Inequalities in Psychiatric Morbidity in Hong Kong and Strategies for Mitigation

Int J Environ Res Public Health. 2022 Jun 9;19(12):7095. doi: 10.3390/ijerph19127095.

Abstract

This study explores the social gradient of psychiatric morbidity. The Hong Kong Mental Morbidity Survey (HKMMS), consisting of 5719 Chinese adults aged 16 to 75 years, was used. The Chinese version of the Revised Clinical Interview Schedule (CIS-R) was employed for psychiatric assessment of common mental disorders (CMD). People with a less advantaged socioeconomic position (lower education, lower household income, unemployment, small living area and public rental housing) had a higher prevalence of depression and anxiety disorder. People with lower incomes had worse physical health (OR 2.01, 95% CI 1.05-3.82) and greater odds of having CMD in the presence of a family history of psychiatric illnesses (OR 1.67, 95% CI 1.18-2.36). Unemployment also had a greater impact for those in lower-income groups (OR 2.67; 95% CI 1.85-3.85), whereas no significant association was observed in high-income groups (OR 0.56; 95% CI 0.14-2.17). Mitigating strategies in terms of services and social support should target socially disadvantaged groups with a high risk of psychiatric morbidity. Such strategies include collaboration among government, civil society and business sectors in harnessing community resources.

Keywords: Hong Kong; inequality; mental health policy; mental morbidity; social gradient.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anxiety Disorders* / epidemiology
  • Hong Kong / epidemiology
  • Humans
  • Income
  • Prevalence
  • Unemployment* / psychology

Grants and funding

The Hong Kong Mental Morbidity Survey is a commissioned project supported by the Health and Health Services Research Fund (Ref: 09101601), Food and Health Bureau, Hong Kong SAR Government. The research in this paper was supported by a research project grant from the Chinese University of Hong Kong Institute of Health Equity, which was funded by the Vice-Chancellor’s Discretionary Fund of the Chinese University of Hong Kong (Project Ref No.: 136604080).