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Journal of Occupational & Environmental Medicine:
doi: 10.1097/JOM.0b013e3182143e77
Original Articles: CME Available for this Article at

Business Travel and Self-rated Health, Obesity, and Cardiovascular Disease Risk Factors

Richards, Catherine A. MPH; Rundle, Andrew G. DrPH

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Continued Medical Education
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Author Information

From the Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.

Address correspondence to: Andrew Rundle, Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th St, Room 730, New York, NY 10032; Email:

Dr Rundle serves on the Medical Advisory Board of EHE International. EHE International did not play a role in the design of the study, analyses of the data, interpretation of the data, in the decision to submit the manuscript for publication or in the writing of the manuscript. EHE International did verify that the text in the “Methods” section describing the company and its programs was factually correct.

Catherine A. Richards and Andrew G. Rundle have no financial interest related to this research.

The JOEM Editorial Board and planners have no financial interest related to this research.

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Objective: To assess associations between extent of travel for business and health.

Methods: Associations between business travel and cardiovascular disease risk factors were assessed using medical record data from 13,057 patients provided by EHE International, Inc.

Results: Compared with light travelers (1 to 6 nights per month), nontravelers were more likely to report poor/fair health (odds ratio = 1.58; 95% confidence interval [CI]: 1.33 to 1.87) and the odds ratios increased with increasing travel, reaching 2.61 (95% CI: 1.57 to 4.33) among extensive travelers (>20 nights per month). Compared with light travelers, the odds ratios for obesity were highest among nontravelers (odds ratio = 1.33; 95% CI: 1.18 to 1.50) and extensive travelers (odds ratio = 1.92; 95% CI: 1.25 to 2.94). Although the differences were small, nontravelers and extensive travelers had the highest diastolic blood pressure and lowest high-density lipoprotein cholesterol levels.

Conclusion: Poor self-rated health and obesity are associated with extensive business travel.

Travel is a prominent feature of business life in the United States, with an estimated 405 million long-distance business trips taken in 2001 to 2002.1 Approximately 75% of these trips were shorter than 250 miles from the point of departure, whereas only 7% of trips were more than 1000 miles.1 Air travel accounted for 16% of all business trips, whereas personal automobile travel accounted for 81% of all business trips.1 There is a large literature on health risks associated with business travel, but the literature is almost exclusively focused on infectious diseases. The literature that does exist for noninfectious disease conditions focuses on international business travel.24 Long-duration air travel is associated with deep vein thrombosis and pulmonary embolism.5 A study of health insurance claims among World Bank staff and consultants found that travelers had significantly higher claims than their nontraveling peers for all conditions considered, including chronic diseases such as asthma and back disorders.2 The highest increase in health related claims was for psychological disorders, and particularly, the subcategory of stress-related disorders.2 Analyses of health risk appraisal surveys conducted at a large multinational corporation found that international business travel was associated with a lower risk of self-reported hypertension, higher alcohol consumption, lower confidence in keeping up with the pace of work, and lower perceived flexibility in fulfilling commitments.4 Business travel is also associated with jet lag, sleep disorders, increased alcohol consumption, exposure to high–energy density “fast” foods, and long periods of sedentary behavior.6,7 These factors have been found to be associated with obesity, which is known to cause numerous poor health conditions.

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Learning Objectives

* Become familiar with previous findings on the health effects of business travel, including the main types of travel and health problems addressed.

* Among employees with differing intensities of business travel, identify the groups with higher rates of poor/fair health and obesity.

* Discuss the implications for workplace interventions and health monitoring of frequent business travelers.

Although the prior research with health claims and health risk appraisal data are intriguing, to our knowledge, there are no reports on business travel and clinically measured chronic disease conditions and risk factors, and thus, we set out to provide initial data on this question. Using a large sample of employed individuals undergoing wellness physical examinations, we conducted a cross-sectional analysis of associations between the extent of business travel and several measures of health, including self-rated health, obesity, blood pressure, cholesterol levels, and fasting blood sugar.

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EHE International, Inc (EHE), provides annual routine screening physical examinations as part of a corporate wellness plan.8 The examinations are provided free of charge to the employees and their spouses. The physical examinations take place at six EHE-owned centers and at a network of more than 60 physician offices across the country, with the largest number examinations taking place in their New York City location. Companies differ in their policies regarding which levels of employees are eligible for the physical examination, but many companies offer it to all levels of employees and their spouses. Since the medical record does not capture whether or not spouses of eligible employees are employed or not, the analyses were restricted to the employees who received the EHE examination through their work benefits program. Spouses who received an examination through their husbands’ or wives’ benefits program were excluded.

Before their visit, patients fill out an extensive online health questionnaire. The questionnaire includes a question that asks, “How would you rate your present health?” Patients are asked to choose from the following answers: excellent, good, fair, or poor. The questionnaire also asks, “How many nights per month are you away from home on business?” The physical examination includes measurements of height and weight using rigid stadiometers and digital scales, which are calibrated daily. During the examination, fasting (overnight fast) blood samples are taken and are analyzed for clinical markers by LabCorp, Inc. Data on high- and low-density lipoprotein (HDL and LDL, respectively) and fasting glucose were used in the analyses presented here. During the physical examination, blood pressure is measured at the right arm while the patient is in a supine position using a cuff sphygmomanometer following American Heart Association guidelines.9 The network offices meet EHE quality-control standards for the examination procedures and submit blood samples to the same central clinical laboratory used by EHE owned centers.

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Statistical Methods

We obtained deidentified data from EHE's medical record database on business travel, body mass index (BMI), self-rated health, systolic and diastolic blood pressure, fasting glucose, LDL cholesterol and HDL cholesterol, as well as demographic characteristics (age, gender, and race) for 13,057 employed patients who underwent an examination at EHE in 2007. The Columbia Presbyterian Medical Center institutional review board approved the study protocol as nonhuman research involving deidentified records previously collected for other purposes.

We used logistic regression analyses to determine whether more nights away from home was associated with a self rated health of fair or poor versus excellent or good and with obesity (BMI ≥ 30 kg/m2). Linear regression analyses were used to determine whether more nights away from home was associated with BMI, blood pressure, blood lipid levels, and fasting blood glucose. Employees were classified as engaging in no business travel, 1 to 6 days of travel per month, 7 to 13 days of travel per month, 14 to 20 days of travel per month, and 21 or more days of travel per month. The SAS LSMEANS function (SAS 9.1, SAS Institute, Inc., Cary, North Carolina) was used to estimate covariate-adjusted mean levels of BMI, diastolic and systolic blood pressure, fasting glucose, and LDL and HDL blood lipid levels. Analyses were controlled for age, gender, and race/ethnicity. Patients self-identified their race as African American/black, Asian, Caucasian, Hispanic, or other with an additional option for a write in. For patients who wrote in their race, the study investigators assigned the patient's race to one of the five categories. Race/ethnicity was controlled for in all analyses because previous research has consistently shown race/ethnicity to be an important predictor of overweight or obesity status.10 Those in the one to six nights away from home category were used as the referent group for regression analyses. A multivariate logistic regression model was also used to test whether nights away from home for business travel independently predicted self-reported health status after controlling for all other measures of health (BMI, diastolic and systolic blood pressure, fasting glucose, and LDL and HDL blood lipid levels).

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As seen nationally, business travelers were more likely to be male and younger than their nontraveling peers (Table 1).1 Although more than 90% of the respondents rated their health as excellent or good, the analyses revealed a nonlinear association between health and nights of business travel, with poorer health found among the nontravelers and among those traveling the most. Table 2 shows odds ratios and adjusted means for the health outcome variables by categories of nights away from home. The odds of reporting fair or poor self-rated health were significantly higher among nontravelers than those traveling one to six nights per month and significantly increased across categories of increasing business travel. Associations between nights of travel and obesity showed a similar trend; the odds of obesity were significantly higher among nontravelers than among those traveling one to six nights per month and then significantly increased across categories of increasing business travel.

Table 1
Table 1
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Table 2
Table 2
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Although the absolute differences were small, associations between nights of travel and BMI and several clinical health markers showed similar nonlinear patterns. Body mass index was lowest among those traveling 1 to 6 days and 7 to 13 days per month and significantly increased among those traveling 14 to 20 and 21 or more days per month. Body mass index was also significantly higher among nontravelers than among those traveling one to six days per month. For diastolic blood pressure, mean values were significantly higher among the nontravelers and those traveling 21 or more days per month than those traveling 1 to 6 days per month. Those traveling 7 to 13 or 14 to 20 days per month had a similar mean diastolic blood pressure to those traveling 1 to 6 days per month. For systolic blood pressure, the highest mean blood pressure was observed among the nontravelers, but blood pressure did not significantly vary across travel categories. Although differences were small, the highest HDL values were observed among those traveling 7 to 14 days per week, and the lowest levels were found among those reporting no traveling and those traveling 21 or more days per week. For LDL and fasting blood sugar, there were no significant differences in values across travel categories.

A multivariate model was used to assess whether, after control for all other health related measures (BMI, diastolic and systolic blood pressure, fasting glucose, and LDL and HDL blood lipid levels), nights away from home was still associated with self-rated health. In this model, nontravelers had 1.35 times the odds of reporting a fair/poor health status (95% confidence interval [CI] = 1.13 to 1.62) compared with those who traveled 1 to 6 days per month. Those traveling 14 to 20 days per month had a significantly higher odds of reporting a fair/poor health status compared with those who traveled 1 to 6 days per month (OR = 1.35, 95% CI = 1.03 to 1.77), as did extensive travelers (OR = 2.07, 95% CI = 1.20 to 3.59). Those who traveled 7 to 13 days per month had similar odds of reporting a fair/poor health status as light travelers (OR = 1.01, 95% CI = 0.82 to 1.25).

One weakness of this study is the lack of information regarding income, and the possibility that income confounds the relationship between business travel and health outcomes. In regards to obesity, income is only associated with obesity in women1113; therefore, if the observed associations are primarily due to confounding by income, business travel and obesity should only be associated in women. Thus as a post hoc sensitivity analysis to evaluate the possible confounding effects of income, we conducted analyses of the association between obesity and business travel among men and women separately (Table 3). These analyses found that business travel and obesity were associated in both men and women, suggesting that the associations could not be explained by confounding by income.

Table 3
Table 3
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Here, we present initial efforts to investigate associations between business travel and chronic disease risk factors and conditions. We found that health outcomes were consistently worse for those not traveling and those traveling the most. Specifically, self-rated health, prevalence of obesity, BMI, and diastolic blood pressure displayed a U-shaped pattern of associations with the extent of business travel. Serum HDL displayed an inverted U-shaped pattern, again with worse outcomes associated with no travel or extensive travel. Although the absolute differences in clinical values for diastolic blood pressure and HDL are small, the results with self-rated health are of concern because this simple measure is a very robust predictor of mortality.14 Likewise, the associations between business travel and obesity are of concern because of the many negative health consequences of this condition. To our knowledge, associations between business travel and self-rated health and clinical indicators of chronic disease outcomes have not been studied previously.

We suggest that the observed U-shaped curve may represent a manifestation of the healthy worker effect coupled with the negative health consequences of travel. The term healthy worker effect was initially coined to describe the observation that employed individuals were healthier than their nonworking peers and had lower mortality.15 More generally, the healthy worker effect describes the various ways in which work status and conditions of employment are nonrandomly distributed in regard to health.15 Our data suggest that the nontraveling group includes a subpopulation with ongoing health conditions who self-select not to, or are not chosen to, travel for business. As a consequence, the nontraveling group displays poor outcomes in our study. Our finding that workers with relatively light travel schedules had a lower BMI than those not traveling for work is consistent with earlier research showing that workers engaging in low frequency, short duration international business travel had a lower BMI than workers who did not engage in international business travel.4 It is possible that those who are unhealthy may choose not to travel for business, either because it is contraindicated, because they do not want to interrupt a treatment regime, or because they do not feel well enough to travel. Alternatively, business managers may not choose unhealthy individuals, or those they perceive to be unhealthy, to represent the company on business trips. For instance, obese women face discrimination in pay and promotions, and this phenomena may also apply to being given opportunities for business travel.16 Among those who do travel for business, we also found extensive travel to be associated with poorer self-rated health, higher body mass index, and worse clinical examination results. The cross-sectional clinical data do not provide direct insight into the mechanisms through which business travel might impact health, but travel is associated with several negative health behaviors.

Past research suggests that business travel is likely to be associated with the consumption of higher calorie meals and with more sedentary behaviors. Analyses of US Department of Agriculture food consumption surveys show that food eaten away from home contains more calories per serving, is higher in total fat and saturated fat per calorie, and contains less dietary fiber than meals prepared at home.17 Likewise, data from 10 European countries show that eating meals outside the home is positively associated with energy intake.18 Surveys of food outlets at airports show that the available food is generally of poor nutritional quality and highway rest stops are generally served by fast food outlets.19,20 Despite the common image of business travel being by plane, most business trips are of relatively short distance and conducted by car.1 Automobile travel is generally sedentary and linked to higher BMI and obesity.10,21,22 Frank and colleagues10 found that each additional hour spent in a car was associated with a 6% increased odds of obesity. A cohort study in China has shown that men purchasing motorized modes of transport significantly gained weight and had higher odds of becoming obese.22 Whether travel is by car or plane, it essentially represents increased sedentary time and represents reduced overall time for physical activity. In addition, overnight stays in hotels may interrupt exercise schedules.

Business travel may have detrimental health consequences because it increases job strain, defined as an increase in psychological job demands and a decrease in job decision latitude.4,23 Be it because of travel delays or being placed under the schedule of the meeting, conference, or sales appointment the employee travels to, business travel often removes the control of the workday from the employee thus reducing job decision latitude. Job strain has been shown to be significantly associated with cardiovascular disease risk factors such as higher systolic and diastolic blood pressure and cholesterol.24,25 Frequent business travel may also cause increased psychological stress. A study by the World Bank found an excess of insurance claims for stress related disorders among travelers, with increasing claims seen with increasing travel.2 A second World Bank study found that almost 75% of the staff reported high or very high stress related to business travel.26 Frequent flying and longer trips were associated with higher stress-related effects.6,7 Chronic stress appears to be associated with a dietary preference for energy-dense foods and, particularly among men, with weight gain.27,28 This suggests another mechanism through which business travel may affect diet and in turn health.

It is possible that unmeasured third variables may explain the observed association between more frequent business travel and poorer health. One possible confounder that could not be directly controlled for is income. Nevertheless, it is not a priori clear whether business travel has a linear positive association with income or whether more senior and better-paid workers can avoid business travel. What is known though is that income is inversely associated with obesity in women only and thus can only act as a confounder among women.1113 That our analyses showed business travel to be associated with obesity in both men and women, suggests that the results are not caused by confounding with income.

Another possible third-variable explanation can be found in “personality type” theory. This theory posits the existence of a type A personality, which is associated with a higher risk of cardiovascular disease and is characterized, in part, as being a time urgent, aggressive, and competitive personality type.29,30 Nevertheless, although this possibility could not directly be addressed in this study because personality type was not measured, the literature on the topic suggests that it is not likely to be a confounder. Studies have shown that among the employed, individuals with type A personalities travel more days per year than non–type A individuals.31 Nevertheless, the findings from studies that have assessed the relationship between type A personality and nonfatal myocardial infarction and coronary heart disease have been inconclusive. Although some early studies found type A personality to be significantly associated with an increased risk of nonfatal myocardial infarction,3234 subsequent studies have mostly shown null findings between type A personality and both nonfatal myocardial infarction and fatal coronary heart disease.3539 As a possible explanation for links to coronary heart disease, type A personality has also been studied in regards to associations with diets high in fat and cholesterol.40 Some studies have found that type A behavior is associated with a diet high in fat,40,41 whereas others have found no association.42,43 Thus, although type A personality does appear to be associated with more frequent business travel, the data regarding its associations with disease outcomes are inconclusive.

Should further research substantiate a link between business travel and obesity and other chronic disease health outcomes, there are several possibilities for workplace interventions. Employee education programs on the association between business travel and health and on strategies to improve diet and activity while traveling are a simple start. If the company reimburses employees for meals while traveling, reimbursement rates could be tied to dietary quality. A “stick” approach might be to reimburse high–energy density food meals at a below cost rate, while a “carrot” approach might be to reimburse healthy meals at an above cost rate. Companies that have arrangements with particular hotel chains for volume or business discounts could make having an available gymnasium part of the criteria for selecting hotel chains. In addition to steering employees to hotels with gymnasiums, companies could also provide financial incentives to employees to exercise while traveling. Lastly, given the link between business travel and work stress and between stress and diet and obesity, stress management classes and workshops may have utility in reducing the impact of business travel on health.23

As noted earlier, the analyses presented in this study are cross-sectional in nature and do not provide definitive data on causal relationships. Furthermore, these analyses are limited in that they represent data from a single third party employee wellness provider and the companies have self-selected to work with that provider. The prevalence of obesity in this population is lower (18.5%) than the prevalence of obesity observed nationally in 2007 to 2008 (33.8%).44 Therefore, the generalizability of the findings may be limited to employed populations similar to the one studied here. In addition, data were not available on mode of travel and whether travel involved crossing time zones, factors that could be important in determining the health effects of travel. Lastly, data were not available on potential lifestyle factors such as diet and exercise patterns. Nevertheless, as discussed earlier, we suggest that business travel negatively affects dietary and physical activity behaviors and so these two variables would not be conceptualized as confounders causing bias, but rather mediators of the effect of travel on health.

Although the analyses have limitations, they represent an important initial effort to investigate associations between chronic health conditions and business travel, a frequent component of modern commerce. In part, the observed nonlinear dose response curves are likely to result from less healthy individuals being selected into the nontraveling group. Our results suggest that individuals who travel extensively for work are at increased risk for health problems and should be encouraged to monitor their health. The mechanisms through which business travel is associated with health require further investigation so that appropriate occupational health prevention programs may be developed.

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