To the best of our knowledge, there is only one work which attempted to study hair morphology in a Malaysian population (Nataraja and Jessica 2015). In that work, the authors have assessed differences between the three major ethnic groups in Malaysia, i.e. Chinese, Malays, and Indians, using only qualitative features of hair, i.e. medulla patterns, cuticle thickness, and inner cuticle margin. In addition, the observed differences were assessed only with descriptive statistics. As a result, this work is the first report that studied the inter-ethnic difference in Malaysian sub-population using quantitative characteristic of hair, and both descriptive and inferential statistics were employed to evaluate the difference. Basically, the findings are in line with that presented by Nataraja and Jessica (2015), i.e. Malays and Chinese could be discriminated based on hair morphology.
On the other hand, some studies concentrated on the discriminatory power of hair morphology in populations other than Malaysian. For instance, it has been reported that twins could be discriminated by using common microscopic hair characteristics (Das-Chaudhuri 1976). However, Sharma et al. (2002) reported contradicting findings when involving more number of twins in a similar study. However, both works focused only on twin subjects. In contrary, this study has collected subjects according to ethnicity and involved no twins.
However, the results presented here is contradicted to other similar works involving non-Malaysian subjects (Kaur and Kumar 2000; Jasuja and Minakshi 2002; Aitken and Robertson 1986; Aitken and Robertson 1987). Those works concluded that the hair morphological parameters were not suitable for forensic casework because the variation was not consistent across two different populations (Kaur and Kumar 2000) or within one specific ethnic group (Jasuja and Minakshi 2002) or even for a particular individual (Aitken and Robertson 1986; Aitken and Robertson 1987; Robertson 1982).
Kaur and Kumar (2000) have considered the ethnic differences between Brahmin and Rajput populations in India. Theoretically, the genotype-specific difference between Malays and Chinese in Malaysia would be higher than that presented by the Brahmin and Rajput populations. This is due to the fact that Malaysian Chinese ancestors are those who migrated from Mainland China upon British colonization. On the other hand, Brahmin and Rajputs are believed to be closely related to each other (Mohan 2016). In fact, this is in line with the fact that hair morphology is partly controlled by genetic factors (Shimomura and Christiano 2010).
On the other hand, Jasuja and Minakshi (2002) have drawn a conclusion based solely on descriptive statistics. They studied intra-variation of hair within one specific ethnic group. However, they have not considered inferential statistics but only descriptive statistics in deriving the conclusion. In contrary, this work employed both the descriptive and inferential statistics to evaluate differences in hair morphology. As such, it seems relevant to suggest that the hypothesis test shall be conducted to confirm observations derived from the descriptive statistics.
Recently, Houck and Budowle (2002) have demonstrated that microscopic analysis of hair is as useful as molecular analysis because both approaches relied on independent types of information. For that reason, it seems worth to invest more effort to explore and assess the discriminatory power of other morphometry of hair in identifying a particular ethnic group (Apama and Yadav 2013). Following that, the study can be expanded later by considering both hair morphology and morphometry properties concurrently to achieve more insights on the subject of concern. In addition, an attempt should be made to construct a prediction model using multivariate modelling algorithm such as linear discriminant analysis or partial least squares-discriminant analysis.
The primary limitation of this work is the small sample sizes. In the context of statistical analysis, sample sizes could affect the reliability of hypothesis test. Due to that reason, we have derived the conclusion with regard to statistical differences by referring to the parametric (i.e. t test) as well as non-parametric (i.e. Wilcoxon’s rank-sum test) statistics. Based on Table 3, none of the pair of hypothesis tests shows disagreement in terms of statistical significance. As such, we could say that the impact of small sample sizes is minor in this work.