Quantifying "stress" in epidemiological studies
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2015/03/01
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By Miller DB
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Description:Using animal data in assessing the cumulative risk caused by exposures to chemical and non-chemical stressors requires extrapolation from animal to human. Incorporating epidemiological data in the evaluation obviates this need but requires methods able to quantify the levels of stress and their association with disease. Prolonged exposure to non-chemical stressors of both a psychological and physical nature (i.e., chronic stress) as well as to various pollutants can play an etiological role in disease including cardiovascular disease (CVD). Dr. Miller will discuss the measurement of stress and the most suitable metrics for quantifying stress in epidemiology studies while emphasizing the caveats and limitations in their use. Data from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study provides information on the body systems (e.g., hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS)) involved in responding to stressors and their possible relationship to CVD. Police officers are a susceptible and marginalized population who, relative to the general population, suffer greater CVD morbidity and mortality that may be linked to inherent police work stressors. These include long work hours, shift work, trauma, high demand, and pollutant exposure. The longitudinal and multi-factorial design of the BCOPS study will allow us to determine whether stress measures/biomarkers are associated with the chronic progression of subclinical CVD, metabolic derangements and psychiatric disorders. In cross-sectional data a deranged HPA response, as measured by the salivary cortisol response to challenge, is associated with impaired brachial artery reactivity and metabolic syndrome - preclinical indicators of CVD. Self-evaluation of police stressors revealed gender specific associations with poor HPA response and low heart rate variability. Our findings suggest a complex association between these various endpoints that often differ by gender but are potentially interpretable and predictive using allostasis models of causation. [Description provided by NIOSH]
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ISSN:1096-6080
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Volume:144
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Issue:1
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NIOSHTIC Number:nn:20045900
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Citation:Toxicologist 2015 Mar; 144(1):170
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Federal Fiscal Year:2015
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Peer Reviewed:False
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Source Full Name:The Toxicologist. Society of Toxicology 54th Annual Meeting and ToxExpo, March 22-26, 2015, San Diego, California
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Main Document Checksum:urn:sha-512:f0428dc5f1fd1b7f6b5b73b7b78c6a2324165a49142c62804e93fd0bcdbc8afc82cdd3a34aa2ba9465ea5ed0ee2a60930131f2d4c8ad6978f54a2569557f1288
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