摘要
【目的】研究不同中医体质类型与骨质疏松症之间的关系，为调护中医体质防治骨质疏松症提供依据。【方法】采用病例对照研究设计，病例组和对照组各401例样本来源于中医体质与健康状况调查数据库。9种中医体质类型判定基于中医体质量表得分，骨质疏松症为自我报告。多元Logistic回归分析的方法使用于分析中医体质类型与骨质疏松症的关系。【结果】以平和质为参照，5种偏颇体质为骨质疏松症的危险因素，其相对危险度比值比（OR）和95％的可信区间（CI）分别为：气虚质（OR：2．3，95％CI：1．5-3．4）、阳虚质（OR：2．1，95％CI：1．3～3．3）、阴虚质（OR：2．1，95％CI：1．2-3．5）、湿热质（OR：2．5，95％CI：1．3-4．5）和血瘀质（OR：2．8，95％CI：1．7—4．5）。【结论】中医体质类型与骨质疏松症之间存在着一定的关联性，应积极调整偏颇体质，降低骨质疏松症发生的风险。
[Objective] To examine the relationship between constitutional types of TCM and osteoporosis to provide the basis for the prevention and treatment of osteoporosis. [Methods] Using case-controlled study resign, the cases were selected from a cross-sectional survey on the TCM constitution and health survey database. The 401 patients with osteoporosis were taken as the case group, and 401 cases were randomly selected from healthy subjects as the comparison group. Standardized constitution in Chinese medicine questionnaire （CCMQ） was used to judge the individual constitutional types, while patients with osteoporosis were self-reported by the participants. A multiple logistic regression analysis was applied in the analysis of TCM constitution risk factors of osteoporosis. [Results] Compared with gentleness type, the occurrence risk of osteoporosis increased significantly in the next five pathological constitution types： OR： 2.3, 95%CI： 1.5-3.4 in patients with Qi deficiency, OR： 2.1, 95%CI： 1.3-3.3 with Yang deficiency, OR： 2.1, 95%CI： 1.2-3.5 with Yin deficiency, OR： 2.5, 95%CI： 1.3-4.5 with Wet heat and OR： 2.8, 95%CI： 1.7-4.5 with blood stasis. [Conclusion] Some relevance was existed between TCM constitutional types and osteoporosis, and the pathological constitution should be actively adjusted for reducing the developing risk of osteoporosis.
出处
《天津中医药》
CAS
2014年第2期71-74,共4页
Tianjin Journal of Traditional Chinese Medicine
基金
国家重点基础研究发展计划(973计划)资助项目(2011CB505403)
科技部基础性工作专项资助项目(2013 FY114400-5)
关键词
中医体质量表
血瘀质
骨质疏松症
病例对照研究
LOGISTIC回归分析
constitution in Chinese medicine questionnaire
blood stasis constitution
osteoporosis
case control study
Logistic regression analysis
