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使用人体测量预测方程评估肌肉和脂肪量来预测身体成分和骨质疏松性骨折。

Body composition and osteoporotic fracture using anthropometric prediction equations to assess muscle and fat masses.

机构信息

Department of Family Medicine, Seoul National University Hospital, Seoul, Korea.

Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea.

出版信息

J Cachexia Sarcopenia Muscle. 2021 Dec;12(6):2247-2258. doi: 10.1002/jcsm.12850. Epub 2021 Oct 27.

Abstract

BACKGROUND

Obesity is protective of bone health; however, abdominal obesity is associated with a higher fracture risk. Little is known about whether body composition protects or adversely affects osteoporotic fractures because of practical issues regarding assessment tools. This study aimed to evaluate the association of predicted body composition with fracture risk to determine the distinctive and differing effects of muscle or fat mass on bone health outcomes in the general population.

METHODS

This population-based, longitudinal cohort study used 2009-2010 Korean National Health Insurance Service data and follow-up data from 1 January 2011 to 31 December 2013, to determine the incidence of osteoporotic fracture (total, spine, and non-spine) defined using the International Classification of Diseases, Tenth Revision codes. The study participants were aged ≥50 years (men, 158 426; women, 131 587). The predicted lean body mass index (pLBMI), appendicular skeletal muscle index (pASMI), and body fat mass index (pBFMI) were used to assess body composition, using anthropometric prediction equations.

RESULTS

Over a 3 year follow-up, we identified 2350 and 6175 fractures in men and women, respectively. The mean age of the participants was 60.2 ± 8.3 and 60.7 ± 8.4 years in men and women, respectively. In a multivariable-adjusted Cox proportional hazards regression model, increasing pLBMI or pASMI was significantly associated with a decreased risk of total fractures in men and women. When comparing individuals in the lowest pLBMI and pASMI (reference groups), men with the highest pLBMI and pASMI had adjusted hazard ratios of 0.63 [95% confidence interval (CI) 0.47-0.83] and 0.62 (95% CI 0.47-0.82), and women with the highest pLBMI and pASMI had adjusted hazard ratios of 0.72 (95% CI 0.60-0.85) and 0.71 (95% CI 0.60-0.85), respectively, for total fractures. The pBFMI had no significant association with total fractures in men or women. Regarding sex-specific or site-specific differences, the protective effects of the pLBMI and pASMI on fractures were greater in men and reduced the risk of spinal fractures. An increased pBFMI was associated with an increased risk of spinal fractures in women.

CONCLUSIONS

An increased pLBMI or pASMI was significantly associated with decreased total osteoporotic fracture risk; however, the pBFMI showed no statistically significant association. Muscle mass was more important than fat mass in preventing future osteoporotic fractures based on anthropometric prediction equations.

摘要

背景

肥胖对骨骼健康具有保护作用,但腹部肥胖与更高的骨折风险相关。由于评估工具方面的实际问题,人们对身体成分是保护还是不利地影响骨质疏松性骨折知之甚少。本研究旨在评估预测身体成分与骨折风险的关联,以确定肌肉或脂肪量对一般人群中骨骼健康结果的独特和不同影响。

方法

本基于人群的纵向队列研究使用了 2009-2010 年韩国国家健康保险服务数据以及 2011 年 1 月 1 日至 2013 年 12 月 31 日的随访数据,使用国际疾病分类,第十次修订版代码确定骨质疏松性骨折(总、脊柱和非脊柱)的发生率。研究参与者年龄≥50 岁(男性 158426 人;女性 131587 人)。使用人体测量预测方程,通过预测瘦体重指数(pLBMI)、四肢骨骼肌指数(pASMI)和体脂肪量指数(pBFMI)来评估身体成分。

结果

在 3 年的随访期间,男性和女性分别确定了 2350 例和 6175 例骨折。参与者的平均年龄分别为男性 60.2±8.3 岁和女性 60.7±8.4 岁。在多变量调整的 Cox 比例风险回归模型中,男性和女性 pLBMI 或 pASMI 的增加与总骨折风险降低显著相关。在比较 pLBMI 和 pASMI 最低的个体(参考组)时,pLBMI 和 pASMI 最高的男性的校正危险比分别为 0.63(95%置信区间 0.47-0.83)和 0.62(95%置信区间 0.47-0.82),pLBMI 和 pASMI 最高的女性的校正危险比分别为 0.72(95%置信区间 0.60-0.85)和 0.71(95%置信区间 0.60-0.85),用于总骨折。pBFMI 与男性或女性的总骨折均无显著相关性。关于性别特异性或部位特异性差异,pLBMI 和 pASMI 对骨折的保护作用在男性中更大,并降低了脊柱骨折的风险。pBFMI 的增加与女性脊柱骨折的风险增加相关。

结论

pLBMI 或 pASMI 的增加与总骨质疏松性骨折风险降低显著相关;然而,pBFMI 无统计学显著关联。基于人体测量预测方程,肌肉量比脂肪量在预防未来骨质疏松性骨折方面更为重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a56c/8718033/29fe4453a4d6/JCSM-12-2247-g005.jpg

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