Risk factors and prevalence of work-related musculoskeletal disorders in metropolitan bus drivers: An assessment of whole body and hand-arm transmitted vibration

Abstract

BACKGROUND:

Metropolitan bus drivers have higher prevalence of work-related musculoskeletal disorders (WMSDs) due to their nature of work and working environment.

OBJECTIVE:

To identify the prevalence of WMSDs and associated risk factors and to conduct real-time testing to evaluate Whole Body Vibration (WBV) and Hand-Arm Vibration (HAV) in buses based on the ISO standards to assess the vibrations levels at different speeds.

METHODS:

Participants in this study were 370 full-time male bus drivers from the north and south zones of 13 depots of Bengaluru Metropolitan Transport Corporation (BMTC), Bengaluru, south India. Information regarding WMSDs symptoms during the previous 7 days and 12 months were collected by Modified Nordic Musculoskeletal Questionnaire (MNMQ). WBV and HAV testing was performed and vibration levels were compared with ISO-2631-1 (1997) and ISO-5349-1-2001 standards. It was found that 68.7% of participants reported WMSDs.

RESULTS:

Several individuals and work-related factors were found to be statistically significant with WMSDs. From the Gini impurity measure, vibration and road types (Asphalt pavement and Rough road) were considered as vital risk factors associated with WMSDs.

CONCLUSION:

From the WBV and HAV evaluations, it was found that for buses on asphalt pavement at > 60 km/h, the vibration level was higher compared to a lower speed. The vibration level exceeded the Exposure Action Value (EAV) on rough roads at all speeds (20km/h, 40km/h and 60km/h) and in several situations considered based on assumptions the vibration level exceeded the Exposure Limiting Value (ELV).

Keywords

WMSDs Bus drivers whole body vibration hand-arm vibration

1 Introduction

The metropolitan cities of India are featured by a high density of vehicles in poorly managed traffic and congested roads. Drivers involved in long-duration driving usually have higher prevalence of WMSDs (Work-related Musculoskeletal Disorders), predominantly low back pain [1 –3]. Drivers are at high risk of developing WMSDs due to prolonged sitting, increased vibration and the long duration of driving [4]. Since drivers are exposed to road and vehicle-induced vibrations and stressful conditions/situations on a daily basis, the driving job was considered as an unhealthy and stressful occupation [5, 6]. Vulnerability to work related stress among professional drivers is due to personality traits and organizational interventions [7]. Drivers are vulnerable to WMSDs due to muscle strain and degenerative changes in the organs of the body [8]. Vehicle condition, road condition, traffic management, individual factors, and other environmental factors influence the prevalence of WMSDs among drivers [9]. The major consequences of WMSDs are lower productivity, early retirement, and absenteeism [10]. Vibrations through vehicle interfaces like seats, driver floors, steering wheel and in-vehicle controls like the clutch, brake, accelerator pedal and gear lever are felt by the drivers. Vibration is also a vital factor in the development of WMSDs [11, 12]. Accelerating, decelerating, maneuvering and steering of a bus in traffic induces vibration and transferred to the driver’s upper and lower extremities. The transmitted vibration energy in the driver’s body will induce discomfort and fatigue, which may lead to WMSDs and impairment of the nervous system [13]. The city bus drivers are exposed to impulsive shocks and continuous vibration daily [14]. Ergonomic considerations in vehicle design can directly influence the chances of getting WMSDs in professional drivers [15]. Due to prolonged sitting, lower back pain is common among bus drivers followed by WMSDs in the lower extremities, wrist and arm regions [16]. Body mass index, age, long driving durations and shift timings are also major contributors to WMSDs [17, 18]. The expensive treatments for WMSDs in multispecialty hospitals are burden to drivers [19]. Public service projects like road construction, metro rail work, sanitary and drinking water, cooking gas pipeline works, laying of optical fiber cable (OFC) and underground electrical cables are also reasons for bad road conditions in the bus routes of metropolitan cities. These projects will certainly alter the surface of the road which leads to road-induced vibration to city buses. Studies have been done on the influence of road types, suspension types, and condition of pavement on whole body vibration [20]. In Bengaluru Metropolitan Transport Corporation (BMTC), only the premium segment city buses have foam cushion seats; the rest of the bus has seats knitted with nylon tubes. Several studies have shown that there is no seat variety that will suit all conditions [21]. Increased pressure in tires is also a major contributor of WBV among drivers. In heavy traffic and on congested roads, driving speed usually varies from 20–60 km/h. At lower speeds, engine vibration is the dominating factor along with the resonances of the other subsystems of the bus.

Previous research indicates the association between WMSDs and whole body vibration [22]. Some real-time studies have reported a positive correlation between the prevalence of WMSDs and WBV, considering the vibration exposure time, floor types (high floor and low floor buses), different seats, tire pressure, body mass index of the driver, and other relevant factors. The vehicles considered in the previous studies were fully designed, built and tested for Noise, Vibration and Harshness performances (NVH) by a single organization/company. In the present study, buses body were built by BMTC as per Centre Motor Vehicle (CMV) rules, India and chassis were procured from the leading manufactures. Besides the water leakage test, no other tests were done after assembling the body over the chassis. An attempt has been made to identify the vibration exposure level considering different road types in the public transport buses.

The purpose of this study was to determine the risk factors contributing to the prevalence of WMSDs and to identify the possible risks of whole body vibration and hand arm vibration on drivers’ health. The outcomes of the present study will be helpful for BMTC to evaluate vibration exposure level in buses after assembling with the procured chassis. For the maintenance personnel, the measured vibration level will be an indicator to inspect and replace the worn out parts, bushes and isolators in the body and chassis components (suspension, brakes, steering,bolting attachments between the chassis, engine and body).

1 Materials and methods

1.1 Selection of sample size

Currently, BMTC has 16,200 drivers, 4,982 drivers-cum-conductors and 5,175 conductors. Drivers-cum-conductors means the personnel driving the bus whenever and wherever required and takes care of the collection of fares from passengers. The questionnaire survey was conducted in the north and south zones of BMTC which consists of 5,058 full-time drivers aged between 24–55 years. 5,058 drivers are considered as the population size (N) for which sample size is 370.4 (n). The sample size was calculated using Yamane’s formula [23]: $n = N / [1 + N [e]^{\land} 2]$ Where, n is the sample size, N is the population size, and e is the sampling error (0.05).

1.2 Participants

Participants selected for this study were full-time male bus drivers from BMTC. These drivers perform 9-10 hours of driving daily with six days on and one day off. Premium segment city bus drivers, drivers with chronic diseases (asthma, diabetes, arthritis and blood pressure) and traumatic injuries in their musculoskeletal systems, drivers who were undergoing treatment for several diseases (piles and skin allergy) at the time of the study, and drivers who are older than 55 years were excluded from the study.

1.3 Ethical consideration

Authors got approval from BMTC to conduct the study. Through Head of Human Resource, BMTC drivers were requested to participate in the study. The purpose of the study was explained in detail to all participants and participation in this study was entirely voluntary and anonymous. The questionnaire was checked and approved (approval no. BMTC: CO: HRD: 1025) by the Chief Engineer, Head of Human Resource, Depot Managers and Divisional Controller (DC) of BMTC, Bengaluru.

1.4 Pilot survey

In a pilot study, 15% of the study sample were individually interviewed during their free time using the questionnaire. These participants were also included in the main study. The authors also travelled with the drivers in many routes to identify the risk factors faced by the drivers in traffic. Based on the feedback by the drivers and the field study, the questionnaire was modified, and the study was then conducted.

2 Data collection

2.1 Work and workplace characteristics

BMTC was formed as an independent corporation with effect from 15 August 1997 after bifurcation from Karnataka State Road Transport Corporation (KSRTC). In BMTC, there are 45 depots, 12 central workshops and one fully equipped training center. As of 31 March 2020, BMTC caters to the transport services in the city and sub-urban areas of Bengaluru in a radius of about 40.4 km. The area was expanded to 3,527 km² to 5,130 km² in view of the greater Bengaluru. 4.4 million passengers utilize BMTC services daily. BMTC operates 2,253 routes covering 55,469.5 km, with an average route length of 24.6 km.

Drivers were assigned to prescribed routes and a bus every day. Drivers’ duties may change weekly or monthly and sometimes daily based on the requirement and availability of buses. Drivers were assigned to achieve the target of 203 km in a day. Due to heavy traffic and weather conditions, drivers can cover around 180–190 km/day. Drivers of BMTC are entitled to 10 paid holidays annually and medical reimbursement as per corporation regulations. With a view to providing better medical facilities, BMTC has empanelled 17 well-equipped hospitals recognized by the Government of Karnataka, wherein the drivers can avail the cashless inpatient facility for treatments. Drivers who were found medically unfit due to WMSDs, accidents, or willing to take voluntary retirements, are entitled to avail additional financial benefits from the corporation.

2.2 Data from questionnaire

During the study, the data were collected by face-to-face interviews with the help of questionnaires and direct observations. Questions were based on the Modified Nordic Musculoskeletal Questionnaire (MNMQ) [24, 25]. Drivers’ opinions, experience, and the incidents that they had experienced earlier were taken into consideration while studying the associated risk factors of driving. The questionnaire consisted of three sections (a). Socio-demographic information (b). Occupational/Behavior/Lifestyle Information (c). Medical/Health (history) information. The first section included information about age, height, weight, education, and marital status. The second section covered the information on shift timings, driving behavior, seat adaptability, ease of egress/ingress, involvement in traffic violence and rash driving, micro breaks,the body bends (Awkward postures while driving) and repetitive tasks, the reachability of in-vehicle controls, exposure to WBV, thermal comfort, stress at work, depending on outside food, smoking/tobacco consumption and drinking habits. The third section asked about the prevalence of WMSDs from the previous 7 days to 12 months. The first section of the questionnaire was comprised of multiple choice questions, the second section had ‘yes’ or ‘no’ type responses, and the third section had body charts to identify the body sites in which they feel discomfort.

2.3 Data from real-time testing

2.3.1 Testing equipment

Procedures for collecting the WBV and HAV measurements and the data acquisition system were followed by ISO-2631-1 (1997) and ISO-5349-2001-1 standards [26, 27]. Seat pad accelerometers (triaxial accelerometer) were placed on the driver’s seat cushion/seat pan [Sensitivity (mV/g) X-100.3, Y-101.3, Z-100.7] and on the back rest [Sensitivity (mV/g) X-100.40, Y-99.44, Z-99.05] (Fig. 1(a)). The seat pad accelerometers used in this study were PCB model-356B41. A triaxial accelerometer [Sensitivity (mV/g) X-103.0, Y-102.7, Z-104.1] of PCB model-T356A15 was mounted on the driver floor (Fig. 1(b)). On the steering wheel, two triaxial accelerometers [PCB model-T356A15] were mounted in the 12 o’clock position [Sensitivity (mV/g) X-102.8, Y-96.4, Z-102.8] and 3 o’clock position [Sensitivity (mV/g) X-101.4, Y-107.0, Z-107.0]. The range of all accelerometers used was ±50 g. Triaxial accelerometers were placed on the steering wheel as shown in Fig. 1(c). A data logger [Prosig model-P8020] which can be operated at temperatures between 0 to 40°C with supply voltage of 10–36 V DC (direct current) was used for vibration data acquisition. The other specifications of data logger are analog input (up to 40 channels plus tachometer), Expansion (flexible packaging options), Dimension (HXWXD –50 mm X 380 mm X 330 mm) and Split rate sampling (multiple sampling rates can run concurrently on separate cards). Before data acquisition, the equipments were calibrated as per the procedures mentioned in ISO-8041-2005 standards. The data logger had an internal global positioning system from which coordinates were used to confirm the start and end points of the road segments.

Fig. 1

Real time vibration testing attributes.

2.3.2 Test route

The test route selected for this study was a recently constructed asphalt pavement road with minimum irregularities. The rough road selected was located near the city outskirts because it was not possible to attain 60 km/h speed within the city limits of the rough road. The asphalt road was a common bus route in the city (Fig. 1(d)). Testing was conducted during non-peak hours in fewer traffic conditions. Buses were empty with no passengers inside when the vibration measurements were taken, leaving only the driver and data acquisition personnel (Fig. 1(e)).

2.3.3 Driver

A male bus driver with the character height of 1.71 meters, body mass of 72 kg, age of 42 years and driving experience of 8 years was selected for this study. The driver had no accidents history, had not undergone any surgery or treatment for the past 12 months. The same driver is considered for data acquisition in both buses (Fig. 1(f)).

2.3.4 Vehicle

The feedback from the Chief Engineer, Works Manager, Depot Managers and Mechanics of the depots were also considered and verified for bus selection to conduct real time testing. The two buses which were selected for testing were commonly available in all the states of India (Fig. 1(g)). The common specification of the bus is provided in Table 1.

Table 1
General specification of chassis of both buses considered for vibration analysis

Particulars Specification

Chassis platform LP/LPO 1512 BS IV Diesel

Engine Cummins B5.9 BS IV Common rail

Max power 130 HP at 2500 RPM

Torque 430 Nm at 1500 RPM

Gear box GBS 40 : 5 forward +1 reverse

Clutch 30 mm organic

Suspension Front: Semielliptical leaf spring

Rear: Air suspension

Tire size 10R 20-16PR

Steering Integral hydraulic power assisted steering

Brakes Dual circuit, Full air S-CAM brake system with ABS

Wheel base in mm 4225

Fuel capacity in liters 160

Front overhang in mm 1185

Rear overhang in mm 1970

Overall length in mm 7380

Turning circle diameter in mm 16800

Gross vehicle mass 16200 kg

Max width 2560 mm

Battery 2^12 V

Alternator capacity 75A

Battery capacity 150Ah

Firing order 1-5-3-6-2-4

No. of cylinders 6

Engine dry mass 420 kg

Chassis section Channel section

Empty weight of the vehicle 8100 kg

Body mass alone 3.5 ton

Aluminium 1 ton

Stainless steel 400 kg

Galvanized iron 2.5 ton

PU paste 20 kg

Paint 28 litre

Normal operating mass No. of seats^(68 kg + luggage mass (7 kg per seat))

46^*(68 + 7)

3450 kg

Total mass of bus under normal operating condition Normal operating mass + empty vehicle mass

3450 + 8100 = 11550 kg

Particulars	Specification
Chassis platform	LP/LPO 1512 BS IV Diesel
Engine	Cummins B5.9 BS IV Common rail
Max power	130 HP at 2500 RPM
Torque	430 Nm at 1500 RPM
Gear box	GBS 40 : 5 forward +1 reverse
Clutch	30 mm organic
Suspension	Front: Semielliptical leaf spring
	Rear: Air suspension
Tire size	10R 20-16PR
Steering	Integral hydraulic power assisted steering
Brakes	Dual circuit, Full air S-CAM brake system with ABS
Wheel base in mm	4225
Fuel capacity in liters	160
Front overhang in mm	1185
Rear overhang in mm	1970
Overall length in mm	7380
Turning circle diameter in mm	16800
Gross vehicle mass	16200 kg
Max width	2560 mm
Battery	2^*12 V
Alternator capacity	75A
Battery capacity	150Ah
Firing order	1-5-3-6-2-4
No. of cylinders	6
Engine dry mass	420 kg
Chassis section	Channel section
Empty weight of the vehicle	8100 kg
Body mass alone	3.5 ton
Aluminium	1 ton
Stainless steel	400 kg
Galvanized iron	2.5 ton
PU paste	20 kg
Paint	28 litre
Normal operating mass	No. of seats^*(68 kg + luggage mass (7 kg per seat))
	46^*(68 + 7)
	3450 kg
Total mass of bus under normal operating condition	Normal operating mass + empty vehicle mass
	3450 + 8100 = 11550 kg

2.3.5 Construction of body (CoB)

In BMTC, for buses the chassis are procured from leading manufacturers like Tata Motors, Ashok Leyland, Eicher, and Swaraj Mazda and their bodies were built by the BMTC in regional workshops under the supervision of the Component Process Department (CPD). The body construction process involves basic frame construction followed by painting, paneling, furnishing of interiors and electrical wiring and the construction process is shown in Fig. 1(h, i). In the final stage of assembly water leakage test and final inspections related to electrical wiring were carried out. The materials used for constructing buses by BMTC are provided in Table 2.

Table 2
Raw materials used for body building of bus in BMTC (Source: Regional workshop, BMTC)

Particulars Material Dimensions

Chassis vibration isolator Balata 12.75 mm

Floor and roof Galvanized iron 3.15 mm

Roof stick or bows Galvanized iron 1.6 mm

Packing material Asbestos 40 mm

Leak proof sheets Self-adhesive plastic 3 mm

Wheel arch Galvanized iron 3.15 mm

U-bolt Galvanized iron 114.5 mm (L), 35 mm (W) and 5.8 mm dia

D-part Cast iron as per standard bolt dimension

Wooden flooring Densified compressed plywood 12 mm

Flooring Poly vinyl sheet 3 mm

Interior Stainless steel 0.8 mm and 2-3 mm

All rectangular frames L^B^H Galvanized iron 45^40^2

Note: dimensions are in mm 60^40^2

55^40^2

50^40^2

40^40^2

40^20^2

25^25^2

Panels below side windows Stainless steel 0.76 meters

Panels below the backlit Aluminium 0.76 meters

Paint Red oxide and epoxy, PU paint 28 litres

Adhesives Polyurethane paste 20 kg

Windows Toughened glass Standard dimension as per Centre Motor Vehicle rule, India

Backlit and front wind shield Laminated glass

Weather strips EPDM rubber

Fasteners Soft and hard rivets

Welding TIG, MIG, arcwelding, ERW NA

Sealants PU seals

Particulars	Material	Dimensions
Chassis vibration isolator	Balata	12.75 mm
Floor and roof	Galvanized iron	3.15 mm
Roof stick or bows	Galvanized iron	1.6 mm
Packing material	Asbestos	40 mm
Leak proof sheets	Self-adhesive plastic	3 mm
Wheel arch	Galvanized iron	3.15 mm
U-bolt	Galvanized iron	114.5 mm (L), 35 mm (W) and 5.8 mm dia
D-part	Cast iron	as per standard bolt dimension
Wooden flooring	Densified compressed plywood	12 mm
Flooring	Poly vinyl sheet	3 mm
Interior	Stainless steel	0.8 mm and 2-3 mm
All rectangular frames L^B^H	Galvanized iron	45^40^2
Note: dimensions are in mm		60^40^2
		55^40^2
		50^40^2
		40^40^2
		40^20^2
		25^25^2
Panels below side windows	Stainless steel	0.76 meters
Panels below the backlit	Aluminium	0.76 meters
Paint	Red oxide and epoxy, PU paint	28 litres
Adhesives	Polyurethane paste	20 kg
Windows	Toughened glass	Standard dimension as per Centre Motor Vehicle rule, India
Backlit and front wind shield	Laminated glass
Weather strips	EPDM rubber
Fasteners	Soft and hard rivets
Welding	TIG, MIG, arcwelding, ERW	NA
Sealants	PU seals

2.3.6 Field measurement procedures

The real-time vibration tests were carried out in two buses (Bus A and B) of the same model and make. All the readings were recorded only after the bus attained the specified speed (20 km/h, 40 km/h, and 60 km/h). To ensure the reproducibility of the data, each test was repeated three times and averaged for the different speeds. All the instruments were calibrated before recording the data, and the data were recorded for 60 seconds for all tests.

2.4 Data analysis

The drivers’ responses were entered in the questionnaire form, and then coded for suitable analysis. Chi-square (χ2) test (with 95% confidence intervals) (using SPSS v. 23) was conducted to assess the relationship between independent and dependent variables. The independent variables considered in this study were socio-demographic, work-related factors and lifestyle/behaviors/occupational information, whereas reported musculoskeletal complaints were considered as a dependent variable.χ2 test results of p < 0.05 were considered statistically significant (Table 3). The data acquired from the field tests in the buses by testing equipment were processed in MATLAB and then compared with ISO and European standards. Prevalence (%) of WMSDs during the previous 12 months and 7 days were also identified. A decision tree model (classification tree) which uses Gini impurity metric was built using Python scikit-learning package. From decision tree model the risk factors identified by Chi-square test were evaluated to determine the factors associated with WMSDs to a greater extent.

Table 3
Association of socio-demographic, lifestyle/health and work-related factors and reported work-related musculoskeletal disorders (WMSDs) (n = 370)

Reported MSDs Statistics

Risk factors n (%) Yes (%) No (%) χ ² df p ^a

(n = 247) (n = 123)

Socio-demographic

Age (years)

24– 28 38 10.27 4.86 18 5.4 20 9.9 2 < 0.05 (7e– 3)

29– 39 187 50.54 32.97 122 17.56 65

≥40 145 39.18 28.91 107 10.27 38

Work-related

Seat adaptability issue

Yes 286 77.29 47.83 177 29.45 109 13 1 < 0.05 (– 2e-4)

No 84 22.7 18.91 70 3.78 14

Prolong sitting

Yes 270 72.97 42.16 156 31.08 115 39 1 < 0.05^(– 1e-5)

No 100 27.03 24.59 91 2.16 8

Frequent posture change*

Yes 276 74.59 43.51 161 31.08 115 35 1 < 0.05 (– 1e-5)

No 94 25.41 23.24 86 2.16 8

On duty breaks

Yes 189 51.08 47.83 177 29.46 109 13 1 < 0.05 (– 2e-4)

No 181 48.92 18.91 70 3.78 14

Egress/ingress

Yes 272 73.51 41.08 152 10 37 33 1 < 0.05 (– 1e-5)

No 98 26.48 25.67 95 23.24 86

Involvement in physical activity

Yes 122 32.97 0.54 2 32.43 120 348 1 < 0.05 (– 1e-5)

No 248 67.02 66.22 245 0.81 3

Posture training

Yes 177 47.83 27.83 103 20 74 11 1 < 0.05 (– 1e-5)

No 193 52.16 38.91 144 13.24 49

In-vehicle controls reachability

Yes 291 78.64 53.5 198 25.13 93 1 1 > 0.05 (8e– 4)

No 79 21.35 13.24 49 8.1 30

Dependency of outside food

Yes 323 87.29 62.16 230 25.13 93 23 1 < 0.05 (– 1e-5)

No 47 12.7 4.59 17 10.81 30

Exposed to vibration on duty

Low magnitude 69 18.64 2.43 9 16.21 60 110 1 < 0.05 (– 1e-5)

High magnitude 301 81.35 64.32 238 17.02 63

Stress at work

Yes 313 84.59 62.16 230 22.43 83 41 1 < 0.05 (– 1e-5)

No 57 15.4 4.59 17 10.81 40

Access to drinking water/restrooms on duty

Yes 104 28.11 8.65 32 19.46 72 84 1 < 0.05 (– 1e-5)

No 266 71.89 58.11 215 13.78 51

Work satisfaction (personally)

Yes 262 70.81 13.24 49 14.86 55 25 1 < 0.05 (– 1e-5)

No 108 29.19 53.51 198 18.38 68

Enough breaks at work

Yes 97 26.22 20.27 75 5.95 22 6.6 1 < 0.05 (0.01)

No 273 73.78 46.49 172 27.3 101

Thermal discomfort in cabin

Yes 213 57.57 50.27 186 7.3 27 96 1 < 0.05 (– 1e-5)

No 157 42.43 16.49 61 25.95 96

Shift timings

First 157 42.43 25.95 96 16.49 61 14 1 < 0.05 (9e-4)

Second 100 27.02 16.22 60 10.81 40

General 113 30.54 24.59 91 5.95 22

Cabin environment

Yes 242 65.41 57.57 213 7.84 29 142 1 < 0.05 (– 1e-5)

No 128 34.59 9.19 34 25.41 94

Body bending to access side mirrors

Yes 198 53.51 41.89 155 11.62 43 37 1 < 0.05 (– 1e-5)

No 172 46.49 22.16 82 24.32 90

Exposed to air pollution on duty

Yes 309 83.51 64.86 240 18.65 69 101 1 < 0.05 (– 1e-5)

No 61 16.49 1.89 7 14.59 54

Risky driving job

Yes 237 64.05 56.76 210 7.3 27 142 1 < 0.05 (– 1e-5)

No 133 35.95 10.00 37 25.95 96

Tendency towards rash driving

Yes 78 21.08 12.16 45 8.92 33 3.7 1 > 0.05 (0.055)

No 292 78.92 54.59 202 24.32 90

Involved in traffic violence

Yes 121 32.7 9.73 36 22.97 85 111 1 < 0.05 (– 1e-5)

No 249 67.3 57.03 211 10.27 38

Reacting to other road users

Yes 189 51.08 39.73 147 11.35 42 21 1 < 0.05 (– 1e-5)

No 181 48.92 27.03 100 21.89 81

Road condition in daily routes

Average/good 110 29.73 10 37 19.73 73 77 1 < 0.05 (– 1e-5)

Bad/worst 260 70.27 56.76 210 13.51 50

Shutting off ignition at signals

Yes 288 77.84 57.84 214 20 74 33 1 < 0.05 (– 1e-5)

No 92 24.86 8.92 33 13.24 49

Problem solved on time for the queries raised on bus condition on daily/weekly basis by maintenance department

Delayed 257 69.46 54.05 200 15.41 57 46 1 < 0.05 (– 1e-5)

Sometimes on time 113 30.54 12.7 47 17.84 66

Protrusion of manholes

In daily routes

Yes 101 27.3 8.65 32 18.65 69 77 1 < 0.05 (– 1e-5)

No 269 72.7 58.11 215 14.59 54

Sleeping in bus after duty

Yes 226 61.08 53.78 199 7.3 27 119 1 < 0.05 (– 1e-5)

No 144 38.92 12.97 48 25.95 96

Health-related

Body mass index

Under weight 22 5.94 5.4 20 0.54 2 8 3 < 0.05 (0.04)

Normal weight 300 81.08 51.89 192 29.18 108

Overweight 42 11.3 8.1 30 3.24 12

Obese 6 0.16 1.35 5 0.27 1

Current health status

Good 83 22.43 18.37 68 4.05 15 21 2 < 0.05 (– 1e-5)

Average 153 41.35 21.8 81 22.16 82

Bad/very bad 134 36.22 21.01 78 12.43 46

Tired at end of the work

Yes 233 62.97 56.76 210 6.22 23 155 1 < 0.05 (– 1e-5)

No 137 37.03 10 37 27.03 100

Lack of strength

Yes 230 62.16 41.8 155 9.46 35 24 1 < 0.05 (– 1e-5)

No 140 37.84 14.05 52 23.78 88

Surgical history

Yes 72 19.46 12.7 47 6.76 25 0.8 1 > 0.05 (0.076)

No 298 80.54 54.05 200 26.49 98

Muscle fatigue during working hours

Yes 276 74.59 63.78 236 10.81 40 172 1 < 0.05 (– 1e-5)

No 94 25.41 2.97 11 22.43 83

Health and safety training

Regularly 136 36.76 26.22 97 10.54 39 2 1 > 0.05 (0.15)

Sometimes 234 63.24 40.54 150 22.7 84

Self-medication for body pain

Yes 98 26.49 13.78 51 12.7 47 13 1 < 0.05 (– 1e-5)

No 272 73.51 52.97 196 20.54 76

	Reported MSDs	Statistics
Socio-demographic
Age (years)
24– 28	38	10.27	4.86	18	5.4	20	9.9	2	< 0.05 (7e– 3)
29– 39	187	50.54	32.97	122	17.56	65
≥40	145	39.18	28.91	107	10.27	38
Work-related
Seat adaptability issue
Yes	286	77.29	47.83	177	29.45	109	13	1	< 0.05 (– 2e-4)
No	84	22.7	18.91	70	3.78	14
Prolong sitting
Yes	270	72.97	42.16	156	31.08	115	39	1	< 0.05^*(– 1e-5)
No	100	27.03	24.59	91	2.16	8
Frequent posture change
Yes	276	74.59	43.51	161	31.08	115	35	1	< 0.05 (– 1e-5)
No	94	25.41	23.24	86	2.16	8
On duty breaks
Yes	189	51.08	47.83	177	29.46	109	13	1	< 0.05 (– 2e-4)
No	181	48.92	18.91	70	3.78	14
Egress/ingress
Yes	272	73.51	41.08	152	10	37	33	1	< 0.05 (– 1e-5)
No	98	26.48	25.67	95	23.24	86
Involvement in physical activity
Yes	122	32.97	0.54	2	32.43	120	348	1	< 0.05 (– 1e-5)
No	248	67.02	66.22	245	0.81	3
Posture training
Yes	177	47.83	27.83	103	20	74	11	1	< 0.05 (– 1e-5)
No	193	52.16	38.91	144	13.24	49
In-vehicle controls reachability
Yes	291	78.64	53.5	198	25.13	93	1	1	> 0.05 (8e– 4)
No	79	21.35	13.24	49	8.1	30
Dependency of outside food
Yes	323	87.29	62.16	230	25.13	93	23	1	< 0.05 (– 1e-5)
No	47	12.7	4.59	17	10.81	30
Exposed to vibration on duty
Low magnitude	69	18.64	2.43	9	16.21	60	110	1	< 0.05 (– 1e-5)
High magnitude	301	81.35	64.32	238	17.02	63
Stress at work
Yes	313	84.59	62.16	230	22.43	83	41	1	< 0.05 (– 1e-5)
No	57	15.4	4.59	17	10.81	40
Access to drinking water/restrooms on duty
Yes	104	28.11	8.65	32	19.46	72	84	1	< 0.05 (– 1e-5)
No	266	71.89	58.11	215	13.78	51
Work satisfaction (personally)
Yes	262	70.81	13.24	49	14.86	55	25	1	< 0.05 (– 1e-5)
No	108	29.19	53.51	198	18.38	68
Enough breaks at work
Yes	97	26.22	20.27	75	5.95	22	6.6	1	< 0.05 (0.01)
No	273	73.78	46.49	172	27.3	101
Thermal discomfort in cabin
Yes	213	57.57	50.27	186	7.3	27	96	1	< 0.05 (– 1e-5)
No	157	42.43	16.49	61	25.95	96
Shift timings
First	157	42.43	25.95	96	16.49	61	14	1	< 0.05 (9e-4)
Second	100	27.02	16.22	60	10.81	40
General	113	30.54	24.59	91	5.95	22
Cabin environment
Yes	242	65.41	57.57	213	7.84	29	142	1	< 0.05 (– 1e-5)
No	128	34.59	9.19	34	25.41	94
Body bending to access side mirrors
Yes	198	53.51	41.89	155	11.62	43	37	1	< 0.05 (– 1e-5)
No	172	46.49	22.16	82	24.32	90
Exposed to air pollution on duty
Yes	309	83.51	64.86	240	18.65	69	101	1	< 0.05 (– 1e-5)
No	61	16.49	1.89	7	14.59	54
Risky driving job
Yes	237	64.05	56.76	210	7.3	27	142	1	< 0.05 (– 1e-5)
No	133	35.95	10.00	37	25.95	96
Tendency towards rash driving
Yes	78	21.08	12.16	45	8.92	33	3.7	1	> 0.05 (0.055)
No	292	78.92	54.59	202	24.32	90
Involved in traffic violence
Yes	121	32.7	9.73	36	22.97	85	111	1	< 0.05 (– 1e-5)
No	249	67.3	57.03	211	10.27	38
Reacting to other road users
Yes	189	51.08	39.73	147	11.35	42	21	1	< 0.05 (– 1e-5)
No	181	48.92	27.03	100	21.89	81
Road condition in daily routes
Average/good	110	29.73	10	37	19.73	73	77	1	< 0.05 (– 1e-5)
Bad/worst	260	70.27	56.76	210	13.51	50
Shutting off ignition at signals
Yes	288	77.84	57.84	214	20	74	33	1	< 0.05 (– 1e-5)
No	92	24.86	8.92	33	13.24	49
Problem solved on time for the queries raised on bus condition on daily/weekly basis by maintenance department
Delayed	257	69.46	54.05	200	15.41	57	46	1	< 0.05 (– 1e-5)
Sometimes on time	113	30.54	12.7	47	17.84	66
Protrusion of manholes
In daily routes
Yes	101	27.3	8.65	32	18.65	69	77	1	< 0.05 (– 1e-5)
No	269	72.7	58.11	215	14.59	54
Sleeping in bus after duty
Yes	226	61.08	53.78	199	7.3	27	119	1	< 0.05 (– 1e-5)
No	144	38.92	12.97	48	25.95	96
Health-related
Body mass index
Under weight	22	5.94	5.4	20	0.54	2	8	3	< 0.05 (0.04)
Normal weight	300	81.08	51.89	192	29.18	108
Overweight	42	11.3	8.1	30	3.24	12
Obese	6	0.16	1.35	5	0.27	1
Current health status
Good	83	22.43	18.37	68	4.05	15	21	2	< 0.05 (– 1e-5)
Average	153	41.35	21.8	81	22.16	82
Bad/very bad	134	36.22	21.01	78	12.43	46
Tired at end of the work
Yes	233	62.97	56.76	210	6.22	23	155	1	< 0.05 (– 1e-5)
No	137	37.03	10	37	27.03	100
Lack of strength
Yes	230	62.16	41.8	155	9.46	35	24	1	< 0.05 (– 1e-5)
No	140	37.84	14.05	52	23.78	88
Surgical history
Yes	72	19.46	12.7	47	6.76	25	0.8	1	> 0.05 (0.076)
No	298	80.54	54.05	200	26.49	98
Muscle fatigue during working hours
Yes	276	74.59	63.78	236	10.81	40	172	1	< 0.05 (– 1e-5)
No	94	25.41	2.97	11	22.43	83
Health and safety training
Regularly	136	36.76	26.22	97	10.54	39	2	1	> 0.05 (0.15)
Sometimes	234	63.24	40.54	150	22.7	84
Self-medication for body pain
Yes	98	26.49	13.78	51	12.7	47	13	1	< 0.05 (– 1e-5)
No	272	73.51	52.97	196	20.54	76

n = number of samples, df = degrees of freedom, χ²= Chi-square value, p^a= Significant/non-significant values, ^*< 1e-5.

2.4.1 Evaluation of WBV and HAV

In order to evaluate the WBV and HAV which were influencing the prevalence of WMSDs among BMTC drivers, there is a need to consider several international standards such as ISO-2631-1-1997, ISO-5349-1-2001 and European directive 2002/44/CE to compare the measured vibration values [28, 29]. Other standards like EN 13059 (DIN, 2009), BS684 (BSI, 1987), OPSP 1093 (OPSI, 2005) were also available to evaluate the WBV exposure. The basic centric coordinate system used for HAV and WBV is shown in Fig. 2.

Fig. 2

Basic centric axis for HAV (Hand-arm vibration) and WBV (Whole body vibration) measurement (Source: ISO-2631-1-1997 and ISO-5349-1).

Considering the steering wheel as primary source of vibration, HAV was evaluated as per ISO 5349-1-2000 whereas WBV was evaluated based on ISO 2631-1-1997 by analyzing the vibration level at the driver seat pan, back rest and driver floor region. EAV and ELV are considered as standards to compare the WBV levels as shown in Fig. 3. The basic evaluation of vibration was carried out by the RMS (root-mean-square) acceleration. Acceleration values obtained from measured signals at different spectral content may have identical values, but their effect on the human body is different. In order to rectify these issues ISO-2631-1-1997 and ISO 5349-1-2000 adopt the idealized weighting curves to be used as filters in order to measure only the relevant part of the oscillatory movement of the body. The curves are frequency dependent and were used as a factor that attributes different weights to the movements depending on the frequency content as shown in Fig. 4. The measured acceleration is weighted resulting in a^w which is given by the Equation 1: $a_{w} = \sqrt{\frac{1}{T} \int_{0}^{T} a_{w} {(t)}^{2} dt}$ (1) Where, a_w(t): Frequency weighted acceleration with time history(t) in m/s²

Fig. 3

Daily acceleration exposure limits as function of the weighted RMS (roo-mean-square) acceleration to the whole body exposure. (Source:ISO-2631-1-1997).

Fig. 4

Weighting curves for whole body vibration (WBV) (Source: ISO-2631-1-1997).

2.4.2 Frequency Weightings (W)

Frequency weightings shall be determined in order to integrate the frequency weighted acceleration with time history. The manner in which the vibration affects the health and comfort is dependent on the vibration frequency content. For different axis of vibration, different frequency weightings were required. For health and comfort two principal frequency weightings were used, W_k for z-direction and W_d for x and y direction. It was recommended using k = 0.8 with frequency weightings for vibration measurement in the x-axis while evaluating the vibration in the seat back rest. The weightings were applied to a seated person with the multiplying factors as shown in the Table 4.

Table 4
Weighting curves and multiplication factors (Source: ISO-2631-1-1997)

Particulars Hand-arm vibration (steering wheel) Whole body vibration (driver floor and seat pan) Whole body vibration (seat back rest)

x y z x y z x y z

Weighting curve Health wh wh wh wd wd wk wd wd wk

Comfort wh wh wh wd wd wk wc wd wd

Multiplication factor Health 1 1 1 1.4 1.4 1 1.4 1.4 1

Comfort 1 1 1 1 1 1 0.8 0.5 0.4

Particulars	Hand-arm vibration (steering wheel)	Whole body vibration (driver floor and seat pan)	Whole body vibration (seat back rest)
Weighting curve	Health	wh	wh	wh	wd	wd	wk	wd	wd	wk
	Comfort	wh	wh	wh	wd	wd	wk	wc	wd	wd
Multiplication factor	Health	1	1	1	1.4	1.4	1	1.4	1.4	1
	Comfort	1	1	1	1	1	1	0.8	0.5	0.4

2.4.3 Total value of weighted RMS acceleration

For comfort analysis, it was required to calculate a_v which can be determined from vibrations in orthogonal coordinates and was calculated by the equation below: $a_{v} = \sqrt{k_{x}^{2} a_{wx}^{2} + k_{y}^{2} a_{wy}^{2} + k_{z}^{2} a_{wz}^{2}}$ (2) Where, a_v: Total value of weighted RMS acceleration.

2.5 Daily exposure calculation A(8)

Driving a bus in different road profiles within the city limits will induce different magnitude of vibrations to the drivers. Vibration measurement for 8 hrs is impractical and expensive and the preferred alternative was to measure the vibration exposure of a particular task for a particular time and then to sum the exposure time (8 hours).

A (8) was calculated for a particular task from a level of vibration and exposure time, as per the equation below:

$A (8) = a_{v} \sqrt{\frac{T}{T_{0}}}$ (3) Where, a_v:Total value of weighted RMS acceleration, T: Measurement of time in seconds, T_o: Fixed reference exposure time (8 hours).

In the present study to assess the WBV and HAV total value of weighted RMS acceleration (a_v) was considered.

City bus drivers were usually exposed to different vibration levels at different times from sources like the steering wheel, in-vehicle controls, floor and seat. Considering the sources individually, partial vibration exposure values were calculated. The overall daily vibration exposure can be calculated from partial vibration exposure values using the equation below: $A (8) = \sqrt{A_{1} {(8)}^{2} + A_{2} {(8)}^{2} + A_{3} {(8)}^{2} + A_{4} {(8)}^{2} + \dots}$ (4) Where, A₁(8), A₂(8), A₃(8) and A₄(8), are the partial vibration exposure values from the different vibration sources.

In order to decide whether the vibration levels measured were harmful to health, EAV and ELV standard limits were given in the ISO-2631-1-1997. Vibration levels below EAV were non-hazardous to health; for vibration levels above ELV, necessary actions should be taken in order to mitigate or eliminate the exposure. Daily acceleration exposure limits are shown in Table 5 as the function of frequency weighted RMS acceleration to the WBV exposure. Vibration levels mentioned in European standards (Directive 2002/44/EC, 2002) were used as a reference to limit the values and are shown in Table 6.

Table 5

Likely reactions to various magnitudes of overall vibration (Source: ISO-2631-1-1997)

Frequency weighted vibration magnitude	Likely reaction in public transport
< 0.35 m/s²	Not uncomfortable
0.315 m/s² – 0.63 m/s²	A little uncomfortable
0.5 m/s² – 1 m/s²	Fairly uncomfortable
0.8 m/s² – 1.6 m/s²	Uncomfortable
1.25 m/s² – 2.5 m/s²	Very uncomfortable
> 2 m/s²	Extremely uncomfortable

Table 6

Exposure action values (EAV) and exposure limit values (ELV)

Reference values in m/s²	EAV	ELV
HAV (Directive 2002/44/EC, 2002)	2.50	5.00
WBV (Approximated from ISO 2631-1-1997)	0.50	0.88

2.6 Comfort analysis

In comfort analysis, the same model of the bus was considered, and they were manufactured in the same year. Both bodies were built in the same regional workshop under the same Central Motor Vehicle (CMV) rules. The only difference between the buses was in terms of the engine run hours, which was 3,000 for Bus A and 7,000 for Bus B. Within these hours, Bus A and Bus B travelled 51,000 km and 109,000 km, respectively. Both buses belonged to same depot and were maintained by the same maintenance personnel. As per the economic survey of Karnataka, 19% of the buses in BMTC have crossed more than 1 million kms. The average life of a bus engine was up to 0.45 million kms, as specified by the manufacturers. After refurbishment, the engine can be used up to 0.8 million km. More than 4,000 buses in BMTC have operated for more than 0.6 million km.

Considering the correct multiplication factor and weighting curves from the equation-2, a_v was calculated for evaluating WBV and HAV in both idle and cruising conditions for all the orthogonal coordinates. Figure 5(a–e) represent the comfort analysis in asphalt pavement (left hand side) and rough road (right hand side) separately for Bus A and Bus B. The acceleration levels are presented as a function of speed ranges, with the x-axis is the speed developed by the bus and the y-axis being the total weighted vibration in m/s². The purpose of considering the idle (800 RPM and 1000 RPM) condition in the present study was to represent the vibration of the bus during frequent stops due to traffic jams, passengers onboarding and off-boarding at the bus stops. Analyzing the steering wheel and seat individually at different speeds, it was observed that the engine-induced vibration was the chief source of vibration followed by the road profile.

Fig. 5

a_w at different speeds.

2.7 Evaluation of A(8) based on assumptions

In order to measure the approximate value of A (8), three assumptions were made based on the daily possible routines of the city bus drivers in BMTC (Table 7).

Table 7
Assumptions of daily possible routines of drivers (values are in terms of hours)

20 km/h 40 km/h 60 km/h

Routine Bus A and B at parking bay Bus at idle (0 km/h) Asphalt pavement Rough road Asphalt pavement Rough road Asphalt pavement Rough road

Case 1 1 1.5 1 1 1.5 0.5 1 0.5

Case 2 1 1.5 1 1 0.5 1.5 0.5 1

Case 3 1 1 1 1 1 1 1 1

20 km/h	40 km/h	60 km/h
Case 1	1	1.5	1	1	1.5	0.5	1	0.5
Case 2	1	1.5	1	1	0.5	1.5	0.5	1
Case 3	1	1	1	1	1	1	1	1

Case 1: Bus A and B operate on asphalt pavement for longer duration (3.5 Hr) and the rest of the time, including resting and idle hours, they operate on rough roads. Idle hours represent the engine-on condition at traffic signals, passenger on and off-boarding at stops, and slow-moving situations in traffic. The resting hours represent the breaks taken by the drivers.

Case 2: Bus A and B operate on rough roads for longer duration (3.5 Hr) and for the rest of the time they operate on asphalt pavement, including resting and idle hours.

Case 3: Bus A and B were utilized equally on both asphalt pavement and on rough road conditions.

3 Results

3.1 General information

Data were collected on 370 male bus drivers: 10.3% were between 24–28 years of age, 50.5% were between 29–39 years of age, and 39.2% were ≥40 years of age. The mean (SD) height, body mass, and age of the participants was 1.70 (SD±0.3) meters, 69.4 (SD±7.7) kg and 40 years (SD±6.9 years), respectively. 42.4% of the drivers worked on the first shift, 27.0% worked in the second shift and 30.5% worked in the general shift. It was found that 22.4% of drivers maintained good health, and the rest had average health status with a history of WMSDs. 80.3% of drivers consumed tobacco/smoked and drank alcohol, and 32.9% of drivers were involved in outdoor sports activities during their free time.

More than half of the study participants reported that they feel muscle fatigue during driving and a lack of strength due to routine work. 77.8% of drivers had a habit of turning off the ignition at traffic signals and 66.1% of drivers reported that they sleep on the bus floors (passenger compartment) at the end of their duty due to unhygienic rest houses in the depots and their own houses that were located far away from the workplace. More than a fifth (21.1%) of drivers had a tendency towards rash driving in order to complete the scheduled trips and over half (57.5%) of drivers complained about the thermal discomfort in the cabin due to heat radiating from the engine, poor ventilation of the cabin, and general environmental conditions. In the current study, it was found that 72.9% of drivers sit for a prolonged period, 77.3% had seat adaptability (adjustments) issues, 70.8% were not satisfied with the job, 84.6% had stress due to tight work schedules and traffic congestion, and 87.3% were dependent on outside food. In addition, 71.9% reported not having proper access to restrooms and drinking water facilities while at work, 81.3% were exposed to vibration due to vehicle and road conditions, and 73.53% were reported egress/ingress issues on the buses.

3.2 Prevalence of WMSDs from previous 7 days

The body part discomfort (BPD) scale has been used to record the self-reported objective rating of pain feeling [30, 31]. Drivers having symptoms with ratings from 3–5 (1-Not uncomfortable, 2-Barely uncomfortable, 3-Quite uncomfortable, 4-Very uncomfortable, 5-Extremely uncomfortable) are considered as suffering from WMSDs. It was found that drivers had experienced symptoms during the previous 7 days in neck (11.0%), shoulder (21.1%), arm (8.7%), forearm (7.2%), upper back (13.6%), lower back (32.7%), hip/buttocks (19.6%), thighs (15.4%), knees (20.4%), fingers (10.0%), and ankle/foot (22.5%). It was also found that the fewest symptoms were experienced by participants in the hand/wrist (5.1%).

3.3 Prevalence of WMSDs from previous 12 months

During the 12 months prior to data collection, participants experienced symptoms in the neck (14%), shoulder (26.3%), arm (9.6%), forearm (14.6%), hand/wrist (8.6%), fingers (12.3%), upper back (24.4%), lower back (37.8%), hip/buttocks (16.9%), thighs (19.9%), knees (36.2%), and ankle/foot (18.2%).

Fig. 6

Decision tree model.

3.4 Gini Impurity decision tree classifier

From the Chi-square test, independent variables which show significant association with WMSDs were determined. To identify the independent variables which have a closer association with WMSDs, a common metric called Gini impurity is used to build the decision tree model [32, 33]. The decision tree model is shown in the Fig. 6. From Table 3, it is observed that the independent variables (except individual factors like age and Body Mass Index-BMI) which influences WMSDs have the response of ‘yes’ or ‘no’ from the participants. If the set of response for independent variables contains ‘yes’ or ‘no’,the minimum Gini impurity is 0 and the maximum impurity is 0.5 when half of the recipes are ‘yes’ and the other half is ‘no’. Likewise Gini impurity was evaluated for independent variables (input) which were significantly associated with WMSDs (target). Each independent variable considered as input will have certain gini impurity and the sum of those should be equal to 1. The independent variable which has gini impurity closer to 1 is considered as a major contributor to WMSDs in this study. Table 8 shows Gini impurity for independent variables (risk factors). For some of the independent variables (tired at the end of the work, self-medication for body pain, involved in traffic violence, reacting to other road users, on duty break and reacting to other road users) Gini impurity was 0 which was not shown in the table. Road types (0.289) and vibration (0.018) were considered as major contributors to WMSDs.

Table 8
Gini Impurity measures

Independent variables (risk factors) associated with WMSDs Gini

impurity

Road condition in daily route (Average/good = Asphalt pavement Bad/worst = Rough road) 0.289

Posture training 0.142

Prolong sitting 0.137

Frequent posture change 0.091

Involvement in physical activity 0.081

Feeling muscle fatigue at work 0.080

Risky driving job 0.064

Seat adaptability issue 0.040

Body bending to access side mirrors 0.029

Smoking/tobacco consumption 0.020

Exposed to vibration 0.018

Dependency on outside food 0.006

Sleeping in bus after duty 0.003

Total 1.00

Independent variables (risk factors) associated with WMSDs	Gini
Road condition in daily route (Average/good = Asphalt pavement Bad/worst = Rough road)	0.289
Posture training	0.142
Prolong sitting	0.137
Frequent posture change	0.091
Involvement in physical activity	0.081
Feeling muscle fatigue at work	0.080
Risky driving job	0.064
Seat adaptability issue	0.040
Body bending to access side mirrors	0.029
Smoking/tobacco consumption	0.020
Exposed to vibration	0.018
Dependency on outside food	0.006
Sleeping in bus after duty	0.003
Total	1.00

3.5 Comfort analysis on asphalt pavement

On the steering wheel at the 12 o’clock position, in bus A the vibration level was 0.43±0.03 m/s² at 60 km/h and in bus B it was 0.46±0.05 m/s² and 0.52±0.03 m/s² at 40 km/h and 60 km/h respectively. Comparatively, the highest mean vibration level in bus B was at 60 km/h. On the steering wheel at the 3 o’clock position at 40 km/h and 60 km/h in bus A 0.32±0.04 m/s² and 0.38±0.06 m/s² respectively, and in bus B the vibration level was 0.42±0.05 m/s² and 0.49 m/s² at 40 km/h and 60 km/h respectively.

On the driver floor in bus A the vibration level was 0.45±0.06 m/s² and 0.5±0.04 m/s² at 40 km/h and 60 km/h respectively. In bus B the vibration level on the driver floor was > 0.5 m/s² at all speeds > 20 km/h. At the seat pan seat pad accelerometer was mounted as per ISO 10326-1 : 1992 standard. The seat pan was made up of nylon tubes for the comfort of the driver. Nylon tubes have a certain damping effect and also by virtue of the human body has damping nature due to muscles and bones. In both buses, the vibration level was recorded < 0.5 m/s² at 20 km/h, 40 km/h and 60 km/h.

3.6 Comfort analysis on rough road

Vibration level of 2.5±0.06 m/s² and 3.0±0.08m/s² were observed at 40 km/h and 60 km/h respectively in bus A on the steering wheel at the 12 o’clock position. In bus B, the mean vibration level exceeded > 2.5 m/s² at all speeds > 20 km/h on the steering wheel at the 12 o’clock position. On the steering wheel at the 3 o’clock position,the vibration level was > 2.5 m/s² at 40 km/h and 60 km/h in both buses. As per the standards (Directive 2002/44/EC, 2002), a vibration level that exceeds EAV > 2.5 m/s² causes harm to the driver. At the driver floor, backrest and seat pan at all speeds > 20 km/h on rough roads in both buses, vibration level exceeded EAV.

3.7 A(8) based on assumptions

From Fig. 7(a, a1-b, b1) it was observed that in Bus A for case 2 and 3, A(8) exceeded the EAV for the backrest, seat pan, and driver floor locations. In case 1, A(8) exceeded EAV in the driver floor and seat pan locations. A(8) exceeded the ELV in the driver floor in case 2 and was within the EAV in the target positions on the steering wheel. In bus B, A(8) for the driver floor exceeded the ELV in all 3 cases. For the seat pan, A(8) exceeded the ELV in case 2 and 3. For the steering wheel at the 12 o’clock position, the A(8) magnitude was nearer to the EAV; for the rest of the conditions, it was within the EAV.

Fig. 7

Evaluation of A(8).

4 Discussion

Driving is a monotonous and risky job. WMSDs were common among professional drivers. In this study results from the questionnaire indicated that 68.7% of participants reported WMSDs. Similar studies also found that approximately 55.8% of Karnataka State Road Transport Corporation (KSRTC) drivers in Karnataka, India [34], 60.4% Malaysian bus drivers [35] and 44.0% US taxi drivers reported WMSDs [36]. Based on the Gini impurity measure, road type (0.289) and vibration (0.018) were considered as major contributors to WMSDs. The real-time vibration measurement was done considering road types (asphalt pavement and rough road) for specific speed (20km/h, 40km/h and 60km/h) of the buses. Comfort analysis and A [8] evaluation was conducted in order to compare the measured vibration with the ISO and European standards. A similar study was conducted considering vehicles of the same category and vibration measurements were done considering the road types and speed of the vehicle [20].

Public service projects like metro rail work, underground cable work, and drinking water and sewage pipeline works occur on a daily basis and affect the road surface. Damage to the road surface can induce a higher vibrations level (> 0.5 m/s²) to the buses and drivers. The asphalt on the poorly constructed pavement road get erode during the rainy season, creating potholes on the road surface. In 2018-2019, Bruhath Bengaluru Mahanagara Palike (BBMP) claimed that there were 31,000 potholes in the road pavement within the city limits. Protrusion of manholes is commonly found in the middle and on the sides of the roads, which induce shock pulses to drivers’ seats and steering wheel when the bus tires come in contact at high speeds.

About 60% of the participants were between the ages of 24 and 40 years. 35.4 % of participants in these age groups were willing to extend shifts for the additional financial benefits. A similar kind of study shows the positive outcomes on extending shifts by drivers for monetary benefits [37]. Extending shifts also contributes to sleep debt among bus drivers. Sleep debt in drivers influences cardiovascular diseases, fatigue, reduce task performance, capacity and increases drowsiness during duty [38, 39]. Drivers need 7-8 hours of sleep every day to keep up good health [40]. Insufficient physical activity, prolonged sitting, and unfavorable sitting postures influence WMSD among drivers [41 –43]. 84.5 % of participants have reported being stressed during work. Work-related stress is considered as one of the risk factors for WMSDs [44]. Taklikar conducted a study on bus drivers regarding occupational stress and its associated health disorders, and found 79% of drivers are suffering from LBP, 15% from neck pain, and 5% from shoulder pain [45].

Drivers’ seats in BMTC buses (excluding premium segment buses) consist of metal frames, knitted with nylon wires at the seat pan/cushion and backrest region. These seats do not have either arm rests or head rests or provision for lumbar and back adjustments. Vibration attenuation is minimum in these kinds of seats as there are no vibration isolators fitted in the seat. Johnson conducted a study on WBV exposures in buses based on the type of seat designs. This study concluded that pedestal seats were suitable for low-floor city buses, but showed negative effects for high-floor buses [46]. Maneuvering and steering buses on congested roads are risky tasks for city bus drivers due to the road condition and other road users. In the upper extremities of drivers, muscle activation is highly dependent on steering and steering torque [47, 48]. Ahlstrom conducted a study on the effect of an active steering system (ASS) on city bus drivers’ muscle activity and found that the ASS was an innovative technology that reduced muscle activity by 15–25% while turning and maneuvering the bus [49]. BMTC should check for the ASS technology when procuring new chassis to reduce drivers’ efforts.

The Deccan Herald, a national-level print media, published an article on 23 December 2019 stating that Karnataka has the second deadliest roads in south India after Tamil Nadu, based on the reports from the Lancet global burden of disease series. Bengaluru, Karnataka is considered one of the largest metropolitan areas in Asia. But the roads within the city limits are characterized by surface unevenness, potholes, irregular pavements and no proper road markings or warning sign boards. Surface distress on roads affects the driver and passengers [50]. Kirbas conducted a study on pavement performance levels that cause human health risks and found that vibration exposure does not affect drivers if the pavement performance level (Pavement condition index (PCI) should be more than 100 in the rating scale for high performance level) is extremely high [51]. Digital Image Processing (DIP) is a technique that can be used to effectively identify speed breakers and other surface distress on roads. DIP alerts the driver with a voice message and display so that the driver can maintain optimum speed to cross the road surface distress, which in turn reduces the road-induced vibration to the driver [52]. Zanol conducted a study on the influence of road types on WBV exposures and reported that the type of roads/pavements influences the WBV than the driver’s influence. Furthermore, the study concluded that the seat mounted in the bus was not efficient for vibration isolation in all frequency bands [53]. Tire stiffness can also significantly affect the transfer of vibration to the driver [54, 55]. The optimum tire inflation pressure reduces the vibration transfer to the driver [56].

In the present study, a year old buses were used for vibration analysis. Annual report of BMTC revealed that there were more older buses in the corporation compared to new buses. Previous studies have reported that vehicle induced vibration level (> 0.5 m/s²) increases with the age of the bus due to maintenance issues and degradation of vehicle subsystems [57]. Long term exposure to vibration causes dysfunction of the nervous system, white finger diseases, swelling in the lower extremities, spinal degeneration, low back pain, and body aches [58 –60]. Statistical analysis and real time measurements show the significant association of road types and vibration exposure with WMSDs.

5 Limitations

(1) Data were collected from self-reported questionnaires. (2) The chances of over or underestimation in reporting the WMSDs by the participants since drivers have no prior exposure/experience in a similar kind of study. (3) To enhance the statistical power, the sampling size could be increased. (4) The number of drivers could be increased in real-time vibration testing to compare the measured vibration in relation with BMI.

6 Conclusion

In this study, results obtained from statistical and vibration analysis (WBV and HAV) indicate that individual factors, vehicle factors, road conditions, and working environmental factors are associated with reported WMSDs among bus drivers. The relationship of vibration exposure and WMSDs has been explored from Chi-square tests and Gini impurity, and vibration testing was conducted to compare with ISO and European standards. Several situations mentioned in the evaluation of A(8) were found to be very uncomfortable to drivers on both asphalt pavement and rough road.

In conclusion, the administration and maintenance departments of BMTC should identify the sources of hazardous vibration in buses and roads in order to rectify the road and vehicle-induced vibration to drivers. Among the possible preventive strategies to reduce WMSDs in bus drivers, BMTC should conduct the vibration performance tests in different road types after assembling the body with the procured chassis. Conducting specific training programs (posture training) and providing the information regarding work related risk factors, it is possible to mitigate the WMSDs in bus drivers. Further, to extend the present work, the prevalence of WMSDs with respect to specific body districts (shoulder, lower back) can be determined using vibration levels, speed of bus and road types.

Footnotes

Acknowledgments

We gratefully acknowledge the support and co-operation of the staff members of BMTC, Bengaluru, Karnataka, India. The authors also thank the Management of VIT University and the Dean of the School of Mechanical Engineering, VIT Chennai, India for the support to publish this work.

Conflict of interest

The authors declare that they have no conflict of interest. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References

Griffin

. Discomfort from feeling vehicle vibration. Vehicle System Dynamics. 2007;45(7-8):679–98.

Griffin

, Griffin

. Handbook of Human Vibration. Elsevier; 1996 Dec 3.

Lis

, Black

, Korn

, Nordin

. Association between sitting and occupational LBP. European Spine Journal. 2007;16(2):283–98.

Burström

, Nilsson

, Wahlström

. Whole-body vibration and the risk of low back pain and sciatica: a systematic review and meta-analysis. International Archives of Occupational and Environmental Health. 2015;88(4):403–18.

Tiemessen

, Hulshof

, Frings-Dresen

. An overview of strategies to reduce whole-body vibration exposure on drivers: A systematic review. International Journal of Industrial Ergonomics. 2007;37(3):245–56.

Kompier

, Di Martino

. Review of bus drivers’ occupational stress and stress prevention. Stress Medicine. 1995;11(1):253–62.

Bergomi

, et al. Work-related stress and role of personality in a sample of Italian bus drivers. Work. 2017;57(3):433–40.

Karsh

. Theories of work-related musculoskeletal disorders: Implications for ergonomic interventions. Theoretical Issues in Ergonomics Science. 2006;7(1):71–88.

Kresal

, Roblek

, Jerman

, Meško

. Lower back pain and absenteeism among professional public transport drivers. International Journal of Occupational Safety and Ergonomics. 2015;21(2):166–72.

10.

Serranheira

, Sousa-Uva

, Heranz

, Kovacs

, Sousa-Uva

. Low Back Pain (LBP), work and absenteeism. Work. 2020 Jan 1(Preprint):1–7.

11.

Burström

, Nilsson

, Wahlström

. Whole-body vibration and the risk of low back pain and sciatica: a systematic review and meta-analysis. International Archives of Occupational and Environmental Health. 2015;88(4):403–18.

12.

Wilder

. The biomechanics of vibration and low back pain. American Journal of Industrial Medicine. 1993;23(4):577–88.

13.

Mohammad Rahimi

, Rahnama

, Mohammad Rahimi

. Prevalence of Musculoskeletal Disorders during and after Driving among Suburban Truck Trailer Drivers in Taybad, Iran, in 2016. Journal of Health Research in Community. 2017;3(2):55–66.

14.

Nahvi

, Fouladi

, Nor

. Evaluation of whole-body vibration and ride comfort in a passenger car. International Journal of Acoustics and Vibration. 2009;14(3):143–9.

15.

Hulshof

, et al. Evaluation of an occupational health intervention programme on whole-body vibration in forklift truck drivers: a controlled trial. Occupational and Environmental Medicine. 2006;63(7):461–8.

16.

Anderson

. The back pain of bus drivers. Prevalence in an urban area of California. Spine. 1992;17(12):1481–8.

17.

Borle

, Gunjal

, Jadhao

, Ughade

, Humne

. Musculoskeletal morbidities among bus drivers in city of Central India. Age (Years). 2012;46(06.69):28–57.

18.

Maciulyte

. Bus drivers’ health and conditions of work. In Symposium conducted at the European Centre for Occupational Health, Safety and the Environment, Kaunas, Lithuania. 2000;4.

19.

Funakoshi

, Taoda

, Tsujimura

, Nishiyama

. Measurement of whole-body vibration in taxi drivers. Journal of Occupational Health. 2004;46(2):119–24.

20.

Kaderli

, Gomes

. Vibration analysis based on health and comfort levels on ride vehicles. International Journal of Vehicle Noise and Vibration. 2015;11(3-4):238–54.

21.

Kim

, et al. Whole body vibration exposures and health status among professional truck drivers: a cross-sectional analysis. Annals of Occupational Hygiene. 2016;60(8):936–48.

22.

Seidel

. On the relationship between whole-body vibration exposure and spinal health risk. Industrial Health. 2005;43(3):361–77.

23.

Yamane

. Elementary sampling theory prentice Inc. Englewood Cliffs. NS, USA. 1967;1(1):371–90.

24.

Dickinson

, et al. Questionnaire development: an examination of the Nordic Musculoskeletal questionnaire. Applied Ergonomics. 1992;23(3):197–201.

25.

Kuorinka

, et al. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Applied Ergo-nomics. 1987;18(3):233–7.

26.

Standardization IO. for. Mechanical vibration and shock Evaluation of human exposure to whole-body vibration-Part 1: General requirements. The Organization. 1997.

27.

ISO I. 5349-1: Mechanical vibration—measurement and evaluation of human exposure to hand-transmitted vibration—part 1: general requirements. Geneva, Switzerland: International Organization for Standardization. 2001.

28.

Standard BS. 6841, Guide to Measurement and Evaluation of Human Exposure to Whole-Body Mechanical Vibration and Repeated Shock. London, UK: BSI. 1987 Sep.

29.

Mansfield

. The European vibration directive–how will it affect the dental profession? British Dental Journal. 2005;199(9):575–7.

30.

Corlett

, Bishop

. A technique for assessing postural discomfort. Ergonomics. 1976;19(2):175–82.

31.

, Yu

, Yang

, Pei

, Zhao

. Effects of long-duration sitting with limited space on discomfort, body flexibility, and surface pressure. International Journal of Industrial Ergonomics. 2017;58:12–24.

32.

Sundhari

. A knowledge discovery using decision tree by Gini coefficient. IEEE International Conference on Business, Engineering and Industrial Applications. 2011:232–235.

33.

Chandra

, Varghese

. Fuzzifying Gini Index based decision trees. Expert Systems with Applications. 2009;36(4):8549–59.

34.

Kumar

, Sakthivel

, Shankar

. Prevalence of work-related musculoskeletal disorders among occupational bus drivers of Karnataka, South India. Work. 2020 May 12(Preprint):1–2.

35.

Tamrin

, Yokoyama

, Jalaludin

, Aziz

, Jemoin

, Nordin

, Naing

, Abdullah

. The association between riskfactors and low back pain among commercial vehicle drivers inpeninsular Malaysia: a preliminary result. Industrial Health. 2007;45(2):268–78.

36.

Murray

, et al. Occupational health risks and intervention strategies for US taxi drivers. Health Promotion International. 2019;34(2):323–32.

37.

Space

. Bus Driver Fatigue and Stress Issues Study Final Report. United States. Federal Highway Administration. Office of Motor Carriers. 1999 Dec 8.

38.

Giahi

, Khoubi

, Amiri

. The association between insomnia and cardiovascular risk factors in bus drivers in Iran. Work. 2016;55(1):207–14.

39.

Meijman

. Mental fatigue and the efficiency of information processing in relation to work times. International Journal of Industrial Ergonomics. 1997;20(1):31–8.

40.

Wang

, Delp

. Health status, job stress and work-related injury among Los Angeles taxi drivers. Work. 2014;49(4):705–12.

41.

Lee

, et al. Lancet Physical Activity Series Working GrouEffect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. The Lancet. 2012;380(9838):219–29.

42.

Okunribido

, Shimbles

, Magnusson

, Pope

. City bus driving and low back pain: a study of the exposures to posture demands, manual materials handling and whole body vibration. Applied Ergonomics. 2007;38(1):29–38.

43.

Evans

, Johansson

, Rydstedt

. Hassles on the job: a study of a job intervention with urban bus drivers. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior. 1999;20(2):199–208.

44.

Bongers

, de Winter

, Kompier

, Hildebrandt

. Psychosocial factors at work and musculoskeletal disease. Scandinavian Journal of Work, Environment & Health. 1993:297–312.

45.

Taklikar

. Occupational stress and its associated health disorders among bus drivers. Int J Community Med Public Health. 2016;3(1):208–11.

46.

Jonsson

, Rynell

, Hagberg

, Johnson

. Comparison of whole-body vibration exposures in buses: effects and interactions of bus and seat design. Ergonomics. 2015;58(7):1133–42.

47.

Gao

, et al. Muscle activity and co-contraction of musculoskeletal model during steering maneuver. Bio-medical Materials and Engineering. 2014;24(6):2697–706.

48.

Liu

, Ji

, Ryouhei

, Takahiro

, Lou

. Function of shoulder muscles of driver in vehicle steering maneuver. Science China Technological Sciences. 2012;55(12):3445–54.

49.

Ahlström

, Gink Lövgren

, Nilsson

, Dukic Willstrand

, Anund

. The effect of an active steering system on city bus drivers’ muscle activity. International Journal of Occupational Safety and Ergonomics. 2019;25(3):377–85.

50.

Cantisani

, Loprencipe

. Road roughness and whole body vibration: Evaluation tools and comfort limits. Journal of Transportation Engineering. 2010;136(9):818–26.

51.

Kırbaş

, Karaşahin

. Pavement performance levels causing human health risks. Građevinar. 2018;70(10.):851–61.

52.

Ullah

, Hussain

, Wasim

, Jahanzaib

. Usage and impacts of speed humps on vehicles: A review. Journal of Advanced Review on Scientific Research. 2016;28(1):1–7.

53.

Zanol

, Miguel

, Becker

. Whole-Body Vibration Exposures in Urban Bus Drivers: The Influence of Road Type. SAE Technical Paper; 2014 Nov 4.

54.

Tiemessen

, Hulshof

, Frings-Dresen

. An overview of strategies to reduce whole-body vibration exposure on drivers: A systematic review. International Journal of Industrial Ergonomics. 2007;37(3):245–56.

55.

Malchaire

, Piette

, Mullier

. Vibration exposure on fork-lift trucks. The Annals of Occupational Hygiene. 1996;40(1):79–91.

56.

Sherwin

, Owende

, Kanali

, Lyons

, Ward

. Influence of tyre inflation pressure on whole-body vibrations transmitted to the operator in a cut-to-length timber harvester. Applied Ergonomics. 2004;35(3):253–61.

57.

Vosoughi

, Rostamzadeh

, Farshad

, Taheri

, Vahabzadeh-Monshi

. Whole-Body Vibration Exposure Study in Intercity Mini-Bus Drivers-The Risk of Musculoskeletal Disorders. Iranian Journal of Health, Safety and Environment. 2019;6(1):1198–205.

58.

Mehta

, Shyam

, Singh

, Verma

. Ride vibration on tractor-implement system. Applied Ergonomics. 2000;31(3):323–8.

59.

Sterud

, Tynes

. Work-related psychosocial and mechanical risk factors for low back pain: a 3-year follow-up study of the general working population in Norway. Occupational and Environmental Medicine. 2013;70(5):296–302.

60.

Eger

, Stevenson

, Boileau

PÉ

, Salmoni

. Predictions of health risks associated with the operation of load-haul-dump mining vehicles: Part 1—Analysis of whole-body vibration exposure using ISO -1 and ISO–5 standards. International Journal of Industrial Ergonomics. 2008;38(9-10):726–38.

	Reported MSDs						Statistics
Risk factors	n	(%)	Yes (%)		No (%)		χ ²	df	p ^a
			(n = 247)		(n = 123)
Socio-demographic
Age (years)
24– 28	38	10.27	4.86	18	5.4	20	9.9	2	< 0.05 (7e– 3)
29– 39	187	50.54	32.97	122	17.56	65
≥40	145	39.18	28.91	107	10.27	38
Work-related
Seat adaptability issue
Yes	286	77.29	47.83	177	29.45	109	13	1	< 0.05 (– 2e-4)
No	84	22.7	18.91	70	3.78	14
Prolong sitting
Yes	270	72.97	42.16	156	31.08	115	39	1	< 0.05^*(– 1e-5)
No	100	27.03	24.59	91	2.16	8
Frequent posture change
Yes	276	74.59	43.51	161	31.08	115	35	1	< 0.05 (– 1e-5)
No	94	25.41	23.24	86	2.16	8
On duty breaks
Yes	189	51.08	47.83	177	29.46	109	13	1	< 0.05 (– 2e-4)
No	181	48.92	18.91	70	3.78	14
Egress/ingress
Yes	272	73.51	41.08	152	10	37	33	1	< 0.05 (– 1e-5)
No	98	26.48	25.67	95	23.24	86
Involvement in physical activity
Yes	122	32.97	0.54	2	32.43	120	348	1	< 0.05 (– 1e-5)
No	248	67.02	66.22	245	0.81	3
Posture training
Yes	177	47.83	27.83	103	20	74	11	1	< 0.05 (– 1e-5)
No	193	52.16	38.91	144	13.24	49
In-vehicle controls reachability
Yes	291	78.64	53.5	198	25.13	93	1	1	> 0.05 (8e– 4)
No	79	21.35	13.24	49	8.1	30
Dependency of outside food
Yes	323	87.29	62.16	230	25.13	93	23	1	< 0.05 (– 1e-5)
No	47	12.7	4.59	17	10.81	30
Exposed to vibration on duty
Low magnitude	69	18.64	2.43	9	16.21	60	110	1	< 0.05 (– 1e-5)
High magnitude	301	81.35	64.32	238	17.02	63
Stress at work
Yes	313	84.59	62.16	230	22.43	83	41	1	< 0.05 (– 1e-5)
No	57	15.4	4.59	17	10.81	40
Access to drinking water/restrooms on duty
Yes	104	28.11	8.65	32	19.46	72	84	1	< 0.05 (– 1e-5)
No	266	71.89	58.11	215	13.78	51
Work satisfaction (personally)
Yes	262	70.81	13.24	49	14.86	55	25	1	< 0.05 (– 1e-5)
No	108	29.19	53.51	198	18.38	68
Enough breaks at work
Yes	97	26.22	20.27	75	5.95	22	6.6	1	< 0.05 (0.01)
No	273	73.78	46.49	172	27.3	101
Thermal discomfort in cabin
Yes	213	57.57	50.27	186	7.3	27	96	1	< 0.05 (– 1e-5)
No	157	42.43	16.49	61	25.95	96
Shift timings
First	157	42.43	25.95	96	16.49	61	14	1	< 0.05 (9e-4)
Second	100	27.02	16.22	60	10.81	40
General	113	30.54	24.59	91	5.95	22
Cabin environment
Yes	242	65.41	57.57	213	7.84	29	142	1	< 0.05 (– 1e-5)
No	128	34.59	9.19	34	25.41	94
Body bending to access side mirrors
Yes	198	53.51	41.89	155	11.62	43	37	1	< 0.05 (– 1e-5)
No	172	46.49	22.16	82	24.32	90
Exposed to air pollution on duty
Yes	309	83.51	64.86	240	18.65	69	101	1	< 0.05 (– 1e-5)
No	61	16.49	1.89	7	14.59	54
Risky driving job
Yes	237	64.05	56.76	210	7.3	27	142	1	< 0.05 (– 1e-5)
No	133	35.95	10.00	37	25.95	96
Tendency towards rash driving
Yes	78	21.08	12.16	45	8.92	33	3.7	1	> 0.05 (0.055)
No	292	78.92	54.59	202	24.32	90
Involved in traffic violence
Yes	121	32.7	9.73	36	22.97	85	111	1	< 0.05 (– 1e-5)
No	249	67.3	57.03	211	10.27	38
Reacting to other road users
Yes	189	51.08	39.73	147	11.35	42	21	1	< 0.05 (– 1e-5)
No	181	48.92	27.03	100	21.89	81
Road condition in daily routes
Average/good	110	29.73	10	37	19.73	73	77	1	< 0.05 (– 1e-5)
Bad/worst	260	70.27	56.76	210	13.51	50
Shutting off ignition at signals
Yes	288	77.84	57.84	214	20	74	33	1	< 0.05 (– 1e-5)
No	92	24.86	8.92	33	13.24	49
Problem solved on time for the queries raised on bus condition on daily/weekly basis by maintenance department
Delayed	257	69.46	54.05	200	15.41	57	46	1	< 0.05 (– 1e-5)
Sometimes on time	113	30.54	12.7	47	17.84	66
Protrusion of manholes
In daily routes
Yes	101	27.3	8.65	32	18.65	69	77	1	< 0.05 (– 1e-5)
No	269	72.7	58.11	215	14.59	54
Sleeping in bus after duty
Yes	226	61.08	53.78	199	7.3	27	119	1	< 0.05 (– 1e-5)
No	144	38.92	12.97	48	25.95	96
Health-related
Body mass index
Under weight	22	5.94	5.4	20	0.54	2	8	3	< 0.05 (0.04)
Normal weight	300	81.08	51.89	192	29.18	108
Overweight	42	11.3	8.1	30	3.24	12
Obese	6	0.16	1.35	5	0.27	1
Current health status
Good	83	22.43	18.37	68	4.05	15	21	2	< 0.05 (– 1e-5)
Average	153	41.35	21.8	81	22.16	82
Bad/very bad	134	36.22	21.01	78	12.43	46
Tired at end of the work
Yes	233	62.97	56.76	210	6.22	23	155	1	< 0.05 (– 1e-5)
No	137	37.03	10	37	27.03	100
Lack of strength
Yes	230	62.16	41.8	155	9.46	35	24	1	< 0.05 (– 1e-5)
No	140	37.84	14.05	52	23.78	88
Surgical history
Yes	72	19.46	12.7	47	6.76	25	0.8	1	> 0.05 (0.076)
No	298	80.54	54.05	200	26.49	98
Muscle fatigue during working hours
Yes	276	74.59	63.78	236	10.81	40	172	1	< 0.05 (– 1e-5)
No	94	25.41	2.97	11	22.43	83
Health and safety training
Regularly	136	36.76	26.22	97	10.54	39	2	1	> 0.05 (0.15)
Sometimes	234	63.24	40.54	150	22.7	84
Self-medication for body pain
Yes	98	26.49	13.78	51	12.7	47	13	1	< 0.05 (– 1e-5)
No	272	73.51	52.97	196	20.54	76

Independent variables (risk factors) associated with WMSDs	Gini
impurity
Road condition in daily route (Average/good = Asphalt pavement Bad/worst = Rough road)	0.289
Posture training	0.142
Prolong sitting	0.137
Frequent posture change	0.091
Involvement in physical activity	0.081
Feeling muscle fatigue at work	0.080
Risky driving job	0.064
Seat adaptability issue	0.040
Body bending to access side mirrors	0.029
Smoking/tobacco consumption	0.020
Exposed to vibration	0.018
Dependency on outside food	0.006
Sleeping in bus after duty	0.003
Total	1.00