Quality of Life and Lifestyle

I will critically discuss the concept of Quality of Life, including its application and value in understanding mental health burdens. Quality of Life (QOL) is a human construct that can be understood from diverse dimensions (CDC, 2000, 2021). One of its domains is the subjective experience of individuals and their families/caregivers concerning their health and, if unwell, its concurrent treatment. The personal experience of QOL can help understand disease burdens, including mental health ones, in a two-way process. The World Health Organization, Harvard School of Public Health, and the World Bank developed the concept “global burden of disease” (GBD) to describe the loss of health and death due to diseases and injuries and their risk factors (Murray & Lopez, 1996). Mind diseases are non-communicable diseases (Bloom et al., 2011), bringing challenges to decision-makers regarding the efficient allocation of resources for prevention. Health-related quality-of-life (HRQOL) measures offer data to ultimately help improve QOL, relating quality-of-life factors to risk ones, and tracking self-reported disease/good health (CDC, 2000; DeSalvo et al., 2006).

Quality of Life and Burden of Disease Concepts

The Center for Disease Control (CDC) defines QOL as a multidimensional concept built from subjective evaluations of domains in life such as health, jobs, housing, schooling, neighbourhood, culture, values, and spirituality (CDC, 2000).  In mental health, a positive quality of life has been historically the ultimate aspiration of successful interventions, not just the absence of disease (Erikson, 1950; Fordham et al., 2021; Kohut, 1977; Winnicott, 1971; Wojtyna et al., 2007). The concept is part of the CDC’s mission statement (CDC, 1994, 2000). A metric that reflects the years gained due to successful interventions is the Quality-Adjusted-Life Years (QALYs). The CDC uses Healthy Days measurements to track health and aid in setting policies to improve populations’ well-being (CDC, 2000). The concept GBD provides information on the economic impact of disease in society. The indicators that define it are the Years of Life Lost (YLL – died due to the condition) and the Years of Life lived with Disability (YLD). The sum of these two indicators shows the Disability Adjusted Life Year (DALY) (GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, 2018; Murray & Acharya, 1997; Whiteford et al., 2015). One DALY is equivalent to one lost year lived in total health. The DALY represents the burden of disease. Using DALYs, mental health disabilities are the most prevalent cause of burden of disease in Europe (Wittchen et al., 2011). As a consequence of the findings of the indicators of burden of disease, the WHO developed the Mental Health Action Plan 2013-2020 – endorsed by the World Health Assembly in 2013 – (WHO, 2013). The plan included four broad objectives to improve mental health in the population. The objectives were related to leadership for mental health, care in the communities, prevention strategies, and evidence, research, and information systems.

Efficient Allocation of Resources

The DALYs measure disease burden without including qualitative differences. This data is not enough for sound resource allocation and the creation of prevention programmes (Anand & Hanson, 1997). The DALYs themselves cannot explain overlapping diseases and comorbidities (Wittchen et al., 2011). Data on children and adolescent lifestyles is critical to impact more efficiently on prevention of adulthood disease. In this case, using QALYs metrics is useful (Augustovski et al., 2017). Understanding quality of life in different geographies, for example, helps underpin causes of burden of disease outcomes giving governments evidence-based data to invest in more efficient (better and cost-effective) treatments and prevention programmes (Whiteford et al., 2015). If quality of life data is left unseen, essential information would be lost. For example, Years of Life Lost reflect the direct cause of death, so if death were due to a physical consequence of the mental disorder, the latter would remain unseen as the death factor (Whiteford et al., 2015), undermining the use of data to improve treatment and prevention. Metrics on healthy lifestyle add data to prevent disease and improve treatment. Descriptive epidemiology (mental health burden numbers, for example) combined with analytical epidemiology (disease causes related to lifestyle, for instance) translates potential causes of disease and health into preventive action plans.

Suggestions on Integrating Information

Quality of Life and Depression, for example, could be aligned as symmetrical entities (de Leval, 1995; de Leval, 1999; Moore et al., 2005). In the broader scale of epidemiology, understanding symmetries would provide data for decision-makers to allocate resources efficiently. Depression implies a reduction in quality of life and is the most expensive disorder in Western societies (GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, 2018). Mental and substance abuse disorders led YLDs in 2010, with depression having the most DALYs (Whiteford et al., 2013). It has been the most disabling single condition in Europe (Wittchen et al., 2011). Depression increases many medical and psychiatric comorbidities. (Saveanu & Nemeroff, 2012). One of the key features of depression is the loss of agency and the impact on the Self. The sense of Self is vital to recovering a positive quality of life (Davidson & Strauss, 1992). The DSM-V includes the feeling of worthlessness in its list of criteria for diagnosis (American Psychiatric Association, 2013). This anhedonia can affect consumption and the pursuit of rewards that link with the loss of work and social involvement that, from a broader perspective, translates into the economic impact of burden of disease. The effect is also on the caregivers of depressed people: helping them cope and survive drains their resources instead of adding a surplus in society (Schulz & Sherwood, 2008). This description links the reduction of quality of life with the burden of disease outcomes. The self-stigma and the social stigma toward the depressed and their families perpetuate a vicious cycle (Corrigan et al., 2006; Ritsher & Phelan, 2004). Another influencer on quality of life in depression is the application of pharmacotherapies. Psychopharmacology is not always provided in tandem with psychotherapy. The latest evidence shows how antidepressants bind with brain-derived neurotrophic factor and hence produce an overall increase in neuroplasticity (Casarotto et al., 2021; Yang et al., 2020). This might be one mechanism by which the brain can begin to heal (Radley et al., 2015). If this neuroplasticity is increased, but the quality of life of the person does not change and does not provide a framework to put into practice new potential coping mechanisms, those life experiences might provoke perpetuation of symptoms (“medication does not work”) or relapse/recurrence of depression. More translational research is needed to test this hypothesis to bring evidence for resource allocation regarding treatment/prevention. In the meantime, mental health clinicians are including broader lifestyle-oriented therapies within the so-called third-wave psychotherapies. Mindfulness-based cognitive therapy – MBCT-, for example, has been shown to reduce the hazard of depression relapse after reduction of depressive symptoms compared to no MBCT (Kuyken et al., 2008).

Understanding Lifestyle and Quality of Life

Modern society brings many gene-environment crashes. It is well known that stress, inflammation, maladaptive aging increase with an unhealthy lifestyle (Radley et al., 2015; Saveanu & Nemeroff, 2012). Nevertheless, social demands can still be counterproductive. For example, chronic disruption of circadian rhythms can bring a range of health issues (Goh et al., 2000). And yet, social behaviour and government regulations of working hours, school hours, and regional time zones do not consider sleep deprivation consequences of social demands. Government policies at the societal level could facilitate the availability of a framework of social life that promotes a healthier lifestyle. A healthy lifestyle includes an active life, social connections, healthy diets, openness to new learning, values that promote self-awareness, and a basic alignment between biological, psychological, and social needs (CDC, 2000; Wang et al., 2020; WHO Regional Office for Europe, 1999). More research oriented explicitly in well-being including epigenetics (Baumeister et al., 2014; Keyes & Susser, 2014), resilience mechanisms (Collins et al., 2011), and translational research involving service users (Callard et al., 2011), would better aid in allocating investment on prevention strategies. Human beings are a species whose evolution has origins in an environment very different from what modern-day society offers. If HRQOL measures aim to improve QOL and lower disease burden, policymakers should be using the data to guide society towards healthier social behaviours. For example, depressive behaviours might have evolved from basic energy-saving mechanisms during weak states, such as illness-behaviour and hibernation, developing into protective reactions triggered by separation from caregivers, as a way to both save energy and not grab the attention of predators when vulnerable (Watt & Panksepp, 2009). Nowadays, we do not have a comprehensive understanding of depression yet. Still, one of the underestimated factors that might be influencing the perpetuation of symptoms could be the enormous gap between our lifestyles and our nature. In line with this hypothesis, enriching social connectedness, for example, seems to be a fundamental need for human mental health. Individualistic values, aggressive competition, and the permanent financial goals of Western societies seem to promote a definition of success that mismatches with achieving health and lowering burden of disease. When governments and international organizations define policies that aim to impact people’s daily lives, the QOL factors should be included at the top of their lists.

Conclusion

The future of mental health well-being must include a holistic approach to lifestyle that aligns the physical, social, mental, and biological needs of human beings with the culture and societies where they live. This alignment will naturally impact quality of life and lower the economic costs of mental health. Combining data of quality of life and disease burden serves this purpose. More research is needed to test the links between lifestyle and well-being, and relapse/recurrence of mental illness, including research on epigenetics. Translational research, in general, will be a crucial factor in the transition to a holistic approach to prevent and treat mental health issues efficiently. The understanding of Quality-of-Life implications should be the guiding star of all mental health-related fields, research funders, national agencies, and decision-makers.

How’s your lifestyle? Just think about it.

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