  In the present study we investigate overall population effects on episodic
memory of an intervention over 15 years that reduces systolic blood pressure in
individuals with hypertension. A limitation with previous research on the
potential risk reduction of such interventions is that they do not properly
account for the reduction of mortality rates. Hence, one can only speculate
whether the effect is due to changes in memory or changes in mortality.
Therefore, we extend previous research by providing both an etiological and a
prognostic effect estimate. To do this, we propose a Bayesian semi-parametric
estimation approach for an incremental threshold intervention, using the
extended G-formula. Additionally, we introduce a novel sparsity-inducing
Dirichlet hyperprior for longitudinal data, that exploits the longitudinal
structure of the data. We demonstrate the usefulness of our approach in
simulations, and compare its performance to other Bayesian decision tree
ensemble approaches. In our analysis of the data from the Betula cohort, we
found no significant prognostic or etiological effects across all ages. This
suggests that systolic blood pressure interventions likely do not strongly
affect memory, whether at the overall population level or in the population
that would survive under both the natural course and the intervention (the
always survivor stratum).
