Presenters: Sean Marchant, College of Education, Exercise & Nutrition Sciences
Authors: Sean Marchant, Harrison Williams, Julian Chan, David Aguilar-Alvarez
Faculty Advisors: Julian Chan, College of Science, Mathematics
Institution: Weber State University
Introduction: Having low levels of HDL and a high total cholesterol level are indicators for elevated risk for cardiovascular disease (CVD). Diet can be a modulator of HDL-C and TC and within the relevant dietary components, consumption of saturated fats have shown to be of significant importance. Purpose/Hypothesis: We analyzed the intake of saturated fats and their association with TC and HDL-C levels among the student participants at Weber State University. We hypothesize that a high intake of saturated fat has a negative effect by decreasing HDL-C and increasing TC levels. Research Methods: Plasma lipids and two-day diet records were analyzed from 385 Weber State students (ages 18-65). Multiple linear regression analysis (MLR) was performed to determine if the type of fat by calories or percentage were predictors of HDL-C and TC. R-studio program was used for statistical analysis. Data Results: Regression analysis suggests the primary predictor for TC (mg/dL), among the variables under consideration, was total calories consumed. On a log scale, the MLR suggests an increase of 100 total calories will result in an average decrease of 0.55% in total cholesterol. Regression analysis for HDL cholesterol (mg) suggests use of a log scale as well, with the following results on average: an increase of 1 g. of saturated fat in an individual’s diet will result in a decrease of 0.54% HDL. Conclusion: The best model to predict HDL-C levels was based on grams of saturated fat consumption. Our current dietary recommendations for saturated fat consumption are based on percent of calories rather than amount consumed in grams. This study hints the importance to also consider amounts of fats to produce predictive models of CVD.