ORIGINAL ARTICLE
Health Risk Factors Associated With Presenteeism in the Workplace Bonnie L. Callen, PhD, RN, Lisa C. Lindley, PhD, RN, and Victoria P. Niederhauser, DrPH, RN
Objective: An emerging concern in the workplace is the productivity of employees who come to work instead of staying home when they are ill, also referred to as presenteeism. This study examined the health risks associated with presenteeism. Methods: Using a cross-sectional correlational design, we used data from a 2010 self-reported wellness surveys. A negative binomial regression model was used to explore the association between employee health risks and presenteeism. Results: The findings revealed that workplace stress (β = 0.76; P < 0.001), stress at home (β = 0.87; P < 0.001), and financial stress (β = 0.59; P < 0.001) were related to presenteeism. Other health risks were not associated with presenteeism. Conclusions: We found that only stress was related to presenteeism, and other health risks were unrelated to presenteeism.
CONCEPTUAL MODEL
U
nited States (US) workers are some of the most productive employees in the world.1 Managers and executives continually strive to maintain high levels of productivity across industries; nevertheless, an emerging concern in the workplace is the productivity influence of employees who come to work instead of staying home when they are ill, also referred to as presenteeism.2 In a recent report by the Society for Human Resources Management,3 the cost of presenteeism to the US economy is more than $180 billion annually, which surpassed the cost of absenteeism at $118 billion annually. Furthermore, presenteeism accounts for 77% of total lost productivity in the workplace compared with 23% of lost productivity that is attributable to absenteeism.4 Presenteeism is a critical problem in the US workplace. Many employees come to work with health issues. For example, a majority of working adults have high blood pressure above 120/80 mm Hg, total cholesterol above 250 mg/dL, and body mass index (BMI) that classifies them as overweight or obese.5 Stress from work, home, and financial factors is common among workers.6 Few get the Centers for Disease Control and Prevention’s recommended exercise amount, although most have a diet high in saturated fats and salt.7,8 Although these risks contribute to serious health problems, including coronary artery disease and stroke, they may also have less obvious effects on daily functioning such as decreasing cognition and concentration, which may reduce worker productivity.9 Although employee attitude, supervision, technology, and employee morale have been identified as factors that affect productivity, employee health also has a critical influence on the ability of employees to effectively and efficiently perform their job.10 In fact, recent studies have found that health risks, such as obesity,5,11–15 lack of physical activity,13,15 poor diet,11 high blood pressure,12 high cholesterol,12 and stress,11,16,17 are related to productivity loss when workers continue to work while sick. Several authors have examined From the College of Nursing, University of Tennessee–Knoxville, Knoxville, Tenn. This publication was funded by a grant from B&W Y-12. The authors declare no conflicts of interest with respect to the authorship and/or publication of this article. Address correspondence to: Bonnie L. Callen, PhD, RN, College of Nursing, University of Tennessee–Knoxville , 1200 Volunteer Blvd, Knoxville, TN 37996 ([email protected]). C 2013 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0b013e3182a200f4
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multiple health risks,11,13,15,18 and yet, we still lack a comprehensive understanding of the health risks linked to presenteeism. Improving our knowledge of presenteeism is important and timely for US managers and executives. Given the current rising health care costs in the workplace, presenteeism may be significant because it exacerbates existing health conditions.19 It may also impede the quality of work life for employees. In addition, organizational practices and policies aimed at reducing absenteeism may encourage workers to attend work while ill, potentially causing more problems through presenteeism.19 Improving our knowledge of presenteeism has implications for the human resource management of the organization. Therefore, the purpose of this study is to examine the underlying health risks that might cause presenteeism.
A conceptual model was developed with the intention to identify the factors possibly related to presenteeism within the context of the study (Fig. 1). Blood pressure was included in the model because employees with elevated systolic and diastolic values may not feel ill enough to call in sick, but rather show up for work and are unproductive.15 As health risks that may contribute to an employee being unproductive, cholesterol and blood glucose were included. Employees who are overweight or obese may experience various health problems such as low back pain, heart disease, and diabetes, and weight may influence whether or not an employee comes to work ill and is not productive. Stress was included in the model because employees who experience stress at home or elsewhere may not be productive at work. Employees, who do not exercise and have a poor diet, may be also unproductive, so exercise and diet were included. Thus, our conceptual model posits that health risk factors are directly related to presenteeism.
METHODS Design and Sample This study was a cross-sectional correlational analysis of data collected in 2010 from a sample of employees who volunteered to participate in a health risk assessment. The work environment, a government security complex, is known to be high-stress, high-stakes workplaces with substantial consequences for human error. Employees were given $300, if they completed the health assessment survey. Two thousand three hundred and forty-five employees, representing about 50% of the workforce, completed the survey. Employees were excluded from the study if they had missing data. Analysis of the missing data found no significant difference between respondents with complete data and those missing responses to survey items. All outliers were individually examined and excluded, resulting in the final sample size of 1728. The internal review board approval for this study was obtained from the employer and the University of Tennessee, Knoxville.
Instrument The Personal Wellness Profile (Wellsource, Inc, Clackamas, OR), a validated and reliable health risk and behavioral survey, was completed by more than 2345 employees during voluntary participation in the assessment phase of an employee wellness program beginning in 2010.20,21 The Personal Wellness Profile consisted of JOEM r Volume 55, Number 11, November 2013
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Health Risks and Presenteeism
were not highly correlated (>0.85) with the exception of total cholesterol and low-density lipoprotein, which represented a minimal risk of multicollinearity. Because of the count nature of the dependent variable, a negative binomial regression was used to estimate the association between health risks and presenteeism, while controlling for demographics and health conditions.24 This model was preferred over a Poisson count regression model because we had overdispersion of zeros in the presenteeism variable. The regression analysis results are presented as unstandardized coefficients that are interpreted as a one-unit increase in an independent variable leads to an increase/decrease in the dependent variable. All analyses were conducted using Stata 11.0 software (StataCorp, College Station, TX).25 FIGURE 1. A conceptual model of presenteeism. 60 multiple-choice items completed by the individual on a Scantron form. The survey contained questions in the following categories: demographics (age, sex, and race), personal history, medical care, physical activity, eating practices, substance use, mental/social health, safety, job satisfaction, readiness to change, and health interests. Physiologic measures assessed at the time of the survey included height, weight, body composition, blood pressure, resting pulse, blood tests (HgA1c, PSA, and cholesterol), fitness assessment, and a 1-mile walk.
Measures Dependent Variable Survey respondents were asked: how many days did poor physical or mental health result in decreased productivity during the past 4 weeks? The responses ranged from 0 to 9 days or more. This was used to measure presenteeism.
Independent Variables A number of health risk variables were constructed for this study. Blood pressure was measured by systolic and diastolic rates. Laboratory values obtained were cholesterol (total cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides) and blood glucose. Body mass index was used as a measure for weight status. Stress variables were created for whether or not a respondent reported experiencing stress at work, home, or over finances. Total days per week of exercise, days per week of strength exercise, and days per week of stretching exercise were measures of self-reported exercise. Two self-reported variables were used to measure diet. Salt was categorized as whether or not a respondent used salt, and fat was categorized as whether or not fats were used in cooking.
Control Variables Several demographic and health condition variables were included in the model as covariates. The total number of years living was the measure for age. Sex was categorized by whether the respondent was male or female. The race variable was operationalized as whether the respondent was white or not. A variety of health condition variables were created for whether an employee was told by their doctor they had allergies, asthma, arthritis, chronic back pain, chronic sinus problems, broken bone, heart disease, cancer, or diabetes in the last 10 years.
Statistical Analyses Descriptive statistics using means and proportions were calculated for all study variables. Independent variables in the statistical model were used in their reported form and not transformed (eg, converted to categorical variables) to avoid the loss of power and residual confounding.22 The independent variables in the model
RESULTS Summary statistics for the variables included in the analytical model are presented in Table 1. More than 500 employees reported at least 1 unproductive day because of illness in the past 4 weeks, and on average they experienced about a half a day of productivity loss because of poor physical or mental health. In fact, 9.00% reported 1, 7.00% reported 2, 5.00% reported 3 to 5, and 1.00% reported 6 to 8 unproductive days in the past 4 weeks. The age of the sample ranged from 20 to 75 years, with the average age of 47 years. Most were male (60.59%) and white (89.12%). Some employees had self-reported health conditions— allergies (35.36%), asthma (7.00%), arthritis (15.22%), chronic back pain (7.58%), sinus problems (7.58%), broken bones (7.58%), heart disease (2.43%), cancer (2.89%), and diabetes (7.00%). The mean blood pressure was high (130/84 mm Hg), with 41.00% of the participants having prehypertension and 24.00% with high blood pressure readings at the time of the assessment. The average blood glucose was within normal parameters at 99.06 mg/dL. The average total cholesterol was high (178.18 mg/dL); nevertheless, the mean low-density lipoprotein (108.26 mg/dL), high-density lipoprotein (44.49 mg/dL), and triglycerides (127.65 mg/dL) were in normal ranges. The average BMI of the employees was 29.60, including 41.00% classified as obese (BMI: ≥30) and another 38.00% overweight (BMI: 25 to 29.9). A majority experienced stress at work (84.09%) and home (83.22%), and 31.37% indicated stress over finances. Employees in the sample reported that they exercised on average 2.5 days a week and did strength and stretching less than 1 day a week. Less than half (40.57%) used salt regularly, and a majority of employees (53.13%) usually used fats in their cooking. The results of the negative binomial regression analysis, estimating the association between health risks and presenteeism, are shown in Table 2. Of the health risks, only stress was positively associated with presenteeism. Experiencing workplace stress (β = 0.76; P < 0.001) increased the expected number of days an employee had decreased productivity because of physical or mental health. The difference in the count of presenteeism days is 0.76 unit higher for those with workplace stress than for those without workplace stress, although holding the other variables constant in the model. Stress at home (β = 0.87; P < 0.001) was also positively related to an increase in the number of days of diminished productivity. Compared with those with no stress at home, the difference in the count of presenteeism days is 0.87 unit higher for those with stress at home. Financial stress was significantly and positively associated (β = 0.59; P < 0.001), with an increase in the number of days an employee had decreased productivity. Employees with financial stress were expected to have the count of presenteeism days 0.59 unit higher than those with no financial stress. Blood pressure, cholesterol, blood glucose, weight, exercise, and diet were not significantly associated with presenteeism. Several control variables were associated with presenteeism in the study. Being female (β = 0.29; P < 0.05) increased the number of days of presenteeism, whereas being nonwhite (β = −0.43;
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TABLE 1. Descriptive Statistics of Study Variables (n = 1728)* Variables Presenteeism Health risks Blood pressure Systolic Diastolic Cholesterol Total LDL HDL Triglycerides Blood glucose Weight BMI Stress, % Work Home Finances Exercise Total Strength Stretching Diet, % Salt Fats Demographics Age Male, % White, % Health conditions, % Allergies Asthma Arthritis Back pain Sinus problems Broken bones Heart disease Cancer Diabetes
N
Percentage/ Mean
Standard Deviation
Minimum
Maximum
1728
0.51
1.23
0
9
1728 1728
130.26 84.39
15.66 8.93
50 40
215 132
1728 1728 1728 1728 1728
178.18 108.26 44.49 127.65 99.06
32.38 27.98 12.86 68.46 18.21
110 40 9 26 49
350 242 108 585 315
1728
29.60
5.92
16
65
1453 1438 542
84.09 83.22 31.37
– – –
0 0 0
1 1 1
1728 1728 1728
2.56 0.89 0.64
1.79 1.18 1.06
0 0 0
7 3 3
701 918
40.57 53.13
– –
0 0
1 1
1728 1047 1540
46.74 60.59 89.12
11.2 – –
20 0 0
75 1 1
611 121 263 131 131 131 42 50 121
35.36 7.00 15.22 7.58 7.58 7.58 2.43 2.89 7.00
– – – – – – – – –
0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1
*Blood pressure scale, mm Hg; cholesterol scale, mg/dL; blood glucose scale, mg/dL. BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
P < 0.05) decreased the number of days an employee had diminished productivity because of health. Controlling for age and health conditions had no significant relationship with presenteeism.
DISCUSSION The goal of the study was to examine the relationship between health risk factors and workplace presenteeism. The health risks found in this sample of employees were significant. About 80% of the participants were overweight or obese, and another 34% had significant risks for cardiovascular disease. In addition, few employees participated in healthy lifestyle behaviors such as adequate exercise and good nutrition. Furthermore, stress was identified in a majority of the employees, and on a daily basis these employees work in a high-stress, high-stakes environment. 1314
Four of five of those participating in this wellness assessment were overweight or obese, far exceeding national and statewide benchmarks. In fact, the rate of obesity in the participants (41%) was 12% higher than the Tennessee average of 29%.26 It has been documented that being obese is associated with an increase in absences related to sickness. In a British study of more than 2000 workers, obese employees took an average of 4 more days off per year for sickness than their healthier counterparts.27 In addition, studies have found a relationship between weight and presenteeism.9,11,28 In one study, moderate or extremely obese workers (those with a BMI ≥35) experienced a 4.2% health-related loss in productivity. This productivity loss was estimated to cost the company $506 per person annually.28 This study did not find the same relationship between weight and presenteeism. A reason for this inconsistent finding may
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Health Risks and Presenteeism
TABLE 2. Results of Regression Analysis for Presenteeism (n = 1728)a
β
Variables Health risks Blood pressure Systolic Diastolic Cholesterol Total LDL HDL Triglycerides Blood glucose Weight BMI Stress Work Home Finances Exercise Total Strength Stretching Diet Salt Fats Demographics Age Sex Race Health conditions Allergies Asthma Arthritis Back pain Sinus problems Broken bones Heart disease Cancer Diabetes
95% Confidence Interval
Confidence Interval
− 0.01 − 0.01
− 0.01 − 0.03
0.01 0.01
0.01 − 0.01 0.01 0.01 0.01
− 0.03 − 0.04 − 0.03 − 0.01 − 0.01
0.03 0.03 0.04 0.01 0.01
− 0.01
− 0.02
0.02
0.76* 0.87* 0.59*
0.32 0.44 0.35
1.19 1.29 0.84
− 0.14* 0.46 0.04
− 0.22 − 0.09 − 0.08
− 0.05 0.18 0.16
− 0.11 − 0.02
− 0.36 − 0.26
0.14 0.23
− 0.01 0.29*** − 0.43***
− 0.02 0.01 − 0.83
0.01 0.56 − 0.2
0.07 0.22 − 0.05 0.11 0.25 0.28 0.27 0.03 0.18
− 0.19 − 0.22 − 0.40 − 0.32 − 0.18 − 0.16 − 0.47 − 0.64 − 0.36
0.33 0.67 0.29 0.55 0.68 0.72 1.01 0.71 0.71
a Blood pressure scale, mm Hg; cholesterol scale, mg/dL; blood glucose scale, mg/dL. *P < 0.001; ** P < 0.01; *** P < 0.05. BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
be our sample. A majority of the employees in this study were overweight or obese. Thus, the power to see a statistical difference in the dependent variable may have been affected. This study found that stressors from home, work, and financials were a significant contributor to employees’ decreased productivity. These findings are consistent with other studies that have explored the relationship between stress and presenteeism.11,17,19 It is interesting to note that the United States has less research in this area than countries such as Sweden or Australia. One Australian study of 60556 full-time employees, psychological distress had an impact
on employee productivity.29 Among blue-collar workers, high psychological distress resulted in an 18% increase in absenteeism rates. High psychological distress led to a presenteeism increase of 6% in both blue- and white-collar employees. Another study conducted in four Scandinavian countries found that increased job stress was associated with both absenteeism and presenteeism.30 A study with employees of a large national corporation examined the relationship between 10 health risks (poor diet, BMI, cholesterol, exercise, stress, preventive services, fulfillment, blood pressure, smoking, diabetes, and stress) and productivity and found that the two risks with the greatest impact on productivity were stress and diabetes.9 One possible reason for the relationship between stress and presenteeism in this study may be related to the nature of the work environment. The employees in this study worked at a government facility involved in the manufacture of high-grade explosives and nuclear materials. These are typically dangerous jobs, but critical to national security. Employees may dismiss their stress and believe that it has no impact on their health because of the importance they place on doing their job; or perhaps because it is a high-stress environment, this is considered “normal” for these employees. Employers and health care providers need to pay attention to stress levels and presenteeism. Many studies link decreased productivity with health conditions and health risks.5,13–15,31,12 Nevertheless, in this study there was no relationship between presenteeism and high blood pressure, cholesterol, blood glucose, weight, exercise, and diet. The findings related to exercise and work productivity are inconsistent with other studies. Burton and colleagues15 found a relationship between being a member of a corporate fitness complex and having fewer work limitations; work limitations were measured by an 8-item survey that addressed four domains, including time management, physical work activities, mental/interpersonal activities, and reported working to the fullest capabilities and accomplishing full work output. One reason for these converse findings in this study may have been the way the variables exercise and presenteeism were defined. In one study, physical activity was defined as whether or not employees participated in a corporate fitness center.13 In this study, to measure presenteeism, we asked people to report the number of unproductive days related to a health issue, whereas the other studies used “improved work outcomes” and “work limitations” as the outcome variables. Perhaps one explanation for the cholesterol and blood glucose findings may have been because the mean value of these physiologic measures was within the normal range. Other explanations might be that presenteeism is not affected by these conditions, but absenteeism rates may be increased. Another interesting finding was the relationship between sex and presenteeism. Females reported that physical or mental health impacted their productivity more than the males. Our findings are similar to one US study where there was a significant relationship between obese or overweight women and work limitations, but nonsignificant findings for the men in the study.32 Nevertheless, the findings are contrary to a Swedish study that reported that presenteeism was more likely in males than in females.33 One possible reason for our results may relate to economics. Women may be more likely to show up to work ill because they need the money. Women generally have lower seniority on the job than men, and in companies where the sick leave is banked on the basis of years of service, women may not have accumulated many sick leaves. Although the Family Leave Act allows for women and men to take time off for illness, the law does not require employers to pay employees for lost time. As a result, many women, especially single mothers, may need to work although ill simply because they cannot afford to stay home and incur the loss of salary. Although other studies have shown insignificant differences in mean productivity by race/ethnicity, this study revealed that diverse ethnic/racial employee groups were less likely to experience presenteeism than white workers. In the literature there is a lack of
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empirical studies that focus on ethnicity or race and the relationship of health risks and presenteeism. This is an important area for further investigation. This study had several limitations that are worth noting. First of all it was a volunteer sample, with only half the workforce participating; therefore, it is not generalizable to the entire workforce or general population. In addition, the low response rate (50%) may present a risk of sampling bias. This study used one question to measure presenteeism, reported days in the last 4 weeks that productivity at work was decreased because of physical or mental health issues. There are multiple self-report presenteeism measures in the literature, with varying reliability and validity statistics. The secondary nature of the data did not allow for instrument selection; nevertheless, future studies should use instruments to measure different aspects of productivity, including quality, quantity, time on task, and personal factors.34 In addition, the self-report measure of presenteeism and other key variables means that there is a significant risk of bias35 ; employees may be reluctant to disclose their lack of productivity to their employer or may be unable to recall diet intake or time spent exercising.
CONCLUSIONS Despite these limitations, the findings from this study have implications for occupational health professionals and employers. The role that stress plays in productivity should not be underestimated and may cause significant losses for the workplace.36 For occupational health care professionals, these results suggest that stress interventions might be important to develop. Offering programs for specific sources of stress, including financial, work, and home stress, would provide employees with a targeted approach to minimizing stress in their lives. For example, a program that teaches employees how to save, invest money, and create a budget may be helpful in reducing financial stress, or programs on effective communication and conflict resolution may lower stress at home. Furthermore, general stress management interventions, such as flexible work hours, on-site fitness centers, ongoing work climate surveys aimed at improving work environment, and training of line managers in effective leadership, can contribute to reducing stress. Creating stress reduction interventions for employees in their work environment could save employers money and improve the mental health of employees. Future research might investigate the cost–benefit of stress reduction programs aimed at reducing presenteeism. From a research perspective, further randomized studies in the area of how health risks and lifestyle behaviors affect presenteeism are needed. In addition, methodological studies for reliable and valid measures of presenteeism need to continue, which may address the issue of inconsistent findings about the relationship between several health risks and presenteeism. Furthermore, intervention studies that examine the impact of employee stress reduction interventions on presenteeism would generate critical knowledge for employers. Finally, the exploration of demographic variables, including race/ethnicity and sex, needs further study.
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ACKNOWLEDGMENT Special thanks to Beth Schewe for her assistance with the manuscript.
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32. Tunceli K, Li K, Williams LK. Long-term effects of obesity on employment and work limitations among U.S. adults, 1986 to 1999. Obesity (Silver Spring). 2006;14:1637–1646. 33. Barclay KJ. Sex Composition of the Workplace and Mortality Risk. J Biosoc Sci. 2012:1–15. 34. Schultz AB, Edington DW. Employee health and presenteeism: a systematic review. J Occup Rehabil. 2007;17:547–579.
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Health Risk Factors Associated With Presenteeism in the Workplace Bonnie L. Callen, PhD, RN, Lisa C. Lindley, PhD, RN, and Victoria P. Niederhauser, DrPH, RN
Objective: An emerging concern in the workplace is the productivity of employees who come to work instead of staying home when they are ill, also referred to as presenteeism. This study examined the health risks associated with presenteeism. Methods: Using a cross-sectional correlational design, we used data from a 2010 self-reported wellness surveys. A negative binomial regression model was used to explore the association between employee health risks and presenteeism. Results: The findings revealed that workplace stress (β = 0.76; P < 0.001), stress at home (β = 0.87; P < 0.001), and financial stress (β = 0.59; P < 0.001) were related to presenteeism. Other health risks were not associated with presenteeism. Conclusions: We found that only stress was related to presenteeism, and other health risks were unrelated to presenteeism.
CONCEPTUAL MODEL
U
nited States (US) workers are some of the most productive employees in the world.1 Managers and executives continually strive to maintain high levels of productivity across industries; nevertheless, an emerging concern in the workplace is the productivity influence of employees who come to work instead of staying home when they are ill, also referred to as presenteeism.2 In a recent report by the Society for Human Resources Management,3 the cost of presenteeism to the US economy is more than $180 billion annually, which surpassed the cost of absenteeism at $118 billion annually. Furthermore, presenteeism accounts for 77% of total lost productivity in the workplace compared with 23% of lost productivity that is attributable to absenteeism.4 Presenteeism is a critical problem in the US workplace. Many employees come to work with health issues. For example, a majority of working adults have high blood pressure above 120/80 mm Hg, total cholesterol above 250 mg/dL, and body mass index (BMI) that classifies them as overweight or obese.5 Stress from work, home, and financial factors is common among workers.6 Few get the Centers for Disease Control and Prevention’s recommended exercise amount, although most have a diet high in saturated fats and salt.7,8 Although these risks contribute to serious health problems, including coronary artery disease and stroke, they may also have less obvious effects on daily functioning such as decreasing cognition and concentration, which may reduce worker productivity.9 Although employee attitude, supervision, technology, and employee morale have been identified as factors that affect productivity, employee health also has a critical influence on the ability of employees to effectively and efficiently perform their job.10 In fact, recent studies have found that health risks, such as obesity,5,11–15 lack of physical activity,13,15 poor diet,11 high blood pressure,12 high cholesterol,12 and stress,11,16,17 are related to productivity loss when workers continue to work while sick. Several authors have examined From the College of Nursing, University of Tennessee–Knoxville, Knoxville, Tenn. This publication was funded by a grant from B&W Y-12. The authors declare no conflicts of interest with respect to the authorship and/or publication of this article. Address correspondence to: Bonnie L. Callen, PhD, RN, College of Nursing, University of Tennessee–Knoxville , 1200 Volunteer Blvd, Knoxville, TN 37996 ([email protected]). C 2013 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0b013e3182a200f4
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multiple health risks,11,13,15,18 and yet, we still lack a comprehensive understanding of the health risks linked to presenteeism. Improving our knowledge of presenteeism is important and timely for US managers and executives. Given the current rising health care costs in the workplace, presenteeism may be significant because it exacerbates existing health conditions.19 It may also impede the quality of work life for employees. In addition, organizational practices and policies aimed at reducing absenteeism may encourage workers to attend work while ill, potentially causing more problems through presenteeism.19 Improving our knowledge of presenteeism has implications for the human resource management of the organization. Therefore, the purpose of this study is to examine the underlying health risks that might cause presenteeism.
A conceptual model was developed with the intention to identify the factors possibly related to presenteeism within the context of the study (Fig. 1). Blood pressure was included in the model because employees with elevated systolic and diastolic values may not feel ill enough to call in sick, but rather show up for work and are unproductive.15 As health risks that may contribute to an employee being unproductive, cholesterol and blood glucose were included. Employees who are overweight or obese may experience various health problems such as low back pain, heart disease, and diabetes, and weight may influence whether or not an employee comes to work ill and is not productive. Stress was included in the model because employees who experience stress at home or elsewhere may not be productive at work. Employees, who do not exercise and have a poor diet, may be also unproductive, so exercise and diet were included. Thus, our conceptual model posits that health risk factors are directly related to presenteeism.
METHODS Design and Sample This study was a cross-sectional correlational analysis of data collected in 2010 from a sample of employees who volunteered to participate in a health risk assessment. The work environment, a government security complex, is known to be high-stress, high-stakes workplaces with substantial consequences for human error. Employees were given $300, if they completed the health assessment survey. Two thousand three hundred and forty-five employees, representing about 50% of the workforce, completed the survey. Employees were excluded from the study if they had missing data. Analysis of the missing data found no significant difference between respondents with complete data and those missing responses to survey items. All outliers were individually examined and excluded, resulting in the final sample size of 1728. The internal review board approval for this study was obtained from the employer and the University of Tennessee, Knoxville.
Instrument The Personal Wellness Profile (Wellsource, Inc, Clackamas, OR), a validated and reliable health risk and behavioral survey, was completed by more than 2345 employees during voluntary participation in the assessment phase of an employee wellness program beginning in 2010.20,21 The Personal Wellness Profile consisted of JOEM r Volume 55, Number 11, November 2013
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Health Risks and Presenteeism
were not highly correlated (>0.85) with the exception of total cholesterol and low-density lipoprotein, which represented a minimal risk of multicollinearity. Because of the count nature of the dependent variable, a negative binomial regression was used to estimate the association between health risks and presenteeism, while controlling for demographics and health conditions.24 This model was preferred over a Poisson count regression model because we had overdispersion of zeros in the presenteeism variable. The regression analysis results are presented as unstandardized coefficients that are interpreted as a one-unit increase in an independent variable leads to an increase/decrease in the dependent variable. All analyses were conducted using Stata 11.0 software (StataCorp, College Station, TX).25 FIGURE 1. A conceptual model of presenteeism. 60 multiple-choice items completed by the individual on a Scantron form. The survey contained questions in the following categories: demographics (age, sex, and race), personal history, medical care, physical activity, eating practices, substance use, mental/social health, safety, job satisfaction, readiness to change, and health interests. Physiologic measures assessed at the time of the survey included height, weight, body composition, blood pressure, resting pulse, blood tests (HgA1c, PSA, and cholesterol), fitness assessment, and a 1-mile walk.
Measures Dependent Variable Survey respondents were asked: how many days did poor physical or mental health result in decreased productivity during the past 4 weeks? The responses ranged from 0 to 9 days or more. This was used to measure presenteeism.
Independent Variables A number of health risk variables were constructed for this study. Blood pressure was measured by systolic and diastolic rates. Laboratory values obtained were cholesterol (total cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides) and blood glucose. Body mass index was used as a measure for weight status. Stress variables were created for whether or not a respondent reported experiencing stress at work, home, or over finances. Total days per week of exercise, days per week of strength exercise, and days per week of stretching exercise were measures of self-reported exercise. Two self-reported variables were used to measure diet. Salt was categorized as whether or not a respondent used salt, and fat was categorized as whether or not fats were used in cooking.
Control Variables Several demographic and health condition variables were included in the model as covariates. The total number of years living was the measure for age. Sex was categorized by whether the respondent was male or female. The race variable was operationalized as whether the respondent was white or not. A variety of health condition variables were created for whether an employee was told by their doctor they had allergies, asthma, arthritis, chronic back pain, chronic sinus problems, broken bone, heart disease, cancer, or diabetes in the last 10 years.
Statistical Analyses Descriptive statistics using means and proportions were calculated for all study variables. Independent variables in the statistical model were used in their reported form and not transformed (eg, converted to categorical variables) to avoid the loss of power and residual confounding.22 The independent variables in the model
RESULTS Summary statistics for the variables included in the analytical model are presented in Table 1. More than 500 employees reported at least 1 unproductive day because of illness in the past 4 weeks, and on average they experienced about a half a day of productivity loss because of poor physical or mental health. In fact, 9.00% reported 1, 7.00% reported 2, 5.00% reported 3 to 5, and 1.00% reported 6 to 8 unproductive days in the past 4 weeks. The age of the sample ranged from 20 to 75 years, with the average age of 47 years. Most were male (60.59%) and white (89.12%). Some employees had self-reported health conditions— allergies (35.36%), asthma (7.00%), arthritis (15.22%), chronic back pain (7.58%), sinus problems (7.58%), broken bones (7.58%), heart disease (2.43%), cancer (2.89%), and diabetes (7.00%). The mean blood pressure was high (130/84 mm Hg), with 41.00% of the participants having prehypertension and 24.00% with high blood pressure readings at the time of the assessment. The average blood glucose was within normal parameters at 99.06 mg/dL. The average total cholesterol was high (178.18 mg/dL); nevertheless, the mean low-density lipoprotein (108.26 mg/dL), high-density lipoprotein (44.49 mg/dL), and triglycerides (127.65 mg/dL) were in normal ranges. The average BMI of the employees was 29.60, including 41.00% classified as obese (BMI: ≥30) and another 38.00% overweight (BMI: 25 to 29.9). A majority experienced stress at work (84.09%) and home (83.22%), and 31.37% indicated stress over finances. Employees in the sample reported that they exercised on average 2.5 days a week and did strength and stretching less than 1 day a week. Less than half (40.57%) used salt regularly, and a majority of employees (53.13%) usually used fats in their cooking. The results of the negative binomial regression analysis, estimating the association between health risks and presenteeism, are shown in Table 2. Of the health risks, only stress was positively associated with presenteeism. Experiencing workplace stress (β = 0.76; P < 0.001) increased the expected number of days an employee had decreased productivity because of physical or mental health. The difference in the count of presenteeism days is 0.76 unit higher for those with workplace stress than for those without workplace stress, although holding the other variables constant in the model. Stress at home (β = 0.87; P < 0.001) was also positively related to an increase in the number of days of diminished productivity. Compared with those with no stress at home, the difference in the count of presenteeism days is 0.87 unit higher for those with stress at home. Financial stress was significantly and positively associated (β = 0.59; P < 0.001), with an increase in the number of days an employee had decreased productivity. Employees with financial stress were expected to have the count of presenteeism days 0.59 unit higher than those with no financial stress. Blood pressure, cholesterol, blood glucose, weight, exercise, and diet were not significantly associated with presenteeism. Several control variables were associated with presenteeism in the study. Being female (β = 0.29; P < 0.05) increased the number of days of presenteeism, whereas being nonwhite (β = −0.43;
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TABLE 1. Descriptive Statistics of Study Variables (n = 1728)* Variables Presenteeism Health risks Blood pressure Systolic Diastolic Cholesterol Total LDL HDL Triglycerides Blood glucose Weight BMI Stress, % Work Home Finances Exercise Total Strength Stretching Diet, % Salt Fats Demographics Age Male, % White, % Health conditions, % Allergies Asthma Arthritis Back pain Sinus problems Broken bones Heart disease Cancer Diabetes
N
Percentage/ Mean
Standard Deviation
Minimum
Maximum
1728
0.51
1.23
0
9
1728 1728
130.26 84.39
15.66 8.93
50 40
215 132
1728 1728 1728 1728 1728
178.18 108.26 44.49 127.65 99.06
32.38 27.98 12.86 68.46 18.21
110 40 9 26 49
350 242 108 585 315
1728
29.60
5.92
16
65
1453 1438 542
84.09 83.22 31.37
– – –
0 0 0
1 1 1
1728 1728 1728
2.56 0.89 0.64
1.79 1.18 1.06
0 0 0
7 3 3
701 918
40.57 53.13
– –
0 0
1 1
1728 1047 1540
46.74 60.59 89.12
11.2 – –
20 0 0
75 1 1
611 121 263 131 131 131 42 50 121
35.36 7.00 15.22 7.58 7.58 7.58 2.43 2.89 7.00
– – – – – – – – –
0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1
*Blood pressure scale, mm Hg; cholesterol scale, mg/dL; blood glucose scale, mg/dL. BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
P < 0.05) decreased the number of days an employee had diminished productivity because of health. Controlling for age and health conditions had no significant relationship with presenteeism.
DISCUSSION The goal of the study was to examine the relationship between health risk factors and workplace presenteeism. The health risks found in this sample of employees were significant. About 80% of the participants were overweight or obese, and another 34% had significant risks for cardiovascular disease. In addition, few employees participated in healthy lifestyle behaviors such as adequate exercise and good nutrition. Furthermore, stress was identified in a majority of the employees, and on a daily basis these employees work in a high-stress, high-stakes environment. 1314
Four of five of those participating in this wellness assessment were overweight or obese, far exceeding national and statewide benchmarks. In fact, the rate of obesity in the participants (41%) was 12% higher than the Tennessee average of 29%.26 It has been documented that being obese is associated with an increase in absences related to sickness. In a British study of more than 2000 workers, obese employees took an average of 4 more days off per year for sickness than their healthier counterparts.27 In addition, studies have found a relationship between weight and presenteeism.9,11,28 In one study, moderate or extremely obese workers (those with a BMI ≥35) experienced a 4.2% health-related loss in productivity. This productivity loss was estimated to cost the company $506 per person annually.28 This study did not find the same relationship between weight and presenteeism. A reason for this inconsistent finding may
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Health Risks and Presenteeism
TABLE 2. Results of Regression Analysis for Presenteeism (n = 1728)a
β
Variables Health risks Blood pressure Systolic Diastolic Cholesterol Total LDL HDL Triglycerides Blood glucose Weight BMI Stress Work Home Finances Exercise Total Strength Stretching Diet Salt Fats Demographics Age Sex Race Health conditions Allergies Asthma Arthritis Back pain Sinus problems Broken bones Heart disease Cancer Diabetes
95% Confidence Interval
Confidence Interval
− 0.01 − 0.01
− 0.01 − 0.03
0.01 0.01
0.01 − 0.01 0.01 0.01 0.01
− 0.03 − 0.04 − 0.03 − 0.01 − 0.01
0.03 0.03 0.04 0.01 0.01
− 0.01
− 0.02
0.02
0.76* 0.87* 0.59*
0.32 0.44 0.35
1.19 1.29 0.84
− 0.14* 0.46 0.04
− 0.22 − 0.09 − 0.08
− 0.05 0.18 0.16
− 0.11 − 0.02
− 0.36 − 0.26
0.14 0.23
− 0.01 0.29*** − 0.43***
− 0.02 0.01 − 0.83
0.01 0.56 − 0.2
0.07 0.22 − 0.05 0.11 0.25 0.28 0.27 0.03 0.18
− 0.19 − 0.22 − 0.40 − 0.32 − 0.18 − 0.16 − 0.47 − 0.64 − 0.36
0.33 0.67 0.29 0.55 0.68 0.72 1.01 0.71 0.71
a Blood pressure scale, mm Hg; cholesterol scale, mg/dL; blood glucose scale, mg/dL. *P < 0.001; ** P < 0.01; *** P < 0.05. BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
be our sample. A majority of the employees in this study were overweight or obese. Thus, the power to see a statistical difference in the dependent variable may have been affected. This study found that stressors from home, work, and financials were a significant contributor to employees’ decreased productivity. These findings are consistent with other studies that have explored the relationship between stress and presenteeism.11,17,19 It is interesting to note that the United States has less research in this area than countries such as Sweden or Australia. One Australian study of 60556 full-time employees, psychological distress had an impact
on employee productivity.29 Among blue-collar workers, high psychological distress resulted in an 18% increase in absenteeism rates. High psychological distress led to a presenteeism increase of 6% in both blue- and white-collar employees. Another study conducted in four Scandinavian countries found that increased job stress was associated with both absenteeism and presenteeism.30 A study with employees of a large national corporation examined the relationship between 10 health risks (poor diet, BMI, cholesterol, exercise, stress, preventive services, fulfillment, blood pressure, smoking, diabetes, and stress) and productivity and found that the two risks with the greatest impact on productivity were stress and diabetes.9 One possible reason for the relationship between stress and presenteeism in this study may be related to the nature of the work environment. The employees in this study worked at a government facility involved in the manufacture of high-grade explosives and nuclear materials. These are typically dangerous jobs, but critical to national security. Employees may dismiss their stress and believe that it has no impact on their health because of the importance they place on doing their job; or perhaps because it is a high-stress environment, this is considered “normal” for these employees. Employers and health care providers need to pay attention to stress levels and presenteeism. Many studies link decreased productivity with health conditions and health risks.5,13–15,31,12 Nevertheless, in this study there was no relationship between presenteeism and high blood pressure, cholesterol, blood glucose, weight, exercise, and diet. The findings related to exercise and work productivity are inconsistent with other studies. Burton and colleagues15 found a relationship between being a member of a corporate fitness complex and having fewer work limitations; work limitations were measured by an 8-item survey that addressed four domains, including time management, physical work activities, mental/interpersonal activities, and reported working to the fullest capabilities and accomplishing full work output. One reason for these converse findings in this study may have been the way the variables exercise and presenteeism were defined. In one study, physical activity was defined as whether or not employees participated in a corporate fitness center.13 In this study, to measure presenteeism, we asked people to report the number of unproductive days related to a health issue, whereas the other studies used “improved work outcomes” and “work limitations” as the outcome variables. Perhaps one explanation for the cholesterol and blood glucose findings may have been because the mean value of these physiologic measures was within the normal range. Other explanations might be that presenteeism is not affected by these conditions, but absenteeism rates may be increased. Another interesting finding was the relationship between sex and presenteeism. Females reported that physical or mental health impacted their productivity more than the males. Our findings are similar to one US study where there was a significant relationship between obese or overweight women and work limitations, but nonsignificant findings for the men in the study.32 Nevertheless, the findings are contrary to a Swedish study that reported that presenteeism was more likely in males than in females.33 One possible reason for our results may relate to economics. Women may be more likely to show up to work ill because they need the money. Women generally have lower seniority on the job than men, and in companies where the sick leave is banked on the basis of years of service, women may not have accumulated many sick leaves. Although the Family Leave Act allows for women and men to take time off for illness, the law does not require employers to pay employees for lost time. As a result, many women, especially single mothers, may need to work although ill simply because they cannot afford to stay home and incur the loss of salary. Although other studies have shown insignificant differences in mean productivity by race/ethnicity, this study revealed that diverse ethnic/racial employee groups were less likely to experience presenteeism than white workers. In the literature there is a lack of
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empirical studies that focus on ethnicity or race and the relationship of health risks and presenteeism. This is an important area for further investigation. This study had several limitations that are worth noting. First of all it was a volunteer sample, with only half the workforce participating; therefore, it is not generalizable to the entire workforce or general population. In addition, the low response rate (50%) may present a risk of sampling bias. This study used one question to measure presenteeism, reported days in the last 4 weeks that productivity at work was decreased because of physical or mental health issues. There are multiple self-report presenteeism measures in the literature, with varying reliability and validity statistics. The secondary nature of the data did not allow for instrument selection; nevertheless, future studies should use instruments to measure different aspects of productivity, including quality, quantity, time on task, and personal factors.34 In addition, the self-report measure of presenteeism and other key variables means that there is a significant risk of bias35 ; employees may be reluctant to disclose their lack of productivity to their employer or may be unable to recall diet intake or time spent exercising.
CONCLUSIONS Despite these limitations, the findings from this study have implications for occupational health professionals and employers. The role that stress plays in productivity should not be underestimated and may cause significant losses for the workplace.36 For occupational health care professionals, these results suggest that stress interventions might be important to develop. Offering programs for specific sources of stress, including financial, work, and home stress, would provide employees with a targeted approach to minimizing stress in their lives. For example, a program that teaches employees how to save, invest money, and create a budget may be helpful in reducing financial stress, or programs on effective communication and conflict resolution may lower stress at home. Furthermore, general stress management interventions, such as flexible work hours, on-site fitness centers, ongoing work climate surveys aimed at improving work environment, and training of line managers in effective leadership, can contribute to reducing stress. Creating stress reduction interventions for employees in their work environment could save employers money and improve the mental health of employees. Future research might investigate the cost–benefit of stress reduction programs aimed at reducing presenteeism. From a research perspective, further randomized studies in the area of how health risks and lifestyle behaviors affect presenteeism are needed. In addition, methodological studies for reliable and valid measures of presenteeism need to continue, which may address the issue of inconsistent findings about the relationship between several health risks and presenteeism. Furthermore, intervention studies that examine the impact of employee stress reduction interventions on presenteeism would generate critical knowledge for employers. Finally, the exploration of demographic variables, including race/ethnicity and sex, needs further study.
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ACKNOWLEDGMENT Special thanks to Beth Schewe for her assistance with the manuscript.
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