Social network analysis of psychological morbidity in an urban slum of Bangladesh: a cross-sectional study based on a community census

BMJ Open. 2018 Jul 16;8(7):e020180. doi: 10.1136/bmjopen-2017-020180.

Abstract

Objectives: To test whether social ties play any roles in mitigating depression and anxiety, as well as in fostering mental health among young men living in a poor urban community.

Setting: A cohort of all young men living in an urban slum in Dhaka, the capital of Bangladesh.

Participants: All men aged 18-29 years (n=824) living in a low-income urban community at the time of the survey.

Primary and secondary outcome measures: Unspecified psychological morbidity measured using the General Health Questionnaire, 12-item (GHQ-12), where lower scores suggest better mental status.

Results: The GHQ scores (mean=9.2, SD=4.9) suggest a significant psychological morbidity among the respondents. However, each additional friend is associated with a 0.063 SD lower GHQ score (95% CI -0.106 to -0.021). Between centrality measuring the relative importance of the respondent within his social network is also associated with a 0.103 SD lower GHQ score (95% CI -0.155 to -0.051), as are other measures of social network ties. Among other factors, married respondents and recent migrants also report a better mental health status.

Conclusions: Our results underscore the importance of social connection in providing a buffer against stress and anxiety through psychosocial support from one's peers in a resource-constraint urban setting. Our findings also suggest incorporating a social network and community ties in designing mental health policies and interventions.

Keywords: mental health; public health; social determinants; social network.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Anxiety / epidemiology
  • Bangladesh / epidemiology
  • Censuses
  • Cross-Sectional Studies
  • Depression / epidemiology
  • Humans
  • Male
  • Mental Health / statistics & numerical data*
  • Morbidity
  • Multivariate Analysis
  • Poverty Areas*
  • Regression Analysis
  • Sex Factors
  • Social Networking*
  • Stress, Psychological / epidemiology
  • Urban Population / statistics & numerical data*
  • Young Adult