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Race, immigrant status, and inequality in physical activity: An intersectional and life course approach.

  • Published In: Canadian Review of Sociology, 2023, v. 60, n. 4. P. 763 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sher, Chloe; Wu, Cary 3 of 3

Abstract

Physical activity improves health and well‐being, but not everyone can be equally active. Previous research has suggested that racial minorities are less active than their white counterparts and immigrants are less active than their native‐born counterparts. In this article, we adopt an intersectional and life course approach to consider how race and immigrant status may intersect to affect physical activity across the life span. This new approach also allows us to test the long‐standing habitual versus structural debate in physical activity. Analysing data from two recent cycles of the Canadian Community Health Survey (CCHS, 2015–2016 & 2017–2018), we find that physical activity is only lower among immigrants who are also racial minorities and that the gap is most significant during adulthood, but rather insignificant during adolescence and late life. The findings that inequality in physical activity is more apparent among the most disadvantaged racialised immigrants and among working‐age adults when structural influences are greater suggest that inequality in physical activity is rooted in structural inequalities, rather than habitual differences. Finally, we demonstrate that the widely observed 'healthy (racialised) immigrant effect' can be underestimated if inequality in physical activity is not considered. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Canadian Review of Sociology. 2023/11, Vol. 60, Issue 4, p763
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:1755-6171
  • DOI:10.1111/cars.12451
  • Accession Number:173516000
  • Copyright Statement:Copyright of Canadian Review of Sociology is the property of Wiley-Blackwell 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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