Mental health in Estonia at the beginning of the 21st century

The World Health Organization (WHO 2001) defines mental health as ‘a state of well-being in which the individual realises his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community“. This definition says something crucial: mental health is more than the absence of a disorder or of „ill-being“ it also involves acting meaningfully within the limits of one’s abilities or extending those limits.

This chapter contains five articles that discuss both positive and negative mental health. The first three articles are based on the WHO’s definition of mental health cited above: the topics are life satisfaction (Ainsaar and Konstabel), stress and coping with it (Lehto et al.) and success, or realising one’s abilities (Täht et al.). The fourth article looks at the occurrence of mental health problems, risk factors and protective factors (Akkermann et al.). The fifth article discusses activities and services supporting mental health in the broadest sense – from prevention to specialist medical care (Randver et al.).

People tend to notice and think about mental health only when something is wrong. Thinking can help fix mistakes, but it can also make things worse. At the individual level, a characteristic response is „rumination“ – thinking about a negative

event over and over. This may help the person avoid similar situations in the future but mostly just prolongs feeling miserable. Looking at the mental health situation of the population, on the other hand, stigmatising a specific age group or emphasising the difficulty and hopelessness of problems can exacerbate the situation.

For example, what are we to make of the information that, based on a self-report survey at the beginning of 2021, more than 50% of 18-to-24-year-olds were at risk of depression in Estonia? One might think disaster is imminent and that to avoid it, the number of psychiatrists must be increased as soon as possible. However, this conclusion should be considered in the proper context. First, we know that during the pandemic, the prevalence of depression and anxiety also increased in other countries and age groups, and negative life events and difficult life periods often lead to symptoms that later subside. We also know that depression is less stigmatised among young people. Therefore, we can assume that younger respondents more readily recognise possible symptoms of depression. Finally, the risk of depression does not automatically translate into a clinical diagnosis.

These considerations do not change the conclusion that the situation is serious and needs attention. But we must pay attention to details and how we interpret the information: we cannot expect the facts to speak for themselves. By changing the emphasis, the situation can be cast as hopeless, which is not useful and limits the possible courses of action (cf. Bandura 1997).

In this chapter, we use two main sources of information on population mental health: registry data and surveys. The primary registry data we use is the Estonian Health Insurance Fund’s database, where a diagnosis is recorded when services are used or medicines prescribed.

These diagnosed cases provide information about mental health disorders, but with an important caveat: only services financed by the Health Insurance Fund are reflected in the database, and the individual must first seek help to receive a diagnosis. Thus, if we rely solely on data about diagnosed cases, we underestimate the rate of ‘ill-being’

in the population and learn nothing about the rate of wellbeing. On the other hand, registry data has important advantages over surveys. The diagnosis is based on a thorough assessment by a specialist; the entire population can be included (not just a sample); the subjects do not have to be approached separately; and uncertainty and bias due to insufficient response rates are avoided.

The questions used in mental health surveys will always involve a degree of subjectivity and ambiguity, which is why verifying the informational value of the questionnaire is particularly important. Information indicating the quality of a questionnaire is described with the blanket term “validity” (Goldstein, Chekerzian and Simpson 2011). Since questionnaires are a less expensive and less accurate tool than diagnoses made by a specialist, the predictions they provide are always approximate, but it is important to know their level of accuracy. One helpful way of describing accuracy is known as ‘positive predictive value’ (PPV): if a respondent is at risk of a disorder according to a test result, how likely is it that they actually have the disorder? For example, the EEK-2 depression scale used in the article by Akkermann et al. has a PPV of 0.44, which means that 44% of respondents with a score exceeding the risk threshold would receive a diagnosis of depression based on the interview. That is a fairly good level of accuracy in this area.

For health and social policy planning, it is important to estimate the prevalence of disorders as accurately as possible: if we want to know the optimal number of psychologists or psychiatrists per 100,000 inhabitants, a 10% difference in the prevalence rate of the relevant disorders matters.

Reliable conclusions about time trends and risk and protective factors can also be drawn from questionnaires with a less well established level of accuracy. Such conclusions are also important and can or could affect our everyday life: for example, knowing that a lack of sleep and physical activity are risk factors for depression (see Akkermann et al. in this chapter and Reile in Chapter 2).

According to a widely cited account (Tarlov 1999) The determinants of population health can be divided into four categories: genetic and biological characteristics, health behaviour, medical care, and social and environmental factors. Tarlov emphasises that the relative importance of these factors cannot be accurately assessed. However, Tarlov does provide a rough diagram in which social and environmental factors have the largest impact, followed by health behaviour and medical care in roughly equal proportions, and last, hereditary (genetic) differences.

It is worth noting that these factors are not independent of each other. For example, social and environmental factors are largely mediated by health behaviour and medical care; medical care, in turn, depends on healthcare organisation, which is part of the social environment.

Complex human characteristics (such as behavioural patterns, personality traits, and mental health and related problems) arise from the interaction of genes and the environment, and they depend on many genes rather than just one or two. In this chapter, Akkermann et al. use the genetic risk score for depression, which encapsulates information on about a hundred known depression-related gene variants. The risk score is related to the likelihood of depression, but even with the highest risk score, a diagnosis of depression is far from certain, just as having the lowest possible risk score does not rule such a diagnosis out. Genetic characteristics are important but are not the only determinant.

In addition to genes, a number of environmental factors (see also Chapters 3 to 5) are known to affect the likelihood of mental health disorders. actors that increase the likelihood of depression include physical, sexual and emotional abuse, stressful work, a sedentary lifestyle, and sleep disorders (Arango et al. 2021). Several of these factors are also discussed in the article by Akkermann et al. in this chapter; once again, the impact of these factors is a matter of probability rather than necessity.

Many indicators of mental and physical health are known to be associated with socioeconomic background factors, such as education, employment status and income (e.g. Marmot et al. 1991). Here, an important mediating factor is stress caused by low status, stressful work and poor living conditions, which in turn is amplified by health and risk behaviours such as smoking, lack of exercise and an unhealthy diet (McEwen 2002). With background factors, a large part of the effect is indirect, although direct effects are not impossible (e.g. better education provides better knowledge about health behaviour, and a better salary allows for a healthier diet).

So people themselves and communities working together can do a number of things to care for mental health. The article by Akkermann et al. in this chapter and the articles in Chapter 2 discuss key health behaviour factors that also affect mental health – sleep, exercise, nutrition and drug use. Ways of coping with stress, which are discussed in the article by Lehto et al. in this chapter, can also be described as health behaviour. All these factors can be modified, although changing behaviour patterns is not easy.

Society can affect how easy or difficult it is for people to make reasonable (desirable) health behaviour choices. Effective prevention and access to mental health care are important, and so are developing the right attitudes,

reducing stigmas and providing health education (see Randver et al. in this chapter). Poor socioeconomic conditions and the stress that results from them are an indirect cause of both physical and mental health disorders. Such factors cannot be eliminated quickly, but measures that help reduce socioeconomic inequality or break the cycles of inequality persisting for generations are helpful (see Täht et al. in this chapter).

This chapter discusses mental health in a broad sense: we cover mental health problems, stress and coping with it, mental health services from prevention to specialist medical care, life satisfaction, and success. These topics derive from the WHO’s definition of mental health.

Life satisfaction is a person’s overall assessment of their life at a given moment: it depends both on their actual situation in life (e.g. health, education, employment status and income) and on mental health in a narrower sense (e.g. depressiveness, optimism and/or hopes for the future). Estonia is close to the European average in terms of life satisfaction. Life satisfaction increased both in Estonia and elsewhere in Europe in the decade before the pandemic.

Higher-than-usual stress levels occur more frequently among women and younger age groups, and the COVID-19 crisis has had a greater impact on women. The prevalence of stress in younger age groups rose sharply even a few years before the COVID-19 pandemic, and young people also experienced the most stress during the crisis. The rising stress levels during the COVID-19 crisis mainly concerned the health risks associated with the virus and overall uncertainty. Reasonable health behaviour and emotion regulation skills help reduce the negative effects of stress.

Success, or realising one’s abilities, is an important component of mental health and wellbeing. Success in school and work depends on a person’s home background. Success in school depends more on the educational resources accessed and attitudes encountered at home and less on the family’s socioeconomic status. In Estonia, the position of children in education is not strongly limited by the economic situation of their parents. Estonians tend to have materialistic and individualistic work values: income is considered essential when choosing a job. However, this tendency is changing, and opportunities for achievement are becoming valued more highly. Success is also important as a determinant of mental and physical health. The more opportunities there are to get a good education or a job despite unfavourable background factors, the less need there is to deal with health problems caused by stress or poor quality of life. In other words, problems in education reproduce mental health problems.

Data indicate that mental health problems are widespread among the adult population of Estonia. Based on self-reports, one in four adults is at risk of depression, and one in five is at risk of generalised anxiety disorder. Young adults are at significantly higher risk. The risk of depression and anxiety disorders increased during the COVID-19 pandemic. These tendencies are similar to those in other European countries. revious interview studies have probably underestimated the prevalence of depression and anxiety; the higher-than-usual stress levels found among young people even before the pandemic indirectly indicate this.

Preventing mental health problems is more cost-effective than treating them, and treating them is more cost-effective than not treating them at all. In Estonia, access to both prevention and treatment is limited, and the stigmatisation of mental health problems is an obstacle to receiving help. Early detection and simpler care pathways would help improve the accessibility and effectiveness of treatment. Developing socio-emotional and self-care skills and creating an environment that supports mental health is necessary to prevent problems.

Arango, C., Dragioti, E., Solmi, M., Cortese, S., Domschke, K., Murray, R. M., Jones, P. B., Uher, R., Carvalho, A. F., Reichenberg, A., Shin, J. I., Andreassen, O. A., Correll, C. U., & Fusar‐Poli, P. (2021). Risk and protective factors for mental disorders beyond genetics: an evidence‐based atlas. World Psychiatry, 20(3), 417–436.doi: 10.1002/wps.20894

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Goldstein, J. M., Cherkerzian, S., & Simpson, J. C. (2011). Validity: Definitions and applications to psychiatric research. in M. T. Tsuang, M. Tohen & P. B. Jones (Eds.) Textbook of Psychiatric Epidemiology (3rd ed.), New York: John Wiley & Sons.

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McEwen, B. (2002). The end of stress as we know it. New York: Dana Press.

Tarlov, A. R. (1999). Public Policy Frameworks for Improving Population Health. Annals of New York Academy of Sciences, 896, 281–93. doi:10.1111/j.1749-6632.1999.tb08123.x

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