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中华临床医师杂志(电子版) ›› 2019, Vol. 13 ›› Issue (02) : 95 -100. doi: 10.3877/cma.j.issn.1674-0785.2019.02.003

所属专题: 全科医学 文献

临床研究

聚类判别法分析社区健康老年人人体测量指标与血液生化指标的关系
郑庆虎1, 顾陈红1, 孙冬梅1,()   
  1. 1. 200129 上海市浦东新区浦兴社区卫生服务中心全科
  • 收稿日期:2018-04-13 出版日期:2019-01-15
  • 通信作者: 孙冬梅
  • 基金资助:
    上海市卫生和计划生育委员会基金资助项目(201440464); 上海市浦东新区卫计委基金资助项目(PWZqt2017-09); 上海市浦东新区科技发展基金民生科研专项资金资助项目(PKJ2017-Y63)

Cluster discriminant analysis of relationship between physical examination parameters and blood biochemical indexes in elderly people

Qinghu Zheng1, Chenhong Gu1, Dongmei Sun1,()   

  1. 1. Department of General Practice, Puxing Community Health Service in Pudong New District, Shanghai 200129, China
  • Received:2018-04-13 Published:2019-01-15
  • Corresponding author: Dongmei Sun
  • About author:
    Corresponding author: Sun Dongmei, Email:
引用本文:

郑庆虎, 顾陈红, 孙冬梅. 聚类判别法分析社区健康老年人人体测量指标与血液生化指标的关系[J]. 中华临床医师杂志(电子版), 2019, 13(02): 95-100.

Qinghu Zheng, Chenhong Gu, Dongmei Sun. Cluster discriminant analysis of relationship between physical examination parameters and blood biochemical indexes in elderly people[J]. Chinese Journal of Clinicians(Electronic Edition), 2019, 13(02): 95-100.

目的

用聚类判别法探讨社区健康老年人无创的人体测量参数与实验室检查结果的关系,并建立判别函数。

方法

整群随机抽取浦东新区浦兴街道的11个社区居民委员会,调查65岁以上居民,横断面调查体质量、血压、血糖、血脂等,排除既往患高血压、糖尿病、冠心病及此次实验室检查肝肾功能不全者。选择年龄、收缩压、舒张压、体质量指数共4个变量进行R型聚类分析,建立判别函数。采用方差分析比较各类老年人人体测量指标及血液生化指标的差异。

结果

共聚为3类。3类人群中,第1类人群年龄最小,无创的肥胖指标及血压最高,同时实验室检测的血糖、血脂、肝功能指标亦最高,经LSD多重比较,除收缩压、空腹血糖的第1类与第2类比较以及胆红素各类差异无统计学意义外,其余参数第1类与其他类比较差异均具有统计学意义(P均<0.0125)。回顾法及交叉验证法两种方法估计判别函数的误判概率,均小于0.2。

结论

对社区健康老年人,可以用无创的人体测量参数预估实验室检查中血糖、血脂以及肝功能等生化指标。

Objective

To investigate the relationship between noninvasive anthropometric parameters and laboratory test results from community healthy elderly people by cluster analysis and generate the discriminant equations.

Methods

Eleven communities were randomly selected from Pudong New District, Shanghai, China. Individuals aged 65 years and above from the communities were recruited. Body mass, blood pressure, blood cholesterol, and glucose were collected. However, individuals with following conditions were excluded: confirmed high blood pressure, diabetes mellitus, coronary heart disease, and hepatic and renal dysfunction. Four variables were selected to perform cluster analysis and establish discriminant function, which included age, systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI). Comparison of anthropometric and blood biochemical indexes of all kinds of elderly people by analysis of variance.

Results

Three subgroups were distinguished. Individuals in cluster 1 were youngest with the highest noninvasive parameters including blood pressure and BMI and highest laboratory test results consisting of blood cholesterol and glucose and hepatic function parameters. The results of multiple comparisons using the Fisher′s least significant difference (LSD) procedure showed that there was no statistical difference in SBP or fasting glucose between cluster 1 and cluster 2, and that there was no statistical difference in bilirubin among the three clusters. However, differences in the other parameters and results were statistically significant (P<0.0125). The error rates of discriminant functions established by both retrospective method and cross validation method were less than 0.2.

Conclusion

Non-invasive anthropometric indexes can be used to estimate the biochemical indexes such as blood glucose, blood lipid and liver function in healthy elderly people in the community.

表1 不同性别老年人基本临床资料比较
表2 聚类变量组内相关性
表3 3类老年人年龄、BMI、腰围、颈围、血压、血糖、血脂、肝功能比较(±s
表4 3类老年人年龄、BMI、腰围、颈围、血压、血糖、血脂、肝功能LSD多重比较
表5 3类老年人肥胖率、血压、血糖、血脂升高率比较[例(%)]
表6 Bayes法的线性判别式函数系数
表7 判别效果评价[例(%)]
图1 聚类为3类的判别函数示意图
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