Evidence map›Paper›PMID 40177093›Full record

ArticleFrontiers in public health2025

National estimates of mortality of unintentional drowning in China from 1990 to 2021 and its predicted level in the next decade: results from the global burden of disease study 2021.

Liuqing You, Jiangmei Liu, Jieming Zhong, Fangrong Fei

Abstract read
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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Liuqing YouZhejiang Center for Disease Control and Prevention (Zhejiang CDC), Hangzhou, China.
Jiangmei LiuNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jieming ZhongZhejiang Center for Disease Control and Prevention (Zhejiang CDC), Hangzhou, China.
Fangrong FeiZhejiang Center for Disease Control and Prevention (Zhejiang CDC), Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: It is reported that burden of unintentional drowning deaths is high in low- and middle-income countries. In recent decades, China has achieved remarkable economic growth and substantial advancements in infrastructure development; however, the understanding of the unintentional drowning burden in China has lagged behind. This article aims to provide an in-depth understanding of the current unintentional drowning situation in China. Methods: Unintentional drowning from GBD 2021 was estimated for cause-specific mortality and, age, sex, and temporal trends from 1990 to 2021. In addition, we used decomposition analysis to quantify the drivers of changes in unintentional drowning from 1990 to 2021 and we also predicted the mortality of unintentional drowning in the next 10 years based on APC model. Results: In 2021, the deaths attributable to unintentional drowning in China were 57554.02 (95% UI: 47463.15~69111.96), corresponding to age-standardized mortality rate (ASMR) of 4.12 (95% UI: 3.39 ~ 4.96) per 100,000 population. The mortality rate was relatively high among children aged 0-10 years and individuals aged 60 years and above and the highest number of deaths were recorded in the age groups of <5 years (3753.78, 95% UI: 2834.88 ~ 4903.46), 5-9 years (4938.93, 95% UI: 4207.74 ~ 5751.58), and 10-14 years (4197.10, 95% UI: 3581.12 ~ 4819.72). The mortality of unintentional drowning was higher for males than females across all age groups. A decline in unintentional drowning mortality rates was observed from 1990 to 2021, with an average annual percentage change (AAPC) of -4.19%. Epidemiological changes were the primary contributors to the observed decline in unintentional drowning deaths (decreased by 124985.81). The ASMR of unintentional drowning would continue to decrease slowly at the national level and that the decreasing trends would be stable in the future. Conclusion: From 1990 to 2021, the mortality rate of unintentional drowning in China showed a downward trend. Males, children under 10 years old, and older adult people aged 65 and above were identified as high-risk factors for drowning. The research findings emphasize the importance of continuing to strengthen data collection systems, identifying risk factors, and developing drowning prevention strategies tailored to China's national conditions.

Indexed as

DrowningAdolescentAdultAgedCause of DeathChildChild, PreschoolChinaFemaleGlobal Burden of DiseaseHumansInfantInfant, NewbornMaleMiddle AgedYoung Adultdeathsdecompositionglobal disease burdenpredictionunintentional drowning

Identifiers

PMID40177093
PMCPMC11961984

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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.