PMID- 36031257
OWN - NLM
STAT- MEDLINE
DCOM- 20220830
LR  - 20221120
IS  - 1879-1247 (Electronic)
IS  - 0022-4375 (Linking)
VI  - 82
DP  - 2022 Sep
TI  - Derived patterns of musculoskeletal symptoms and their relationships with 
      ergonomic factors among electronic assembly workers: A latent class analysis.
PG  - 293-300
LID - S0022-4375(22)00080-9 [pii]
LID - 10.1016/j.jsr.2022.06.004 [doi]
AB  - INTRODUCTION: Multi-site musculoskeletal symptoms (MSS) are considered to be more 
      common and have more serious consequences than single-site MSS. This study aimed 
      to determine whether derived patterns of MSS may be identified in electronic 
      assembly workers and if extracted MSS classes are associated with personal and 
      work-related factors. METHOD: A cross-sectional questionnaire study was performed 
      with 700 participating electronic assembly workers. The questionnaire included 
      individual factors, psychosocial and physical exposures, and MSS. The derived 
      patterns of MSS and their relationships with ergonomic factors were analyzed 
      using latent class analysis (LCA) and multinomial logistic regression models 
      (MLRM). RESULTS: The 1-year prevalence of MSS affecting only one body site or two 
      or more body sites was 14.9% and 32.7%, respectively. The results of LCA showed 
      three distinct classes of MSS patterns, which were labelled 'MSS in most sites' 
      (5.0%), 'MSS in neck and shoulder' (27.0%), and 'MSS in one or no site' (68.0%). 
      The results of MLRM showed that the 'MSS in neck and shoulder' was associated 
      with job tenure (OR 5.579, 95% CI 2.488-12.511), excessive dynamic and static 
      loads (OR 3.868, 95% CI 1.702-8.793 and OR 5.270, 95% CI 2.020-13.747, 
      respectively); while the 'MSS in most sites' was associated with high job demands 
      (OR 4.528, 95% CI 1.647-12.445) and excessive dynamic loads (OR 111.554, 95% CI 
      4.996-2490.793). CONCLUSIONS: The results showed unique patterns of MSS among 
      electronic assembly workers that were associated with personal and work-related 
      factors. PRACTICAL APPLICATIONS: The findings highlight that the high prevalence 
      of multi-site MSS in this group should be a focus. It also provides further 
      evidence that LCA considering the number and location of anatomical sites 
      involving MSS can be used to determine distinct classes of MSS patterns, which is 
      of great significance for the epidemiological study and management of MSS in the 
      future.
CI  - Copyright (c) 2022. Published by Elsevier Ltd.
FAU - Dong, Yidan
AU  - Dong Y
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China.
FAU - Jiang, Ping
AU  - Jiang P
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China.
FAU - Jin, Xu
AU  - Jin X
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China.
FAU - Maimaiti, Nazhakaiti
AU  - Maimaiti N
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China.
FAU - Wang, Shijuan
AU  - Wang S
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China.
FAU - Yang, Liyun
AU  - Yang L
AD  - Institute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, 
      Sweden; Division of Ergonomics, KTH Royal Institute of Technology, 14157 
      Huddinge, Sweden.
FAU - Forsman, Mikael
AU  - Forsman M
AD  - Institute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, 
      Sweden; Division of Ergonomics, KTH Royal Institute of Technology, 14157 
      Huddinge, Sweden.
FAU - He, Lihua
AU  - He L
AD  - Department of Occupational and Environmental Health, School of Public Health, 
      Peking University, Beijing 100191, China. Electronic address: alihe2009@126.com.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220618
PL  - United States
TA  - J Safety Res
JT  - Journal of safety research
JID - 1264241
SB  - IM
MH  - Cross-Sectional Studies
MH  - Electronics
MH  - Ergonomics
MH  - Humans
MH  - Latent Class Analysis
MH  - *Musculoskeletal Diseases
MH  - *Occupational Diseases
MH  - Prevalence
MH  - Risk Factors
MH  - Surveys and Questionnaires
OTO - NOTNLM
OT  - Electronic assembly workers
OT  - Latent class analysis
OT  - Musculoskeletal symptoms
OT  - Pain patterns
OT  - Risk factors
COIS- Conflicts of Interest The authors declare no conflict of interest in this work.
EDAT- 2022/08/29 06:00
MHDA- 2022/08/31 06:00
CRDT- 2022/08/28 21:04
PHST- 2021/06/23 00:00 [received]
PHST- 2022/01/08 00:00 [revised]
PHST- 2022/06/07 00:00 [accepted]
PHST- 2022/08/28 21:04 [entrez]
PHST- 2022/08/29 06:00 [pubmed]
PHST- 2022/08/31 06:00 [medline]
AID - S0022-4375(22)00080-9 [pii]
AID - 10.1016/j.jsr.2022.06.004 [doi]
PST - ppublish
SO  - J Safety Res. 2022 Sep;82:293-300. doi: 10.1016/j.jsr.2022.06.004. Epub 2022 Jun 
      18.