Fat-free mass index and fat mass index percentiles in Caucasians aged 18-98 y

Int J Obes Relat Metab Disord. 2002 Jul;26(7):953-60. doi: 10.1038/sj.ijo.0802037.


Objective: To determine reference values for fat-free mass index (FFMI) and fat mass index (FMI) in a large Caucasian group of apparently healthy subjects, as a function of age and gender and to develop percentile distribution for these two parameters.

Design: Cross-sectional study in which bioelectrical impedance analysis (50 kHz) was measured (using tetrapolar electrodes and cross-validated formulae by dual-energy X-ray absorptiometry in order to calculate FFMI (fat-free mass/height squared) and FMI (fat mass/height squared).

Subjects: A total of 5635 apparently healthy adults from a mixed non-randomly selected Caucasian population in Switzerland (2986 men and 2649 women), varying in age from 24 to 98 y.

Results: The median FFMI (18-34 y) were 18.9 kg/m(2) in young males and 15.4 kg/m(2) in young females. No difference with age in males and a modest increase in females were observed. The median FMI was 4.0 kg/m(2) in males and 5.5 kg/m(2) in females. From young to elderly age categories, FMI progressively rose by an average of 55% in males and 62% in females, compared to an increase in body mass index (BMI) of 9 and 19% respectively.

Conclusions: Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner. In contrast to BMI, similar reference ranges seems to be utilizable for FFMI with advancing age, in particular in men.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipose Tissue*
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Body Composition*
  • Body Mass Index*
  • Cross-Sectional Studies
  • Electric Impedance
  • Female
  • Humans
  • Male
  • Middle Aged
  • Obesity
  • Reference Values
  • Regression Analysis