Muscle Performance as a Predictor of Bone Health: Among Community-Dwelling Postmenopausal Japanese Women from Setagaya-Aoba Study

Mohd-Tahir NA, Li SC (2017) Economic burden of osteoporosis-related hip fracture in Asia: a systematic review. Osteoporos Int 28:2035–2044. https://doi.org/10.1007/s00198-017-3985-4

Article  PubMed  Google Scholar 

Suzuki T, Yoshida H (2010) Low bone mineral density at femoral neck is a predictor of increased mortality in elderly Japanese women. Osteoporos Int 21:71–79. https://doi.org/10.1007/s00198-009-0970-6

Article  CAS  PubMed  Google Scholar 

Orimo H, Nakamura T, Hosoi T et al (2012) Japanese 2011 guidelines for prevention and treatment of osteoporosis-executive summary. Arch Osteoporos 7:3–20. https://doi.org/10.1007/s11657-012-0109-9

Article  PubMed  PubMed Central  Google Scholar 

Tsuda-Futami E, Hans D, Njeh CF et al (1999) An evaluation of a new gel-coupled ultrasound device for the quantitative assessment of bone. Br J Radiol 72:691–700

Article  CAS  PubMed  Google Scholar 

Marshall D, Johnell O, Wedel H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. Br Med J 312:1254–1259. https://doi.org/10.1136/bmj.312.7041.1254

Article  CAS  Google Scholar 

Haïat G, Padilla F, Laugier P (2008) Sensitivity of QUS parameters to controlled variations of bone strength assessed with a cellular model. IEEE Trans Ultrason Ferroelectr Freq Control 55:1488–1496. https://doi.org/10.1109/TUFFC.2008.824

Article  PubMed  Google Scholar 

Métrailler A, Hans D, Lamy O et al (2023) Heel quantitative ultrasound (QUS) predicts incident fractures independently of trabecular bone score (TBS), bone mineral density (BMD), and FRAX: the OsteoLaus Study. Osteoporos Int 34:1401–1409. https://doi.org/10.1007/s00198-023-06728-4

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kidokoro T, Tomkinson GR, Noi S, Suzuki K (2022) Japanese physical fitness surveillance: a greater need for international publications that utilize the world’s best physical fitness database. J Phys Fit Sports Med 11:161–167. https://doi.org/10.7600/jpfsm.11.161

Article  Google Scholar 

Japan Osteoporosis Foundation (2021) Current status of osteoporosis screening in 2021 [in Japanese]

Angulo J, El Assar M, Álvarez-Bustos A, Rodríguez-Mañas L (2020) Physical activity and exercise: strategies to manage frailty. Redox Biol 35:101513. https://doi.org/10.1016/j.redox.2020.101513

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yakabe M, Hosoi T, Akishita M, Ogawa S (2020) Updated concept of sarcopenia based on muscle–bone relationship. J Bone Miner Metab 38:7–13. https://doi.org/10.1007/s00774-019-01048-2

Article  PubMed  Google Scholar 

Cianferotti L, Brandi ML (2014) Muscle-bone interactions: basic and clinical aspects. Endocrine 45:165–177

Article  CAS  PubMed  Google Scholar 

Guralnik JM, Simonsick EM, Ferrucci L et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49:85–94

Article  Google Scholar 

Jones CJ, Rikli RE, Beam WC (1999) A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Res Q Exerc Sport 70:113–119

Article  CAS  PubMed  Google Scholar 

Toraman A, Yildirim NÜ (2010) The falling risk and physical fitness in older people. Arch Gerontol Geriatr 51:222–226. https://doi.org/10.1016/j.archger.2009.10.012

Article  PubMed  Google Scholar 

Ohta T, Nagashima J, Sasai H et al (2021) Sport program service study and Setagaya- Aoba study. J Phys Fit Sports Med. https://doi.org/10.7600/jpfsm.11.127

Article  Google Scholar 

Von Elm E, Altman DG, Egger M et al (2007) The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 4:e296

Article  Google Scholar 

Bossuyt PM, Reitsma JB, Bruns DE et al (2015) STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. https://doi.org/10.1136/bmj.h5527

Article  PubMed  PubMed Central  Google Scholar 

Lees B, Stevenson JC (1993) Preliminary evaluation of a new ultrasound bone densitometer. Calcif Tissue Int 53:149–152. https://doi.org/10.1007/BF01321829

Article  CAS  PubMed  Google Scholar 

Otani T, Fukunaga M, Yho K et al (2018) Attempt at standardization of bone quantitative ultrasound in Japan. J Med Ultrason 45:3–13. https://doi.org/10.1007/s10396-017-0814-5

Article  Google Scholar 

Ikeda Y, Iki M, Morita A et al (2002) Age-specific values and cutoff levels for the diagnosis of osteoporosis in quantitative ultrasound measurements at the calcaneus with SAHARA in healthy Japanese women: Japanese population-based osteoporosis (JPOS) study. Calcif Tissue Int 71:1–9. https://doi.org/10.1007/s00223-001-2079-6

Article  CAS  PubMed  Google Scholar 

Bujang MA, Adnan TH (2016) Requirements for minimum sample size for sensitivity and specificity analysis. J Clin Diagn Res 10:YE01–YE06. https://doi.org/10.7860/JCDR/2016/18129.8744

Article  PubMed  PubMed Central  Google Scholar 

Hirono A, Kusunose K, Kageyama N et al (2018) Development and validation of optimal cut-off value in inter-arm systolic blood pressure difference for prediction of cardiovascular events. J Cardiol 71:24–30. https://doi.org/10.1016/j.jjcc.2017.06.010

Article  PubMed  Google Scholar 

Fischer JE, Bachmann LM, Jaeschke R (2003) A readers’ guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med 29:1043–1051. https://doi.org/10.1007/s00134-003-1761-8

Article  PubMed  Google Scholar 

Perkins NJ, Schisterman EF (2006) The inconsistency of “optimal” cut-points using Two ROC based criteria. Am J Epidemiol 163:670–675

Article  PubMed  Google Scholar 

Japan Sports Agency Physical Fitness and Athletic Performance Survey. https://www.mext.go.jp/sports/en/index.htm. Accessed 13 Mar 2024

Abdalla PP, dos Santos CA, dos Santos AP et al (2020) Cut-off points of knee extension strength allometrically adjusted to identify sarcopenia risk in older adults: a cross-sectional study. Arch Gerontol Geriatr 89:104100. https://doi.org/10.1016/j.archger.2020.104100

Article  PubMed  Google Scholar 

Rikkonen T, Sirola J, Salovaara K et al (2012) Muscle strength and body composition are clinical indicators of osteoporosis. Calcif Tissue Int 91:131–138. https://doi.org/10.1007/s00223-012-9618-1

Article  CAS  PubMed  Google Scholar 

Collantes MB, García CLA, Fonseca AA et al (2012) Reliability of Arm Curl and Chair Stand tests for assessing muscular endurance in older people. Revista Ciencias de la Salud 10:173–193. https://doi.org/10.12804/revistas.urosario.edu.co/revsalud/a.2179

Article  Google Scholar 

Ma Y, Fu L, Jia L et al (2018) Muscle strength rather than muscle mass is associated with osteoporosis in older Chinese adults. J Formos Med Assoc 117:101–108. https://doi.org/10.1016/j.jfma.2017.03.004

Article  PubMed  Google Scholar 

Lord SR, Murray SM, Chapman K et al (2002) Sit-to-stand performance depends on sensation, speed, balance, and psychological status in addition to strength in older people. J Gerontol 57:M539-543. https://doi.org/10.1093/gerona/57.8.M539

Article  Google Scholar 

de Almeida Marques BR, de Souza VM, Felício de Souza V et al (2022) Muscle strength is associated with fracture risk obtained by fracture risk assessment tool (FRAX) in women with breast cancer. BMC Cancer. https://doi.org/10.1186/s12885-022-10203-4

Article  Google Scholar 

Alajlouni D, Tran T, Bliuc D et al (2022) Muscle strength and physical performance improve fracture risk prediction Beyond Garvan and FRAX: the osteoporotic fractures in men (MrOS) study. J Bone Miner Res 37:411–419. https://doi.org/10.1002/jbmr.4483

Article  PubMed  Google Scholar 

Severinsen MCK, Pedersen BK (2020) Muscle-organ crosstalk: the emerging roles of myokines. Endocr Rev 42:97–99

Comments (0)

No login
gif