Abstract
The allostatic load model expands the stress-disease literature by proposing a temporal cascade of multi-systemic physiological dysregulations that contribute to disease trajectories. By incorporating an allostatic load index representing neuroendocrine, immune, metabolic, and cardiovascular system functioning, numerous studies have demonstrated greater prediction of morbidity and mortality over and beyond traditional detection methods employed in biomedical practice. This article reviews theoretical and empirical work using the allostatic load model vis-à-vis the effects of chronic stress on physical and mental health. Specific risk and protective factors associated with increased allostatic load are elucidated and policies for promoting successful aging are proposed.
Keywords
Allostatic load; Chronic stress; Aging; Resilience; Health; Cognition; Biomedicine
Introduction
Chronic psychosocial stress and consequent physiological dysregulations are increasingly viewed as catalysts of accelerated aging and agitators of disease trajectories. Individual differences in the brain's interpretations of and the body's reactions to environmental stressors are nevertheless the ultimate determinants of either vulnerability towards or resilience against stress-related diseases (Lupien et al., 2009, McEwen, 1998b, McEwen, 2009). Health and successful aging can therefore be conceptualized as one's ability to adapt and effectively respond to the dynamic challenges of being alive. Embodying this notion is the allostatic load model, which assesses physiological dysregulations that ensue when normal homeostatic functioning is shifted towards abnormal ranges via the prolonged secretion of stress hormones and the subsequent mal-adaptations this strain exerts on interdependent systems. This review summarizes theoretical developments and studies that incorporate allostatic load algorithms used to predict health and cognitive outcomes throughout lifespan development.
Conclusion
Decomposing which protective factors render individuals resilient to age-related health and cognitive declines depends on our conceptual definitions of successful aging and appreciation of individual differences (Lupien and Wan, 2004). Rather than being the absence of pathology or deceleration of senescence, resilience is a state of adaptation to a lifetime of stress and strain. Evidence from AL studies have clearly demonstrated that maladapting to stressful environments has serious consequences, yet more importantly have also shed light on the specific protective and risk factors involved. While AL does appear to increase as one ages and differs by sex (McEwen, 2000c), we can additionally proclaim associations throughout lifespan development that include SES, social/relationship, workplace, lifestyle, race/ethnic, and genetic factors. Specific protective factors (e.g, parental bonding, education, social support, healthy workplaces, sense ofmeaning, etc.) are available ormanifest at different timepoints throughout lifespan development, and yet they each have the capacity to promote life-long resiliency against AL. Targeting the antecedents of AL at critical periods and implementing programs that cultivate resiliency is therefore essential to improving public health.
The next stage in AL research could be to assess the efficacy of interventions in reducing AL with these factors in mind. At an individual level, programs that encourage improved sleep quality/quantity, social support, sense of purpose, self-esteem, healthy diet, substance avoidance, and physical activity, while those at a social level might include policies that create incentives for beneficial practices in the workplace, cleaner and safer neighborhoods, and the motivation towards higher education are but a few examples of life-long benefits that could improve mental and physical health (McEwen, 2008). Specifically for the elderly, wellbeing therapy emphasizing autonomy, purpose in life, personal growth, positive relations with others, environmental mastery, and self-acceptance could be applied (Singer et al., 2005) and cognitive interventions could focus on physical and social activities (Elias and Wagster, 2007). These person-centered approaches to diminishing AL communally represent a move away from polypharmaceutical panaceas that currently plague biomedical treatment strategies.
In conclusion, the AL model has received compelling empirical support in its ability to predict a plethora of health outcomes using a multi-systemic approach, while it also conceptually extends multidisciplinary literatures on stress, SES, and successful aging that collectively carry important public policy and biomedical implications.