Coronary heart disease risk factors among tri-ethnic students at Florida International University

The present study identified and compared Coronary Heart Disease (CHD) risk factors quantified as “CHD risk point standards” (CHDRPS) among tri-ethnic (White non-Hispanic [WNH], Hispanic [H], and Black non-Hispanic [BNH]) college students. All 300 tri-ethnic subjects completed the Cardiovascular Risk Assessment Instruments and had blood pressure readings recorded on three occasions. The Bioelectrical Impedance Analysis (BIA) was used to measure body composition. Students' knowledge of CHD risk factors was also measured. In addition, a 15 ml fasting blood sample was collected from 180 subjects and blood lipids and Homocysteine (tHcy) levels were measured. Data were analyzed by gender and ethnicity using one-way Analysis of Variance (ANOVA) with Bonferroni's pairwise mean comparison procedure, Pearson correlation, and Chi-square test with follow-up Bonferroni's Chi-square tests. ^ The mean score of CHDRPS for all subjects was 19.15 ± 6.79. Assigned to the CHD risk category, college students were below-average risk of developing CHD. Males scored significantly (p < 0.013) higher for CHD risk than females, and BNHs scored significantly (p < 0.033) higher than WNHs. High consumption of dietary fat saturated fat and cholesterol resulted in a high CHDRPS among H males and females and WNH females. High alcohol consumption resulted in a high CHDRPS among all subjects. Mean tHcy ± SD of all subjects was 6.33 ± 3. 15 μmol/L. Males had significantly (p < 0.001) higher tHcy than females. Black non-Hispanic females and H females had significantly (p < 0.003) lower tHcy than WNH females. Positive associations were found between tHcy levels and CHDRPS among females (p < 0.001), Hs (p < 0.001), H males (p < 0.049), H females (p < 0.009), and BNH females (p < 0.005). Significant positive correlations were found between BMI levels and CHDRPS in males (p < 0.001), females (p < 0.001), WNHs (p < 0.008), Hs (p < 0.001), WNH males (p < 0.024), H males (p < 0.004) and H females (p < 0.001). The mean knowledge of CHD questions of all subjects was 71.70 ± 7.92 out of 100. The mean knowledge of CHD was significantly higher for WNH males (p < 0.039) than BNH males. A significant inverse correlation (r = 0.392, p < 0.032) was found between the CHD knowledge and CHDRPS in WNH females. The researcher's findings indicate strong gender and ethnic differences in CHD risk factors among the college-age population. ^

Statistical analysis and optimal classification of blood cell populations using Gaussian distributions

This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gaussian distributions through a novel concept that relates the Fisher distance to the percentage of data overlap. The derivations are expanded to provide a generalized mathematical platform for determining an optimal separating boundary of Gaussian distributions in multiple dimensions. Real-world data used for implementation and in carrying out feasibility studies were provided by Beckman-Coulter. It is noted that although the data used is flow cytometric in nature, the mathematics are general in their derivation to include other types of data as long as their statistical behavior approximate Gaussian distributions. ^ Because this new figure of merit is heavily based on the statistical nature of the data, a new filtering technique is introduced to accommodate for the accumulation process involved with histogram data. When data is accumulated into a frequency histogram, the data is inherently smoothed in a linear fashion, since an averaging effect is taking place as the histogram is generated. This new filtering scheme addresses data that is accumulated in the uneven resolution of the channels of the frequency histogram. ^ The qualitative interpretation of flow cytometric data is currently a time consuming and imprecise method for evaluating histogram data. This method offers a broader spectrum of capabilities in the analysis of histograms, since the figure of merit derived in this dissertation integrates within its mathematics both a measure of similarity and the percentage of overlap between the distributions under analysis. ^