Conclusions. One approach to understanding allostatic load and aging utilizes translational studies in animals that inform the process of “wear and tear” and aging in humans. While the complexity of interacting variables—not to mention the redundancy that is built into many of our systems (such as is exhibited in the proinflammatory cytokine cascade)—may appear daunting, it is important to understand how a lifetime burden of stressors impacts the aging process. In tandem, studies should consider ameliorating these potentially deleterious effects, either pharmacotherapeutically or via psychological or physical (e.g., exercise) interventions.
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The Ohio State University
The Allostatic Load Model has been important in focusing researchers on the concept of cumulative physiological risk. Of special note is its attention to the temporal dimension. In our own work we have proposed the Prolonged Activation Model with an emphasis on anticipatory stress and delayed recovery, in the context of our broader Neurovisceral Integration Model. Similar to the Allostatic Load Model, our Prolonged Activation Model seeks to identify the pathogenic state that leads to organic disease. We feel that the cumulative load put on the system is a critical factor on the path from psychological stress to morbidity and mortality.
There are several areas where our models have focused that may be under-represented in the Allostatic Load Model. One area is individual differences. Whereas the Allostatic Load Model uses individual differences in allostatic load scores to predict morbidity and mortality, we use individual differences in heart rate variability (HRV), for example, to predict differences in stress reactivity per se including anticipatory stress and delayed recovery. Thus we are able to look at individual differences in the regulation of allostatic systems at a more fine grained level than is common in the Allostatic Load Model. This has implications for the understanding of gender and ethnic differences in the accumulation of risk.
A second area is the relationship between the central nervous system and the peripheral nervous system. Our studies of simultaneous measurement of cerebral blood flow or other indices of CNS function and peripheral measures such as HRV allow us to make inferences about the central concomitants of the regulatory processes being indexed by our peripheral measures. We are also able to show how these central and peripheral interactions might be changing with aging or as a function of genotype.
A third area involves the cognitive processes that lead to prolonged activation. In this context our Perseverative Cognition Hypothesis provides insights into the toxic cognitive mechanism that leads to prolonged stress responses and thus the excess wear and tear (cumulative load) on the system. What is actually going on inside the heads, as it were, and how to modify those thought processes represent potential avenues of intervention to decrease cumulative risk.
A fourth area is the use of nonlinear dynamical systems theory and especially the role of inhibitory processes. The interplay of excitatory and inhibitory processes is essential for the proper functioning of a nonlinear dynamical system. Importantly, a little bit of inhibition at the right place and/or the right time can be a critical factor in stress responsivity and whether it leads to prolonged activation or not. Nonlinear dynamical systems theory also provides a broader perspective for the generation of testable hypotheses about the pathways and mechanisms associated with cumulative physiological risk. From a measurement perspective the integration of indices of the parasympathetic nervous system should enhance the measurement of allostatic load.
A fifth area involves possible interventions that could help to reduce cumulative risk. We are currently testing both psychological (e.g., worry reduction and CBT) as well as behavioral (dietary e.g., omega-3 and exercise) interventions to decrease markers of cumulative risk. Interventions aimed at improving allostatic load scores might be fruitfully employed to reduce cumulative risk as well.
And finally, the next steps for moving research on cumulative risk forward include funding mechanisms that allow for such interdisciplinary research to take place. The current disease specific funding mechanisms can not accommodate the type of integrative models that the allostatic load model exemplifies. Further incorporation of these ideas into the allostatic load concept could make it more valuable to researchers.