Attribution for everyday discrimination typologies and mortality risk among older black adults: Evidence from the health and retirement study?

Ryon J Cobb; Violeta J Rodriguez; Tyson H Brown; Patricia Louie; Heather R Farmer; Connor M Sheehan; Dawne M Mouzon; Roland J Thorpe Jr

doi:10.1016/j.socscimed.2022.115166

Attribution for everyday discrimination typologies and mortality risk among older black adults: Evidence from the health and retirement study?

Soc Sci Med. 2023 Jan:316:115166. doi: 10.1016/j.socscimed.2022.115166. Epub 2022 Jul 6.

Authors

Ryon J Cobb¹, Violeta J Rodriguez², Tyson H Brown³, Patricia Louie⁴, Heather R Farmer⁵, Connor M Sheehan⁶, Dawne M Mouzon⁷, Roland J Thorpe Jr⁸

Affiliations

¹ Rutgers University, New Brunswick, USA. Electronic address: Ryon.Cobb@Rutgers.edu.
² University of Georgia, USA.
³ Duke University, USA.
⁴ University of Washington, USA.
⁵ University of Delaware, USA.
⁶ Arizona State University, USA.
⁷ Rutgers University, New Brunswick, USA.
⁸ Johns Hopkins University, USA.

PMID: 36450613
DOI: 10.1016/j.socscimed.2022.115166

Abstract

Background: The present study assessed how attributions of everyday discrimination typologies relate to all-cause mortality risk among older Black adults.

Methods: This study utilized data from a subsample of older Black adults from the 2006/2008 Health and Retirement Study (HRS). Attributions for everyday discrimination (i.e., ancestry, age, gender, race, physical appearance, physical disability, sexual orientation, weight, and other factors) were based on self-reports, while their vital statuses were obtained from the National Death Index and reports from key informants (spanning 2006-2019). We applied latent class analysis (LCA) to identify subgroups of older Black adults based on their attributions to everyday discrimination. Cox proportional hazards models were used to analyze time to death as a function of LCA group membership and other covariates.

Results: Based on fit statistics, we selected a four-class model that places respondents into one of the following classes: Class One (7%) attributed everyday discrimination to age, race, and physical disability; Class Two (72%) attributed everyday discrimination to few/no sources, Class Three (19%) attributed everyday discrimination to race and national origin; and Class Four (2%) attributed everyday discrimination to almost every reason. After adjusting for sociodemographic, behavioral, multisystem physiological dysregulation, and socioeconomic characteristics, we found that the relative risk of death remained higher for the respondents in Class One (Hazard Ratio [H.R.]: 1.80, 95% Confidence Interval [C.I.]: (1.09-2.98) and Class Four (H.R.: 3.92, 95% C.I.: 1.62-9.49) compared to respondents in Class Two.

Conclusions: Our findings illustrate the utility of using attribution for everyday discrimination typologies in research on the psychosocial dimensions of mortality risk among older Black adults. Future research should assess the mechanisms that undergird the link between everyday discrimination classes and all-cause mortality risk among older Black adults.

Keywords: Ageing; Minority Health; Perceived Discrimination; Psychosocial factors; Public health.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Adult
Black People
Disabled Persons*
Female
Humans
Male
Retirement*
Social Perception

Abstract

Publication types

MeSH terms

Grants and funding