What is the purpose of using regression equations in stature estimation?

• A. To convert measured bone lengths into an estimate of living stature, accounting for sex and ancestry differences.
• B. To estimate time since death from bone length.
• C. To estimate age at death from long bone measurements.
• D. To determine ancestry from bone lengths.

Answer: (C)

Regression equations in stature estimation are used to predict living height from measurable bone lengths. They’re developed from reference samples where both bone measurements and the person’s actual height are known, so the equation translates a length (for example, a tibia or femur) into an estimate of how tall the person would have stood in life. Because limb proportions differ by sex and ancestry, these equations are typically sex-specific or population-specific, or include ancestry as a factor to improve accuracy for a given individual. This focus on converting bone length to stature, with adjustments for sex and population differences, is what makes regression the appropriate tool for stature estimation. Time since death, age at death from long bone measurements, or directly determining ancestry from bone lengths are not the primary purposes of these regression equations.