A rigorous small area modelling-study for the helicobacter pylori epidemiology Original Research Article

This paper presents an investigation into spatial risk differences over small distances for the Helicobacter pylori infection in the city of Leipzig, Germany and two rural districts. A model, using Bayesian inference, was developed that adjusts the risk for individual-specific factors, and for spatial or individual over-dispersion, respectively. Additionally, the model takes into account conditional spatial autocorrelation. We found a significant positive association to the H. pylori infection risk for: “more than three children live in the household” (OR = 2.4, p = 0.001), “more persons live per sq.m than average” (OR = 1.4, p = 0.03), “home situated at main road” (OR = 1.4, p = 0.04) and “using well water” (OR = 2.3, p = 0.05). A protective effect was identified for “travelled to low prevalence region” (OR = 0.4, p < 0.0001) and “born in Germany” (OR = 0.2, p < 0.0001). Three administrative areas with significantly increased spatial risk were identified: one in the rural district and two in the city of Leipzig. The model explained 24.9% of the total deviance. Contrary to expectations, the largest part of deviance of the data was not explained by the identified significant risk factors, but by individual-specific heterogeneities. We conclude that further – so far not discussed – factors influence the risk and the spatial variation of the H. pylori infection. Furthermore, from the results we speculate about a possible impact of long-time air pollution and surface water.