Evidence map›Paper›PMID 26230266›Full record

ArticlePloS one2015

Associations of Individual-Related and Job-Related Risk Factors with Nonfatal Occupational Injury in the Coal Workers of Shanxi Province: A Cross-Sectional Study.

Yan Cui, Shuang-Shuang Tian, Nan Qiao, Cong Wang, Tong Wang, Jian-Jun Huang, Chen-Ming Sun, Jie Liang, Xiao-Meng Liu

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In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
–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

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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  5. Article
  6. Which Shiftwork Pattern Is the Strongest Predictor for Poor Sleep Quality in Nurses?International journal of environmental research and public health · 2022
    Article
  7. Review
  8. Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China.International journal of environmental research and public health · 2020
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  12. Observational
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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

9 authors.

Yan CuiDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Shuang-Shuang TianDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China; Department of Health Statistics, Taiyuan Xinghualing District Food & Drug Administration, Taiyuan, China.
Nan QiaoDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Cong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Tong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China; Center for Postgraduate Education Innovation of Shanxi Province, Taiyuan, China.
Jian-Jun HuangDepartment of Neurosurgery, General Hospital of Datong Coal Mining Group, Taiyuan, China; Center for Postgraduate Education Innovation of Shanxi Province, Taiyuan, China.
Chen-Ming SunDepartment of Urology, General Hospital of Datong Coal Mining Group, Taiyuan, China.
Jie LiangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Xiao-Meng LiuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the relationships between the risk factors and the incidence of nonfatal occupational injury of coal mine workers of Shanxi Province.

methodsA cross-sectional study was conducted from July 2013 to December 2013, and 4319 workers were recruited from more than 200,000 coal mine employees who are exposed to continuous potential risk of occupational injuries by using a two-stage stratified cluster sampling method. Trained interviewers having necessary medical knowledge conducted face-to-face interviews with the participants. Univariate and multivariable logistic regression models were used to estimate the odds ratio (OR) and the 95% confidence interval (CI).

resultsA total number of 3618 effective respondents were got from 4319 participants (83.77%) and the mean age of the participants was 41.5 years with the standard deviation of 8.65. Significant crude odds ratios were observed for all factors considered except for marital status, education, work duration, BMI, EPQ-RSC(P) scale and EPQ-RSC(L) scale. Results from multivariable logistic regression model showed significant adjusted odds ratios for risk factors including gender (female vs male 0.275, 0.094-0.800), age (≥55 vs ≤25yr 0.169, 0.032-0.900), work type (light physical labor vs heavy physical labor 0.504, 0.328-0.774), workplace (underground auxiliary vs underground front-line 0.595, 0.385-0.919), length of shiftwork experience (0~5yr vs no shift 2.075, 1.287-3.344 and ≥15yr vs no shift 2.076, 1.230-3.504) and EPQ-RSC(E) score (extraversion vs introversion 0.538, 0.334-0.867).

conclusionsSeveral risk factors of nonfatal occupational injury were identified including male, age, heavy physical labor, underground front-line, length of shiftwork experience and introversion. The coal mining enterprises should pay attention to controlling the hazards associated with frontline physical work. Workers' behaviors, life styles and personality traits should also be considered, so that the enterprises could set achievable targets for workers and lessen the exposed period to the risky underground workstation.

Indexed as

CoalAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedOccupational InjuriesRisk FactorsCoal

Identifiers

PMID26230266
PMCPMC4521807

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LicenceCC BY
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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.