Zero inflated statistical count models for analysing the costs imposed by GERD and dyspepsia

Abstract

Background and study aimsRecent studies have shown that the high prevalence and the various clinical presentations of gastro-oesophageal reflux disease (GERD) and dyspepsia impose an enormous economic burden on society. Economic cost data have unique characteristics: they are counts, and they have zero inflation. Therefore, these data require special models. Poisson regression (PR), negative binomial regression (NB), zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) regression are the models used for analysing cost data in this paper. Patients and methodsIn this study, a cross-sectional household survey was distributed to a random sample of individuals between May 2006 and December 2007 in the Tehran province of Iran to determine the prevalence of gastrointestinal symptoms and disorders and their related factors. The cost associated with each item was calculated. PR, NB, ZIP and ZINB models were used to analyse the data. The likelihood ratio test and the Voung test were used to conduct pairwise comparisons of the models. The log likelihood, the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were used to compare the performances of the models. ResultsAccording to the likelihood ratio test and the Voung test and all three criteria used to compare the performance of the models, ZINB regression was identified as the best model for analysing the cost data. Sex, age, smoking status, BMI, insurance status and education were significant predictors. ConclusionBecause the NB model demonstrated a better fit than the PR and ZIP models, over-dispersion was clearly only due to unobserved heterogeneity. In contrast, according to the likelihood ratio test, the ZINB model was more appropriate than the ZIP model.The ZINB model for the cost data was more appropriate than the other models.