| Description: |
This review critically appraises the reported differences in human hair fibre within three related domains of research: hair classification approaches, fibre characteristics and properties. The most common hair classification approach is based on geo-racial origin, defining three main groups: African, Asian and Caucasian hair. This classification does not account sufficiently for the worldwide hair diversity and intergroups variability in curl, shape, size and colour. A global classification into eight curl types has been proposed but may be too complex for reproducibility. Beyond that, hair cross-sectional shape and area have been found to have an inverse relation to curl: straighter fibres are circular with larger cross-sectional area, whilst the curlier fibres are elliptical with smaller cross-sectional area. These geometrical differences have been associated with bilateral vs homogenous distribution of cortical cell in curly vs straight hair respectively. However, there is no sufficient data demonstrating significant differences in hair amino composition, but proteomic studies are reporting associations of some proteins with curly hair. Eumelanin's relative abundance has been reported in all hair colours except for red hair which has a high pheomelanin content. Higher tensile and fatigue strength of straight hair are reported, however, curly hair fragility is attributed to knotting, and crack and flow formations rather than the structural variations. African hair has been found to have the highest level of lipids, whilst the water sorption of Caucasian hair is the highest, and that of Asian hair the lowest. Not all comparative studies clearly report their hair sampling approaches. Therefore, to strengthen the robustness of comparative studies and to facilitate cross-study data comparisons, it is recommended that the following hair defining characteristics are reported in studies: hair cross sectional diameter/area, curl type, hair assembly colour, as well as where possible donor data (age/gender) and sample pooling approach. |
