# A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients
## 4 Discussion
Although the multivariate tool (Table 3) showed a significant effect of chronological age, the univariate tool confirmed that the chronological age alone has inadequate explicative power for the estimation of the skeletal age. When evaluating skeletal age, it is of utmost importance to consider the sex-related differences that are typical of these age groups and are related to sex hormones [40]. Indeed, sex showed a significant explicative value, as the odds ratio for females was indicative of a higher degree of skeletal maturation [44]. Other biometric data included in the present evaluation were height and weight. These parameters are useful when evaluating patients' development and growth. It has been stated that early menarche in girls is constantly associated with higher adult BMI because circulating hormones, such as leptin and insulin, provide signals reflecting body fat stores [42,45]. In the current evaluation, variables such as height and weight were also represented with BMI. Indeed, the statistical analysis highlighted that height and weight were significant explicators of skeletal maturity; however, when those two variables were combined to calculate BMI, their explicative value decreased remarkably. It could be inferred that weight and height are less related to each other in this age group, thus explaining why BMI performs worse than weight and height taken individually. This is a remarkable finding, because BMI is a commonly used index in clinical practice and research to reduce the number of variables (because BMI is a synthesis of two variables). The present results suggest that this should be performed with caution, due to the possibility of type II errors. Finally, among the biometric data considered, the wrist circumference was also statistically significant in the univariate analysis, but it loses its significance in the multivariate analyses. This finding suggests that this variable should not be considered explanatory for the estimation of skeletal age. Apart from biometric data, radiographic images were evaluated in this study. It is known that radiographs are particularly useful for skeletal age assessment, too. Dental radiology is the most frequent diagnostic radiological investigation in the industrialized world, representing one-third of all radiological examinations in Europe [46,47]. Among these, the most frequent imaging techniques are the OPG and periapical radiographs [43]. Considering that OPG provides a good overview of the most important dental and skeletal structures of the maxillary complex with a low radiation dose, it is recognized as an adequate tool for oral health screening [48,49]. Indeed, it is always recommended to have an OPG of the patient for formulating the correct orthodontic diagnosis. Since the OPG is the most common dental radiograph, the rationale for the present study was to optimize the information that can be obtained from it. One of the variables considered for the estimation of skeletal age in this research article was the dental maturation stage. This method was precisely defined by [PERSON] et al. [19] and used by different authors for assessing skeletal age. All the previous articles using this method considered only the right or left side of the jaws; in the current research study, to contain the number of variables to be inserted in the tool, a single tooth from the left side was considered. The lower left premolars are the teeth whose development encompasses the entire timeframe considered hereby and seemed suitable to be used for skeletal age assessment; moreover, the first premolars were preferred over the second premolars because the latter can be relatively frequently missing because of agenesis, thus impairing the generalizability of the current explicative tool. The dental maturation stage is a very easy and quick variable to evaluate, since only an OPG is required, which is virtually always available for every patient.