1http://dx.doi.org/10.20396/bjos.v20i00.8658796 Volume 20 2021 e218796 Original Article 1 Department of Social Odontology, Legal Odontology Division, Piracicaba Dental School, University of Campinas, São Paulo, Brazil. 2 Biostatistic of the post-graduation course from Paulista University, Brazil. 3 Forensic Odontology Service, Afrânio Peixoto Legal Medicine Institute, Rio de Janeiro, Brazil. Corresponding author: Luiz Francesquini Júnior Department of Social Odontology, Legal Odontology Division, Piracicaba Dental School, University of Campinas, Avenida Limeira, nº 901, Bairro Areião, Piracicaba, SP, Brazil, CEP: 13414-903, Phone Number: +55 19 21065281, e-mail: francesq@unicamp.br Editor: Dr Altair A. Del Bel Cury Received: March 20, 2020 Accepted: March 6, 2021 Evaluation of effectiveness of cranial morphological characteristics for sex estimation in a Brazilian sample Larissa Stasievski1 , Viviane Ulbricht1 , Vanessa Gallego Arias Pecorari2 , Vanessa Moreira Andrade1,3 , Luiz Francesquini Júnior1,* Forensic physical anthropometry allows the determination of animal species and estimates sex, ancestry, age and height. Aim: To analyze the effectiveness of a cranioscopic/ morphological evaluation for sex estimation with a sample of the Brazilian mixed-race population by conducting a qualitative visual assessment without prior knowledge of sex. Methods: This is a blind cross-sectional study that evaluated 30 cranial characteristics of 192 skulls with mandible, 108 male and 84 female individuals, aged 22 to 97 years, from the Osteological and Tomographic Biobank. The qualitative characteristics were classified and compared to the actual sex information of the Biobank database. The statistical analysis was used to calculate de Cohen’s kappa coefficient, total percentage of agreement, sensitivity and specificity of visual sex classification. Results: Of the 30 cranial variables analyzed, 15 presented moderate degree of agreement, achieving value of Kappa test between 0.41–0.60: Glabella (Gl), Angle and lines (At), Mental eminence (Em), Mandible size (Tm), Cranial base (Bc), Mouth depth (Pb), Nasal aperture (Anl), Supraorbital region (Rs), Orbits (Orb), Mastoid processes (Pm), Alveolar arches (Aa), Zygomatic arch (Az), Orbital edge (Bo), Supraorbital protuberances (Pts), and Supramastoid crests and rugosity (Crsm). The Facial physiognomy (Ff) presented substantial reliability (0.61-0.80) with 89.8% sensitivity for male sex and 70.2% specificity. Conclusions: Cranial morphological characteristics present sexual dimorphism; however, in this study only 15 variables showed moderate degree of agreement and can be used in sex estimation. Only one variable (Ff) 81.2% total agreement with substantial reliability. Quantitative methods can be associated for safe sex estimation. Keywords: Sex characteristics. Forensic anthropology. Skull. Mandible. https://orcid.org/0000-0003-4516-5493 https://orcid.org/0000-0001-7441-7667 https://orcid.org/0000-0002-0300-5697 https://orcid.org/0000-0002-1291-9642 https://orcid.org/0000-0002-6344-3488 2 Stasievski et al. Introduction In an anthropological examination for forensic purposes, the determination of sex, species, ethnic group and estimated age and height are essential as such information help build an individual’s biological profile1,2 and subsequent identification. Musilová et al.2 (2016) e Durić et al.3 (2005) portrayed that the pelvis is the structure of the human skeleton that presents the highest degree of sexual dimorphism, being the most reliable bone for sex estimation. According to Musilová et al.2 (2016) the pelvis responds with evolutionary adaptation to bipedal locomotion and birth mechanisms, enabling parturition of children with relatively big brains. But, in situations where the skeleton is not complete4 or when the pelvis is not fully recov- ered, sex estimation can be achieved by performing a cranial analysis. As mentioned by Spradley and Jantz4 (2011), the skull has a high correct classification of sex, of 90-91%. In a skull examination, an anthropologist may use quantitative (metric) and/or quali- tative (non-metric) methods2,5,6. Lewis and Garvin (2016)7, Biancalana et al. (2015)8, Godde (2015)9, Tallman and Go (2018)10, Walker (2008)11 and Langley et al. (2018)12 are some authors which esti- mated the sex based on the skull morphology. This qualitative analysis is based on visual examination of the presence or degree of expression of morphological charac- teristics7, but despite its subjectivity8-11,13, may be the only possible method in cases of bone fragmentation7. An examination of non-metric traits also ensures an easy and fast analysis, without requiring any devices7,10,12. In general, bone aspects such as prominences, crests and apophyses are more nota- ble in men, while women have more delicate and less pronounced characteristics14. Walker (2008)11 stated that the accuracy of sex determinations based on visual inspection depends on the osteologist’s familiarity with the population being studied. And Franklin et al. (2013)15 mentioned that the forensic practitioner should access an osteological database for their specific geographic jurisdiction. This changes in skull shape and size are population-specific11,15, and can be explained because each population is submitted to its own forces of evolution1,9,10. Environmen- tal interventions8,10,15, nutritional status8,9, temporal changes8-12 and biomechanical processes related to neck, face and head movement9 can alter cranial morphological aspects, smoothing or enhancing the robustness of some characteristics. In view of these situations, this study aimed to analyze the effectiveness of a cranio- scopic/morphological evaluation (a qualitative visual assessment without prior knowl- edge of sex) with a sample of the Brazilian mixed-race population, for sex estimation. Materials and methods This study was approved by the Research Ethics Committee (CAAE nº 38522714.6.0000.5418). The main sample consisted of 192 human skulls without alterations that impaired the analysis of morphological characteristics, 108 were male and 84 were female skulls, 3 Stasievski et al. aged between 22 and 97 years, with median age of 57 years, from the Osteological and Tomographic Biobank. The year of death of this sample varied from 2006 to 2010. The skulls of individuals who were 22 years or older at the time of their death were analyzed, excluding skulls of individuals who had not reached puberty as they show slightly pronounced qualitative characteristics, providing little information for sex estimation12,14. All analyses were performed by a single rater. The researcher was previous calibrated analysing all the dichotomous variables (male or female) in 10 skulls, obtaining 100% of consensual agreement between itself and a gold rater. The calibration has not been made through a statistical test. And the sample used for calibration was not included in the main sample. Then the main sample of 192 skulls was evaluated, of which 30 cranial anatomical structures that were analyzed by this rater through visual inspection, using a non-met- ric method without prior knowledge of sex. Table 1 shows the morphological charac- teristics analyzed in this study. Table 1. Morphological characteristics of skulls according to sex. Acronym Description Female Male Pe Weight Less heavy Heavier At Angle and lines Less angled, round and thin More angled and pronounced lines Iof Frontal bone inclination Vertical Inclined Pts Supraorbital protuberances Level Pronounced Rs Supraorbital region None to moderate Medium to excessive Gl Glabella Flat and not very delimited Prominent Bo Orbital edge Thin and sharp Thick Fc Canine fossa Not very deep Deep Pm Mastoid processes Small, little protruding in lower plane Robust, protruding in lower plane Rcrm Condyle protuberance in relation to the mastoid With greater protuberance Without greater protuberance Mcsp Skull movement on a flat surface Does not move when supported Moves when supported Sd Digastric groove Not very deep and narrow Deep and wide Az Zygomatic arch Thinner and shorter More robust and wide Enl Nasal spine Less prominent More prominent Anl Nasal aperture Less tall and wide, with rounded edges Taller and wider, with sharp edges Ff Facial physiognomy Indicates female Indicates male Orb Orbits Tall and round Low and angular Ct Temporal crests Slightly marked Marked Lns Superior nuchal lines Slightly marked Marked Rpn Nuchal plane surface Slightly marked and smooth Rough continue 4 Stasievski et al. The visual analysis of all 30 variables generated a subjective differentiation between female and male skulls (nominal qualitative variable). Based on the knowledge of actual sex of the individuals, the degree of agreement was measured using Kappa test, considering the significance level α=0.05, the levels of strength of agreement measure by Cohen’s kappa are interpreted as proposed by Landis and Koch16 (1977): almost perfect (0.81–1.00), substantial (0.61–0.80), moderate (0.41–0.60), fair (0.21–0.40), slight (0.00–0.20), or poor (<0.00). The percentage of correct sex was calculated using frequency tables (Crosstab) and the Cohen’s kappa coefficient, total percentage of agreement, sensitivity, specificity visual sex classification were calculated. It was used SPSS Statistics version 25 sta- tistical package (IBM Corporation, Chicago, USA) for data processing. Results The frequency and percentage of skull’s real sex are described in Table 2. The sample was relativily balanced with 56.3% of male and 43.8% female. 32.8% of the sample consisted of skulls which age range was between 26–50 years old, 33.3% between 51–70 years and 30.7% over 70 years old. And 96.5% of the skulls analysed presented the year of death 2010. Table 2. Frequency and percentage of actual sex classification, range age and death’s date of the skulls. Sample Frequency n % Actual sex Female 84 43.8 Male 108 56.3 Age range ≤ 25 6 3.1 26 a 50 63 32.8 51 a 70 64 33.3 over 70 59 30.7 Death date 2006 1 0.5 2009 6 3.1 2010 185 96.4 Crsm Supramastoid crests and rugosity Just perceptible Marked Aa Alveolar arches Small Raised Td Tooth size Smaller Larger Tm Mandible size Smaller Larger Emd Mandible thickness Smaller Larger Cm Mandibular condyles Smaller Larger Am Mandibular angle More obtuse Straighter Em Mental eminence Pointed, rounded Square Pb Mouth depth Narrow and not very deep Larger and deeper Bc Skull base Level and delicate Rough and strong continuation 5 Stasievski et al. Due to the sample consisted of skulls aged older than 22 years, the authors performed the skull concordance tests without separating them by age. Table 3 shows the frequency and percentage of sex classification based on a subjec- tive analysis of different variables. Through Kappa test, variables Pe (k=0.08) and Ct (k=-0.04), should not be used to deter- mine sex, as they do not present statistical significance in the agreement test (p>0.05). Table 3. Frequency and percentage of sex classification based on a subjective rater analysis of different variables. Sex Male N (%) Female N (%) Pe 111 (57.8) 81 (42.2) At 117 (60.9) 75 (39.1) Iof 135 (70.3) 57 (29.7) Pts 141 (73.4) 51 (26.6) Rs 136 (70.8) 56 (29.2) Gl 123 (64.1) 69 (35.9) Bo 108 (56.3) 84 (43.8) Fc 99 (51.6) 93 (48.4) Pm 127 (66.1) 65 (33.9) Rcrm 108 (56.3) 84 (43.8) Mcsp 77 (40.1) 115 (59.9) Sd 104 (54.2) 88 (45.8) Az 88 (45.8) 104 (54.2) Enl 106 (55.2) 86 (44.8) Anl 125 (65.1) 67 (34.9) Ff 122 (63.5) 70 (36.5) Orb 141 (73.4) 51 (26.6) Ct 148 (77.1) 44 (22.9) Lns 152 (79.2) 40 (20.8) Rpn 151 (78.6) 41 (21.4) Crsm 144 (75.0) 48 (25.0) Aa 96 (50.0) 96 (50.0) Td 69 (35.9) 32 (16.7)* Tm 121 (63.0) 71 (37.0) Emd 130 (67.7) 24 (32.3) Cm 138 (71.9) 54 (28.1) Am 106 (55.2) 86 (44.8) Em 98 (51.0) 94 (49.0 Pb 132 (68.7) 60 (31.3) Bc 135 (70.3) 57 (29.7) Actual sex 108 (56.3) 84 (43.8) *Absent structures did not allow sex classification. 6 Stasievski et al. Although the variable tooth size (Td) has been visually analyzed, its statistical analysis was not made due to several skulls had no tooth. The other variables showed statistically significant agreement from slight to fair level. Among these variables, Lns and Am had a slight level of agreement (0.00–0.20); Emd, Iof, Cm, Mcsp, Enl, Fc, Rpn, Sd and Rcrm showed a fair level of agreement (0.21–0.40); Gl, At, Em, Tm, Bc, Pb, Anl, Rs, Orb, Pm, Aa, Az, Bo, Pts and Crsm presented a moderate level of agreement (0.41–0.60). And only Ff presented substantial level of agreement (0.61–0.80). Table 4 shows the degree of agreement according to Kappa test and the p-value of all morphological variables, and the 16 variables with the best agreement degrees are highlighted with †symbol. Table 4. Percentage of total agreement, Cohen’s kappa coefficient and 95% CI kappa of variables in relation to actual sex. Total agreement (%) Cohen’s Kappa coefficient IC 95% Kappa Pe 54.7 0.08 -0.06 – 0.217 At 81.7 0.60*† 0.49 – 0.72 Iof 71.4 0.40* 0.27 – 0.52 Pts 73.5 0.44*† 0.31 – 0.56 Rs 76.1 0.49*† 0.37 – 0.61 Gl 80.7 0.60*† 0.49 – 0.71 Bo 72.9 0.43*† 0.32 – 0.58 Fc 72.4 0.34* 0.21 – 0.47 Pm 73.4 0.45*† 0.32 – 0.58 Rcrm 62.5 0.24* 0.10 – 0.37 Mcsp 66.2 0.34* 0.21 – 0.46 Sd 65.6 0.30* 0.17 – 0.44 Az 72.9 0.46*† 0.34 – 0.58 Enl 66.7 0.32* 0.20 – 0.46 Anl 75.5 0.49*† 0.37 – 0.61 Ff 81.2 0.61*† 0.50 – 0.72 Orb 74.5 0.46*† 0.34 – 0.58 Ct 51.1 -0.04 -0.12 – 0.12 Lns 62.5 0.19* 0.07 – 0.31 Rpn 68.3 0.32* 0.19 – 0.44 Crsm 72.9 0.42*† 0.30 – 0.54 Aa 74.0 0.48*† 0.36 – 0.60 Tm 77.6 0.54*† 0.42 – 0.66 Emd 70.8 0.39* 0.26 – 0.52 Cm 70.9 0.38* 0.26 – 0.51 Am 59.4 0.18* 0.04 – 0.32 Em 79.1 0.58*† 0.47 – 0.69 Pb 77.0 0.52*† 0.40 – 0.64 Bc 76.6 0.51*† 0.40 – 0.62 *Indicates significance in the Kappa’s test (p<0.05); † Represent the variables with the best agreement degrees (k>0.40). 7 Stasievski et al. Table 5 shows the percentage of correct sex through Crosstab of 16 (sixteen) vari- ables that presented statistically significant moderate and substantial agreement (k>0.40; p<0.05). The visual sex classification of Ff, At and Gl variables presented more than 80% of total agreement. The visual sex classification of Ff variable showed 89.8% sensitivity and 70.2% specificity for male sex classification. The At showed 87% sensitivity and 72.6% for male sex specificity and Gl showed 89.8% sensitivity and 69.0% specificity. The visual classification was more sensitivity for male sex, whereas for the female classification the sensitivity was lower. Table 5. The sensitivity, specificity for visual sex classification of the variables that presented moderate and substantial reliability in Cohen’s kappa coefficient (k>0.40; p<0.05). Male N (%) Female N (%) Total Gl# Actual sex Male 97 (89.8)* 11 (10.2) 108 (100.0) Female 26 (31.0) 58 (69.0)†‡ 84 (100.0) At# Actual sex Male 94 (87.0)* 14 (13.0) 108 (100.0) Female 23 (27.4) 61 (72.6)†‡ 84 (100.0) Ff# Actual sex Male 97 (89.8)* 11 (10.2) 108 (100.0) Female 25 (29.8) 59 (70.2)†‡ 84 (100.0) Em# Actual sex Male 91(84.3)* 17 (15.7) 108 (100.0) Female 39 (46.4) 45 (53.6)†‡ 84 (100.0) Tm Actual sex Male 93 (86.1)* 15 (13.9) 108 (100.0) Female 28 (33.3) 56 (66.7)†‡ 84 (100.0) Bc Actual sex Male 99 (91.7)* 9 (8.3) 108 (100.0) Female 36 (42.9) 48 (57.1)†‡ 84 (100.0) Pb# Actual sex Male 98 (90.7)* 10 (9.3) 108 (100.0) Female 34 (40.5) 50 (59.5)†‡ 84 (100.0) Anl Actual sex Male 93 (86.1)* 15 (13.9) 108 (100.0) Female 32 (38.1) 52 (61.9)†‡ 84 (100.0) Rs# Actual sex Male 99 (91.7)* 9 (8.3) 108 (100.0) Female 37 (44.0) 47 (56.0)†‡ 84 (100.0) Orb# Actual sex Male 100 (92.6)* 8 (7.4) 108 (100.0) Female 41 (48.8) 43 (51.2)†‡ 84 (100.0) Pm # Actual sex Male 92 (85.2)* 16 (14.8) 108 (100.0) Female 35 (41.7) 49(58.3)†‡ 84 (100.0) Aa Actual sex Male 77 (71.3)* 31 (28.7) 108 (100.0) Female 19 (22.6) 65 (77.4)†‡ 84 (100.0) Az Actual sex Male 72 (66.7)* 36 (33.3) 108 (100.0) Female 16 (19.0) 68 (81.0)†‡ 84 (100.0) Bo Actual sex Male 82 (75.9)* 26 (24.1) 108 (100.0) Female 26 (31.0) 58 (69.0)†‡ 84 (100.0) Pts# Actual sex Male 99 (91.7)* 9 (8.3) 108 (100.0) Female 42 (50.0) 42 (50.0)†‡ 84 (100.0) continue 8 Stasievski et al. The variable Orb showed 92.6% sensitivity for male sex, however, 51.2% of specificity. The Ff, Gl and At were the variables with the highest index of sensitivity and specificity. The percentages of correct sex for the 10 morphological variables with the best agreement degrees are highlighted with a hash in the same Table 5 and are pre- sented in the Figure 1; all of them had higher percentages in the determination of male in relation to female sex, that is, such characteristics are more evident and facilitate identification in male sex. Crsm# Actual sex Male 100 (92.6)* 8 (7.4) 108 (100.0) Female 44 (52.4) 40 (47.6)†‡ 84 (100.0) # Represent the variables with the best results; * Sensitivity to Male sex classification; † Specificity to Male sex classification; ‡ Sensitivity to Female sex classification. continuation A B C D E F G H Figure 1. A: Glabella (Gl); B: Supraorbital region (Rs) and Supraorbital protuberances (Pts); C: Orbits (Orb); D: Mastoid processes (Pm); E: Angle and lines (At) and Facial physiognomy (Ff); F: Mental eminence (Em); G: Mouth depth (Pb); H: Supramastoid crests and rugosity (Crsm). 9 Stasievski et al. Discussion In our study, using a balanced sample, although 30 cranial characteristics were ana- lysed, only 15 variables achieved moderate agreement and one substantial agree- ment, but according to Cicchetti and Feinstein17 (1990) a low kappa can occur at a high agreement. It is remarkable that age is a variable that can influence the quantitative measurement of bone size. However, the present study classified each skull qualitatively and the sample consisted of skulls aged older than 22 years, not dealing with the stage before puberty, between 10 and 21 yearsold which can be a confounding bias in the identi- fication of the gender. For this reason, the skulls concordance tests were performed without separating them by age. As the sex of all skulls was indexed in the Biobank, it was possible to estimate the per- centage of correct sex for female and male population, which was not obtained in the study by Biancalana et al.8 (2015). Correct sex percentages for the 10 characteristics presenting the best agreement results were high, ranging from 47.6% to 92.6%. Being observed that this qualitative classification is more sensitivity for male sex. As observed in other studies2,7,13,18,19, glabella presented a high sexual dimorphism index, reaching 89.8% sensitivity and 69.0% of specificity for male sex classification, and a total agreement of 80.7%. In a qualitative analysis of the glabella region similar to ours, Abdel Fatah et al.13 (2014) and Walker11 (2008) found correct sex classification of 82% and 82.6%, respectively. Langley et al.12 (2018), when analyzing non-metric cranial traits, observed that mental eminence was the only variable that did not present a reasonable to moderate agree- ment for sex estimation, and should be avoided for such purpose. Low accuracy of 45.03% was also obtained in the study by Durić et al.3 (2005) for the size of mental eminence. In contrast, in our study, mental eminence was among the 10 best vari- ables, with total agreement of 79.1%, having 84.3% of sensitivity for male sex and 53.6% for female sex. Similarly, Lewis and Garvin7 (2016) and Walker11 (2008) found correct sex classification for this variable of 75.0% and 76.6%, respectively. In our study, regarding supraorbital protuberances (Pts), moderate agreement was observed (73.5%), while Lewis and Garvin7 (2016), when evaluating the eyebrow region, obtained 96.7% of correct sex classification. Nikita and Michopoulou19 (2018) also analyzed the mastoid process profile and found for this variable, up to 75.2% and 74.5% correct classification for both sexes, similar to the percentages found by Walker11 (2008), while our study found for this characteris- tic, 85.2% of sensitivity for male sex and 58.3% for female sex. In a study conducted by Graw et al.20 (1999), the analysis of the supraorbital margin shape allowed correct identification of sex, with about 70% accuracy, an index that is similar to what was observed by Walker11 (2008), while Durić et al.3 (2005) reported sharpness of the supraorbital margins as the least reliable indicator with 28.75% accuracy only. Regarding orbits (Orb), our study showed the best percentage (92.6%) of sensitivity for male sex. 10 Stasievski et al. In a qualitative study conducted with European skulls, Williams and Rogers21 (2006) obtained high accuracy value for gonial angle (80.0%), which do not agree with the results of our study, as the strength of agreement for that variable was slight with a Cohen’s Kappa coefficient of 0.18. In addition, the authors mentioned above20 reported orbit shape and position, and forehead inclination should not be considered as reliable variables for sex determination. In contrast, in our study, the orbits showed moderate strength of agreement with 74.5% of total agreement and frontal bone inclination presenting a fair level of strength of agreement with 71.4% of total agreement. When analyzing jaw robustness, Durić et al.3 (2005) found high accuracy (70.93%) for sex determination. In our study, mandible variables reached different agreements, such as mandible size (presenting moderate agreement), mandible thickness and mandibular condyles (fair agreement), and mandibular angle (slight agreement). Sim- ilarly, Keen22 (1950) reports that the angle of the mandible did not present a high index in sex differentiation. In 2018, Tallman and Go10 evaluated Asian skulls, qualitatively analyzing nuchal crest, mastoid process, supraorbital margin, glabella and mental eminence, and obtaining 57.9% correct classification for female and 92.4% for male sex. Similarly, was observed in our study that the visual classification of the cranial charac- teristics was more sensitivity for male sex. And to increase the probability of correct sex determination, we agree with Loth and Henneberg23 (1996) when they advise that a complete examination should be made of all available bones known to belong to an individual, combining qualitative and quantitative methodologies, to ensure improved certainty and reliability of forensic anthropological reports. The percentages showed here are helpful for forensic practioners according to which preserved cranial trait is available in the skull that they are working on, and according to the population the skull is originated. However, this study presents some limitations, as the analyses were performed by only one examiner, and although calibrated, by being a qualitative analysis it can be influenced by subjectivity, so the authors suggest that future studies use some exam- iners. Another limitation was common lighting and tables to analyze the skulls, being evaluated with the naked eye. In conclusion, the visual classification of Ff variable presented the best sensitiv- ity and specificity to male sex with substantial reliability. Next in decreasing order for the best qualitative evaluation of sex were the variables Gl, At, Em, Tm, Bc, Pb, Anl, Rs, Orb Pm, Aa, Az, Bo, Pts and Crsm which presented moderate agreement (41% to 60%). The visual classification was more sensitivity for male sex. How- ever, for improved certainty and reliability in sex estimation, quantitative methods are recommended. Acknowledgments The authors thank Espaço da Escrita/UNICAMP’s General Coordination for the trans- lation services provided. 11 Stasievski et al. References 1. Krüger GC, L’Abbé EN, Stull KE, Kenyhercz MW. Sexual dimorphism in cranial morphology among modern South Africans. Int J Legal Med. 2015 Jul;129(4):869-75. doi: 10.1007/s00414-014-1111-0. 2. Musilová B, Dupej J, Velemínská J, Chaumoitre K, Bruzek J. Exocranial surfaces for sex assessment of the human cranium. 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