Mental health in the slums of Dhaka - a geoepidemiological study

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.

Figures

Figure 1

Geo-epidemiological approach used for this study. Parallelograms stand for geoprocessing or statistical processes, rhombuses for selection criteria and rectangles for outcomes. Note that levels were used only for conceptualising the socio-physical environment. All variables were available on the individual level, i.e. for each respondent separately and no aggregation to higher levels was done in order to prevent information loss.

Figure 2

Histograms for derived factors. Descriptive statistics for the factors extracted through factor analysis in SPSS 17.

Figure 3

Descriptive statistics for WHO-5 scores (mental well-being), self-rated health and diseases. For A and B, a bootstrap hypothesis test of equality between the both groups was applied with gender being equal (p value = 0.55) and wealth group being significantly different from each other (p value = 0.04), indicated by a reference band in grey. For B, least poor implies to the upper wealth index quintile, while most poor implies to the lowest. Note that for C and D, a WHO-5 scored 13 or above has been found to be indicative of good mental well-being in high-income country settings (cf. horizontal line).