Dhana Klodian, Koolhaas Chantal M, Schoufour Josje D, Rivadeneira Fernando, Hofman Albert, Kavousi Maryam, Franco Oscar H
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
Maturitas. 2016 Jun;88:96-100. doi: 10.1016/j.maturitas.2016.03.018. Epub 2016 Apr 1.
The decrease in fat-free mass (FFM) seen in many elderly people is usually associated with an increase in fat mass (FM), a state referred to as sarcopenic obesity. It is not clear which anthropometric measures are best used to identify sarcopenic obesity. We therefore evaluated which anthropometric measures are differentially associated with FM and FFM.
The anthropometric measures tested were body mass index (BMI), waist circumference (WC), and a body shape index (ABSI = WC/(BMI(2/3)*Height(1/2))). FM and FFM were estimated by dual-energy X-ray absorptiometry. An index-score was calculated for both FM (FMI) and FFM (FFMI) by dividing FM and FFM by height. Multivariable linear regression models were used to assess the associations of BMI, WC and ABSI with FMI and FFMI among 3612 participants (2092 women) from the prospective population-based Rotterdam Study.
In multivariate models adjusted for confounders, BMI and WC were positively associated with both FMI and FFMI in men and women. ABSI was positively associated with FMI (β 1.01, 95% confidence interval (95%CI) 0.85, 1.17) and negatively associated with FFMI (β -0.28, 95%CI -0.38, -0.17) in men. In women, ABSI was not associated with FMI and was positively associated with FFMI (β 0.18, 95%CI 0.10, 0.26).
While BMI and WC were both positively associated with FM and FFM, ABSI showed a differential association with FM and FFM in men, but not in women. Since sarcopenic obesity is associated with decreased FFM and increased FM, ABSI could be a useful tool for identifying men at higher risk of sarcopenic obesity.
许多老年人出现的去脂体重(FFM)下降通常与脂肪量(FM)增加有关,这种状态被称为肌少症性肥胖。目前尚不清楚哪种人体测量方法最适合用于识别肌少症性肥胖。因此,我们评估了哪些人体测量方法与FM和FFM存在差异关联。
所测试的人体测量指标包括体重指数(BMI)、腰围(WC)和身体形状指数(ABSI = WC /(BMI(2/3)*身高(1/2)))。通过双能X线吸收法估算FM和FFM。通过将FM和FFM除以身高来计算FM(FMI)和FFM(FFMI)的指数得分。使用多变量线性回归模型评估来自基于人群的前瞻性鹿特丹研究的3612名参与者(2092名女性)中BMI、WC和ABSI与FMI和FFMI之间的关联。
在针对混杂因素进行调整的多变量模型中,BMI和WC与男性和女性的FMI和FFMI均呈正相关。在男性中,ABSI与FMI呈正相关(β 1.01,95%置信区间(95%CI)0.85,1.17),与FFMI呈负相关(β -0.28,95%CI -0.38,-0.17)。在女性中,ABSI与FMI无关联,与FFMI呈正相关(β 0.18,95%CI 0.10,0.26)。
虽然BMI和WC与FM和FFM均呈正相关,但ABSI在男性中与FM和FFM存在差异关联,而在女性中则不然。由于肌少症性肥胖与FFM降低和FM增加有关,ABSI可能是识别肌少症性肥胖风险较高男性的有用工具。