Maria Lazo-Porras1, Antonio Bernabe-Ortiz2, Andrea Ruiz-Alejos3, Liam Smeeth4, Robert H Gilman5, William Checkley6, German Málaga7, J Jaime Miranda8. 1. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; CONEVID Unidad de Conocimiento y Evidencia, Universidad Peruana Cayetano Heredia, Lima, Peru. Electronic address: maria.lazo@upch.pe. 2. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom. Electronic address: antonio.bernabe@upch.pe. 3. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru. Electronic address: aoriette@gmail.com. 4. Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom. Electronic address: Liam.Smeeth@lshtm.ac.uk. 5. Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States; Área de Investigación y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru. Electronic address: gilmanbob@gmail.com. 6. Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD, United States. Electronic address: wcheckl1@jhmi.edu. 7. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; CONEVID Unidad de Conocimiento y Evidencia, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru. Electronic address: german.malaga@upch.pe. 8. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru. Electronic address: Jaime.Miranda@upch.pe.
Abstract
AIMS: This study aimed to (1) estimate the prevalence of prediabetes according to different definitions, (2) evaluate regression to normal glucose levels and progression towards T2DM, and (3) determine factors associated with regression and progression across four diverse geographical settings in a Latin American country. METHODS: The CRONICAS Cohort Study was conducted in four different areas in Peru. Enrollment started in September 2010 and follow-up was conducted in 2013. Prediabetes, T2DM and normal glucose levels were determined according to definitions from the World Health Organization (WHO), American Diabetes Association (ADA), and National Institute for Health and Care Excellence (NICE). The main outcomes were regression to normal glucose levels and incidence of T2DM. Prevalence estimates and 95% confidence intervals (95% CI) were calculated. Crude and adjusted models using Poisson regression were performed and relative risk ratios (RRR) and 95% CI were calculated. RESULTS: At baseline, the prevalence of prediabetes varied markedly by definition used: 6.5%(95% CI 5.6-7.6%), 53.6% (95% CI 51.6-55.6%), and 24.6% (95% CI 22.8-26.4%) according to WHO, ADA and NICE criteria, respectively. After 2.2 years of follow-up, in those with prediabetes, the cumulative incidence of regression to euglycemia ranged between 31.4% and 68.9%, whereas the incidence of T2DM varied from 5.5% to 28.8%. Factors associated with regression to normal glucose levels and progression to diabetes were age, body mass index, and insulin resistance. CONCLUSIONS: Regression from pre-diabetes back to euglycemia was much more common than progression to diabetes.
AIMS: This study aimed to (1) estimate the prevalence of prediabetes according to different definitions, (2) evaluate regression to normal glucose levels and progression towards T2DM, and (3) determine factors associated with regression and progression across four diverse geographical settings in a Latin American country. METHODS: The CRONICAS Cohort Study was conducted in four different areas in Peru. Enrollment started in September 2010 and follow-up was conducted in 2013. Prediabetes, T2DM and normal glucose levels were determined according to definitions from the World Health Organization (WHO), American Diabetes Association (ADA), and National Institute for Health and Care Excellence (NICE). The main outcomes were regression to normal glucose levels and incidence of T2DM. Prevalence estimates and 95% confidence intervals (95% CI) were calculated. Crude and adjusted models using Poisson regression were performed and relative risk ratios (RRR) and 95% CI were calculated. RESULTS: At baseline, the prevalence of prediabetes varied markedly by definition used: 6.5%(95% CI 5.6-7.6%), 53.6% (95% CI 51.6-55.6%), and 24.6% (95% CI 22.8-26.4%) according to WHO, ADA and NICE criteria, respectively. After 2.2 years of follow-up, in those with prediabetes, the cumulative incidence of regression to euglycemia ranged between 31.4% and 68.9%, whereas the incidence of T2DM varied from 5.5% to 28.8%. Factors associated with regression to normal glucose levels and progression to diabetes were age, body mass index, and insulin resistance. CONCLUSIONS: Regression from pre-diabetes back to euglycemia was much more common than progression to diabetes.
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