Advertisement

Age estimation by measuring open apices in teeth: a new formula for two samples of South African black and white children

  • N. Angelakopoulos
  • S. De LucaEmail author
  • L. A. Velandia Palacio
  • E. Coccia
  • L. Ferrante
  • V. Pinchi
  • R. Cameriere
Original Article

Abstract

In this cross-sectional study, the accuracy of Cameriere’s European formula was tested and a new specific model was developed for two samples of black and white South African children with known age and sex. For these purposes, 970 children of black South African ethnicity (girls 491, boys 479) and 974 with European ethnicity, living in South Africa (girls 493, boys 481), were retrospectively analyzed. The application of the European formula showed that there is a trend in the error estimates: the ages of the younger children are overestimated and those of the older children are underestimated, in both white and black children. A new model, based on the relationship between the apical width and the tooth length (maturity index) of the seven permanent mandibular teeth, was therefore constructed. The new developed equation for the South African population was able to explain 76% of total variance in white girls and 80% in white boys’ subgroup. On the other side, the model explained 76% of total variance in black girls and 78% in the black boys’ subgroup. The mean absolute error of the residuals (residuals = predicted age minus observed age) ranged from 0.718 to 0.769 years, with the interquartile range (IQRres) ranging from 1.19 to 1.31 years. Differently from the Cameriere’s European formula, the plot did not tend to underestimate the chronological age significantly as the age increases. Cameriere’s maturity index is reproducible in both samples of South African black and white children, for forensic purposes, and the Bayesian calibration approach is useful for a more accurate and precise estimation.

Keywords

Forensic sciences Dental age estimation South Africa Forensic statistics Bayesian calibration 

Notes

Compliance with ethical standards

The study was carried out in accordance with the ethical standards laid down by the Declaration of Helsinki (Finland).

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Cunha E, Baccino E, Martrille L, Ramsthaler F, Prieto J, Schuliar Y, Lynnerup N, Cattaneo C (2009) The problem of aging human remains and living individuals: a review. Forensic Sci Int 193:1–13CrossRefGoogle Scholar
  2. 2.
    Eikvil L, Kvaal SI, Teigland A, Haugen M, Grøgaard J (2012) Age estimation in youths and young adults: a summary of the needs for methodological research and development. Norwegian Computing Center 3–26Google Scholar
  3. 3.
    Kvaal SI, Kolltveit KM, Thomsen IOB, Solheim T (1995) Age estimation of adults from dental radiographs. Forensic Sci Int 74:175–185CrossRefGoogle Scholar
  4. 4.
    Schmeling A, Grundman C, Fuhrmann A, Kaatsch HJ, Knell B, Ramsthaler F, Reisinger W, Riepert T, Ritz-Timme S, Rösing FW, Rötzscher K, Geserick G (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–460CrossRefGoogle Scholar
  5. 5.
    Annual Crime Report (ACR) of the South African Police Service (SAPS) (2017) Crime Statistics 2016–2017 financial year (www.saps.gov.za)
  6. 6.
    Campbell EK (2006) Reflections on illegal immigration in Botswana and South Africa. Afr Popul Stud 21:23–44Google Scholar
  7. 7.
    Statistics South Africa (2015) Documented immigrants in South Africa. Statistical release P0351.4. Pretoria http://www.statssa.gov.za/
  8. 8.
    Angelakopoulos N, De Luca S, Velandia Palacio LA, Coccia E, Ferrante L, Cameriere R (2018) Third molar maturity index (I3M) for assessing age of majority: study of a black south African sample. Int J Legal Med 132(5):1457–1464CrossRefGoogle Scholar
  9. 9.
    Africa’s orphaned and vulnerable generations (2006) Children affected by AIDS, UNICEF, IOP Publishing PhysicsWeb. https://www.unicef.org/publications/files/Africas_Orphaned_and_Vulnerable_Generations_Children_Affected_by_AIDS.pdf. Accessed 18 April 2019
  10. 10.
    Cameriere R, Ferrante L, Cingolani M (2006) Age estimation in children by measurement of open apices in teeth. Int J Legal Med 120:49–53CrossRefGoogle Scholar
  11. 11.
    Cameriere R, De Angelis D, Ferrante L, Scarpino F, Cingolani M (2007) Age estimation in children by measurement of open apices in teeth: a European formula. Int J Legal Med 121(6):449–453CrossRefGoogle Scholar
  12. 12.
    Fernandes MM, Parreiras de Braganca DP, Junior LF (2011) Age estimation by measurements of the developing teeth: accuracy of Cameriere’s method on a Brazilian sample. J Forensic Sci 56:1616–1619CrossRefGoogle Scholar
  13. 13.
    Guo YC, Yan CX, Lin XW, Zhou H, Li JP, Pan F, Zhang Z, Wei L, Zheng T, Chen T (2015) Age estimation in northern Chinese children by measurement of open apices in tooth roots. Int J Legal Med 129(1):179–186CrossRefGoogle Scholar
  14. 14.
    Rai B, Kaur J, Cingolani M, Ferrante L, Cameriere R (2010) Age estimation in children by measurement of open apices in teeth: an Indian formula. Int J Legal Med 124:237–241CrossRefGoogle Scholar
  15. 15.
    Ferrante L, Cameriere R (2009) Statistical methods to assess the reliability of measurements in the procedures for forensic age estimation. Int J Legal Med 123:277–283CrossRefGoogle Scholar
  16. 16.
    Leatherman G (1971) Two-digit system of designating teeth—FDI submission. Aust Dent J 16:394–394CrossRefGoogle Scholar
  17. 17.
    Rani Das K, Rahmatullah Imon AHM (2016) A brief review of tests for normality. AJTAS 5(1):5–12CrossRefGoogle Scholar
  18. 18.
    R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna https:// www.R-project.org/
  19. 19.
    Ferrante L, Skrami E, Gesuita R, Cameriere R (2015) Bayesian calibration for forensic age estimation. Stat Med 34(10):1779–1790CrossRefGoogle Scholar
  20. 20.
    Cameriere R, Pacifici A, Pacifici L, Polimeni A, Federici F, Cingolani M, Ferrante L (2016) Age estimation in children by measurement of open apices in teeth with Bayesian calibration approach. Forensic Sci Int 258:50–54CrossRefGoogle Scholar
  21. 21.
    Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227Google Scholar
  22. 22.
    Phillips V, van Wyk Kotze T (2009) Testing standard methods of dental age estimation by Moorrees, fanning and hunt and Demirjian, Goldstein and Tanner on three South African children samples. J Forensic Odontostomatol 27(2):20–28Google Scholar
  23. 23.
    Uys A, Fabris-Rotelli I, Bernitz H (2014) Estimating age in black South African children. SADJ 69(2):54–58 60–1Google Scholar
  24. 24.
    LA Hargreaves PE, Cleaton-Jones LP, Fati P, Roberts GJ, Hargreaves V (1997) Eruption of primary teeth in South Africans from one year of age. S Afr J Sci 93:81–84Google Scholar
  25. 25.
    Esan TA, Schepartz LA (2018) The WITS atlas: a black Southern African dental atlas for permanent tooth formation and emergence. Am J Phys Anthropol 166:208–218CrossRefGoogle Scholar
  26. 26.
    Willems G, Lee SS, Uys A, Bernitz H, Cadenas de Llano-Pérula M, Fieuws S, Thevissen P (2018) Age estimation based on Willems method versus new country-specific method in South African black children. Int J Legal Med 132(2):599–607CrossRefGoogle Scholar
  27. 27.
    Willems G, Van Olmen A, Spiessens B, Carels C (2001) Dental age estimation in Belgian children: Demirjian’s technique revisited. J Forensic Sci 46(4):893–895CrossRefGoogle Scholar
  28. 28.
    De Luca S, De Giorgio S, Butti AC, Biagi R, Cingolani M, Cameriere R (2012) Age estimation in children by measurement of open apices in tooth roots: study of a Mexican sample. Forensic Sci Int 221:155.e1–155.e7Google Scholar
  29. 29.
    Gulsahi A, Tirali RE, Cehreli SB, De Luca S, Ferrante L, Cameriere R (2015) The reliability of Cameriere’s method in Turkish children: a preliminary report. Forensic Sci Int 249:319.e1–319.e5  https://doi.org/10.1016/j.forsciint.2015.01.031 CrossRefGoogle Scholar
  30. 30.
    Latić-Dautović M, Nakaš E, Jelešković A, Cavrić J, Galić I (2017) Cameriere’s European formula for age estimation: a study on the children in Bosnia and Herzegovina. South Eur J Orthod Dentofac Res 4(2):26–30Google Scholar
  31. 31.
    Mazzilli LEN, Melani RFH, Lascala CA, Velandia Palacio LA, Cameriere R (2018) Age estimation: Cameriere’s open apices methodology accuracy on a southeast Brazilian sample. J Forensic Legal Med 58:164–168CrossRefGoogle Scholar
  32. 32.
    Aykroyd R, Lucy D, Pollard A, Roberts C (1999) Nasty, brutish, but not necessarily short: a reconsideration of the statistical methods used to calculate age at death from adult human skeletal and dental indicators. Am Antiq 64:55–70CrossRefGoogle Scholar
  33. 33.
    Thevissen PW, Fieuws S, Willems G (2010) Human dental age estimation using third molar developmental stages: does a Bayesian approach outperform regression models to discriminate between juveniles and adults? Int J Legal Med 124:35–42CrossRefGoogle Scholar
  34. 34.
    Tangmose S, Thevissen P, Lynnerup N, Willems G, Boldsen J (2015) Age estimation in the living: transition analysis on developing third molars. Forensic Sci Int 257:512e1–512e7CrossRefGoogle Scholar
  35. 35.
    Metsäniitty M, Waltimo-Sirén J, Ranta H, Fieuws S, Thevissen P (2019) Dental age estimation in Somali children and sub-adults combining permanent teeth and third molar development. Int J Legal Med.  https://doi.org/10.1007/s00414-019-02053-w
  36. 36.
    Aykroyd R, Lucy D, Pollard AM, Solheim T (1997) Regression analysis in adult age estimation. Am J Phys Anthropol 104(2):259–265CrossRefGoogle Scholar
  37. 37.
    Lucy D, Pollard AM (1995) Further comments on the estimation of error associated with the Gustafson dental age estimation method. J Forensic Sci 40(2):222–227CrossRefGoogle Scholar
  38. 38.
    European Network of Forensic Scientific Institutes (ENFSI) (2015) ENFSI guideline for evaluative reporting in forensic science: Strengthening the Evaluation of Forensic Results Across EuropeGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Orthodontics and Dentofacial OrthopedicsUniversity of BernBernSwitzerland
  2. 2.Área de Identificación Forense, Unidad de Derechos HumanosServicio Médico LegalSantiago de ChileChile
  3. 3.AgEstimation ProjectMacerataItaly
  4. 4.Department of Odontostomatologic and Specialized Clinical Sciences (DISCO)Polytechnic University of MarcheAnconaItaly
  5. 5.Center of Epidemiology, Biostatistics and Medical Information Technology, Department of Biomedical Science and Public HealthPolytechnic University of MarcheAnconaItaly
  6. 6.Department of Health SciencesUniversity of FlorenceFlorenceItaly

Personalised recommendations