Azizi F, Hadaegh F, Hosseinpanah F, Mirmiran P, Amouzegar A, Abdi H, et al. Metabolic health in the Middle East and north Africa. Lancet Diab Endocrinol. 2019;7(11):866–79.
Article
Google Scholar
Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 44 million participants. Lancet (London, England). 2016;387(10027):1513-30.
Tohidi M, Hasheminia M, Mohebi R, Khalili D, Hosseinpanah F, Yazdani B, et al. Incidence of chronic kidney disease and its risk factors, results of over 10 year follow up in an Iranian cohort. PLoS ONE. 2012;7(9):e45304.
Article
CAS
Google Scholar
Sardarinia M, Akbarpour S, Lotfaliany M, Bagherzadeh-Khiabani F, Bozorgmanesh M, Sheikholeslami F, et al. 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. PLoS ONE. 2016;11(12):e0167623.
Article
Google Scholar
Danaei G, Farzadfar F, Kelishadi R, Rashidian A, Rouhani OM, Ahmadnia S, et al. Iran in transition. Lancet (London, England). 2019;393(10184):1984–2005.
Article
Google Scholar
Faraji O, Etemad K, Akbari Sari A, Ravaghi H. Policies and programs for prevention and control of diabetes in iran: a document analysis. Global J Health Sci. 2015;7(6):187–97.
Article
Google Scholar
Peykari N, Hashemi H, Dinarvand R, Haji-Aghajani M, Malekzadeh R, Sadrolsadat A, et al. National action plan for non-communicable diseases prevention and control in Iran; a response to emerging epidemic. J Diab Metab Disorders. 2017;16:3.
Article
Google Scholar
Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: a Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596–646.
PubMed
Google Scholar
Abbasi A, Peelen LM, Corpeleijn E, van der Schouw YT, Stolk RP, Spijkerman AMW, et al. Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study. Br Med J. 2012;345:e5900.
Article
Google Scholar
Sattar N, Gill JMR, Alazawi W. Improving prevention strategies for cardiometabolic disease. Nat Med. 2020;26(3):320–5.
Article
CAS
Google Scholar
Nelson RG, Grams ME, Ballew SH, Sang Y, Azizi F, Chadban SJ, et al. Development of Risk Prediction Equations for Incident Chronic Kidney Disease. Jama. 2019.
D’Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743–53.
Article
Google Scholar
Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I Follow-up Study cohort. Lancet (London, England). 2008;371(9616):923–31.
Article
Google Scholar
Joseph P, Yusuf S, Lee SF, Ibrahim Q, Teo K, Rangarajan S, et al. Prognostic validation of a non-laboratory and a laboratory based cardiovascular disease risk score in multiple regions of the world. Heart. 2018;104(7):581–7.
Article
CAS
Google Scholar
Khalili D, Hadaegh F, Soori H, Steyerberg EW, Bozorgmanesh M, Azizi F. Clinical usefulness of the framingham cardiovascular risk profile beyond its statistical performance: the tehran lipid and glucose Study. Am J Epidemiol. 2012;176(3):177–86.
Article
Google Scholar
Alssema M, Newson RS, Bakker SJ, Stehouwer CD, Heymans MW, Nijpels G, et al. One risk assessment tool for cardiovascular disease, type 2 diabetes, and chronic kidney disease. Diabetes Care. 2012;35(4):741–8.
Article
Google Scholar
Dekker JM, Alssema M, Janssen PG, Goudswaard LN. Summary of the practice guideline ‘The Prevention Visit’ from the Dutch College of General Practitioners. Ned Tijdschr Geneeskd. 2011;155(18):A3428.
PubMed
Google Scholar
Rauh SP, Rutters F, van der Heijden AAWA, Luimes T, Alssema M, Heymans MW, et al. External validation of a tool predicting 7-year risk of developing cardiovascular disease, type 2 diabetes or chronic kidney disease. J Gen Intern Med. 2018;33(2):182–8.
Article
Google Scholar
Azizi F, Ghanbarian A, Momenan AA, Hadaegh F, Mirmiran P, Hedayati M, et al. Prevention of non-communicable disease in a population in nutrition transition: tehran Lipid and Glucose Study phase II. Trials. 2009;10(1):5.
Article
Google Scholar
Levey AS, Coresh J, Bolton K, Culleton B, Harvey KS, Ikizler TA, et al. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. American Journal of Kidney Diseases. 2002;39(2 SUPPL. 1).
Levey A. A simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol. 2000;11:A0828.
Google Scholar
Kabootari M, Asgari S, Mansournia MA, Khalili D, Valizadeh M, Azizi F, et al. Different weight histories and risk of incident coronary heart disease and stroke: tehran lipid and glucose study. J Am Heart Assoc. 2018;7(4):e006924.
Article
Google Scholar
Khalili D, Azizi F, Asgari S, Zadeh-Vakili A, Momenan AA, Ghanbarian A, et al. Outcomes of a longitudinal population-based Cohort Study and pragmatic community trial: Findings from 20 years of the Tehran Lipid and Glucose Study. Int J Endocrinol Metab. 2018;16(4 Suppl).
Hosmer DW Jr, Lemeshow S, Sturdivant RX. Applied logistic regression. New York: Wiley; 2013.
Book
Google Scholar
Hadaegh F, Asgari S, Bozorgmanesh M, Jeddi S, Azizi F, Ghasemi A. Added value of total serum nitrate/nitrite for prediction of cardiovascular disease in middle east caucasian residents in Tehran. Nitric Oxide. 2016;54:60–6.
Article
CAS
Google Scholar
Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157–72.
Article
Google Scholar
Nattino G, Lemeshow S, Phillips G, Finazzi S, Bertolini G. Assessing the calibration of dichotomous outcome models with the calibration belt. Stata J. 2017;17(4):1003–14.
Article
Google Scholar
Steyerberg EW. Clinical prediction models. New York: Springer; 2019.
Book
Google Scholar
Derakhshan A, Sardarinia M, Khalili D, Momenan AA, Azizi F, Hadaegh F. Sex specific incidence rates of type 2 diabetes and its risk factors over 9 years of follow-up: Tehran Lipid and Glucose Study. PLoS ONE. 2014;9:7.
Article
Google Scholar
Tohidi M, Hasheminia M, Mohebi R, Khalili D, Hosseinpanah F, Yazdani B, et al. Incidence of chronic kidney disease and its risk factors, results of over 10 year follow up in an Iranian cohort. PLoS ONE. 2012;7:9.
Article
Google Scholar
Van der Heijden GJ, Donders ART, Stijnen T, Moons KG. Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. J Clin Epidemiol. 2006;59(10):1102–9.
Article
Google Scholar
Perkins NJ, Schisterman EF. The inconsistency of “optimal” cutpoints obtained using two criteria based on the receiver operating characteristic curve. Am J Epidemiol. 2006;163(7):670–5.
Article
Google Scholar
Hadaegh F, Zabetian A, Sarbakhsh P, Khalili D, James W, Azizi F. Appropriate cutoff values of anthropometric variables to predict cardiovascular outcomes: 7.6 years follow-up in an Iranian population. Int J Obes. 2009;33(12):1437–45.
Article
CAS
Google Scholar
Chadban SJ, Briganti EM, Kerr PG, Dunstan DW, Welborn TA, Zimmet PZ, et al. Prevalence of kidney damage in Australian adults: the AusDiab kidney study. J Am Soc Nephrol. 2003;14(suppl 2):S131–8.
Article
Google Scholar
Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA, et al. The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes. Obesity and Lifestyle Study. Diabetes care. 2002;25(5):829–34.
Article
Google Scholar
Sattar N, Preiss D. Reverse causality in cardiovascular epidemiological research: more common than imagined? Am Heart Assoc. 2017;135(24):2369–72.
Google Scholar
Shahid Beheshti University of medical sciences. http://www.sbmu.ac.ir/index.jsp?fkeyid=&siteid=1&pageid=2055. Accessed 14 June 2020.
Tehran University of medical sciences. Health care centers. https://sthn.tums.ac.ir/index.php/%D9%85%D8%B1%D8%A7%DA%A9%D8%B2-%D9%88-%D8%AE%D8%A7%D9%86%D9%87-%D9%87%D8%A7%DB%8C-%D8%A8%D9%87%D8%AF%D8%A7%D8%B4%D8%AA.html. Accessed 14 June 2020.
Iran medical University. https://iums.ac.ir/page/1496/%D9%85%D8%B1%D8%A7%DA%A9%D8%B2-%D9%88-%D8%B4%D8%A8%DA%A9%D9%87-%D9%87%D8%A7%DB%8C-%D8%A8%D9%87%D8%AF%D8%A7%D8%B4%D8%AA%DB%8C-%D8%AF%D8%B1%D9%85%D8%A7%D9%86%DB%8C. Accessed 14 June 2020.
Ministry of Health and Education. http://zaums.ac.ir/21257. Accessed 14 June 2020.
Joseph P, Yusuf S, Lee SF, Ibrahim Q, Teo K, Rangarajan S, et al. Prognostic validation of a non-laboratory and a laboratory based cardiovascular disease risk score in multiple regions of the world. Heart (British Cardiac Society). 2018;104(7):581–7.
CAS
Google Scholar
Hippisley-Cox J, Coupland C. Predicting the risk of chronic Kidney Disease in men and women in England and Wales: prospective derivation and external validation of the QKidney Scores. BMC Family Practice. 2010;11:49.
Article
Google Scholar
Bozorgmanesh M, Hadaegh F, Ghaffari S, Harati H, Azizi F. A simple risk score effectively predicted type 2 diabetes in Iranian adult population: population-based cohort study. Eur J Pub Health. 2011;21(5):554–9.
Article
Google Scholar
Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275–86.
Article
CAS
Google Scholar
Lotfaliany M, Hadaegh F, Asgari S, Mansournia MA, Azizi F, Oldenburg B, et al. Non-invasive Risk Prediction Models in Identifying Undiagnosed Type 2 Diabetes or Predicting Future Incident Cases in the Iranian Population. Arch Iran Med. 2019;22(3):116–24.
PubMed
Google Scholar
Asgari S, Lotfaliany M, Fahimfar N, Hadaegh F, Azizi F, Khalili D. The external validity and performance of the no-laboratory American Diabetes Association screening tool for identifying undiagnosed type 2 diabetes among the Iranian population. Primary Care Diabetes. 2020.
Badenbroek IF, Stol DM, Nielen MM, Hollander M, Kraaijenhagen RA, de Wit GA, et al. Design of the INTEGRATE study: effectiveness and cost-effectiveness of a cardiometabolic risk assessment and treatment program integrated in primary care. BMC Family Pract. 2014;15:90.
Article
Google Scholar
Badenbroek IF, Stol DM, Nielen MM, Hollander M, Kraaijenhagen RA, de Wit GA, et al. Erratum to: design of the INTEGRATE study: effectiveness and cost-effectiveness of a cardiometabolic risk assessment and treatment program integrated in primary care. BMC Family Pract. 2016;17:42.
Article
Google Scholar
World Health Organization, Regional Office for Eastern Mediterranean 2020. http://www.emro.who.int/entity/ncds/index.html. Accessed 3 May 2020.