Assessment of Occupational Stress Index and Lipid Profile among Professional Drivers in Ismailia City, Egypt ^†

Abstract

Background: Driving is a stressful job. Professional drivers are high risk group for occupational stress. Occupational stress has been associated with abnormal levels of lipids. However, many studies could not find any association. Aim and Objectives: The study aimed at contributing to improving the professional drivers' health through assessing occupational stress, lipid profile and their association. Subjects and Methods: It was a cross-sectional study conducted at Suez Canal Authority in Ismailia City, Egypt, including 131 professional drivers. A structured interview questionnaire was used to assess occupational stress index (OSI) and cardiovascular risk factors. Lipid profile in form of cholesterol, triglyceride, low density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were assessed. Results: The total OSI score was 79.98 ± 6.14. The prevalence of dyslipidemia was 79.4%, 51.9% of drivers had hypercholesterolemia, 37.4% had hypertriglyceridemia, 50.4% had high level of LDL-C, and 45% had low level of HDL-C. The total OSI score and OSI aspects did not have statistically significant relationship with dyslipidemia. The high demand aspect score of OSI had statistically significant relationship with hypercholesterolemia. The conflict aspect had statistically significant relationship with high LDL-C. The noxious exposure and conflict aspects of OSI had weak positive significant correlations with cholesterol level (r = 0.163, 0.162 respectively). A weak positive significant correlation (r = 0.149) was found between noxious exposure aspect score and LDL-C level. Binary logistic regression analysis was conducted to assess independent risk factors of dyslipidemia. The model included aspects of OSI, total OSI score, driving hours a day, smoking status, passive smoking, body mass index (BMI) and dietary habits. It identified conflict aspect of OSI, driving hours a day, and BMI as predictors of dyslipidemia. Conclusion: Professional drivers are exposed to occupational stress, and dyslipidemia is prevalent among them. Total OSI score does not have statistically significant relationship with dyslipidemia. However, certain aspects of OSI have significant relationship with abnormal lipid profile.

1. Introduction

Despite the fact that occupational stress is not a new phenomenon, it becomes progressively globalized and has effects on workers, families and overall society. It is in constant growth and presents a growing medical and economical problem [1]. This stress may occur due to the responsibilities related to the work itself, or conditions that are based on personality conflicts or corporate culture. It can affect individuals' wellbeing if not managed appropriately [2]. Driving is a stressful job which needs high levels of attention and caution if drivers are to cope appropriately with job demands. Driver stress can also occur due to timetables and working hours, traffic and weather conditions, passenger and goods safety, and responsibility if an error and/or an accident occur [3]. Cardiovascular diseases (CVDs) of professional drivers remain a key concern in clinical practice and occupational health research [4]. The risk of cardiovascular events has already been well documented among professional drivers [5]. Occupation is a major socioeconomic factor that together with a prolonged exposure to stress at workplace may have a direct effect on the autonomic nervous system and neuroendocrine activity, which may lead to increased incidence of diabetes mellitus, development of hypertension, and lipid disorders [6].

Professional drivers are exposed to several occupational risk factors such as long working hours, shift work, noise, carbon monoxide, and chemical materials. These factors increase the probability of emerging CVDs. Moreover, these drivers are more prone to developing obesity as they burn fewer calories due to the nature of the work activities, eating poor and irregular diets and driving in a sitting position for long durations every day [5]. Dyslipidemia is a well-established modifiable cardiovascular risk factor [7]. It is a heterogeneous disorder which may occur due to multiple etiologies. Most dyslipidemia is secondary to dietary habits and lifestyle [8]. The risk factors of dyslipidemia include age, smoking, genetics, diet, physical activity, and stress [9]. Although cross-sectional studies have linked occupational stress with lipid disorders, this association is still not consistent [4].

2. Methods

This cross-sectional study was performed during 2016–2017 in Suez Canal Authority, Ismailia City, on 131 professional drivers (44 car drivers, 43 bus drivers, and 44 truck drivers) selected randomly. The conclusion criterion was spending at least one year as professional driver. A structured interview questionnaire was prepared by the researcher. It included socio-demographic data, occupational history, medical history, Occupational Stress Index (OSI) and cardiovascular risk factors.

2.1. Occupational Stress Index

Permission of the first author Karen Belkić was taken before using this questionnaire. The OSI is arranged as a two-dimensional matrix, the vertical axis being composed of level of information transmission and the stressor aspects placed along the horizontal axis. It was developed also from a cognitive ergonomics perspective. Within the OSI the work environment is seen as a whole, including work schedule, task level concerns, broader organizational factors and physical and chemical exposures. The elements are equally weighted, scored from 0–2 (maximum), from absent to strongly present, with higher scores meaning higher level of burden. The elements are summed to yield aspects of seven groups: high demands, strictness, underload, extrinsic time pressure, noxious exposure, avoidance, and conflict. The total score of each aspect is calculated by adding input, output, central, and general scores of this aspect. The total OSI score is obtained by adding the total of the seven aspects together [10].

2.2. Cardiovascular Risk Factors Assessment

Cardiovascular risk factors were assessed to investigate risk factors other than occupational stress that may affect lipid profile, such as lifestyle (including active and passive smoking, sports practice, and environment), sleep, life stress, medical history, family history of CVD, blood sugar, and dietary habits. These factors were evaluated and scored according to Sydney cardiovascular risk assessment questionnaire [11].

2.3. Clinical examination

Blood pressure was measured for all participants. The participant was considered as having normal blood pressure if the systolic blood pressure was less than 120 mmHg and diastolic less than 80 mmHg. Prehypertension or at risk was considered at systolic blood pressure 120–139 mmHg and diastolic 80–89 mmHg. High blood pressure was considered at systolic blood pressure 140 mmHg or higher and diastolic 90 mmHg or higher [12].

Body mass index (BMI) was calculated after measuring height and weight. Below 18.5 was considered underweight; 18.5–<25 normal or healthy weight; 25.0–<30 overweight; thirty or above obese [13].

2.4. Determination of Lipid Profile

After 12 hours of fasting, a venous blood sample (5 mL) was taken. Quantitative determination of the lipid profile of participants including total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol, after centrifugation of the blood separation of serum, was done [14]. Dyslipidemia was operationally defined by one or more of the following abnormalities: Total cholesterol > 200 mg/dL, triglycerides > 150 mg/dL, LDL-C > 130 mg/dL, HDL-C < 40 mg/dL in men; hypercholesterolemia: Total cholesterol > 200 mg/dL; hypertriglyceridemia: triglycerides > 150 mg/dL; hypoHDLaemia: HDL-C < 40 mg/dL; hyperLDLaemia: LDL-C > 130 mg/dL [15].

2.5. Statistical Analysis

All statistical analyses were performed using the Statistical Package for Social Science (SPSS) version 20.0. Data were coded and entered into the computer statistical program and presented as means, standard deviations, and medians for quantitative data. Percentages were computed for categorical data. Tabulation or graphical presentations were done as required. Chi-squared tests were computed for categorical variables. Student t-test was used for quantitative variables between two groups and ANOVA test for more than two groups; corresponding non-parametric tests were used for non-parametric data as suitable. Logistic regression analyses for risk factors of dyslipidemia were done. Statistical significance was set at p < 0.05.

3. Results and Discussion

Regarding sociodemographic characteristics of participants,

Table 1. Sociodemographic characteristics of the studied drivers (n = 131).

Sociodemographic Characteristics	No.	%
Age (years)	5 73 31 22	3.8 55.7 23.7 16.8
20– 30– 40– 50–60
Range Mean ± SD	27–59 39.7 ± 8.3
Educational level
No formal education	12	9.2
Primary or preparatory	15	11.4
Secondary or vocational school	91	69.5
University	13	9.9
Marital status
Single	5	3.8
Married	122	93.1
Divorced or widow	4	3.1

shows that the mean age of the studied drivers was 39.8 ± 8.3 years, ranging from 27 to 59 years. The age of about half of drivers (55.7%) was between 30 < 40 years. The highest percentage (69.5%) had completed secondary or vocational school. Most of them (93.1%) were married.

Nearly half of the studied drivers (47.3%) drive both inside the city and between cities. The average duration of driving hours per day was 7.2 ± 2.6 hours a day with median of eight hours (

Table 2. Occupational history of the studied drivers (n = 131).

Occupational history	No.	%
City
Inside the city	36	27.5
Between cities	33	25.2
Both	62	47.3
Average duration of driving hours per day
Range Mean ± SD Median	1–14 7.2 ± 2.6 8.0
Years as professional driver
Range Mean ± SD Median	1–40 14.1 ± 9.4 11.0

).

Table 3. Occupational stress index aspects and total score among studied drivers.

Occupational Stress Index (OSI) Aspects (Maximum Score) (n = 131)	Mean ± SD	Median(IQR)
Total underload (20)	9.56 ± 2.58	10.00(3.00)
Total high demand (30)	16.92 ± 2.58	17.00(4.00)
Total strictness (21)	17.22 ± 1.61	18.00(1.00)
Total extrinsic time pressure (9)	7.56 ± 1.38	7.00(2.00)
Total noxious exposure (12)	6.75 ± 1.29	7.00(2.00)
Total symbolic aversiveness (avoidance) (20)	9.22 ± 1.58	9.00(2.00)
Total conflict (29)	12.76 ± 2.04	12.00(3.00)
Total OSI score (141)	79.98 ± 6.14	81.00(9.00)

IQR: Interquartile Range.

describes the different aspects of OSI and the total OSI score among the studied drivers. The mean scores of underload, high demand, strictness, extrinsic time pressure, noxious exposure, symbolic aversiveness, and conflict aspects of stress were (9.56 ± 2.58, 16.92 ± 2.58, 17.22 ± 1.61, 7.56 ± 1.38, 6.75 ± 1.29, 9.22 ± 1.58, 12.76 ± 2.04) respectively. The total OSI mean score was 79.98 ± 6.14 among them.

Table 4. Occupational index stress among car, bus and truck drivers (Kruskal-Wallis test) (n = 131).

OSI Aspects	Car Drivers n = 44	Bus Drivers n = 43	Truck Drivers n = 44	p-Value
Total underload	8.50 ± 2.11 ^	9.12 ± 2.12 #	11.07 ± 2.76	0.000 *
Total high demand	16.82 ± 2.31 ^	17.56 ± 2.00 #	16.39 ± 1.33	0.020 *
Total strictness	16.36 ± 2.27 ^	17.58 ± 1.07 #	17.58 ± 0.62	0.000 *
Total extrinsic time pressure	8.00 ± 1.12 @	7.44 ± 1.42	7.23 ± 1.49	0.046 *
Total noxious exposure	6.82 ± 1.28 ^ @	5.72 ± 0.96 #	7.68 ± 0.74	0.000 *
Total symbolic aversiveness	8.84 ± 1.74	9.44 ± 1.80	9.39 ± 1.04	0.189
Total conflict	12.20 ± 2.38 ^	13.40 ± 1.87	12.68 ± 1.67	0.035 *
Total OSI	77.55 ± 6.79 ^ @	80.26 ± 6.02	82.16 ± 4.62	0.003 *

OSI Occupational Stress Index, * Statistically significant at p < 0.05, ^{^} Mann-Whitney test between car drivers is statistically significant at p < 0.05 compared with bus drivers, ^@ Mann-Whitney test between car drivers is statistically significant at p < 0.05 compared with truck drivers, ^# Mann-Whitney test between bus drivers is statistically significant at p < 0.05 compared with truck drivers.

demonstrates statistically significant differences among driver groups regarding underload, high demand, extrinsic time pressure, noxious exposure, strictness, and conflict aspects scores of OSI. Additionally, the total OSI score shows a statistically significant difference among car drivers, bus drivers, and truck drivers (p = 0.003). As Figure 1 shows, 79.4% of the drivers have dyslipidemia.

Table 5. Lipid profile of studied drivers (n = 131).

Lipid profile (mg/dL)	Normal		Abnormal
	No.	%	No.	%
Cholesterol	63	48.1	68	51.9
Range Mean ± SD Median (IQR)	113–281 204.37 ± 37.01 205.00 (49.00)
Triglycerides	82	62.6	49	37.4
Range Mean ± SD Median (IQR)	44–610 146.79 ± 90.86 126.00(94.00)
LDL-C	65	49.6	66	50.4
Range Mean ± SD Median (IQR)	54–229 133.56 ± 38.74 133.00(56.00)
HDL-C	72	55.0	59	45.0
Range Mean ± SD Median (IQR)	22–88 42.40 ±11.32 41.00(11.00)

LDL-C: Low-density lipoprotein cholesterol; HDL-C: High-density lipoprotein cholesterol; IQR: Interquartile Range.

shows that 51.9% of the studied drivers suffered from hypercholesterolemia. The mean of the cholesterol level was 204.37 ± 37.01 mg/dL. In addition, 37.4% had hypertriglyceridemia. The mean of the triglycerides was 146.79 ± 90.86 mg/dL. The LDL-C was high among 50.4% of the studied drivers. The mean of the LDL-C was 133.56 ± 38.74 mg/dL, and the HDL-C level was low among 45% of them. The mean of the HDL-C was 42.40 ± 11.32 mg/dL.

To assess the lipid profile among the three driver groups, Figure 2 reveals that 70.5% of car drivers, 86% of bus drivers and 81.6% of truck drivers have dyslipidemia but that this difference is statistically insignificant.

Regarding the cardiovascular risk factors scores,

Table 6. Cardiovascular risk factors scores among studied drivers (n = 131).

Cardiovascular risk factors scores (Maximum score)	Range	Mean ± SD	Median
Family history of CVD (45)	0–45	12.25 ± 12.45	15.00
Lifestyle (138)	0–138	68.95 ± 39.57	58.00
Exercise practice (20)	–25–20	16.73 ± 9.22	20.00
Smoking status (80)	0–80	33.51 ± 36.12	10.00
Exposure to passive smoking (25)	0–25	14.50 ± 12.39	25.00
Environment (13)	0–9	4.21 ± 2.47	3.00
Sleep (24)	0–22	4.34 ± 4.30	3.00
Life stress (331)	–10–89	5.12 ± 14.68	0.00
Blood sugar (110)	0–110	11.60 ± 29.06	0.00
Diet (48)	−8–26	6.33 ± 7.63	5.00

CVD: cardiovascular disease.

shows that the family history of CVD score ranged from 0–45. In addition, the lifestyle score ranged from 0–138. Besides, the range of sleep score was 0–22. Moreover, life-stress score ranged from –10–89 and blood-sugar score ranged from 0–110. Furthermore, the diet-score range was 8–26.

Regarding occupational risk factors of dyslipidemia,

Table 7. Occupational risk factors of dyslipidemia among drivers with normal lipid profile and drivers with dyslipidemia (Mann-Whitney U Test) (n = 131).

Occupational Risk Factors	No Dyslipidemia (n = 27)	Dyslipidemia (n = 104)	p-Value
Underload aspect	9.00 ± 2.45	9.71 ± 2.60	0.170
High-demand aspect	17.11 ± 1.91	16.87 ± 1.99	0.508
Strictness aspect	17.41 ± 2.02	17.17 ± 1.49	0.931
Extrinsic time pressure aspect	7.41 ± 1.42	7.60 ± 1.37	0.500
Noxious exposure aspect	6.44 ± 1.45	6.83 ± 1.24	0.246
Symbolic aversiveness aspect	9.22 ± 1.60	9.22 ± 1.58	0.942
Conflict aspect	12.14 ± 1.49	12.91 ± 2.14	0.114
Total OSI	78.74 ± 6.09	80.31 ± 6.14	0.239
Average driving hours a day	6.0 ± 2.7	7.2 ± 2.3	0.017 *
Years as professional driver	12.3 ± 8.3	12.5 ± 7.9	0.308
City			0.139 c
Inside the city	10 (37.0%)	26 (25.0%)
Between cities	3 (11.1%)	30 (28.8%)
Both	14 (51.9%)	48 (46.2%)

SCA: Suez Canal Authority; ^c Chi-squared test, * Statistically significant at p < 0.05.

reveals that average duration of driving hours per day is the only statistically significant risk factor associated with dyslipidemia with a mean of 6.00 ± 2.69 hr per day among drivers with normal lipids profiles compared with 7.20 ± 2.31 hr per day among drivers with dyslipidemia. By contrast, OSI aspects, total OSI score, driving inside a city or between cities do not have a statistically significant relationship with dyslipidemia among the studied drivers.

Table 8. Correlations between occupational stress index and lipid profile (n = 131).

Occupational Stress Index (OSI) Aspects	Spearman Rank Correlation Coefficient (r)
	Cholesterol	Triglycerides	LDL-C	HDL-C
Underload	0.086	0.033	0.079	−0.048
High demand	−0.072	−0.148 *	−0.034	−0.002
Strictness	0.020	0.010	−0.039	0.099
Extrinsic time pressure	−0.061	−0.019	−0.020	0.024
Noxious exposure	0.163 *	0.112	0.149 *	0.057
Symbolic aversiveness	−0.127	-0.065	−0.081	0.034
Conflict	0.162 *	−0.137	0.234 *	0.297
Total OSI	0.093 a	−0.086	0.104	0.044

^a Pearson correlation, * Statistically significant at p < 0.05.

shows that noxious exposure and conflict aspects of the OSI have weak positive significant correlations with cholesterol level (r = 0.163, 0.162, respectively). The correlations between OSI and triglycerides level are insignificant except a weak negative significant correlation between high demand aspect and triglyceride level (r = –0.148). Weak positive significant correlations are shown between conflict aspect score and LDL-C (r = 0.234) and between noxious exposure aspect score and LDL-C level (r = 0.149).

With regards to non-occupational risk factors of dyslipidemia,

Table 9. Non-occupational risk factors of dyslipidemia (n = 131).

Non-Occupational Risk Factors	No Dyslipidemia (n = 27)	Dyslipidemia (n = 104)	p-Value
Age	41.4 ± 9.0	39.3 ± 8.1	0.325 a
Family history score	12.78 ± 12.27	12.12 ± 12.55	0.753 a
Lifestyle score	66.00 ± 39.04	69.72 ± 39.86	0.709 a
Exercise practice score	15.81 ± 11.05	16.97 ± 8.73	0.638 a
Smoking status
Never	14(51.9%)	43(41.3%)
Ex-smoker	3(11.1%)	12(11.5%)
Current smoker fewer than 20 cigarettes/day	4(14.8%)	12(11.5%)	0.592 b
Current smoker equal or more than 20 cigarettes/day	6(22.2%)	37(35.6%)
Number of cigarettes/day	24.0 ± 12.0	27.5 ± 10.7	0.372 a
Years of smoking if current	15.9 ± 7.1	15.71 ± 7.0	0.896 a
Passive smoker	21(27.6%)	55(72.4%)	0.020 c*
Environment score	4.00 ± 2.45	4.59 ± 2.38	0.637 a
Sleep score	4.33 ± 3.04	4.86 ± 4.29	0.505 a
Life-stress score	10.78 ± 20.81	5.47 ± 16.31	0.896 a
Blood-sugar score	6.67 ± 21.30	12.89 ± 30.71	0.430 a
Diet score	7.00 ± 6.00	9.00 ± 6.91	0.179 d
BMI	27.73 ± 4.44	29.79 ± 4.06	0.023 d*
Systolic Blood Pressure	121.1 ± 14.5	122.2 ± 12.2	0.839 a
Diastolic Blood Pressure	78.5 ± 9.9	79.3 ± 9.4	0.995 a

BMI: Body mass index, ^a Mann-Whitney U test, ^b Fisher exact test, ^c Chi-squared test, ^d Student t-test, * Statistically significant at p < 0.05.

shows that 72.4% of drivers exposed to passive smoking had dyslipidemia compared with 27.6% who did not have dyslipidemia and that this difference is statistically significant. Moreover, the BMI mean is higher among dyslipidemic drivers (29.79 ± 4.06) compared with drivers having normal lipid profile (27.73 ± 4.44) and the difference is statistically significant. Other non-occupational factors do not have a statistically significant relationship with dyslipidemia.

Regarding independent significant risk factors of dyslipidemia, binary logistic regression analysis identified conflict aspect of the OSI, average duration of driving hours per day, and BMI as positive statistically significant independent risk factors for dyslipidemia (

Table 10. Logistic regression of independent risk factors of dyslipidemia (n = 131).

Covariates of Dyslipidemia	ß	p Value	OR	(95% CI )
Strictness score	−0.296	0.087	0.744	(0.530–1.044)
Conflict score	0.281	0.042*	1.324	(1.010–1.736)
Average of driving hours a day	0.346	0.002*	1.414	(1.137–1.759)
BMI	0.176	0.006*	1.192	(1.052–1.351)
Constant	−4.428	0.199	0.012
Model χ2 = 21.690		0.000*

BMI: Body mass index. Variables entered and excluded: underload aspect, high demand aspect, extrinsic time pressure aspect, noxious exposure aspect, symbolic averseness aspect, total occupational stress index score, smoking status, passive smoking status, and diet. * Statistically significant at p < 0.05. Cox and Snell R Square = 0.153. Nagelkerke R Square = 0.239.

).

In the present study, the total OSI score mean was 79.98 ± 6.14 among the studied drivers. This agrees with the results of a Serbian study conducted on 417 male professional drivers, where total OSI was 63.9 ± 8.8 [1]. Professional drivers are exposed to occupational stress because driving is a stressful task. Occupational stress of drivers can also occur due to timetables and working hours, traffic and weather conditions, and passenger and goods safety [3].

The current study reveals that 79.4% of the studied drivers have dyslipidemia and 51.9% of them suffer from hypercholesterolemia, 37.4% have hypertriglyceridemia. 50.4% have high LDL-C and 45% have a low HDL-C level. This is in agreement with the results of an Iranian study conducted on 429 bus and truck male drivers where 53.4% had elevated triglyceride and 48.7% have low HDL-C levels [16]. Also, these findings partly support the results of a Korean study conducted on 443 male bus drivers, where 64.2% of them had high triglyceride, 38.6% had high cholesterol, 36.3% had low HDL-C, and 25.4% had high LDL-C [5].

By contrast, Biglari et al.’s (2016) results showed that 28.3% of the studied drivers had hypercholesterolemia with a cholesterol level of >200 mg/dL and 15.2% had hypertriglyceridemia with a triglycerides level of > 240 mg/dL [17]. The difference in prevalence of dyslipidemia among studies may arise from the multifactorial etiology of dyslipidemia, which is a heterogeneous disorder that may occur due to multiple etiologies. Most of dyslipidemia is secondary to dietary habits and lifestyle. So, modern diet and lifestyle factors such as tobacco use, high fat intake, obesity, and sedentary activity play roles in the current epidemic of atherosclerosis [8].

Regarding the association of occupational stress and lipid profile, according to the results obtained in the present study, the total OSI score does not have a statistically significant relationship with dyslipidemia among studied drivers. Moreover, insignificant correlations are found between total OSI score and cholesterol level, triglycerides, LDL-C, or HDL-C. These results corroborate with findings from a meta-analysis conducted to investigate occupational stress and cardiovascular disease risk factors. No association was found between occupational stress and lipid profile [6]. The present study results also concur with Biglari et al. (2016) who did not reveal a significant relationship between job stress and dyslipidemia. In addition, the correlation tests do not demonstrate significant correlations between stress and blood cholesterol or triglycerides levels [18]. Moreover, Tsutsumi et al. (2003) concluded that job control or job strain (the ratio of demands to control) did not have a significant association with any of the lipid levels in males or females and suggest that psychologically demanding jobs may be related to an unfavorable lipid profile, but that the effect of job strain on atherogenic lipids is negligible [18].

This is in contrast to Jovanović et al.'s (2008) results, which reveal statistically significant relations between OSI and total cholesterol, LDL-C and triacylglycerol [1]. In addition, Djindjic et al.'s (2012) results found a significant association between total OSI score and any lipid profile abnormality. The group as a whole showed significant associations between total OSI and hypercholesterolemia, hypertriglyceridemia, and low (HDL) cholesterol [19]. Furthermore, Djindjić et al.'s (2013) results suggest a significant difference in prevalence of dyslipidemia associated with total OSI and some OSI aspects among professional drivers. Logistic regression analysis showed that total OSI score is significant risk factor for high triglycerides, high LDL-C, and low HDL-C [20].

4. Conclusions

The professional drivers in the study setting are exposed to occupational stress, with a high proportion having dyslipidemia. The total occupational stress index score does not have a statistically significant relationship with dyslipidemia, while certain aspects of occupational stress index have significant relations with lipid profile.