Body condition indices are widely used by ecologists, but many indices are used without empirical validation. To test the validity of a variety of indices, we compared how well a broad range of body condition indices predicted body fat mass, percent body fat and residual fat mass in mice Mus musculus. We also compared the performance of these condition indices with the multiple regression of several morphometric variables on body fat mass, percent body fat and residual fat mass.
In our study population, two ratio based condition indices – body mass/body length and log body mass/log body length – predicted body fat mass as well as or better than other ratio and residual indices of condition in females. In males one ratio based condition index (log body mass/log body length) and one residual index (residuals from a regression of pelvic circumference on body length) were best at predicting body fat mass. All indices were better at estimating body fat mass, and residual fat mass than at estimating percent body fat. The predictions of body fat were much better for females than for males.
Multiple regressions incorporating pelvic circumference (i.e. girth at the iliac crests) were the best predictors of body fat mass, residual fat mass, and percent body fat, and these multiple regressions were better than any of the condition indices.
We recommend 1) that condition be precisely defined, 2) that predictors of condition be empirically validated, 3) that pelvic circumference be considered as a potential predictor of fat content, and 4) that, in general, multiple regression be considered as an alternative to condition indices.