Title of article :
The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran 2010-2011
Author/Authors :
Sarvi, Fatemeh Department of Epidemiology and Biostatistics - School of Public Health - Hamadan University of Medical Science, Hamadan, Iran , Momenian, Somayeh Faculty Member - Epidemiology and Biostatistics Department - Qom University of Medical Sciences, Iran , Khodadost, Mahmoud Department of Epidemiology and Biostatistics - Iran University of Medical Sciences, Tehran, Iran , Pahlavanzadeh, Bagher Department of Biostatistics - Shahid Beheshti University of Medical Science, Tehran, Iran , Nasehi, Mahshid Department of Epidemiology and Biostatistics - Iran University of Medical Sciences, Tehran, Iran , Sekhavati, Eghbal Faculty Member - Larestan School of Medical Sciences, Larestan, Iran
Abstract :
Background: Poverty and low socioeconomic status are the most important reasons of increasing the global
burden of tuberculosis, not only in developing countries but also in developed countries for particular groups.
The purpose of this study was to assess the association between socioeconomic factors and the number of tuberculosis
patients using quantile regression for count data.
Methods: This cross-sectional study was conducted on 11,320 tuberculosis patients from March 2010 to
March 201 in Iran. Data was gathered from the 345 sections of Iran by Ministry of Health and Medical Education
and Statistical Center of Iran. The jittering method was applied for smoothing, and then, the quantile regression
for count data was fitted. The AIC was used to compare the fitness of quantile regression for count data
model and Poisson log-linear model. The R (3.0.1) software and Quantreg and AER packages were used for all
analysis and modeling of the data.
Results: The results of fitting the quantile regression for count data showed that in all percentiles, the more
increase in immigration rate, illiteracy rate, unemployment and urbanization rates, the more tuberculosis morbidity
rate was increased. The maximum increase of tuberculosis due to immigration rate, urbanization rate,
unemployment rate, and illiteracy rate was in 95th percentile (β ̂=0.315), 85'Th percentile (β ̂=0.162), 75'Th percentile
(β ̂=0.114), and 95'Th percentile (β ̂=0.304), respectively. For 50th percentiles and higher percentiles,
with increasing the sum of physicians to the number of population, the tuberculosis morbidity rate was decreased,
and the maximum decrease was in 95'Th percentile (β ̂=-0.1). For all percentiles, the AIC showed that
quantile regression for count data had been a better fit to data.
Conclusion: With respect to the relationship between socioeconomic factors and TB rate, health care observers
should pay close attention to improving these factors in Iran to reduce the TB mortality and morbidity.
Keywords :
Iran , Tuberculosis , Poisson regression , Quantile regression
Journal title :
Astroparticle Physics