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The Cost of Poor Sleep: Workplace Productivity Loss and Associated Costs

Authors:
  • San Jose State University Research Foundation/NASA Ames Research Center
  • M3 Alertness Management

Abstract and Figures

To assess the impact of sleep disturbances on work performance/productivity. Employees (N = 4188) at four US corporations were surveyed about sleep patterns and completed the Work Limitations Questionnaire. Respondents were classified into four categories: insomnia, insufficient sleep syndrome, at-risk, and good sleep. Employer costs related to productivity changes were estimated through the Work Limitations Questionnaire. Performance/productivity, safety, and treatment measures were compared using a one-way analysis of variance model. Compared with at-risk and good-sleep groups, insomnia and insufficient sleep syndrome groups had significantly worse productivity, performance, and safety outcomes. The insomnia group had the highest rate of sleep medication use. The other groups were more likely to use nonmedication treatments. Fatigue-related productivity losses were estimated to cost $1967/employee annually. Sleep disturbances contribute to decreased employee productivity at a high cost to employers.
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ORIGINAL ARTICLE
The Cost of Poor Sleep: Workplace Productivity Loss and
Associated Costs
Mark R. Rosekind, PhD, Kevin B. Gregory, BS, Melissa M. Mallis, PhD, Summer L. Brandt, MA, Brian Seal, PhD,
and Debra Lerner, PhD
Objective: To assess the impact of sleep disturbances on work performance/
productivity. Methods: Employees (N4188) at four US corporations were
surveyed about sleep patterns and completed the Work Limitations Question-
naire. Respondents were classified into four categories: insomnia, insuffi-
cient sleep syndrome, at-risk, and good sleep. Employer costs related to
productivity changes were estimated through the Work Limitations Ques-
tionnaire. Performance/productivity, safety, and treatment measures were
compared using a one-way analysis of variance model. Results: Compared
with at-risk and good-sleep groups, insomnia and insufficient sleep syn-
drome groups had significantly worse productivity, performance, and safety
outcomes. The insomnia group had the highest rate of sleep medication use.
The other groups were more likely to use nonmedication treatments.
Fatigue-related productivity losses were estimated to cost $1967/employee
annually. Conclusions: Sleep disturbances contribute to decreased em-
ployee productivity at a high cost to employers.
Sleep disorders are among the most common presenting problems
encountered by clinicians.
1,2
According to a 2005 National
Institutes of Health consensus statement, 30% of adults in the
United States (US) had disrupted sleep and 10% had symptoms of
daytime functional impairment consistent with insomnia.
3
In the
2008 National Sleep Foundation (NSF) annual Sleep in America
poll, 32% of respondents reported getting a good night’s sleep only
a few times per month or less.
4
Fifteen percent had symptoms of
sleep apnea, and 11% had insomnia symptoms such as difficulty
falling or staying asleep, awakening during the night, and awaken-
ing too early.
4
For some individuals, insomnia can be chronic,
persisting for 6 months.
5
Despite the high prevalence of sleep problems and related
disorders (eg, restless leg syndrome [RLS]), their detection, diag-
nosis, and treatment are inadequate. In the United States, only about
20% of the estimated 20 million individuals with sleep apnea have
been diagnosed and treated.
4,6
Similarly, only 1% of respondents to
the 2008 NSF poll were receiving treatment for RLS, a proportion
far lower than the actual percentage of adults who have this
disorder, as indicated by surveys and polls (5% to 28%).
2,4,7
In
addition, gaps in the diagnosis and treatment of insomnia are
presumed to occur because the disorder is often regarded by
physicians and individuals as a personal choice rather than a health
problem.
8
Sleep disorders carry numerous personal and societal
consequences.
9
Research has documented that poor sleep is
related to depression, suicide, anxiety, and disability,
7,10,11
dia-
betes mellitus, obesity, and hypertension.
7,12–15
Compared with
individuals who receive adequate sleep, those who report exces-
sive daytime sleepiness due to disturbed sleep are more vulner-
able to accidents and injuries both on and off the job.
4
This article reports data from a study that focused on sleep
disturbances and their relation to health, safety, and performance
outcomes. Work schedules (regular vs irregular) can directly affect
sleep and circadian rhythms, as evidenced by a growing body of
literature that has examined the effects of factors including noctur-
nal work and rotating shifts on employee well-being.
5,8,9
Results
from direct comparisons between employees working regular ver-
sus irregular schedules was hypothesized to show greater health-,
safety-, and performance-related risks for employees in the irregu-
larly scheduled group.
METHODS
Survey Methods
Survey Overview and Objectives
A web-based anonymous survey, sponsored by sanofi-aven-
tis (Bridgewater, NJ), of employees at four US-based companies,
was conducted by Alertness Solutions (Cupertino, CA) between
November 2006 and March 2007. The survey instrument consisted
of questions required for the classification of respondents into
sleep-disturbed groups, based on the American Academy of Sleep
Medicine and the Diagnostic and Statistical Manual of Mental
Disorders (Fourth Edition Text Revision) criteria for primary and
secondary insomnia and insufficient sleep syndrome (ISS).
16,17
The
validated Work Limitations Questionnaire (WLQ) was used to
assess health-related limitations in ability to work as well as
associated productivity losses and costs.
18,19
Company and Employee Inclusion Criteria
The four US-based companies constituted a convenience
sample chosen to represent different industries (health care, man-
ufacturing, ground- and air-based transportation) and geographic
locations. Each company had an opportunity to review the survey
instrument before its administration. In addition, study procedures
were approved by an independent institutional review board.
A subset of employees at each company was randomly
selected to receive an e-mail from a coordinator at each company
that described the survey and its purpose and requested their
participation. An embedded link made the survey available for a
2-week period. At two of the companies, employers elected to
provide the employees with a participation incentive (an opportu-
nity to enter a random drawing for gift cards at popular retailers).
To ensure participant anonymity, the survey did not obtain identifying
information, such as names and addresses. Completed survey forms
were returned as e-mails but without a personal address sent through
a generic server that provided anonymity for the respondent. The
returned survey data were then written to a log file.
From Alertness Solutions (Dr Rosekind, Mr Gregory), Cupertino, Calif; Insti-
tutes for Behavior Resources, Inc. (Dr Mallis), Baltimore, Md; San Jose State
University Research Foundation (Ms Brandt), Moffett Field, Calif; sanofi-
aventis (Dr Seal), Bridgewater, NJ; and Tufts Medical Center and the Tufts
University School of Medicine, Sackler Graduate School of Biomedical
Sciences (Dr Lerner), Boston, Mass.
Address correspondence to: Mark R. Rosekind, PhD, Alertness Solutions, 1601
South De Anza Blvd, Suite 200, Cupertino, CA 95014; E-mail:
bealert@alertsol.com.
Copyright © 2010 by American College of Occupational and Environmental
Medicine
DOI: 10.1097/JOM.0b013e3181c78c30
JOEM Volume 52, Number 1, January 2010 91
The survey instrument took 20 minutes to complete, con-
sisted of 55 questions presented in a variety of formats and was
divided into two parts. The first part included questions on demo-
graphics and other general information, health status (medical and
psychological conditions), sleep information, disturbed sleep treat-
ment use and other strategies, the effects of disturbed sleep, and
work scheduling. Questions were written for purposes of this
survey to allow for the classification of respondents according to
accepted minimum diagnostic criteria for “primary” and “second-
ary” insomnia and for ISS.
16,17
This process was not intended to
provide a clinical diagnosis but rather to extend clinical diagnostic
criteria to subjective survey data.
On the basis of the sleep data, employees were classified into
the following four groups: insomnia (those who met the Diagnostic
and Statistical Manual of Mental Disorders [Fourth Edition Text
Revision] minimum criteria for primary insomnia and included
secondary insomnia), ISS (those who met the criteria for ISS based
on the American Academy of Sleep Medicine diagnostic classifi-
cation system), at-risk (those who did not meet the criteria for
primary insomnia and reported a medical, psychological, or
sleep condition and at least one sleep complaint), and good sleep
(those who did not meet the criteria for any of the other groups
and reported no more than one sleep complaint) (Table 1).
The second portion consisted of the 25-item WLQ,
18,19
a
validated instrument for measuring the degree to which health-
related problems interfere with job performance and productivity.
The WLQ includes four subscales that measure on-the-job time
management, physical performance, mental performance, interper-
sonal functioning, and output.
An additional series of questions was developed and written
for this project asking about work performance problems related to
memory, concentration, decision-making, social functioning, com-
munication, and attention while at work. Safety outcomes examined
included unintentional sleeping while at work, injuring oneself at
work due to tiredness or sleepiness, nodding off while driving, and
poor driving/accidents due to tiredness or falling asleep while
driving.
Statistical Methods
The analysis included employees who completed all survey
questions pertaining to the classification criteria for insomnia and
ISS, all WLQ questions, and 90% of the other survey questions.
Statistical comparisons of individual survey items, as well as WLQ
subscale scores, were made among the four sleep groups using a
one-way analysis of variance model for continuous data or
2
tests
for proportional data. Microsoft Excel and JMP statistical software
(2004, SAS Institute, Cary, NC) were used for data processing and
analysis. For continuous measures, post hoc pairwise comparisons
were conducted using the Tukey–Kramer Honestly Significant
Difference test. All statistical comparisons were two-sided and
conducted at a significance level of 0.05.
Mean salary figures were provided by three of the partici-
pating companies. For the fourth company, mean salary data were
determined for similar companies in the same industry, and an
overall industry mean figure was applied to calculations for that
company. Productivity costs were estimated using this wage data
and a validated algorithm based on WLQ scores.
RESULTS
Participants andSleep Information
Among the 26,175 workers invited to participate, 4188
(16% response rate) completed the survey. The sample consisted
of respondents located in 45 of the 48 contiguous states. On
average, employees had been with their present employer 7.3
7.8 years. At the time of the survey, 31% held managerial
positions, 22% held technical positions, 18% held administrative
positions, and 29% held “other” positions. Most (65%) were
married and were in generally good health; 16.5% said they had
a general medical condition whereas 7.5% stated that they had a
psychological condition. Approximately two thirds (66.8%)
were overweight or obese (ie, had a body mass index of 25
kg/m
2
). Among the participants diagnosed with a sleep disorder
by a physician (n395 [9.4%] of 4188), sleep-disordered
breathing was the most common disorder (57.1%), followed by
insomnia (27.6%) and RLS (14.4%).
Respondents reported working a mean of 9.3 1.5 hr/d and,
given the variety of modern work schedules, additional analyses
were conducted that compared individuals with regular (n2080)
versus those with irregular (n2180) schedules. Irregular sched-
ules were defined as work periods that included rotating shifts,
weekends, nights, changing start and end times, and work outside
traditional daytime hours (7 AM to 6 PM). Individuals who worked
irregular schedules worked more hours daily (9.8 vs 8.8) and
weekly (47.4 vs 43.9) than those with regular schedules, and 65%
reported working some overtime.
Respondents stated that they needed an average sleep time of
7.6 1.0 hr/d to feel rested, but length of sleep averaged 6.4 1.0
hr/d. Table 1 indicates the demographic and sleep characteristics of
the respondents by sleep group. Respondents in the insomnia, ISS,
and at-risk groups reported significantly shorter total sleep times,
longer sleep latencies, and more awakenings than the good-sleep
respondents (all P0.001).
Individuals who worked irregular schedules reported more
impaired sleep than those on regular schedules. They reported less
TABLE 1. Demographic and Sleep Characteristics by Sleep Group (N4,188)
Parameter
Insomnia
(n403)
ISS
(n247)
At-Risk
(n1,660)
Good Sleep
(n1,878)
Prevalence, % 9.6 5.9 39.6 44.8
Age, yr, mean (SD) 40.0 (10.3) 36.3 (11.0) 40.3 (11.1) 40.2 (11.4)
Male, % 38.7 54.7 50.4 59.0
BMI, mean (SD) 27.7 (5.9) 27.1 (5.1) 28.8 (6.4) 27.3 (5.3)
Sleep need, h/d, mean (SD) 7.8 (1.1) 8.0 (1.1) 7.7 (1.1) 7.5 (1.0)
Sleep total, h/d, mean (SD) 6.0 (1.2)* 5.9 (0.9)* 6.3 (1.1)* 6.7 (0.9)
Sleep latency, min, mean (SD) 32.0 (28.3)* 24.1 (20.7)* 26.8 (22.3)* 14.3 (11.7)
Awakenings/sleep period,
mean (SD)
3.0 (2.1)* 2.3 (2.0)* 2.4 (2.1)* 1.5 (1.4)
*Compared with results of the good-sleep group; P0.001, based on one-way ANOVA.
92 © 2010 American College of Occupational and Environmental Medicine
Rosekind et al JOEM Volume 52, Number 1, January 2010
total sleep (6.3 vs 6.5; P0.001), more awakenings (2.2 vs 2.0;
P0.001), and worse sleep quality ratings (5.7 vs 6.0; P0.001).
In addition, more workers with irregular schedules were classified
as insomnia or ISS (17.3% vs 13.8%; P0.01), and fewer were in
the good-sleep category (40.5% vs 49.2%; P0.001).
On-the-Job Productivity
Figure 1 illustrates the mean WLQ subscale scores for each
sleep group. Compared with individuals in the at-risk and good-
sleep groups, respondents in the insomnia and ISS groups had
significantly greater decrements in their ability to perform work
tasks. Significant differences occurred on each of the four scales
with time management having the highest (poorest) scores. Mean
productivity loss (Fig. 2) was significantly higher for the insomnia
group (6.1%) than for the at-risk (4.6%) and good-sleep (2.5%)
groups (all P0.05). The ISS group had an intermediate level of
productivity loss (5.5%).
On-the-Job Performance
Highly negative effects of sleepiness or fatigue at work
were seen in a broad range of responses to the individual survey
questions. Figure 3 shows that, compared with individuals in the
ISS, at-risk, and good-sleep groups, individuals in the insomnia
group reported significantly greater negative effects of fatigue
on attention, decision-making, memory, and motivation at work.
Similar negative effects were seen in the insomnia group for
survey items assessing the ability to concentrate, social func-
tioning, and communication (all P0.01 vs the at-risk group
and P0.001 vs the good-sleep group).
FIGURE 1. Percent work time with
performance limited, by work dimen-
sion and sleep group. *Versus insom-
nia group;
P0.05.
FIGURE 2. Overall average productiv-
ity loss, by sleep group. *Versus in-
somnia group; P0.05.
© 2010 American College of Occupational and Environmental Medicine 93
JOEM Volume 52, Number 1, January 2010 Cost of Poor Sleep
Safety Outcomes
Safety was reported to be impaired in the sleep-disturbed
groups across the full range of outcomes evaluated. Figure 4
illustrates that, compared with the at-risk and good-sleep groups,
the insomnia and ISS groups had significantly more reports of
unintentional sleep at work, injury at home due to being sleepy or
tired, nodding off while driving, and having a near miss or auto-
mobile accident due to sleepiness or tiredness. Interestingly, the ISS
group had significantly more reports of unintentional sleep at work
and nodding off while driving than the insomnia group.
Effects of Irregular
Work Schedules
Workers on irregular schedules reported significantly
greater decrements (P0.001) in their on-the-job productivity
for all WLQ measures compared with regular-schedule workers,
with time management showing the poorest score. Productivity
loss also was greater for individuals on irregular schedules
(4.2% vs 3.5%; P0.001).
Individuals on irregular work schedules reported more safe-
ty-related issues, including acting in an unsafe manner (24.1% vs
13.6%; P0.001), being hurt more at home due to being tired or
sleepy (7.6% vs 3.9%; P0.001), and more reports of falling
asleep at work (40.2% vs 35.8%; P0.01). Those with irregular
schedules also reported more driving safety issues, including nod-
ding off while driving (25.3% vs 16.8%; P0.001) and near
misses or accidents due to being tired (13.5% vs 8.1%; P0.001).
Treatment Use
Among survey respondents as a whole, 72% reported the use
of a treatment for sleep disturbances. A small portion of the sample
as a whole reported having seen a physician about sleep distur-
FIGURE 3. Negative job performance
while sleepy or tired, by sleep group.
*Versus insomnia group; P0.01.
FIGURE 4. Safety outcomes, by sleep
group. *Versus ISS group; P0.05.
†Versus insomnia and ISS groups; P
0.01. ‡Versus insomnia and ISS
groups; P0.001.
94 © 2010 American College of Occupational and Environmental Medicine
Rosekind et al JOEM Volume 52, Number 1, January 2010
bances. As shown in Fig. 5, larger proportions of the insomnia
group stated that they used over-the-counter (OTC) and/or prescrip-
tion sleep medications compared with the ISS, at-risk, and good-
sleep groups. Among individuals in the insomnia group, 11.7%
reported the use of both an OTC and a prescription sleep medica-
tion; this is at least twice the rate of such treatment use reported by
any of the other sleep groups (range, 0.6% to 5.8%) (data not
shown). Conversely, other approaches used by individuals to help
improve their sleep, including herbal remedies, lifestyle changes,
alcohol, and relaxation techniques, were reported by signifi-
cantly larger proportions of individuals in the ISS, at-risk, and
good-sleep groups compared with the insomnia group (Fig. 5).
Economic Cost of Poor Sleep
Based on the salary figures provided by each participating
company, the mean estimated annual cost per employee (expressed
in 2007 $US) of sleep-disturbance–related at-work productivity
loss was greatest for the insomnia group at $3156/employee (range
among the four companies, $2531 to $3980). For the ISS group, the
mean figure was $2796/employee (range, $2410 to $3556), and for
the at-risk group, it was $2319/employee (range, $1790 to $2996).
The good-sleep group had the lowest mean figure, $1293/employee
(range, $1148 to $1593). Estimated annual costs related to produc-
tivity losses per sleep group are summarized in Table 2. As shown
in Table 2, extending these productivity loss/cost calculations to the
total employee population at all four companies, it was estimated
that work productivity loss due to insomnia, insufficient sleep, and
sleep disturbances would reach a cost of $54 million annually.
DISCUSSION
Although occupational medicine has demonstrated the im-
portance and benefits of addressing a variety of health issues in the
workplace (eg, cardiovascular disease, smoking, alcohol use, dia-
betes mellitus, back problems), insomnia and sleep disturbances are
rarely the focus of public health and workplace safety initia-
tives.
20,21
Nevertheless, the competitive global economy and local
issues, such as long commutes, have increased the number of
people working nonstandard shifts.
22
This changing nature of work
and increased emphasis on productivity creates a challenge for
maintaining normal sleep.
8,23
In addition to regular/irregular work
schedules, there are a host of issues extending beyond traditional
perspectives that can detrimentally affect circadian physiology,
including time zone changes, extended and/or consecutive work
periods, reduced time/insufficient recovery between shifts, on-call
or reserve status, and day-to-night/night-to-day transitions.
24
Al-
though nonbiological factors (eg, workload) can negatively influ-
ence employees, the most significant effects will occur through
acute and cumulative sleep loss, disturbed sleep, and circadian
clock disruption.
8,23,24,25
Although difficulties in initiating and
maintaining normal sleep contribute to insomnia, which can
result in decreased performance and safety issues, night work
through a window of circadian low can also produce similar
effects.
8,24,25
These work and schedule-related issues are likely
to affect 80 million Americans
26
and are likely to exacerbate
the prevalence of sleep problems. Minimal information is avail-
able to quantify the effects of sleep disruption and insomnia on
individuals’ work performance, safety, and productivity.
27
Po-
tential indirect economic costs of outcomes related to lost
FIGURE 5. Treatment of sleep distur-
bances, by sleep group. *Versus
insomnia group; P0.05. †Versus
insomnia group; P0.01. Rx denotes
prescription.
TABLE 2. Estimated Annual Costs* of Productivity Loss
Due to Disturbed Sleep, bySleep Group
Parameter Insomnia ISS At-Risk
Good
Sleep
Surveyed respondents, n403 247 1,660 1,878
Mean cost per employee, $ 3,156 2,796 2,319 1,293
Estimated annual cost for sleep
group as a whole, $
1.3 M 0.7 M 3.8 M 2.4 M
Estimated annual cost for entire
employee population, $
8.9 M 4.3 M 24.3 M 16.5 M
Total estimated annual costs,
$54.0 M
*Costs are expressed in 2007 $US.
© 2010 American College of Occupational and Environmental Medicine 95
JOEM Volume 52, Number 1, January 2010 Cost of Poor Sleep
productivity due to insomnia and sleep disturbances also have
not been well quantified.
28
This survey examined sleep and sleep disturbances in 4000
employees from several work populations in four US companies.
About one in 10 (9.6%) met the criteria for insomnia, whereas one
in 16 (5.9%) met the criteria for ISS. The findings demonstrate that,
in general, these sleep disturbances were associated with lower
at-work productivity, impaired work performance, and poorer
safety outcomes, based on various WLQ-derived measures,
compared with scores seen for respondents in the at-risk and
good-sleep groups. Although the large majority of respondents
(72%) reported that they used strategies and treatments to
ameliorate sleep disturbances, respondents in the insomnia
group more frequently used OTC or prescription sleep medica-
tions. Fatigue-related decrements in at-work productivity were
linked to significant estimated annual costs to employers, rang-
ing from a high of $3156/employee in the insomnia group to a
low of $1293/employee in the good-sleep group.
Sleep and Job Performance
The current findings suggest that disturbed sleep is related to
poor at-work functioning. Insomnia and ISS respondents in the
present survey reported impairments in job performance and re-
duced productivity marked by decreased attention, memory, social
and interpersonal functioning, and communication. Similar perfor-
mance deficits resulting from disturbed or inadequate sleep have
been firmly established by other researchers.
29–31
One study of
sleep habits and sleep disturbances among industrial workers in
Israel found that more pre-sleep and post-sleep complaints, mid-
sleep disturbances, work accidents, employment dissatisfaction,
and increased prevalence of asthma, hypertension, headaches, ar-
thritis, and ulcers were noted.
29–31
The present findings also agree
with those of a recent investigation of individuals with obstructive
sleep apnea. Mulgrew et al
31
found that severe obstructive sleep
apnea in blue-collar workers was associated with impaired time
management and mental/interpersonal interactions, based on the
WLQ. Moreover, subjective sleepiness, based on the Epworth
Sleepiness Scale, was strongly associated with limitations in job
performance according to three of the four WLQ subscales (work
output, mental/interpersonal interactions, and time management).
31
The decrements in performance and productivity linked to sleep
disturbances in the present survey and in prior research have
important implications for both job safety and employer costs.
Sleep and Safety
The current investigation raises further concerns about de-
creased work safety due to sleepiness or tiredness in individuals
with a sleep disturbance. Average total sleep time among the
insomnia group in the present sample was 6.0 hr/d, less than the
average adult daily sleep need of 8 hours, which is required
physiologically to maintain alertness.
32
Respondents who reported
sleep disturbances were more likely to report unintentional sleep at
work and injury to themselves or others while at work. This is not
unexpected, as other researchers have found that sleep loss slowed
reaction times on a psychomotor vigilance test, divided attention,
reduced memory recall, and decreased self-rated qualities of per-
formance.
33
Problems with safety related to inadequate sleep have
also been described in health care settings, in which a strong
positive relationship between level of physician fatigue and rate of
patient treatment error has been observed consistently.
30,34
The findings are also consistent with those of other reports
highlighting a strong link between inadequate sleep and driving
accidents.
35,36
According to the National Transportation Safety
Board, sleepiness is the third leading cause of accidents in the
United States.
37,38
The data suggest that individuals in the insomnia
and ISS groups were significantly more likely than individuals in
the good-sleep group to report nodding off while driving and to
have a near miss or accident due to sleepiness. Other studies have
also shown that individuals with insomnia incur significantly
greater direct and indirect health care costs than do individuals
without insomnia.
39
Treatment Use
The use of hypnotic drugs, medications, and behavioral
techniques has long been shown to be a reliable way to aid sleep.
The large majority (72%) of respondents to the present survey
indicated that they used at least one treatment for their sleep
disturbances. However, many reported using “treatments” that do
not improve sleep and may worsen it, such as alcohol. Alcohol
tends to be a common choice among those with a sleep distur-
bance,
40
rather than herbal remedies or relaxation techniques.
41
Unfortunately, this may be ineffective as it tends to produce
interrupted sleep.
40,42
Such use of alcohol is also risky as it is
subject to the development of tolerance and dependence. Few
respondents (13%) reported having seen a physician for disturbed
sleep; this included only 30% of individuals in the insomnia
group. Among individuals in this group, 30% reported the use of
prescription sleep medications and 30% reported the use of relax-
ation techniques. This approach tends to be effective if used
properly and is associated with high ratings for patient satisfaction
compared with other treatment types.
43
Economic Impact
In the present investigation, decreases in productivity related
to tiredness or sleepiness ranged from a high of 6.1% in the
insomnia group to a low of 2.5% in the good-sleep group. Esti-
mated costs per employee linked to productivity decreases were
also highest for individuals in the insomnia group ($3156), in
contrast to a low of $1293 in the good-sleep group. Extending the
15% of respondents classified in the insomnia and ISS groups to
the total workforce for all four participating companies would result
in an estimated 4000 workers affected by insomnia or insufficient
sleep. The estimated cost of lost productivity associated with these
individuals is $13.2 million annually. Inclusion of the at-risk group
increases the number of affected employees to 14,000, with
estimated lost productivity costs of $37.5 million. For the entire
respondent group, work productivity lost due to insomnia, insuffi-
cient sleep, and sleep disturbances would reach costs of $54 million
annually. Other researchers have shown that higher costs to em-
ployers related to sleep disturbance may occur due to increased
absenteeism.
44
In their study of health care employees, Godet-
Cayre´ et al found that employees with insomnia were absent from
work an average of 11.5 d/yr, compared with only 7 d/yr for good
sleepers. Extra costs related to increased absenteeism among em-
ployees with insomnia were estimated at 1472/yr (approximately
$US 1984/yr), and employers bore most of this cost. These esti-
mated costs of lost workplace productivity provide a strong ratio-
nale for improving the detection and treatment of insomnia and
sleep disturbances and present the opportunity to reduce associated
productivity deficits.
45,46
Remedies
There are a number of steps employers and employees can
take to address workplace sleepiness related to sleep disturbances.
Some evidence shows that workplace flexibility (allowing more
flexible work start and end times) may contribute to positive
lifestyle behaviors, and may play an important role in effective
worksite health promotion programs.
47
Another possible step is to
address the complex and often contentious issues related to work
schedule policies and practices.
26
Researchers have also shown that
allowing for “unwinding” time between work and home improves
sleep patterns; negative work-to-home transition interference has
96 © 2010 American College of Occupational and Environmental Medicine
Rosekind et al JOEM Volume 52, Number 1, January 2010
the potential to decrease the risk of poor sleep quality. Adequate
rest between work periods and workdays may help to increase
unwinding and, in turn, sleep quality.
48
Employers can also play a
role in educating workers about the importance of sleep and how to
effectively and safely manage sleep loss/fatigue through a variety
of proven strategies, including naps, better managed work demands,
regular exercise, duty hour considerations, and instructing them on
the basics of good sleep habits.
49–53
Study Limitations
A number of the present findings are derived from responses
to the WLQ, a validated and well-characterized measure of job
productivity. The findings, however, should be viewed in light of a
number of study limitations. First, no systematic criteria were
used to select participating companies; geographic location
within the 48 contiguous states was key. Whether the sample
was representative of the general US population is not known.
The high proportion of employees who reported nonstandard
working hours (50.3%) was much higher in the current survey
sample than in a recent report based on the NSF 2008 poll that
indicated about 7% of the American workforce works nonstandard
hours (ie, shift work).
4
Moreover, the survey did not obtain data
regarding ethnicity. However, it should be noted that survey
responses were obtained from employees located in 45 of the 48
contiguous states and represented a broad range of skills—including
managerial, technical, administrative, and “other”—and income levels.
A second limitation of the study was that different methods
were used to encourage employee participation; at two companies
no incentives were offered, whereas at the other two companies
employees who completed the survey had the opportunity to enter
a drawing for gift cards. The potential impact of this difference was
not examined. The low level of incentive offered may account for
the low response rate obtained (16%). A third limitation was that all
survey outcome measures were based entirely on self-reporting, and
the extent to which responses were reliable and valid is not known.
Although survey-based measures of sleep may lack robust
reliability and validity and have larger error margins compared with
alternate approaches to measuring sleep (including polysomnogra-
phy), it should be noted that these “gold standard” laboratory
recordings would be expensive, extremely time consuming for
participants, geographically difficult to obtain a large, distributed
participant population, and not provide any data on the work-related
aspects that would still require a subjective survey component.
CONCLUSIONS
Insomnia and disturbed sleep were prevalent in the surveyed
workforces and were associated with decreased job performance
and productivity. Individuals meeting the criteria for insomnia
reported the greatest losses and impairments. The associated annual
economic costs due to lost productivity for the entire work popu-
lation at the participating companies were estimated to be $54
million ($1967/employee). Our findings highlight the potential
for the improved detection and treatment of sleep disturbances to
significantly improve workplace safety and productivity and reduce
the associated economic costs.
ACKNOWLEDGMENTS
This study was supported by sanofi-aventis, Bridgewater, NJ.
REFERENCES
1. Lamberg L. World Health Organization targets insomnia. JAMA. 1997;278:
1652.
2. Lamberg L. Promoting adequate sleep finds a place on the public health
agenda. JAMA. 2004;291:2415–2417.
3. National Institutes of Health. State-of-the-Science Conference Statement on
Manifestations and Management of Chronic Insomnia in Adults. Available
at: http://consensus.nih.gov/2005/2005InsomniaSOS026html.htm. Ac-
cessed December 8, 2008.
4. National Sleep Foundation. 2008 Sleep in America Poll: Summary of
Findings. Available at: http://www.sleepfoundation.org/atf/cf/%7Bf6bf2668 –
a1b4 – 4fe8-8d1a-a5d39340d9cb%7D/2008%20POLL%20SOF.PDF. Accessed
December 8, 2008.
5. Walsh JK. Clinical and socioeconomic correlates of insomnia. J Clin
Psychiatry. 2004;65(Suppl 8):13–19.
6. Young T, Evans L, Finn L, Palta M. Estimation of the clinically diagnosed
proportion of sleep apnea syndrome in middle-aged men and women. Sleep.
1997;20:705–706.
7. Alattar M, Harrington JJ, Mitchell CM, Sloane P. Sleep problems in primary
care: a North Carolina Family Practice Research Network (NC-FP-RN)
study. J Am Board Fam Med. 2007;20:365–374.
8. Bedrosian RC. An alarming wake-up call: the impact of insomnia on
health and productivity. J Health Prod. 2008;3:16–21.
9. Rosekind MR. Underestimating the societal costs of impaired alertness:
safety, health and productivity risks. Sleep Med. 2005;6(Suppl 1):S21–S23.
10. Drake CL, Roehrs T, Roth T. Insomnia causes, consequences, and therapeu-
tics: an overview. Depress Anxiety. 2003;18:163–176.
11. Roberts RE, Roberts CR, Duong HT. Chronic insomnia and its negative
consequences for health and functioning of adolescents: a 12-month pro-
spective study. J Adolesc Health. 2008;42:294–302.
12. Chen MY, Wang EK, Jeng YJ. Adequate sleep among adolescents is
positively associated with health status and health-related behaviors. BMC
Public Health. 2006;6:59.
13. Goodfriend TL. Obesity, sleep apnea, aldosterone, and hypertension. Curr
Hypertens Rep. 2008;10:222–226.
14. Hayashino Y, Fukuhara S, Suzukamo Y, Okamura T, Tanaka T, Ueshima H;
HIPOP-OHP Research group. Relation between sleep quality and quantity,
quality of life, and risk of developing diabetes in healthy workers in Japan:
the High-risk and Population Strategy for Occupational Health Promotion
(HIPOP-OHP) Study. BMC Public Health. 2007;7:129–137.
15. Lamberg L. Rx for obesity: eat less, exercise more, and—maybe— get more
sleep. JAMA. 2006;295:2341–2344.
16. American Academy of Sleep Medicine. International Classification of Sleep
Disorders, Revised: Diagnostic and Coding Manual. Chicago, IL: American
Academy of Sleep Medicine; 2001:87.
17. American Psychiatric Association. Diagnostic and Statistical Manual of
Mental Disorders. 4th ed. Washington, DC: American Psychiatric Associa-
tion; 2000.
18. Lerner D, Amick BC III, Rogers WH, Malspeis S, Bungay K, Cynn D. The
work limitations questionnaire. Med Care. 2001;39:72–85.
19. Lerner D, Amick BC III, Lee JC, et al. Relationship of employee-reported
work limitations to work productivity. Med Care. 2003;41:649– 659.
20. DeHart RL, Davis JR, eds. Fundamentals of Aerospace Medicine. 3rd ed.
Baltimore, MD: Lippincott Williams & Wilkins; 2002.
21. Walsh JK. In: Kryger MH, Roth T, Dement WC, eds. Principles and
Practice of Sleep Medicine. 4th ed. Philadelphia, PA: WB Saunders; 2005.
22. Beers TM. Flexible schedules and shift work: replacing the “9-to-5” work-
day? Mon Labor Rev Online. Available at: http://www.bls.gov/opub/mlr/
2000/06/art3abs.htm. Accessed December 8, 2008.
23. Baulk SD, Fletcher A, Kandelaars KJ, Dawson D, Roach GD. A field study
of sleep and fatigue in a regular rotating 12-h shift system. Appl Ergon.
2009;40:694 – 698.
24. Akerstedt T. Shift work and disturbed sleep/wakefulness. Sleep Med Rev.
1998;2:117–128.
25. Melamed S, Oksenberg A. Excessive daytime sleepiness and risk of occu-
pational injuries in non-shift daytime workers. Sleep. 2002;25:315–322.
26. Rosekind MR. Managing work schedules: an alertness and safety perspec-
tive. In: Kryger MA, Roth T, Dement WC, eds. Principles and Practice of
Sleep Medicine. 4th ed. Philadelphia, PA: Elsevier Saunders; 2005:680
690.
27. Le´ger D, Massuel MA, Metlaine A; SISYPHE Study Group. Professional
correlates of insomnia. Sleep. 2006;29:171–178.
28. Ozminkowski RJ, Wang S, Walsh JK. The direct and indirect costs of
untreated insomnia in adults in the United States. Sleep. 2007;30:263–273.
29. Lavie P. Sleep habits and sleep disturbances in industrial workers in Israel:
main findings and some characteristics of workers complaining of excessive
daytime sleepiness. Sleep. 1981;4:147–158.
30. Lockley SW, Barger LK, Ayas NT, Rothschild JM, Czeisler CA, Landrigan
CP; Harvard Work Hours, Health and Safety Group. Effects of health care
© 2010 American College of Occupational and Environmental Medicine 97
JOEM Volume 52, Number 1, January 2010 Cost of Poor Sleep
provider work hours and sleep deprivation on safety and performance. Jt
Comm J Qual Patient Saf. 2007;33(Suppl 11):7–18.
31. Mulgrew AT, Ryan CF, Fleetham JA, et al. The impact of obstructive sleep
apnea and daytime sleepiness on work limitation. Sleep Med. 2007;9:42–53.
32. Ferrara M, De Gennaro L. How much sleep do we need? Sleep Med Rev.
2001;5:155–179.
33. Roehrs T, Burduvali E, Bonahoom A, Drake C, Roth T. Ethanol and sleep
loss: a “dose” comparison of impairing effects. Sleep. 2003;26:981–985.
34. Mountain SA, Quon BS, Dodek P, Sharpe R, Ayas NT. The impact of house
staff fatigue on occupational and patient safety. Lung. 2007;185:203–209.
35. Leechawengwongs M, Leechawengwongs E, Sukying C, Udomsubpayakul
U. Role of drowsy driving in traffic accidents: a questionnaire survey of Thai
commercial truck/bus drivers. J Med Assoc Thai. 2006;89:1845–1850.
36. Vanlaar W, Simpson H, Mayhew D, Robertson R. Fatigued and drowsy
driving: a survey of attitudes, opinions and behaviors. J Safety Res. 2008;
39:303–309.
37. American Automobile Association Foundation for Traffic Safety. Changing
Behaviors to Prevent Drowsy Driving and Promote Traffic Safety: Review of
Proven, Promising, and Unproven Techniques. Available at: http://www.
aaafoundation.org/resources/index.cfm?buttondrowsy. Accessed December 8,
2008.
38. National Transportation Safety Board. Factors That Affect Fatigue in Heavy
Truck Accidents. Washington, DC: NTSB; 1995. NTSB No. SS-95/01.
Available at: http://www.ntsb.gov/publictn/1995/SS9502.pdf. Accessed De-
cember 8, 2008.
39. Simon GE, VonKorff M. Prevalence, burden, and treatment of insomnia in
primary care. Am J Psychiatry. 1997;154:1417–1423.
40. Kaneita Y, Uchiyama M, Takemura S, et al. Use of alcohol and hypnotic
medication as aids to sleep among the Japanese general population. Sleep
Med. 2007;8:723–732.
41. Pearson NJ, Johnson LL, Nahin RL. Insomnia, trouble sleeping, and com-
plementary and alternative medicine: analysis of the 2002 National Health
Interview Survey data. Arch Intern Med. 2006;166:1775–1782.
42. Gillin JC. In: Kryger MH, Roth T, Dement WC, eds. Principles and Practice
of Sleep Medicine. 4th ed. Philadelphia, PA: WB Saunders; 2005.
43. Allaert FA, Urbinelli R. Sociodemographic profile of insomniac patients
across national surveys. CNS Drugs. 2004;18(Suppl 1):3–7.
44. Godet-Cayre´ V, Pelletier-Fleury N, Le Vaillant M, Dinet J, Massuel MA,
Le´ ger D. Insomnia and absenteeism at work: who pays the cost? Sleep.
2006;29:179 –184.
45. Bunn WB III. The employer perspective of insomnia. Manag Care.
2006;15(9 Suppl 6):13–17.
46. Pandi-Perumal SR, Verster JC, Kayumov L, et al. Sleep disorders, sleepiness
and traffic safety: a public health menace. Braz J Med Biol Res. 2006;39:
863– 871.
47. Grzywacz JG, Casey PR, Jones FA. The effects of workplace flexibility on
health behaviors: a cross-sectional and longitudinal analysis. J Occup Envi-
ron Med. 2007;49:1302–1309.
48. Nyle´n L, Melin B, Laflamme L. Interference between work and outside-
work demands relative to health: unwinding possibilities among full-time
and part-time employees. Int J Behav Med. 2007;14:229–236.
49. Davidhizar R, Shearer R. Your best preparation for a good day’s work: a
good night’s sleep. Health Care Manag (Frederick). 2000;19:38– 49.
50. Hirose T. An occupational health physician’s report on the improvement in
the sleeping conditions of night shift workers. Ind Health. 2005;43:58– 62.
51. Jansson M, Linton SJ. Psychosocial work stressors in the development and
maintenance of insomnia: a prospective study. J Occup Health Psychol.
2006;11:241–248.
52. Owens JA. Sleep loss and fatigue in healthcare professionals. J Perinat
Neonatal Nurs. 2007;21:92–100.
53. Rosekind MR, Boyd JN, Gregory KB, Glotzbach SF, Blank RC. Alertness
management in 24/7 settings: lessons from aviation. Occup Med. 2002;17:
247–259.
98 © 2010 American College of Occupational and Environmental Medicine
Rosekind et al JOEM Volume 52, Number 1, January 2010
... Poor sleep quality also increases the overall rate of premature mortality. [3][4][5][6][7] The WHO has classified poor sleep quality as a public health issue that exacerbates the risk of disease and death. 8 It can lead to poor health and an increased risk of diseases such as diabetes, 9 hypertension, 10 obesity, 9 cardiovascular disease 11 and depression. ...
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