美国西南部现代美洲印第安人的身材估算方程

IF 2.2 3区 医学 Q1 MEDICINE, LEGAL Forensic science international Pub Date : 2024-08-01 DOI:10.1016/j.forsciint.2024.112151
{"title":"美国西南部现代美洲印第安人的身材估算方程","authors":"","doi":"10.1016/j.forsciint.2024.112151","DOIUrl":null,"url":null,"abstract":"<div><p>Stature estimation is a core component to the biological profile in forensic anthropology casework. Here we provide mathematical equations for estimating stature for contemporary American Indians (AI), which currently are lacking in forensic anthropology. Drawing on postmortem computed tomography data from the New Mexico Decedent Image Database we regressed cadaveric length on four long bone length measures of the tibia, femur, and humerus to produce 11 combinations of models. Separate regression models were calculated for the entire pooled sample, by sex, broad AI language groups, and age + sex subsamples and compared. Sex-specific models were statistically better than general models, which were more accurate than language group and age + sex models. Equations were created for general and sex-specific models. Application to an independent test sample demonstrates the equations are accurate for stature estimation with overestimates of less than 1 cm. The equations provide similar levels of precision to stature estimation programs like the FORDISC 3.0 module and other stature equations in the literature. We provide recommendations for equation use in casework based on our results. These equations are the first for estimating stature in contemporary AI. This paper demonstrates the appropriateness of these newly created stature equations for use in New Mexico and the surrounding region.</p></div>","PeriodicalId":12341,"journal":{"name":"Forensic science international","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stature estimation equations for modern American Indians in the American Southwest\",\"authors\":\"\",\"doi\":\"10.1016/j.forsciint.2024.112151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Stature estimation is a core component to the biological profile in forensic anthropology casework. Here we provide mathematical equations for estimating stature for contemporary American Indians (AI), which currently are lacking in forensic anthropology. Drawing on postmortem computed tomography data from the New Mexico Decedent Image Database we regressed cadaveric length on four long bone length measures of the tibia, femur, and humerus to produce 11 combinations of models. Separate regression models were calculated for the entire pooled sample, by sex, broad AI language groups, and age + sex subsamples and compared. Sex-specific models were statistically better than general models, which were more accurate than language group and age + sex models. Equations were created for general and sex-specific models. Application to an independent test sample demonstrates the equations are accurate for stature estimation with overestimates of less than 1 cm. The equations provide similar levels of precision to stature estimation programs like the FORDISC 3.0 module and other stature equations in the literature. We provide recommendations for equation use in casework based on our results. These equations are the first for estimating stature in contemporary AI. This paper demonstrates the appropriateness of these newly created stature equations for use in New Mexico and the surrounding region.</p></div>\",\"PeriodicalId\":12341,\"journal\":{\"name\":\"Forensic science international\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forensic science international\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0379073824002329\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, LEGAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic science international","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0379073824002329","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, LEGAL","Score":null,"Total":0}
引用次数: 0

摘要

身材估计是法医人类学案例工作中生物特征的核心组成部分。在这里,我们提供了估算当代美洲印第安人(AI)身材的数学公式,这是法医人类学目前所缺乏的。利用新墨西哥州死者图像数据库中的尸检计算机断层扫描数据,我们将尸体长度与胫骨、股骨和肱骨的四种长骨长度测量值进行回归,生成了 11 种组合模型。我们按性别、广泛的人工智能语言组和年龄+性别子样本,分别计算了整个汇总样本的回归模型,并进行了比较。在统计学上,性别特异性模型优于一般模型,而一般模型又比语言组和年龄+性别模型更准确。为一般模型和性别特定模型创建了方程。在独立测试样本中的应用表明,这些等式在估计身材时非常准确,高估率低于 1 厘米。这些方程的精确度与 FORDISC 3.0 模块等身材估计程序和文献中的其他身材方程相近。根据我们的研究结果,我们提出了在个案工作中使用方程的建议。这些方程是当代人工智能中第一个用于估计身材的方程。本文证明了这些新创建的身材方程在新墨西哥州及周边地区的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Stature estimation equations for modern American Indians in the American Southwest

Stature estimation is a core component to the biological profile in forensic anthropology casework. Here we provide mathematical equations for estimating stature for contemporary American Indians (AI), which currently are lacking in forensic anthropology. Drawing on postmortem computed tomography data from the New Mexico Decedent Image Database we regressed cadaveric length on four long bone length measures of the tibia, femur, and humerus to produce 11 combinations of models. Separate regression models were calculated for the entire pooled sample, by sex, broad AI language groups, and age + sex subsamples and compared. Sex-specific models were statistically better than general models, which were more accurate than language group and age + sex models. Equations were created for general and sex-specific models. Application to an independent test sample demonstrates the equations are accurate for stature estimation with overestimates of less than 1 cm. The equations provide similar levels of precision to stature estimation programs like the FORDISC 3.0 module and other stature equations in the literature. We provide recommendations for equation use in casework based on our results. These equations are the first for estimating stature in contemporary AI. This paper demonstrates the appropriateness of these newly created stature equations for use in New Mexico and the surrounding region.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Forensic science international
Forensic science international 医学-医学:法
CiteScore
5.00
自引率
9.10%
发文量
285
审稿时长
49 days
期刊介绍: Forensic Science International is the flagship journal in the prestigious Forensic Science International family, publishing the most innovative, cutting-edge, and influential contributions across the forensic sciences. Fields include: forensic pathology and histochemistry, chemistry, biochemistry and toxicology, biology, serology, odontology, psychiatry, anthropology, digital forensics, the physical sciences, firearms, and document examination, as well as investigations of value to public health in its broadest sense, and the important marginal area where science and medicine interact with the law. The journal publishes: Case Reports Commentaries Letters to the Editor Original Research Papers (Regular Papers) Rapid Communications Review Articles Technical Notes.
期刊最新文献
Sensitivity assessment of the modified ABAcard® HemaTrace® and p30 immunochromatographic test cards Degradation and preservation of nitrites in whole blood Post mortem chiral analysis of MDMA and MDA in human blood and hair The 2 stages of cartridge primer toolmark production and the implied impact of cartridge manufacturing tolerances Letter to Editor regarding article “Ok Google, Start a Fire. IoT devices as witnesses and actors in fire investigations”
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1