Body fat assessment in women. Special considerations.

Methods of in vivo body fat estimation are based on simple assumptions about body composition which work reasonably well for men, while estimations in women have been largely extrapolated from the male studies so that women are treated as men with just more of the same fat. Compared to men, fat regulation in women is considerably more elaborate, with more and different sites for storage and a larger proportion of fat distributed to the extremities and in subcutaneous locations. Thus, a ratio of waist-to-hips girth which reflects increasing fatness in men only specifies 2 different extremes of a broader spectrum of possibilities for fat distribution in women. This complicates anthropometric prediction of total fatness and clearly limits the generalisability of any female equations. Anthropometric methods are further confounded by difficulties in the criterion methods against which they are developed. For example, the validity of assumptions about the fractional contributions of bone mineral and body water to fat-free mass and density may not hold through the reproductive cycles. Women athletes involved in weight-bearing or strength training may increase bone mineral content above average values but if they become amenorrhoeic, bone mineral density may fall significantly below average values. Fit premenopausal women distribute fat differently and have a higher bone mineral content than unfit postmenopausal women. Genetic factors which also affect criterion method assumptions in men are superimposed on these additional complications in women. Body fat in female athletes extends across almost the entire range of female fatness, with some of the lowest measurements in distance runners and body builders which fall into the normal male range, but also with some relatively high values in swimmers and strength athletes, which would classify these women as obese by male standards. Thus, total body fat reflects a more complex regulation and has a different meaning to health and performance in women than it does for men. Predictive equations for women athletes should be developed with a view to the specific group and ultimate purpose to which they will be applied.