Using Cardiovascular Disease Risk Factors to Predict Blood Glucose Levels

Wednesday, April 1, 2009
Exhibit Hall RC Poster Sessions (Tampa Convention Center)
Melissa Jackson, Points2Health, Plantation, FL, Michael E. Young, New Mexico State University, Las Cruces, NM and Tina M. Penhollow, Florida Atlantic University, Davie, FL
Introduction: Diabetes is the sixth leading underlying cause of death in the United States. Complications of this disease can be prevented by controlling blood glucose levels, blood pressure, blood lipids, and regular preventive care and practices. Purpose: The purpose of the study was to identify the cardiovascular disease (CVD) risk factors or combinations of risk factors which were associated with undiagnosed and diagnosed diabetes mellitus.

Methods: The National Health and Nutrition Examination Survey (NHANES), 1999-2004 was used to study predictors associated with CVD and plasma blood glucose. A national sample of adults age 20 and older (N=5,258) with plasma blood glucose values were assessed.

Analysis/Results: SAS was used to perform the weighted analyses. The data were analyzed using frequency counts and logistic regression. The level of significance was set at p < .05. The sample included 50.23% men and 49.77% women. Fifty-five (55.76%) percent of the participants were Non-Hispanic White, 19.51% were Non-Hispanic Black, and 24.72% were Mexican American. The mean age was 46.64 years old. Thirty-nine (39.54%) percent of the sample had elevated glucose (≥ 100 mg/dl). There were 30.77% of the participants who had pre-diabetes and 8.77% with provisional diagnosis of diabetes. Thirty-seven (39.77%) percent Non-Hispanic Whites, 31.77% Non-Hispanic Blacks, and 45.15% Mexican Americans had elevated glucose. Logistic regression analyses were conducted to predict the probability of elevated blood glucose. When gender and ethnicity were used with the logistic regression model, waist circumference (p < .0001), systolic blood pressure (p < .0001) and triglycerides (p < .005) were significant in predicting plasma blood glucose. Three independent variables statistically fit the model for predicting elevated plasma blood glucose with gender: waist circumference (p < .0001), high cholesterol (p < .0001), and diagnosed hypertension (p < .0001). Overall, when considering only gender, men were more likely than women to have elevated blood glucose levels (OR = 1.64). Conclusions: Results of this investigation reveal that a number of CVD risk factors are related to an increase in blood glucose levels, which is shown to be associated with diagnosed diabetes. Addressing these risk factors and lifestyle changes can prevent or delay the onset of diabetes among high-risk adults.