JOURNAL ARTICLE

Sexual and reproductive health and rights knowledge and learning experiences of 1.5-generation Bangladeshi women in Toronto: An intersectional analysis.

  • Published In: Canadian Journal of Human Sexuality, 2025, v. 34, n. 1. P. 124 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nowshin, Nahela; Kapiriri, Lydia; Davison, Colleen M. 3 of 3

Abstract

This article examines the sexual and reproductive health and rights (SRHR) knowledge and learning experiences of 1.5-generation Bangladeshi women—those who immigrated to Canada as children or adolescents—living in Toronto, Ontario. Using an intersectional framework, the study identifies significant gaps in participants’ understanding of sexually transmitted diseases/infections (STDs/STIs), their transmission, prevention, symptoms, and contraception, alongside limited uptake and depth of school-based sex education. The research highlights how intersecting social identities (age, gender, ethnicity, religion) and contextual factors (family, culture of origin, country of emigration, media) shape SRHR knowledge formation, with cultural taboos and limited parental communication further constraining information access. The findings underscore the need for improved, culturally sensitive sex education in schools and community-based initiatives that engage families to better support the SRHR information needs of Bangladeshi immigrant youth in Toronto.

Additional Information

  • Source:Canadian Journal of Human Sexuality. 2025/04, Vol. 34, Issue 1, p124
  • Document Type:Article
  • Subject Area:Geography and Cartography
  • Publication Date:2025
  • ISSN:1188-4517
  • DOI:10.3138/cjhs-2024-0015
  • Accession Number:184837025
  • Copyright Statement:Copyright of Canadian Journal of Human Sexuality is the property of University of Toronto Press 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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