Are parturition scars truly signs of birth? The estimation of parity in a well-documented modern sample

Parturition scars have been frequently studied in the last decades, but their association with pregnancy and birth is still controversial. Other biomechanical, biometric, and lifestyle factors are also likely to influence the development of pelvic features. Most previous studies of pelvic features were based on skeletal collections with no reliable information on parity or even sex and thus were unable to disentangle these factors. Here, we study the association of pelvic features with birth and other body variables (age, stature, weight, osteoarthritis, and centrum-collum-diaphyseal angle) using multiple regression and path modeling in a modern sample of female individuals from New Mexico (USA) with detailed background information (n = 150). We also explored the utility of pelvic features to predict the number of births. To this end, we scored the expression of the preauricular sulcus, sacral preauricular extension, extended pubic tubercle, exostosis at the pectineal line, dorsal, and ventral pubic pitting using CT scans from the New Mexico Decedent Image Database. Quantitative measurements of pelvic features were then used as predictors of parity. Overall, the regression models accounted only for relatively small fractions of variance in pelvic feature expression. The only feature significantly associated with the number of births was dorsal pubic pitting (R-2 = 0.2372), whereas the expression of most pelvic features increased with age, independent of parity. Presumably, the development of dorsal pubic pitting is affected both by biomechanical stress and the increased hormonal secretion during pregnancy and birth. The individual prediction of parity based on pelvic features is too imprecise for forensic or archeological applications. However, using a size score of dorsal pubic pitting allowed us to estimate the mean parity in groups of individuals relatively well. Hence, pelvic features may still be used to compare average parity across recent or historic populations.