Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global Burden of Cardiovascular Diseases and Risk factors, 1990–2019: Update from the GBD 2019 study. J Am Coll Cardiol. 2020;76(25):2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010.
Article PubMed PubMed Central Google Scholar
Global regional. National age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the global burden of Disease Study 2017. Lancet. 2018;392(10159):1736–88. https://doi.org/10.1016/s0140-6736(18)32203-7.
Kim HC. Epidemiology of cardiovascular disease and its risk factors in Korea. Glob Health Med. 2021;3(3):134–41. https://doi.org/10.35772/ghm.2021.01008.
Article PubMed PubMed Central Google Scholar
Beaglehole R, Bonita R, Horton R, Adams C, Alleyne G, Asaria P, et al. Priority actions for the non-communicable disease crisis. Lancet. 2011;377(9775):1438–47. https://doi.org/10.1016/s0140-6736(11)60393-0.
Gheorghe A, Griffiths U, Murphy A, Legido-Quigley H, Lamptey P, Perel P. The economic burden of cardiovascular disease and hypertension in low- and middle-income countries: a systematic review. BMC Public Health. 2018;18(1):975. https://doi.org/10.1186/s12889-018-5806-x.
Article PubMed PubMed Central Google Scholar
Pereira E, Pereira H. Socioeconomic impact of cardiovascular disease. Revista Portuguesa de Cardiologia (English edition). 2020;39(5):253–4. https://doi.org/10.1016/j.repce.2020.10.006.
Magnus P, Beaglehole R. The real contribution of the major risk factors to the coronary epidemics: time to end the only-50% myth. Arch Intern Med. 2001;161(22):2657–60. https://doi.org/10.1001/archinte.161.22.2657.
Article CAS PubMed Google Scholar
Jee SH, Jang Y, Oh DJ, Oh BH, Lee SH, Park SW, et al. A coronary heart disease prediction model: the Korean Heart Study. BMJ Open. 2014;4(5):e005025. https://doi.org/10.1136/bmjopen-2014-005025.
Article PubMed PubMed Central Google Scholar
Cho SMJ, Lee H, Lee HH, Baek J, Heo JE, Joo HJ, et al. Dyslipidemia Fact Sheets in Korea 2020: an analysis of Nationwide Population-based data. J Lipid Atheroscler. 2021;10(2):202–9. https://doi.org/10.12997/jla.2021.10.2.202.
Article CAS PubMed PubMed Central Google Scholar
Ikezaki H, Lim E, Cupples LA, Liu CT, Asztalos BF, Schaefer EJ. Small dense low-density lipoprotein cholesterol is the most atherogenic lipoprotein parameter in the prospective Framingham offspring study. J Am Heart Assoc. 2021;10(5):e019140. https://doi.org/10.1161/jaha.120.019140.
Article CAS PubMed PubMed Central Google Scholar
Kanonidou C. Small dense low-density lipoprotein: Analytical review. Clin Chim Acta. 2021;520:172–8. https://doi.org/10.1016/j.cca.2021.06.012.
Article CAS PubMed Google Scholar
Dobiásová M, Frohlich J. [The new atherogenic plasma index reflects the triglyceride and HDL-cholesterol ratio, the lipoprotein particle size and the cholesterol esterification rate: changes during lipanor therapy]. Vnitr Lek. 2000;46(3):152–6.
Choudhary MK, Eräranta A, Koskela J, Tikkakoski AJ, Nevalainen PI, Kähönen M, et al. Atherogenic index of plasma is related to arterial stiffness but not to blood pressure in normotensive and never-treated hypertensive subjects. Blood Press. 2019;28(3):157–67. https://doi.org/10.1080/08037051.2019.1583060.
Article CAS PubMed Google Scholar
Dobiásová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apob-lipoprotein-depleted plasma (FER(HDL)). Clin Biochem. 2001;34(7):583–8. https://doi.org/10.1016/s0009-9120(01)00263-6.
Burns SF, Lee SJ, Arslanian SA. Surrogate lipid markers for small dense low-density lipoprotein particles in overweight youth. J Pediatr. 2012;161(6):991–6. https://doi.org/10.1016/j.jpeds.2012.06.013.
Article CAS PubMed PubMed Central Google Scholar
Dobiásová M, Frohlich J, Sedová M, Cheung MC, Brown BG. Cholesterol esterification and atherogenic index of plasma correlate with lipoprotein size and findings on coronary angiography. J Lipid Res. 2011;52(3):566–71. https://doi.org/10.1194/jlr.P011668.
Article CAS PubMed PubMed Central Google Scholar
Dobiásová M. [AIP–atherogenic index of plasma as a significant predictor of cardiovascular risk: from research to practice]. Vnitr Lek. 2006;52(1):64–71.
Hetherington E, Plamondon A, Williamson T. Trajectory modeling with latent groups: potentials and pitfalls. Curr Epidemiol Rep. 2020;7(4):171–8. https://doi.org/10.1007/s40471-020-00242-5.
Kwon J-Y, Sawatzky R, Baumbusch J, Lauck S, Ratner PA. Growth mixture models: a case example of the longitudinal analysis of patient-reported outcomes data captured by a clinical registry. BMC Med Res Methodol. 2021;21(1):79. https://doi.org/10.1186/s12874-021-01276-z.
Article PubMed PubMed Central Google Scholar
Song M, Hu FB, Wu K, Must A, Chan AT, Willett WC, et al. Trajectory of body shape in early and middle life and all cause and cause specific mortality: results from two prospective US cohort studies. BMJ. 2016;353:i2195. https://doi.org/10.1136/bmj.i2195.
Article PubMed PubMed Central Google Scholar
Allen NB, Siddique J, Wilkins JT, Shay C, Lewis CE, Goff DC, et al. Blood pressure trajectories in early adulthood and subclinical atherosclerosis in middle age. JAMA. 2014;311(5):490–7. https://doi.org/10.1001/jama.2013.285122.
Article CAS PubMed PubMed Central Google Scholar
Yang S, Kwak S, Song Y-H, Han SS, Lee HS, Kang S, et al. Association of longitudinal trajectories of insulin resistance with adverse renal outcomes. Diabetes Care. 2022;45(5):1268–75. https://doi.org/10.2337/dc21-2521.
Baik I, Cho NH, Kim SH, Shin C. Dietary information improves cardiovascular disease risk prediction models. Eur J Clin Nutr. 2013;67(1):25–30. https://doi.org/10.1038/ejcn.2012.175.
Article CAS PubMed Google Scholar
Seo MH, Lee WY, Kim SS, Kang JH, Kang JH, Kim KK, et al. 2018 korean Society for the study of obesity Guideline for the management of obesity in Korea. J Obes Metab Syndr. 2019;28(1):40–5. https://doi.org/10.7570/jomes.2019.28.1.40.
Article PubMed PubMed Central Google Scholar
Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9 Suppl):498–504. https://doi.org/10.1097/00005768-200009001-00009.
Jang M, Won C, Choi H, Kim S, Park W, Kim D, et al. Effects of physical activity on fractures in adults: A Community-Based korean Cohort Study. Korean J Sports Med. 2017;35(2):97–102. https://doi.org/10.5763/kjsm.2017.35.2.97.
2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020;43(Suppl 1):14–s31. https://doi.org/10.2337/dc20-S002.
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, et al. Seventh report of the Joint National Committee on Prevention, detection, evaluation, and treatment of high blood pressure. Hypertension. 2003;42(6):1206–52. https://doi.org/10.1161/01.HYP.0000107251.49515.c2.
Article CAS PubMed Google Scholar
Joint committee for guideline r. 2016 Chinese guidelines for the management of dyslipidemia in adults. J Geriatr Cardiol. 2018;15(1):1–29. https://doi.org/10.11909/j.issn.1671-5411.2018.01.011.
Cure MC, Tufekci A, Cure E, Kirbas S, Ogullar S, Kirbas A, et al. Low-density lipoprotein subfraction, carotid artery intima-media thickness, nitric oxide, and tumor necrosis factor alpha are associated with newly diagnosed ischemic stroke. Ann Indian Acad Neurol. 2013;16(4):498–503. https://doi.org/10.4103/0972-2327.120438.
Article PubMed PubMed Central Google Scholar
Onat A, Can G, Kaya H, Hergenç G. Atherogenic index of plasma (log10 triglyceride/high-density lipoprotein-cholesterol) predicts high blood pressure, diabetes, and vascular events. J Clin Lipidol. 2010;4(2):89–98. https://doi.org/10.1016/j.jacl.2010.02.005.
Fernández-Macías JC, Ochoa-Martínez AC, Varela-Silva JA, Pérez-Maldonado IN. Atherogenic index of plasma: Novel Predictive Biomarker for Cardiovascular Illnesses. Arch Med Res. 2019;50(5):285–94. https://doi.org/10.1016/j.arcmed.2019.08.009.
Article CAS PubMed Google Scholar
Kim JJ, Yoon J, Lee YJ, Park B, Jung DH. Predictive value of the Atherogenic Index of plasma (AIP) for the risk of Incident Ischemic Heart Disease among non-diabetic Koreans. Nutrients. 2021;13(9). https://doi.org/10.3390/nu13093231.
Sadeghi M, Heshmat-Ghahdarijani K, Talaei M, Safaei A, Sarrafzadegan N, Roohafza H. The predictive value of atherogenic index of plasma in the prediction of cardiovascular events; a fifteen-year cohort study. Adv Med Sci. 2021;66(2):418–23. https://doi.org/10.1016/j.advms.2021.09.003.
Nagin DS. Group-based trajectory modeling: an overview. Ann Nutr Metab. 2014;65(2–3):205–10. https://doi.org/10.1159/000360229.
Article CAS PubMed Google Scholar
McFarlane SI, Banerji M, Sowers JR. Insulin resistance and cardiovascular disease. J Clin Endocrinol Metab. 2001;86(2):713–8. https://doi.org/10.1210/jcem.86.2.7202.
Comments (0)