ArticleJournal of pharmacy & bioallied sciences2023
Age Estimation using Cephalometrics-A Cross-Sectional Study among Teenagers of Salem District, Tamil Nadu.
Article in Journal of pharmacy & bioallied sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Gonial Angle in Forensic Anthropology to Determine Age and Gender: A Population-Specific Analysis.Cureus · 2024Article
- Digital versus Manual Tracing in Cephalometric Analysis: A Systematic Review and Meta-Analysis.Journal of personalized medicine · 2024Review
- Article
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Authors and funding
6 authors.
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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.
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