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Sex estimation using the mandibular canine index components

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Abstract

The mandibular canine index (MCI) has been described as a suitable methodology for sex estimation in forensic scenarios but there are contradictory reports about its accuracy. Moreover, the two mandibular canine teeth must be available, which is not always a viable option. The aim of this study was to strip the MCI by analyzing the MCI itself and its components, in order to optimize its use for sex estimation. The mesiodistal dimensions of the mandibular canine crown and the mandibular canine arch width were measured in a sample of 120 cast models. Five predictor variables were considered in this study: the standard MCI, a variation of the MCI using the left canine, and MCI components (MD43, MD33 and D33–43). Multivariate binary logistic regression was performed using stepwise forward approach to select the most statistical relevant variables on the probability of a cast being from a female. The estimated probability was then analyzed with respect to performance in sex classification (ROC analysis and optimal cut-offs accuracy) and compared with the performance of the univariate variables. MCI43 and MCI33 presented the lowest performance (64.2% and 63.3% respectively), and the highest overall accuracy was attained using the MD43 and MD33 (85.8% in both cases). The multivariate logistic model obtained (using MD43 and MD33) exhibited the same accuracy as the logistic model based solely on MD43 (85.8%). Our results suggest that MD43 should be used instead of MCI for sex estimation.

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Acknowledgements

This work was partially supported by the Portuguese Foundation for Science and Technology (FCT) – with national (MEC) and European structural funds through the programs FEDER, under the partnership agreement PT2020 - within IEETA/UA project UID/CEC/00127/2013, CIDMA/UA project UID/MAT/04106/2013 and CMUP/UP project UID/MAT/00144/2013. S. Gouveia acknowledges the postdoctoral grant by FCT (ref. SFRH/BPD/87037/2012). All dental casts are the property of the Faculdade de Medicina Dentária do Porto, Portugal, and information regarding these data can be provided upon request.

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Authors and Affiliations

  1. Faculdade de Medicina Dentária da Universidade do Porto, Rua Dr. Manuel Pereira da Silva, 4200 – 393, Porto, Portugal

    Álvaro Azevedo, Maria Lurdes Pereira & Inês Morais Caldas

  2. EPIUnit – Instituto de Saúde Pública da Universidade do Porto, Rua das Taipas, 135, 4050 – 091, Porto, Portugal

    Álvaro Azevedo & Maria Lurdes Pereira

  3. Institute of Electronics and Informatics Engineering of Aveiro (IEETA) and Center for R&D in Mathematics and Applications (CIDMA), University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

    Sónia Gouveia

  4. Departamento de Matemática da Faculdade de Ciências da Universidade do Porto and Centro de Matemática da Universidade do Porto, Rua do Campo Alegre 1021/1055, 4169-007, Porto, Portugal

    João Nuno Tavares

  5. Departamento de Ciências da Vida, Centre for Functional Ecology, University of Coimbra (CFE-UC), Calçada Martim de Freitas, 3000-456, Coimbra, Portugal

    Inês Morais Caldas

  6. IINFACTS - Institute of Research and Advanced Training in Health Sciences, Department of Sciences, University Institute of Health Sciences (IUCS), CESPU, Rua Central de Gandra, 1317, 4585-116, Gandra, PRD, Portugal

    Inês Morais Caldas

Authors
  1. Álvaro Azevedo
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  2. Maria Lurdes Pereira
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  3. Sónia Gouveia
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  4. João Nuno Tavares
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  5. Inês Morais Caldas
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Corresponding author

Correspondence to Inês Morais Caldas.

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The authors declare that they have no conflict of interest.

Ethical approval

The study was approved by the ethics committee of the Faculty of Dental Medicine of the University of Porto, Portugal.

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Informed consent was waived as the data used was completely anonymized.

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Azevedo, Á., Pereira, M.L., Gouveia, S. et al. Sex estimation using the mandibular canine index components. Forensic Sci Med Pathol 15, 191–197 (2019). https://doi.org/10.1007/s12024-018-0051-2

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  • DOI: https://doi.org/10.1007/s12024-018-0051-2

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