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重型车辆驾驶员和办公室职员肌肉骨骼疾病的患病率:使用机器学习方法的比较分析

Prevalence of Musculoskeletal Disorders in Heavy Vehicle Drivers and Office Workers: A Comparative Analysis Using a Machine Learning Approach.

作者信息

Raza Mohammad, Bhushan Rajesh Kumar, Khan Abid Ali, Ali Abdulelah M, Khamaj Abdulrahman, Alam Mohammad Mukhtar

机构信息

Department of Mechanical Engineering, National Institute of Technology Manipur, Imphal 795004, India.

Department of Mechanical Engineering, Aligarh Muslim University, Aligarh 202001, India.

出版信息

Healthcare (Basel). 2024 Dec 19;12(24):2560. doi: 10.3390/healthcare12242560.

DOI:10.3390/healthcare12242560
PMID:39765986
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11675938/
Abstract

: Job profiles such as heavy vehicle drivers and transportation office workers that involve prolonged static and inappropriate postures and forceful exertions often impact an individual's health, leading to various disorders, most commonly musculoskeletal disorders (MSDs). In the present study, various individual risk factors, such as age, weight, height, BMI, sleep patterns, work experience, smoking status, and alcohol intake, were undertaken to see their influence on MSDs. The modified version of the Nordic Questionnaire was administered in the present cross-sectional study to collect data from 48 heavy vehicle drivers and 40 transportation office workers. : The analysis revealed low back pain (LBP), knee pain (KP), and neck pain (NP) to be the dominant pains suffered by the participants from both occupational groups. LBP, KP, and NP were suffered by 56%, 43.75%, and 39% heavy vehicle drivers and 47.5%, 40%, and 27.5% transport office workers, respectively. From the insignificant value of Chi-square, it can be inferred that the participants from both occupations experience similar levels of LBP, KP, and NP. The Bayesian model applied to the total sample showed that NP influenced KP, which further influenced the LBP of the workers. Age was predicted as LBP's most significant risk factor by the logistic regression model when applied to the total sample, while NP was found to decrease with an increase in per unit sleep. The overall results concluded that heavy vehicle drivers and office workers, irrespective of their different job profiles, endured pain similarly.

摘要

诸如重型车辆司机和运输办公室工作人员等职业,涉及长时间保持静态和不适当的姿势以及用力过度,常常会影响个人健康,导致各种疾病,最常见的是肌肉骨骼疾病(MSD)。在本研究中,研究了各种个体风险因素,如年龄、体重、身高、体重指数、睡眠模式、工作经验、吸烟状况和酒精摄入量,以观察它们对肌肉骨骼疾病的影响。在本横断面研究中,使用了北欧问卷的修改版,从48名重型车辆司机和40名运输办公室工作人员那里收集数据。分析显示,下背痛(LBP)、膝盖痛(KP)和颈部疼痛(NP)是这两个职业群体参与者所遭受的主要疼痛。重型车辆司机中分别有56%、43.75%和39%患有LBP、KP和NP,运输办公室工作人员中分别有47.5%、40%和27.5%患有这些疼痛。从卡方检验的无显著值可以推断,两个职业的参与者经历的LBP、KP和NP水平相似。应用于总样本的贝叶斯模型表明,NP影响KP,进而影响工人的LBP。当逻辑回归模型应用于总样本时,年龄被预测为LBP最显著的风险因素,而发现NP随着每单位睡眠时间的增加而减少。总体结果得出结论,重型车辆司机和办公室工作人员,无论他们的工作类型如何,遭受疼痛的情况相似。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b114/11675938/47853527ecb9/healthcare-12-02560-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b114/11675938/0b50d6a20632/healthcare-12-02560-g001.jpg
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