1. Teede, HJ, Misso, ML, Costello, MF, et al. Recommendations from the international evidence-based guideline for the assessment and management of polycystic ovary syndrome. Hum Reprod 2018; 33: 1602–1618.
Google Scholar | Crossref | Medline2. Rosenfield, RL . Polycystic ovary syndrome and insulin-resistant hyperinsulinemia. J Am Acad Dermatol 2001; 45(Suppl. 3): S95–S104.
Google Scholar | Crossref | Medline3. Tune, JD, Goodwill, AG, Sassoon, DJ, et al. Cardiovascular consequences of metabolic syndrome. Transl Res 2017; 183: 57–70.
Google Scholar | Crossref | Medline4. Legro, RS, Arslanian, SA, Ehrmann, DA, et al. Diagnosis and treatment of polycystic ovary syndrome: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab 2013; 98: 4565–4592.
Google Scholar | Crossref | Medline5. Couto Alves, A, Valcarcel, B, Makinen, VP, et al. Metabolic profiling of polycystic ovary syndrome reveals interactions with abdominal obesity. Int J Obes 2017; 41: 1331–1340.
Google Scholar | Crossref6. Agrawal, H, Aggarwal, K, Jain, A. Visceral adiposity index: simple tool for assessing cardiometabolic risk in women with polycystic ovary syndrome. Indian J Endocrinol Metab 2019; 23: 232–237.
Google Scholar | Crossref | Medline7. Tomas, Z, Skaric-Juric, T, Zajc Petranovic, M, et al. Waist to height ratio is the anthropometric index that most appropriately mirrors the lifestyle and psychological risk factors of obesity. Nutr Diet 2019; 76: 539–545.
Google Scholar | Crossref | Medline8. Paredes, S, Fonseca, L, Ribeiro, L, et al. Novel and traditional lipid profiles in metabolic syndrome reveal a high atherogenicity. Sci Rep 2019; 9: 11792.
Google Scholar | Crossref | Medline9. Ruotolo, G, Howard, BV. Dyslipidemia of the metabolic syndrome. Curr Cardiol Rep 2002; 4: 494–500.
Google Scholar | Crossref | Medline10. Abruzzese, GA, Cerrrone, GE, Gamez, JM, et al. Lipid accumulation product (LAP) and visceral adiposity index (VAI) as markers of insulin resistance and metabolic associated disturbances in young Argentine women with polycystic ovary syndrome. Horm Metab Res 2017; 49: 23–29.
Google Scholar | Medline11. Hosseinpanah, F, Barzin, M, Erfani, H, et al. Lipid accumulation product and insulin resistance in Iranian PCOS prevalence study. Clin Endocrinol 2014; 81: 52–57.
Google Scholar | Crossref | Medline12. Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group . Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertil Steril 2004; 81: 19–25.
Google Scholar | Crossref13. Alberti, KG, Eckel, RH, Grundy, SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120: 1640–1645.
Google Scholar | Crossref | Medline14. Kaluzna, M, Czlapka-Matyasik, M, Wachowiak-Ochmanska, K, et al. Effect of central obesity and hyperandrogenism on selected inflammatory markers in patients with PCOS: a WHtR-matched case-control study. J Clin Med 2020; 9: 3024.
Google Scholar | Crossref15. Friedewald, WT, Levy, RI, Fredrickson, DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18: 499–502.
Google Scholar | Crossref | Medline16. Kahn, HS . The ‘lipid accumulation product’ performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord 2005; 5: 26.
Google Scholar | Crossref | Medline17. Amato, MC, Giordano, C, Galia, M, et al. Visceral adiposity index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 2010; 33: 920–922.
Google Scholar | Crossref | Medline18. Matthews, DR, Hosker, JP, Rudenski, AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412–419.
Google Scholar | Crossref | Medline19. Vekic, J, Zeljkovic, A, Stefanovic, A, et al. Obesity and dyslipidemia. Metabolism 2019; 92: 71–81.
Google Scholar | Crossref | Medline20. Wild, RA, Rizzo, M, Clifton, S, et al. Lipid levels in polycystic ovary syndrome: systematic review and meta-analysis. Fertil Steril 2011; 95: 1073–1079.e1–e11.
Google Scholar | Crossref21. Bajuk Studen, K, Pfeifer, M. Cardiometabolic risk in polycystic ovary syndrome. Endocr Connect 2018; 7: R238–R251.
Google Scholar | Crossref | Medline22. Guleken, Z, Bulut, H, Bulut, B, et al. Assessment of the effect of endocrine abnormalities on biomacromolecules and lipids by FT-IR and biochemical assays as biomarker of metabolites in early Polycystic ovary syndrome women. J Pharm Biomed Anal 2021; 204: 114250.
Google Scholar | Crossref | Medline23. Guleken, Z, Bulut, H, Bahat, PY, et al. Elevated serum level of DHEAS as a hormone and IL-6 as a proinflammatory cytokine may better indicate metabolic syndrome in PCOS women. J Med Physiol Biophys 2021; 71: 5–11.
Google Scholar24. Guo, M, Chen, ZJ, Macklon, NS, et al. Cardiovascular and metabolic characteristics of infertile Chinese women with PCOS diagnosed according to the Rotterdam consensus criteria. Reprod Biomed Online 2010; 21: 572–580.
Google Scholar | Crossref | Medline25. Rossi, B, Sukalich, S, Droz, J, et al. Prevalence of metabolic syndrome and related characteristics in obese adolescents with and without polycystic ovary syndrome. J Clin Endocrinol Metab 2008; 93: 4780–4786.
Google Scholar | Crossref | Medline26. Gu, Z, Zhu, P, Wang, Q, et al. Obesity and lipid-related parameters for predicting metabolic syndrome in Chinese elderly population. Lipids Health Dis 2018; 17: 289.
Google Scholar | Crossref | Medline27. Hosmer, DW, Lemeshow, S. Applied logistic regression. 2nd ed. New York: Wiley, 2000.
Google Scholar | Crossref28. Unluturk, U, Sezgin, E, Yildiz, BO. Evolutionary determinants of polycystic ovary syndrome: part 1. Fertil Steril 2016; 106: 33–41.
Google Scholar | Crossref | Medline29. Austin, PC . An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46: 399–424.
Google Scholar | Crossref | Medline30. Bozic-Antic, I, Ilic, D, Bjekic-Macut, J, et al. Lipid accumulation product as a marker of cardiometabolic susceptibility in women with different phenotypes of polycystic ovary syndrome. Eur J Endocrinol 2016; 175: 551–560.
Google Scholar | Crossref | Medline31. Bil, E, Dilbaz, B, Cirik, DA, et al. Metabolic syndrome and metabolic risk profile according to polycystic ovary syndrome phenotype. J Obstet Gynaecol Res 2016; 42: 837–843.
Google Scholar | Crossref | Medline32. Ehsani, B, Moslehi, N, Mirmiran, P, et al. A visceral adiposity index-related dietary pattern and the cardiometabolic profiles in women with polycystic ovary syndrome. Clin Nutr 2016; 35: 1181–1187.
Google Scholar | Crossref | Medline33. de Medeiros, SF, de Medeiros, MAS, Barbosa, BB, et al. The role of visceral adiposity index as predictor of metabolic syndrome in obese and nonobese women with polycystic ovary syndrome. Metab Syndr Relat Disord 2021; 19: 18–25.
Google Scholar | Crossref | Medline34. Bronczyk-Puzon, A, Jagielski, P, Kulik-Kupka, K, et al. Usefulness of a new anthropometric indicator – VAI (visceral adiposity index) in the evaluation of metabolic and hormonal disorders in women with polycystic ovary syndrome. Adv Clin Exp Med 2017; 26: 825–828.
Google Scholar | Crossref | Medline35. Rashid, N, Nigam, A, Kauser, S, et al. Assessment of insulin resistance and metabolic syndrome in young reproductive aged women with polycystic ovarian syndrome: analogy of surrogate indices. Arch Physiol Biochem. Epub ahead of print 8 February 2020. DOI: 10.1080/13813455.2020.1724157.
Google Scholar | Crossref | Medline36. Macut, D, Bozic Antic, I, Bjekic-Macut, J, et al. Lipid accumulation product is associated with metabolic syndrome in women with polycystic ovary syndrome. Hormones 2016; 15: 35–44.
Google Scholar | Crossref | Medline37. Echiburu, B, Crisosto, N, Maliqueo, M, et al. Metabolic profile in women with polycystic ovary syndrome across adult life. Metabolism 2016; 65: 776–782.
Google Scholar | Crossref | Medline38. Tola, EN, Yalcin, SE, Dugan, N. The predictive effect of inflammatory markers and lipid accumulation product index on clinical symptoms associated with polycystic ovary syndrome in nonobese adolescents and younger aged women. Eur J Obstet Gynecol Reprod Biol 2017; 214: 168–172.
Google Scholar | Crossref | Medline39. Behboudi-Gandevani, S, Ramezani Tehrani, F, Cheraghi, L, et al. Could ‘a body shape index’ and ‘waist to height ratio’ predict insulin resistance and metabolic syndrome in polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 2016; 205: 110–114.
Google Scholar | Crossref | Medline40. Costa, EC, Sa, JC, Soares, EM, et al. Anthropometric indices of central obesity how discriminators of metabolic syndrome in Brazilian women with polycystic ovary syndrome. Gynecol Endocrinol 2012; 28: 12–15.
Google Scholar | Crossref | Medline41. Techatraisak, K, Wongmeerit, K, Dangrat, C, et al. Measures of body adiposity and visceral adiposity index as predictors of metabolic syndrome among Thai women with PCOS. Gynecol Endocrinol 2016; 32: 276–280.
Google Scholar | Crossref | Medline42. Yuan, C, Liu, X, Mao, Y, et al. Polycystic ovary syndrome patients with high BMI tend to have functional disorders of androgen excess: a prospective study. J Biomed Res 2016; 30: 197–202.
Google Scholar | Medline43. Wohlfahrt-Veje, C, Tinggaard, J, Winther, K, et al. Body fat throughout childhood in 2647 healthy Danish children: agreement of BMI, waist circumference, skinfolds with dual X-ray absorptiometry. Eur J Clin Nutr 2014; 68: 664–670.
Google Scholar | Crossref | Medline44. World Health Organization . Obesity: preventing and managing the global epidemic. Geneva: World Health Organization, 1998.
Google Scholar45. Borrayo, G, Basurto, L, Gonzalez-Escudero, E, et al. Tg/HDL-C ratio as cardio-metabolic biomarker even in normal weight women. Acta Endocrinol 2018; 14: 261–267.
Google Scholar46. Song do, K, Lee, H, Sung, YA, et al. Triglycerides to high-density lipoprotein cholesterol ratio can predict impaired glucose tolerance in young women with polycystic ovary syndrome. Yonsei Med J 2016; 57: 1404–1411.
Google Scholar | Crossref | Medline47. Chu, SY, Jung, JH, Park, MJ, et al. Risk assessment of metabolic syndrome in adolescents using the triglyceride/high-density lipoprotein cholesterol ratio and the total cholesterol/high-density lipoprotein cholesterol ratio. Ann Pediatr Endocrinol Metab 2019; 24: 41–48.
Google Scholar | Crossref | Medline48. Karli, S, Kiranmayi, VS, Namburi, RP, et al. Association of triglycerides/high density lipoprotein cholesterol ratio with insulin resistance in polycystic ovary syndrome. Int J Res Med Sci 2018; 6: 4028.
Google Scholar | Crossref49. Abbasian, M, Delvarianzadeh, M, Ebrahimi, H, et al. Lipid ratio as a suitable tool to identify individuals with MetS risk: a case-control study. Diabetes Metab Syndr 2017; 11(Suppl. 1): S15–S19.
Google Scholar | Crossref | Medline50. Rizzo, M, Longo, RA, Guastella, E, et al. Assessing cardiovascular risk in Mediterranean women with polycystic ovary syndrome. J Endocrinol Invest 2011; 34: 422–426.
Google Scholar | Crossref |