Top

International Journal of Legal Medicine

Published in:

01-09-2018 | Population Data

Third molar maturity index (I_3M) for assessing age of majority: study of a black South African sample

Authors: N. Angelakopoulos, S. De Luca, L. A. Velandia Palacio, E. Coccia, L. Ferrante, R. Cameriere

Published in: International Journal of Legal Medicine | Issue 5/2018

Abstract

Aims

The evaluation of the cutoff value of I_3M = 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.

Results

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. I_3M 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 I_3M = 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).

Conclusion

The results show that I_3M is a valuable method to distinguish subjects who are around legal adult age in South Africa.

Annual Crime Report (ACR) of the South African Police Service (SAPS) (2017) Crime Statistics 2016–2017 financial year (www.saps.gov.za)

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

Statistics South Africa (2015) Documented immigrants in South Africa. Statistical release P0351.4. Pretoria http://www.statssa.gov.za/

United Nations High Commissioner for Refugees (2015) UNHCR operation in South Africa, Lesotho and Swaziland

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. https://doi.org/10.1111/j.1556-4029.2008.00961.x CrossRefPubMed

Liversidge HM (2008) Dental age revisited. In: Irish JD, Nelson GC (eds) Technique and application in dental anthropology. Cambridge University Press, Cambridge, pp 234–252CrossRef

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. https://doi.org/10.1016/j.jflm.2012.04.037 CrossRef

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. https://doi.org/10.1016/j.forsciint.2007.04.220 CrossRefPubMed

Liversidge HM, Molleson TI (1999) Developing permanent tooth length as an estimate of age. J Forensic Sci 44:917–920CrossRefPubMed

10.

Thevissen PW, Fieuws S, Willems G (2011) Third molar development: measurements versus scores as age predictors. Arch Oral Biol 56(10):1035–1040. https://doi.org/10.1016/j.archoralbio.2011.04.008 CrossRefPubMed

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. https://doi.org/10.1007/s00414-005-0047-9 CrossRefPubMed

12.

Willems G (2001) A review of the most commonly used dental age estimation techniques. J Forensic Odontostomatol 19:9–17PubMed

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. https://doi.org/10.1007/s00414-008-0254-2 CrossRefPubMed

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-NCrossRef

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. https://doi.org/10.1016/j.forsciint.2011.08.024 CrossRef

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. https://doi.org/10.1007/s00414-008-0279-6 CrossRefPubMed

17.

World Medical Association (2013) World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310:2191–2194CrossRef

18.

Lin L (2000) A note on the concordance correlation coefficient. Biometrics 56:324–325CrossRef

19.

Lin L (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268CrossRefPubMed

20.

Lin L (1992) Assay validation using the concordance correlation coefficient. Biometrics 48(2):599–604CrossRef

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. https://doi.org/10.1007/s00414-009-0349-4 CrossRefPubMed

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. https://doi.org/10.1080/13854040802524229 CrossRefPubMed

23.

Ferrante L, Skrami E, Gesuita R, Cameriere R (2015) Bayesian calibration for forensic age estimation. Stat Med 34(10):1779–1790. https://doi.org/10.1002/sim.6448 CrossRefPubMed

24.

R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna https://www.R-project.org/

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. https://doi.org/10.1093/bmb/lds014 CrossRefPubMed

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. https://doi.org/10.7196/samj.2016.v106i11.11407 CrossRef

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. https://doi.org/10.1038/sj.bdj.2010.976 CrossRefPubMed

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. https://doi.org/10.2319/101906-430.1 CrossRefPubMed

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. https://doi.org/10.1016/j.jflm.2010.04.010 CrossRef

30.

Gleiser I, Hunt EE Jr (1955) The permanent mandibular first molar: its calcification, eruption and decay. Am J Phys Anthropol 13:253–283CrossRefPubMed

31.

Kohler S, Schmelzle R, Loitz C, Puschel K (1994) Development of wisdom teeth as a criterion of age determination. Ann Anat 176:339–345CrossRefPubMed

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. https://doi.org/10.1111/1556-4029.12063 CrossRefPubMed

33.

Moorrees CF, Fanning EA, Hunt EE Jr (1963) Age variation of formation stages for ten permanent teeth. J Dent Res 42:1490–1502CrossRefPubMed

34.

Demirjian A, Goldstein H, Tanner JM (1973) A new system of dental age assessment. Hum Biol 45:211–227PubMed

35.

Liversidge HM (2008) Timing of human mandibular third molar formation. Ann Hum Biol 35(3):294–321. https://doi.org/10.1080/03014460801971445 CrossRefPubMed

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. https://doi.org/10.1016/j.aanat.2015.08.001 CrossRefPubMed

37.

Liversidge HM (2008) Predicting mandibular third molar agenesis from second molar formation. Acta Stomatol Croat 42:311–317

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):29–44PubMed

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):20–28PubMed

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. https://doi.org/10.1007/s00414-004-0434-7 CrossRefPubMed

41.

Tompkins R (1996) Human population variability in relative dental development. Am J Phys Antropol 99:79–102CrossRef

42.

Reid D, Dean M (2006) Variation in modern human enamel formation times. J Hum Evol 50:329–346. https://doi.org/10.1016/j.jhevol.2005.09.003 CrossRefPubMed

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 38:379–390CrossRefPubMed

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. https://doi.org/10.1111/j.1556-4029.2006.00356.x CrossRefPubMed

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. https://doi.org/10.1016/j.jchb.2004.08.003 PubMedCrossRef

46.

Harris EF, McKee JH (1990) Tooth mineralization standards for blacks and whites from the middle southern United States. J Forensic Sci 35:859–872CrossRefPubMed

47.

Tosam MJ (2015) The ethical and social implications of age-cheating in Africa. Int J Philos 3(1):1–11. https://doi.org/10.11648/j.ijp.20150301.11 CrossRef

48.

Marriage Act (1961) Act 25 of 1961. South Africa

49.

Civil Union Act (2006) Act No. 17 of 2006. South Africa

50.

Recognition of Customary Marriages (1998) Act 120 of 1998. South Africa

51.

United Nations Children’s Fund (UNICEF) (2005) Early marriage: a harmful traditional practice, New York

52.

UNICEF (2001) Early marriage: child spouses, Innocenti Digest, Florence, Italy: UNICEF, No. 7 The Convention on the Rights of the Child (CRC, 1989)

53.

African Charter on the Rights and Welfare of the Child OAU Doc. CAB/LEG/24.9/49 (1990)

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. https://doi.org/10.1363/4105815 CrossRefPubMed

55.

The Criminal Law (2007) Sexual offences and related matters. Amendment act, 2007 act no. 32 of 2007

56.

Children’s Act (2007) No 38 of 2005. South Africa

57.

Mettler FA, Huda W, Yoshizumi TT, Mahesh M (2008) Effective doses in radiology and diagnostic nuclear medicine: a catalog. Radiology 248:254–263. https://doi.org/10.1148/radiol.2481071451 CrossRefPubMed

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, Sydney

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. https://doi.org/10.3238/arztebl.2016.0044 PubMedPubMedCentralCrossRef

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. https://doi.org/10.1007/s00414-017-1766-4

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. https://doi.org/10.1016/j.forsciint.2017.01.004 CrossRefPubMed

62.

Cavrić J, Galić I, Vodanović M, Brkić H, Gregov J, Viva S, Rey L, Cameriere R (2016) Third molar maturity index (I_3M) for assessing age of majority in a black African population in Botswana. Int J Legal Med 130:1109–1120. https://doi.org/10.1007/s00414-016-1344-1 CrossRefPubMed

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. https://doi.org/10.1016/j.forsciint.2016.07.020 CrossRef

64.

Pepe MS (2003) The statistical evaluation of medical tests for classification and prediction. Oxford University Press, New York, pp 14–34

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 51–68

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. https://doi.org/10.1016/j.forsciint.2004.08.018 CrossRefPubMed

67.

Pobjoy JM (2017) An Age-Sensitive Assessment of Risk. In: The child in international refugee law. Cambridge University Press, Cambridge, pp 79–99CrossRef

68.

Franklin D (2010) Forensic age estimation in human skeletal remains: current concepts and future directions. Leg Med (Tokyo) 12(1):1–7. https://doi.org/10.1016/j.legalmed.2009.09.001 CrossRef

69.

Altman DG, Bland JM (1994) Diagnostic tests 2: predictive values. BMJ 309:102CrossRefPubMedPubMedCentral

70.

Barnhart HX, Haber M, Song J (2002) Overall concordance correlation coefficient for evaluating agreement among multiple observers. Biometrics 58:1020–1027. https://doi.org/10.1111/j.0006-341X.2002.01020.x CrossRefPubMed

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. https://doi.org/10.1016/j.forsciint.2015.04.030 CrossRef

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. https://doi.org/10.1016/j.jflm.2015.04.016 CrossRef

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. https://doi.org/10.1016/j.forsciint.2014.10.013 CrossRef

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 63:283–294PubMed

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. https://doi.org/10.1016/j.forsciint.2016.04.034 CrossRef

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. https://doi.org/10.1016/j.forsciint.2016.06.032 CrossRef

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. https://doi.org/10.1016/j.forsciint.2015.12.032 CrossRefPubMed

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. https://doi.org/10.1016/j.legalmed.2017.01.003 CrossRef

Title: Third molar maturity index (I3M) for assessing age of majority: study of a black South African sample
Authors: N. Angelakopoulos
S. De Luca
L. A. Velandia Palacio
E. Coccia
L. Ferrante
R. Cameriere
Publication date: 01-09-2018
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Legal Medicine / Issue 5/2018
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-018-1818-4

At a glance: The STEP trials

Springer Medicine

Third molar maturity index (I_3M) for assessing age of majority: study of a black South African sample

Abstract

Aims

Material and methods

Results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Aims

Material and methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 5/2018

The forensic value of X-linked markers in mixed-male DNA analysis

Biomechanical approach for the assessment of contacts with deformable objects

Genetic diagnosis of acute aortic dissection in South China Han population using next-generation sequencing

Forensic molecular genetic diversity analysis of Chinese Hui ethnic group based on a novel STR panel

A test and analysis of Calce (2012) method for skeletal age-at-death estimation using the acetabulum in a modern skeletal sample

Immunohistochemical study on dystrophin expression in CAD-related sudden cardiac death: a marker of early myocardial ischaemia