Comprehensive Assessment of Cardiovascular Risk Factors among Long-Haul Truck Drivers in South Brazil and its Impact on 3-year follow-up of Cardiovascular Events

doi:10.21203/rs.3.rs-4692789/v1

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Research Article

Comprehensive Assessment of Cardiovascular Risk Factors among Long-Haul Truck Drivers in South Brazil and its Impact on 3-year follow-up of Cardiovascular Events

https://doi.org/10.21203/rs.3.rs-4692789/v1

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Background

Cardiovascular diseases are a significant concern among truck drivers due to their profession's nature, involving long hours of sedentary work and exposure to various risk factors. Prevalence of risk factors associated with cardiovascular health in long-haul truck drivers and their impact on incidence of cardiovascular events are less studied.

Methods

A prospective cohort study was conducted among long-haul truck drivers traveling on BR 277, a major federal highway in Brazil. Truck drivers aged 18 years and above were recruited from four strategically selected locations along the route and were sequentially invited to participate while waiting to load and unload cargo. Clinical evaluations, including socio-demographic information, occupational factors, chronic disease history, medication use, lifestyle habits, and screening for obstructive sleep apnea, were performed. Physical measurements, blood glucose levels, lipid profile, ultrasensitive protein C-reactive, ankle-brachial index, left ventricular hypertrophy and heart rate variability were assessed. Participants were followed up for three years to detect the incidence of major cardiovascular events.

Results

The study revealed that obesity, diabetes and smoking were highly prevalent among long-haul truck drivers. A significant proportion of drivers met the criteria for metabolic syndrome and had a high-risk score for cardiovascular events. Moreover, subclinical inflammation, vascular stiffness, left ventricular overload and increased cardiac sympathetic modulation were also highly prevalent. The presence of multiple risk factors and medical conditions was associated with an increased likelihood of a major cardiovascular event.

Conclusion

The findings emphasize the need for targeted interventions to improve the cardiovascular health of truck drivers and promote roadway safety.

cardiovascular diseases

truck driver

risk assessment

clinical evaluation

cohort study

Road freight transport is essential for global economies [1]. Brazil boasts the fourth-largest road network in the world, spanning over 1,700,000 kilometers, making it the primary means of transporting goods and passengers in the country. Approximately 60% of all goods moved within Brazil rely on road transportation to meet demand [2]. Notably, the agricultural sector plays a significant role in this context, being fundamental for Brazil and a key player in the country's post-COVID-19 pandemic economic recovery.

The risk factors associated with being a professional truck driver are well-established [3] [4] [5]. The sedentary nature of the occupation, highly regulated work and rest schedules, irregular sleep patterns, limited opportunities for exercise or access to nutritious food on the road all contribute to an increased risk of various health conditions [3]. Back pain, hypertension, obesity, sleep apnea, diabetes, and depression are frequent among this group [6]. Given the estimated tripling of global freight demand by 2050 [7], the transport sector must invest in its workers and address health and lifestyle risk factors associated with truck driving. Improving the workforce's health will directly benefit drivers and secure the future stability of road freight transportation [8].

Professional drivers, including bus, taxi, and long-haul truck drivers experience higher health issues rates than other occupations [9]. They suffer from acute and chronic health conditions at higher rates than the general working population, including increased risk of cardiovascular disease [10] [11], obesity and metabolic syndrome [4] and are more stressed [12] [13]. Long-distance truck drivers have a higher risk of work-related injuries [14], are at risk for poor health outcomes, and experience significant difficulty accessing healthcare services [15].

It is important to note that truck driving is not a homogeneous profession. Long-distance and short-distance drivers face different occupational demands, working conditions, personal environments and risk factors. Long-distance drivers are more likely to be exposed to long periods of isolated and sedentary working hours, poor sleep hygiene, and a lack of access to nutritious food on the road [16]. On the other hand, short-distance drivers spend more time driving in high-density traffic and may face more significant time pressures to make multiple deliveries in a day [17]. Personal factors, such as relationships with family and friends, also impact the health and well-being of these populations. For example, long-distance drivers spend many nights away from their families, potentially disrupting family relationships. Furthermore, the observed medication utilization patterns and limited access to mental health services imply that drivers do not consistently receive care aligned with evidence-based practices, as outlined in recommended guidelines [18].

To develop personalized intervention approaches for these occupational roles, the government requires a deeper understanding of how work-related factors differentially affect the health of long-distance and short-distance drivers [19] [20]. Up to this point, there is a lack of research on truck drivers' physical and mental health in Brazil. Any intervention aimed at improving the health and well-being of drivers must be implemented in the local context, making it essential to understand the specific health challenges Brazilian drivers face.

Therefore, the main objectives of this article are: a) to characterize the cardiovascular risk profile among long-haul Brazilian truck drivers and b) to assess the impact of this risk profile on the prevalence of cardiovascular events during a 3-year follow-up period.

Study Design and Setting:

This prospective cohort study was conducted among long-distance truck drivers traveling on BR 277, one of the main federal highways in the country known for heavy truck traffic transporting agricultural inputs, grain harvests, and fuels. As in a previous study [5], participant sampling and evaluation were carried out at four locations along the BR 277 route, including two-grain processing, storage, and distribution facilities, a fuel storage and distribution company and an agricultural input distributor. Authorization was obtained to conduct the study at these locations, with a specific request for appropriate physical space to ensure participant confidentiality and comfort. The study was approved by the Research Ethics Committee of the Universidade Estadual do Centro-Oeste (approval number 1.593.832/2016) and was conducted from June 2016 to September 2021.

Study Population and Inclusion Criteria:

Truck drivers over the age of 18 were included in the study. Sequential invitations to participate in the research were extended to subjects as they arrived and awaited cargo loading and unloading, from 8 a.m. to 5 p.m., on all days of the week. Inclusion criteria required participants to be able to: 1) provide informed consent by signing a consent form; 2) transport cargo over long distances, exceeding a 160 km radius from their home terminal; 3) be able to return to the exact location for follow-up visits on two future dates and 4) not use non-steroidal anti-inflammatory drugs.

Protocol Sequence

All participants underwent clinical assessments at three distinct timepoints. Subsequently, the truck drivers were monitored via telephone for three consecutive years regarding any health-related incidents to identify cardiovascular outcomes. Furthermore, at the end of the three-year monitoring period, a search was conducted in the national mortality (DATASUS- SIM: Mortality Information System) and hospitalization (SIH-SUS: Hospital Information System) database (Figure 1).

Clinical evaluation

This study conducted a thorough clinical evaluation to assess the cardiovascular risk factors among truck drivers. The assessment involved interviews to gather information on socio-demographic characteristics, occupational factors, chronic disease history, medication use, lifestyle habits, and family history of cardiovascular disease. Additionally, routine and specific exams to detect cardiovascular structure and function (target organ damage) were performed to provide objective data related to cardiovascular health. These variables collectively provide comprehensive information on the demographic, occupational, medical, and physiological aspects of cardiovascular health among truck drivers.

Interview-based variables:

Socio-demographic characteristics: Age, Education level, Race/color and

Home state

Truck Driver Profession-related Factors years in the job (years of professional experience as a truck driver); Hours driven per day; Kilometers driven per day
Medical History and Lifestyle Habits: Prior diagnosis of chronic diseases: Use of medications (including details of drug class and dose); Physically active or sedentary lifestyle; Consumption of alcohol or other stimulants; Smoking habits; Family history of cardiovascular disease (specifically, heart disease, myocardial infarction, bypass surgery, or cardiac catheterization in first-degree relatives under the age of 55 for males and 65 for females)

The definitions and criteria used to ensure precise characterization of crucial factors during cardiovascular risk assessment among truck drivers are presented as supplement 1.

Electrocardiogram (ECG) recordings: The resting 12-lead ECG was obtained using a standardized approach with the Micromed device (Wincardio USB - Version 4.4.a. MICROMED Biotecnology Ltda, Brasília - DF) for all study participants. The acquired ECGs were carefully analyzed to assess the cardiac rhythm and determine the presence of left ventricular hypertrophy (LVH). To evaluate LVH, we employed both the Sokolow-Lyon criteria and the Cornell voltage-duration product criteria.

Heart rate variability – signal acquisition and analyses: Electrocardiogram (ECG) recordings were obtained using a digital electrocardiograph (Micromed, Brazil) at a sampling ratio of 250 Hz. Wincardio (4.4a) software was utilized to automatically generate the R-R interval series from the 12-lead derivations, employing traditional adhesive disposable electrodes. Manual removal of incorrect detections or ectopic beats was performed as necessary. The ECG recordings were obtained to ensure optimal data acquisition while the trucker rested in a supine position in a quiet room, breathing spontaneously. The 15-minute recording was obtained following a 15-minute adaptation period. Before the recording, participants were instructed to refrain from consuming food, caffeine or cigarettes for at least 30 minutes. The stored ECG data were subsequently analyzed to calculate heart rate variability (HRV) values, using CardioSeries software (version 2.4, CardioSeries Software, Universidade de São Paulo, Brazil). All recorded segments were visually inspected, and nonstationary data segments were discarded. A Hanning window was used to minimize artifacts, and the spectrum of each segment was computed using a direct Fast Fourier Transform (FFT). Spectral bands were defined according to established literature references for human HRV evaluation, including low frequency (LF) in the range of 0.04-0.15 Hz, high frequency (HF) in the 0.15-0.4 Hz range, and total power. Spectral components were expressed in absolute values (ms2) and normalized units (nu). Normalized units were calculated by determining the percentage of LF and HF components concerning the total power after subtracting the power of the very-low-frequency component (frequencies <0.04 Hz). Following established methods, the LF/HF ratio of HRV was calculated to assess sympatho-vagal balance. Analysis of the computation of HRV parameters using this well-established technique ensured an accurate assessment of the heart rate variability and sympathetic-vagal balance among the study participants.

The ankle-brachial index (ABI): The ankle-brachial index (ABI) is the systolic blood pressure (SBP) ratio measured at the ankle to that measured at the brachial artery. We used the method indicated by the American Heart Association Statement [22]. Briefly, with the patient resting supine, blood pressure cuffs were placed around the upper arms and ankles to perform the ABI measurement. A Doppler ultrasound device (Medpej - DF-7000-VB, Alphaville, São Paulo, Brazil) was used to detect flow arterial signals of both brachial arteries and of the posterior tibial and dorsalis pedis arteries of both ankles. To calculate the ankle-brachial index, we used the higher ankle systolic blood pressure divided by the higher brachial systolic pressure. An ABI value around 1.0-1.4 indicates normal blood flow, while values below 0.9 suggest the presence of peripheral artery disease.

Follow-up of cardiovascular outcomes monitoring:

After completing the inclusion protocol to monitor cardiovascular outcomes, we conducted telephone interviews with the truck drivers or their family members for three years. These interviews aimed to collect information about their health status, occurrences of health problems and traffic accidents. Additionally, we conducted consultations in the National Mortality System (SIM-SUS) and Hospitalizations (SIH-SUS), which are national databases managed by the Department of Informatics of the Unified Health System (DATASUS).

Statistical analyses

We analyzed the data descriptively and presented absolute and relative frequencies for categorical variables and summary measures (mean, quartiles, minimum, maximum, and standard deviation) for numerical variables. We used the Chi-Square test to verify the existence of associations between two categorical variables. We used Fisher's exact test as an alternative for small samples. We used the standardized adjusted residual to identify local differences for differences in distributions. Cells with absolute values above 1.96 indicate evidence of associations (local) between the categories relative to those cells. We compared two and more than two means using the Student's t-test and Analysis of Variance (ANOVA), respectively. Both tests assume normality in the distribution of data and homoscedasticity, which we verified using the Kolmogorov-Smirnov and Levene's tests, respectively. If data normality was violated, we compared means using the non-parametric Mann-Whitney test (comparison of two means) and the Kruskal-Wallis test. If we detected differences in means in ANOVA and the Kruskal-Wallis test, we would identify groups of distinct means using Duncan's multiple comparisons and Dunn-Bonferroni, respectively, maintaining a global significance level of 5%. We assessed linear associations between numerical variables via Spearman correlation due to the absence of normality in the data distribution. We used univariate and multivariate Poisson regressions to evaluate the effects of general, clinical, and heart rate variability characteristics on CVD incidence rate. This model is used to count data observed over some time. We performed tests of fit adequacy of multivariate models to verify the existence of overdispersion (dispersion of observations higher than expected). In the initial multivariate model, we considered significant variables at 10% in the univariate analysis as predictors due to the number of predictor variables versus the sample size. Then, we excluded non-significant variables at 5%, one by one in order of significance (backward method). For all statistical tests, we used a significance level of 5%. We performed the analyses using SPSS 20.0 and STATA 17 software packages.

This study analyzed information from 309 truck drivers. Subjects were middle-aged adults, considering their average age of 45 years, with a minimum age of 20 and a maximum of 68 year It is important to highlight that 24 subjects were under 30 years of age.

Most of the participants (75%) had been in the profession for over 10 years, with an average of 19.3 years, and 57.3% were employed by transportation companies. The average distance traveled was 572.7 ± 208.6 km/day, and 18.4% reported driving for more than 12 hours per day.

The study revealed a high prevalence of lifestyle risk factors, such as smoking (22%), regular alcohol consumption (75.7%), lack of physical activity (68.6%), and stimulant use during work (10.4%). Hypertension was reported by 23% and diabetes by 6%, but few subjects were under specific medications. Additionally, a significant proportion of the truck drivers reported a family history of early cardiovascular disease in first-degree relatives (37.9%).

The clinical characteristics assessed in the truck drivers showed several parameters related to poor cardiovascular outcomes, including excess body mass, metabolic alterations (high TC, LDL, and HbA1c levels), hypertension (25%), and diabetes mellitus (20%). Notably, there was a high prevalence of prehypertension (22.2%) and prediabetes (42.2%), indicating potential underdiagnosis of these chronic conditions (Table 1). The study also found a high prevalence of Metabolic Syndrome and a relevant CV risk profile among the participants. Besides, increased hs CRP (mg/l) was predominant subclinical, suggesting a chronic subclinical inflammation process. According to the Berlin Questionnaire,152 truck drivers, almost half of the subjects, had a high risk for OSA.

Heart rate variability (HRV) analysis revealed an imbalance in the autonomic nervous system, with higher sympathetic activity compared to vagal activity (Table 1; Table 2).

Subclinical target organ damage was detected in almost 30% of the truck drivers, with alterations in the ankle-brachial index (ABI) and left ventricular hypertrophy (LVH) being the most common findings.

Regression analyses identified factors associated with target organ damage, such as Afro-descendant ethnicity and alcohol abuse. Afro-descendent subjects were 3.4 times more likely to have left ventricle overload on EKG compared to white individuals. At the same time, alcohol abuse increased by 2.1 times the chance of having left ventricle overload on EKG or increased BAI compared to nonalcohol users (Table 2).

Positive correlations were found between years in the job and various clinical parameters, including blood pressure, body mass index, abdominal and cervical circumference, and glycated hemoglobin indices. Longer time in the profession was also associated with alterations in HRV, particularly a decrease in vagal activity, evidenced by reduced in both SDNN and MSSD parameters (Table 3).

During the 3-year follow-up period, 11 major cardiovascular outcomes occurred among 10 truck drivers: one death from cardiogenic shock, three angioplasties, two ischemic cerebrovascular accidents, two cases of congestive heart failure, one case of peripheral arterial disease with lower limb amputation, one case of chronic renal failure related to hypertension, and one case of recurrent hospitalizations due to hypertensive crisis, resulting in an incidence rate of 1.10 CVD per 100 truck drivers per year. The incidence rate of CVD in this middle-aged population was 1.10 CVD per 100 truck drivers per year (95% CI: 0.57 to 2.12).

The multivariate Poisson regression model identified years of profession, abdominal circumference, and confirmed diabetes mellitus as significant predictors of CVD risk (Table 4). Therefore, an increase of 1 year in the years of profession leads to a 17% increase in the risk of CVD, and an increase of 1 cm in abdominal circumference results in an 8% increase in the risk of CVD. Additionally, the risk of CVD in truck drivers with confirmed diabetes mellitus is 5.95 times higher than in those without this condition.

A predictive risk model was established based on these variables, estimating the expected number of CVD cases within five years for different clinical profiles (Table 5). This model predicts that in a group of truck drivers with more than 25 years of profession, with abdominal circumference of 102 cm and confirmed diabetes mellitus, it is expected that approximately 15 cases of CVD will occur within five years.

The results of this study highlight the high prevalence of cardiovascular risk factors and the incidence of CVD among long-haul truck drivers in South Brazil. The findings emphasize the need for targeted interventions and health promotion strategies to improve the cardiovascular health of this occupational group.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide, and certain occupational groups, such as long-haul truck drivers, may be at increased risk due to their unique work environment and lifestyle factors. This study aimed to comprehensively assess the prevalence of cardiovascular risk factors and the incidence of major cardiovascular events among 309 long-haul truck drivers in South Brazil, revealing alarming findings that underscore the urgent need for targeted interventions to improve the cardiovascular health of this critical occupational group.

Our findings on the high prevalence of CVD risk factors are consistent with our previous publication [5] and other studies that have demonstrated the significant presence of CVD risk factors among truck drivers worldwide [23, 24]. When comparing the prevalence of CV risk factors in truck drivers to data from a general population surveyed in a National Program [25], we found that hypertension was present at a similar prevalence (25%). However, truck drivers had a higher prevalence of obesity (44% vs. 20%), diabetes (25% vs. 9%), and smoking (22% vs. 11%). Furthermore, up to 51% of the participants in our study had abnormal lipid levels. A significant proportion of the drivers met the criteria for Metabolic Syndrome and had a high risk for CV events.

The presence of cardiovascular risk factors and medical conditions may have a significant impact on roadway safety. A large cross-sectional study demonstrated a positive correlation between the presence of CV risk factors in commercial motor vehicle drivers (N = 797) and crashes. After adjusting for confounders, drivers in the two highest CVD risk groups had a nearly threefold higher likelihood of crashes. There was a significant trend of increasing crash prevalence with an increasing CVD risk score (p = 0.0298) [4]. Another study analyzed a retrospective cohort of 38,184 drivers and evaluated concomitant medical conditions and subsequent crashes from 2005 to 2012. Drivers with three or more medical conditions had a significantly increased risk of crashes and preventable crashes with injuries after adjustment for covariates [8]. Similarly, our population has many concomitant medical conditions, which imposes a significant risk factor for preventable crashes with injuries.

Roadway safety is a highly complex issue influenced by various factors, including irregular work hours, inconsistent sleep schedules, poor eating and exercise habits, and mental and physical stress, all of which contribute to fatigue [26]. Additionally, overweight and obesity, metabolic disorders, and obstructive sleep apnea (OSA) are highly prevalent among commercial motor vehicle (CMV) drivers.

Sleep disorders are common in commercial drivers, with OSA being the best-studied and most identifiable [27]. The gold standard for diagnosing OSA is nocturnal polysomnography (PSG), which is defined through the apnea-hypopnea index (AHI). However, patients must stay overnight at a proper PSG laboratory, which is time-consuming and costly. Therefore, we used the Berlin Questionnaire (BQ) to identify subjects at risk for OSA and found a significantly high number of truck drivers with a high risk for this condition. The BQ is a validated questionnaire covering three categories: presence of nighttime snoring (five questions), excessive daytime sleepiness (four questions), and diagnosis of hypertension or obesity (one question). Categories are scored as follows: two or more positive answers in categories 1 and 2 and a positive answer to the question in category three or BMI > 30kg/m2. When two or more categories are considered positive, this indicates a high risk for OSA [28]. It is well established that there is a good correlation between BQ and OSA diagnosed with nocturnal polysomnography in Metabolic Syndrome patients [29]. A robust finding of this study was that, particularly in patients with severe OSA, BQ has been shown to have high sensitivity for OSA screening (91%) [29].

As cognitive and motor processing declines with fatigue and sleep disorders, driver performance decreases, and the risk of errors, near crashes, and crashes increases. However, another possibility is the occurrence of acute cardiovascular events in long-distance truck drivers, which may jeopardize roadway safety. We can suggest this hypothesis considering the burden of risk factors and the evidence of subclinical target organ damage detected in our population. Vascular stiffness, left ventricular overload, inflammatory state, and increased cardiac sympathetic modulation were highly prevalent in our population. Moreover, major clinical events, including acute coronary syndromes and cardiovascular death, occurred rapidly in our population.

It is well-recognized that subclinical inflammation is independently associated with the components of Metabolic Syndrome and with OSA [30]. Increased levels of the inflammatory biomarker high-sensitivity C-reactive protein (hs-CRP) independently predict future vascular events and improve global risk classification, regardless of the LDL cholesterol level [31] [32] [33]. We demonstrated that our subjects had a moderate to high cardiovascular risk based on their CRP levels. A prospective outcome trial has directly addressed whether healthy persons with elevated hs-CRP levels and LDL cholesterol levels below current treatment thresholds might benefit from statin therapy [34]. Most of the long-distance truck drivers in the present study had clinical characteristics like those in the statin therapy trial. For men aged 50 and over, with an hs-CRP level of 2.0 mg per liter or more, rosuvastatin significantly reduced the incidence of major cardiovascular events [34]. Therefore, we can speculate that our subjects had an increased risk of CV events and would likely benefit from statin therapy.

In addition to the CV risks detected, we also registered an increased sympathetic modulation and a decreased parasympathetic modulation to the heart by calculating heart rate variability (HRV). HRV is a non-invasive method that assesses the autonomic nervous system's influence on the heart, providing valuable information about the balance between sympathetic and parasympathetic activity [35]. In our study, we observed a shift in the autonomic balance towards increased sympathetic and decreased parasympathetic modulation in the long-distance truck drivers. This finding is particularly relevant, as an imbalance in the autonomic nervous system, characterized by increased sympathetic activity and reduced parasympathetic activity, has been associated with an increased risk of cardiovascular events, such as arrhythmias, myocardial infarction, and sudden cardiac death [36] [37]. The increased sympathetic modulation observed in our subjects may be attributed to various factors, including chronic stress, sleep disorders, and the presence of metabolic syndrome components [38] [39]. On the other hand, the decreased parasympathetic modulation may be related to the high prevalence of obstructive sleep apnea and obesity in this population [40] [41]. These findings highlight the importance of assessing autonomic function in long-distance truck drivers, as it may provide additional insights into their cardiovascular risk profile and help guide preventive strategies to reduce the incidence of cardiovascular events in this high-risk population.

Some limitations need to be mentioned. The first relates to the low number of major CV events. However, considering the small follow-up period and the low age of subjects, the rate of events can be considered significantly elevated. The combined LVH outcome measured by EKG may result in underestimating the number of participants with cardiac hypertrophy since echocardiography, considered the gold-standard measure, was not performed. We analyzed HRV only once while the subjects were on their workday on the road. We need to find out whether these alterations persist during rest days.

In conclusion, our study highlights the high prevalence of cardiovascular risk factors and the increased incidence of major cardiovascular events among long-haul truck drivers in South Brazil. These findings emphasize the need for targeted interventions to improve the cardiovascular health of this critical occupational group, which may have significant implications for roadway safety and public health. Future research should focus on developing and evaluating effective strategies to mitigate fatigue, promote healthy lifestyles, and improve access to healthcare services for long-distance truck drivers.

DATASUS- SIM - Mortality Information System

SIH-SUS - Hospital Information System

ECG- Electrocardiogram

LVH - Left Ventricular Hypertrophy

HRV - Heart Rate Variability

FFT – Fast Fourier Transform

LF - Low Frequency

HF- High Frequency

ABI - Ankle-Brachial Index

CVD - Cardiovascular Disease

SBP: Systolic Blood Pressure

DBP: Diastolic Blood Pressure

BMI: Body Mass Index

AC: Abdominal circumference

NC: Neck Circumference

TC: Total Cholesterol

LDL: Low density Lipoprotein;

HDL: High Density Lipoprotein

HbA1c: hemoglobin A1C

hsCRP: High-sensitivity C-reactive protein

Ethics approval and consent to participate

The study was approved by the Research Ethics Committee of the Universidade Estadual do Centro-Oeste (approval number 1.593.832/2016) and was conducted in accordance with the World Medical Association’s International Medical Ethics Code (Declaration of Helsinki).

Consent for publication

Not applicable.

Availability of data and materials

All data generated are included in this article and its supplementary information files. The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

FMCC receives grants for research from National Council for Scientific and Technological Development - CNPq, Brazil

Authors' contributions

CTS conceived and designed the protocol, collected, analyzed, performed the variability data analyzes, interpreted the data and wrote the paper; JSB, JCS,WRG recruited participants, undertook the data collection and drafted the article; MRT, TB, MHL, BP have planned, operationally ran and wrote part of the paper; JVS analyzed data and co-wrote the paper and FCC facilitated the conduct of the study and provided overall guidance for the conception and discussions and in writing and editing the manuscript. All authors approved the final version.

Acknowledgements

We acknowledge to Araucaria Foundation to Support the Scientific and Technological Development of the State of Paraná (FA) for financial support for scholarships. We also thank the Agraria Cooperative by providing room for evaluation of truck drivers.

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Table 1. Clinical profile of long-distance truck drivers

	Mean±SD	Median (minimum- maximum)
SBP (mmHg)	134.00 ± 18.83	130. 00 (80.00 – 200.00)
DBP (mmHg)	83.00 ± 13.00	80.00 (50.00 – 150.00)
BMI (kg/m²)	29.27 ± 4.54	28.83 (17.76 – 48.39)
AC (cm)	104.36 ± 11.60	103.00 (77.00 – 149.00)
NC (cm)	42.11 ± 3.10	42.00 (29.00 – 50.00)
TC (mg/dl)	203.21 ± 42.64	200.11 (102.80 - 332.20)
LDL (mg/dl)	125.79 ± 37.92	122.90 (39.70 – 254.90)
HDL (mg/dl)	44.85 ± 6.97	44.00 (30.00 – 72.00)
HbA1c	6.00 ± 0.90	5.90 (4.11 – 11.59)
hsCRP (mg/l)	3.21 ± 4.48	1.87 (0.12 – 37.62)
LF(nu)	56.63 ± 14.28	57.00 (5.00 – 92.00)
HF(nu)	42.94 ± 14.00	43.00 (8.00 – 95.00)
LF/HF ratio	2.00 ± 1.77	1.60 (0.6 – 3.95)
ABI	1.16 ± 0.20	1.10 (0.54 – 2.12)

SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BMI: Body Mass Index; AC: Abdominal circumference; NC: Neck Circumference; TC: Total Cholesterol; LDL: Low density Lipoprotein; HDL: High Density Lipoprotein; HbA1c: hemoglobin A1C; hsCRP: High-sensitivity C-reactive protein; ABI - Ankle Brachial Index; LF (nu): low frequency in normalized units; HF (nu):high frequency in normalized units.

Table 2. Associated factors with the presence of subclinical target organ damage among long-distance truck drivers.

	Initial Multivariate Model		Final Multivariate Model
	Adjusted CR (95% CI)	p	Adjusted CR (95% CI)	p
Color/Ethnicity (ref. White)		0,050		0,038
Afro	3,26 (1,10 - 9,63)	0,032	3,42 (1,19 - 9,83)	0,023
Brown	1,65 (0,85 - 3,17)	0,136	1,62 (0,85 - 3,09)	0,141
Marital status (ref. = married)		0,066		-
Single	2,92 (1,25 - 6,83)	0,013	-	-
Stable union	0,79 (0,28 - 2,25)	0,656	-	-
Divorced/Widowed	1,69 (0,52 - 5,50)	0,386	-	-
Alcohol consumption	1,95 (0,98 - 3,89)	0,058	2,12 (1,07 - 4,18)	0,031
BMI at risk	0,49 (0,25 - 0,97)	0,141	-	-
Neck circumference (cm)	0,92 (0,83 - 1,02)	0,116	-	-

Table 3. Correlations between time in the profession and clinical variables among long-distance truck drivers

Variables	Years in the professional job
	r²	p-value
Age (years)	0.752	0.000
Years of Education	-0.366	0.000
SBP (mmHg)	0.384	0.000
DBP (mmHg)	0.233	0.000
IMC (kg/m²)	0.200	0.000
AC (cm)	0.347	0.000
NC (cm)	0.280	0.000
TC (mg/dl)	0.078	0.239
HDL (mg/dl)	-0.145	0.027
LDL (mg/dl)	0.065	0.325
HbA1c (%)	0.396	0.000
hsCRP (mg/dl)	0.069	0.292
SDNN (ms)	-0.166	0.050
rMSSD (ms)	- 0.231	0.000
LFnu	0.210	0.000
HFnu	- 0.144	0.017
LF/HF	0.039	0.525

SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BMI: Body Mass Index; AC: Abdominal circumference; NC: Neck Circumference; TC: Total Cholesterol; LDL: Low density Lipoprotein; HDL: High Density Lipoprotein; HbA1c: hemoglobin A1C; hsCRP: High-sensitivity C-reactive protein; SDNN: Standard deviation of all NN intervals (ms); rMSSD: square root of the mean of the sum of the squares of differences between adjacent NN intervals; LF (nu): low frequency in normalized units; HF (nu):high frequency in normalized units; Ratio LF/HF.

Table 4. Variables associated with the occurrence of cardiovascular disease among long-distance truck drivers.

	Initial Multivariate Model		Final Multivariate Model
	Adjusted RR (95% CI)	p	Adjusted RR (95% CI)	p
Age group - over 55 (ref. under 55)	3,34 (0,05 - 244,82)	0,583	-	-
Education (ref. = illiterate/Primary)		0,706
Elementary school	0,34 (0,02 - 4,91)	0,428	-	-
Secondary school	1,97 (0,12 - 33,22)	0,637	-	-
Higher Education	(1)	0,998	-	-
Time in the profession (years)	1,08 (0,91 - 1,28)	0,380	1,17 (1,07 - 1,29)	0,001
Employment relationship - hired (ref.= self-employed)	0,40 (0,03 - 5,82)	0,502	-	-
Family history of CVD	3,04 (0,10 - 93,78)	0,525	-	-
Informed DM	0,36 (0,00 - 132,24)	0,734	-	-
Informed SAH	243,90 (0,34 - 176.085,33)	0,102	-	-
Difference in SBP	1,89 (0,18 - 20,39)	0,599	-	-
Antihypertensive use	0,02 (0,00 - 10,09)	0,216	-	-
BMI (kg/m2)	1,09 (0,49 - 2,45)	0,833	-	-
Abdominal Circumference (cm)	1,07 (0,82 - 1,40)	0,622	1,08 (1,01 - 1,16)	0,033
ABI	10,55 (0,25 - 447,00)	0,218	-	-
Sleep disorder - altered	3,21 (0,00 - 3.078,84)	0,739	-	-
HbA1c	1,28 (0,29 - 5,71)	0,743	-	-
DM confirmed - Diabetes mellitus	6,78 (0,29 - 156,73)	0,232	5,95 (1,43 - 24,68)	0,014

Table 5. Predictive model of cardiovascular disease risk in truck drivers

Profile			Estimated total (N=309)
Time in the profession (years)	Abdominal Circumference (cm)	DM confirmed - Diabetes mellitus	Within 3 years	Within 5 years	Within 10 years
11,0	102,0	Yes	0,84 (0,00 - 1,67)	1,39 (0,00 - 2,79)	2,79 (0,00 - 5,58)
16,0	102,0	Yes	1,85 (0,28 - 3,41)	3,08 (0,47 - 5,68)	6,15 (0,95 - 11,36)
21,0	102,0	Yes	4,08 (1,80 - 6,36)	6,79 (2,99 - 10,59)	13,59 (5,99 - 21,19)
25,0	102,0	Yes	9,00 (4,91 - 13,09)	15,00 (8,18 - 21,82)	30,01 (16,37 - 43,65)

No competing interests reported.

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Comprehensive Assessment of Cardiovascular Risk Factors among Long-Haul Truck Drivers in South Brazil and its Impact on 3-year follow-up of Cardiovascular Events

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