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Determinants of respiratory and cardiovascular health impacts of traffic

policemen: A perception based comparative analysisNishitha Bajaja, Tanya Sharmaa, Dimpy Sunejaa, Suresh Jaina, b, c1, Prashant Kumarc, d

aDepartment of Natural Resources, TERI University, Delhi, 10, Institutional Area, Vasant Kunj, New Delhi 110070, IndiabDepartment of Energy and Environment, TERI University, Delhi, 10, Institutional Area, Vasant Kunj, New Delhi 110070, IndiacDepartment of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United KingdomdEnvironmental Flow (EnFlo) Research Centre, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom

Abstract

This study investigates the determining factors behind the adverse health effects of traffic policemen in National Capital Territory (NCT) of Delhi. A comparative analysis between 532 traffic policemen (subject population) and 150 office workers (control group) was undertaken to study the prevalence of disease. A primary survey was conducted over a period of six months between July 2015 and February 2016 using a questionnaire survey as a primary tool. A significantly higher (p = 0.005) prevalence rate of respiratory and cardiovascular diseases was observed among traffic policemen compared with the control group. Symptoms such as thick sputum, pain in joints, and shortness of breath were prevalent in approximately 59%, 56%, and 45% of subjects, as compared to about 15%, 11% and 6% of the control population. The relative risk of developing respiratory and cardiovascular diseases was found to be significantly higher (RR>1) for the traffic policemen in comparison to the office workers (control group). This is a first cross-sectional study to highlight the plight of traffic policemen in the NCT region of Delhi. The influence of factors such as Body Mass Index (BMI), age, habits (smoking and alcohol consumption) and service duration on disease prevalence was assessed among traffic policemen using statistical tests. The service duration was found to be the most important determinant compared with other influencing factors such as BMI, age, which is significantly (p = 0.02) affecting the health of traffic policemen in the current study. A number of potential measures for improving the health conditions of traffic policemen are also discussed.

Keywords: Traffic policemen vs. office workers; Prevalence rate; Relative Risk; Health survey;

Health symptoms due to traffic-related air pollution

1Corresponding author, Department of Natural Resources, TERI University, 10, Institutional Area, Vasant Kunj, New Delhi-110070, India; Tel: +91-11-7180 0222; Fax: +91-11-2612 2874; Email: sureshjain_in@yahoo.com; sureshj@teri.res.in

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1. Introduction

Air pollution is a major global concern due to its possible cause of adverse effects on the

environment and human health (Aggarwal and Jain, 2015; Carugno et al., 2016; Phung et al., 2016;

Woodward and Levine, 2016; Jain and Khare, 2010). Numerous studies have reported an

association between air pollution and increased rates of mortality and morbidity among exposed

populations (Kumar et al., 2011; Evans et al., 2012; Hamra et al., 2014; Aggarwal and Jain, 2015;

Yorifuji et al., 2015; Nieuwenhuijsen et al., 2016; Woodward and Levine, 2016). Air pollution is

ranked as one of the ten major factors causing the global health burden (Lim et al., 2012).

Furthermore, it has also been estimated that ambient air pollution was responsible for over 3.7

million premature deaths globally in the year 2012 (WHO, 2014). In India, air pollution has been

ranked as the fifth largest health risk that was responsible for nearly 620,000 deaths and 18 million

healthy life years lost in 2010 (GBD, 2010). A significant increase in motorised vehicular density

in urban areas worldwide can be considered as a major cause for the increased concentration of air

pollutants in the ambient environment (Kumar et al., 2014; Jain et al., 2016).

With a metropolitan population of 16.78 million in 2011, Delhi has been ranked as the

second most densely populated urban agglomeration in India (Census of India, 2011). The

population of Delhi has experienced a shift in its travel preferences from public transport to

majorly private transport, which is also reflected in a significant increase in the number of

registered vehicles in the city (Khanna et al., 2011; Jain et al., 2014; Jain et al., 2016; Nagpure et

al., 2016). With a compound annual growth rate of 7.1% for the number of registered motor

vehicles during 2002-2012, Delhi is ranked fifth among other Indian cities for having the largest

number of registered motor vehicles. According to the Transport Department, Government of

National Capital Territory (GNCT) of Delhi, the total number of registered vehicles in the year

2013-2014 were nearly 8.82 million (GNCTD, 2014).

Since the road length in Delhi has not increased proportionately, the carrying capacity of

the roads are at saturation level. This has led to road congestion as well as a decrease in average

travel speed (RITES, 2010). An increased shift to motorised personal vehicles, instead of using

public transport, has significantly contributed to increased concentration of air pollutants in the

city (Sharma et al., 2013; Kumar et al., 2013, 2015; Aggarwal and Jain, 2015, 2016). The

degradation of air quality in the city can be attributed to several factors such as an increase in

vehicular density, construction sites, roadside dust as well as biomass and refuse waste burning

(Kumar et al., 2015). 2

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The increasing levels of air pollutants are responsible for a higher incidence rate of

cardiovascular and pulmonary diseases as compared with previously in the city's history (Jain et

al., 2015; Lim et al., 2012). Numerous studies have reported that both the long- and short-term

exposures to air pollutants cause respiratory morbidity (Brunekreef and Holgate, 2002; Gauderman

et al., 2007; Anderson et al., 2012; Hoek et al., 2013; WHO, 2013; Feng et al., 2016; Phung et al.,

2016; Zhang et al., 2016). Vehicular emissions are attributed to be one of the major factors for

elevated air pollutant levels as they exhibit small-scale spatial variation with high accumulation in

a confined area (Sharma et al., 2013; Kumar et al., 2013, 2014). Thus, vehicular emissions are a

potential threat to the road-users as well as people who are in proximity to the roads. Road users

such as pedestrians and cyclists are exposed to a relatively higher concentration of air pollutants as

compared to individuals working in closed environments (Hoek et al., 2002; Zuurbier et al., 2011;

Goel and Kumar, 2015, 2016). One such group is the traffic policemen who, due to the nature of

their occupation, spend around 8-10 hours near roads and road intersections. A number of studies

have found that the health of traffic policemen deteriorates with time during their service periods

(Alhawat and Shukla, 2010; Pal et al., 2010; Pramila and Girija, 2013). Past work has also reported

that traffic policemen are likely to have a higher prevalence of cough, expectoration, nasal

irritation and rhinosinusitis compared with the unexposed population (Parlewar et al., 2012;

Estévez-García et al., 2013). However, the studies published in the literature have been performed

with a relatively small sample size. Moreover, most of these studies have employed odds ratio as

an epidemiological tool to explain the disease prevalence among exposed population. Thus, in

order to bridge these gaps, the current study has taken into account the perception of 532 traffic

policemen to understand the correlation between environmental exposure and prevalence of

disease. Furthermore, this study has also calculated the relative risk rather than odds ratio, as a

novel approach to delineate the increased impacts on the subject population and is the first cross-

sectional study undertaken specifically for traffic policemen in NCT of Delhi. Therefore, the aim

of this work is to analyze the determining factors that can be attributed to increased health risk of

traffic policemen in the NCT of Delhi. We carried out extensive questionnaire-based field surveys

in the study region to create a new database about the health issues in the subject population.

2. Methodology

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Figure 1 presents the overall framework used to conduct this study. We took a perception

based comparative approach to assess the influence of different factors that affect the health of the

subject (traffic policemen) and control (office workers) population. The analysis was performed

based on the perception of subject and control population. No medical tests were performed during

interviews with respondents.

2.1. Study area and data collection

The study is confined to Delhi NCT region. Delhi (Latitude 28o61’N, Longitude 77o23’E)

has a surface area of 1483 km2 with the highest road density of 2,103 km/100 km2 in India. The

city is highly dependent upon the road based transportation modes and had a road network of

33,198 km in 2013 (GNCTD, 2014). The data related to respiratory and cardiovascular health

status of traffic policemen was collected using personal interviews. Data was also collected for a

group of people working in a controlled environment but with similar socio-economic status and

age group as the subjects. The control group was selected so as to differentiate the level of

exposure to vehicular emissions with respect to the subject population, and hence analyse the

prevalence of diseases. A questionnaire was designed to extract information about the personal

identity, lifestyle, habits (smoking and alcohol consumption), employment history, working hours,

prior occupational exposure and health status of the respondents. It was first pilot-tested by

interviewing 20 traffic personnel. The sample size was estimated using methodology proposed by

National Statistical Survey, 2015 (with 5% margin of error) using a population size of the subject

population from Delhi Traffic Police data as in October 2014. A total of 532 traffic policemen,

along with 150 control group respondents were interviewed over a period of six months from July

to September 2015 and from January to February 2016. Stratified random sampling technique was

adopted to collect data from 11 traffic circles in the NCT of Delhi, and included 70 locations

across the city (Figure 2).

2.2. Statistical analysis

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Statistical analysis of data was carried out using Minitab 14.0 and Microsoft Excel 2013

(Data analysis tool). The influential parameters identified during the study were analysed using

correlation and regression analysis, and hypothesis testing. Many authors have employed statistical

tools such as regression analysis and tested their hypotheseses to evaluate the correlation between

prevalence of disease and environmental exposures. Regression analysis has been successfully

used for various applications in the literature (Valipour, 2014a,b, 2015). Multivariate analysis has

been recognized as one of the important tools to justify the variations in disease prevalence

(dependent variable) with determinants (independent variables) (Pal et al., 20010; Anbazhagan et

al., 2010; Majumder et al., 2012; Estévez-García et al., 2013; Lewis and Ward, 2013).

2.2.1. Correlation and Regression Analysis

The dependence of prevalence of disease or disease symptoms on age, Body Mass Index

(BMI) and service duration among the subject and control population was evaluated on the basis of

the correlation coefficient (R). The value of R lies between –1 and 1, which explains the strength

of linear association between dependent and independent variables.

2.2.2. Hypothesis Testing

The difference in prevalence of disease symptoms in our subjects and control population

was analysed using hypothesis testing for difference of means using two-sample t-test. Further,

this test was also used to analyse the effect of smoking and alcohol consumption habits on disease

prevalence in respondents. Based on the responses obtained during the survey, the subject and

control population were divided into the following sub-categories: smoking and non-smoking, and

consumers and non-consumers of alcohol. We have tested difference of means between smoking

vs. non-smoking traffic policemen (Hypothesis A1); smoking vs. non-smoking control group

(Hypothesis A2); traffic policemen vs. control group with smoking habits (Hypothesis A3) and

traffic policemen vs. control group with non-smoking habits (Hypothesis A4). We have further

tested difference of means between alcoholic vs. non-alcoholic traffic policemen (Hypothesis B1);

alcoholic vs. non-alcoholic control group (Hypothesis B2); traffic policemen vs. control group

with alcoholic habits (Hypothesis B3) and traffic policemen vs. control group with non-alcoholic

habits (Hypothesis B4) as presented in Table S2 and S3. The null hypothesis for t-test stated that

there is no difference between the means of the prevalence of disease or disease symptom (i.e., d =

0) of the two populations considered for analysis (H0: µ1 = µ2; H1: µ1 ≠ µ2).

2.2.3. Relative Risk

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Relative Risk or Relative Ratio (RR) is the ratio of the probability of an event occurring in

an exposed group to the probability of the event occurring in an unexposed group. A value of RR

greater than 1 indicates that the exposed group is at a higher risk of developing a disease as

compared to the unexposed group.

3. Results and Discussions

3.1. Respiratory and cardiovascular problems in traffic policemen

The general characteristics and prevalence rate of respiratory and cardiovascular problems

in traffic policemen and control population are presented in Table 1. The analysis revealed that

traffic policemen had a greater prevalence of various health ailments. For instance, 59%, 56% and

45% of the subject population complained of thick sputum, pain in joints and shortness of breath,

respectively, as opposed to only 15%, 11% and 6% of the control population. A similar trend was

observed in the case of coughing with a little amount of blood. This symptom was prevalent in

26% of the subject population while none of the respondents from control population complained

about it. Ahlawat and Shukla (2010) reported similar findings that the traffic policemen are at a

higher health risk in comparison to the control group. They observed a higher prevalence of

coughing, shortness of breath and chest pain in the subject population as compared to control

group in their study conducted in Rohtak city (Haryana, India). Similar results have been reported

by Estévez-García et al. (2013) in traffic policemen due to personal exposures to PM10 working in

the metropolitan area of Bogata in Columbia.

3.2. Analysis of Influencing Factors

3.2.1. Service duration, BMI, and Age

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The dependence of disease prevalence in the subject population was found to be significant

for the variable, service duration (p = 0.02). The value of R (0.93) obtained for BMI revealed that

even though BMI is an important variable in determining the prevalence of disease or disease

symptoms in the study population, yet it cannot be considered in the study due to low confidence

level indicated by its p-value as 0.22. Moreover, the relationship between the prevalence of disease

or disease symptoms and BMI is not significant in the case of the control group. Thus, BMI cannot

be considered as an influential variable for the subject population. Similar results have been

reported by Shrestha et al. (2015) in Kathmandu valley, Nepal. They observed that the service

duration had a larger impact on the respiratory and cardiovascular health of traffic policemen

posted on traffic duty in the study region as compared to their control group. They further reported

a significant decrease in spirometric parameters such as Peak Expiratory Flow Rate (PEFR),

Forced Expiratory Flow (FEF, 25%-75%), FEF 25%, FEF 50%, and FEF 75% among the subject

population.

Analysis of the relationship between age of respondents and prevalence of disease or

disease symptoms revealed that the influence of age is not a significant factor owing to the lower

value of R in the case of traffic policemen (R = 0.54) and higher p-value (0.49) in the case of

control group. Hence, it can be concluded that traffic policemen are at a higher risk of respiratory

and cardiovascular diseases due to higher exposure to air pollutants, mainly traffic-induced

emissions during their duty hours. A similar study conducted by Devi et al. (2009) in Hyderabad

showed the genotoxic effect of vehicular exhaust on traffic policemen. They reported that the

frequency of chromosomal aberration increased among the subject population with an increase in

exposure duration. Their study further validates the fact that service duration has a significant

contribution in determining the health status of traffic policemen. In our case, we found an

abnormal decrease in the prevalence of diseases or disease symptoms in subjects that were over 50

years of age, which may be attributed to a low number of respondents for this sub-category.

3.2.2. Effect of smoking and alcohol habits on health

The results of hypothesis testing used to analyse the impact of smoking and alcohol

consumption habits on disease prevalence among the subject and control population have been

summarised in Supplementary Information (SI) Tables S2 and S3.

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Within-Group Analysis: The results of hypothesis testing for prevalence disease or disease

symptoms in the case of the subject population: smokers versus non-smokers as well as consumers

and non-consumers of alcohol showed that the null hypothesis is rejected in both the cases. This

indicates that there exists a significant difference in disease prevalence among these groups. From

the statistical evidence, it can also be interpreted that the subject population (i.e., traffic policemen)

is at a higher risk of developing respiratory and cardiovascular diseases as compared to the control

population. However, when a similar comparison was done between control population (i.e.,

smokers versus non-smokers, and consumers versus non-consumers of alcohol), the null

hypothesis was accepted. Acceptance of null hypothesis indicates that there is no significant

difference in disease prevalence among the control population. These observations show that

smoking and alcohol habits do not significantly affect the prevalence of disease or disease

symptoms considered in this work.

Between Group Analysis: The results of hypothesis testing for disease prevalence in the case of

smoking population (i.e., subject versus control, and consumers of alcohol: subject versus control)

showed that null hypothesis is rejected in both the cases. Similar results were obtained when a

comparison was made between non-smoking and non-consumers of alcohol: subject versus control

population. The rejection of null hypothesis in all these cases reveals that traffic policemen are

more prone to developing respiratory and cardiovascular diseases compared with our control

population. Moreover, it was also concluded that traffic policemen who engage in the consumption

of alcohol and smoke tobacco are at a higher risk than those who refrain from these habits (Figures

3a-b). Pal et al. (2010) analyzed the influence of smoking habits on the respiratory health status of

traffic policemen using spirometric tests. Their study also revealed a significant decline in

respiratory health status of the subject population who smoke tobacco compared with their control

population.) A similar study in Tirupati, Andhra Pradesh (India) evaluated pulmonary function

tests that were performed on 50 non-smoking traffic policemen and 50 individuals working in a

controlled environment (Sayyad et al., 2013). They reported that there was a significant decrease

in forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEF 25%-75%, FEF

75%-85% and peak expiratory flow (PEF) in the subject population compared with their control

population.

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Our primary survey revealed that traffic policemen spent about 8-10 hours of the day on-

road. They are exposed to traffic-related emissions of varying intensities during their service

duration. Since service duration is concluded to be an influential variable for disease prevalence,

Figure 4 was plotted to show a correlation between the service duration of traffic policemen (i.e.,

the number of years spent on-duty) and the prevalence of disease or disease symptoms. The rate of

increase in the frequency of disease occurrence is rather low for respondents with service duration

up to 3 years. However, a sudden increase can be observed from service duration of 2-3 years to

that of 3-4 years. This can be attributed to the increase in duration of exposure to traffic and traffic

induced emissions (Figure 4). However, a decline in the prevalence of disease or disease

symptoms was observed in the case of a subject population that served for more than 5 years. This

may be attributed to a relatively lower number of respondents in this sub-category since there

occurs a shift in the duties of traffic policemen from on-road patrolling to other departments of

Delhi police. These results are in agreement with other studies discussed in previous sections

(Uzma et. al., 2008; Devi et. al., 2009; Pal et. al., 2010; Estévez-García et. al., 2013; Sayyad et. al.,

2013; Shrestha et. al., 2015).

3.3. Relative Risk

Table 2 shows the values of RR calculated for various respiratory and cardiovascular

diseases. The values of RR were found to be greater than 1 for every disease, except tuberculosis,

indicating that traffic policemen are at a higher risk of developing respiratory and cardiovascular

diseases than the control group. The RR values showed a greater health risk in traffic policemen in

terms of various problems like shortness of breath, wheezing, pain in joint, allergic reactions, etc. as

compared with the control group.

3.4. Measures to reduce the health risk to subject population

Considering the results of this study, it is necessary to take effective measures to decrease

the effect of air pollution on this affected group. A number of measures can be adopted to reduce

impact of traffic-induced emissions on the health of traffic policemen:

Compulsory use of protective equipment such as the nose mask and eyeglasses during their

duty hours to protect them from vehicular emissions (Gupta et al., 2011).

Regular health check-ups of traffic policemen and providing health education to traffic

police and their families to ensure adequate health facilities to traffic policemen and their

families. (Gupta et al., 2011).

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Timely transfer of traffic policemen to avoid their duties in heavy traffic zones for an

extended duration.

Providing renewable energy powered booths at their workplace to provide basic amenities

such as fan, light source, cordless mike, and provision for charging the wireless handset,

first aid box etc. during duty hours.

Pollution hazard allowance (i.e., incentivize with additional allowance in salary) to

compensate for unhealthy working conditions provided to traffic policemen. This is a

relatively new concept in India and has been initiated in some states (e.g., Telangana and

Mumbai) where an increase up to 30% in the salary of traffic policemen is applied. This

measure may encourage policemen to prefer traffic duties for additional allowance;

therefore, it is important to adopt a proper mechanism to avoid exploitation of resources at

the cost of health damage.

A few measures have already been implemented in India, though a number of inexplicable factors

contribute to their ineffectiveness. Therefore, it is imperative for the officials concerned with the

planning of interventions to develop cost-effective strategies that can reduce the health burden

among traffic policemen due to air pollution exposure.

4. Summary and Conclusions

Delhi has seen a radical increase in the number of registered vehicles, which has resulted in

increased emissions and poor air quality in the city. Due to their occupation, traffic policemen are

exposed to toxic air pollutants that have deteriorating impacts on their health. The current study

has evaluated the factors that influence the respiratory and cardiovascular health of traffic

policemen by using a perception based comparative analysis approach.

Our analysis shows that there is a higher prevalence of respiratory and cardiovascular

diseases in the traffic policemen compared with the control population. Furthermore, it was found

that disease prevalence among the subject population is directly related to service duration rather

than factors such as smoking and alcohol habits, BMI and age. The prevalence of disease or

disease symptoms per policeman showed an increasing trend with service duration. The RR values

(RR>1) also showed a high risk to traffic policemen’s health in terms of various problems like

shortness of breath, wheezing, pain in joint, allergic reactions, etc., compared with the control

group. Further, service duration was found to be the most important determinant which was found

to significantly affect the health of traffic policemen (p = 0.02) compared with other influencing

factors such as BMI and age. 10

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The measures suggested under this study show that there is a broad scope of reducing

health risk on the subject population by merely improving and implementing traffic management

strategies. Thus, the current study emphasises the importance of understanding the plight of this

vulnerable group and undertaking suitable actions to reduce their health risks. However, authors

would like to mention the importance of medical examination/tests to confirm the health risk in

traffic policemen for better informed decision making as no medical examination has been

conducted in the current study.

Acknowledgements

The authors greatly acknowledge the Society for Environmental Awareness and Research

(SEAR), New Delhi for their assistance in conducting the field survey and providing other

infrastructure supports. We would also like to acknowledge the support from all the students who

had contributed to data collection during the questionnaire surveys. Both SJ and PK thank the

Commonwealth Scholarship Commission for the Commonwealth Professional Fellowship that

allowed SJ to work at the University of Surrey, UK. The authors gratefully acknowledge the

cooperation of Mr. Neeraj Sharma for editorial assistance. The editors and anonymous referees are

gratefully acknowledged.

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List of Figure Captions

Figure 1: Framework for health risk assessment of traffic policemen

Figure 2: Delhi map with coordinates of survey locations

Figure 3(a): Comparison of prevalence of diseases or disease symptoms in smoking and non-smoking subject and control population

Figure 3(b): Comparison of prevalence of diseases or disease symptoms in alcohol consumers and non-consumers- subject and control population

Figure 4: Prevalence of disease or disease symptoms as a function of service duration of subject population

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Figure 1: Framework for health risk assessment of traffic policemen

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Figure 2: Delhi map with coordinates of survey locations

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Diabete

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Emphys

ema

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d Pres

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s0

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80Smoking Population Subject Control

Res

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)

Health endpoint/Diseases

Diabete

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(skin

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Odo

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Emphys

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Shortn

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80Non-smoking Population Subject Control

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)

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Figure 3(a): Comparison of prevalence of diseases or disease symptoms in smoking and non-smoking subject and control population

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Diabete

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Figure 3(b): Comparison of prevalence of diseases or disease symptoms in alcohol consumers and non-consumers- subject and control population

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0-1 1-2 2-3 3-4 4-50

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f(x) = 0.674 x + 2.246R² = 0.867455431478285

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s per

per

son

Figure 4: Prevalence of disease or disease symptoms as a function of service duration of subject population

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List of Table Captions

Table 1: General characteristics and symptoms of various problems in traffic policemen

Table 2: Relative Risk Ratio for prevalence of diseases or disease symptoms in subject and control

population

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Table 1: General characteristics and disease or disease symptoms of various problems in traffic

policemen

Parameter Traffic Policemen Control

Number of respondents 532 150Age (yr) 37 ± 8 (22-55) 39 ± 13 (24-54)Height (cm) 176 ± 6.4 (152-188) 172 ± 7.36 (166-184)Weight (kg) 77 ± 7.7 (52-91) 72 ± 8.4 (50-87)BMI 25 ± 2.6 (17-36) 25 ± 3.2 (17-35)Service Duration (yr) 0.0-0.50.5-1.01.0-1.51.5-2.02.0-2.52.5-3.03.0-3.53.5-4.04.0-4.54.5-5.0

4412456

10270563628610

N.A.

Smoking Habit 30% 47%Alcohol Habit 21.8% 32%Diseases or disease symptoms Prevalence Rate (in %) Prevalence Rate (in %)

DiabetesAllergic reactions (skin)Trouble in smelling odorsEmphysemaTuberculosisShortness of breath Wheezing Thick sputumBlood, while coughingChest painHigh Blood PressureCholesterolBody Ache/ Pain in Joints

7%50%56%0.5%2%

45%50%59%26%10%14%5%

56%

3.3 %16%6.7%

--8%6%

1.3%14.7%

--4%

16%1.3%

10.7%

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Table 2: Relative Risk Ratio for prevalence of diseases or disease symptoms in subject and control population

Diseases or disease symptoms Relative Risk

Diabetes 1.97

Allergic Reactions (skin) 3.10

Trouble Smelling Odors 8.34

Emphysema Not Defined

Tuberculosis 0.28

Shortness of Breath 7.58

Wheezing 37.5

Thick Sputum 4.04

Blood, while Coughing Not Defined

Chest Pain 2.53

High Blood Pressure 0.89

Cholesterol 3.66

Body Ache/ Pain in Joints 5.26

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