中国黄种人与白种人脑颅骨特征差异初探

目的建立利用脑颅骨特征推断黄种人和白种人种族的判别方程,并评价其法医学意义。方法收集141例成年人脑颅骨样本,其中黄种人60例,白种人81例。选取脑颅骨10项特征指标,对125例样本进行测量,运用SPSS16.0软件对指标数据进行t检验和Fisher判别分析,建立判别方程。并使用16例样本对方程的判别正确率进行盲测。结果本文选择的10项脑颅骨特征指标变量均具有显著性种族差异(P0.05);建立了5组单项指标和4组多项指标进行种族推断的判别方程,综合判别率为74.4%~94.4%;随机选取16例样本的盲测结果,正确率为81.3%~100%。结论脑颅骨具有种族差异性,本文建立的判别方程可在黄种人和白种人的种族推断中选用。     

面颅的种族差异性研究

目的探索面颅在中国黄种人与欧洲白种人种族鉴定方面的差异性。方法通过对150例中国黄种人和欧洲白种人样本(各75例)面颅骨的观测、分析,选取与种族变化关系密切的51项观测指标进行观测,使用SPSS16.0软件对观测数据逐级进行统计学分析、处理,建立判别方程。从研究样本外随机抽取白种人和黄种人各10例标本进行盲测。结果筛选出7项测量结果相对稳定、种族差异较大指标建立全指标、逐步和多指标判别函数方程共5对,综合判别率在73.2%~89.8%。盲测正确率在75%~95%,结果令人满意,说明判别方程稳定、可靠,对种族鉴别的应用性较好。结论本研究所建立的种族判别方程可应用于中国黄种人与欧洲白种人的种族鉴定。     

利用下颌骨进行种族判定的初步研究

目的探讨下颌骨在种族差异性方面的应用价值。方法选取18个常规测量项进行测量,将测量数据输入计算机,使用SPSS统计软件进行两独立样本T检验和Fisher判别分析。结果使用6个种族之间的差异性有统计学意义(P<0.05)的指标建立了6组全指标、逐步和多指标判别方程。结论下颌骨的种族差异性可为种族判别提供借鉴。     

枢椎种族差异的初步研究

目的探讨枢椎椎骨在种族间是否存在差异。方法对黄种人已知确切性别的33例枢椎椎骨进行研究,测量枢椎椎骨的8项指标,所得数据与白种人进行比对。结果8项指标中,其中6项指标在男性种族间存在显著的种族差异、3项指标在女性种族间存在显著的种族差异。结论枢椎椎骨在种族方面存在一定差异,可以进行进一步的深入研究,本文对骨骼种族方面的鉴定研究有一定的借鉴意义。     

中国汉族人颅骨数字模型的性别判别方法

目的利用步进Fisher法建立多元性别判别函数,对西安地区成年人颅骨进行性别判别。方法从颅面数据库中选择西安地区133个（73男,60女）三维颅骨模型,利用计算机软件测量并统计颅骨的12项几何测量指标和2项角度测量指标,利用步进Fisher方法建立多元性别判别函数,并对方程进行回代检验。结果男性的12项几何测量指标均值大于女性,女性的2项角度测量指标均值大于男性,除2项指标（X7和X14）外,其他指标均存在显著性差异（P〈0.01）。由4项指标建立的判别方程,判别率男性为87.5%,女性为86.67%。结论利用计算机软件可以实现完整颅骨和无下颌的颅骨的性别判别。     

现代人面颅角度测量的种族差异性

目的探索面颅角度指标在种族鉴定方面的差异性。方法选取现代人头骨57例,其中中国黄种人头骨30例（女性9例,男性21例）,包括吉林1例,河北5例,山东4例,青海4例,安徽4例,江西3例,云南3例,贵州3例,广西3例。欧洲自种人头骨27例,性别不详,取自欧洲Zellemdorf、Vresovice、Kysperka3地。按体质人类学测量方法,通过参考相关文献和对颅骨形态特点的观察,设计面颅左侧眶角、右侧眶角、鼻颌角3个角度指标进行测量。对测量数据进行描述性统计分析和两独立样本之间的t检验。结果3个角度指标在种族差异性方面,眶角的种族差异性具有显著统计学意义（P〈0．01）,而鼻颌角之间的种族差异性无统计学意义（P〉0．05）。结论有些角度指标显示出明显的种族差异性,今后需要加强此方面的研究。     

利用中国汉族成年人胸部正位CR片影像学特征判定年龄

目的建立利用胸部正位CR片影像学变化判定年龄的方程,并评价其法医学意义。方法收集381例汉族成年人胸部正位CR片样本,其中男性208例,女性173例。选取胸部右侧第一肋胸骨端、左侧第一肋胸骨端、右侧第五肋胸骨端、左侧锁骨骨小梁和左侧锁骨松质骨网眼5项特征性指标,对351例样本进行描述评分,运用SPSS 19.0软件进行多元线性回归模型条件的基本论证,建立回归方程。并使用30例样本对方程的准确性进行盲测。结果本文所选取的5项胸部正位CR片特征性指标与年龄的关系可以使用线性回归模型(P0.05);建立了1组全指标回归方程和2组分组逐步回归方程,全指标回归方程估计值的标准误男性和女性分别为2.83岁和3.41岁,低年龄组(18~35岁)男性和女性分别为2.47岁和2.79岁,高年龄组(36~50岁)男性和女性分别为2.39岁和2.55岁;随机选取30例样本的盲测结果,误差在3岁以内的,全指标回归方程男性和女性分别为80.0%和73.3%,分组回归方程男性和女性分别为86.7%和80.0%。结论利用胸部正位CR片影像学特征变化可判定年龄。     

西南地区成人面颅骨的性别判定

目的建立适合西南地区成人的颅骨性别判定函数。方法性别明确的颅骨67个,测量颅骨最大长、颅骨最大宽、颅高等16项指标,所得数据进行统计学分析,建立单一变量及多变量性别判定方程,并对5个无名颅骨进行回带检验。结果 16项指标中有13项存在显著的性别差异,男性大于女性,单变量函数推断性别以鼻高(男78.4%,女83.3%)、颅骨最大长(男83.8%,女73.3%)准确率较高。多变量性别判定函数以颅周长、鼻高贡献最大,判定准确率男89.2%,女90.0%。结论单变量推断颅骨性别以鼻高或颅骨最大长较为理想,但以颅周长、鼻高联合推断性别准确率更高。     

根据骨盆CT片特征指标进行同一认定的研究

目的选择骨盆CT片上的特征指标,建立逐步回归方程,探讨其在法医学同一认定中的应用价值。方法收集160名不同被检查者骨盆CT影像片各1张,70名被检查者不同次骨盆CT影像片各2张。选择并测量骨盆CT片上的14项指标值,分别计算不同人随机分组相同测量指标的组间的差值,以及相同人不同次测量指标间的差值,运用二分类logistic逐步回归分析,建立各项指标的一元回归方程和多项指标的多元回归方程,并对方程进行盲测检验。结果建立的14个一元方程中同一认定的正确率在61.1%(骶骨耳状面后缘宽)~80.5%(第一骶椎平面左右髂骨前端间距)之间;建立的6个多元回归方程的正确率在80.5%~93.8%之间。盲测准确率为100%。结论本文在CT片上选择的14项特征指标可以用于同一认定,在使用时应尽可能选用多元指标以得到更准确的结果。     

马和人股骨碎片组织形态学结构特征及其鉴别

目的研究成体马和成年人的股骨组织形态学结构,分析其组织学特征,建立人与马之间的种属鉴别方法。方法取来源于尸体检验的成人右股骨中段约4cm,同时收集马的右腿股骨,取中段约4cm,脱钙后制作成厚约25μm的骨组织切片,在光学显微镜下观察,将显微镜下的图像录入电脑,选取25项指标进行逐步判别分析。结果马和人在哈氏系统数量、哈氏系统直径等13个指标上具有显著差异,用这些指标建立种属判别数学模型,经盲测检验,二者的判别率可达99.6%。结论马和人的股骨组织学结构具有明显的种属特征,建立的判别方程可以有效地鉴别马和人的股骨碎片。     

Morphological variation in cervical spinous processes: potential applications in the forensic identification of race from the skeleton.

Determination of race (ancestry) is an important step in the identification of individuals in forensic cases. Race is most commonly assessed using cranial traits. Few reliable postcranial indicators are known. In this study, the frequency of bifidity of cervical spinous processes at different vertebral levels was examined in a sample of 359 Americans of African (black) and European (white) descent. The sample was selected from the Hamann-Todd collection, a large modern anatomical collection of known sex and race. Spinous processes were classified as "bifid," "partially bifid," or "nonbifid" based on previously defined criteria. Sex and race were kept entirely unknown to the classifier (S.M.D.) during data collection. Data were analyzed using Chi-square and logistic regression analysis. At C2, most individuals (91%) had bifid spinous processes. At C7, nearly all (98%) had nonbifid spinous processes. Significant differences between race/sex subgroups were found at C3-C6. At each of these levels, whites showed a higher frequency of bifidity than blacks and males a higher frequency of bifidity than females. Differences between races were greater than differences within races. Logistic regression analysis revealed C3 and C4 to be the most useful levels for identifying race. Based on these levels, 76.05% of a validation subsample was correctly classified by race (80.25% for whites, 72.09% for blacks). Pending further study, morphology of the cervical spinous processes may provide an additional method for the determination of race in skeletal forensic cases.     

Determination of sex by discriminant function analysis of postcranial skeletal measurements

Thieme and Schull [16] took measurements of seven postcranial traits from black skeletons of known sex to devise a method for accurately sexing human remains. With a linear discriminant function analysis of the data they obtained a 98.5% accuracy. The research reported here was designed to assess the accuracy of their method in the hands of other investigators using a sample of the same black population and its applicability to other populations of the same and different races. None of the samples used in this study were sexed with the same rate of accuracy either achieved or predicted by Thieme and Schull. However, two samples did reach 91% or better. Such results suggest that the methods employed have considerable value if used with appropriate precautions. Our multiple discriminant function analysis strongly indicates that neither side nor observer techniques affected the results. Sex accounts for a predominant fraction of the total variation among samples and race accounts for most of that remaining.     

A new method for discriminating African-American from European-American skeletons using postcranial osteometrics reflective of body shape.

A discriminant function analysis based on seven postcranial measurements for the metric assessment of race is presented. A sample from the Terry Collection (NMNH) was used to create independent functions for African-American males and females, and European-American males and females. The functions were tested using known forensic cases from the Maxwell Museum of Anthropology and the C.A. Pound Human Identification Laboratory. Based on the Terry Collection sample, correct classification of race for males was 87.0%, and for females 100.0%. For the independent test population, correct classification for males was 81.8%, and for females only 57.1%. The low classification for females is most likely due to sample bias.     

Metric analysis of sex differences in South African black and white pelves

Sex determination of unknown skeletal material is one of the most vital determinations made by forensic anthropologists. Numerous studies have focussed on the differences, both osteometric and morphological, between the sexes of a particular racial phenotype and population. Previous work by a variety of researchers has underscored the necessity of population specific standards. The purpose of this research is to metrically assess sex differences in the pelvis of South African whites and blacks and develop standards tailored to these groups. Data were collected from 400 known sex/race skeletons from the Pretoria and Dart Collections. Nine measurements (traditional and newly developed) were taken and subjected to SPSS stepwise and direct discriminant analysis. Results indicated that there are significant differences (p < or = 0.001) between the sexes of both races for most measurements. Discriminant function analysis selected ischial length as the most sexually dimorphic dimension in whites (averaged 86% accuracy), while acetabulum diameter was most diagnostic in blacks (averaged 84% accuracy). Six functions were developed from the pelvic dimensions. Highest accuracy was achieved from Function 1 (including all dimensions) which averaged 95.5% correct classification in whites and 94% in blacks. Functions based on selected parts of the pelvis were not as effective and ranged from 73-86% in whites and 72-84% in blacks. This research provided evidence of the significant sex differences that exist between the pelves of South African whites and blacks whilst measurements used here for discriminant function analysis gave classifications with high accuracies. These results can be used to aid in the identification of human skeletal remains in South Africa.     

Ancestry Estimation Using Cranial and Postcranial Macromorphoscopic Traits

Ancestry estimation methods using macromorphoscopic (MMS) traits commonly focus exclusively on cranial morphology. The objective of this study was to demonstrate the value of postcranial MMS traits, highlighting a combined cranial/postcranial trait approach to ancestry estimation using quadratic discriminant function and a variety of machine learning classification models including artificial neural networks (aNN), random forest models, and support vector machine. Eight cranial and eleven postcranial MMS traits were collected from the Terry and Bass Skeletal Collections (American Black = 81; American White = 173). Our classification models using cranial and postcranial traits correctly classified 88–92% of the sample, improving classification accuracies by nearly fifteen percent over models relying exclusively on cranial data. These same results demonstrate the importance of a multivariate statistical framework incorporating cranial and postcranial data and the nearly unlimited potential of machine learning models to improve the accuracy of ancestry estimates over traditional methods of analysis. To facilitate implementation in casework, one of the more robust models (aNN) is incorporated into a web-based application, ComboMaMD Analytical, to facilitate cranial and postcranial MMS traits analysis for ancestry estimation.     

A reevaluation of the sex prediction accuracy of the minimum supero-inferior femoral neck diameter for modern individuals

The results of an independent test of the minimum supero-inferior femoral neck diameter as a sex predictor are presented. Seidemann et al. (1) generated discriminant functions for Caucasians, African-Americans, and a combined race sample from the Hamann-Todd skeletal collection. Jackknifed classification matrices and the use of independent, random validation samples indicated a sex prediction accuracy in the 90% range. This, combined with a high rate of preservation, makes the femoral neck a significant measure for forensic applications. However, the method has not been evaluated on a truly modern sample. Data were collected for 94 males and 49 females from the Documented Collection at the University of New Mexico. The sample consists of 94 Caucasians, 33 African Americans, three modern Native Americans, two Hispanics, and 11 individuals of unknown ancestry. All individuals were born after the turn of the century. We evaluate the accuracy of the discriminant functions generated from the Hamann-Todd control sample. For Caucasians, 83% were correctly classified, for African Americans 97% were correctly classified and for the combined race function 85% were correctly classified. This decrease in accuracy is the result of the increase in African American male and all female sample means. This effectively decreases the separation between males and females for the femoral neck diameter. We generate new discriminant functions from the modern data and jackknife the classification matrices. The Caucasian function was 84% accurate, the African-American function was 82% accurate and the combined sample function was 85% accurate. The femoral neck may provide a useful alternative to multivariate techniques for individuals who are poorly preserved.     

Further evidence to show population specificity of discriminant function equations for sex determination using the talus of South African blacks

Several studies have shown that osteometric differences exist between different population groups. Thus, discriminant function equations derived for the determination of sex from skeletal elements are population specific. In a previous study, the authors derived such equations from nine measurements of the talus of South African whites with high levels of average accuracies. The validity of some of the equations was tested on data collected from a South African black sample that consisted of 120 tali, equally distributed by sex, derived from the Raymond A. Dart Collection of Human Skeletons. The average accuracies dropped significantly. This necessitated the derivation of new equations for the South African black population and the average accuracies obtained ranged between 80% and 89%. The validity of the equations derived from the present study was tested using the leave-one-out classification and two independent samples (1 and 2). The applicability of the equations with very high classification rate from the present study was tested on Independent sample 1 of 10 white tali with poor results. The result of the validity of these equations on an Independent sample 2 of 10 black tali revealed acceptably high average accuracies in correct classification thereby supporting earlier observations on population specificity of discriminant function equations.     

Metric assessment of race from the pelvis in South Africans

It is well known that there are measurable differences between whites and blacks in the size and proportions of skeletal components. There are also metric differences among populations within these racial phenotypes. The population specific quantification of this variation can be used to aid in the identification of racial affinity in the absence of a more racially definitive skeletal element like the skull. Therefore, the purpose of this research is to quantify these differences in the pelvis of South African whites and blacks. A sample of 400, ostensibly healthy known sex/race os coxae was examined. Skeletal material was obtained from the Pretoria and Dart collections. A series of 13 measurements were taken Data were subjected to SPSS stepwise and direct discriminant function analysis. Pubic length was chosen as best for discriminating between races for males and iliac breadth as best in females. Highest average accuracies (Function 1) were 88% for males (pubic length, greater sciatic notch posterior width, acetabulum diameter, total height) and 85% for females (pubic length, greater sciatic notch posterior width, acetabulum diameter, iliac breath). In conclusion, this research resulted in the development of standards of identification tailored to this population and unquestionably demonstrates that race differences in the skeleton are highly significant and must be considered in all skeletal analyses.