Fat-Free Mass Index (FFMI) - Actual and Estimated  
 
  
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Background 
BMI  (kg/m2 
FFMI (kg/m2 ) + FMI (kg/m2 ) 
 
Data (Inputs) 
Inches 
Centimeters 
     
Kilograms 
Pounds 
 
Male 
Female 
 
 
Key References
(direct quotes) 
Key Reference
 
Mittal, R. , Goyal, M. , Dasude, R. , Quazi, S. and Basak, A. (2011)
Measuring obesity: results are poles apart obtained by BMI and
bio-electrical impedance analysis. Journal of Biomedical Science and
Engineering, 4, 677-683. doi: 10.4236/jbise.2011.411084.   
Objective : To analyse the use of BMI and
bioelectrical impedance analysis (BIA) in assessment of adiposity among young and elderly population. Materials and
methods: Age, height, weight and percent body fat (PBF) of 101
young and 276 elder subjects were recorded. PBF was measured
directly by BIA instrument (PBFb) and also calculated from BMI
(PBFf). The classification of subjects into underweight, normal,
overweight and obese was based on the age- and sex-specific BMI
cutoff values and PBFb following standard guidelines. Results : The calculated mean BMI values of
young and old age groups were statistically the same. PBF was
significantly high in elder subjects.
There was no statistical
difference in mean PBFb and PBFf in young subjects but the
difference was significant in eldery subjects . The PBFf
values were highly correlated (r: 0.92 to 0.96) with PBFb values
in young age groups unlike elder groups of both males and
females. PBFb based categorization of subjects’ presented
totally different scenario com-pared to results obtained by BMI
analysis to assess adiposity. Conclusion : The cases such as increasing
fatness with aging even when BMI remains constant, the causes of
country or ethnic differences in BMI analysis, poor correlation
in PBFb and PBFf values in elder age group emphasize on the
limitations of BMI based analysis. PBFb within limitations seems
to be an improved phenotypic characteristic over BMI.Significance of PBF over BMI Studies indicate that relative fatness in adults increases
with age. Although the mechanisms behind this observation are
not fully understood, an important and as yet unanswered
question is whether the greater fatness with older age, even
after BMI is same as of young population, poses additional
health risks. Experts has recommend to measure adiposity in
combination of BIA and with other risk factors of morbidity and
mortal-ity; rather than relying only on BMI cut-points. However,
our results shows that increased PBF and its consequences cannot
be predicted by BMI analysis in elder group of both, males and
females. 
 
 
 
 
Key Reference
 
Schutz, Y., Kyle, U. & Pichard, C.. Fat-free mass index and fat mass index
percentiles in Caucasians aged 18-98 y. Int J Obes Relat Metab Disord. 2002;
26(7):953-60.
https://doi.org/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.Results : The median FFMI (18-34 y) were
18.9 kg/m2 in young males and 15.4 kg/m2 in young females. No
difference with age in males and a modest increase in females
were observed. The median FMI was 4.0 kg/m2 in males and 5.5
kg/m2 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.The major shortcoming of the BMI is that the actual
composition of body weight is not taken into account: excess
body weight may be made up of adipose tissue or conversely
muscle hypertrophy, both of which will be judged as ‘excess
mass’. On the other hand, a deficit of BMI may be due to a
fat-free mass (FFM) deficit (sarcopenia) or a mobilization of
adipose tissue or both combined. 
The partitioning of BMI into FFMI and FMI is obviously not
possible without associated measurements of body composition.
Note that the original idea of calculating the FFM and fat mass
(FM) indexes, in analogy to the BMI, was proposed several years
ago. The potential advantage is that only one component of body
weight, ie FFM or FM, is related to the height squared.
Surprisingly, these indexes have not found a wide application
yet, probably because appropriate reference standards have yet
to be defined. By determining these indexes, quantification of
the amount of excess (or deficit) of FFM, respectively FM, can
be calculated for each individual. 
Calculation of FFM and FM indexesFFMI   (Fat-free mass index) = fat-free
mass [kg]/height[m]2 FMI  (Fat mass index) = fat mass [kg] /
height[m]2  
BMI  (kg/m2 
FFMI (kg/m2 ) + FMI (kg/m2 )  Expression of FFM :Age related issues : 
 
 
 
Key Reference
 
Kyle UG, Schutz Y, Dupertuis YM, Pichard C. Body composition
interpretation. Contributions of the fat-free mass index and the
body fat mass index. Nutrition. 2003 Jul-Aug;19(7-8):597-604. doi:
10.1016/s0899-9007(03)00061-3. PMID: 12831945. 
Effect of Aging on FFMI and BFMI  
Interpretation of FFMI and BFMI   
OBJECTIVE : Low and high body mass index (BMI)
values have been shown to increase health risks and mortality
and result in variations in fat-free mass (FFM) and body fat
mass (BF). Currently, there are no published ranges for a
fat-free mass index (FFMI; kg/m2), a body fat mass index (BFMI;
kg/m2), and percentage of body fat (%BF). The purpose of this
population study was to determine predicted FFMI and BFMI values
in subjects with low, normal, overweight, and obese BMI.
 
METHODS : FFM and BF were determined in 2986
healthy white men and 2649 white women, age 15 to 98 y, by a
previously validated 50-kHz bioelectrical impedance analysis
equation. FFMI, BFMI, and %BF were calculated.
 
RESULTS : FFMI values were 16.7 to 19.8 kg/m2
for men and 14.6 to 16.8 kg/m2 for women within the normal BMI
ranges. BFMI values were 1.8 to 5.2 kg/m2 for men and 3.9 to 8.2
kg/m2 for women within the normal BMI ranges. BFMI values were
8.3 and 11.8 kg/m2 in men and women, respectively, for obese BMI
(>30 kg/m2). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to
33.2 for men and women, respectively.
 
CONCLUSION  BMI alone cannot provide information
about the respective contributions of FFM and FM to body weight.
This study presented the FFMI, BFMI, and %BF values that
correspond to low, normal, overweight, and obese BMIs. FFMI and
BFMI can provide meaningful information about body compartments,
regardless of height.
 
 
 
 
 
 
 
 
 
References
 
Janmahasatian S, Duffull SB, Ash S, Ward LC, Byrne NM, Green B:
Quantification of lean bodyweight. Clin Pharmacokinet. 2005, 44
(10): 1051-1065. 10.2165/00003088-200544100-00004. 
Kim CH, Chung S, Kim H, Park JH, Park SH, Ji JW, Han SW, Lee JC, Kim
JH, Park YB, Nam HS, Kim C. Norm references of fat-free mass index and
fat mass index and subtypes of obesity based on the combined FFMI-%BF
indices in the Korean adults aged 18-89 yr. Obes Res Clin Pract. 2011
Jul-Sep;5(3):e169-266. doi: 10.1016/j.orcp.2011.01.004. PMID: 24331103. 
Kouri EM, Pope HG Jr, Katz DL, Oliva P. Fat-free mass index in users and
nonusers of anabolic-androgenic steroids. Clin J Sport Med. 1995
Oct;5(4):223-8. doi: 10.1097/00042752-199510000-00003. PMID: 7496846. [Normalized
FFMI] 
Kyle UG, Schutz Y, Dupertuis YM, Pichard C. Body composition
interpretation. Contributions of the fat-free mass index and the body
fat mass index. Nutrition. 2003 Jul-Aug;19(7-8):597-604. doi:
10.1016/s0899-9007(03)00061-3. PMID: 12831945. 
Lee, K., Lee, S., Kim, S.Y. et al. (2007) Percent body fat cutoff
values for classifying overweight and obesity recommended by the
International Obesity Task Force (IOTF) in Korean children. Asia Pacific
Journal of Clinical Nutrition, 16, 649-655. 
Mittal, R. , Goyal, M. , Dasude, R. , Quazi, S. and Basak, A. (2011)
Measuring obesity: results are poles apart obtained by BMI and
bio-electrical impedance analysis. Journal of Biomedical Science and
Engineering, 4, 677-683. doi: 10.4236/jbise.2011.411084.
 
Nyman U. James Lean Body Weight Formula Is Not Appropriate for Determining
CT Contrast Media Dose in Patients with High Body Mass Index. Radiology.
2016 Mar;278(3):956-7. doi: 10.1148/radiol.2016152031. PMID: 26885737. 
Schutz, Y., Kyle, U. & Pichard, C.. Fat-free mass index and fat mass index
percentiles in Caucasians aged 18-98 y. Int J Obes Relat Metab Disord. 2002;
26(7):953-60.
https://doi.org/10.1038/sj.ijo.0802037  
Yu, S., Visvanathan, T., Field, J. et al. Lean body mass: the
development and validation of prediction equations in healthy adults.
BMC Pharmacol Toxicol 14, 53 (2013).
https://doi.org/10.1186/2050-6511-14-53.