Page 49 - 2022-22-中国全科医学

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OSO based on inter-correlations of its diagnostic variables and exploring its structural properties may offer insights into clinical
prevention and treatment of OSO. Objective To explore the structural properties of OSO，providing a theoretical basis for
individualized diagnosis and treatment of the disease. Methods A cross-sectional study was conducted with a random sample
of OSO patients（ ≥ 60 years old）who underwent physical examination in Physical Examination Center，the 2nd Affiliated
Hospital of Harbin Medical University from January 2018 to December 2020. The data collected include 9 diagnostic variables
for OSO〔skeletal muscle index，grip strength，body fat percentage，BMD of the lumbar spine（L1-L4），hip and femoral
neck，BMI，waist circumference，walking pace〕，sociodemographic characteristics，lifestyle and prevalence of common
chronic diseases. KMO test and Bartlett's test of sphericity were used to evaluate the suitability of diagnostic variables for factor
analysis. The components with an eigenvalue equal to or greater than 1.000 were extracted by principal component analysis，and
the varimax orthogonal rotation matrix was obtained by the varimax orthogonal rotation method. The common factors were named
according to the orthogonal rotation matrix of factors. On the basis of factor analysis，thesum of squares and systematic cluster
analysis were used to develop a dendrogram for classifying patients. The structural properties of OSO were analyzed by comparing
the values of diagnostic variables and clinical features among patients of different categories. Results A total of 107 cases were
2
included. The KMO value（0.688）and the result of Bartlett's test of sphericity（χ =492.374，P<0.001）indicated that the data
of diagnostic variables were suitable for factor analysis. Three common factors（osteoporosis factor，muscle + body fat factor and
obesity factor）with an eigenvalue greater than 1.000 were extracted，explaining 81.408% variance of the total. The load value
of each diagnostic variable on its common factor ranged from 0.770 to 0.918. The patients were divided into 3 categoriesby cluster
analysis using the common factors. The skeletal muscle index，grip strength，body fat percentage，BMD of L1-L4，hip and
femoral neck，BMI and waist circumference varied significantly across patients of different categories（P<0.05）. The values
of BMD of L1-L4，hip and femoral neck of OSO patients in the first category were significantly lower than those of the other two
categories（P<0.05）. The BMI and waist circumference values of OSO patients in the second category were lower than those of
the other two categories（P<0.05）. OSO patients in the third category had higher values of skeletal muscle index，grip strength
and BMD of L1-L4，hip and femoral neck，but lower body fat percentage than those of the other two categories（P<0.05）.
There were statistically significant differences in sex ratio，distribution of education level and total cholesterol（TC），high-
density lipoprotein cholesterol（HDL-C），uric acidand creatinine in the serum among different categories of patients（P<0.05）.
OSO patients in the first category had higher prevalence of below the undergraduate education level than those in the third
category（P<0.017）. OSO patients in the second category had higher level of TC than those in the third category（P<0.05）. In
comparison with those in other two categories，OSO patients in the third category had higher personal monthly income equal to or
greater than 5 000 yuan，and lower female ratio（P<0.017）. Moreover，OSO patients in the third category also demonstrated
higher levels of uric acid and creatinine in the serum（P<0.05）. Conclusion OSO diagnostic variables can be generalized and
interpreted in terms of osteoporosis，muscle and body fat，and obesity. And OSO patients have different structural properties. The
application of multivariate statistical methods to study the structural properties of OSO patients will contribute to the individualized
management of such patients.
【Key words】 Osteosarcopenic obesity；Factor analysis；Cluster analysis；Multivariate statistical analysis

骨量肌量减少性肥胖综合征（OSO）是指机体出现 肌少症和肥胖作为独立疾病来研究，否则会造成患者的
骨量减少、肌肉量下降、肌肉功能减低，同时伴随着脂 骨折风险被低估。此外，一项针对癌症患者的研究结果
肪组织增加的一种综合征，即骨质疏松、肌少症和肥胖 显示，伴有 OSO 的癌症患者患骨性关节炎，以及发生
3 种疾病共存于同一个体。骨质疏松、肌少症和肥胖是 跌倒、失能的风险明显高于单纯合并肌少症、肥胖或肌
［8］
多因素疾病，三种疾病有共同的病因、发病机制和危险 肉减少性肥胖症的癌症患者，并且生存时间明显缩短 。
因素 ［1-5］ 。澳大利亚一项对≥ 70 岁社区男性居民的前 由此可见，骨质疏松、肌少症和肥胖三种疾病可相互作
瞻性研究发现，合并肥胖的男性肌少症患者两年内跌倒 用，进而加速 OSO 的进展 ［8］ 。
和骨折的发生率均高于健康男性 ［6］ 。另一项平均随访 作为一种严重影响老年人健康和生活质量的疾病，
时间长达 10.7 年的研究报道，合并肌少症的男性肥胖 OSO 的临床研究尚处于初期阶段。现有研究主要将 OSO
患者与单纯性肥胖男性相比，腰椎骨密度（BMD）和全 作为一种单一疾病来研究，在诊断 OSO 患者时要求患
身 BMD 更低，较健康男性非椎体骨折发生率更高；而 者符合三种疾病诊断标准，多将诊断变量视为相对独立
在女性群体中，肌少症合并肥胖患者全髋 BMD 比单纯 的变量 ［9-11］ ，忽略了诊断变量间的联系、三种疾病间
性肥胖患者低，且骨折发生率高 ［7］ 。因此，研究者提 的相互作用及不同疾病在 OSO 发展中发挥的作用可能
出应将三种疾病综合起来进行分析，不能把骨质疏松、 不尽相同。相较于相对割裂地看待肌少症、骨质疏松和