期刊论文详细信息
International Journal of Biomedical and Advance Research
“A study to correlate the stature with the length of ulna in living humans in various age groups”
savita hemant gadekar1 
关键词: ulna;    multiplication factor;    regression equation;   
DOI  :  10.7439/ijbar.v3i12.880
学科分类:药学、药理学、毒理学(综合)
来源: Scholar Science Journals
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【 摘 要 】

Absract Aim -The purpose of the study was to establish the correlation between length of ulna with height of a person in various age groups and in both sexes. The study also intended to compare the two basic parameters used globally for such correlations, namely multiplication factor (M.F.) and regression equation; and try to comment on the efficacy of one formula over the other.Introduction-Height of an individual has evoked great interest since ancient time. The subject as a whole has been dealt with in different ways to predict the human stature.In ancient times, physicians & surgeons likeCharak & Sushruta1were well acquainted with the relation of different parts of body with height. According to Charak, the height of an average man should be 84 -anguls, thigh-21 anguls, forearm -15 anguls & arm-16 anguls. Dwarfism and gigantism, both resulting from hormonal dysfunction, are examples of variations in normal body height.Method & material -In the present study 504 individuals were studied. Study ranged across the age groups from 8 years to 22 years. Equal participation of males and females was ensured. Thus, 252 males (50%) and 252 females (50%) were included in the study.Observation ? On an average the M.F. for male is between 6.05 ?6.76 for right ulna and 6.08-6.79 for left ulna.Discussion-It was observed that height estimation using M.F. is much simpler, easy and less time consuming; yet enough efficient; as compared to using regression equation. ?Coclusions- 1-M.F. is more applicable in medico-legal cases where one may be confronted with a single or fragmented bone, and person?? height needs to be ascertained. 2- Regression equation is applicable in sample study of large population. ?Key words: ulna, multiplication factor, regression equation

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