Association Between Sleep and Productivity Loss Among 598 676 Employees From Multiple Industries

Design

All data for this cross-sectional study were collected using the StayWell® health risk assessment (HRA). ^10,11 The HRA had 47 questions, though the online version used in this study had adaptive logic, reducing the question set to items relevant to the user. All data were collected as part of employer-sponsored health and well-being programs.

Sample

This study included the last HRA completed online by any employee in calendar years 2014 and 2015. Employees were typically given the opportunity to complete the HRA each year, with voluntary follow-up interventions available. Engagement strategies varied by employer and HRA completion rates averaged 42%, ranging between 12% and 98%. There was little variation by industry type. Duplicates were removed, so a given employee was only represented once. The study included employees ages 18 to 80 who had complete data for the 4 items described below.

Measures

Each employee was asked to report the average number of hours they slept per night (sleep quantity), as well as how often they felt tired during their waking hours (fatigue). Response options are shown in Table 1.

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Table 1.

Descriptive Statistics of the Study Sample.

Attribute	Frequency, %
Age
18-24	3.1
25-34	21.3
35-44	25.1
45-54	27.6
55-64	20.7
65+	2.3
Gender
Female	45.5
Male	54.5
Industrya
Information and professional services	36.2
Manufacturing, mining, and construction	32.2
Administration, education, and health care	21.7
Retail trade	7.4
Utilities	2.5
On average, how many hours of sleep do you get daily?
5 or fewer hours	8.1
6 hours	28.4
7 hours	40.4
8 hours	20.9
9 hours	1.9
10 or more hours	0.2
How often do you feel tired during your waking hours?
Almost never	25.6
Sometimes	58.6
Quite often	12.8
Almost always	3.1
How many days did you miss from your job because of illness or injury in the last 12 months?
None	50.2
1 days	13.7
2 days	13.1
3 days	7.8
4 days	3.8
5 days	3.7
6 days	1.2
7 days	1.1
8 days	0.5
9 days	0.2
10 or more days	4.5
During the time you were at work in the last 12 months, how much did health problems limit you in the kind or amount of work you could do?
0%	79.8
10%	8.0
20%	4.3
30%	2.3
40%	1.0
50%	1.2
60%	0.4
70%	0.4
80%	0.4
90%	0.4
100%	1.9

^aThese industry categories were assigned using the North American Industry Classification System (NAICS) as a guide.

Absence was measured by asking the number of days an employee was absent for health reasons in the previous 12 months (range: 0-10+ days). This item has been studied for validity. ¹²

Presenteeism, the extent to which health problems limited work, was assessed on a scale of 0 to 10 (0 = “did not limit my work at all”; 10 = “completely prevented me from working”). Responses were treated as indicative of the percentage that one’s work was limited due to health problems. In past studies, this measure correlated well with health risks and changes in health risks. ¹³

Analysis

All bivariate analyses were conducted using IBM SPSS Statistics, version 22. Due to the very large size of the data set, virtually all results met typical statistical significance thresholds, so no statistical significance results were reported.

Demographics

The study sample is described in Table 1. A total of 598 676 employees were included in this analysis. The average age was 44.4 years and 54.5% were male. Employees were from 66 different organizations representing 5 broad industry categories.

The most common sleep duration was 7 hours (40.4% of employees). A majority of employees (58.6%) reported being “sometimes” tired during their waking hours. For absence, 50.2% of employees reported zero absences in the past 12 months. The mean days absent was 1.64. A large majority (79.8%) reported no lost productivity at work, and the mean presenteeism reported was 6.3%.

Sleep and Productivity

The cross-sectional relationships between the 2 sleep measures and absence and presenteeism measures are shown in Table 2. The relationship between hours of sleep and mean absence formed a U-shaped pattern. A similar pattern was found with mean presenteeism. This pattern, however, was not observed with median absence or median presenteeism.

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Table 2.

Mean and median absence days and presenteeism by sleep behavior categories.

	Mean Absence Days (Median)	Mean Presenteeism (Median)
On average, how many hours of sleep do you get daily?
5 or fewer hours	2.22 (1)	10.3% (0%)
6 hours	1.72 (1)	6.7% (0%)
7 hours	1.53 (0)	5.6% (0%)
8 hours	1.48 (0)	5.5% (0%)
9 hours	1.82 (0)	7.9% (0%)
10 or more hours	2.39 (0)	12.3% (0%)
How often do you feel tired during your waking hours?
Almost never	1.09 (0)	3.6% (0%)
Sometimes	1.64 (1)	6.0% (0%)
Quite often	2.39 (1)	11.0% (0%)
Almost always	2.92 (2)	15.8% (0%)

Employees who reported more frequent fatigue had higher mean reported absence days and presenteeism. A similar relationship was observed with median absence, though the median value was consistently lower than the mean. Median presenteeism was 0% across all categories of fatigue.

Summary

This study builds on previous research ^{4 –6} but adds to the generalizability of the relationship between sleep and productivity with data from nearly 600 000 employees, 66 employers, and several industries. Having 8 hours of sleep was associated with the lowest productivity loss, though having 7 hours of sleep was very similar. “Almost always” and “Almost never” feeling tired were associated with the highest and lowest mean presenteeism and absence, respectively.

Median productivity loss was consistently lower than mean productivity loss, suggesting that some people can sleep too few or too many hours while being productive at work. It may be beneficial to focus interventions on employees who report both sleep and productivity impairments. Optimizing sleep behaviors for those employees may be one factor in moving toward peak performance.

Limitations

This study’s limitations include the simplicity of the analysis and the self-reported nature of the measures. Cross-sectional studies prevent the determination of causality. Both productivity measures have been studied previously, with promising validity. ^12,13 Self-reported hours of sleep is not an uncommon measure ³ and is a practical necessity in employer-sponsored health and well-being programs. Other validated instruments for fatigue are typically longer and may be less useful in workplace settings. ^7,8 Future research should examine the relationships described here using study designs that can control confounding variables and detect the temporal relationship between variables.

Significance

Poor sleep has long been recognized as a serious health risk, and this study enhances the generalizability of the literature demonstrating its association with productivity loss.