Advertisement

Examination of regressive features of third molars for the purpose of age assessment in the living by means of rescaled regression analyses

  • M. TimmeEmail author
  • W. H. Timme
  • A. Olze
  • C. Ottow
  • J. Gladitz
  • H. Pfeiffer
  • R. Dettmeyer
  • A. Schmeling
Original Article

Abstract

The main criterion of dental age assessment in living adolescents and young adults is the evaluation of third molars’ mineralization. Concerning forensic age assessment after the completion of third molars’ mineralization, apposition of secondary dentine and narrowing of the periodontal membrane as seen as decreasing radiolucent areas in the radiographs for mandibular third molars have already been described as regressive features. The present study examines the combination of both these features for the purpose of age assessment in regression analyses after rescaling the data to make it on the interval scale. To this end, a total of 1245 orthopantomograms was evaluated, taken from 606 females and 639 males in the age group of 15–40 years. The apposition of secondary dentine and narrowing of the periodontal membrane as seen as decreasing radiolucent areas in the radiographs were determined for the lower third molars. The correlation of the features with the chronological age was assessed by means of rescaled regression analyses. Furthermore, regression formulas for age assessment were established. The values of the standard error of estimate ranged between 3.55 and 4.52 years. In general, the rescaled regression of the examined features appears to be suited for forensic age assessment. A limitation of the present study is the comparatively low number of evaluable teeth in the examined age group. Due to an incomplete development or a lack of the mandibular third molars, only a mere half of the respective teeth could be included in the statistical analysis.

Keywords

Age assessment Third molars Regressive changes Rescaled regression analyses 

Notes

Compliance with ethical standards

Ethical approval for the study was obtained from the Medical Ethical Committee of the University of Gießen, Germany (181/11).

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Mansour H, Fuhrmann A, Paradowski I, van Well EJ, Püschel K (2017) The role of forensic medicine and forensic dentistry in estimating the chronological age of living individuals in Hamburg, Germany. Int J Legal Med 131:593–601.  https://doi.org/10.1007/s00414-016-1517-y CrossRefGoogle Scholar
  2. 2.
    Schmeling A, Dettmeyer R, Rudolf E, Vieth V, Geserick G (2016) Forensic age estimation. Dtsch Arztebl Int 113:44–50.  https://doi.org/10.3238/arztebl.2016.0044 PubMedCentralGoogle Scholar
  3. 3.
    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 CrossRefGoogle Scholar
  4. 4.
    Engebretsen L, Steffen K, Bahr R, Broderick C, Dvorak J, Janarv PM, Johnson A, Leglise M, Mamisch TC, McKay D, Micheli L, Schamasch P, Singh GD, Stafford DEJ, Steen H (2010) The International Olympic Committee Consensus statement on age determination in high-level young athletes. Br J Sports Med 44:476–484.  https://doi.org/10.1136/bjsm.2010.073122 CrossRefGoogle Scholar
  5. 5.
    Parzeller M (2015) Juristische Aspekte der forensischen Altersdiagnostik: Rechtsprechung-Update 2010–2014. Rechtsmedizin 25:21–29.  https://doi.org/10.1007/s00194-014-1004-z CrossRefGoogle Scholar
  6. 6.
    Timme M, Steinacker JM, Schmeling A (2017) Age estimation in competitive sports. Int J Legal Med 131:225–233.  https://doi.org/10.1007/s00414-016-1456-7 CrossRefGoogle Scholar
  7. 7.
    Kvaal S, Solheim T (1989) Fluorescence from dentin and cementum in human mandibular second premolars and its relation to age. Scand J Dent Res 97:131–138Google Scholar
  8. 8.
    Kvaal SI, Solheim T (1995) Incremental lines in human dental cementum in relation to age. Eur J Oral Sci 103:225–230CrossRefGoogle Scholar
  9. 9.
    Kvaal SI, Koppang HS, Solheim T (1994) Relationship between age and deposit of peritubular dentine. Gerodontology 11:93–98CrossRefGoogle Scholar
  10. 10.
    Lorentsen M, Solheim T (1989) Age assessment based on translucent dentine. J Forensic Odontostomatol 7:3–9Google Scholar
  11. 11.
    Solheim T (1992) Amount of secondary dentin as an indicator of age. Scand J Dent Res 100:193–199Google Scholar
  12. 12.
    Solheim T (1992) Recession of periodontal ligament as an indicator of age. J Forensic Odontostomatol 10:32–42Google Scholar
  13. 13.
    Solheim T (1989) Dental root translucency as an indicator of age. Scand J Dent Res 97:189–197Google Scholar
  14. 14.
    Solheim T (1988) Dental attrition as an indicator of age. Gerodontics 4:299–304Google Scholar
  15. 15.
    Solheim T (1988) Dental color as an indicator of age. Gerodontics 4:114–118Google Scholar
  16. 16.
    Solheim T (1972) Forensic dentistry. Tid Tann 33:140–141Google Scholar
  17. 17.
    Solheim T, Kvaal S (1993) Dental root surface structure as an indicator of age. J Forensic Odontostomatol 11:9–21Google Scholar
  18. 18.
    Olze A, Solheim T, Schulz R, Kupfer M, Schmeling A (2010) Evaluation of the radiographic visibility of the root pulp in the lower third molars for the purpose of forensic age estimation in living individuals. Int J Legal Med 124:183–186.  https://doi.org/10.1007/s00414-009-0415-y CrossRefGoogle Scholar
  19. 19.
    Olze A, Solheim T, Schulz R, Kupfer M, Pfeiffer H, Schmeling A (2010) Assessment of the radiographic visibility of the periodontal ligament in the lower third molars for the purpose of forensic age estimation in living individuals. Int J Legal Med 124:445–448.  https://doi.org/10.1007/s00414-010-0488-7 CrossRefGoogle Scholar
  20. 20.
    Timme M, Timme WH, Olze A, Ottow C, Ribbecke S, Pfeiffer H, Dettmeyer R, Schmeling A (2017) The chronology of the radiographic visibility of the periodontal ligament and the root pulp in the lower third molars. Sci Justice 57:257–261.  https://doi.org/10.1016/j.scijus.2017.03.004 CrossRefGoogle 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.
    Van der Kooij AJ (2007) Prediction accuracy and stability of regression with optimal scaling transformations. Leiden University, DissertationGoogle Scholar
  23. 23.
    Van der Kooij AJ, Meulmann JJ, Heiser WJ (2006) Local minima in categorical multiple regression. Comput Stat Data Anal 50:446–462CrossRefGoogle Scholar
  24. 24.
    Altman DG (1991) Practical statistics for medical research. Chapman & Hall, New YorkGoogle Scholar
  25. 25.
    Kvaal SI, Kolltveit KM, Thomsen IO, Solheim T (1995) Age estimation of adults from dental radiographs. Forensic Sci Int 74:175–185CrossRefGoogle Scholar
  26. 26.
    Paewinsky E, Pfeiffer H, Brinkmann B (2005) Quantification of secondary dentine formation from orthopantomograms--a contribution to forensic age estimation methods in adults. Int J Legal Med 119:27–30.  https://doi.org/10.1007/s00414-004-0492-x CrossRefGoogle Scholar
  27. 27.
    Landa MI, Garamendi PM, Botella MC, Alemán I (2009) Application of the method of Kvaal et al. to digital orthopantomograms. Int J Legal Med 123:123–128.  https://doi.org/10.1007/s00414-008-0268-9 CrossRefGoogle Scholar
  28. 28.
    Meinl A, Tangl S, Pernicka E, Fenes C, Watzek G (2007) On the applicability of secondary dentin formation to radiological age estimation in young adults. J Forensic Sci 52:438–441.  https://doi.org/10.1111/j.1556-4029.2006.00377.x CrossRefGoogle Scholar
  29. 29.
    Mittal S, Nagendrareddy SG, Sharma ML, Agnihotri P, Chaudhary S, Dhillon M (2016) Age estimation based on Kvaal’s technique using digital panoramic radiographs. J Forensic Dent Sci 8:115.  https://doi.org/10.4103/0975-1475.186378 CrossRefPubMedCentralGoogle Scholar
  30. 30.
    Cameriere R, De Luca S, Alemán I, Ferrante L, Cingolani M (2012) Age estimation by pulp/tooth ratio in lower premolars by orthopantomography. Forensic Sci Int 214:105–112.  https://doi.org/10.1016/j.forsciint.2011.07.028 CrossRefGoogle Scholar
  31. 31.
    Cameriere R, Cunha E, Wasterlain SN, De Luca S, Sassaroli E, Pagliara F, Nuzzolese E, Cingolani M, Ferrante L (2013) Age estimation by pulp/tooth ratio in lateral and central incisors by peri-apical X-ray. J Forensic Legal Med 20:530–536.  https://doi.org/10.1016/j.jflm.2013.02.012 CrossRefGoogle Scholar
  32. 32.
    Olze A, Hertel J, Schulz R, Wierer T, Schmeling A (2012) Radiographic evaluation of Gustafson’s criteria for the purpose of forensic age diagnostics. Int J Legal Med 126:615–621.  https://doi.org/10.1007/s00414-012-0701-y CrossRefGoogle Scholar
  33. 33.
    Gustafson G (1947) Aldersbestämniningar pa tända. Odont Tidskr 55:556–568Google Scholar
  34. 34.
    Timme M, Timme WH, Olze A, Ottow C, Ribbecke S, Pfeiffer H, Dettmeyer R, Schmeling A (2017) Dental age estimation in the living after completion of third molar mineralization: new data for Gustafson’s criteria. Int J Legal Med 131:569–577.  https://doi.org/10.1007/s00414-016-1492-3 CrossRefGoogle Scholar
  35. 35.
    Si X, Chu G, Olze A, Schmidt S, Schulz R, Chen T, Pfeiffer H, Guo Y, Schmeling A (2019) Age assessment in the living using modified Gustafson’s criteria in a northern Chinese population. Int J Legal Med 133:921–930.  https://doi.org/10.1007/s00414-019-02024-1 CrossRefGoogle Scholar
  36. 36.
    Eklund SA, Pittman JL (2001) Third-molar removal patterns in an insured population. J Am Dent Assoc 132:469–475.  https://doi.org/10.14219/jada.archive.2001.0209 CrossRefGoogle Scholar
  37. 37.
    Carter K, Worthington S (2015) Morphologic and demographic predictors of third molar agenesis: a systematic review and meta-analysis. J Dent Res 94:886–894.  https://doi.org/10.1177/0022034515581644 CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Institute of Legal MedicineUniversity Hospital MünsterMünsterGermany
  2. 2.Institute of Legal MedicineUniversity of GießenGiessenGermany
  3. 3.Institute of Legal MedicineCharité-Universitätsmedizin BerlinBerlinGermany
  4. 4.Department of Clinical RadiologyUniversity Hospital MünsterMünsterGermany
  5. 5.Statistik-Service Dr. GladitzBerlinGermany

Personalised recommendations