International Journal of Legal Medicine

, Volume 118, Issue 3, pp 170–173

Forensic age estimation in living subjects: the ethnic factor in wisdom tooth mineralization

Authors

  • Andreas Olze
    • Institute of Legal Medicine (Charité)Humboldt University of Berlin
    • Institute of Legal Medicine (Charité)Humboldt University of Berlin
  • Mari Taniguchi
    • Department of Legal MedicineOsaka City University Medical School
  • Hitoshi Maeda
    • Department of Legal MedicineOsaka City University Medical School
  • Piet van Niekerk
    • Department of Oral Pathology and Oral BiologyUniversity of Pretoria
  • Klaus-Dieter Wernecke
    • Institute of Medical Biometry (Charité)Humboldt University of Berlin
  • Gunther Geserick
    • Institute of Legal Medicine (Charité)Humboldt University of Berlin
Original Article

DOI: 10.1007/s00414-004-0434-7

Cite this article as:
Olze, A., Schmeling, A., Taniguchi, M. et al. Int J Legal Med (2004) 118: 170. doi:10.1007/s00414-004-0434-7

Abstract

Radiological assessment of the mineralization stage of third molars is a major criterion for age estimation of living people involved in criminal proceedings. To date insufficient knowledge has been obtained about how the ethnic origin can influence tooth mineralization. A comparative study of wisdom tooth mineralization was carried out on three population samples: one German, one Japanese and one South African. To this end, 3,652 conventional orthopantomograms were evaluated on the basis of Demirjian’s stages. The Japanese subjects were on average 1–2 years older than their German counterparts upon reaching stages D–F, whereas the South African subjects were on average 1–2 years younger than the Germans when displaying stages D–G. To enhance the accuracy of forensic age estimates based on wisdom tooth mineralization we recommend the use of population-specific standards.

Keywords

Dental ageThird molarTooth mineralizationEthnicity

Introduction

Forensic age estimation is one of the key research areas in the field of forensic medicine (Ohtani et al. 2003; Ritz-Timme et al. 2003; Schmeling et al. 2004; Takasaki et al. 2003). In recent years it has become increasingly important to determine, in particular, the age of living persons (Schmeling et al. 2001b). From a legal perspective, such age estimates are carried out to determine whether a suspect without valid identification documents has reached the age of criminal responsibility and whether general criminal law in force for adults is to be applied. In many countries the age thresholds of relevance to criminal prosecution lie between 14 and 18 (Dünkel et al. 1997).

Age evaluations carried out lege artis by order of a judge contribute substantially to enhancing legal security. They do so by promoting equitable treatment of offenders under the judicial system regardless of whether those concerned possess identity papers or not, and also by serving to disprove allegations of perjury if the statement a defendant has made about his or her age is thereby confirmed.

In line with recommendations drawn up by the international, interdisciplinary Study Group on Forensic Age Diagnostics (http://www.charite.de/rechtsmedizin/agfad/index.htm), a forensic age diagnosis for the purpose of criminal investigations should consist of a clinical examination, including the recording of body measurements and an evaluation of signs of sexual maturity, an X-ray examination of the left hand, and a dental examination which records dentition status and evaluates an orthopantomogram (Schmeling et al. 2001a). One major criterion for dental age assessment is the evaluation of third molar mineralization.

To date insufficient knowledge has been obtained about how ethnic origin can influence tooth mineralization. This, however, constitutes a restraint on the reliability of age estimates and hence on the forensic value of information essential to legal security. The present study is intended to present comparative data on third molar mineralization in Caucasoid, Mongoloid and African population samples.

Materials and methods

A total of 3,652 conventional orthopantomograms were examined from 1,430 German, 1,597 Japanese and 584 black South African subjects, all aged between 12 and 26 and with known dates of birth. The patient’s identification number, gender, date of birth and date of X-ray were recorded. The patient’s age was calculated from the date of birth and the date of the X-ray. Table 1 shows the age and gender distribution of the sample sets.
Table 1

Age and gender distribution in the population samples examined

Age (years)

Number of German males

Number of German females

Number of Japanese males

Number of Japanese females

Number of South African males

Number of South African females

12

2

10

1

2

6

4

13

5

24

0

0

8

5

14

15

39

0

3

5

5

15

34

44

5

11

12

5

16

37

56

17

21

10

12

17

22

54

9

24

15

6

18

31

69

21

44

23

7

19

36

61

78

91

37

7

20

57

72

69

115

45

13

21

67

84

85

137

55

9

22

71

87

85

146

73

13

23

71

88

100

142

64

15

24

66

96

104

108

61

7

25

42

62

75

51

37

6

26

15

13

27

26

17

2

Total

571

859

676

921

468

116

The mineralization status of the third molars was assessed using the formation stages described by Demirjian et al. (1973) (Fig. 1). All these assessments were carried out by the same observer (A.O.).
Fig. 1

Diagrammatic representation of the formation stages A–H of third molars as described by Demirjian et al. (1973)

Results are expressed as mean ±standard deviation (SD) or median with lower and upper quartiles. Statistical analyses were performed using SPSS for Windows (Release 11.0.1, SPSS Inc. 1989–2001). To cope with outliers and/or skew distributions, differences between interesting groups of individuals were analysed using non-parametric statistical tests (Kruskal-Wallis test for several groups, Mann-Whitney-U test for two independent groups or Wilcoxon test for paired observations). Exact versions of the tests were applied to handle major differences in sample sizes (StatXact 5, Cytel Software Corp. Cambridge, MA). Significance was assessed at p< 0.05, exact and two-sided.

Results

In the present study, the Demirjian stages D–H were established for each sample population. Table 2 shows mean values and standard deviations as well as median values with lower and upper quartiles for tooth 48 at each stage in relation to ethnic group, age and gender. As the mean value and standard deviation for stage H, which marks the end of dental mineralization, depends on the age group under investigation, additional data are provided on age of first incidence and age of 50% frequency (Table 3).
Table 2

Statistical measurement data and significant population differences for tooth 48

Stage

Sample

Mean±SD

Median, LQ, UQ

D

German males

16.1±3.01, 2

15.3, 14.2, 16.9

German females

15.8±2.61

15.2, 14.2, 16.7

Japanese males

18.1±2.91, 3

16.8, 15.8, 20.0

Japanese females

18.0±2.51, 3

17.6, 15.9, 19.9

South African males

13.9±1.32, 3

13.9, 12.9, 15.1

South African females

14.5±2.33

14.1, 12.6, 15.7

E

German males

16.7±2.11, 2

16.1, 15.3, 17.7

German females

17.2±2.41, 2

16.8, 15.3, 18.9

Japanese males

18.6±2.91, 3

19.1, 15.7, 20.2

Japanese females

18.2±2.31, 3

18.5, 16.6, 19.7

South African males

15.2±2.42, 3

15.2, 13.4, 16.2

South African females

15.9±2.32, 3

15.6, 14.5, 16.8

F

German males

18.2±2.11

18.1, 16.7, 19.4

German females

19.0±2.51

18.7, 17.3, 20.7

Japanese males

19.8±2.21, 3

19.5, 18.8, 21.3

Japanese females

20.3±1.91, 3

20.2, 19.1, 21.7

South African males

18.7±2.33

18.7, 17.0, 20.3

South African females

17.4±2.53

17.5, 15.9, 19.2

G

German males

21.2±1.91

20.7, 19.9, 22.5

German females

21.6±2.12

21.7, 20.2, 23.1

Japanese males

21.8±2.11, 3

21.8, 20.2, 23.6

Japanese females

21.5±1.83

21.4, 20.2, 23.0

South African males

20.8±2.23

20.6, 19.1, 22.5

South African females

19.8±2.32, 3

20.1, 17.7, 22.1

H

German males

22.5±1.7

22.7, 21.4, 23.9

German females

22.9±1.7

23.2, 21.6, 24.1

Japanese males

22.5±1.8

22.8, 21.0, 23.9

Japanese females

22.1±1.8

22.2, 21.1, 23.5

South African males

22.6±1.9

22.8, 21.3, 24.2

South African females

22.4±1.9

22.7, 21.0, 23.8

1Statistically significant differences (p<0.05) between Japanese and Germans.

2Statistically significant differences (p<0.05) between South Africans and Germans.

3Statistically significant differences (p<0.05) between Japanese and South Africans.

SD Standard deviation.

LQ Lower quartile.

UQ Upper quartile.

Table 3

Age at initial incidence and at 50% frequency for stage H

Sample

Age at initial incidence

Age at 50% frequency

German males

17

20–21

German females

17

22–23

Japanese males

18

21–22

Japanese females

16

23–24

South African males

17

20

South African females

17

20–21

Statistically significant differences between German and Japanese males were noted for stages D–G of mineralization. Significant differences between Japanese and German females were observed for stages D–F. According to our findings, Japanese males and females were approximately 1–2 years older than their German counterparts when they reached stages D–F.

Significant age differences between South African and German males applied to stages D–E and significant age differences between South African and German females were observed for stages E and G. The South African subjects were approximately 1–2 years younger than the German subjects upon achieving these stages of mineralization.

Significant age differences between the South African and Japanese samples were ascertained for both genders at stages D–G. The South African subjects were approximately 1–4 years younger than the Japanese subjects upon reaching these stages.

A similar structure of significance was derived for teeth 18, 28 and 38.

Discussion

A question of major practical relevance to estimating age is whether the reference data customarily used for forensic diagnosis, derived from white North Americans on the one hand and central and northern Europeans on the other, can also be applied to members of other ethnic groups. In the context of this study, the term “ethnicity” is used exclusively to indicate a population’s origins by ancestry. Taking a typology of 110 genetic markers in over 1,800 indigenous populations as their basis, Cavalli-Sforza et al.(1994) divided the world’s population into 4 principal ethnic groups: Africans, Australians, Caucasoids and Mongoloids.

Extensive analysis of the literature on skeletal development has shown that ossification follows identical defined stages in the populations of all principal ethnic groups under investigation (Schmeling et al. 2000). Ethnic origin apparently exerts no noteworthy influence on the speed of ossification for a particular age group. Skeletal maturity is, on the other hand, greatly determined by the socio-economic status of a population. A relatively low socio-economic status delays development and is thus conducive to the underestimation of a subject’s age. Therefore, when the usual reference studies are applied to individuals from socio-economically less developed populations, these individuals are not disadvantaged in terms of criminal prosecution—quite the reverse.

In previous studies the methods used to assess dental mineralization varied from one author to another, so that the results are not directly comparable (Hägg and Matsson 1985; Pöyry et al. 1986).

Stages of formation have been defined differently in past publications by Gleiser and Hunt (1955), Moorrees et al. (1963) Kullman et al. (1992) and Köhler et al. (1994). The stages described in these classifications are sometimes numerous and difficult to match against each other. Moreover, a distinction is drawn between, for example one-quarter, one-third, one-half and two-thirds of the estimated future length of root, resulting in a rather subjective approach to estimation (Demirjian 1986).

Demirjian et al. (1973) presented a breakdown based on four distinct stages each for the crown and the root (stages A–H). The authors avoided numbering the stages in order not to create the impression that they are all of the same duration. Demirjian’s stages are defined by changes in shape and do not depend on speculative estimates of length. For this reason, we chose Demirjian’s classification as the most suitable for our investigation.

Few comparative studies are available on the subject of wisdom tooth mineralization.

Gorgani et al. (1990) examined 229 black and 221 white US citizens aged 6–14 years. Among the black subjects crown mineralization of the third molars was completed 1 year earlier.

Harris and McKee (1990) studied 655 white and 335 black US citizens aged 3.5–13 years. Whereas the black subjects reached the earlier stages of wisdom tooth mineralization about 1 year earlier, the gap appeared to narrow for later stages.

This trend is confirmed by the work of Mincer et al. (1993). They examined 823 US citizens (80% white, 19% black) aged 14–25 years but did not establish any significant differences in the time frame for wisdom tooth mineralization.

Daito et al. (1992) addressed wisdom tooth mineralization in 9,111 Japanese youngsters aged 7–16 years and compared their data with the values provided by Gravely (1965), Rantanen (1967) and Haavikko (1970) for Caucasoid populations. No significant differences were discovered.

These studies only lend themselves to limited comparison due to small sample sizes, varying methods and assessment by different observers. A further problem lies in the fact that the age data for subjects of black African origin were often not verified (Krumholt et al. 1971). Moreover, most available studies focus on the earlier stages of mineralization.

As far as the present authors are aware, this is the first study to supply comparable reference data on wisdom tooth mineralization for Caucasoid, Mongoloid and African population samples of forensically relevant age for whom dates of birth have been checked under standardized conditions. Potential interobserver error was eliminated by ensuring that all estimates were performed by the same observer.

Summing up our results, we can state that if we consider the predominant stage of mineralization in any given age group, the Caucasoid sample we investigated occupied the middle position by age for each stage of mineralization investigated. For stages D–F the Mongoloid subjects were on average 1–2 years older, whereas for stages D–G the African subjects were about 1–2 years younger than Caucasoid subjects who had obtained the same level of mineralization.

The population differences observed here may be due to differences in palatal dimensions between the ethnic groups surveyed. The largest palatal dimensions are observed in Africans and the smallest in Mongoloids, with Caucasoids assuming the middle rank (Byers et al. 1997). Inadequate space in the maxillary crest causes delay in wisdom tooth eruption, if not retention (Fanning 1962). In turn, retained wisdom teeth mineralize later than teeth where eruption has not been impeded (Köhler et al. 1994). This would explain why Caucasoid populations occupy the middle position in relative terms when it comes to wisdom tooth mineralization, while Mongoloid populations display a comparative delay and African populations a relative acceleration.

It may safely be concluded that population-specific standards would enhance the accuracy of forensic age estimates based on wisdom tooth mineralization in living subjects.

Acknowledgments

This study was supported by a grant from the Deutsche Forschungsgemeinschaft (SCHM 1609/1–1).

Copyright information

© Springer-Verlag 2004