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Third molar maturity index (I3M) for assessing age of majority in a black African population in Botswana

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Abstract

Assessment of legal age, also known as age of majority, is a controversial issue as there are few body biomarkers or evidence during late adolescence differentiating a subject from being a minor or adult. The third molar was recognized as a suitable site for age examination in late adolescence. We analyzed the development of the left mandibular third molar by the third molar maturity index (I3M) and a specific cut-off value of I3M = 0.08, established by Cameriere et al. in 2008 and used it for discriminating between minors and adult black Africans from Gaborone, Botswana. A final sample of panoramic radiographs (OPTs) of 1294 people (582 males and 712 females) aged between 13 and 23 years was evaluated. The real age decreased as I3M gradually increased. There was no statistically significant difference in the third molar development evaluated using I3M between males and females (p > 0.05) across different I3M classes. Results of 2 × 2 contingency tables for different cut-off values indicated that I3M = 0.08 was useful in discriminating between adults and minors. Precisely, for I3M = 0.08, the values of accuracy or overall fraction of correctly classified were 0.91 in males with a 95 % confidence interval (95 % CI) of 0.88 to 0.93 and 0.92 (95 % CI, 0.90 to 0.93) in females. Values of sensitivity of the test or the proportion of participants being 18 years and older were 0.88 (95 % CI, 0.87 to 0.90) in males and 0.88 (95 % CI, 0.90 to 0.93) in females, while values of specificity or proportion of individuals younger than 18 who have I3M <0.08 were 0.94 (95 % CI, 0.91 to 0.96) in males and 0.96 (95 % CI, 0.94 to 0.98) in females. Positive predictive values of the test, where the participants whose I3M <0.08 were adults, were 0.94 (95 % CI 0.91 to 0.96) in males and 0.97 (95 % CI, 0.94 to 0.98) in females, while negative predictive values of the test, where the participants whose I3M was ≥0.08 were minors, were 0.88 (95 % CI 0.85 to 0.90) in males and 0.97 (95 % CI, 0.94 to 0.98) in females. The likelihood ratios of the positive test (LR+) were 13.67 (95 % CI, 9.21 to 21.02) in males and 23.73 (95 % CI, 14.20 to 42.28) in females, while likelihood ratios of the negative test (LR−) were 0.12 (95 % CI 0.10 to 0.16) in males and 0.12 (95 % CI, 0.11 to 0.15) in females. Bayes post-test probabilities, p, were 0.94 (95 % CI 0.90 to 0.98) in males and 0.97 (95 %CI, 0.93 to 1.00) in females. These results indicate with high accuracy that I3M may be a useful alternative method in legal and forensic practice to discriminate individuals of black African origin who are around the legal adult age of 18 years in Botswana. Further studies should address the usefulness of this method and specific cut-off for different adolescent populations.

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References

  1. Novak A (2009) Guilty of murder with extenuating circumstances: transparency and the mandatory death penalty in Botswana. Boston Univ Int Law J 27:173–204

    Google Scholar 

  2. Thevissen PW, Kvaal SI, Willems G (2012) Ethics in age estimation of unaccompanied minors. J Forensic Odontostomatol 30(Suppl 1):84–102

    PubMed  Google Scholar 

  3. Cattaneo C, De Angelis D, Ruspa M, Gibelli D, Cameriere R, Grandi M (2008) How old am I? Age estimation in living adults: a case report. J Forensic Odontostomatol 26:39–43

    CAS  PubMed  Google Scholar 

  4. Focardi M, Pinchi V, De Luca F, Norelli GA (2014) Age estimation for forensic purposes in Italy: ethical issues. Int J Legal Med 128:515–22

    PubMed  Google Scholar 

  5. Botswana e-laws. Age of maturity, Interpretation act, CAP 01:04 Section 49. In: Attorney Generals Chambers, editor.2013.

  6. Cole R (2010) Juvenile offenders and the criminal justice system in Botswana: exploring the restorative approach. In: Maundeni T (ed) Thari ya bana—reflections on children in Botswana 2010. UNICEF Botswana and University of Botswana, Gaborone, pp 54–7

    Google Scholar 

  7. Ohenjo N, Willis R, Jackson D, Nettleton C, Good K, Mugarura B (2006) Health of Indigenous people in Africa. Lancet 367:1937–46

    Article  PubMed  Google Scholar 

  8. Seitio-Kgokgwe O, Gauld RDC, Hill PC, Barnett P (2014) Assessing performance of Botswana’s public hospital system: the use of the World Health Organization health system performance assessment framework. Int J Health Policy Manag 3:179–89

    Article  PubMed  PubMed Central  Google Scholar 

  9. Miller CM, Gruskin S, Subramanian SV, Rajaraman D, Heymann SJ (2006) Orphan care in Botswana’s working households: growing responsibilities in the absence of adequate support. Am J Public Health 96:1429–35

    Article  PubMed  PubMed Central  Google Scholar 

  10. Children’s Act 2009 in Botswana. 2009.

  11. Marriage Act Botswana. Section 14. 2001.

  12. Penal Code in Botswana. 1964.

  13. Campbell EK (2006) Reflections on illegal immigration in Botswana and South Africa. Afr Popul Stud 21:23–44

    Google Scholar 

  14. UN High Commissioner for Refugees. National and international responses to the Zimbabwean exodus: implications for the refugee protection regime. Geneva: UNHCR; 2009.

  15. Solheim T (2003) The Scandinavian Star Ferry Disaster 1990. Experience and Recommendation for Records in Dental Practice. Acta Stomat Croat 37:292–3

  16. Schmeling A, Reisinger W, Geserick G, Olze A (2008) Forensic age estimation of live adolescents and young adults. In: Tsokos M, editor. Humana Press, Forensic Pathology Reviews, pp 269–88

    Google Scholar 

  17. Schmeling A, Reisinger W, Geserick G, Olze A (2006) Age estimation of unaccompanied minors. Part I. General considerations. Forensic Sci Int 159(Suppl 1):S61–4

    Article  PubMed  Google Scholar 

  18. Schmeling A, Olze A, Reisinger W, Rosing FW, Geserick G (2003) Forensic age diagnostics of living individuals in criminal proceedings. Homo Internationale Zeitschrift fur die vergleichende Forschung am Menschen 54:162–9

    CAS  PubMed  Google Scholar 

  19. Schmeling A, Olze A, Reisinger W, Hermann KG, Rossel U (2003) Age determination of an unknown body in early adulthood. Arch Kriminol 211:129–38

    PubMed  Google Scholar 

  20. Schmeling A, Olze A, Reisinger W, Geserick G (2004) Forensic age diagnostics of living people undergoing criminal proceedings. Forensic Sci Int 144:243–5

    Article  CAS  PubMed  Google Scholar 

  21. Schmeling A, Olze A, Reisinger W, Geserick G (2001) Age estimation of living people undergoing criminal proceedings. Lancet 358:89–90

    Article  CAS  PubMed  Google Scholar 

  22. Schmeling A, Grundmann C, Fuhrmann A, Kaatsch HJ, Knell B, Ramsthaler F et al (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–60

    Article  CAS  PubMed  Google Scholar 

  23. Baccino E. Forensic Anthropology Society of Europe (FASE), a subsection of the IALM, is 1 year old. International Journal of Legal Medicine. 2005;119:N1-N.

  24. Feijoo G, Barberia E, De Nova J, Prieto JL (2012) 2012. Forensic Sci Int 214(213):e1–6

    Google Scholar 

  25. Ambarkova V, Galić I, Vodanović M, Bioćina-Lukenda D, Brkić H (2014) Dental age estimation using Demirjian and Willems methods: cross sectional study on children from the Former Yugoslav Republic of Macedonia. Forensic Sci Int 234(187):1–7

  26. Maber M, Liversidge HM, Hector MP (2006) Accuracy of age estimation of radiographic methods using developing teeth. Forensic Sci Int 159(Suppl 1):S68–73

    Article  PubMed  Google Scholar 

  27. Galić I, Vodanovic M, Cameriere R, Nakaš E, Galić E, Selimović E et al (2011) Accuracy of Cameriere, Haavikko, and Willems radiographic methods on age estimation on Bosnian-Herzegovian children age groups 6–13. Int J Legal Med 125:315–21

  28. Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–27

    CAS  PubMed  Google Scholar 

  29. Liversidge HM (2008) Timing of human mandibular third molar formation. Ann Hum Biol 35:294–321

    Article  CAS  PubMed  Google Scholar 

  30. Liversidge HM (2008) Predicting mandibular third molar agenesis from second molar formation. Acta Stomat Croat 42:311–7

    Google Scholar 

  31. 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

    Article  CAS  PubMed  Google Scholar 

  32. 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 122:493–7

    Article  CAS  PubMed  Google Scholar 

  33. Thevissen P, Altalie S, Brkić H, Galić I, Fieuws S, Franco A et al (2013) Comparing 14 country-specific populations on third molars development: consequences for age predictions of individuals with different geographic and biological origin. J Forensic Odontostomatol 31:87–8

    Google Scholar 

  34. Thevissen PW, Alqerban A, Asaumi J, Kahveci F, Kaur J, Kim YK et al (2010) Human dental age estimation using third molar developmental stages: accuracy of age predictions not using country specific information. Forensic Sci Int 201:106–11

    Article  CAS  PubMed  Google Scholar 

  35. Thevissen PW, Fieuws S, Willems G (2010) Human third molars development: comparison of 9 country specific populations. Forensic Sci Int 201:102–5

    Article  CAS  PubMed  Google Scholar 

  36. 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 124:35–42

    Article  CAS  PubMed  Google Scholar 

  37. Liversidge HM (2008) Dental age revisted. In: Irish JD, Nelson GC (eds) Technique and application in dental anthropology. Cambridge University Press, Cambridge, pp 234–52

    Chapter  Google Scholar 

  38. Galić I, Vodanović M, Janković S, Mihanović F, Nakaš E, Prohić S et al (2013) Dental age estimation on Bosnian-Herzegovinian children aged 6–14 years: evaluation of Chaillet’s international maturity standards. J Forensic Leg Med 20:40–5

  39. 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 174:217–21

  40. Martin-de las Heras S, Garcia-Fortea P, Ortega A, Zodocovich S, Valenzuela A (2008) Third molar development according to chronological age in populations from Spanish and Magrebian origin. Forensic Sci Int 174:47–53

    Article  PubMed  Google Scholar 

  41. Corradi F, Pinchi V, Barsanti I, Manca R, Garatti S (2013) Optimal age classification of young individuals based on dental evidence in civil and criminal proceedings. Int J Legal Med 127:1157–64

    Article  PubMed  Google Scholar 

  42. Corradi F, Pinchi V, Barsanti I, Garatti S (2013) Probabilistic classification of age by third molar development: the use of soft evidence. J Forensic Sci 58:51–9

    Article  PubMed  Google Scholar 

  43. 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):e1–5

  44. 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 Leg Med 33:111–5

  45. De Luca S, Biagi R, Begnoni G, Farronato G, Cingolani M, Merelli V et al (2014) Accuracy of Cameriere’s cut-off value for third molar in assessing 18 years of age. Forensic Sci Int 235(102):e1–6

    Google Scholar 

  46. Cameriere R, Santoro V, Roca R, Lozito P, Introna F, Cingolani M et al (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

    Google Scholar 

  47. 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 63:283–94

    CAS  PubMed  Google Scholar 

  48. 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 38:379–90

    Article  CAS  PubMed  Google Scholar 

  49. Olze A, Bilang D, Schmidt S, Wernecke KD, Geserick G, Schmeling A (2005) Validation of common classification systems for assessing the mineralization of third molars. Int J Legal Med 119:22–6

    Article  PubMed  Google Scholar 

  50. Gleiser I, Hunt EE Jr (1955) The permanent mandibular first molar: its calcification, eruption and decay. Am J Phys Anthropol 13:253–83

    Article  CAS  PubMed  Google Scholar 

  51. Kohler S, Schmelzle R, Loitz C, Puschel K (1994) [Development of wisdom teeth as a criterion of age determination]. Ann Anat 176:339–45

    Article  CAS  PubMed  Google Scholar 

  52. Thevissen PW, Fieuws S, Willems G (2013) Third molar development: evaluation of nine tooth development registration techniques for age estimations. J Forensic Sci 58:393–7

    Article  PubMed  Google Scholar 

  53. Moorrees CF, Fanning EA, Hunt EE Jr (1963) Age variation of formation stages for ten permanent teeth. J Dent Res 42:1490–502

    Article  CAS  PubMed  Google Scholar 

  54. Cavrić J, Vodanović M, Marušić A, Galić I (2016) Time of mineralization of permanent teeth in children and adolescents in Gaborone, Botswana. Ann Anat Anatomischer Anz 203:24–32

    Article  Google Scholar 

  55. World Medical Association (2013) World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310:2191–4

    Article  CAS  Google Scholar 

  56. Rasband WS. Image J. Bethesda, Maryland,USA: U. S. National Institutes of Health; 1997–2013

  57. Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–93

    Article  CAS  PubMed  Google Scholar 

  58. Schisterman EF, Perkins NJ, Liu A, Bondell H (2005) Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples. Epidemiol (Cambridge, Mass) 16:73–81

    Article  Google Scholar 

  59. Fletcher R, Fletcher S. Diagnosis. In: Fletcher R, Fletcher S, editors. Clinical epidemiology The essentials. Baltimore: Wolters, Kluwer, Lippincott, Williams & Wilkins; 2005. p. 35–58.

  60. Deeks JJ, Altman DG (2004) Diagnostic tests 4: likelihood ratios. BMJ 329:168–9

    Article  PubMed  PubMed Central  Google Scholar 

  61. Central Statistics Office in Botswana. Resident population on the January, 1st 2014. 2011.

  62. Thevissen PW, Kaur J, Willems G (2012) Human age estimation combining third molar and skeletal development. Int J Legal Med 126:285–92

    Article  CAS  PubMed  Google Scholar 

  63. Nystrom ME, Ranta HM, Peltola JS, Kataja JM (2007) Timing of developmental stages in permanent mandibular teeth of Finns from birth to age 25. Acta Odontol Scand 65:36–43

    Article  PubMed  Google Scholar 

  64. Harris EF (2007) Mineralization of the mandibular third molar: a study of American blacks and whites. Am J Phys Anthropol 132:98–109

    Article  PubMed  Google Scholar 

  65. Garn SM, Lewis AB, Polacheck DL (1959) Variability of tooth formation. J Dent Res 38:135–48

    Article  CAS  PubMed  Google Scholar 

  66. Garn SM, Lewis AB, Vicinus JH (1962) Third molar agenesis and reduction in the number of other teeth. J Dent Res 41:717

    Article  CAS  PubMed  Google Scholar 

  67. Lewis JM, Senn DR (2010) Dental age estimation utilizing third molar development: a review of principles, methods, and population studies used in the United States. Forensic Sci Int 201:79–83

    Article  PubMed  Google Scholar 

  68. 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 154:3–12

    Article  CAS  PubMed  Google Scholar 

  69. Dhanjal KS, Bhardwaj MK, Liversidge HM (2006) Reproducibility of radiographic stage assessment of third molars. Forensic Sci Int 159(Suppl 1):S74–7

    Article  PubMed  Google Scholar 

  70. 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 52:428–33

    Article  PubMed  Google Scholar 

  71. 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 57:209–17

    CAS  PubMed  Google Scholar 

  72. Harris EF, McKee JH (1990) Tooth mineralization standards for blacks and whites from the middle southern United States. J Forensic Sci 35:859–72

    Article  CAS  PubMed  Google Scholar 

  73. Haub C, Kaneda T (2014) 2014 world population data sheet. Population Reference Bureau, Washington

    Google Scholar 

  74. Nuzzolese E (2012) Missing people, migrants, identification and human rights. J Forensic Odontostomatol 30(Suppl 1):47–59

    PubMed  Google Scholar 

  75. Cameriere R, Giuliodori A, Zampi M, Galic I, Cingolani M, Pagliara F et al (2015) Age estimation in children and young adolescents for forensic purposes using fourth cervical vertebra (C4). Int J Legal Med 129:347–55

    Article  CAS  PubMed  Google Scholar 

  76. 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 54:428–32

    Article  PubMed  Google Scholar 

  77. Pinchi V, Norelli GA, Pradella F, Vitale G, Rugo D, Nieri M (2012) Comparison of the applicability of four odontological methods for age estimation of the 14 years legal threshold in a sample of Italian adolescents. J Forensic Odontostomatol 30:17–25

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Authors and Affiliations

  1. Henry M. Goldman School of Dental Medicine, Boston University, 100 E Newton St, Boston, MA, 02118, USA

    Jelena Cavrić

  2. Departments of Research in Biomedicine and Health and Dental Medicine, University of Split School of Medicine, Šoltanska 2, Split,, 21000, Croatia

    Ivan Galić

  3. Department of Dental Anthropology, School of Dental Medicine, University of Zagreb, Gundulićeva 5, 10000, Zagreb, Croatia

    Marin Vodanović & Jelena Gregov

  4. School of Dental Medicine, University of Zagreb, Gundulićeva 5, 10000, Zagreb, Croatia

    Hrvoje Brkić

  5. Dipartimento di Civilta e Forme del Sapere, University of Pisa, Via L. Galvani 1, I-56126, Pisa, Italy

    Serena Viva

  6. AgEstimation Project, Institute of Legal Medicine, University of Macerata, Macerata, Italy

    Laura Rey & Roberto Cameriere

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  1. Jelena Cavrić
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  2. Ivan Galić
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  3. Marin Vodanović
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  4. Hrvoje Brkić
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  5. Jelena Gregov
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  6. Serena Viva
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  7. Laura Rey
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  8. Roberto Cameriere
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Corresponding author

Correspondence to Ivan Galić.

Ethics declarations

The study was conducted in accordance to the ethical standards laid down by the Declaration of Helsinki [55]. The approval for the study was granted by the Human Research and Development Committee (HRDC) of the Ministry of Health in Botswana and by the Ethical Council of the School of Dental Medicine at the University of Zagreb. Jelena Cavrić and Ivan Galić equally contributed to this article.

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Jelena Cavrić and Ivan Galić contributed equally to this work.

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Cavrić, J., Galić, I., Vodanović, M. et al. Third molar maturity index (I3M) for assessing age of majority in a black African population in Botswana. Int J Legal Med 130, 1109–1120 (2016). https://doi.org/10.1007/s00414-016-1344-1

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