Kolbasi Esma Nur, Demirdag Filiz, Yildiz Kubra, Murat Sadiye, Balkaya Gozde
Istanbul Medeniyet University, Department of Physiotherapy and Rehabilitation, Istanbul - Turkey.
Istanbul Medeniyet University Göztepe Training and Research Hospital, Department of Internal Medicine, Istanbul, Turkey.
Medeni Med J. 2020;35(1):23-28. doi: 10.5222/MMJ.2020.50133. Epub 2020 Feb 28.
The objective of this study was to determine the predictors of bone health in older adults.
A total of 313 subjects older than 65 years (mean age 74.2±6.4 years, 70.6% female) were included in the study. Demographic characteristics of participants such as gait speed, handgrip strength, level of physical activity (using Rapid Assessment of Physical Activity-RAPA scale), vitamin D levels, T scores of femur neck (FN) and lumbar spine (LS) were recorded.
Based on FN, 40.7% of participants had normal T scores whereas 46.2% and 13.1% of them were osteopenic and osteoporotic, respectively. FN was correlated with age (r:-0.184, p<0.001), BMI (r:0.269, p<0.001), and handgrip strength (r:0.149, p:0.009) in addition to the aerobic subscale of RAPA (RAPA-aerobic) (r:-0.133, p:0.02). Similarly, the LS was correlated with female gender (r:-0.207, p<0.001), age (r:0.136, p:0.016), body mass index (BMI) (r:0.246, p<0.001) and handgrip strength (r:0.217, p<0.001). The predictors of bone health were decided upon using multiple logistic regression analysis. The deterministic model consisted of age, gender, BMI, height, weight, handgrip strength, gait speed, RAPA-aerobic and vitamin D. For LS dependent variable, the overall model was significant (F:10.149, p<0.001). However, only two variables were significant predictors in the model ie. weight (β:0.389, p<0.001) and handgrip strength (β=0.186, p<0.001). Similarly for independent variable of FN, the overall model was significant (F:6.525, p<0.001) and only two variables were significant predictors: weight (β:0.371, p<0.001) and RAPA-Aerobic (β:0.148, p:0.009).
Lower levels of body weight, participation in aerobic activity and handgrip strength might be risk factors for deterioration of bone health in older adults.
本研究的目的是确定老年人骨骼健康的预测因素。
共有313名65岁以上的受试者(平均年龄74.2±6.4岁,女性占70.6%)纳入本研究。记录参与者的人口统计学特征,如步速、握力、身体活动水平(使用身体活动快速评估-RAPA量表)、维生素D水平、股骨颈(FN)和腰椎(LS)的T值。
基于FN,40.7%的参与者T值正常,而其中46.2%和13.1%分别为骨量减少和骨质疏松。除RAPA的有氧亚量表(RAPA-有氧)外,FN与年龄(r:-0.184,p<0.001)、BMI(r:0.269,p<0.001)和握力(r:0.149,p:0.009)相关(r:-0.133,p:0.02)。同样,LS与女性性别(r:-0.207,p<0.001)、年龄(r:0.136,p:0.016)、体重指数(BMI)(r:0.246,p<0.001)和握力(r:0.217,p<0.001)相关。使用多元逻辑回归分析确定骨骼健康的预测因素。确定性模型包括年龄、性别、BMI、身高、体重、握力、步速、RAPA-有氧和维生素D。对于LS因变量,总体模型具有显著性(F:10.149,p<0.001)。然而,模型中只有两个变量是显著的预测因素,即体重(β:0.389,p<0.001)和握力(β=0.186,p<0.001)。同样,对于FN自变量,总体模型具有显著性(F:6.525,p<0.001),只有两个变量是显著的预测因素:体重(β:0.371,p<0.001)和RAPA-有氧(β:0.148,p:0.009)。
体重较低、参与有氧运动和握力较低可能是老年人骨骼健康恶化的危险因素。