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Estimation of body fat in female rhesus monkeys
Author(s) -
Walker Margaret L.,
Schwartz Susan M.,
Wilson Mark E.,
Musey Paul I.
Publication year - 1984
Publication title -
american journal of physical anthropology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 119
eISSN - 1096-8644
pISSN - 0002-9483
DOI - 10.1002/ajpa.1330630309
Subject(s) - skinfold thickness , classification of obesity , rump , abdominal fat , subcutaneous fat , population , body mass index , regression analysis , body weight , linear regression , body adiposity index , body water , zoology , medicine , physiology , mathematics , biology , fat mass , statistics , adipose tissue , environmental health
Measurement of height (crown–rump length), body weight, and abdominal subcutaneous fat depth, based on skinfold thickness taken from 13 female rhesus monkeys comprising two age groups were correlated with body fat values derived from tritiated water determinations of total body water. The manner with which each measure was related to percent body fat differed as a function of age of the animal. In the young, nulliparous females, crown–rump length was the single best predictor of body fat, whereas in the older, multiparous females, skinfold thickness correlated most highly with body fat. When all measurements, including the Quetelet index [(wt/ht) 2 × 1,000], were combined statistically and regressed against percent body fat, a significant increase in predictive ability was obtained. When each age group was considered separately, the resulting equations again reflected the agegroup biases. In addition, as an internal check on the validity of the regression equations, an additional regression analysis was performed using morphometric data from selected animals in each age group. These equations yielded accurate estimates of body fat when compared to determinations made from total body water. These analyses indicate that the predictive accuracy of morphometric data is greatly enhanced by using these measurements in concert. Furthermore, the utility of such predictions is influenced by the specific physical characteristics of the subject population.