Background: Sex estimation of fragmentary remains is a critical problem which is further aggravated by the changing pattern of sexual dimorphism due to temporal/secular changes. Previously cranial chord variables were examined only to deduce cranial abnormalities and hominin evolution. In forensic anthropological literature to date, no studies have examined the importance of cranial chord variables in sex determination and neither have secular changes been reported in those measurements to date.Aim: The present study aims to examine the sexual dimorphism and temporal changes in chord measurements in the Indian population and to provide updated sex discriminant formulae.Subjects and methods: A total of 483 (contemporary: n = 158; sub-recent: n = 325) adult crania (18-70 years) from two temporally distinct North Indian populations were included in the study. Seven chord variables were measured and data were subjected to discriminant function analysis using SPSS 16.00.Results: Analysis of the data using the t-test demonstrated significant sexual and population variations over time. Univariate discriminant analysis revealed the glabella-bregma chord as the best variable in both populations (78.5 and 74.5% accuracy in the contemporary and sub-recent populations, respectively). Using multivariate analysis classification accuracy reached 86.1% in the contemporary sample.Conclusion: It is concluded that Indian crania are going through secular changes as the contemporary population has larger chord dimensions than their predecessors and chord variables can be applied for sex estimation in the Indian population.

中文翻译：

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颅骨和弦变量的长期趋势：北印度人口1954-2011年间性二态性变化的研究。

背景：残骸的性别估计是一个关键问题，由于时空变化，性二态性的变化模式使这一问题进一步恶化。以前，仅检查颅骨和弦变量才能推断出颅骨异常和人的进化。迄今为止，在法医人类学文献中，没有研究检查颅骨和弦变量在性别确定中的重要性，并且迄今为止也没有报道世俗的变化。目的：本研究旨在检查和弦测量中的性二态性和时间变化受试者和方法：总数为483（同期：n = 158；次近距离：n = 325）来自两个在时间上不同的北印度人口的成年狂犬病（18-70岁）被纳入研究。测量了七个和弦变量，并使用SPSS 16.00对数据进行了判别功能分析。结果：使用t检验对数据进行分析表明，随着时间的推移，性别和人口存在显着变化。单变量判别分析表明，在两个人群中，glabella-bregma和弦是最好的变量（在当代人群和近现代人群中，准确率分别为78.5和74.5％）。使用多变量分析，当代样本中分类的准确性达到86.1％。结论：