## 1 Introduction  
Over the past decades, obesity has become a significant contributor to the deterioration of the health status of the global population, and this is affecting both developed and developing countries. With industrialization and urbanization, physical activity tends to decrease, which leads to a decrease in muscle mass (risk of sarcopenia) and a certain increase in overall and central obesity, and subsequently to an increase in the prevalence of cardiometabolic and other non-communicable diseases [1, 2]. Obesity is characterized by excessive accumulation of body fat with possible loss of muscle mass (sarcopenia obesity), which poses significant health risks for the individual and society [3]. Obesity is the result of a multifactorial interaction of genetic, metabolic, behavioral and environmental factors [4]. The consequences of obesity are associated with serious health complications, such as impaired glucose tolerance, increased blood pressure, impaired lipid and lipoprotein metabolism, vascular diseases, reproductive disorders, psychological problems and many others [5]. Research clearly confirms that the obese population has a higher mortality rate from all causes than the population with an optimal body weight [6]. Obesity diagnosis in clinical practice is carried out using simple anthropometric measurements using only waist tape measures, height measures and body scales. The data obtained are key for calculating the most commonly used indicators for the assessment of both total and central obesity, such as body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) [7]. However, it has been found that both BMI and WC have significant limitations. Several studies have pointed out the limitations of BMI as a reliable indicator of obesity, as it cannot distinguish between fat and muscle mass. Its accuracy is also affected by differences in body adiposity at the same BMI value depending on age, gender and ethnicity [5, 8]. Doubts about the reliability of BMI as a tool for classifying overweight and obesity are also confirmed by the results of a meta-analysis by [PERSON] et al. [9], which show that almost half of individuals with excessive body fat are incorrectly classified as normal weight. WC reflects central obesity, but it also does not take into account muscle mass, which distorts the assessment of health risks [10]. [PERSON] et al. [11] emphasize the need for clear standards for the obesity diagnosis, as their absence leads to false negative and false positive diagnostic conclusions. If we diagnose metabolic disease, we must, according to the authors, purposefully choose adequate indicators. In response to these facts and limitations, [PERSON] et al. [8] introduced the weight-adjusted waist index (WWI) as a new anthropometric measure. The WWI is defined as the waist circumference divided by the square root of body weight, providing a more nuanced understanding of body composition by integrating both fat and muscle mass [10]. The main purpose of the WWI is to improve the assessment of health risks associated with obesity, especially in populations in which traditional measures may be inadequate [12, 13]. The popularity of the WWI is growing, due to its proven diagnostic and prognostic value. A recent study suggested that the WWI is positively correlated with several chronic diseases, be it diabetes, cardiovascular disease or some types of cancer [5]. Several clinical studies have verified the WWI's significant relation to liver diseases, kidney function, orthopaedic disorders, respiratory diseases, etc. [14, 15, 16, 17]. [PERSON] et al. [18] showed that the new anthropometric parameter WWI is significantly associated with increased mortality from all causes and is closely related to depressive symptoms. [PERSON] et al. [19] found that each unit increase in the WWI is associated with an 18% increase in the occurrence of depressive symptoms.