Although the research on physiological correlates of mental well-being is scarce, an increasing number of studies show that positive psychological functioning is related to good physical health, reduced mortality, and longevity (Chida and Steptoe 2008; Cohen and Pressman 2006; Dockray and Steptoe 2010; Ryff and Singer 1998, 2008; Steptoe et al. 2009). In addition to research on factors pertaining to resilience, such as optimism (Seligman 1998) and sense of coherence (Antonovsky 1985, 1987), positive affective states have been more consistently linked to various physical health outcomes (for reviews, see Pressman and Cohen 2005; Cohen and Pressman 2006; Steptoe et al. 2009). A now classic example is the longitudinal study of catholic nuns by Danner et al. (2001), which showed that positive emotional content expressed in writing by nuns in their early twenties was inversely associated with risk of mortality 60 years later. These relationships between various types of positive psychological functioning and physical health outcomes are likely to be coupled with physiological processes (e.g., Ryff and Singer 1998; Steptoe et al. 2005). This assumption also draws on the fact that mental disorders, apart from deteriorating psychological functioning, most often involve physiological changes reflected in deviations at the neurophysiological, hormonal, or other bodily levels (Ganzel et al. 2010; McEwen 2007). With this in mind, delineating how mental well-being relates to physiology will advance the knowledge of health-promoting and protective bodily processes.

When it comes to explaining the nature of the relationships between positive psychological functioning and physical health, different mechanisms have been suggested (Pressman and Cohen 2005; Ryff and Singer 1998; Steptoe et al. 2005). Among these are mechanisms including behavioral and psychobiological processes, respectively. A mechanism focusing on behavioral factors suggests that mental well-being may be coupled with health-promoting behaviors, including a healthy lifestyle, which, in turn, promote better physical health. According to mechanisms including psychophysiological processes, the interaction between mental well-being and physical health involve psychobiological processes, including various bodily systems and their functioning, which, in turn, influence physical health.

Physiological indicators can be used to investigate bodily functioning and health-related outcomes. Considering that the brain plays a central role in interpreting, evaluating, and responding to daily life challenges and demands, central physiological processes relating to an individual’s interpretation, evaluation, and response to situations in daily life reverberate through the body, which, in turn, signal back to the brain. This means that there is a constant ongoing interaction between central and peripheral processes that is reflected in central and peripheral physiological activity (e.g., Ganzel et al. 2010; McEwen 2007). From this, physiological indicators can be measured at different levels (McEwen and Seeman 1999). In describing the different levels of physiological correlates, it is useful to distinguish between peripheral and central indicators. While central indicators reflect central functioning in terms of brain activity, peripheral indicators reflect physiological functioning in the rest of the body (Ganzel et al. 2010). Since valid assessment of central indicators typically requires careful measurements using technically advanced and sophisticated equipment, the assessment of central indicators is commonly restricted to the laboratory setting. In contrast, the development of portable devices has facilitated the assessment of peripheral indicators reflecting, for instance, cardiovascular functioning in different settings, including situations in daily life and controlled experimental settings (Andreassi 2006). Other peripheral indicators, for instance, that assess functioning within the endocrine system are commonly measured in blood, saliva, or urine. These indicators can thus be measured in different settings, including both laboratory and daily life settings. Also the use of saliva and urine for the assessment of physiological indicators is noninvasive, which allows for intensive repeated sampling over time without causing any harm to study participants (Lundberg 2005). Among the commonly studied peripheral physiological indicators are physiological indicators that reflect activity within the cardiovascular, endocrine, metabolic, and immune systems. Physiological indicators from these different systems have independently and together been linked to various health outcomes (Ganzel et al. 2010; McEwen and Seeman 1999).

The cardiovascular system consists of the heart, systemic circulation, and pulmonary circulation with the primary function of supplying blood and transporting oxygen, nutrients, and other substances to different bodily organs and tissues (e.g., Andreassi 2006). The cardiovascular system is influenced by activity within the sympathoadrenomedullary (SAM) system, which involves brain mechanisms and plays a central role in physiological arousal. Commonly assessed indicators of the functioning of the cardiovascular system include systolic and diastolic blood pressure and heart rate. Increased levels of blood pressure and heart rate have repeatedly been associated with adaptive responses to acute challenges and demands. However, chronically high levels of cardiovascular activity, such as high blood pressure, have been identified as a risk factor for physical ill health and disease.

Apart from influencing activity within the cardiovascular system, the SAM system influences the endocrine system and the release of the catecholamines adrenaline and noradrenaline. Both adrenaline and noradrenaline are secreted peripherally into the blood by the adrenal medulla and then circulated around the body. Besides catecholamines, there is another set of endocrine markers: glucocorticoids. Glucocorticoids are released peripherally into the blood from the adrenal cortex upon activation of the hypothalamic-pituitary-adrenal (HPA) axis. Cortisol is one of the most important and well-researched glucocorticoids, and cortisol receptors are found in all major organs and bodily tissues. This means that cortisol can have a major impact on bodily functioning. By stimulating the peripheral release of endocrine markers, the central mechanisms of the SAM system and the HPA axis trigger a set of coordinated physiological changes that have an adaptive function and increase an individual’s readiness to respond to and act on challenges or demands in the environment. Such acute physiological changes are adaptive. In contrast, long-term physiological activity, characterized by chronic changes in endocrine activity, has been associated with bodily wear and tear. Cortisol, in particular, has diversified short-term and long-term effects on bodily functioning with chronic changes being linked to various diseases, including type 2 diabetes, hypertension, cardiovascular diseases, depression, and autoimmune conditions (Ganzel et al. 2010; McEwen and Seeman 1999).

The metabolic system is involved in distributing energy resources throughout the body. These energy resources include glucose and blood lipids such as cholesterol and triglycerides. Generally, different types of cholesterol are distinguished, the main types being low-density (LDL) lipoproteins and high-density (HDL) lipoproteins, with total cholesterol as a measure reflecting the total amount of lipids circulating in the blood stream. While HDL is considered to promote health and to protect against atherosclerosis, high levels of triglycerides might be a risk factor for disease. Additionally, LDL and total cholesterol are associated with cardiovascular ill health. Triglycerides are another commonly investigated blood lipid, reflecting fat deposits, with higher values associated with diabetes and obesity. In addition to blood lipids, measures of glucose are also included among metabolic indicators. Glycosylated hemoglobin (HbA1c) is an integrated measure reflecting an individual’s glucose metabolism during the previous 30–90 days and that has been linked to diabetes.

Recent research underscores the importance of immune system functioning and inflammatory mechanisms underlying various diseases, including cardiovascular disease (Kiecolt-Glaser 2009; Glaser and Kiecolt-Glaser 2005). The immune system plays a central role as a barrier, active in defending and protecting the body from infections and other threats. There are a number of immune system markers, including several different cytokines, which have their specific functions in the complex process of protecting the body. These processes are further complicated by the fact that acute and long-term responses of the immune system involve diverse parts of the immune system.

In addition to investigating separate physiological systems and focusing on physiological indicators reflecting activity within a specific system, the concept of allostatic load has been proposed as a complementary approach that underscores the mutual interactions between different bodily systems by describing how physiological functioning within theses bodily systems relates to health and disease (e.g., McEwen 2007; McEwen and Seeman 1999). The allostatic load model also takes into account the ability of bodily systems to reach stability through change and distinguishes between the effects of acute and chronic responses. While acute responses that are necessary to adapt to current challenges and demands have a protective effect when they are followed by periods of rest and recovery, prolonged activation of different bodily systems increases the wear and tear of bodily resources. Partly, such wear and tear is related to natural life course changes and the reduced flexibility of aging bodily systems. Young and healthy functioning bodily systems respond with activity within a given and optimal range. However, daily wear and tear may, over time, result in physiological dysregulation. Dysregulation in multiple bodily systems, characterized by activity deviating from the optimal range or by increased difficulties in returning to baseline levels (or resting levels) after various bodily challenges, may result in allostatic load. Such cumulative dysregulation may result in an allostatic load that, in turn, increases the risk for future ill health and disease and reduces the chances for long-term physical health. To reflect the multisystems approach, allostatic load has been operationalized as a summary indicator of physiological challenge across multiple bodily systems (McEwen and Seeman 1999). Typically, a measure of allostatic load includes one or several physiological indicators of cardiovascular, endocrine, immune, and metabolic system functioning. To date, research has shown that high allostatic load is associated with different health-related outcomes, including cardiovascular disease, cognitive decline, and mortality (Ganzel et al. 2010).

Based on how mental well-being is defined, the research within the field can be divided into two broad orientations (Deci and Ryan 2008; Ryan and Deci 2001). Each of these orientations focuses on different, yet overlapping, aspects of well-being, namely, hedonic aspects of well-being and eudaimonic aspects of well-being (Kashdan et al. 2009; Keyes et al. 2002). While the hedonic orientation focuses on subjective well-being, the eudaimonic orientation underscores the pursuit of growth, human fulfillment, and psychological well-being. The differences between the two orientations become clear when looking at how these different aspects of mental well-being are defined and assessed (e.g., Ryan and Deci 2001). Subjective well-being is commonly associated with happiness. The assessment of subjective well-being includes measures of positive affect, affect balance, happiness, and life satisfaction (Diener 1984; Ryan and Deci 2001). In contrast, psychological well-being refers to a broader conceptualization, including characteristics of the optimally functioning individual. Over the past several decades, psychological well-being has mainly been measured using the six well-being dimensions included in the Ryff scales (Ryff 1989; Ryff and Keyes 1995). However, other ways of measuring psychological well-being cover individual strengths relating to meaningfulness, such as sense of coherence (Antonovsky 1985, 1987). Theoretical reviews (Deci and Ryan 2008; Kashdan et al. 2009; Ryan and Deci 2001) comparing the philosophical underpinnings, measures, and empirical findings of the two orientations conclude that in investigating different aspects of mental well-being using different yet slightly overlapping self-report measures, the two lines of research complement each other. This complementary perspective is supported by empirical studies of mental well-being profiles, including measures of both subjective and psychological well-being (Keyes et al. 2002).

Most of the existing research on physiological correlates of mental well-being has focused on the hedonic aspects of well-being in terms of positive affect and positive emotions (for detailed reviews, see Pressman and Cohen 2005; Steptoe et al. 2009). In contrast, the research investigating physiological correlates of more complex aspects of hedonic well-being, such as life satisfaction and subjective well-being which go beyond pure ratings of emotions or affect, is scarce. In part, this results from psychology’s primary concern with emotion and affect. However, with regard to the linkages to various health-related outcomes, emotion and affect have been suggested to explain how psychosocial stress can influence physical health (Pressman and Cohen 2005).

Research on central physiological correlates (i.e., brain functioning) of positive affect draws on findings showing that there is a differentiation between positive and negative emotional processes in the brain. The prefrontal cortex has been identified as a part of the brain that is involved in emotional processes, and so this part of the brain appears to be particularly important for mental well-being (Davidson 2004). Studies on mental well-being have also focused on such measures as those used in earlier findings relating to asymmetric activity between the left and right hemispheres. As regards levels of activity in the brain, a study focusing on mental well-being has shown that greater left than right activation of the prefrontal cortex is associated with higher levels of positive affect. However, activation of the left and right frontal hemispheres was shown to not be associated with positive affect (Urry et al. 2004).

As regards cardiovascular indicators, systematic reviews show that positive affect and positive emotions are related to increases in cardiovascular responses (Pressman and Cohen 2005). These relationships have been found both in experimental and correlational studies. However, increases in blood pressure have been established in both experimental and correlational research, while increases in heart rate have been found in experimental studies only. When it comes to the size of the increase, the magnitude is typically relatively small. A related line of research investigating the form and function of positive emotions has shown that the experience of positive emotions, by restoring autonomic activity to midrange levels, decreases the duration of cardiovascular arousal and thus facilitates physiological recovery, which, in turn, may hinder detrimental processes and promote health (Fredrickson 1998, 2004; Fredrickson et al. 2000). However, other experimental studies have failed to replicate these findings (Steptoe et al. 2005).

For endocrine measures, including cortisol and catecholamines (adrenaline and noradrenaline), experimental research inducing positive affect by active techniques, including study participants’ experiences, results in increased cortisol levels (Pressman and Cohen 2005). Yet, laboratory studies inducing positive affect by passive techniques (showing film clips, listening to music, or similar) show no consistent cortisol increases but rather a decrease or no change at all. In contrast, research in real-life settings typically shows that positive affect is associated with lower cortisol levels. However, these results tend to be stronger for trait positive affect than for state positive affect. As regards catecholamines, positive affect (trait and state) has been coupled with lower levels of both adrenaline and noradrenaline in studies conducted in real-life settings; however, some studies have shown null findings. For laboratory studies, the findings on catecholamines are mixed, with some studies showing positive affect as being associated with higher noradrenaline levels or both higher levels of adrenaline and noradrenaline, while other studies show null findings. As for cortisol, the mixed laboratory findings can be explained by differences in inducing positive affect, with active techniques being associated with a clear increase, while results for passive techniques are less clear (Pressman and Cohen 2005; Steptoe et al. 2009). It is important to bear the differences in mind for individuals who are reacting emotionally to active and passive experimental techniques, as well as the potential differences between state and trait positive affect, when transferring the research findings between settings and when evaluating the associations between positive affect and health outcomes.