Angadi Punnya V, Hemani S, Prabhu Sudeendra, Acharya Ashith B
Department of Oral Pathology, K.L.E.V.K. Institute of Dental Sciences, Nehru Nagar, Belagavi (Belgaum) 590010, Karnataka, India.
J Forensic Leg Med. 2013 Aug;20(6):673-7. doi: 10.1016/j.jflm.2013.03.040. Epub 2013 Apr 28.
Correct sex assessment of skeletonized human remains allows investigators to undertake a more focused search of missing persons' files to establish identity. Univariate and multivariate odontometric sex assessment has been explored in recent years on small sample sizes and have not used a test sample. Consequently, inconsistent results have been produced in terms of accuracy of sex allocation. This paper has derived data from a large sample of males and females, and applied logistic regression formulae on a test sample. Using a digital caliper, buccolingual and mesiodistal dimensions of all permanent teeth (except third molars) were measured on 600 dental casts (306 females, 294 males) of young adults (18-32 years), and the data subjected to univariate (independent samples' t-test) and multivariate statistics (stepwise logistic regression analysis, or LRA). The analyses revealed that canines were the most sexually dimorphic teeth followed by molars. All tooth variables were larger in males, with 51/56 (91.1%) being statistically larger (p < 0.05). When the stepwise LRA formulae were applied to a test sample of 69 subjects (40 females, 29 males) of the same age range, allocation accuracy of 68.1% for the maxillary teeth, 73.9% for the mandibular teeth, and 71% for teeth of both jaws combined, were obtained. The high univariate sexual dimorphism observed herein contrasts with some reports of low, and sometimes reverse, sexual dimorphism (the phenomenon of female tooth dimensions being larger than males'); the LRA results, too, are in contradiction to a previous report of virtually 100% sex allocation for a small heterogeneous sample. These reflect the importance of using a large sample to quantify sexual dimorphism in tooth dimensions and the application of the derived formulae on a test dataset to ascertain accuracy which, at best, is moderate in nature.
对骨骼化人类遗骸进行准确的性别评估，可使调查人员更有针对性地查找失踪人员档案以确定身份。近年来，单变量和多变量牙测量性别评估在小样本量上进行了探索，且未使用测试样本。因此，在性别分配准确性方面产生了不一致的结果。本文从大量男性和女性样本中获取数据，并在一个测试样本上应用逻辑回归公式。使用数字卡尺，对600个年轻成年人（18 - 32岁）的牙模（306名女性，294名男性）上所有恒牙（第三磨牙除外）的颊舌径和近远中径进行测量，并对数据进行单变量（独立样本t检验）和多变量统计（逐步逻辑回归分析，即LRA）。分析表明，犬齿是最具性别二态性的牙齿，其次是磨牙。所有牙齿变量在男性中都更大，51/56（91.1%）在统计学上更大（p < 0.05）。当将逐步LRA公式应用于同一年龄范围的69名受试者（40名女性，29名男性）的测试样本时，上颌牙的分配准确率为68.1%，下颌牙为73.9%，上下颌牙齿综合准确率为71%。本文观察到的高单变量性别二态性与一些低性别二态性（有时甚至是相反的，即女性牙齿尺寸大于男性的现象）的报告形成对比；LRA结果也与之前关于一个小的异质样本几乎100%性别分配的报告相矛盾。这些反映了使用大样本量来量化牙齿尺寸性别二态性以及在测试数据集上应用推导公式以确定准确性的重要性，而准确性充其量只是中等程度。
