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, p < 0.001) and MedDiet adherence (OR 1.40, 95% CI 1.07–1.84, p = 0.015), while reducing trainees' soft drink consumption (OR 0.56, 95% CI 0.37–0.85, p = 0.007). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally (p < 0.001). 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.

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Symptoms of constipation occur at all ages, with the greatest prevalence in individuals older than 60 years of age. It is estimated that 35 million individuals suffer from constipation in the USA, but only a small number will ever be diagnosed. Patients identify constipation symptoms differently than physicians. Whereas a patient may define their constipation by symptoms of bloating, distension, feeling of incomplete evacuation, abdominal discomfort, hard stools, and excessive straining, physicians often interpret prolonged timing between movements as the most essential criteria. An evaluation of constipation begins with a focused history of a person's bowel habit, medications, diet, physical activity, and an anorectal examination. In the absence of alarm signs, diagnostic testing for constipation is not routinely recommended in the initial evaluation. First-line management includes lifestyle changes of increased physical activity, high-fiber diets, adequate fluid intake, and bowel management techniques such as a straight back sitting position, using known triggers to stimulate bowel contractions, and a foot stool to elevate knees above bottom during toileting. When refractory to initial management, patients should have anorectal manometry to assess outlet function; additional testing may be required. Biofeedback is an effective treatment option for dyssynergic defecation. A range of traditional and new pharmacologic therapies are available to remedy constipation, from stool softeners to agents that increase intestinal transit. Managing the primary and secondary causes of constipation, incorporating effective bowel management techniques, along with the judicious use of laxatives can reduce constipation symptoms and improve quality of life.

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