Evidence map›Paper›PMID 37460920›Full record

ReviewJournal of racial and ethnic health disparities2024

Unspoken Consequences of Structural Racism in the USA: Diabetes and COVID-19.

Nicole Taikeff, Angela Achkar, Elie Naous, Joanna Mitri

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of racial and ethnic health disparities, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

4 authors.

Nicole Taikeff *Division of Clinical Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.ORCID 0000-0003-3832-8899
Angela Achkar *Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA. aachkar@bwh.harvard.edu.ORCID 0000-0002-1882-5874
Elie NaousDivision of Internal Medicine, St. Elizabeth's Medical center, Tufts Medical School and Boston University Medical School, Brighton, MA, 02135, USA.ORCID 0000-0001-7755-8844
Joanna MitriJoslin Diabetes Center, Harvard Medical School, Boston, MA, 02215, USA.ORCID 0000-0002-3257-3618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesBlack, Indigenous, and People of Color (BIPOC) are disproportionately impacted by the diabetes epidemic. This health inequity, aggravated by environmental, lifestyle, and genetic factors, has been further exacerbated by the COVID-19 pandemic. The increased risk of severe complications due to COVID-19 in BIPOC communities speaks to the importance of understanding the impacts of social and structural factors on health. This report aims to outline the connection between diabetes and vulnerability to COVID-19 through the lens of racism. STUDY

designReview of original report and subsequent modeling and interpretations.

methodsWe reviewed and analyzed original data in relation to health inequity, diabetes, COVID-19, and BIPOC.

resultsThis holistic approach framed the disproportionate prevalence of diabetes and vulnerability to COVID-19 not just as a health disparity, but as a health inequity.

conclusionDefining the relationship between diabetes, vulnerability to COVID-19, and systems of advantage, such as racism, can further support the design of health interventions and policies that reduce the disproportionate impact of these diseases on the health of BIPOC communities.

Indexed as

COVID-19Diabetes MellitusHealth Status DisparitiesSystemic RacismBlack or African AmericanHumansMinority GroupsUnited StatesCOVID-19DiabetesDisparityEthnicityRaceUSA

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.