Browsing by Author "Cameron, Noël"

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    Evaluating morphometric body mass prediction equations with a juvenile human test sample: accuracy and applicability to small-bodied hominins.
    (Journal of human evolution, 2018-02) Walker, Christopher S; Yapuncich, Gabriel S; Sridhar, Shilpa; Cameron, Noël; Churchill, Steven E
    Body mass is an ecologically and biomechanically important variable in the study of hominin biology. Regression equations derived from recent human samples allow for the reasonable prediction of body mass of later, more human-like, and generally larger hominins from hip joint dimensions, but potential differences in hip biomechanics across hominin taxa render their use questionable with some earlier taxa (i.e., Australopithecus spp.). Morphometric prediction equations using stature and bi-iliac breadth avoid this problem, but their applicability to early hominins, some of which differ in both size and proportions from modern adult humans, has not been demonstrated. Here we use mean stature, bi-iliac breadth, and body mass from a global sample of human juveniles ranging in age from 6 to 12 years (n = 530 age- and sex-specific group annual means from 33 countries/regions) to evaluate the accuracy of several published morphometric prediction equations when applied to small humans. Though the body proportions of modern human juveniles likely differ from those of small-bodied early hominins, human juveniles (like fossil hominins) often differ in size and proportions from adult human reference samples and, accordingly, serve as a useful model for assessing the robustness of morphometric prediction equations. Morphometric equations based on adults systematically underpredict body mass in the youngest age groups and moderately overpredict body mass in the older groups, which fall in the body size range of adult Australopithecus (∼26-46 kg). Differences in body proportions, notably the ratio of lower limb length to stature, influence predictive accuracy. Ontogenetic changes in these body proportions likely influence the shift in prediction error (from under- to overprediction). However, because morphometric equations are reasonably accurate when applied to this juvenile test sample, we argue these equations may be used to predict body mass in small-bodied hominins, despite the potential for some error induced by differing body proportions and/or extrapolation beyond the original reference sample range.
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    Morphometric panel regression equations for predicting body mass in immature humans.
    (American journal of physical anthropology, 2018-05) Yapuncich, Gabriel S; Churchill, Steven E; Cameron, Noël; Walker, Christopher S
    OBJECTIVES:Predicting body mass is a frequent objective of several anthropological subdisciplines, but there are few published methods for predicting body mass in immature humans. Because most reference samples are composed of adults, predicting body mass outside the range of adults requires extrapolation, which may reduce the accuracy of predictions. Prediction equations developed from a sample of immature humans would reduce extrapolation for application to small-bodied target individuals, and should have utility in multiple predictive contexts. MATERIALS AND METHODS:Here, we present two novel body mass prediction equations derived from 3468 observations of stature and bi-iliac breadth from a large sample of immature humans (n = 173) collected in the Harpenden Growth Study. Prediction equations were generated using raw and natural log-transformed data and modeled using panel regression, which accounts for serial autocorrelation of longitudinal observations. Predictive accuracy was gauged with a global sample of human juveniles (n = 530 age- and sex-specific annual means) and compared to the performance of the adult morphometric prediction equation previously identified as most accurate for human juveniles. RESULTS:While the raw data panel equation is only slightly more accurate than the adult equation, the logged data panel equation generates very accurate body mass predictions across both sexes and all age classes of the test sample (mean absolute percentage prediction error = 2.47). DISCUSSION:The logged data panel equation should prove useful in archaeological, forensic, and paleontological contexts when predictor variables can be measured with confidence and are outside the range of modern adult humans.