Cost of depression in Europe

J Ment Health Policy Econ. 2006 Jun;9(2):87-98.


Background: Depression is one of the most disabling diseases, and causes a significant burden both to the individual and to society. WHO data suggests that depression causes 6% of the burden of all diseases in Europe in terms of disability adjusted life years (DALYs). Yet, the knowledge of the economic impact of depression has been relatively little researched in Europe.

Aims of the study: The present study aims at estimating the total cost of depression in Europe based on published epidemiologic and economic evidence.

Methods: A model was developed to combine epidemiological and economic data on depression in Europe to estimate the cost. The model was populated with data collected from extensive literature reviews of the epidemiology and economic burden of depression in Europe. The cost data was calculated as annual cost per patient, and epidemiologic data was reported as 12-month prevalence estimates. National and international statistics for the model were retrieved from the OECD and Eurostat databases. The aggregated annual cost estimates were presented in Euro for 2004.

Results: In 28 countries with a population of 466 million, at least 21 million were affected by depression. The total annual cost of depression in Europe was estimated at Euro 118 billion in 2004, which corresponds to a cost of Euro 253 per inhabitant. Direct costs alone totalled dollar 42 billion, comprised of outpatient care (Euro 22 billion), drug cost (Euro 9 billion) and hospitalization (Euro 10 billion). Indirect costs due to morbidity and mortality were estimated at Euro 76 billion. This makes depression the most costly brain disorder in Europe, accounting for 33% of the total cost. The cost of depression corresponds to 1% of the total economy of Europe (GDP).

Discussion: Our cost results are in good agreement with previous research findings. The cost estimates in the present study are based on model simulations for countries where no data was available. The predictability of our model is limited to the accuracy of the input data employed. As there is no earlier cost-of-illness study conducted on depression in Europe, it is, however, difficult to evaluate the validity of our results for individual countries and thus further research is needed.

Conclusion: The cost of depression poses a significant economic burden to European society. The simulation model employed shows good predictability of the cost of depression in Europe and is a novel approach to estimate the cost-of-illness in Europe. IMPLICATIONS FOR HEALTH CARE PROVISION AND POLICIES: Health and social care policy and commissioning must be evidence-based. The empirical results from this study confirm previous findings, that depression is a major concern to the economic welfare in Europe which has consequences to both healthcare providers and policy makers. One important way to stop this explosion in cost is through increased research efforts in the field. Moreover, better detection, prevention, treatment and patient management are imperatives to reduce the burden of depression and its costs. Mental healthcare policies and better access to healthcare for mentally ill are other challenges to improve for Europe.

Implications for further research: This study has identified several research gaps which are of interest for future research. In order to better understand the impact of depression to European society long-term prospective epidemiology and cost-of-illness studies are needed. In particular data is lacking for Central European countries. On the basis of our findings, further economic evaluations of treatments for depression are necessary in order to ensure a cost-effective use of European healthcare budgets.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cost of Illness*
  • Depressive Disorder / economics*
  • Depressive Disorder / epidemiology*
  • Europe / epidemiology
  • Health Care Costs / statistics & numerical data*
  • Humans
  • Mental Health Services / economics*
  • Mental Health Services / statistics & numerical data
  • Models, Econometric
  • Prevalence