Regression equation for estimation of stature from cephalofacial measurements in males. Regression equation for estimation of stature from cephalofacial measurements in females. The descriptive statistics for all the CF measurements recorded in the sample are shown in Table 3. Separate regression equations have been obtained for stature determination from each CF measurement individually for males [ Table 6 ] and females [ Table 7 ].
Stature estimation has been considered as one of the parameters of forensic anthropology which will assist in establishing the biological profile of a person. This technique is based on a principle that bones or human body parts correlate positively with the stature. Whenever someone wants to estimate stature from a given bone or human body part, there must be a known relationship of that bone or human body part with the stature.
Stature and cephalofacial measurements. This is not only because of the sex differences, but also because of ethnic, dietary, and climatic variations among individuals. Sometimes, obesity makes percutaneous measurements difficult and may increase the margin of error. However, if different measurements from different body parts are compared, we can conclusively determine the stature of an individual from unknown human remains. Considering this fact, an attempt had been made in the present study to estimate stature from CF measurements.
The findings in the present study indicate that all CF measurements are positively and significantly correlated with stature.
The formulae of stature estimation showed high degree of reliability which may be because the growth of skull CF is mainly genetically determined through local epigenetic factors such as growth of brain. Comparative statistical analysis among both genders revealed that out of all variables, horizontal head circumference emerged as the major predictor of stature among both males and females. The study indicates that the CF measurements were significantly higher in males as compared to females.
The results of the present study when compared with similar available studies on specific population of India varied slightly.
The results of the present study from the CF parameters vary slightly from that of the studies conducted by Krishan and Kumar in [ 9 ] and Krishan in [ 10 ] and widely from the study conducted by Kumar and Gopichand in [ 18 ] [ Table 8 ] for estimating stature using similar CF anthropometric parameters.
Although all these studies were conducted in neighboring regions of the present study population, few minor changes are evident on comparison. Although the present study was conducted among a mixed population belonging to the same geographical area, as compared to previous studies[ 9 , 10 ] which were conducted among people belonging to a particular community, the results are similar with certain minor differences.
Comparison of various studies conducted incorporating similar cephalofacial anthropometric parameters. Since studies by Krishan and Kumar[ 9 ] and Krishan[ 10 ] were conducted only among men, the data obtained from only male participants of the present study could be taken for comparison. BGD had the least correlation coefficient r value in the present study on contrary to the previous studies where MFL has the least r value among the considered CF parameters.
The results of the study conducted by Kumar and Gopichand[ 18 ] vary drastically from that of all the previous and the present studies. Although adequate sample size has been considered during the present study for the representative population [ Table 1 ], the participants fall under a particular age group of 20—25 years.
Hence, when generalizing the regression equation derived from the study participants to the entire population, certain factors such as age-related decline in stature need prime concern. Dequeker et al. Thinning of intervertebral discs, loss of vertebral body height, stooping posture, decreased tone in muscles, and osteoporosis are considered as the major reasons of age-related decline in stature.
Although the present regression equation may be applied in stature estimation taking into account the mean age-related stature loss, in future, studies should be conducted among people of different age groups and arrive at age specific-regression equations for stature calculation.
The population-, gender-, and age-specific regression models proposed will be of immense practical use in medicolegal, anthropological, and archaeological studies, where the total height of a participant can be calculated if the cranial dimensions are known.
From the present study, it can be concluded that the recommended anthropometric data provided serve as a template for the locality from which this study was carried out and confirm that there are geographical and sexual dimorphism in anthropometric parameters and therefore should be considered in forensic or criminal investigations.
A more extensive research on similar lines in different populations will help in establishing stature in the field of forensic science. The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given his consent for his images and other clinical information to be reported in the journal. The patient understand that name and initials will not be published and due efforts will be made to conceal identity, but anonymity cannot be guaranteed.
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Suheir Muzakkir, Sp. PD dr. Irsan Abubakar, Sp. Additional regressions can be found throughout the literature are listed in this table, as the above formula found in The Anatomy and Biology of the Human Skeleton Steel and Bramblett The humerus can be broken down into four segments. If the humerus is found in its entirety then its length can be used to estimate stature.
However, if only segments of the humerus are recovered then a combination of segments can be used to estimate stature. The tibia can be broken down into five segments. If the tibia is found in its entirety then its length can be used to estimate stature.
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