Public health nutrition | 2021
Meta-analysis and machine learning-augmented mixed effects cohort analysis of improved diets among 5,847 medical trainees, providers, and patients.
Abstract
OBJECTIVE\nWe sought to produce the first meta-analysis (of medical trainee competency improvement in nutrition counseling) informing the first cohort study of patient diet improvement through medical trainees and providers counseling patients on nutrition.\n\n\nDESIGN\n(Part A) A systematic review and meta-analysis informing (Part B) the intervention analyzed in the world s largest prospective multi-center cohort study on hands-on cooking and nutrition education for medical trainees, providers, and patients.\n\n\nSETTINGS\n(A) Medical educational institutions. (B) Teaching kitchens.\n\n\nPARTICIPANTS\n(A) Medical trainees. (B) Trainees, providers, and patients.\n\n\nRESULTS\n(A) Of the 212 citations identified (N=1,698 trainees), 11 studies met inclusion criteria. The overall effect size was 9.80 (95%CI 7.15-12.456.87-13.85; p<0.001), comparable to the machine learning (ML)-augmented results. The number needed to treat for the top performing high quality study was 12. (B) The hands-on cooking and nutrition education curriculum from the top performing study was applied for medical trainees and providers who subsequently taught patients in the same curriculum (N=5,847). The intervention compared to standard medical care and education alone significantly increased the odds of superior diets (high/medium versus low Mediterranean diet adherence) for residents/fellows most (OR 10.79, 95%CI 4.94-23.58; p<0.001) followed by students (OR 9.62, 95%CI 5.92-15.63; p<0.001), providers (OR 5.19, 95%CI 3.23-8.32, p<0.001), and patients (OR 2.48, 95%CI 1.38-4.45; p=0.002), results consistent with those from ML.\n\n\nCONCLUSIONS\nThis study suggests that medical trainees and providers can improve patients diets with nutrition counseling in a manner that is clinically and cost effective and may simultaneously advance societal equity.