Mapping Tridosha Prakriti to Anthropometric Somatotype and Body Composition: A Cross-sectional Study

Ayurveda prioritizes prevention and personalized treatment based on Tridosha composition. Very few studies have adopted the transdiagnostic approach of associating Tridosha with anthropometric and body composition parameters, especially in the Indian population.

To map Tridosha with anthropometric somatotypes and body compositions, and develop regression models for predicting Vata, Pitta, and Kapha from physical parameters.

This cross-sectional study assessed 57 healthy male Indian university students who underwent anthropometric and body composition assessments including Heath-Carter somatotyping, and Tridosha profiling (using Ayusoft®). Chi-square tests with Cramer's-V statistics evaluated associations between Tridosha, somatotype, and body mass index (BMI) categories. Least absolute shrinkage and selection operator (LASSO) regression models were developed to predict Vata, Pitta, and Kapha from physical parameters.

Vata and Kapha showed significant (P < .001) negative and positive correlations, respectively, with weight, BMI, lean body mass, soft lean mass, mean body fat, body fat%, waist and hip circumference, waist-height ratio, endomorph, and mesomorph. Pitta showed a similar trend as Kapha in waist circumference, BMI, waist-height and height-weight ratio, mesomorph, and ectomorph only; however, the correlations were weak (|r| < 0.32). LASSO regression identified that anthropometric and body composition parameters significantly predict Vata (R2 = 0.77, RMSE = 4.92) and Kapha (R2 = 0.60, RMSE = 6.77), while Pitta (R2 = 0.24, RMSE = 6.45) appeared independent of these measurements.

This transdiagnostic relationship between Tridosha, body composition, and somatotype maps traditional Ayurvedic knowledge with contemporary science, and has potential implications for integrative healthcare applications.

Anthropometry, Ayurveda, Ayusoft, Body Fat, Prakriti, Somatotype.