# Facial Soft Tissue Thickness Values for Romanian Adult Population
## 3 Results
Next, the mean values of the facial landmarks were compared with values found in other studies concerning similar populations using the same method of data collection. Figure 4 displays the comparative average facial soft tissue thicknesses measured using needle puncture methods on female and male cadavers from three different geographic origins, Portugal, Romania, and Spain, based on the paper published by [9; 21]. The chart includes eight landmarks, since only these are common in both our study and the study concerning Portugal and Spain [9]. Figure 3: Non-parametric tests for assessing the differences between sex on nasion (**left**) and _l_mid_zigomatic (**right**). Based on another paper concerning the population of Brazil [22], Figure 5 compares the mean values (of the the same eight-landmark set) between Brazil and Romania, without grouping according to sex (as the data on sex were not available for Brazil). Figure 4: Comparison of average facial soft tissue thicknesses measured using needle puncture methods on cadavers from groups with different geographic origin. Figure 5: Comparison between Romanian and Brazilian adult population using the same method for the measurements. The next topic of interest for the Romanian dataset was to assess if the distribution of values referring to the facial landmarks varies significantly among weight categories. Table 3 contains the descriptive statistics of the \"Romanian\" dataset variables, overall and grouped by the three weight categories. The last column in Table 3 refers to the \(p\)-value of the statistical tests concerning the differences among categories. Since, in this study, three weight categories were included, and the distribution of facial landmarks was non-normal, the Kruskal-Wallis test was preferred (instead of ANOVA). The overweight group was smaller since it is represented by only 8 observatios, compared to 50 observations for the _underweight_ group, and 42 for the _normal weight_ group. The median age was considerable larger for the _overweight_ group (67 vs. 52 for both _underweight_ and _normal weight_ groups). Nevertheless, as the last column in the table shows, the differences among the three groups, as assessed through the non-parametric Kruskal-Wallis test, do not appear to be statistically significant (\(p\)-value = 0.8). Regarding the sex vs. weight category frequency table, Table 3 shows that the overall females/male's proportion (42/58) is preserved by the _underweight_ group but reversed in the _overweight_ group. The [PERSON]'s exact test assessed as non-significant the association between weight category and sex. Seven landmarks appear to vary significantly among the three weight categories: _supraglabella_, _glabella_, _nasion_, _hition_, _gation_, _r_mid_infaroorbital_, _l_mid_zygomatic_, whereas for _supramentale_, the difference is close to the significance level (\(p\)-value = 0.051). Another subject of interest was to examine the bivariate correlation among numerical variables, so that whenever the value of a given facial landmark is missing, it could be inferred based on its association with other landmarks and/or additional personal variables. As the distribution of all variables (except _age years_) is not normal, the non-parametric Spearman coefficient was preferred instead of the parametric (Pearson) one. Figure 6 displays the correlation plot, as produced by the _corrplot_ package. The largest positive correlation coefficients were recorded for the following pairs of variables: _pogonion_ and _supra_mentale_ (0.72); _mid_philtrum_ and _supra_mentale_ (0.71); _r_mid_infaroorbital_ and _r_mid_supraorbital_ (0.68); _l_zygion_ and _r_zygion_ (0.68); _r_mid_infaroorbital_  
Figure 6: Non-parametric correlation among numerical variables. and _supraglabella_ (0.64); _glabella_ and _l_mid_supraorbital_ (0.63); _glabella_ and _r_mid_infraorbital_ (0.63); _mid_philtrum_ and _pogonion_ (0.62); _gathion_ and _mid_philtrum_ (0.61). Negative correlations were considerable weaker.