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Estimation of stature from dimensions of the fourth lumbar vertebra in contemporary middle-aged Finns.
- Source :
-
Forensic Science International . Nov2018, Vol. 292, p71-77. 7p. - Publication Year :
- 2018
-
Abstract
- <bold>Background: </bold>Accurate stature estimation plays an essential role in the identification of unknown deceased individuals. For cases in which conventional methods of stature estimation are not applicable, we studied the stature estimation potential of the fourth lumbar vertebra (L4) among a large living sample of representative contemporary Finns. We also generated stature estimation equations for the middle-aged Finnish population.<bold>Material and Methods: </bold>Our study population comprised the Northern Finland Birth Cohort 1966 for which lumbar magnetic resonance imaging (MRI) scans and objective measurements of stature were available from midlife (n=1358). After screening the MRI scans for vertebral pathologies, we measured the maximum and minimum widths, depths and heights of the L4 body with high precision and reliability. We then calculated their sums and means together with approximations of vertebral cross-sectional area and volume. By constructing simple and multiple linear regression models around the L4 parameters, we generated equations for stature prediction, and investigated their accuracy on the basis of the adjusted R squared (R2) and standard error of the estimate (SEE) values of the models.<bold>Results: </bold>The multiple linear regression models of the mean width, depth and height of L4 yielded the highest prediction accuracies with the lowest prediction errors (for the entire sample, R2=0.621 and SEE=5.635cm; for men, R2=0.306 and SEE=5.125cm; for women, R2=0.367 and SEE=4.640cm).<bold>Conclusion: </bold>When conventional methods for estimating stature are not applicable, the lumbar vertebrae may be utilized for this purpose. Relatively accurate stature estimates can be given on the basis of only L4 dimensions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03790738
- Volume :
- 292
- Database :
- Academic Search Index
- Journal :
- Forensic Science International
- Publication Type :
- Academic Journal
- Accession number :
- 132826232
- Full Text :
- https://doi.org/10.1016/j.forsciint.2018.09.001