  Background: The direct modeling of water networks is not a common practice in
modern epidemiology. While space often serves as a proxy, it can be
problematic. There are multiple ways to directly model water networks, but
these methods are not straightforward and can be difficult to implement. This
study suggests a simple approach for modeling water networks and diseases, and
applies this method to a dataset of self-reported gastrointestinal conditions
from a questionnaire-based population health survey in central Norway.
  Method: Our approach is based on a standard conditional autoregressive (CAR)
model. An inverse matrix was constructed, with nodes weighted based on the
distance to neighboring nodes within the networks. This matrix was then fitted
as a generic model. To illustrate its possible use, we utilized data taken from
a questionnaire-based population health survey, the HUNT Study, to measure
self-reported gastrointestinal complaints. For hypothesis testing, we used the
deviance information criterion (DIC) and included variables in a stepwise
manner.
  Results: The full model converged after six hours. We found no relation
between the water networks and the health conditions of people whose residences
connected to different parts of the network in the geographical area studied.
  Conclusion: All water network models are simplifications of the real
networks. Nevertheless, we suggest a valid approach for distinguishing between
the general spatial effect and the water network using a generic model.
