Samson SL, Garber AJ. Metabolic syndrome. Endocrinol Metab Clin North Am. 2014;43(1):1–23.
Li X, Cao C, Tang X, et al. Prevalence of metabolic syndrome and its determinants in newly-diagnosed adult-onset diabetes in china: a multi-center cross-sectional survey. Front Endocrinol. 2019;10:661.
Scott R, Donoghoe M, Watts GF, et al. Impact of metabolic syndrome and its components on cardiovascular disease event rates in 4900 patients with type 2 diabetes assigned to placebo in the FIELD randomised trial. Cardiovasc Diabetol. 2011;10:102.
Rhee SY, Park SY, Hwang JK, et al. Metabolic syndrome as an indicator of high cardiovascular risk in patients with diabetes: analyses based on Korea National Health and Nutrition Examination Survey (KNHANES) 2008. Diabetol Metab Syndr. 2014;6(1):98.
Lu J, Wang L, Li M, et al. Metabolic syndrome among adults in China: the 2010 China noncommunicable disease surveillance. J Clin Endocrinol Metab. 2017;102(2):507–15.
Katsiki N, Anagnostis P, Kotsa K, Goulis DG, Mikhailidis DP. Obesity, metabolic syndrome and the risk of microvascular complications in patients with diabetes mellitus. Curr Pharm Des. 2019;25(18):2051–9.
Chuang SM, Shih HM, Chien MN, et al. Risk factors in metabolic syndrome predict the progression of diabetic nephropathy in patients with type 2 diabetes. Diabetes Res Clin Pract. 2019;153:6–13.
Oh B, Cho B, Han MK, et al. The effectiveness of mobile phone-based care for weight control in metabolic syndrome patients randomized controlled trial. JMIR mHealth uHealth. 2015;3(3):e83.
Reuter CP, Brand C, Silveira JFC, et al. Reciprocal longitudinal relationship between fitness, fatness, and metabolic syndrome in brazilian children and adolescents: a 3-year longitudinal study. Pediatr Exerc Sci. 2021;33(2):74–81.
Kalinkovich A, Livshits G. Sarcopenic obesity or obese sarcopenia: a cross talk between age-associated adipose tissue and skeletal muscle inflammation as a main mechanism of the pathogenesis. Ageing Res Rev. 2017;35:200–21.
Lee J, Hong YP, Shin HJ, Lee W. Associations of sarcopenia and sarcopenic obesity with metabolic syndrome considering both muscle mass and muscle strength. J Prev Med Public Health. 2016;49(1):35–44.
Bijlsma AY, Meskers CG, van Heemst D, et al. Diagnostic criteria for sarcopenia relate differently to insulin resistance. Age. 2013;35(6):2367–75.
Kurinami N, Sugiyama S, Morita A, et al. Ratio of muscle mass to fat mass assessed by bioelectrical impedance analysis is significantly correlated with liver fat accumulation in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract. 2018;139:122–30.
Lee HS, Kim SG, Kim JK, et al. Fat-to-lean mass ratio can predict cardiac events and all-cause mortality in patients undergoing hemodialysis. Ann Nutr Metab. 2018;73(3):241–9.
Seo YG, Song HJ, Song YR. Fat-to-muscle ratio as a predictor of insulin resistance and metabolic syndrome in Korean adults. J Cachexia Sarcopenia Muscle. 2020;11(3):710–25.
Ramírez-Vélez R, Carrillo HA, Correa-Bautista JE, et al. Fat-to-muscle ratio: a new anthropometric indicator as a screening tool for metabolic syndrome in young Colombian people. Nutrients. 2018. https://doi.org/10.3390/nu10081027.
Park J, Kim S. Validity of muscle-to-fat ratio as a predictor of adult metabolic syndrome. J Phys Ther Sci. 2016;28(3):1036–45.
Kutáč P. Inter-daily variability in body composition among young men. J Physiol Anthropol. 2015;34(1):32.
Lee LC, Hsu PS, Hsieh KC, et al. Standing 8-electrode bioelectrical impedance analysis as an alternative method to estimate visceral fat area and body fat mass in athletes. Int J Gen Med. 2021;14:539–48.
Fang WH, Yang JR, Lin CY, et al. Accuracy augmentation of body composition measurement by bioelectrical impedance analyzer in elderly population. Medicine. 2020;99(7): e19103.
Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998;21(12):2191–2.
Chen Y, He D, Yang T, et al. Relationship between body composition indicators and risk of type 2 diabetes mellitus in Chinese adults. BMC Public Health. 2020;20(1):452.
Park SW, Goodpaster BH, Strotmeyer ES, et al. Accelerated loss of skeletal muscle strength in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes Care. 2007;30(6):1507–12.
Pechmann LM, Jonasson TH, Canossa VS, et al. Sarcopenia in type 2 diabetes mellitus: a cross-sectional observational study. Int J Endocrinol. 2020;2020:7841390.
Wang Q, Zheng D, Liu J, Fang L, Li Q. Skeletal muscle mass to visceral fat area ratio is an important determinant associated with type 2 diabetes and metabolic syndrome. Diabetes Metab Syndr Obes. 2019;12:1399–407.
Volpato S, Bianchi L, Lauretani F, et al. Role of muscle mass and muscle quality in the association between diabetes and gait speed. Diabetes Care. 2012;35(8):1672–9.
Su X, Xu J, Zheng C. The relationship between non-alcoholic fatty liver and skeletal muscle mass to visceral fat area ratio in women with type 2 diabetes. BMC Endocr Disord. 2019;19(1):76.
Park SH, Park JH, Song PS, et al. Sarcopenic obesity as an independent risk factor of hypertension. J Am Soc Hypertens. 2013;7(6):420–5.
Baek SJ, Nam GE, Han KD, et al. 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. 2014;37(3):247–60.
Shida T, Akiyama K, Oh S, et al. Skeletal muscle mass to visceral fat area ratio is an important determinant affecting hepatic conditions of non-alcoholic fatty liver disease. J Gastroenterol. 2018;53(4):535–47.
Lindström I, Protto S, Khan N, et al. Statin use, development of sarcopenia, and long-term survival after endovascular aortic repair. J Vasc Surg. 2021. https://doi.org/10.1016/j.jvs.2021.04.054.
Parker BA, Capizzi JA, Grimaldi AS, et al. Effect of statins on skeletal muscle function. Circulation. 2013;127(1):96–103.
Scott D, Blizzard L, Fell J, Jones G. Statin therapy, muscle function and falls risk in community-dwelling older adults. QJM. 2009;102(9):625–33.
Lopez-Lopez JP, Cohen DD, Ney-Salazar D, et al. The prediction of metabolic syndrome alterations is improved by combining waist circumference and handgrip strength measurements compared to either alone. Cardiovasc Diabetol. 2021;20(1):68.
Lima TR, González-Chica DA, D’Orsi E, Sui X, Silva DAS. Muscle strength cut-points for metabolic syndrome detection among adults and the elderly from Brazil. Appl physiol Nutr Metab. 2021;46(4):379–88.