Specific count model for investing the related factors of cost of GERD and functional dyspepsia.
OBJECTIVE
The purpose of this study is to analyze the cost of GERD and functional dyspepsia for investing its related factors.


BACKGROUND
Gastro-oesophageal reflux disease GERD and dyspepsia are the most common symptoms of gastrointestinal disorders. Recent studies showed high prevalence and variety of clinical presentation of these two symptoms imposed enormous economic burden to the society. Cost data that related to economics burden have specific characteristics. So this kind of data needs to specific models. Poisson regression (PR) and negative binomial regression (NB) are the models that were used for analyzing cost data in this paper.


METHODS
This study designed as a cross-sectional household survey from May 2006 to December 2007 on a random sample of individual in the Tehran province, Iran to find the prevalence of gastrointestinal symptoms and disorders and its related factors. The Cost in each item was counted. PR and NB were carried out to the data respectively. Likelihood ratio test was performed for comparison between models. Also Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models.


RESULTS
According to Likelihood ratio test and all three criterions that we used to compare performance of the models, NB was the best model for analyzing this cost data. Sex, age and insurance statues were being significant.


CONCLUSIONS
PR and NB models were carried out for this data and according the results improved fit of the NB model over PR, it clearly indicates that over-dispersion is involved due to unobserved heterogeneity and/or clustering. NB model in cost data more appropriate fit than PR.
Department of Community Medicine & Health, Medical School, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Alireza
A
Abadi
Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Asma
A
Pourhoseingholi
Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Samira
S
Chaibakhsh
Department of Control & prevention of diseases, Deputy of Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Azadeh
A
Safaee
Department of Control & prevention of diseases, Deputy of Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Bijan
B
Moghimi-Dehkordi
Cost; Count models; Dyspepsia; GERD; Zero inflated models