北京社区老年男性衰弱现状及其影响因素  

Frailty status of elderly men in Beijing communities and its influencing factors

作　　者：徐率轩 王芳 曹梦宇[2,3] 刘金炜 马爽 陈超 陈蔚 张倪惠[2,3,4] 康靖汶 彭楠[2,3] XU Shuai-Xuan;WANG Fang;CAO Meng-Yu;LIU Jin-Wei;MA Shuang;CHEN Chao;CHEN Wei;ZHANG Ni-Hui;KANG Jing-Wen;PENG Nan(Institute of Psychiatry and Neuroscience,Xinxiang Medical University,Xinxiang 453000,Henan Province,China;Department of Rehabilitation Medicine,Second Medical Center,Chinese PLA General Hospital,Beijing 100853,China;National Clinical Research Center for Geriatric Diseases,Chinese PLA General Hospital,Beijing 100853,China;Medical School of Chinese PLA,Beijing 100853,China)

机构地区：[1]新乡医学院精神神经医学研究院,河南新乡453000 [2]中国人民解放军总医院第二医学中心康复医学科,北京100853 [3]中国人民解放军总医院国家老年疾病临床医学研究中心,北京100853 [4]解放军医学院,北京100853

出　　处：《中华老年多器官疾病杂志》2022年第12期918-922,共5页Chinese Journal of Multiple Organ Diseases in the Elderly

基　　金：国家重点研发计划(2018YFC2002004)。

摘　　要：目的分析慢病、躯体功能、骨骼肌质量、脂肪等因素对老年男性衰弱患者的影响。方法2021年4月至6月,共纳入北京市社区658名≥60岁老年男性为研究对象。采用Fried衰弱表型(FP)诊断是否衰弱,衰弱期或衰弱前期老年人纳入衰弱组(n=124),其余为非衰弱组(n=534)。采用Charlson共病指数(CCI)评估慢病患病情况。测试躯体功能并采用人体成分分析仪分析骨骼肌、脂肪等体成分。采用SPSS 26.0统计软件进行数据分析。根据数据类型分别采用t检验、Mann-Whitney U检验或χ2检验进行组间比较。应用logistic回归分析衰弱的影响因素。结果单因素分析结果显示,衰弱组与非衰弱组患者年龄、身高、体质量、骨骼肌质量指数、体脂肪量、内脏脂肪面积、基础代谢率、蛋白质、骨矿物质含量、握力、步速及5次起坐时间情况比较,差异均有统计学意义(P<0.05)。衰弱组CCI较非衰弱组明显增高,其中高血压、冠心病、糖尿病、低骨量、前列腺增生、慢性支气管炎、慢性肾病患者比例较高,差异均有统计学意义(P<0.05)。校正年龄、身高、体质量后,多因素logistic回归分析结果显示,CCI(OR=1.256,95%CI 1.012~1.558,P=0.039)、低骨量(OR=2.312,95%CI 1.308~4.088,P=0.004)和5次起坐时间(OR=1.110,95%CI 1.022~1.205,P=0.013)是衰弱的独立影响因素。结论CCI增高、低骨量和5次起坐时间延长与衰弱的发生密切相关。Objective To analyze the effects of chronic diseases, physical function, skeletal muscle index, fat and other factors on elderly male patients with frailty. Methods From April to June 2021, a total of 658 men aged ≥60 years in Beijing communities were enrolled. They were divided into frail group(n=124) and non-frail group(n=534) based on the evaluation with Fried frailty phenotype(FP) scale. Charlson comorbidity index(CCI) was used to assess the chronic diseases. Physical functions were tested, skeletal muscle index, fat mass, and other body compositions were measured with the body composition analyzer. SPSS statistics 26.0 was used for data analysis. Depending on data type, t-test, Mann-Whitney U test and χ^(2) test were performed for comparison between groups. Logistic regression analysis was used to analyze the influencing factors of frailty. Results Univariate analysis showed that frail and non-frail groups differed statistically significantly in age, height, body mass, skeletal muscle index, body fat mass, visceral fat area, basal metabolic rate, protein, bone mineral content, grip strength, walking speed and 5-time chair stand time(P<0.05). CCI of the frail group was significantly higher than that of the non-frail group, and the former showed a higher proportion of hypertension, coronary heart disease, diabetes mellitus, low bone mass, prostatic hyperplasia, chronic bronchitis and chronic renal disease than the latter, the difference being statistically significant(P<0.05). Multivariate logistic regression analysis showed that, after adjusting for age, height and body mass, CCI(OR=1.256, 95%CI 1.012-1.558, P=0.039), low bone mass(OR=2.312, 95%CI 1.308-4.088, P=0.004), and 5-time chair stand time(OR=1.110, 95%CI 1.022-1.205, P=0.013) were independent influencing factors for frailty. Conclusion Increased CCI, low bone mass, and long 5-time chair stand time are strongly associated with frailty.

关 键 词：衰弱 共病指数 低骨量 影响因素 

分 类 号：R592[医药卫生—老年医学]