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<p>The current study explores diversity in morphological traits, including facial features, scalp and facial hair characteristics, ear morphology, and eye morphology, across six distinct North Indian population groups, focusing on sex- and population-based variation. These traits were selected for their relevance in forensic DNA phenotyping.&#xa0;This cross-sectional study included 521 participants aged 18–50 from six North Indian population groups: Sunni Muslims (Kashmir), Gujjar (Uttar Pradesh), Garhwali (Uttarakhand), Khatri (Punjab), Jaat (Haryana), and Khas Bodhi (Himachal Pradesh). Sociodemographic variables (age, sex, and community), phenotypic data, and 2D facial photographs were collected. Descriptive statistics were used to calculate trait frequencies. Associations between categorical traits and sex, population group, and age categories were evaluated using Chi-square tests (<i>p</i> &lt; 0.05). The strength of significant associations was assessed using Cramér’s V.&#xa0;The analysis revealed significant sexual dimorphism and inter-population variation across multiple externally visible characteristics, including hair colour, hair shape and texture, monobrow presence, eyebrow and beard features, male pattern baldness, ear traits, eye colour, double eyelids, epicanthic fold, nose and lip shape, and cheek dimples (<i>p</i> &lt; 0.05). Age-wise analysis demonstrated a strong, statistically significant association with male pattern baldness and hairy ear, with increasing severity and prevalence observed with advancing age. Effect size estimates indicated moderate to strong associations for several sex- and age-dependent traits.&#xa0;Observed variation in externally visible characteristics among North Indian populations reflects the combined influence of genetic background, sex, age, and environmental factors. These findings provide population-specific reference data that can enhance forensic DNA phenotyping, anthropological inference, and regionally calibrated appearance prediction models.</p>

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Morphological classification of externally visible characteristics (EVCs) among North Indians for DNA phenotyping applications

  • 期刊论文

  • 发表日期：

    2026年3月25日

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  • Suraj Kataria,
  • Sonal Jain,
  • Kallur Nava Saraswathy

摘要

The current study explores diversity in morphological traits, including facial features, scalp and facial hair characteristics, ear morphology, and eye morphology, across six distinct North Indian population groups, focusing on sex- and population-based variation. These traits were selected for their relevance in forensic DNA phenotyping. This cross-sectional study included 521 participants aged 18–50 from six North Indian population groups: Sunni Muslims (Kashmir), Gujjar (Uttar Pradesh), Garhwali (Uttarakhand), Khatri (Punjab), Jaat (Haryana), and Khas Bodhi (Himachal Pradesh). Sociodemographic variables (age, sex, and community), phenotypic data, and 2D facial photographs were collected. Descriptive statistics were used to calculate trait frequencies. Associations between categorical traits and sex, population group, and age categories were evaluated using Chi-square tests (p < 0.05). The strength of significant associations was assessed using Cramér’s V. The analysis revealed significant sexual dimorphism and inter-population variation across multiple externally visible characteristics, including hair colour, hair shape and texture, monobrow presence, eyebrow and beard features, male pattern baldness, ear traits, eye colour, double eyelids, epicanthic fold, nose and lip shape, and cheek dimples (p < 0.05). Age-wise analysis demonstrated a strong, statistically significant association with male pattern baldness and hairy ear, with increasing severity and prevalence observed with advancing age. Effect size estimates indicated moderate to strong associations for several sex- and age-dependent traits. Observed variation in externally visible characteristics among North Indian populations reflects the combined influence of genetic background, sex, age, and environmental factors. These findings provide population-specific reference data that can enhance forensic DNA phenotyping, anthropological inference, and regionally calibrated appearance prediction models.