Literature DB >> 21617883

Fasting glucose cutoff point: where does the risk terminate? Tehran lipid and glucose study.

Mohammadreza Bozorgmanesh1, Farzad Hadaegh, Navid Saadat, Fereidoun Azizi.   

Abstract

The aim of this study is to determine safe fasting plasma glucose (FPG) levels. We included data on 5,960 individuals aged ≥20 years at baseline with at least one follow-up examination. Diabetes was ascertained in accordance with American Diabetes Association criteria, using standard 2-h post-challenge plasma glucose test. Multivariate restricted cubic splines Weibull regression was implemented for interval-censored survival data on incident diabetes. We used Harrell's C statistic for discrimination, Nam-D'Agostino χ(2) for calibration, and Royston's R(2) for variations in the outcome explained by models. During a 6-year median follow-up, 369 incident cases of diabetes were ascertained. Family history of diabetes, systolic blood pressure, waist-to-height ratio, and triglyceride-to-high-density lipoprotein cholesterol ratio, independent of FPG and each other remained associated with incident diabetes. The cubic splines model achieved good calibration (χ(2) = 12.1) and discrimination (C = 0.828) and explained 75% of variation in the time until incident diabetes. A J-shaped FPG-diabetes relationship was observed. Descending arm of the dose-response relationship curve corresponded to increasing FPG levels up to 4.0 mmol l(-1), where it started increasing. The risk of incident diabetes decreased with decreasing levels of FPG down to 4.0 mmol l(-1), where the risk stopped decreasing. Multivariate-adjusted risk of incident diabetes was zero at FPG = 5.05 mmol l(-1). Although currently there is no firm evidence to show that early intervention among individuals with the elevated FPG levels could prevent or delay onset of diabetes, individuals with FPG levels below 5.05 mmol l(-1) could be safely reassured about their near-term risk of developing incident diabetes and screened on a less frequent basis.

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Year:  2011        PMID: 21617883     DOI: 10.1007/s00592-011-0298-5

Source DB:  PubMed          Journal:  Acta Diabetol        ISSN: 0940-5429            Impact factor:   4.280


  6 in total

1.  Trends in cardiovascular disease risk factors in people with and without diabetes mellitus: a Middle Eastern cohort study.

Authors:  Younes Jahangiri-Noudeh; Samaneh Akbarpour; Mojtaba Lotfaliany; Neda Zafari; Davood Khalili; Maryam Tohidi; Mohammad Ali Mansournia; Fereidoun Azizi; Farzad Hadaegh
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

2.  Sex specific incidence rates of type 2 diabetes and its risk factors over 9 years of follow-up: Tehran Lipid and Glucose Study.

Authors:  Arash Derakhshan; Mahsa Sardarinia; Davood Khalili; Amir Abbas Momenan; Fereidoun Azizi; Farzad Hadaegh
Journal:  PLoS One       Date:  2014-07-16       Impact factor: 3.240

3.  Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study.

Authors:  Azra Ramezankhani; Esmaeil Hadavandi; Omid Pournik; Jamal Shahrabi; Fereidoun Azizi; Farzad Hadaegh
Journal:  BMJ Open       Date:  2016-12-01       Impact factor: 2.692

4.  Change in fasting plasma glucose and incident type 2 diabetes mellitus: results from a prospective cohort study.

Authors:  Amirhossein Mozaffary; Samaneh Asgari; Maryam Tohidi; Sara Kazempour-Ardebili; Fereidoun Azizi; Farzad Hadaegh
Journal:  BMJ Open       Date:  2016-05-23       Impact factor: 2.692

5.  Risk Factors for Incidence of Cardiovascular Diseases and All-Cause Mortality in a Middle Eastern Population over a Decade Follow-up: Tehran Lipid and Glucose Study.

Authors:  Mahsa Sardarinia; Samaneh Akbarpour; Mojtaba Lotfaliany; Farideh Bagherzadeh-Khiabani; Mohammadreza Bozorgmanesh; Farhad Sheikholeslami; Fereidoun Azizi; Farzad Hadaegh
Journal:  PLoS One       Date:  2016-12-08       Impact factor: 3.240

6.  Optimal cut-points of different anthropometric indices and their joint effect in prediction of type 2 diabetes: results of a cohort study.

Authors:  Neda Zafari; Mojtaba Lotfaliany; Mohammad Ali Mansournia; Davood Khalili; Fereidoun Azizi; Farzad Hadaegh
Journal:  BMC Public Health       Date:  2018-06-05       Impact factor: 3.295

  6 in total

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