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INTRODUCTION
The mandible is an unpaired, symmetrical bone located in the lower third of the face. It consists of an arched body in the shape of a horseshoe and two rami which extend from the posterior ends of the body to cranial (Alves & Cândido, 2016). It starts to form during the 6th week of intrauterine development, when the first branchial arch starts to produce mandibular cartilage, indicating the location of the mandible. Its ossification is intramembranous. After birth the mandible fuses in the region of the mandibular symphysis during the first year of life, and this symphysis usually disappears by the age of 18 years (Lipski et al., 2013).
Estimating sex is the first step in the identification of human remains, followed by determination of other elements such as age, height and ethnic composition (Ruff, 2010; Franklin et al., 2014). Physical anthropology uses the morphological and metrical aspects of bone structures for estimating and determining the principal characteristics of an individual; the training and knowledge of the professional is fundamental for identifying bone remains, regardless of their condition (decomposed, burnt, dismembered) (Taylor & Kieser, 2016). In human sex identification, the pelvic and cranial bones are highly reliable; however, in the absence of the pelvic bones, analysis of the mandible may be the best alternative due to its strong sexual dimorphism (Moore, 2013; Alves & Deana, 2019).
In modern humans, the mandible is generally smaller in female individuals than in males (Alves & Deana, 2019), the mean size being 92.4 % of that of the male mandible (Humphrey et al., 1999). The mandibular ramus and the condyle have been widely used as indicators for sexual diag- nosis because they are regions that undergo important morphological changes which increase sexual dimorphism (Humphrey et al., 1999). Standards of sex differentiation which are valid for one population may not be useful for another (Vodanovic´ et al., 2006), since cultural and ethnic aspects may influence the development of the mandible, determining differences between populations (Iscan & Kennedy, 1989; Saini et al., 2011). For this reason it is important to consider not only the accuracy of sex identification in different populations, but also which parameters present the greatest dimorphism for each population. Thus the research question for this study was: Which metric parameters of the mandibular ramus present the greatest sexual dimorphism? The object of the present study was to carry out a systematic review to determine the metric parameters of the mandibular ramus that present the greatest sexual dimorphism. Furthermore, we analysed the accuracy of the angle of mandible (MA) in determining sex. A second object was to analyse the accuracy of the mandibular ramus in predicting sex in different populations.
MATERIAL AND METHOD
Eligibility criteria. We included documents in English, Spanish and Portuguese which analysed sex estimation or sex diagnosis by metric analysis of the mandibular ramus in humans (Homo sapiens). We included studies carried out in dry mandibles or by imaging methods (panoramic radiography (PR), computed tomography (CT), cone-beam computed tomography (CBCT) or spiral cone-beam computed tomography (SCBCT)). Studies were included that assessed sex estimation by analysis of metric characteristics of the mandibular ramus. Only studies that presented results for at least one variable of the mandibular ramus were included.
Studies were excluded that assessed non-metric parameters alone, sexual dimorphism alone, other metric parameters of the mandible, or that did not present results for at least one of the parameters assessed in the mandibular ramus in isolation. Literature reviews, systematic reviews, letters to the editor and conference summaries were excluded. Studies that analysed differences between the sexes only by analysis of mean differences were also excluded.
Information sources and search. We performed a systematic search of the scientific literature to identify original studies that assessed sex estimation by metric analysis of the mandibular ramus. The search was conducted in PubMed/MEDLINE, EMBASE and LILACS, up to December 2020. In addition, we examined the reference lists of the selected studies to identify other studies that met the inclusion criteria. We did not limit the search by date or publication status, however only studies in English, Spanish and Portuguese were included.
The search strategy carried out in MEDLINE was: ((((((((((((Dry skull) OR Dry mandible) OR Orthopantomography) OR Panoramic*) OR radiographic) OR ("Cone-Beam Computed Tomography"[Mesh] AND "Spiral Cone-Beam Computed Tomography"[Mesh])) OR cone beam computed tomography) OR cone beam*) OR Computed tomography*) OR CBCT*)) AND (((((((((((Coronoid*) OR condylar height) OR Gnation) OR Gonial angle) OR Bicondylar) OR mandibular ramus*) OR bigonial*) OR "Mandible"[Mesh]) OR mandible)) AND (((((((((forensic*) OR Physical anthropology) OR physical anthropology) OR sex determination) OR ("Sex Determination Processes"[Mesh] OR "Sex Determination by Skeleton"[Mesh] OR "Sex Determination Analysis"[Mesh])) OR Sex characteristics) OR Sex prediction) OR Sexual dimorphism) OR Gender estimation).
Study Selection. All references identified were extracted to an EndNote X9 database to facilitate management and delete duplicate articles. Selection by title and abstract was carried out using the Rayyan software (http://rayyan.qcri.org). Titles and/or abstracts of studies retrieved using the search strategy, and those from additional sources, were screened independently by two review authors (L.M., N.F.D.) to identify studies that potentially met the inclusion criteria. We obtained full texts of all relevant and potentially relevant studies, those appearing to meet the inclusion criteria, and those for which there were insufficient data in the title and abstract to make a clear decision. Any disagreement between the two review authors over the eligibility of particular studies was resolved through discussion with a third reviewer (N.A.).
The extraction of the descriptive data was performed independently by two researchers (L.M., F.C.) using a standardised data collection form including: Author, year, title, country, number of participants, type of study, parameters assessed, principal results.
Risk of bias. Two review authors (L.M., F.C.) independently assessed the risk of bias of the eligible works using the AQUA tool. In cases of discrepancy, consensus was obtained by consulting a third reviewer (N.F.D.). The AQUA tool consists of 20 questions and five domains, which evaluate: 1. Object(s) and subject characteristics; 2. Study design; 3. Characterization of the methodology; 4. Descriptive anatomy; and 5. Reporting of results. The signalling questions are answered as Yes, No, or Unclear. The answers to these signalling questions, Yes, No and Unclear, indicate low, high, and unclear risk of bias respectively. The risk of bias question is judged as Low, High, or Unclear: if all the signalling questions for a domain are answered Yes, then the risk of bias can be judged Low. If any signalling question is answered No, this indicates the potential for bias. The Unclear option should be used only when the reported data are insufficient to allow for a clear judgment (Henry et al., 2017; Evidence-Based Anatomy, 2021).
Report of quality indicators. The following quality indicators were analysed: information on randomisation; sample size calculation; approval by a scientific ethics committee; conflicts of interest and funding, and intraobserver and/or interobserver analysis. Quality indicators were classified as reported or not reported.
Synthesis of the results. A narrative synthesis of the findings was made. Tables were used to present information on the principal characteristics of the studies. The graphs were prepared with the Excel, Prisma GraphPad and RStudio software, version 1.4.1106, 2021, using the Plotly package.
RESULTS
Search results. The search identified 538 articles. After the exclusion of 14 duplicate studies and analysis of the titles and abstracts, 60 articles were selected for full text reading. Of these, 35 were excluded at this stage: 20 tested mean differences between sexes, but without assessing estimation (other outcomes), 3 did not assess sex estimation in the mandibular ramus or the angle of mandible, 12 were excluded for reasons of their design, and 1 because the study was not carried out in the population of interest. Fifteen additional studies were included after reading of the title and abstract. Finally 39 full text studies were included in the qualitative analysis (Fig. 1).
Characteristics of the studies included. Of the 39 studies included, 18 were in dry mandibles (Vodanovic et al., 2006; Franklin et al., 2006, 2008; Dayal et al., 2008; Saini et al., 2011; Carvalho et al., 2013; Marinescu et al., 2013; Pokhrel & Bhatnagar, 2013; Kranioti et al., 2014; Wankhede et al., 2015; Sharma et al., 2016; Álvarez Villanueva et al., 2017; Lopez-Capp et al., 2018; Vignesh et al., 2018; Bertsatos et al., 2019; Alves & Deana, 2019) and 21 in imaging studies, i.e. 10 by CBCT (Kharoshah et al., 2010; Ilguy et al., 2014; Dong et al., 2015; Gamba et al., 2016; Inci et al., 2016; Tunis et al., 2017; Lopez et al., 2017; Deng et al., 2017; Gillet et al., 2020; Motawei et al., 2020), 2 by CT (Lin et al., 2014; Alias et al., 2018), and 10 by radiography (Barthélémy et al., 1999; Indira et al., 2012; Damera et al., 2016; Sairam et al., 2016; Sambhana et al., 2016; Samatha et al., 2016; More et al., 2017; Maloth et al., 2017; Belaldavar et al., 2019; Ortiz et al., 2020) (Table I). A total of 7270 participants were included, 1981 in dry mandible studies and 5289 in imaging studies.
The definition and description of the parameters analysed are reported in Table II. The studies were carried out in different populations, 13 in India, 6 in Brazil, 4 in South Africa. Two studies each were published in China, Egypt, France, Greece and Turkey, and one each in Croatia, Israel, Korea, Malaysia, Mexico and Romania (Tables I and III).
Table I Characteristics of the imaging studies and principal results.
*Other measurements related with the body of the mandible were used.
Table III Characteristics of studies in dry mandibles and principal results.
*Other measurements related with the body of the mandible were used.
Risk of bias. No study presented low risk of bias in all 5 domains of the AQUA tool. In the domain Study objects and characteristics, many of the studies (33/39) did not state clearly how the sample was selected or did not justify the number of participants necessary for the sample. The studies provided little information on the characteristics of the individuals, so they were classified as high risk of bias for this domain. In the domain Results reporting, 37/39 studies did not assess or did not analyse the potential confusion factors, and the other studies did not state the confusion factors clearly, so they were all classified as high risk of bias. In the domain Characterization of the methodology, the studies failed to report clearly the speciality and experience of the people carrying out the study, or simply omitted the information. They also failed to take adequate measures to reduce interobserver (or intraobserver) variability. The majority of the studies (32/39) were therefore classified as high risk of bias for this domain. In the domain Descriptive anatomy, 12/39 studies were classified as high risk of bias because of the absence of information on the anatomical definition of the variables analysed, or lack of clarity in the illustrations showing the measurements of the predictive variables. In the domain Study design, most of the studies were classified as low risk of bias (29/39); a few were classified as high risk of bias (10/39), mainly due to poor reporting, which undermined judgment domains (Fig. 2).
Report of Quality Indicators. The majority of the studies did not report data on conflicts of interest (25/39) or approval of the study by a scientific ethics committee (23/39). In 18/ 39 studies the authors reported funding data; intraobserver analysis was carried out in 7/39 studies, interobserver analysis in 3/39 studies, and both in 8/39 studies (Fig. 3).
Analysis of sex determination. Fourteen sex-estimation parameters in the mandibular ramus were analysed, plus the MA, bringing the total to 15 (Fig. 4). The mandibular ramus height (RH) was reported in 23/39 studies as one of the best measurements for sex differentiation, followed by the bigonial breadth (BG), reported by 13/39 studies, and the bicondylar breadth (BC) reported by 9/39 studies as the best predictor (Fig. 4). Only two studies did not report the best parameter for sex differentiation (Carvalho et al., 2013); 1 study in a population in India reported that the parameter analysed did not present good differentiation (Belaldavar et al., 2019). RH, MiRB, MaRB, RW, PHB, MA, CoH and BC were the parameters with the greatest dimorphism in the Indian population. In Brazilian studies, RH, MiRB, MA, BG and BC proved to be good predictors for differentiating the sexes. In South-African studies, RH, RW, CoH, BG, BCB and BC were the parameters with the greatest dimorphism. The parameters with greatest dimorphism in other populations can be analysed in Figure 4.
The percentage accuracy was presented for isolated parameters or in conjunction, and was reported by 19 studies. Of these, 13 indicated accuracy higher than 80 %. Figure 5 shows the percentage accuracy by country and sample used. The highest percentage accuracy was presented by the Turkish population; MDCT was used in the analysis of parameters of the mandibular ramus, achieving 99 % accuracy (Inci et al., 2016). In individuals in South Africa, 92.5 % accuracy was achieved in a study in cadavers, using 4 parameters in conjunction: ramus height, coronoid height, maximum mandible length and bicoronoid breadth (Franklin et al., 2006). Good accuracy (88.8 %) was also found for the Korean population by CT scans, using all the parameters of the mandibular ramus flexure (Lin et al., 2014). The lowest percentage was found in a radiography study in an Indian population, using only the angle of mandible, which presented an accuracy of 56.3 % (Belaldavar et al., 2019). All the other studies presented accuracy higher than 70 % (Fig. 5, Tables I and III).
DISCUSSION
In the present review we analysed the metric parameters of the mandibular ramus that present the greatest sexual dimorphism, considering the differences between different populations. The advantage of metric analysis is that it eliminates subjectivity in the analysis of morphological characteristics, increasing confidence in the results (Dabbs & Moore-Jansen, 2010). Morphometric methods are based on the operator's experience in observing the details of the points of reference in the bones, followed by measurements that may help construct differentiating functions and thus estimate sex. These methods can achieve an accuracy higher than 80 % in estimating sex (Dayal et al., 2008), without involving high costs.
Many visible sexual characteristics are absent in infancy and childhood, and develop completely at puberty, apparently due to endocrine stimulation. Other gender differences are related with the individual's activity (Slaus et al., 1997). Muscle size and specific relief emerge as the most diagnostic sexual characteristics (Rosas et al., 2002). Distinctive female muscle characteristics include small size and smooth insertions, while male muscles are larger with strongly marked insertions (Vodanovic et al., 2006). All the parameters presenting sexual dimorphism are influenced by the size of the mandible. This may be explained by genetically determined factors such as tooth size, or local environmental factors like muscle strength. During mastication, females exert a smaller muscular force on average, resulting in smooth muscle insertions and small mandibles. Males exert greater muscular force; they have more strongly marked muscle insertions, especially in the gonion and the coronoid process, and larger mandibles than females (Vodanovic et al., 2006). The sexual dimorphism found in the mandible of modern human individuals is due to differences related with musculoskeletal development, and others related with the differences in growth trajectory between males and females (Rosas et al., 2002). The present review included 39 studies which assessed a total of 14 sex-estimation parameters in the mandibular ramus and the MA. The expression of sexual dimorphism in the mandible shares certain characteristics in different populations (Bertsatos et al., 2019). In the present review, RH was indicated as a sex-estimation n parameter in 10 different populations. BG, BC and CoH were also highlighted as important sex-estimation parameters in different populations. BG, BC and RH presented over 80 % accuracy for Brazilian (Alves & Deana, 2019) and French populations (Barthélémy et al., 1999; Gillet et al., 2020). In another study, Carvalho et al. (2013) reported that in a Brazilian population 76.47 % accuracy was found for males and 78.13 % for females using BG and RH; while in a Greek population the combination of these two parameters achieved 80 % accuracy (Kranioti et al., 2014).
Although these parameters of the mandibular ramus may present good sexual dimorphism, it should be noted that they are generally less effective for sex estimation individually than when they are analysed in conjunction. Damera et al. (2016) report that RH was the parameter that presented the best sex differentiation in isolation, however the use of 4 indicators in conjunction produced an accuracy of 83.3 %, higher than the accuracy of any individual parameter. Deng et al. (2017) reported a similar finding: the parameters BC, BG, BANB and bimental foramina breadth used in conjunction presented sex estimation accuracy of 82.2 %, which was higher than the value for the best indicator, the BC with 77.6 %.
In the present review, metric analysis of the parameters of the mandibular ramus achieved accuracy higher than 80 % in the majority of the studies, regardless of the sample analysed (dry mandible, tomography or radiography). The highest accuracy was found for a Turkish population, and the lowest for an Indian population. It may be noted that in Indian populations only, the majority of the studies presented accuracy rates below 80 %. On the other hand, Damera et al. (2016) achieved 83.3 % accuracy by analysing 4 parameters in conjunction (RH, PHR, CoH, BG). A similar result is observed in Brazilian studies, where greater accuracy was achieved depending on the parameters analysed; it is therefore important to take into account which parameters give the best sex differentiation in each population.
The MA is located in the posteroinferior region of the mandibular ramus (Alves & Cândido, 2016), and is a valuable tool for sex differentiation (Chole et al., 2013). The MA was among the parameters with the greatest sexual dimorphism in Croat (Vodanovic et al., 2006), Brazilian (Gamba et al., 2016), Turkish (Ilguy et al., 2014) and Egyptian (Kharoshah et al., 2010) populations. Analysis of the angle of mandible in isolation achieved 56.3 % accuracy, however some authors report that the MA did not present sexual dimorphism, for example in Indian (Sharma et al., 2016; Sambhana et al., 2016; Vignesh et al., 2018) and Mexican (Álvarez Villanueva et al., 2017) populations. The angle of the mandible is 140º in elderly people, and less in adults (Standring, 2021); however, Sharma et al. (2016) reported that although elderly women presented a greater angle, no statistical differences were found in the MA between older and younger individuals of either sex. Previous studies have reported that there is no association between the MA and age, however the angle is found to increase in edentate individuals (Upadhyay et al., 2012). These are two important aspects that must be considered in sex estimation by analysis of the mandible. The investigator must consider these groups in the analysis to avoid reaching a false conclusion due to failure to control the confusion factors of the study.
In studies to determine sex by metric analysis of mandibular parameters, certain important points must be taken into consideration to diminish the bias and increase the quality of the evidence. Firstly, it is fundamental that the investigators should be masked when carrying out the analysis, since they may be biased by suggestion if they know the sex of the individual beforehand. Furthermore the investigators must be calibrated previously to avoid errors in the measurements. In the present review, 46.2 % of the studies did not report carrying out intra or inter-observer analysis. This is an aspect that can easily be remedied in future studies, increasing the reliability of the results. Factors that may cause confusion must also be controlled, for example: not carrying out the analysis based on age ranges, since young individuals (less than 18 years) do not present clearly marked sexual differentiation; or not adapting the analysis to the type of population, when more than one population or ethnic group may be involved. In a previous study by our team, we showed metric differences between black- and white-skinned individuals; therefore the ethnic factor must also be considered, as it may affect measurements (Alves & Deana, 2015). Another factor to consider is the method used to take the measurements, for example whether the dry mandible was stabilised to ensure that it remained in the same position throughout. In imaging studies, data on the equipment and software used to take the measurements should be included, as well as the size of voxel or window used, for example. Another important point is determination of the sample size. In the present review, the majority of authors did not show how the sample was selected or calculated; this may affect the power and degree of evidence of the study.
Limitations. We identified some limitations in our review process that deserve comment. First, limitations derived from the systematic nature of the review: despite performing the search in the most important databases in the field of health sciences, we may have failed to identify all articles. However, we believe that this limitation was minimised by the sensitive search strategy used, the additional search of references by hand, and the double independent review process followed. In addition, we only selected studies published in English, Spanish or Portuguese, being the languages the reviewers are fluent in; however no study was excluded on the basis of language. Second, no study with low risk of bias was included in our review; and many reports were far from transparent. Furthermore, our meta-analysis was limited by the high heterogeneity between the studies; however, high heterogeneity is to be expected in prevalence studies, and may be determined in large samples; it is not necessarily related with the heterogeneity of the actual studies. Another limitation is that the estimation intervals produced very wide ranges, indicating that future studies may find very diverse results. Finally, we only assessed the sex estimation indicators of the mandibular ramus, therefore other indicators that are also good predictors of sex were not assessed in the present review.
CONCLUSION
The mandibular ramus presents great sexual dimorphism in different populations, independent of the type of sample used (tomography, dry mandible or radiography). Sex estimation by MA is variable; it is a good predictor only for some populations. RH, BG, BC and CoH were cited as predictive parameters in the majority of studies; however their power of differentiation will depend on the population analysed. Depending on the population analysed, some parameters of the mandibular ramus can present accuracy of almost 80 % when analysed in isolation; however, more accurate sex estimation is achieved when the parameters are analysed in conjunction. The accuracy of sex determination by the mandibular ramus may differ between populations, and the best parameters must be chosen according to the study population.
