Christopher B. Ruff, Ian J. Wallace, Amaya Abeyta-Brown, Madison Butler, Taylor Busby
{"title":"Technical note: Prediction of body mass from stature and pelvic breadth","authors":"Christopher B. Ruff, Ian J. Wallace, Amaya Abeyta-Brown, Madison Butler, Taylor Busby","doi":"10.1002/ajpa.25004","DOIUrl":null,"url":null,"abstract":"<p>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 (<i>n</i> = 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.</p>","PeriodicalId":29759,"journal":{"name":"American Journal of Biological Anthropology","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Biological Anthropology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ajpa.25004","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.