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Reconceptualizing the relationship between racial health disparities and allostatic load through physiological risk profile cluster analysis


Sunday, November 1, 2015

Amber Johnson, MPH, Department of Public Health Education, University of North Carolina at Greensboro, Greensboro, NC
William Dudley, PhD, Department of Public Health Education, University of North Carolina at Greensboro, Greensboro, NC
Laurie Wideman, BSc, MS, PHD, Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC
objective: The objective of this study was to expand upon the seminal work in racial disparities and allostatic load (AL) by Geronimus using population based data from the National Health and Nutritional Examination Survey (NHANES). We aim to further Geronimus’s work by retaining raw data scores to identify risk clusters from biomarkers used to calculate AL.  Further, we aim to explore predictors of cluster membership.

methods: NHANES data was used to conduct a two-step cluster analysis. Multinomial logistic regression was used to identify predictors of cluster memberships adjusting for age.  We explored odds of cluster membership by race, gender, and food security. 

results: Cluster analysis revealed five physiological profiles: Vascular Risk (n=382), Kidney Risk (n=793) Inflammatory Risk (n=460), Low Overall Risk (n=1862) and Cholesterol Risk (n=1888).   Race, gender, and food security were significant predictors of risk profile. The odds for each risk profile were significantly higher for men for all but the inflammation risk. Compared to Whites, Blacks had 104.6% higher odds of a kidney risk, 51% higher odds of an inflammatory risk, but a 46.6% lower odds of a cholesterol risk. Hispanics also yielded greater odds of inflammatory risk while exhibiting lower odds of a kidney risk. The odds of inflammatory risk was significantly higher for those with very low food security compared to full food security.

conclusion: The cluster analysis process with raw data provided expanded Geronimus’s work by revealing risk profiles for Blacks and Hispanics who have been shown to experience AL earlier in life.

Learning Areas:

Epidemiology
Public health or related research
Social and behavioral sciences

Learning Objectives:
Identify and describe physiological risk clusters associated with variables used to calculate allostatic load. Identify predictors of physiological risk cluster memberships.

Keyword(s): Epidemiology, Health Disparities/Inequities

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I began conducting statistical analyses during my undergraduate studies and have worked to strengthen my skills in data analysis. I have also obtained a Master's in Public Health and hold a Certificate in Field Epidemiology. Additionally, I conducted data analysis and interpretation for this abstract with the assistance of my co-authors.
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.

Back to: 2066.0: Poster Session - Health Behavior, Disparity Research and related Topics in Public Health Epidemiology