IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v316y2023ics0277953622003045.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953622003045
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2022.114998?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Glei, Dana A. & Lee, Chioun & Weinstein, Maxine, 2022. "Income, wealth, and Black-White disparities in cognition," Social Science & Medicine, Elsevier, vol. 310(C).
    2. Liu, Chelsea & Murchland, Audrey R. & VanderWeele, Tyler J. & Blacker, Deborah, 2022. "Eliminating racial disparities in dementia risk by equalizing education quality: A sensitivity analysis," Social Science & Medicine, Elsevier, vol. 312(C).
    3. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    4. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    5. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    6. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    7. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    8. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    9. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    10. Mélissa Lemoine & Gerhard Gmel & Simon Foster & Simon Marmet & Joseph Studer, 2020. "Multiple trajectories of alcohol use and the development of alcohol use disorder: Do Swiss men mature-out of problematic alcohol use during emerging adulthood?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    11. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.
    12. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    13. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    14. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    15. Esef Hakan Toytok & Sungur Gürel, 2019. "Does Project Children’s University Increase Academic Self-Efficacy in 6th Graders? A Weak Experimental Design," Sustainability, MDPI, vol. 11(3), pages 1-12, February.
    16. J M van Niekerk & M C Vos & A Stein & L M A Braakman-Jansen & A F Voor in ‘t holt & J E W C van Gemert-Pijnen, 2020. "Risk factors for surgical site infections using a data-driven approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    17. Joost R. Ginkel, 2020. "Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 185-205, March.
    18. Lara Jehi & Xinge Ji & Alex Milinovich & Serpil Erzurum & Amy Merlino & Steve Gordon & James B Young & Michael W Kattan, 2020. "Development and validation of a model for individualized prediction of hospitalization risk in 4,536 patients with COVID-19," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.
    19. Matthew Carli & Mary H. Ward & Catherine Metayer & David C. Wheeler, 2022. "Imputation of Below Detection Limit Missing Data in Chemical Mixture Analysis with Bayesian Group Index Regression," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    20. Gerko Vink & Laurence E. Frank & Jeroen Pannekoek & Stef Buuren, 2014. "Predictive mean matching imputation of semicontinuous variables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 61-90, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:316:y:2023:i:c:s0277953622003045. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.