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Metabolic disturbances in sedentary and active Polish male students with normal body mass index and waist circumference


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Bajpai A. (2022) Waist-to-Height Ratio-Time for a New Obesity Metric? Indian J. Pediatr., 89(6): 534-535. DOI: 10.1007/s12098-022-04173-5. Search in Google Scholar

Benatar J.R., Stewart R.A.H. (2018) Cardiometabolic risk factors in vegans; A meta-analysis of observational studies. PLoS One. 13(12): e0209086. DOI: 10.1371/journal. pone.0209086. Search in Google Scholar

Bochenek T., Godman B., Lipowska K., Mikrut K., Zuziak S., Pedzisz M., Nowak A., Pilc A. (2016) Over-the-counter medicine and dietary supplement consumption among academic youth in Poland. Expert. Rev. Pharmacoecon Outcomes Res., 16(2): 199-205. DOI: 10.1586/14737167.2016.1154790. Search in Google Scholar

Chen Q., Zhou Y., Dai C., Zhao G., Zhu Y., Zhang X. (2021) Metabolically Abnormal But Normal-Weight Individuals Had a Higher Risk of Type 2 Diabetes Mellitus in a Cohort Study of a Chinese Population. Front Endocrinol. (Lausanne). 12: 724873. DOI: 10.3389/fendo.2021.724873. Search in Google Scholar

Corbin L.J., Timpson N.J. (2016) Body mass index: Has epidemiology started to break down causal contributions to health and disease? Obesity (Silver Spring). 24(8): 1630-1638. DOI: 10.1002/oby.21554. Search in Google Scholar

Csige I., Ujvárosy D., Szabó Z., Lőrincz I., Paragh G., Harangi M., Somodi S. (2018) The Impact of Obesity on the Cardiovascular System. J. Diabetes Res., 2018: 3407306. DOI: 10.1155/2018/3407306. Search in Google Scholar

Du X.M., Kim M.J., Hou L., Le Goff W., Chapman M.J., Van Eck M., Curtiss L.K., Burnett J.R. et al. (2015) HDL particle size is a critical determinant of ABCA1-mediated macrophage cellular cholesterol export. Circ. Res., 116(7): 1133-1142. DOI: 10.1161/CIRCRESAHA.116.305485. Search in Google Scholar

Durnin J.V., Womersley J. (1974) Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br. J. Nutr., 32(1): 77-97. DOI: 10.1079/bjn19740060. Search in Google Scholar

Friedewald W.T., Levy R.I., Fredrickson D.S. (1972) Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin. Chem., 18(6): 499-502. PMID: 4337382. Search in Google Scholar

Gacek M., Kosiba G., Wojtowicz A. (2020) Frequency of consuming selected product groups among Polish and Spanish physical education students. Rocz. Panstw. Zakl. Hig. 71(3): 261-270. DOI: 10.32394/rpzh.2020.0121. Search in Google Scholar

Gao P., Wen X., Ou Q., Zhang J. (2022) Which one of LDL-C /HDL-C ratio and non-HDL-C can better predict the severity of coronary artery disease in STEMI patients. BMC Cardiovasc. Disord., 22(1): 318. DOI: 10.1186/s12872-022-02760-0. Search in Google Scholar

Gayoso-Diz P., Otero-González A., Rodriguez-Alvarez M.X., Gude F., García F., De Francisco A., Quintela A.G. (2013) Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr. Disord., 13: 47. DOI: 10.1186/1472-6823-13-47. Search in Google Scholar

Gažarová M., Galšneiderová M., Mečiarová L. (2019) Obesity diagnosis and mortality risk based on a body shape index (ABSI) and other indices and anthropometric parameters in university students. Rocz Panstw Zakl Hig. 70(3):267-275. DOI: 10.32394/rpzh.2019.0077. Search in Google Scholar

Grundy S.M. (2015) Adipose tissue and metabolic syndrome: too much, too little or neither. Eur. J. Clin. Invest., 45(11): 1209-1217. DOI: 10.1111/eci.12519. Search in Google Scholar

Hales C.M., Fryar C.D., Carrol M.D., Ogden C.L. (2018) Trends in obesity and severe obesity prevalence in US youth and adults by sex and age. 2007–2008 to 2015–2018. JAMA, 339: 1723-1725. DOI: 10.1001/jama.2018.3060. Search in Google Scholar

Holme I., Aastveit A.H., Jungner I., Walldius G. (2008) Relationships between lipoprotein components and risk of myocardial infarction: age, gender and short versus longer follow-up periods in the Apolipoprotein MOrtality RISk study (AMORIS). J. Intern. Med., 264(1): 30-38. DOI: 10.1111/j.1365-2796.2008.01925.x. Search in Google Scholar

International Diabetes Federation. Global Guidelines for type 2 diabetes. https://www.idf.org. Search in Google Scholar

Kelishadi R., Poursafa P. (2014) A review on the genetic, environmental, and lifestyle aspects of the early-life origins of cardiovascular disease. Curr. Probl. Pediatr. Adolesc. Health Care, 44(3): 54-72. DOI: 10.1016/j. cppeds.2013.12.005. Search in Google Scholar

Kuznetsova T. (2018) Sex Differences in Epidemiology of Cardiac and Vascular Disease. Adv. Exp. Med. Biol., 1065: 61-70. DOI: 10.1007/978-3-319-77932-4_4. Search in Google Scholar

Lee J.J., Pedley A., Therkelsen K.E., Hoffman U., Massaro J.M., Levy D., Long M.T. (2017) Upper body sub-cutaneous fat is associated with cardiometabolic risk factors. Am. J. Med., 130: 958-966. DOI: 10.1016/j.amj-DOI: 10.1016/j.amj-med.2017.01.044. Search in Google Scholar

Liu H., Liu J., Liu J., Xin S., Lyu Z., Fu X. (2022) Triglyceride to High-Density Lipoprotein Cholesterol (TG/HDL-C) Ratio, a Simple but Effective Indicator in Predicting Type 2 Diabetes Mellitus in Older Adults. Front. Endocrinol. (Lausanne). 13: 828581. DOI: 10.3389/fendo.2022.828581. Search in Google Scholar

Malakar A.K., Choudhury D., Halder B., Paul P., Uddin A., Chakraborty S. (2019) A review on coronary artery disease, its risk factors, and therapeutics. J. Cell Physiol., 234(10): 16812-16823. DOI: 10.1002/jcp.28350. Search in Google Scholar

Matsumoto I., Misaki A., Kurozumi M., Nanba T., Takagi Y. (2018) Impact of nonfasting triglycerides/high-density lipoprotein cholesterol ratio on secondary prevention in patients treated with statins. J. Cardiol., 71: 10-15. DOI: 10.1016/j.jjcc.2017.07.012. Search in Google Scholar

Matthews D.R., Hosker J.P., Rudenski A.S., Naylor B.A., Treacher D.F., Turner R.C. (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 28(7): 412-419. DOI: 10.1007/BF00280883. Search in Google Scholar

Mehta P., Tawfeeq S., Padte S., Sunasra R., Desai H., Surani S., Kashyap R. (2023) Plant-based diet and its effect on coronary artery disease: A narrative review. World J. Clin. Cases, 11(20): 4752-4762. DOI: 10.12998/wjcc. v11.i20.4752. Search in Google Scholar

Millán J., Pintó X., Muñoz A., Zúñiga M., Rubiés-Prat J., Pallardo L.F., Masana L., Mangas A. et al. (2009) Lipoprotein ratios: Physiological significance and clinical usefulness in cardiovascular prevention. Vasc. Health Risk Manag., 5: 757-765. DOI: 10.2147/VHRM.S6269. Search in Google Scholar

Nishida C., Ko G.T., Kumanyika S. (2010) Body fat distribution and noncommunicable diseases in populations: overview of the 2008 WHO Expert Consultation on Waist Circumference and Waist-Hip Ratio. Eur. J. Clin. Nutr., 64(1): 2-5. DOI: 10.1038/ejcn.2009.139. Search in Google Scholar

Nordestgaard B.G., Langsted A., Mora S., Kolovou G., Baum H., Bruckert E., Watts G.F., Sypniewska G. et al. (2016) Fasting Is Not Routinely Required for Determination of a Lipid Profile: Clinical and Laboratory Implications Including Flagging at Desirable Concentration Cutpoints-A Joint Consensus Statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine. Clin. Chem., 62(7): 930-946. DOI: 10.1373/clin-10.1373/clin-chem.2016.258897. Search in Google Scholar

Padwal R., Leslie W.D., Lix L.M., Majumdar S.R. (2016) Relationship among body fat percentage, body mass index, and all-cause mortality. Ann. Intern. Med., 164: 532-541. DOI: 10.7326/M15-1181. Search in Google Scholar

Piché M.E., Vasan S.K., Hodson L., Karpe F. (2018) Relevance of human fat distribution on lipid and lipo-protein metabolism and cardiovascular disease risk. Curr. Opin. Lipidol., 29(4): 285-292. DOI: 10.1097/MOL.0000000000000522. Search in Google Scholar

Seo D.C., Choe S., Torabi M.R. (2017) Is waist circumference ≥102/88cm better than body mass index ≥30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Prev. Med., 97: 100-108. DOI: 10.1016/j.ypmed.2017.01.012. Search in Google Scholar

Stefanescu A., Revilla L., Lopez T., Sanchez S.E., Williams M.A., Gelaye B. (2020) Using A Body Shape Index (ABSI) and Body Roundness Index (BRI) to predict risk of metabolic syndrome in Peruvian adults. J. Int. Med. Res., 48(1): 300060519848854. DOI: 10.1177/0300060519848854. Search in Google Scholar

Tian S., Zhang X., Xu Y., Dong H. (2016) Feasibility of body roundness index for identifying a clustering of cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices: the China Health and Nutrition Survey, 2008 to 2009. Medicine (Baltimore). 95(34): e4642. DOI: 10.1097/MD.0000000000004642. Search in Google Scholar

Tomiyama A.J., Hunger J.M., Nguyen-Cuu J., Wells C. (2016) Misclassification of cardiometabolic health when using body mass index categories in NHANES 2005-2012. Int. J. Obes. (Lond). 40(5): 883-886. DOI: 10.1038/ijo.2016.17. Search in Google Scholar

Tucker W.J., Fegers-Wustrow I., Halle M., Haykowsky M.J., Chung E.H., Kovacic J.C. (2022) Exercise for Primary and Secondary Prevention of Cardiovascular Disease: JACC Focus Seminar 1/4. J. Am. Coll. Cardiol., 80(11): 1091-1106. DOI: 10.1016/j.jacc.2022.07.004. Search in Google Scholar

Urbina E.M., McCoy C.E., Gao Z., Khoury P.R., Shah A.S., Dolan L.M., Kimball T.R. (2017) Lipoprotein particle number and size predict vascular structure and function better than traditional lipids in adolescents and young adults. J. Clin. Lipidol., 11(4): 1023-1031. DOI: 10.1016/j.jacl.2017.05.011. Search in Google Scholar

Vega G.L., Barlow C.E., Grundy S.M., Leonard D., DeFina L.F. (2014) Triglyceride-to-high-density-lipo-protein-cholesterol ratio is an index of heart disease mortality and of incidence of type 2 diabetes mellitus in men. J. Investig. Med., 62(2): 345-349. DOI: 10.2310/JIM.0000000000000044. Search in Google Scholar

Walli-Attaei M., Joseph P., Rosengren A., Chow C.K., Rangarajan S., Lear S.A., AlHabib K.F., Davletov K. et al. (2020) Variations between women and men in risk factors, treatments, cardiovascular disease incidence, and death in 27 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet, 396(10244): 97-109. DOI: 10.1016/S0140-6736-(20)30543-2. Search in Google Scholar

Weir C.B., Jan A. (2023) BMI Classification Percentile And Cut Off Points. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2023 Jan–. Bookshelf ID:. NBK541070. PMID: 31082114. Search in Google Scholar

Winzer E.B., Woitek F., Linke A. (2018) Physical Activity in the Prevention and Treatment of Coronary Artery Disease. J. Am. Heart Assoc., 7(4): e007725. DOI: 10.1161/JAHA.117.007725. Search in Google Scholar

Wojtyniak B., Goryński P. red. (2020) Sytuacja zdrowotna ludności Polski i jej uwarunkowania. Raport. https://www.pzh.gov.pl/download/21980/ Search in Google Scholar

Wong C.X., Brown A., Lau D.H., Chugh S.S., Albert C.M., Kalman J.M., Sanders P. (2019) Epidemiology of Sudden Cardiac Death: Global and Regional Perspectives. Heart Lung. Circ., 28(1): 6-14. DOI: 10.1016/j. hlc.2018.08.026. Search in Google Scholar

Zhou Y., Zhang X., Zhang L., Li Z., Wu Q., Jin Z., Chen S., He D. et al. (2021) Increased Stroke Risk in Metabolically Abnormal Normal Weight: a 10-Year Follow-up of 102,037 Participants in China. Transl. Stroke Res., 12(5): 725-734. DOI: 10.1007/s12975-020-00866-1. Search in Google Scholar

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