Journal article
Modeling the Salivary Cortisol Profile in Population Research
American journal of epidemiology, v 176(10), pp 918-928
15 Nov 2012
PMID: 23100245
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Abstract
In many studies, it has been hypothesized that stress and its biologic consequences may contribute to disparities in rates of cardiovascular disease. However, understanding of the most appropriate statistical methods to analyze biologic markers of stress, such as salivary cortisol, remains limited. The authors explore the utility of various statistical methods in modeling daily cortisol profiles in population-based studies. They demonstrate that the proposed methods allow additional insight into the cortisol profile compared with commonly used summaries of the profiles based on raw data. For instance, one can gain insights regarding the shape of the population average curve, characterize the types of individual-level departures from the average curve, and better understand the relation between covariates and attained cortisol levels or slopes at various points of the day, in addition to drawing inferences regarding common features of the cortisol profile, such as the cortisol awakening response and the area under the curve. The authors compare the inference and interpretations drawn from these methods and use data collected as part of the Multi-Ethnic Study of Atherosclerosis to illustrate them.
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Details
- Title
- Modeling the Salivary Cortisol Profile in Population Research
- Creators
- Brisa N SánchezMeihua WuTrivellore E RaghunathanAna V Diez-Roux
- Publication Details
- American journal of epidemiology, v 176(10), pp 918-928
- Publisher
- Oxford University Press
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative; Epidemiology and Biostatistics
- Web of Science ID
- WOS:000310892700009
- Scopus ID
- 2-s2.0-84869054588
- Other Identifier
- 991014878273604721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Public, Environmental & Occupational Health