|Year : 2016 | Volume
| Issue : 4 | Page : 310-314
Correlation of dental age, skeletal age, and chronological age among children aged 9-14 years: A retrospective study
Vignesh Palanisamy1, Arathi Rao1, Ramya Shenoy2, Suprabha Srikrishna Baranya1
1 Department of Paedodontics and Preventive Dentistry, Manipal College of Dental Sciences, Manipal University, Mangalore, Karnataka, India
2 Department of Public Health Dentistry, Manipal College of Dental Sciences, Manipal University, Mangalore, Karnataka, India
|Date of Web Publication||29-Sep-2016|
Department of Paedodontics and Preventive Dentistry, Manipal College of Dental Sciences, Manipal University, Mangalore, Karnataka
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Growth can be one of the most uncertain variations, but understanding the same is very important for diagnosis and treatment planning. Skeletal age and dental age have been used to determine a child's developmental age. Several researchers have evaluated the association between dental and skeletal maturity with chronologic age on different population. The purpose of the present study was to find out whether dental age estimation can be replaced for skeletal age estimation in the Dakshina Kannada population. Methods: A total of 104 samples equally distributed among both genders in the age group of 9-14 years were selected. Skeletal age was estimated using hand-wrist radiographs and Fishman's skeletal maturation index and dental age was measured using Demirjian's method. Results: Spearman's rank-order correlation coefficients were used to measure the association between the skeletal maturity and dental maturity. The mean ages of male and female samples were determined as 11.89 ± 1.867 years and 12.21 ± 1.473 years, respectively. Chronological age was found to be positively correlated to dental age and skeletal age and found to be statistically significant (P < 0.01). The correlation between dental age and skeletal age was also found to be statistically significant with P < 0.001 and correlation coefficient of 0.683 and 0.704 for males and females. Conclusion: The present study showed a strong relation between the developmental ages in mixed dentition population; hence, dental age can be considered as a replacement in the study population.
Keywords: Demirjian′s method, dental age, hand-wrist radiograph, skeletal age
|How to cite this article:|
Palanisamy V, Rao A, Shenoy R, Baranya SS. Correlation of dental age, skeletal age, and chronological age among children aged 9-14 years: A retrospective study. J Indian Soc Pedod Prev Dent 2016;34:310-4
|How to cite this URL:|
Palanisamy V, Rao A, Shenoy R, Baranya SS. Correlation of dental age, skeletal age, and chronological age among children aged 9-14 years: A retrospective study. J Indian Soc Pedod Prev Dent [serial online] 2016 [cited 2022 Dec 5];34:310-4. Available from: http://www.jisppd.com/text.asp?2016/34/4/310/191408
| Introduction|| |
Human physical growth is a sequence of events that converts one cell into a vastly complex mature individual. It is essential to learn the normal human growth and maturity to recognize abnormal or pathologic growth. Growth can be one of the most uncertain variations, but understanding the same is very important for diagnosis and treatment planning. 
Height and weight may be used as a tool for growth assessment but need longitudinal data for evaluation. Skeletal age and dental age have been used to determine a child's developmental age. Many researchers have found that skeletal maturity is closely related to the craniofacial growth. The disadvantage of skeletal radiographs is that dental professionals are less familiar with skeletal landmarks and also patient is exposed to additional radiation. The other method is an evaluation of dental age through orthopantomogram taken routinely in dental practice. Several researchers have evaluated the association between dental and skeletal maturity with chronologic age. Many studies were performed on growths which are representative of a population providing data from which the standards are developed.  However, no previous reports exist to investigate this relation in Dakshina Kannada population of South India.
The purpose of the present study was to find out whether dental age estimation can be replaced for skeletal age estimation in the study population.
| Methods|| |
The present study was a retrospective study. Ethical clearance was obtained from the Institutional Ethics Committee. The study included 104 samples. The sample size was calculated keeping the effect size as 0.6, assuming "r" value as 0.4 between dental age and skeletal age, at 95% confidence interval, power of the study at 90% using G*Power 3.1.2 software (Heinrich-Heine-Universitδt Düsseldorf), sample size for the study was 52 in male and female groups each with a total sample of 104. The required data were obtained from the pretreatment records of children who visited the department.
The inclusion criteria were:
- Patients with Dakshina Kannada as nativity
- Age between 9 and 14 years (mixed dentition stage)
- No systemic disease affecting growth
- No history of orthodontic treatment
- Good quality of the radiographs
- No abnormal dental conditions (e.g., impaction, congenitally missing teeth).
The exclusion criteria were:
- Incomplete patient records
- History of premature extractions.
Patient's radiographs (orthopantomogram and hand-wrist radiographs), detailed patient's records, cephalometric tracing sheets, ruler, scale, X-ray viewer, eraser, reference charts for Demirjian's method, and Fishman's skeletal maturation index (SMI) were used for the study.
Chronological age estimation
Chronological age was calculated by subtracting the date of birth from the date on which radiograph was taken.
Dental age estimation
Dental age was calculated using Demirjian's method where seven permanent teeth in the third quadrant were included - incisors, canine, premolars, and molars (first and second) were traced in the cephalometric tracing sheet [Figure 1]. Based on the apex closure, the teeth were rated accordingly from Stage A to H. All the scores were summed up and the final score was calculated from which the dental age was obtained using the Demirjian's table [Table 1]. 
Skeletal age estimation
Skeletal age assessment was done using hand-wrist radiographs using Fishman's SMI  where four stages of bone maturation found in six anatomical sites - thumb, third finger, fifth finger, and the radius were considered [Figure 2].
The radiographs were assessed based on the skeletal maturity index  and scores were given accordingly [Table 2].
With the reference table [Table 3], the skeletal age of the patient was estimated using SMI.
|Table 3: Chronological age values for adolescent skeletal maturity indicators|
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| Results|| |
A total of 104 samples were included in the study. The samples were equally distributed among both genders including 52 male and 52 female patients among the age group of 9-14 years. Correlations of dental and skeletal ages with chronological ages were done. Spearman's rank-order correlation coefficients were used to measure the association between the skeletal maturity and dental maturity.
The mean ages of male and female samples were determined as 11.89 ± 1.867 years and 12.21 ± 1.473 years, respectively. Correlations between skeletal, dental, and chronological ages were determined by correlation coefficient for males and females separately. Chronological age was found to be positively correlated to dental age and skeletal age and found to be statistically significant (P < 0.01).
For males, the correlation coefficient between dental and chronological ages was 0.711 and between skeletal and chronological ages was 0.863 with P < 0.01 [Table 4]. Correlation between dental age and skeletal age was found to be statistically significant with P < 0.001 and correlation coefficient of 0.683.
|Table 4: Correlation of chronological age with dental age and skeletal age|
Click here to view
For females, the correlation coefficient between dental and chronological ages was 0.821 and between skeletal and chronological ages was 0.788 with P < 0.01. Correlation between dental and skeletal ages was found to be statistically significant with P < 0.001 and correlation coefficient of 0.704.
| Discussion|| |
Human beings exhibit considerable variations in growth pattern, but show certain features, which has led to the concept of assessing biological or physiological maturity. An accurate estimation of chronological age is achieved from developmental stages - skeletal maturation, secondary sexual characters, and dental development.  The degree of skeletal development shows the degree of physiological maturation, which is reflected on the basis of the degree of bone ossification.  Skeletal maturity is a measure of development based on the size, shape, and degree of mineralization of bone to define its proximity to full maturity and can be seen radiologically. The sequence of changes is relatively consistent for a given bone in every person. However, the timing of these changes varies because each person has his or her own biological clock. 
The age criteria of the samples in the study include the patients with late mixed dentition period starting from 9 years since the Fishman's SMI can be applied for samples over 9 years of age. Furthermore, the beginning of pubertal growth spurt occurs on an average of 10 years in females and 12 years in males, thus offering the best opportunity to accomplish the objectives of orthodontic treatment in the shortest time. 
The most reliable and widely used method of skeletal age estimation is a hand-wrist analysis done using hand-wrist radiograph, whose validity has been proved in many studies.  Fishman  published a method for radiographic evaluation of the SMI in which 11 indicators were evinced during adolescence. The sequence of the four stages of maturation, which proved stable, progressed by the increase in width of the selected epiphyseal, ossification of the adductor sesamoid, capping of the epiphysis over the shafts, and finally their merging.
Demirjian's method was used to estimate the dental age in the study because of its high accuracy which has been reported as the most accurate for dental age estimation by many authors. ,,,,,
The present study was a cross-sectional study, in which a large number of individuals of selected age were chosen. This method has an advantage of accumulating more information about growth at many ages in a short period. Cross-sectional studies provide the best data for establishing the national standards for growth and comparing growth in different populations. 
The study was aimed to correlate the skeletal and dental ages with the chronological ages of the children with mixed dentition. Correlation of the ages helps a clinician to estimate the growth left in the child and the possible treatment that can be carried out utilizing it. The results of the study showed a strong correlation between skeletal and dental ages with the chronological age in both male and female population. When dental and skeletal ages were compared in male and female groups, the r value was estimated as 0.683 and 0.704, respectively, which shows the strong correlation between the dental and skeletal ages themselves.
Few studies conducted in India showed a similar correlation between the ages. Hegde and Sood  conducted a study on 197 cases (6-13 years) to find the applicability of Demirjian's method using orthopantomogram in Belgaum population and found a mean difference of 0.14 years between true and assessed age (overestimation by 51 days) and females showed a minimal difference of 0.04 years (overestimation by 15 days) and they showed significant positive linear correlation between dental and chronological ages.
| Conclusion|| |
It is essential for a pedodontist to study the growth of the child to compare with the normalcy and treatment planning. The present study showed a strong relation between the developmental ages in mixed dentition population; hence, dental age can be considered as a replacement in the study population. Studies with a larger sample size should be carried out for more reliable results.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]
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