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Determining the Age-At-Death of Infants, Children, and Teens

Researchers have developed a tool that uses dental remains to accurately determine the age-at-death of the young and very young.
Date Published
April 16, 2024

Despite decades of research, determining the age-at-death of skeletal remains of individuals ranging from birth to about 20 years old (referred to in forensics as subadults) has proven daunting for forensic investigators. A team of researchers led by anthropologists Nicholas Herrmann, Texas State University, and Joseph Hefner, Michigan State University, has developed a statistical framework that enables more precise age estimations.

Herrmann’s project, supported by National Institute of Justice (NIJ) grant 2018-DU-BX-0182, created a large reference sample of developmental dental data from diverse international populations. It also addressed common issues encountered in forensic casework, such as missing teeth, that can both inform and restrict the ability of accurately estimating a decedent's dental age.

The project examines dental development within a transitional analysis framework that allows for statistical rigor in analyzing dental radiographs of individuals from the United States, Europe, and Africa. The researchers’ primary goal is to update existing dental modeling with a reference database that uses a representative sample from modern populations “to aid in forensic identification of subadult human remains.” The project examined the “age-at-transition” values of development for three baby and 10 permanent teeth in subadults. By focusing on specific teeth, the researchers created “the most appropriate numerical parameters from which to most accurately estimate age.”

The researchers had collected almost 12,000 radiographs when they submitted their final report to NIJ in May 2023 and anticipate having more than 13,500 images when they complete the project. The data represent subadults from various ethnic and socioeconomic backgrounds, including African American, European American, American Hispanic, British, and South African.

The resulting database is the basis for the Transition Analysis Dental Age (TADA) estimation tool, a publicly available online tool for estimating age using dental development codes. The NIJ-funded TADA website provides “forensic practitioners with an accurate age estimation method based on a large, demographically diverse, modern subadult sample that captures the variation in dental development.” 

Forensic investigators score teeth using a developmental code and then run an age analysis. “The final estimation includes a maximum likelihood age estimate based on the tooth stage of each tooth present,” the researchers said. It gives confidence levels of 90% or 95%, depending on the specific measurements.

Given that subadults represent a large portion of the missing and unidentified persons in the United States, it is important to improve several different identification methods. “Because it is not yet possible to reliably determine sex in subadult skeletal remains (outside of DNA analysis) and very little research has been conducted on determining ancestry for these individuals,” the researchers said, “age determination is currently the most reliable method of narrowing down candidate lists for identification.”

The TADA tool not only produces the most accurate age-at-death estimation possible, it also “will meet the Daubert standards for expert witness testimony,” the researchers said. Trial judges use the Daubert standard to determine if expert testimony has a valid scientific basis. The researchers have also consulted with a forensic odontologist to ensure that the TADA method conforms to American Board of Forensic Odontology standards.

Herrmann’s team continues to expand the database by working with institutions in India, Cyprus, and Guatemala. They intend to look at the impact of socioeconomic status on dental development in subadults to determine if there is a relationship between dental score patterns and demographic parameters, such as sex and ancestry.

About This Article

The research described in this article was funded by NIJ award 2018-DU-BX-0182, awarded to Texas State University, San Marcos, Texas. This article was based on the grantee report “Investigation of Subadult Dental Age-at-death Estimation using Transitional Analysis and Machine Learning Methods,” by Nicholas P. Herrmann and Joseph Hefner. 

Date Published: April 16, 2024