To compare the characteristics of body composition for different gender and age in a large number of apparently healthy Chinese subjects, and to determine reference values for fat-free mass index (FFMI) and fat mass index (FMI).
In total, 61 382 Chinese adults (age range: 18–92 years) were consecutively enrolled into the study. Body composition was measured using bioelectrical impedance analysis with a tetrapolar impedance meter.
The skeletal muscle mass, fat-free mass (FFM), FFMI and body mass index (BMI) were significantly higher in men than in women (P<0.05), but FM% and FMI were significantly higher in women (P<0.05). In the group with normal BMI (BMI 18.5–23.9 kg/m2, 18–92 years), the reference values (5th–95th percentile) of FM%, FFMI and FMI were 9.7–34.5%, 14.15–19.76 and 1.99–7.75 kg/m2 in men, and 18.1–35.8%, 13.82–17.89 and 3.68–8.16 kg/m2 in women, respectively.
Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in FFM with or without excess FM for a given age category, complementing the classical concept of BMI in a more qualitative manner, although these indices are only suggestive indications for the degree of obesity. In contrast to BMI, similar reference ranges of FFMI seem to be more utilizable with advancing age.
The problem of obesity, and its related complications, has become a major health concern globally. Prevention and treatment of this global problem is proving to be a challenge. The degree of obesity is simply classified in most epidemiological studies by means of the body mass index (BMI). Reference standards for the ‘normality’ of BMI have been defined to classify various degrees of overweight and obesity, but universal cutoff points have been challenged.1 Significant changes in body composition occur over a lifetime. Progressive increases in adiposity and decreases in fat-free mass (FFM) during adulthood have been noted.2 Excess adiposity, increased body fatness and depletion of FFM or muscle mass are associated with certain chronic diseases, such as cardiovascular disease3 and respiratory insufficiency,4 respectively. 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 fat or conversely muscle hypertrophy. On the other hand, a deficit of BMI may be due to FFM deficit or a mobilization of fat or both combined.5 Weight and BMI alone are inadequate to detect underlying changes in FFM and FM with age and disease.6
The concept of fat-free mass index (FFMI) and fat mass index (FMI), in analogy to the BMI but using a two compartment model, appears to be of interest in the classification of adiposity. We expressed body-composition data as FMI and FFMI, as first suggested by Van Itallie et al.7 In this approach, BMI is understood as a simple sum of fat and fat-free components of body weight (FMI+FFMI), each of which is adjusted for (divided by) height2. These height-adjusted indices may have advantages over both unadjusted measures of lean mass and fat mass (FFM and FM) and weight-adjusted measures of fat mass (% BF) for the tracking of nutritional status.
The partitioning of BMI into FFMI and FMI needs measurements of body composition. Bioelectrical impedance analysis (BIA) is an easily performed and non-invasive way to measure body composition including total body water, skeletal muscle mass and body FM.8, 9, 10 The value of BIA in the estimation of body adiposity both on a clinical basis in the individual and epidemiologically in large groups to define the presence or prevalence of obesity, respectively, is of great interest. BIA appears to be a more accurate measure of FFM and percentage of body fat than body weight, height or BMI. Aging is associated with decreased total body weight, bone mass and FFM,5 so it would be useful to obtain FMI and FFMI reference values for the elderly.
The aims of this study were to describe the reference values of FFMI and FMI and to compare the body composition for different gender and age in a large number of apparently healthy Chinese subjects.
Subjects and methods
In total, 61 382 healthy adults (age range: 18–92 years, 39 855 men and 21 527 women) were consecutively enrolled into the study between May 2005 and February 2011 at the health examination center of Chinese PLA general hospital. The experimental protocol was approved by the local Ethics Committee. Exclusion criteria were pregnant or lactating women; the presence of major debilitating diseases; major cardiovascular events; treatment with systemic glucocorticoids within the previous 3 months. Subjects wore uniform indoor clothing and shoes. Body height was measured to the nearest 0.5 cm and body weight to the nearest 0.1 kg. Body composition was measured using BIA with a tetrapolar impedance meter (Human-IM Scan; VIVENTE SILVER, Seoul, Korea).
Calculation of FFM and FM indexes
The FFM and FM indexes are equivalent concepts to the BMI, FFM was calculated according to the formula by Van Itallie et al.,7 as shown in the following definition:
Note that, mathematically, BMI (kg/m2)=FFMI(kg/m2)+FMI(kg/m2).
Resistance and reactance were measured by BIA generators and used to first mathematically derive FFM and FM as described previously.11, 12, 13, 14, 15, 16 The following formula was used: V=ρ × ht2/R in which the conductive volume (V) is assumed to represent FFM, ρ is the specific resistivity of the conductor, height (ht) is assumed to represent the length of the conductor and (R) is the whole-body resistance. FFM derived from BIA has been validated previously against dual-energy X-ray absorptiometry.17
Cutoff points of overweight or obesity according to BMI in China
According to the prevention and control guide of Chinese adult overweight and obesity, patients with BMI <18.5 were classified as underweight, BMI 18.5–23.9 as ideal weight, BMI 24.0–27.9 as overweight and BMI ⩾28 as obese.
The statistical analysis was performed using the Statistical Package for the Social Sciences—SPSS version 11.5 (Somers, NY, USA) for Windows. The results are expressed as mean±standard deviation (x±s.d.). Age- and sex-specific percentile distributions were calculated for each of the following parameters: FFMI and FMI. The data were stratified by steps of 10 years according to age. The differences between sex groups calculated using a t-test. The differences among age groups were analyzed by analysis of variance. Statistical significance was defined as P<0.05.
Table 1 presents the anthropometric characteristics of the men and women. The skeletal muscle mass, FFM, FFMI and BMI were significantly higher in men than in women (P<0.05). There was no significant difference in FM between men and women, but FM% and FMI were significantly higher in women (P<0.05).
The results of the anthropometric data categorized by gender and age are given in Table 2. With the increase of age, the skeletal muscle mass, FFM, FFMI, FM, FM%, FMI and BMI increased significantly before the age of 50 years in men. In women, the FM, FM% and FMI increased with aging even over 70 years (P<0.05), but the skeletal muscle mass, FFM and FFMI began to decrease at the age of 60 years (P<0.05). The data were categorized by gender and BMI, as shown in Table 3. In men, the FM, FM% and FMI were significantly lower, while the skeletal muscle mass, FFM and FFMI were significantly higher than in women even with the same ‘normality’ of BMI (BMI 18.5–23.9 kg/m2, P<0.05).
In the group with normal BMI (BMI 18.5–23.9 kg/m2, 18–92 years), the reference values (5th–95th percentile) of FM%, FFMI and FMI were 9.7–34.5%, 14.15–19.76 and 1.99–7.75 kg/m2 in men, and 18.1–35.8%, 13.82–17.89 and 3.68–8.16 kg/m2 in women, respectively. The gender and age stratified reference ranges were shown in Table 4.
Considering that BMI is the sum of FFMI+FMI, an increase (or a decrease) in BMI could be accounted for by a rise (or a drop) in one component, in the other or in both components. Therefore, the advantage of the combined use of these indices is that one can judge whether the deficit or excess of body weight is selectively due to a change in FFM vs FM or both combined. One advantage of FMI, as compared with the BMI concept, is that it amplifies the relative effect of aging on body fat. Expression of a change in body FM in absolute value fails to allow an appropriate comparison among subjects of different sizes.
This study showed that the skeletal muscle mass, FFM, FFMI and BMI were significantly higher in men than in women, but FM% and FMI were significantly higher in women, which was as expected. In men, the FM, FM% and FMI were significantly lower, while the skeletal muscle mass, FFM and FFMI were significantly higher than in women even with the same ‘normality’ of BMI (BMI 18.5–23.9 kg/m2). With the increase of age, the skeletal muscle mass, FFM, FFMI, FM, FM%, FMI and BMI increased significantly before the age of 50 years in men. In women, the FM, FM% and FMI increased with aging even over 70 years, but the skeletal muscle mass, FFM and FFMI began to decrease at the age of 60 years. The earlier change (decrease) in FFM in adults suggests that the age-related weight increase was not sufficient to offset an age-related FFM decrease and thus resulted in a lower ratio of FFM to height in older than in younger Chinese especially in women. During aging, the weight gain is mostly explained by a gain in body fat, but this is linked to a slight rise in FFM. Low FFM is a major contributor to the loss of functional ability and health.18
Up to now, reference ranges for FFMI and FMI have not been clearly defined, at least in a large group of healthy individuals in China. It is proposed that reference values may be useful, in a clinical setting or in field surveys, for comparative purposes in the evaluation of the nutritional status and body composition of patients with excess energy stores (such as obesity) on the one hand or deficit of muscle mass (such as in wasting disease) on the other hand. The concept of FFMI has been previously described in adults and elderly individuals, as an indicator of nutritional status,7, 19 as well as in chronic obstructive pulmonary disease patients.20
In this study, the size of the sample is large and includes the effect of gender and age, bracketing a large age range in adulthood. In the whole group (18–92 years), the reference values (5th–95th percentile) of FFMI and FMI were 15.3–22.3 and 3.0–10.5 kg/m2 in men, and 14.0–20.0 and 3.8–11.5 kg/m2 in women, respectively. Note that the sum of FFM+FMI was mathematically equivalent to BMI, in our sample, if a subject was at percentile 95 for both FFMI and FMI, then the BMI would highly exceed 28 kg/m2, the China criteria for obesity based on BMI. So, it was not the appropriate reference values. Since body weight increases in developing countries, 23.5% males and 13.1% females were with obesity in this sample. While in the group with normal BMI (BMI 18.5–23.9 kg/m2), the reference values (5th–95th percentile) of the FFMI and FMI were 14.15–19.76 and 1.99–7.75 kg/m2 in men, and 13.82–17.89 and 3.68–8.16 kg/m2 in women, respectively. By this means, if a subject is at percentile 95 for both FFMI and FMI, then the BMI will be still <28 kg/m2.
Deurenberg-Yap et al.21 demonstrated that there is a discrepancy between average BMI and average relative body fat in certain ethnic group (Chinese population). Their study showed a higher percentage body fat for the same BMI as compared with Caucasians. This indicates that FMI will be higher at the same BMI compared with other populations. Schutz et al.22 reported that FMIs >8.2 kg/m2 in men and 11.8 kg/m2 in women would define the ‘overfat’ status (rather than the overweight range) in terms of FM in a Caucasian population in Switzerland aged 18–98 years. As in our study, the FMI cutpoints were 7.75 kg/m2 in men and 8.16 kg/m2 in women, which were lower than in Caucasian.
In summary, reference intervals of FMI vs FFMI can be used as indicative values for the evaluation of nutritional status of apparently healthy subjects and can provide complementary information to the classical expression of body composition reference values.23 FMI is able to identify individuals with elevated BMI but without excess FM. Conversely, FMI can identify subjects with ‘normal’ BMI but who are at potential risk because of elevated FM. The data in this study are cross-sectional, and body composition estimates in this study were not based on criterion measures but were calculated from BIA resistance and anthropometric measurements. Longitudinal studies are required to confirm these observations of changes in FFM and BF with age, and to elucidate the relationship between the reference ranges for FFMI and FMI with potential risk factors and subsequent mortality.
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The authors declare no conflict of interest.
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Cite this article
Lu, Y., Shu, H., Zheng, Y. et al. Comparison of fat-free mass index and fat mass index in Chinese adults. Eur J Clin Nutr 66, 1004–1007 (2012). https://doi.org/10.1038/ejcn.2012.86
- fat-free mass
- body composition
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