International Journal of Epidemiology
Volume 43 Issue 2 April 2014
Psychiatric epidemiology and global mental health: joining forces
1Department of Epidemiology, Mailman School of Public Health, Columbia University and New York State Psychiatric Institute, New York, USA, and
Department of Epidemiology, Mailman School of Public Health, 722 W. 168th St, #1030, New York, NY 10032, USA.
2London School of Hygiene and Tropical Medicine, London, UK, 3Sangath, Goa, India and 4Centre for Mental Health, Public Health Foundation of India, New Delhi, India.
In our view, population mental health is integral to population health, or put more simply, there can be ‘no health without mental health’.1 It follows that there can be ‘no epidemiology of health without mental health.’ One obvious reason for paying more attention to mental health is the large contribution of mental disorders to the burden of disease across the globe.2 Another reason is that people with severe mental disorders represent a vulnerable and socially excluded population.3 Their lives are more likely to be afflicted by poverty, discrimination, human rights violations and increased morbidity and mortality rates. If we wish to ameliorate social inequality, we need to find ways to improve the living conditions as well as the health of this especially disadvantaged group. There are also many other relationships between social inequality and mental health. For example, socially advantaged groups tend to have more access in early life to environments that stimulate social, emotional and cognitive development, and these early advantages are related to a range of better mental health and social outcomes across the life course. Taking the broadest view, one could argue that the most valuable resource of modern societies is ‘human capital’, that the benchmark of progress is ‘human development’ and that mental health is fundamental to both.4–7
The reviews in this issue portray a remarkably diverse range of contributions that epidemiologists and other researchers have made to understanding and improving the mental health of populations across the globe. The thread that connects them is an exploration of the interface between psychiatric epidemiology and global mental health, and how closer links might be forged to the mutual benefit of both fields. Our introduction and the three accompanying commentaries8–10 focus on this theme from different angles.
Commentary: Epidemiological mental health research: contribution from low- and middle-income countries is essential
Paulo Rossi Menezes
Faculdade de Medicina da Universidade de São Paulo, Av. Dr Arnaldo 455, São Paulo, SP Brazil.
The burden of mental disorders is very high all over the world, as already pointed out in the previous comments of this special issue of IJE. Hopefully, the relevance of mental disorders as one of the world’s main public health priorities has started to become acknowledged. In its 2014 meeting, the World Economic Forum had mental health as one of its relevant topics (http://www.weforum.org/events/world-economic-forum-annual-meeting-2014). Last year the World Health Organization and member states approved the Mental Health Action Plan 2013, during the 65th World Health Assembly, which highlights the need for improvement in research capacity and academic collaboration on research in mental health in Low- And Middle-Income Countries (LAMIC), especially for operational research that can lead to service development and implementation. However, the challenge ahead is not simple. An investigation in 114 LAMIC in three continents showed that there is scarcity of both resources and capacity for mental health research, and that existing resources and capacity are very unevenly distributed.1 This special issue of IJE, focused on reviewing research evidence related to global mental health on its methodological aspects, aetiology, burden and impact, prevention and service evaluation, confirms how limited is the production of scientific knowledge about these topics in LAMIC.
Good quality epidemiological mental health research in LAMIC is urgently needed for several reasons. For instance, it can give better understanding about the aetiology of mental disorders, which can then lead to preventive public health actions, and it is essential to produce data that …
Estimating the coverage of mental health programmes: a systematic review
Mary J De Silva1,*, Lucy Lee1, Daniela C Fuhr1, Sujit Rathod1, Dan Chisholm2, Joanna Schellenberg3 and Vikram Patel1,4
1Centre for Global Mental Health, London School of Hygiene and Tropical Medicine, London, UK, 2Department of Mental Health and Substance Abuse, World Health Organization, Geneva, Switzerland, 3Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK and 4Sangath, Alto-Porvorim, Goa, India
Corresponding author. Centre for Global Mental Health, Department of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT. E-mail: email@example.com
Accepted August 21, 2013.
Background The large treatment gap for people suffering from mental disorders has led to initiatives to scale up mental health services. In order to track progress, estimates of programme coverage, and changes in coverage over time, are needed.
Methods Systematic review of mental health programme evaluations that assess coverage, measured either as the proportion of the target population in contact with services (contact coverage) or as the proportion of the target population who receive appropriate and effective care (effective coverage). We performed a search of electronic databases and grey literature up to March 2013 and contacted experts in the field. Methods to estimate the numerator (service utilization) and the denominator (target population) were reviewed to explore methods which could be used in programme evaluations.
Results We identified 15 735 unique records of which only seven met the inclusion criteria. All studies reported contact coverage. No study explicitly measured effective coverage, but it was possible to estimate this for one study. In six studies the numerator of coverage, service utilization, was estimated using routine clinical information, whereas one study used a national community survey. The methods for estimating the denominator, the population in need of services, were more varied and included national prevalence surveys case registers, and estimates from the literature.
Conclusions Very few coverage estimates are available. Coverage could be estimated at low cost by combining routine programme data with population prevalence estimates from national.