Facial Soft Tissue Thicknesses in Australian Adult Cadavers

• Published in: Journal of forensic sciences Vol. 51; no. 1; pp. 5 - 10
• Main Authors: Domaracki, Monica, Stephan, Carl N.
• Format: Journal Article
• Language: English
• Published: Malden, USA Blackwell Science Inc 01.01.2006; Wiley Subscription Services, Inc
• Subjects: Adults; Aged; Aged, 80 and over; Australia; Cadaver; Cephalometry; craniofacial identification; Face; Face - anatomy & histology; facial approximation; facial reconstruction; facial reproduction; Female; forensic anthropology; Forensic Anthropology - methods; forensic science; Forensic sciences; Gender differences; Humans; Male; Middle Aged; Needles; Sex Characteristics; superimposition; Tissues; Australia
• ISSN: 0022-1198; 1556-4029
• DOI: 10.1111/j.1556-4029.2005.00009.x

Craniofacial identification methods heavily rely on the knowledge of average soft tissue depths. This study measured soft tissue thicknesses of an Australian cadaver sample (N=33) using published needle puncture techniques at 13 anatomical locations. Data were compared and contrasted with other studies that used essentially identical samples and methods. Full descriptive statistics were calculated for measurements made in this study and means, medians, and modes were reported. Differences between mean values for males and females were found to be minimal (2.2 mm or less) and considerable overlap was found between the groups. There were no statistically significant differences between the soft tissue depths of the sexes (P>0.05). These findings indicate that differences between male and female soft tissue depths are of little practical significance for craniofacial identification and, therefore, data (means, standard deviations, and sample sizes) reported for Australians were pooled across the sexes and the studies. Although these new pooled means have increased statistical power, data distributions at some landmarks were skewed and thus emphasis is placed on median and modes reported for this study rather than upon the collapsed data means.