Assessment of Risk Status for Coronary artery disease in Terms of selected risk factors among bus Drivers

 

Sr. Kanikkai Parvin¹, Dr. Devakirubai², Dr. Nalini Jeyavanth Santha³, Dr. G. Selvarani⁴

¹Post Graduate Student in Nursing, Sacred Heart Nursing College, Madurai–625020

²HOD and Professor, Department of Medical Surgical Nursing, Sacred Heart Nursing College, Madurai–20

³Principal, Sacred Heart Nursing College, Madurai–20

⁴Associate Professor of Cardiology, Madurai Medical College

 

ABSTRACT:

Background: Coronary Artery Disease (CAD) is a type of blood vessel disorder that is included in the general category of atherosclerosis. It is the leading cause of mortality accounting for more than half of all deaths resulting from NCDs. Among many occupations, bus drivers are known to be at high risk for developing cardiovascular diseases owing to sedentary life style, stress, incorrect dietary pattern, poor sleep etc., This study intended to assess the risk status for coronary artery disease among the bus drivers of Tamilnadu state transport corporation of Madurai district. Method: Quantitative research approach was adopted with the research design being non-experimental descriptive research design. Purposive sampling technique was used to select 200 bus drivers. Assessment of risk status was done using Coronary Artery Disease Risk Assessment Tool (CADRAT) and the techniques used were interview and biophysical measurements. Data was analyzed using descriptive and inferential statistics. Results: Among 200 drivers, 19% were overweight and 49% were obese; 46% had a waist circumference between 94 – 102 cm and 26% had > 102 cm; 24,5% were current smokers; 44% had the habit of consuming alcohol; 11% did not have the habit of performing exercise; 89.5% moderately healthy dietary pattern and 2% followed unhealthy dietary pattern; 72.5% were either moderately or severely stressful; 23.5% were diabetics; 33.5% had pre hypertension, 16.5% had stage I hypertension and 42.5% had isolated hypertension; and 11..5% had family of CAD. In terms of risk status, 71.5% had medium risk for CAD and 28.5% had high risk for CAD. Conclusion: The current study findings conclude that there is high prevalence of certain risk factors among bus drivers increasing their risk to develop CAD. There is a vast scope for modification of risk factors among the bus drivers that has the potential to alter the natural history of atherosclerosis and slow CAD progression.

 

 

 

INTRODUCTION:

Non-Communicable diseases (NCDs) are the leading cause of death. Annually 41 million people worldwide die from NCDs, including cancer, cerebrovascular disease, diabetes, respiratory diseases, and mental disorders. Approximately 85% of these deaths occur in Low- and Middle-Income Countries (LMICs) where 15 million people aged 30 to 69 die prematurely (World Health Organization, 2018). Non communicable diseases now account for more than one-half of the global burden of disease (Roth, 2016). The situation is no different in India and India’s burden of NCDs is also escalating. NCDs include cancers, cardiovascular diseases, respiratory diseases, diabetes and mental disorders. Cardiovascular Diseases (CVDs) are a group of disorders of the heart and blood vessels and includes coronary heart disease, cerebrovascular disease (stroke), raised blood pressure (hypertension.) peripheral artery disease, rheumatic heart disease, congenital disease and heart failure (WHO, 2012). Ischemic heart disease and stroke constitute the majority of CVD mortality in India and is significantly higher than the global average and is comparable to that of western industrialized countries. Together, IHD and stroke are responsible for more than one-fifth (21.1%) of all deaths and one-tenth of the years of life lost in India (Prabhakaran and Ajay, 2017).

 

Coronary artery disease is a type of blood vessel disorder that is included in the general category of atherosclerosis. The term arthrosclerosis comes from two Greek words, athere meaning “fatty mush”. And skleros meaning ‘hard’. The combination implies that atherosclerosis begins as soft deposits of fat that harden with age. Consequently, atherosclerosis is commonly referred to as “hardening of the arteries” (Linda and Johnson, 2015). Conventional risk factors for CAD have been extensively studied. Obesity, diabetes, hypertension, dyslipidemia, metabolic syndrome and smoking are all highly associated with CAD development (Ardeshna et al., 2017). The risk factors can be classified as either modifiable or non-modifiable. Modifiable risk factors are cigarette smoking, obesity, and hypertension, physical inactivity, diabetes mellitus, alcohol consumption, stress, elevated lower density lipoprotein (LDL), and reduced high density lipoprotein (HDL). Non modifiable risk factors are age, race, ethnicity and family history. Coronary artery disease affects millions of people world over (Chawhan and Aeri, 2013). India is seen as the diabetes and coronary artery disease capital of the world. According to current estimates, India will soon have the highest number of the heart disease cases in the world. (Mittal, Chowdhary, Arora and Jain 2017). Coronary artery disease is the largest killer disease in developed countries and is rapidly assuming a similar role in developing countries. The WHO has drawn attention to the fact that the coronary artery disease is our modern epidemic, not an unavoidable attribute of aging (Krishnan, 2016).

 

Among many occupations, bus drivers are known to be highly at risk of developing cardiovascular disease. Occupation is one of the established risk factors of cardio vascular diseases and death. (Yook, Lee, Kim and Hong, 2018). Workers in the transportation industry particularly drivers are at greater risk of an incorrect diet and sedentary behaviour. Obesity and hypertension are important risk factors for cardiovascular disease and is common among professional drivers. Increased trend of cardio vascular and cerebrovascular disease such as stroke in seen among professional drivers. Drivers employed in public or private transport industries who carry passengers are at greater risk than those who carry goods. (Udayar, Kumar, Kumar, Vairamuthu and Thakutu, 2015). The prevalence of CAD as well the risk factors of CAD is high in general population as proved by previous researches (Ardeshna et al., 2017; Krishnan, 2016). Not only in general population but similar statistics are found among bus drivers too (Yook, Lee, Kim and Hong, 2018; Singaravel and Kandasamy, 2017; Jeyarajah, Jeyakodi, Jeyanth and Wijeratne, 2017; Matto, Yates, Stencel, Biddle, and Clemes, 2015).

 

The WHO has recommended the following approaches for the primary prevention of chronic diseases where the risk factors are established: a) population strategy b) high risk strategy. High risk Strategy aims to bring preventive care to individuals at special risk. This requires detection of individuals at high risk by the optimum use of clinical methods (Park, 2017). Early identification of CAD may afford the opportunity for timely and aggressive risk factors, modification that has the potential to alter the natural history of atherosclerosis and slow CAD progression (Hansson, 2005).

 

STATEMENT OF THE PROBLEM:

A descriptive study to determine the risk status for coronary artery disease in terms of selected risk factors among bus drivers of Tamilnadu State Transport Corporation of Madurai District.

 

OBJECTIVES:

(i)         To assess the frequency of selected risk factors for coronary artery disease among bus drivers of Tamilnadu State Transport Corporation of Madurai District.

(ii)       To assess the risk status for coronary artery disease in terms of selected risk factors among bus drivers of Tamilnadu State Transport Corporation of Madurai District.

(iii)      To associate selected demographic variables of bus drivers with their risk status for Coronary Artery Disease.

 

CONCEPTUAL FRAME WORK:

The Conceptual framework for the current study is designed by the researcher after a wide literature review and is partly adopted from the conceptual framework of risk factors for the development of diabetes by Black (2002). The conceptual framework for the current study is termed as “Conceptual Framework on Assessment of Risk Status for CAD”. The key concepts of the conceptual framework are primary prevention, assessment of risk status for CAD, modifiable risk factors, non - modifiable risk factors and risk status for CAD.

 

RESEARCH METHODOLOGY:

 

 

Pilot study was conducted among 20 drivers. The main study was conducted for a period of five weeks after obtaining ethical committee clearance from the institution review board. The data was collected individually from each driver (which took approximately 45 minutes) using CADRAT after getting written informed consent. Data was collected from 8–10 drivers every day. After data collection, data were tabulated and analyzed using descriptive and inferential statistics according to the objectives of the study.

 

RESULTS OF THE STUDY:

Demographic description of the bus drivers:

Among 200 bus drivers 61% belongs to the age group of 40-50 years. Majority (98.5%) of the drivers were married. In terms of work experience, 36% of them had experience between 2-10 years of experience and whereas 31% had experience between 10-20 years and 20-30 years each. Majority (89%) of the drivers were driving town buses whereas 18% of the drivers were driving muffsal buses. Majority (88%) of the bus drivers had completed higher secondary education whereas 10% of the drivers had completed undergraduate and 2% of drivers had completed post graduate education. An overwhelming majority (98%) belonged to middle socio economic status and majority (99%) of them had social support.

 

Table – 1: Distribution of bus drivers based on BMI classification

N=200

S. No	BMI Classification	Frequency	Percentage
1	Under Weight (< 18.50)	2	1%
2	Normal (18.5 – 24.9)	62	31%
3	Over weight (25.0 – 29.9)	98	49%
4	Obese 1 (> 29.9)	38	19%
5	Obese 2	_	_

Table 1 depicts that a little less than half of them (49%) were overweight and 19% of them were classified as obese – 1. None of them were in obese – II classification.

 

Table -2: Distribution of bus drivers based on waist circumference classification N=200

S. No	Waist Circumference	Frequency	Percentage
1	Recommended (< 94cm)	56	28%
2	Increased Risk (94 – 102 cm)	92	46%
3	Greatest Risk (>102 cm)	52	26%

 

Table 2 portrays that a little less than half of them (46%) had a waist circumference 94- 102cm placing them at increased risk for CAD while 26% of bus drivers were in the greatest risk category with an abdominal girth of more than 102 cm.

 

Table – 3: Distribution of bus drivers based on their smoking habit N = 200

S. No	Smoking Habit	Frequency	Percentage
1	No	132	66%
2	Previous Smoker	19	9.5%
3	Yes	49	24.5%

 

Table 3depicts that nearly 2/3^rd of the bus drivers (66%) were non-smokers and 9.5% were former smokers; 24.5% were current smokers.

 

Table – 4: Distribution of bus drivers based on their habit of alcoholism N = 200

S.No.	Alcohol Consumption	Frequency	Percentage
1	No	112	56%
2	Yes	88	44%

 

Table 4 portrays that 44% of them had the habit of consuming alcohol.

 

Table -5: Distribution of bus drivers based on their pattern of physical exercise N = 200

S. No	Physical Exercise	Frequency	Percentage
1	No exercise	22	11. %
2	Moderate exercise / once / week	23	11.5%
3	Moderate exercise – 2-3 times a week	21	10.5%
4	Moderate exercise – 4-5 times a week	37	18.5%
5	Moderate exercise – 5 or more times a week	97	48.50%

 

Table 5 portrays that nearly half of them (48.50%) were doing moderate exercise for 5 or more times a week while 18.5% of them were doing moderate exercise for 4-5 times a week. In contrast, 11% (22 out of 200) did not have the habit of exercising at all.

 

Table -6: Distribution of bus drivers based on their dietary pattern N = 200

S.No.	Dietary pattern classification	Frequency	Percentage
1	Healthy dietary pattern (0-11)	18	9%
2	Moderately healthy dietary pattern (12-22)	179	89.5%
3	Un Healthy dietary pattern (23-32)	3	1.5%

 

Table 6 depicts that on over whelming majority (89.5%) of the bus drivers had moderately healthy dietary pattern whereas only 9% only had healthy dietary pattern. Out of 200, 3 (1.50%) of them had unhealthy dietary pattern in terms of CAD.

 

Table -7: Distribution of bus drivers based on their level of stress

N = 200

S. No	Level of Stress	Frequency	Percentage
1	Nil Stress (0)	1	0.5%
2	Mild Stress (1-16)	54	27%
3	Moderate Stress (17-32)	107	53.5%
4	Severe Stress (33-64)	38	19%

 

Table 7 portrays that nearly half of the bus drivers (53.5%) had moderate level of stress while 19% reported severe stress.

 

Table – 8: Distribution of bus drivers based on their medical history of diabetes                                                                     N = 200

S. No	History of DM	Frequency	Percentage
1	No Symptoms of DM	113	56.5%
2	Family History of DM	41	20.5%
3	Pre diabetes	1	0.5%
4	DM with dietary control	13	6.5%
5	On oral hypoglycemic agents	30	15%
6	Insulin	2	1%

 

Table 8 portrays that 23.5% were diabetics (45 out of 200) out of which 13 were under dietary control (6.50%), 30 (15%) were on oral hypoglycaemic agents and 2(1%) were on insulin. Out of 154, who did not have diabetes, 41(20.5%) had a family history of diabetes.

 

Table - 9: Distribution of bus drivers based on Blood Pressure classification

N = 200

S. No	Hypertension classification (mm of Hg)	Frequency	Percentage
1	Normal (90-119) / (60-79)	13	15.5%
2	Prehypertension (120-139) /(80-89)	67	33.5%
3	Stage -1 Hypertension (140-159)/ (90-99)	13	6.5%
4	Stage – II Hypertension > 160 />100	4	2%
5	Isolated hypertension > 1-140/ <90	85	42.5%

 

Table 9 depicts that only 15.5% (31 out of 200) had normal blood pressure reading and nearly one – third of the bus drivers (33.5%) had a BP reading suggestive of prehypertension. Out of 200, 13 (6.5%) of them had stage I Hypertension, 4 (2%) of them had Stage II hypertension and 85 (42.5%) of them had isolated hypertension. Out of 200, 5.5% is a known case of hypertensive.

 

Table -10: Distribution of bus drivers based on their risk status for CAD

N = 200

S. No	Risk status for CAD	No	Percentage
1.	Low risk (0-5)	0	0%
2.	Medium risk (6-18)	143	71.5 %
3.	High risk (19-45)	57	28.5%

 

Table 10 portrays that majority (71.5%) of the bus drivers had moderate risk for CAD while at high risk for CAD.

 

DISCUSSION:

The incidence and prevalence of patients with coronary artery disease in increasing world-wide and in India. In the current study the risk factors assessed for CAD were anthropometric measurements like height, weight, BMI and waist circumference, life style habits in terms of smoking, alcohol consumption and physical exercise, dietary pattern, level of stress, personal medical history (diabetes mellitus, hypertension) blood pressure measurement and family history of coronary artery disease. In the current study 49% (98/200) were overweight and 19% (38/10) were classified as obese I (Table No.1). A little less than half of them (46%) had a waist circumference of 94-102cm placing them at increased risk for CAD and 26% had abdominal girth of >102cm placing them at greatest risk for CAD (Table No.2). The markers of obesity, namely BMI, waist size and waist hip ratio have a positive relationship with major cardiovascular risk factors like hypertension, metabolic diseases like diabetes; while the waist hip ratio also correlates with dyslipidemia (Prasad, kabir, Dash, and Das, 2011).

 

In the current study one fourth of the bus drivers (24.5%) were smokers while 9.5% were previous smokers. Out of the 49 current smokers around 96% smoked anywhere between 1-10 cigars/day while 4% smoked between 11-20 cigars/ day. Literature clearly elucidates smoking as a major modifiable risk factor for CAD. A study by Dankar, Dey, Inamdar and Nanaware, (2014) conducted in Mumbai revealed that heavy smokers had a highly significant (p<0.001) increase in serum cholesterol levels than moderate smokers. Drinking alcohol is well known to be positively associated with the development of hypertension. Alcohol consumption is linearly related to increased blood pressure and the CVD risk also linearly increases according to blood pressure level. In the current study 44% (88/200) had the habit of consuming alcohol. Out of 88, 12 samples were consuming it for more than 10 years and the rest 66 for less than 10 years. Nearly 83% were consuming > 250ml/ drink with 4% taking alcohol daily and 18% consuming it weekly. and the current study finding closely parallels with the study conducted by Udayar et al., (2015) among transport drivers in rural area of Andhra Pradesh in which 56.96% were alcohol consumed per session was 175.30  68.39ml. According to WHO, lack of physical activity is a significant risk factor for non-communicable diseases including coronary artery disease (WHO, 2019). In the current study findings 11% did not have the habit of exercising at all placing them at greater risk for CAD while 11.5% had been exercising only once a week and 10.5% exercising 2-3 times a week placing them at risk for CAD than who had been exercising 4-5 times a week and 5 or more times a week. Driving as an occupation can best be described as a ‘compulsory sedentary occupation’ (Wong, 2014). Prolonged time sitting has been linked to increased risk of cardiovascular disease, cardiovascular mortality, all-cause mortality and diabetes, independent of leisure time physical activity (Wilmot, Edwardson and Achana, 2012).

 

An overwhelming majority (89.5%) of the samples followed a moderately healthy dietary pattern, with only 9% following healthy dietary pattern and 1.5% following unhealthy dietary pattern. Samples with unhealthy dietary pattern are at risk for developing CAD which is substantiated by a systematic review on association between dietary pattern and risk of cardiovascular disease. The results of the study found that the western dietary pattern was associated with an increased risk of dyslipidemia (Chiswell et al., 2016). In the current study 19% of the samples reported severe stress while 53.5% reported moderated stress. The role of work stress on CAD is supported by a review of evidence from 27 cohort studies which suggest that work stressors such as job strain and long working hours, are associated with a moderately elevated risk of incident coronary heart disease and stroke. The excess risk for exposed individuals is 10-40% compared with those fear of such stressors (Pop, Manea, trambitasu, Matei and Mos, 2015). In the current study 23.5% were diabetics as elicited via self-report. Evidence from literature review clearly portray that among adults with diabetes mellitus, there is a prevalence of 75% to 85% of hypertension, 10% to 80% for elevated LDL, and 60% to 70% for obesity. Diabetes mellitus is associated with a 2-4 fold increased mortality risk from heart disease. The findings related to prevalence of diabetes were heterogenic in 2 studies conducted among bus drivers (Shin et al., (2013), Jeyarajah et al., (2016). In one study, the prevalence was 8.2% and in the other it was 49.9% and the current findings are midway between the two studies. Based on the BP level, 33.33% were pre hypertensives, 6.3% were with Stage I hypertension, 2% were with stage II hypertension, and 42.5% were with isolated hypertension. Hypertension is a major risk factor for coronary artery disease. Among the numerous risk factors associated with CHD, hypertension plays a major role given its high frequency and its physiopathogenesis. Mixed findings were noted in two researches conducted among bus drivers (Shin et al., (2013), Jeyarajah, et al., (2016). when compared to the current study findings. In the current study 42.5% were found to have isolated hypertension

 

Numerous epidemiologic studies have shown that isolated systolic hypertension is independently associated with future cardiovascular events. (Antikainen, Jousilahti andTolomilehto; Wilking and Belanger (as cited in Bavishi, Goel and Messerli (2016). It is estimated that 50% of the etiopathogenesis of coronary artery disease may be explained by genetic factors. The family history or premature CAD has been used as an equivalent marker of genetic predisposition for CAD (Pereira et al., 2017).

 

In the current study, 11.5% (23/200) of them had a family history of CAD. In the current study, majority 71.5% had a medium risk for CAD while 28.5% had a high risk for CAD. None of them fell into the low risk category. Previous researches done by Shin et al., (2013) and Udayar et al., (2015) support the present study findings. Driving being a ‘compulsory sedentary occupation’ puts them at high risk for CAD. The high prevalence of risk factors identified among bus drivers in the current study points to the fact that addressing the modifiable risk factors in this group is the key for prevention of CAD. The prophylactic measures must be dealt with collectively because there is overwhelming evidence that the occurrence of CVDs can be reduced by approximately 80% by making lifestyle modifications. The preventive strategies against CVDs must be targeted at a primary health promotion level before some of the approaches would help in reducing not only employee absenteeism but also the hospital and drug costs burdening the health care systems of both developed and developing countries (Buttar and Ravi, 2005).

 

CONCLUSION:

The present study determined the risk status for coronary artery disease interms of selected risk factors. The findings bring to light the various risk factors and the most prevalent ones in descending order are: moderately healthy diet pattern (89.5%), hypertension 84.5% [stage I or II hypertension (8.5%), pre hypertension (33.50%), isolated hypertension (42.5%),moderate or severe stress (72.5%), obesity (68%), abdominal obesity (72%), alcoholism (44%), smoking (24.5%), diabetes (23.5%) or non-engagement in physical exercise (11%), family history of CAD (11.5%). In terms of risk status, 28.5% were at high risk and 71.5% were at medium risk for development of CAD. Given the high prevalence of risk factors among bus drivers it is mandatory to create awareness on early identification of CAD and life style modification. With the dramatic increase in the prevalence of CVD world-wide and in India, the current study findings has huge implication for nurses practicing in the hospitals and community settings.

 

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Received on 03.03.2020          Modified on 24.03.2020

Accepted on 12.04.2020      ©AandV Publications All right reserved