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Tools for Measuring and Analyzing Cortisol Levels in Population Studies of Health Disparities

a PSC Research Project

Investigators:   Ana Diez Roux, Jeffrey Morenoff, Trivellore Raghunathan, Brisa Ney Sanchez Loya

Disparaties in health by socioeconomic position and race/ethnicity have been documented for numerous health outcomes. Developing a more comprehensive understanding of the reasons for health disparaties that integrates factors defined at multiple levels (e.g. from community-level or neighborhood processes to biological factors) and that explicates common or interreleated processes that generate disparities in multiple health conditions remains a major challenge. This is important not only to understand the etiology of multiple diseases, but also to develop strategies to eliminate health disparities. One process that has been hypothesized to contribute to disparities in multiple health domains is psychosocial stress. It has been argued that exposure to psychosocial stressors repeatedly over long periods has biological consequences with implications for multiple health conditions, including outcomes as diverse as low birth weight, asthma, and cardiovascular disease. Two major challenges in studying the role of psychosocial stress include the (1) measurement and characterization of biological markers of the stress response (2) examining how this complex biological response varies as a function of higher-level (or upstream) determinants such as socioeconomic position and community characteristics. We propose to address both challenges through the development of methodological tools necessary to characterize and analyze biolmarkers of the stress response (specifically cortisol profiles) in population-based studies. The overall goal of our project is to improve the methodolocial tools and data collection protocols necessary to understand how upstream determinants (such as neighborhood-level factors) trigger biological processes (specifically in the stress response) that may generate disparaties in multiple disease outcomes in the population. We will use a unique multilevel dataset to investigate the use of different methodological approches in order to make specific recommendations regarding (a) data collection protocols for salivary cortisol data (specifically regarding number and timing of samples) and (b) data analyses involving cortisol profiles as outcomes or predictors. The specific aims of our project are: (1) To investigate and contrast statistical methods useful in characterizing different features of the biological stress response, as assessed by repeat measures of salivary cortisol. (2) To examine measurement properties of the features of the cortisol curve in order to be able to make specific recommendations regarding the best data collection tools and protocols in future studies and (3) To investigate and contrast methods useful in examining how features of the stress reponse curve are related to neighborhood and individual-level predictors as well as to individual-level outcomes. Addressing these Aims will improve the tools available to researchers to study how communities and neighborhoods trigger biological processes in humans that relate to health disparities in the population (one of the stated aims of this RFA).

Funding Period: 09/26/2007 to 07/31/2012

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