interpretation results and minimum of data

[Sònia Gil]

Hi all,
I would like to understand what is the interpertration of my results. I apply a bym model for some cancer data:

formula <- Y ~ f(idarea, model = "bym", graph = g) +
  f(idarea1,  model = "iid")

#results
res <- inla(formula,
            family = "poisson", data = d,
            E = E,
            control.predictor = list(compute = TRUE),
            control.compute=list(return.marginals.predictor=TRUE)
)

The result of the smoothed incidence ratio is in all areas close to 1. Could it be because there is a minimum of data to be used? It happens to me when I disaggregate and have n around 1000.

Thank you!