Age Estimation using Cephalometrics—A Cross-Sectional Study among Teenagers of Salem District, Tamil Nadu

Author:

Murali Kruthika1,Nirmal R. Madhavan2,Balakrishnan Sekar3,Shanmugam Shankar4,Altaf Syed Khalid5,Nandhini D6

Affiliation:

1. Reader, Department of Pedodontics and Preventive Dentistry, Vivekananda Dental College for Women, Tiruchengode, Tamil Nadu, India

2. Professor, Department of Oral and Maxillofacial Pathology, Rajah Muthiah Dental College and Hospital, Chidambaram, Tamil Nadu, India

3. Professor, Department of Oral and Maxillofacial Pathology, Vinayaka Mission Sankarachariyar Dental College, Salem, Tamil Nadu, India

4. Professor, Department of Public Health Dentistry, Vivekananda Dental College for Women, Tiruchengode, Tamil Nadu, India

5. Professor, Department of Orthodontics, Vivekananda Dental College for Women, Tiruchengode, Tamil Nadu, India

6. Student Internee, Vivekananda Dental College for Women, Tiruchengode. Tamil Nadu, India

Abstract

ABSTRACT Background: Age estimation is important not only in identifying dead body of a person but also in living persons since there is an increasing rate of juvenile delinquencies recorded every year. To avoid foul play by age fabrication, legal age estimation becomes important. Facial growth alteration takes place in the jawbones as age advances which can be observed with lateral cephalometry. Thus, the aim of the study is to create a regression formula for age estimation using cephalometrics of teenagers in Salem population. Materials and Methods: A cross-sectional study was done using 770 lateral cephalometrics of teenagers (13–19 yrs) in Salem population. Nine cephalometric points with two linear hard tissue measurements (condylion to mandibular plane (AFH) and palatal plane to menton (PFH)) and one angular soft tissue measurement (z angle) were recorded as predictor variables using a digital lateral cephalometric software (Carestream CS8100 SC) which were subjected to regression analysis using SPSS version 21.0 to develop a formula for age estimation. Results: Significant association on age was obtained for the two linear measurements. The regression formula generated for estimating the age was Age = 7.146 + 0.044 (AFH) + 0.146 (PFH) with R2 value = 0.674 Conclusion: Within the limitations of the present study, age estimation of teenagers in Salem population can be estimated. The predictability of the age can be increased by taking more cephalometric variables in generating the formula with increase in sample size.

Publisher

Medknow

Subject

General Pharmacology, Toxicology and Pharmaceutics,General Biochemistry, Genetics and Molecular Biology,Bioengineering,General Pharmacology, Toxicology and Pharmaceutics,General Biochemistry, Genetics and Molecular Biology,Bioengineering

Reference14 articles.

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3. Forensic age estimation in human skeletal remains current concepts and future directions;Franklin;Leg Med (Tokyo),2010

4. Age estimation from third molar development a radiological study;Darji;J Indian Acad Forensic Med,2011

5. Timing of human mandibular third molar formation;Liversidge;Ann Hum Biol,2008

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