## 1 Introduction  
The importance of body fat in multiple areas such as health, due to its association with various pathologies and their comorbidities, or sports, due to its relationship with the optimization of physical performance, has led the scientific community to look for different ways to quantify it [1; 2; 3]. However, in the classical approach to fat mass estimation, one of the main problems in estimating body composition, and more specifically its adipose component, has been the confusion in using the terms fat, lipids, and adiposity as synonyms, when they are not [4; 5]. In this respect, body composition, regardless of the method used, can be approached based on five levels of increasing complexity [6; 7; 8]. Model 1, at the atomic level, considers body mass as the sum of the amount of hydrogen; carbon; oxygen; nitrogen, calcium, phosphorus, and other atoms. Model 2, at the molecular level, considers body mass as the sum of lipid mass and lipid-free mass, including water, proteins, carbohydrates, and minerals. Model 3, at the cellular level, considers body mass as the sum of fat mass, intracellular water, intracellular solids, extracellular water, and extracellular solids. Model 4, at the tissue level, considers body mass as the sum of adipose tissue, skeletal muscular mass, bone mass, and lean soft tissue, which includes connective tissue,and residual mass. Finally, Model 5 is based on a whole-body level of complexity, in which body mass is the sum of different body segments, such as the head, trunk, and limbs [7,8]. In this respect, it is important to differentiate that the adipose mass considers the totality of the adipocyte's components, 90% of which is fat and the remaining 10% water, minerals, proteins, etc. Of this fat component, 16% corresponds to glycerol and the remaining 83% corresponds to the lipid component inside the fat cell [7,8]. However, these three concepts have classically been used as homonyms in the estimation of body composition, inducing errors around 8-10% in the approach to the adipose component [9]. Considering the impossibility of measuring body composition directly, for which in vivo dissection would be necessary [10], previous studies have described a large number of methods to determine the adipose component of a subject, among which dual X-ray absorptiometry (DXA), bioimpedance (BIA) and anthropometry stand out as the most widely used [6]. DXA is based on absorptiometry through which the attenuation of emitted photons is detected [11]. This method estimates adipose mass using a tissue model approach (model 4) [6,7]. The most important advantages of this method are its ease of application, safety, and non-invasive nature [10]. However, it also has important disadvantages, such as the variability between devices, the difficulty in evaluating subjects taller than 190 cm, and its low accessibility [12]. On the other hand, BIA is a method based on the electrical conductivity properties of the different tissues of the human body [13]. This method performs lipid mass estimation using a molecular model approach (model 2) [7]. It is a fast, easy-to-apply, and non-invasive method, but it has limitations that affect its reliability and validity, calling into question not only the final lipid mass values given, but also the impedance value obtained from which the estimates are made [14]. More specifically, any context where total body water is affected will have a direct impact on impedance and therefore on the estimated lipid component [6,7,15] As a consequence of the above, although it is a relatively inexpensive method, it is only a valid method for assessing populations, but not individuals in particular [14], and its use in clinical practice is also limited because it is not reliable when evaluating the evolution of patients or athletes [16].