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Resilience resources may buffer some middle-aged and older Black Americans from memory decline despite experiencing discrimination

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  • McDonough, Ian M.
  • Byrd, DeAnnah R.
  • Choi, Shinae L.

Abstract

Experiences of discrimination have been associated with poorer episodic memory in Black Americans. However, resilience resources at multiple levels (individual, social, and endowed) may act as a buffer to protect future memory decline, especially in the face of discrimination.

Suggested Citation

  • McDonough, Ian M. & Byrd, DeAnnah R. & Choi, Shinae L., 2023. "Resilience resources may buffer some middle-aged and older Black Americans from memory decline despite experiencing discrimination," Social Science & Medicine, Elsevier, vol. 316(C).
    • Handle: RePEc:eee:socmed:v:316:y:2023:i:c:s0277953622003045
    DOI: 10.1016/j.socscimed.2022.114998
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    References listed on IDEAS

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    1. Beaton, Derek & Chin Fatt, Cherise R. & Abdi, Hervé, 2014. "An ExPosition of multivariate analysis with the singular value decomposition in R," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 176-189.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Shannon Sisco & Alden L. Gross & Regina A. Shih & Bonnie C. Sachs & M. Maria Glymour & Katherine J. Bangen & Andreana Benitez & Jeannine Skinner & Brooke C. Schneider & Jennifer J. Manly, 2015. "The Role of Early-Life Educational Quality and Literacy in Explaining Racial Disparities in Cognition in Late Life," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 70(4), pages 557-567.
    4. Laura B ZahodnePhD & Ketlyne SolPhD & Zarina KraalMS, 2019. "Psychosocial Pathways to Racial/Ethnic Inequalities in Late-Life Memory Trajectories," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 74(3), pages 409-418.
    5. Janessa O. Carvalho & Doug Tommet & Paul K. Crane & Michael L. Thomas & Amy Claxton & Christian Habeck & Jennifer J. Manly & Heather R. Romero, 2015. "Deconstructing Racial Differences: The Effects of Quality of Education and Cerebrovascular Risk Factors," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 70(4), pages 545-556.
    6. Proust-Lima, Cécile & Philipps, Viviane & Liquet, Benoit, 2017. "Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i02).
    7. MacMahon, B., 1983. "The National Death Index," American Journal of Public Health, American Public Health Association, vol. 73(11), pages 1247-1248.
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