|Year : 2010 | Volume
| Issue : 2 | Page : 91-95
Age estimation in 25-45 yrs. old females by physical and radiological methods
Vikrant Kasat1, FR Karjodkar2, Walter Vaz3
1 Department of Oral Medicine and Radiology, Rural Dental College, Loni, India
2 Department of Oral Medicine and Radiology, Nair Hospital Dental College, Mumbai, India
3 Department of Forensic Medicine, KEM Hospital, Mumbai, Maharashtra, India
|Date of Web Publication||20-May-2011|
Department of Oral Medicine and Radiology, Rural Dental College, Loni - 413 736, Maharashtra
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Aim:The purpose of this study was to estimate the age in living females in the later years (25 to 45 years) from general physical features and radiographic changes in the sternum and the mandible. Materials and Methods:A cross-sectional study was conducted on 64 females (32 subjects in each study and control group). All the subjects were physically examined for graying of scalp, body, pubic hair, and for wrinkling of skin of the forehead, temporal region, and below the eyes. A right lateral view of the chest was taken to determine fusion of the components of the sternum. Combined Hair Score, Combined Skin Score, and Combined Bone Fusion Score were calculated. An orthopantomogram of each patient was traced for lower jaw, mandibular canal and teeth, and D 1 , D 2 , A values were calculated. SPSS Software Version 10.1 was used for the execution of the regression command on the 32 cases of the control group, whose ages were known. Results:Combined skin score, mandible right D 2 , mandible right angle, and mandible left angle turned out significant in the prediction of age. Using the regression equation obtained, the age of the 32 subjects in the study group was estimated. In 9.3% of cases, the predicted ages exactly matched the actual ages. A variation of 1−4 years was seen in 75% of the cases. A variation of 6−7 years was seen in 15.6% of the cases. Conclusion:This study succeeded in most instances in predicting the ages of the study group and in arriving at a formula for age estimation between the ages of 25 and 45 years without using any invasive, costly, time - consuming, or troublesome method.
Keywords: Age, hair, mandible, skin, sternum
|How to cite this article:|
Kasat V, Karjodkar F R, Vaz W. Age estimation in 25-45 yrs. old females by physical and radiological methods. J Forensic Dent Sci 2010;2:91-5
|How to cite this URL:|
Kasat V, Karjodkar F R, Vaz W. Age estimation in 25-45 yrs. old females by physical and radiological methods. J Forensic Dent Sci [serial online] 2010 [cited 2021 Jan 20];2:91-5. Available from: https://www.jfds.org/text.asp?2010/2/2/91/81290
| Introduction|| |
The day a person is born, he starts his journey towards death. As each day passes the person becomes older and older, but many people don't even know their exact age. Also, evidence of age may be demanded in the various circumstances like as an aid in identification of an individual in forensic cases, marriage contract, attainment of major status, rape, judicial punishment, competency as a witness, eligibility for employment and promotion, senior citizen concession, old age pension, and retirement disputes.
Various parameters which help in age estimation upto 25 years of age are length of femur, secondary sexual characteristics, ossification of bones, etc. Parameters like ossification of cartilages in the hyoid, larynx, ribs, and obliteration of the skull sutures may be suggestive of advancing age, but give no precise evidence.
Age estimation from teeth is frequently used, because teeth can be preserved for long time even when all other tissues including bone have disintegrated. The dental age estimation methods most frequently referred to, require extraction  and preparation of microscopic sections of at least one tooth. , These methods are time - consuming and expensive , and a destructive approach may not be acceptable for ethical, religious, or scientific reasons. Among living humans, dental age estimation has to be based on clinical experience as well as evidence of attrition, increased root coloration  or periodontal recession in extracted teeth. These factors are strongly influenced by habits and pathological processes and age estimation based on these factors is in many ways uncertain.
Hence, an attempt to arrive at a conclusive age range after 25 years was proposed. The aim of the present study was to study general physical features (graying of hair and wrinkling of skin) as well as radiographic changes in the sternum and mandible of living females in their later years to arrive at a formula for precise age estimation.
| Materials and Methods|| |
The study was conducted in the Department of Oral Medicine, Diagnosis, and Radiology, Nair Hospital Dental College, Mumbai, on 64 female staff of age group 25 to 45 years, working in the Hospital. Of these, 32 were randomly selected as the study group. Their ages, as stated by them, were noted down by a third person. Another 32, whose ages were known to the investigator from their birth certificates, constituted the control group. Both study and control groups were further divided into 4 subgroups of the age ranges of 25+ to 30 years, 30+ to 35 years, 35+ to 40 years, and 40+ to 45 years (Denoted as I A, I B, I C, I D and II A, II B, II C, II D respectively). 0 Pregnant females were excluded from the study. Written informed consent especially with regards to the radiation exposure was obtained from all subjects.
All subjects were physically examined for graying of scalp, body, pubic hair, and for wrinkling of skin of the forehead, temporal region and below the eyes (Examined by a female staff).
A right lateral view of the chest was taken (Hiliophos D, 500mA, Siemen, India X-ray machine). To determine fusion of the components of the sternum, the opinion of a radiologist was taken. Combined Hair Score (CHS), Combined Skin Score (CSS) and Combined Bone Fusion Score (CBFS) were calculated [Figure 1].
|Figure 1: Right lateral view of chest demonstrating unfused manubriosternal and xiphisternal joints|
Click here to view
An orthopantomogram (OPG) of each patient was taken (Planmeca Proline CC PM 2002 CC). It was traced using 0.5 mm acetic acid paper for lower jaw, mandibular canal, and teeth. Tangents were drawn along the lower border of body of mandible and posterior border of ramus of mandible. The mental foramen was identified on both right and left sides, and a perpendicular line was drawn on both sides from the lowest part of outline of the mental foramen to the tangent drawn along the lower border of the body of the mandible. Another point was marked on the lower border of the mandibular canal on both right and left sides such that it was closest to the lower border of the mandible. Perpendicular lines were drawn from these points to tangents drawn along the lower border of the body of the mandible.
With the help of the scale and protractor, the following parameters were measured:
D 1 - Perpendicular distance of the mental foramina from tangents drawn along the lower borders of the body of the mandible. D 2 - Least perpendicular distance of the mandibular canals from tangents drawn along the lower borders of the body of the mandible. A- Angle between tangents drawn along the posterior borders of the rami of the mandible and the lower borders of the body of the mandible. The readings were taken by three observers and an average was calculated [Figure 2].
|Figure 2: Tracing of the orthopantomogram of one subject for measurement of D1, D2, and angle of the mandible|
Click here to view
Statistical Package for Social Science (SPSS) Software Version 10.1 was used for the execution of the regression command. The 32 cases of the control group, whose ages were known, were used for the regression.
| Results|| |
Pearson Chi-Square test revealed that the association between the age groups of study and control was not significant for graying of hair in scalp region. None of the subjects either in the study or control group had graying of body and pubic hair. The first composite variable, i.e., CHS was calculated by a linear addition of 1 point each for the presence of graying of hair at the three different sites viz. scalp, body, pubic. In case, there was no graying 0 score was allocated. Thus, the total score ranged from a minimum of 0 to a maximum of 3. CHS was 0.067 with a statistically insignificant P value of 0.943. It was, therefore, not used for the equation for estimation of age in the prediction model.
Pearson Chi-Square test revealed that the association between the age groups of study and control was significant for the age group of 35±40 for wrinkling of skin in the forehead region. None of the subjects either in the study or control group had wrinkling of skin in the temporal region. Pearson Chi-Square revealed that the association between the age groups of study and control was insignificant for the wrinkling of skin below eyes. The second composite variable, i.e., CSS was calculated in the same way as CHS. It was 2.074, with a statistically significant P value of 0.008. It was, therefore, used for the equation for estimation of age in the prediction model.
None of the subjects in either the study or control group showed fusion of the xiphoid process and the manubrium with the body of the sternum. CBFS was 0. Hence, it got deleted from the analysis.
ANOVA test was applied for mandibular parameters and statistically significant difference between the groups was found for Right Mandible-D 2 , Right Mandible-A, Left Mandible-D 1 [Table 1].
Independent variables of CSS [Figure 3], CHS, CBFS, Mandible Right D 1 , Mandible Right D 2 [Figure 4], Mandible Right Angle [Figure 5], Mandible Left D 1 , Mandible Left D 2 and Mandible Left Angle [Figure 6] were linearly regressed against the known dependent variable "Age" to develop a Prediction Model for Age Estimation.
CSS, Mandible Right D 2 , Mandible Right Angle and Mandible Left Angle turned out significant in the prediction of age. There was a very high correlation between the predicted values and the observed values of the dependent variable- Age, given by the regression model [Table 2]. (Correlation coefficient, R=0.919). Around 85% of the variation in the dependent variable - Age can be explained by the independent variables.
The model yielded the following regression equation-
Age = 22.673 (Constant) + 2.074 (CSS) + 9.550 (Right Mandible-D 2 ) + 0.273 (Right Mandible-A) - 0.242 (Left Mandible-A).
Using the regression equation, the age of the 32 subjects in the study group was estimated. In 9.3% of cases, the predicted ages exactly matched the actual ages. A variation of 1?4 years was seen in 75% of the cases. A variation of 6?7 years was seen in 15.6% of the cases.
| Discussion|| |
In the present study, graying of scalp hair was seen as early as 25−30 years of age. This finding was opposite to that of the study carried out by Singhal,  where graying is seen after 40 years of age. In the present study, none of the patients had graying of body or pubic hair, which was consistent with the finding of Nandy.  In the present study, graying of hair was found to be of no statistical significance for the estimation of age. The reason may be the fact that the patterns of graying of hair are very unreliable. Many factors have been held responsible for this, among them nutrition, grief, shock, cosmetics, coloring for concealment of age, and artificial coloring according to the dictates of current fashion. Color changes due to occupation have also been observed, e.g., a greenish hue in ebony turners and copper smelters, and blue in indigo workers.  A plethora of hereditary factors (autosomal dominant conditions like progeria, Werner's syndrome, Fisch's syndrome, Rothmund - Thomson syndrome, Seckel's syndrome), autoimmune disorders (pernicious anemia, hypothyroidism, hyperthyroidism), infections (e.g., HIV), certain metabolic defects (oculocutaneous albinism, Hemansky- Pudlack syndrome, Cross Mc Cusick- Breen syndrome, Tietz syndrome) and drugs such as chloroquine, triparanol, fluorobutyrophnon, mephenesin, and dixyrazine, all play a greater or lesser role in the early or delayed graying of hair. 
In the present study, none of the patients showed fusion of the manubrium with body of the sternum. This finding is consistent with that of Singhal.  None of the patients showed fusion of the xiphoid process with body of the sternum which is in contradiction to that of Singhal.  In the present study, the fusion of the components of the sternum, as visualized in the right lateral view of chest X- rays, was not found to be useful for the age estimation. The reason for this finding is the fact that, although sexual differences occur in the appearance and fusion of ossification centers, the sample size is obviously small. The process of ossification may also have been influenced by food habits, nutritional status, hormonal changes, and physical activity. Further, in females the breasts extend vertically from the second to sixth rib.  Due to the shadow of the breasts, assessment of fusion of the xiphisternal joint becomes difficult on radiographs as compared to males. To overcome this difficulty, another investigation (like ultrasonography) may be performed.
In the present study, the statistically significant variables were skin changes, position of the mandibular canal on the right side, and mandibular angles on both sides. Of these, the skin changes are least reliable because of the variety of factors affecting them, viz, heredity (ageing genes, cellular senescence, and non-enzymatic glycosylation), nutrition, oxidative stress, amino acid racemisation, exposure to sunlight (photoageing - one of the crucial factors in the Indian subcontinent), smoking, treatments like photoprotection, antioxidants or hormonal therapy, caloric restriction, applications of cosmetics and more recently, injections of medications in the skin and muscles (Botulinum toxin A and B)  as a remedy for wrinkling of the skin. In the present study, wrinkling in the forehead region was seen as early as 30−35 years of age in contradiction with the study of Modi  where it was seen after 40 years. In the present study, wrinkling below the eyes was seen as early as 25−30 years, which is contradictory to the study of Narayan Reddy  (occurs at 35−40 years).
Changes in the mandibular right angle, mandibular left angle, and position of the mandibular canal on the right side were determined to be of greater value in age estimation. Position of the mandibular canal on the left side was found to be insignificant. The reasons for such a difference are thought to be a missing tooth / teeth or partial dentures on either side, chewing habits, malocclusion and handedness of the person. Handedness of a person is related to the dominance of the cerebral hemisphere. Therefore, in a right-handed person, as in majority of population,  use of the dominant hand will result in more pressure on the right side of the mandible while brushing the teeth than the left handed person, which will induce more age-related changes on the right side than on the left side.
As mentioned by Chaurasia,  Narayan Reddy,  and Gray,  the angle of the mandible at birth is obtuse (140° or more) because the head is in line with the body. In adults, it reduces to about 110 ° or 120° because the ramus becomes almost vertical. In old age, the angle again becomes obtuse (140°) because the ramus is oblique. Thus, as age advances, there is a change in the angle of the mandible from more obtuse to less obtuse and again to more obtuse. These changes might explain the usefulness of the right and left mandibular angles as significant predictors for age estimation.
In the present study, the predicted ages exactly matched the actual ages in 9.3% of cases. A variation of 1−4 years in the predicted ages compared to the actual ages was seen in 75% of the cases. This is less than that of Bang and Ramm,  Mornstad  where a variation of 5−12 years in the predicted ages compared to the actual ages was seen.
Compared to the present study, Shendarkar et al.  in his study using same parameters on male population, found that CBFS was an additional significant parameter for age estimation.
| Conclusions|| |
Finally, it may be said that this particular study has succeeded in most instances in predicting the ages of the study group and in arriving at a formula for age estimation between the ages of 25 and 45 years without using any invasive, costly, time - consuming, or troublesome method. However, as the sample size is small, more detailed research using a larger sample, a variety of populations, and adequate consideration of the numerous factors affecting the parameters employed is required.
| Acknowledgments|| |
I sincerely thank Dr. Ajay Shendarkar, Department of Forensic Medicine, BYL Nair Hospital for his valuable advice and help. I would also like to thank Dr. Kasabe who did the analysis for the study.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2]