Behavioral and Social Research Program National Institute on Aging

Charge to Participants in the NIA Workshop on Allostatic Load

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Charge to Participants in the NIA Workshop on Allostatic Load

In preparation for the upcoming NIA Exploratory Workshop on Allostatic Load, participants were asked to prepare a short (2-4 pages) statements outlining their views on how research on allostatic load and the study of cumulative risk more generally can be most fruitfully advanced in the behavioral and social sciences.  These statements are intended to set the foundations for dialogue, at the workshop, on research and resource needs for achieving this goal.

As described in the foregoing background document, there are a number of conceptual and methodological issues that could be addressed at the workshop. Participants were asked to offer creative, well-informed input on where the emerging research opportunities and needs lie within thier own and related fields.  
Participants were asked to consider the following when preparing their statements:

  1. How has the concept of allostatic load had a positive (or negative) impact on work in your field? Are there more valuable alternative approaches to the study of cumulative physiological risk, and if so, what are they and what is their relative advantage?

  2. What could be done to make this concept more valuable to research on social and behavioral factors in aging?

  3. What are the most critical measurement issues, in your view? Are there specific data needs for addressing these questions?

  4. What would be the most important "next steps" in moving research on allostatic load, or cumulative physiological risk more generally, forward?

Statements from invited participants follow.

John Cacioppo

University of Chicago
What is adaptive or maladaptive, healthy or unhealthy, depends on context, and what may be good for one tissue may be life saving, but may have negative impact on another tissue with mortal consequences in the long run. The regional positioning of immunocytes in response to acute stress may provide the host with a selective advantage should aggressive behavioral interactions lead to cutaneous wounding and the possibility of infection (Dhabhar & McEwen, 1997). The selective advantage that may accompany acute stress does not extend to chronic forms of stress, however, as the prolonged activation of the HPA axis and sympathetic nervous system seen in chronic stress tends to suppress cellular immunity (Lupien & McEwen, 1997; Sheridan, 1998), reduce response to vaccination (Kiecolt-Glaser et al., 1996), and slow the healing of experimental cutaneous and mucosal wounds (Kiecolt-Glaser et al., 1995; Marucha et al., 1998; Padgett, Marucha, & Sheridan, 1998). These complexities underscore the interdependence between organisms and their physical and social environments. Restorative mechanisms such as a balanced diet, moderate exercise, sleep, and rich social connections may have the salutogenic (e.g., stress buffering) effects, whereas a diet high in fat, the use of tobacco and alcohol, a sedentary lifestyle, and hostility and isolation exacerbate the deleterious effects of chronic stress. Our understanding of the complex regulative and restorative processes of the organism – and the balance within –is therefore fostered by a multi-level integrative analysis.

Although the biological substrates for the etiology and course of chronic disease are influenced profoundly by the physical and social world, it remains to be determined to what extent these influences result in individual differences in allostatic load as a consequence of differential exposure to stressors, differential reactivity to stressors, or differential recovery from stressors – and why.

Second, a good deal is now known about stress physiology (e.g., Chrousos, 2001), but the rostral neurobehavioral systems that orchestrate organismic-environmental transactions (Berntson et al., 1998, in press) and the psychological transduction mechanisms (e.g., health behaviors, health utilization, stress buffering) remain only partially mapped. “Stress” has been assigned a special role in the development of allostatic load, but the concept of stress itself is often vaguely (or circularly) defined. Operationalizations and measures across studies, especially across animal and human studies, were regularly so different (e.g., restraint, hypoglycemic, orthostatic, mathematic stressors) that results are sometimes difficult to compare or reconcile.

Third, stressors are not always negative, either, as positive as well as negative events are considered stressors in studies focused on predicting health (Holmes & Rahe, 1967). Further complicating matters, the measurements of stress within a given study are often so weakly correlated that they provide poor convergent validity for the construct of stress (e.g., Lacey, 1959; Johnson & Anderson, 1990). In short, neither stress nor health is a simple, unitary concept, and the search for a singular universal mechanism relating stress to health is doomed to failure. The concept of allostatic load, too, while useful at a molar level of analysis, is misleading if applied to specific underlying mechanisms as if there were a single cause of wear and tear. The concept is useful because it represents a broad and multifarious category of specific and largely unrelated transduction mechanisms that contribute to the wear and tear on the organism.

Why not simply ignore the molar constructs of integrative physiology and focus on the details of the cellular machinery? As Claude Bernard (1878/1974) opined over a century ago and Lewontin (2000) has echoed more recently, the organization and function of the elemental parts of an organism can be understood comprehensively only within the context of its transactions with its physical and social environment. Lewontin’s (2000) analysis suggesting that the reduction in mortality from infectious diseases during the late 1800’s and early 1900’s is attributable to a general trend of increases in real wage, an increase in the state of nutrition, and a decrease in the number of hours worked – that is, a decrease in the wear and tear on the organism and improved opportunities for the organism to heal itself – hints at causal factors and targets of interventions to which we would be blind by focusing on cellular mechanisms alone. Although we are beginning to understand how the brain integrates the regulatory and restorative forces of the body to foster health and adaptation to environmental challenges, it is clear that health psychology will have much to contribute to this understanding for a long time to come.

The theory of allostasis remains to be fully delineated. Improvements in operationalizations and construct-valid measures would promote theoretical tests and refinements. Specification of the neurobiological basis of allostasis would advance our understanding of the functional system. Collaborative studies involving animal models and longitudinal human studies would promote a mapping of CNS-PNS orchestration and the decay of this orchestration.

Sheldon Cohen

Carnegie Mellon University

Allostatic Load/Cumulative physiological risk
This is a quick list of my thoughts about Allostatic Load (AL) Theory and primarily about AL measurement. I should say that while I have been involved multiple discussion about AL that occurred in the MacArthur SES network and in various other forums starting when Bruce first drafted the NEJM paper, I do not carefully follow research in AL or changes in its conceptualization or measurement. Hence I hope you will excuse any issues raised below that may have been addressed more recently as the theory and measurement of AL has grown.
General Opinion: I like the AL heuristic, I don’t like the way it has been operationalized. McEwen’s NEJM paper suggests that enduring chronic stressors can result in the disturbance (dysregulation) of multiple systems. Dysregulation can mean that the system overreacts, underreacts, overreacts but cannot return to normal, etc. The application of this idea to the study of specific systems can be powerful. For example, chronic stress influences how effectively we regulate our immune response, it does not just cause immunosuppression.
Which system is influenced in an individual presumable would be moderated by individual vulnerabilities, e.g., genetic, previous illness, etc. Less clear (and in my recall not a part of the original theory) is the hypothesis that chronic stress disrupts multiple systems and consequently aggregating across systems is an appropriate way of measuring AL. However, this is how AL is generally measured.
I think there have been two underlying weakness in AL measurement. The first, as suggested above, is aggregation across multiple systems without adequate consideration of the possibility that a single or specific sets of individual systems are what is important. The second is that it is based on what has been (and in some cases can easily be) measured rather than what needs to be measured to provide an assessment of dysregulation. (This includes CARDIA at 15 years where pretty much every standard measure that might assess AL and was practical was selected, rather than asking what is the minimum requirement for assessing dysregulation across multiple systems.)
Up or Down or in the Middle? Clearly a problem with many attempts to assess AL is that they don’t focus on regulation but rather on markers moving in what is considered a direction of pathogenic risk based on standard risk factor type analysis (e.g., high blood pressure is bad). A measure consistent with the theory would focus on dysregulation whether assessed as low, high, over and under reaction to stress, or inability to return baseline after stress.
Apples and Oranges? Many of the studies presumed to measure “allostatic load” aggregate across biomarkers representing a range of different physiological systems. Interestingly, they generally unit weight biomarkers, not systems. Many of the biomarkers are measures of various cardiovascular functions and metabolic functions. As a consequence, if the measure is related to something (e.g., measure of SES or chronic stress or disease risk) it could be entirely due to its influence on a single system. If an association is not found, there may be relationships with individual systems, but the overall effect is wiped out (or the effect size is reduced) by randomness across other systems.
If one believes that aggregating across systems is important, than one should 1) define the important systems to measure (e.g., ANS, SAM, HPA, Cardiovascular, Immune, etc.); 2) develop adequate measures of the REGULATION of each of these systems; and 3) equally weigh systems or determine weights based on a theoretical basis in creating an aggregate.
Specificity or generality? There are reasons to think that specific biomarkers used in assessing AL should be associated with specific disease outcomes. (For example, cardiovascular system markers are associated with cardiovascular disease risk). Comparisons of additional variance accounted for after controlling for the system that one expects to predict would be helpful. For example, it is possible that failure in one system drives (or is otherwise correlated with) failure in another. This doesn’t mean that you need failure in both to influence a specific disease outcome, although aggregation of system failure may make it look this way.
Does it depend when it happens for whether it counts toward AL? AL measures also tend to include both what McEwen called primary and secondary mediators. Primary measures are immediate nonspecific biomarkers of stress, e.g., catecholamines and cortisol. Anything further downstream is considered secondary. Current work does not differentiate between secondary measures that are markers of disease risk versus disease pathology.
More recently, inflammation has been considered part of the primary mechanism (see background statement). Although inflammation may play an upstream role in disease progression (as hypothesized for coronary artery disease), it clearly is a measure of underlying inflammatory processes. Inflammation occurs in response to tissue damage. Therefore it is a marker of an ongoing (although sometimes premorbid) disease process. Hard to see it as a primary mediator…
Should dysregulation be assessed as a process?

Maybe we should consider an assessment of AL that addresses HOW FAR DOWN STREAM the dysregulation has moved. For example, the difference between a person with elevated cortisol and one with elevated cortisol and inflammatory markers?


  1. Develop the measures as assessments of dysregulation (not just convenient measures of risk). This would include some thought about the nature of dysregulation and assessments of reactivity and recovery as well as the usual basal measures.

  1. Develop measures of individual systems. This requires a clear conceptualization of each system and preliminary empirical work to see how measures cluster. For example, Steve Cole did some initial work with measuring the ANS that was successful in linking social inhibition to HIV progression.

  1. Consider the individual variables that might predict individual differences in what system(s) would show vulnerabilities under stress.

  1. Consider an assessment of AL that addresses HOW FAR DOWN STREAM the dysregulation has moved. For example, the difference between a person with elevated cortisol and one with elevated cortisol and high blood pressure, and one with elevated cortisol, high blood pressure and inflammatory markers…

  1. Studies that focus on the stability/changes in the stress (social and physical) environment over time.

Steve Cole

I study social regulation of gene expression. My work maps the “social signal transduction pathways” by which socio-environmental processes regulate broad patterns of gene transcription across the entire human genome (and across viral and tumor genomes). This work is generally molecular biological and computational/bioinformatic, with a concrete focus on neuroendocrine receptors, intracellular signal transduction pathways, transcription factor activation, and other aspects of gene regulation. My lab focuses on the subset of gene regulation pathways that are empirically responsive to social inequality, social isolation, and “stress”. We are not concerned with the activity of any individual gene, except insofar as it provides a good generalizable example of how social regulation of gene expression takes place. Our primary objective is understanding the higher logic of a socio-environmentally responsive genome, including:
1) Which broad groups of genes are sensitive to social factors?,

2) Which signal transduction pathways mediate those effects?,

3) Which genetic polymorphisms moderate those effects?, and,

4) What teleologic purpose is served by socially responsive genome?

I was trained as a social psychologist (Stanford), am employed as a molecular biologist (UCLA School of Medicine and HopeLab Foundation), and do most of my work with math and computers. I began this work as a virologist, detailing the molecular processes by which psychosocial factors drive the HIV-1 virus. We eventually determined that HIV-1, and most other successful human viruses, have evolved to take advantage of a biochemical “stress niche” in their hosts (us). My work now focuses on understanding that human genomic niche, and ameliorating its impact on viral infections and cancer.

(1) How has the concept of allostatic load had a positive (or negative) impact on work in your field? Are there more valuable alternative approaches to the study of cumulative physiological risk, and if so, what are they and what is their relative advantage?
I believe the general theory of Allostatic Load is likely correct, potentially quite useful, and not currently being operationalized in ways that are scientifically helpful. My inclination would not be to seek other theories, but to seek better biological (and behavioral) measures of cumulative biological “wear and tear” and health risk. It would be helpful if researchers maintained a clearer distinction between the hypothesized mediator (allostatic load) and the outcomes it is invoked to explain (e.g., disease biology).
(2) What could be done to make this concept more valuable to research on social and behavioral factors in aging?
The concept of allostatic load is valuable, but most biomarkers currently used as measures of allostatic load do not fit the bill. Many biomarkers offered as measures of allostatic load may actually be measures of the chronic disease processes that allostatic load is invoked to explain (e.g., cytokine levels) or measures of transient states rather than cumulative states (e.g., hormone levels). Telomere length is, in principle, a good biomarker of cumulative challenge because the state of the biological “analyte” (the thing being measured) is known to change in a cumulative fashion with stimulation (i.e., cell turn-over progressively shortens the terminal chromosome cap, though telomerase introduces complications). Glucocorticoid resistance in leukocytes may also reflect cumulative exposure, and it is conceivable that flattened diurnal cortisol slopes might also (more longitudinal work is needed to validate the later). Current hormone or cytokine levels do not have that cumulative property and thus cannot serve as measures of a cumulative process. Any biological parameter that does not show a monotonic change in value over time must indicate something else instead of (or in addition to) cumulative biological challenge.
(3) What are the most critical measurement issues, in your view? Are there specific data needs for addressing these questions?
a) Better biomarkers of cumulative biological effects,

b) better behavioral/neurobiological measures of cumulative risk exposure, and

c) a clear distinction between measures of cumulative challenge and measures of current disease biology.
Neural proxies for cumulative challenge should be developed more fully (e.g., functional neural imaging responses to targeted probe stimuli, progressive innervation or denervation of solid tissues, epigenetic regulation of neural genomes or neurally-responsive cells such as leukocytes, etc.). Much of this biological “history” may be encoded in the internal regulatory structure of cellular response to environmental stimulus (e.g., glucocorticoid resistance) rather than in the extracellular parameters released from cells (e.g., circulating hormone levels).
(4) What would be the most important "next steps" in moving research on allostatic load, or cumulative physiological risk more generally, forward?
a) A greater focus on biological parameters that are truly cumulative (e.g., more the quality of telomere shortening) or are functionally historical (e.g., glucocorticoid resistance)

b) treatment of “state” parameters (e.g., hormone levels, cytokine levels, CRP levels, etc.) as outcomes to be explained rather than cumulative mediators, and

c) a greater understanding of cumulative neurobiological allostasis, and its biomarkers. This would provide measurement advantages (relative to self-report) and fill in an important missing piece in the basic theory of how historical environmental stimuli alter the current functional activity of the body.
I believe the later concept represents the most significant contribution of Allostatic Load theory. How is it that past events can affect the functional characteristics of the present body? To answer this question, it might be helpful if Allostatic Load theorists borrow more deeply and directly from developmental biology and psychology. Telomeres are clever in this regard. What else might we borrow from the biology of life-span development?
Eileen Crimmins

University of Southern California
Re: Relevance of Allostatic Load to Measuring Risk in Large Populations

How has the concept of allostatic load had a positive (or negative) impact on work in your field? Are there more valuable alternative approaches to the study of cumulative physiological risk, and if so, what are they and what is their relative advantage?

The work on allostatic load has been central in promoting the idea that the body has a set if integrated physiological systems. The demonstration that large components of allostatic load can be measured in community settings, has led to the incorporation of many of these indicators in population level surveys. All of this has been extremely valuable and changed the world of data collection very rapidly

However, the measurement to date still has limited physiological coverage in populations because of difficulty of measuring some physiological systems. So the theoretical idea may not be fully addressed. In addition while allostatic load has an emphasis on reaction to stress, there is a category of markers of organ reserve that might be more appropriate for use as an indicator of “frailty” or loss of function that is appropriate for evaluating population health change. In general a separation into indictors of early and late trajectory physiological change would be useful.

What could be done to make this concept more valuable to research on social and behavioral factors in aging?

Review of conceptual issues to clarify how empirical tests are able to address theoretical ideas.of allostatic load and integration of this concept with ideas of population health change.

What are the most critical measurement issues, in your view? Are there specific data needs for addressing these questions?

In population studies, the use of new methods has increased the data collection more rapidly than the development of assays using non invasive collection methods such as saliva and blood spots.

What would be the most important "next steps" in moving research on allostatic load, or cumulative physiological risk more generally, forward?

Most immediately, the large national samples are not measuring stress indicators. This seems essential to test the most important hypotheses about stress and discrimination as factors in health differentials.

Elissa Epel

Influence of Allostatic load (AL), Allostasis and health.

The concept of allostasis and allostatic load have had a large impact on my research. AL model promotes a developmental model of disease progression, toward general pathways, across systems, away from single biomarkers. It is important in stress mechanism research both to understand general pathways of chronic disease (AL, met syndrome) as well as specific pathways (ie, Lutgendorf’s model of ovarian cancer, Dhabhar’s model of skin cancer).

To understand health, not disease, it is helpful to measure allostasis (albeit a moving target) and, further, whether ‘enhanced allostasis’ exists (functioning above baseline, characteristic of youthful systems) (See Bower et al, 2007). Examples of enhanced allostasis may be the high levels of variability (heart rate variability, hormonal pulses) in youthful systems, which degrade over time. The concept of recovery is crucial to understanding allostasis. Most reactivity studies do not examine longer term recovery from acute stressors. This may be one critical period during which emotional regulation and cognition (positive appraisals vs. rumination) are more closely tied to physiology/states of arousal. My preliminary data (that I will show) suggests that emotional reactivity and rumination during recovery are linked to cellular aging markers. High variability and rapid recovery may represent enhanced allostasis, which may be predictors of longevity. This is mere speculation, but to understand aging, we need studies that test whether there are unique mechanisms that predict longevity, which may be different than those that predict early disease. The AL model provides hypotheses or phenotypes about healthy vs. aged profiles of arousal during acute and chronic stress states. The concept is clarifying, the operationalization of both allostasis and AL is challenging (below).
What could be done to make this concept more valuable to research on social and behavioral factors in aging?
It would be helpful to have better measurement of primary mediators, which is challenging. We need better identification of the key measures in an allostatic load battery, and which aspects are most closely tied to behavior, stress, and genetics. One long standing obstacle in stress research, only recognized more recently, is that primary mediators such as cortisol levels are a dynamic measure, and dysregulation can lead to both hyper or hypocortisolemia. Researchers need better statistical models to deal with ‘bimodal’ variables of dysregulation, and to use variance like this as a way to understand different phenotypes of dysregulation. We need markers of chronic stress that don’t depend on how stressful one’s day was. For example, imaging measures of adrenal volume, thymus involution, and possibly dexamethasone nonsupression, should represent a history of chronic stress arousal, at least ACTH or cortisol.
It would be helpful to develop better measurement of chronic stress. One might wonder why AL is not related to distress in several population based studies. Often we are trying to link a ‘state’ measure available, like depression over the last two weeks with what may be largely a long term reflection of lifestyle and wear and tear. Why should recent mood be strongly linked to long standing footprints of dysregulation? We need cumulative models of distress. We are currently trying to measure lifetime histories of depression better. Measuring stress retrospectively is even more problematic. Measurement of emotional reactivity may be more closely linked with allostasis than trait measures of negative affect or depression. What types of stress are most damaging, and what does this look like in the brain? Studies linking brain chemistry and activity with peripheral biomarkers would be invaluable. However, we are limited by our inability to measure important central peptides in humans peripherally (eg, NPY, oxtytocin, opioids in the VTA) and there is a lack of ligands that would allow us to see PET scan activity.
Given the central role that chronic stress plays in accelerating aging, we need a better multilevel understanding of stress vulnerability and stress resistance. The problem becomes obvious when we realize that there is no agreed upon operationalization of either term. What is stress vulnerability or stress resistance, psychologically or physiologically? Many of us have answers to that, from our individual paradigms, but they probably have little “shared variance.” It is imperative to identify the most common phenotypes of a maladaptive stress response—including whatever components are most important in the pathway toward aging--- affective, cognitive, genetic, and in terms of neural activity and biochemical substrates centrally and peripherally.
We need to move beyond tautological models – eg, linking high blood pressure to hypertension to CVD, to studies that point to mechanism. This is where models of somatic cellular aging or immunosenescence, and gene expression may be helpful. Focusing on cell based markers of biological aging allows us to measure aging in youthful systems as they develop, and allows examination of life course perspectives. Markers of how cells age –such as telomere length—and the biochemical mediators such as Insulin exposure, oxidative stress, and inflammation-- may reflect poor allostasis even in young people. However, mid life is a time that a critical mass of mitotic cells become senescent and thus biological aging becomes manifested in phenotypes of aging (graying, wrinkling, clinically measurable disease). It is helpful to have aging studies start at mid-life or earlier.
What would be the most important "next steps" in moving research on allostatic load, or cumulative physiological risk more generally, forward?
There is a need for ‘mechanistic’ longitudinal studies. Given the nonlinearity of physiological processes (eg, bidirectional relationships, webs of interconnections), cross sectional research can lead to false assumptions. With limited resources, there should be more focus on causal mechanisms. This includes longitudinal studies with experimental studies embedded (like MIDUS). Well characterized samples could be taken advantage of. The lack of investment in samples that cannot be followed sufficiently, due to limited funds to extend research longitudinally, is an obstacle to understanding the process of aging.
Once we have developed more advanced conceptual models of phenotypes of “stress” –we need multilevel research examining how “stress vulnerability” leads to transmission of disease risk and conversely, how “stress resilience” may confer longevity. This might require multigenerational studies that include prenatal conditions. Large longitudinal studies that examine women and men in young adulthood, and how they pass on traits such as emotional reactivity, stress hormone reactivity, insulin resistance, and telomere length to their progeny, and substudies to examine mechanisms in depth. Such studies require multi level analyses, and need to include social factors, genetic, behavioral phenotypes, neurobiology at least as well as it can be measured in humans.
Importance of health behaviors as moderators and mediators not covariates.

How much of AL is related to health behaviors, and how much of our health behaviors are environmentally constrained or influenced by genetic variations? Linear models are limiting, and the large effects of stress may be in interaction with behavior. Health behaviors are often used as covariates but actually affected by stress. Behavior can mediate negative effects of stress (such as the interaction of high fat diet and stress) or, in the case of exercise, can moderate and buffer impact of stress. As an example, there have been many iterations of human studies addressing relationships between stress and visceral fat in cross sectional ways. Some studies find this relationship and others do not. New rat research shows how chronic stress interacts with a high fat diet to recruit and enlarge visceral fat cells through NPY. Chronic stress alone did not significantly increase visceral fat (ie, no main effects), but only in interaction with eating fat. The action was in the interaction, and it required an animal studies to unravel the mechanism. We need more animal studies addressing questions about behavior/stress interactions.

Lisa Fredman

Boston University

  1. How has the concept of allostatic load had a positive (or negative) impact on work in your field? Are there more valuable alternative approaches to the study of cumulative physiological risk and if so, what are they and what is their relative advantage?

I am a psychosocial epidemiologist and my research focuses on the health effects of caregiving stress. I think that the concept of allostatic load has had a big impact, both positive and negative, on the field of psychosocial epidemiology, and little impact on caregiving research. It has had a huge impact on my own research: here is how.

I have been conducting a prospective cohort study on a sample of elderly women caregivers and non-caregivers who are participants in the Study of Osteoporotic Fractures (aka Caregiver-SOF). Its theoretical framework is the stress and coping model. The Caregiver-SOF caregivers are more stressed than the non-caregivers, but have lower rates of functional decline and mortality. I could not explain this methodologically or theoretically until I read Teresa’s studies of allostatic load. The strengths of the concept were that the “wear and tear of chronic stress” affected multiple, inter-related homeostatic systems, and that it predicted established measures of health decline in an epidemiologic study. High allostatic load could be the physiologic pathway between caregiving and health decline. I performed a cross-sectional pilot study: caregivers and non-caregivers did not differ on allostatic load, although the caregivers had more stress. Therefore, I theorized that a subset of caregivers – those who were stressed AND developed high allostatic load – would have higher rates of health decline, whereas those who were stressed but who did not progress to allostatic load would not differ from non-caregivers. The prospective study design would reveal the temporal relationships between chronic caregiving stress, development of allostatic load, and health decline.
I submitted and resubmitted several proposals to test this hypothesis to NIH. Reviewers from multiple study sections criticized the concept and the measurement of allostatic load on the grounds that a single score was used to reflect a multidimensional concept, validity studies were lacking, and that the measure combined cardiovascular, metabolic, and neuroendocrine indicators which could mask the true physiologic mechanism.
Based on these critiques and recent studies of stress-induced metabolic syndrome, I revised my conceptual model. Metabolic syndrome replaced allostatic load as the pivotal mediator between chronic caregiving stress and health decline. This new model incorporates theories that stress-induced disruptions in the neuroendocrine and/or immune systems may increase the risk of metabolic syndrome, leading to health decline. It is supported by epidemiologic studies (see Yaffe et al, 2004 on the combined effects of inflammatory markers and metabolic syndrome on cognitive decline). It is consistent with the theory of allostatic load. Moreover, data from Caregiver-SOF and our pilot study support this model.
I revised my proposals, submitted them to NIH, and got funded! That is how allostatic load has influenced my research.
In general, I think that the concept of allostatic load can give us tremendous insights into the physiological mechanism(s) by which chronic stress affects health. It would strengthen studies of caregiving outcomes which, with few exceptions (e.g., studies by Grant and by Vitaliano), focus on single biomarkers if they include biomarkers at all, and do not address effects on multiple physiological systems, or the downstream effects on physical or cognitive health decline.

  1. What could be done to make this concept more valuable to research on social and behavioral factors on aging?

In epidemiologic research, the concept of allostatic load might be more valuable if prospective studies were designed to evaluate sequential changes in the components of allostatic load, and the subsequent effects on functional, cognitive, and disease outcomes. This would involve taking multiple measures of the components of allostatic load at multiple time points, such as annual or biennial followup interviews. Such studies would allow researchers to disaggregate the components of allostatic load, and to tie it to other theories of physiological responses to chronic stress. A limitation of many epidemiologic studies is that biomarkers of allostatic load are collected at only one or two time points, which prevents seeing how changes in one system lead to downstream changes in other, multiple systems.

Secondly, since allostatic load is theorized to result from chronic stress, we need prospective cohort studies on populations exposed to chronic stress and comparable populations that are not exposed to that stress, to determine how chronic stress leads to allostatic load and components of allostatic load. Samples of caregivers and non-caregivers could serve this purpose, but the selection of non-caregiver comparison groups can introduce potential selection biases (ie, married non-caregivers are often healthier than caregivers, elderly non-caregivers are less physically active than caregivers). Other high-stress populations might include workers in high-stress occupations or spouses of veterans. I am concerned that some epidemiologic measures of “life course stressors” actually indicate non-stress risk factors for components of allostatic load: for example, low socioeconomic status may lead to metabolic syndrome through poor diet rather than through stress, so epidemiologic studies need to include measures of these confounders.
Third, perform research on factors that may prevent or reduce allostatic load components in the face of chronic stress. For example, studies could evaluate how stress reduction programs affect allostatic load components and ultimately prevent chronic stress from progressing to allostatic load.

  1. What are the most critical measurement issues? Are there specific data needs for addressing these questions?

Epidemiologists express the need for validity studies of allostatic load. In addition, there are questions about how to operationalize an “allostatic load” score. There are also questions about how to operationalize the components of allostatic load: as continuous variables, z-scores, or categorical measures. One concern is that studies that use categorical measures tend to base the cutpoint on the sample-based distribution (for example, top tertile of cortisol). But the cutpoints differ from study to study. Therefore, it would be helpful to compare measures of allostatic load and the distribution of its components in different samples and across multiple time points.

  1. What would be the most important “next steps” in moving forward research on allostatic load or cumulative physiological risk?

Researchers are increasingly including biomarkers in their studies, often without a strong conceptual framework. Perhaps research would be moved forward if there were more articles in discipline-specific journals that emphasized the conceptual strengths of the allostatic load model or on models of cumulative risk.

More research is needed on the points raised in the previous sections: the temporal relationships among the components of allostatic load; evaluating whether there are critical aspects of allostatic load, such as metabolic syndrome, that link chronic stress to disease outcomes; conducting parallel studies of allostatic load in different populations and high-stress groups to identify similarities and differences in the mediating role of allostatic load between chronic stress and health decline.
A practical issue is how to get studies on allostatic load favorably reviewed by NIH study sections. This is important for advancing research in this area.

Noreen Goldman

For the past eight years, I have been involved in a data collection effort in Taiwan known as SEBAS.1 This survey, which took place in 2000 and 2006, includes home-based interviews, collection of blood and 12-hour urine samples, and physicians’ health exams, from about 1000 middle-aged and elderly respondents who comprise a random subsample from an ongoing, national longitudinal survey. The underlying objective of SEBAS has been to examine the relationships among the social environment, stressful experience and mental and physical health and to identify the intervening physiological pathways. A subsidiary goal has been to evaluate the utility of the allostatic load framework and existing measures of allostatic load in elucidating the linkages between stressful experience and health.
In the Princeton workshop last spring, I outlined five sets of questions that have plagued analyses, including our own, that attempt to analyze these relationships in broad (non-clinical) populations.

  1. How well have we measured (or can we measure) stressful experience in interview surveys? How should we measure stressful experience – e.g., traumatic events, major life events, short-term stressors, perceptions of stress?

  2. Are we obtaining the “correct” biomarkers from large-scale surveys? How do we determine whether a biomarker is a potentially important component of the allostatic load framework? How often should we attempt to measure these biomarkers? How can we best parameterize a large number of biomarker values in terms of variables or scores?

  3. How well have we measured (or can we measure) individual characteristics that may moderate the impact of stressful experience (e.g., personality, coping mechanisms, social position)? Can our statistical models and sample sizes support this type of complexity?

  4. Are studies such as SEBAS focusing on too old ages – e.g., a period in the life span when the effects of social factors and challenge may be less important than earlier in life and when many persons at risk have already died?

  5. How much variation in these relationships do we expect to occur across populations (or across individuals within populations)? For example, is it reasonable to think that associations found in the US or other Western populations would be of a similar magnitude to those in Taiwan?

Although I continue to believe that these are pressing issues, I think it would be useful to focus some of our discussion on a more basic question:

What types of findings would offer strong support (or a strong refutation) of the construct of allostatic load (in human populations)?
I believe that some of the claims in the literature that purport to find support for this construct are unfounded. For example, much of the research to date on human populations that assesses the allostatic load framework does so by examining the connection between an array of biomarkers and a set of health (or survival) outcomes. Indeed, some recent studies have included in an “allostatic load score” physiological measurements that do not appear to be related to the stress response (e.g., grip strength), but are known to be strong predictors of future health status. Given the established associations between most of the biomarkers used in population surveys and a multitude of mental and physical illnesses, statistically significant associations between the two should come as no surprise. That is, the links between these physiological measurements and health may arise from numerous pathways, many of which are probably not what we would think of as stress-related mechanisms. Similarly, the demonstration that a score of allostatic load (e.g., a summation of the number of these biomarkers that fall outside normal operating ranges) has a stronger correlation with downstream health measures than do individual markers is also an expected result in light of potential measurement error and the fact that the sum of small effects is typically a larger effect.
Thus, it seems that one needs to set a higher bar to evaluate the construct of allostatic load, one that demonstrates linkages between stressful experiences and poor physiological profiles (however defined). There are two issues that require attention in this regard. One pertains to how we define a “stressor.” Physiologists often focus on health-related mechanisms such as pain, pathogens, or lack of sleep. Social scientists are apt to think instead of life challenges, such as the death of a loved one, trauma, serious illness, loss of job, financial hardships, discrimination, or repeated daily hassles. Perhaps we need to distinguish here between the animal and human literatures. The second point pertaining to the link between stressors and poor physiological profiles concerns the role of socioeconomic status (SES). Social epidemiologists have argued that the social gradients in health come about in large part because persons of lower SES experience greater stress than their higher status counterparts. This conclusion is sometimes based on little more than statistically significant associations between SES (typically measured by education, income or occupational status) and a handful of biomarkers (e.g., blood pressure, cholesterol level, BMI, or fibrinogen). Much more compelling evidence is needed to identify the importance of “stress” in driving social inequalities in health. Researchers also need to keep in mind that “stress” can play two different roles in the SES-health link: persons of lower SES may experience more (or more serious) stressful events and they may be more vulnerable (have a greater physiological response) to stressors. Researchers have rarely been explicit about these two mechanisms and have generally not attempted to establish their veracity.
Igor Grant

1. How has the concept of allostatic load had an impact on work in your field? Are there more valuable alternative approaches to the study of cumulative physiological risk, and if so, what are they and what is their relative advantage?
The concepts of allostasis and allostatic load derive from a long tradition stretching back to Claude Bernard’s observations on the physiological necessity of the “fixite du milieu interieur” which was then elaborated by Walter Cannon in the concept of homeostasis. To me, the concepts of allostasis and allostatic load have been particularly useful in their ability to unite notions of homeostatsis and acute and chronic stress. Of particular heuristic importance has been the elaboration of the notion of primary mediators (e.g., catecholamines and glucocorticoids) and the categorization as effects of these mediators into primary (cellular), secondary (e.g., downstream metabolomic changes), and tertiary (actual organ disease).
These notions have been very useful in framing our own program of research into the health effects on elderly spousal caregivers of being married to and looking after a dementia husband or wife. Our overarching concept is that the stresses associated with caregiving, which are both chronic and punctuated by acute events, can lead to a state of sympathoadrenal medullary (SAM) arousal characterized by greater fluxes in circulating catecholamines, including norepinephrine and epinephrine. Consistent with notions of allostasis, we measure not only basal and stress-induced catecholamines, but also the receptor system upon which they act (in our case we focus on beta adrenergic receptors and on lymphocytes as a model of effects that may be occurring in other tissues). We then attempt to link these changes to changes in molecules such as D-dimer and IL6 (being examples of indicators of the coagulation environment and inflammation), which would be examples of secondary outcomes in the McEwen et al., model. Our work is now examining more downstream outcomes which may be thought of as transitions from secondary to tertiary outcomes — for example, changes in baroreflex, in endothelial function as measured by flow mediated dilation, and evidence of early arteriosclerosis as determined through ultrasound.
Our model also examines the effects of resiliency factors such as coping skills involving degrees of mastery, as these might moderate the above relationships.
In sum, the concepts of allostasis and allostatic load very much map onto the theoretical issues that concern us.
2. What could be done to make this concept more valuable?
The first steps to improve the usefulness of the concept have already been taken in the elaboration of concepts such as primary mediators and primary, secondary, and tertiary outcomes. These help to frame what groups of variables it would be useful to study and provide the beginnings of a framework for interrelating them. In my view, these “levels” could be refined further. For example, much of the focus in secondary outcomes has been focused on measures relating to energy metabolism (e.g., insulin, lipids, and other indicators of metabolic syndrome). A second focus has been on immune dysregulation. Clearly, both classes of events are of importance in various outcomes including cardiovascular disease and possibly autoimmune diseases and cancer. Additional classes of variables deserve study. One of these includes inflammatory markers of various sorts (research on these is actually underway). A second group of mediators concerns hemostasis. Allostatic load in the hemostasis system may be indicated by increases in “procoagulatory” markers such as D-dimer and fibrinogen. Markers such as these have been linked to increased likelihood of cardiovascular disease and stroke, but have not been very systematically studied among elderly under chronic and acute stress. Other indicators of “vascular health” such as responsiveness of the endothelium to baro or hypoxic stress are also worthy of focus, since responsive endothelial functioning may protect against the sorts of injuries to vessel linings that form the precursors to arteriosclerosis.
The area of vulnerability and resilience also deserves better conceptualization. As in inherent in models of allostasis, genetic factors may predispose to chronic allostatic load in some but not others. Studies on genetics, gene expression, proteomics, and metabolomics should ultimately be done to clarify who under what circumstances responds in what manner, and how such proteomic and metabolomic changes influence downstream organ health and disease.
A great deal of work has been done in the fields of psychosomatic medicine and behavioral medicine generally on resilience factors including concepts like problem focused coping, mastery, etc. Better linkage between these notions and studies of psychobiology of aging under conditions of acute and chronic stress are needed.
3. What are the most critical measurement issues?
Research into allostasis and allostatic load would be advanced by developing normative data in regard to primary and secondary outcomes. For example, what represents “normal” response to a stressor for men and women of different ages, socioeconomic strata, educational levels, or race/ethnicity? In neuropsychology a great deal of progress has been made in the ability to detect and monitor change in neurocognitive performance in respect to illness or aging by developing expected ranges of performance on various neurocognitive tests with respect to age, education, gender, and race/ethnicity. Such standards allow us to determine whether responses of groups of interest are within the expected range, or may represent maladaptive responses. Until we have good data on how, for example, elderly men and women who are in generally good health and not under conditions of severe stress respond to acutely stressful circumstances in terms of catecholamines, glucocorticoids, ACTH, etc., it will be difficult to explore notions of change in “set point” that may be occasioned by chronic stress.
Related to this, several groups of investigators have attempted to create overall measures of allostatic load. These have involved creation of standard scores, counting of scores outside particular ranges, etc. These are useful starting points, but if we had more data on “normals” then it might be possible to generate Z or T-scores for the primary and secondary outcome measures that are more reliable.
4. What would be the most important "next steps" in moving research on allostatic load forward?
Some of these notions have been covered in #3 above. Another useful approach would be the design of experiments that are able to test the theorized mechanistic pathways linking stress to primary, secondary, and tertiary outcomes in a more precise way. From the example of hemostatic variables mentioned above, can we, for example, link changes in basal and/or stress induced hemostatic response to changes in endothelial function, vascular response, or early indicators of arteriosclerosis? Mapping these more fine-grained associations would permit moving us from studies that are correlative in nature to those in which it may be possible to test models of causality. Implied in this strategy is the importance of examining people or animal models over time with a view to accumulating sufficient longitudinal information to test such causal models.

Arun Karlamangla


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