Logo-aim
Arch Iran Med. 2014;17(12): 0.
PMID: 25481318
Scopus ID: 84916197597
  Abstract View: 3034
  PDF Download: 1769

Study Protocol

National and Sub-national Prevalence, Trend, and Burden of Asthma in Iran from 1990 to 2013; the Study Protocol

Mehdi Varmaghani, Arash Rashidian, Abbas Kebriaeezadeh, Maziar Moradi-Lakeh, Mostafa Moin, Anoosheh Ghasemian, Ehsan Rezaei-Darzi, Sadaf Ghajarieh Sepanlou, Niloofar Peykari, Nazila Rezaei, Mahboubeh Parsaeian, Farshad Farzadfar*
*Corresponding Author: Email: f-farzadfar@tums.ac.ir

Abstract

BACKGROUND: Asthma is a chronic inflammatory airway disease caused or worsened by environmental factors in genetically vulnerable people. The study of national and sub-national burden of asthma aims to provide a quantitative method and valid estimates for the prevalence, incidence, and economic burden of asthma disease in Iran from 1990 to 2013 and this papers explains measures, data sources, methods, and challenges that we will use in the study.
METHODS: In order to conduct this study, we will use all available unpublished data sources, including claim databases and data collected by the food and drug organization (FDO). Moreover, we will devise and run a systematic review of all studies and literature published about asthma epidemiology in Iran, which includes all cross-sectional, cohort and case-control studies with asthma epidemiology focus that are population based. In this study, we will use two statistical models, including spatio-temporal and multilevel autoregressive models to estimate mean and uncertainty intervals for the parameters under study by gender, age, year, and province. All programs will be written in R statistical packages (version 3.0.1).
CONCLUSION: This study helps to obtain information concerning the variation among regions and provinces, and in general among sub-national divisions. Our study can be contribute to better allocation of resources, since it helps policymakers to recognize inequalities between regions and provinces and consequently help them to allocate resources more efficiently.

First Name
Last Name
Email Address
Comments
Security code


Abstract View: 3035

Your browser does not support the canvas element.


PDF Download: 1769

Your browser does not support the canvas element.