Human scalp hair: geometry, biochemistry, growth parameters and mechanical characteristics
type: CreativeWork
description: Scalp hair is increasingly being used as a testing substrate for toxins and monitoring treatment adherence. The biochemistry of human hair is assumed to be similar; however, a recent study reported higher concentration of lipids in African hair. The effect of hair curvature, if any, on drug incorporation (e.g. lipid soluble drugs) is unknown. Racial description of hair morphology is unscientific. A geometric classification of hair into 8 groups (I-straight to VIII-tightly curly) was recently proposed, however its reliability has not been confirmed. The aim of this thesis was to investigate the reliability of the geometric classification (and to assess whether it could be improved) and investigate relationships between morphology and other hair characteristics. Virgin hair was collected from 128 volunteers using a standardized protocol. Geometric measurements of hair using published templates were conducted for classification. Reliability was assessed using Kappa statistics. Characteristics assessed included mechanical properties (miniature tensile tester), growth rate and hair density (TrichoScan® trichogram), biochemistry (Vanillin assay for lipids and Fourier Transform Infrared adsorption) and imaging (Electron and Fluorescent Light Microscopy). Inter-observer agreement was poor for 8-groups (k=0.418) but improved for 6-groups (k=0.671). The intra-observer agreement also improved [ranges: k=0.444 to 0.648 (8-groups) and k=0.599 to 0.836 (6-groups)]. The yield strength of all hair groups was higher than reported for racially grouped samples. Curly hair groups had lower growth rates and tensile strengths. The TrichoScan based growth rate was for fastest for the straightest (0.72±0.3 cm/month) and slowest for the curliest (0.39 ± 0.2 cm/month) hair. No correlation with biochemistry was detected for either the 8 or 6-group classification, although a trend toward higher absorption of lipid (C-H) bands was noted for curly hair. A supervised statistical approach applied …
abstract: Scalp hair is increasingly being used as a testing substrate for toxins and monitoring treatment adherence. The biochemistry of human hair is assumed to be similar; however, a recent study reported higher concentration of lipids in African hair. The effect of hair curvature, if any, on drug incorporation (e.g. lipid soluble drugs) is unknown. Racial description of hair morphology is unscientific. A geometric classification of hair into 8 groups (I-straight to VIII-tightly curly) was recently proposed, however its reliability has not been confirmed. The aim of this thesis was to investigate the reliability of the geometric classification (and to assess whether it could be improved) and investigate relationships between morphology and other hair characteristics. Virgin hair was collected from 128 volunteers using a standardized protocol. Geometric measurements of hair using published templates were conducted for classification. Reliability was assessed using Kappa statistics. Characteristics assessed included mechanical properties (miniature tensile tester), growth rate and hair density (TrichoScan® trichogram), biochemistry (Vanillin assay for lipids and Fourier Transform Infrared adsorption) and imaging (Electron and Fluorescent Light Microscopy). Inter-observer agreement was poor for 8-groups (k=0.418) but improved for 6-groups (k=0.671). The intra-observer agreement also improved [ranges: k=0.444 to 0.648 (8-groups) and k=0.599 to 0.836 (6-groups)]. The yield strength of all hair groups was higher than reported for racially grouped samples. Curly hair groups had lower growth rates and tensile strengths. The TrichoScan based growth rate was for fastest for the straightest (0.72±0.3 cm/month) and slowest for the curliest (0.39 ± 0.2 cm/month) hair. No correlation with biochemistry was detected for either the 8 or 6-group classification, although a trend toward higher absorption of lipid (C-H) bands was noted for curly hair. A supervised statistical approach applied …
author: Mkentane, Kwezikazi
language: eng
date published: 2016
date modified: 2026-07-22T22:23:31Z
provider: University of Cape Town
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Department of Medicine

PropertyValue
property ID: Handle
value: http://hdl.handle.net/11427/23419