The Foot 23 (2013) 136–139
Contents lists available at ScienceDirect
The Foot journal homepage: www.elsevier.com/locate/foot
Estimation of stature from the width of static footprints—Insight into an Indian model Tanuj Kanchan a,∗ , Kewal Krishan b , Disha Geriani c , Iman Sajid Khan c a b c
Department of Forensic Medicine, Kasturba Medical College, Mangalore, Manipal University, India Department of Anthropology, Panjab University, Chandigarh, India Kasturba Medical College, Mangalore, Manipal University, India
a r t i c l e
i n f o
Article history: Received 1 April 2013 Received in revised form 1 July 2013 Accepted 30 October 2013 Keywords: Forensic podiatry Forensic anthropology Stature estimation Static footprints
a b s t r a c t Background: Footprints give an estimate of the height of an individual using gender-dependent models derived for different population and ethnic groups. However, estimation of ethnicity, age and gender from a footprint may not always be possible in forensic case work. Objectives: The present study is done to develop models for stature (height) estimation from the width of footprints in the Indian population that are independent of the age and gender of individuals. Methods: The present research was conducted on 100 young adults from different regions of India. Footprints were obtained from both feet using standard techniques. Stature, and metatarsophalangeal joint (MPJ) Width (distance across the widest part of the forefoot) and calcaneal (Calc) Width (distance across the widest section of the heel) were measured on 200 footprints. Regression models were derived for estimation of stature. Results: A positive correlation is observed between footprint measurements and stature. Regression models derived from the forefoot region give a more accurate estimate of stature than the heel region of the footprint. Multiple linear regression models gave more accurate estimates of stature than the single linear regression models. Conclusions: Regression models derived in the study for Indian population may be valuable in establishing the stature of a footprint in practical scenario when the age and gender are unknown. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Forensic podiatrists deal with many aspects of pedal evidence in a legal context. This pedal evidence may take the form of partial or complete footprints, shoe prints, foot-step analysis, gait patterns, dismembered feet and parts of, and foot bones etc. Forensic podiatry can be expressed as the application of sound and researched podiatry knowledge and experience in forensic investigations, to show the association of an individual with the scene of crime, or to answer any other legal question regarding the foot or footwear that requires knowledge of the functioning foot [1,2]. Forensic podiatrists are working on the association of pedal evidence with the crime scene and criminals. They are also engaged in making forensic standards which can further be used in the evaluation of crime by individualisation of criminals. Footprints are generally recovered at the crime scenes especially in developing countries where the people are more likely to be walking barefoot [3,4]. Hence, the
∗ Corresponding author. Tel.: +91 9448252394; fax: +91 824 2428183. E-mail addresses: [email protected], [email protected] (T. Kanchan). 0958-2592/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foot.2013.10.015
evaluation and the examination of footprints are becoming increasingly important in crime scene investigations and other forensic examinations. Footprints are often encountered in cases pertaining to homicides, robberies and sexual assaults. The forensic significance of footprints has been established in the investigations conducted on the individualistic characteristics of footprints [5–11] and for the estimation of stature and gender from various footprint dimensions [11–16]. Stature and build are useful components of personal identification in forensic casework [17]. Estimation of stature is considered one of the more important parameters in establishing the biological profile of an individual. The burden of the investigating officer is reduced manifolds, if a forensic expert is able to estimate stature from the partial or complete footprints recovered at the crime scene. In most of the previously conducted studies on the estimation of stature from footprints, the authors [13,16,18,19] have focussed mainly on the estimation of stature from the length of footprints that has shown a better correlation with stature than any other dimension of the footprint. At times, only partial footprints are recovered from the crime scene, and consequently the models developed for the estimation of stature from footprint length alone cannot be utilised for identification purposes. The present research
T. Kanchan et al. / The Foot 23 (2013) 136–139
137
was thus, intended to develop models for stature estimation from the width of the static footprints in the Indian population that are independent of the age and gender of individuals. 2. Material and methods The study was conducted at Kasturba Medical College, Mangalore (affiliated to Manipal University), India. One hundred participants (50 males and 50 females) of Indian nationality from different regions of India were included in the study. The age of the participants ranged between 20 and 25 years. Healthy individuals without any apparent visual deformity of the spine/foot were included in the study. Participants were informed about the study before taking their footprints and an informed consent was obtained. 2.1. Techniques for taking stature and footprints The stature of each participant was measured in centimetres using standard techniques followed from Vallois [20]. Stature is the vertical distance between the point vertex and the floor. Participants were asked to stand in an erect posture with their backs against a wall without any headwear and footwear. The feet axis was parallel or slightly divergent and the head was in Frankfort horizontal plane when the stature was noted. The study participants were asked to wash their feet clean with soap and water. A clean glass plate was uniformly smeared with black duplicating ink using a roller. Participants were asked to apply their feet to the smeared plate and then transfer their footprints on to a sheet of white paper. Regular pressure was applied on the foot area to obtain the footprints. The footprints were taken one by one from both feet in each participant. Thus, a total of 200 footprints were examined. The measurements for the width of footprints were taken as described by Reel et al. [21]. The measurements included the MPJ Width (the measurement across the widest part of the fore footprint), and the Calc Width (the measurement across the widest section of the heel) in both left and right footprints of each participant. The measurements are illustrated in Fig. 1. The data obtained were statistically analysed using SPSS (Statistical Package for Social Sciences) version 11.0 computer software (SPSS, Inc., Chicago, IL, USA). The paired t-test was used to compare the means of the measurements of the right and left sides. Pearson’s correlation coefficients were calculated between stature and footprint measurements. Linear regression models were derived for estimation of stature from MPJ Width and Calc Width separately in left and right footprints. Fig. 1. Width measurements on a static footprint. MPJ Width: The measurement across the widest part of the forefoot on a footprint. Calc Width: The measurement across the widest section of the heel on a footprint.
3. Results Descriptive statistics for stature and width of footprints at forefoot and heel are shown in Table 1. Forefoot measurements
Table 1 Descriptive statistics of stature (cm) and foot print measurements (cm) in study participants (n = 100).
Stature MPJ Width – R MPJ Width – L Calc Width – R Calc Width – L
Range
Mean
S.D.
148.0–192.0 7.3–10.8 7.4–10.9 3.6–5.8 3.6–6.0
165.7 8.8 8.9 4.8 4.8
10.5 0.7 0.7 0.4 0.4
S.D. – standard deviation, MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left.
were observed to be larger than the heel region. Bilateral differences in footprint breadth were observed for forefoot region only (t = 3.171, p = 0.002). Statistically significant correlation was observed between stature and foot print breadth (Table 2). MPJ Width on the right side gives the maximum correlation (r = 0.698) with the stature, hence this can be considered as the most reliable measurement for estimating stature. Single linear regression models derived for footprints of the right side are likely to give more accurate estimates of stature than for the left side. Similarly, the single linear regression models derived for the footprints from the forefoot region provided a more accurate estimate of stature than those derived from the heel part of the footprint. This was shown by the low standard error of estimate (SEE) obtained for MPJ Width (7.6 cm for the right side and 7.7 cm for the left side) than for
138
T. Kanchan et al. / The Foot 23 (2013) 136–139
Table 2 Single linear regression models for reconstruction of stature. Model 70.870 + 10.754 (MPJ Width – R) 70.074 + 10.735 (MPJ Width – L) 95.666 + 14.744 (Calc Width – R) 97.546 + 14.314 (Calc Width – L)
S.E.E
R2
R *
7.6 7.7 8.3 8.5
0.698 0.687* 0.627* 0.596*
0.487 0.472 0.393 0.355
MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left, S.E.E – standard error of estimate (cm). * p-Value < 0.05.
Table 3 Multiple linear regression models for reconstruction of stature. Model
S.E.E
R
R2
65.317 + 7.782 (MPJ Width – R) + 6.684 (Calc Width – R) 66.552 + 8.294 (MPJ Width – L) + 5.305 (Calc Width – L)
7.3
0.728*
0.530
7.6
0.705*
0.496
MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left, S.E.E – standard error of estimate (cm). * p-Value < 0.05.
Calc Width (8.3 cm for the right and 8.5 cm for the left side) in the study. R and R2 values obtained for the multiple linear regression models were higher than those of single linear regression models. Hence, multiple linear regression models were shown to provide more accurate estimates of stature than single linear regression models. Single linear and multiple linear regression models derived in the study are shown in Tables 2 and 3 respectively. 4. Discussion The very fact that the foot dimensions were well correlated with the stature of an individual has been confirmed in earlier studies and can be utilised in estimating stature from the foot and footprints in forensic examinations [22–24]. Owing to the population variations and well-established male/female differences in growth and maturity, most of the studies on stature estimation from foot dimensions over the last decade have been conducted on various ethnic and population groups and consequently the regression formulae for estimation of stature are derived separately for males and females. Effect of age upon stature is well-known and hence, age also has been used as a co-variable in some of these regression models [25]. Thus, a number of age and gender dependent models for estimation of stature are available for various ethnic/population groups. In this regard, the recently published paper by Reel et al. [21] raises a very pertinent issue of problems associated with estimation of ethnicity, gender and age of a footprint in practical forensic case work. The applicability of age and gender specific regression models developed for each ethnic/population group may be limited if the same cannot be established on a footprint and hence, a need to develop regression formula that are independent of ethnicity, gender, and age. Mean dimensions of static footprints observed in the study by Reel et al. [21] were larger than those observed in the present study and have a narrower range for forefoot print width. These variations may be attributed to population variations as 95% of the participants in the study by Reel et al. [21] were Caucasians in contrast to the present study on population of Indian origin. Standard error of estimate (SEE) is a measure of the accuracy of a regression model in stature estimation. The present study indicates a higher SEE than that observed by Reel et al. [21] for the same dimensions. Genderspecific regression models derived from the length of footprints are
shown to give a more accurate estimate of stature than the models that are independent of gender [16]. A research on estimation of stature from foot dimensions describes the utility of universal regression models that are independent of gender [26]. Multiple linear regression models are considered better than single linear regression models in stature estimation [27] and the currentstudy findings confirm the same. The difference however, was observed to be marginal. Previous studies from India on the estimation of foot and foot print measurements have derived models separately for different population groups residing in the different parts of the country [12,13,22,25–27]. The present research presents regression models for stature estimation from the width of static footprints, which are independent of the region, age and gender of the individuals of Indian origin. These universal regression models may prove to be useful in establishing the stature of a footprint in a practical scenario when the age and gender are unknown. Participants in the present study were all young individuals. Foot measurements may vary with age [25] and hence, limiting the applicability of the models derived in the study on older individuals. Diverse population groups reside in India, and although the study attempts to generate models applicable to the general Indian population at large irrespective of their region of origin, the study sample may not be a representation of the same owing to its small sample size. The present study should be considered as a preliminary investigation and similar studies on larger sample inclusive of participants from different parts of India and of all age groups are recommended. The present study focussed on the static footprints, and we recommend similar studies investigate dynamic footprints also. The analysis of dynamic footprints may be significant in forensic investigations as recovery of dynamic footprints at the crime scene are common. Authors’ contributions TK conceived and designed the study, analysed and interpreted the data, wrote results, made all the tables and figures, and helped in the review of literature. KK contributed to the introduction and discussion of the paper, reviewed and edited the manuscript. DG and ISK analysed the footprints and helped in manuscript writing. All authors have read and approved the final manuscript. Funding The authors did not receive any specific funding for the aforementioned research. Conflict of interest None of the authors have a conflict of interest to declare. Acknowledgements The authors are grateful to the participants who voluntarily took part in the study. Authors are grateful to the Dean, Kasturba Medical College, Mangalore and Vice-Chancellor, Manipal University, India, for encouraging research and its publication in international journals of repute. References [1] Vernon DW, McCourt FJ. Forensic podiatry – a review and definition. Br J Podiatr 1999;2:45–8. [2] DiMaggio JA, Vernon W. Forensic podiatry – principles and methods. New York/Dordrecht/Heidelberg/London: Springer/Humana Press; 2011. [3] Krishan K. Determination of stature from foot and its segments in a north Indian population. Am J Forensic Med Pathol 2008;29:297–303.
T. Kanchan et al. / The Foot 23 (2013) 136–139 [4] Krishan K, Kanchan T. Foot length is a functional parameter for assessment of height. The Foot 2013;23:54–5. [5] Krishan K. Individualizing characteristics of foot prints in Gujjars of north India – forensic aspects. Forensic Sci Int 2007;169:137–44. [6] Robbins LM. The individuality of human footprints. J Forensic Sci 1978;23:778–85. [7] Kanchan T. Somatometry of the foot in identification of dismembered remains. J South India Medicoleg Assoc 2010;2:56–9. [8] Laskowski GE, Kyle VL. Barefoot impressions – a preliminary study of identification characteristics and population frequency of their morphological features. J Forensic Sci 1988;33:378–88. [9] Qamra SR, Sharma BR, Kaila P. Naked footmarks – a preliminary study of identification factors. Forensic Sci Int 1980;16:145–52. [10] Winkelmann W. Use of footprints, especially forefoot prints, from the forensic viewpoint. Z Rechtsmed 1987;99:21–128. [11] Robbins LM. Footprints – collection, analysis and interpretation. Springfield, IL, USA: Charles C. Thomas; 1985. [12] Jasuja OP, Singh J, Jain M. Estimation of stature from foot and shoe measurements by multiplication factors: a revised attempt. Forensic Sci Int 1991;50:203–15. [13] Krishan K. Estimation of stature from footprint and foot outline dimensions in Gujjars of North India. Forensic Sci Int 2008;175:93–101. [14] Atamturk D. Estimation of sex from the dimensions of foot, footprints, and shoe. Anthropol Anz 2010;68:21–9. [15] Reel S, Rouse S, Vernon W, Doherty P. Reliability of a two-dimensional footprint measurement approach. Sci Justice 2010;50:113–8. [16] Kanchan T, Krishan K, ShyamSunder S, Aparna KR, Jaiswal S. Analysis of footprints and its parts for stature estimation in Indian population. Foot (Edinb) 2012;22(3):175–80.
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[17] Krishan K, Kanchan T. In: Siegel JA, Saukko PJ, editors. Stature and build in encyclopedia of forensic sciences (second edition). London, UK: Academic Press, Elsevier; 2013. p. 49–53. [18] Fawzy IA, Kamal NN. Stature and body weight estimation from various footprint measurements among Egyptian population. J Forensic Sci 2010;55(4): 884–8. [19] Barker SL, Scheuer JL. Predictive value of human footprints in a forensic context. Med Sci Law 1998;38:341–6. [20] Vallois HV. Anthropometric techniques. Curr Anthropol 1965;6:127–43. [21] Reel S, Rouse S, Vernon W, Doherty P. Estimation of stature from static and dynamic footprints. Forensic Sci Int 2012;219(283):e1–5. [22] Krishan K, Kanchan T, Passi N. Estimation of stature from the foot and its segments in a sub-adult female population of North India. J Foot Ankle Res 2011;4(1):24. ˇ s R, Masnicová S. Stature estimation from various foot dimen[23] Uhrová P, Benuˇ sions among Slovak population. J Forensic Sci 2013;58(2):448–51. [24] Zeybek G, Ergur I, Demiroglu Z. Stature and gender estimation using foot measurements. Forensic Sci Int 2008;181(1–3):54.e1–5. [25] Kanchan T, Menezes RG, Moudgil R, Kaur R, Kotian MS, Garg RK. Stature estimation from foot dimensions. Forensic Sci Int 2008;179(241): e1–5. [26] Kanchan T, Menezes RG, Moudgil R, Kaur R, Kotian MS, Garg RK. Stature estimation from foot length using universal regression formula in a North Indian population. J Forensic Sci 2010;55:163–6. [27] Krishan K, Kanchan T, Passi N, DiMaggio JA. Stature estimation from the lengths of the growing foot – a study on North Indian adolescents. The Foot 2012;22(4):287–93.
Contents lists available at ScienceDirect
The Foot journal homepage: www.elsevier.com/locate/foot
Estimation of stature from the width of static footprints—Insight into an Indian model Tanuj Kanchan a,∗ , Kewal Krishan b , Disha Geriani c , Iman Sajid Khan c a b c
Department of Forensic Medicine, Kasturba Medical College, Mangalore, Manipal University, India Department of Anthropology, Panjab University, Chandigarh, India Kasturba Medical College, Mangalore, Manipal University, India
a r t i c l e
i n f o
Article history: Received 1 April 2013 Received in revised form 1 July 2013 Accepted 30 October 2013 Keywords: Forensic podiatry Forensic anthropology Stature estimation Static footprints
a b s t r a c t Background: Footprints give an estimate of the height of an individual using gender-dependent models derived for different population and ethnic groups. However, estimation of ethnicity, age and gender from a footprint may not always be possible in forensic case work. Objectives: The present study is done to develop models for stature (height) estimation from the width of footprints in the Indian population that are independent of the age and gender of individuals. Methods: The present research was conducted on 100 young adults from different regions of India. Footprints were obtained from both feet using standard techniques. Stature, and metatarsophalangeal joint (MPJ) Width (distance across the widest part of the forefoot) and calcaneal (Calc) Width (distance across the widest section of the heel) were measured on 200 footprints. Regression models were derived for estimation of stature. Results: A positive correlation is observed between footprint measurements and stature. Regression models derived from the forefoot region give a more accurate estimate of stature than the heel region of the footprint. Multiple linear regression models gave more accurate estimates of stature than the single linear regression models. Conclusions: Regression models derived in the study for Indian population may be valuable in establishing the stature of a footprint in practical scenario when the age and gender are unknown. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Forensic podiatrists deal with many aspects of pedal evidence in a legal context. This pedal evidence may take the form of partial or complete footprints, shoe prints, foot-step analysis, gait patterns, dismembered feet and parts of, and foot bones etc. Forensic podiatry can be expressed as the application of sound and researched podiatry knowledge and experience in forensic investigations, to show the association of an individual with the scene of crime, or to answer any other legal question regarding the foot or footwear that requires knowledge of the functioning foot [1,2]. Forensic podiatrists are working on the association of pedal evidence with the crime scene and criminals. They are also engaged in making forensic standards which can further be used in the evaluation of crime by individualisation of criminals. Footprints are generally recovered at the crime scenes especially in developing countries where the people are more likely to be walking barefoot [3,4]. Hence, the
∗ Corresponding author. Tel.: +91 9448252394; fax: +91 824 2428183. E-mail addresses: [email protected], [email protected] (T. Kanchan). 0958-2592/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foot.2013.10.015
evaluation and the examination of footprints are becoming increasingly important in crime scene investigations and other forensic examinations. Footprints are often encountered in cases pertaining to homicides, robberies and sexual assaults. The forensic significance of footprints has been established in the investigations conducted on the individualistic characteristics of footprints [5–11] and for the estimation of stature and gender from various footprint dimensions [11–16]. Stature and build are useful components of personal identification in forensic casework [17]. Estimation of stature is considered one of the more important parameters in establishing the biological profile of an individual. The burden of the investigating officer is reduced manifolds, if a forensic expert is able to estimate stature from the partial or complete footprints recovered at the crime scene. In most of the previously conducted studies on the estimation of stature from footprints, the authors [13,16,18,19] have focussed mainly on the estimation of stature from the length of footprints that has shown a better correlation with stature than any other dimension of the footprint. At times, only partial footprints are recovered from the crime scene, and consequently the models developed for the estimation of stature from footprint length alone cannot be utilised for identification purposes. The present research
T. Kanchan et al. / The Foot 23 (2013) 136–139
137
was thus, intended to develop models for stature estimation from the width of the static footprints in the Indian population that are independent of the age and gender of individuals. 2. Material and methods The study was conducted at Kasturba Medical College, Mangalore (affiliated to Manipal University), India. One hundred participants (50 males and 50 females) of Indian nationality from different regions of India were included in the study. The age of the participants ranged between 20 and 25 years. Healthy individuals without any apparent visual deformity of the spine/foot were included in the study. Participants were informed about the study before taking their footprints and an informed consent was obtained. 2.1. Techniques for taking stature and footprints The stature of each participant was measured in centimetres using standard techniques followed from Vallois [20]. Stature is the vertical distance between the point vertex and the floor. Participants were asked to stand in an erect posture with their backs against a wall without any headwear and footwear. The feet axis was parallel or slightly divergent and the head was in Frankfort horizontal plane when the stature was noted. The study participants were asked to wash their feet clean with soap and water. A clean glass plate was uniformly smeared with black duplicating ink using a roller. Participants were asked to apply their feet to the smeared plate and then transfer their footprints on to a sheet of white paper. Regular pressure was applied on the foot area to obtain the footprints. The footprints were taken one by one from both feet in each participant. Thus, a total of 200 footprints were examined. The measurements for the width of footprints were taken as described by Reel et al. [21]. The measurements included the MPJ Width (the measurement across the widest part of the fore footprint), and the Calc Width (the measurement across the widest section of the heel) in both left and right footprints of each participant. The measurements are illustrated in Fig. 1. The data obtained were statistically analysed using SPSS (Statistical Package for Social Sciences) version 11.0 computer software (SPSS, Inc., Chicago, IL, USA). The paired t-test was used to compare the means of the measurements of the right and left sides. Pearson’s correlation coefficients were calculated between stature and footprint measurements. Linear regression models were derived for estimation of stature from MPJ Width and Calc Width separately in left and right footprints. Fig. 1. Width measurements on a static footprint. MPJ Width: The measurement across the widest part of the forefoot on a footprint. Calc Width: The measurement across the widest section of the heel on a footprint.
3. Results Descriptive statistics for stature and width of footprints at forefoot and heel are shown in Table 1. Forefoot measurements
Table 1 Descriptive statistics of stature (cm) and foot print measurements (cm) in study participants (n = 100).
Stature MPJ Width – R MPJ Width – L Calc Width – R Calc Width – L
Range
Mean
S.D.
148.0–192.0 7.3–10.8 7.4–10.9 3.6–5.8 3.6–6.0
165.7 8.8 8.9 4.8 4.8
10.5 0.7 0.7 0.4 0.4
S.D. – standard deviation, MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left.
were observed to be larger than the heel region. Bilateral differences in footprint breadth were observed for forefoot region only (t = 3.171, p = 0.002). Statistically significant correlation was observed between stature and foot print breadth (Table 2). MPJ Width on the right side gives the maximum correlation (r = 0.698) with the stature, hence this can be considered as the most reliable measurement for estimating stature. Single linear regression models derived for footprints of the right side are likely to give more accurate estimates of stature than for the left side. Similarly, the single linear regression models derived for the footprints from the forefoot region provided a more accurate estimate of stature than those derived from the heel part of the footprint. This was shown by the low standard error of estimate (SEE) obtained for MPJ Width (7.6 cm for the right side and 7.7 cm for the left side) than for
138
T. Kanchan et al. / The Foot 23 (2013) 136–139
Table 2 Single linear regression models for reconstruction of stature. Model 70.870 + 10.754 (MPJ Width – R) 70.074 + 10.735 (MPJ Width – L) 95.666 + 14.744 (Calc Width – R) 97.546 + 14.314 (Calc Width – L)
S.E.E
R2
R *
7.6 7.7 8.3 8.5
0.698 0.687* 0.627* 0.596*
0.487 0.472 0.393 0.355
MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left, S.E.E – standard error of estimate (cm). * p-Value < 0.05.
Table 3 Multiple linear regression models for reconstruction of stature. Model
S.E.E
R
R2
65.317 + 7.782 (MPJ Width – R) + 6.684 (Calc Width – R) 66.552 + 8.294 (MPJ Width – L) + 5.305 (Calc Width – L)
7.3
0.728*
0.530
7.6
0.705*
0.496
MPJ Width – measurement across the widest part of the fore foot print, Calc Width – measurement across the widest section of the heel print, R – right, L – left, S.E.E – standard error of estimate (cm). * p-Value < 0.05.
Calc Width (8.3 cm for the right and 8.5 cm for the left side) in the study. R and R2 values obtained for the multiple linear regression models were higher than those of single linear regression models. Hence, multiple linear regression models were shown to provide more accurate estimates of stature than single linear regression models. Single linear and multiple linear regression models derived in the study are shown in Tables 2 and 3 respectively. 4. Discussion The very fact that the foot dimensions were well correlated with the stature of an individual has been confirmed in earlier studies and can be utilised in estimating stature from the foot and footprints in forensic examinations [22–24]. Owing to the population variations and well-established male/female differences in growth and maturity, most of the studies on stature estimation from foot dimensions over the last decade have been conducted on various ethnic and population groups and consequently the regression formulae for estimation of stature are derived separately for males and females. Effect of age upon stature is well-known and hence, age also has been used as a co-variable in some of these regression models [25]. Thus, a number of age and gender dependent models for estimation of stature are available for various ethnic/population groups. In this regard, the recently published paper by Reel et al. [21] raises a very pertinent issue of problems associated with estimation of ethnicity, gender and age of a footprint in practical forensic case work. The applicability of age and gender specific regression models developed for each ethnic/population group may be limited if the same cannot be established on a footprint and hence, a need to develop regression formula that are independent of ethnicity, gender, and age. Mean dimensions of static footprints observed in the study by Reel et al. [21] were larger than those observed in the present study and have a narrower range for forefoot print width. These variations may be attributed to population variations as 95% of the participants in the study by Reel et al. [21] were Caucasians in contrast to the present study on population of Indian origin. Standard error of estimate (SEE) is a measure of the accuracy of a regression model in stature estimation. The present study indicates a higher SEE than that observed by Reel et al. [21] for the same dimensions. Genderspecific regression models derived from the length of footprints are
shown to give a more accurate estimate of stature than the models that are independent of gender [16]. A research on estimation of stature from foot dimensions describes the utility of universal regression models that are independent of gender [26]. Multiple linear regression models are considered better than single linear regression models in stature estimation [27] and the currentstudy findings confirm the same. The difference however, was observed to be marginal. Previous studies from India on the estimation of foot and foot print measurements have derived models separately for different population groups residing in the different parts of the country [12,13,22,25–27]. The present research presents regression models for stature estimation from the width of static footprints, which are independent of the region, age and gender of the individuals of Indian origin. These universal regression models may prove to be useful in establishing the stature of a footprint in a practical scenario when the age and gender are unknown. Participants in the present study were all young individuals. Foot measurements may vary with age [25] and hence, limiting the applicability of the models derived in the study on older individuals. Diverse population groups reside in India, and although the study attempts to generate models applicable to the general Indian population at large irrespective of their region of origin, the study sample may not be a representation of the same owing to its small sample size. The present study should be considered as a preliminary investigation and similar studies on larger sample inclusive of participants from different parts of India and of all age groups are recommended. The present study focussed on the static footprints, and we recommend similar studies investigate dynamic footprints also. The analysis of dynamic footprints may be significant in forensic investigations as recovery of dynamic footprints at the crime scene are common. Authors’ contributions TK conceived and designed the study, analysed and interpreted the data, wrote results, made all the tables and figures, and helped in the review of literature. KK contributed to the introduction and discussion of the paper, reviewed and edited the manuscript. DG and ISK analysed the footprints and helped in manuscript writing. All authors have read and approved the final manuscript. Funding The authors did not receive any specific funding for the aforementioned research. Conflict of interest None of the authors have a conflict of interest to declare. Acknowledgements The authors are grateful to the participants who voluntarily took part in the study. Authors are grateful to the Dean, Kasturba Medical College, Mangalore and Vice-Chancellor, Manipal University, India, for encouraging research and its publication in international journals of repute. References [1] Vernon DW, McCourt FJ. Forensic podiatry – a review and definition. Br J Podiatr 1999;2:45–8. [2] DiMaggio JA, Vernon W. Forensic podiatry – principles and methods. New York/Dordrecht/Heidelberg/London: Springer/Humana Press; 2011. [3] Krishan K. Determination of stature from foot and its segments in a north Indian population. Am J Forensic Med Pathol 2008;29:297–303.
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