Evidence map›Paper›PMID 31101032›Full record

ArticleBMC public health2019

An exploratory model for the non-fatal drowning risks in children in Guangdong, China.

Haofeng Xu, Xuhao Zhu, Zhishan Zhou, Yanjun Xu, Yongjian Zhu, Lifeng Lin, Jinying Huang, Ruilin Meng

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
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  9. Mapping Trends in Drowning Research: A Bibliometric Analysis 1995-2020.International journal of environmental research and public health · 2021
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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.

Haofeng XuGuangdong Provincial Center for Disease Control and Prevention, Institute of Control and Prevention for Chronic Non-infective Disease, Guangzhou, China.
Xuhao ZhuQingyuan City Center for Disease Control and Prevention, Qingyuan, 511515, China.
Zhishan ZhouQingxin District Center for Disease Control and Prevention, Qingyuan, 511000, China.
Yanjun XuGuangdong Provincial Center for Disease Control and Prevention, Institute of Control and Prevention for Chronic Non-infective Disease, Guangzhou, China.
Yongjian ZhuQingxin District Center for Disease Control and Prevention, Qingyuan, 511000, China.
Lifeng LinGuangdong Provincial Center for Disease Control and Prevention, Center Director's office, Guangzhou, China.
Jinying HuangQingyuan City Center for Disease Control and Prevention, Qingyuan, 511515, China.
Ruilin MengGuangdong Provincial Center for Disease Control and Prevention, Institute of Control and Prevention for Chronic Non-infective Disease, Guangzhou, China. rlmeng@126.com.ORCID http://orcid.org/0000-0001-7987-4269
Guangdong Provincial Center for Disease Control and Prevention · CNQingdao Municipal Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrowning is a leading cause of accidental death in children under 14 years of age in Guangdong, China. We developed a statistical model to classify the risk of drowning among children based on the risk factors.

methodsA multiple-stage cluster random sampling was employed to select the students in Grades 3 to 9 in two townships in Qingyuan, Guangdong. Questionnaire was a self-reported measure consisting of general information, knowledge, attitudes and activities. A univariate logistic regression model was used to preliminarily select the independent variables at a P value of 0.1 for multivariable model. Three-quarters of the participants were randomly selected as a training sample to establish the model, and the remaining were treated as a testing sample to validate the model.

resultsA total of 8390 children were included in this study, about 12.18% (1013) experienced drowning during the past one year. In the univariate logistic regression model, introvert personality, unclear distributions of water areas on the way to school, and bad relationships with their classmates and families were positively associated with drowning. However, females, older age and lower swimming skills were negatively associated with drowning. After employing the prediction model with these factors to estimate drowning risk of the students in the testing samples, the results of Hosmer-Lemeshow tests showed non-significant differences between the predictive results and actual risk (χ2 = 5.97, P = 0.65).

conclusionsMale, younger children, higher swimming skills, bad relationship with their classmates and families, introvert personality and unclear distributions of water areas on the way to school were important risk factors of non-fatal drowning among children. The prediction model based on these variables has an acceptable predictive ability.

Indexed as

Models, StatisticalAdolescentChildChild, PreschoolChinaCluster AnalysisDrowningFemaleHumansLogistic ModelsMaleMultivariate AnalysisRisk AssessmentRisk FactorsSchoolsSelf ReportChildrenDrowningLogistic regression modelPredictionRisk factors

Identifiers

PMID31101032
PMCPMC6525405
OpenAlexW2945431911

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.