Analysis of the correlation between anthropometric indices and levels of selected hormones in relation to problematic Internet use

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Methods The study was conducted in 2020-2021 on a group of 427 men aged 18-30 (24.82 ± 3.83) who declared that they used the Internet and played computer games and/or online games, including gambling. Participation in the study was voluntary and anonymous. Anthropometric indices, HOMA-IR as well as biochemical and hormonal parameters were calculated. Results Lipid Accumulation Product (LAP) and Visceral Adiposity Index (VAI) positively correlate with both the moderate (LAP r=0.41; p=0.000), (VAI r=0.043; p=0.000) and high degree (LAP r=0.40; p=0.004), (VAI r=0.37; p=0.004) in the IUT. In multivariate logistic regression, a correlation between testosterone (TT) in the anthropometric indices— LAP, VAI and Body Adiposity Index (BAI)—and the moderate and high degrees in the IUT questionnaire is found. Conclusions Our study highlights the usefulness of anthropometric indices in assessing hormone distribution and glucose metabolism. VAI can be used as a marker for estimating the risk of metabolic disorders. Serotonin, together with LAP and VAI, increases with the degree of Internet use in the IUT questionnaire, which predisposes to cardiovascular problems. Internet addiction is an important independent risk factor for clinicians to use in assessment along with physical activity and psychosocial problems, but they also indicate the risk of fertility problems in increasingly younger men due to hormonal disorders. Biological sciences/Biochemistry Biological sciences/Psychology Health sciences/Health care Health sciences/Risk factors Health sciences/Signs and symptoms Internet use test serotonin dopamine biochemical parameters behavioral addiction young men Introduction The Internet has become an integral part of our lives. It helps us in our daily lives and our careers. Undeniably, its use is highly beneficial, but it can have negative effects as well. Recently, the number of disorders related to inappropriate use of the Internet, or addiction to it, has increased. As a result, the topic of addiction and the search for causal relationships have become increasingly popular in the literature [1]. Internet use disorder is characterized by, among other things, a loss of control over Internet use. This may be related to social and health problems, as well as anthropometric [2, 3, 4] and hormonal parameters [5]. It seems important to look for factors that influence anthropometric parameters or the concentration of hormones that regulate processes in the body and influence our health or prevent the occurrence of diseases of affluence. Among the anthropometric parameters used to evaluate body fat, the body mass index (BMI) [6] and indices that take into account anthropometric indices—such as LAP (lipid accumulation product) [7], VAI (visceral adiposity index) [8, 9], and BAI (body adiposity index) [10, 11]—are the most common. For the body mass index (BMI) factors that affect the mass of visceral adipose tissue and its function are not taken into account. Therefore, it is not an objective index to evaluate adipose tissue function [6]. Consequently, other indices are used, such as VAI, which is used as a marker for visceral adipose tissue dysfunction [9].The visceral adiposity index (VAI) is associated with both tissue insulin sensitivity and visceral adipose tissue [8]. Another valuable index is the lipid accumulation product (LAP) which describes excessive lipid accumulation associated with central obesity and the metabolic risk [12-15]. It also helps identify the risk of cardiovascular disease and diabetes [7, 16]. Another is the body adiposity index (BAI) which was developed to directly evaluate the body fat percentage (%) [17]. The formation of behavioral addiction is explained, for example, using a neurobiological model based on the dopamine system, which regulates, among other things, cognitive functions, the experience of pleasure, concentration, attention, or memory [18]. Reduced levels of serotonin, also known as the "happiness hormone," can lead to problems with behavioral control and increased risk of developing behavioral addictions [19]. Dopamine, often associated with reward and motivation, is released in response to rewarding stimuli, reinforcing these behaviors [20]. Studies have demonstrated that individuals with behavioral addictions exhibit altered dopamine signaling, including increased dopamine release or heightened sensitivity to dopamine. Conversely, serotonin, involved in mood regulation and impulse control, has been found to be dysregulated in individuals with these conditions. Lower levels of serotonin or reduced serotonin receptor sensitivity may contribute to impulsivity and difficulty in resisting cravings associated with behavioral addictions [21]. The interplay between dopamine and serotonin is complex and likely contributes to the development and maintenance of behavioral addictions. For instance, reduced serotonin levels may potentiate the reinforcing effects of dopamine, leading to increased reward-seeking behavior [22]. Additionally, dysregulation of dopamine and serotonin systems may interact with other neurotransmitter systems, such as the opioid and glutamate systems, further contributing to the addictive process. Understanding the neural mechanisms underlying behavioral addictions is essential for developing effective prevention and treatment strategies. Future research should focus on identifying specific neural targets for therapeutic interventions, such as medications that modulate dopamine and serotonin signaling [5, 23]. The aim of the study was to assess the relationship between anthropometric indices (BMI, VAI, LAP, and BAI) and the concentration of hormonal parameters in relation to problematic Internet use or even addiction. Materials and methods Study Sample The study was conducted in 2020-2021 (province of West Pomerania) in Poland, on a group of 427 men aged 18-30 (24.82 ± 3.83) who declared that they used the Internet and played computer games and/or online games and gambling. The inclusion criteria for the study were male gender, age between 18 and 30 years of age, declared Internet use, completed questionnaire and provided written informed consent to participate in the study. The exclusion criteria included the presence of oncological or endocrine diseases and being under the care of a psychiatrist or psychologist. Recruitment for the study was done by means of social networking, online forums, advertising and leafleting. Participation in the study was voluntary and anonymous. Questionnaires The study was conducted in accordance with the standards of the Declaration of Helsinki and was approved by the Bioethics Committee of the Pomeranian Medical University (KB-0012/90/18). The project was conducted at the request of the National Bureau for Drug Prevention (currently the National Centre for the Prevention of Addictions). The study was conducted using our original questionnaire concerning the amount of time spent on computer games during the weekdays and days off work, as well as the manner, purpose, and degree of Internet use. The Internet Use Test, developed by Ryszard Poprawa from the Institute of Psychology at the University of Wrocław, which shows psychological, social, and health problems caused by Internet use was used. The total score is the sum of 23 ratings on a scale from 0 (‘never’) to 5 (‘always’). The minimum raw score is 0 points and the maximum score is 115 points. The higher the score, the stronger the problematic Internet use; 50 points and above reflect strong compulsive Internet use (Poprawa 2011) [24]. The study analyzed the results obtained from the questionnaires and the degree of risky behaviors with regard to Internet use. In the study group 13 individuals had asthma. Some suffered from type 1 diabetes, hypothyroidism, migraines, allergies, atopic dermatitis, hearing loss, and other conditions, but they were not criteria for exclusion from the study. The course of the study was not affected by these conditions. Statistical Analysis Statistical analysis was performed using Statistica software version 13 (StatSoft, Krakow, Poland). Continuous variables were characterized by arithmetic means (X), standard deviation (SD), and data range. The distribution of the data was tested using the Shapiro–Wilk test. The Kruskal–Wallis test was used to evaluate the differences between the groups. A post hoc analysis was used to compare multiple groups. Spearman’s rho correlation analysis and multivariate linear regressions were also performed. To perform logistic regression analysis, the patients were divided into two groups—a group of individuals with no symptoms of Internet addiction and a group of moderately and highly addicted Internet users. Age-adjusted logistic regression analysis was performed. Results are presented using an adjusted odds ratio (OR), beta regression coefficient (β), and statistical significance (p). Independent variables were the results from other questionnaires. The significance level was set at p≤0.05. Test material collection For testing, a qualified nurse collected blood into a 9 ml tube. Blood was drawn between 7 and 10 a.m., from fasted individuals, in the premises of the Pomeranian Medical University in Szczecin, in places designated and prepared for blood collection. Then it was centrifuged and serum was stored in a freezer in the laboratory of the Faculty of Health Sciences of the Pomeranian Medical University in Szczecin. Parameters such as abdominal circumference, weight and height were also measured. Abdominal circumference was measured using a tape measure at the level of the umbilicus, while weight and height were self-reported. Determination of biochemical and hormonal parameters In order to calculate anthropometric indices and HOMA-IR in blood serum of the patients, the following parameters were determined using the standard method in the diagnostic laboratory: high-density lipoprotein (HDL), triglycerides (TG) and the concentration of fasting plasma glucose (FPG). Serum concentrations of the luteinizing hormone (LH), follicle stimulating hormone (FSH), testosterone (TT), sex hormone binding globulin (SHBG), dehydroepiandrosterone sulphate (DHEAs), estradiol (E2), prolactin (PRL) and insulin (I) were determined using the Enzyme-Linked Immunosorbent Assay (ELISA). The serum concentration of serotonin (5-HT) and dopamine (DA) was determined in the Research Laboratory of the Pomeranian Medical University in Szczecin. HOMA-IR was calculated. It is a parameter that allows to evaluate the insulin resistance of the body tissue. It is calculated in the case of abdominal obesity, problems with weight loss, drowsiness or elevated glucose concentration. The formula HOMA-IR = insulin concentration (mu/ml) x glucose level (mmol/l) / 22.5 was used to calculate HOMA-IR. A value below 2.5 is the norm. A score above 2.5 indicates suspected insulin resistance [25]. Anthropometric indices—BMI (body mass index), VAI (visceral adiposity index), LAP (lipid accumulation product), and BAI (body adiposity index)—were calculated for the purpose of data analysis. In order to calculate BMI, the formula BMI = body weight (kg) by the height squared (m 2 ) was used. According to the World Health Organization (WHO), obesity is diagnosed in adults whose BMI is ≥ 30 kg/m 2 . The visceral adiposity index (VAI) was calculated to assess visceral fat accumulation and cardiometabolic risk using the formula: VAI = waist circumference (cm) / (39.68 + (1.88 × BMI)) × ((TG/1.03) × (1.31/HDL)) [8]. The proper value of VAI was assumed to be VAI = 1 [26]. The lipid accumulation product (LAP) is a marker for visceral adipose tissue and metabolic syndrome [12]. It is also a predictor of the risk of diabetes and cardiovascular disease. For the male population, the formula: LAP = ((waist circumference (cm) - 65) × TG (mmol)) is used to calculate LAP [7, 27]. Since the literature does not provide consistent information on the cut-off point, LAP was divided into quartiles. Therefore, a Q3 quartile of 63.36 was used. The body adiposity index (BAI) cut-offs to identify obese women and men were proposed according to the relationship between FM% and BMI, recognized by Bergman et al. (2011) for the Caucasian population: > 39 for women and > 25 for men aged 20–39. BAI = (hip circumference (cm) / [height (m)1.5 - 18]) [10]. Determination of Serotonin and Dopamine Serum Levels Serum serotonin and dopamine levels were quantified using commercially available double-antibody sandwich Enzyme-Linked Immunosorbent Assay (ELISA) kits. These assays utilized pre-coated microplates with specific antibodies for serotonin and dopamine, ensuring high specificity. Whole blood samples were collected and allowed to clot at room temperature to facilitate serum separation. Serum was obtained by centrifugation at 3000 rpm for 10 minutes, carefully aspirated to avoid contamination with cellular components, and stored at 2-8°C for short-term use, or at -20°C/-80°C for long-term storage, maintaining analyte stability. Samples were thawed and mixed thoroughly before use, avoiding repeated freeze-thaw cycles. Prior to the assay, all reagents were equilibrated to room temperature. Standards, controls, and serum samples were added in duplicate to the pre-coated wells, following the manufacturer’s instructions. For serotonin, 50 µL of standards and samples were added, while for dopamine, a specific dilution was performed. Subsequently, 50 µL of HRP-conjugated antibodies were added, and the microplate was incubated at 37°C for 60 minutes. Following incubation, wells were washed five times with 300 µL of diluted wash buffer. Chromogen solutions A and B were added, and the plate was incubated for 15 minutes at 37°C, protected from light. The reaction was stopped with Stop Solution, and absorbance was measured at 450 nm using an ELISA plate reader. A standard curve was generated using a 4PL curve fit, and sample concentrations were determined by interpolation. Quality control included duplicate measurements and user-generated standard curves, adhering to manufacturer’s protocols. The standard curve, generated by plotting the average of optical density (OD) (450 nm) for each standard concentration, was used to determine the contents in unknown samples. Results The study compared anthropometric indices, serum concentrations of biochemical and hormonal parameters, and the tissue insulin resistance index with the results of the questionnaire concerning the degree of Internet use. Internet use is measured in low, moderate, and high degrees as per the IUT questionnaire. There was no correlation between the concentration of biochemical and hormonal parameters and the tissue insulin resistance index in relation to the degree of Internet use (Table 1). Values close to statistical significance were found for LH (p=0.051) and 5-HT (p=0.093) and FPG (p=0.083). Analysis of the values of hormonal parameters in serum and anthropometric indices, for which the degree of Internet use was taken into account, demonstrated that TT is negatively correlated with LAP, VAI and BAI for each degree in the IUT and it correlates with BMI for the moderate and high degrees in the IUT. SHBG is negatively correlated with BMI and VAI for each degree in the IUT. For the low and moderate degrees in the IUT it correlates with LAP, and for the moderate degree it correlates with BAI. Insulin positively correlates with VAI for each degree in the IUT. It is moderately and highly correlated with BMI and LAP, and moderately correlated with BAI. E2 has a moderate negative correlation with LAP and VAI. PRL negatively correlates with BAI for the moderate degree in the IUT. 5-HT, on the other hand, is positively correlated with LAP and VAI for the high degree in the IUT and for the low degree in the IUT it correlates with BAI. Prolactin is moderately negatively correlated with BAI for the moderate degree in IUT (Table 2). The correlation between the value of the tissue insulin resistance index and anthropometric indices and the degree of Internet use was analyzed. BMI (r=0.21; p=0.001) and BAI (r=0.25; p=0.000) were found to be positively correlated with the moderate degree in the IUT questionnaire. LAP and VAI positively correlate with both the moderate (LAP r=0.41; p=0.000), (VAI r=0.43; p=0.000) and high degree (LAP r=0.40; p=0.004) (VAI r=0.37; p=0.004) in the IUT (Table 3). In multivariate logistic regression, a correlation between TT in the anthropometric indices — LAP (p=0.000*, OR=0.581), VAI (p=0.028*, OR=0.479) and BAI (p=0.000*, OR=0.624) — and the moderate and high degrees in the IUT questionnaire is found. A correlation was found between the SHBG concentration in the LAP index and the low (p=0.004*, OR=0.893), moderate and high (p=0.000*, OR=0.941) degrees in the IUT questionnaire, as well as for BAI and the moderate and high degrees (p=0.000*, OR=0.925) in the IUT. A correlation was found between the concentration of DHEAs (p=0.037*, OR=1.003) and 5-HT (p=0.023*, OR=0.996) for the LAP index and the moderate and high degrees in the IUT. A correlation was found between the concentration and the moderate and high degrees in the IUT E2 (p=0.038*, OR=1.114) and between the PRL (p=0.041*, OR=1.005) concentration and the low degree in the IUT for VAI (Table 4). Discussion In our study on Internet addiction and hormonal parameters, tissue insulin resistance index and anthropometric indices in 427 young men were examined. A review of the available literature reveals that not too many studies on similar topics have been performed to date. Most reports on similar topics focus on addiction to the Internet or a smartphone and its correlation with BMI. Tayhan et al. (2021) found that among students of both sexes aged 19-29, those with a potential Internet addiction had a higher BMI and higher risk of developing eating disorders compared to those without addiction (23.7 ± 5.1 kg/m 2 and 22.2 ± 2.9 kg/m 2 ) [28]. In addition, when examining smartphone use, they reported that the results of the Internet addiction test were positively correlated with the results of the BMI and smartphone addiction ( p <0.05) [28]. Alpaslan et al. (2015) also found that people with a potential Internet addiction have a much higher BMI than people without a potential Internet addiction, and a high BMI is a potential risk factor for Internet addiction [29]. Eliacik et al. (2016) and Tabatabaee HR et al. (2018) also confirmed a correlation between internet addiction and BMI [30,31]. Furthermore, Tabatabaee HR et al. (2018) proved the impact of this addiction on sleep quality, physical activity, and eating habits [31]. People who use the Internet on a regular basis may not be aware of how much food they consume. They may procrastinate, postpone going to bed, or skip meals, as well as consume unhealthy processed and convenience foods—often because they are more convenient and quicker to prepare or do not require cooking. Such activities can become automated and unconscious, causing appetite problems and future health problems. As a result, this can lead to undesirable weight gain as well as psychological and social problems. [4, 28]. Addiction to the Internet and the intensification of this disorder over time were found in 2013 by researchers from Turkey [32]. They published a study of a group of 1938 students between the ages of 14 and 18 years. 10.5% of the study group were "problem Internet users" or "Internet addicts". The authors showed a significant positive correlation between BMI and the Internet Addiction Test (IAT) according to Young (r=0.307; p<0.01) and weekly Internet use (r=0.215; p<0.01). Linear regression analysis showed a significant independent correlation between the IAT and BMI (r=0.235; p<0.001). Surfing the Internet, watching online videos, chatting and messaging, as well as playing online games were significantly correlated with an increased value of BMI (p<0.05) [32]. In our study, we investigated no such correlations but focused on examining health effects with regard to hormonal parameters in relation to degrees of addiction specified in the IUT. In addition, a meta-analysis by Mohadeseh Aghasi (2020) shows that Internet use is associated with a sedentary lifestyle and, therefore, it is a potential risk factor for excess weight or obesity [33]. Jabłonowska-Lietz B et al. (2017) conducted a study on a small group of women and men at an average age of 39.0 ± 5.9 years with an average BMI of 32.6 ± 2.4 kg/m 2 . They found that HOMA-IR was positively correlated with both VAI and BMI [26]. However, in our study, HOMA-IR correlated with BMI, VAI, as well as LAP and BAI for the moderate degree in the IUT, and with VAI and LAP for the high degree in the IUT, which may be related to the size of the study group for each degree in the IUT. Amato et al. (2010) reported a negative correlation between VAI and insulin sensitivity as evaluated using the hyperinsulinemic-euglycemic buckle method in healthy weight individuals [8], which we did not find in our study. Köprülü Ö. et al. (2022) investigated the results of the HOMA-IR index in children with Attention Deficit Hyperactivity Disorder in relation to screen addiction. However, the authors found no association between addiction and HOMA-IR [34]. Kim H. et al. (2019) analyzed differences in glucose metabolism and metabolic connectivity in young men. Compared to a group of healthy men, those who suffered from IGD (internet gaming disorder) were found to have hypometabolism in the anterior cingulate cortex, frontal cortex, temporal cortex and parietal cortex as well as in the striatum. It can be stated that hypometabolism and altered metabolic connectivity in IGD may be associated with abnormal sensory function as a result of prolonged gaming and dysfunction of impulsive/motivational states [35], which is related to the motivation and reward system. Other findings report that men with online gaming disorder, and, indirectly, Internet use disorder, are found to have altered grey matter density and functional amygdala connectivity during resting state fMRI [36]. Canan F et al. (2017) states that this indicates neural mechanisms of the correlation between prenatal testosterone levels and behaviors that may be addictive, particularly Internet addiction among young men [37]. Our study may be the first to analyze hormonal parameters and anthropometric indices in relation to Internet use. In addition, the results of our study support some of the previous reports indicating that Internet addiction increases the risk of developing eating disorders. Smartphone addiction is associated with both eating disorders and increased anthropometric parameters, and, therefore, the fact that this addiction is a health hazard should be taken into consideration and appropriate public health interventions should be implemented. Limitation and Future Directions The current study has a number of limitations. In the study, we could not establish a causal relationship between variables, only correlations. In addition, this study does not represent the entire population, as it was conducted only on a volunteer group of young adult men from a specific region. Consequently, individual differences in physical activity or diet that may affect the parameters should be taken into account. Additionally, the most correlated values are for the moderate degree of Internet use, which may have resulted from a large number of subjects participating in the study group. It should be considered a limitation that parameters such as weight and height were self-reported by respondents, which could distort the actual parameters due to the tendency to overestimate or underestimate one's own weight or height. The examination and collection of biological material was done outside the activity, i.e. Internet use, so we were unable to observe hormonal discharges during potentially addictive activities. Research on a larger population is needed to explore the potential of Internet addiction. While this study provides valuable insights, it is not without limitations. Primarily, its cross-sectional design precludes the establishment of causal relationships. Future research should therefore prioritize longitudinal approaches to better elucidate the dynamics of these changes. Our findings underscore the necessity for public health interventions that address both the psychological and physiological aspects of Internet addiction. We recommend the implementation of preventive programs, the education of clinicians, and the promotion of healthy lifestyle behaviors. In the future, it is imperative to conduct interventional studies to evaluate the efficacy of various therapeutic modalities, as well as investigations into the biological mechanisms underlying the association between Internet addiction and hormonal and metabolic alterations. Conclusion The study is one of very few reports on the topic of anthropometric indices, selected hormonal parameters, and problematic Internet use. Our analysis shows that the Internet is often used in a state of long-term immobility leading to excess weight and obesity, which is visible in the results of anthropometric indices and hormonal parameters. Additionally, one may indicate that the anthropometric index, BAI, may be useful in predicting disorders of glucose metabolism. Our study highlights the usefulness of anthropometric indices in assessing hormone distribution and glucose metabolism. VAI can be used as a marker for estimating the risk of metabolic disorders. However, further studies are needed to identify cut-off values for anthropometric indices associated with impaired glucose metabolism and increased metabolic risk. In our study, we found that serotonin, together with LAP and VAI, increases with the degree of Internet use in the IUT questionnaire, which predisposes to cardiovascular problems. In addition, the lower concentration of the SHBG hormone as a protein carrier, the lower the distribution of hormones in the body. It is worth noting that statistical significance was found to be higher in the group of subjects with a moderate degree in the IUT, and at a slightly lower but comparable level in the group with a high degree in the IUT, despite the fact that the groups were different in size. Our findings, and those of many other authors, indicate that Internet addiction is an important independent risk factor for clinicians to use in assessment along with physical activity and psychosocial problems, but they also indicate the risk of fertility problems in increasingly younger men due to hormonal disorders. Research studies in this area provide a basis for addressing the problem of Internet use. This can reduce the incidence of obesity and its effects at a young age as well as many health and psychological problems later in life. Declarations Declarations of competing interest: NONE TO DECLARE Primary funding: The project was conducted at the request of the National Bureau for Drug Prevention (currently the National Centre for the Prevention of Addictions) Data availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Zajac, K., Ginley, M. K., Chang, R., Petry N. M. 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J Res Health Sci. 18 , e00423 (2018). Canan, F., et al. 467 – The Relationship between Internet Addiction and Body Mass Index in Turkish Adolescents. European Psychiatry. 28 , 1 (2013). Aghasi, M., Matinfar, A., Golzarand, M., Salari-Moghaddam, A., Ebrahimpour-Koujan, S. Internet Use in Relation to Overweight and Obesity: A Systematic Review and Meta-Analysis of Cross-Sectional Studies. Adv Nutr . 11 , 349-356 (2020). Köprülü, Ö., et. al. The Effect of Screen Addiction and Attention-Deficit Hyperactivity Disorder on Insulin Resistance in Children. J Dr Behcet Uz Child Hosp . 12 , 20-26 (2022). Kim, H., Kim, Y. K., Lee, J. Y., Choi, A. R., Kim, D. J., Choi, J. S. Hypometabolism and altered metabolic connectivity in patients with internet gaming disorder and alcohol use disorder. Prog Neuropsychopharmacol Biol Psychiatry. 95 , 109680 (2019). Ko, C. H., et al. Altered gray matter density and disrupted functional connectivity of the amygdala in adults with Internet gaming disorder . Prog Neuropsychopharmacol Biol Psychiatry . 57 , 185-192 (2015). Canan, F., et al. The relationship between second-to-fourth digit (2D:4D) ratios and problematic and pathological Internet use among Turkish university students. J Behav Addict. 6 , 30-41 (2017). Tables Table 1. Descriptive statistics of the study group, n=427 Low degree in IUT questionnaire n=80 Moderate degree in IUT questionnaire n=276 High degree in IUT questionnaire n=71 Parameter X Me Q1 Q3 X Me Q1 Q3 X Me Q1 Q3 p value Anthropometric indices BMI 25.32 24.69 22.84 26.57 25.11 24.22 22.51 26.71 25.58 24.30 22.66 27.78 0.776 LAP 50.80 36.71 21.40 71.05 49.85 35.73 22.00 58.84 51.79 37.99 21.58 75.54 0.922 VAI 4.23 3.58 2.94 4.76 3.91 3.47 2.74 4.44 3.96 3.38 2.71 4.98 0.525 BAI 21.70 21.96 19.06 24.04 22.71 22.67 20.19 25.07 22.69 22.58 18.85 25.32 0.224 Biochemical parameters HDL 52.25 51.55 43.15 60.20 51.98 51.60 43.90 58.65 53.11 52.30 43.70 63.20 0.946 TG 137.74 113.50 80.00 172.00 132.65 110.00 77.00 164.00 133.22 117.00 80.00 176.00 0.926 FPG 90.07 85.00 77.00 93.50 83.87 82.50 75.00 90.00 92.43 85.00 78.00 94.00 0.083 Hormonal parameters LH 9.70 5.62 4.45 7.41 6.09 5.35 3.91 7.03 8.25 6.22 4.81 7.35 0.051 FSH 7.74 3.79 2.69 5.50 4.91 3.38 2.38 4.78 6.58 3.65 2.68 4.52 0.444 TT 7.10 4.20 3.25 5.73 5.48 4.99 3.66 6.31 4.93 4.70 3.31 6.22 0.342 SHBG 32.02 28.46 21.65 37.38 32.86 30.96 22.51 39.47 32.37 29.11 21.30 41.92 0.594 DHEAS 377.21 350.10 282.85 411.65 377.96 362.75 282.90 456.40 404.36 387.50 295.60 498.90 0.396 E2 24.14 23.35 18.10 30.05 26.23 25.00 20.10 31.70 26.66 26.00 20.10 32.60 0.242 PRL 246.80 226.00 171.00 318.00 272.45 240.00 187.00 312.00 280.14 242.00 177.00 354.00 0.367 I 21.78 11.90 6.77 22.75 17.74 10.20 6.80 19.50 22.85 12.30 7.52 29.20 0.310 5-HT 195.97 101.03 37.23 160.34 119.13 98.93 60.40 159.42 134.96 91.91 56.15 135.44 0.093 DA 88.65 78.11 50.76 128.12 81.98 70.35 52.33 106.41 85.88 98.26 48.63 115.56 0.283 Tissue insulin resistance index HOMA-IR 3.09 2.17 1.19 3.41 2.97 1.88 1.12 3.49 4.43 2.34 1.20 4.55 0.435 Abbreviations: X, arithmetic mean; Me, median; p, statistically significant value; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; HDL, high-density lipoprotein; TG, triglycerides; FPG, fasting plasma glucose; LH, luteinizing hormone; FSH, follicle stimulating hormone; TT, total testosterone; SHBG, sex hormone binding globulin; DHEAs, dehydroepiandrosterone sulfate; E2, estradiol; PRL, prolactin; I, insulin; 5-HT, serotonin; DA, dopamine; HOMA-IR, Homeostatic Model Assessment–Insulin Resistance, Kruskal–Wallis test Table 2. Analysis of hormonal parameters and anthropometric indices in relation to the level of Internet use Low degree in IUT questionnaire n=80 Moderate degree in IUT questionnaire n=276 High degree in IUT questionnaire n=71 Parameter R p R p R p BMI TT -0.14 0.243 -0.38 0.000* -0.41 0.001* SHBG -0.26 0.023* -0.38 0.000* -0.41 0.001* I 0.16 0.171 0.26 0.000* 0.28 0.025* LAP TT -0.34 0.004* -0.48 0.000* -0.56 0.000* SHBG -0.31 0.008* -0.30 0.000* -0.23 0.107 E2 0.07 0.569 -0.17 0.012* -0.05 0.711 I 0.20 0.090 0.45 0.000* 0.41 0.003* 5-HT 0.13 0.368 -0.01 0.915 0.34 0.041* VAI TT -0.27 0.017* -0.39 0.000* -0.51 0.000* SHBG -0.30 0.008* -0.27 0.000* -0.31 0.012* E2 -0.01 0.918 -0.15 0.014* -0.01 0.925 I 0.24 0.040* 0.46 0.000* 0.35 0.005* 5-HT 0.11 0.408 0.08 0.297 0.36 0.020* BAI TT -0.30 0.011* -0.36 0.000* -0.52 0.000* SHBG -0.07 0.579 -0.41 0.000* -0.24 0.081 PRL -0.22 0.070 -0.16 0.021* -0.03 0.819 I 0.11 0.354 0.28 0.000* 0.24 0.082 5-HT 0.35 0.012* 0.05 0.506 0.05 0.756 Abbreviations: R, correlation coefficient; p, statistically significant value; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; TT, total testosterone; SHBG, sex hormone-binding globulin; I, insulin; E2, estradiol; 5-HT, serotonin; PRL, prolactin; *, statistically significant difference, Spearman’s rho correlation analysis Table 3. Analysis of HOMA-IR results and anthropometric parameters in relation to the degree of Internet use Low degree in IUT questionnaire n=80 Moderate degree in IUT questionnaire n=276 High degree in IUT questionnaire n=71 Parameter R p R p R p HOMA-IR BMI 0.20 0.089 0.21 0.001* 0.15 0.229 LAP 0.09 0.453 0.41 0.000* 0.40 0.004* VAI 0.12 0.340 0.43 0.000* 0.37 0.004* BAI 0.09 0.458 0.25 0.000* 0.17 0.217 Abbreviations: R, correlation coefficient; p, statistically significant value; HOMA-IR, Homeostatic Model Assessment–Insulin Resistance; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; *, statistically significant difference, Spearman’s rho correlation analysis Table 4. Multivariate logistic regression explaining the age-adjusted result of hormonal parameters and anthropometric indices in relation to the degree of Internet use. Low degree in IUT questionnaire Moderate and high degree in IUT questionnaire Parameter p OR Trust OR -95% Trust OR 95% p OR Trust OR -95% Trust OR 95% BMI TT 0.686 0.499 0.017 14.484 0.270 3.647 0.366 36.342 SHBG 0.641 1.091 0.757 1.573 0.462 0.918 0.731 1.153 DHEAs 0.260 1.050 0.964 1.144 0.501 0.983 0.936 1.033 E2 0.376 0.678 0.287 1.604 0.784 0.930 0.554 1.562 PRL 0.744 0.996 0.969 1.023 0.692 0.995 0.974 1.018 5-HT 0.619 1.006 0.982 1.031 0.906 1.001 0.987 1.015 DA 0.252 0.963 0.903 1.027 0.401 1.019 0.976 1.063 LAP TT 0.867 0.997 0.967 1.029 0.000* 0.581 0.467 0.722 SHBG 0.004* 0.893 0.826 0.965 0.000* 0.941 0.913 0.970 DHEAs 0.226 1.004 0.998 1.009 0.037* 1.003 1.000 1,005 E2 0.622 0.985 0.927 1.046 0.230 0.980 0.948 1.013 PRL 0.653 1.001 0.995 1.007 0.954 1.000 0.998 1.002 5-HT 0.358 0.997 0.990 1.004 0.023* 0.996 0.993 0.999 DA 0.318 1.009 0.991 1.028 0.371 0.996 0.987 1.005 VAI TT 0.055 0.709 0.498 1.007 0.028* 0.479 0.249 0.924 SHBG 0.801 1.005 0.966 1.046 0.081 0.912 0.822 1.011 DHEAs 0.997 1.000 0.997 1.003 0.072 0.996 0.991 1.000 E2 0.412 1.025 0.966 1.088 0.038* 1.114 1.006 1.232 PRL 0.041* 1.005 1.000 1.011 0.377 0.998 0.993 1.003 5-HT 0.984 1.000 0.996 1.004 0.307 0.998 0.993 1.002 DA 0.926 0.999 0.988 1.011 0.196 0.990 0.975 1.005 BAI TT 0.051 1.543 0.998 2.386 0.000* 0.624 0.516 0.753 SHBG 0.108 1.051 0.989 1.117 0.000* 0.925 0.897 0.955 DHEAs 0.307 0.998 0.994 1.002 0.281 0.999 0.997 1.001 E2 0.315 0.969 0.912 1.030 0.527 1.010 0.980 1.041 PRL 0.308 1.003 0.997 1.010 0.109 1.002 1.000 1.004 5-HT 0.246 0.998 0.993 1.002 0.583 0.999 0.997 1.002 DA 0.349 0.990 0.969 1.011 0.701 0.998 0.990 1.007 Abbreviations: p, statistically significant value; OR, odds ratio; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; TT, total testosterone; SHBG, sex hormone-binding globulin; DHEAs, dehydroepiandrosterone sulfate; E2, estradiol; PRL, prolactin; 5-HT, serotonin; DA, dopamine; *, statistically significant difference, multivariate logistic regression analysis Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 21 Apr, 2025 Reviews received at journal 15 Apr, 2025 Reviewers agreed at journal 15 Apr, 2025 Reviewers invited by journal 30 Mar, 2025 Submission checks completed at journal 26 Mar, 2025 First submitted to journal 18 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5101951","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":436053239,"identity":"a79e676f-b7da-4617-b490-d2943878d02b","order_by":0,"name":"Natalia Tomska","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYLCCBwYQmrGBwQbC4gFiPpzqmRkYEgwgioBa0hBa2PBqYYBrOUxYizn7+YMfEgrsGOzZu5M/zqg5n2dw7QDjg7dtDHm4tFj2JDNLJBgkM/DwnN0mueHY7WKD2wnMhnPbGIpxaTE4kMwA1MLMwCORu43xAdvtxA23E9ikedsYEttwaTn/mPlHgkE9SMvmjw/+nQNpYf+NV8uNZDagLYdBWjZIbmw7ALaFGb+Wx2YWCQbHeXjOAP0ysy+5WPJ2YrPknHMSuP1yPvHxjQ9/quXY23s3f+z5ZpfHdzv54Ic3ZTZ5/Di0wAAPjJEAjh4GYJgQ0IEACRiMUTAKRsEoGPEAAGyJWmB6uvNmAAAAAElFTkSuQmCC","orcid":"","institution":"Pomeranian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Tomska","suffix":""},{"id":436053240,"identity":"a6d0e2f6-8fe1-4a5a-9642-2337f406b170","order_by":1,"name":"Aleksandra Rył","email":"","orcid":"","institution":"Pomeranian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Aleksandra","middleName":"","lastName":"Rył","suffix":""},{"id":436053241,"identity":"cb78c4b4-7098-452a-8549-73692a97ba59","order_by":2,"name":"Joanna Palma","email":"","orcid":"","institution":"Pomeranian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"","lastName":"Palma","suffix":""},{"id":436053242,"identity":"00b3351c-e164-4203-aeae-6d5822cf7723","order_by":3,"name":"Agnieszka Turoń-Skrzypińska","email":"","orcid":"","institution":"Pomeranian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Turoń-Skrzypińska","suffix":""},{"id":436053243,"identity":"b7222ab3-a3b3-4571-bcb7-04e1563a4ebc","order_by":4,"name":"Iwona Rotter","email":"","orcid":"","institution":"Pomeranian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Iwona","middleName":"","lastName":"Rotter","suffix":""}],"badges":[],"createdAt":"2024-09-17 09:03:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5101951/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5101951/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-99516-5","type":"published","date":"2025-04-24T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81569877,"identity":"e83e1c7b-0954-4ad9-94aa-1144d3178a8b","added_by":"auto","created_at":"2025-04-28 16:12:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1139798,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5101951/v1/1042a2f5-7ea9-423c-ac07-c7ab903e176b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the correlation between anthropometric indices and levels of selected hormones in relation to problematic Internet use","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Internet has become an integral part of our lives. It helps us in our daily lives and our careers. Undeniably, its use is highly beneficial, but it can have negative effects as well. Recently, the number of disorders related to inappropriate use of the Internet, or addiction to it, has increased. As a result, the topic of addiction and the search for causal relationships have become increasingly popular in the literature [1].\u003c/p\u003e\n\u003cp\u003eInternet use disorder is characterized by, among other things, a loss of control over Internet use. This may be related to social and health problems, as well as anthropometric [2, 3, 4] and hormonal parameters [5].\u003c/p\u003e\n\u003cp\u003eIt seems important to look for factors that influence anthropometric parameters or the concentration of hormones that regulate processes in the body and influence our health or prevent the occurrence of diseases of affluence. Among the anthropometric parameters used to evaluate body fat, the body mass index (BMI) [6] and indices that take into account anthropometric indices—such as LAP (lipid accumulation product) [7], VAI (visceral adiposity index) [8, 9], and BAI (body adiposity index) [10, 11]—are the most common.\u003c/p\u003e\n\u003cp\u003eFor the body mass index (BMI) factors that affect the mass of visceral adipose tissue and its function are not taken into account. Therefore, it is not\u0026nbsp;an objective index to evaluate adipose tissue function [6]. Consequently, other indices are used, such as VAI, which is used as a marker for visceral adipose tissue dysfunction [9].The visceral adiposity index (VAI) is associated with both tissue insulin sensitivity and visceral adipose tissue [8].\u0026nbsp;Another valuable index is the lipid accumulation product (LAP) which describes excessive lipid accumulation associated with central obesity and the metabolic risk [12-15]. It also helps identify the risk of cardiovascular disease and diabetes [7, 16]. Another is the body adiposity index (BAI) which was developed to directly evaluate the body fat percentage (%) [17].\u003c/p\u003e\n\u003cp\u003eThe formation of behavioral addiction is explained, for example, using a neurobiological model based on the dopamine system, which regulates, among other things, cognitive functions, the experience of pleasure, concentration, attention, or memory [18]. \u0026nbsp;Reduced levels of serotonin, also known as the \"happiness hormone,\" can lead to problems with behavioral control and increased risk of developing behavioral addictions [19]. Dopamine, often associated with reward and motivation, is released in response to rewarding stimuli, reinforcing these behaviors [20]. Studies have demonstrated that individuals with behavioral addictions exhibit altered dopamine signaling, including increased dopamine release or heightened sensitivity to dopamine. Conversely, serotonin, involved in mood regulation and impulse control, has been found to be dysregulated in individuals with these conditions. Lower levels of serotonin or reduced serotonin receptor sensitivity may contribute to impulsivity and difficulty in resisting cravings associated with behavioral addictions [21]. The interplay between dopamine and serotonin is complex and likely contributes to the development and maintenance of behavioral addictions. For instance, reduced serotonin levels may potentiate the reinforcing effects of dopamine, leading to increased reward-seeking behavior [22]. Additionally, dysregulation of dopamine and serotonin systems may interact with other neurotransmitter systems, such as the opioid and glutamate systems, further contributing to the addictive process. Understanding the neural mechanisms underlying behavioral addictions is essential for developing effective prevention and treatment strategies. Future research should focus on identifying specific neural targets for therapeutic interventions, such as medications that modulate dopamine and serotonin signaling [5, 23].\u003c/p\u003e\n\u003cp\u003eThe aim of the study was to assess the relationship between anthropometric indices (BMI, VAI, LAP, and BAI) and the concentration of hormonal parameters in relation to problematic Internet use or even addiction.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in 2020-2021 (province of West Pomerania) in Poland, on a group of 427 men aged 18-30 (24.82 \u0026plusmn; 3.83) who declared that they used the Internet and played computer games and/or online games and gambling. The inclusion criteria for the study were male gender, age between 18 and 30 years of age, declared Internet use, completed questionnaire and provided written informed consent to participate in the study. The exclusion criteria included the presence of oncological or endocrine diseases and being under the care of a psychiatrist or psychologist. Recruitment for the study was done by means of social networking, online forums, advertising and leafleting. Participation in the study was voluntary and anonymous.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuestionnaires\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the standards of the Declaration of Helsinki and was approved by the Bioethics Committee of the Pomeranian Medical University (KB-0012/90/18). The project was conducted at the request of the National Bureau for Drug Prevention (currently the National Centre for the Prevention of Addictions).\u003c/p\u003e\n\u003cp\u003eThe study was conducted using our original questionnaire concerning the amount of time spent on computer games during the weekdays and days off work, as well as the manner, purpose, and degree of Internet use. The Internet Use Test, developed by Ryszard Poprawa from the Institute of Psychology at the University of Wrocław, which shows psychological, social, and health problems caused by Internet use was used. The total score is the sum of 23 ratings on a scale from 0 (\u0026lsquo;never\u0026rsquo;) to 5 (\u0026lsquo;always\u0026rsquo;). The minimum raw score is 0 points and the maximum score is 115 points. The higher the score, the stronger the problematic Internet use; 50 points and above reflect strong compulsive Internet use (Poprawa 2011) [24].\u003c/p\u003e\n\u003cp\u003eThe study analyzed the results obtained from the questionnaires and the degree of risky behaviors with regard to Internet use. In the study group 13 individuals had asthma. Some suffered from type 1 diabetes, hypothyroidism, migraines, allergies, atopic dermatitis, hearing loss, and other conditions, but they were not criteria for exclusion from the study. The course of the study was not affected by these conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using Statistica software version 13 (StatSoft, Krakow, Poland).\u0026nbsp;Continuous variables were characterized by arithmetic means (X), standard deviation (SD), and data range. The distribution of the data was tested using the Shapiro\u0026ndash;Wilk test. The Kruskal\u0026ndash;Wallis test was used to evaluate the differences between the groups. A post hoc analysis was used to compare multiple groups. Spearman\u0026rsquo;s rho correlation analysis and multivariate linear regressions were also performed. To perform logistic regression analysis, the patients were divided into two groups\u0026mdash;a group of individuals with no symptoms of Internet addiction and a group of moderately and highly addicted Internet users. Age-adjusted logistic regression analysis was performed. Results are presented using an adjusted odds ratio (OR), beta regression coefficient (\u0026beta;), and statistical significance (p). Independent variables were the results from other questionnaires. The significance level was set at p\u0026le;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTest material collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor testing, a qualified nurse collected blood into a 9 ml tube.\u0026nbsp;Blood was drawn between 7 and 10 a.m., from fasted individuals, in the premises of the Pomeranian Medical University in Szczecin, in places designated and prepared for blood collection. Then it was centrifuged and serum was stored in a freezer in the laboratory of the Faculty of Health Sciences of the Pomeranian Medical University in Szczecin. Parameters such as abdominal circumference, weight and height were also measured. Abdominal circumference was measured using a tape measure at the level of the umbilicus, while weight and height were self-reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of biochemical and hormonal parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to calculate anthropometric indices and HOMA-IR in blood serum of the patients, the following parameters were determined using the standard method in the diagnostic laboratory: high-density lipoprotein (HDL), triglycerides (TG) and the concentration of fasting plasma glucose (FPG). Serum concentrations of the luteinizing hormone (LH), follicle stimulating hormone (FSH), testosterone (TT), sex hormone binding globulin (SHBG), dehydroepiandrosterone sulphate (DHEAs), estradiol (E2), prolactin (PRL) and insulin (I) were determined using the Enzyme-Linked Immunosorbent Assay\u0026nbsp;(ELISA). The serum concentration of serotonin (5-HT) and dopamine (DA) was determined in the Research Laboratory of the Pomeranian Medical University in Szczecin.\u003c/p\u003e\n\u003cp\u003eHOMA-IR was calculated. It is a parameter that allows to evaluate the insulin resistance of the body tissue. It is calculated in the case of abdominal obesity, problems with weight loss, drowsiness or elevated glucose concentration.\u0026nbsp;The formula HOMA-IR = insulin concentration (mu/ml) x glucose level (mmol/l) / 22.5 was used to calculate HOMA-IR. A value below 2.5 is the norm. A score above 2.5 indicates suspected insulin resistance [25].\u003c/p\u003e\n\u003cp\u003eAnthropometric indices\u0026mdash;BMI (body mass index), VAI (visceral adiposity index), LAP (lipid accumulation product), and BAI (body adiposity index)\u0026mdash;were calculated for the purpose of data analysis. In order to calculate BMI, the formula BMI = body weight (kg) by the height squared (m\u003csup\u003e2\u003c/sup\u003e) was used. According to the World Health Organization (WHO), obesity is diagnosed in adults whose BMI is \u0026ge; 30 kg/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe visceral adiposity index (VAI) was calculated to assess visceral fat accumulation and cardiometabolic risk using the formula: VAI = waist circumference (cm) / (39.68 + (1.88 \u0026times; BMI)) \u0026times; ((TG/1.03) \u0026times; (1.31/HDL)) [8].\u0026nbsp;The proper value of VAI was assumed to be VAI = 1 [26]. The lipid accumulation product (LAP) is a marker for visceral adipose tissue and metabolic syndrome [12]. It is also a predictor of the risk of diabetes and cardiovascular disease. For the male population, the formula: LAP = ((waist circumference (cm) - 65) \u0026times; TG (mmol)) is used to calculate LAP [7, 27]. Since the literature does not provide consistent information on the cut-off point, LAP was divided into quartiles. Therefore, a Q3 quartile of 63.36 was used. The body adiposity index (BAI) cut-offs to identify obese women and men were proposed according to the relationship between FM% and BMI, recognized by Bergman et al. (2011) for the Caucasian population: \u0026gt; 39 for women and \u0026gt; 25 for men aged 20\u0026ndash;39. BAI = (hip circumference (cm) / [height (m)1.5 - 18]) [10].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of Serotonin and Dopamine Serum Levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum serotonin and dopamine levels were quantified using commercially available double-antibody sandwich Enzyme-Linked Immunosorbent Assay (ELISA) kits. These assays utilized pre-coated microplates with specific antibodies for serotonin and dopamine, ensuring high specificity. Whole blood samples were collected and allowed to clot at room temperature to facilitate serum separation. Serum was obtained by centrifugation at 3000 rpm for 10 minutes, carefully aspirated to avoid contamination with cellular components, and stored at 2-8\u0026deg;C for short-term use, or at -20\u0026deg;C/-80\u0026deg;C for long-term storage, maintaining analyte stability. Samples were thawed and mixed thoroughly before use, avoiding repeated freeze-thaw cycles.\u003c/p\u003e\n\u003cp\u003ePrior to the assay, all reagents were equilibrated to room temperature. Standards, controls, and serum samples were added in duplicate to the pre-coated wells, following the manufacturer\u0026rsquo;s instructions. For serotonin, 50 \u0026micro;L of standards and samples were added, while for dopamine, a specific dilution was performed. Subsequently, 50 \u0026micro;L of HRP-conjugated antibodies were added, and the microplate was incubated at 37\u0026deg;C for 60 minutes. Following incubation, wells were washed five times with 300 \u0026micro;L of diluted wash buffer. Chromogen solutions A and B were added, and the plate was incubated for 15 minutes at 37\u0026deg;C, protected from light. The reaction was stopped with Stop Solution, and absorbance was measured at 450 nm using an ELISA plate reader. A standard curve was generated using a 4PL curve fit, and sample concentrations were determined by interpolation. Quality control included duplicate measurements and user-generated standard curves, adhering to manufacturer\u0026rsquo;s protocols. The standard curve, generated by plotting the average of optical density (OD) (450 nm) for each standard concentration, was used to determine the contents in unknown samples. \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study compared anthropometric indices, serum concentrations of biochemical and hormonal parameters, and the tissue insulin resistance index with the results of the questionnaire concerning the degree of Internet use. Internet use is measured in low, moderate, and high degrees as per the IUT questionnaire.\u0026nbsp;There was no correlation between the concentration of biochemical and hormonal parameters and the tissue insulin resistance index in relation to\u0026nbsp;the degree of Internet use (Table 1). Values close to statistical significance were found for LH (p=0.051) and 5-HT (p=0.093) and FPG (p=0.083).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Analysis of the values of hormonal parameters in serum and anthropometric indices, for which the degree of Internet use was taken into account, demonstrated that TT is negatively correlated with LAP, VAI and BAI for each degree in the IUT and it correlates with BMI for the moderate and high degrees in the IUT. SHBG is negatively correlated with BMI and VAI for each degree in the IUT. For the low and moderate degrees in the IUT it correlates with LAP, and for the moderate degree it correlates with BAI. Insulin positively correlates with VAI for each degree in the IUT. It is moderately and highly correlated with BMI and LAP, and moderately correlated with BAI. E2 has a moderate negative correlation with LAP and VAI. PRL negatively correlates with BAI for the moderate degree in the IUT. 5-HT, on the other hand, is positively correlated with LAP and VAI for the high degree in the IUT and for the low degree in the IUT it correlates with BAI. \u0026nbsp;Prolactin is moderately negatively correlated with BAI for the moderate degree in IUT (Table 2).\u003c/p\u003e\n\u003cp\u003eThe correlation between the value of the tissue insulin resistance index and anthropometric indices and the degree of Internet use was analyzed. BMI (r=0.21; p=0.001) and BAI (r=0.25; p=0.000) were found to be positively correlated with the moderate degree in the IUT questionnaire. LAP and VAI positively correlate with both the moderate (LAP r=0.41; p=0.000), (VAI r=0.43; p=0.000) and high degree (LAP r=0.40; p=0.004) (VAI r=0.37; p=0.004) in the IUT (Table 3).\u003c/p\u003e\n\u003cp\u003eIn multivariate logistic regression, a correlation between TT in the anthropometric indices — LAP (p=0.000*, OR=0.581), VAI (p=0.028*, OR=0.479) and BAI (p=0.000*, OR=0.624) — and the moderate and high degrees in the IUT questionnaire is found. A correlation was found between the SHBG concentration in the LAP index and the low (p=0.004*, OR=0.893), moderate and high (p=0.000*, OR=0.941) degrees in the IUT questionnaire, as well as for BAI and the moderate and high degrees (p=0.000*, OR=0.925) in the IUT.\u003c/p\u003e\n\u003cp\u003eA correlation was found between the concentration of DHEAs (p=0.037*, OR=1.003) and 5-HT (p=0.023*, OR=0.996) for the LAP index and the moderate and high degrees in the IUT. A correlation was found between the concentration and the moderate and high degrees in the IUT E2 (p=0.038*, OR=1.114) and between the PRL (p=0.041*, OR=1.005) concentration and the low degree in the IUT for VAI (Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study on Internet addiction and hormonal parameters, tissue insulin resistance index and anthropometric indices in 427 young men were examined. A review of the available literature reveals that not too many studies on similar topics have been performed to date. Most reports on similar topics focus on addiction to the Internet or a smartphone and its correlation with BMI. Tayhan et al. (2021) found that among students of both sexes aged 19-29, those with a potential Internet addiction had a higher BMI and higher risk of developing eating disorders compared to those without addiction (23.7 \u0026plusmn; 5.1 kg/m\u003csup\u003e2\u003c/sup\u003e and 22.2 \u0026plusmn; 2.9 kg/m\u003csup\u003e2\u003c/sup\u003e) [28]. In addition, when examining smartphone use, they reported that the results of the Internet addiction test were positively correlated with the results of the BMI and smartphone addiction (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) [28]. Alpaslan et al. (2015) also found that people with a potential Internet addiction have a much higher BMI than people without a potential Internet addiction, and a high BMI is a potential risk factor for Internet addiction [29]. Eliacik et al. (2016) and Tabatabaee HR et al. (2018) also confirmed a correlation between internet addiction and BMI [30,31]. Furthermore, Tabatabaee HR et al. (2018) proved the impact of this addiction on sleep quality, physical activity, and eating habits [31].\u003c/p\u003e\n\u003cp\u003ePeople who use the Internet on a regular basis may not be aware of how much food they consume.\u0026nbsp;They may procrastinate, postpone going to bed, or skip meals, as well as consume unhealthy processed and convenience foods\u0026mdash;often because they are more convenient and quicker to prepare or do not require cooking. Such activities can become automated and unconscious, causing appetite problems and future health problems.\u0026nbsp;As a result, this can lead to undesirable weight gain as well as psychological and social problems. [4, 28].\u003c/p\u003e\n\u003cp\u003eAddiction to the Internet and the intensification of this disorder over time were found in 2013 by researchers from Turkey [32]. They published a study of a group of 1938 students between the ages of 14 and 18 years. 10.5% of the study group were \u0026quot;problem Internet users\u0026quot; or \u0026quot;Internet addicts\u0026quot;. The authors showed a significant positive correlation between BMI and the Internet Addiction Test (IAT) according to Young (r=0.307;\u0026nbsp;p\u0026lt;0.01) and weekly Internet use (r=0.215; p\u0026lt;0.01). \u0026nbsp;Linear regression analysis showed a significant independent correlation between the IAT and BMI (r=0.235; p\u0026lt;0.001). Surfing the Internet, watching online videos, chatting and messaging, as well as playing online games were significantly correlated with an increased value of BMI (p\u0026lt;0.05) [32]. In our study, we investigated no such correlations but focused on examining health effects with regard to hormonal parameters in relation to degrees of addiction specified in the IUT. In addition, a meta-analysis by Mohadeseh Aghasi (2020) shows that Internet use is associated with a sedentary lifestyle and, therefore, it is a potential risk factor for excess weight or obesity [33].\u003c/p\u003e\n\u003cp\u003eJabłonowska-Lietz B et al. (2017) conducted a study on a small group of women and men at an average age of 39.0 \u0026plusmn; 5.9 years with an average BMI of 32.6 \u0026plusmn; 2.4 kg/m\u003csup\u003e2\u003c/sup\u003e. They found that HOMA-IR was positively correlated with both VAI and BMI\u0026nbsp;[26]. However, in our study, HOMA-IR correlated with BMI, VAI, as well as LAP and BAI for the moderate degree in the IUT, and with VAI and LAP for the high degree in the IUT, which may be related to the size of the study group for each degree in the IUT.\u0026nbsp;Amato et al. (2010) reported a negative correlation between VAI and insulin sensitivity as evaluated using the hyperinsulinemic-euglycemic buckle method in healthy weight individuals [8], which we did not find in our study.\u003c/p\u003e\n\u003cp\u003eK\u0026ouml;pr\u0026uuml;l\u0026uuml; \u0026Ouml;. et al. (2022) investigated the results of the HOMA-IR index in children with Attention\u0026nbsp;Deficit Hyperactivity Disorder in relation to screen addiction. However, the authors found no association between addiction and HOMA-IR [34].\u003c/p\u003e\n\u003cp\u003eKim H. et al. (2019)\u0026nbsp;analyzed differences in glucose metabolism and metabolic connectivity in young men. Compared to a group of healthy men, those who suffered from IGD (internet gaming disorder) were found to have hypometabolism in the anterior cingulate cortex, frontal cortex, temporal cortex and parietal cortex as well as in the striatum. It can be stated that hypometabolism and altered metabolic connectivity in IGD may be associated with abnormal sensory function as a result of prolonged gaming and dysfunction of impulsive/motivational states [35], which is related to the motivation and reward system.\u003c/p\u003e\n\u003cp\u003eOther findings report that men with online gaming disorder, and, indirectly, Internet use disorder, are found to have altered grey matter density and functional amygdala connectivity during resting state fMRI\u0026nbsp;[36]. Canan F et al.\u0026nbsp;(2017) states that this indicates neural mechanisms of the correlation between prenatal testosterone levels and behaviors that may be addictive, particularly Internet addiction among young men [37].\u003c/p\u003e\n\u003cp\u003eOur study may be the first to\u0026nbsp;analyze hormonal parameters and anthropometric indices in relation to Internet use. In addition, the results of our study support some of the previous reports indicating that Internet addiction increases the risk of developing eating disorders. Smartphone addiction is associated with both eating disorders and increased anthropometric parameters, and, therefore, the fact that this addiction is a health hazard should be taken into consideration and appropriate public health interventions should be implemented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitation and Future Directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study has a number of limitations. In the study, we could not establish a causal relationship between variables, only correlations. In addition, this study does not represent the entire population, as it was conducted only on a volunteer group of young adult men from a specific region. Consequently, individual differences in physical activity or diet that may affect the parameters should be taken into account. Additionally, the most correlated values are for the moderate degree of Internet use, which may have resulted from a large number of subjects participating in the study group. \u0026nbsp;\u0026nbsp;It should be considered a limitation that parameters such as weight and height were self-reported by respondents, which could distort the actual parameters due to the tendency to overestimate or underestimate one\u0026apos;s own weight or height. The examination and collection of biological material was done outside the activity, i.e. Internet use, so we were unable to observe hormonal discharges during potentially addictive activities. Research on a larger population is needed to explore the potential of Internet addiction. While this study provides valuable insights, it is not without limitations. Primarily, its cross-sectional design precludes the establishment of causal relationships. Future research should therefore prioritize longitudinal approaches to better elucidate the dynamics of these changes. Our findings underscore the necessity for public health interventions that address both the psychological and physiological aspects of Internet addiction. We recommend the implementation of preventive programs, the education of clinicians, and the promotion of healthy lifestyle behaviors. In the future, it is imperative to conduct interventional studies to evaluate the efficacy of various therapeutic modalities, as well as investigations into the biological mechanisms underlying the association between Internet addiction and hormonal and metabolic alterations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study is one of very few reports on the topic of anthropometric indices, selected hormonal parameters, and problematic Internet use. Our analysis shows that the Internet is often used in a state of long-term immobility leading to excess weight and obesity, which is visible in the results of anthropometric indices and hormonal parameters. Additionally, one may indicate that the anthropometric index, BAI, may be useful in predicting disorders of glucose metabolism. Our study highlights the usefulness of anthropometric indices in assessing hormone distribution and glucose metabolism. VAI can be used as a marker for estimating the risk of metabolic disorders.\u003c/p\u003e\n\u003cp\u003eHowever, further studies are needed to identify cut-off values for anthropometric indices associated with impaired glucose metabolism and increased metabolic risk. In our study, we found that serotonin, together with LAP and VAI, increases with the degree of Internet use in the IUT questionnaire, which predisposes to cardiovascular problems. In addition, the lower concentration of the SHBG hormone as a protein carrier, the lower the distribution of hormones in the body. It is worth noting that statistical significance was found to be higher in the group of subjects with a moderate degree in the IUT, and at a slightly lower but comparable level in the group with a high degree in the IUT, despite the fact that the groups were different in size.\u003c/p\u003e\n\u003cp\u003eOur findings, and those of many other authors, indicate that Internet addiction is an important independent risk factor for clinicians to use in assessment along with physical activity and psychosocial problems, but they also indicate the risk of fertility problems in increasingly \u0026nbsp; \u0026nbsp; \u0026nbsp;younger men due to hormonal disorders. Research studies in this area provide a basis for addressing the problem of Internet use. This can reduce the incidence of obesity and its effects at a young age as well as many health and psychological problems later in life.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eDeclarations of competing interest: NONE TO DECLARE\u003c/p\u003e\n\u003cp\u003ePrimary funding: The project was conducted at the request of the National Bureau for Drug Prevention (currently the National Centre for the Prevention of Addictions)\u003c/p\u003e\n\u003cp\u003eData availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZajac, K., Ginley, M. K., Chang, R., Petry N. M. 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Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. \u003cem\u003eDiabetologia.\u003c/em\u003e\u003cstrong\u003e28\u003c/strong\u003e, 412-419 (1985).\u003c/li\u003e\n\u003cli\u003eJabłonowska-Lietz, B., Wrzosek, M., Włodarczyk, M., Nowicka, G. New indexes of body fat distribution, visceral adiposity index, body adiposity index, waist-to-height ratio, and metabolic disturbances in the obese. \u003cem\u003eKardiol Pol.\u003c/em\u003e\u003cstrong\u003e75\u003c/strong\u003e, 1185-1191 (2017).\u003c/li\u003e\n\u003cli\u003eNascimento-Ferreira, M. V., et al. The lipid accumulation product is a powerful tool to predict metabolic syndrome in undiagnosed Brazilian adults. \u003cem\u003eClin Nutr.\u003c/em\u003e\u003cstrong\u003e36\u003c/strong\u003e, 1693-1700 (2017).\u003c/li\u003e\n\u003cli\u003eTayhan Kartal, F., Yabancı Ayhan, N. Relationship between eating disorders and internet and smartphone addiction in college students. Eat Weight Disord. \u003cstrong\u003e26\u003c/strong\u003e, 1853-1862 (2021).\u003c/li\u003e\n\u003cli\u003eAlpaslan, A. H., Ko\u0026ccedil;ak, U., Avci, K., Uzel Taş, H. The association between internet addiction and disordered eating attitudes among Turkish high school students. \u003cem\u003eEat Weight Disord.\u003c/em\u003e\u003cstrong\u003e20\u003c/strong\u003e, 441-448 (2015).\u003c/li\u003e\n\u003cli\u003eEliacik, K., Bolat, N., Ko\u0026ccedil;yiğit, C., Kanik, A., Selkie, E., Yilmaz, H. Internet addiction, sleep and health-related life quality among obese individuals: a comparison study of the growing problems in adolescent health\u003cem\u003e. \u003c/em\u003e\u003cem\u003eEat Weight Disord Stud Anorex Bulim Obes. \u003c/em\u003e\u003cstrong\u003e21\u003c/strong\u003e, 709\u0026ndash;717 (2016).\u003c/li\u003e\n\u003cli\u003eTabatabaee, H. R., Rezaianzadeh, A., Jamshidi, M. Mediators in the Relationship between Internet Addiction and Body Mass Index: A Path Model Approach Using Partial Least Square. \u003cem\u003eJ Res Health Sci.\u003c/em\u003e\u003cstrong\u003e18\u003c/strong\u003e, e00423 (2018).\u003c/li\u003e\n\u003cli\u003eCanan, F., et al. 467 \u0026ndash; The Relationship between Internet Addiction and Body Mass Index in Turkish Adolescents. \u003cem\u003eEuropean Psychiatry.\u003c/em\u003e\u003cstrong\u003e28\u003c/strong\u003e, 1 (2013).\u003c/li\u003e\n\u003cli\u003eAghasi, M., Matinfar, A., Golzarand, M., Salari-Moghaddam, A., Ebrahimpour-Koujan, S. Internet Use in Relation to Overweight and Obesity: A Systematic Review and Meta-Analysis of Cross-Sectional Studies. \u003cem\u003eAdv Nutr\u003c/em\u003e. \u003cstrong\u003e11\u003c/strong\u003e, 349-356 (2020).\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;pr\u0026uuml;l\u0026uuml;, \u0026Ouml;., et. al. The Effect of Screen Addiction and Attention-Deficit Hyperactivity Disorder on Insulin Resistance in Children. \u003cem\u003eJ Dr Behcet Uz Child Hosp\u003c/em\u003e. \u003cstrong\u003e12\u003c/strong\u003e, 20-26 (2022).\u003c/li\u003e\n\u003cli\u003eKim, H., Kim, Y. K., Lee, J. Y., Choi, A. R., Kim, D. J., Choi, J. S. Hypometabolism and altered metabolic connectivity in patients with internet gaming disorder and alcohol use disorder. \u003cem\u003eProg Neuropsychopharmacol Biol Psychiatry.\u003c/em\u003e\u003cstrong\u003e95\u003c/strong\u003e, 109680 (2019).\u003c/li\u003e\n\u003cli\u003eKo, C. H., et al. Altered gray matter density and disrupted functional connectivity of the amygdala in adults with Internet gaming disorder\u003cem\u003e. \u003c/em\u003e\u003cem\u003eProg Neuropsychopharmacol Biol Psychiatry\u003c/em\u003e. \u003cstrong\u003e57\u003c/strong\u003e, 185-192 (2015).\u003c/li\u003e\n\u003cli\u003eCanan, F., et al. The relationship between second-to-fourth digit (2D:4D) ratios and problematic and pathological Internet use among Turkish university students. \u003cem\u003eJ Behav Addict.\u003c/em\u003e\u003cstrong\u003e6\u003c/strong\u003e, 30-41 (2017).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Descriptive statistics of the study group, n=427\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1017\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 275px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 283px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=276\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 283px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh degree in IUT questionnaire\u003cbr\u003e\u0026nbsp;n=71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"bottom\" style=\"width: 1017px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnthropometric indices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e24.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e22.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e24.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e24.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e27.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eLAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e50.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e36.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e21.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e71.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e49.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e35.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e58.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e51.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e37.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e21.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e75.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eVAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eBAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e21.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e21.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e19.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e24.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e20.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e18.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"bottom\" style=\"width: 1017px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiochemical parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e52.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e51.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e43.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e60.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e51.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e51.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e43.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e58.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e53.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e52.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e43.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e63.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e137.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e113.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e80.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e172.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e132.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e110.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e77.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e164.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e133.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e117.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e80.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e176.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eFPG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e90.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e85.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e77.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e93.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e83.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e82.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e75.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e90.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e92.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e85.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e78.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e94.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"bottom\" style=\"width: 1017px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHormonal parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eLH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e9.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e5.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e8.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eFSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e5.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e5.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e32.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e28.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e21.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e37.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e32.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e30.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e39.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e32.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e29.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e21.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e41.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eDHEAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e377.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e350.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e282.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e411.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e377.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e362.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e282.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e456.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e404.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e387.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e295.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e498.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.396\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e24.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e23.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e18.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e30.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e25.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e20.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e31.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e20.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e32.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003ePRL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e246.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e226.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e171.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e318.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e272.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e240.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e187.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e312.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e280.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e242.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e177.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e354.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e21.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e11.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e6.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e17.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e10.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e19.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e22.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e12.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e7.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e29.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e195.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e101.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e37.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e160.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e119.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e98.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e60.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e159.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e134.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e91.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e56.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e135.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e88.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e78.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e50.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e128.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e81.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e70.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e52.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e106.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e85.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e98.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e48.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e115.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"bottom\" style=\"width: 1017px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue insulin resistance index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e3.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: X, arithmetic mean; Me, median; p, statistically significant value; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; HDL, high-density lipoprotein; TG, triglycerides; FPG, fasting plasma glucose; LH, luteinizing hormone; FSH, follicle stimulating hormone; TT, total testosterone; SHBG, sex hormone binding globulin; DHEAs, dehydroepiandrosterone sulfate; E2, estradiol; PRL, prolactin; I, insulin; 5-HT, serotonin; DA, dopamine; HOMA-IR, Homeostatic Model Assessment\u0026ndash;Insulin Resistance, Kruskal\u0026ndash;Wallis test\u003c/p\u003e\n\u003cp\u003eTable 2. Analysis of hormonal parameters and anthropometric indices in relation to the level of Internet use\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"580\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=276\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 57px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.025*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 57px;\"\u003e\n \u003cp\u003eLAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.041*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 57px;\"\u003e\n \u003cp\u003eVAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.017*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.040*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.020*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 57px;\"\u003e\n \u003cp\u003eBAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePRL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.021*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: R, correlation coefficient; p, statistically significant value; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; TT, total testosterone; SHBG, sex hormone-binding globulin; I, insulin; E2, estradiol; 5-HT, serotonin; PRL, prolactin; *, statistically significant difference, Spearman\u0026rsquo;s rho correlation analysis\u003c/p\u003e\n\u003cp\u003eTable 3. Analysis of HOMA-IR results and anthropometric parameters in relation to the degree of Internet use\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"579\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=276\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 71px;\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eLAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eVAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eBAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: R, correlation coefficient; p, statistically significant value; HOMA-IR, Homeostatic Model Assessment\u0026ndash;Insulin Resistance; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; *, statistically significant difference, Spearman\u0026rsquo;s rho correlation analysis\u003c/p\u003e\n\u003cp\u003eTable 4. Multivariate logistic regression explaining the age-adjusted result of hormonal parameters and anthropometric indices in relation to the degree of Internet use.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 256px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate and high degree in IUT questionnaire\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;Parameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eTrust OR -95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eTrust OR 95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eTrust OR -95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eTrust OR 95%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e14.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e36.342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eDHEAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003ePRL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n 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style=\"width: 64px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVAI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n 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style=\"width: 64px;\"\u003e\n \u003cp\u003e1.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eDHEAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n 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style=\"width: 64px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e5-HT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n 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\u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: p, statistically significant value; OR, odds ratio; BMI, body mass index; LAP, lipid accumulation product; VAI, visceral adiposity index; BAI, body adiposity index; TT, total testosterone; SHBG, sex hormone-binding globulin; DHEAs, dehydroepiandrosterone sulfate; E2, estradiol; PRL, prolactin; 5-HT, serotonin; DA, dopamine; *, statistically significant difference, multivariate logistic regression analysis\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Internet use test, serotonin, dopamine, biochemical parameters, behavioral addiction, young men","lastPublishedDoi":"10.21203/rs.3.rs-5101951/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5101951/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aim of the study was to assess the relationship between anthropometric indices and the concentration of hormonal parameters in relation to problematic Internet use or even addiction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in 2020-2021 on a group of 427 men aged 18-30 (24.82 ± 3.83) who declared that they used the Internet and played computer games and/or online games, including gambling. Participation in the study was voluntary and anonymous. Anthropometric indices, HOMA-IR as well as biochemical and hormonal parameters were calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLipid Accumulation Product (LAP) and Visceral Adiposity Index (VAI) positively correlate with both the moderate (LAP r=0.41; p=0.000), (VAI r=0.043; p=0.000) and high degree (LAP r=0.40; p=0.004), (VAI r=0.37; p=0.004) in the IUT. In multivariate logistic regression, a correlation between testosterone (TT) in the anthropometric indices— LAP, VAI and Body Adiposity Index (BAI)—and the moderate and high degrees in the IUT questionnaire is found.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study highlights the usefulness of anthropometric indices in assessing hormone distribution and glucose metabolism. VAI can be used as a marker for estimating the risk of metabolic disorders. Serotonin, together with LAP and VAI, increases with the degree of Internet use in the IUT questionnaire, which predisposes to cardiovascular problems. Internet addiction is an important independent risk factor for clinicians to use in assessment along with physical activity and psychosocial problems, but they also indicate the risk of fertility problems in increasingly younger men due to hormonal disorders.\u003c/p\u003e","manuscriptTitle":"Analysis of the correlation between anthropometric indices and levels of selected hormones in relation to problematic Internet use","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 09:18:16","doi":"10.21203/rs.3.rs-5101951/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-21T07:55:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-15T04:41:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247827723721302523022686360916692464337","date":"2025-04-15T04:33:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-31T01:44:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-26T06:06:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-18T18:38:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fcf70d35-7830-4a87-a8b0-a49f65922188","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46423508,"name":"Biological sciences/Biochemistry"},{"id":46423509,"name":"Biological sciences/Psychology"},{"id":46423510,"name":"Health sciences/Health care"},{"id":46423511,"name":"Health sciences/Risk factors"},{"id":46423512,"name":"Health sciences/Signs and symptoms"}],"tags":[],"updatedAt":"2025-04-28T16:06:10+00:00","versionOfRecord":{"articleIdentity":"rs-5101951","link":"https://doi.org/10.1038/s41598-025-99516-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-24 15:57:57","publishedOnDateReadable":"April 24th, 2025"},"versionCreatedAt":"2025-04-01 09:18:16","video":"","vorDoi":"10.1038/s41598-025-99516-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-99516-5","workflowStages":[]},"version":"v1","identity":"rs-5101951","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5101951","identity":"rs-5101951","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}