Neuroscience and biobehavioral reviews · 2017
Stress, autonomic imbalance, and the prediction of metabolic risk: A model and a proposal for research.
СтатьяПоддержка исследования: вне правительства СШАСистематический обзорНазвание и аннотация: Перевод в очереди
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Wulsin Lawson, Herman James, Thayer Julian F
Аннотация
BACKGROUND: Devising novel prevention strategies for metabolic disorders will depend in part on the careful elucidation of the common pathways for developing metabolic risks. The neurovisceral integration model has proposed that autonomic imbalance plays an important role in the pathway from acute and chronic stress to cardiovascular disease. Though generally overlooked by clinicians, autonomic imbalance (sympathetic overactivity and/or parasympathetic underactivity) can be measured and modified by methods that are available in primary care.
METHOD: This review applies the neurovisceral integration concept to the clinical setting by proposing that autonomic imbalance plays a primary role in the development of metabolic risks. We present a testable model, a systematic review of the evidence in support of autonomic imbalance as a predictor for metabolic risks, and specific approaches to test this model as a guide to future research on the role of stress in metabolic disorders.
CONCLUSIONS: We propose that autonomic imbalance deserves consideration by researchers, clinicians, and policymakers as a target for early interventions to prevent metabolic disorders.
METHOD: This review applies the neurovisceral integration concept to the clinical setting by proposing that autonomic imbalance plays a primary role in the development of metabolic risks. We present a testable model, a systematic review of the evidence in support of autonomic imbalance as a predictor for metabolic risks, and specific approaches to test this model as a guide to future research on the role of stress in metabolic disorders.
CONCLUSIONS: We propose that autonomic imbalance deserves consideration by researchers, clinicians, and policymakers as a target for early interventions to prevent metabolic disorders.