Stature estimation based on tibial length in different stature groups of Spanish males

Journal Pre-proof Stature estimation based on tibial length in different stature groups of Spanish males Gonzalo Saco-Ledo, Jordi Porta, Izzet Duyar, Ana Mateos

PII:

S0379-0738(19)30385-8

DOI:

https://doi.org/10.1016/j.forsciint.2019.109973

Reference:

FSI 109973

To appear in:

Forensic Science International

Received Date:

25 February 2019

Revised Date:

20 September 2019

Accepted Date:

26 September 2019

Please cite this article as: Saco-Ledo G, Porta J, Duyar I, Mateos A, Stature estimation based on tibial length in different stature groups of Spanish males, Forensic Science International (2019), doi: https://doi.org/10.1016/j.forsciint.2019.109973

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

1

Stature estimation based on tibial length in different stature groups of Spanish males

Gonzalo Saco-Ledo a, b, Jordi Porta a, Izzet Duyar c, Ana Mateos b

a

Catalan School of Kinanthropometry, National Institute of Physical Education of Catalonia, University of Barcelona. Barcelona, Spain. b CENIEH, National Research Center of Human Evolution. Burgos, Spain. c Department of Anthropology. Faculty of Letters. Istanbul University. Istanbul. Turkey.

ro of

Affiliation address: Dr. Gonzalo Saco-Ledo. E-mail address: [email protected]. Full postal address: National Institute of Physical Education of Catalonia, University of Barcelona. Barcelona, Spain. Present address1 1

E-mail address: [email protected] (Saco-Ledo, G)

re

Abstract

-p

Corresponding author at: Centro Nacional de Investigación sobre la Evolución Humana (CENIEH). Paseo Sierra Atapuerca 3. 09002 Burgos, España.

It is well-known that secular trends affect human stature and constitution, and this fact

lP

should be taken into consideration in forensic anthropology, especially in stature estimation. Recently, stature-group-specific equations have been developed to take into account these variations. The aim of the present study is to estimate living stature

na

according to tibial length in different stature groups in a sample of Spanish adult males in order to improve the accuracy of previous equations. A cross-sectional study was conducted on a sample of 495 Spanish Caucasian participants who were randomized into

ur

two groups, the study group with 249 participants and the cross-validation group with 246 participants. Specific equations were obtained according to stature groups using the

Jo

15th and 85th percentiles as cut off points. The results showed that the coefficient of determination (R2) and standard error of estimation (SEE) were lower with the specific equations based on stature groups (R2 = 0.22–0.57; SEE = 2.12–2.66 cm) than the equation with all participants of the study group (R2 = 0.77; SEE = 3.29 cm). The equations were tested in the cross-validation group, whose results showed more accuracy in the equations for a stature < 185.9 cm (i.e., in people with short and medium statures). In conclusion, the stature-group-specific equations based on tibial lengths of Spanish adult males are more accurate for stature estimation than other equations that have been

2

formulated in the Spanish population. In forensic settings, it is recommended to use regression equations specific to stature groups when estimating stature.

Keywords: Forensic Anthropology Population Data; Stature estimation; Secular trend; Tibia; Anthropometry. 1. Introduction Stature estimation in forensic anthropological and medico-legal investigations has provided extensive information for human identification mainly since the 20th century

ro of

[1–8]. Different bone dimensions have been studied for stature estimation, including the bones of the upper limb [9–13], bones of the lower limb [14–24], skull [25, 26], sternum

[27, 28], parts of the vertebral column [29–31], fragmented bones [32, 33] and multiple bones [34–39]. The regression equations provided more accurate stature estimation with

-p

long bones than with short bones, and it is known that the association between stature and

long bones of the lower limb is higher than with the bones of the upper limb, especially

re

the femur and tibia [2, 16, 39]. The fact that they are the longest bones of the human body and contribute directly to stature may clarify this close association. However, more research in this area is needed due to the secular trends in human stature and constitution

lP

[40–42]. For instance, stature has increased in some Southern European countries, such as Spain [43, 44], limb length relative to body size has varied among modern and past humans [44], and environment has influenced leg length and body proportions more than

na

genes [45]. Thus, these proportional changes in the human body need to be taken into consideration in order to make more reliable predictions for forensic anthropological

ur

cases.

One of the most important problems encountered when determining the length of the long

Jo

bones for stature estimation is that shorter individuals are taller than they are, and the taller ones are shorter than they are [46, 47]. Therefore, one of the recommended methods to reduce the errors in stature estimation is stature-group-specific equations for short, medium, and tall statures, instead of a single general formula. In this regard, several studies on Turkish populations have analysed specific equations based on stature groups and have shown high accuracy for stature estimates [48–50]. Hence, it seems necessary to continue studying equations based on stature groups in different human populations. In fact, we have not found any studies that have obtained stature prediction equations with

3

Spanish individuals according to stature groups, and the others have shown a high standard error of estimation [15, 16, 31]. To offset the lack of studies, the aim of the present study is to estimate the living stature based on tibial length according to stature groups in a sample of Spanish adult males to improve the accuracy of previous equations.

2. Material and methods 2. 1. Study design A cross-sectional study was conducted on a Spanish sample, and the participants were

ro of

randomized into two groups, study and cross-validation. In the study group, three subgroups were made according to stature, following previous studies [48–50] with the 15th

and 85th percentiles of body height as cut off points. The same three stature sub-groups were made in the cross-validation group. Furthermore, the tibial length was categorized

in three sub-groups using the 15th and 85th percentiles as cut off points with the study

-p

group. Group T1, tibial length ≤ 37.8 cm; Group T2, tibial length between 37.9 and 43.1 cm; and Group T3, tibial length ≥ 43.2 cm. The reason for generating three sub-groups

re

based on length measurements is the assumption that body proportions will vary in short, medium and tall individuals and more successful height estimations will be made by

lP

creating equations specific to body height groups.

The study followed the recommendations of the Declaration of Helsinki on Human Rights [51]. In addition, the project was approved by the Clinical Research Ethics Committee of

2.2. Participants

na

the Sports Administration of Catalonia with the reference number 12/2015/CEICEGC.

ur

The sample consisted of 495 Spanish Caucasian adult male participants who were randomized into two groups, one study group with 249 participants and one cross-

Jo

validation group with 246 participants, using the random function of the Statistical Package for Social Sciences (SPSS). The categories of the study group were three stature groups, Group ST1, stature ≤ 170.9 cm (n = 37); Group ST2, stature between 171.0 and 185.8 cm (n = 175); and Group ST3, stature ≥ 185.9 cm (n = 37). The cross-validation group included 31, 183, and 32 participants, respectively. The participants were evaluated in the National Institute of Physical Education of Catalonia (INEFC) of Barcelona, the sports facilities of the Bernat Picornell Swimming

4

Pools in Barcelona, the Holmes Places Europolis Gym in Barcelona, the Faculty of Medicine of the University of Barcelona (UB), the Faculty of Sciences of Physical Activity and Sports in A Coruña and the gyms of the Club Method of A Coruña. The inclusion criteria were: age between 18 and 55 years and Spanish Caucasian ethnicity. The exclusion criteria were: obesity (BMI ≥ 30 kg/m2) and physical malformations that could affect the anthropometric evaluation. 2.3. Anthropometric measurements Two anthropometrists certified by the International Society for the Advancement of Kinanthropometry (ISAK) performed the anthropometric measurements between 2014

ro of

and 2016. The stature1 and tibial length2 were measured in centimetres by a Harpenden

Anthropometer (Holtain Model 601) and a Harpenden Stadiometer (Holtain Model 603), respectively, in the laboratory. Other anthropometric instruments used in the evaluations

were a square with attached level, an anthropometric bench of 40 cm high x 50 cm wide

-p

x 30 cm deep, and a segmometer (UWA) in the fieldwork. The anthropometrists followed the ISAK recommendations in the protocols to carry out the measurements [52]:

re

- Stature. The stretch stature method required the participant to stand with the feet and heels together and the buttocks and upper part touching the scale. The researcher placed

lP

the hands far enough along the line of the jaw of the participant to ensure that upward pressure was transferred through the mastoid process. The participant was instructed to take and hold a deep breath while keeping the head in the Frankfort plane, and the

na

researcher applied gentle upward lift through the mastoid process. The assistant watched that the feet did not come off the floor and the position of the head was maintained in the Frankfort plane. The measurement was taken at the end of a deep inward breath.

ur

- Tibial length. The subject was seated with the right ankle resting over the left knee so that the medial aspect of the leg was able to be measured (Fig. 1). The length between the

Jo

tibiale mediale3 and sphyrion tibiale4 was measured.

1

Stature is the perpendicular distance between the vertex and the bottoms of the feet. Tibial length is the linear distance between the most superior point on the medial border of the head of the tibia and the most distal tip of the medial malleolus. 3 Tibiale mediale is an anatomical landmark located on the most superior point on the medial border of the head of the tibia. 4 Sphyrion tibiale is an anatomical landmark located on the most distal tip of the medial malleolus. 2

5

2.4. Technical errors of the measurements The technical error of measurement (TEM) and intra-class correlation coefficient (ICC) were calculated with 20 individuals in the fieldwork [53]. The values were considered as acceptable based on the ISAK recommendations for this type of measurement (TEM % ≤ 1.0, intra-observer; TEM % ≤ 1.5%, inter-observer). 2.5. Statistical analysis Normality of the variables was verified using the Kolmogorov-Smirnov test, and the

ro of

equality of variances was verified through the Levene test in the variables. Group

comparisons were performed with the T test for independent samples, the Mann-Whitney U test, Kruskal-Wallis test and Scheffe test. Pearson correlations, regression equations, coefficients of determination and standard errors of estimation were calculated among the

-p

variables to verify the association between tibial length and stature. Normality and homoscedasticity of the residual were verified. Linear regression equations were devised

re

using the measurement data from the study group, and data from the cross-validation group were used to test these equations. The statistical analysis was performed with SPSS

lP

software (IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0, Armonk, NY: IBM Corp). The scatterplots were made by using SigmaPlot software (Version 12.0, Systat Software Inc., San Jose, CA, USA). The level of significance was

3. Results

na

established at p < 0.05.

ur

3.1. Anthropometric variables

Table 1 shows the descriptive statistics of the sample. No significant differences (p >

Jo

0.05) were found between the study group and the cross-validation group in the variables. The stature of both groups was almost the same, and the tibial length and tibia length ratio showed the same values. This means that the two groups had similar demographic and anthropometric characteristics (i.e., they were drawn from the same population). Figs. 2 and 3 show the scatterplot of stature and the tibial length of both groups. The correlation coefficient (Pearson’s r) between tibial length and stature was 0.87 (p ≤ 0.001) in the study group and 0.81 (p ≤ 0.001) in the cross-validation group. As can be seen, the association between tibial length and body height was slightly higher in the study group.

6

Table 2 shows significant differences (p ≤ 0.001) in the anthropometric variables between all stature sub-groups. The tibial length and tibia length ratio showed lower values in the shorter individuals and they increased as the stature increased. The results imply that the differences between the three classification groups was based on their stature threshold and thus the need for specific stature-group formulae.

Scatterplot diagrams (Figs. 4–6) indicate the effects of the application of stature-group specific equations in estimating the living body height. Figs. 4–6 depict the height estimations using the regression equation for short, medium, and tall individuals,

ro of

respectively, in the cross-validation data set. When the general formula was applied, 15

estimates were outside the confidence interval of 95% (Fig. 3), this number decreased to

13 by using stature-group-specific equations, with 1 estimate in the short sub-group (Fig.

4), 11 estimates in the medium sub-group (Fig. 5), and 1 estimate in the tall sub-group

re

-p

(Fig. 6).

3.2. Regression equations

lP

Table 3 shows the regression equations obtained to estimate the stature in the study group, with its correlation value (R), coefficient of determination (R2), adjusted coefficient of determination (AdjR2), and standard error of estimation (SEE). Although the R2 values

na

were lower for the group-specific regression equations, the SEE statistics were lower than those of all participants. The main reason for the lower values of R2 in the group-specific equations was that the total sample size was divided into three groups, decreasing the

ur

number of participants per group. On the other hand, the SEE values for group-specific equations were obviously lower than that of all participants. This means that the group-

Jo

specific equations may provide approximately 1.0 cm less erroneous predictions than those of the general equation.

3.3. Differences of stature estimates using the equations of the study group with the crossvalidation group As stated earlier, the cross-validation group was used to test the equations generated from the study group. Table 4 shows the differences between the measured and estimated

a Differences between stature using the equation developed from the study group on the cross-validation group. b Differences between stature using stature-group-specific equations developed from the study group on the crossvalidation group.

7

statures using the general and group-specific equations in the cross-validation group. Generally, the mean values for the two estimating techniques indicated that the groupspecific equations gave less erroneous predictions, particularly for the short and medium stature groups. When the stature-group-specific equations were used, the average of estimation error decreased by 2.96 cm in short individuals and 2.35 cm in medium individuals. On the other hand, in taller individuals, the group-specific equation did not contribute to the improvement of estimation accuracy. 4. Discussion In forensic anthropology literature, studies aiming to generate regression equations to

ro of

estimate living stature are generally derived from a single developmental sample.

However, it is important to test these equations on independent samples in order to reach more accurate equations. This condition has been fulfilled in our study showing high

accuracy, mainly in the short and medium stature groups. In addition, the stature-group-

-p

specific equations based on tibial length of the present study show more accurate stature estimation than other equations in Spanish male participants with stature mean between

re

170.7 and 175.2 cm [15, 16, 31].

It would be appropriate to start our assessment with the investigations carried out on a

lP

Spanish population. Muñoz et al. [15] studied different bone dimensions using radiographic imaging to estimate living stature on a Spanish sample. The SEE for the tibial length in males was 0.7 cm higher than the equation for all participants, and between

na

1.39 and 1.89 cm higher than the values of the stature-group-specific equations of the present study. In addition, the SEEs with other bones, such as the femur, fibula, humerus, radius and ulna, also show higher SEEs than the equation of all participants ranging from

ur

0.31 to 1.89 cm and the stature-group-specific equations ranging from 1.48 to 2.52 cm. Rodriguez et al. [16, 31] conducted two studies to estimate living stature with different

Jo

bone measurements that were evaluated by radiographic imaging in a Spanish population. The first study analysed the association in different measurements of the first cervical vertebra and the second cervical vertebra with the stature [16]. The second study was designed to estimate the stature with the maximum length of the first and second metatarsals [31]. The equations of both studies on a Spanish population showed between 2.98 and 4.94 cm higher SEEs than the stature-group-specific equations. The findings of

8

the Spanish populations reveal that the stature-group-specific equations are more successful in predicting more accurate living body height estimates. As for human populations outside Spain, recently, a study on one Southern European population by Gualdi-Russo et al. [17] estimated the stature based on percutaneous tibial length in Italian university students. The equation with the highest accuracy was obtained in Italian females (SEE = 4.62 cm). The other equations showed a 0.39 cm higher SEE in Italian males and a 1.39 cm higher SEE in the combined sexes as compared with the equation for Italian females. The regression equation of Italian males was obtained from participants with a mean stature of 178.2 cm, which was similar as compared to all

ro of

Spanish male participants. The study showed that correlations of tibial length and stature were statistically significant in both sexes and combined sexes. In addition, the authors

tested different equations with few participants from the same population, and the

equations showed better results than other equations used in the literature [1, 7, 46],

-p

mainly in males and the combined sexes. The authors suggested to use the equations for

unidentified mutilated or decomposed human bodies in a forensic context from Southern Europe. However, the equation of the Italian males had a 1.72 cm higher SEE than the

re

equation of all Spanish participants and between a 2.45 and 2.88 cm higher SEE according to the stature-group-specific equations. In this regard, Mohanty [18] studied the stature

lP

estimation based on percutaneous tibial length in a large sample of 1000 participants ranging from 20 to 80 years old, consisting of 500 of each sex from the Oriya population in India. The stature mean of Oriya male participants was 161.9 cm, which was a much

na

shorter stature as compared to the Spanish males. The correlation coefficient between the tibial length and stature in participants of both sexes was significant, and the equation of

ur

Oriya males showed a 0.57 cm higher SEE than the equation of Oriya females. The results indicated that the SEE of the equation in Oriya males was 0.42 cm lower than the equation

Jo

of all Spanish participants and between 0.26 and 0.75 cm higher than the stature-groupspecific equations. The authors considered that the SEE from the Oriya population was acceptable according to biological aspects to estimate the stature of a known population. In another study, Trotter and Gleser [2] analysed different long bones to estimate living stature from American White and Negro military individuals and the Terry Anatomical Collection. The measurements in military individuals were evaluated during life and the measurements of long bones after death. The measurements in the Terry Collection subjects were made on cadavers. Therefore, the authors considered two things for stature

9

estimation, the stature measured on cadavers was greater than the living individual and the estimation of stature should be reduced to obtain the estimated stature of individuals over 30 years old. In addition, the stature measurements of the military individuals were made by many different observers, which could increase the observational error and reduce the correlation between variables. The authors suggested the need to use specific equations for estimating stature according to sex in White and Negro subjects. Regardless, the study did not analyse stature-specific equations, but the equations for estimation of living stature based on tibial length showed a 0.08 cm higher SEE in White military males between 18 and 30 years old as compared to the equation according to all Spanish

ro of

participants and between a 0.71 and 1.25 cm higher SEE based on the stature-groupspecific equations. However, more precise results could be obtained from multiple regression equations, for instance, including the lengths of the tibia and femur although

the results showed still a higher SEE than the stature-specific equations of the present

study. On the other hand, Oliver et al. [7] tried to improve different classical formulae for

-p

estimating stature from a series of studies that were published in French. However, the number of participants was increased and the statistical method was improved. In one part

re

of their study, the authors analysed the dimensions of different long bones of 140 males whose stature mean was 170.3 cm before death and ranging from 20 to 32 years old. The

lP

simple linear regression equation for living stature estimation based on tibial length showed a slightly higher SEE of 0.29 cm (SEE = 3.58 cm, right side) as compared to the equation according to all Spanish participants and between a 0.92 to 1.46 cm higher SEE

na

based on the stature-group-specific equations. In the multiple linear regression equations including the femur and tibia (SEE = 3.17 cm, both sides), the accuracy was improved from the simple regression equations, but the SEE was still higher than the stature-group-

ur

specific equations of the present study.

Jo

Other studies analysed tibial length for stature estimation with simple regression equations in other populations, such as Mexicans [24, 34], Japanese [19, 35], Croatians [36], Thais [33, 37], and Koreans [38], which showed SEE statistics between 2.0 and 4.92 cm. In general, the stature-group-specific equations of this study indicated a lower error of estimation than the previous studies, except the equation for Croatian male cadavers that had a lower SEE. On the other hand, the multiple regression equations with bones such as the femur and tibia showed better results than the simple regression equations [2, 19, 37], although a higher error of estimation than that in the stature-group-specific

10

equations. In addition, the multiple regression equation in Japanese males showed a slightly lower SEE with the femur and tibia lengths than the equations of the medium and tall Spanish participants [35]. Nevertheless, we could not compare the SEE based on stature groups between studies, because the previous studies did not develop specific equations according to stature groups. Therefore, the stature-group-specific equations were compared with equations based on other approaches. In addition, the mean stature of Asian [18, 19, 30, 33] and Mexican [24, 34] participants was shorter than the mean stature of all Spanish participants, and some studies used cadavers [30, 36–38] or image processing [19, 30] to quantify the length of bones to estimate living stature.

ro of

When the findings of the studies conducted outside Spain were compared with the results of the present study, it was clear that the stature-group-specific regression equations provided better estimates of living stature. However, some authors argued that various

group-specific formulae did not yield more successful results than generic ones. Albanese

-p

et al. [39] studied univariate and multivariate sex-specific and generic equations to estimate stature with a sample from the Terry Collection using independent samples from the Forensic Anthropology Databank and the Lisbon Collection. The best results of

re

multivariate generic equations were obtained with the humerus, femur and tibia, although the femur was the bone with the best accuracy to estimate the stature with the univariate

lP

equation. The authors recommended using the generic equations, because they could estimate stature regardless of age at death, sex or population. However, they were aware that specific equations could sometimes have better accuracy, because the probability of

na

choosing the wrong sex to estimate the stature could have a negative impact on the results. The study examined various group-specific equations, but the authors did not include the

ur

stature-group-specific equations in their analysis. Nevertheless, the results of the present study suggest that when estimating body height, stature-group-specific equations provide

Jo

more accurate results.

Generally speaking, the results of studies carried out on various human populations indicated that stature group-specific regression equations yield more accurate body height estimates. This was probably due to body proportions [49], as mentioned earlier (Table 2), the ratio of tibial length to stature was not constant in different stature groups. It was proportionally shorter in the short people but proportionally longer in the tall people. Apparently, regression equations specific to the stature groups better reflect the proportional change. In a study conducted on a Turkish population using the stature-

11

group-specific equations from tibial length, the estimation error was reduced by approximately 2.5 cm for the short stature group and by about 3.0 cm for the tall stature group, whereas no significant change was observed in the medium stature subjects [48, 49]. In another study, Duyar et al. [50] examined the combination of the tibia and ulna bones to estimate body height based on stature groups and concluded that stature groupspecific equations provided more accurate estimates of stature, particularly for individuals who are short or tall relative to the average of the population. The results of this study on Spanish male adults suggest that the group-specific equations are effective in reducing the estimation error in the short and medium stature groups (Table 4). On the

ro of

other hand, it has been found that the mean prediction error of the tall group increased by more than 1.0 cm, unlike the Turkish sample. This difference observed among the tallest

participants of the two studies raises the question that the estimation of stature in forensic

anthropological cases may be more problematic in taller people. The two possible causes

occurring in these two populations [43, 49, 54].

-p

of this difference are constitutional differences and/or variations in secular trends

Therefore, it is necessary to take caution to estimate stature when we must choose an

re

equation to estimate stature, due to different characteristics between populations and the secular trends of stature and body proportionality [41–45]. It is known that distal

lP

segments of the limbs are more sensitive to environmental factors [55]. Some researchers suggest that the proportional change of the distal segments of the limbs is related to improvement of socioeconomic conditions, health status, and nutrition [41, 45, 56]. This

na

means that the tibial length will continue to increase absolutely and proportionally. Considering the fact that the improvement in socioeconomic and health conditions will

ur

continue in Southern European countries in the near future, it will have effects on the bones of the lower extremities and the accuracy of stature estimation. Additionally, more

Jo

studies conducted on different populations using stature groups are recommended in order to improve accuracy and obtain more prediction equations. In fact, the specific equations need to know the stature group and sex [57–59] before choosing the equation to estimate the stature, which could be a limitation of the present study given that female participants were not included. However, the categories of tibial length of the present study help to choose the right specific equation based on stature group, although we feel that the shortest and tallest stature groups including too few participants was a limitation. 5. Conclusions

12

The stature-group-specific equations for stature estimation show higher accuracy than other equations in Spanish participants. Therefore, this study could contribute to the development of population-specific standards in forensic anthropology for the 21st century. From a future perspective, it could be investigated whether the estimation error for stature in tall individuals is due to the difference between the populations or the variations in the secular trends. Moreover, it is recommended to analyse stature estimation based on stature groups with tibial length and other bones of the lower extremities in Spanish females and other worldwide populations.

Study concept and design: Gonzalo Saco-Ledo, Izzet Duyar, Jordi Porta. Methodology and supervision: Jordi Porta, Gonzalo Saco-Ledo, Izzet Duyar. Analysis and interpretation of data: Gonzalo Saco-Ledo, Izzet Duyar. Drafting of the manuscript: Gonzalo Saco-Ledo, Izzet Duyar. Statistical analysis: Gonzalo Saco-Ledo. Critical revision of the manuscript: Jordi Porta, Ana Mateos, Izzet Duyar.

-p

-

ro of

Author Contributions:

re

Funding sources

This research did not receive any specific grant from funding agencies in the public,

na

Declarations of interest

lP

commercial, or not-for-profit sectors.

ur

None.

Acknowledgements

Jo

We would like to express our most sincere appreciation to all participants in the study, and all the persons who gave us the permission to use the different facilities for the data collection. Dr. Irurtia (Director of Catalan School of Kinanthropometry at the University of Barcelona), Dr. Agrasar (Professor of Anatomy, Faculty of Sport Sciences and Physical Education at the University of A Coruña), Mr. Martínez (Director of Bernat Picornell Pools of Barcelona), Mr. Viladot (Administration, CEO Holmes Places), and Dr. Agell (Department of Cell Biology, Immunology and Neurosciences at the University of Barcelona).

13

References [1] Pearson K. Mathematical contributions to the theory of evolution. On the reconstruction of the stature of prehistoric races. Philosophical Transactions of the Royal Society of London, Ser. A Contain. Papers Math. Phys. Character. 1899;192:169-244. [2] Trotter M, Gleser GC. Estimation of stature from long bones of American Whites and Negroes.

Am

J

Phys

Anthropol.

1952

Dec;10(4):463-514.

https://doi.org/10.1002/ajpa.1330100407.

ro of

[3] Trotter M, Gleser GC. A re-evaluation of estimation of stature based on measurements of stature taken during life and of long bones after death. Am J Phys Anthropol. 1958 Mar;16(1):79-123. https://doi.org/10.1002/ajpa.1330160106.

[4] Dupertuis CW, Hadden JA Jr. On the reconstruction of stature from long bones. Am

-p

J Phys Anthropol. 1951 Mar;9(1):15-53. https://doi.org/10.1002/ajpa.1330090104.

[5] Fully G. New method of determination of the height. Ann Med Leg Criminol Police

re

Sci Toxicol. 1956 Sep-Oct;36(5):266-73.

[6] Telkkä A. On the prediction of human stature from the long bones. Acta Anat (Basel).

lP

1950;9(1-2):103-17. https://doi.org/10.1159/000140434.

[7] Olivier G, Aaron C, Fully G, Tissier G. New estimations of stature and cranial capacity

na

in modern man, J Hum Evo. 1978 Sep;7(6):513-518. https://doi.org/10.1016/S00472484(78)80020-7.

[8] Raxter MH, Auerbach BM, Ruff CB. Revision of the Fully technique for estimating Am

J

ur

statures.

Phys

Anthropol.

2006

Jul;130(3):374-84.

Jo

https://doi.org/10.1002/ajpa.20361. [9] Torimitsu S, Makino Y, Saitoh H, Sakuma A, Ishii N, Hayakawa M, Yajima D, Inokuchi G, Motomura A, Chiba F, Iwase H. Stature estimation based on radial and ulnar lengths using three-dimensional images from multidetector computed tomography in a Japanese

population.

Leg

Med

(Tokyo).

2014

Jul;16(4):181-6.

https://doi.org/10.1016/j.legalmed.2014.03.001. [10] Meadows L, Jantz RL. Estimation of stature from metacarpal lengths. J Forensic Sci. 1992 Jan;37(1):147-54. https://doi.org/10.1520/JFS13222J.

14

[11] Sağir M. Estimation stature from X-rays of metacarpals in the Turkish population. Anthropol Anz. 2006 Dec;64(4):377-88. [12] Krishan K, Sharma A. (2007) Estimation of stature from dimensions of hands and feet in a North Indian population. J Forensic Leg Med. 2007 Aug;14(6):327-32. https://doi.org/10.1016/j.jcfm.2006.10.008. [13] Giurazza F, Del Vescovo R, Schena E, Cazzato RL, D'Agostino F, Grasso RF, Silvestri S, Zobel BB. Stature estimation from scapular measurements by CT scan evaluation in an Italian population. Leg Med (Tokyo). 2013 Jul;15(4):202-8.

ro of

https://doi.org/10.1016/j.legalmed.2013.01.002. [14] Cordeiro C, Muñoz-Barús JI, Wasterlain S, Cunha E, Vieira DN. Predicting adult

stature from metatarsal length in a Portuguese population. Forensic Sci Int. 2009 Dec 15;193(1-3):131.e1-4. https://doi.org/10.1016/j.forsciint.2009.09.017.

-p

[15] Muñoz JI, Liñares-Iglesias M, Suárez-Peñaranda JM, Mayo M, Miguéns X,

Rodríguez-Calvo MS, Concheiro L. Stature estimation from radiographically determined

re

long bone length in a Spanish population sample. J Forensic Sci. 2001 Mar;46(2):363-6. [16] Rodríguez S, Miguéns X, Rodríguez-Calvo MS, Febrero-Bande M, Muñoz-Barús JI.

population.

Forensic

lP

Estimating adult stature from radiographically determined metatarsal length in a Spanish Sci

Int.

2013

Mar

10;226(1-3):297.e1-4.

https://doi.org/10.1016/j.forsciint.2012.12.006.

na

[17] Gualdi-Russo E, Bramanti B, Rinaldo N. Stature estimation from tibia percutaneous length: New equations derived from a Mediterranean population. Sci Justice. 2018

ur

Nov;58(6):441-446. https://doi.org/10.1016/j.scijus.2018.08.001. [18] Mohanty NK. Prediction of height from percutaneous tibial length amongst Oriya

Jo

population. Forensic Sci Int. 1998 Dec;98(3):137-41. https://doi.org/10.1016/S03790738(98)00144-3. [19] Hishmat AM, Michiue T, Sogawa N, Oritani S, Ishikawa T, Fawzy IA, Hashem MA, Maeda H. Virtual CT morphometry of lower limb long bones for estimation of the sex and stature using postmortem Japanese adult data in forensic identification. Int J Legal Med. 2015 Sep;129(5):1173-82. https://doi.org/10.1007/s00414-015-1228-9.

15

[20] Baba, M, Hyodoh, H, Okazaki S, Shimizu J, Mizuo, K, Rokukawa M, Watanabe S, Matoba K, Inoue, H. Stature estimation from anatomical landmarks in femur using postmortem

CT.

J

Forensic

Radiol

Imaging.

2015;

7,

28-32.

https://doi.org/10.1016/j.jofri.2016.11.002. [21] Hauser R, Smoliński J, Gos T. The estimation of stature on the basis of measurements of

the

femur.

Forensic

Sci

Int.

2005

Jan;147(2-3):185-90.

https://doi.org/10.14260/jemds/2014/2261. [22] Bidmos M. Adult stature reconstruction from the calcaneus of South Africans of descent.

J

Clin

Forensic

Med.

https://doi.org/10.1016/j.jcfm.2005.11.010.

2006

Jul;13(5):247-52.

ro of

European

[23] Singh B, Krishan K, Kaur K, Kanchan T. Stature estimation from different

combinations of foot measurements using linear and multiple regression analysis in a Indian

male

population.

J

Forensic

https://doi.org/10.1016/j.jflm.2018.12.007.

Leg

Med.

2019

Feb;62:25-33

-p

North

re

[24] Chay S, Batún J, Vázquez-Gómez A, Tiesler V, Dickinson F.New linear regression equations to calculate body height from tibial length in modern Maya populations. Homo.

lP

2018 Nov;69(6):340-346. doi: 10.1016/j.jchb.2018.09.007. [25] González-Colmenares G, Medina CS, Báez LC. Estimation of stature by cephalometric facial dimensions in skeletonized bodies: study from a sample modern skeletal

remains.

Forensic

Sci

Int.

2016

Jan;258:101.e1-6.

na

Colombians

https://doi.org/10.1016/j.forsciint.2015.10.016.

ur

[26] Shrestha R, Shrestha PK, Wasti H, Kadel T, Kanchan T, Krishan K. Craniometric analysis for estimation of stature in Nepalese population - A study on an autopsy sample.

Jo

Forensic Sci Int. 2015 Mar;248:187.e1-6. https://doi.org/10.1016/j.forsciint.2014.12.014. [27] Yonguc GN, Kurtulus A, Bayazit O, Adiguzel E, Unal I, Demir S, Acar K. Estimation of stature and sex from sternal lengths: an autopsy study. Anat Sci Int. 2015 Mar;90(2):89-96. https://doi.org/10.1007/s12565-014-0235-0. [28] Menezes RG, Kanchan T, Kumar GP, Rao PP, Lobo SW, Uysal S, Krishan K, Kalthur SG, Nagesh KR, Shettigar S. Stature estimation from the length of the sternum in South Indian males: a preliminary study. J Forensic Leg Med. 2009 Nov;16(8):441-3. https://doi.org/10.1016/j.jflm.2009.05.001.

16

[29] Klein A, Nagel K, Gührs J, Poodendaen C, Püschel K, Morlock MM, Huber G.On the relationship between stature and anthropometric measurements of lumbar vertebrae. Sci Justice. 2015 Dec;55(6):383-7. https://doi.org/10.1016/j.scijus.2015.05.004. [30] Torimitsu S, Makino Y, Saitoh H, Sakuma A, Ishii N, Hayakawa M, Inokuchi G, Motomura A, Chiba F, Hoshioka Y, Iwase H. Stature estimation in Japanese cadavers based on the second cervical vertebra measured using multidetector computed tomography.

Leg

Med

(Tokyo).

2015

May;17(3):145-9.

https://doi.org/10.1016/j.legalmed.2014.11.003. [31] Rodríguez S, Rodríguez-Calvo MS, González A, Febrero-Bande M, Muñoz-Barús

ro of

JI. Estimating height from the first and second cervical vertebrae in a Spanish population. Leg Med (Tokyo). 2016 Mar;19:88-92. https://doi.org/10.1016/j.legalmed.2015.08.002.

[32] Bidmos MA. Stature reconstruction using fragmentary femora in South Africans of

European descent. J Forensic Sci. 2008 Sep;53(5):1044-8. https://doi.org/10.1111/j.1556-

-p

4029.2008.00808.x.

re

[33] Fongkete, I, Singsuwan, P, Prasitwattanaseree, S, Riengrojpitak, S, Case, DT, Mahakkanukrauh, P. Estimation of stature using fragmentary femur and tibia lengths in a

Thai

population.

Aust

J

Forensic

Sci.

2015.

1-10.

lP

https://doi.org/10.1080/00450618.2015.1052758.

[34] Menéndez Garmendia A, Sánchez-Mejorada G, Gómez-Valdés JA. Stature

bones.

J

na

estimation formulae for Mexican contemporary population: A sample based study of long Forensic

Leg

Med.

2018

Feb;54:87-90.

ur

https://doi.org/10.1016/j.jflm.2017.12.019. [35] Hasegawa I, Uenishi K, Fukunaga T, Kimura R, Osawa M. Stature estimation formulae from radiographically determined limb bone length in a modern Japanese

Jo

population.

Leg

Med

(Tokyo).

2009

Nov;11(6):260-6.

https://doi.org/10.1016/j.legalmed.2009.07.004. [36] Petrovecki V, Mayer D, Slaus M, Strinović D, Skavić J. Prediction of stature based on radiographic measurements of cadaver long bones: a study of the Croatian population. J

Forensic

Sci.

4029.2007.00419.x.

2007

May;52(3):547-52.

https://doi.org/10.1111/j.1556-

17

[37] Mahakkanukrauh P, Khanpetch P, Prasitwattanseree S, Vichairat K, Troy Case D. Stature estimation from long bone lengths in a Thai population. Forensic Sci Int. 2011 Jul 15;210(1-3):279.e1-7. https://doi.org/10.1016/j.forsciint.2011.04.025. [38] Choi BY, Chae YM, Chung IH, Kang HS. Correlation between the postmortem stature and the dried limb-bone lengths of Korean adult males. Yonsei Med J. 1997 Apr;38(2):79-85. [39] Albanese J, Tuck A, Gomes J, Cardoso HF. An alternative approach for estimating stature from long bones that is not population- or group-specific. Forensic Sci Int. 2016

ro of

Feb;259:59-68. https://doi.org/10.1016/j.forsciint.2015.12.011. [40] Wilson RJ, Herrmann NP, Jantz LM. Evaluation of stature estimation from the database for forensic anthropology. J Forensic Sci. 2010 May;55(3):684-9. https://doi.org/10.1111/j.1556-4029.2010.01343.x.

-p

[41] Tanner JM, Hayashi T, Preece MA, Cameron N. Increase in length of leg relative to

trunk in Japanese children and adults from 1957 to 1977: comparison with British and

re

with Japanese Americans. Ann Hum Biol. 1982; 9:411-423.

[42] NCD Risk Factor Collaboration (NCD-RisC). A century of trends in adult human

lP

height. Elife. 2016 Jul 26;5. pii: e13410. https://doi.org/10.7554/eLife.13410. [43] Sánchez González E, Carrascosa Lezcano A, Fernández García JM, Ferrández

na

Longás A, López de Lara D, López-Siguero JP. Spanish growth studies: the current situation, their effectiveness and recommendations for their use. An Pediatr (Barc). 2011 Mar;74(3):193.e1-16. https://doi.org/10.1016/j.anpedi.2010.10.005.

stature

ur

[44] Ruff CB, Niskanen M, Maijanen H, Mays S. Effects of age and body proportions on estimation.

Am

J

Phys

Anthropol.

2019

Feb;168(2):370-377.

Jo

https://doi.org/10.1002/ajpa.23740. [45] Bogin B, Varela-Silva MI. Leg length, body proportion, and health: a review with a note on beauty. Int J Environ Res Public Health. 2010 Mar;7(3):1047-75. https://doi.org/10.3390/ijerph7031047. [46] Sjøvold T. Estimation of stature from long bones utilizing the line of organic correlation. Human Evolution, 1990; 5: 431–447.

18

[47] Konigsberg LW, Hens SM, Jantz LM, Jungers WL. Stature estimation and calibration: Bayesian and maximum likelihood perspectives in physical anthropology. Am J Phys Anthropol. 1998;Suppl 27:65-92. [48] Duyar I, Pelin C. Body height estimation based on tibia length in different stature groups. Am J Phys Anthropol. 2003 Sep;122(1):23-7. https://doi.org/10.1002/ajpa.10257. [49] Pelin C, Duyar I. Estimating stature from tibia length: a comparison of methods. J Forensic Sci. 2003 Jul;48(4):708-12. https://doi.org/10.1520/JFS2002228. [50] Duyar, I., Pelin, C., Zagyapan, R. A new method of stature estimation for forensic

ro of

anthropological application. Anthropol Sci. 2006;114(1):23-27. [51] World Medical Association. World Medical Association Declaration of Helsinki:

Ethical principles for medical research involving human subjects. JAMA. 2013 Nov

-p

27;310(20):2191-4. https://doi.org/10.1001/jama.2013.281053.

[52] Stewart A, Marfell-Jones, M, Olds T, de Ridder H. International standards for

the Advancement of Kinanthropometry.

re

anthropometric assessment. 2011. Potchefstroom, South Africa, International Society for

with

economy

class.

lP

[53] Porta J, Saco-Ledo G, Cabañas MD. The ergonomics of airplane seats: The problem Int

J

Ind

Ergon.

2019

Jan;

69:

90-95.

https://doi.org/10.1016/j.ergon.2018.10.003.

na

[54] Duyar I. Growth studies in Turkey (1917-2007): an anthropological perspective. Euras J Anthropol. 2010;1(2):59-78.

ur

[55] Seeman E. An exercise in geometry. J Bone Miner Res. 2002 Mar;17(3):373-80. https://doi.org/10.1359/jbmr.2002.17.3.373.

Jo

[56] Jantz LM, Jantz RL. Secular change in long bone length and proportion in the United States,

1800-1970.

Am

J

Phys

Anthropol.

1999

Sep;110(1):57-67.

https://doi.org/10.1002/(SICI)1096-8644(199909)110:1<57::AID-AJPA5>3.0.CO;2-1.| [57] Iscan MY, Miller-Shaivitz P. Am J Phys Anthropol. Determination of sex from the tibia. 1984 May;64(1):53-7. https://doi.org/10.1002/ajpa.1330640104.

19

[58] Slaus M, Bedić Z, Strinović D, Petrovečki V. Sex determination by discriminant function analysis of the tibia for contemporary Croats. Forensic Sci Int. 2013 Mar 10;226(1-3):302.e1-4. https://doi.org/10.1016/j.forsciint.2013.01.025. [59] González-Reimers E, Velasco-Vázquez J, Arnay-de-la-Rosa M, SantolariaFernández F. Sex determination by discriminant function analysis of the right tibia in the prehispanic population of the Canary Islands. Forensic Sci Int. 2000 Feb 28;108(3):165-

Jo

ur

na

lP

re

-p

ro of

72. https://doi.org/10.1016/S0379-0738(99)00205-4.

lP

re

Fig. 1. Percutaneous measurement of tibial length.

-p

ro of

20

48

na

46

40 38

ur

42

Jo

Tibial length (cm)

44

36 34 32

160

165

170

175

180

185

190

195

200

Stature (cm)

Fig. 2. Scatterplot with 95% prediction intervals (dotted lines) for tibial length and stature in the study group.

21

48 46

Tibial length (cm)

44 42 40 38

ro of

36 34 32 160

165

170

175

180

185

190

195

Stature (cm)

200

re

-p

Fig. 3. Scatterplot with 95% prediction intervals (dotted lines) for tibial length and stature in the crossvalidation group.

lP

42

na

38

36

Jo

34

ur

Tibial length (cm)

40

32

160

162

164

166

168

170

172

Stature (cm)

Fig. 4. Scatterplot with 95% prediction intervals (dotted lines) for tibial length and stature in the crossvalidation short stature group.

22

46

Tibial Length (cm)

44

42

40

38

ro of

36

34 170

172

174

176

178

180

182

184

186

Stature (cm)

188

re

-p

Fig. 5. Scatterplot with 95% prediction intervals (dotted lines) for tibial length and stature in the crossvalidation medium stature group.

lP

50

na

46

44

Jo

42

ur

Tibial length (cm)

48

40

184

186

188

190

192

194

196

198

Stature (cm)

Fig. 6. Scatterplot with 95% prediction intervals (dotted lines) for tibial length and stature in the crossvalidation tall stature group.

23 Table 1. Descriptive statistics of the study group and the cross-validation group Cross-validation group

(n = 249)

(n = 246)

SD

(Min.–Max.)

SD

Age (years)

28.6 ± 8.9

(18.0–54.1)

29.5 ± 9.0

Stature (cm)

178.5 ± 6.8

(163.2–196.7)

Tibial length (cm)

40.5 ± 2.4

TLR

22.6 ± 0.7

Min. = Minimum; Max. = Maximum; length *100/stature).

(Min.–Max.)

F

Sig

(18.1–53.8)

1.012

0.315

178.3 ± 6.6

(161.8–196.0)

0.747

0.388

(35.0–47.3)

40.5 ± 2.3

(34.6–47.3)

0.086

0.769

(20.3–24.9)

22.6 ± 0.8

(20.6–24.6)

2.625

0.106

= Arithmetic mean; SD = Standard deviation; TLR= Tibia length ratio (tibial

ro of

Variable

Study group

Table 2. Descriptive statistics of the study group based on stature groups ≤ 170.9 cm (n = 37)

Age (years)

F

Sig

27.7 ±8.5

1.3

0.258

189.3 ± 3.1

298.3

0.000

SD

30.8 ± 10.6

28.4 ± 8.6

SD

168.1 ± 2.3

178.4 ± 4.0

Tibia length (cm)

37.3 ± 1.2

40.4 ± 1.8

43.8 ± 1.6

138.6

0.000

TRL

22.1 ± 0.6

22.6 ± 0.6

23.1 ± 0.6

18.3

0.000

re

Stature (cm)

SD

≥ 185.9 cm (n = 37)

-p

Variable

171.0–185.8 cm (n = 175)

Jo

ur

na

lP

= Arithmetic mean; SD = Standard deviation; TRL= Tibia relative length (tibia length *100/stature).

24

Table 3. Regression equations obtained to estimate the stature from the study group Study group R

R2

S = (2.00 x TL) + 92.00

0.47

0.22

0.19

175

S = (2.00 x TL) + 98.00

0.75

0.57

≥ 185.9 cm

37

S = (1.20 x TL) + 140.40

0.60

All participants

249

S = (3.29 x TL) + 48.00

0.87

Stature group

n

≤ 170.9 cm

37

171.0–185.8 cm

Equation

AdjR2 SEE

F

P

2.12

9.92

0.003

0.56

2.66

229.9 0.001

0.36

0.35

2.51

20.29 0.001

0.77

0.77

3.29

831.5 0.001

ro of

S = Stature; SEE = Standard error of estimate; TL = Tibia length; R = Correlation; R 2 = Coefficient of determination; AdjR2 = Adjusted coefficient of determination.

Table 4. Differences between measured and estimated stature in the cross-validation group

Mean difference

≤ 170.9 cm

31

-3.36

170.1–185.8 cm

183

2.74

≥185.9 cm

32

All controls

246

Mean difference

SD

4.80

-0.40

3.31

4.90

-0.39

3.36

2.66

3.03

-3.90

1.85

-2.87

4.66

-

-

na ur Jo

SD

re

n

lP

Stature group

Stature-group-specific equations b

-p

Equation of all participants a