Spatial structure of depression in South Africa: A longitudinal panel survey of a nationally representative sample of households

Cuadros, D.F., Tomita, A., Vandormael, A. , Slotow, R., Burns, J.K. and Tanser, F (2019) Spatial structure of depression in South Africa: A longitudinal panel survey of a nationally representative sample of households. Scientific Reports, 9 . p. 979. ISSN 2045-2322

Full content URL: https://doi.org/10.1038/s41598-018-37791-1

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Item Type:Article
Item Status:Live Archive

Abstract

Wider recognition of the mental health burden of disease has increased its importance as a global public health concern. However, the spatial heterogeneity of mental disorders at large geographical scales is still not well understood. Herein, we investigate the spatial distribution of incident depression in South Africa. We assess depressive symptomatology from a large longitudinal panel survey of a nationally representative sample of households, the South African National Income Dynamics Study. We identified spatial clusters of incident depression using spatial scan statistical analysis. Logistic regression was fitted to establish the relationship between clustering of depression and socio-economic, behavioral and disease risk factors, such as tuberculosis. There was substantial geographical clustering of depression in South Africa, with the excessive numbers of new cases concentrated in the eastern part of the country. These clusters overlapped with those of self-reported tuberculosis in the same region, as well as with poorer, less educated people living in traditional rural communities. Herein, we demonstrate, for the first time, spatial structuring of depression at a national scale, with clear geographical ‘hotspots’ of concentration of individuals reporting new depressive symptoms. Such geographical clustering could reflect differences in exposure to various risk factors, including socio-economic and epidemiological factors, driving or reinforcing the spatial structure of depression. Identification of the geographical location of clusters of depression should inform policy decisions.

Additional Information:cited By 1
Divisions:College of Social Science > Lincoln Institute of Health
ID Code:37516
Deposited On:09 Oct 2019 14:30

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