Relation between Tuberculosis Incidence and Migration Using Quantile Regression Model in Iran 2010

The quantile regression model is an efficient method for prediction and estimation the relationship between explanatory variables and percentiles of the distribution. In this study we used the model to examine the relationship between TB and inter-districts migration in Iran. This cross-sectional study was conducted on 11,320 Patients whose TB was diagnosed between March 2010 and March 2011 in Iran. Data were collected from the Ministry of Health and Medical Education and Statistical Center of Iran. To study the effect of migration on extreme quantiles of the distribution of TB incidence among districts, quantile regression model was used adjusting for some socioeconomic indicators. To examine the goodness of fit of the model, the Akaike information criterion (AIC) was applied. For data analysis and modeling, Quantreg package in R software was employed. The results of the quantile regression model showed that the tuberculosiss incidence rate was elevated as the immigration rate increased. For 50th, 60th, 70th, 80th and 95th percentiles of TB incidence, immigration rate showed significant relationship. The Tuberculosis and migration were associated together typically for high percentiles of the TB Incidence.