International Journal of Legal Medicine

, Volume 132, Issue 5, pp 1457–1464 | Cite as

Third molar maturity index (I3M) for assessing age of majority: study of a black South African sample

  • N. Angelakopoulos
  • S. De LucaEmail author
  • L. A. Velandia Palacio
  • E. Coccia
  • L. Ferrante
  • R. Cameriere
Population Data



The evaluation of the cutoff value of I3M = 0.08 for discriminating black South African minors from adults, and its relationship with chronological age.

Material and methods

A sample of 833 panoramic radiographs of healthy black South African subjects (500 females and 333 males), in the age range of 14 to 24 years (mean age 17.67 years in females and 17.42 years in males), was retrospectively evaluated.


ICC values were 99.10% (95% CI 97.70 to 99.70%) and 99.20% (95% CI 98.00 to 99.60%), for the intra- and inter-observer reliability, respectively. I3M decreased as the real age gradually increased in both sexes. According to the logistic regression model, the variable sex was not significant when the probability that an individual is 18 years or older was calculated. The I3M = 0.08 was valuable in discriminating between adults and minors. The overall accuracy (ACC = fraction of accurately classified subjects) is 0.90 (95% CI 0.87–0.91); the proportion of correctly classified subjects (Se = sensitivity) is 0.80 (95% CI 0.76–0.84), and specificity (Sp) is 0.95 (95% CI 0.93–0.97). The PPV (predictive positive value) is 0.96 (95% CI 0.95–0.97), and the negative predictive value is 0.76 (95% CI 0.72–0.80).


The results show that I3M is a valuable method to distinguish subjects who are around legal adult age in South Africa.


Legal medicine Dental age estimation Age of majority Third molar maturity index South Africa 



The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper.

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.


  1. 1.
    Annual Crime Report (ACR) of the South African Police Service (SAPS) (2017) Crime Statistics 2016–2017 financial year (
  2. 2.
    Campbell EK (2006) Reflections on illegal immigration in Botswana and South Africa. Afr Popul Stud 21:23–44Google Scholar
  3. 3.
    Statistics South Africa (2015) Documented immigrants in South Africa. Statistical release P0351.4. Pretoria
  4. 4.
    United Nations High Commissioner for Refugees (2015) UNHCR operation in South Africa, Lesotho and SwazilandGoogle Scholar
  5. 5.
    Thevissen PW, Pittayapat P, Fieuws S, Willems G (2009) Estimating age of majority on third molars developmental stages in young adults from Thailand using a modified scoring technique. J Forensic Sci 54(2):428–432. CrossRefPubMedGoogle Scholar
  6. 6.
    Liversidge HM (2008) Dental age revisited. In: Irish JD, Nelson GC (eds) Technique and application in dental anthropology. Cambridge University Press, Cambridge, pp 234–252CrossRefGoogle Scholar
  7. 7.
    Galić I, Vodanović M, Janković S, Mihanović F, Nakaš E, Prohić S, Galić E, Brkić H (2013) Dental age estimation on Bosnian-Herzegovinian children aged 6–14 years: evaluation of Chaillet’s international maturity standards. J Forensic Legal Med 20:40–45. CrossRefGoogle Scholar
  8. 8.
    Cameriere R, Brkić H, Ermenc B, Ferrante L, Ovsenik M, Cingolani M (2008) The measurement of open apices of teeth to test chronological age of over 14-year olds in living subjects. Forensic Sci Int 174:217–221. CrossRefPubMedGoogle Scholar
  9. 9.
    Liversidge HM, Molleson TI (1999) Developing permanent tooth length as an estimate of age. J Forensic Sci 44:917–920CrossRefPubMedGoogle Scholar
  10. 10.
    Thevissen PW, Fieuws S, Willems G (2011) Third molar development: measurements versus scores as age predictors. Arch Oral Biol 56(10):1035–1040. CrossRefPubMedGoogle Scholar
  11. 11.
    Cameriere R, Ferrante L, Cingolani M (2006) Age estimation in children by measurement of open apices in teeth. Int J Legal Med 120:49–52. CrossRefPubMedGoogle Scholar
  12. 12.
    Willems G (2001) A review of the most commonly used dental age estimation techniques. J Forensic Odontostomatol 19:9–17PubMedGoogle Scholar
  13. 13.
    Schmeling A, Grundmann 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 122:457–460. CrossRefPubMedGoogle Scholar
  14. 14.
    Baccino E (2005) Forensic Anthropology Society of Europe (FASE), a subsection of the IALM, is 1 year old. Int J Legal Med 119:N1-NCrossRefGoogle Scholar
  15. 15.
    Feijoo G, Barberia E, De Nova J, Prieto JL (2012) Permanent teeth development in a Spanish sample. Application to dental age estimation. Forensic Sci Int 214(213):e1–e6. CrossRefGoogle Scholar
  16. 16.
    Cameriere R, Ferrante L, De Angelis D, Scarpino F, Galli F (2008) The comparison between measurement of open apices of third molars and Demirjian stages to test chronological age of over 18 year olds in living subjects. Int J Legal Med 122:493–497. CrossRefPubMedGoogle Scholar
  17. 17.
    World Medical Association (2013) World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310:2191–2194CrossRefGoogle Scholar
  18. 18.
    Lin L (2000) A note on the concordance correlation coefficient. Biometrics 56:324–325CrossRefGoogle Scholar
  19. 19.
    Lin L (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268CrossRefPubMedGoogle Scholar
  20. 20.
    Lin L (1992) Assay validation using the concordance correlation coefficient. Biometrics 48(2):599–604CrossRefGoogle Scholar
  21. 21.
    Ferrante L, Cameriere R (2009) Statistical methods to assess the reliability of measurements in the procedures for forensic age estimation. Int J Legal Med 123:277–283. CrossRefPubMedGoogle Scholar
  22. 22.
    Crawford JR, Garthwaite PH, Betkowska K (2009) Bayes’ theorem and diagnostic tests in neuropsychology: interval estimates for post-test probabilities. Clin Neuropsychol 23(4):624–644. CrossRefPubMedGoogle Scholar
  23. 23.
    Ferrante L, Skrami E, Gesuita R, Cameriere R (2015) Bayesian calibration for forensic age estimation. Stat Med 34(10):1779–1790. CrossRefPubMedGoogle Scholar
  24. 24.
    R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Google Scholar
  25. 25.
    Aynsley-Green A, Cole TJ, Crawley H, Lessof N, Boag LR, Wallace RMM (2012) Medical, statistical, ethical and human rights considerations in the assessment of age in children and young people subject to immigration control. Br Med Bull 102(1):17–42. CrossRefPubMedGoogle Scholar
  26. 26.
    Tiemensma M, Phillips VM (2016) The dilemma of age estimation of children and juveniles in South Africa. S Afr Med J 106(11):1061. CrossRefGoogle Scholar
  27. 27.
    Liversidge HM, Marsden PH (2010) Estimating age and the likelihood of having attained 18 years of age using mandibular third molars. Br Dent J 209:E13. CrossRefPubMedGoogle Scholar
  28. 28.
    Sisman Y, Uysal T, Yagmur F (2007) Third molar development in relation to chronological age in Turkish children and young adults. Angle Orthod 77(6):1040–1045. CrossRefPubMedGoogle Scholar
  29. 29.
    Rai B, Kaur J, Jafarzadeh H (2010) Dental age estimation from the developmental stages of the third molars in Iranian population. J Forensic Med 17(6):309–311. CrossRefGoogle Scholar
  30. 30.
    Gleiser I, Hunt EE Jr (1955) The permanent mandibular first molar: its calcification, eruption and decay. Am J Phys Anthropol 13:253–283CrossRefPubMedGoogle Scholar
  31. 31.
    Kohler S, Schmelzle R, Loitz C, Puschel K (1994) Development of wisdom teeth as a criterion of age determination. Ann Anat 176:339–345CrossRefPubMedGoogle Scholar
  32. 32.
    Thevissen PW, Fieuws S, Willems G (2013) Third molar development: evaluation of nine tooth development registration techniques for age estimations. J Forensic Sci 58:393–397. CrossRefPubMedGoogle Scholar
  33. 33.
    Moorrees CF, Fanning EA, Hunt EE Jr (1963) Age variation of formation stages for ten permanent teeth. J Dent Res 42:1490–1502CrossRefPubMedGoogle Scholar
  34. 34.
    Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227PubMedGoogle Scholar
  35. 35.
    Liversidge HM (2008) Timing of human mandibular third molar formation. Ann Hum Biol 35(3):294–321. CrossRefPubMedGoogle Scholar
  36. 36.
    Cavrić J, Vodanović M, Marusić A, Galić I (2016) Time of mineralization of permanent teeth in children and adolescents in Gaborone, Botswana. Ann Anat 203:24–32. CrossRefPubMedGoogle Scholar
  37. 37.
    Liversidge HM (2008) Predicting mandibular third molar agenesis from second molar formation. Acta Stomatol Croat 42:311–317Google Scholar
  38. 38.
    Phillips V, van Wyk Kotze T (2009) Dental age-related tables for children of various ethnic groups in South Africa. J Forensic Odontostomatol 27(2):29–44PubMedGoogle Scholar
  39. 39.
    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):20–28PubMedGoogle Scholar
  40. 40.
    Olze A, Schmeling A, Taniguchi M, Maeda H, van Niekerk P, Wernecke K (2004) Forensic age estimation in living subjects: the ethnic factor in wisdom tooth mineralization. Int J Legal Med 118(3):170–173. CrossRefPubMedGoogle Scholar
  41. 41.
    Tompkins R (1996) Human population variability in relative dental development. Am J Phys Antropol 99:79–102CrossRefGoogle Scholar
  42. 42.
    Reid D, Dean M (2006) Variation in modern human enamel formation times. J Hum Evol 50:329–346. CrossRefPubMedGoogle Scholar
  43. 43.
    Mincer HH, Harris EF, Berryman HE (1993) The A.B.F.O. study of third molar development and its use as an estimator of chronological age. J Forensic Sci 38:379–390CrossRefPubMedGoogle Scholar
  44. 44.
    Blankenship JA, Mincer HH, Anderson KM, Woods MA, Burton EL (2007) Third molar development in the estimation of chronologic age in American blacks as compared with whites. J Forensic Sci 52:428–433. CrossRefPubMedGoogle Scholar
  45. 45.
    Olze A, van Niekerk P, Schmidt S, Wernecke KD, Rosing FW, Geserick G et al (2006) Studies on the progress of third-molar mineralisation in a Black African population. Homo internationale Zeitschrift fur die vergleichende Forschung am Menschen 57:209–217. PubMedCrossRefGoogle Scholar
  46. 46.
    Harris EF, McKee JH (1990) Tooth mineralization standards for blacks and whites from the middle southern United States. J Forensic Sci 35:859–872CrossRefPubMedGoogle Scholar
  47. 47.
    Tosam MJ (2015) The ethical and social implications of age-cheating in Africa. Int J Philos 3(1):1–11. CrossRefGoogle Scholar
  48. 48.
    Marriage Act (1961) Act 25 of 1961. South AfricaGoogle Scholar
  49. 49.
    Civil Union Act (2006) Act No. 17 of 2006. South AfricaGoogle Scholar
  50. 50.
    Recognition of Customary Marriages (1998) Act 120 of 1998. South AfricaGoogle Scholar
  51. 51.
    United Nations Children’s Fund (UNICEF) (2005) Early marriage: a harmful traditional practice, New YorkGoogle Scholar
  52. 52.
    UNICEF (2001) Early marriage: child spouses, Innocenti Digest, Florence, Italy: UNICEF, No. 7 The Convention on the Rights of the Child (CRC, 1989)Google Scholar
  53. 53.
    African Charter on the Rights and Welfare of the Child OAU Doc. CAB/LEG/24.9/49 (1990)Google Scholar
  54. 54.
    Maswikwa B, Richter L, Kaufman J, Nandi A (2015) Minimum marriage age laws and the prevalence of child marriage and adolescent birth: evidence from sub-Saharan Africa. Int Perspect Sex Reprod Health 41(2):58–68. CrossRefPubMedGoogle Scholar
  55. 55.
    The Criminal Law (2007) Sexual offences and related matters. Amendment act, 2007 act no. 32 of 2007Google Scholar
  56. 56.
    Children’s Act (2007) No 38 of 2005. South AfricaGoogle Scholar
  57. 57.
    Mettler FA, Huda W, Yoshizumi TT, Mahesh M (2008) Effective doses in radiology and diagnostic nuclear medicine: a catalog. Radiology 248:254–263. CrossRefPubMedGoogle Scholar
  58. 58.
    AHRC (2012) An age of uncertainty: inquiry into the treatment of individuals suspected of people smuggling offences who say that they are children. Australian Human Rights Commission, SydneyGoogle Scholar
  59. 59.
    Schmeling A, Dettmeyer R, Rudolf E, Vieth V, Geserick G (2016) Forensic age estimation. Methods, certainty, and the law. Dtsch Arztebl Int 113(4):44–50. PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Santiago BM, Almeida L, Cavalcanti YW, Magno MB, Maia LC (2017) Accuracy of the third molar maturity index in assessing the legal age of 18 years: a systematic review and meta-analysis. IJLM.
  61. 61.
    AlQahtani S, Kawthar A, AlAraik A, AlShalan A (2017) Third molar cut-off value in assessing the legal age of 18 in Saudi population. Forensic Sci Int 272:64–67. CrossRefPubMedGoogle Scholar
  62. 62.
    Cavrić J, Galić I, Vodanović M, Brkić H, Gregov J, Viva S, Rey L, Cameriere R (2016) Third molar maturity index (I3M) for assessing age of majority in a black African population in Botswana. Int J Legal Med 130:1109–1120. CrossRefPubMedGoogle Scholar
  63. 63.
    Dardouri A, Cameriere R, De Luca S, Vanin S (2016) Third molar maturity index by measurements of open apices in a Libyan sample of living subjects. Forensic Sci Int 267:230.e1–230.e6. CrossRefGoogle Scholar
  64. 64.
    Pepe MS (2003) The statistical evaluation of medical tests for classification and prediction. Oxford University Press, New York, pp 14–34Google Scholar
  65. 65.
    Sackett DL, Haynes RB, Guyatt GH, Tugwell P (1991) Clinical epidemiology: a basic science for clinical medicine. Little Brown and Co, New York, pp 51–68Google Scholar
  66. 66.
    Garamendi PM, Landa MI, Ballesteros J, Solano MA (2005) Reliability of the methods applied to assess age minority in living subjects around 18 years old. A survey on a Moroccan origin population. Forensic Sci Int 154(1):3–12. CrossRefPubMedGoogle Scholar
  67. 67.
    Pobjoy JM (2017) An Age-Sensitive Assessment of Risk. In: The child in international refugee law. Cambridge University Press, Cambridge, pp 79–99CrossRefGoogle Scholar
  68. 68.
    Franklin D (2010) Forensic age estimation in human skeletal remains: current concepts and future directions. Leg Med (Tokyo) 12(1):1–7. CrossRefGoogle Scholar
  69. 69.
    Altman DG, Bland JM (1994) Diagnostic tests 2: predictive values. BMJ 309:102CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Barnhart HX, Haber M, Song J (2002) Overall concordance correlation coefficient for evaluating agreement among multiple observers. Biometrics 58:1020–1027. CrossRefPubMedGoogle Scholar
  71. 71.
    Galić I, Lauc T, Brkić H, Vodanović M, Galić E, Biazevic MG et al (2015) Cameriere’s third molar maturity index in assessing age of majority. Forensic Sci Int 252(191):e1–e5. CrossRefGoogle Scholar
  72. 72.
    Deitos AR, Costa C, Michel-Crosato E, Galić I, Cameriere R, Biazevic MG (2015) Age estimation among Brazilians: younger or older than 18? J Forensic Legal Med 33:111–115. CrossRefGoogle Scholar
  73. 73.
    Cameriere R, Santoro V, Roca R, Lozito P, Introna F, Cingolani M, Galić I, Ferrante L (2014) Assessment of legal adult age of 18 by measurement of open apices of the third molars: study on the Albanian sample. Forensic Sci Int 245C(205):e1–e5. CrossRefGoogle Scholar
  74. 74.
    Cameriere R, Pacifici A, Viva S, Carbone D, Pacifici L, Polimeni A (2014) Adult or not? Accuracy of Cameriere’s cut-off value for third molar in assessing 18 years of age for legal purposes. Minerva Stomatol 63:283–294PubMedGoogle Scholar
  75. 75.
    Gulsahi A, De Luca S, Cehreli SB, Tirali RB, Cameriere R (2016) Accuracy of the third molar index for assessing the legal majority of 18 years in Turkish population. Forensic Sci Int 584:e1–584.e6. CrossRefGoogle Scholar
  76. 76.
    Franklin D, Karkhanis S, Flavel A, Collini F, De Luca S, Cameriere R (2016) Accuracy of a cut-off value based on the third molar index: validation in an Australian population. Forensic Sci Int 266:575.e1–575.e6. CrossRefGoogle Scholar
  77. 77.
    Zelic K, Galic I, Nedeljkovic N, Jakovljevic A, Milosevic O, Djuric M, Cameriere R (2016) Accuracy of Cameriere's third molar maturity index in assessing legal adulthood on Serbian population. Forensic Sci Int 259:127–132. CrossRefPubMedGoogle Scholar
  78. 78.
    Quispe Lizarbe RJ, Solís Adrianzén C, Quezada-Márquez MM, Galić I, Cameriere R (2017) Demirjian’s stages and Cameriere’s third molar maturity index to estimate legal adult age in Peruvian population. Leg Med (Tokyo) 25:59–65. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Dentistry, Division of Cariology and Endodontics and Pediatric DentistryUniversity of GenevaGenevaSwitzerland
  2. 2.Unidad Especial de Identificación ForenseServicio Médico LegalSantiago de ChileChile
  3. 3.AgEstimation Project, Institute of Legal MedicineUniversity of MacerataMacerataItaly
  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

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