Heterogeneity in associations between food insecurity and diabetes outcomes.

ABSTRACT:

Background

Food insecurity is associated with worse diabetes outcomes, but how that association may vary across individuals is unclear. We sought to better understand possible heterogeneity in the association between food insecurity and diabetes outcomes.

Methods

Longitudinal cohort study of adults with type 2 diabetes assessed for food insecurity in community-based health centres. Diabetes outcomes were haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, and low-density lipoprotein cholesterol (LDL), 12 months after food insecurity assessment. We used three machine learning methods (generalised random forest (GRF), X-Learner and Doubly Robust Learner) to assess outcome heterogeneity across the following variables: age, sex, race and ethnicity, health insurance,

SUBMITTER: Berkowitz SA 

PROVIDER: S-EPMC12359045 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature