Evidence map›Paper›PMID 42730015›Full record

ArticleInternational journal of women's health2026

Spatiotemporal Epidemiology of Endometriosis: Global, Regional, and National Trends from 1990 to 2019.

Xiaoyan Lu, Shanshan Ni

Abstract read
In one paragraph

Article in International journal of women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Xiaoyan LuDepartment of Obstetrics, Beilun People's Hospital, Ningbo, Zhejiang, 31580, People's Republic of China.
Shanshan NiDepartment of Obstetrics, Beilun People's Hospital, Ningbo, Zhejiang, 31580, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study utilized 1990-2019 data from the Global Burden of Disease (GBD) 2019 study to comprehensively evaluate global and regional temporal trends of endometriosis burden. Patients and Methods: Age-standardized incidence rates (ASIR) and disability-adjusted life year (DALY) rates were extracted from GBD 2019. Using the DisMod-MR 2.1 modeling framework, we analyzed three-decade trends across 204 countries and territories. Results: Globally, endometriosis presented opposing trends in age-standardized incidence rate (ASIR) and age-standardized DALY rate from 1990 to 2019. The global age-standardized DALY rate declined markedly, with an EAPC of -0.82, while the ASIR rose steadily (EAPC = 0.46). Stratified by Socio-Demographic Index (SDI), high-SDI regions witnessed the most prominent growth in ASIR, with an EAPC of 0.54. Among the 21 GBD geographic regions, High-income North America had the fastest ASIR growth (EAPC = 0.65). Eastern Europe was the only region with rising age-standardized DALY rates (EAPC = 0.16). Oceania bore the world's largest overall endometriosis burden, with the highest ASIR and age-standardized DALY rates globally. At the national level, New Zealand had the highest disease burden, whereas San Marino and Sweden showed the steepest increases in incidence rates. Conclusion: These findings reveal persistent global growth in endometriosis incidence coupled with stark interregional disparities. The paradox of rising incidence alongside declining disability warrants further investigation, particularly given Oceania's disproportionately high burden despite its advanced SDI status.

Indexed as

adultdisability adjusted life yearendometriosisincidencesocio-demographic index

Identifiers

PMID42730015
PMCPMC13564468

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.