Abstract
The determination of sex and the estimation of stature from bones play an important role in identifying unknown bodies, parts of bodies or skeletal remains. In medico-legal practice statements on the probable sex of a decomposed body or part of a body are often expected even during autopsy. The present study was, therefore, restricted to few easily accessible dimensions from bones which were prepared only by mechanically removing soft tissues, tendons and ligaments. The specimens came from the Anatomical Institutes in Munich and Cologne from the years 1994–1998 including a total of 143 individuals (64 males and 79 females). The mean age was 79 years (46–108), the mean body height 161 cm (134–189). The following measurements were taken: maximum humeral length (mean: 33.4 cm in males; 30.7 cm in females), vertical humeral head diameter (mean: 5.0 cm in males, 4.4 cm in females), humeral epicondylar width (mean: 6.6 cm in males; 5.8 cm in females), maximum ulnar length (mean: 26.5 cm in males, 23.8 cm in females), proximal ulnar width (mean: 3.4 cm in males, 2.9 cm in females), distal ulnar width (mean: 2.2 cm in males; 1.8 cm in females), maximum radial length (mean: 24.6 cm in males; 22.0 cm in females), radial head diameter (mean: 2.6 cm in males, 2.2 cm in females) and distal radial width (mean: 3.6 cm in males; 3.2 cm in females). The differences between the means in males and females were significant ( P<0.0005). A discriminant analysis was carried out with good results. A percentage of 94.93% of cases were correctly classified when all measures of the radius were applied jointly, followed by humerus (93.15%) and ulna (90.58%). Applied singly, the humeral head diameter allowed the best distinction (90.41% correctly grouped cases), followed by the radial length (89.13%), the radial head diameter (88.57%) and the humeral epicondylar width (88.49%). The linear regression analysis for quantifying the correlation between the bone lengths and the stature led to unsatifactory results with large 95%-confidence intervals for the coefficients and high standard errors of estimate.
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