Development and Validation of Estimation Equations for Appendicular Skeletal Muscle Mass in Chinese Community-Dwelling Older Adults

References

• Liu M, Zhou S, Li M, Wa L. Study of muscle mass prediction models through simple muscle strength in community-dwelling elderly. Pract Geriatr. 2021;35(02):149–154. doi:10.3969/j.issn.1003-9198.2021.02.010
   Google Scholar
• Hirschfeld HP, Kinsella R, Duque G. Osteosarcopenia: where bone, muscle, and fat collide. Osteoporos Int. 2017;28(10):2781–2790. doi:10.1007/s00198-017-4151-8
   PubMed Web of Science ®Google Scholar
• Brotto M, Invernizzi M, Ireland A, Klein GL. Editorial: osteoporosis and the role of muscle. Front Endocrinol. 2022;13:951298. doi:10.3389/fendo.2022.951298
   PubMed Web of Science ®Google Scholar
• Kirk B, Feehan J, Lombardi G, Duque G. Muscle, bone, and fat crosstalk: the biological role of myokines, osteokines, and adipokines. Curr Osteoporos Rep. 2020;18(4):388–400. doi:10.1007/s11914-020-00599-y
   PubMed Web of Science ®Google Scholar
• Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019;393(10191):2636–2646. doi:10.1016/s0140-6736(19)31138-9
   PubMed Web of Science ®Google Scholar
• Cho MR, Lee S, Song SK. A review of sarcopenia pathophysiology, diagnosis, treatment and future direction. J Korean Med Sci. 2022;37(18):e146. doi:10.3346/jkms.2022.37.e146
   PubMed Web of Science ®Google Scholar
• Zhang Y, Zhang J, Ni W, et al. Sarcopenia in heart failure: a systematic review and meta-analysis. ESC Heart Fail. 2021;8(2):1007–1017. doi:10.1002/ehf2.13255
   PubMed Web of Science ®Google Scholar
• Yang J, Jiang F, Yang M, Chen Z. Sarcopenia and nervous system disorders. J Neurol. 2022;269(11):5787–5797. doi:10.1007/s00415-022-11268-8
   PubMed Web of Science ®Google Scholar
• Shu X, Lin T, Wang H, et al. Diagnosis, prevalence, and mortality of sarcopenia in dialysis patients: a systematic review and meta-analysis. J Cachexia, Sarcopenia Muscle. 2022;13(1):145–158. doi:10.1002/jcsm.12890
   PubMed Web of Science ®Google Scholar
• Fielding RA, Vellas B, Evans WJ, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. J Am Med Dir Assoc. 2011;12(4):249–256. doi:10.1016/j.jamda.2011.01.003
   PubMed Web of Science ®Google Scholar
• Studenski SA, Peters KW, Alley DE, et al. The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates. J Gerontol a Biol Sci Med Sci. 2014;69(5):547–558. doi:10.1093/gerona/glu010
   PubMed Web of Science ®Google Scholar
• Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31. doi:10.1093/ageing/afy169
   PubMed Web of Science ®Google Scholar
• Chen LK, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300–307.e2. doi:10.1016/j.jamda.2019.12.012
   PubMed Web of Science ®Google Scholar
• Abdalla PP, da Silva LSL, Venturini ACR, et al. Anthropometric equations to estimate appendicular muscle mass from dual-energy X-ray absorptiometry (DXA): a scoping review. Arch Gerontol Geriatr. 2023;110:104972. doi:10.1016/j.archger.2023.104972
   PubMed Web of Science ®Google Scholar
• Massimino E, Izzo A, Riccardi G, Della Pepa G. The impact of glucose-lowering drugs on sarcopenia in type 2 diabetes: current evidence and underlying mechanisms. Cells. 2021;10(8):1958. doi:10.3390/cells10081958
   PubMed Web of Science ®Google Scholar
• Ebihara K, Iwanami Y, Yamasaki K, et al. Appendicular skeletal muscle mass correlates with patient-reported outcomes and physical performance in patients with idiopathic pulmonary fibrosis. Tohoku J Exp Med. 2021;253(1):61–68. doi:10.1620/tjem.253.61
   PubMed Web of Science ®Google Scholar
• Santos LP, Gonzalez MC, Orlandi SP, Bielemann RM, Barbosa-Silva TG, Heymsfield SB. New prediction equations to estimate appendicular skeletal muscle mass using calf circumference: results from NHANES 1999–2006. JPEN J Parenter Enteral Nutr. 2019;43(8):998–1007. doi:10.1002/jpen.1605
   PubMed Web of Science ®Google Scholar
• Zapata-Gómez D, Cerda-Kohler H, Burgos C, Báez EI, Ramirez-Campillo R. Validation of a novel equation to predict lower-limb muscle mass in young soccer players: a brief communication. Int J Morphol. 2020;38(3):665–669. doi:10.4067/S0717-95022020000300665
   Web of Science ®Google Scholar
• Kawakami R, Miyachi M, Tanisawa K, et al. Development and validation of a simple anthropometric equation to predict appendicular skeletal muscle mass. Clin Nutr. 2021;40(11):5523–5530. doi:10.1016/j.clnu.2021.09.032
   PubMed Web of Science ®Google Scholar
• Hsiao MY, Chang KV, Wu WT, Huang KC, Han DS. Grip strength and demographic variables estimate appendicular muscle mass better than bioelectrical impedance in Taiwanese older persons. J Am Med Dir Assoc. 2021;22(4):760–765. doi:10.1016/j.jamda.2020.08.003
   PubMed Web of Science ®Google Scholar
• Katano S, Honma S, Nagaoka R, et al. Anthropometric parameters-derived estimation of muscle mass predicts all-cause mortality in heart failure patients. ESC Heart Fail. 2022;9(6):4358–4365. doi:10.1002/ehf2.14121
   PubMed Web of Science ®Google Scholar
• Powell RM, Rolfe EDL, Day FR, et al. Development and validation of total and regional body composition prediction equations from anthropometry and single frequency segmental bioelectrical impedance with DEXA. medRxiv. 2020. doi:10.1101/2020.12.16.20248330
   Google Scholar
• Lee G, Chang J, Hwang SS, Son JS, Park SM. Development and validation of prediction equations for the assessment of muscle or fat mass using anthropometric measurements, serum creatinine level, and lifestyle factors among Korean adults. Nutr Res Pract. 2021;15(1):95–105. doi:10.4162/nrp.2021.15.1.95
   PubMed Web of Science ®Google Scholar
• Wu P, Chen L, Jin J, et al. Estimation of appendicular skeletal muscle: development and validation of anthropometric prediction equations in Chinese patients with knee osteoarthritis. Australas J Ageing. 2020;39(1):e119–e126. doi:10.1111/ajag.12709
   PubMed Web of Science ®Google Scholar
• Chien KY, Chen CN, Chen SC, Wang HH, Zhou WS, Chen LH. A community-based approach to lean body mass and appendicular skeletal muscle mass prediction using body circumferences in community-dwelling elderly in Taiwan. Asia Pac J Clin Nutr. 2020;29(1):94–100. doi:10.6133/apjcn.202003_29(1).0013
   PubMed Web of Science ®Google Scholar
• Wen X, Wang M, Jiang CM, Zhang YM. Anthropometric equation for estimation of appendicular skeletal muscle mass in Chinese adults. Asia Pac J Clin Nutr. 2011;20(4):551–556.
   PubMed Web of Science ®Google Scholar
• Hwang AC, Liu LK, Lee WJ, Peng LN, Chen LK. Calf circumference as a screening instrument for appendicular muscle mass measurement. J Am Med Dir Assoc. 2018;19(2):182–184. doi:10.1016/j.jamda.2017.11.016
   PubMed Web of Science ®Google Scholar
• Joseph VR. Optimal ratio for data splitting. Statl Anal Data Min. 2022;4:15.
   Google Scholar
• Lee DH, Keum N, Hu FB, et al. Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006. Br J Nutr. 2017;118(10):858–866. doi:10.1017/s0007114517002665
   PubMed Web of Science ®Google Scholar
• Musa IR, Omar SM, Adam I. Mid-upper arm circumference as a substitute for body mass index in the assessment of nutritional status among adults in eastern Sudan. BMC Public Health. 2022;22(1):2056. doi:10.1186/s12889-022-14536-4
   PubMed Web of Science ®Google Scholar
• Gonzalez MC, Mehrnezhad A, Razaviarab N, Barbosa-Silva TG, Heymsfield SB. Calf circumference: cutoff values from the NHANES 1999–2006. Am J Clin Nutr. 2021;113(6):1679–1687. doi:10.1093/ajcn/nqab029
   PubMed Web of Science ®Google Scholar
• Roberts HC, Denison HJ, Martin HJ, et al. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423–429. doi:10.1093/ageing/afr051
   PubMed Web of Science ®Google Scholar
• Fess EE. American Society of Hand Therapists. J Hand Surg. 1983;8(5):625–627. doi:10.1016/S0363-5023(83)80141-5
   Web of Science ®Google Scholar
• Kline RB. Principles and Practice of Structural Equation Modeling. 2nd ed. Guilford publications; 2004.
   Google Scholar
• Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135–160. doi:10.1177/096228029900800204
   PubMed Web of Science ®Google Scholar
• Shi J, He Q, Pan Y, Zhang X, Li M, Chen S. Estimation of appendicular skeletal muscle mass for women aged 60–70 years using a machine learning approach. J Am Med Dir Assoc. 2022;23(12):1985.e1–1985.e7. doi:10.1016/j.jamda.2022.09.002
   PubMed Web of Science ®Google Scholar
• Santana F, Farah BQ, Soares AHG, Correia M, Dias RMR. Anthropometric Parameters as Predictors of Muscle Mass in Older Women. Motricidade. 2015;11(2):107–114.
   Google Scholar
• H BAI, J SUN, Chen M, Xie H, Xu D, Chen Y. Relationship between calf circumference and skeletal muscle mass, strength and function in the elderly. Chinese J Clin Nutr. 2018;26(5):284–287. doi:10.3760/cma.j.issn.1674-635X.2018.05.005
   Google Scholar
• Asai C, Akao K, Adachi T, et al. Maximal calf circumference reflects calf muscle mass measured using magnetic resonance imaging. Arch Gerontol Geriatr. 2019;83:175–178. doi:10.1016/j.archger.2019.04.012
   PubMed Web of Science ®Google Scholar
• Yang L, Wu Y, Zhang L, et al. Sarcopenia and its related factors in elderly population in Suzhou. Chin J Osteop Bone Mineral Res. 2019;12(3):213–220. doi:10.3969/j.issn.1674-2591.2019.03.002
   Google Scholar
• De la Cámara M, Higueras-Fresnillo S, Sadarangani KP, Esteban-Cornejo I, Martinez-Gomez D, Veiga ÓL. Clinical and ambulatory gait speed in older adults: associations with several physical, mental, and cognitive health outcomes. Phys Ther. 2020;100(4):718–727. doi:10.1093/ptj/pzz186
   PubMed Web of Science ®Google Scholar
• Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–310. doi:10.1016/S0140-6736(86)90837-8
   PubMed Web of Science ®Google Scholar