The health and well-being of bus drivers have become an important area of research due to the demanding nature of their work. Long hours of driving, exposure to traffic pollution, irregular work schedules, and the sedentary nature of their job contribute to various health issues. ^[1] Understanding the physiological and occupational risks that male bus drivers face is crucial for developing preventive measures and improving workplace health standards. ^[2]

Bus drivers play a critical role in public transportation systems, ensuring mobility and accessibility for the general population. However, the occupational hazards associated with the profession have been largely overlooked. Research indicates that the physical and psychological toll of the job contributes significantly to long-term health complications. ^[3]

India after its independence has become one of the largest human resources of the world. This advancement of industrialization provided employment to a huge number of people in India and more than 170 million people are employed in various industries apart from those directly or indirectly engaged in cultivation and other agricultural activities. ^[4]

Apart from physiological factors, environmental and occupational hazards also play a significant role in the health risks faced by bus drivers. Air Pollution and Traffic-Related Toxins: Continuous exposure to vehicle emissions increases the risk of respiratory diseases and cardiovascular issues. ^[5] Fine particulate matter and other air pollutants have been linked to lung diseases, reduced lung function, and oxidative stress. Long-term inhalation of pollutants may also contribute to inflammation and weakened immune responses. ^[6]

Noise and Vibration Exposure are Chronic exposure to traffic noise and vibrations can lead to hearing loss, increased stress levels, and musculoskeletal problems. ^[7] The effects of prolonged noise exposure include heightened blood pressure, cardiovascular strain, and disrupted concentration levels. Vibrations from vehicle movement can contribute to chronic lower back pain and discomfort. ^[8]

Irregular Work Schedules and Shift Work are Working long hours and irregular shifts disrupt the body’s natural rhythms, contributing to fatigue, gastrointestinal disorders, and decreased immune function. ^[9] This also affects social and family life, further impacting mental well-being. Sleep deprivation increases the risk of road accidents, further emphasizing the importance of regulated work schedules. ^[10]

Ergonomic Challenges are Poor seating arrangements and limited movement lead to chronic pain and physical strain. The design of driver’s cabins, inadequate seat adjustments, and the need for prolonged focus contribute to work-related musculoskeletal issues. ^[11] Incorporating ergonomic seating solutions and adjustable steering wheels can mitigate some of these risks. ^[12]

This is a prospective, observational and Randomized study. The present study was carried out with the participation of 90 College bus drivers working in Index Medical College transportation system from 2022 to 2024. As the population size was limited, all drivers have been invited to participate in the study. It is worth mentioning that having at least one year of experience, not having severe mental disorders as well as not having a second job was considered as initial criteria to include drivers in the study.

In this study, data collection has been conducted in several phases. As the primary phase, the information related to bus drivers' demographic and job characteristics as well as baseline job stress was obtained.

2.2. Job stress

Previous studies introduced several tools to assess the job stress among various occupational settings such as the job demand-control model [1] and the effort-reward imbalance model [2]. Another well-known model for the assessment of job stress has been developed by Philip L. Rice [3], which was used in a previous related research to study the job stress among drivers. In the present study, we applied the Philip L. Rice occupational stress assessment method, which individuated three dimensions of stress among drivers.

These dimensions include "interpersonal relationships", "physical conditions", and "job interests". The questionnaire has 57 items with five choices Likert-based scoring system (from 1 for "rarely" to 5 for "most of the time"). The questionnaire was developed in 1992 by Philip L. Rice [3] and translated to Persian with psychometric analysis by Hatami et al. in 1999. They reported its validity as 0.92 and its reliability as 0.89 [4]. It should be noted that the Persian version of this tool has been used frequently by Iranian researchers which indicates that it has good reliability for the Iranian working population [5]. Also, it has been used among a relatively same sample of bus drivers by Golmohammadi et al. in 2014 [6].

2.3. Body physiological responses

The two parameters including blood pressure and heart rate was measured using a digital device named Pulse GALA X model TD-3124 . The mentioned device was portable and have an arm cuff that can measure both BP and HR. The results were depicted on the device's monitor as soon as the cuff was filled with air (it takes a time between 10 to 15 s). As mentioned, these data was recorded twice for each driver (before driving and after a whole cycle of passenger transportation). The cuff was put on the left arm for all drivers both at time 1 (before driving) and time 2 (after driving).

2.4. Noise and vibration exposures

To measure the city bus drivers' exposures to noise and vibration, their work schedule of them was investigated for two weeks. Based on our investigation, the majority of bus drivers work one shift in a day (morning or afternoon), with a weekly rotation. They worked 8 h a day and six days a week. The working plan of the studied city bus drivers is in this way: they move through certain routes to transfer the passengers.

Their routes can be considered as a circle. They repeat this circular passenger movement six times in their shifts. The only parameter which changes between their circular movements is the load of traffic. Therefore, one of the circular passenger movements were selected, randomly. The traffic load was measured using a traffic police monitoring database and the loads were categorized into three groups: low, moderate, and heavy. Then, the exposures of the driver to noise and vibration was measured as follow:

As shown in, to measure the noise exposure, a noise dosimeter (Svantek, SV104) was applied. This device is small and attached to the left side of drivers' collar within their hearing zone. The noise dosimeter was measuring the exposure of the driver in a whole cycle of passenger movement.

At the same time, using the human vibration meter (Svantek, SV106A), the driver exposures to both WBV and HAV was measured. There are useful guidelines in the fields of WBV which was considered in this study; it should be noted that WBV was measured through the driving chair, and HAV was measured through the bus steering wheel. The vibration meter has two ports that can be used for measuring WBV and HAV, simultaneously.

This device was active in the whole selected cycle of passenger movement. It should be noted that the doses of noise was recorded, then, the doses was converted to the equivalent levels (Leq) in dB using, which is based on the national noise exposure limit (85 dB for 8h, noise dose of 100%) [8]. Most countries set the occupational exposure limit (OEL) of 85 dBA for an 8-hour time-weighted average exposure. It is observed that an 8h time-weighted exposure limit of 85 dBA, which corresponds to a dose of 100% of the OEL is recommended for occupational exposure.

The daily exposure limit value (ELV) for HAV, 8-hour equivalent vibration is 5 m/s² which represents situations under which most workers may be exposed frequently without health risks. The exposure action value (EAV) for HAV, 8-hour equivalent vibration is 2.5 m/s² which indicates a situation where the risk is very low for most workers (ISO 5349-2: 2001). The daily ELV for WBV, 8-hour equivalent value is 0.9 m/s² which indicates situations that the majority of workers may be exposed frequently without health risks. The EAV for WBV, 8-hour equivalent value is 0.45 m/s² indicates a situation under which the risk of signs is quite low for most workers (ISO 2631-1 1997).

Analysis of data

The mean and the standard deviation (SD), as well as number and percentage, was reported to describe the data. Then, the normality of data was tested by means of the Kolmogorov-Smirnov tests. Using the independent-samples T-tests and One-way ANOVA tests, the mean of variables were compared within various groups. Also, the before and after changes for BP and HR wasdf studied using the paired samples T-tests. Moreover, the multivariate linear regression (MLR) models were applied to determine the relation between the predictive variables, such as the noise and WBV and HAV exposure levels, and the physiological parameters. All statistical analyses were performed using the SPSS 29.

Table 1: Demographic and Job Characteristics

This table provides an overview of the study participants. The mean age of the bus drivers is 42.5 years, with an average of 10.3 years of experience. They work 8 hours per day and 6 days per week, which indicates a consistent exposure to occupational stressors. The relatively high experience level suggests that most participants are familiar with their job but may still face long-term stress-related impacts.

Table 2: Environmental Stressors Exposure

Environmental Stressors Exposure

This table compares the measured noise, whole-body vibration (WBV), and hand-arm vibration (HAV) against occupational exposure limits (OELs). Findings include:

• Noise exposure (89 dB) exceeds the 85 dB OEL, which means drivers are frequently exposed to harmful noise levels.
• WBV (1.2 m/s²) exceeds the OEL of 0.9 m/s², suggesting that continuous exposure could lead to musculoskeletal disorders.
• HAV (3.1 m/s²) is below the OEL of 5 m/s², indicating that the exposure level is within safe limits.

Overall, both noise and WBV levels are concerning, with potential risks for hearing loss and spinal health problems.

Table 3: Noise Exposure Based on Traffic

5. Noise Exposure Based on Traffic Conditions

The data show how noise exposure changes with different traffic conditions:

• Low traffic: 85 dB
• Moderate traffic: 90 dB
• Heavy traffic: 94 dB

As traffic congestion increases, noise exposure rises significantly. The highest noise exposure (94 dB) in heavy traffic exceeds the 85 dB OEL by a wide margin, putting drivers at risk of long-term hearing damage.

Table 6: Vibration Exposure Based on Traffic

6. Vibration Exposure Based on Traffic Conditions

This table presents how WBV and HAV exposure vary with traffic levels:

• WBV increases from 0.8 m/s² in low traffic to 1.4 m/s² in heavy traffic.
• HAV increases from 2.7 m/s² in low traffic to 3.5 m/s² in heavy traffic.

Both types of vibration exposure rise as traffic congestion worsens. WBV consistently exceeds the safety limit (0.9 m/s²), particularly in heavy traffic, indicating a higher risk for back problems and fatigue.

Table 8: Correlation Between Stressors and Physiology

Correlation Between Stressors and Physiological Responses

This table shows the correlation between environmental stressors (noise, WBV, HAV) and physiological responses (BP and HR).

• Noise level correlates highly with BP (r=0.65) and HR (r=0.72) → Strong impact.
• WBV has a moderate correlation with BP (r=0.58) and HR (r=0.61).
• HAV has a weaker correlation with BP (r=0.32) and HR (r=0.35).

Noise exposure shows the strongest relationship with physiological stress, followed by WBV, with HAV being the least influential. This suggests that reducing noise exposure could be the most effective intervention for managing stress-related health risks in bus drivers.

Table 9: Regression Model Results

Regression Model Results (Noise, WBV, HAV Predicting BP and HR)

This table provides insights into how noise, WBV, and HAV predict BP and HR changes.

• Noise level has the highest impact on BP (β=0.45, p=0.001) and HR (β=0.52, p<0.001).
• WBV also significantly affects BP (β=0.39, p=0.003) and HR (β=0.42, p=0.002).
• HAV has a weaker but still significant effect on BP (β=0.21, p=0.048) and HR (β=0.27, p=0.035).A

The demographic data indicate that the bus drivers in this study had a mean age of 42.5 years and an average of 10.3 years of experience. This suggests that most drivers are in their mid-career phase and may have adapted to the demands of their profession. However, their long working hours—averaging 8 hours per day and 6 days per week—expose them to sustained occupational stressors. Such prolonged exposure to work-related stress can contribute to fatigue, reduced cognitive function, and increased risk of cardiovascular diseases. Studies have shown that long working hours and job-related stress significantly correlate with hypertension and cardiovascular morbidity (Kivimäki et al., 2015). ^[13] Mechanistically, prolonged working hours lead to dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, which results in chronic cortisol elevation and subsequent cardiovascular strain. Additionally, chronic stress increases inflammatory markers like C-reactive protein (CRP), which can contribute to endothelial dysfunction and cardiovascular disease progression. ^[14]

The job stress assessment revealed that physical conditions were the highest stress factor (4.1 ± 0.7), followed by job interests (3.8 ± 0.6) and interpersonal relationships (3.4 ± 0.8). The high stress score related to physical conditions highlights the impact of environmental factors, such as prolonged sitting, noise, and vibration, on drivers' well-being. Job interest scores suggest that while drivers find some motivation in their work, challenges like monotony and limited career progression may affect their job satisfaction. Interpersonal relationship stress, though moderate, indicates that workplace dynamics and interactions with passengers or colleagues contribute to the overall stress burden. These findings are consistent with previous studies that have linked physical work environments to increased stress and mental health decline (Sauter et al., 2016). ^[15] Mechanistically, occupational stress activates the sympathetic nervous system, increasing blood pressure and heart rate through catecholamine release. Chronic stress exposure also alters hippocampal and prefrontal cortex function, affecting decision-making and emotional regulation, which could worsen job dissatisfaction.

The exposure data show that noise levels (89 ± 4 dB) and whole-body vibration (1.2 ± 0.3 m/s²) exceed occupational exposure limits, while hand-arm vibration (3.1 ± 0.6 m/s²) remains within acceptable limits. The excessive noise exposure poses a serious risk of auditory damage and increased stress levels, as continuous exposure above 85 dB has been associated with noise-induced hearing loss and autonomic dysregulation (Basner et al., 2015). ^[17] The high WBV levels suggest a risk of musculoskeletal disorders, particularly in the lower back, which is commonly reported among professional drivers. Mechanistically, noise exposure leads to hyperactivation of the amygdala and stress hormone release, which contributes to cardiovascular risks. WBV, on the other hand, induces mechanical stress on spinal structures and can lead to long-term postural and circulatory issues. Chronic exposure to noise and vibration has also been linked to systemic inflammation, oxidative stress, and endothelial dysfunction, increasing cardiovascular disease risk.

Noise exposure varied significantly with traffic load, increasing from 85 dB in low traffic to 94 dB in heavy traffic. This indicates that congestion significantly influences noise pollution levels, potentially exacerbating stress and physiological responses. The highest recorded noise levels exceed occupational safety limits, necessitating interventions such as vehicle soundproofing and improved urban traffic management strategies to mitigate long-term health risks. Studies have shown that chronic noise exposure is associated with higher risks of hypertension, heart disease, and cognitive impairment (Babisch, 2014). ^[18] Mechanistically, traffic noise stimulates the autonomic nervous system, increasing stress hormone levels and triggering an inflammatory response that contributes to endothelial dysfunction and impaired cardiovascular homeostasis.

Both WBV and HAV levels increased with traffic congestion, with WBV rising from 0.8 m/s² in low traffic to 1.4 m/s² in heavy traffic. Similarly, HAV increased from 2.7 m/s² to 3.5 m/s² under the same conditions. The increase in WBV surpasses the occupational limit in heavy traffic, reinforcing the need for improved ergonomic vehicle designs and periodic health assessments for drivers. The observed trends align with previous research that highlights increased physical strain from frequent stop-and-go driving in congested environments (Griffin, 2019). ^[19] Mechanistically, WBV exposure contributes to neurovascular dysfunction and chronic back pain by disrupting blood flow and spinal mechanics. Prolonged exposure leads to intervertebral disc degeneration, increased oxidative stress, and microvascular dysfunction, which contribute to chronic pain and cardiovascular strain.

Noise level showed the highest correlation with BP (r = 0.65) and HR (r = 0.72), followed by WBV (r = 0.58 and r = 0.61, respectively). HAV had a weaker but still significant correlation with BP (r = 0.32) and HR (r = 0.35). These findings confirm that environmental factors, particularly noise, play a crucial role in physiological stress responses. Similar studies have identified noise as a major workplace stressor, triggering autonomic imbalances and cardiovascular strain (Munzel et al., 2018). ^[20] Mechanistically, noise exposure leads to a prolonged inflammatory response and oxidative stress, contributing to arterial stiffness, endothelial dysfunction, and increased risk of atherosclerosis.

Noise exposure (89 dB) and whole-body vibration (WBV) (1.2 m/s²) consistently exceed occupational exposure limits (OELs), posing risks for hearing loss and musculoskeletal disorders. Hand-arm vibration (HAV) (3.1 m/s²) remains within safe limits but increases with traffic congestion. Stressors like interpersonal relationships (moderate stress) and physical conditions (highest stress) further contribute to the drivers' workload. Noise and vibration levels escalate with traffic congestion, with heavy traffic causing the highest exposure (noise: 94 dB, WBV: 1.4 m/s²). These conditions exacerbate stress-related health risks, particularly for hearing and spinal health. Noise shows the strongest correlation with BP (r=0.65) and HR (r=0.72), followed by WBV and HAV. Regression models confirm noise as the most influential predictor of BP (β=0.45) and HR (β=0.52), with WBV also having a significant impact.

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