Exploring Musculoskeletal Complaints in a Needle Manufacturing Industry: A Cross-Sectional Study.


Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
29 Jul 2024
Historique:
received: 17 06 2024
revised: 20 07 2024
accepted: 27 07 2024
medline: 31 8 2024
pubmed: 31 8 2024
entrez: 29 8 2024
Statut: epublish

Résumé

Musculoskeletal disorders (MSD) encompass a variety of conditions affecting muscles, joints, and nerves. In Portugal, MSDs are the most prevalent occupational health problem in companies. Based on the relevance of work-related MSD (WMSD), this study aims to assess the prevalence of MSD complaints in a needle manufacturing industry in Northern Portugal, following a cross-sectional approach. Thus, 526 workers from five departments (i.e., operator, tuning, maintenance, administration, and logistics) answered a sociodemographic questionnaire and the Nordic Musculoskeletal Questionnaire (NMQ). Within the last 12 months, females exhibited a higher frequency of complaints than males across all body parts except for ankles/feet. The body parts eliciting the most percentage of complaints for both genders include the lower back (54.2%), neck (42.2%), shoulders (39.0%), ankles/feet (38.2%), and wrists/hands (35.7%). No significant association was found between Body Mass Index (BMI) and body part complaints. Tuners reported the highest complaint rate, with occupations as substantial predictors of complaints in certain body parts. Likewise, complaints tend to increase with age. The findings advocate for ergonomic interventions that are gender-, age-, and job-sensitive.

Identifiants

pubmed: 39200607
pii: ijerph21080996
doi: 10.3390/ijerph21080996
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : FCT - Fundação para a Ciência e Tecnologia
ID : 2023.00456.BDANA

Auteurs

Paulo C Anacleto Filho (PC)

ALGORITMI Research Center/LASI, University of Minho, 4800-058 Guimarães, Portugal.

Ana Cristina Braga (AC)

ALGORITMI Research Center/LASI, University of Minho, 4800-058 Guimarães, Portugal.

Paula Carneiro (P)

ALGORITMI Research Center/LASI, University of Minho, 4800-058 Guimarães, Portugal.

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Classifications MeSH