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Prevalence of metabolic syndrome in commercial truck drivers: A review J. Erin Mabry a,c,n, Kathy Hosig b, Richard Hanowski c, Donald Zedalis d, John Gregg e, William G. Herbert a a Laboratory for Health and Exercise Science, Department of Human Nutrition, Foods and Exercise, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061 USA b Department of Population Health Sciences, Virginia-Maryland Regional College of Veterinary Medicine, Blacksburg, VA, 24061 USA c Center for Truck and Bus Safety, Virginia Tech Transportation Institute, Blacksburg, VA, 24061 USA d Allergy & Asthma Associates & Sleep Disorders Network of Southwest Virginia, Christiansburg, VA, 24073 USA e Department of Oral and Maxillofacial Surgery, Virginia Commonwealth University, 521 N 11th St #311, Richmond, VA, 23298 USA
art ic l e i nf o
Keywords: Metabolic syndrome Commercial driver Truck driver Occupational health Obesity
a b s t r a c t Introduction: The lifestyle of commercial truck drivers may increase this occupational groups' susceptibility to health disparities, including obesity, cardiovascular and metabolic disorders. Identification of Metabolic Syndrome (MetSyn) in commercial truck drivers may aid in early recognition of risk for cardiovascular disease to support primary intervention techniques. Epidemiological studies have yet to evaluate MetSyn among commercial drivers; however, studies have examined the prevalence of the individual components. Objective: To examine the prevalence of components of the MetSyn among commercial truck drivers, compare to those of the general U.S. adult population, and identify the most prevalent components to prioritize initiatives for health interventions. Methods: A review of the literature was conducted that evaluated one or more MetSyn component in commercial truck drivers. Articles were collected from a Pub Med MEDLINE search that was limited to research conducted on commercial truck drivers published within the previous 10 years (2005–2015). Twenty-seven articles met the criteria for inclusion in this systematic review. Results: All studies were original reports with sample sizes ranging from 30 to 88,246 subjects, all of which were commercial truck drivers. The mean driver age range in the studies reviewed was 38–48 years of age. Studies included cross-sectional investigations, longitudinal, cohort, naturalistic, descriptive, and case-control studies. Abdominal obesity may affect 19–74% of commercial truck drivers; overweight and obesity, 23–53% and 15–70% of drivers, respectively; hypertension, 5–48% of drivers; dyslipidemia may affect 7–46% of drivers; and diabetes, and 1–22% of commercial truck drivers. Conclusions: Abdominal obesity is the most prevalent MetSyn component and risk factor for CVD among commercial truck drivers. Additional, research is necessary to evaluate large, representative groups of drivers and to collect measured indices of MetSyn to more accurately predict MetSyn prevalence among this group. Future health intervention studies for commercial truck drivers should focus on obesity prevention, management and treatment. & 2016 Published by Elsevier Ltd.
1. Introduction 1.1. Commercial truck drivers Commercial truck drivers play a crucial role in the flow of commerce and goods across America. In 2008, the trucking industry hauled 68.8% of all the tons of freight transported in the U.S., equating to 10.2 billion tons of freight hauled by over 29 million trucks and
n
Correspondence to: Center for Truck and Bus Safety, 3500 Transportation Research Plaza, Blacksburg, VA 24061, USA. Fax: þ540 231 1555. E-mail address:
[email protected] (J. Erin Mabry).
http://dx.doi.org/10.1016/j.jth.2016.06.012 2214-1405/& 2016 Published by Elsevier Ltd.
Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
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3.4 million truck drivers (Trucking Trends, 2008–2009). The trucking industry is an astounding $660 billion industry; representing 83.1% of the nation's freight bill (U.S. Freight Transportation Forecast to…2020). The typical lifestyle of a commercial motor vehicle (CMV) truck driver may include irregular work and sleep hours, physical inactivity, poor eating habits and nutrition, and mental and physical stress. Since the update to the Hours of Service regulations in 2011, a long-haul driver may spend up to 11 h of driving and 14 h on-duty per day, and up to 60 total driving hours in a 7-day period or 70 driving hours in an 8-day period (Hours of Service Regulations, 2011). Truck drivers typically work irregular schedules and must frequently invert their sleep-wake cycle, sleeping during the day and remaining awake at night. Their day to night work schedule can also change frequently, depending on work demand. In order to cope with these schedule demands, professional drivers may be unable to obtain enough sleep and thus suffer partial sleep deprivation (Kecklund and Akerstedt, 2000). Long hours spent driving and inadequate sleep can limit motivation and opportunities for exercise, in addition to encouraging unhealthy eating habits. Drivers may spend the majority of their day in their truck cab and sleeper berth, further constraining their daily physical activity. To maximize their federally-restricted driving hours, truck drivers may snack all day to keep their energy up and consume one large meal at the end of their shift. This group is also restricted to eating at the restaurants they are able to access with their large trucks, which primarily includes truck stop diners and fast food restaurants. The limited cab space inside the truck also makes it difficult to store and prepare healthier meals on the road. CMV truck drivers are subjected to a number of physical and psychological stresses inherent in their occupation, including work overload, high mileage exposure, and irregular work/rest schedules. They are also commonly isolated at work and may be exposed to daily frustrations while driving (da Silva-Junior et al., 2009). These combined circumstances have major implications for the truck driving industry and the result can compromise roadway safety and the drivers’ longterm health (Dinges, 1995; Lyznicki et al., 1998). 1.2. Commercial truck drivers and health risks The unique demands of CMV truck driving result in elevated levels of occupational fatalities, injuries, and lifestyle-related illnesses. Truck drivers account for 12% of all work-place fatalities in the Unites States and consistently rank among the top three occupations in total nonfatal injuries and illnesses (Burea of Labor Statistics, 2009a, 2009b). Additionally, these unique lifestyle characteristics may increase their susceptibility to many health risks, including obesity, cardiovascular disease (CVD), and metabolic disorders. Existing evidence suggests that commercial truck drivers may have overweight and obesity rates (body mass index [BMI] Z 25 kg/m2 and Z30 kg/m2, respectively) that far exceed that of the general American population (Thiese et al., 2015a; Harshman et al., 2008; Flegal et al., 2010). Obesity is linked to heart disease, the number-one killer of Americans, in addition to increased prevalence of hypertension (HTN), dyslipidemia, type II insulin dependent diabetes mellitus (DM), stroke, osteoarthritis, sleep apnea, and several major cancers (Anon.,1998). According to the World Health Organization (2016), approximately 90% of people living with type II insulin dependent DM are overweight or obese (WHO Fact Sheet); obesity puts pressure on the body's ability to use insulin to properly control blood sugar levels, resulting in insulin resistance. The health consequences of obesity and associated disorders may be causing CMV truck drivers to live shortened lives; evidence suggests that drivers may have a 12–19 year reduced life expectancy compared to the general U.S. male population (Saltzman and Belzer, 2007). In addition to the lifestyle and environmental factors that influence CMV drivers' risk for obesity and cardiometabolic disorders, genetics and disease interactions may also play a role, as well as complex interactions between factors. There is substantial evidence for the heritability of obesity, and research has identified genes with significant roles in the etiology of obesity; although little is known regarding the specific mechanisms that lead to the obesity phenotype (Albuquerque et al., 2015). Additionally, other diseases, such as hypothyroidism, and treatments such as steroids and antidepressants may also cause weight gain. 1.3. Metabolic syndrome Many definitions of metabolic syndrome (MetSyn) with slightly different characterizations, have been proposed; however, the most commonly used clinical definition in the U.S. is that of the National Cholesterol Education Program Adult Treatment Panel (NCEP ATP) III that includes any three component combination of the following 5 risk factors: elevated fasting glucose ( Z110 mg/dL), elevated waist circumference ( 4102 cm for men, 4 88 cm for women), hypertension (Z130/ Z85 mm Hg), elevated triglycerides (TG) (Z 150 mg/dL), and low high density lipoprotein-cholesterol (HDL-C) (o40 mg/dL for men, o 50 mg/dL for women) (Grundy et al., 2004). This review paper will focus on the NCEP ATP III markers that define the MetSyn to evaluate the prevalence of MetSyn components in the CMV truck driver population. Based on the NCEP ATP III guidelines, more than one-third of American adults may be characterized as having MetSyn (Ervin, 2009). The National Health Statistics Reports examined the prevalence of the individual risk factors for MetSyn as well as the prevalence of MetSyn using the National Health and Nutrition Examination Survey (NHANES) 2003–2006. NHANES is a cross-sectional nationally representative health and nutrition examination survey conducted by the Centers for Disease Control and Prevention's National Center for Health Statistics (Ervin, 2009). Age-adjusted estimates indicate that 34% of the U.S. population 20 years of age and over meets the NCEP ATP III criteria for MetSyn. This survey also found that abdominal obesity, HTN, and hyperglycemia are the most frequently occurring risk factors for MetSyn, with prevalence rates of 53%, 40%, and 39%, respectively. Elevated TG and low HDL-C were noted less frequently in NHANES, with U.S. prevalence rates of 31% and 25%, respectively. These findings indicate that MetSyn increases with age and BMI. Considering the average age of truck drivers is older than the U.S. labor force (49–52 years vs. 40.2 years, respectively) (American Trucking Association 2014 Driver Compensation Study), the majority of commercial truck drivers are male (95.1%) (Trucking Trends, 2008–2009) and overweight or obese (Harshman et al., 2008; Thiese et al., 2015a), it is hypothesized that the prevalence of MetSyn in this group may be higher than that of the U.S. population, but has yet to be elucidated. The pathogenesis of the MetSyn is complex and not yet fully elucidated but appears to have two primary points of origin that include obesity and insulin resistance. Other factors that have been implicated as contributors to the development of MetSyn include age, proinflammatory state, and abnormalities in hormones such as C-reactive protein, and growth hormone. The NCEP ATP III considers obesity the main contributing factor for the development of MetSyn. Obesity contributes to HTN, dyslipidemia, hyperglycemia, and is associated with risk for CVD. Abdominal obesity, specifically, is associated with metabolic dysregulation, as excess adipose tissue in the abdominal Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
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Table 1 MEDLINE keyword search terms. Primary term
Commercial motor vehicle driver
Hypertension
Obesity
Dyslipidemia
Diabetes
Synonym term
Truck driver Professional driver Trucker
Blood pressure
Overweight Waist circumference Body mass index Central fat
Hyperlipidemia Cholesterol Cholesterol Lipids High density lipoprotein-cholesterol
Glucose Insulin Resistance Insulin Resistance
region releases adipocytokines that can intensify metabolic risk factors, causing insulin resistance, which in turn exacerbates these metabolic risk factors, thereby promoting a continuous cycle of metabolic dysregulation (Grundy, 2007). 1.4. Metabolic syndrome, cardiovascular disease, and commercial truck drivers Individuals with MetSyn are at increased risk for CVD; researchers found that the MetSyn alone predicted 25% of all new-onset CVD (Lakka et al., 2002). Additionally, the primary outcome of MetSyn is CVD, according to the NCEP ATP III (Grundy et al., 2004). Research supports that it is the clustering of several of these cardiovascular risk factors, or MetSyn, that further increases risk for CVD, beyond that of the individual risk factors alone (Golden et al., 2002; Klein et al., 2002). Cardiovascular disease is not only a health concern for commercial truck drivers, as it is the leading cause of death in the U.S., but also a safety concern that can impact their livelihood. Research efforts have not determined whether truck drivers with CVD are at increased risk for a crash; however, the literature supports that, overall, motor vehicle operators with CVD are at increased risk for a crash compared to those without CVD (Federal Motor Carrier Safety Administration, 2007). Until additional research is performed, these findings from the general driving population provide supporting evidence that commercial drivers with CVD may be at increased risk for a crash. Dabrh and colleagues reviewed and summarized evidence regarding the impact of CVM driver health on crash risk, concluding that there was an association between obesity, sleep disorders, and diabetes and crash risk (Abu Dabrh et al., 2014). The Federal Motor Carrier Safety Administration (FMCSA) within the U.S. Department of Transportation is dedicated to improving the safety of commercial motor vehicles and saving lives; the FMCSA is charged with regulating the trucking industry. FMCSA regulations state that “a person is physically qualified to drive a commercial motor vehicle if that person has no current clinical diagnosis of myocardial infarction, angina pectoris, coronary insufficiency, thrombosis, or any other CVD of a variety known to be accompanied by syncope, dyspnea, collapse, or congestive cardiac failure” (Federal Motor Carrier Safety Administration Medical Examiner Handbook). Therefore, if a commercial driver has any of the above diagnoses, he/she may lose their job because they do not meet qualification standards. Thus, increased risk for development of CVD reflected in antecedent markers of MetSyn and early recognition of such increased risk is of considerable concern to both public safety and drivers' eligibility for continued licensure. The purpose of this review paper is to examine the prevalence rates and other variables indicative of individual components of MetSyn among commercial truck drivers, worldwide and to discuss these rates in relation to those of the general U.S. population. A secondary purpose is to identify the most prevalent of these MetSyn components in this group to provide a focus for future health intervention studies for truck drivers aimed at reducing health risks.
2. Methods Articles were collected from a Pub Med MEDLINE search that was limited to research conducted on CMV truck drivers, English-written articles, and those published within the previous 10 years (2005–December 2015). Abstracts were excluded, as were articles that included only bus, transit and railway drivers. Articles that discussed CMV non-truck drivers as well as CMV truck driver were included, but only the results of the truck drivers were included in this review. A complete list of the search terms is included in Table 1. This literature search resulted in 72 potential papers, 45 of which were further disqualified due to (i) irrelevance to the topic of the review paper, i.e., study results and findings were not relevant to include in the review; (ii) insufficient reporting of data to include in the review, i.e., raw data not reported; biased reporting of results due to characteristics of the research participants, i.e., research participants included only diabetic drivers. Twenty-seven articles met the criteria for inclusion in this systematic review.
3. Results 3.1. Overview of studies Table 2 reviews study findings of published articles that report the components of the MetSyn in commercial truck drivers. All studies were original reports with sample sizes ranging from 30 to 88,246 subjects, all of which were truck drivers. The mean driver age range in the studies reviewed (for those that included a mean age) was 38–48 years of age. The majority of subjects were male, with ten studies including only males (Cui et al., 2009; da da Silva-Junior et al., 2009, Martin et al., 2009; Moreno et al., 2006; Sakurai et al., 2007; Leyton 2011; Apostolopoulos 2013; Marqueze et al., 2013; Sangaleti et al., 2014; Mansur et al., 2015). Studies included cross-sectional investigations, longitudinal, cohort, naturalistic, descriptive, and case-control studies. Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
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Author
Year
n
Age (y)
Country Metabolic Syndrome Component Obesity Mean BMI (kg/m2)
Sabbagh-Ehrlich 2005 Souza 2005 Moreno
2006
Cui Jacobson 60.0% (F) Sakurai Harshman Stasko Cui
2006 2007
Parks Martin Wiegand da Silva-Junior Xie Smith Leyton Anderson Apostolopoulos Marqueze Angeles Sieber Thiese Rosso Birdsey Sangaleti Mansur Thiese
2007 2008 2007 2009
160 39 260 38.2 (10.6) 4878 40.0 (10.0) 1313 92
1465 501 42.5 30 5320 44.7 (9.3) 2009 456 39.2 (11.7) 2009 2590 45.2 (10.4) 2009 103 2009 300 37.8 (9.3) 2011 1890 43.7 (11.5) 2011 595 2011 452 40.0 (10.8) 2012 744 2013 316 44.2 (10.7) 2013 57 39.8 (6.6) 2014 406 2014 1670 48 2015a 88246 46.0 (10.4) 2015 308 42.8 (9.7) 2015 1265 Z 20 2014 250 41.9 (10) 2015 2228 43.1 (10.8) 2015b 797 47.2 (10.5)
Israel Brazil
a a
27.6 (4.3)
Brazil
a
27.8 (4.5)
Japan U.S.
a
24.0
Japan U.S. U.S. Japan
Overweight (%) Obese (%) Abdominal obesity 37.5
a
a 35 29.7
28.2
53.4
HTN (%) Mean SBP (mm Hg) a
5
a
13.8
Mean DBP (mm Hg)
BP Meds (%)
8.1
73.6% (M) a 28.1 28.3 a 36.7 a 30
6.2 a 1
21.0
41
127.3
79.5
a 7.6 41.5
a
a
a
10.4
123.1 (11.7)
79.1 (8.4)
128.0 (13.1)
81.0 (8.6)
126.8 (13.2)
81.1 (8.1) a
11
129.7 (14.0)
69.1 (30.2)
53.4 a
U.S.
30.5 (6.6)
U.S. Brazil
a
35.9
33.9
Brazil
43.9
Canada U.S. U.S.
a
a
Italy 32.6 27.9 (3.9)
Brazil
46.8
30.5 83.4
15.7
6.9
a
21.5
a
39.5 16.8
a
4.4
a
22
33.7
19.3
7 a
a
53.2 22.8 31.0
a
68.9 53.3
a
a
a
a
46
50
27.5
a
a
21
30
55.2–65.5 32.9 (7.5)
a
69.6
a
31.7 (7.2)
a
4.7
a
U.S. U.S.
U.S.
17.3
16.0
U.S. Brazil
U.S. Brazil
6.9
a
55
32.0 (7.3)
TG (%)
a
57.1
30
U.S.
Hyperlipidemia (%) HDL-C
15 26.5
a
29.1 (5.0)
Hypertension
a
90
U.S.
Dyslipidemia
a
29.8 24.8 (3.6)
Insulin Resistance % DM
61.9
45.6
7 14.4
38.6%
21.7
35.1
26.3
1
58.2%
16.4
19.8–52.8%
10.1–14.9
44.6 (6.8) in. (WC)
a
45.6%
10.7
45.2
a
4.4–13.9 38.8
25.8– 39.6% 36.6 (14.1) mg/dL
132 (17)
84.4 (10.3)
131.9 (17.4)
84.3 (10.7)
24–39.6 47.9
All mean values expressed as Mean7 SD. Abbreviations: BMI¼ body mass index, WC¼ waist circumference, M ¼male, F ¼ female, DM ¼diabetes mellitus, HDL-C¼ high density lipoprotein-cholesterol, TG-triglycerides, HTN-hypertension, SBP ¼systolic blood pressure, DBP¼ diastolic blood pressure, BP ¼blood pressure. a
Indicates self-report.
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Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
Table 2 Reviewed studies including components of the MetSyn among commercial truck drivers.
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3.2. Prevalence of MetSyn components in CMV drivers 3.2.1. Abdominal obesity Abdominal obesity, considered the primary component of the MetSyn, is accurately defined by waist circumference (WC), a marker of abdominal fat mass. Android obesity, or excess abdominal fat, is a greater predictor of cardiometabolic health risk as compared to gynoid obesity, excess fat in the hip or thigh region (Despres and Lemieux, 2006). A WC measure greater than 40 in. (102 cm) for men and 35 in. (88 cm) for women is considered a risk factor for cardiometabolic disease in the U.S. Ancillary measures that are evaluated more frequently for research and clinical purposes, and also indicate obesity, include BMI, a measure of weight for height. Overweight is defined as a BMI between 25 and 30 kg/m2 and obesity is defined as a BMI greater than 30 kg/m2. Although BMI is not a direct measure of body fat and composition and does not consider fitness level or body shape, it is strongly correlated with metabolic and disease outcomes consistent with more direct measures of body fatness, i.e., skinfold measurements, densitometry, etc. (Steinberger et al., 2005). Of the studies reviewed, all but four reported at least one measure of obesity (i.e. mean WC or BMI or prevalence of overweight, obesity, or elevated WC) for the sample. The prevalence of elevated WC, indicative of abdominal obesity, was 19.8–73.6% among study participants included in this review (Jacobson et al., 2007; Sangaleti et al., 2014; Mansur et al., 2015). One study evaluated mean WC among participants [mean ¼ 44.6 (6.8) in.] and reported values indicative of abdominal obesity and risk for cardiometabolic disease (Thiese et al., 2015b). Mean BMI was reported in thirteen studies; five studies included participant self-report via questionnaires or interviews (range¼24.0–33.9 kg/m2) (Souza et al., 2005; Moreno et al., 2006; Cui et al., 2006, 2009; Smith and Phillips, 2011). Eight studies reported measured calculations of driver BMIs (range¼27.9–32.9 kg/m2) from either a Department of Transportation (DOT) physician during a routine physical or a researcher as part of the study procedures (Harshman et al., 2008; Parks et al., 2009; Martin et al., 2009; Xie et al., 2011; Thiese et al., 2015a, 2015b; Birdsey et al., 2015; Sangaleti et al., 2014). Prevalence rates of overweight and/or obesity were reported in twenty studies, nine of which were self-reports of height and weight from study participants (range ¼ 22.8–53.2% overweight; range¼15– 69.6% obese) (Sabbagh-Ehrlich et al., 2005; Souza et al., 2005; Cui et al., 2006; Smith and Phillips, 2011; Anderson, 2012; Apostolopoulos et al., 2013; Angeles 2014; Sieber 2014; Rosso 2015). Eleven studies reported measured rates of overweight and/or obesity (range ¼ 27.5.2– 50% overweight; range¼ 19.3–61.9% obese), which were either measured during physical examinations by DOT physicians or assessed by researchers (Jacobson et al., 2007; Harshman et al., 2008; Cui et al., 2009; Parks et al., 2009; Wiegand et al., 2009; Xie et al., 2011; Marqueze et al., 2013; Thiese et al., 2015a, 2015b; Sangaleti et al., 2014; Mansur et al., 2015). Three studies reported a combined prevalence rate of overweight and obesity ranging from 55.2 to 90% (Harshman et al., 2008; Apostopolous, 2013; Mansur et al., 2015). 3.2.2. Hypertension The NCEP definition of HTN used for the purpose of this review is Z 130/ Z85 mm Hg, based on the average of two or more properly measured, seated blood pressure (BP) readings on each of two or more office visits. For the purposes of medically certifying drivers to obtain their commercial driver's license, the FMCSA recognizes the Joint National Committee (JNC) definition for HTN (SBPZ140 mm Hg or DBP Z99 mm Hg) (The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure, 2004). Several articles included in this review used medical certification records for identifying HTN and therefore defined hypertension by the FMCSA standards (Thiese et al., 2015a, 2015b; Harshman et al., 2008). Although this is a limitation for standardizing prevalence rates of HTN across reviewed studies, because the JNC definition is more stringent than the NCEP definition, the resulting prevalence rates of hypertension from the literature review is likely a conservative estimate. Prevalence rates of diagnosed HTN and subjects taking one or more medication to control elevated BP are also indicators of HTN for the groups included in these studies. Of the studies reviewed, twenty reported at least one variable indicative of HTN (i.e., prevalence of HTN, use of medications to control elevated BP, mean systolic blood pressure (SBP) and diastolic blood pressure (DBP)). Sixteen studies reported the prevalence of HTN in the subject sample, nine of which were self-report observations that reported a broad range of prevalence rates (range ¼5.0–39.5%) (SabbaghEhrlich et al., 2005; Moreno et al., 2006; Sakurai et al., 2007; Stasko and Neale, 2007; Cui et al., 2009; da da Silva-Junior et al., 2009; Xie et al., 2011; Smith and Phillips, 2011; Leyton 2011). Seven studies reported measured rates of HTN among the sample (range ¼ 24–47.9%) (Harshman et al., 2008; Martin et al., 2009; Marqueze et al., 2013; Sieber, 2014; Sangaleti et al., 2014; Mansur et al., 2015; Thiese et al., 2015b). Five studies reported use of medications to control high BP among their samples and 4 were self-reported (range ¼ 7.6–11% use of BP medications) (Cui et al., 2006; Sakurai et al., 2007; Cui et al., 2009; Rosso, 2015). One study measured use of BP medications and found that 41.5% of the sample was taking at least one of these medications (Harshman et al., 2008). Seven studies reported means for SBP and DBP and six were measured variables (SBP range¼123–132 mm Hg and DBP range¼ 79–84 mm Hg) (Harshman et al., 2008; Parks et al., 2009; Martin et al., 2009; Thiese et al., 2015a, 2015b; Sangaleti et al., 2014). One study included self-report BP from study participants (mean¼ 130 (14)/69 (30) mm Hg) (Cui et al., 2009). 3.2.3. Dyslipidemia Dyslipidemia represents two components of the MetSyn, elevated TG ( Z150 mg/dL) and low HDL-C (o40 [males]; o 50 [females] mg/ dL) (Ervin, 2009). Although elevated total cholesterol (TC) (4240 mg/dL) is not a defined risk factor for MetSyn, it was included and reported in this review due to its relationship with characterizing dyslipidemia (NHLBI, 2005). Studies that reported prevalence rates of diagnosed dyslipidemia and mean values for HDL-C and TG are included in this review. Seven studies included in this review reported at least one variable indicative of dyslipidemia. The prevalence of hyperlipidemia was reported in six studies (range: 4.4–45.6%) (Moreno et al., 2006; Martin et al., 2009; Marqueze et al., 2013; Sieber, 2014; Mansur et al., 2015; Thiese et al., 2015b). Marqueze et al. (2013) reported low HDL-C values for 45.6% of their driver population, while Thiese et al. (2015b) reported the mean value for HDL-C (mean¼ 36.6) (14.1 mg/dL). The prevalence of hypertriglyceridemia was 25.8–39.6 as reported by two studies (Marqueze et al., 2013; Mansur et al., 2015). 3.2.4. Diabetes mellitus For the purpose of this review, diabetes was defined by the prevalence of diagnosed type II insulin dependent DM, the most common form of diabetes and highly associated with obesity, and mean fasting glucose indicative of DM for the subject samples. According to the Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
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American Diabetes Association, fasting glucose values above 126 mg/dL indicate diabetes (American Diabetes Association, 2009). The NCEP ATP III defines fasting glucose levels Z110 mg/dL as the criteria for the MetSyn risk factor. Of the studies included in this review, fifteen reported one or more variable indicative of pre-diabetes or DM, eleven of which relied on self-report from CMV drivers (range¼1–22% prevalence of DM) (Moreno et al., 2006; Harshman et al., 2008; Stasko and Neale, 2007; da da Silva-Junior et al., 2009; Xie et al., 2011; Leyton 2011; Apostolopoulos et al., 2013; Angeles, 2014; Sieber, 2014; Rosso, 2015; Thiese et al., 2015b). Four studies used either driver DOT examination records, carrier health claims data, or blood glucose analyzes to determine disesase prevalence of DM (range¼7–16%) (Martin et al., 2009; Marqueze et al., 2013; Sangaleti et al., 2014; Mansur et al., 2015).
4. Discussion Overall, the published studies in this review indicate a range of prevalence rates of individual components of MetSyn in commercial truck drivers, worldwide. However, the more rigorous studies that included measured variables and anonymous self-report variables from driver participants, indicated prevalence rates higher than those of the general U.S. population for abdominal obesity, HTN, and dyslipidemia. Findings from this review indicate that the prevalence of insulin dependent DM may be lower in commercial truck drivers, compared to that of the general U.S. adult population. It should be noted that the number of studies that examined dyslipidemia was small. The studies included in this review identify abdominal obesity as the most prevalent MetSyn component and risk factor for CVD in this high-risk group. 4.1. Self-report vs. measured variables Table 3 highlights the differences in self-report versus measured prevalence rates for MetSyn components and variables indicative of MetSyn. It should be noted that the accuracy of the self-report data should be considered carefully. Commercial truck drivers must be in fair health and meet the physical requirements of the FMCSA to continue driving. Health disorders, including uncontrolled hypertension and DM may disqualify a driver from driving a commercial vehicle or require them to complete DOT physicals more frequently for monitoring and certification to drive (Federal Motor Carrier Safety Administration Medical Examiner Handbook). Therefore, drivers may be tempted to withhold information on questionnaires or interviews asking about health history and personal health conditions for fear that their responses may incriminate them for being at risk for disqualifying medical conditions and require them to undergo testing, treatment, or both, or risk losing their commercial license. Main contrasts between values for self-report and measured variables existed for prevalence of HTN (range 5–39.5% vs. 24–47.9%, respectively), use of BP medication (range ¼ 7.6–11.0% vs. 41.5%, respectively), mean DBP (range¼ 69.1 vs. 79.4–84.4%) and prevalence of hyperlipidemia (range ¼ 21.7% vs. 4.4–45.6%). Variables that were similar between studies that included self-report and measured variables indicative of MetSyn components included mean BMI, prevalence of overweight and obesity, and mean SBP. Several variables were reported as measured variables only (prevalence of abdominal obesity, hypertriglyceridemia, and low HDL-C); therefore a comparison between self-report and measured components cannot be made. 4.2. Prevalence of MetSyn components: A comparison In comparison to the U.S. prevalence rates of MetSyn and MetSyn components from the findings from the National Health Statistics Reports, worldwide CMV truck drivers may be at high risk for MetSyn, as shown in Table 4. The National Health Statistics Reports indicate that abdominal obesity is the most prevalent of the MetSyn components, affecting 53% of U.S. adults (Ervin, 2009). In contrast, this review indicates that abdominal obesity may affect up to 74% of drivers. Findings from the literature review of overweight and obesity in commercial truck drivers indicate that up to 53% of drivers may be overweight while nearly 70% may be considered obese (note that prevalence rates are mutually exclusive). According to the National Health Statistics Reports, hypertension and hyperglycemia affect 40%, and 39% of U.S. adults, respectively. In this review, prevalence of HTN and insulin dependent DM was reported to be as high as 48% and 22%, respectively, among truck drivers. The National Health Statistics Reports also indicate that elevated TGs and low HDL-C were less prevalent among U.S. adults, with prevalence rates of 31% and 25%, respectively. Findings from the literature review indicate that hyperlipidemia, hypertriglyceridemia, and low HDL-C may affect up to 46%, 40%, and 46% of CMV drivers, respectively. It should be noted that the number of studies in this literature review that reported prevalence of dyslipidemia in CMV truck drivers was small (n¼ 6) and only three reported prevalence rates and values for triglycerides and HDL-C in their results. The National Health Statistics Reports indicate Table 3 Self-report vs. measured prevalence rates of MetSyn components. Components of the metabolic syndrome Obesity Mean BMI % Ovwt
% Obese Abdominal obesity
Self-report studies
24.0–33.9
22.8–53.2 15–69.6
Measured reports
27.9–32.9
27.5–50.0 19–61.9
19.8–73.6
Diabetes Dyslipidemia
Hypertension
% DM
% Hyperlipidemia HDL-C TG
% HTN
1–22
21.7
7–16
4.4–45.6
–
45.6
–
Mean SBP (mm Hg)
5–39.5 129.7
25.8–39.6 24–47.9
123.1–132.0
Mean DBP (mm Hg)
% BP Meds
69.1
7.6– 11.0
79.4–84.4
41.5
Abbreviations: BMI¼ body mass index, DM¼ diabetes mellitus, HDL-C ¼ high density lipoprotein-cholesterol, TG-triglycerides, HTN-hypertension, SBP ¼ systolic blood pressure, DBP¼ diastolic blood pressure, BP ¼blood pressure.
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Table 4 Prevalence of MetSyn components among commercial truck drivers vs. general U.S. population. Metabolic syndrome component
Prevalence among general U.S. adult population (%)
Prevalence among worldwide commercial truck drivers (%)
Abdominal Obesity Hypertension Hyperlipidemia Elevated Triglycerides Low HDL-C Hyperglycemia/ Diabetes Metabolic Syndrome
53 40 – 31 25 39
19–74 5–48 4–46 26–39 46 1–22
34
Not Determined
Abbreviations: HDL-C ¼ high density lipoprotein-cholesterol.
that 34% of the general U.S. adult population meets the NCEP criteria for MetSyn. Due to the increased prevalence of MetSyn components, particularly abdominal obesity, among commercial truck drivers compared to the general population, it may be suggested that MetSyn is highly prevalent among truck drivers, as obesity is thought to be the strongest predictor of MetSyn (Palaniappan et al., 2004). 4.3. Limitations There are some limitations affecting interpretation of available studies related to MetSyn and MetSyn components in commercial truck drivers. The definition of commercial truck driver, while limited for this review to exclude non-truck commercial drivers, may be considered broad. There are many types of commercial truck drivers and some share very different work environments, i.e., interstate versus intrastate driving or short-haul versus long-haul driving or truck type, i.e., express trucks, semi-trucks, etc. Mileage driven, time spent in the truck, and job-related activities and physical demands such as loading and unloading vary among these job types. Lack of discussion regarding the commercial truck driver populations included in the papers reviewed limits the interpretation of this review and warrants future research to examine truck drivers by type, rather than as a collective group. A second limitation affecting interpretation of the findings of this review are the inter-country differences for health disparities among the driver participants included in this review. Genetic and environmental factors that influence the prevalence of MetSyn and its components, including diet, physical activity, age, and body habitus, are largely mediated by cultural and regional differences (Cameron et al., 2004; Procopiou and Philippe, 2005). Finally, criteria for risk factors of interest and definitions of MetSyn may vary by country. For example, the diagnostic criteria for MetSyn in Japan differs slightly from the NCEP definition in America; the Japanese criteria for waist circumference indicative of abdominal obesity is much lower for men than the American criteria for men (85 cm vs. 102 cm, respectively). The International Diabetes Federation (IDF) recognized the need for a single, universally accepted diagnostic tool and developed the IDF definition for MetSyn that addresses both clinical and research needs while providing an accessible, diagnostic tool suitable for worldwide use (Alberti et al., 2005). The IDF definition standardizes criteria for hyperlipidemia, hypertension, and impaired fasting glucose while providing ethnic specific values for waist circumference to define central obesity. The IDF definition of MetSyn includes central obesity and any two additional risk factors. While these international definition differences may be viewed as a limitation in this review paper, the authors feel these may help to normalize data, considering race and regional differences so that health risks can be compared across countries. Additionally, this review paper focuses on prevalence rates rather than clinical values to further standardize comparisons. 4.4. Other factors influencing metabolic syndrome Lifestyle factors and additional health disparities may also play a role in the development of MetSyn due in part to their metabolic influence on obesity, suggested to be the best predictor of MetSyn (Palaniappan et al., 2004). Physical activity and diet directly influence obesity and MetSyn as important determinants of body composition. Physical inactivity reduces caloric expenditure and vascular function to promote obesity, dyslipidemia, and HTN, all of which are risk factors for development of MetSyn (Hamburg et al., 2007). There is also a strong relationship between physical inactivity and insulin resistance, a primary point of origin in the pathogenesis of MetSyn (Venables and Jeukendrup, 2009). Poor diet also directly impacts MetSyn through its influence on the components that comprise the disorder. Diets that are high in calories, saturated and trans fats, cholesterol, simple carbohydrates, sugar and sodium promote obesity, DM, and dyslipidemia. Insulin resistance is driven by excessive dietary fat and simple sugar intake and diets high in sodium promote HTN (Basciano et al., 2005; Kraegen et al., 1991). Stress and tobacco use have also been shown to contribute to the MetSyn (Hjemdahl 2002; Will et al., 2001). Health disparities such as obstructive sleep apnea (OSA), the most common sleep disorder caused by obstruction of the upper airway, are associated with MetSyn and may even play a role in the development of the disorder. OSA has been found to be independently associated with individual metabolic components of the MetSyn, as well as with an increased prevalence of MetSyn (Coughlin et al., 2004). One study found that individuals with OSA had a fivefold increased risk for also having MetSyn and that the severity of OSA correlated with number of MetSyn components (Lam et al., 2006). 4.5. Health promotion programs for commercial truck drivers Driver health and wellness is being identified by leading transportation companies as a key area of focus for maintaining continued corporate leadership, improving safety, decreasing health care and workers' compensation costs and insurance premiums, increasing employee morale and job satisfaction, and improving retention of valued, healthier drivers (Husting and Biddle, 2005). In response to a Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i
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cultural shift in the transportation industry toward recognizing the connection between health, wellness and safety, and embracing models of company-driven health and wellness programs, proactive carriers are adapting various elements of driver wellness programs into corporate operations, thereby making employee wellness part of their overall corporate culture of excellence. Addressing health and wellness concerns for commercial truck drivers is challenging due to the varied work environments in which drivers operate, the work schedules they keep, and often the lifestyles they choose. According to a Synthesis on commercial driver health and wellness programs, the most common risks to commercial driver health and wellness include regular tobacco use, obesity, hypertension, poor eating and drinking habits and inadequate diet and nutrition, lack of physical activity and proper exercise and degrading states of physical fitness, and alcohol and chemical abuse. (Commercial Truck and Bus Safety Synthesis, 2007). These risks impact not only the acute and long-term health of drivers, but also their life expectancy, quality of life, and safety. The authors concluded that a long-term cultural change in the transportation industry is needed toward embracing integrated models of health, safety, and productivity management. This change should be a joint and shared responsibility of individual drivers, fleet managers, and senior carrier management. Authors also agree that transportation companies interested in developing their own employee health and wellness programs need guidance and resources on how to do so and are in need of better tools and innovative practices for doing so successfully. 4.6. Future research The findings of this literature review indicate the need for additional research to examine the prevalence of the individual components of the MetSyn among commercial truck drivers. Future studies should also focus on direct biomarker measures of these components to establish risk and prevalence, rather than relying on self-report. Additionally, studies to assess the prevalence of MetSyn among commercial truck drivers are warranted, due to the high rates of abdominal obesity in this group. Furthermore, examining MetSyn and its components in commercial truck drivers by driver type, such as short-haul and long-haul, rather than as a more generally defined group, may provide insight into which specific populations are high risk and should be prioritized for focused health interventions. Future research should demonstrate the connection between health, wellness, and safety to encourage carriers to embrace models of company-driven health and wellness programs and make employee wellness part of their overall corporate culture.
5. Conclusions Among all the reviewed studies that reported prevalence rates for MetSyn components, abdominal obesity may affect up to 74% of truck drivers and overweight and obesity may affect 23–53% and 15–70%, respectively. In contrast, HTN may affect 5–48% of commercial truck drivers, dyslipidemia 4–46%, and DM 1–22%. The number of studies that reported prevalence rates for the MetSyn components included; obesity (n ¼23), HTN (n ¼20), dyslipidemia (n ¼ 6), and DM (n¼ 15).Collectively, the available published studies indicate a wide range of prevalence rates for individual components of MetSyn among worldwide commercial truck drivers; the inclusion of self-report in many of the studies likely explains the widely varying estimates of prevalence for MetSyn components. Findings from this review indicate abdominal obesity is the most prevalent MetSyn component and risk factor for CVD in this high-risk group of professional CMV truck drivers. Findings from this review indicate high prevalence rates among commercial truck drivers for abdominal obesity, HTN, and dyslipidemia (Table 4). Considering studies that used more stringent methods of assessment, i.e. measured values rather than self-report (Table 3), these rates may be higher than those of the general U.S. population, but cannot be confirmed from the findings of this review. Findings indicate that the prevalence of DM may be lower in commercial truck drivers, compared to those for the general U.S. adult population; however, the evidence is inconclusive due to the limited number of studies that objectively measured this risk factor. Additional, research is necessary to accurately assess the prevalence of MetSyn and determine whether its individual constituent biomarkers differ from the general population. Evaluating large, representative groups of drivers from the industry and collecting biomarkers of MetSyn is important for accurately determining MetSyn prevalence. Future health intervention studies for commercial truck drivers aiming to reduce health disparities, including MetSyn and CVD, should focus on obesity prevention, management and treatment. Health promotion programs targeting truck drivers should consider the unique work environment drivers experience and the lifestyle they lead in order to develop a successful and self-sustaining health and wellness program.
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Please cite this article as: Erin Mabry, J., et al., Prevalence of metabolic syndrome in commercial truck drivers: A review. Journal of Transport & Health (2016), http://dx.doi.org/10.1016/j.jth.2016.06.012i