Pacific D
Statistical Modeling of Setting Foods Healthy Index (306650)
Mason Chen, Stanford OHS*Mason Chen, Stanford OHS
Keywords: Health Index, Health Metric, Priciple Component Analysis
This presentation would demonstrate how to set the Foods Healthy Index of preventing cardiovascular disease (CVD). In modern Health Policy, Statistics can model the Health Index and innovate the Health Metric and Policy. Several Caffeine products are analyzed. A health index was constructed considering different nutritions, including: saturated fat, cholesterol, sodium, carbohydrates, dietary fiber, sugars, protein, and caffeine. The first health index was derived based on Scientific Literature Research. Antioxidant activity of flavonoids from Caffeine component can reduce free radical formation and scavenge free radicals. The second Health Index was derived based on the eigenvalues and eigenvectors of the first two Principle Components. The Principle Component Analysis (PCA) was used to explore all nutrition factors to inform on the utility of the health index in relation to its link to CVD prevention. Two health indexes have been observed 80% correlation across Caffeine products associated with CVD health risk. This Healthy Index methodology can be commonly practiced across all Foods Products for Disease Risk Management as a critical part of making Health Policy effectively.