Multimorbidity analysis with low condition counts: a robust Bayesian approach for small but important subgroups.

ABSTRACT:

Background

Robustly examining associations between long-term conditions may be important in identifying opportunities for intervention in multimorbidity but is challenging when evidence is limited. We have developed a Bayesian inference framework that is robust to sparse data and used it to quantify morbidity associations in the oldest old, a population with limited available data.

Methods

We conducted a retrospective cross-sectional study of a representative dataset of primary care patients in Scotland as of March 2007. We included 40 long-term conditions and studied their associations in 12,009 individuals aged 90 and older, stratified by sex (3039 men, 8970 women). We analysed associations obtained with Relative Risk (RR), a standard measure in the literature, and compare

SUBMITTER: Romero Moreno G 

PROVIDER: S-EPMC10966445 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature