Keywords
sleep - physical activity - health professionals - COVID-19 - sleepiness
Introduction
As the pandemic evolved and the number of cases sharply increased, frontline health
professionals fighting against COVID-19 faced additional workload and pressure.[1] They dealing directly and indirectly with the pandemic were exposed daily to a great
risk of getting sick themselves.[2] The high contamination rate is related to challenges in acquiring, wearing, and
handling personal protective equipment (PPE).[3] Once infected, professionals must get isolated to prevent infecting their workmates,
patients, and relatives, overloading the teams and causing high levels of anxiety
and distress. Such a scenario greatly fatigues workers, causing physical and mental
diseases, stress, and poor quality of life and sleep.[4]
Recent studies demonstrated a decrease in the sleep quality of individuals infected
with COVID-19; however, its mechanisms have not been fully clarified yet.[5]
[6] Insomnia has been diagnosed more often in post-COVID-19 patients than in non-infected
people.[7] Furthermore, the sleep of infected patients has poor quality, is less efficient
and shows lower latency and duration and higher fragmentation, causing daytime dysfunction
and possibly lasting up to 6 months after COVID-19 symptoms onset[8]
[9]
.
Besides sleep impairment, social distancing, and confinement – which were essential
to reduce COVID-19 dissemination – decreased the levels of physical activity in the
general population.[10]
[11] It was likewise decreased in infected people, due to both isolation and muscle fatigue
caused by the disease.[12]
Hence, frontline health professionals fighting the COVID-19 pandemic not only have
to cope with increased workload and stress and anxiety levels but also the infection
with this virus may affect their sleep and physical activity. Therefore, the objective
of this study was to compare the sleep quality, excessive daytime sleepiness, and
physical activity level in health professionals with and without COVID-19.
Material and Methods
Study Design and Participants
This is an observational cross-sectional study based on online forms filled out in
Google Forms by 96 participants (37 with COVID-19, 59 without COVID-19). Data were
collected from October 2020 to May 2021, upon approval by the Human Research Ethics
Committee of the Federal University of Pernambuco (UFPE) in September 2020, under
evaluation report number 4.289.462.
The research inclusion criteria were as follows: health professionals (physicians,
physical therapists, nurses, and nurse assistants) who cared for COVID-19 patients
in hospitals in the Recife metropolitan area, in Pernambuco, Brazil, with no restriction
on sex or age. The following were the exclusion criteria: professionals who worked
in departments that did not receive COVID-19 patients or who had been on a leave of
absence for more than 30 days at the time of the research.
Data Collection
Participants were recruited via publicization of the research in digital media and
indication by other research participants. The participants were invited to the survey
using Google Forms platform under the Free Informed Consent Term (FICT), pursuant
to resolution 466/2012 of the National Health Council, and answered questions on personal,
anthropometric, sociodemographic, and occupational information and validated questionnaires
on excessive daytime sleepiness (Epworth Sleepiness Scale – ESE), sleep quality (Pittsburgh
Sleep Quality Index – PSQI), and physical activity level (International Physical Activity
Questionnaire – IPAQ), minimizing the risk of measurement bias.
Epworth Sleepiness Scale (ESE)
ESE has been validated, translated, and adapted for use in Brazil. It assesses excessive
daytime sleepiness by evaluating whether one is likely to fall asleep in eight everyday
situations, thus identifying people rather prone to having excessive daytime sleepiness.
The total score can reach up to 24 points, and subjects are classified as sleepy if
their score is ≥ 10 points.[13]
Pittsburgh Sleep Quality Index (PSQI)
PSQI subjectively assesses sleep quality regarding the previous month. The questionnaire
– which has been validated, translated, and adapted for use in Brazil – has 19 self-
assessment questions that classify sleep quality as good or poor. The overall score
ranges from 0 to 21 points, stratifying sleep quality as either good (< 5) or poor
(≥ 5).[14]
International Physical Activity Questionnaire (IPAQ)
IPAQ, which has been validated and translated for use with the Brazilian population,
assesses the physical activity level in the previous week. The instrument estimates
the weekly time spent in mild, moderate, and vigorous physical activities, as well
as walking and sitting. Hence, it classifies people into physically inactive, moderately
active, and highly active and calculates their energy expenditure in MET-minute/week.[15]
Sample Size
The sample size was calculated with GPOWER statistical package software, version 3.1.3
(Franz Faul; Universität, Kiel, Germany), with a 0.3 effect size, 95% significance
level, and 80% study power, reaching a total sample size of 72 individuals (36 in
each group).
Statistical Analysis
Data were analyzed in the Statistical Package for the Social Sciences (SPSS), version
20.0. The means ± standard deviations (SD) and percentages (%) of the variables were
calculated. The statistical significance level was set at p≤0.05. Normality was analyzed
with the Kolmogorov– Smirnov test. Continuous quantitative variables were compared
between the groups with the Mann-Whitney test (for non-normal distribution) and the
independent sample T-test (for normal distribution); as for the qualitative variables,
the Fisher exact test (when there were fewer than five cases per cell) and chi-square
test (for the remaining ones) were used.
Results
Sample characterization is presented in [Table 1]. There were no differences between the groups with and without COVID-19, except
for weekly workload (p = 0.013). Professionals who had been contaminated with COVID-19
had a greater workload than those who had not been contaminated with the disease.
Table 1
Sample characteristics
|
COVID-19 Positive
(n = 37)
|
COVID-19 Negative
(n = 59)
|
p-value
|
|
Age (years)
|
31.70 ± 7.96
|
31.97 ± 7.52
|
0.871
|
|
Sex
|
|
|
0.973
|
|
Males (n/%)
|
7 (38.9%)
|
11 (61.1%)
|
|
|
Females (n/%)
|
30 (38.5%)
|
48 (61.5%)
|
|
|
Weight (kg)
|
70.84 ± 14.65
|
69.02 ± 15.88
|
0.574
|
|
Height (m)
|
1.64 ± 0.08
|
1.64 ± 0.10
|
0.925
|
|
BMI (kg/m2)
|
26.10 ± 4.94
|
25.38 ± 4.78
|
0.477
|
|
Occupation
|
|
|
0.059
|
|
Physicians (n/%)
|
3 (25%)
|
9 (75%)
|
|
|
Physical therapists (n/%)
|
15 (34.9%)
|
28 (65.1%)
|
|
|
Nurses (n/%)
|
12 (66.7%)
|
6 (33.3%)
|
|
|
Nurse assistants (n/%)
|
7 (30.4%)
|
16 (69.6)
|
|
|
Health service
|
|
|
0.163
|
|
Private (n/%)
|
6 (75%)
|
2 (25%)
|
|
|
Public (n/%)
|
20 (37%)
|
34 (63%)
|
|
|
Mixed (public and private in the same service) (n/%)
|
5 (38.5%)
|
8 (61.5%)
|
|
|
Both (public and private in different services) (n/%)
|
6 (28.6%)
|
15 (71.4%)
|
|
|
Work schedule
|
|
|
0.832
|
|
Daily (4, 6, or 8 hours a day) (n/%)
|
6 (42.9%)
|
8 (57.1%)
|
|
|
12-hour shifts (n/%)
|
24 (39.3%)
|
37 (60.7%)
|
|
|
Both (n/%)
|
7 (33.3%)
|
14 (66.7%)
|
|
|
work shift
|
|
|
0.980
|
|
Daytime (n/%)
|
12 (40%)
|
18 (60%)
|
|
|
Nighttime (n/%)
|
3 (37.5%)
|
5 (62.5%)
|
|
|
Both (n/%)
|
22 (37.9%)
|
36 (62.1%)
|
|
|
Weekly workload (hours)
|
61.24 ± 22.69
|
51.15 ± 16.38
|
0.013**
|
|
Comorbidities (yes) (n/%)
|
9 (69.2%)
|
4 (30.8%)
|
0.057
|
|
Asthma (n/%)
|
4 (80%)
|
1 (20%)
|
|
|
Diabetes Mellitus (n/%)
|
1 (50%)
|
1 (50%)
|
|
|
SAH (n/%)
|
4 (66.7%)
|
2 (33.3%)
|
|
|
Medication (yes) (n/%)
|
8 (66.7%)
|
4 (33.3%)
|
0.09
|
|
Antidepressants (n/%)
|
6 (66.7%)
|
3 (33.3%)
|
|
|
Anxiolytics (n/%)
|
2 (66.7%)
|
1 (33.3%)
|
|
Data are presented in absolute numbers (percentage) and means ± standard deviations.
SAH = systemic arterial hypertension, BMI = body mass index; # Fisher exact test.
χ2 chi-square test.
*Mann-Whitney test p < 0.05.
**T- test p < 0.05.
The comparison of the physical activity levels between health professionals with and
without COVID-19 is shown in [Table 2]. There were no differences between the groups regarding either the weekly energetic
expenditure (p = 0.522) or the physical activity levels, classified as sedentary,
moderately active, and highly active (p = 0.850).
Table 2
Comparison of physical activity levels between health professionals with and without
COVID-19
|
Variable
|
COVID-19
Positive
(n = 37)
|
COVID-19 Negative
(n = 59)
|
P-value (Mann- Whitney)
|
DM (95% CI)
|
|
IPAQ (MET-min/week)
|
2097.00
(2844.00)
|
1965.00 (2666.00)
|
0.522
|
328.70 (- 1451.70 to 794.29)
|
|
IPAQ (Sedentary)
|
9 (34.6%)
|
17 (65.4%)
|
|
|
|
IPAQ
(Moderately Active)
|
11 (42.3%)
|
15 (57.7%)
|
0.850#
|
|
|
IPAQ (Highly Active)
|
17 (38.6%)
|
27 (61.4%)
|
|
|
IPAQ= International Physical Activity Questionnaire. # Fisher exact test. χ2 chi-square test.
*Mann-Whitney test p < 0.05
**T- test p < 0.05
[Table 3] compares PSQI components, sleep quality, and excessive daytime sleepiness between
health professionals with and without COVID-19. In the comparison of PSQI components
between the groups, subjective sleep quality (p = 0.01), presence of sleep disorders
(p = 0.014), use of sleeping medication (p = 0.047), and daytime dysfunction (p = 0.001)
obtained higher values in the group of professionals infected with COVID-19. This
group also had a poorer sleep quality (p = 0.001) and excessive daytime sleepiness
(p = 0.016).
Table 3
Comparison of PSQI components, PSQI total score, and ESE between health professionals
with and without COVID-19
|
Variable
|
COVID-19 Positive
(n = 37)
|
COVID-19 Negative
(n = 59)
|
P-value (T-test)
|
DM (95% CI)
|
|
PSQI subjective sleep quality (C1)
|
2 (1)
|
1 (1)
|
0.01*
|
0.42 (0.74 to 0.10)
|
|
PSQI sleep latency (C2)
|
2 (2)
|
1 (1)
|
0.121
|
0.35 (-0.79 to 0.94)
|
|
PSQI sleep duration (C3)
|
2 (0)
|
2 (1)
|
0.081
|
0.33 (-0.70 to 0.04)
|
|
PSQI habitual sleep efficiency (C4)
|
1 (2)
|
0 (1)
|
0.127
|
0.31 (-0.72 to 0.09)
|
|
PSQI sleep disorders (C5)
|
2 (1)
|
1 (1)
|
0.014*
|
0.33 (0.60 to 0.07)
|
|
PSQI use of sleeping medication (C6)
|
0 (1)
|
0 (0)
|
0.047*
|
0.43 (0.86 to 0.007)
|
|
PSQI daytime dysfunction (C7)
|
2 (1)
|
1 (1)
|
0.021*
|
0.38 (0.70 to 0.05)
|
|
PSQI total score
|
10.46 ± 3.75
|
7.88 ± 3.75
|
0.001**
|
2.57 (4.14 to 1.01)
|
|
PSQI poor sleep quality (≥ 5 points)
|
34 (41%)
|
49 (59%)
|
|
|
|
PSQI good sleep quality (< 5 points)
|
3 (23.1%)
|
10 (76.9%)
|
|
|
|
Excessive daytime sleepiness (ESE score)
|
10.19 ± 3.05
|
8.44 ± 3.85
|
0.016**
|
1.74 (3.15 to 0.33)
|
|
Excessive daytime sleepiness (ESE > 10)
|
19 (46.3%)
|
22 (53.7%)
|
|
|
|
Absence of excessive daytime sleepiness (ESE < 10)
|
18 (32.7%)
|
37 (67.3%)
|
|
|
PSQI = Pittsburgh Sleep Quality Index; ESE = Epworth Sleepiness Scale. Values presented
in medians (interquartile range), means ± standard deviation, and absolute numbers
(percentages). # Fisher exact test. χ2 chi-square test
*Mann-Whitney test p < 0.05
**T- test p < 0.05
Discussion
The objective of this study was to compare the sleep quality, excessive daytime sleepiness,
and physical activity level in health professionals with and without COVID-19. No
difference was found between health professionals with and without COVID-19 regarding
weekly energy expenditure and physical activity level. On the other hand, professionals
who had been contaminated had a poorer sleep quality and excessive daytime sleepiness
in comparison with non-contaminated ones.
A paper by Tran et al. (2020)[16] corroborates the data found in this study, in that there were no differences between
health professionals with and without COVID-19 regarding their physical activity level.
In the study, conducted with health professionals in Vietnam, most research participants
reported not having changed their physical activity level during the COVID- 19 pandemic.[17] This may be explained by the intensive workloads and shifts experienced by health
professionals during the COVID-19 pandemic, helping maintain a high level of physical
activity.[7]
[18]
Sleep quality was poor in both study groups, though even poorer in the group of those
infected with COVID-19. Such a result in the present paper corroborates the study
by Bozan et al. (2021),[7] conducted with health professionals in Turkey. They demonstrated that the sleep
quality after COVID-19 infection was poorer than before the disease. Another study,
conducted in Egypt by Omar DI et al. (2022),[19] assessed the sleep quality of nurses during the COVID-19 pandemic and likewise found
it to be poor – which was even poorer in those who had COVID-19. This may be explained
by the heavy workloads, extenuating shifts, and unstable working conditions. They
are constantly under great psychological pressure, which causes high stress levels
and poorer sleep quality.[4] As both groups had been exposed to such factors, the poorer sleep quality in the
infected group is justified.
The poorer sleep quality in the infected group is believed to be due to the possible
presence of SARS-CoV-2 in the brain of those with COVID-19. The presence of the virus
in the brain causes a cytokine storm and endothelial inflammation, impairing the integrity
of the hematoencephalic barrier and favoring the development of sleep disorders.[20] Moreover, the inflammatory cascade is directly influenced by the circadian rhythm;
therefore, people whose circadian rhythm is dysregulated, such as health professionals,
may be more susceptible to various infections and clinical manifestations.[21]
The infected group had higher values in the following PSQI components: subjective
sleep quality (C1), presence of sleep disorders (C5), use of sleeping medication (C6),
and daytime dysfunction (C7). The study by Omar DI et al. (2022)[19] found changes mainly in sleep duration, sleep latency, sleep effectiveness, and
(like in our study) the presence of sleep disorders. However, the said study did not
divide participants into infected and non-infected groups. The infected group presents
with physiological changes in the brain, with increased local inflammation. This compromises
the hematoencephalic barrier, favoring the presence of sleep disorders and decreasing
the sleep quality – which explains the results obtained in this study.[20] In the present paper, health professionals infected with COVID-19 also had excessive
daytime sleepiness. A study conducted in Turkey with recovered patients assessed excessive
daytime sleepiness among other symptoms and found that most patients had poor sleep
quality and daytime sleepiness. The results of this study suggest that excessive daytime
sleepiness may be a persistent symptom in patients after COVID-19 infection.[22] San Martin et al. (2020)[23] demonstrated that health professionals had a poor sleep quality during the COVID-19
pandemic. On the other hand, this study did not find excessive daytime sleepiness,
which may be explained by a great incidence of insomnia in this population, decreasing
sleep quality without causing excessive daytime sleepiness. These results also explain
why the group of health professionals non-contaminated with COVID-19 had poor sleep
quality without excessive daytime sleepiness in the present study.
The main limitation of this study was that the questionnaire responses were given
online by the volunteers, which may have influenced the data. Nevertheless, this was
the safest way to conduct the research assessment, given the need to keep social distance
and respect the protocols to reduce contagion and contamination. Another aspect to
point out is the definition of COVID-19 severity experienced by the contaminated group,
which could better stratify the conditions and possible sequelae of the disease. Such
a stratification was not made in the present study because it was self-reported online
research, conducted not necessarily when the volunteers were still infected with COVID-19.
Hence, it was not possible to collect clinical data on severity markers.
Conclusion
This study demonstrated that health professionals contaminated with COVID-19 had a
heavier workload, poorer sleep quality, and excessive daytime sleepiness, in contrast
with health professionals who had not been infected. However, there were no differences
in weekly energy expenditure and physical activity level between health professionals
with and without COVID-19.
Further studies on the topic should be made, addressing the long-term consequences
of COVID-19 in this population, as well as an objective analysis to provide more reliable
data on the variables related to sleep quality, excessive daytime sleepiness, and
physical activity. Moreover, studies addressing associations between the SARS-CoV-2
mechanism of action in the brain and sleep parameters and physical activity level
could be helpful to clarify this question.
