REVIEW ARTICLE


Typology of Social Network Structures and Late-Life Depression in Low- and Middle-Income Countries



Akin Ojagbemi1, *, Oye Gureje1
1 World Health Organization (WHO) Collaborating Centre for Research and Training in Mental Health, Neurosciences, and Substance Abuse, Department of Psychiatry, University of Ibadan, Ibadan, Nigeria


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Creative Commons License
© 2019 Ojagbemi & Gureje.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Psychiatry, College of Medicine, University of Ibadan, P.M.B 5017 (G.P.O) Ibadan, Nigeria; Tel: +234-8036737171;
E-mails: drakinjagbemi@yahoo.com; akinojagbemi@gmail.com


Abstract

Background:

Rapid social changes and youth migration ensures a continuous drain on the social networks of the elderly in Low- and Middle-Income Countries (LMICs).

Objective:

We reviewed available literature on the relationship between social network structures and depression among community dwelling older persons in LMICs with a view to identifying patterns that might provide information for designing preventive psychosocial interventions.

Methods:

We searched the MEDLINE database through Pubmed, extracted information on the typologies of social network structures in LMICs and identified dimensions with the strongest systematic association with late-life depression, by weight, using the inverse of variance method. All analyses were conducted using the Cochrane review manager version 5.3.

Results:

Fourteen community-based surveys drawn from 16 LMIC contexts met criteria for syntheses. They included a total of 37,917 mostly female (58.8%) participants with an average age of 73.2 years. Social network size, contact with network, diversity of network, co-residency with own child, having more friends than family in the network, and prestigious standing of persons in the social network were protective structures against late-life depression. Conversely, low network diversity contributed 44.2% of the weight of all social network structures that are predictive of late-life depression.

Conclusion:

Recommendations are made for the design of new measures of social network structures in LMICs that captures the key dimensions identified. Epidemiological studies using such tools will provide more precise information for planning and prioritization of scarce resources for the prevention of late-life depression in LMICs.

Keywords: Social relationships, Social support, Socio-economic transition, Extended family systems, Socio-economic context, Socio-cultural context.