Work‐Related Stress Is Associated With Unfavorable Cardiovascular Health: The Multi‐Ethnic Study of Atherosclerosis

Data used in this study are available from the MESA (Multi‐Ethnic Study of Atherosclerosis). To obtain the data, interested investigators should submit an analytical proposal online at https://internal.mesa‐nhlbi.org/.

The baseline characteristics of the study sample stratified by the presence and absence of work‐related stress are presented in Table 1. The study sample comprised 3579 participants with 48% women and a mean±SD age of 57±8 years. Participants with work‐related stress were younger, and a larger proportion were aged <65 years compared with the proportion of participants without work‐related stress. Among participants who reported work‐related stress, a larger proportion were women compared with men. Likewise, a larger proportion of White participants reported work‐related stress compared with the proportion of White participants who did not report work‐related stress. However, the proportion of Chinese American and Hispanic participants with work‐related stress was smaller compared with their counterparts without work‐related stress. The baseline characteristics of the study sample stratified by CVH score is shown in Table S2. The distribution of number of ideal metrics and individual CVH metrics stratified by work‐related stress is shown in Table S3.

Table 2 shows the association between work‐related stress and CVH. Compared with participants without work‐related stress, those with work‐related stress had lower odds of having average and optimal CVH scores (OR, 0.75 [95% CI, 0.62–0.92] and OR, 0.73 [95% CI, 0.58–0.92], respectively). In addition, the presence of work‐related stress was associated with lower odds of having 2 to 3, 4 to 5, and 6 to 7 ideal metrics (OR, 0.64 [95% CI, 0.46–0.89], OR, 0.56 [95% CI, 0.40–0.78], and OR, 0.52 [95% CI, 0.32–0.85], respectively) compared with having 0 to 1 ideal metrics.

The associations between work‐related stress and the individual CVH metrics are reported in Table 3. Participants with work‐related stress had lower odds of having the ideal physical activity (OR, 0.70 [95% CI, 0.56–0.86)]. We found a similar direction of association between work‐related stress and the ideal metrics for smoking, BMI, diet, total cholesterol, blood pressure, and blood glucose, but the CIs included the null (OR, 0.82 [95% CI, 0.65–1.03], OR, 0.79 [95% CI, 0.63–1.00], OR, 0.57 [95% CI, 0.19–1.70], OR, 0.83 [95% CI, 0.64–1.07], OR, 0.89 [95% CI, 0.72–1.10], and OR, 0.85 [95% CI, 0.61–1.17], respectively). In the supplemental analyses, we did not find evidence of effect measure modification by age (<65 versus ≥65 years), sex, or race and ethnicity (Tables S4–S11). Additionally, the presence of work‐related stress for ≥6 months was also associated with lower odds of having favorable CVH (Tables S12 and S13). Similar conclusions were also found when ordinal logistic regression was used to examine the association of work‐related stress with CVH instead of polytomous logistic regression (Table S14).

In this multiethnic community‐based cohort of adults free of CVD at the time of study enrollment, participants with work‐related stress had lower odds of having favorable CVH scores and lower odds of having higher numbers of ideal CVH metrics compared with participants without work‐related stress. In addition, work‐related stress was associated with lower odds of having the ideal metrics for physical activity. Although a similar association was observed for smoking, BMI, diet, total cholesterol, blood pressure, and blood glucose, the CIs included the null. We did not find evidence of effect measure modification by age (<65 versus ≥65 years), sex, or race and ethnicity.

The findings of this study are similar to the findings from prior studies that examined work‐related stress and CVH as defined by the American Heart Association. Chou and colleagues conducted a cross‐sectional hospital‐based study in Taiwan among 1329 medical professionals with a mean age of 38 years. Their results showed that high job strain was associated with a greater prevalence of unfavorable CVH.¹³ In addition, study participants with high job strain had 1.9 times greater odds of physical inactivity compared with study participants with low job strain.¹³ In another cross‐sectional study conducted in Rio Branco, Brazil, among university employees with mean±SD age of 44.3±12 years, Muniz and colleagues found that high job strain was associated with greater odds of unfavorable CVH. However, the CIs were not precise and included the null.¹⁴ Additionally, among study participants with high job strain, the odds of having poor diet or obesity were >2 times greater compared with study participants with low job strain.¹⁴

Prior studies have also shown a harmful association between other types of stress, such as perceived stress on CVH.^{7, 8} For example, in the Paris Prospective Study III of adults, aged 50 to 75 years, with no history of CVD, Poirat and colleagues found an inverse association between perceived stress and CVH after 4 years of follow‐up.⁷ Perceived stress can be defined as a person's subjective interpretation of the magnitude of stress experienced at a particular time or over a period of time.²³ Unlike perceived stress, work‐related stress may be a potential upstream risk factor for unfavorable CVH that is more directly amenable to population‐level interventions in the workplace.

Several biological pathways mediated by elevated levels of cortisol and epinephrine produced in response to psychosocial stress could explain the findings of this study, showing that work‐related stress was associated with unfavorable CVH.^{11, 24} Cortisol is known to decrease inflammation, but excessive secretion of cortisol may cause resistance to its anti‐inflammatory properties and increase susceptibility to inflammatory disorders, such as atherosclerosis.^{11, 25, 26} Work‐related stress also increases epinephrine levels, resulting in long‐term sympathetic activation, which facilitates platelet and macrophage activation as well as the upregulation of inflammatory cytokines.^{11, 24} Consequently, both hormones may act synergistically to increase the inflammatory processes that enhance the risk of unfavorable CVH. Furthermore, maladaptive coping strategies triggered in response to stress may explain the link between work‐related stress and CVH.²⁷ This explanation is supported by the findings of prior studies that demonstrated an independent association between work‐related stress and the adoption of detrimental health behaviors, such as smoking, physical inactivity, and poor dietary habits.^{11, 27, 28}

Currently, the US workforce constitutes ≈60% of the US population, with an increasing proportion of employees who are aged ≥55 years.²⁹ This makes the workplace a suitable environment for initiating comprehensive wellness programs to reduce the risk of unfavorable CVH.³⁰ Approximately 25% to 30% of the annual health care expenditure of employers is spent on employees with major risk factors for CVD and stroke, such as smoking, physical inactivity, obesity, hypertension, dyslipidemia, and diabetes.^{30, 31} Furthermore, the prevalence of some of the major CVD risk factors has increased over the past 2 decades. For instance, from 2009 to 2020, the prevalence of diabetes in US adults increased from 3.0% (95% CI, 2.2%–3.7%) to 4.1% (95% CI, 3.5%–4.7%). Similarly, the prevalence of obesity climbed from 32.7% (95% CI, 30.1%–35.3%) to 40.9% (95% CI, 37.5%–44.3%), and the prevalence of hypertension increased from 9.3% (95% CI, 8.1%–10.5%) to 11.5% (95% CI, 9.6%–13.4%).³² Therefore, the importance of comprehensive workplace wellness programs that include stress management and risk factor reduction cannot be overstated.³⁰

The strengths of this study include the large community‐based multiethnic sample and the use of standardized methods and procedures for the collection of data on the CVH metrics. This study also has limitations. First, with the cross‐sectional design, we cannot establish that a definitive causal link exists between work‐related stress and CVH because reverse causation is a possibility. Second, social desirability bias and recall bias may have impacted the accuracy of the data collected by self‐administered questionnaires on the CVH metrics for smoking, physical activity, and diet. Third, data were collected on work‐related stress and CVH only at baseline and may not reflect the future stress levels or CVH status of study participants. Fourth, the lack of an association in the expected direction among study participants aged ≥65 years in the stratified analysis shown in Tables S4 and S8 may be attributable to the exclusion of participants aged ≥65 years who might have already retired because of higher work‐related stress and poorer CVH leaving a healthier subpopulation of older adults in the analytic sample. Furthermore, in the stratified analysis, we observed inconsistent results for Chinese American participants. These findings could be explained by the smaller sample size of 389 compared with White participants (n=1488), Black participants (n=969), and Hispanic participants (n=733). The smaller sample size may have led to increased variability in our results, and this could be responsible for the unstable estimates and reversal of the expected direction of the associations observed in some of the supplemental tables. Last, the self‐administered questionnaire on work‐related stress was created for the MESA cohort and has not been validated in other cohorts. The lack of formal validation of this questionnaire may raise concerns about the accuracy and reliability of measuring the intended construct. Future studies should prioritize the validation of this quick and easy‐to‐administer questionnaire so it can be used as an initial screening tool to identify employees who may be at risk of unfavorable CVH, especially in resource‐poor settings. However, given that a binary score may oversimplify the complexity of work‐related stress, a continuous score with different dimensions may be preferable for the assessment of work‐related stress. The continuous score has the advantage of capturing the varying degrees and nuances of work‐related stress among study participants, which may be more appropriate for monitoring changes over time as well as evaluating the effectiveness of workplace interventions designed for stress management.

In this multiethnic community‐based cohort of men and women free of CVD at the time of study enrollment, we found that work‐related stress was associated with greater odds of having unfavorable CVH measured by the CVH scores, number of ideal CVH metrics, and individual CVH metrics. Our findings support the importance of workplace wellness programs designed to manage stress, promote CVH, and reduce the risk of CVD events. Additional research that uses a prospective study design may be needed to establish a definitive causal link between work‐related stress and unfavorable CVH.

The Multi‐Ethnic Study of Atherosclerosis was supported by contracts HHSN268201500003I, N01‐HC‐95159, N01‐HC‐95160, N01‐HC‐95161, N01‐HC‐95162, N01‐HC‐95163, N01‐HC‐95164, N01‐HC‐95165, N01‐HC‐95166, N01‐HC‐95167, N01‐HC‐95168 and N01‐HC‐95169 from the National Heart, Lung, and Blood Institute, and by grants UL1‐TR‐000040, UL1‐TR‐001079, and UL1‐TR‐001420 from the National Center for Advancing Translational Sciences. Dr Ogunmoroti is supported by the National Heart, Lung, and Blood Institute (T32HL130025). Dr Osibogun is supported by the National Institute on Drug Abuse (K01DA055127). Dr Michos is funded by the American Heart Association grant 946222 and the Amato Fund for Women's Cardiovascular Health Research at Johns Hopkins University.

Unrelated to this work, Dr Michos has served as a consultant for Amgen, Arrowhead, AstraZeneca, Boehringer Ingelheim, Edwards Life Science, Esperion, Ionis, Lilly, Medtronic, Merck, New Amsterdam, Novartis, Novo Nordisk, and Pfizer. The remaining authors have no disclosures to report.

The authors thank the other investigators, staff, and participants of the Multi‐Ethnic Study of Atherosclerosis for their valuable contributions. A full list of participating investigators and institutions can be found at https://www.mesa‐nhlbi.org/.