Evidence map›Paper›PMID 36935708›Full record

ArticleFrontiers in public health2023

The risk of injuries during work and its association with precipitation: New insight from a sentinel-based surveillance and a case-crossover design.

Tian Tian, Xiao Lin, Tingyuan Huang, Kai Zhang, Congxing Shi, Pengyu Wang, Shimin Chen, Tong Guo, Zhiqiang Li, Pengzhe Qin and 3 more

Open access · goldFull text read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

13 authors at 3 institutions in 2 countries.

Tian TianGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Xiao LinGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Tingyuan HuangGuangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Kai ZhangDepartment of Environmental Health Sciences, University at Albany, The State University of New York, Rensselaer, NY, United States.
Congxing ShiGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Pengyu WangGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Shimin ChenGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Tong GuoGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Zhiqiang LiGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Pengzhe QinGuangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Boheng LiangGuangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Wangjian ZhangGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Yuantao HaoGuangdong Key Laboratory of Medicine, Department of Medical Statistics, Center for Health Information Research, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Sun Yat-sen University · CNGuangzhou Center for Disease Control and Prevention · CNUniversity at Albany, State University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Injuries during work are often exogenous and can be easily influenced by environmental factors, especially weather conditions. Precipitation, a crucial weather factor, has been linked to unintentional injuries, yet evidence of its effect on work-related injuries is limited. Therefore, we aimed to clarify the impact of precipitation on injuries during work as well as its variation across numerous vulnerability features. Methods: Records on the work-related injury during 2016-2020 were obtained from four sentinel hospitals in Guangzhou, China, and were matched with the daily weather data during the same period. We applied a time-stratified case-crossover design followed by a conditional logistic regression to evaluate the association between precipitation and work-related injuries. Covariates included wind speed, sunlight, temperature, Results: Daily precipitation was a positive predictor of work-related injuries, with each 10 mm increase in precipitation being associated with an increase of 1.57% in the rate of injuries on the same day and 1.47-1.14% increase of injuries on subsequent 3 days. The results revealed that precipitation had a higher effect on work-related injuries in winter (4.92%; 95%CI: 1.77-8.17%). The elderly (2.07%; 95%CI: 0.64-3.51%), male (1.81%; 95%CI: 0.96-2.66%) workers or those with lower educational levels (2.58%; 95%CI: 1.59-3.54%) were more likely to suffer from injuries on rainy days. There was a higher risk for work-related injuries caused by falls (2.63%; 95%CI: 0.78-4.52%) or the use of glass products (1.75%; 95%CI: 0.49-3.02%) on rainy days. Conclusions: Precipitation was a prominent risk factor for work-related injury, and its adverse effect might endure for 3 days. Certain sub-groups of workers were more vulnerable to injuries in the rain.

Indexed as

Occupational InjuriesAgedCross-Over StudiesHumansMaleSeasonsTemperatureWeathercase-crossoverprecipitationsentinel-surveillancesusceptibilitywork-related injury

Identifiers

PMID36935708
PMCPMC10018157
OpenAlexW4322773745

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read33
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.