Evidence map›Paper›PMID 38702093›Full record

ArticleThe Lancet. Public health2024

Differences across the lifespan between females and males in the top 20 causes of disease burden globally: a systematic analysis of the Global Burden of Disease Study 2021.

Vedavati Patwardhan, Gabriela F Gil, Alejandra Arrieta, Jack Cagney, Erin DeGraw, Molly E Herbert, Mariam Khalil, Erin C Mullany, Erin M O'Connell, Cory N Spencer and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 149 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
149citing papers in PubMed, 3 pooled it
–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

149 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Review
  7. Article
  8. Review
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. The Apparent Discrepancy Between Social Inequality in Disability-Free and Quality-Adjusted Life Expectancy.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026
    Article

89 more citing papers are in PubMed but not listed here.

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

14 authors.

Vedavati PatwardhanCenter on Gender Equity and Health, University of California, San Diego, CA, USA.
Gabriela F GilInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Alejandra ArrietaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Jack CagneyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Erin DeGrawInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Molly E HerbertInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Mariam KhalilInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Erin C MullanyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Erin M O'ConnellInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Cory N SpencerInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Caroline SteinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Aiganym ValikhanovaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Emmanuela GakidouInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Luisa S FlorInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA. Electronic address: lsflor@uw.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSex and gender shape health. There is a growing body of evidence focused on comprehensively and systematically examining the magnitude, persistence, and nature of differences in health between females and males. Here, we aimed to quantify differences in the leading causes of disease burden between females and males across ages and geographies.

methodsWe used the Global Burden of Disease Study 2021 to compare disability-adjusted life-year (DALY) rates for females and males for the 20 leading causes of disease burden for individuals older than 10 years at the global level and across seven world regions, between 1990 and 2021. We present absolute and relative differences in the cause-specific DALY rates between females and males.

findingsGlobally, females had a higher burden of morbidity-driven conditions with the largest differences in DALYs for low back pain (with 478·5 [95% uncertainty interval 346·3-632·8] more DALYs per 100 000 individuals among females than males), depressive disorders (348·3 [241·3-471·0]), and headache disorders (332·9 [48·3-731·9]), whereas males had higher DALY rates for mortality-driven conditions with the largest differences in DALYs for COVID-19 (with 1767·8 [1581·1-1943·5] more DALYs per 100 000 among males than females), road injuries (1012·2 [934·1-1092·9]), and ischaemic heart disease (1611·8 [1405·0-1856·3]). The differences between sexes became larger over age and remained consistent over time for all conditions except HIV/AIDS. The largest difference in HIV/AIDS was observed among those aged 25-49 years in sub-Saharan Africa with 1724·8 (918·8-2613·7) more DALYs per 100 000 among females than males.

interpretationThe notable health differences between females and males point to an urgent need for policies to be based on sex-specific and age-specific data. It is also important to continue promoting gender-sensitive research, and ultimately, implement interventions that not only reduce the burden of disease but also achieve greater health equity.

fundingBill & Melinda Gates Foundation.

Indexed as

Disability-Adjusted Life YearsGlobal Burden of DiseaseAdolescentAdultAgedChildCost of IllnessCOVID-19FemaleGlobal HealthHumansLongevityMaleMiddle AgedSex FactorsYoung Adult

Identifiers

PMID38702093
PMCPMC11080072

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.