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

Biomedical Human Kinetics
Volume 16 (2024): Issue 1 (January 2024)
By:
Open Access
|Dec 2023

References

  1. 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 ScholarBack to article
  2. 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 ScholarBack to article
  3. 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 ScholarBack to article
  4. 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 ScholarBack to article
  5. 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 ScholarBack to article
  6. 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 ScholarBack to article
  7. 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 ScholarBack to article
  8. 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 ScholarBack to article
  9. 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 ScholarBack to article
  10. 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 ScholarBack to article
  11. 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 ScholarBack to article
  12. 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 ScholarBack to article
  13. 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 ScholarBack to article
  14. 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 ScholarBack to article
  15. 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 ScholarBack to article
  16. 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 ScholarBack to article
  17. International Diabetes Federation. Global Guidelines for type 2 diabetes. https://www.idf.org.
    Search in Google ScholarBack to article
  18. 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 ScholarBack to article
  19. 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 ScholarBack to article
  20. 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 ScholarBack to article
  21. 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 ScholarBack to article
  22. 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 ScholarBack to article
  23. 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 ScholarBack to article
  24. 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 ScholarBack to article
  25. 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 ScholarBack to article
  26. 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 ScholarBack to article
  27. 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 ScholarBack to article
  28. 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 ScholarBack to article
  29. 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 ScholarBack to article
  30. 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 ScholarBack to article
  31. 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 ScholarBack to article
  32. 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 ScholarBack to article
  33. 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 ScholarBack to article
  34. 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 ScholarBack to article
  35. 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 ScholarBack to article
  36. 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 ScholarBack to article
  37. 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 ScholarBack to article
  38. 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 ScholarBack to article
  39. 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 ScholarBack to article
  40. 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 ScholarBack to article
  41. Wojtyniak B., Goryński P. red. (2020) Sytuacja zdrowotna ludności Polski i jej uwarunkowania. Raport. https://www.pzh.gov.pl/download/21980/
    Search in Google ScholarBack to article
  42. 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 ScholarBack to article
  43. 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 ScholarBack to article
DOI: https://doi.org/10.2478/bhk-2024-0002 | Journal eISSN: 2080-2234
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Language: English
Page range: 12 - 18
Submitted on: Sep 20, 2023
Accepted on: Nov 26, 2023
Published on: Dec 30, 2023
Published by: University of Physical Education in Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Metabolic disturbances,
Lipoproteins,
Insulin,
Glucose,
Physical activity
Related subjects:
Medicine,
Basic medical science,
Basic medical science, other,
Clinical medicine,
Public health,
Sports and recreation,
Sports and recreation, other,
Physical education

© 2023 Marzena Malara, Patrycja Widłak, published by University of Physical Education in Warsaw
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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