JOURNAL ARTICLE

Ethnic disparities in mental health problems in New Caledonia and French Polynesia.

  • Published In: Australian & New Zealand Journal of Psychiatry, 2024, v. 58, n. 11. P. 952 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sebbane, Déborah; Wathelet, Marielle; Amadeo, Stéphane; Goodfellow, Benjamin; Roelandt, Jean-Luc; Dourgnon, Paul; Chevreul, Karine 3 of 3

Abstract

This article focuses on the prevalence of mental health problems among Indigenous peoples in New Caledonia and French Polynesia, comparing these rates to those of non-indigenous populations while accounting for associated demographic and socioeconomic factors. Using data from the Mental Health in the General Population (MHGP) survey and the Mini-International Neuropsychiatric Interview (MINI), the study found that Indigenous participants exhibited higher rates of depressive disorder, alcohol use disorder, and suicide risk than their non-indigenous counterparts. However, after adjusting for factors such as age, education, income, and marital status, these differences largely disappeared except for alcohol use disorder, which remained significantly more prevalent among Indigenous individuals. The findings suggest that socioeconomic disparities largely explain mental health differences, highlighting the need for further research on healthcare access and utilization among Indigenous populations in these French overseas territories.

Additional Information

  • Source:Australian & New Zealand Journal of Psychiatry. 2024/11, Vol. 58, Issue 11, p952
  • Document Type:Article
  • Subject Area:Geography and Cartography
  • Publication Date:2024
  • ISSN:0004-8674
  • DOI:10.1177/00048674241267238
  • Accession Number:180428191
  • Copyright Statement:Copyright of Australian & New Zealand Journal of Psychiatry is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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