Evidence map›Paper›PMID 41857402›Full record

ArticleInternational journal of legal medicine2026

Effectiveness of combining third molar maturity index and palatal median suture maturity for age assessment in Yunnan adolescents.

Cheng Li, Fayi Zhao, Junjiang Cheng, Mengcheng Tang, Lanxin Yang, Lanjiang Li

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Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Cheng LiNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China.
Fayi ZhaoNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China.
Junjiang ChengNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China.
Mengcheng TangNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China.
Lanxin YangNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China.
Lanjiang LiNHC Key Laboratory of Drug Addiction Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, 650500, China. lanjiang1230@qq.com.ORCID http://orcid.org/0000-0001-6905-7193

Funding

2024 Joint project of Science and Technology Department of Yunnan Province-Kunming Medical University 202401AY070001-0982024 Scientific Research Fund of Education Department of Yunnan Province 2024J0210NHC Key Lab of Drug Addiction Medicine (Kunming Medical University)Open Projects Fund KN202414NHC Key Laboratory of Forensic Science (Xi'an Jiaotong University) Open Projects Fund 2024FYXH002the 2025 University Students' Innovation Training Program Project of Yunnan Province 1465
6 · The paper itself

Abstract

Accurately determining whether an individual has reached the legal age of adulthood (e.g., 18 years old) is crucial in judicial practice. With increasing global migration flows, developing reliable biological age assessment methods has become a significant challenge in forensic anthropology. This study aims to explore the value of combined third molar maturity and palatal midline maturity in assessing adulthood among Han adolescents in Yunnan Province through cone-beam computed tomography (CBCT), This study included dental CBCT images from 300 individuals aged 16 to 21 years, comprising 140 males and 160 females. The Demirjian developmental stage of the left mandibular third molar and the Angelieri maturity stage of the midpalatal suture were assessed and subjected to statistical analysis. Both the multiple linear regression model and Fisher’s discriminant function demonstrated statistical significance (P < 0.01). Both the Demirjian stage of the third molar and the palatal midline maturation stage showed significant positive correlations with chronological age (P < 0.01). The combined model constructed using multiple linear regression exhibited a higher coefficient of determination and lower prediction error compared to single-indicator models. The discriminant function designed for the 18-year-old threshold demonstrated good discriminatory efficacy. A multimodal age estimation model based on the combined development of third molars and palatal midline maturation enhances the accuracy of age estimation for Han adolescents in Yunnan Province, and can be used as a region-specific reference for forensic age assessment of this target population.

Indexed as

Age Determination by TeethMolar, ThirdAdolescentChinaCone-Beam Computed TomographyDiscriminant AnalysisFemaleHumansLinear ModelsMaleYoung AdultAge estimationCone-beam Computed TomographyForensic AnthropologyPalatal Suture MaturityThird Molar Maturity

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.