MétaCan
Menu
← Back to cohort
Record W4308991735 · doi:10.1101/2022.11.12.22282253

Excess Mortality and Years of Potential Life Lost Among Black People in the US from 1999 to 2020

2022· preprint· en· W4308991735 on OpenAlexaff
César Caraballo, Daisy Massey, Chima D. Ndumele, Trent Haywood, Shayaan Kaleem, Terris King, Yuntian Liu, Yuan Lu, Marcella Nuñez-Smith, Herman A. Taylor, Karol E. Watson, Jeph Herrin, Clyde W. Yancy, Jeremy Samuel Faust, Harlan M. Krumholz

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Toronto
FundersYale UniversityPfizer
KeywordsYears of potential life lostDemographyExcess mortalityMedicineGerontologyMortality rateBlack womenWhite (mutation)PopulationEnvironmental healthLife expectancySurgery

Abstract

fetched live from OpenAlex

ABSTRACT Importance Amid efforts in the United States to promote health equity, there is a need to assess progress in reducing excess deaths and years of potential life lost (YPLL) among Black people compared with White people. Objective To evaluate trends in excess mortality and YPLL among Black people compared with White people. Design Serial cross-sectional. Setting National data from the Centers for Disease Control and Prevention, 1999-2020 Participants Non-Hispanic White and non-Hispanic Black people Exposures Race as documented in the death certificates. Main outcomes and measures Excess age-adjusted all-cause and disease-specific mortality rate (per 100,000 individuals) and YPLL among Black people compared with White people. Results From 1999 to 2020, the total number of excess deaths was 658,356 and 1,154,108 among Black females and males, representing 34,938,070 and 47,005,048 excess YPLL among Black females and males. The excess deaths and YPLL were largest among infants and non-elderly adults. Heart disease had the most excess deaths. From 1999, the age-adjusted excess mortality rate declined at an annual average of -9.0 (95% CI: -10.0, -8.0; P<0.001) until 2015 among Black women and at an annual average of -16.3 (95% CI: -20.9, -11.6; P<0.001) until 2012 among Black men, followed by no significant change until 2019 in either group. From 2019 to 2020, excess deaths increased from 90.4 to 192 per 100,000 Black women and from 209.8 to 395 per 100,000 Black men, reaching rates approximating those of 1999. The trends in rates of excess YPLL followed a similar pattern. Conclusions and relevance Over a recent 22-year period, Black people in the US lost more than 80 million years of life when compared with White people. After a period of progress, improvements stalled, and most gains were eliminated in 2020. KEY POINTS Question How many excess deaths and years of potential life lost (YPLL) for Black people, compared with White people, occurred in the United States from 1999 through 2020? Findings Based on Centers for Disease Control and Prevention data, excess deaths and YPLL persisted throughout the period, with initial progress followed by little improvement, and then worsening in 2020 to about 1999 levels. Black people had 1.8 million excess deaths and over 80 million YPLL over the study period. Meaning After initial progress, excess mortality and YPLL among Black people stagnated and then worsened, indicating a need for new approaches.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.341
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuemedRxiv→Same topicHealth disparities and outcomes→French-language works237,207→