These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
110 related articles for article (PubMed ID: 30548993)
1. Peripheral fat distribution versus waist circumference for predicting mortality in metabolic syndrome. Wu CJ; Kao TW; Chen YY; Yang HF; Chen WL Diabetes Metab Res Rev; 2019 May; 35(4):e3116. PubMed ID: 30548993 [TBL] [Abstract][Full Text] [Related]
2. Does the Additional Component of Calf Circumference Refine Metabolic Syndrome in Correlating With Cardiovascular Risk? Wu CJ; Kao TW; Chang YW; Peng TC; Wu LW; Yang HF; Chen WL J Clin Endocrinol Metab; 2018 Mar; 103(3):1151-1160. PubMed ID: 29346655 [TBL] [Abstract][Full Text] [Related]
3. Neck circumference as a simple tool for identifying the metabolic syndrome and insulin resistance: results from the Brazilian Metabolic Syndrome Study. Stabe C; Vasques AC; Lima MM; Tambascia MA; Pareja JC; Yamanaka A; Geloneze B Clin Endocrinol (Oxf); 2013 Jun; 78(6):874-81. PubMed ID: 22804918 [TBL] [Abstract][Full Text] [Related]
4. Optimal waist circumference cutoff values for predicting metabolic syndrome among older adults in Ecuador. Orces CH; Montalvan M; Tettamanti D Diabetes Metab Syndr; 2019; 13(2):1015-1020. PubMed ID: 31336437 [TBL] [Abstract][Full Text] [Related]
5. Associations between metabolic syndrome components and markers of inflammation in Welsh school children. Thomas NE; Rowe DA; Murtagh EM; Stephens JW; Williams R Eur J Pediatr; 2018 Mar; 177(3):409-417. PubMed ID: 29273941 [TBL] [Abstract][Full Text] [Related]
6. Healthy Chilean Adolescents with HOMA-IR ≥ 2.6 Have Increased Cardiometabolic Risk: Association with Genetic, Biological, and Environmental Factors. Burrows R; Correa-Burrows P; Reyes M; Blanco E; Albala C; Gahagan S J Diabetes Res; 2015; 2015():783296. PubMed ID: 26273675 [TBL] [Abstract][Full Text] [Related]
7. Metabolic syndrome in men with low testosterone levels: relationship with cardiovascular risk factors and comorbidities and with erectile dysfunction. García-Cruz E; Leibar-Tamayo A; Romero J; Piqueras M; Luque P; Cardeñosa O; Alcaraz A J Sex Med; 2013 Oct; 10(10):2529-38. PubMed ID: 23898860 [TBL] [Abstract][Full Text] [Related]
8. Optimal Cutoffs of Cardiometabolic Risk for Postmenopausal Korean Women. Kim HR; Kim HS Asian Nurs Res (Korean Soc Nurs Sci); 2017 Jun; 11(2):107-112. PubMed ID: 28688495 [TBL] [Abstract][Full Text] [Related]
9. Waist circumference alone predicts insulin resistance as good as the metabolic syndrome in elderly women. Nilsson G; Hedberg P; Jonason T; Lönnberg I; Tenerz A; Forberg R; Ohrvik J Eur J Intern Med; 2008 Nov; 19(7):520-6. PubMed ID: 19013381 [TBL] [Abstract][Full Text] [Related]
10. Gender- and race-specific metabolic score and cardiovascular disease mortality in adults: A structural equation modeling approach--United States, 1988-2006. Mercado CI; Yang Q; Ford ES; Gregg E; Valderrama AL Obesity (Silver Spring); 2015 Sep; 23(9):1911-9. PubMed ID: 26308480 [TBL] [Abstract][Full Text] [Related]
11. Associations of sarcopenic obesity with the metabolic syndrome and insulin resistance over five years in older men: The Concord Health and Ageing in Men Project. Scott D; Cumming R; Naganathan V; Blyth F; Le Couteur DG; Handelsman DJ; Seibel M; Waite LM; Hirani V Exp Gerontol; 2018 Jul; 108():99-105. PubMed ID: 29649572 [TBL] [Abstract][Full Text] [Related]
12. Cut-off values of waist circumference to predict metabolic syndrome in obese adolescents. Masquio DC; Ganen Ade P; Campos RM; Sanches Pde L; Corgosinho FC; Caranti D; Tock L; de Mello MT; Tufik S; Dâmaso AR Nutr Hosp; 2015 Apr; 31(4):1540-50. PubMed ID: 25795939 [TBL] [Abstract][Full Text] [Related]
13. Usefulness of the metabolic syndrome criteria as predictors of insulin resistance among obese Korean women. Lee K Public Health Nutr; 2010 Feb; 13(2):181-6. PubMed ID: 19706218 [TBL] [Abstract][Full Text] [Related]
14. Biological aging mediates the associations of metabolic score for insulin resistance with all-cause and cardiovascular disease mortality among US adults: A nationwide cohort study. Li X; Wang J; Zhang M; Li X; Fan Y; Zhou X; Sun Y; Qiu Z Diabetes Obes Metab; 2024 Sep; 26(9):3552-3564. PubMed ID: 38853301 [TBL] [Abstract][Full Text] [Related]
15. High cardiometabolic risk in healthy Chilean adolescents: associations with anthropometric, biological and lifestyle factors. Burrows R; Correa-Burrows P; Reyes M; Blanco E; Albala C; Gahagan S Public Health Nutr; 2016 Feb; 19(3):486-93. PubMed ID: 25990645 [TBL] [Abstract][Full Text] [Related]
17. Anthropometric parameter that best predict metabolic syndrome in South west Nigeria. Adejumo EN; Adejumo AO; Azenabor A; Ekun AO; Enitan SS; Adebola OK; Ogundahunsi OA Diabetes Metab Syndr; 2019; 13(1):48-54. PubMed ID: 30641748 [TBL] [Abstract][Full Text] [Related]
18. High-molecular weight adiponectin/HOMA-IR ratio as a biomarker of metabolic syndrome in urban multiethnic Brazilian subjects. de Abreu VG; Martins CJM; de Oliveira PAC; Francischetti EA PLoS One; 2017; 12(7):e0180947. PubMed ID: 28746378 [TBL] [Abstract][Full Text] [Related]
19. Metabolic syndrome and all-cause and cardiovascular disease mortality: Japan Public Health Center-based Prospective (JPHC) Study. Saito I; Iso H; Kokubo Y; Inoue M; Tsugane S Circ J; 2009 May; 73(5):878-84. PubMed ID: 19282609 [TBL] [Abstract][Full Text] [Related]
20. Comparison of anthropometric indices for predicting the risk of metabolic syndrome and its components in Chinese adults: a prospective, longitudinal study. Wang H; Liu A; Zhao T; Gong X; Pang T; Zhou Y; Xiao Y; Yan Y; Fan C; Teng W; Lai Y; Shan Z BMJ Open; 2017 Sep; 7(9):e016062. PubMed ID: 28928179 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]