Accuracy and Reliability of Total Body Mass Estimation Techniques from Stature and Bi-iliac Breadth in Non-Hispanic U.S. Whites from the Bass Donated Skeletal Collection

Technical note: Prediction of body mass from stature and pelvic breadth

Equations for predicting body mass from stature and bi-iliac (maximum pelvic) breadth have been developed, but have had variable success when applied to living or recently deceased individuals, calling into question their general applicability. Here we test these equations on a large, ethnically diverse sample. Skeletal and anthropometric data for 507 recently deceased Indigenous, Hispanic, and non-Hispanic White adults were obtained from the New Mexico Decedent Image Database. The body mass of individuals with a "normal" body mass index (BMI = 18.5-24.9) is very accurately predicted, with an average directional bias of about 1% and an average random error of less than 8%. Underweight individuals (BMI < 18.5) are overpredicted, while overweight (BMI = 25-29.9) and especially obese (BMI≥30) individuals are underpredicted. Within BMI categories, there is a strong and isometric relationship between predicted and true body mass. Individual body mass prediction errors using the stature/bi-iliac method are mainly dependent on variation in BMI. Because earlier humans were more likely to fall within or close to the normal BMI range, the equations should be applicable, on an individual basis, in archeological and paleontological contexts. Because of the prevalence of obesity in many modern populations, these equations are not applicable in a general forensic context. We derive new equations from nonobese individuals in our sample (n = 338), which produce reasonable average prediction errors. If obese individuals can be identified using other skeletal parameters, these equations may be useful in estimating body mass in nonobese forensic cases.

Body mass estimation from dimensions of the fourth lumbar vertebra in middle-aged Finns

Although body mass is not a stable trait over the lifespan, information regarding body size assists the forensic identification of unknown individuals. In this study, we aimed to study the potential of using the fourth lumbar vertebra (L4) for body mass estimation among contemporary Finns. Our sample comprised 1158 individuals from the Northern Finland Birth Cohort 1966 who had undergone measurements of body mass at age 31 and 46 and lumbar magnetic resonance imaging (MRI) at age 46. MRI scans were used to measure the maximum and minimum widths, depths, and heights of the L4 body. Their means and sum were calculated together with vertebral cross-sectional area (CSA) and volume. Ordinary least squares (OLS) and reduced major axis (RMA) regression was used to produce equations for body mass among the full sample (n = 1158) and among normal-weight individuals (n = 420). In our data, body mass was associated with all the L4 size parameters (R = 0.093-0.582, p ≤ 0.019 among the full sample; R = 0.243-0.696, p ≤ 0.002 among the normal-weight sample). RMA regression models seemed to fit the data better than OLS, with vertebral CSA having the highest predictive value in body mass estimation. In the full sample, the lowest standard errors were 6.1% (95% prediction interval ±9.6 kg) and 7.1% (±9.1 kg) among men and women, respectively. In the normal-weight sample, the lowest errors were 4.9% (±6.9 kg) and 4.7% (±5.7 kg) among men and women, respectively. Our results indicate that L4 dimensions are potentially useful in body mass estimation, especially in cases with only the axial skeleton available.