Body physiological responses of city bus drivers subjected to noise and vibration exposure in working environment

Investigating the Relationship Between Environmental and Cognitive Ergonomics with Work-Related Musculoskeletal Disorders: A Case Study in an Automobile Industry

BACKGROUND

Cognitive and environmental parameters are among the most important influencing factors in the prevalence of WRMSDs, which have been studied less compared to physical ergonomic in automobile industry.

OBJECTIVE

This study was conducted with the aim of investigating the relationship between environmental and cognitive ergonomics with the prevalence of WRMSDs in an automotive industry.

METHODS

This study was conducted in 2023 in an automobile company. The sample size was 740 workers. The prevalence of WRMSDs was assessed using the Cornell Musculoskeletal Discomfort Questionnaire. Occupational stress, mental workload, sleep quality, and cognitive failure were assessed by Job Content Questionnaire, NASA-TLX Questionnaire, Pittsburgh Sleep Quality Index, and Cognitive Failure Questionnaire, respectively. Noise were measured by KIMO-DB300 sound analyzer. The intensity of lighting was measured using a Hanger Screen Master illuminance meter. Heat stress was measured by Wet Bulb Globe Temperature (WBGT).

RESULTS

72.58% reported the musculoskeletal disorders in at least one of their body parts during the past 12 months. The average values of occupational stress, mental workload, sleep quality, and cognitive failure among workers with WRMSDs were higher than the participants without WRMSDs (p-value < 0.05). There was a significant difference between the values of all studied physical harmful factors between the two investigated groups, except thermal stress (p-value < 0.05).

CONCLUSION

Findings from this study highlight the critical need for a holistic approach that considers both the external work environment and internal cognitive processes to effectively prevent and manage WRMSDs among automobile industry workers.

The impact of environmental noise on drivers' cognitive abilities: A case study on in-vehicle voice interaction interfaces

To investigate the impact of environmental noise on the cognitive abilities of drivers, this study, using in-vehicle voice interaction as an example, conducted laboratory experiments to assess the effects of road traffic noise, entertainment noise, and white noise stimuli on drivers' attention and short-term memory. The noise levels simulated to mimic acoustic conditions during car driving ranged from 35 dB(A) to 65 dB(A). The conclusions drawn were as follows: (1) Noise levels directly influenced subjective annoyance levels, with annoyance linearly increasing as noise levels escalated; (2) Both attention and short-term memory task reaction times of drivers were significantly influenced by noise types. Compared to traffic noise and white noise, drivers' cognitive efficiency was lower under entertainment noise. (3) Performance in complex cognitive tasks was more susceptible to noise levels compared to simple cognitive tasks; (4) Experimentally, it was found that drivers exhibited the highest cognitive efficiency in cognitive tasks when the environmental noise level was 55 dB(A), as opposed to noise levels of 35 dB(A), 45 dB(A), and 65 dB(A).

Investigating the relationship between physical, cognitive, and environmental factors of ergonomics with the prevalence of musculoskeletal disorders: A case study in a car-parts manufacturing industry

BACKGROUND

Work-related musculoskeletal disorders (WRMSDs) is a multi-factorial disorder in most occupational setting and it has increased significantly in recent years.

OBJECTIVE

This study aimed to investigate the relationship between physical, cognitive, and environmental factors of ergonomics with the prevalence of WRMSDs in a car-parts manufacturing industry.

METHODS

This cross-sectional study was performed among 220 workers in a milling unit of a car parts manufacturing company in 2021-2022. The prevalence of WRMSDs was assessed using the Extended Version of the Nordic Musculoskeletal Questionnaire. Noise exposure was evaluated using dosimetry method. Mental and physical workload were evaluated by the NASA-TLX and key index methods (KIM-MHO and KIM-LHC), respectively. Data analysis was performed using SPSS version 25.0.

RESULTS

The subjects' mean age and work experience were 36.3±6.5 and 8.35±6.41 years, respectively. Eighty-five percent of the subjects reported WRMSDs in at least one area of the body. The results of mental workload assessment revealed a high workload mean range (73.23±14.89) in all of the subjects. Mean score of KIM-LHC and KIM-MHO were 738.18±336.42 and 201.86±36.41, respectively with odds ratio of 1.32 for KIM-LHC in creating the WRMSDs. There was a significant relationship between the noise exposure, mental and physical workload and the prevalence of WRMSDs (p-value <  0.05).

CONCLUSION

The results of the present study revealed that environmental, physical and cognitive factors can simultaneously be effective in the prevalence of WRMSDs. Therefore, performing effective control measures requires comprehensive attention to physical, environmental, and cognitive ergonomics in the algorithm of ergonomics management in the workplace.

A risk model for occupational noise-induced hearing loss in workers

BACKGROUND

Occupational hearing loss is one of the most common work-related diseases with various risk factors and considerable negative impacts on both physical and mental well-being of affected workers. Occupational noise-induced hearing loss (ONIHL) has a complex interaction with personal, environmental and occupational factors.

OBJECTIVE

This study aimed to develop a risk model for ONIHL in workers by identifying risk factors and their interactions.

METHODS

The subjects were 605 males in an industrial factory in Arak, Iran. The study took place between 2022 and 2023. The sociodemographic and occupational characteristics were collected by a health technician using questionnaires and medical records. Hearing status was assessed using audiometry by a qualified audiologist. Hearing loss was analyzed by univariate logistic analysis including age, smoking, medical history, type of occupation, and some workplace hazards. The risk model was generated by logistic regression.

RESULTS

Hearing loss in the participants was 44.13% (n = 267). In univariate logistic analysis, age (OR: 2.93,95% CI: 1.848-4.656), smoking (OR: 1.80, 95% CI: 1.224-2.655), work experience (OR: 1.06, 95% CI: 1.016-1.107), previous exposure to noise (OR: 1.60, 95% CI: 1.112-2.312) or vibration (OR: 1.68, 95% CI: 1.150-2.475) and type of occupation (OR: 2.126, 95% CI: 1.055-4.285) were associated with an increased risk of ONIHL (P < 0.05).

CONCLUSION

It was found that vibration exposure, work experience, previous noise exposure, type of occupation as well as age and smoking significantly affected the likelihood of developing ONIHL. This risk model could help management to prevent ONIHL and enhance application-oriented research on the condition.

Experimental Research on the Influence of Short-Term Noise Exposure on Miners’ Physiology

Coal mine noise affects human physiology, psychology, and behavior. It causes errors at work and increases accidents. In this study, we built a coal mine noise simulation experiment system. The system not only included an experimental environment simulation system and a physiological indicator test system, but it also added a miners’ working simulation system. This paper aimed to study the effect of different short-term (25 min) noise levels (60 dB, 70 dB, 80 dB, 90 dB, and 100 dB) on human physiology (skin conductivity and heart rate). Critical analysis showed that the stronger the noise intensity is, the shorter the contact time it takes for physiological indicators to present significant changes, and by setting different noises and measuring the skin conductivity and heart rate of human body, it was concluded that the noise level should be reduced to 90 dB to reduce accidents of miners.

Automated identification and assessment of environmental noise sources

Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points.

Investigating the effect of workplace noise exposure on cardiovascular disease risk factors in a power plant industry: A case-control study

BACKGROUND

Occupational noise exposure is a significant health problem. In addition to hearing impairments, noise as a stressor may cause cardiovascular problems.

OBJECTIVE

This study aimed to investigate the effect of exposure to workplace noise on cardiovascular disease risk factors.

METHODS

This case-control study was conducted in 2021 in a power plant in Iran. In this study, the health status of 406 employees in both exposed (n = 203) and non-exposed (n = 203) to noise groups was examined for cardiovascular disease risk factors. Also, the trend of changes in the studied variables from 2012 to 2020 in exposed employees was examined. Data were collected from participants' annual physical examinations and occupational noise exposure measurements. To measure the noise in the present study, the KIMO-DB300 noise level meter was used. Data were analyzed in SPSS-26 software.

RESULTS

The results revealed that mean fasting blood sugar (FBS), triglyceride, liver enzyme (SGOT), blood pressure, and body mass index were significantly different in the two groups (p-value<0.05). There was no significant difference in the mean of creatinine, cholesterol, and liver enzyme (SGPT) between the two groups (p-value>0.05). In the exposed group, the mean of all studied variables except diastolic blood pressure was statistically different during the study years (p-value<0.05).

CONCLUSION

This study demonstrates that exposure to noise above the permissible level can affect the cardiovascular disease risk factors, so it is recommended to apply engineering and management measures like using Hearing Conservation Programme (HCP) to reduce the risk of these diseases with periodically assessing the health status of employees and timely diagnosis.

The effect of selected rest break activities on reaction time, balance, and perceived discomfort after one hour of simulated occupational whole-body vibration exposure in healthy adults

MATERIALS & METHODS

Eleven healthy adults participated in four 1-hour sessions of ecologically valid WBV exposure followed by one of four 5-minute activities: sitting, walking, 2 min of gaze stabilization exercise (GSE) coupled with 3 min of trunk mobility exercise (GSE + MOBIL), or 2 min of GSE coupled with a 3-minute walk (GSE + WALK). Baseline and post-activity measurements (rating of perceived discomfort, balance and postural sway measurements, 5-minute psychomotor vigilance task test) were submitted to a paired t-test to determine the effect of WBV exposure and activities on physical, cognitive, and sensorimotor systems and to a repeated measures ANOVA to determine any differences across activities.

RESULTS

We observed degradation of the slowest 10% reaction speed outcomes between baseline and post-activity after walking (7.3%, p < 0.05) and sitting (8.6%, p < 0.05) but not after GSE + MOBIL or GSE + WALK activities. Slowest 10% reaction speed after GSE + MOBIL activity was faster than all other activities. The rating of perceived discomfort was higher after SIT and WALK activities. There were no notable differences in balance outcomes.

CONCLUSION

When compared to sitting for 5 min, an activity including GSE and an active component, such as walking or trunk mobility exercises, resulted in maintenance of reaction time after WBV exposure. If confirmed in occupational environments, GSE may provide a simple, rapid, effective, and inexpensive means to protect against decrements in reaction time after WBV exposure.