Development of age-estimation formula using postmortem oral findings: A pilot study

•Age estimation can support forensic activity through intraoral findings.•A new formula was developed to estimate age more accurately between 60 and 79 years old.•Normal tooth and untreated missing tooth correlated with age.•Tooth stump, attrition, and dental protheses also were correlated with age....

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Veröffentlicht in:Legal medicine (Tokyo, Japan) Japan), 2022-02, Vol.54, p.101973-101973, Article 101973
Hauptverfasser: Yamashita, Hiromi, Murase, Takehiko, Kondo, Hisayoshi, Umehara, Takahiro, Abe, Yuki, Shingu, Keita, Shinba, Yoriko, Mitsuma, Masahide, Ikematsu, Kazuya
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container_title Legal medicine (Tokyo, Japan)
container_volume 54
creator Yamashita, Hiromi
Murase, Takehiko
Kondo, Hisayoshi
Umehara, Takahiro
Abe, Yuki
Shingu, Keita
Shinba, Yoriko
Mitsuma, Masahide
Ikematsu, Kazuya
description •Age estimation can support forensic activity through intraoral findings.•A new formula was developed to estimate age more accurately between 60 and 79 years old.•Normal tooth and untreated missing tooth correlated with age.•Tooth stump, attrition, and dental protheses also were correlated with age. The goal of this pilot study was to develop an age-estimation formula and assess its effectiveness after evaluating individual intraoral findings. A total of 198 Japanese adults were included, and intraoral findings were collected from the corpses. To analyze the condition of each tooth, 20 items were established for intraoral findings, and seven tooth states were established. Logistic regression analysis was used to estimate the impact of age on each intraoral finding. Sequentially, linear regression was applied to verify the correlation between age and type of tooth, and multiple regression was used to correlate age-dependent factors. The intraoral findings with age dependency were tooth stump, edentulous jaw, attrition, no caries, dental prostheses, partial dentures, and complete dentures. Tooth stump, attrition, and dental prostheses showed positive multicollinearity. Missing tooth, extant tooth, normal teeth, and untreated lost teeth were age-correlated. Multiple regression analysis included age as the response variable and five factors as the explanatory variables in a new age-estimation formula, resulting in ± 10 years for 86.96% of cases (60–69 years old), 76.47% (70–79 years old), and 61.05% of all cases. The multiple correlation was 0.551, and the contribution rate of the multiple regression formula was 0.304. The accuracy of the proposed age-estimation formula was within ± 10 years for 61.05% of all subjects. However, the accuracy of age estimation in subjects aged 60–79 years was excellent (76.47–86.96%), which showed that this age-estimation formula would be effective for estimating the age of middle-aged to older subjects.
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Multiple regression analysis included age as the response variable and five factors as the explanatory variables in a new age-estimation formula, resulting in ± 10 years for 86.96% of cases (60–69 years old), 76.47% (70–79 years old), and 61.05% of all cases. The multiple correlation was 0.551, and the contribution rate of the multiple regression formula was 0.304. The accuracy of the proposed age-estimation formula was within ± 10 years for 61.05% of all subjects. 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subjects Adult
Age Determination by Teeth
Age estimation
Age Factors
Aged
Dental prothesis
Forensic activity
Humans
Intraoral findings
Linear Models
Middle Aged
Pilot Projects
Postmortem findings
Regression Analysis
Tooth
title Development of age-estimation formula using postmortem oral findings: A pilot study
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