increased oxidative stress. In this case, muscle mass may not directly affect AS and vice versa, but rather a distinct complication of a common factor which is oxidative stress. Oxidative stress happens when there is an imbalance between the antioxidant and free radicals in the body that leads to damage to the cellular protein, lipid and nucleic acids (Wu et al., 2013). Oxidative stress is related to sarcopenia (Bellanti et al., 2018) through modulations of transcription factors and inflammatory mediators such as nuclear factor-κB, Forkhead box (FOXO) and mitogen-activated protein kinase that lead to muscle apoptosis and reduced protein synthesis. Besides, oxidative stress causes myocardial DNA damage and dysfunction which later leads to muscle apoptosis and sarcopenia (Meng and Yu, 2010). Additionally, oxidative stress is related to the formation of AS through reduction in NO (Zhao et al., 2011; Förstermann et al., 2017; Guzik and Touyz, 2017). The proposed, complex mechanisms that explain the association between AS and muscle indices are summarized in Figure 2.

The strength of this study is that we focused on the established markers of PWV which are cfPWV and baPWV. However, there are certain limitations of this study that include (1) the cross-sectional design of the selected studies, in which cause-effect associations between muscle indices and arterial stiffness could not be determined, and (2) the absence of studies related to AS and muscle flexibility, which is one of important markers for muscular functions. On the other hand, we also excluded several studies that reported significant associations between AS and muscle indices that were derived from simple correlations without adjustment for confounders (Yamamoto et al., 2009; Komatsu et al., 2017; Logan et al., 2018). Thus, future studies should be conducted with a detail analysis adjusted for the covariates to address such associations.

There is an inverse association between muscle indices and AS in healthy subjects and subjects with established CVD and CVD risk factors. However, most of the studies reviewed are cross-sectional studies, hence no causal relationship or explanatory capacity between muscle indices and AS could be established. Therefore, more prospective studies should be conducted in the future to determine the interaction between muscle indices and AS.

BC and NJ performed the screening of articles. AA, MN, NM, and LZ drafted the manuscript. AA and AU finalized the manuscript. NC and NS contributed to the revision and editing of the manuscript. All authors read and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.