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基于当代意大利样本中牙槽测量的性别估计预测模型。

Predictive models for sex Estimation based on alveolar measurements in a contemporary Italian sample.

作者信息

Tanga Carmen, Viciano Joan

机构信息

Department of Legal Medicine, Toxicology and Physical Anthropology, University of Granada, Granada, Spain.

Independent Researcher, Turin, Italy.

出版信息

Int J Legal Med. 2025 Jul 1. doi: 10.1007/s00414-025-03555-6.

DOI:10.1007/s00414-025-03555-6
PMID:40590928
Abstract

Teeth play a significant role in reconstructive identification, aiding in the estimation of an individual's biological profile, such as population affinity, sex, and age at death. However, when teeth are lost postmortem-a common occurrence in forensic contexts-alternative methods are required. This study aimed to develop predictive models for sex estimation using alveolar measurements and to evaluate their reliability with a validation sample. Mesiodistal and buccolingual alveolar diameters from both arches were measured in 127 adults (64 males, 63 females) from the Certosa Cemetery osteological collection in Bologna. Binary logistic regression models were developed using a training subsample and tested on a hold-out subsample. The results indicated that the canine alveoli in both arches exhibited the highest sexual dimorphism, followed by those of the central incisor, first premolar, lateral incisor, and second premolar. In the training subsample, univariate predictive models achieved sex classification accuracy ranging from 57.3 to 83.9%, while multivariate models ranged from 68.0 to 91.3%. In the hold-out subsample of 19 individuals, sex was accurately estimated in 89.5% of cases, with a match rate of 63.2% compared with known biological sex. This study highlights the potential of alveolar measurements as a reliable alternative in forensic anthropology, offering a viable method for sex estimation when teeth are unavailable for measurement.

摘要

牙齿在重建身份识别中起着重要作用,有助于估计个体的生物学特征,如群体亲缘关系、性别和死亡年龄。然而,当牙齿在死后缺失时(这在法医背景下很常见),就需要其他方法。本研究旨在开发利用牙槽测量进行性别估计的预测模型,并使用验证样本评估其可靠性。在来自博洛尼亚切尔托萨公墓骨骼收藏的127名成年人(64名男性,63名女性)中测量了两个牙弓的近远中向和颊舌向牙槽直径。使用训练子样本开发二元逻辑回归模型,并在留出的子样本上进行测试。结果表明,两个牙弓中的犬齿牙槽表现出最高的性别二态性,其次是中切牙、第一前磨牙、侧切牙和第二前磨牙的牙槽。在训练子样本中,单变量预测模型的性别分类准确率在57.3%至83.9%之间,而多变量模型的准确率在6

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本文引用的文献

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