As far as the development is concerned, the humankind has achieved a remarkable feat over the course of years in various fields of industrialization, transport, and medical facilities. The following development has led to massive growth in the trend of urbanization of the population. Majority of the urbanization goes unplanned and hence gives rise to various health-related problems. It has also paved way for increase in the air pollution due to increased transport and industrialization, which in turn has shown detrimental side effects on human health over time setting aside other effects on the environment. Respiratory morbidities attributed to air pollution are on the rise and it has also played an important role in the development of other noncommunicable diseases such as hypertension, myocardial infarction, and stroke among others.
Chronic obstructive pulmonary disease (COPD) is considered to be the fourth leading cause of death. The disease is characterized by persistent and usually progressive airflow limitation, which is not fully reversible, characterized by over-responsiveness of the airway to pollutants and other noxious particles. It includes three conditions namely emphysema, chronic bronchitis, and small airway disease. The common symptoms of COPD are breathlessness, cough with moderate-to-excessive sputum production, and the complaints of chronic duration. The main risk factors of COPD are (i) tobacco smoking which accounts for a majority of cases; (ii) indoor as well as outdoor air pollution; and (iii) occupational exposure to the dust, vapors, and fumes. According to the WHO, COPD has been accounting for 5% of total deaths worldwide and is estimated to become the third leading cause or 8.6% of deaths worldwide by 2030.[1,2] Besides causing morbidity, COPD causes a major economic burden on patients as well as the healthcare infrastructure of the country.
India is a developing country with a major burden of COPD having a prevalence of 4.3% in 2016 and with 75.6% of disability-adjusted life years (DALYs) among those due to chronic respiratory illnesses.[1,3] Along with China, India contributes to 66% of the total COPD mortality, which can be attributed to environmental pollution in the major cities of these 2 countries. Furthermore, the risk factors vary across the country because of variations in socio-demographic characteristics, cultural practices, behavioral habits, and ethnicities.
Delhi is one of the top-ranked cities for air pollution levels and many occupational groups are regularly exposed to the same. One of the important occupational groups at risk of COPD is auto rickshaw drivers. In low- and middle-income countries, auto rickshaws constitute an important medium of public transport as it is cheaper and convenient mode of transport in crowded urban areas. However, the drivers are constantly exposed to the environmental pollutants owing to open cabin. Furthermore, many studies have shown that the prevalence of tobacco smoking is high in this group. The auto drivers form an economically productive group in the society and also, they are the sole breadwinners of most of the families. They play a major role in the local public transport. There is a dearth of major studies carried out on auto rickshaw drivers showing the prevalence of COPD, especially in North India, hence this study reflects the burden of the same. To the best of our knowledge, this is the first study on COPD in auto rickshaw drivers of Delhi (can mention no study has been published in Delhi).
The aims and objectives of this study were as follows:
- To study the prevalence of COPD among auto rickshaw drivers of East Delhi
- To study the risk factors associated with COPD among the study subjects.
MATERIALS AND METHODS
Delhi, the capital city of India has a total of 11 districts. This cross-sectional study was carried out in the East district of Delhi in the Kalyanpuri circle. Data were collected from January to December 2019 in the Three-Seater Rickshaw (TSR) stands. The sample size was calculated based on a study by Stephen et al., wherein the prevalence of reduced peak expiratory flow rate (PEFR) was found to be 28%. Using the following formula:
N = (Z1-α/2) 2 × p × (1 − p)/E2
Where, Z1-α/2 = 1.96 (95% confidence interval)
P = 0.28 5
E = 0.056 (Relative error = 20% of p)
N = 257.14
After applying a design effect of 1.5, the sample size was calculated to be 385.5 and the final sample was rounded off to 400. Kalyanpuri circle which consists of 38 TSR stands was selected as the study area, out of which 10 TSR stands were selected by simple random sampling and 40 consecutive rickshaw drivers were selected per stand. A total of 409 auto rickshaw drivers aged 20–60 years, driving for a minimum of 3 years were involved in the study. Individuals with known heart diseases or chest deformities or those not giving consent were excluded from the study.
Every consecutive auto rickshaw driver was chosen from TSR stands of Kalyanpuri circle who fulfilled the inclusion and exclusion criteria. Written consent was taken and the details of the study were explained to the study participants and patient participation sheet was handed over. After receiving the consent, a self-designed, pretested, semi-structured interview schedule, Indian Study on Epidemiology of Asthma, Respiratory symptoms, and Chronic Bronchitis questionnaire was administered to the study subjects. It included the general demographic data, driving habits, behavioral habits, and questions about chronic respiratory complaints. A general physical examination was done which comprised anthropometry, blood pressure, pulse, SpO2, and other vitals. Height was measured using a portable stadiometer, weight using a digital weighing scale by health sense, SpO2 was measured using a digital pulse oximeter, and measuring tape was used for the measurement of chest circumference and chest expansion.
Respiratory system examination followed by spirometry was carried out in the field setup using separate, disposable mouthpieces made of cardboard material. The spirometer used was a turbine-based spirometer produced by Uni-Med India, with the software supplied along with the product. Prior training was taken for 2 weeks from a tertiary care hospital to carry out the spirometry. Predicted values of spirometry were based on Chhabra’s predicted values for North Indian males.
While conducting spirometry, the auto rickshaw drivers were made to sit comfortably and upright without back support to allow free expansion of the chest. A nose clip was applied and mouthpiece was placed in the mouth such that at least two-third was inside the mouth with pursed lips covering the whole mouthpiece without any gap and they were asked to lightly grasp the mouthpiece with their incisors. They were made to take a deep inspiration and blow forcefully into the mouthpiece for 6 s followed by deep inspiration again. The parameters that were done using spirometry were forced expiratory volume at first second (FEV1), forced vital capacity (FVC), PEFR, and FEV1/FVC ratio. The predicted values were preset in the spirometer software to the Indian standards. Individuals with FEV1/FVC <0.7 were called for follow-up spirometry measurement. The follow-up visit was carried out at Urban Health Centre, Kalyanpuri, which is a field practice area of the department of community medicine of a premier medical college of Delhi. The drivers were administered salbutamol and postbronchodilator PFT was carried out 15 min after administration. Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria were used for grading of COPD.
Before the commencement of the study, approval was taken from the institutional ethical committee. Data were entered and analysed in Statistical Package of Social Sciences (SPSS) Version 22 which is developed by International Business Machines (IBM) India in the year 2013. After data cleaning, mean and standard deviation (SD) was calculated for quantitative data, and proportions were calculated for qualitative data. Chi-square test, binary logistic, and multinomial logistic regression analysis were applied for qualitative data, and analysis of variance was applied for quantitative data. P < 0.05 was considered statistically significant.
The study included 409 auto rickshaw drivers aged 20–60 years, fulfilling the inclusion and exclusion criteria. Out of 441 drivers approached, 2 auto rickshaw drivers were excluded for having ischemic heart disease and 30 individuals did not give consent for the study with a nonresponse rate of 7.3%. Majority of the study subjects belonged to the age group of 31–40 years (43.8%), followed by 41–50 (34%). All of them were male. The mean age was 39 with SD of 7.54 years. The minimum age was 22 years and the maximum age was 59 years. Of 409 auto rickshaw drivers, 63% drove auto rickshaw for more than 10 years with mean years of driving being 14.92 years with SD of 7.489 years ranging from 3 to 40 years. Hour years of driving, obtained as a product of hours of driving, and years of driving were used for measuring the exposure. Forty-five percent of the auto drivers had 100–200 h years of driving, followed by 39.4% with <100 h years of driving. The mean hour years of driving was found to be 137 ± 75.1 years ranging from 18 to 480 h years.
Of the 409 auto rickshaw drivers studied, 56 (13.7%) of them were diagnosed with COPD by spirometry based on GOLD criteria [Table 1]. The need for postbronchodilator is based on the pre-bronchodilator value of FEV1/FVC ratio. When the value is less than 0.7, it would require repetition of spirometry after the administration of a bronchodilator to check for reversibility. One hundred and two (24.9%) individuals were found to have reduced FEV1/FVC ratio without bronchodilator. Eighty-eight (86.3%) of these subjects were followed up for postbronchodilator spirometry evaluation. Reversibility of postbronchodilator value (more than 12% increase in percentage predicted of FEV1) was seen in 32 out of 88 individuals who had come for follow-up. COPD is said to be present when the postbronchodilator value of FEV1/FVC ratio remains below 0.7. Out of those who had COPD, 16% had mild COPD, 64% had moderate COPD, 20% had severe COPD and all the cases were diagnosed by Chhabra’s lower limit of normal criteria for North Indian males. Severity was diagnosed as per GOLD criteria.
Among the risk factors, there was a significant association with the age of the study subjects (P = 0.001) and hour years of driving (P = 0.002) [Table 2]. There was no significant association found in the current study with smoking.
On binary logistic regression analysis, nighttime driving, less servings of fruits and vegetables, vegetarian diet, presence of obstructive, and restrictive pattern on spirometry were found to be significantly associated with the prevalence of COPD [Table 3]. On multinomial logistic regression analysis, higher age, higher hour years of driving, and presence of breathlessness were found to be significantly associated with prevalence of COPD [Table 4].
COPD causes irreversible damage to the lung parenchyma by destroying the elastic tissues, and hence affecting spontaneous recoil of the lungs during expiration. This, in turn, results in a condition of “air trapping,” where the expiration is not complete which further leads to increase in the lung size evident as increased lung fields on radiological imaging. COPD results in a great reduction in lung capacities hence affecting the ability of the affected person in carrying daily activities, causes significant mortal and morbidity and loss of DALYs.
The levels of pollution in the city of Delhi have steadily increased in the past few years resulting in increased risk of exposure, especially during winters. The study focused on the prevalence of COPD in auto rickshaw drivers of East Delhi as they are constantly exposed to risk factors such as environmental pollutants and tobacco smoke owing to their occupational exposure. Furthermore, the design of having an open cabin in an auto rickshaw and being a smaller than most other vehicles facilitate more exposure as compared to other close cabin or bigger vehicles. In the current study, which mainly focused on the prevalence of COPD among auto rickshaw drivers with grading of severity and finding an association with the known risk factors.
Among 409 study subjects that were included in the study, all were male with a mean age of the study subjects found to be 39 years (39 ± 7.54 years). This is comparable to the mean age of 40 ± 8.7 years in the study by Stephen P et al. and 36.5 ± 4.10 years in a study conducted by Farooque and Jayachandra. This also signifies the occupation was mainly taken up by males, and even though there are female auto rickshaw drivers females are involved in driving electrical rickshaws. The mean years of driving in the current study were 14.92 ± 7.489 years, ranging from 3 to 40 years. The mean years of driving are comparable to that found in the study by Stephen et al. (16 ± 8.3 years). Three out of five auto drivers (63.1%) in the current study drove for 10 years or more and the remaining (36.9%) drove for <10 years. Hour years of driving were also used as the measure of exposure to the environmental pollutants, which is the product of hours of driving and years of driving. The amount of exposure is directly proportional to hour years of driving which is more sensitive when compared to years of driving. Two hundred and thirty-seven drivers (57.9%) were driving between 101 and 300-h years of driving, and only 2.7% had >300-h years of exposure. Other studies that were reviewed did not use the parameter of hour years of driving as the measurement of exposure. Proper usage of masks is considered for their protection against the pollutants, as the auto-drivers are constantly exposed to environmental pollutants all through the driving hours owing to the open driver cabin. N95 masks which are snug-fitting and having a valves respirator, certified by NIOSH are advised for protect against the particulate matter. Still, only 7.3% of the rickshaw drivers were using face masks, predominantly cloth masks. The mask was worn occasionally in all, and this will not be overly protective against the pollutant levels in the environment. Even though N95 masks are better suited for polluted areas, high cost creates a barrier in buying and using the same.
COPD was diagnosed purely using a turbine-based Spirometer. The overall prevalence of COPD in the current study was 13.7% that is 56 out of 409 respondents. The diagnosis was made after administration of an inhalational bronchodilator and repeating the test after 15 min.
The risk factors considered in the current study were those mentioned in various literature as well as those that are rarely explored or have been predicted to have better outcomes in terms of respiratory health. Known risk factors assessed in the study were smoking, environmental smoke exposure, age, and presence of respiratory complaints. The genetic component which is alpha-1-antitrypsin deficiency was not assessed as they are out of scope of the current community-based study. There was a statistically significant association between the prevalence of COPD and with age groups of the study subjects (P = 0.001). Other studies in our review, though had not considered COPD diagnosis, statistically significant association was found between spirometric pattern and age in the study by Babu and Damodar, McKay et al. in their study noted the importance of advancing age in the development of COPD in their review article.[8,9] Similar association was found in Nag et al.’s study. The finding can be attributed to increased risk of development of COPD with increasing age, which progress decreases the elasticity of the lungs.[11–13]
While considering the driving habits of the study subjects, statistically significant association (P = 0.002) was seen in terms of hour years of driving, which can be considered as the better indicator of exposure to the environmental pollutants. Increase in hour years of driving also proportionately increases the risk of developing COPD as well by increasing the exposure to the pollutants. Increased hours of driving during the winters, when the pollution levels are high can also be a contributing factor needing further assessment.[14–17]
On binary logistic regression analysis, statistically significant association was found with the prevalence of COPD with consumption of <5 servings of fruits and vegetables per day (P = 0.011), as the high antioxidants in colored vegetables and fruits are known to prevent against the oxidative damage caused by the pollutants and cigarette smoke.[13,18,19] The presence of obstruction in spirometry had highly statistically significant association (P = 0.000), as obstruction precedes the development of COPD.[11,19,20] Furthermore, there was a significant association of prevalence of COPD with a restrictive pattern on spirometry (P = 0.013).
On multinomial logistic regression, the association of prevalence of COPD was statistically highly significant with the age group of 31–40 years (P = 0.000) and 41–50 years (P = 0.000) and statistically significant with the age group of 51–60 years (P = 0.023). Progressing age increases the odds of developing COPD, hence justifying the risk factor of advancing age in the development of COPD in various reviews and studies.[12,21,22] Statistically significant association was also found in higher hour years of driving, i.e., 201–300 h years of driving (P = 0.000) and more than 300 h years of driving (P = 0.05) and presence of breathlessness (P = 0.014). Various studies have shown the amount of exposure in terms of pollutant levels to be associated with increased prevalence of COPD.[13,16,18,23,24]
Hence, our study showed a higher prevalence of COPD among auto rickshaw drivers as compared to the general population of the same age groups. This can be attributed to years of driving and hence, the amount of pollutant exposure, signifying the impact air pollution can have on the health of certain occupation groups including auto rickshaw drivers.
CONCLUSION AND RECOMMENDATIONS
The prevalence of COPD was found to be 13.7% in our current study which is higher than the general population, forming an important occupational group which requires attention regarding respiratory health. Furthermore, the prevalence of COPD was found to be higher age groups. Most of them were having moderate COPD (64.3%) followed by severe and mild COPD (19.6% and 16.1%, respectively). The prevalence was found tone significantly increase with advancing age and longer years of driving.
Therefore, owing to the impact this sector has on public transport adequate attention should be given on respiratory morbidity among the cohort. Adequate policy designing regarding the health of the individuals in this unorganized sector with respect to cabin design, work hours, and usage of masks is also necessary. Further measures to reduce air pollution will have an impact on multiple sectors including the transport sector that requires constant exposure to ambient air.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
1. Global Health estimates:Deaths disability-adjusted life year (DALYs) years of life lost (YLL) and years lost due to disability (YLD) by cause age sex and member country 2000-2016 Geneva World Health Organisation (WHO) http://www.who.int/healthinfo/global_burden_disease/estimates/en/
last assessed on 15 March 2020 at 1500 hrs.
2. Kasper DL, Fauci AS, Hauser SL, Longo DL, Jameson JL, Loscalzo J. Harrison's principles of internal medicine 19th edition New York McGraw Hill 2015.
3. Chronic Respiratory diseases:Chronic obstructive pulmonary disease (COPD) Geneva WHO http://www.who.int/respiratory/copd/en/
[last assessed on 09 September 2018 at 1500 hrs].
4. Stephen P, Mahalakshmy T, Manju R, Laksham KB, Subramani S, Panda K, et al. High prevalence of chronic respiratory symptoms among autorickshaw drivers of urban Puducherry, South India. Indian J Occup Environ Med 2018;22:40–4.
5. Chhabra SK Interpretation of spirometry:Selection of predicted values and defining abnormality. Indian J Chest Dis Allied Sci 2015;57:91–105.
6. Global Initiative for Chronic Obstructive Lung Disease (GOLD). Pocket Guide for COPD Diagnosis, Management and Prevention 2017 Available from:https://goldcopd.org/wp-content/uploads/2016/12/wms-GOLD-2017-Pocket-Guide.pdf
[Last accessed on 2020 Jun 15, at 1400 hrs].
7. Farooque I, Jayachandra S Pulmonary function tests in nonsmoking auto rickshaw drivers. Al Ameen Journal of medical sciences 2014;7 (3) 240–243.
8. Babu VK, Damodar KS Effect of outdoor air pollution on pulmonary function of non-smoking auto-rickshaw drivers in Bangalore. Int J Clin Exp Physiol [serial online] 2017 [Last accessed on 2018 Sep 9] 4:30–3 Available at:https://go.gale.com/ps/ i.d o?p=AONE&u =googlescholar&id=GALE%7C A485630011 &v=2.1&it=r&sid=googleSch olar&a sid=f361b260
9. McKay AJ, Mahesh PA, Fordham JZ, Majeed A Prevalence of COPD in India:A systematic review. Prim Care Respir J 2012;21:313–21.
10. Nag A, Vyas H, Nag P Occupational health scenario of Indian informal sector. Ind Health 2016;54:377–85.
11. Koul PA Chronic obstructive pulmonary disease:Indian guidelines and the road ahead. Lung India 2013;30:175–7.
12. Gao W., Sanna M., Hefler M., Wen CP Air pollution is not “the new smoking”:comparing the disease burden of air pollution and smoking across the globe, 1990–2017. British Medical Journal 2020;29:715–18 Assessed from doi:10.1136/tobaccocontrol-2019-055181 (Last assessed on 20 June 2020 at 1730 hrs).
13. Jindal SK Indian Study on Epidemiology of Asthma, Respiratory symptoms and Chronic Bronchitis (INSEARCH):A Multi-centre study (2006-2009). Indian Council of Medical Research (ICMR) New Delhi 2013.
14. Wani RT Socioeconomic status scales-modified Kuppuswamy and Udai Pareekh's scale updated for 2019. J Family Med Prim Care 2019;8:1846–9.
15. Ajay KT, Vatsala AR, Prabhuraj, Sangam Comparative Study of PEFR between Auto Drivers with the Residents of Urban Davangere. India Journal of Pharmaceutical sciences and Research 2014;6 (5) 226–228.
16. Pramanik P, Ganguly NI, Chowdhury A, Ghosh B A study to assess the respiratory impairments among three wheeler auto taxi drivers. Int J Life Sci Pharma Res 2013;3:94–9.
17. Gavali S, Singh R, Kharche JS, Pranita A. Prevalence of Restrictive Lung Disorders in Auto Rickshaw Drivers Available from:http://themedicalacademy.in/fxconsult1/userfiles/5%20PREVALENCE%20OF%20RESTRICTIVE%20LUNG%20DISORDERS%20IN%20AUTO%20RICKSHAW%20.pdf
[Last accessed on 2018 Sep 09, at 1530 hrs].
18. Afroz A, Veeresh BS, Manjushree S, Amrutha SI A comparative study among the three wheeler automobile drivers on pulmonary function tests in adult males of Gulbarga city. Int J Med Res Health Sci 2013;2:35–9.
19. Bhome AB COPD in India:Iceberg or volcano?. J Thorac Dis 2012;4:298–309.
20. Kotaki K, Ikeda H, Fukuda T, Yuhei K, Yuki F, Kawasaki M, et al. Trends in the prevalence of COPD in elderly individuals in an air-polluted city in Japan:A cross-sectional study. Int J Chron Obstruct Pulmon Dis 2019;14:791–8.
21. Wang M, Aaron CP, Madrigano J, Hoffman EA, Angelini E, Yang J, et al. Association between long-term exposure to ambient air pollution and change in quantitatively assessed emphysema and lung function. JAMA 2019;322:546–56.
22. Yan P, Liu P, Lin R, Xiao K, Xie S, Wang K, et al. Effect of ambient air quality on exacerbation of COPD in patients and its potential mechanism. Int J Chron Obstruct Pulmon Dis 2019;14:1517–26.
23. Doiron D, de Hoogh K, Probst-Hensch N, Fortier I, Cai Y, De Matteis S, et al. Air pollution, lung function and COPD:Results from the population-based UK Biobank study. Eur Respir J 2019;54:1802140.
24. Dragonieri S, Lacedonia D, Scioscia G, Palladino GP, Quaranta VN, Carratù P, et al. Assessment of induced sputum cellularity in COPD patients belonging to two different classes of air pollution exposure. Arch Bronconeumol (Engl Ed) 2020;56:214–7.