Department of Anatomy, Faculty of Health Sciences, University of Pretoria, Private Bag X323, Arcadia, 0007, South Africa.
Department of Anthropology, University of Tennessee, Knoxville, TN, USA.
Int J Legal Med. 2024 Nov;138(6):2635-2646. doi: 10.1007/s00414-024-03283-3. Epub 2024 Jul 10.
Continual re-evaluation of standards for forensic anthropological analyses are necessary, particularly as new methods are explored or as populations change. Indian South Africans are not a new addition to the South African population; however, a paucity of skeletal material is available for analysis from medical school collections, which has resulted in a lack of information on the sexual dimorphism in the crania. For comparable data, computed tomography scans of modern Black, Coloured and White South Africans were included in addition to Indian South Africans. Four cranial morphoscopic traits, were assessed on 408 modern South Africans (equal sex and population distribution). Frequencies, Chi-squared tests, binary logistic regression and random forest modelling were used to assess the data. Males were more robust than females for all populations, while White South African males were the most robust, and Black South African females were the most gracile. Population differences were noted among most groups for at least two variables, necessitating the creation of populations-specific binary logistic regression equations. Only White and Coloured South Africans were not significantly different. Indian South Africans obtained the highest correct classifications for binary logistic regression (94.1%) and random forest modelling (95.7%) and Coloured South Africans had the lowest correct classifications (88.8% and 88.0%, respectively). This study provides a description of the patterns of sexual dimorphism in four cranial morphoscopic traits in the current South African population, as well as binary logistic regression functions for sex estimation of Black, Coloured, Indian and White South Africans.
需要不断重新评估法医人类学分析的标准,特别是在探索新方法或人口发生变化时。印度南非人并不是南非人口的新增加;然而,医学院收藏的骨骼材料很少可用于分析,这导致了颅骨性别二态性的信息缺乏。为了获得可比数据,除了印度南非人外,还纳入了现代黑人、有色人和白人南非人的计算机断层扫描。评估了 408 名现代南非人(性别和人口分布均等)的 4 个头骨形态特征。使用频率、卡方检验、二元逻辑回归和随机森林模型来评估数据。所有人群中,男性的体格都比女性健壮,而南非白人男性最健壮,南非黑人女性最纤细。至少有两个变量在大多数群体中存在人群差异,需要创建特定于人群的二元逻辑回归方程。只有白人和有色人种南非人没有显著差异。印度南非人在二元逻辑回归(94.1%)和随机森林模型(95.7%)中的正确分类率最高,而有色人种南非人的正确分类率最低(分别为 88.8%和 88.0%)。本研究描述了当前南非人口中四个颅骨形态特征的性别二态性模式,以及用于估计黑人、有色人、印度人和白人南非人性别的二元逻辑回归函数。