title: Projection of Diabetes Population Size and Associated Economic Burden through 2030 in Iran: Evidence from Micro-Simulation Markov Model and Bayesian Meta-Analysis.
abstract: BACKGROUND
  The aim of this study was to estimate the economic burden of diabetes mellitus (DM) in Iran from 2009 to 2030.
  
  
  METHODS
  A Markov micro-simulation (MM) model was developed to predict the DM population size and associated economic burden. Age- and sex-specific prevalence and incidence of diagnosed and undiagnosed DM were derived from national health surveys. A systematic review was performed to identify the cost of diabetes in Iran and the mean annual direct and indirect costs of patients with DM were estimated using a random-effect Bayesian meta-analysis. Face, internal, cross and predictive validity of the MM model were assessed by consulting an expert group, performing sensitivity analysis (SA) and comparing model results with published literature and national survey reports. Sensitivity analysis was also performed to explore the effect of uncertainty in the model.
  
  
  RESULTS
  We estimated 3.78 million cases of DM (2.74 million diagnosed and 1.04 million undiagnosed) in Iran in 2009. This number is expected to rise to 9.24 million cases (6.73 million diagnosed and 2.50 million undiagnosed) by 2030. The mean annual direct and indirect costs of patients with DM in 2009 were US$ 556 (posterior standard deviation, 221) and US$ 689 (619), respectively. Total estimated annual cost of DM was $3.64 (2009 US$) billion (including US$1.71 billion direct and US$1.93 billion indirect costs) in 2009 and is predicted to increase to $9.0 (in 2009 US$) billion (including US$4.2 billion direct and US$4.8 billion indirect costs) by 2030.
  
  
  CONCLUSIONS
  The economic burden of DM in Iran is predicted to increase markedly in the coming decades. Identification and implementation of effective strategies to prevent and manage DM should be considered as a public health priority.
authors.affiliation: Health Economics Research Unit, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Javanbakht
authors.affiliation: Endocrine Research Center, Institute of Endocrinology & Metabolism, Iran University of Medical Sciences, Tehran, Iran.
authors.forename: Atefeh
authors.initials: A
authors.lastname: Mashayekhi
authors.affiliation: Endocrine Research Center, Institute of Endocrinology & Metabolism, Iran University of Medical Sciences, Tehran, Iran.
authors.forename: Hamid R
authors.initials: HR
authors.lastname: Baradaran
authors.affiliation: Kerman University of Medical Sciences, Kerman, Iran.
authors.forename: AliAkbar
authors.initials: A
authors.lastname: Haghdoost
authors.affiliation: Friedman School of Nutrition Science and Policy, Tufts University, Boston, United States of America.
authors.forename: Ashkan
authors.initials: A
authors.lastname: Afshin
mesh_terms: D001499:Bayes Theorem; D017281:Cost of Illness; D003920:Diabetes Mellitus / Q000191:economics* / Q000453:epidemiology*; D017048:Health Care Costs / Q000639:trends; D006306:Health Surveys; D006801:Humans; D015994:Incidence; D007492:Iran / Q000453:epidemiology; D008390:Markov Chains; D017059:Models, Econometric; D015995:Prevalence