Using Reduced Rank Regression to Identify Patterns of Diet and Serum Biomarkers of Obesity to Predict Risk of Cardiovascular Disease and All-Cause Mortality – A New Approach Applied in Epidemiology
Methods: Data (n=13,687 in subjects aged 20 and older) from the third National Health and Nutrition Examination Survey Dietary markers are analyzed. Multiple dietary indicators (vitamins C and D, magnesium, calcium, sodium, vegetable protein, dietary fiber, animal protein, and total fat) obtained using 24-hour Food History Questionnaire, and serum biomarkers (total cholesterol, LDL-C, HDL-C, triglycerides, HbA1c, and CRP) were clustered using traditional and newly proposed RRR approaches to classify patterns of these factors, and associations of RRR1 with CVD and all-cause mortality are analyzed using Cox's regression models.
Results: During an average 12-year follow-up, 3,425 subjects died from all-causes (17.68%) and 1,375 died from CVD (6.90%). As compared to the first quintile of RRR1 score, hazard ratios (HRs,95%CI) of the second to fifth quintiles of RRR1 for CVD mortality were 0.91 (0.68-1.21), 1.02 (0.74-1.39), 1.16 (0.89-1.51) and 1.88 (1.49-2.38), respectively (test for trend, p<0.001). Blacks had 23% higher risk of CVD mortality (HR: 1.23, 95%CI: 1.01-1.52) than Whites after controlling multiple covariates. Similar results were observed in the associations between RRR1 and all-cause mortality. As compared to traditional approaches, RRR1 had a higher predictive power.
Conclusions: RRR provides a better tool to identify patterns of diet and biomarkers of obesity, and improves the predictive power of the associations between exposures and outcomes.
Learning Areas:Public health or related research
Qualified on the content I am responsible for because: I am a senior educator and research in public health for more than 20 years.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.