Work engagement is defined as “a positive, fulfilling, work-related state of mind characterized by vigor, dedication, and absorption.”1 In turn, “vigor” is characterized by high levels of energy, the willingness to invest effort in one‘s work, and persistence in the face of difficulties. “Dedication” refers to being strongly involved in one‘s work, and experiencing a sense of significance, enthusiasm, inspiration, pride, and challenge. Finally, “absorption” is characterized by fully concentrating and being engrossed in one‘s work, whereby time passes quickly.
Work engagement is considered the polar opposite of burnout. According to the Job Demands-Resource model, work engagement (vs burnout) is a product of the balance between job demands (ie, workload and time pressure) and available resources (ie, decision latitude, supervisor support, coworker support, and extrinsic reward).2 Work engagement is mainly predicted by the availability of job resources, whereas burnout is mainly predicted by job demands and the lack of job resources.2 While burnout has been previously linked to health impairment,2 most studies have examined work engagement as a predictor of job performance and employee turnover.2 However, more recent research has focused on the positive consequences of high work engagement for health-related outcomes among employees.3–5 Studies to date have revealed that work engagement is related to lower risk of ill-health, as assessed by the corresponding scales of the Brief Job Stress Questionnaire,4 and lower levels of high-sensitivity C-reactive protein.6 However, the association between work engagement and health-related behaviors remains unclear.
In the burgeoning field of positive psychology, it is debated whether positive psychological states (such as work engagement) predict health outcomes independent of negative psychological states, such as stress. In other words, do the health benefits of work engagement merely reflect the absence of a negative state of mind? Thus, the present study sought to examine longitudinally whether work engagement among Japanese workers at baseline was associated with three health-related behaviors at a 1-year follow-up.
We hypothesized that higher work engagement not only improves organizational outcomes (such as productivity) but also leads to the adoption of healthier behaviors among workers. Previous research on work engagement has focused almost exclusively on productivity outcomes. However, our findings extend our understanding of engagement by suggesting positive spillover benefits on employee health maintenance behaviors. For organizational leaders, work engagement may be a useful target for interventions to improve their employees’ health condition.
We analyzed longitudinal data collected in an occupational cohort study on social class and health in Japan (Japanese Study of Health, Occupation, and Psychosocial Factors Related Equity: J-HOPE). The baseline survey was collected from April to June 2011, while the 1-year follow-up survey was administered from April to June 2012.6 The study population consisted of employees working for 12 workplaces, representing a wide variety of industries: information technology, hospitals/medical facilities, manufacturing, pharmaceutical, service industries, transportation, and housing sales. These companies were selected to represent Japan's industrial structure; the companies that obtained permission were used in J-HOPE. All employees were offered to take part in this survey. The original sample consisted of 10,742 and 11,393 responders in the first and second waves (response rate: 77.0% and 81.7%, respectively). Data were mainly collected during regular employee health check-ups. In Japan it is legally mandated that employers provide annual health check-up for all employees where screening is offered for metabolic syndrome, cancer detection, etc. Our questionnaire was administered to employees presenting for their annual check-up.
Assessment of Work Engagement
The nine-item Japanese version of the Utrecht Work Engagement Scale (UWES-9)7,8 was used to assess work engagement at baseline. The UWES-9 includes three domains tapping into vigor (three items), dedication (three items), and absorption (three items) on a seven-point response scale from 0 (never) to 6 (always/every day). We used the average of nine items to assess work engagement. The UWES-9 was translated into Japanese with acceptable internal consistency and reliability, as well as factor and construct validity.8 Cronbach α coefficient for the total score was 0.94.
Outcomes and Definition of Healthy Behaviors
The following three lifestyle behaviors were included in the analysis: smoking status, frequency and quantity of alcohol consumption, and frequency of physical exercise. Smoking status was classified as “never smoked,” “former smoker,” or “current smoker.” The frequency of alcohol drinking was divided into “does not drink,” “drinks but not every day,” and “drinks every day.” Alcohol consumption quantity was measured by the question: “How many glasses of alcohol do you drink per sitting? (One gou of Japanese Sake, two glasses of wine, or a large glass of beer being the equivalent of 20 g of alcohol).” Physical exercise was classified as either “no exercise,” “light exercise more than once a week,” “heavy exercise once or twice a week,” or “heavy exercise more than three times a week.”
The following three definitions of healthy behavior were used in the analysis:
- Quit smoking (N = 2353): Among smokers at baseline, those who reported at the 1-year follow-up that they had quit.9
- Moderate drinking (N = 8050): No drinking or less than 20 g of alcohol per day at the 1-year follow up.10–12
- Healthy exercise behavior (N = 8050): One or more occasions of exercise per week at the 1-year follow.13,14
Demographics and Socioeconomic Conditions
Age, sex, and highest educational attainment were self-reported in the 2010 survey. We used educational attainment, occupation, and annual household income as indicators of socioeconomic status (SES). Education level was categorized into two groups: “less than or equal to 12 years” or “more than 12 years” of formal education. Occupations were categorized into four groups “manager,” “non-manual,” “manual,” and “others.” Annual household income was defined as the sum of all family members’ income, and the number of family members was based on responses to a self-administered questionnaire. Each participant was asked to indicate to which of six income levels their household income belonged: (1) less than 3.0 million JPY/yr; (2) 3.0 to 4.99 million JPY/yr; (3) 5.0 to 7.99 million JPY/yr; (4) 8.0 to 9.99 million JPY/yr; (5) 10.0 to 15.0 million JPY/yr; (6) more than 15.0 million JPY/yr. For the analysis, the average household income in each category was used, standardized for household size by dividing by the square root of the number of household members.15
Job Stress and Support
The short version of the Job Content Questionnaire (JCQ) was adapted and validated for the Japanese population by Kawakami et al.16 The JCQ is a standardized instrument used to assess social and psychological characteristics of jobs based on the theoretical model developed by Karasek17 and Johnson and Hall.18 It comprises 22 questions with response options ranging from “strongly disagree” to “strongly agree” scored on a Likert scale (1–4). The block regarding social support is composed of eight questions on relationships with coworkers and supervisors. These variables were coded according to the Job Content Questionnaire User's Guide. Scores for each quartile on job demand variables were calculated. Scores in the top quartile were labeled the “high” (reference) group; the bottom quartile was the “low” group, and scores in the middle quartiles were collapsed into the “medium” group. The job control and social support scores were similarly divided into three groups.
We also used the K6, a six-item self-report questionnaire designed to screen for mood and anxiety disorders, as an indicator of psychological distress.19 We used a cut-off point of five, which has been used in screening for clinical depression.20
Assessment of Confounders
The following factors were considered potential confounders between work engagement and healthy behaviors; age, sex, household income, education, occupational stress, supervisor and colleague support, K6 score, occupation, workplace, smoking history, drinking history, and amount of exercise at baseline.
According to the Job Demands-Resource model, the demands and level of control associated with the job, as well as the support of the supervisor and colleagues, are each associated with work engagement. Hence, we controlled for these job characteristics as potential confounders.
In addition, previous studies have shown that higher K6 scores are correlated with low work engagement.21 This may be because either low work engagement leads to more psychological distress, or alternatively, workers experiencing high distress are less likely to be engaged. Since psychological distress is also robustly correlated with poor health behaviors, we considered K6 scores as a potential confounder of the relationship between work engagement and health behaviors.22
Written informed consent was obtained from all participants. The protocol and documents explaining our study were approved by the ethics committee of the Graduate School of Medicine and Faculty of Medicine at the University of Tokyo (No. 2772), Kitasato University School of Medicine Hospital (B12–103), and the University of Occupational and Environmental Health, Japan (10–004).
A total 10,742 participants were enrolled in the study at baseline. We excluded participants who did not provide responses to the survey on work engagement (N = 503), had a history of cardiovascular disease or cancer at baseline (N = 239), or had missing data at baseline or at 1-year follow-up (N = 1950). The final sample for analysis comprised 8050 participants (Fig. 1).
Participant characteristics at baseline and healthy behavior at 1-year follow-up are summarized in Table 1. Continuous data were expressed as mean (standard deviation), and categorical data were expressed as percentages.
Associations between work engagement and other covariates at baseline and healthy behavior at 1-year follow up were estimated from a logistic regression model. Odds ratios (OR) for adopting healthy behavior at 1e-year follow up were estimated after adjusting for age, sex, family income, education, occupational stress (demand/control model), support of supervisor and colleagues, K6, and type of occupation/workplace, as well as smoking history, drinking history, and exercise at baseline. We fit separate multivariate logistic regression models with work engagement as a continuous variable and as a categorical exposure (classified as less than or equal to 2.4, 2.41 to 3.4, and more than or equal to 3.41 from the UWES-9 score) (Tables 2 and 3) As a separate sensitivity analysis, we analyzed baseline work engagement linked to changes in health behavior between baseline and follow-up (Fig. 2). For example, in the case of drinking, we stratified the sample into those who were already engaged in healthy drinking (up to 20 g per day) at baseline versus those who were heavier drinkers. We then estimated the odds ratio of adopting healthy drinking behavior at the 1-year follow-up. For exercise, we stratified workers into those who were already engaged in exercising at least once a week at baseline versus those who were sedentary. We then estimated the odds ratio for becoming active at the 1-year follow-up, according to level of work engagement at baseline (Fig. 2).
Finally, we performed supplemental stratified analyses to examine whether the association of work engagement with health behavior was modified by education level, occupational status, or household income (Supplemental Table 1, http://links.lww.com/JOM/A693). These analyses were performed to test whether work engagement is beneficial mainly for high SES workers, or whether the health benefits are more generalized.
A two-tailed P-value <0.05 was considered statistically significant. All analyses were performed using IBM SPSS Statistics version 21.0J (IBM SPSS Japan Inc., Tokyo, Japan).
Participant characteristics are shown in Table 1. The mean age was 40.6 ± 10.4 years, and 77.4% of the participants were men. The mean work engagement score was 2.9 ± 0.9. Healthy behavior percentages at the 1-year follow-up were: smokers who had quit: 7.4%; no drinking or less than 20 g of alcohol: 73.3%; and exercise once or more per week: 39.6%.
The unadjusted associations between work engagement and healthy behavior at the 1-year follow up are shown in Table 2. Work engagement (as a continuous variable) was positively associated with exercise (OR 1.22, 95% CI: 1.16 to 1.28), but not with smoking or drinking. We obtained similar results when we examined work engagement as a categorical variable.
As shown in Fig. 2, among smokers there was no significant association between higher work engagement at baseline and quitting smoking at the 1-year follow up (OR 0.97, 95% CI: 0.79 to 1.18, P = 0.78). On the other hand, there was a significant association between higher work engagement and healthy drinking behavior (either no drinking or less than 20 g of alcohol per day) among all participants (OR 1.08, 95% CI: 1.01 to 1.15, P = 0.018). When further stratified by baseline drinking habits, work engagement was not significantly associated with improved drinking behavior among those who already reported unhealthy alcohol drinking behavior at baseline. However, among those who reported healthy drinking behavior at baseline, higher work engagement was protectively associated with unhealthy drinking behavior at follow-up (OR 0.98, 95% CI: 0.86 to 1.16, P = 0.99). In other words, work engagement protected healthy individuals from progressing to unhealthy drinking behavior at follow-up. There was a significant association between higher work engagement and regular exercise among all participants (OR 1.19, 95% CI: 1.12 to 1.26, P < 0.001), as well as among participants who did not have healthy exercise behavior at baseline (OR 1.21, 95% CI: 1.10 to 1.32, P < 0.001). However, among those who already reported healthy exercise behavior at baseline, there was no significant association between higher work engagement and sedentary behavior at the 1-year follow up (OR 0.92, 95% CI: 0.98 to 1.04, P = 0.21).
Table 3 shows the results of the multivariate analysis with adjustment for potential confounders. Work engagement (as a continuous variable) was significantly positively associated with healthy drinking pattern (OR 1.08, 95% CI: 1.01 to 1.15, P = 0.018) and exercise (OR 1.19, 95% CI: 1.12 to 1.26, P < 0.001), but not with smoking cessation (OR 0.97, 95% CI: 0.79 to 1.18, P = 0.78).
The OR and 95% CI of work engagement and healthy behaviors within different socioeconomic strata are shown in Supplemental Table 1, http://links.lww.com/JOM/A693. We did not find evidence of effect modification by SES; that is, work engagement was similarly associated with health behaviors regardless of educational attainment, household income, and occupational type.
In this longitudinal study, we found that higher work engagement was associated with healthier drinking and exercise patterns over the course of a 1-year follow-up. The strongest signal was found for workers who were sedentary at baseline. Among these workers, higher work engagement was correlated with the adoption of regular exercise 1 year later. However, we found no correlation between work engagement and smoking cessation. Also, work engagement was found to be correlated with healthy drinking behavior only among workers who already reported a healthy drinking pattern at baseline. Importantly, SES did not significantly modify the association between work engagement and health behavior. In other words, we did not find evidence that work engagement selectively improves the health advantage of high SES workers. To our knowledge, this is the first study to examine whether work engagement is associated with the adoption of health behaviors over time in a large sample of adults, suggesting that work-engagement improvements may be a viable target for workplace interventions aimed at helping adults adopt healthier behaviors.
The underlying mechanism relating work engagement and healthy behaviors is not fully understood. Previous studies investigating an association between positive psychological well-being and healthy behaviors provide some clues. A random-effects meta-analysis found that more optimistic individuals tended to engage in healthier behaviors such as physical activity, healthy nutrition, and non-smoking, compared with less optimistic individuals.23 In another study, prospective data from the English Longitudinal Study of Ageing reported that psychological well-being was independently associated with attaining and maintaining higher physical activity levels over 11 years.24 Psychological well-being may lead to better health behaviors via a number of processes. For example, people with higher psychological well-being actively seek favorable life outcomes, and as a result they are more likely to persist at achieving life goals.25 Thus, psychological well-being may lead us to adopt better health behaviors, through goal setting, self-efficacy, motivation, and self-regulation.26 Work engagement may be considered a positive psychological force in people's lives. Another idea about this is that employee may improve their health condition in order to optimize their work performance. On other hand, based on a previous study, we cannot exclude the possibility that causality runs in the opposite direction, suggesting that health behaviors promote work engagement. In fact, there is a positive association between exercise (1 hour or more per day) and work engagement, as well as a negative association between tobacco use and work engagement.21 That is, workers with healthier behaviors may also become more strongly engaged over time (Fig. 3).
In our study, higher levels of work engagement were related to healthy drinking and exercise behaviors but not with smoking cessation. We hypothesize that the force of nicotine dependence may be difficult to overcome through improvements in work engagement alone. According to previous estimates, the lifetime prevalence rates of nicotine dependence in men ever-smokers were 26% to 42%, meaning that about one of three to four smokers in Japan were considered nicotine dependent.27 Such individuals are likely to need access to nicotine replacement therapy, and other evidence-based smoking cessation methods.
Public health and health care professionals often have difficulty persuading adults to increase their health behaviors. Results from this study suggest that higher levels of work engagement may precede improved health behavior; therefore, it is possible that work engagement could be a novel target for prevention and intervention efforts. In addition, work engagement intervention appears to change health behavior for people across all socioeconomic conditions.
There were several limitations to our study. First, the findings cannot be generalized to other ethnic or age groups. Workers in Japan tend to report lower work engagement scores compared with other countries.28 The association between work engagement and healthy behavior may vary in other social contexts. Second, we could not adjust for a full set of potential confounders, such as company size, industrial category, and detailed work duties, corporate social responsibility (CSR), or organizational justice, all of which may affect work engagement. CSR, especially internal CSR refers to the voluntary behaviors of the corporation, such as providing their employees with fair treatment, organizing good working environment, career development opportunities and facilities to improving their health condition and affect their organizational outcome and behavior.29 And external CSR refers to social responsibility actions targeted a local community or natural environment. Specifically, the donation for protection of natural and cultural property, development of education program, and local beautification activity.30 Previous studies implied a positive association between CSR and work engagement/ employees‘ behaviors.31,32 That is, the CSR might be one of the confounders between work engagement and health behaviors of employees. In additional to CSR, due to previous studies, organizational justice may be an important potential confounder, meaning that organizational justice not only affect work engagement but also influence people's behavior and attitude.33,34 In addition to these factors, according to the latest reviews, there are various methods that improve work engagement. For instance, mindfulness is gathering attention, which may affect both work engagement and our health.35 Third, we did not have information on the survey to control for potential variations in adoption of CSR or other human resource management systems.36 These factors may confound the association between workplace engagement and employee health behaviors. On the other hand, our regression models included fixed effects for each workplace, which is a method that controls for all unobserved time-invariant confounding factors associated with each workplace. Fourth, the follow-up interval for the study was only 1 year, which limited our ability to examine changes in work engagement as a predictor of changes in health behavior. That is, we also investigated the association between change in work engagement and change in health behaviors. However, because the follow-up interval for the study was only 1 year, we did not find a significant association. Last, the association between work engagement and other healthy behaviors, such as eating habits and sleep, could not be examined. This is an important area for examination in future work. In conclusion, we found that higher work engagement was associated with healthier drinking and exercise patterns over the course of a 1-year follow-up.
In summary, our findings suggest a potential new direction for research on work engagement and workplace outcomes. Beyond the usual focus on productivity and morale, our findings suggest that worker engagement has positive spillover effects on employees’ health behaviors. In turn, improved health behaviors may have additional knock-on benefits in terms of reduced sickness absenteeism, reduced health insurance premiums, reduced employee turnover. Organizational leaders need to understand that investing in employee work engagement can not only improve the bottom line (corporate profits) but also contribute to employee wellbeing. The spillover benefits that we have identified should be priced into the decision-making process when organizations commit to investing in processes to improve their workplace climate.
Our study was approved by the ethics committee of the Graduate School of Medicine and Faculty of Medicine at the University of Tokyo (No. 2772), Kitasato University School of Medicine Hospital (B12-103), and the University of Occupational and Environmental Health, Japan (10-004).
The authors thank Prof. Masaaki Matsuura, who is a part of the Graduate School of Public Health, Teikyo University, for his comments.
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