alexa THE UTILITY OF RED CELL DISTRIBUTION WIDTH AS A PARAMETER FOR CALCULATING INDICES OF ALLOSTATIC LOAD
ISSN: 2161-0711

Journal of Community Medicine & Health Education
Open Access

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2nd World Congress on Public Health & Nutrition
March 22-23, 2017 | Rome, Italy

Ghalib A Belloa and Gerard G Dumancas
Icahn School of Medicine at Mount Sinai, USA
Louisiana State University, USA
Posters & Accepted Abstracts: J Community Med Health Educ
DOI: 10.4172/2161-0711.C1.025
Abstract
Allostatic Load is a construct used To quantify the cumulative burden of exposure to stress that, over the course of an individual’s life, exert a toll on the body’s physiological functions, predisposing to the development of various chronic ailments and conditions. The systemic physiological dysregulation resulting from increasing allostatic load can be quantified through chemical imbalances in various organ systems. Many studies have attempted to do this by combining multiple clinical parameters (e.g. albumin, C-reactive protein, cholesterol, etc.) to produce univariate indices that serve as measures of allostatic load. The general validity of these indices has been confirmed through studies showing they are good predictors of adverse health outcomes, mortality, hospital utilization and age-related pathologies. They have also used to demonstrate the existence of socioeconomic and demographic health disparities. In this study, we show the value of including red blood cell distribution width (RDW) among the panel of clinical parameters used to calculate allostatic load. RDW quantifies the degree of heterogeneity in erythrocyte volume and has shown strong correlations with mortality and a broad spectrum of diseases. A review of the existing literature on allostatic load reveals its underutilization in this area, despite being a standard component of blood count panels. Using Cox Proportional Hazards regression and Adaptive Index models, we show that calculating allostatic load using RDW (in addition to the common set of clinical parameters typically used in most studies) yields a significantly improved index. It demonstrates a superior ability to predict mortality, health status and comorbidities than the standard version currently in use.
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