Occupational exposure of vehicular emissions and cardiorespiratory risk among urban metropolitan bus drivers: A cross-sectional comparative study

Abstract

BACKGROUND:

Vehicular emissions on long-term exposure predispose metropolitan bus drivers to cardiorespiratory ailments.

OBJECTIVE:

To evaluate the cardiorespiratory risk of urban metropolitan bus drivers related to vehicular emission exposure.

METHODS:

Bus drivers (with service >5 years, n = 254) and their administrative controls (primarily engaged in indoor white collared jobs, n = 73) were recruited. Demographic, occupational and clinical details were collected through pre-validated standardized format. Pulmonary Function Test (PFT) and lipid profile were carried out with standard protocol. Risk for cardiovascular events for preceding 10-years was estimated with WHO/ISH risk prediction chart and QRISK3 score. Exposure assessments for particulate matter (PM) were performed for both groups while duty hours.

RESULTS:

Exposure of drivers to PM_2.5 six times and PM₁₀ five times higher in comparison to administration staff (PM_2.5- 970.9 v/s 145.0μg/m³ TWA and PM₁₀- 1111.7 v/s 233.8μg/m³ TWA). Bus drivers exhibited significantly higher prevalence of respiratory symptoms (dyspnea-25% v/s 6.8% and cough-20.1% v/s 9.8%) and compromised PFT (obstructive–21% v/s 5.7% and restrictive–4.2% v/s 2.9%) in comparison to controls. Multivariate regression statistics reveal a significant decline for FEV₁/FVC and FEV_25–75 % among bus drivers compared to controls, controlling the influence of physiological and environmental factors. The difference between predicted cardiac age and their respective chronological age was twice higher (8.3 v/s 4.3 years) among drivers compared to their administration staff.

CONCLUSION:

Bus drivers were exposed to high levels of outdoor air pollutants. Further, the drivers exhibited higher risk for ischemic attack and obstructive airway diseases as compared to administration staff.

Keywords

Particulate matter exposure ischemic heart disease risk pulmonary function test (PFT)traffic-related air pollution

1 Introduction

Air pollution poses a considerable threat to health across the world by increasing the risk for cardiovascular and respiratory ailments [1]. Air pollutants are chemically and physically complex in nature and are commonly derived from industrial emissions, combustion of hydrocarbon fuel, and other activities. Poor ambient air quality contributes to 3.7 million premature deaths across the globe with more than half a million deaths annually in the developing nations of the Asia Pacific region [2, 3].

Certain occupations by virtue of their job mandate, involve relatively higher exposure to air pollutants. Public transit drivers are among such occupations that involve higher exposure and pose an increased risk for cardiorespiratory ailments [4 –9]. Numerous studies have reported an association between exposure to vehicular exhaust / poor air quality and cardiorespiratory ailments, some of these studies have involved drivers as individuals with exposure to relatively higher levels of air pollution / vehicular exhaust / poor air quality [6 –10]. However, these studies were limited by non-assessment of precise exposure to air pollutants (levels of PM_2.5/ PM₁₀), non-consideration of potential confounding factors (tobacco smoking, domestic cooking practices) smaller sample size, choice of poor tools for assessing the risk for cardiorespiratory illness and inefficient study design [5 , 7–9].

The present study intended to comprehensively evaluate the cardio-respiratory health of public transit drivers, assess the levels of their exposure to particulate matters (PM_2.5 and PM₁₀), and estimate the risk of cardiorespiratory disease in comparison to the control group participants who were engaged in indoor white-collared desk jobs.

2 Material and methods

2.1 Study setting

The present cross-sectional study was carried out among employees (drivers and administrative staff) of the local urban public transit service of Ahmedabad (Gujarat, India) over a period of two calendar years. The study was initiated in June 2019; however, was discontinued around March 2020 in view of the COVID-19 pandemic. The study was resumed around late September 2021 when COVID-19 restrictions were relaxed and completed by March 2022.

Ahmedabad is a metropolitan city located in the western part of India at 23.033863 latitudes and 72.585022 longitudes. In the last few decades, industrialization has generated plenty of opportunities for employment to the residents, resulting in the rapid expansion of the city in terms of population and geography. In order to cater the transportation requirements of the city’s rapid expansion, the vehicular traffic and the associated particulate matter and air pollutants have tremendously increased. As per World Health Organization report, it is the fifth most polluted city of India and fifteenth at global level [11]. Local public transit services (governed by municipal corporation) are operated by 209 routes spread across the city. The drivers of these public transit services are exposed to vehicular emissions during their work hours, whereas administrative staff of the transit department are relatively unexposed as they primarily engaged in indoor desk job. The workplaces of the participants, the transit drivers and administrative staff were equipped with fans and windows for circulation of the air. While no additional preventive / control methods were adopted at these workplaces.

2.2 Sample size and data collection

The desired sample size (n = 246) for the study was calculated using Open-Epi version 3.01 web application [12], with an assumption of 24% cardiovascular morbidities prevalence (based on earlier observations by Taklikar et al. [9]), with <5 error and 95% power, design effect-1 (one) and 5% attrition (including missing / incomplete data, attrition and non-response rate). About 265 consenting male drivers with a minimum of five years of employment as public transit drivers, no contraindication to perform spirometry and no obvious cardiorespiratory illness (also not among the first-degree relatives) were invited to participate in the study. The line list of drivers including their details such as age, job duration, work hours and nature of job provided by the division of Transport Corporation were used to select the participants meeting the inclusion and exclusion criteria. Conventionally all drivers assemble at the offices located adjacent to transit depot to begin their transit services for the day. Data collection team including the investigators followed-up every day at the transit depot to recruit the participants. Consecutive drivers meeting the inclusion and exclusion criteria were recruited in the study until the desired sample was achieved. However, data of 254 participants meeting the inclusion and exclusion criteria were available for final analysis. The flowchart of the participant recruitment is shown in Supplementary Figure 1. For comparison purposes, all individuals employed in administration of the city’s transport services primarily engaged in indoor white collared jobs (administrative jobs) and adhere to study enrollment criteria were invited as controls. All consenting administrative staff, age and gender matched with the transit drivers, with more than five years of employment in the administration of transportation services (within indoors) and without history of ischemic heart disease and chronic lung disease in self and among the first-degree relatives were invited to participate in the study. Participants with known contraindications to perform spirometry were also excluded. Basic socio-clinico-demographic and occupational details were collected from all consented participants using semi-structured pre-validated questionnaires. In addition, detailed clinical examination of cardio-respiratory system, assessment of pulmonary function and fasting blood samples were collected from all the consented participants. Further, drivers and administrative staff were monitored for particulate matter exposures during work hours.

Fig. 1

Risk for ischemic heart disease for 10-years as per WHO/ISH risk prediction chart.

2.3 Assessment of PM_2.5 and PM₁₀ exposure using an aerosol monitor

The local public transit services operates 209 services, catering the public transportation needs of the city. The direction (routes) of all these public transit services were mapped and reviewed to decide the sampling routes. About 20 (∼10%) transit routes traversing across the city and reaching long distances were selected for assessing ambient PM_2.5 and PM₁₀ levels. Each of the transit routes were independently assessed for exposure assessment for a single day. The transit drivers carried the sampler for the entire day during their duty hours. The pre-calibrated portable aerosol monitor (TSI Inc., DustTrak^TM DRX8533) was placed in the breathing zone of the driver as recommended by the manufacturer. In similar weather conditions, exposure assessments of administrative staff with regard to particulate matter were carried out at six representative administrative sections at their indoor seating place. Exposure to bus drivers for each selected transit route and administrative staff were calculated as 8-hour Time Weighted Average (TWA) as μg/m³ unit. Average of all transit route and administration section measurements were regarded as average particulate matter (PM_2.5 and PM₁₀) exposure to bus drivers and administrative staff during duty hours, respectively.

2.4 Clinical and laboratory assessments

In view of collection of blood samples for lipid profile and spirometry evaluation, participants were encouraged to provide blood sample with fasting and avoid smoking eight hours prior to participation.

2.4.1 Respiratory symptoms

The American Thoracic Society Division of Lung Disease (ATS-DLD) developed and validated set of questions (questionnaire) for epidemiologic assessment of respiratory symptoms and ailments such as cough, breathlessness (dyspnea), phlegm and chest pain. The modified version of the respiratory questionnaire (ATS-DLD-78a) was used to assess the respiratory ailments and its risk factors among the study participants [13].

2.4.2 Pulmonary function test (spirometry)

The pulmonary function of the consented participants was evaluated using pneumotach type spirometer (Schiller SP-10, Made in Switzerland) as recommended by American Thoracic Society – European Respiratory Society (ATS-ERS) [14]. Pulmonary function test (PFT) parameters such as Forced Vital Capacity (FVC), Forced Expiratory Volume in first second (FEV1), Forced Expiratory Flow in middle half of the FVC (FEF25-75%) and Peak Expiratory Flow Rate (PEFR) were recorded for each of the participant. Age-gender-ethnic (Indian) reference values were derived to categorize participants as “normal” type when FVC≥80% of the reference and observed FEV₁/FVC≥70%, “obstructive” type of pulmonary compromise when FVC≥80% of the reference and observed FEV1/FVC<70%, and “restrictive” type of pulmonary compromise when FVC<80% of the reference and observed FEV₁/ /FVC≥70% of the reference and mixed type of pulmonary compromise (i.e. both obstructive and restrictive) when the FVC<80% of reference and observed FEV1₁/FVC<70% [15].

2.4.3 Cardiovascular system

Blood pressure was measured adhering to the American Heart Association (AHA) recommendations with a pre-calibrated Omron digital sphygmomanometer (Omron HealthCare, Kyoto, Japan) [16]. Participants were asked to relax for five minutes prior to measurement of blood pressure. The blood pressure was evaluated thrice, with a five-minute interval between each measurement. The average of the second and third measurement was considered for the study. Individuals with Systolic Blood pressure ≥140 mm Hg and/or Diastolic Blood Pressure ≥90 mm Hg were categorized as hypertensive as termed by the Eighth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure Guidelines (JNC-8) [17].

World Health Organization and International Society of Hypertension (WHO/ISH) developed charts for risk prediction of heart attacks and strokes in people living in low and middle-income countries based on age, sex, blood pressure, smoking status, total blood cholesterol and presence/absence of diabetes mellitus. WHO/ISH chart applicable for the South East Asian Region – D (SEAR-D) was used to predict the 10-year risk of a fatal/non-fatal major cardiovascular event of the recruited participants [18].

Similar to WHO/ISH, Q-Research Database Risk version 3 (QRISK3) is an algorithm to predict 10-year cardiovascular risk. The QRISK3 considers age, ethnicity, deprivation, systolic blood pressure, body mass index, total cholesterol: high density lipoprotein cholesterol ratio, smoking, family history of coronary heart disease in the first degree relative aged <60 years, type 1 or 2 diabetes, hypertension, rheumatoid arthritis, atrial fibrillation, chronic kidney disease, a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, systemic lupus erythematosus, use of atypical antipsychotics, severe mental illness, erectile dysfunction (for male), and HIV/AIDs. The 10-year risk for cardiovascular diseases was estimated using the QRISK3 algorithm available online [19].

2.4.4 Blood sample collection and laboratory investigations

About 3 ml of venous blood was collected under aseptic precautions, serum was immediately separated and stored for further analysis. Lipid profile tests viz. total cholesterol, direct low density lipoprotein (LDL), direct high density lipoprotein (HDL), triglycerides were performed with the automated clinical chemistry analyzer (AutoQuant 100 Amaratrademark) based on colorimetric and immunoturbidimetric principle.

2.5 Ethics statement

The study was approved by the Institutional Ethics Committee. Informed written consent from each study participant was taken prior to enrollment. Reports of laboratory tests were shared with all study participants individually and in case of requirement referred to tertiary care health facilities for further diagnosis and treatment. All Bio-Medical Waste (BMW) generated during sample collection and laboratory process were processed as per the instruction of the local regulatory agency. The Declaration of Helsinki of 1964 was adhered to throughout the research study to ensure compliance to ethics of medical research.

2.6 Data analysis

All statistical analyses were performed using SPSS statistical software Version 17.0. [20]. Parametric analysis (Independent samples t-test) of the quantitative data was performed on confirming normality distribution (Shapiro-Wilk test). A multivariate regression analysis was performed to explore the association of pulmonary function parameters with driver group, controlling for potential confounders such as age (continuous data), height (continuous data measured using a non-stretchable validated scale), smoking habits (recorded as yes/no), type of kitchen at residence (recorded as separate kitchen-yes/no) and type of cooking fuel (recorded as usage of biomass-yes/no). Lastly, the association between the job duration and the PFT changes were explored. The results of all statistical analyses were regarded as significant at p < 0.05.

3 Results

A total of 327 male participants including 254 drivers and 73 control participants (engaged predominantly with indoor responsibilities) consented for study. Basic demographic and occupational details are described in Table 1. The mean (SD) age of driver and control group subjects were 47.7 (6.4) years and 48.4 (7.5), respectively. Anthropometric parameters such as height, weight and BMI were not significantly different for both groups. Both groups did not statistically differ with respect to proximity of residence from main road, type of cooking fuel at home, availability of separate kitchen, average time spent for commute (between home and job) and tobacco usage (both smoke and smokeless form) (Table 1). The drivers were exposed to 970.9(258–1340) μg/m³ TWA and 1111.7(298–1480) μg/m³ TWA of PM_2.5 and PM_10, respectively. Whereas controls were exposed to 145.0(133–166) μg/m³ TWA and 233.8(214–267) μg/m³ TWA of PM_2.5 and PM_10, respectively.

Table 1
Basic demographic and occupational details of driver and control group

Variable Drivers (n = 254) Control (n = 73) Significance level

Distance of house from the main road

<100 meters 29 (11.4%) 5 (6.8%) 0.38

100–300 meters 39 (15.4%) 9 (12.4%)

>300 meters 186 (73.2%) 59 (80.8%)

Type of fuel

LPG 246 (96.9%) 72 (98.6%) 0.412

Biomass/other fossil fuel 8 (3.1%) 1 (1.4%)

Type of kitchen

Separate 227 (89.4%) 69 (94.5%) 0.186

Within living room 27 (10.6%) 4 (5.5%)

Duration of travel for service each day

<1/2 hour 74 (29.1%) 19 (26.0%) 0.57

1/2–1 hour 106 (41.7%) 36 (49.3%)

1–2 hours 50 (19.7%) 14 (19.2%)

>2 hours 24 (9.5%) 4 (5.5%)

Duration of service as an urban transport service driver

<10 years 52 (20.4%) ——– NA

10–15 years 21 (8.3%) ——–

≥15 years 181 (71.3%) ——–

Smoking habit

Non-smokers 187 (73.6%) 61 (83.6%) 0.21

Ex-smokers 19 (7.5%) 3 (4.1%)

Present smokers 48 (18.9%) 9 (12.3%)

Tobacco chewer

Non-chewer 112 (44.1%) 40 (54.8%) 0.106

Chewer 142 (55.9%) 33 (45.2%)

Anthropometric parameters (mean±SD)

Age (years) 47.7±6.4 48.4±7.5 0.419

Height (cm) 169.8±5.3 168.7±5.5 0.134

Weight (kg) 71.7±13.0 71.4±12.8 0.891

BMI 24.8±4.4 25.0±3.9 0.756

Variable	Drivers (n = 254)	Control (n = 73)	Significance level
Distance of house from the main road
<100 meters	29 (11.4%)	5 (6.8%)	0.38
100–300 meters	39 (15.4%)	9 (12.4%)
>300 meters	186 (73.2%)	59 (80.8%)
Type of fuel
LPG	246 (96.9%)	72 (98.6%)	0.412
Biomass/other fossil fuel	8 (3.1%)	1 (1.4%)
Type of kitchen
Separate	227 (89.4%)	69 (94.5%)	0.186
Within living room	27 (10.6%)	4 (5.5%)
Duration of travel for service each day
<1/2 hour	74 (29.1%)	19 (26.0%)	0.57
1/2–1 hour	106 (41.7%)	36 (49.3%)
1–2 hours	50 (19.7%)	14 (19.2%)
>2 hours	24 (9.5%)	4 (5.5%)
Duration of service as an urban transport service driver
<10 years	52 (20.4%)	——–	NA
10–15 years	21 (8.3%)	——–
≥15 years	181 (71.3%)	——–
Smoking habit
Non-smokers	187 (73.6%)	61 (83.6%)	0.21
Ex-smokers	19 (7.5%)	3 (4.1%)
Present smokers	48 (18.9%)	9 (12.3%)
Tobacco chewer
Non-chewer	112 (44.1%)	40 (54.8%)	0.106
Chewer	142 (55.9%)	33 (45.2%)
Anthropometric parameters (mean±SD)
Age (years)	47.7±6.4	48.4±7.5	0.419
Height (cm)	169.8±5.3	168.7±5.5	0.134
Weight (kg)	71.7±13.0	71.4±12.8	0.891
BMI	24.8±4.4	25.0±3.9	0.756

For the significant difference between the two groups for data ‘n (%)’ chi-square test and for data ‘Mean±SD’ independent sample t-test was applied. p < 0.05 was considered a significant difference for both tests.

3.1 Respiratory symptoms and pulmonary function assessments

Symptomatic evaluation of participants (with usage of Modified ATS-DLS-78a respiratory questionnaire) show significantly high prevalence of cough (p = 0.04) and dyspnea (p = 0.001) among drivers (20.1% and 25.2%, respectively) in comparison to control participants (9.8% and 6.8%, respectively) (Table 2). PFT results were available for 308 participants (238 drivers and 70 controls) and for 19 subjects the PFT observations were not available due to non-consented, non-adherence or non-comprehension to instructions of ATS/ERS guidelines. The prevalence of either obstructive or restrictive type of pulmonary function compromise was significantly (p = 0.009) higher among the driver group (21% and 4.2%, respectively) as compared to the control participants (5.7% and 2.9%, respectively). The forced vital capacity (FVC) and forced expiratory volume during the initial second (FEV₁) of the drivers did not statistically differ from that of control participants, however the ratio of FEV₁ and FVC and the FEF_25–75 % were statistically lower among the drivers as compared to controls (Table 2). Further, multivariate regression analysis revealed that FEV₁/FVC and FEF_25–75 % as significantly lower among drivers (β, [95% CI] –0.19, [–8.91, –2.44] and –0.18 [–0.85, –0.24] respectively) after, controlling for potential confounders such as age, height, presence of smoking habits, presence of separate kitchen at residence and usage of biomass as domestic fuel / cooking (Table 3). The exploratory analysis investigating the association between job duration and pulmonary function parameters by comparing the drivers with <15 years of experience (n = 68) as against ≥15 years (n = 170) revealed a trend of lower PFT values and higher prevalence of abnormal lung function among the higher experienced group (Supplementary Table 1). Further, correlational analysis between the job duration and the PFT parameters of the drivers revealed weak but significant (p < 0.05) association (Supplementary Table 2).

Table 2
Comparison of respiratory symptoms and pulmonary functions among urban service drivers and controls

Variable Drivers Control Significance level

Respiratory symptoms

Cough 51 (20.1%) 7 (9.8%) 0.04*

Phlegm 13 (5.1%) 5 (6.8%) 0.56

Dyspnea 64 (25.2 %) 5 (6.8%) 0.001*

Chest pain 6 (2.4%) 3 (4.1%) 0.64

Total 254 73

Spirometry test

Result of PFT test in number (%)

Normal 178 (74.8%) 64 (91.4%) 0.009*

Obstructive 50 (21%) 4 (5.7%)

Restrictive 10 (4.2%) 2 (2.9%)

Dispersion of observed PFT variables (mean±SD)

FVC (liter) 3.56±0.87 3.39±0.85 0.171

FEV1 (liter) 2.70±0.60 2.76±0.64 0.476

FEV1/FVC (%) 76.62±11.96 81.46±8.91 <0.001*

FEF_{25 %–75 %} (liter/sec) 2.56±1.21 3.01±1.21 0.006*

Total 238 70

Variable	Drivers	Control	Significance level
Respiratory symptoms
Cough	51 (20.1%)	7 (9.8%)	0.04*
Phlegm	13 (5.1%)	5 (6.8%)	0.56
Dyspnea	64 (25.2 %)	5 (6.8%)	0.001*
Chest pain	6 (2.4%)	3 (4.1%)	0.64
Total	254	73
Spirometry test
Result of PFT test in number (%)
Normal	178 (74.8%)	64 (91.4%)	0.009*
Obstructive	50 (21%)	4 (5.7%)
Restrictive	10 (4.2%)	2 (2.9%)
Dispersion of observed PFT variables (mean±SD)
FVC (liter)	3.56±0.87	3.39±0.85	0.171
FEV1 (liter)	2.70±0.60	2.76±0.64	0.476
FEV1/FVC (%)	76.62±11.96	81.46±8.91	<0.001*
FEF_{25 %–75 %} (liter/sec)	2.56±1.21	3.01±1.21	0.006*
Total	238	70

Symbol ‘*’ indicates a significant difference (p < 0.05) between two groups as per chi-square test [for data n(%)] and independent sample t-test [for data Mean±SD].

Table 3

Influence of multiple factors on pulmonary functions of the drivers and control group

Variable	FVC	FEV1	FEV1/FVC	FEF_25–75 %
Age	–0.19[–0.04,–0.01]*	–0.29[–0.04,–0.02]*	–0.10[–0.40,0.01]	–0.24[–0.06,–0.03]*
Height	0.08[–0.01, 0.04]	0.16[0.01,0.03]*	0.09[–0.04,0.45]	0.17[0.02,0.06]*
Smoking habit^#	–0.06[–0.15,0.04]	–0.14[–0.14,–0.02]*	–0.14[–2.85,–0.40]*	–0.13[–0.26,–0.03]*
Separate kitchen^$	0.04[–0.24,0.49]	0.03[–0.17,0.29]	0.01[–4.38,4.83]	0.03[–0.31,0.56]
Kitchen fuel^@	0.08[–0.21,1.09]	0.04[–0.24,0.58]	–0.04[–11.66,4.92]	–0.03[–1.03,0.53]
Occupation^∧	0.06[–0.11,0.40]	–0.07[–0.03,0.05]	–0.19[–8.91,–2.45]*	–0.18[–0.85,–0.24]*

Statistical test used: Multivariate regression analysis. Values represent β value [95% Confidence Interval of B]. ^#coded as “0” for non-smokers and “1” for smokers, ^$coded as “0” for separate kitchen and “1” for kitchen within living room, ^@coded as “0” for participants using relatively clean fuel for cooking such as LPG fuel, while those using biomass / smoke emitting fuel is coded as “1”, ^∧coded as “0” for workers engaged in administrative jobs (predominantly indoor) and “1” for the driver participants* indicates statistical significance (p < 0.05).

3.2 Evaluation of cardiovascular parameters

The prevalence of hypertension (32% vs 27%) was relatively higher among drivers as compared to control participants (p = 0.13). Alarmingly, a larger fraction of drivers (14%) were newly diagnosed as hypertension, in comparison to the controls (5%). In comparison to control group, drivers exhibited significantly higher Total Cholesterol (203.6±52.3 mg/dl v/s 187.2±45.1 mg/dl; p = 0.008) and LDL (138.7±54.8 mg/dl v/s 125.3±39.4 mg/dl; p = 0.02), whereas HDL of the drivers was significantly lower compare to control group (40.3±9.1 mg/dl v/s 43.3±9.3 mg/dl; p = 0.013). The ratio between cholesterol and HDL for drivers and control were 4.6±0.9 and 4.7±0.9, respectively.

The 10-year ischaemic heart disease risk scores estimated using WHO/ISH risk score, revealed a higher trend among driver group (p > 0.05). Notably, the proportion of participants with lower CVD risk (i.e. 10% risk) were relatively higher among the control group (83%) as compared to the driver group (73%), suggesting an elevated CVD risk among the drivers group (Fig. 1). The QRISK3 results consistently exhibited higher ischemic heart disease risk score (10.24±8.26 vs 9.42±7.9, p = 0.45) and relative risk for cardiovascular diseases (2.18±1.35 vs 1.95±1.08, p = 0.18) among drivers as compared to control participants. The QRISK3 predicted cardiac age of the driver group (56±10.3 years) was on average eight years higher as compared to their chronological age (47.7±6.4 years), whereas the in case of control subjects predicted cardiac age (52.8±8.4 years) was four years higher as compared to their chronological age (48.4±7.6 years). As per QRISK3 difference between predicted cardiac age and their respective chronological age in case of driver and control group were about eight and four years respectively.

4 Discussion

The present study attempted to comprehensively screen for cardiorespiratory ailments and their risk, among a group of individuals with relatively high exposure to urban air pollutants by virtue of their job requirements. The study enrolled 254 drivers from the local urban public transit services and 73 age, socio-demographic matched consented volunteers, primarily engaged in indoor white collared jobs. Further, exposure to particulate matter (PM_2.5 and PM₁₀) during job hours were measured with usage of aerosol monitor for representative bus routes (n = 20) and administration sections. Drivers of the public transit services exhibited significant compromise in pulmonary function of obstructive type (FEV₁/FVC and FEF_25–75 %) after controlling for potential confounding factors and increased risk for cardiovascular illness as compared to control participants. Further, the drivers exhibited a trend of declining PFT with increasing job duration.

To the best of our knowledge, the current study is the earliest and unique Indian study to report the noxious effects on pulmonary function of the drivers of public transit services exposed to demonstrably high levels of PM_2.5 (970.9μg/m³ TWA) and PM₁₀ (1111.7μg/m³ TWA). The exposure levels were found to be outrageously higher as compared to their administrative control group (PM_2.5 - 145.0μg/m³ TWA and PM₁₀ - 233.8μg/m³ TWA). The results are consistent with studies executed similar observations elsewhere in world, reporting increased prevalence of respiratory and cardiovascular ailments among drivers exposed to very high levels of air pollutants (such as PM, CO₂, NO₂ and SO₂) [21, 22].

The cardiovascular evaluations revealed increased prevalence of hypertension and higher risk of ischemic and other cardiovascular diseases (QRISK3 and WHO-ISH evaluations) among the drivers as compared to control participants. WHO/ISH revealed 27% of the drivers were at greater risk (>10%) for ischemic heart diseases during the next 10 years, consistent with the QRISK3 evaluation, that exhibited significantly higher risk for cardiovascular ailments as compared to the control participants. Further, the predicted cardiac age (health) of the driver participants were average eight years older than their chronological age. A fraction of the investigated parameters identified to elevate the risk of cardiovascular diseases among the drivers, were potentially attributable to their nature of job, personal habits (tobacco usage) and exposure to poor air quality. As per current evidence vehicular pollution not only affects respiratory functions but also increases risk of CHD on long-term exposure. Similar to the present study, high prevalence of hypertension and relative risk of cardiovascular disease were reported among bus drivers in Hong Kong [5].

A recent systematic review reported positive association between cardiovascular mortality (0.92% with 95% CI of 0.44 – 1.39), respiratory mortality (0.7% with 95% CI of 0.01 – 1.4) and exposure to air pollutants (Nitrous oxides), while similar associations were observed between air pollutant exposure (Sulfur-dioxide) and cardiovascular morbidity (0.5% with 95% CI 0.01 – 1) and respiratory morbidity (0.73% with 95% CI 0.04 – 1.42) in East Asia and Pacific region low middle income countries [23]. These observations recapitulate the positive association between air pollution exposure and increased risk of cardiorespiratory ailments. The compromise in respiratory function and elevated cardiovascular risk in the study participants (drivers) may be also associated with their personal habit / lifestyle (such as smoking and relatively sedentary work profile). However, the relative difference as compared to the matched controls support the association between the cardiorespiratory aberrations and exposure to outdoor air pollutants. The possible molecular mechanism could be explained by free radical generation, oxidative stress, DNA damage, inflammatory pathways and hyper responsiveness with regards to exposure ofpollutants [24 –27].

Mbelmbela et al. reported a higher prevalence of respiratory symptoms as well as impaired pulmonary function among those exposed to road traffic emission (bus drivers, conductors and taxi–motorcyclists), which is consistent with the present study observations [28]. Additionally, the present study observed a trend of weaker association between job duration and some of the PFT parameters among the drivers. Several studies in India and other countries have already observed high prevalence of respiratory symptoms, diseases and/or compromised ventilatory function tests among study subjects as effects of vehicular emission exposure, but have several limitations in terms of sample size, inadequately matched control subjects, estimation of exposure and controlling for confounders effect [5 , 22]. To overcome these limitations, the present study estimated the air pollutants (particulate matters) and considered following aspect in study design: (1) age, sex, physiological and socio-demographic matched control participants with predominant indoor work profile in the study design (2) statistically corrected the influences of smoke (tobacco and household cooking fuel) and (3) involved participants (drivers of public transit) with consistent and relatively longer duration of exposure to air pollution / vehicular emission (average duration of employment for the drivers was17 years).

However, there are certain limitations in the present study. Firstly, as the particulate matter exposure assessments were carried out for only representative bus routes on a single occasion which were also insufficient to represent previous exposure, the dose-response relationship between pollution exposure and health effects could not be measured. Current study compared two occupational groups, with variable levels of hazards i.e. exposure to TRAP, sedentary lifestyle, nature of the job, exposure to extreme weather conditions and anxiety-provoking working conditions. Hence, the cardiorespiratory changes observed among the transit drivers may be attributed to these additional hazards. Also, due to the inherent limitations of a cross-sectional study design, further multi-centric longitudinal studies with the sequential evaluation of cardiorespiratory health of subjects along with periodic exposure assessment is advised to understand the dose-response relationship between varied quality/quantity of pollutants and health consequences.

Thus to conclude the study suggests the effects of particulate matter on respiratory and cardio-respiratory systems of drivers. The control strategies from employers such as periodic health checkup, suitable personal protective devices (like face mask FFP2 with valve), rotational transit routes and/or duty hours, educational and awareness programs, targeted health intervention such as smoking cessation programs, promotion for physical activities are suggested to curtail cardiorespiratory risk among drivers [29]. Further, as a long-term goal to improve air quality and reduce vehicular emission measures like phase out of old/inefficient vehicles with eco-friendly vehicles (like battery operated vehicles), control of vehicular traffic through reduced congestion (flyovers/widening of road/regulation of parking) should also be planned.

5 Conclusion

Bus drivers were exposed to a significantly high level of particulate matter because of vehicular emissions. Long-term vehicular emission exposure not only impairs respiratory functions but also deleteriously enhances the risk of ischemic heart disease among drivers. Suitable control strategies along with preventive and interventional measures are required to protect the health of bus drivers.

Ethical approval

The study was approved by the Institutional Ethics Committee of the Indian Council of Medical Research (ICMR), National Institute of Occupational Health, Ahmedabad (Document no.: ICMR-NIOH/ethics/2018/Agenda 3.9, date: 28.09.2018).

Informed consent

All participants involved in the study provided written informed consent.

Conflict of interest

None of the authors have any conflict of interest to report.

Footnotes

Acknowledgments

The authors are thankful to Mr. Mehul Madiya, Mr. Moinuddin Mansuri and Mr. Praveen Kumar of the Division of Health Sciences for coordinating data collection and data entry. Also, the authors thank Mrs. Rupal Thasale, Mr. Rajnish Gupta and Mr. Asif Mansuri for the estimation of particulate matter. Lastly, the authors are thankful to the Municipal Transport Service Department for their approval and participation in the study.

Funding

The study was executed using the Intramural project funds of ‘ICMR-National Institute of Occupational Health’- An Autonomous Central Government Institute from Department of Health Research (DHR), Ministry of Health and Family Welfare (MoHFW), Government of India.

Supplementary materials

The supplementary files are available from .

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