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BioMed Research International
Volume 2018 (2018), Article ID 5051289, 10 pages
Research Article

Machine Learning-Augmented Propensity Score-Adjusted Multilevel Mixed Effects Panel Analysis of Hands-On Cooking and Nutrition Education versus Traditional Curriculum for Medical Students as Preventive Cardiology: Multisite Cohort Study of 3,248 Trainees over 5 Years

1The Goldring Center for Culinary Medicine, Tulane University School of Medicine, 300 N. Broad St., Suite 102, New Orleans, LA 70119, USA
2Tulane University School of Public Health & Tropical Medicine, New Orleans, LA, USA
3Texas Christian University, Fort Worth, TX, USA
4Texas College of Osteopathic Medicine, Fort Worth, TX, USA
5University of Texas School of Medicine in San Antonio, San Antonio, TX, USA
6Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
7Lake Erie College of Osteopathic Medicine, Arnot Ogden Medical Center, Erie, PA, USA
8Meharry Medical College, Nashville, TN, USA
9University of Illinois-Chicago College of Medicine, Chicago, IL, USA
10University of Colorado-Denver School of Medicine, Denver, CO, USA
11Western University of Health Sciences College of Osteopathic Medicine of the Pacific-Northwest, Lebanon, OR, USA
12University of Chicago Pritzker School of Medicine, Chicago, IL, USA
13Pennsylvania State University College of Medicine, Hershey, PA, USA

Correspondence should be addressed to Dominique J. Monlezun; ude.enalut@uzelnomd

Received 15 December 2017; Accepted 28 February 2018; Published 15 April 2018

Academic Editor: Abdelaziz M. Thabet

Copyright © 2018 Dominique J. Monlezun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Cardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world’s first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students. Methods. This analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies. Results. 3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00–2.28, ) and MedDiet adherence (OR 1.40, 95% CI 1.07–1.84, ), while reducing trainees’ soft drink consumption (OR 0.56, 95% CI 0.37–0.85, ). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally (). Discussion. This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students’ own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic.