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A Life Course Perspective on How Racism May Be Related to Health Inequities
Open accessAbstract
Recent studies show that racism may influence health inequities. As individuals grow from infancy into old age, they encounter social institutions that may create new exposures to racial bias. Yet, few studies have considered this idea fully. We suggest a framework that shows how racism and health inequities may be viewed from a life course perspective. It applies the ideas of age-patterned exposures, sensitive periods, linked lives, latency period, stress proliferation, historic period, and cohorts. It suggests an overarching idea that racism can structure one's time in asset-building contexts (e.g., education) or disadvantaged contexts (e.g., prison). This variation in time and exposure can contribute to racial inequities in life expectancy and other health outcomes across the life course and over generations.
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“There is no way to identify racial trauma other than through a life-course approach that captures the complex nature of individual, collective, historical, and intergenerational experiences of racism experienced by BIPOC communities in Western society.”
From Complex Racial Trauma: Evidence, Theory, Assessment, and Treatment (2023) · cites this paper as Gee et al., 2012
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“This finding suggests that the detrimental impact of racism may attenuate over time, perhaps because of the fading impact of brief exposure or due to individuals becoming ‘hardened’ to racism over time [412, 413].”
From Racism as a Determinant of Health: A Systematic Review and Meta-Analysis (2015) · cites this paper as [413]
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“Gee, Walsemann and Brondolo [413] have argued that explicit attention to the timing of racism is critical both for theoretical and empirical reasons, especially these dimensions of time: (1) the length of exposure to discriminatory events; (2) the timing of these events within the life course; and (3) the etiological period between exposure and the onset of illness.”
From Racism as a Determinant of Health: A Systematic Review and Meta-Analysis (2015) · cites this paper as [413]
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The Impact of Neighborhoods on Diabetes Risk and Outcomes: Centering Health Equity
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Metadata
- Authors
- Gee, G. C., Walsemann, K. M., & Brondolo, E.
- Affiliations
- St. John's University (US)
- Venue
- American Journal of Public Health
- Publisher
- American Public Health Association
- Published
- 2012-05
- Volume
- 102
- Issue
- 5
- Pages
- 967-974
- ISSN
- 0090-0036 (ISSN-L)
- 1541-0048
- PMC
- PMC3483932
- OpenAlex
- W2074565935
- Cited by
- 547
- References
- 97
- Citations by year
- 2026: 19 · 2025: 51 · 2024: 62 · 2023: 56 · 2022: 56 · 2021: 73 · 2020: 49 · 2019: 43 · 2018: 31 · 2017: 25 · 2016: 19 · 2015: 26 · 2014: 19 · 2013: 14 · 2012: 4
- FWCI
- 66.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Public Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Scholar Commons (University of South Carolina) (submittedVersion)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24HD041022)
- Topics
- Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
- Social Sciences › Health › Health disparities and outcomes
- Social Sciences › Sociology and Political Science › Gender, Health, and Social Inequality
- Keywords
- racism, health disparities, life course perspective, racial bias, sensitive period, linked lives, latency period, historical periods, cohort, asset building, disadvantaged contexts, life expectancy
- MeSH terms
- Age Factors, Humans, Prejudice, Social Environment, Stress, Psychological, Health Status Disparities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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