Through this process, the project succeeded in predicting the sex of individuals with 94 percent accuracy, age group with 83 percent accuracy, and region of origin with 61 percent accuracy. Researchers also report detecting Type II diabetes with 100 percent accuracy. The researchers collected hair samples from 97 U.S. residents and 94 residents of Jordan. Each participant completed a questionnaire on biometrics, nutritional habits, lifestyle, health, and region of origin. The samples were analyzed through bulk isotope-ratio mass spectrometry (IRMS), which is the traditional method of analyzing whole hair samples. A portion of the samples were used to conduct a more detailed isotopic analysis of the individual types of amino acids that compose the hair. The results of the analysis were then incorporated into an existing global database of approximately 3,500 individual isotope samples. Geographic analysis of the U.S. subjects' data is pending. Using combinations of isotope measurements, the researchers attempted to identify body mass index, age, and diet of the sample group members. They also attempted to predict the presence of Type II diabetes from the amino acids in the hair samples. The researchers report that "At this time, we do not expect these fundamental research findings to affect public policy or routine casework in crime laboratories; however, we have made significant strides toward the development of novel investigative leads."
Using Isotopes in Human Hair to Reveal Personal Characteristics for Forensic Investigations
NCJ Number
251662
Date Published
April 2018
Length
2 pages
Annotation
This is a summary of the full report on NIJ-funded research that investigated the potential of using isotopes in specific amino acids in human hair to obtain information on an individual's age, sex, race, body mass, genetic disorders, health, and region of origin.
Abstract
Date Published: April 1, 2018