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尸温相关因素推断死亡时间的研究
引用本文:杨宇雷,马开军,陈新,吴荣奇,费耿,林中圣,施群,肖碧,王黎扬,葛延昌,孟航.尸温相关因素推断死亡时间的研究[J].中国司法鉴定,2012(5):75-78.
作者姓名:杨宇雷  马开军  陈新  吴荣奇  费耿  林中圣  施群  肖碧  王黎扬  葛延昌  孟航
作者单位:上海市公安局物证鉴定中心上海市现场物证重点实验室,上海,200083
基金项目:公安部应用创新计划项目(2008YYCXSHSJ032)
摘    要:目的 统计分析影响尸体温度下降多因素和死亡时间的相关性,探索尸温推断死亡时间的创新应用.方法 建立影响尸体温度(直肠温度)下降相关因素的采集标准,收集实践工作中的157例明确死亡时间真实案例的相关数据,根据实际工作经验结合统计学的基本要求对各因素进行量化评分,利用EXCEL和SPSS软件对数据进行处理,采用多元线性回归的方法统计分析各影响系数同死亡时间的相关性.结果 获得了具有统计学意义的回归方程,Y=25.993+0.04X1+0.172X2+0.88X3+0.047X4+0.373X5+0.347X6-0.766X7,决定系数R2=0.876.结论 该方法为尸温推断死亡时间的创新应用,经测试可用于实际工作.

关 键 词:尸体温度  死亡时间  影响因素  量化评分  多元线性回归

Study on Estimating Postmortem Interval with Factors Related to Body Temperature
YANG Yu-lei,WU Rong-qi,FEI Geng,LIN Zhong-sheng,SHI Qun,XIAO Bi,WANG Li-yang,GE Yah-chang,MENG Hang,MA Kai-jun,CHEN Xin.Study on Estimating Postmortem Interval with Factors Related to Body Temperature[J].Chinese Journal of Forensic Sciences,2012(5):75-78.
Authors:YANG Yu-lei  WU Rong-qi  FEI Geng  LIN Zhong-sheng  SHI Qun  XIAO Bi  WANG Li-yang  GE Yah-chang  MENG Hang  MA Kai-jun  CHEN Xin
Institution:(Shanghai Key Laboratory of Crime Scene Evidence, Institute of Forensic Science, Shanghai Public Security Bureau, Shanghai 200083, China)
Abstract:Objective To statistically analyze the correlation between factors related to body temperature drop and postmortem interval, and to establish an innovative method for estimating postmortem interval by body temperature. Methods The collection standard of the factors influencing body temperature drop was established. Data of 157 cases which had exact postmortem intervals were collected. The related factors were quantitatively scored according to practical experience and basic statistic requirements. The data were processed by EXCEL and SPSS software, and the correlations between the factors and the postmortem intervals were analyzed with multiple linear regression. Results A statistically significant regression equation was obtained: Y = 25.993 + 0.04X1 + 0.172X2 + 0.88X3 +0.047X4+0.373X5+0.347X6-0.766X7. The correlation coefficient R2 was 0.876. Conclusion The study presented an innovation application of body temperature for estimating postmortem interval, which had been tested in the practical work.
Keywords:body temperature  postmortem interval  related factor  quantitative score  multiple linear regression
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