Evidence map›Paper›PMID 40408105›Full record

ArticleJAMA network open2025

Priority Health Conditions and Global Life Expectancy Disparities.

Omar Karlsson, Angela Y Chang, Ole F Norheim, Wenhui Mao, Sarah Bolongaita, Dean T Jamison

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
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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

6 authors.

Omar KarlssonCentre for Economic Demography, School of Economics and Management, Lund University, Lund, Sweden.
Angela Y ChangDanish Institute for Advanced Study, University of Southern Denmark, Copenhagen, Denmark.
Ole F NorheimDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Wenhui MaoCentre for Policy Impact in Global Health, Duke University, Durham, North Carolina.
Sarah BolongaitaDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Dean T JamisonInstitute for Global Health Sciences, University of California, San Francisco.

Funding

STALLARD Admin Supp: Predicting Future Care Needs and Costs for Individual Medicare Enrollees with Incident Suspected Alzheimer's DiseaseP30AG034424 · NIA · DUKE UNIVERSITY · PI SCOTT M. LYNCH · 2009 to 2026
$12.2M
Science CoreP2CHD065563 · NICHD · DUKE UNIVERSITY · PI Giovanna M Merli · 2015 to 2026
$5.7M
NIA NIH HHS P30 AG034424NICHD NIH HHS P2C HD065563
6 · The paper itself

Abstract

Importance: Life expectancy is a composite health measure reflecting acute and life-course exposures. Identifying conditions behind disparities in life expectancy can guide policy, planning, and financing to battle the most urgent health problems. Objective: To examine the contribution of 33 causes of death to life expectancy disparities, highlighting 2 sets of priority conditions-8 infectious and maternal and child health conditions (I-8) and 7 noncommunicable diseases and injuries (NCD-7). Design, Setting, and Participants: This cross-sectional study examined life expectancy disparities in 7 global regions and 165 countries from 2000 to 2021. Western Europe and Canada (hereafter referred to as the North Atlantic) in 2019 were used as a benchmark for life expectancy achievable with advanced health care and living standards. Life expectancy gaps in locations with life expectancy lower than the benchmark were decomposed by cause of death using the Pollard decomposition on the Global Health Estimates from the World Health Organization. Data were analyzed from February to March 2025. Exposure: Geographic location (countries and regions). Main Outcome and Measure: Life expectancy at birth. Results: In the median country in 2019, the I-8 and NCD-7 together accounted for 80% (IQR, 71%-88%) of the life expectancy gap compared with the North Atlantic. Outside sub-Saharan Africa, the NCD-7 accounted for the largest share of the gap; for example, more than the total life expectancy gap in China, or 5.5 (95% uncertainty bounds [UB], 5.0-6.0) years of a 4.3-year life expectancy gap; and 6.4 (95% UB, 5.9-6.8) years of a 11.5-year gap in India. However, reduced mortality from the I-8 contributed to enormous improvements in sub-Saharan Africa, accounting for 21.4 (95% UB, 20.6-22.2) years of a 31-year gap in 2000 and 11.4 (95% UB, 10.9-11.8) years of a 22-year gap in 2019. India transitioned from having most of the gap accounted for by the I-8 in 2000, or 11.9 (95% UB, 11.0-13.0) years of a 19.6-year life expectancy gap, to having a larger share accounted for by the NCD-7 in 2019. Conclusions and Relevance: This cross-sectional study suggests that a limited number of causes account for most life expectancy disparities. Together with current information on risk factors, interventions, and morbidity not yet reflected in life expectancy, the varying contributions of these causes to gaps in life expectancy can help focus health policy and guide interventions to reduce risk factors and treat conditions.

Indexed as

Global HealthHealth PrioritiesHealth Status DisparitiesLife ExpectancyNoncommunicable DiseasesAdultCause of DeathChildCross-Sectional StudiesFemaleHumansMaleMiddle Aged

Identifiers

PMID40408105
PMCPMC12102710

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.