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Open Access Highly Accessed Research article

Mental health in the slums of Dhaka - a geoepidemiological study

Oliver Gruebner1*, M Mobarak H Khan2, Sven Lautenbach135, Daniel Müller14, Alexander Krämer2, Tobia Lakes1 and Patrick Hostert1

Author Affiliations

1 Geomatics Lab, Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany

2 Department of Public Health Medicine, School of Public Health, University of Bielefeld, Bielefeld, Germany

3 Department for Computational Landscape Ecology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany

4 Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), Halle (Saale), Germany

5 Department of Urban Planing and Real Estate Management, Institute of Geodesy and Geoinformation- IGG Bonn, Universität Bonn, Bonn, Germany

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BMC Public Health 2012, 12:177  doi:10.1186/1471-2458-12-177

Published: 9 March 2012

Abstract

Background

Urban health is of global concern because the majority of the world's population lives in urban areas. Although mental health problems (e.g. depression) in developing countries are highly prevalent, such issues are not yet adequately addressed in the rapidly urbanising megacities of these countries, where a growing number of residents live in slums. Little is known about the spectrum of mental well-being in urban slums and only poor knowledge exists on health promotive socio-physical environments in these areas. Using a geo-epidemiological approach, the present study identified factors that contribute to the mental well-being in the slums of Dhaka, which currently accommodates an estimated population of more than 14 million, including 3.4 million slum dwellers.

Methods

The baseline data of a cohort study conducted in early 2009 in nine slums of Dhaka were used. Data were collected from 1,938 adults (≥ 15 years). All respondents were geographically marked based on their households using global positioning systems (GPS). Very high-resolution land cover information was processed in a Geographic Information System (GIS) to obtain additional exposure information. We used a factor analysis to reduce the socio-physical explanatory variables to a fewer set of uncorrelated linear combinations of variables. We then regressed these factors on the WHO-5 Well-being Index that was used as a proxy for self-rated mental well-being.

Results

Mental well-being was significantly associated with various factors such as selected features of the natural environment, flood risk, sanitation, housing quality, sufficiency and durability. We further identified associations with population density, job satisfaction, and income generation while controlling for individual factors such as age, gender, and diseases.

Conclusions

Factors determining mental well-being were related to the socio-physical environment and individual level characteristics. Given that mental well-being is associated with physiological well-being, our study may provide crucial information for developing better health care and disease prevention programmes in slums of Dhaka and other comparable settings.