Literature DB >> 21384232

Leptin cut-off values for determination of metabolic syndrome: third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007).

Alireza Esteghamati1, Ali Zandieh, Basira Zandieh, Omid Khalilzadeh, Alipasha Meysamie, Manouchehr Nakhjavani, Mohammad Mehdi Gouya.   

Abstract

Leptin is strongly contributed to the clustering of metabolic syndrome (MetS) components and potentially can be regarded as a single predictor of MetS. This population-based study, for the first time, reports the diagnostic accuracy of different leptin cut-points for determining MetS. Further, the current study compares the predictive ability of the appropriate threshold of leptin with insulin resistance. Data of the individuals without history of known diabetes mellitus, aged 25-64 years, from the third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) were analyzed. MetS was defined due to either adult treatment panel III (ATPIII) or the modified international diabetes federation (IDF) criteria. Receiver-operating characteristic (ROC) curves were depicted to define cut-off of serum leptin, using the maximum Youden index and the shortest distance methods. Further, the values of leptin cut-offs in prediction of MetS were compared with those of insulin resistance (defined as homeostasis model assessment of insulin resistance >1.775). In men, the optimal cut-offs of leptin for IDF- and ATPIII-defined MetS were 3.6 ng/ml (positive predictive value, PPV: 56.5%; negative predictive value, NPV: 72.7%) and 4.1 ng/ml (PPV: 49.6%; NPV: 78.1%), respectively. In women, the optimal threshold was equal to 11.0 ng/ml (PPV: 53.8%; NPV: 73.0% for IDF criteria and PPV: 60.1%; NPV: 64.9% for ATPIII criteria). The diagnostic accuracy of these values in identifying MetS was similar to that of insulin resistance. Therefore, leptin is comparable to insulin resistance in identifying MetS and can be used as single predictor of MetS.

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Year:  2011        PMID: 21384232     DOI: 10.1007/s12020-011-9447-4

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  33 in total

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2.  The CAG repeat polymorphism in the androgen receptor gene modulates body fat mass and serum concentrations of leptin and insulin in men.

Authors:  M Zitzmann; J Gromoll; A von Eckardstein; E Nieschlag
Journal:  Diabetologia       Date:  2002-12-20       Impact factor: 10.122

Review 3.  Use and abuse of HOMA modeling.

Authors:  Tara M Wallace; Jonathan C Levy; David R Matthews
Journal:  Diabetes Care       Date:  2004-06       Impact factor: 19.112

Review 4.  Role of adipose tissue in body-weight regulation: mechanisms regulating leptin production and energy balance.

Authors:  P J Havel
Journal:  Proc Nutr Soc       Date:  2000-08       Impact factor: 6.297

5.  Chronic cardiovascular and renal actions of leptin: role of adrenergic activity.

Authors:  Megan Carlyle; Oscar B Jones; Jay J Kuo; John E Hall
Journal:  Hypertension       Date:  2002-02       Impact factor: 10.190

Review 6.  Etiology of the metabolic syndrome: potential role of insulin resistance, leptin resistance, and other players.

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7.  Optimal cut-off of homeostasis model assessment of insulin resistance (HOMA-IR) for the diagnosis of metabolic syndrome: third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007).

Authors:  Alireza Esteghamati; Haleh Ashraf; Omid Khalilzadeh; Ali Zandieh; Manouchehr Nakhjavani; Armin Rashidi; Mehrdad Haghazali; Fereshteh Asgari
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8.  Relation of visfatin to cardiovascular risk factors and adipocytokines in patients with impaired fasting glucose.

Authors:  Daniel Antonio de Luis; Manuel González Sagrado; Rosa Conde; Rocio Aller; Olatz Izaola
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9.  Leptin and high-sensitivity C-reactive protein and their interaction in the metabolic syndrome in middle-aged subjects.

Authors:  Olavi Ukkola; Y Antero Kesäniemi
Journal:  Metabolism       Date:  2007-09       Impact factor: 8.694

10.  Leptin predicts diabetes but not cardiovascular disease: results from a large prospective study in an elderly population.

Authors:  Paul Welsh; Heather M Murray; Brendan M Buckley; Anton J M de Craen; Ian Ford; J Wouter Jukema; Peter W Macfarlane; Chris J Packard; David J Stott; Rudi G J Westendorp; James Shepherd; Naveed Sattar
Journal:  Diabetes Care       Date:  2008-11-10       Impact factor: 19.112

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  4 in total

Review 1.  The role of leptin in obesity and the potential for leptin replacement therapy.

Authors:  Helin Feng; Lihua Zheng; Zhangying Feng; Yaheng Zhao; Ning Zhang
Journal:  Endocrine       Date:  2012-12-29       Impact factor: 3.633

2.  A HPLC-Q-TOF-MS-based urinary metabolomic approach to identification of potential biomarkers of metabolic syndrome.

Authors:  Zhi-Rui Yu; Yu Ning; Hao Yu; Nai-Jun Tang
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2014-04-08

3.  Metabolic syndrome in South Asians.

Authors:  Kaushik Pandit; Soumik Goswami; Sujoy Ghosh; Pradip Mukhopadhyay; Subhankar Chowdhury
Journal:  Indian J Endocrinol Metab       Date:  2012-01

Review 4.  Prevalence of Metabolic Syndrome and Its Components in the Iranian Adult Population: A Systematic Review and Meta-Analysis.

Authors:  Bahareh Amirkalali; Hossein Fakhrzadeh; Farshad Sharifi; Roya Kelishadi; Farhad Zamani; Hamid Asayesh; Saeid Safiri; Tahereh Samavat; Mostafa Qorbani
Journal:  Iran Red Crescent Med J       Date:  2015-12-27       Impact factor: 0.611

  4 in total

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