Osteometric Regression Equations for Stature Estimation: A Global Database (1929–2025)

This dataset is a comprehensive compilation of 157 linear regression equations used to estimate human height based on measurements of long bones. The data were extracted from a literature review of 32 primary sources, spanning nearly a century of anthropological research (from 1929 to the present). The dataset allows for filtering specific formulas based on:Biological dimension: Differentiation by sex (Male/Female) and bone type (Femur, Tibia, Humerus, Radius, Ulna, and Fibula).Population context: Geographic and ethnic applicability (populations from Asia, Europe, the Americas, etc.). Statistical parameters such as standard error (SE), sample size (n), and regression coefficients (a and b) are included. The utility of this dataset lies in the centralization and standardization of formulas that, until now, were scattered across historical and regional publications that were difficult to access. The dataset facilitates the estimation of biological profiles in skeletal remains by applying specific formulas for the population closest to the analyzed individual, thereby reducing the margin of error inherent in generic formulas. By breaking down the equations into their mathematical components (Intercept and Slope), the dataset allows for direct integration into statistical analysis software or digital calculators, eliminating the risk of manual transcription errors.