Evidence map›Paper›PMID 39315583›Full record

ArticleCancer medicine2024

Global burden of lung cancer in women of childbearing age attributable to ambient particulate matter pollution: 1990-2021.

Ying-da Song, Ruizhe Wang, Jia-Xuan Wang, Xun-Wu Tan, Jun Ma

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ying-da SongDepartment of Thoracic Surgery, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China.
Ruizhe WangDepartment of Thoracic Surgery, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China.
Jia-Xuan WangFirst Clinical Medical College, Changzhi Medical College, Changzhi, Shanxi, China.
Xun-Wu TanSecond Clinical Medical College, Changzhi Medical College, Changzhi, Shanxi, China.
Jun MaDepartment of Thoracic Surgery, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China.ORCID https://orcid.org/0009-0001-3512-4244

Funding

Natural Science Foundation of Shanxi Province 202103021224383
6 · The paper itself

Abstract

backgroundThis study aimed to evaluate the global burden of lung cancer due to ambient particulate matter (PM) pollution in women of childbearing age from 1990 to 2021.

methodsThis was a secondary analysis utilizing data from the Global Burden of Disease (GBD) 2021, with a focus on the temporal trends of the lung cancer burden attributable to ambient PM2.5 among women of childbearing age.

resultsIn 2021, the global mortality and disability-adjusted life years (DALYs) number of lung cancer burden attributable to ambient PM2.5 among women of childbearing age were approximately 5205 and 247,211, respectively. The rate of lung cancer attributable to ambient PM2.5 among women of childbearing age increased between 1990 and 2021, with the age-standardized mortality rate (ASMR) increasing from 0.22 (95% uncertainty interval [UI]; 0.13 to 0.33) to 0.25 (95% UI; 0.14 to 0.37; average annual percent change [AAPC] = 0.40) and the age-standardized DALYs rate (ASDR) increasing from 10.39 (95% UI; 5.96 to 15.72) to 12.06 (95% UI; 6.83 to 17.51; AAPC = 0.41). The middle sociodemographic index (SDI) region, East Asia, and China had the heaviest burden, while the high SDI region showed the highest decrease. ASMR and ASDR exhibited an inverted U-shaped relationship with the SDI.

conclusionsFrom 1990 to 2021, the lung cancer burden attributable to ambient PM2.5 among women of childbearing age exhibited an increasing trend. Furthermore, increasing attention should be paid to the middle SDI region, East Asia, and China, as ambient PM pollution remains a critical target for intervention.

Indexed as

Air PollutionGlobal Burden of DiseaseLung NeoplasmsParticulate MatterAdolescentAdultAir PollutantsDisability-Adjusted Life YearsEnvironmental ExposureFemaleGlobal HealthHumansMiddle AgedYoung AdultAir PollutantsParticulate Matterambient particulate matter air pollutionepidemiologyGlobal Burden of Disease 2021lung cancerwomen of childbearing age

Identifiers

PMID39315583
PMCPMC11420659

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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.