Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T03:48:42.383Z Has data issue: false hasContentIssue false

Relationship between sarcopenia and cardiovascular disease risk among Taiwanese older adults

Published online by Cambridge University Press:  23 March 2022

Yuan-Yuei Chen
Affiliation:
Department of Pathology, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Department of Pathology, Tri-Service General Hospital Songshan Branch and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China
Wei-Liang Chen
Affiliation:
Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, 114Taipei, Taiwan, Republic of China Department of Biochemistry, National Defense Medical Center, TaipeiTaiwan, Republic of China
Tao-Chun Peng
Affiliation:
Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, 114Taipei, Taiwan, Republic of China
Fang-Yih Liaw
Affiliation:
Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, 114Taipei, Taiwan, Republic of China
Yuan-Ping Chao
Affiliation:
Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, 114Taipei, Taiwan, Republic of China
Tung-Wei Kao*
Affiliation:
Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital and School of Medicine, National Defense Medical Center, 114Taipei, Taiwan, Republic of China
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective:

Increasing evidence supports sarcopenia as an important parameter for predicting cardiometabolic risks. The objective of this study was to investigate the relationship between muscle mass, muscle strength, and physical performance, and cardiovascular risk among older community-dwelling adults.

Design:

The associations between dynapenia, sarcopenia, and Framingham risk score (FRS) were estimated by multivariate regression models.

Setting:

Muscle mass is estimated by skeletal muscle mass index using a bioelectrical impedance analysis. Muscle strength is measured by handgrip strength using an analogue isometric dynamometer. Physical performance is measured by gait speed using a 6-m walking distance. Dynapenia was defined as low muscle strength and/or slow gait speed presents with normal muscle mass. The diagnosis of presarcopenia and sarcopenia was based on criteria proposed by the Asian Working Group for Sarcopenia in 2014. The FRS was used for evaluating 10-year coronary heart disease (CHD) risk.

Participants:

Adults aged 65 years and older who attended health examinations from 2015 to 2017 were recruited.

Results:

There were totally 709 subjects enrolled in this study. Dynapenic men (n 47) had 17·70 ± 5·08 % FRS and sarcopenic women (n 74) had 7·74 ± 6·06 % FRS. Participants with presarcopenia had the lowest FRS (men: 15·41 ± 5·35 %; women: 5·25 ± 3·70 %). Men with dynapenia had higher FRS than the presarcopenia group with odds ratio (OR) of 2·52 (95 % confidence interval (CI): 1·03, 6·14). Women with sarcopenia had significantly higher FRS than the presarcopenia group with OR of 2·81 (95 % CI: 1·09, 7·27).

Conclusion:

Older dynapenic men and older sarcopenic women had higher risks of 10-year CHD. Presarcopenic older adults had the lowest CHD risk in both genders.

Type
Research Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

Sarcopenia is a multifactorial condition which is characterised by the decline of muscle mass with reduced muscle strength and poor physical performance(Reference Morley, Baumgartner and Roubenoff1). European Working Group on Sarcopenia in Older People (EWGSOP) demonstrated an operational definition and diagnostic strategy for sarcopenia in 2010 that had become the most widely used consensus in the world(Reference Cruz-Jentoft, Bahat and Bauer2). To reflect the severity in clinical practice, sarcopenia is suggested to be classified into conceptual staging as ‘presarcopenia’, ‘sarcopenia’ and ‘severe sarcopenia’. In Taiwan, the reported prevalence from several community studies was about 5·4–10·8 % in men and 2·5–7·8 % in women by using the EWGSOP definition(Reference Lee, Liu and Peng3,Reference Wu, Lin and Hsiung4) . Sarcopenia is associated with the risk of morbidity and disability in the elderly population, including loss of independence, poor quality of life and even death(Reference Cruz-Jentoft, Bahat and Bauer2,Reference Janssen, Heymsfield and Ross5) . Numerous studies have reported that sarcopenia is a potential predictor of cardiometabolic health problems such as insulin resistance, dyslipidemia and CVD(Reference Cleasby, Jamieson and Atherton6Reference Han, Yu and Ma8). Dynapenia is defined as the age-related muscle strength decline that is not caused by neurologic or muscular diseases(Reference Clark and Manini9). The consequences of dynapenia are including increased risks of physical disability, poor physical performance and even death. Several evidences have reported a direct relationship between low muscle strength, metabolic syndrome and insulin resistance(Reference Aubertin-Leheudre, Anton and Beavers10). In a cross-sectional study, dynapenia is proposed to be associated with increased risks of CVD, which may lead to incident cardiovascular events(Reference Alves, Bruch-Bertani and Galinatti11).

CVD is the leading cause of death in the world, and the prevalence is increasing in Taiwan(Reference Wu, Juang and Chiang12,Reference Chiu, Mau and Chang13) . Numerous studies have reported the effects of muscle quality and function on CVD risk. Low muscle mass is associated with coronary calcification and considered an independent risk of coronary heart disease (CHD)(Reference Ko, Chang and Jung14). In a prospective cohort study, muscle strength is suggested to be more important for CVD risk than muscle mass(Reference Stephen and Janssen15). Furthermore, sarcopenia is reported to be associated with increased CVD risk and may be an early predictor of its susceptibility in both elderly and middle-aged adults in Korea(Reference Byeon, Kang and Kang16,Reference Kim, Cho and Park17) . Among several different scores in estimating CVD risk, the Framingham risk score (FRS) is a simplified and gender-specific clinical algorithm for the assessment of the 10-year CVD risk of an individual(Reference Wilson, D’Agostino and Levy18). Numerous studies have supported that the predictive values of the FRS for CVD events were varied in asymptomatic men and women(Reference Brindle, Beswick and Fahey19); in addition, the cut-off values to define different degree of dynapenia and sarcopenia in men and women were different. For these reasons, we hypothesised that gender is a potential clinical factor in the relation of muscle decline and CVD risks. The purpose of our study was to investigate the gender-specific difference in the relationship between different degree of sarcopenia and CVD risk in the Taiwanese community-dwelling elderly population.

Method

Study population

In this cross-sectional study, we included participants who attended health check-up at Tri-Service General Hospital (TSGH) in Taiwan during the period of 2015–2017. All participants were asked to complete questionnaires, measurements of muscle mass and muscle strength, and laboratory examinations. The exclusion criteria were that participants who were younger than 65 years and missing data of self-reported questionnaires or examinations. All analytic procedures were conducted by well-trained medical staff at the health check-up centre following the guidelines of TSGH. To access data from the medical examination, participants were requested to complete written informed consent. The study design was approved by the Institutional Review Boards of TSGH, Taiwan.

Definition and diagnosis of robust, sarcopenia, presarcopenia and dynapenia

According to the guidelines proposed by the Asian Working Group for Sarcopenia (AWGS) in 2014(Reference Chen, Liu and Woo20), the cut-off values of skeletal muscle mass index (SMI) is 7·0 kg/m2 for men and 5·7 kg/m2 for women evaluated by using bioelectric impedance analysis (BIA, InBody720, Biospace). The definition of low handgrip strength is below 26 kg for men and lower than 18 kg for women measured by using an analogue isometric dynamometer. The indication of low gait speed is slower than 0·8 m/s which is derived from calculating the 6-m walking distance divided by time in seconds. Robust was defined as having normal SMI, normal handgrip strength and normal gait speed. Participants with normal SMI but had low handgrip strength and/or low gait speed were categorised as dynapenia. Presarcopenia was defined as low SMI with normal handgrip strength and normal gait speed; sarcopenia was indicated by low SMI with either low handgrip strength or low gait speed or both.

Ten-year CHD Risk Scores

Several scoring systems exist to help clinicians evaluate the 10-year CHD risk score. The FRS, calculated the risk at 10 years in percent, is the most widely used globally and is applied in the present study. D’Agostino et al. outlined the Framingham algorithm to calculate the risk score based on age, gender, high-density lipoprotein cholesterol (HDL-C), total cholesterol, systolic blood pressure, and history of smoking and diabetes mellitus(Reference D’Agostino, Vasan and Pencina21). Participants were classified as never, current and former smokers by self-reported questionnaire. Diabetes mellitus was determined as self-reported medical diagnosis and/or using any hypoglycemic medication. Systolic blood pressure was estimated by a standard sphygmomanometer when the participants were seated. Serum total cholesterol and HDL-C were collected from participants after fasting for at least 8 h. The higher FRS in male and female individuals is 20 % and 10 %, respectively.

Variable assessment

Body mass index (BMI) was estimated that the weight (kg) divided by the square of height (m) (kg/m2). Waist circumference was estimated in the horizontal plane between the iliac crest and the lowest rib. Body fat was measured by BIA. History of alcohol drinking, hypertension, stroke and coronary artery disease was obtained from participants’ self-reported questionnaires.

Statistical analysis

All statistical estimations were calculated using the Statistical Package for the Social Sciences, version 22.0 (SPSS Inc.) for Windows. Continuous variables were presented as means and standard deviation (sd), while categorical variables were presented as frequencies and percentages (%). The differences between the gender groups in terms of demographic information and laboratory data were examined by ANOVA for continuous variables and chi-square test for categorical parameters. Statistical significance was defined as a two-sided P-value of ≤ 0·05. The association between different degrees of sarcopenia and higher FRS was analysed using logistic regression with an unadjusted and adjusted model for all pertinent variables in the study.

Results

Characteristics of the study population

The characteristic information of male and female population was represented in Table 1 and Table 2. A total of 305 men and 404 women were included in the final analysis of the study. The mean age of participants in robust, dynapenia, presarcopenia and sarcopenia group was 72·1 ± 6·6, 77·6 ± 8·8, 76·0 ± 8·5 and 83·9 ± 5·9 years in men and 70·2 ± 5·6, 73·6 ± 6·6, 70·9 ± 5·2 and 75·1 ± 7·1 years in women. Men with sarcopenia had significantly lower SMI, and handgrip strength, and higher body fat and fat to muscle ratio than other groups. Participants in men with dynapenia had significantly lower gait speed, total cholesterol, and higher BMI and waist circumference than other groups. In terms of women, participants with sarcopenia had significantly lower systolic blood pressure, SMI, and grip strength and higher FRS than other groups. Dynapenic female participants had significantly lower gait speed, total cholesterol and HDL-C and higher BMI, waist circumference , systolic blood pressure, SMI, body fat and fat to muscle ratio than other groups.

Table 1 Characteristics of male participants

BP, blood pressure; BMI, body mass index; HDL, high-density lipoprotein; SMI, skeletal muscle mass index; FRS, Framingham risk scores.

* Values in the continuous variables were expressed as mean and standard deviation unless otherwise specified.

Values in the categorical variables were expressed as number (percent).

Table 2 Characteristics of female participants

BP, blood pressure; BMI, body mass index; HDL, high-density lipoprotein; SMI, skeletal muscle mass index; FRS, Framingham risk scores.

* Values in the continuous variables were expressed as mean and standard deviation unless otherwise specified.

Values in the categorical variables were expressed as number (percent).

Association between different sarcopenia degrees and cardiovascular risk

Table 3 displayed the association between different sarcopenia degrees and the odds ratio (OR) of higher FRS in men and women. After adjustment of pertinent variables, men with dynapenia had significantly higher FRS than presarcopenia group with OR of 2·52 (95 % confidence interval (CI): 1·03, 6·14). However, no significant finding was found in participants with sarcopenia. In terms of women, those with sarcopenia had significantly higher FRS than presarcopenia group with OR of 2·81 (95 % CI: 1·09, 7·27) after adjusting variables.

Table 3 Comparison of Framingham risk scores among four groups of participants in both genders

CI, confidence interval; OR, odds ratio.

* Adjusted covariates: alcohol consumption and history of stroke.

Discussion

Several researchers propose that the prevalence of sarcopenia is related to CVD risks in elderly adults. Numerous evidence have reported that patients with low handgrip strength are at risk of CVD mortality(Reference Zhang, Jiao and Zhu22). In a cross-sectional study, physical disability is suggested an important risk factor for CVD mortality in elderly adults(Reference Martinez-Gomez, Guallar-Castillon and Higueras-Fresnillo23). Recently, higher levels of skeletal muscle mass was proposed to be linked to lower 10-year CVD risk(Reference Tyrovolas, Panagiotakos and Georgousopoulou24). In comparison with previous studies, we categorised participants into dynapenia, presarcopenia and sarcopenia groups based on the criteria rather than individual components. We demonstrated a gender difference that older dynapenic men and older sarcopenic women had higher risks of 10-year CHD, respectively. To the best of our knowledge, our study was the first to compare the relationships between different sarcopenia degrees and CVD risk in an elderly population.

Sarcopenia is considered as a precipitating factor of insulin resistance and glucose metabolism in an elderly population(Reference Srikanthan, Hevener and Karlamangla25). Sarcopenic obesity is also suggested to have a positive association with metabolic syndrome in adults(Reference Rubio-Ruiz, Guarner-Lans and Perez-Torres26,Reference Zhang, Lin and Gao27) . Kim et al. demonstrated that sarcopenic obesity was significantly associated with increased CVD risks such as glucose intolerance and metabolic syndrome in Korean adults(Reference Kim, Cho and Park17). Smoking was considered an important risk factor of sarcopenia, especially in men(Reference Jo, Linton and Choi28). The different anthropometric index also had gender difference in the effect on CVD risk(Reference Kim, Choi and Lim29). Accordingly, loss of skeletal muscle mass is indicated to have a relation with several health outcomes. In a cross-sectional study that included 3042 adults, Tyrovolas et al. reported that decline of skeletal muscle mass was associated with an increased 10-year cardiovascular incidence in those older than 45 years of age(Reference Tyrovolas, Panagiotakos and Georgousopoulou24). The muscle cells exert an endocrine function by secreting myokines with beneficial effects on the cardiovascular system(Reference Pedersen and Febbraio30). Loss of skeletal muscle mass and impaired endocrine function could lead to poor CVD outcomes(Reference Kang, Park and Choi31); however, the detailed mechanisms should be further investigated. In addition, skeletal muscle mass is known for its major role in the glucose metabolism pathway in the human body(Reference Pedersen and Febbraio32). Impaired glucose metabolism and altered insulin resistance caused by decreased skeletal muscle mass have an adverse impact on CVD events(Reference Srikanthan and Karlamangla33,Reference Kjaer, Kiens and Hargreaves34) .

Epidemiological data for the prevalence of sarcopenia and dynapenia between older men and women are conflicting(Reference Landi, Liperoti and Fusco35,Reference Patel, Syddall and Jameson36) . Several studies demonstrate that men have greater muscle loss than women in older population(Reference Payette, Roubenoff and Jacques37). Fried et al. proposed that women were more likely to develop frailty and sarcopenia because women had lower muscle mass and muscle strength than men at the same age(Reference Fried, Tangen and Walston38). In the present study, we demonstrated that older women with sarcopenia had a higher CVD risk than relative healthy participants.

Testosterone levels are suggested to be associated with decreased muscle quality(Reference Srinivas-Shankar, Roberts and Connolly39). Testosterone supplementation stimulates muscle protein synthesis and inhibits muscle protein degradation leading to the contribution of muscle fibre hypertrophy(Reference Herbst and Bhasin40). Low testosterone level is considered an indicator of sarcopenia and may lead to the development of frailty in older men(Reference Bhasin41). In a population-based study that included 927 Taiwanese, Lee et al. reported that handgrip strength was related to FRS in men but not in women(Reference Lee, Peng and Chiou42). It is consistent with our finding that male participants with dynapenia have significantly higher FRS than females. However, the underlying mechanisms for relationships between decline of muscle mass, muscle strength and risk of CVD have not been clearly recognised, and it deserved to be explored in future studies.

The strength of this study deserved to be addressed. Previous researches defined muscle mass and muscle function by variety of indicators. We defined the cut-off point of low muscle mass, low muscle strength and low physical performance according to the consensus of AWGS. Instead of estimating the correlation between single muscle health indicator and cardiovascular outcome, we categorised these muscle parameters into dynapenia, presarcopenia and sarcopenia to adapt the current critical issue of geriatric syndrome in clinical practice. From this study, it is given a hint for medical providers to take caution on changes of muscle quantity and quality among old people in clinical practice. In addition, public health interventions are required for developing effective strategies to promote prevention and treatment of low muscle mass and low muscle function in general practice.

There are some limitations that should be noted in the present study. The cross-sectional study design limited us to identify the causal relationships between different sarcopenia degrees and 10-year CVD risk. A long-term observation period should be considered in future studies. Second, we included Taiwanese participants in this study. Extrapolation of our findings to other ethnicities may be limited. Third, the CVD risk estimated by the FRS was not an actual CVD outcome. The Framingham risk model was originally applied for Western populations. Lastly, it may not reflect the different genetic, environmental and social factors in the Taiwanese population.

Conclusion

In summary, we found that elderly men with dynapenia and elderly women with sarcopenia were independently associated with increased FRS scores. From this study, we recognise that old people with low muscle mass or low muscle function have an increased risk of CVD. Further studies on the causal effect of sarcopenia on CVD risk were required, which might not only expand understanding of the mechanism in our study but also establish new prevention strategies of muscle quantity and quality for old people in clinical practice.

Acknowledgements

Acknowledgements: None. Financial support: This study was supported by grant MOST 104-2314-B-016-011-MY3 from the Ministry of Science and Technology (MOST) in Taiwan. Conflict of interest: All authors declare no conflict of interest. Authorship: Y-Y.C. contributed to the design of the study, was responsible for the management and retrieval of data, contributed to initial data analysis and interpretation, and drafted the initial manuscript. Y-Y.C., W-L.C., T-C.P., F-Y.L., Y-P.C. and T-W.K. decided upon the data collection methods. Y-Y.C. and T-W.K. were also responsible for the data analysis decisions. T-W.K. conceptualised and designed the study, supervised all aspects of the study, critically reviewed and revised the manuscript, and approved the final manuscript as submitted. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving research study participants were approved by the guidelines of Tri-Service General Hospital. Written informed consent was obtained from all patients before enrolment, and approval for the study was granted by the Institutional Review Board of Tri-Service General Hospital, Taiwan.

References

Morley, JE, Baumgartner, RN, Roubenoff, R et al. (2001) Sarcopenia. J Lab Clin Med 137, 231243.10.1067/mlc.2001.113504CrossRefGoogle ScholarPubMed
Cruz-Jentoft, AJ, Bahat, G, Bauer, J et al. (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48, 1631.10.1093/ageing/afy169CrossRefGoogle ScholarPubMed
Lee, WJ, Liu, LK, Peng, LN et al. (2013) Comparisons of sarcopenia defined by IWGS and EWGSOP criteria among older people: results from the I-Lan longitudinal aging study. J Am Med Dir Assoc 14, 528.e521–527.10.1016/j.jamda.2013.03.019CrossRefGoogle ScholarPubMed
Wu, IC, Lin, CC, Hsiung, CA et al. (2014) Epidemiology of sarcopenia among community-dwelling older adults in Taiwan: a pooled analysis for a broader adoption of sarcopenia assessments. Geriatr Gerontol Int 14, 5260.10.1111/ggi.12193CrossRefGoogle ScholarPubMed
Janssen, I, Heymsfield, SB & Ross, R (2002) Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 50, 889896.CrossRefGoogle ScholarPubMed
Cleasby, ME, Jamieson, PM & Atherton, PJ (2016) Insulin resistance and sarcopenia: mechanistic links between common co-morbidities. J Endocrinol 229, R67R81.10.1530/JOE-15-0533CrossRefGoogle ScholarPubMed
Baek, SJ, Nam, GE, Han, KD et al. (2014) Sarcopenia and sarcopenic obesity and their association with dyslipidemia in Korean elderly men: the 2008–2010 Korea National Health and Nutrition Examination Survey. J Endocrinol Invest 37, 247260.CrossRefGoogle Scholar
Han, P, Yu, H, Ma, Y et al. (2017) The increased risk of sarcopenia in patients with cardiovascular risk factors in Suburb-Dwelling older Chinese using the AWGS definition. Sci Rep 7, 9592.10.1038/s41598-017-08488-8CrossRefGoogle ScholarPubMed
Clark, BC & Manini, TM (2012) What is dynapenia? Nutrition 28, 495503.CrossRefGoogle ScholarPubMed
Aubertin-Leheudre, M, Anton, S, Beavers, DP et al. (2017) Dynapenia and metabolic health in obese and nonobese adults aged 70 years and older: the LIFE study. J Am Med Dir Assoc 18, 312319.CrossRefGoogle ScholarPubMed
Alves, BC, Bruch-Bertani, JP, Galinatti, CBM et al. (2019) Obesity, dynapenia and high cardiovascular risk co-exist in post-liver transplant setting: results of a cross-sectional study. Clin Res Hepatol Gastroenterol 43, 140147.CrossRefGoogle ScholarPubMed
Wu, CK, Juang, JJ, Chiang, JY et al. (2018) The Taiwan Heart Registries: its influence on cardiovascular patient care. J Am Coll Cardiol 71, 12731283.CrossRefGoogle ScholarPubMed
Chiu, H-C, Mau, L-W, Chang, Y-Y et al. (2004) Risk factors for cardiovascular disease in the elderly in Taiwan. Kaohsiung J Med Sci 20, 279286.CrossRefGoogle ScholarPubMed
Ko, BJ, Chang, Y, Jung, HS et al. (2016) Relationship between low relative muscle mass and coronary artery calcification in healthy adults. Arterioscler Thromb Vasc Biol 36, 10161021.10.1161/ATVBAHA.116.307156CrossRefGoogle ScholarPubMed
Stephen, WC & Janssen, I (2009) Sarcopenic-obesity and cardiovascular disease risk in the elderly. J Nutr Health Aging 13, 460466.10.1007/s12603-009-0084-zCrossRefGoogle ScholarPubMed
Byeon, CH, Kang, KY, Kang, SH et al. (2015) Sarcopenia is associated with Framingham risk score in the Korean population: korean National Health and Nutrition Examination Survey (KNHANES) 2010–2011. J Geriatr Cardiol 12, 366372.Google ScholarPubMed
Kim, JH, Cho, JJ & Park, YS (2015) Relationship between sarcopenic obesity and cardiovascular disease risk as estimated by the Framingham risk score. J Korean Med Sci 30, 264271.CrossRefGoogle ScholarPubMed
Wilson, PW, D’Agostino, RB, Levy, D et al. (1998) Prediction of coronary heart disease using risk factor categories. Circulation 97, 18371847.10.1161/01.CIR.97.18.1837CrossRefGoogle ScholarPubMed
Brindle, P, Beswick, A, Fahey, T et al. (2006) Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart 92, 17521759.CrossRefGoogle ScholarPubMed
Chen, LK, Liu, LK, Woo, J et al. (2014) Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc 15, 95101.CrossRefGoogle ScholarPubMed
D’Agostino, RB, Vasan, RS, Pencina, MJ et al. (2008) General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 117, 743753.CrossRefGoogle ScholarPubMed
Zhang, X-M, Jiao, J, Zhu, C et al. (2021) Association between low handgrip strength and 90-day mortality among older Chinese inpatients: a national multicenter prospective cohort study. Front Nutr 8, 628628.CrossRefGoogle ScholarPubMed
Martinez-Gomez, D, Guallar-Castillon, P, Higueras-Fresnillo, S et al. (2018) Physical activity attenuates total and cardiovascular mortality associated with physical disability: a national cohort of older adults. J Gerontol A Biol Sci Med Sci 73, 240247.10.1093/gerona/glx117CrossRefGoogle ScholarPubMed
Tyrovolas, S, Panagiotakos, D, Georgousopoulou, E et al. (2020) Skeletal muscle mass in relation to 10 year cardiovascular disease incidence among middle aged and older adults: the ATTICA study. J Epidemiol Community Health 74, 2631.CrossRefGoogle ScholarPubMed
Srikanthan, P, Hevener, AL & Karlamangla, AS (2010) Sarcopenia exacerbates obesity-associated insulin resistance and dysglycemia: findings from the National Health and Nutrition Examination Survey III. PLOS ONE 5, e10805.10.1371/journal.pone.0010805CrossRefGoogle ScholarPubMed
Rubio-Ruiz, ME, Guarner-Lans, V, Perez-Torres, I et al. (2019) Mechanisms underlying metabolic syndrome-related sarcopenia and possible therapeutic measures. Int J Mol Sci 20, 647.10.3390/ijms20030647CrossRefGoogle ScholarPubMed
Zhang, H, Lin, S, Gao, T et al. (2018) Association between sarcopenia and metabolic syndrome in middle-aged and older non-obese adults: a systematic review and meta-analysis. Nutrients 10, 364.10.3390/nu10030364CrossRefGoogle ScholarPubMed
Jo, Y, Linton, JA, Choi, J et al. (2019) Association between cigarette smoking and sarcopenia according to obesity in the middle-aged and elderly Korean population: the Korea National Health and Nutrition Examination Survey (2008–2011). Korean J Fam Med 40, 8792.CrossRefGoogle Scholar
Kim, JH, Choi, SH, Lim, S et al. (2013) Sarcopenia and obesity: gender-different relationship with functional limitation in older persons. J Korean Med Sci 28, 10411047.10.3346/jkms.2013.28.7.1041CrossRefGoogle ScholarPubMed
Pedersen, BK & Febbraio, MA (2012) Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat Rev Endocrinol 8, 457465.10.1038/nrendo.2012.49CrossRefGoogle ScholarPubMed
Kang, DO, Park, SY, Choi, BG et al. (2019) Prognostic impact of low skeletal muscle mass on major adverse cardiovascular events in coronary artery disease: a propensity score-matched analysis of a single center all-comer cohort. J Clin Med 8, 712.CrossRefGoogle ScholarPubMed
Pedersen, BK & Febbraio, MA (2008) Muscle as an endocrine organ: focus on muscle-derived interleukin-6. Physiol Rev 88, 13791406.CrossRefGoogle ScholarPubMed
Srikanthan, P & Karlamangla, AS (2011) Relative muscle mass is inversely associated with insulin resistance and prediabetes. Findings from the third National Health and Nutrition Examination Survey. J Clin Endocrinol Metab 96, 28982903.CrossRefGoogle ScholarPubMed
Kjaer, M, Kiens, B, Hargreaves, M et al. (1991) Influence of active muscle mass on glucose homeostasis during exercise in humans. J Appl Physiol 71, 552557.CrossRefGoogle ScholarPubMed
Landi, F, Liperoti, R, Fusco, D et al. (2012) Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol A Biol Sci Med Sci 67, 4855.CrossRefGoogle ScholarPubMed
Patel, HP, Syddall, HE, Jameson, K et al. (2013) Prevalence of sarcopenia in community-dwelling older people in the UK using the European Working Group on Sarcopenia in Older People (EWGSOP) definition: findings from the Hertfordshire Cohort Study (HCS). Age Ageing 42, 378384.CrossRefGoogle Scholar
Payette, H, Roubenoff, R, Jacques, PF et al. (2003) Insulin-like growth factor-1 and interleukin 6 predict sarcopenia in very old community-living men and women: the Framingham Heart Study. J Am Geriatr Soc 51, 12371243.CrossRefGoogle ScholarPubMed
Fried, LP, Tangen, CM, Walston, J et al. (2001) Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 56, M146M 156.10.1093/gerona/56.3.M146CrossRefGoogle ScholarPubMed
Srinivas-Shankar, U, Roberts, SA, Connolly, MJ et al. (2010) Effects of testosterone on muscle strength, physical function, body composition, and quality of life in intermediate-frail and frail elderly men: a randomized, double-blind, placebo-controlled study. J Clin Endocrinol Metab 95, 639650.CrossRefGoogle ScholarPubMed
Herbst, KL & Bhasin, S (2004) Testosterone action on skeletal muscle. Curr Opin Clin Nutr Metab Care 7, 271277.Google ScholarPubMed
Bhasin, S (2003) Testosterone supplementation for aging-associated sarcopenia. J Gerontol A Biol Sci Med Sci 58, 10021008.10.1093/gerona/58.11.M1002CrossRefGoogle ScholarPubMed
Lee, WJ, Peng, LN, Chiou, ST et al. (2016) Relative handgrip strength is a simple indicator of cardiometabolic risk among middle-aged and older people: a nationwide population-based study in Taiwan. PLoS One 11, e0160876.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Characteristics of male participants

Figure 1

Table 2 Characteristics of female participants

Figure 2

Table 3 Comparison of Framingham risk scores among four groups of participants in both genders