Takahashi Ikuko, Watanabe Kei, Kawashima Hiroyuki, Noguchi Hideo, Sato Junko, Ishii Yoshinori
Ishii Orthopaedic & Rehabilitation Clinic, 1089 Shimo-Oshi, Gyoda, Saitama, 361-0037, Japan.
Niigata Spine Surgery Center, 2-5-22 Nishimachi, Konanku, Niigata, Niigata, 950-0165, Japan.
J Orthop. 2024 Jun 15;57:104-108. doi: 10.1016/j.jor.2024.06.014. eCollection 2024 Nov.
Osteoporosis significantly predisposes patients to fragility fractures and a reduced quality of life. Therefore, osteoporosis prevention plays an important role in extending healthy life expectancy. The purpose of this study was to identify whether physical functional status was associated with low bone mineral density, and to determine cut-off values of physical status indicators for osteoporosis.
This cross-sectional study evaluated 343 women aged 60 years or older who were able to walk independently. The measured variables were the body mass index, lumbar and total hip bone mineral density, grip strength, 5-m normal walking speed, one-leg standing time, timed up-and-go test, and skeletal muscle mass using bioelectrical impedance analysis. The associations between physical status indicators and low bone mineral density were analyzed and the cut-off values for detecting osteoporosis were calculated using receiver operating characteristic curve analyses.
The prevalence of osteoporosis was 29.2 %. All measured variables significantly differed between the osteoporotic and non-osteoporotic groups (p < 0.05). Multivariate logistic regression analysis showed that the factors associated with osteoporosis were the skeletal muscle mass index, walking speed, and body mass index. In the receiver operating characteristic curve analysis, the cut-off values of the skeletal muscle mass index, walking speed, and body mass index associated with osteoporosis were 6.31 kg/m, 1.29 m/s, and 22.6 kg/m, respectively.
Older women with low bone mineral density have lower skeletal muscle mass, slower walking speed, and lower body mass index. Measuring the skeletal muscle mass index, walking speed, and body mass index might be useful for daily exercise guidance or osteoporosis screening.
骨质疏松症显著增加了患者发生脆性骨折的风险,并降低生活质量。因此,骨质疏松症的预防对于延长健康预期寿命起着重要作用。本研究的目的是确定身体功能状态是否与低骨密度相关,并确定骨质疏松症身体状态指标的临界值。
这项横断面研究评估了343名60岁及以上能够独立行走的女性。测量的变量包括体重指数、腰椎和全髋骨密度、握力、5米正常行走速度、单腿站立时间、计时起立行走测试,以及使用生物电阻抗分析测量的骨骼肌质量。分析身体状态指标与低骨密度之间的关联,并使用受试者工作特征曲线分析计算检测骨质疏松症的临界值。
骨质疏松症的患病率为29.2%。所有测量变量在骨质疏松组和非骨质疏松组之间均有显著差异(p<0.05)。多因素逻辑回归分析表明,与骨质疏松症相关的因素是骨骼肌质量指数、步行速度和体重指数。在受试者工作特征曲线分析中,与骨质疏松症相关的骨骼肌质量指数、步行速度和体重指数的临界值分别为6.31kg/m、1.29m/s和22.6kg/m。
骨密度低的老年女性骨骼肌质量较低、步行速度较慢且体重指数较低。测量骨骼肌质量指数、步行速度和体重指数可能有助于日常运动指导或骨质疏松症筛查。