Evidence map›Paper›PMID 38409004›Full record

ArticleBMC public health2024

The threaten of typhoons to the health of residents in inland areas: a study on the vulnerability of residents to death risk during typhoon "Lekima" : In Jinan, China.

Yiwen Ma, Xianhui Zhang, Yingjian Zhang, Jipei Du, Nan Chu, Jinli Wei, Liangliang Cui, Chengchao Zhou

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 27% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

8 authors at 2 institutions in 1 country.

Yiwen MaSchool of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen-hua-xi Road, Jinan, Shandong, 250012, China.
Xianhui ZhangJinan Municipal Center for Disease Control and Prevention, affiliated to Shandong University, 2 Weiliu Road, Huaiyin District, Jinan, 250021, China.
Yingjian ZhangJinan Municipal Center for Disease Control and Prevention, affiliated to Shandong University, 2 Weiliu Road, Huaiyin District, Jinan, 250021, China.
Jipei DuSchool of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen-hua-xi Road, Jinan, Shandong, 250012, China.
Nan ChuSchool of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen-hua-xi Road, Jinan, Shandong, 250012, China.
Jinli WeiSchool of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen-hua-xi Road, Jinan, Shandong, 250012, China.
Liangliang CuiJinan Municipal Center for Disease Control and Prevention, affiliated to Shandong University, 2 Weiliu Road, Huaiyin District, Jinan, 250021, China. cll602@163.com.
Chengchao ZhouSchool of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wen-hua-xi Road, Jinan, Shandong, 250012, China. zhouchengchao@sdu.edu.cn.
Shandong University · CNShandong Center for Disease Control and Prevention · CN

Funding

Cheeloo Youth Scholar Grant, Shandong University IFYT1810National Science Foundation of China 71774104National Science Foundation of China 72274109the China Medical Board 16-257the Science and Technology Innovation Development Plan of Jinan City (Clinical Medicine) 202134008
6 · The paper itself

Abstract

backgroundStudies had suggested increased risk of death of residents was associated with typhoons, particularly coastal regions. However, these findings ignored the impact of inland typhoons on the health of residents, especially the indirect death risk caused by typhoons. This study aimed to investigate the acute death risk of residents during inland typhoon Lekima in Jinan, further identify vulnerable populations and areas.

methodsWe selected the daily death from 11 to 27th August 2019 in Jinan as case period, and conducted a time-stratified case-crossover design to match the contemporaneous data from 2016 to 2018 as control period. We used the generalized linear Poisson models to estimate the related effects of death risk during typhoon Lekima and lag days.

resultsDuring the Lekima typhoon month, there were 3,366 deaths occurred in Jinan. Compared to unexposed periods, the acute death risk of non-accidental diseases (especially circulatory diseases), female and the older adults increased significantly in the second week after the typhoon. The maximum significant effect of circulatory disease deaths, female and older adult deaths were appeared on lag9, lag9, and lag13 respectively. And the typhoon-associated RR were 1.19 (95%CI:1.05,1.34), 1.28 (95%CI:1.08,1.52), and 1.22 (95%CI:1.06,1.42) respectively. The acute death risk of residents living in TQ and CQ increased significantly on Lag2 and Lag6 after the typhoon, respectively, while those living in LX, LC, HY, JY, and SH occurred from Lag 8 to Lag 13 after the typhoon. LC lasted the longest days.

conclusionsTyphoons would increase the vulnerability of residents living in Jinan which mainly occurred from the seventh day after the typhoon. Residents suffering from non-accidental diseases (circulatory diseases), female and the older adults were more vulnerable. The vulnerability of TQ and CQ occurred on Lag2 and Lag6 after typhoon Lekima, respectively, and the other areas except ZQ and PY occurred from Lag 8 to Lag 13. LC lasted the longest duration. Our findings emphasized the importance of the emergency response, which would help policymakers to identify vulnerable regions and populations accurately during typhoons and formulate the emergency response plan.

Indexed as

Cardiovascular DiseasesCyclonic StormsAgedChinaCross-Over StudiesFemaleHumansMaleInland typhoonMortalityTime-stratified case-crossoverVulnerability

Identifiers

PMID38409004
PMCPMC10895747
OpenAlexW4392159421

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.