Evidence map›Paper›PMID 36361315›Full record

ArticleInternational journal of environmental research and public health2022

Prevalence of Musculoskeletal Disorders and Their Associated Risk Factors among Furniture Manufacturing Workers in Guangdong, China: A Cross-Sectional Study.

Yan Yang, Jiancheng Zeng, Yimin Liu, Zhongxu Wang, Ning Jia, Zhi Wang

Abstract read
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Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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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

6 authors.

Yan YangKey Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou 510620, China.
Jiancheng ZengKey Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou 510620, China.ORCID 0000-0002-2320-6357
Yimin LiuKey Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou 510620, China.
Zhongxu WangNational Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Ning JiaNational Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Zhi WangKey Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou 510620, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to investigate the one-year prevalence and the associated factors of work-related musculoskeletal disorders (WMSDs) among furniture manufacturing workers in Guangdong, China.

methodsA cross-sectional study of 4181 (2953 males and 1228 females) furniture manufacturing workers was conducted between September 2019 and December 2019. All information about WMSDs was collected by the electronic version of Chinese Musculoskeletal Questionnaires (CMQ). Descriptive statistics and a binary logistic regression model were used to interpret the data.

resultThe overall prevalence of WMSDs was 31.57%. The WMSD symptoms most commonly occurred in the neck (16.77%), followed by the shoulders (14.90%), ankles/feet (14.64%), hands/wrists (13.30%), upper back (11.48%), and lower back (10.95%). Multiple logistic regression analysis revealed that several individual, labor organization, and ergonomics-related factors conferred significant risks to WMSDs at different body sites.

conclusionsWMSDs remain the major occupational health problem for furniture manufacturing workers. Hence, some effective and feasible protective measures for furniture manufacturing workers are required in order to alleviate the health burden caused by WMSDs.

Indexed as

Musculoskeletal DiseasesOccupational DiseasesCross-Sectional StudiesFemaleHumansInterior Design and FurnishingsMalePrevalenceRisk FactorsSurveys and Questionnairesfurniture manufacturing workersmusculoskeletal disordersrisk factors

Identifiers

PMID36361315
PMCPMC9654235

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.