Evidence map›Paper›PMID 40358946›Full record

ArticleJAMA network open2025

African Genetic Ancestry, Structural and Social Determinants of Health, and Mortality in Black Adults.

Hari S Iyer, Iona Cheng, Chidinma Opara, Katherine Lin, Nur Zeinomar, Loïc Le Marchand, Lynne Wilkens, Salma Shariff-Marco, David V Conti, Christopher A Haiman and 2 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Aortic dissection mortality in the United States, 1968-2023: Trends, disparities, and deep learning forecasts.International journal of cardiology. Cardiovascular risk and prevention · 2025
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Hari S IyerSection of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute, New Brunswick, New Jersey.
Iona ChengDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Chidinma OparaSection of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute, New Brunswick, New Jersey.
Katherine LinDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Nur ZeinomarSection of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute, New Brunswick, New Jersey.
Loïc Le MarchandEpidemiology Program, University of Hawaii Cancer Center, Honolulu.
Lynne WilkensEpidemiology Program, University of Hawaii Cancer Center, Honolulu.
Salma Shariff-MarcoDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
David V ContiCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles.
Christopher A HaimanCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles.
Scarlett L GomezDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Timothy R RebbeckDivision of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.

Funding

Understanding Population Differences in Cancer: The MEC StudyU01CA164973 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI HAIMAN, CHRISTOPHER ALAN, LE MARCHAND, LOIC · 2015 to 2025
$37.4M
Training Program in Cancer EpidemiologyT32CA009001 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI A. Heather Eliassen, Meir Stampfer · 1985 to 2026
$17.3M
Leveraging Prospective Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk ScoresU01CA261339 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fei Chen, David V Conti · 2021 to 2026
$5.2M
Precision Interception of Aggressive Prostate Cancer in African American MenP20CA233255 · NCI · DANA-FARBER CANCER INST · PI REBBECK, TIMOTHY R · 2018 to 2020
$3.2M
NCI NIH HHS P20 CA233255NCI NIH HHS T32 CA009001NCI NIH HHS U01 CA164973NCI NIH HHS U01 CA261339
6 · The paper itself

Abstract

Importance: Although structural and social determinants of health (SSDH) have been consistently associated with health disparities, percentage African genetic ancestry (AGA) has been suggested as a risk factor associated with common diseases in Black populations. Appropriate use and interpretation of percentage AGA in understanding health disparities has been complicated by the fact that percentage AGA is correlated with genetic and nongenetic factors. Objective: To evaluate associations of SSDH with mortality in the context of percentage AGA and how percentage AGA is correlated with SSDH. Design, Setting, and Participants: This cohort study investigated data from the Multiethnic Cohort (MEC) Study, in which participants were enrolled from 1993 through 1996 and followed up until death or censoring on December 31, 2019. Participant data were analyzed between March and June 2023. The population-based sample was predominantly from Los Angeles County, California, consisting of self-identified Black adults aged 45 to 75 years who enrolled into the MEC Study; completed a baseline demographic, clinical, and lifestyle questionnaire; and provided biospecimens. Exposures: The Index of Concentration at the Extremes (ICE), capturing social polarization based on income and racial composition, and a neighborhood socioeconomic status (NSES) index were computed from the 1990 Census, scaled to county-specific quintiles, and linked to residential census tracts at study enrollment. Percentage AGA was estimated using 21 431 single-nucleotide variations based on similarity with African continental referent data. Main Outcomes and Measures: Multivariable hazard ratios (HRs) for all-cause mortality were estimated from Cox models. Correlation of percentage AGA with SSDH measures was described. Results: After exclusions, 9685 participants were included (mean [SD] age, 61.0 [8.9] years; 5593 female [57.7%]), with a mean (SD) percentage AGA of 75.0% (14.0%). There were 5504 deaths over 204 463 person-years of follow-up. Comparing the most with least advantaged quintile, income ICE (adjusted HR [aHR], 1.30; 95% CI, 1.16-1.45) and NSES (aHR, 1.37, 95% CI, 1.20-1.56) were associated with lower all-cause mortality. Minimal changes were observed after adjusting for percentage AGA; for example, comparing the most with least advantaged quintile, NSES (aHR, 1.36; 95% CI, 1.19-1.55) remained associated with lower all-cause mortality. There was no association between percentage AGA and mortality after adjustment (aHR per 10-percentage point change in percentage AGA, 1.01; 95% CI, 0.99-1.03). Conclusions and Relevance: In this study, associations of SSDH with mortality persisted with adjustment for percentage AGA. Findings support the hypothesis that SSDH should be the primary factors to consider for eliminating health disparities.

Indexed as

Black or African AmericanHealth Status DisparitiesMortalitySocial Determinants of HealthAgedCaliforniaCohort StudiesFemaleHumansMaleMiddle AgedRisk Factors

Identifiers

PMID40358946
PMCPMC12076178

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.