Excessive day time sleepiness, poor sleep quality, and their association to caffeine consumption among young Informational Technology professionals

Abstract

Background:

Sleep is essential for promoting physical and mental wellbeing. Short sleep duration and poor sleep quality are becoming more common among Informational Technology (IT) professionals; many IT workers seem to be using caffeine as a coping mechanism to alleviate the negative effects of insufficient sleep. Caffeine reduces sleep quality, prolongs sleep latency, and shortens sleep duration. Information on the sleep quality of young IT professionals is required to determine whether there may be a link between sleep quality, excessive daytime sleep, and caffeine usage.

Aim:

This cross-sectional study examined sleep quality in IT professionals and the associations between sleep quality, excessive daytime sleep, and caffeine consumption.

Materials and Methods:

Caffeine Consumption, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index questionnaires were administered to 200 IT professionals aged 23–40 years via the online survey.

Results:

The average daily caffeine intake was 156.2 (98.7–252.5) mg per day, with coffee and tea being the primary contributor. A high prevalence of poor sleep quality (70%) was observed in the study population. Daily caffeine consumption was associated with poor sleep quality (r = 0.510, P > 0.01), and excessive day time sleep was associated with increased caffeine consumption (r = 0.363, P > 0.01). Excessive caffeine intake tends to be a predictive factor of poor sleep quality with an odd’s ratio of OR 3.15, CI 2.34–4.25), P < 0.01.

Conclusion:

These findings reveal that poor sleep quality is prevalent among IT professionals. More research is required to determine the methods to improve sleep issues. Additionally, health education should be provided regarding the quantity of caffeine in products to avoid excess caffeine consumption and to improve sleep quality.

Sleep is essential for maintaining one’s physical and mental health. The immediate effect of poor sleep is the decrease in the capacity to perform tasks, daytime sleepiness, and fatigue. As an essential modulator of hormone release, cardiometabolic regulation, sleep has been observed to have significant effects on a person’s quality of life.[1] Measures of poor sleep include both indices of sleep quantity and sleep quality. Though both are found to be an important indicator of wellbeing and health, wellness indicators better relate to sleep quality which comprises sleep latency, sleep depth, how the person feels upon waking, restfulness, and general satisfaction with sleep.

Both sleep loss and accumulating sleep debt lead to disruption of sleep patterns, excessive daytime sleepiness, enervation, inattentiveness, compromised endocrine and immune function causing increased risks for cardiometabolic disorder, mood disorders, substance abuse, and other health issues.[2,3] Poor sleep not only impairs quality of life but also poses several health-related problems and has been considered as an important public health problem. It is a well-established phenomenon that duration of sleep and compromised sleep quality are commonly observed in shift workers and shiftwork in itself is a major risk factor for various noncommunicable diseases.

Shift work is common in the Information Technology (IT) sector as they often work in American, European, or Australian timings (shifts). In order to cope with the symptoms of sleep debt, there is a tendency to drink excess coffee during their work. Sleep disturbances are more prevalent in IT professionals than in the general population and are associated with excessive daytime sleepiness (EDS), which are characterized by difficulty maintaining wakefulness and an increased tendency of falling asleep during the day.[4] Another issue that is linked with EDS is increased caffeine consumption to remain awake and alert.[5]

The impact of caffeine on behavior, cognition, and overall health is a double-edged sword. Benefits and drawbacks depend on both the amount and the timing of consumption. Short sleep duration and poor sleep quality are becoming more common among IT professionals; it appears that many are using caffeine to try and offset the effects of their sleep debt and EDS.[6] Caffeine is the most common central nervous system stimulant consumed by 80% of the world’s population. It makes the person alert and awake and improves performance, so it is commonly used in coffee, tea, aerated beverages, chocolates, and energy drinks.[7]

The most common adverse effect of caffeine is sleep disturbance. Caffeine is an adenosine receptor antagonist. Adenosine is a sleep-promoting/regulating substance, so increased caffeine consumption can disrupt sleep. Caffeine consumption significantly reduces sleep duration, lengthens the time of onset of sleep, and impairs sleep quality. Increased caffeine ingestion has been associated with increases in nocturnal body movements, nocturnal awakening, sleep fragmentation, prolonged latency to sleep, a decrease in stages 2 and 4 of nonrapid eye movement (NREM) sleep, and changes in the temporal organization of slow wave and rapid eye movement during sleep.[8] Furthermore, studies have shown that caffeine dependence may develop among individuals who consume caffeine because of a subliminal need to counteract sleep inertia.[9]

Given the lack of research on sleep in IT professionals in India, in the present study, we focused on IT professionals, who also report to have high adherence to caffeine consumption to tackle the major concern of their work pattern, work shifts, deadlines for target achievements, long working hours, and pervasive use of electronic devices which also contribute their inability to obtain sufficient sleep.[10,11] In India, the spread of advanced information and communication technologies has been exponential in the past 2 decades. India is home to thousands of IT web where the clients are from developed countries. Hence, the time zone difference leads to the majority of the work shifts, which in turn leads to reduced sleep quality and health.[12] Due to this reason, IT professionals look out for stimulants to remain alert and concentrate on the work, which later becomes an addiction. Hence, this study was designed to assess the pattern of caffeine consumption among IT employees and its association with sleep quality and daytime functioning.

MATERIALS AND METHODS

The current study is a cross-sectional study, where the questionnaire was sent to prospective participants via e-mail and WhatsApp. IT professionals working in the same shift who have consented to take part in the study were recruited. This study was approved by the Institutional Ethics Committee (Project No: Member Project/12/2020/9) Approved on 12.7.2020. The research adhered to the ethical principles outlined in the Declaration of Helsinki and the 2017 National Ethical Guidelines for Biomedical and Health Research established by the Indian Council of Medical Research.

Considering the prevalence of poor sleep quality among IT professionals from a study by Mathiazhakan et al.[13] with 10% precision and 95% confidence interval, the minimum sample size was calculated to be 195 and with a 5% nonresponse rate rounded to 200 IT professionals.

Sociodemographic details including age, gender, work experience, and time spent in front of electronic media per day were collected. The study included questionnaires recording the quantity and frequency of sources of caffeine consumption over a 1-week period like tea, coffee, carbonated beverages, energy drinks, chocolates, and miscellaneous foods. Information on the caffeine content of foods, beverages, drugs, and dietary supplements was obtained by reviewing technical publications and the Internet for pertinent data.[14,15] The total amount of caffeine consumed for each participant was determined for 1 week and then averaged daily intake.

The Epworth Sleepiness Scale[16] is an eight-item questionnaire designed for identifying individuals with excessive daytime sleep. Each item addresses, on a Likert scale ranging from 0 to 3, the possibility of falling asleep in daily living yielding a score of 0 (minimum) to 24 (maximum). A total score of 10 or greater than 10 indicates EDS. The scale has high internal consistency and reliability. The Cronbach alpha for the ESS scale in this sample was 0.84.

Pittsburgh Sleep Quality Index (PSQI)[17] is a well-established tool with 19 self-reported items to measure sleep quality over the past month. This questionnaire assesses various aspects of sleep, including how well someone sleeps (subjective sleep quality), how long it takes to fall asleep (sleep latency), total sleep duration, sleep efficiency (percentage of time spent sleeping in bed), sleep disturbances, sleep medication use, and daytime dysfunction. Each sleep component is scored from 0 (no difficulty) to 3 (most difficulty). Higher total scores (maximum of 21) indicate poorer sleep quality. A score exceeding 5 is generally considered indicative of significant sleep problems. The PSQI demonstrates good internal consistency and reliability.

Statistical analysis was done using SPSS 23.0 (IBM Corp., Armonk, NY, USA) software. Normality of the data was checked using Shapiro–Wilk test. All normally distributed data were represented as mean and standard deviation. Non-normally distributed data were represented as median and interquartile range. The Pearson correlation coefficient was determined to find the association between caffeine consumption and sleep quality, screen time, sleep duration, and excessive daytime sleep. Multiple linear regression analyses were performed between sleep quality and caffeine intake, Epworth sleep score, sleep duration, and screen time after controlling for the effect of other variables. P < 0.05 with two-tailed tests was considered significant.

RESULTS

Demographic characteristics of the study population

Demographic characteristics of the study population are represented in Table 1. The respondents were 136 males and 64 females with a mean age of 29.4 ± 3.7 working in the same shift (12.30 pm to 10.30 pm). 32% of the study population reported having at least 1 drink/week, and 29.5% were current smokers. 29% were physically active considering in a week (including activity in working time, to and fro transport and leisure time activities), if they were involved in at least 150 minutes of moderate-intensity physical activity or 75 minutes of vigorous-intensity physical activity. Most of the IT professionals (96%) consumed caffeine in some form. The average caffeine intake among the study population ranged from 0 to 525 mg/day. Coffee and tea showed high contribution to caffeine intake.

Table 1.

Demographic characteristics of study population

General characteristics	n (200)
Age (in years)	29.4±3.7
Gender	Male – 136 (68%) Female - 64 (32%)
Marital status	Married - 126 (63%) Unmarried - 66 (33%) Divorced - 8 (4%)
Average screen time (hours)	9.3±1.8*
Caffeine intake (mg per day)	156.2 (98.7-252.5)#
Alcohol consumption	64 (32%)
Cigarette smoking	59 (29.5%)
Physical activity	59 (29%)

*Mean±SD ^#Median and interquartile range

70% of the study population were found to be poor sleepers (PQSI sleep score >5), and 42.5% of the total population slept <6 hours. 55% of the population reported poor quality of sleep. 60.5% reported daytime dysfunction. 40% have score ≥10 in Epworth sleepiness score indicating excessive daytime sleep as shown in Table 2.

Table 2.

Sleep quality component score of the study population

Parameters	n (percentage)
Sleep quality
Very Good	24 (12%)
Fairly Good	66 (33%)
Fairly Bad	76 (38%)
Very Bad	34 (17%)
Enhanced sleep latency	136 (68%)
Average sleep duration	5.74±1.15*
Good sleep efficiency	84 (42%)
No Sleep Disturbance	17 (8.5%)
Use of medication for sleep	37 (18.5%)
No Daytime dysfunction	59 (29.5%)
PQSI Global score	7.39±3.61*
Epworth sleepiness score	10 (6-12.75)#

*Mean±SD ^#Median and interquartile range

Caffeine per day and sleep duration have negative association and have positive association with PQSI, ESS, and average screen time in work. Excessive daytime sleep as indicated by Epworth sleep score shows positive association with screen time (r = 0.350, P < 0.01) and excessive day time sleep (r = 0.643, P < 0.01), indicating caffeine is associated with poor sleep quality, duration, and excessive day time sleep and prolonged screen time as shown in Table 3.

Table 3.

Association of relative caffeine intake with sleep duration, PQSI, ESS, and screen time

Caffeine intake (mg/day)		r		P
Sleep duration		-0.265		<0.01
PQSI		0.510		<0.01
ESS		0.363		<0.01
Screen time		0.305		<0.01

Linear regression showed there is a significant correlation of parameters with sleep quality (r2 = 0.619, P < 0.001). After adjustment for the other parameters, the caffeine intake, Epworth sleep score, and screen correlated positively and sleep duration correlated negatively with sleep quality, as depicted in Table 4.

Table 4.

Partial regression coefficient between sleep quality and caffeine intake, Epworth sleep score, sleep duration, and screen time

Parameter	β	P	Partial correlation
Epworth sleep score	0.395	0.000	0.476
Caffeine intake (mg/day)	0.237	0.000	0.324
Sleep duration (hours)	-0.365	0.000	-0.477
Age (in Years)	-0.051	0.266	-0.080
Screen time (hours)	0.103	0.038	0.148
R	R 2	SEE	Significance
0.787	0.619	2.26	<0.001

Excessive caffeine intake tends to be a predictive factor of poor sleep quality with an odds ratio of OR 3.15, CI 2.34–4.25, P < 0.01. The odds ratio of excessive daytime sleep in a person with poor sleep quality is OR 2.14, CI 1.66–2.5). The odds ratio of increased caffeine intake in a person with excessive daytime sleep is OR 4.40, CI 2.04–9.48, indicating the cycle of caffeine consumption and sleep disturbance.

DISCUSSION

The present study shows the associations of consumption of caffeine with poor sleep quality, and this effect is biologically plausible since caffeine is a methylxanthine and adenosine receptor blocker that has potent psychostimulant properties.[18] The caffeine intake is driven not only by taste, given that it is a common additive in our day-to-day diet, but also by its reputation as a psychoactive substance. Adenosine is the physiological sleep factor, and its concentration in the brain determines the depth and duration of sleep. Adenosine is also an important component of homeostatic sleep regulation and circadian rhythm. Accumulation of adenosine leads to drowsiness and change in electroencephalogram toward enhancing slow wave activity.[19]

When caffeine is consumed, it acts as an adenosine receptor blocker enhancing alertness and combat sleep dept.[20,21] Additionally, previous studies by Landolt et al. have reported that caffeine causes dissipation of homeostatic sleep pressure and decreases slow wave power in electroencephalogram recording in the frontal, central, and parietal regions.[22] This shows the physiological basis of how adenosine promotes sleep and caffeine blocks adenosine’s sleep-promoting effects and acts as a stimulant and causes sleep debt.

Alternatively, the relationship may be bidirectional, in which individuals with poor sleep quality and excessive day time sleep consume caffeinated beverages in order to maintain alertness. Tolerance may develop to the alertness-enhancing effects of caffeine and may lead to use of higher caffeine to combat sleep and improve alertness, which is becoming increasingly common among adults.[5] The impact of caffeine consumption on sleep complicates an analysis of causation, and we have found that feeling tired and excessive sleep in the daytime lead to high caffeine intake, which in turn is associated with impaired subsequent sleep quality, what might be called a “caffeine sleep cycle”, as explained in Figure 1. In line with our study, Pecotić et al. have shown poor sleep habits were associated with excessive tiredness, leading to increased consumption of caffeine and more caffeine associated with sleep disturbance.[23] The present results also show that high doses of caffeine have a negative impact upon sleep duration and enhance sleep latency. In summary, our data suggest that there is a positive association between caffeine intake and poor sleep quality and excessive day time sleep among IT professionals.

Figure 1.

Cycle of caffeine consumption and sleep disturbance

CONCLUSION

Poor sleep quality is prevalent among IT employees, which is significantly higher than that of the general population. The results were in line with the study hypothesis that the quality of sleep is compromised in IT professionals and the excessive caffeine consumption has a major contributary role in it. Additionally, health education should be provided regarding the quantity of caffeine in products to avoid excess caffeine consumption and to improve sleep quality to create awareness among the users regarding being watchful of the caffeine content in their beverages to avoid excess consumption and also regarding the importance of sleep quality in general for a healthy living. To improve sleep issues, researchers should design tailored sleep interventions that account for demographic, psychological, and sociobehavioral factors that may place them at risk for poor sleep quality, excessive daytime sleepiness, and short sleep duration.

Limitations

The cross-sectional nature of this study precludes us to find the causality. The study highly relied on self-reported questionnaires. The sample was selected from a very specific occupational group, and so, the findings may not be generalizable to the population. Despite these limitations, the study does point out a possibility of caffeine intake in poor sleep quality. There are other factors that affect sleep, such as effect of noise in bedroom, illuminated lights, stress, diet, and sleep hygiene, which need to be addressed in future research.

Authors’ contributions

Concept, design, literature search, data acquisition, manuscript editing, and manuscript review: AR, JF. Definition of intellectual content, literature search, data acquisition, statistical analysis, manuscript preparation MC, JF, AR. Manuscript editing and manuscript review: AR, MC, JF.

Ethical statement

This study was approved by the INTERNATIONAL CENTRE FOR PSYCHOLOGICALCOUNSELING AND SOCIAL RESEARCH (Project No: 12/2020/10) dated 12.7.2020, The research adhered to the ethical principles outlined in the Declaration of Helsinki and the 2017 National Ethical Guidelines for Biomedical and Health Research established by the Indian Council of Medical Research.

Data availability statement

All the data is reported in the manuscript.

Patients’ consent

All participants provided written informed consent for the study, no image of the participants is used in the study.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.