Multi-component models of body composition are a class of inference models that use more than one source of measurement data to achieve a more valid estimate of body composition.
The human body can be described in terms of its different components (or “compartments”), each of which contains different types of atomic, molecular, cellular or tissue material. These components can be assessed and combined to describe the composition of the human body; as described in Table 1, models typically use between 2 and 4 components, but 5- and 6-component models also exist The components which comprise different multi-component models are summarised in Figure 1.
Figure 1 Components measured to generate different multi-component models.
Source: MRC Epidemiology Unit.
Important: Figure is not to scale and represents the assumptions of the models, not the exact relationships between different components in-vivo.
*Includes water, protein, glycogen, bone mineral content, and non- osseous mineral content.
**Includes protein, glycogen, bone mineral content, and non-osseous mineral content.
***There is a difference between mineral content and mineral mass. Measures of mineral content are typically converted to mineral mass to reflect the ashing process.
Assessment of body composition requires quantification of at least two components; we refer to this as a 2-component (2C) model, the most common of which divides total body mass into fat-free mass (FFM) and fat mass (FM).This model assumes that fat-free mass and fat mass have densities of 1.1 kg/L and 0.9 kg/L respectively and this approach typically uses the following equations to estimate % body fat:
Measurements that allow inferences to be made on these components include:
However, the 2C model is subject to error due to inter-individual variation in the composition of the fat-free mass compartment. Fat-free mass consists of minerals, proteins and water. The 2C model assumes constant values for water content (hydration fraction), bone mineral content (BMC), and density of fat-free mass, but these do vary between ethnicities, age groups, pubertal status, pregnancy, weight loss status, and in patients with deranged hydration (e.g. chronic renal failure, cirrhosis). The 2C model is therefore not ideal for assessing fat-free mass under these conditions and circumstances.
3- and 4-component models
Models that assess 3 or 4 components expand upon 2-component models by measuring fat-free mass constituents with greater certainty. The 3-component (3C) model divides body mass into fat, water, and fat-free dry mass (proteins and minerals). This model avoids the assumption that water content of fat-free mass is constant between individuals, however the ratio between the proteins and minerals of fat-free dry mass is assumed to be constant. This model requires the following data:
The 4-component (4C) model further divides fat-free dry mass into protein and bone mineral content (BMC). This model requires the same information applied in the 3C approach, with the addition of the measurement of bone mineral content by dual-energy X-ray absorptiometry) Estimating bone mineral content and protein mass avoids the assumption that the protein-to-mineral ratio in fat-free mass is constant; the 4C model still assumes that the ratio between bone mineral and non-osseous mineral content is constant. However, this model is robust to major differences in this ratio.
Table 1 Summary of differences between 2-, 3-, and 4-component models.
|Model||Components||Measurements needed||Assumptions relating to composition|
1. Fat mass
2. Fat-free mass
Bioelectrical impedance analysis
Whole body counting of total body potassium
Constant density of fat-free mass
Constant water content of fat-free mass
Constant bone mineral to muscle ratio in fat-free mass
1. Fat mass
3. Fat-free dry mass
|Constant protein-to-mineral ratio of fat-free dry mass|
1. Fat mass
4. Bone mineral content
Dual-energy X-ray absorptiometry (DEXA)
|Constant bone mineral content to non-osseous mineral content ratio|
*Densitometry methods include: hydrostatic underwater weighing and air displacement plethysmography.
5- and 6-component models
Other models have been developed, which assess 5-6 components. The five component model (5C) divides total body mass into water, fat mass, protein mass, bone mineral mass and non-osseous mineral mass (notably soft tissue minerals). While, the six component model developed by Wang et al. (2015), includes estimates for residual mass components soft tissue mineral and glycogen.
However, these models are used less frequently than the 4C model, which is considered the reference method for the in-vivo assessment of overall body composition (but not for fat distribution). It is robust to inter-individual variability in the composition of FFM as more measurements are performed on this compartment, thus the inference requires fewer assumptions.
Several measurements are required to construct 3C and 4C models, as shown in Table 1. Information about these methods is available on separate pages.
Body weight and body volume are measured using densitometry (e.g. hydrostatic underwater weighing or air displacement plethysmography) and total body water is measured using hydrometry (isotope dilution) or bioelectric impedance analysis if following the 3C model.
For the 4C model, the same data applied in the 3C approach are used, with the addition of the measurement of bone mineral content (BMC) using dual-energy X-ray absorptiometry (DEXA).
Taking into account the various assumptions underlying the densities and constant ratios (protein-to-mineral ratio in the 3C model; and the bone mineral content to non-osseous mineral ratio in the 4C model), fat mass can be estimated from the combined measurements of:
The above measures are combined using the formulae in Table 2. There are different equations available for the same input variables but their output results for fat mass are very similar as they are all based on similar assumptions. They share assumed constant densities for fat 0.9007 g/cm3, water (0.99371 g/cm3 and for bone mineral (2.982 g/cm3), but two different approaches are taken in developing the equations:
Table 2 shows a selection of multi-component models to estimate overall body fat. In these models, four quantities are measured: body volume, total body water, bone mineral and body mass.
Table 2 Selection of multi-component models to estimate overall body fat mass.
|1 Siri (1961)||FM = 2.057*BV-0.786*TBW-1.286*BM|
|2 Lohman (1986)||FM = 6.386*BV+3.961*M-6.09*BM|
|3 Silva (2004)||FM = 2.122*BV-0.779*TBW-1.356*BM|
|4- to 6-component models||
|4 Selinger (1977)||FM = 2.747*BV-0.714*TBW+1.129*Mo-2.037*BM|
|5 Lohman (1992)||FM = 2.747*BV-0.714*TBW+1.146*Mo-2.053*BM|
|6 Heymsfield et al. (1990)||FM = 2.748*BV-0.6744*TBW+1.4746*TBBA-2.051*BM|
7 Baumgartner et al. (1991)
||FM = 2.747*BV-0.7175*TBW+1.148*Mo-2.058BM|
|8 Fuller et al. (1992)||FM = 2.747*BV-0.710*TBW+1.460*TBBA-2.05*BM|
|9 Withers et al. (1992)||FM = 2.513*BV-0.739*TBW+0.947*Mo-1.790*BM|
|10 Friedl et al. (1992)||FM = 2.559*BV-0.734*TBW+0.983*Mo-1.841*BM|
|11 Siconolfi et al. (1995)||FM = 2.7474*BV-0.7145*TBW+1.1457*Mo-2.0503*BM|
|12 Heymsfield et al. (1996)||FM = 2.513*BV-0.739*TBW+0.947*Mo-1.79*BM|
|13 Forslund et al. (1996)||FM = 2.559*BV-0.734*TBW+0.983*Mo-1.841*BM|
|14 Wang et al. (2002)a||FM = 2.748*BV -0.699*TBW+1.129*Mo-2.051*BM|
|15 Wang et al. (2014)b||FM = 2.720*BV -0.715*TBW+1.108*Mo-2.020*BM|
Adapted from Wang (2005) and Heymsfield et al. (2015).
BM = Body mass (kg); BV = body volume (L); FM = fat mass (kg); M= total mineral mass (kg); Mo = bone mineral mass (kg); TBBA = total body bone ash (kg); TBW = total body water (L).
Total mineral mass (M) includes bone mineral mass (Mo) and non-osseous mineral mass.
Bone mineral mass (Mo) includes total body bone ash (TBBA) and non-osseous mineral mass.
Some equations in Table 2 require that the bone mineral content from DEXA is converted to bone mineral mass (Mo) or total body mineral mass (Mo + non-osseous) in Table 2.
Body mineral content or total body bone ash (TBBA) is typically converted to bone mineral mass (Mo) by multiplying TBBA*1.0436. This is to reflect the ashing process. Most DEXA systems have adjusted for this process (see Heymsfield 2015).
Different conversion factors also exist for the derivation of total body water mass from labelled water dilution volumes. Each equation takes a different strategy to derive soft non-osseous mineral mass. Non-osseous minerals, glycogen and other residual mass components are taken into account. Refer to each equation for the various strategies/assumptions and conversation factors (see reference list).
An overview of multi-component models is outlined in Table 3.
Table 3 Characteristics of multi-component models.
|Number of participants||Small|
|Participant burden||High as several techniques are required|
|Researcher burden of data collection||High as several techniques are required|
|Researcher burden of coding and data analysis||High|
|Risk of reactivity bias||No|
|Risk of recall bias||No|
|Risk of social desirability bias||No|
|Risk of observer bias||No|
|Suitability for field use||Low|
|Participant literacy required||No|
Considerations relating to the use multi-component models in specific populations are described in Table 4.
Table 3 Use of multi-component models in different populations.
|Pregnancy||3C models are typically used as DEXA (required for 4C) is not feasible (ionizing radiation )*.|
|Infancy and lactation||Suitable.|
|Toddlers and young children||Suitable (3C approach might be used more often as the use of DEXA in this population can be challenging).|
*Forsum et al. (2014).
Refer to section: practical considerations for objective anthropometry