873
Views
6
CrossRef citations to date
0
Altmetric
Research Article

Gendered Patterns in Depression and Anxiety among African Immigrants in the United States

&
Pages 392-405 | Published online: 24 Apr 2020
 

ABSTRACT

Purpose

This study sought to examine gendered variations in determinants of depression and anxiety symptoms among African immigrants in the United States.

Methods

Data were drawn from a cross-sectional survey of first and second-generation immigrants from African countries living in the United States (N = 409).

Results

Ordinary Least Squares (OLS) regression results revealed gendered differences in factors that influence depression and anxiety symptoms. Second-generation immigrants showed decreased depression and anxiety symptoms among men, while income and marital status showed significant effects on depression and anxiety symptoms for women. Loneliness and discrimination were found to negatively impact the mental health of both female and male immigrants. Additionally, we found that gender did not moderate the effects of loneliness on depression and anxiety symptoms.

Conclusion

Findings highlight the need for practitioners to better understand the unique risk and protective factors affecting female and male African immigrants in their efforts to provide effective mental health services to members of this population.

Disclosure statement

The researchers do not perceive any conflicts of interest in regard to the presented study.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 360.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.