A Bayesian functional approach to test models of life course epidemiology over continuous time.

ABSTRACT:

Background

Life course epidemiology examines associations between repeated measures of risk and health outcomes across different phases of life. Empirical research, however, is often based on discrete-time models that assume that sporadic measurement occasions fully capture underlying long-term continuous processes of risk.

Methods

We propose (i) the functional relevant life course model (fRLM), which treats repeated, discrete measures of risk as unobserved continuous processes, and (ii) a testing procedure to assign probabilities that the data correspond to conceptual models of life course epidemiology (critical period, sensitive period and accumulation models). The performance of the fRLM is evaluated with simulations, and the approach is illustrated with empirical applica

SUBMITTER: Bodelet J 

PROVIDER: S-EPMC10859158 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature