Assessing three novel composite anthropometric-metabolic indices for predicting 10-year incidence of metabolic syndrome: findings from the kerman coronary artery disease risk factors study (KERCADRS)

Fahed G, Aoun L, Bou Zerdan M, Allam S, Bou Zerdan M, Bouferraa Y et al (2022) Metabolic Syndrome: Updates on Pathophysiology and Management in 2021. Int J Mol Sci 23(2):786. https://doi.org/10.3390/ijms23020786

Article  CAS  PubMed  PubMed Central  Google Scholar 

Saklayen MG (2018) The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep 20(2):12. https://doi.org/10.1007/s11906-018-0812-z

Article  PubMed  PubMed Central  Google Scholar 

Zafar U, Khaliq S, Ahmad HU, Manzoor S, Lone KP (2018) Metabolic syndrome: an update on diagnostic criteria, pathogenesis, and genetic links. Horm (Athens) 17(3):299–313. https://doi.org/10.1007/s42000-018-0051-3

Article  Google Scholar 

Gesteiro E, Megía A, Guadalupe-Grau A, Fernandez-Veledo S, Vendrell J, González-Gross M (2021) Early identification of metabolic syndrome risk: A review of reviews and proposal for defining pre-metabolic syndrome status. Nutr Metab Cardiovasc Dis 31(9):2557–2574. https://doi.org/10.1016/j.numecd.2021.05.022

Article  CAS  PubMed  Google Scholar 

Ching YK, Chin YS, Appukutty M, Gan WY, Chan YM (2020) Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia. Sci Rep 10(1):20861. https://doi.org/10.1038/s41598-020-78035-5

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wu L, Zhu W, Qiao Q, Huang L, Li Y, Chen L (2021) Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults. Nutr Metab (Lond) 18(1):3. https://doi.org/10.1186/s12986-020-00536-x

Article  CAS  PubMed  Google Scholar 

Mirr M, Skrypnik D, Bogdański P, Owecki M (2021) Newly proposed insulin resistance indexes called TyG-NC and TyG-NHtR show efficacy in diagnosing the metabolic syndrome. J Endocrinol Invest 44(12):2831–2843. https://doi.org/10.1007/s40618-021-01608-2

Article  CAS  PubMed  PubMed Central  Google Scholar 

Motamed N, Khonsari MR, Rabiee B, Ajdarkosh H, Hemasi GR, Sohrabi MR et al (2017) Discriminatory Ability of Visceral Adiposity Index (VAI) in Diagnosis of Metabolic Syndrome: A Population Based Study. Exp Clin Endocrinol Diabetes 125(3):202–207. https://doi.org/10.1055/s-0042-119032

Article  CAS  PubMed  Google Scholar 

Bijari M, Jangjoo S, Emami N, Raji S, Mottaghi M, Moallem R et al (2021) The Accuracy of Visceral Adiposity Index for the Screening of Metabolic Syndrome: A Systematic Review and Meta-Analysis. Int J Endocrinol 2021(6684627). https://doi.org/10.1155/2021/6684627

Khan SH, Sobia F, Niazi NK, Manzoor SM, Fazal N, Ahmad F (2018) Metabolic clustering of risk factors: evaluation of Triglyceride-glucose index (TyG index) for evaluation of insulin resistance. Diabetol Metab Syndr 10:74. https://doi.org/10.1186/s13098-018-0376-8

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chamroonkiadtikun P, Ananchaisarp T, Wanichanon W (2020) The triglyceride-glucose index, a predictor of type 2 diabetes development: A retrospective cohort study. Prim Care Diabetes 14(2):161–167. https://doi.org/10.1016/j.pcd.2019.08.004

Article  PubMed  Google Scholar 

Tao LC, Xu JN, Wang TT, Hua F, Li JJ (2022) Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations. Cardiovasc Diabetol 21(1):68. https://doi.org/10.1186/s12933-022-01511-x

Article  CAS  PubMed  PubMed Central  Google Scholar 

Nabipoorashrafi SA, Seyedi SA, Rabizadeh S, Ebrahimi M, Ranjbar SA, Reyhan SK et al (2022) The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: A systematic review and meta-analysis. Nutr Metab Cardiovasc Dis 32(12):2677–2688. https://doi.org/10.1016/j.numecd.2022.07.024

Article  CAS  PubMed  Google Scholar 

Taverna MJ, Martínez-Larrad MT, Frechtel GD, Serrano-Ríos M (2011) Lipid accumulation product: a powerful marker of metabolic syndrome in healthy population. Eur J Endocrinol 164(4):559–567. https://doi.org/10.1530/eje-10-1039

Article  CAS  PubMed  Google Scholar 

Jafari A, Najafipour H, Shadkam M, Aminizadeh S (2023) Evaluation of the novel three lipid indices for predicting five- and ten-year incidence of cardiovascular disease: findings from Kerman coronary artery disease risk factors study (KERCADRS). Lipids Health Dis 22(1):169. https://doi.org/10.1186/s12944-023-01932-x

Article  CAS  PubMed  PubMed Central  Google Scholar 

Motamed N, Razmjou S, Hemmasi G, Maadi M, Zamani F (2016) Lipid accumulation product and metabolic syndrome: a population-based study in northern Iran, Amol. J Endocrinol Invest 39(4):375–382. https://doi.org/10.1007/s40618-015-0369-5

Article  CAS  PubMed  Google Scholar 

Xia C, Li R, Zhang S, Gong L, Ren W, Wang Z et al (2012) Lipid accumulation product is a powerful index for recognizing insulin resistance in non-diabetic individuals. Eur J Clin Nutr 66(9):1035–1038. https://doi.org/10.1038/ejcn.2012.83

Article  CAS  PubMed  Google Scholar 

Armstrong T, Bull F (2006) Development of the world health organization global physical activity questionnaire (GPAQ). J Public Health 14:66–70

Article  Google Scholar 

Najafipour H, Mirzazadeh A, Haghdoost A, Shadkam M, Afshari M, Moazenzadeh M et al (2012) Coronary Artery Disease Risk Factors in an Urban and Peri-urban Setting, Kerman, Southeastern Iran (KERCADR Study): Methodology and Preliminary Report. Iran J Public Health 41(9):86–92

CAS  PubMed  PubMed Central  Google Scholar 

Kahn HS (2005) The lipid accumulation product performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord 5:26. https://doi.org/10.1186/1471-2261-5-26

Article  PubMed  PubMed Central  Google Scholar 

Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F (2008) The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord 6(4):299–304. https://doi.org/10.1089/met.2008.0034

Article  CAS  PubMed  Google Scholar 

Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M et al (2010) Visceral Adiposity Index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 33(4):920–922. https://doi.org/10.2337/dc09-1825

Article  PubMed  PubMed Central  Google Scholar 

Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, National Heart, Lung, and Blood Institute; American Heart Association (2009) Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention. Circulation 120(16):1640–1645. World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity10.1161/circulationaha.109.192644

Article  CAS  PubMed  Google Scholar 

Gozashti MH, Najmeasadat F, Mohadeseh S, Najafipour H (2014) Determination of most suitable cut off point of waist circumference for diagnosis of metabolic syndrome in Kerman. Diabetes Metab Syndr 8(1):8–12. https://doi.org/10.1016/j.dsx.2013.10.022

Article  PubMed  Google Scholar 

Chiang JK, Koo M (2012) Lipid accumulation product: a simple and accurate index for predicting metabolic syndrome in Taiwanese people aged 50 and over. BMC Cardiovasc Disord 12:78. https://doi.org/10.1186/1471-2261-12-78

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ray L, Ravichandran K, Nanda SK (2018) Comparison of Lipid Accumulation Product Index with Body Mass Index and Waist Circumference as a Predictor of Metabolic Syndrome in Indian Population. Metab Syndr Relat Disord 16(5):240–245. https://doi.org/10.1089/met.2017.0119

Article  PubMed  Google Scholar 

Son DH, Lee HS, Lee YJ, Lee JH, Han JH (2022) Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome. Nutr Metab Cardiovasc Dis 32(3):596–604. https://doi.org/10.1016/j.numecd.2021.11.017

Article  CAS  PubMed  Google Scholar 

Lin HY, Zhang XJ, Liu YM, Geng LY, Guan LY, Li XH (2021) Comparison of the triglyceride glucose index and blood leukocyte indices as predictors of metabolic syndrome in healthy Chinese population. Sci Rep 11(1):10036. https://doi.org/10.1038/s41598-021-89494-9

Article  CAS 

留言 (0)

沒有登入
gif