The associaTion beTween viTamin D sTaTus anD carDiomeTabolic DisorDers in overweighT anD obese aDolescenTs

An increase in the prevalence of overweight and obese adolescents is often combined with a low level of vitamin D that may be associated with lipid and carbohydrate metabolism disorders, which underlie the development of arterial hypertension and cardiometabolic changes. This work aimed to determine the association between vitamin D status and the main parameters of lipid and carbohydrate metabolism, and anthropometric measurements. A total of 196 adolescents (129 boys and 67 girls) from the Ternopil region were examined. Their mean age was 15.5 ± 2.3 years. Based on the body mass index (BMI): 60 adolescents had normal body weight, 60 were overweight, and 76 were obese. Anthropometric measurements and general examinations were performed. In blood serum 25(OH)D levels and the main parameters of lipid and carbohydrate metabolism were determined. Low levels of 25(OH)D were found. Prevalence of vitamin D deficiency among adolescents with BMI up to the 85th percentile was 56.7%, with BMI in the 85-97th percentiles was 70.0% and with BMI over the 97th percentile was 77.6%. Serum 25(OH)D levels in overweight and obese adolescents had a significant correlation with BMI (r = -0.427, P < 0.001), waist circumference (r = -0.462, P < 0.001), highdensity lipoprotein cholesterol (HDL-C, r = 0.214, P = 0.023), low-density lipoprotein cholesterol (LDL-C, r = -0.226, P = 0.011), atherogenic index (r = -0.284, P = 0.001), insulin level (r = -0.483, P < 0.001), and HOMA-IR index (r = -0.454, P < 0.001). We concluded that the development of cardiometabolic disorders in overweight and obese adolescents is associated with vitamin D status.

This work aimed to determine the association between vitamin D status and the main parameters of lipid and carbohydrate metabolism, and anthropometric measurements in adolescents with overweight and obesity.

materials and methods
The research was conducted at the Department of Pediatrics № 2, I. Horba-chevsky Ternopil National Medical University based on the communal institution of the Ternopil Regional Council "Ternopil Regional Children's Clinical Hospital". The study was conducted according to the ethical standards in the Helsinki Declaration of 1975, as revised in 2008 (5), as well as national law. The patient safety rules and the ethical standards and procedures for research on human beings (2000) were followed in carrying out the work. The Ethics Committee of the I. Horbachevsky Ternopil National Medical University approved the study on the 29 th of April 2020, session's protocol number 58.
In all cases, informed consent was obtained from patients and their parents.
The inclusion criteria for the study were the following: age 12-17 years, body mass index (BMI) at or above the 85 th percentiles according to age-sex nomograms, written informed consent of parents and patients for the examination, and the No-vember-March, 2020 time period. The exclusion criteria were: obesity due to endo-crine diseases (hypercorticism, hypopituitarism, hypothyroidism, hypothalamic-pituitary injury), taking anticonvulsant drugs, glucocorticoids, or drugs that affect blood pressure, hereditary and congenital disorders, or diabetes mellitus.
A total of 196 adolescents (129 boys and 67 girls) from the Ternopil region were examined. Their mean age was 15.5 ± 2.3 years.
Anthropometric measurements were made and included: body weight (within the accuracy of 0.1 kg), height (within the accuracy of 0.1 cm), waist circumference (WC) and hip circumference (HC). Measurements were carried out with the use of generally accepted methods with the help of a floor weight scale, height meter, and flexible centimeter tape measure. WC was measured with the tape measure at the point midway between the iliac crest and the costal margin (lower rib). HC was measured at the level of the greatest protrusion of the buttocks. Next, the waist-hip ratio (WHR) was calculated as WC divided by HC. The waist-to-height ratio (WHtR) was defined as WC divided by height. BMI was calculated according to the formula (body weight (kg)/height 2 (m 2 )).
BMI was assessed by percentile curves for girls and boys separately. Over-weight was diagnosed in cases when BMI was greater than the 85 th to 97 th percentile, obesity when BMI exceeded the 97 th percentile, and normal body weight when BMI was less than the 85 th percentile, according to gender and age charts based on the World Health Organization (WHO) recommendations [14].
The blood pressure values were interpreted according to 2017 AAP Guidelines [15].
The results of anthropometric and blood pressure measurements are presented in Table 1.
Vitamin D status was determined according to the level of 25(OH)D (calcidiol) in blood serum by the immunoassay method with the use of the 25-OH Vitamin D ELISA test kit (EUROIMMUN, Lubeck, Germany) on the Multiskan FC analyzer (Thermo Scientific, Waltham, MA, USA), with an intra-assay coefficient of variation (CV) of 3.2-4.9% and an inter-assay CV of 4.0-7.8%.
To establish the association between vitamin D status and cardiometabolic factors, adolescents with overweight and obesity were divided into 4 subgroups, according to the level of calcidiol in blood serum.
To determine lipid metabolism, serum concentrations of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) were measured by the enzymatic colorimetric method, using the Cholesterol Reagent and Cobas c111 automatic analyzer by Roche Diagnostics test systems (Rotkreuz, Switzerland). The low-density lipoprotein cholesterol (LDL-C) level was calculated by the Friedewald equation (LDL-C=TC -(TG/2.2+HDL-C). The very low-density lipoprotein cholesterol (VLDL-C) level was calculated as Note. Quantitative data are presented as mean (M) and standard deviation (SD). BMI -body mass index; WC -waist circumference, HC -hip circumference; WHR -ratio of waist circumference to hip circumference, WHtR -ratio of waist circumference to height; SBP -systolic blood pressure; DBP -diastolic blood pressure VLDL-C=TG/2.2. Non-HDL-C was calculated as TC -HDL-C. The atherogenic index (AI) was calculated as follows: AI=(TC -HDL-C)/HDL-C [20].
To determine carbohydrate metabolism, the blood glucose level, basal insulin level in the blood serum, and impaired glucose tolerance (IGT) were determined and the index of insulin resistance (homeostasis model assessment of insulin resistance, HOMA-IR) was calculated. An oral glucose tolerance test was performed to determine the level of fasting glucose and insulin in the blood and at 0, 30, 60, 120, and 180 min after glucose loading. Blood glucose levels were determined by the glucose oxidase method [21]. Blood insulin levels were measured by ELICA (immunochemical with electrochemiluminescent detection) using the Cobas 6000 analyzer and Roche Diagnostics test systems (Switzerland). The HOMA-IR index was calculated by the formula: HOMA-IR=(fasting glucose × fasting insulin)/22.5. Insulin resistance was detected at values of HOMA-IR that were 3.19 and higher. Impaired fasting glycemia (IFG) was defined as glucose levels from 5.6 to 6.9 mmol/l in fasting patients [21][22]. IGT was defined as fasting plasma glucose less than 7.0 mmol/l and as blood glucose level of 7.8 mmol/l or more but less than 11.1 mmol/l after a 2-hour oral glucose tolerance test (after ingestion of 1.75 g/kg body weight, but not more than a 75 g oral glucose load) [21][22].
Statistical analysis was conducted using the Statistica 12.0 software package (StatSoft Inc., Inc. Tulsa, OK, USA). The assessment of the normality of the distribution of features in the variation series was carried out according to the Shapiro-Wilk criteria. Quantitative data were presented depending on the nature of the characteristics distribution. In the case of the normal distribution of features, the data were presented as the mean (M) and standard deviation (SD). In cases of non-normal distribution we calculated the median (Me), lower (Lq) and upper (Uq) quartiles.
Post hoc analysis between groups was performed using one-way analysis of variance (ANO-VA) with Tukey's test. Comparisons of two independent samples with non-normal distributions of values were made using the nonparametric Mann-Whitney U-test. Statistical differences in qualitative features were determined using the chi-squared test (χ 2 ) with Yates correction. To evaluate possible associations be-tween 25(OH)D levels and variables of lipid metabolism, carbohydrate metabolism, and anthropometric measurements the Spearman correlation coefficients were determined.
The significance of the differences between the values was considered signifi-cant at P < 0.05.

results and Discussion
The median serum 25(OH)D values in adolescents with normal body weight was 17.90 (12.16-24.93) ng/ml, in overweight was 14.69 (10.27-20.30) ng/mL, and in obese adolescents was 12.71 (9.36-17.37) ng/ml. Using the Mann-Whitney U-test, the mean values of serum 25(OH)D levels were significantly less in the over-weight adolescents than in those with normal body weight (P = 0.011), and in obese adolescents compared to those with normal body weight (P < 0.001).
The frequency of vitamin D sufficiency was 2.25 times lower in overweight adolescents and 3.79 times lower in obese adolescents than in adolescents with nor-mal body weight (Fig. 1).
The frequency of vitamin D deficiency in overweight adolescents increased by 23.52% (χ 2 = 2.29; P = 0.130) and in obese adolescents by 36.99% (χ 2 = 5.88; P = 0.010) compared to that in adolescents with normal body weight.
The results of this study have shown that the prevalence of vitamin D deficiency among adolescents was higher than among adolescents in Poland, where 17.1% of 25(OH)D values were within the normal range, 36.2% were insufficient, and as much as 46.7% showed vitamin D deficiency [23], and also more than among adolescents in Italy where vitamin D deficiency was determined in 32.3% [24]. Overweight and obesity negatively affect the vitamin D status and the activity of vitamin D metabolites, and contribute to the development of vitamin D deficiency, which develops into more severe metabolic disease [25]. Accumulation of excessive adipose tissue in the body leads to the accumulation of inactive forms of vitamin D metabolites and decreases its bioavailability [26]. It has been established that vitamin D metabolism and 25(OH)D synthesis are impaired as a result of nonalcoholic hepatic steatosis formation in obesity [27].
The serum 25(OH)D levels in overweight and obese adolescents are character-ized by significant inverse correlations with the main anthropometric measurements ( Table 2).
In obese children, vitamin D is sequestered in adipose tissue [28]. Adipose tissue expresses vitamin D receptors, and 1-alpha-hydroxylase converts 25(OH)D to calcitriol, and thus this tissue is a direct target for vitamin D and is a site of local synthesis of calcitriol [29]. At the same time, locally in adipose tissue vitamin D metabolites activity, it affect the differentiation of preadipocytes to mature adipocytes [30][31].
An increase in the amount of visceral fat is important in the development of cardiometabolic disorders, which can be determined by measuring the WC. In our study, 76 (75.2%) adolescents with vitamin D deficiency and 13 (46.4%) adolescents with vitamin D insufficiency had abdominal obesity (i.e., increased WC, WHR), and this was more than in  [32]. With vitamin D deficiency the lipogenesis process is activated and lipolysis is suppressed, which leads to a growing amount of adipose tissue [28], development of adipocyte hypertrophy, atypical fat distribution, hypoxia, and chronic stress [33].

T a b l e 2. Correlations between 25(OH)D levels and anthropometric measure-ments in overweight and obese adolescents (n = 136)
The associations between lipid metabolism variables and vitamin D status in overweight and obese adolescents have been determined (Table 3).
Researchers in Turkey have found an association between low 25(OH)D levels and impaired lipid profile, and in their study of adolescents with vitamin D deficiency 69.23% had dyslipidemia [34]. The frequencies of altered lipid metabolism variables in our study are shown in Fig. 2.
Generally, compared with adolescents who had sufficient vitamin D levels the levels of proatherogenic lipids (i.e., LDL-C, VLDL, non-HDL-C) were significantly increased in adolescents with vitamin D deficiency (subgroup 3) by 15.27% and in adolescents with severe vitamin D deficiency (subgroup 4) by 26.54%.

Fig. 2. The frequencies of altered lipid metabolism variables in adolescents with vitamin D deficiency. TC -total cholesterol; HDL-C -high-density lipoprotein cholesterol; LDL-C -low-density lipoprotein cholesterol; TG -triglycerides
The associations between dyslipidemia and vitamin D levels were established by direct correlation between the 25(OH)D level and HDL-C and by inverse correla-tions between calcidiol and TC, LDL-C, VLDL-C, TG, non-HDL-C, and AI (Table 4).
Increasing proatherogenic lipids that are associated with vitamin D deficiency contribute to increased cardiovascular risk [35]. It has been established that the effect of proatherogenic lipids is one of the important factors that contributes to developing hypertension [35]. The active vitamin D metabolite, calcitriol, through its effect on the reninangiotensin system is characterized by the ability to regulate blood pressure and to influence the functional state of endothelial cells, cardiomyocytes, and vascular smooth muscle cells [36].
Increased SBP ≥ 130 mm Hg and DBP ≥ 85 mm Hg were in 48 (81.3%) obese adolescents with vitamin D deficiency, and in 25 (59.5%) overweight adolescents with vitamin D deficiency. Among all 101 adolescents with overweight or obesity and vitamin D deficiency, increased blood pressure was found in 73 (72.3%) adolescents, consistent with an Italian study in which 60% had clinical hypertension [37].
There was a significant direct correlation between SBP and DBP and lipid metabolism variables, in particular with TC, LDL-C, TG, non-HDL-C, and AI. There were inverse correlations for SBP and DBP with HDL-C. The next step was to study carbohydrate metabolism variables depending on the vitamin D level. IFG in overweight and obese adolescents was found in 14.29% with vitamin D insufficiency, and in 32.67% with vitamin D deficiency (Table 5). IGT in overweight and obese adolescents was found in 7.15% with vitamin D insufficiency and in 7.92% with vitamin D deficiency. These findings confirm the results of other researchers [38]. There was no impaired glucose tolerance in adolescents with vitamin D sufficiency.
Hyperinsulinemia combined with vitamin D insufficiency was diagnosed in 7.15% of overweight and obese adolescents, and with vitamin D deficiency in 57.43%. Compared to adolescents with vitamin D sufficiency, the insulin level in adolescents with 25(OH)D levels from 10 to 20 ng/ml was 1.45 times higher, and in those with 25(OH)D < 10 ng/ml was 1.91 times higher. Insulin resistance in adolescents with vitamin D insufficiency was found in 46.43%, and with vitamin D deficiency in 82.18%. There were significant correlations between 25(OH)D levels and the basal insulin level (r = -0.483; P < 0.001) and HOMA-IR (r = -0.454; P < 0.001) in overweight and obese adolescents, as determined by Spearman correlations. Our data confirm the results of studies by researchers in other countries concerning the correlations of serum 25(OH)D levels with insulin and HOMA-IR [39], but in our study, there was no correlation between 25(OH)D levels and blood glucose.
It is believed that vitamin D is associated with a positive effect on improving insulin secretion by pancreatic β-cells through nuclear vitamin D receptors, and also due to the calbindin effect on protein function through the regulation of intracellular cal-  [17,40]. Vitamin D affects sensitivity of tissues and to insulin by stimulating the gene expression for insulin sensitivity, and through vitamin D receptors, which are in the cell nucleus [40][41].