eISSN: 2300-6722
ISSN: 1899-1874
Medical Studies/Studia Medyczne
Bieżący numer Archiwum Artykuły zaakceptowane O czasopiśmie Suplementy Rada naukowa Bazy indeksacyjne Prenumerata Kontakt Zasady publikacji prac
Panel Redakcyjny
Zgłaszanie i recenzowanie prac online
2/2020
vol. 36
 
Poleć ten artykuł:
Udostępnij:
Artykuł oryginalny

Rola polimorfizmu rs1421085 w patogenezie otyłości

Małgorzata Biskup
1, 2
,
Paweł Macek
2, 3
,
Halina Król
2, 4
,
Artur Kowalik
5
,
Łukasz Madej
2
,
Marek Żak
2
,
Stanisław Góźdź
2, 6

1.
Department of Rehabilitation, Hollycross Cancer Centre, Kielce, Poland
2.
Collegium Medicum, Jan Kochanowski University, Kielce, Poland
3.
Department of Epidemiology and Cancer Control, Hollycross Cancer Centre, Kielce, Poland
4.
Research and Education Department, Hollycross Cancer Centre, Kielce, Poland
5.
Department of Molecular Diagnostic, Hollycross Cancer Centre, Kielce, Poland
6.
Clinical Oncology Clinic, Hollycross Cancer Centre, Kielce, Poland
Medical Studies/Studia Medyczne 2020; 36 (2): 110–115
Data publikacji online: 2020/06/30
Plik artykułu:
Pobierz cytowanie
 
Metryki PlumX:
 

Introduction

Obesity is a rapidly growing social problem affecting an increasing number of adults as well as children and adolescents. The occurrence of obesity is associated with a higher risk of developing, among other diseases, diabetes, cardiovascular disease or cancer. In the pathogenesis of this disease, the role of genetic factors is suggested, including polymorphisms of genes coding for leptin, adiponectin, FTO and TCF7L2 [1–5].
In 2007, due to genome-wide association study (GWAS), the association of polymorphisms in the FTO gene with the risk of obesity was detected [6]. The FTO gene occupies 400 bp on chromosome 16 at position q12.2 and consists of 9 exons.
Scientific studies indicate that the FTO gene has the greatest impact on the occurrence of obesity in polygenic predisposition to this disease [7, 8]. It is believed that polymorphisms in the FTO are much more associated with food consumption than with energy expenditure [8–10].
On the basis of literature data, the authors selected for genotyping an FTO gene polymorphism associated with an increased risk of obesity (rs1421085) [11, 12]. Data on the Polish population are scarce [12].
The aim of the research is to look for a significant correlation between the presence of the rs1421085 polymorphism of the FTO gene and the occurrence of overweight or obesity. The frequency of TT, CT and CC genotypes in a group of 100 obese people will be assessed compared to people with normal body weight (body mass index – BMI, etc.). The presence of CT and CC genotypes is associated with an increased risk of obesity, 1.3× and 1.7×, respectively [13]. According to data collected in the 100Genomes project, the frequency of genotypes is as follows: TT: 0.360 (181) CC: 0.225 (113) CT: 0.416 (209) [14].
The obtained results will allow us to deepen the understanding of the etiopathogenesis of such socially significant diseases as overweight and obesity, and will significantly affect the standards of clinical practice, allowing for more effective prevention of diabetes and obesity.

Aim of the research

Analysis of the relationship between the FTO rs1421085 gene polymorphism (NC_000016.10: g.53767042T> C) and the risk of obesity among participants of the PONS (Polish Norwegian Study).

Material and methods

In accordance with the right of access to PONS data, this study only used information about participants who had a permanent registration address in the city of Kielce. The verification covered data from 4.799 (33.7% of men) study participants aged 45–64. The purpose of the PONS project, i.e. “Establishment of infrastructure for population health research in Poland”, was the collection of data on the population to assess the determinants of health and the main causes of morbidity and mortality in Poland. The study protocol included the Health Status Questionnaire, medical examination, basic anthropometric measurements, and blood and urine sampling. The PONS study was conducted in 2010–2011, and the analysis of blood samples in 2019.

Verification of data

In the research, using the random number calculator from the whole group (n = 4.799), 98 participants were selected who were the test group, who, according to the World Health Organization (WHO) recommendation, had BMI indicating the presence of obesity (BMI ≥ 30 kg/m2). In order to minimize the selection of bias between the study and control groups, the propensity score matching method (PSM) was used. A control group of 102 people with normal BMI (18.5 kg/m2 ≤ BMI < 25.0 kg/m2) was fitted to the study group with similarity in the distribution of variables: age, sex, marital status, education, professional activity and smoking status. In the above group, there were no obesity or other chronic metabolic and endocrine diseases that could predispose to overweight and obesity.

Anthropometric measurements

Body weight was measured with the Tanita S.C.-240 MA body composition analyzer with an accuracy of 0.1 kg. Body height was measured using the Seca height measure (with accuracy of 0.1 cm). Body mass index was calculated as the ratio of body weight (in kg) divided by the square of body height (in meters). The natural waist indentation or navel was a marker for measuring waist circumference (WC). Hip circumference was measured at the widest part of the hips. Waist to hip ratio (WHR) was calculated as the quotient of waist circumference and hip circumference. Systolic and diastolic blood pressure were measured using Omron (M3 Intellisense model) and calculated as the arithmetic mean of two consecutive readings taken by medical personnel.

Laboratory measurements

Total cholesterol (TC) was obtained by the cholesterol oxidase and cholesterol esterase method. High density lipoprotein concentration (HDL-C) was obtained by the direct method with TOOS and surfactant. Triglyceride concentration (TG) was determined by means of the phosphoglyceride oxidase-peroxidase method. Fasting blood glucose was determined by the enzymatic method with hexokinase. Laboratory tests were carried out with CB 350i Wiener Lab. Low density lipoprotein level (LDL-C) were estimated using the Friedewald equation for TG levels below 400 mg/dl.

Genotyping methods

From the available blood samples DNA was isolated from peripheral blood lymphocytes to perform genotyping using Genomic Blood AX Micro Gravity (A & A Biotechnology). The quality and quantity of DNA obtained was checked using a NanoDrop One/ OneC spectrophotometer (Thermo Scientific). The polymorphism change study was performed using a commercial probe and primer kit for the FTO rs 1421085 gene (Thermo Scientific) and the TaqManTM Genotyping Master Mix (Thermo Scientific) using a QuantStudio 5 RealTime PCR System (Thermo Scientific) according to the manufacturer’s protocol.

Health Status Questionnaire

Self-reported socio-demographic and lifestyle-related information was based on the Health Status Questionnaire. The variables were classified as: marital status (single/in a relationship), education (lower level/upper level), professional activity (professional inactive/professional active), smoking status (never smoking/current smoking) and comorbidities (no/yes). The basic characteristics of the test and control groups are presented in Table 1.

Statistical analysis

The basic characteristics of the variables studied were presented in the form of means ± standard deviations as well as numbers and percentages. The significance of the differences in the studied variables in the study and control groups was examined by the independent t test (continuous variables) or chi-square test (categorized variables). P-values < 0.05 were considered to be statistically significant. All statistical analyses were pursued in R version 3.5.3.

Results

The study group consisted of 200 people, including 154 (76.87%) women and 46 (23.13%) men. A hundred and forty-four respondents declared being in a relationship, 173 have a university degree, 85 work professionally. In an interview 122 patients declared smoking. Twenty-one (21.35%) subjects had diabetes, 80 (89.15%) subjects had hypertension, 18 (18.33%) had coronary heart disease, and 21 (21.35%) had circulatory failure. People with obesity had statistically significantly higher systolic blood pressure (p < 0.001), higher triglyceride concentration (p < 0.001), and lower total cholesterol (p < 0.01). In the serum of obese people statistically significantly higher glucose levels were found compared to the control group (p < 0.001). Obese people were also characterized by a higher incidence of diabetes, hypertension, coronary heart disease and circulatory failure. The results of anthropometric and biochemical tests are summarized in Table 1.

Genotype distribution for the rs1421085 FTO gene polymorphism

The genotype distribution for the rs1421085 FTO gene polymorphism in the entire study group was 29.5% for TT homozygotes, 45% for CT heterozygotes, and 25.5% for CC homozygotes. There were no statistically significant differences between the occurrence of a given polymorphism and the presence of obesity in the studied group of women and men (Table 2).
The distribution of alleles in the above study complies with Hardy Weinberg’s law. The frequency of the dominant allele (T) is 7.96% higher in the control group compared to the study group.

Discussion

The research results among patients with an abnormal BMI showed significantly higher incidence of higher blood pressure, higher triglycerides, glucose and lower total cholesterol. Hypertension, diabetes, circulatory failure and ischemic heart disease were also more commonly reported.
Results similar to those mentioned above were also obtained by Woźny et al. [12]. People with overweight and obesity have certain metabolic disorders compared to people without obesity. Among the metabolic disorders in the group of obesity, the authors mention a significantly higher incidence of hypertension and diabetes, higher systolic and diastolic blood pressure, and higher fasting glucose [12]. Diabetes occurs in people who are overweight and obese much more often than in the general population, and its incidence increases with the degree of obesity. The occurrence of diabetes and other types of carbohydrate metabolism disorders in obesity is caused by many pathophysiological factors. Undoubtedly, insulin resistance associated with obesity is the most important factor. When considering the occurrence of diabetes in obesity, the type of obesity should be taken into account. The development of diabetes is particularly favored by the so-called polymetabolic syndrome, especially abdominal android obesity. A larger amount of abdominal fat accelerates the development of diabetes due to the greater generation of insulin resistance and overproduction of fatty acids (lipotoxicity). However, these relationships are not linear and are also associated with the degree of overall overweight [5].
The involvement of environmental and genetic factors in the pathogenesis of obesity is suggested. Identification of mutations or polymorphisms in genes may contribute to understanding the etiology of the disease. In the search for these genetic changes, the so-called GWA study has been a very useful tool in recent years. It is a project that aims to identify genetic differences that shape variability in disease susceptibility. It is based on a comparison of polymorphic changes in people belonging to the study and control group. Detection of statistically significant differences allows one to determine the polymorphic relationship with a given disease. In GWA studies, single nucleotide polymorphisms (SNPs) are analyzed [15].
The HapMap Project also brings a lot of relevant information regarding polymorphic changes and related diseases. The goal of this international project is to identify and determine the incidence and correlation of gene variants that shape variability in disease incidence. The HapMap Project bases its research on population groups from parts of Africa, Europe and Asia. Projects such as the Genome-Wide Association and the HapMap Project offer the chance to significantly speed up genetic testing and to learn about the genetic aspects of many diseases. Recent discoveries related to the FTO gene as the one responsible for obesity are very promising. The genome-wide association study showed a link between the simultaneous occurrence of polymorphisms such as the rs1421085 FTO gene and rs17782313 MC4R gene and obesity. Research results from 4,700 Finnish residents and more than 3,000 French people have shown that carriers of three or four risk alleles (the FTO gene and MC4R) are three times more susceptible to developing obesity, especially during childhood. A simultaneous carrier of the FTO and MC4R gene risk allele has significantly increased risk of obesity and type 2 diabetes. It was also found that low physical activity deepens the effect of rs1421085 polymorphism on the development of obesity. Physically inactive carriers of the risk allele of the FTO gene had a higher BMI value, while active carriers had comparable BMI to non-carriers. It was also investigated whether there is a relationship between other FTO gene polymorphisms – rs1421085 and rs17817449 – and the occurrence of obesity and biochemical features associated with it. Among surveyed 900 overweight residents (mean BMI value = 27.6 kg/m2) from Quebec, it was found that there is a relationship between the polymorphisms studied and BMI, body weight and waist circumference, as well as insulin sensitivity and leptin concentration [15].
Albuquerque et al. also found significant associations between rs1421085 polymorphism and body weight, BMI, waist circumference and hip circumference in Portuguese children [16].
Kopelman et al. reported that obesity-related quantitative features such as body weight, waist circumference, and fat mass were significantly increased in A allele carriers [17].
Cha et al. reported that the rs1421085 C allele was significantly associated with increased BMI [18]. Dougkas et al., in turn, reported that FTO polymorphisms are associated with a change in the feeling of satiety and may play a role in regulation of food intake [19].
The authors of the study examined the relationship between rs1421085 polymorphism and obesity in the Polish population. Despite the confirmed literature data, there was no significant relationship between FTO gene polymorphisms and obesity in the study group.
Also, Solak et al. did not find a significant relationship when comparing rs9939609 genotypes (TT, TA, AA) and rs1421085 genotypes (TT, TC, CC) in terms of anthropometric measurements and body composition results [20]. Ohashi et al. reported that Oceanic populations showed no significant association between FTO polymorphisms, including rs1421085 and BMI, as opposed to European populations [21]. In addition, they suggested that population frequencies in Oceanic populations were similar to those of southwestern and eastern Asia. The Anatolian peninsula (Turkey) served as a junction connecting the Middle East, Europe and Central Asia, and thus was subject to large population movements [21].
The authors of the study did not find any relationship between FTO polymorphisms and obesity in the study group. According to the discussion, the research on this topic is divergent. The reason for the discrepancy may be due to regional differences, a limited study group, lifestyle or age. However, the results of our own research, similarly to other authors, clearly show that the risk of developing cardiovascular complications in obese people is much higher than those maintaining a normal body weight [22, 23]. It is therefore important to consider what to do to prevent overweight and obesity developing.

Conclusions

The rs1421085 polymorphism of the FTO gene does not show a statistically significant association with the occurrence of obesity in the Polish population. The lack of association between the rs1421085 polymorphism of the FTO gene and obesity may result from the small size of the examined group. Analyses of a larger group of respondents are necessary.

Conflict of interest

The authors declare no conflict of interest.

References

1. Krekora-Wollny K, Suliga E. Changes in body mass during weight loss treatment – a two-year prospective study. Med Stud 2017; 33: 290-294.
2. Majda A, Zalewska-Puchała J, Kamińska A, Bodys-Cupak I, Suder M. Risk factors for diseases of the cardiovascular system among Catholics living in areas of southern Poland. Med Stud 2017; 33: 88-94.
3. Zara-Lopes T, Galbiatti-Dias LSA, Urbanin Castanhole-Nunes MM, Padovani-Júnior JA, Maniglia JV, Pavarino EC, Goloni-Bertollo EM. Polymorphisms in MTHFR, MTR, RFC1 and CbetaS genes involved in folate metabolism and thyroid cancer: a case-control study. Arch Med Sci 2019; 15: 522-530.
4. Kabała M, Wilczynski J. Otyłość a stabilność posturalna kobiet po mastektomii. Stud Med 2019; 35: 48-54.
5. Kała E, Bodek I, Trelińska O, Gładysz P, Lepiarczyk O, Śmigel A, Gola M, Grzeszczak W. Polymorphism rs7903146 of TCF7L2 gene and occurrence of being overweight and obesity among patients admitted to outpatient clinic. Ann Acad Med Siles 2014; 68: 200-206.
6. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JRB, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW, Barrett JC, Ellard S, Groves CJ, Knight B, Patch AM, Ness AR, Ebrahim S, Lawlor DA, Ring SM, Ben-Shlomo Y, Jarvelin MR, Sovio U, Bennett AJ, Melzer D, Ferrucci L, Loos RJF, Barroso I, Wareham NJ, Karpe F, Owen KR, Cardon LR, Walker M, Hitman GA, Palmer CNA, Doney ASF, Morris AD, Smith GD, The Wellcome Trust Case Control Consortium, Hattersley AT, McCarthy MI. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889-894.
7. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937-948.
8. Larder R, Cheung MKM, Tung YCL, Yeo GSH, Coll AP. Where to go with FTO? Trends Endocrinol Metab 2011; 22: 53-59.
9. Speakman JR, Rance KA, Johnstone AM. Polymorphisms of the FTO gene are associated with variation in energy intake, but not energy expenditure. Obesity 2008; 16: 1961-1965.
10. Speakman JR. The “fat mass and obesity related” (FTO) gene: mechanisms of impact on obesity and energy balance. Curr Obes Rep 2015; 4: 73-91.
11. Ehrlich AC, Friedenberg FK. Genetic associations of obesity: the fat-mass and obesity-associated (FTO) gene citation. Clin Transl Gastroenterol 2016; 7: e140.
12. Woźny Ł, Wojtas E, Chuchmacz G, Maciejiczek J, Karon M, Kandefer B, Śnit M, Grzeszczak W. The effect of rs1421085 polymorphism of FTO gene on progress of hypertension in overweight and obese subjects. Ann Acad Med Siles 2016; 70: 51-55.
13. https://www.snpedia.com/index.php/Rs1421085 (Access from: 15.08.2019).
14. http://browser.1000genomes.org (Access from: 15.08.2019).
15. Kolackov K, Łaczmański Ł, Bednarek-Tupikowska G. Influence of FTO gene polymorphisms on the risk of obesity. Endokrynol Otyłość Zaburzenia Przem Materii 2010; 2: 101-107.
16. Albuquerque D, Nobrega C, Manco L. Association of FTO polymorphisms with obesity and obesity-related outcomes in Portuguese children. PLoS One 2013; 8: e54370.
17. Kopelman P. Health risks associated with overweight and obesity. Obes Rev 2007; 8 Suppl 1: 13-17.
18. Cha SW, Choi SM, Kim KS, Park BL, Kim JR, Kim JY, Shin HD. Replication of genetic effects of FTO polymorphisms on BMI in a Korean population. Obesity 2008; 16: 2187-2189.
19. Dougkas A, Yaqoop P, Givens DI, Reynolds CK, Minihane AM. The impact of obesity-related SNP on appetite and energy intake. Br J Nutr 2013; 110: 1151-1156.
20. Solak M, Erdogan MO, Yildiz SH, Ucok K, Yuksel S, Terzi E, Bestepe A. Association of obesity with rs1421085 and rs9939609 polymorphisms of FTO gene. Mol Biol Rep 2014; 41: 7381-7386.
21. Ohashi J, Naka I, Kimura R, Natsuhara K, Yamauchi T, Furusawa T, Nakazawa M, Ataka Y, Patarapotikul J, Nuchnoi P, Tokunaga K, Ishida T, Inaoka T, Matsumura Y, Ohtsuka R. FTO polymorphisms in oceanic populations. J Hum Genet 2007; 52: 1031-1035.
22. Macek P, Biskup M, Terek-Derszniak M, Stachura M, Krol H, Gozdz S, Zak M. Optimal body fat percentage cut-off values in predicting the obesity-related cardiovascular risk factors – a cross-sectional cohort study. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2020; 13: 1587-1597.
23. Macek P, Zak M, Terek-Derszniak M, Biskup M, Ciepiela P, Krol H, Smok-Kalwat J, Gozdz S. Age-dependent disparities in the prevalence of single and clustering cardiovascular risk factors: a cross-sectional cohort study in middle-aged and older adults. Clin Interv Aging 2020; 15: 161-169.

Address for correspondence:

Małgorzata Biskup PhD
Department of Rehabilitation
Hollycross Cancer Centre
Kielce, Poland
Phone: +48 606 645 865
E-mail: mbiskup@onet.eu
1. Krekora-Wollny K, Suliga E. Changes in body mass during weight loss treatment – a two-year prospective study. Med Stud 2017; 33: 290-294.
2. Majda A, Zalewska-Puchała J, Kamińska A, Bodys-Cupak I, Suder M. Risk factors for diseases of the cardiovascular system among Catholics living in areas of southern Poland. Med Stud 2017; 33: 88-94.
3. Zara-Lopes T, Galbiatti-Dias LSA, Urbanin Castanhole-Nunes MM, Padovani-Júnior JA, Maniglia JV, Pavarino EC, Goloni-Bertollo EM. Polymorphisms in MTHFR, MTR, RFC1 and CbetaS genes involved in folate metabolism and thyroid cancer: a case-control study. Arch Med Sci 2019; 15: 522-530.
4. Kabała M, Wilczynski J. Otyłość a stabilność posturalna kobiet po mastektomii. Stud Med 2019; 35: 48-54.
5. Kała E, Bodek I, Trelińska O, Gładysz P, Lepiarczyk O, Śmigel A, Gola M, Grzeszczak W. Polymorphism rs7903146 of TCF7L2 gene and occurrence of being overweight and obesity among patients admitted to outpatient clinic. Ann Acad Med Siles 2014; 68: 200-206.
6. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JRB, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW, Barrett JC, Ellard S, Groves CJ, Knight B, Patch AM, Ness AR, Ebrahim S, Lawlor DA, Ring SM, Ben-Shlomo Y, Jarvelin MR, Sovio U, Bennett AJ, Melzer D, Ferrucci L, Loos RJF, Barroso I, Wareham NJ, Karpe F, Owen KR, Cardon LR, Walker M, Hitman GA, Palmer CNA, Doney ASF, Morris AD, Smith GD, The Wellcome Trust Case Control Consortium, Hattersley AT, McCarthy MI. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889-894.
7. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937-948.
8. Larder R, Cheung MKM, Tung YCL, Yeo GSH, Coll AP. Where to go with FTO? Trends Endocrinol Metab 2011; 22: 53-59.
9. Speakman JR, Rance KA, Johnstone AM. Polymorphisms of the FTO gene are associated with variation in energy intake, but not energy expenditure. Obesity 2008; 16: 1961-1965.
10. Speakman JR. The “fat mass and obesity related” (FTO) gene: mechanisms of impact on obesity and energy balance. Curr Obes Rep 2015; 4: 73-91.
11. Ehrlich AC, Friedenberg FK. Genetic associations of obesity: the fat-mass and obesity-associated (FTO) gene citation. Clin Transl Gastroenterol 2016; 7: e140.
12. Woźny Ł, Wojtas E, Chuchmacz G, Maciejiczek J, Karon M, Kandefer B, Śnit M, Grzeszczak W. The effect of rs1421085 polymorphism of FTO gene on progress of hypertension in overweight and obese subjects. Ann Acad Med Siles 2016; 70: 51-55.
13. https://www.snpedia.com/index.php/Rs1421085 (Access from: 15.08.2019).
14. http://browser.1000genomes.org (Access from: 15.08.2019).
15. Kolackov K, Łaczmański Ł, Bednarek-Tupikowska G. Influence of FTO gene polymorphisms on the risk of obesity. Endokrynol Otyłość Zaburzenia Przem Materii 2010; 2: 101-107.
16. Albuquerque D, Nobrega C, Manco L. Association of FTO polymorphisms with obesity and obesity-related outcomes in Portuguese children. PLoS One 2013; 8: e54370.
17. Kopelman P. Health risks associated with overweight and obesity. Obes Rev 2007; 8 Suppl 1: 13-17.
18. Cha SW, Choi SM, Kim KS, Park BL, Kim JR, Kim JY, Shin HD. Replication of genetic effects of FTO polymorphisms on BMI in a Korean population. Obesity 2008; 16: 2187-2189.
19. Dougkas A, Yaqoop P, Givens DI, Reynolds CK, Minihane AM. The impact of obesity-related SNP on appetite and energy intake. Br J Nutr 2013; 110: 1151-1156.
20. Solak M, Erdogan MO, Yildiz SH, Ucok K, Yuksel S, Terzi E, Bestepe A. Association of obesity with rs1421085 and rs9939609 polymorphisms of FTO gene. Mol Biol Rep 2014; 41: 7381-7386.
21. Ohashi J, Naka I, Kimura R, Natsuhara K, Yamauchi T, Furusawa T, Nakazawa M, Ataka Y, Patarapotikul J, Nuchnoi P, Tokunaga K, Ishida T, Inaoka T, Matsumura Y, Ohtsuka R. FTO polymorphisms in oceanic populations. J Hum Genet 2007; 52: 1031-1035.
22. Macek P, Biskup M, Terek-Derszniak M, Stachura M, Krol H, Gozdz S, Zak M. Optimal body fat percentage cut-off values in predicting the obesity-related cardiovascular risk factors – a cross-sectional cohort study. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2020; 13: 1587-1597.
23. Macek P, Zak M, Terek-Derszniak M, Biskup M, Ciepiela P, Krol H, Smok-Kalwat J, Gozdz S. Age-dependent disparities in the prevalence of single and clustering cardiovascular risk factors: a cross-sectional cohort study in middle-aged and older adults. Clin Interv Aging 2020; 15: 161-169.
Copyright: © 2020 Jan Kochanowski University in Kielce This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License (http://creativecommons.org/licenses/by-nc-sa/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
© 2024 Termedia Sp. z o.o.
Developed by Bentus.