Inflammatory markers provide invaluable tools for studying health and disease across the lifespan. Inflammation is central to the immune system’s response to infection and wounding; it also can increase in response to psychosocial stress. In addition, depression and physical symptoms such as pain and poor sleep can promote inflammation and, because these factors fuel each other, all contribute synergistically to rising inflammation. With increasing age, persistent exposure to pathogens and stress can induce a chronic proinflammatory state, a process known as inflamm-aging. Inflammation’s relevance spans the life course, from childhood to adulthood to death. Infection-related inflammation and stress in childhood, and even maternal stress during pregnancy, may presage heightened inflammation and poor health in adulthood. In turn, chronically heightened inflammation in adulthood can foreshadow frailty, functional decline, and the onset of inflammatory diseases in older age. The most commonly measured inflammatory markers include C-reactive protein (CRP) and proinflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α). These biomarkers are typically measured in serum or plasma through blood draw, which capture current circulating levels of inflammation. Dried blood spots offer a newer, sometimes less expensive collection method but can capture only a limited subset of markers. Due to its notable confounds, salivary sampling cannot be recommended. Inflammatory markers can be added to a wide range of lifespan developmental designs. Incorporating even a single inflammatory assessment to an existing longitudinal study can allow researchers to examine how developmental profiles and inflammatory status are linked, but repeated assessments must be used to draw conclusions about the associations’ temporal order and developmental changes. Although the various inflammatory indices can fluctuate from day to day, ecological momentary assessment and longitudinal burst studies have not yet incorporated daily inflammation measurement; this represents a promising avenue for future research. In conclusion, mounting evidence suggests that inflammation affects health and disease across the lifespan and can help to capture how stress “gets under the skin.” Incorporating inflammatory biomarkers into developmental studies stands to enhance our understanding of both inflammation and lifespan development.
Stephanie J. Wilson, Alex Woody, and Janice K. Kiecolt-Glaser
Thomas M. Hess, Erica L. O'Brien, and Claire M. Growney
Blood pressure is a frequently used measure in studies of adult development and aging, serving as a biomarker for health, physiological reactivity, and task engagement. Importantly, it has helped elucidate the influence of cardiovascular health on behavioral aspects of the aging process, with research demonstrating the negative effect of chronic high blood pressure on various aspects of cognitive functioning in later life. An important implication of such research is that much of what is considered part and parcel of getting older may actually be reflective of changes in health as opposed to normative aging processes. Research has also demonstrated that situational spikes in blood pressure to emotional stressors (i.e., reactivity) also have implications for health in later life. Although research is still somewhat limited, individual differences in personal traits and living circumstances have been found to moderate the strength of reactive responses, providing promise for the identification of factors that might ameliorate the effects of age-related changes in physiology that lead to normative increases in reactivity. Finally, blood pressure has also been successfully used to assess engagement levels. In this context, recent work on aging has focused on the utility of blood pressure as a reliable indicator of both (a) the costs associated with cognitive engagement and (b) the extent to which variation in these costs might predict both between-individual and age-related normative variation in participation in cognitively demanding—but potentially beneficial—activities. This chapter elaborates on these three approaches and summarizes major research findings along with methodological and interpretational issues.
Carolyn M. Aldwin and Ritwik Nath
Erythocyte sedimentation rate (ESR) is one of the oldest measures of inflammation. It is used extensively in clinical medicine and has shown some utility in biomedical research. It is a nonspecific inflammation assay, and although it is less sensitive than more modern measures such as C-reactive protein, it is a useful measure in chronic illnesses. In general, ESR increases with age and appears to be a biomarker of aging in general. It predicts both cardiovascular disease (CVD) and cancer and is elevated in autoimmune disorders such as rheumatoid arthritis. Further, it predicts mortality both in the general population and in those with chronic illnesses such as CVD and cancer, independent of other indicators of illness severity. Interestingly, ESR is not associated with anxiety or general measures of distress but is consistently associated with measures of depression and suicidal ideation. Further, the effect of depressive symptoms on mortality appears to be mediated through increases in ESR. Studies of the relationship between stress and ESR have been less consistent, primarily because early studies were largely cross-sectional and in small samples. Studies using more modern, longitudinal analyses in larger samples may show more consistent results, especially if multilevel modeling was used that examined within-person changes in ESR in response to stress. Given that other large, longitudinal studies, such as the Baltimore Longitudinal Study on Aging, the Rotterdam Study, The Reykjavik Cohort Study, and Women’s Healthy Ageing Study have included ESR in their biomedical assays, it should be possible to analyze existing data to examine how psychosocial factors influence inflamm-aging in humans.
Christiane A. Hoppmann, Theresa Pauly, Victoria I. Michalowski, and Urs M. Nater
Everyday salivary cortisol is a popular biomarker that is uniquely suited to address key lifespan developmental questions. Specifically, it can be used to shed light on the time-varying situational characteristics that elicit acute stress responses as individuals navigate their everyday lives across the adult lifespan (intraindividual variability). It is also well suited to identify more stable personal characteristics that shape the way that individuals appraise and approach the stressors they encounter across different life phases (interindividual differences). And it is a useful tool to disentangle the mechanisms governing the complex interplay between situational and person-level processes involving multiple systems (gain-loss dynamics). Applications of this biomarker in areas of functioning that are core to lifespan developmental research include emotional experiences, social contextual factors, and cognition. Methodological considerations need to involve careful thought regarding sampling frames, potential confounding variables, and data screening procedures that are tailored to the research question at hand.
Sarah E. Hampson
Although the belief that personality is linked to health goes back at least to Greek and Roman times, the scientific study of these links began in earnest only during the last century. The field of psychosomatic medicine, which grew out of psychoanalysis, accepted that the body and the mind were closely connected. By the end of the 20th century, the widespread adoption of the five-factor model of personality and the availability of reliable and valid measures of personality traits transformed the study of personality and health. Of the five broad domains of personality (extraversion, agreeableness, conscientiousness, emotional stability, and intellect/openness), the most consistent findings in relation to health have been obtained for conscientiousness (i.e., hard-working, reliable, self-controlled). People who are more conscientious have better health and live longer lives than those who are less conscientious. These advantages are partly explained by the better health behaviors, good social relationships, and less stress that tend to characterize those who are more conscientious. The causal relation between personality and health may run in both directions; that is, personality influences health, and health influences personality. In addition to disease diagnoses and longevity, changes on biomarkers such as inflammation, cortisol activity, and cellular aging are increasingly used to chart health in relation to personality traits and to test explanatory models. Recognizing that both personality and health change over the life course has promoted longitudinal studies and a life-span approach to the study of personality and health.
The most dynamic postnatal brain development takes place during human infancy. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The improvements in noninvasive imaging techniques, especially magnetic resonance imaging, magnetic resonance spectroscopy, electroencephalography, magnetoencephalography, positron emission tomography, and near-infrared spectroscopy, have provided unprecedented opportunities to quantify and map the early developmental changes at whole brain and regional levels. Unique to infant brain imaging, tailored infant image acquisition and analysis methods—such as motion correction, high-resolution imaging, optimization of imaging parameters for smaller and immature brain, age-specific brain atlas and parcellation scheme, age-specific white matter tractography, functional connectivity analysis given incomplete brain networks, and advanced gray and white matter segmentation for infant brains should be taken into consideration. Delineating functional, physiological, and structural changes of the infant brain through imaging provides insights into the complicated processes of both typical development and the neuropathological mechanisms underlying various brain disorders with early onset in infancy, such as autistic spectrum disorder. Identification of imaging biomarkers of neurodevelopmental disorders during infancy by leveraging techniques such as machine learning may offer a valuable time window for early intervention.