Gender-Specific Biases in Age Estimation Methods: A Comparative Analysis of Chaillet and Morris Methods in Forensic Anthropology

ABSTRACT

Background:

Accurate age estimation is crucial in various fields, particularly in forensic and anthropological contexts, where it aids in identification and legal proceedings. However, discrepancies and biases may exist in age estimation methods, necessitating comprehensive evaluation, especially across gender groups.

Materials and Methods:

This study used ANOVA and t-tests to analyze age estimation data obtained from the Chaillet and Morris methods, alongside actual ages, across male and female groups. Descriptive statistics including mean, median, standard deviation, and range were calculated to provide detailed insights into the distribution of age estimates.

Results:

ANOVA revealed significant differences in age estimates between the Chaillet and Morris methods, as well as actual ages, for both males and females (P < 0.05). However, t-tests did not indicate statistically significant gender differences in age estimates from either method. Notably, a significant difference was observed in actual ages, with males having lower ages on average than females. Descriptive statistics showed consistent underestimation of actual ages by both estimation methods, with females exhibiting higher actual ages compared with males.

Conclusion:

This study underscores the importance of considering gender-specific biases and variations in age estimation methods. Although the Chaillet and Morris methods may not show significant gender disparities in estimates, they consistently underestimate actual ages, with females having higher actual ages on average. These findings highlight the need for continued refinement and validation of age estimation techniques to ensure accuracy and fairness across diverse populations.

INTRODUCTION

Accurate estimation of age is paramount in various fields such as forensic anthropology and legal contexts, where it plays a crucial role in identification and decision-making processes.[1,2] Age estimation methods typically rely on skeletal or dental characteristics, with various techniques developed to assess age from these biological markers.[3] However, the reliability and accuracy of these methods can be influenced by factors such as gender, population-specific characteristics, and methodological variations.[4,5]

In recent years, researchers have emphasized the importance of evaluating age estimation methods across diverse populations and considering potential gender biases.[2] Gender-specific differences in skeletal morphology and dental development have been documented, suggesting the need for tailored approaches to age estimation.[6,7] Furthermore, discrepancies between age estimation methods and actual chronological age have been observed, highlighting the necessity of thorough validation and calibration of these techniques.[8,9]

This study aims to assess the accuracy and variability of age estimation methods, namely the Chaillet and Morris methods, across gender groups. By employing statistical analyses and descriptive statistics, this research seeks to elucidate potential gender differences in age estimation and provide insights into the reliability of these methods in diverse populations.

MATERIALS AND METHODS

Study population

The study population consisted of individuals whose age was assessed using the Chaillet and Morris methods, as well as individuals with known actual ages. The sample included both males and females, drawn from diverse populations to ensure representation across genders and demographic backgrounds.

Age estimation methods

The Chaillet Method: This method uses dental development and involves assessing the stages of tooth formation to estimate age (1). The Morris Method: This method relies on skeletal characteristics, particularly the development and fusion of skeletal elements, to estimate age (2). Actual Ages: The actual ages of individuals were obtained from documented records or reliable sources to serve as the reference standard for comparison.

Statistical analysis

ANOVA: Analysis of Variance (ANOVA) was conducted to assess differences in age estimates among the Chaillet method, Morris method, and actual ages within each gender group. T-tests: Independent samples t-tests were performed to compare age estimates and actual ages between males and females for each method. Descriptive Statistics: Descriptive statistics including mean, median, standard deviation, minimum, and maximum values were calculated for each age estimation method and actual ages within male and female groups.

Ethical considerations

This study adhered to ethical guidelines for research involving human subjects. Institutional review board approval was obtained, and informed consent was obtained from all participants or their legal guardians.

Data analysis software

Statistical analyses were conducted using appropriate software packages, including Statistical Package for the Social Sciences (SPSS) or similar statistical software.

RESULTS

This table indicates whether the different age estimation methods significantly differ within each gender group [Table 1].

Table 1.

Significant differences between the age estimates provided by the chaillet method, morris method, and the actual age

Group	F-statistic	P
Males	48.35	2.11e-18
Females	71.05	5.50e-24

Interpretation

For both males and females, the F-statistic is high, and the P values are very low, indicating that there are significant differences between the age estimates provided by the Chaillet method, Morris method, and the actual age.

T-tests results

This table shows the comparison of age estimations and actual ages between males and females.

Interpretation

• Chaillet Method: The t-statistic is negative, suggesting that males tend to have lower estimates than females, though the P value indicates this difference is not statistically significant (P > 0.05).

• Morris Method: The t-statistic is positive, suggesting males have higher estimates than females, but this difference is also not statistically significant.

• Actual Age: The negative t-statistic indicates that males have lower actual ages on average compared to females, and this difference is statistically significant (P < 0.05).

• Chaillet Method: Both genders have similar estimates around 10 years, though males have a wider range of estimates.

• Morris Method: Consistently lower estimates than Chaillet, with less variability, particularly in females.

• Actual Age: Generally higher than both methods’ estimates, with females showing a higher mean and wider range.

The ANOVA tests were performed to evaluate if there are statistically significant differences among the three age estimation methods (Chaillet, Morris, and actual age) within each gender group. For both males and females, the results indicate significant differences [Table 1]:

• Males: The F-statistic was approximately 48.35 with a P value near 2.11 × 10−182.11 × 10−18, suggesting strong evidence of significant differences among the three methods of age estimation.

• Females: Similarly, the F-statistic was about 71.05 with a P value around 5.50 × 10−245.50 × 10−24. This also provides strong evidence of significant differences among the age estimation methods for females.

These results imply that the methods do not agree with each other and each estimates age differently.

T-tests were conducted to compare the age estimations and actual ages between males and females for each method [Table 2]:

Table 2.

Comparison of measured age by chaillet and morris method with actual age

Comparison	t-statistic	P
Chaillet Method	-1.68	0.094
Morris Method	1.33	0.186
Actual Age	-2.00	0.047

• Chaillet Method: The t-statistic was -1.68 with a P value of 0.094. This indicates a tendency for males to have lower age estimates compared to females, though the difference is not statistically significant (P > 0.05).

• Morris Method: The t-statistic was 1.33 with a P value of 0.186, suggesting that males might have slightly higher age estimates than females, but again, this difference is not statistically significant.

• Actual Age: The t-statistic was -2.00 with a P value of 0.047, showing that males have a statistically significantly lower actual age compared to females. This is the only comparison where the difference was statistically significant.

The descriptive statistics provided insights into the distribution of age estimates and actual ages by method and gender [Table 3]:

Table 3.

Comparison of result by Chaillet And Morris Method in males Comparison of result by Chaillet And Morris Method in males

Statistic	Chaillet Method	Morris Method	Actual Age
Males
Count	82	82	82
Mean	9.83	8.05	11.09
Std	2.03	0.47	2.74
Females
Count	68	67	68
Mean	10.32	7.95	12.04
Std	1.38	0.48	3.09

• Males: The average age estimated by the Chaillet method was approximately 9.83 years, while the Morris method gave an average of 8.05 years, both underestimating the actual average age of 11.09 years. The data showed considerable variation in the Chaillet method compared to the Morris method.

• Females: The Chaillet method estimated an average age of about 10.32 years, and the Morris method 7.95 years, compared to an actual average age of 12.04 years. Similar to the male data, the Chaillet method estimates were more variable than those of the Morris method.

Overall, both the Chaillet and Morris methods tend to underestimate the actual age, with the Morris method showing a more pronounced underestimation. The actual ages of females were on average higher than those of males, and this was the only category where a statistically significant difference was observed between genders. These analyses highlight the variability and potential biases in the different methods used for age estimation.

DISCUSSION

The results of this study shed light on the accuracy and variability of age estimation methods, namely the Chaillet and Morris methods, across gender groups. The findings from the ANOVA tests indicate significant differences in age estimates provided by these methods, as well as actual ages, for both males and females. These results are consistent with previous research emphasizing the need to consider gender-specific biases and variations in age estimation techniques.[1,2]

In terms of the t-tests comparing age estimations and actual ages between males and females, the Chaillet and Morris methods did not show statistically significant gender differences in estimates. However, a significant difference was observed in actual ages, with males having lower ages on average than females. This discrepancy highlights the importance of using validated and gender-specific age estimation methods, as well as considering demographic factors such as gender in forensic and anthropological analyses.[3,4]

The descriptive statistics provided further insights into the distribution of age estimates and actual ages by method and gender. Both the Chaillet and Morris methods tended to underestimate the actual age, with the Morris method showing a more pronounced underestimation. These findings are consistent with previous studies indicating discrepancies between estimated and actual ages, particularly in forensic contexts.[2,5]

The observed discrepancies between estimated and actual ages, particularly the tendency for both the Chaillet and Morris methods to underestimate actual ages, underscore the complexity inherent in age estimation techniques. These findings highlight the importance of ongoing validation and refinement of age estimation methods to enhance their accuracy and reliability in diverse populations. Moreover, the identification of gender-specific biases in age estimation emphasizes the need for tailored approaches that account for variations in skeletal and dental development between males and females.

Furthermore, the significant difference in actual ages between males and females suggests potential implications for forensic and anthropological analyses. Understanding and addressing gender disparities in age estimation are essential for ensuring fairness and equity in legal proceedings and identification processes. Future research endeavors should prioritize the development of gender-specific age estimation models and explore novel methodologies to mitigate biases and enhance the accuracy of age estimation techniques across diverse demographic groups.

CONCLUSION

Overall, this study underscores the need for continued refinement and validation of age estimation techniques to ensure accuracy and fairness across diverse populations. Future research should focus on developing more robust and gender-specific age estimation methods, as well as exploring the underlying factors contributing to discrepancies in age estimates between genders.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.