Novel Pooling Method for Nonlinear Cohort Analysis and Meta-analysis Estimates: Predicting Health Outcomes from Dietary Changes.

ABSTRACT:

Background

Projections for major health outcomes are crucial for decision-making to enable early interventions. Pooling results from meta-analyses with estimates based on individual participant data can reduce uncertainty and improve generalizability. However, current methods for meta-meta-analyses of nonlinear functions have remained underdeveloped.

Methods

We proposed a novel meta-analysis method to pool pointwise nonlinear function literature estimates with parameter estimates, applied here to the association of dietary change scenarios with mortality and ischemic heart disease (IHD) based on Finnish individual participant data. We linked individual-level demographic and risk factor data from the Health 2000, FINRISK 2007, FINRISK 2012, and FinHealth 2017 surveys (n = 20,

SUBMITTER: Harkanen T 

PROVIDER: S-EPMC12851546 | biostudies-literature | 2026 Mar

REPOSITORIES: biostudies-literature