|Year : 2018 | Volume
| Issue : 1 | Page : 7-17
Stature estimation from footprint dimensions in an adult Nigerian student population
Emeka Ambrose Okubike, Nwachukwu Mike Ibeabuchi, Olaleye Andrew Olabiyi, Michael Ebe Nandi
Department of Anatomy, College of Medicine, University of Lagos, Lagos, Nigeria
|Date of Web Publication||30-Mar-2018|
Emeka Ambrose Okubike
Department of Anatomy, College of Medicine, University of Lagos, Lagos
Source of Support: None, Conflict of Interest: None
Examination of footprints provides important evidence in crime scene investigations and helps in stature prediction of criminals. This study aimed to derive regression equations and multiplication factors for stature estimation from footprint dimensions in adult Nigerian medical students of the University of Lagos. Using an ink pad and a stadiometer, bilateral footprints and stature, respectively, were obtained from 230 subjects (100 males and 130 females) of Nigerian ancestry, aged 18-36 years upon satisfaction of the inclusion criteria and full written consent. The data collected were analyzed using SPSS version 20. Sexual dimorphism in stature and footprint dimensions was found to be statistically significant (P < 0.05) with males having greater values than the females. Analyses of bilateral asymmetry indicated significant left footprint preponderance (P < 0.05). There exist positive significant correlations (P < 0.05) between stature and footprint dimensions (T.1-T.5 lengths, breadth at ball [BAB], and breadth at heel [BAH]) in the males, females, and the pooled sample, with the only exception being the right and left breadths at heel in the males (r = 0.112 and 0.183, respectively). The right and left T.2 lengths exhibited the highest correlation with stature in the males, females, and the pooled sample with values of 0.704 and 0.703, 0.749 and 0.736, and 0.853 and 0.848, respectively. Footprint dimensions are significantly correlated with stature, with the footprint length (T.1-T.5) dimensions showing more reliability and accuracy in stature prediction than the footprint breadth (BAH and BAB) dimensions.
Keywords: Correlation, footprints, forensic, stature
|How to cite this article:|
Okubike EA, Ibeabuchi NM, Olabiyi OA, Nandi ME. Stature estimation from footprint dimensions in an adult Nigerian student population. J Forensic Sci Med 2018;4:7-17
|How to cite this URL:|
Okubike EA, Ibeabuchi NM, Olabiyi OA, Nandi ME. Stature estimation from footprint dimensions in an adult Nigerian student population. J Forensic Sci Med [serial online] 2018 [cited 2018 Sep 24];4:7-17. Available from: http://www.jfsmonline.com/text.asp?2018/4/1/7/228999
| Introduction|| |
An aspect of human identity that has received scant attention from forensic anthropologists is the study of human footprints made by the feet.  A footprint is an impression of the weight-bearing areas of the plantar surface of the foot, and personal identification using footprint analysis is an emerging biometric technique. , The characteristic features can provide useful clues to establish identity whenever complete or partial footprints are recovered at crime scenes.  Foot impressions are still found at crime scenes since offenders often tend to remove their footwears either to avoid noise or to gain better grip in climbing walls, etc., while entering or exiting.  Footprints can be found on newly waxed floors, freshly cemented surfaces, moistened surfaces, in dust, oil, paint, and blood at murder scenes.  Like fingerprints, footprints of an individual are unique to that individual. ,, Hence, footprints linked to a crime can be compared with a suspect's footprints as a means of confirming or ruling out involvement in that crime.
Analyses of foot , and footprints ,, help in estimation of an individual's stature because of the existence of a strong correlation between one's stature and foot size. For stature estimation from footprint parameters, researchers have indicated that toes-to-heel footprint length in a footprint has more reliability of prediction than from any other measurements, such as breadth at ball (BAB)/breadth at heel (BAH) and big toe breadth/length. Accurate estimation from known parameters is a fundamental aspect of science and is evident as an emerging approach in the area of footprints and stature estimation,  because foot length displays a biological correlation with stature that suggests the latter might be estimated from footprints. 
Various studies have been conducted on estimation of stature from the measurement of footprint dimensions. ,,[13-22] Nataraja and Hairunnisa  estimated stature from footprint length of an adult Malaysian population. A prospective study was carried out by Krishan  on adult male Gujjars of North India which sought to predict stature from footprint dimensions. Hemy et al. carried out a study aimed at estimating stature from footprint dimensions in an Australian population. Fawzy and Kamal  also derived regression equations for stature estimation from footprint dimensions in an Egyptian population. The above studies ,,, and a host of others have all established stature prediction models from footprint dimensions, but there is need for population-specific standards due to variability in the relative expression of morphological characteristics used to estimate sex, age, and stature.  In Nigeria, there is dearth of forensic data for stature prediction from footprint dimensions. Although Ukoha et al.  have estimated stature from footprint dimensions in an adult Nigerian population, very little is still known about such studies; hence, the present study aimed to help fill this lacuna by deriving regression equations and multiplication factors for stature estimation from footprint dimensions in an adult Nigerian population.
| Materials and Methods|| |
The study population comprised randomly selected Nigerian medical students of the College of Medicine , University of Lagos. The various Nigerian ethnic groups were represented in the study.
A total of 230 participants (100 males and 130 females) aged 18-36 years were recruited for this research work by simple random sampling. Participation of the research subjects was strictly on voluntary basis upon satisfaction of the inclusion criteria which required the participants to be within the age range, have both parents of Nigerian ancestry, and also free from any apparent symptomatic musculoskeletal, dermatological, or congenital deformity that might affect the measurements.
Ethical clearance to conduct this study was sought and obtained from Health Research Ethics Committee, College of Medicine , University of Lagos, with reference no: CM/HREC/12/16/084.
Sampling variables including gender, age, stature, and footprint dimensions were recorded in a data collection sheet.
0The stretch stature was measured with a stadiometer. This instrument a SECA 220 stadiometer (Germany) has a convenient eye-level read in case of measurement of very tall subjects. It has a measuring range of 60 cm-200 cm, and the measuring rod is graduated in 1 mm/1/8 inch. International Society for the Advancement of Kinanthropometry protocol for stature measurement was adopted for this study. 
The effect of diurnal variation can be reduced using the stretch stature method.  The stretch stature method required the subjects to stand with the feet together and the heels, buttocks, and the upper part of the back touching the scale. The head when held in the Frankfort plane need not be touching the scale, and this plane was achieved when the orbitale (lower edge of eye socket) was in the same horizontal plane as the tragion (the notch superior to the tragus of the ear). With the hands placed far enough along the line of the jaw of the subject to ensure that upward pressure is transferred through the mastoid process, the subject was instructed to take and hold a deep breath. An upward gentle lift through the mastoid process ensured that the head was still kept in the Frankfort plane. The headboard was then placed firmly down on the vertex, crushing the hair as much as possible. Measurement was taken at the end of an inward breath. The value was recorded to the nearest 0.1 cm.
A total of 460 footprints were obtained from the left and right feet of the sample population [Figure 1]. First, the blue-colored delible endorsing ink was poured into the foot ink pad, after which the soles of each participant were cleaned with soap and water. The subjects were then asked to step on the ink pad which already contains the endorsing ink, after which they were directed to place the inked foot firmly on the white duplicating A4 papers attached to the flat wooden board lying on the ground surface.
Marked anatomical landmarks
With the foot still on the paper, the following anatomical landmarks were carefully noted and marked on the paper close to the footprints using a sharp-pointed pencil:
- Mid-rear heel point (pternion)
- Medial metatarsal point (mt.m)
- Lateral metatarsal point (mt.l)
- Calcaneal concavity medial (cc.m)
- Calcaneal tubercle lateral (ctu.l).
A total of seven (7) measurements were taken on the left and right footprints. Following the method employed by Krishan,  the designated longitudinal axis (DLA) and baseline (BL) was drawn on the footprints in a bid to establish a definite axial orientation for length measurements. The DLA is from the pternion, which is the most posterior point of the rear heel margin, to the lateral side of the toe 1 margin. The DLA enables one to take foot length measurement from a specific landmark along the foot to the rear of the foot while keeping the line of measurement parallel to the DLA. The BL extends from the landmark pternion at the rear of the heel in both the medial and lateral directions while maintaining its perpendicular alignment with the DLA.
The measurements taken on the footprints include as follows:
- Footprint length measurements (T.1, T.2, T.3, T.4, and T.5 lengths) were taken from the pternion to the most anterior point of each toe, i.e., dt. 1, dt. 2, dt. 3, dt. 4, and dt. 5, respectively
- Footprint BAB was measured from the metatarsal lateral (mt.l), the most lateral point on the metatarsophalangeal joint of toe 5, to the metatarsal medial (mt.m), the most medial point of the metatarsophalangeal joint of toe1
- Footprint BAH was measured from the calcaneal concavity (cc.m) to calcaneal tubercle laterale (ctu.l).
All measurements were recorded to the nearest 0.1 cm.
After the collation of data, it was then analyzed using Statistical Package for the Social Sciences (SPSS) for Windows, Version 20.0, Armonk, New York: IBM Corporation. The prediction intervals were obtained using Minitab 18 Statistical Software (Minitab Inc.).
Mean, standard deviation, standard error of estimation (SEE), and independent and paired t-tests were used as statistical tools to analyze the data collected. Kolmogorov-Smirnov test was employed to test the normality of the sample. Comparisons were made of stature and footprint dimensions between the males and females using the Student's (independent) t-test to ascertain if sexual dimorphism exists in the study. Furthermore, comparisons made between corresponding right and left footprint dimensions of each subject was aimed at determining if bilateral asymmetry exists, and this was carried out using the paired t-test. The differences were considered statistically significant at 95% confidence level (i.e., when P < 0.05). Correlation coefficients (r), the standard measure of association between stature and the various parameters, were determined for the male and female subjects and also for the whole population. Coefficients of determination (R2 ) which is the statistical method that explains how much of the variability of a dependent variable can be caused or explained by its relationship to another factor were derived too.
Multiplication factors, which in this study are the mathematical relationships between stature and footprint dimensions, were also determined for the subjects; M.F = Stature χ Footprint dimensions. Linear and multiple regression equations were also derived using the variables and this serves as models for stature estimation.
| Results|| |
The results were summarized in [Table 1], [Table 2], [Table 3], [Table 4] [Table 5], [Table 6] [Table 7], [Table 8], [Table 9], [Table 10] and Graphs 1-6[Additional file 1], [Additional file 2], [Additional file 3], [Additional file 4], [Additional file 5], [Additional file 6].
|Table 1: Summary of the descriptive statistics of the footprint dimensions, age, stature, and also the bilateral differences in the footprint dimensions of the male population |
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|Table 2: Summary of the descriptive statistics of the footprint dimensions, age, stature, and also the bilateral differences in the footprint dimensions of the female population |
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|Table 3: Summary of the descriptive statistics of the footprint dimensions, age, stature, and also the bilateral differences in the footprint dimensions in the pooled sample |
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|Table 4: Gender differences in age, stature, and footprint dimensions of the study population |
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|Table 5: Pearson's correlation coefficients of stature with footprint dimensions of the males, females, and the pooled sample |
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|Table 6: Multiplication factor values for stature estimation from footprint dimensions of the males, females, and the pooled sample |
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|Table 7: Linear regression equations for stature estimation from footprint dimensions of the males, females, and the pooled sample |
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|Table 8: Estimated stature values using the linear regression equations from footprint dimensions of the males, females, and the pooled sample |
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|Table 9: Multilinear regression equations for stature estimation from combined footprint length dimensions of the male and female samples |
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|Table 10: Prediction intervals from the linear regression equations for stature estimation using footprint dimensions of the males, females, and the pooled sample |
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| Discussion|| |
Footprints are sometimes present as trace evidence at crime scenes and are also an accurate representation of foot size. The same principles regarding foot measurements therefore can be extrapolated to footprints. There is a growing body of research that has successfully documented the relationship between measurements from feet, including footprints and footwear, relative to living height. 
The descriptive statistics for the present study was recorded and tabulated for the males, females, and the pooled sample. Mean stature values of 176.44 ± 6.47 cm, 164.71 ± 6.70 cm, and 169.80 ± 8.79 cm were reported for the males, females, and the pooled sample of the present study respectively. Mean footprint length values (T.5L-T.1L) ranged from 22.08 ± 0.99 to 26.44 ± 1.19 cm and 22.14 ± 1.07 to 26.45 ± 1.21 cm for the right and left sides of the males. For the females, the mean footprint length values (T.5L-T.1L) for the right and left sides ranged from 20.15 ± 1.07 to 24.11 ± 1.20 cm and 20.12 ± 1.04 to 24.18 ± 1.20 cm, respectively. For the pooled sample, the mean footprint length values (T.5L-T.1L) for the right and left sides ranged from 20.97 ± 1.42 to 25.13 ± 1.67 cm and 20.99 ± 1.45 to 25.17 ± 1.65 cm, respectively. A similar study by Hairunnisa and Nataraja  on a Malaysian population which predicted stature from footprint dimensions reported lower stature and footprint values than was obtainable in the present study. They recorded mean stature values of 164.80 ± 5.70 cm, 153.50 ± 6.20 cm, and 159.20 ± 8.20 cm for the males, females, and pooled sample, respectively. The mean footprint length values (T.5L-T.1L) in the males ranged from 19.60 ± 1.0 to 23.20 ± 1.10 cm for both sides. For the females, the mean footprint length values (T.5L-T.1L) for the right and left sides ranged from 18.0 ± 0.90 to 21.20 ± 1.10 cm and 17.90 ± 1.0 to 21.20 ± 1.10 cm, respectively. For the pooled sample, the mean footprint length values (T.5L-T.1L) for both right and left sides ranged from 18.80 ± 1.30 to 22.20 ± 1.50 cm, respectively. Mean stature and footprint length values which lie in close approximation with those of the present study were reported by Ukoha et al. on a Nigerian Igbo population. They reported mean stature values of 175.70 ± 5.87 cm and 165.10 ± 6.41 cm for the males and females, respectively. The mean footprint lengths (T.5L-T.1L) for the males ranged from 21.96 ± 0.88 to 26.19 ± 1.09 cm and 22.07 ± 0.90 to 26.29 ± 1.04 cm for the right and left sides, respectively; while for the females, the mean footprint lengths (T.5L-T.1L) ranged from 20.61 ± 0.91 to 24.12 ± 1.09 cm and 20.51 ± 0.96 to 24.06 ± 1.11 cm for the right and left sides, respectively.
The values recorded for the present study revealed that the mean stature and footprint length measurements of an adult Nigerian student population are greater than that of Iban  and Bidayuh  Ethnics of East Malaysia, Urban Indian population of Chhattisgarh,  Tamils of the South Indian population,  Gujjars of the North Indian population,  and a Western Australian population.  However, when compared to the values reported by Ukoha et al.  on a Nigerian population, it can be discovered that the values from the present study lie in very close approximation with ones they reported. This inter- and intra-populational variability of stature and footprint dimensions in the Negroid and non-Negroid populations and also among similar populations in other climes indicates the need for the establishment of population-specific standards for improved forensic identification.
The human phenotype is diverse and our species can vary in body size and shape, both between and within populations. , In general, however, these differences tend to be geographically patterned, with variability greater between populations than within.  This variability is due to both genetic and environmental factors, many of which have been impacting our development over the course of human evolution.  Humans as species are unique in that we can apply cultural strategies that influence our adaptations to be genetic and environmental stresses. , The physical environment can also influence long-term genetic adaptations of a population.  Climate, altitude, and latitude can all affect the body shape and size of individuals from specific geographical regions.  The need to regulate body temperature and maximize oxygen intake has resulted in allometric differences that result in the underlying physiological functioning. For example, variations in the ratio between body surface area and body mass have been observed in populations from different climates, whereby populations from hotter regions tend to have longer limbs and more narrowbodies to increase ratio, and those from colder climes have relatively shorter limbs and wider bodies for the opposite effect. , The findings from the comparison of the stature and footprint dimensions from the present study and those carried out in other studies are in tandem with the observation by Samira et al. that higher values in body dimensions are discovered in Negroid populations. The little intra-populational variability between the present study and the study by Ukoha et al.  which are both studies on Nigerian populations can be explained on the basis of ethnic differences, where the former considered the Nigerian Igbo tribe only and the latter study considered adult Nigerians, irrespective of ethnicity, and it has been reported from previous studies by Fawehinmi et al.  and Numan et al. that there exist differences in the values of body dimensions of Nigerians of different ethnicities.
Another salient observation from this research and the studies by Hemy et al.,  Ukoha et al.,  and Abledu et al. on Australian, Nigerian, and Ghanaian populations, respectively, was that the T.1L in the males and females recorded the longest mean footprint length dimension, which indicates the prevalence of the Egyptian foot type in the aforementioned populations, ,, as opposed to the Greek foot type in the Malaysian populations , where the T.2L was the longest mean footprint length dimension in the males and the pooled sample, with the exception being the female population where the T.2L had the same mean value with T.1L. This provides an exception to the trend where there exists a progressive decrease in footprint length dimensions from the big toe to the small toe (T.1-T.5).
Considering real crime scenarios where the sex of the perpetrator is unknown, it is suggested that a better regression equation for stature estimation is one without sex indicators. Hence, the present study considered male and female subjects separately, as well as the pooled sample where stature prediction models from footprint dimensions were derived irrespective of gender.
From this study, gender differences (sexual dimorphism) in stature and footprint dimensions were found to be statistically significant (P < 0.05) with the males having higher values than the females. This is in tandem with the findings of Hairunnisa and Nataraja,  Hemy et al.,  and Ukoha et al.  in Malaysian, Australian, and Nigerian populations, respectively, where the existence of sexual dimorphism in stature and footprint dimensions were reported, with the males having significantly higher values than the females. Abledu et al. in their study on gender determination using footprint dimensions in a Ghanaian population also reported the existence of significant sexual dimorphism, with the males having significantly higher values than the females. There were no reports on sexual dimorphism in similar studies by Krishan,  Fawzy and Kamal,  and Nataraja et al. as they all considered only male samples. Earlier studies on foot dimensions by Wunderlich and Cavanagh,  Ashizawa et al.,  and Bob-Manuel and Didia  all reported the existence of gender differences, with the males having significantly higher values. This is because, humans show a degree of sexual dimorphism; and males on the average are larger than the females,  and it can be attributed to the fact that fusion of epiphyses of bones occurs earlier in females in comparison to males, as the latter has two more years of bony growth than the former.  Frey  also reported that women generally tend to have a narrower heel in relation to the forefoot and narrower feet than men relative to length. However, in contrast to these findings, Shukla et al.  in their study in India reported that their mean stature and footprint dimension values are slightly higher in the males than the females, though not significant statistically; a report which contrasts the finding of the present study and several other earlier reports. ,,, This phenomenon might be obtainable in societies where survival is based on physical labor; hence, sex differences in body dimensions are less because most members of the society have to perform similar laborious work irrespective of gender. 
The present study reports the existence of bilateral differences in footprint dimensions for the males, females, and the pooled sample, with the left footprint dimensions being significantly higher than the right (P < 0.05). Some differences with the negative (−) sign also indicated that the left-sided dimensions were higher, though not statistically significant. This observation is in consonance with the findings of Krishan  on a male Indian population, where T.2 and T.5 footprint lengths, with the BAB, were reported to be bilaterally asymmetric, being statistically higher on the left side. Nataraja et al.  also reported higher left footprint length measurements than the right on male Indian Tamils, with the T.1 and T.2 lengths being found to be statistically more asymmetric than the remaining footprint length parameters. Fawzy and Kamal  in their study on a male Egyptian population reported that all variables, except footprint BAB, were found to be significantly larger (P < 0.01) on the left side, which is very similar to the findings from the male population of the present study, where the existence of bilateral differences for all the footprint parameters were reported, with the only difference being that in the present study, footprint BAB demonstrated significant bilateral asymmetry, while T.1 length, T.5 length, and BAH exhibited bilateral differences that are not significant statistically. Ukoha et al.  reported the existence of bilateral differences in the footprint dimensions of the males and females in their study on a Nigerian population, an observation which conforms with the findings of the present study. In contrast, Hairunnisa and Nataraja  reported the nonexistence of significant bilateral asymmetry in footprint dimensions in their study on male and female Iban Ethnics of East Malaysia. Nataraja and Hairunnisa  also reported the nonexistence of significant bilateral asymmetry in footprint dimensions in the males and females of an adult Bidayuh population of East Malaysia. Furthermore, in the study by Shukla et al.,  bilateral asymmetry on the footprint of the urban population of Chhattisgarh, Central India, was not statistically significant. Their findings are also supported by similar reports by Philip  and Robbins,  who also observed nonsignificant bilateral asymmetry on the footprints of South Indian and US population, respectively. This indicates that the pattern of asymmetry is not consistent across all population groups.
It is common knowledge that right-handed persons prefer to kick with the right foot, and this has been correlated with the dominance of the contralateral cerebral hemisphere.  However, observations recorded by Singh  and Chhibber and Singh  suggested that in the majority of both right-handed and left-handed persons, the left lower limb is more used than the right. These observations include greater wear on the left shoe, a marked tendency to put the left foot forward first on starting to walk, and the ability to apply greater pressure with the left foot. This in turn enlarges the bones of the dominant foot and therefore produces a footprint of larger dimensions.  The preferred foot is mostly utilized for object manipulation or other activities involving motor coordination, while the contralateral nonpreferred side is used for postural and stabilizing support during such activities and may actually be subjected to higher mechanical loads than the preferred limb, causing the contralateral side to be heavier and longer. 
Correlation coefficients of stature with footprint dimensions in the males, females, and pooled sample in this study were derived and recorded. The findings of Ukoha et al.  are congruent with that of the present study since they reported that all footprint lengths exhibited significant correlation with stature. Their report on the noncorrelation of stature with the footprint BAH for both feet in the males conforms to the findings of this study, while the noncorrelation of stature with footprint BAB for both feet in their male sample contrasts the findings of the present study which reported significant correlation. For the female samples in both studies, there are huge similarities, because there exist positive significant correlations between stature and all the footprint dimensions. It was also observed that the present study exhibited higher correlation values than the report from the aforementioned study, indicating that the association between stature and footprint dimensions is stronger in the present study. The present study found the T.2 lengths in both feet to have the highest correlation with stature in the males, females, and the pooled sample. This is very similar to the report by Hairunnisa and Nataraja  for the male, female, and pooled sample in their study where T.2 length for the right footprint has the highest correlation with stature. However, for the left footprint, T.5 and T.1 lengths exhibited the highest correlation with stature for the male and female samples, respectively, with the T.1 length also being the dimension from the left footprint with the highest correlation for the pooled sample. Ukoha et al.  also reported that the T.1 length exhibited the highest correlation with stature for the right footprint dimensions in the males and also for both feet in the females. For the left footprint dimensions of the male population in their study, T.3 length exhibited the highest correlation with stature, and these observations are not similar to the findings of the present study. The findings of this study are however consistent with the reports by Hairunnisa and Nataraja  and Oberoi et al.  that the pooled sample exhibited the highest correlation with stature than when both genders were considered separately.
Stature estimates may not be exact and should always be expressed with range of error.  SEE values from the regression equations were derived for the estimation of stature from footprint dimensions of the males, females, and the pooled sample of this study. The present study reports that T.2 lengths for both feet exhibited the least SEE and the BAH showed the highest SEE for the males, females, and the pooled sample. This is not in keeping with the findings of Ukoha et al.,  which reported right and left T.1 lengths as the best predictors of stature with the least SEE values in the females and right footprint dimensions of the males. Furthermore, T.3 length provided the best and most reliable predictive equation in left footprint dimensions in the male sample of their study. For the present study, BAH was the least predictor of stature in both males and females, but this is only obtainable for the females in their study  with the males exhibiting the highest SEE values for the BAB. Krishan  reported that lower range of SEE values for right footprints dimensions (±2.16 cm-±3.68 cm) in his study on adult male Gujjars than was obtainable from the male subjects in the present study (±4.627 cm-±6.47 cm). Hairunnisa and Nataraja  also reported lower SEE range for the footprint length dimensions in male (±3.52-±3.73 cm) and female (±3.810-±4.294 cm) Iban Ethnics of East Malaysia. This indicates that stature prediction from footprint dimensions in the Indian and Malaysian populations may be more accurate than in the present study. However, higher range of SEE values was reported in the studies by Ukoha et al.  and Hemy et al. with values of range ±4.84-±9.85 cm for the males and ±5.11-±6.21 cm for the females in the former and values of range ±4.88-±6.43 cm and ±5.006-±6.926 cm for the males and females in the latter. This demonstrates that the regression equations for stature prediction from footprint dimensions in the present study will likely provide more reliability when compared to those established by the Ukoha et al.  and Hemy et al.
The present study considered a Nigerian population irrespective of their ethnicity. This is important because, Metropolitan cities in Nigeria such as Lagos, Onitsha, Jos, and Abuja are inhabited by Nigerians of different ethnicities and backgrounds. Hence, the findings of this study will provide forensic reference data on stature prediction from footprints, which will help curb the dearth of literature on such studies in a Nigerian population.
| Conclusion|| |
The current study has demonstrated the utility of stature estimation standards developed from footprint dimensions of an adult Nigerian population. The findings from this study have important applications in the formulation of biological profiles during forensic investigations and disaster victim identification through the provision of multiplication factors and regression equations for stature prediction from the footprint parameters employed in this study. Further research on this study will apply the derived regression equations on an independent sample, in a bid to test reliability of the established prediction models.
We are grateful to the medical students of the College of Medicine, University of Lagos, who were the research participants.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Jakhar JK, Vijay P, Paliwal P. Estimation of height from measurement of foot length in Haryana region. J Indian Acad Forensic Med 2010;32:231-3.
Ambeth K, Ramakrishna M. Legacy of footprints recognition: A review. Int J Comput Appl 2011;35:9-16.
Abledu JK, Abledu GK, Offei EB, Antwi EM. Determination of sex from footprint dimensions in a Ghanaian population. PLoS One 2015;10:e0139891.
Krishan K. Individualizing characteristics of footprints in Gujjars of North India - Forensic aspects. Forensic Sci Int 2007;169:137-44.
Nataraja M, Hairunnisa KM. Estimation of stature from footprint anthropometry using regression analysis: A study on the Bidayuh population of East Malaysia. Arab J Forensic Sci Forensic Med 2015;1:114-22.
Qamra SR, Sharma BP, Kaila P. Naked foot marks - A preliminary study of identification factors. Forensic Sci Int 1980;16:145-52.
Kennedy RB, Pressman IS, Chen S, Petersen PH, Pressman AE. Statistical analysis of barefoot impressions. J Forensic Sci 2003;48:55-63.
Kennedy RB. Uniqueness of bare feet and its use as a possible means of identification. Forensic Sci Int 1996;82:81-7.
Moorthy NT, Sulaiman SF. Individualizing characteristics of footprints in Malaysian Malays for person identification in forensic perspective. Egypt J Forensic Sci 2015;5:13-22.
Giles E, Vallandigham PH. Height estimation from foot and shoeprint length. J Forensic Sci 1991;36:1134-51.
Anil A, Peker T, Turgut HB, Ulukent SC. An examination of the relationship between foot length, foot breath, ball girth, height and weight of Turkish university students aged between 17 and 25. Anthropology 1997;55:79-87.
Robbins LM. Estimating height and weight from size of footprints. J Forensic Sci 1986;31:143-52.
Oberoi V, Kuruvilla A, Saralaya K, Rayee A, Ashok B, Nagesh K, et al
. Estimation of stature and sex from footprint length using regression formulae and standard footprint length formula respectively. J Punjab Acad Forensic Med Toxicol 2006;6:5-8.
Krishan K. Estimation of stature from footprint and foot outline dimensions in Gujjars of North India. Forensic Sci Int 2008;175:93-101.
Reel S, Rouse S, Vernon W, Doherty P. Estimation of stature from static and dynamic footprints. Forensic Sci Int 2012;219:283.e1-5.
Hairunnisa MK, Nataraja MT. Stature estimation from the anthropometric measurements of footprint in Iban ethnics of East Malaysia by regression analysis. J Forensic Sci Criminol 2014;2:201.
Nataraja M, Ahmad M, Boominathan R, Raman N. Stature estimation from footprint measurements in Indian Tamils by regression analysis. Egypt J Forensic Sci 2014;4:7-16.
Kanchan T, Krishan K, ShyamSundar S, Aparna KR, Jaiswal S. Analysis of footprint and its parts for stature estimation in Indian population. Foot (Edinb) 2012;22:175-80.
Fawzy IA, Kamal NN. Stature and body weight estimation from various footprint measurements among Egyptian population. J Forensic Sci 2010;55:884-8.
Hemy N, Flavel A, Ishak NI, Franklin D. Estimation of stature using anthropometry of feet and footprints in a Western Australian population. J Forensic Leg Med 2013;20:435-41.
Nataraja MT, Ang YL, Sanfee AS, Nik FNH. Estimation of stature from footprint and foot outline measurements in Malaysian Chinese. Aust J Forensic Sci 2014;46: 136-59.
Ukoha U, Egwu O, Ezeani M, Anyabolu A, Ejimofor O, Nzeako H, et.al.
Estimation of stature using footprints in an adult student population in Nigeria. Int J Biomed Adv Res 2013;4:11.
International Society for the Advancement of Kinanthropometry. International Stand Assess Under Dale, South Africa; 2006. p. 54-5.
Ridley M. Evolution. 3 rd
ed. Oxford: Blackwell Scientific Publications; 1993.
Shukla RK, Lodha AS, Das S. Stature estimation from footprint: A study on central Indian population. Eur J Forensic Sci 2017;4:11-19.
Stinson S. Growth variation: Biological and cultural factors. In: Stinson S, Bogin B, O'Rourke D, editors. Human Biology: An Evolutionary and Biocultural Approach. New York: Wiley-Liss; 2000. p. 425-64.
Ruff C. Variation in human body size and shape. Annu Rev Anthropol 2002;31:211-32.
Marks J. Human Biodiversity: Genes, Race and History (Foundations of Human Behavior). New Brunswick: Transaction Publishers; 1995.
Molnar S. Human Variation: Races, Types and Ethnic Groups. 5 th
ed. New Jersey: Prentice Hall; 2002.
Schutkowski H. Between Biology and Culture. United Kingdom: Cambridge University Press; 2008.
Lasker GW. Human biological adaptability. The ecological approach in physical anthropology. Science 1969;166:1480-6.
Samira H, Jahan AB, Laila AB, Fashiur R. Prediction of stature from hand length and breadth: An anthropometric study on Christian Garo tribal Bangladesh females. Bangladesh J Anat 2010;8:21-7.
Fawehinmi HB, Ogoun TR, Okoseimiema SC. Determination of femur stature ratio of the Ijaw and Ikwerre ethnic groups in Nigeria. Sci Afr 2013;12:28-39.
Numan AI, Idris MO, Zirahel JV, Amaza DS, Dalori MB. Prediction of stature from hand anthropometry: A comparative study in the three major ethnic groups in Nigeria. Br J Med Med Res 2013;3:1062-73.
Wunderlich RE, Cavanagh PR. Gender differences in adult foot shape: Implications for shoe design. Med Sci Sports Exerc 2001;33:605-11.
Ashizawa K, Kumakura C, Kusumoto A, Narasaki S. Relative foot size and shape to general body size in Javanese, Filipinas and Japanese with special reference to habitual footwear types. Ann Hum Biol 1997;24:117-29.
Bob-Manuel IF, Didia BC. Sexual dimorphism in foot dimensions among adult Nigerians. Internet J Biol Anthropol 2009;3:1.
Mysorekar VR, Nandedkar AN, Sarma TC. Estimation of stature from parts of humerus and radius. Med Sci Law 1982;22:178-80.
Ewunonu EO, Egwu AO, Eleudo AN, Ajoku KI. Bilateral foot asymmetry and sexual dimorphism in young adult Igbo people of South Eastern Nigeria. Eur J Biotechnol Biosci 2014;1:1-5.
Frey C. Foot health and foot wear for women. Clin Orthop 2000;372:32-4.
Ghosh S, Malik SL. Sex differences in body size and shape among Santhals of West Bengal. Anthropologist 2007;9:143-9.
Philip TA. Formulae for establishing stature from foot size by regression method. J Indian Acad Forensic Med 1990;12:57-62.
Robbins LM. A Method for Analyzing Footprints/Shoeprints. In: Proceedings of the 10 th
Triennial Meeting of the International Association of Forensic Sciences. England: Oxford; 1984.
Singh I. Functional asymmetries in lower limbs. Acta Anatomica 1970;77:131-8.
Chhibber SR, Singh I. Asymmetry in muscle weight and one-sided dominance in the human lower limbs. J Anat 1970;106:553-6.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9], [Table 10]