Psychiatric epidemiology studies the distribution and causal mechanisms of mental disorders in the population (McQuistion, 2008). It is a branch of epidemiology with its own set of challenges, including difficult assessment of caseness, high comorbidity, complex measurement of risk-factors such as stress or lack of social support, costly diagnostics, and information bias (Burger & Neeleman, 2007). Despite these challenges, researchers have attempted to analyse epidemiological data to assess the impact of mental disorders on the global population. These studies, mostly based on the Global Burden of Disease data from the World Health Organization (WHO), provide useful comparative insights between higher and lower income countries.
According to a systematic review of WHO epidemiological data from 1990 and 2000 (Ferrari et al., 2013), depressive disorders are a leading cause of years lived with disability (YLDs) and of disability adjusted life years (DALYs), with Major Depressive Disorder (MDD) accounting for 85% of YLDs and DALYs in 2010. The authors acknowledge that this burden is likely to be underestimated due to their inability to quantify all of the outcomes of MDD. Despite the general prevalence of MDD regardless of socio-economic factors, the study shows some significant variations between higher and lower income countries.
For example, the study found an overall higher prevalence of MDD in North Africa and the Middle East, which could be explained by the rise of conflicts in those regions (Murray et al., 2012). There is indeed extensive evidence that major life changes, stress, and in particular trauma such as the one experienced by the population in these post-conflict countries are major factors in the prevalence of depressive disorders (Sabin et al., 2003; Roberts et al., 2009). Another study showed significantly variating levels of alcohol use disorder (AUD) between various countries: AUD DALYs can vary as much as ten times between regions, with the largest number at the global level in Eastern Europe, which has a comparatively lower income (Whiteford et al, 2013). Here again, there is strong evidence for the comorbidity of alcohol use disorder and MDD, which represents one of the most prevalent psychiatric combinations (Brière et al., 2014). MDD and substance abuse are in turn linked to higher suicide rates in these countries (Ferrari et al., 2014; Bertolote & Fleischmann, 2015).
On the other hand, higher income countries such as the United States and European countries show a lower prevalence of substance abuse, but a higher prevalence of dementia, including Alzheimer’s disease (Qiu et al., 2009). This variance can be explained by differences in the age structure of the populations: the prevalence rates of Alzheimer’s disease at ages 65, 75 and 85 are respectively 0.9%, 4.2%, and 14.7% (Brookmeyer, 2007). As the average age of the population of developing countries converges with the one of higher income countries, dementia is likely to become more prevalent (Kalaria et al., 2008).
It is important to note that cultural differences sometimes trump socio-economic influences on the prevalence of mental health disorders in a country. For example, Japan and South Korea, with high income levels, also have high suicide rates. But even in those cases some researchers have argued that an economic crisis could be the initiating event (Chang et al., 2009).
In addition to the strain on health budgets, mental health disorders place a significant burden on both lower-income and higher-income societies across individuals, families, workplaces and the wider economy, resulting in lower labour engagement, earlier retirement, and welfare dependency (Doran, 2017). Many factors impacted by public policies such as urbanisation, new forms of communications, global trade regulations, and migrations have an influence on population mental health (Susser & Patel, 2014).
Thus, epidemiological data is essential to design policies and interventions, ensuring unmet needs are addressed. For example, in Europe, mental disorders represent a significant disability burden in terms of number of work days lost, but less than a third of all cases of mental disorders receive any treatment (Wittchen & Jacobi, 2011). The situation is worse in lower-income economies, where resources such as mental health services, funding, and human resources are not readily available, which means that populations with the highest need for mental health care have the lowest access to it (Saxena et al., 2007).
More resources and research are needed: the current studies all have limitations, with little data around lower-prevalence disorders such as bipolar disorders. This is why a consortium of researchers advocates for future research across all disorders and age groups (Collins et al., 2011) so factors can be better understood, prevention and intervention strategies better designed, healthy systems transformed to deliver effective treatments, and outcomes more accurately measured.
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