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Journal Abstract Search

223 related items for PubMed ID: 34750510

  • 21. Comparison of Different Obesity Indices for Predicting Incident Hypertension.
    Janghorbani M, Aminorroaya A, Amini M.
    High Blood Press Cardiovasc Prev; 2017 Jun; 24(2):157-166. PubMed ID: 28160265
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  • 22. BMI is strongly associated with hypertension, and waist circumference is strongly associated with type 2 diabetes and dyslipidemia, in northern Chinese adults.
    Feng RN, Zhao C, Wang C, Niu YC, Li K, Guo FC, Li ST, Sun CH, Li Y.
    J Epidemiol; 2012 Jun; 22(4):317-23. PubMed ID: 22672914
    [Abstract] [Full Text] [Related]

  • 23. Screening for Metabolic Syndrome Using an Integrated Continuous Index Consisting of Waist Circumference and Triglyceride: A Preliminary Cross-sectional Study.
    Liu PJ, Lou HP, Zhu YN.
    Diabetes Metab Syndr Obes; 2020 Jun; 13():2899-2907. PubMed ID: 32884316
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  • 24. Simultaneous prediction of hyperglycemia and dyslipidemia in school children in Santa Catarina State, Brazil based on waist circumference measurement.
    Rosini N, Machado MJ, Webster IZ, Moura SA, Cavalcante Lda S, da Silva EL.
    Clin Biochem; 2013 Dec; 46(18):1837-41. PubMed ID: 24012695
    [Abstract] [Full Text] [Related]

  • 25. Predictive performance of traditional and novel lipid combined anthropometric indices to identify prediabetes.
    Ramdas Nayak VK, Nayak KR, Vidyasagar S, P R.
    Diabetes Metab Syndr; 2020 Dec; 14(5):1265-1272. PubMed ID: 32688243
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  • 26. Anthropometric cutoff values for predicting metabolic syndrome in a Saudi community: from the SAUDI-DM study.
    Al-Rubean K, Youssef AM, AlFarsi Y, Al-Sharqawi AH, Bawazeer N, AlOtaibi MT, AlRumaih FI, Zaidi MS.
    Ann Saudi Med; 2017 Dec; 37(1):21-30. PubMed ID: 28151453
    [Abstract] [Full Text] [Related]

  • 27. Determining the best method for evaluating obesity and the risk for non-communicable diseases in women of childbearing age by measuring the body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, A Body Shape Index, and hip index.
    Hewage N, Wijesekara U, Perera R.
    Nutrition; 2023 Oct; 114():112135. PubMed ID: 37453224
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  • 29. Predictive Ability of Seven Anthropometric Indices for Cardiovascular Risk Markers and Metabolic Syndrome in Adolescents.
    Cristine Silva K, Santana Paiva N, Rocha de Faria F, Franceschini SDCC, Eloiza Piore S.
    J Adolesc Health; 2020 Apr; 66(4):491-498. PubMed ID: 31980321
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  • 32. Factors associated with glycemic control in community-dwelling elderly individuals with type 2 diabetes mellitus in Zhejiang, China: a cross-sectional study.
    Zhu HT, Yu M, Hu H, He QF, Pan J, Hu RY.
    BMC Endocr Disord; 2019 Jun 06; 19(1):57. PubMed ID: 31170961
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  • 33. 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 Jun 06; 13(1):48-54. PubMed ID: 30641748
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  • 34. The association between anthropometric indices and ischemic heart disease: a large-scale cross-sectional study on the Iranian population.
    Nakhostin-Ansari A, Razavi E, Seifi S, Ahmadi M, Hoveidaei AH, Nalini M, Gandomkar A, Malekzadeh F, Poustchi H, Fattahi MR, Anushiravani A, Malekzadeh R.
    Sci Rep; 2024 Aug 15; 14(1):18950. PubMed ID: 39147775
    [Abstract] [Full Text] [Related]

  • 35. Comparison of visceral, general and central obesity indices in the prediction of metabolic syndrome in maintenance hemodialysis patients.
    Zhou C, Zhan L, Yuan J, Tong X, Peng Y, Zha Y.
    Eat Weight Disord; 2020 Jun 15; 25(3):727-734. PubMed ID: 30968371
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  • 36. Comparison of anthropometric indices for predicting the risk of metabolic syndrome in older adults.
    Khosravian S, Bayani MA, Hosseini SR, Bijani A, Mouodi S, Ghadimi R.
    Rom J Intern Med; 2021 Mar 01; 59(1):43-49. PubMed ID: 32881711
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  • 37. Anthropometric Cutoffs for Increased Cardiometabolic Risk Among Lebanese Adults: A Cross-Sectional Study.
    Nasreddine L, Bachir N, Kharroubi S, Chamieh MC, Mehio Sibai A, Hwalla N, Naja F.
    Metab Syndr Relat Disord; 2019 Dec 01; 17(10):486-493. PubMed ID: 31566527
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  • 38. The cutoff values of visceral fat area and waist circumference for identifying subjects at risk for metabolic syndrome in elderly Korean: Ansan Geriatric (AGE) cohort study.
    Seo JA, Kim BG, Cho H, Kim HS, Park J, Baik SH, Choi DS, Park MH, Jo SA, Koh YH, Han C, Kim NH.
    BMC Public Health; 2009 Dec 02; 9():443. PubMed ID: 19951442
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  • 40. Insulin Resistance-Related Cardiometabolic Risk Among Nondiabetic Childbearing Age Females.
    Hewage N, Wijesekara U, Perera R.
    Metab Syndr Relat Disord; 2024 Aug 02; 22(6):447-453. PubMed ID: 38603585
    [Abstract] [Full Text] [Related]

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