The Association between Cardiovascular Disease Risk Factors and Motor Vehicle Crashes among Professional Truck Drivers

Abstract

Objective

This study assesses relationships between the Framingham Cardiovascular Disease Risk (CVD risk) Score and prevalence of US Department of Transportation (DOT)-reportable crashes in commercial motor vehicle (CMV) drivers, after controlling for potential confounders.

Methods

Data were analyzed from CMV drivers (N=797) in a large cross-sectional study. CVD risk was calculated for each driver. Adjusted odds ratios (OR) and 95% Confidence Intervals (95% CI) between CVD risk and DOT-reportable crashes were calculated.

Results

Drivers in the two highest CVD risk groups had significantly higher likelihood of crash (OR=2.08, 95% CI=1.20-3.63 and OR=1.99, 95% CI=1.05-3.77, respectively) after adjusting for confounders. There was a significant trend of increasing prevalence of crashes with an increasing CVD risk score (p=0.0298).

Conclusion

Drivers with high CVD risk had a higher likelihood of a crash after controlling for confounders.

INTRODUCTION

Heart disease is the leading cause of death in the United States for both men and women, with around 610,000 deaths per year^[1]. The National Health and Nutrition Examination Survey data showed that nearly 47% of adults had at least one risk factor for cardiovascular disease (CVD) ^[2]. CVD risk factors vary across ethnic, socioeconomic and/or occupational groups ^[1]. Truck drivers have been shown to have a particularly high prevalence of CVD risk factors ^[3-7].

Drivers are required to have a Commercial Driver Medical Examination (CDME) in order to become a licensed commercial motor vehicle (CMV) driver. This CDME is valid for up to 24 months, however a certificate can be given for less than 24 months when it is desirable to monitor a condition, such as hypertension ^[8]. Yet, CMV drivers have been shown to have poor overall health^{[3, 6, 7, 9-12]} and have higher prevalence of CVD risk factors,^[3-7] particularly tobacco use, hypertension and obesity, compared to the general population ^[3-7]. The poor health status of truck drivers is commonly attributed to both lifestyle and occupational factors that include diet, physical inactivity, and prolonged sitting ^{[4-6, 11, 12]}.

Currently there are an estimated three million CMV drivers in the United States^[13]. In 2012, there were 333,000 large trucks (large trucks defined as weighing more than 10,000 pounds) involved in motor vehicle crashes in the United States^[14]. There were 104,000 people injured in crashes involving large trucks with 79,000 (76%) of those injured having been occupants of other vehicles or non-occupants (pedestrians, cyclists, etc.) ^[14]. In addition to those injured, there were 3,921 fatalities in crashes involving large trucks, with 3,224 (83%) of these fatalities having been occupants of other vehicles or non-occupants ^[14].

In 2012 the FMCSA estimated a total cost estimate of $38 Billon for crashes involving large trucks that caused injuries, and a total of $40 Billon for fatal crashes ^[15]. Many factors have been cited as contributing causes to crashes such as speeding, distraction/inattention and impairment ^[16]. A 1989 study conducted by the National Transportation Safety Board, 189 fatal truck accidents were analyzed. Ten percent of the accidents were attributed to medical problems, and of these 10 percent, 90 percent were classified as cardiovascular-related^[17]. Other studies have shown that cardiovascular disease has been associated with an increased crash risk among private drivers ^[18-21]. Therefore an understanding of the relationship between a driver's CVD risk factors and crashes is warranted.

Cardiovascular disease risk factors can be quantified using various risk scores and risk calculators. The Framingham Risk Score has been used to assess and predict a person's individual risk for developing CVD over the next 10 years ^[22]. The scale provides a way to effectively quantify CVD risk ^[23]. The Framingham Risk Score is comprised of blood pressure, total cholesterol, high density lipoprotein (HDL) cholesterol, smoking, age and blood pressure medications ^[22-24]. This risk score has been shown to be effective in predicting the development of cardiovascular disease ^[23].

The goal of this assessment was to analyze the relationship between the CVD risk score and the prevalence of US Department of Transportation (DOT)-reportable crashes among CMV drivers, after controlling for potential confounding factors.

MATERIALS AND METHODS

Study Population and Design

This cross-sectional study was approved by the University of Utah (IRB #: 22252) and the University of Wisconsin-Milwaukee Institutional Review Boards (IRB#: 07.02.297). As a prior publication has detailed methods, abbreviated methods follow.^[25]

Participants (N=858) were required to be a commercial truck driver with a current U.S. commercial driver's license (CDL) at the time of study enrollment. Participants were enrolled from 2008-2011 at various truck stops and professional truck shows in Utah and Wisconsin, and at truck shows in Kentucky, Texas, Nevada, and Iowa. Informed consent was obtained from all participants. Demographic and health information are provided in Table 2.

Table 2.

Demographics and Cardiovascular Disease Risk Factors.

VARIABLES	N	%
Age*	47.2	10.5
Gender*
Male	685	85.90%
Race
White	687	86.2%
Black or African American	37	4.6%
Hispanic or Latino	49	6.1%
Other	21	2.6%
Decline to Answer	3	0.4%
BMI	32.9	7.5
Underweight (<18.5 kg/m2)	5	0.63%
Normal (18.5-24.9 kg/m2)	80	10.0%
Overweight (25-29.9 kg/m2)	219	27.5%
Obese (30-30.9 kg/m2)	379	47.6%
Morbidly Obese (> 40 kg/m2)	114	14.3%
Waist Circumference (cm)	113.2	17.3
Smoke*
Yes	395	49.60%
Regular Exercise
Yes	460	57.70%
Truck Crash
Yes	308	38.60%
Diagnosed with High Blood Pressure*
Yes	230	28.90%
Alcohol
Yes	469	58.90%
Diabetes Mellitus
No	712	89.30%

VARIABLES	MEAN	STD DEV
Weight in Kilograms (kg)	103.4	24.2
Waist Circumference (cm)	113.2	17.3
Total weekly physical activity (min)	281	365.9
Diastolic Blood Pressure (mmHg)	84.3	10.7
Systolic Blood Pressure (mmHg)*	131.9	17.4
HDL (mg/dL)*	36.6	14.1
Total Cholesterol (mg/dL)*	191.5	41.2
Hemoglobin A1c	5.0	1.2
Glucose (mg/dL)	121.7	54.8
Average 10-year Cardiovascular Disease Risk**	8.9	8.2

^*Variable used to calculate Framingham 10-year Cardiovascular Risk

^**Average 10-year cardiovascular disease risk is an estimate of an individual's chance (%) for developing CVD within the next ten years. Average 10-year risk was calculated using the variables: systolic blood pressure, total cholesterol, HDL cholesterol, smoking, age, and gender.

After enrollment and consent, participants completed computer-based questionnaires. Research assistants provided assistance to participants if they had any questions or difficulties. The questionnaire gathered demographic information, history of reportable motor vehicle crashes, past medical history, physical activities, hobbies, psychosocial factors and many other elements.

Research assistants recorded driver's neck circumference, chest circumference, waist circumference, hip circumference, height, weight, and blood pressure. A finger-stick was analyzed including for total cholesterol, HDL cholesterol, LDL cholesterol, and triglyceride levels.

The entire enrollment process took an average of 1 hour and all subjects were provided a $20 gift-card for participation. There was no follow-up with participants as this study was of cross-sectional design.

Cardiovascular Risk Factor Exposures

The Framingham Heart Study was originally incepted in 1948 ^{[22, 24]}. From that cohort study, the Framingham Risk Scale has been developed ^[22-24] and was used to assess 10-year cardiovascular disease risk among this study population. The risk factors assessed were age, gender, total cholesterol, high density lipoprotein (HDL) cholesterol, smoking, systolic blood pressure and use of blood pressure medications. A detailed description of CVD risk calculation is provided in Table 1. Each risk variable (e.g., total cholesterol) is assigned a point value based on the value of the risk variable, and the age and gender of the participant. For example, a 45 year old male who is a smoker with a total cholesterol level of 205mg/dL, an HDL level of 43mg/dL and unmedicated systolic blood pressure of 135 mmHg received 3 points for age, 5 points for total cholesterol, 5 points for smoking, 1 point for HDL and 1 point for systolic blood pressure. The points are summed for a total score of 15 in this case, which translates to a 10 year CVD risk estimate of 20% for this participant.

Table 1.

Point values given for the various CVD risk factors according to the Framingham Scale. Scores for each individual risk factor (according to gender and age of the participant) were summed to give a total. The total score equated to a percentage used to quantify CVD risk.

Table 1. Framingham Score Calculation
For Men
Age	Age Points	Total Cholesterol (mg/dL)				Smoking	HDL (mg/dL)				Systolic Blood Pressure (mmHg)
		160-199	200-239	240-279	280+	Smoker	60+	50-59	40-49	<40	120-129	130-139	140-159	160+
20-34	−9	4	7	9	11	8	−1	0	1	2	If Untreated with Medication
35-39	−4										0	1	1	2
40-44	0	3	5	6	8	5
45-49	3
50-54	6	2	3	4	5	3
55-59	8										If Treated with Medication
60-64	10	1	1	2	3	1					1	2	2	3
65-69	11
70-74	12	0	0	1	1	1
75-79	13

For Women
Age	Age Points	Total Cholesterol(mg/dL)*				Smoking+	HDL (mg/dL)				Systolic Blood Pressure(mmHg)**
		160-199	200-239	240-279	280+	Smoker	60+	50-59	40-49	<40	120-129	130-139	140-159	160+
20-34	−7	4	8	11	13	9	−1	0	1	2	If Untreated with Medication
35-39	−3										1	2	3	4
40-44	0	3	6	8	10	7
45-49	3
50-54	6	2	4	5	7	4
55-59	8										If Treated with Medication
60-64	10	1	2	3	4	2					3	4	5	6

^*Total Cholesterol <160 mg/dL was a 0 value for all age groups and both genders.

⁺Non-smokers had a 0 value for all age groups and both genders.

^**Systolic Blood Pressure < 120mmHg was a 0 value for all age groups and both genders.

The Framingham Risk Scale was used to quantify CVD risk for each driver in this study. Drivers were categorized into seven groups based on the percentage risk for developing cardiovascular disease within the next 10 years. Each group included close to 100 participants to ensure stable estimates for each group. The groups ranged from lowest risk (0%) to highest risk (21-30%) (Table 3).

Table 3.

Adjusted Odds Ratios and 95% Confidence Intervals for being involved in a Crash for the Seven Groups of Cardiovascular Disease Risks.

Framingham 10-Year CVD Risk	N (%)	Number or drivers reporting having been in a DOT crash (%)	Odds Ratio	95% Confidence Intervals
Lowest Risk (0%)	123 (15.4)	36 (29.3)	1.00	(Reference)
1-2%	149 (18.7)	47 (31.5)	1.14	0.67	1.94
3-5%	107 (13.4)	43 (40.2)	1.58	0.90	2.78
6-8%	108 (13.6)	41 (38.0)	1.30	0.73	2.29
9-12%	120 (15.1)	48 (40.0)	1.45	0.83	2.54
13-20%	122 (15.3)	60 (49.2)	2.06*	1.18	3.60
Highest Risk (21-30%)	68 (8.5)	33 (48.5)	2.00*	1.05	3.77

^*p<0.05 adjusted for gender, body mass index and cell phone use while driving in the city. There was a significant trend in increased risk for crash across the CVD risk groups (p= 0.0046).

Crash Outcomes Assessment

There was one question asked in the questionnaire that assessed truck crashes among the truck drivers. The question was: Have you ever had any reportable motor vehicle crashes? A DOT-reportable crash is one that involved a fatality, an injury requiring immediate treatment away from the scene, or any vehicle involved having to be towed due to disabling damage.^[16]

Personal injury was not assessed as part of the questionnaire. However, near misses, number of crashes and cause of each crash were each examined in the questionnaire.

Statistical Analysis

SAS 9.4 software (SAS Institute Inc. Cary, NC) was used for data analysis. Multivariate logistic regression analysis was used to analyze the relationship between CVD risk and DOT-reportable crash. Each CVD risk group (e.g., High Risk Group (21-30%)) was compared to the lowest risk group (0%) in order to assess the relationship between increased CVD risk and DOT reportable crash.

The potential confounding factors age, gender, body mass index, cell phone use while driving in the city, depression, alcohol and drug use, physical exhaustion, professional driving time, sleep problems, sleep apnea, sitting time while not on the road, diabetes and psychosocial factors were assessed. Only Age, gender, BMI, and cell phone use while driving remained in the adjusted model because they showed a relationship with CVD risk and DOT reportable accidents. Adjusted Odds ratios and confidence intervals were used to assess statistical signficance at (p<0.05). Means and frequencies were used to describe the population.

RESULTS

Demographic Data

Complete data for 797 of the 858 drivers enrolled (92.9%) were available for analysis. Drivers were excluded from final analyses for the following reasons: missing or incomplete questionnaire data, inconsistencies in their responses in the questionnaire and enrolling in the study twice at different locations. One complete data set was kept from duplicate participants.

Most drivers were male 685 (85.9%) (see Table 2), the mean age was 47.2 years old and 687 (86.2%) participants were Caucasian. Drivers had a mean body mass index of 32.9 kg/m² and 507 were classified as obese (BMI ≥ 30 kg/m²). Most drivers also reported drinking alcohol at least once in the past year, 569 (58.9%). Drivers reported weekly physical activity averaging 281 minutes and more than half of the drivers reported participating in regular exercise. However, 102 drivers (12.8%) reported no physical activity on a weekly basis. Drivers filled out information about their physical activity and participation in individual sports and activities. MET levels were derived using the information about the time and frequency a driver spent performing a certain activity (e.g. swimming, running, walking). The mean MET level estimated from their recalled activities was 12.97±23.6 mL/kg/min. Drivers also reported sitting on average 4.3 hours per day outside of work.

More than a fourth of drivers (28.9%) had been told that they had high blood pressure by a physician. Of those diagnosed with high blood pressure, 76.9% reported taking medication to lower their blood pressure. 26.7% of drivers reported having been diagnosed with high cholesterol and 50% of them were taking cholesterol-lowering medication. A total of 308 (38.6%) drivers reported having been in at least one DOT-reportable crash.

The Seven CVD Risk Categories

The average 10-year CVD risk percentage was 8.9% according to the Framingham Risk Scale. This variable was derived by adding up the total points for each individual CVD risk factor (see Table 1). The total CVD risk score correlates with an individual risk percentage according to the National Heart, Lung, and Blood Institute (NHLBI)^[22]. More than one-third of drivers (38.9%) had a CVD risk percentage of 9% or higher, and nearly 10% of drivers (8.5%) had a risk greater than 20. Drivers with the highest risk for cardiovascular disease (Framingham Score >20) and those with the second highest risk (Framingham Score 16-20) were more likely have a reportable crash than the drivers with the lowest risk score (0%), OR= 2.00 (95% CI, 1.05-3.77) and OR= 2.06 (95% CI, 1.18-3.60) respectively (Table 3). There was a statistically significant trend of increasing prevalence of crashes with an increasing CVD risk score (p=0.0298). Analyses of quartiles and tertiles demonstrated similar relationships but are not presented, as they were less informative. Figure 1 shows the odds ratios and 95 % confidence intervals for the seven CVD risk groups.

Figure 1.

Cardiovascular Disease (CVD) Risk Factor Scores with Odds Ratios and 95% Confidence Intervals for DOT-reportable Crash compared to the Reference Group (0% CVD risk).

When drivers were divided up into risk categories based on CVD risk [Low Risk (0-9%), Moderate Risk (10-20%) and High Risk (>20%)] only the moderate risk group showed a significantly higher OR compared to the low risk group for reportable crashes, OR= 1.40 (95% CI, 1.00-1.95). The high risk group did not show a significant difference, however, the OR approached significance (p=0.08), OR = 1.60 (95% CI, 0.95-2.71).

DISCUSSION

As the CVD risk estimate rose, truck drivers had up to a doubled risk of having been in a DOT-reportable accident. This increased accident risk puts CMV drivers, as well as pedestrians and other drivers at greater risk for injury and death. Drivers showed an average 10-year CVD risk of 8.9% according to the Framingham Heart Scale, and more than one third of the drivers (38.9%) had a CVD risk of 9% or greater. Nearly 10% of drivers (8.5%) had a CVD risk percentage greater than 20%. Truck drivers also had a high prevalence of individual CVD risk factors such as low HDL levels that averaged 36 mg/dL, smoking among nearly half of the drivers, and more than half of the drivers (61.9%) were obese.

Many other factors have been found to be associated with crashes in truck drivers. In a recent analysis with the same cohort of drivers, all of the following were associated with increased risk of crashes: increasing age, increasing truck driving experience, male sex, low back pain, heart disease, pulse pressure, cell phone use, feeling tense and feeling physically exhausted after work ^[25]. Many of these factors are also related to CVD risk, including pulse pressure, increasing age and male sex. Other studies have shown that truck drivers have an increased prevalence of hypertension, smoking, obesity, and diabetes ^{[3-7, 9-12]}.

Although drivers have mandatory participation in CDMEs and licensing procedures, drivers continue to show high rates of CVD risk factors. In a large cohort of drivers (N=88,246) it was found that the prevalence of obese (25.3% to 28.2%) and morbidly obese (22.2% to 31.1%) drivers increased from the year 2005 to 2012^[26]. In addition it was found that the prevalence of drivers with four or more health conditions increased from 0.5% to 2.3% and the number of drivers with three or more health conditions increased from 2.7% to 8.8%^[26]. Thus CMV drivers’ health appears to be getting worse, despite the medical examination all drivers take at least every 24 months.

One reason for the elevated CVD risk factors and overall poor health of truck drivers could be that physical activity and exercise intensity may be lower in truck drivers compared to other occupational groups ^[27]. Drivers in our study reported not meeting the minimum physical activity recommendations for adults of 150 minutes per week of moderate to vigorous exercise ^[27]. Drivers also reported sitting an average 4.3 hours per day while not on the road. Lack of moderate to vigorous physical activity on a regular basis plus excess sitting time (both occupationally and in leisure time) may have an adverse impact on drivers’ cardiovascular health and of chronic diseases ^{[3, 6, 7]}.

There have been few interventional studies to address CVD risk factors in truck drivers^{[12, 28-30]}, many of whom are largely unable to participate in traditional health promotion programs due to occupational demands^[12] of long haul driving. Interventional studies should be aimed at helping truck drivers improve their cardiovascular health. Successful, truck driver-specific exercise and nutrition interventions may help drivers obtain more physical activity and proper nutrition while on the road.

To our knowledge, this is the first study to systematically evaluate cardiovascular disease risk factors/scores and DOT-reportable crashes within commercial motor vehicle drivers. Strengths of the study include the large sample of CMV drivers and objective measurements of BMI, cholesterol, HDL cholesterol, and blood pressure. Weaknesses of this study include the usual limitations associated with a cross-sectional study. These include the potential for recall biases, although to produce this study's results, would require the bias or confounder to incrementally increase across the categories. Longitudinal studies are needed to confirm these results. Studies would also need to assess if improvement of CVD risk factors or overall cardiovascular health are associated with a decrease in crash frequency among CMV drivers over time.

CONCLUSION

Truck drivers with higher risks for cardiovascular disease also have greater risk of having been in motor vehicle crashes than drivers who were at lower risk for cardiovascular disease. Cohort studies are needed to further evaluate the relationship between CVD Risk and crashes in CMV drivers. The lifestyle and work environment of CMV drivers may contribute to these elevated cardiovascular disease risk factors. The high prevalence of CVD risk factors among truck drivers may provide additional opportunities for crash prevention such as interventions aimed at improving drivers’ health.