CC BY-NC-ND 4.0 · Sleep Sci 2024; 17(01): e64-e74
DOI: 10.1055/s-0043-1776743
Original Article

Evaluation of the Association between Medication Use and Sleep Quality among Shift Workers versus Day Workers

1   Cardiology Department, Hospital Espírito Santo EPE, Évora, Portugal
,
Lucinda Sofia Carvalho
2   Interdisciplinary Research Unit on Building Functional Ageing Communities (AGE.COMM), Escola Superior de Saúde Dr. Lopes Dias, Instituto Politécnico de Castelo Branco, Castelo Branco, Portugal
,
André Coelho
3   Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL), Instituto Politécnico de Lisboa, Lisboa, Portugal
› Author Affiliations
Funding The authors declare that they have received no funding from agencies in the public, private or non-profits sectors for the conduction of the present study.
 

Abstract

Objective Different factors, such as medication use and shift work, can influence sleep quality. We aimed to determine the association between medication use and sleep quality in shift workers versus daytime workers.

Materials and Methods We conducted a quantitative cross-sectional study with a convenience sample of active workers. Online questionnaires were applied to assess sleep quality, sleepiness, medication use, and sociodemographic characteristics.

Results A total of 296 participants were included: 124 (41.89%) daytime workers and 172 (58.11%) shift workers. In total, 130 (43.92%) participants worked in the healthcare sector, 116 (39.19%), in industry, and 50 (16.89%), in other sectors. After a bivariate analysis, poor sleep quality was associated with the presence of sleep disorders (p < 0.001), type of work (shift or day work) (p < 0.001), and the use of sleeping medication (p < 0.001). Although shift workers had worse sleep quality, no differences were found regarding the use of medications that act directly on the central nervous system or with proven effects on sleep. No association was found between medication use and sleep quality. When adjusted for the different variables that were individually associated with poor sleep quality, through a logistic regression model, none showed an increased risk of poor sleep quality.

Discussion In spite of the need for further research, our results have shown that sleep quality is influenced by many different factors whose impact must be evaluated in combination, and not just in a bivariate manner. There are many factors individually associated with poor sleep quality, but when adjusted to each other, they have shown no increased risk of having poor sleep quality.


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Introduction

Sleep is a physiological and biological process which is fundamental for human survival.[1] It performs a multiplicity of vital functions, such as the conservation and restoration of energy, the regulation of metabolic processes, among others.[2] [3] [4] Disturbances in sleep quality can trigger significant changes in the individual's physical, occupational, cognitive and social functioning, substantially compromising quality of life.[2] Low quality and/or quantity of sleep is considered a public health problem.[5] Sleep disorders are associated, among other pathologies, with an increased risk of acute myocardial infarction, stroke, and depression.[5]

Sleep quality can be influenced by different factors, such as previous medical conditions, use of medications and/or stimulant substances, working schedules, among others.[3]

In the labor context, there is an increasing number of workers performing their tasks in shifts in several activity sectors, as a consequence of technological changes and economic globalization, which require the availability of goods and services 24/7.[6] [7] Those work conditions may enhance changes in the individual's endogenous biological rhythm, resulting in a temporal conflict between the biological clock and the externally-imposed social scheme.[8] The use of medication to relieve sleep disorders caused by working hours, such as insomnia, is common; however, if abused, without supervision and monitoring, it can trigger new pathological conditions.[9] [10] On the other hand, the prescription of different medications for the treatment of several clinical conditions can have adverse effects in sleep.[10]

Therefore, it is of paramount importance to evaluate medication use in shift workers compared to daytime workers and its consequences on sleep quality, to promote the rational and safe use of medications.

The present work aims to determine the association between medication use and sleep quality in shift workers versus daytime workers.


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Materials and Methods

Study Design and Study Population

We conducted a quantitative cross-sectional study using a convenience sample of active workers, regardless of the activity sector. The participants were divided in two groups: shift and daytime schedule workers. Individuals aged ≥ 18 years who had been holding a job for at least six months were included.


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Data Collection

Data was collected using a combination of three questionnaires: the first one, which was developed for the present study to collect sociodemographic characteristics, associated comorbidities and medication use; the Epworth Sleepiness Scale (ESS) was used to assess the level of sleepiness; and the Pittsburgh Sleep Quality Index (PSQI), to assess the sleep quality. The questionnaires were available online between October and December 2021, and the link to access them was sent through e-mail and social media using the “snowball” method. Access to the questionnaires was only granted after agreement with a participant information document, which contained all the necessary information for participation in the study.


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Data Analyses

The IBM SPSS Statistics for Windows (IBM Corp., Armonk, NY, United States) software, version 26.0, and the Microsoft Excel software (Microsoft Corp., Redmond, WA, United States) were used for the statistical analysis. Simple descriptive analysis (absolute and relative frequencies) was performed for the nominal and ordinal variables, as well as central tendency and dispersion measures for the quantitative variables. Bivariate associations between variables were determined using the Chi-squared statistical test, with a significance level of 5%. A logistic regression model was developed, in which all variables that showed an association with sleep quality were included, also adopting a significance level of 5%.


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Ethical Considerations

The present study was approved by the Ethics Committee of Escola Superior de Tecnologia da Saúde de Lisboa under process number 41-2021. Anonymity and confidentiality of the data obtained were guaranteed. All participants could withdraw from the study, hide any information, or refuse to answer any question.


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Results

Characterization of Study Participants

Of the 296 study participants, 109 individuals (36.82%) were male and 187 (63.18%), female, with a mean age of 36.03 ± 8.93 years, and 130 (43.92%) subjects worked in the health sector. The mean time of professional activity was of 11 ± 8.69 years. Most (58.11%) of the participants worked in shifts, and 51.7% had been working in their current shifts for five or more years.

No cardiovascular (CV) risk factors were reported by 182 (61.49%) participants; among those who did report risk factors, smoking had the highest prevalence. In total, 87 (29.39%) participants, mainly women, reported having some prediagnosed pathology, specially psychological ones.

In terms of sleep disorders, most participants (91.89%) reported having none. Of the 24 participants who reported having a sleep disorder, insomnia was the most mentioned. All data are shown in [Table 1].

Table 1

Characteristics of the study participants.

Male

Female

Total

Study participants

109 (36.82%)

187 (63.18%)

296 (100.00%)

Age (in years): mean ± standard deviation

38.50 ± 9.69

34.59 ± 8.12

36.03 ± 8.93

Professional sector: n (%)

 Health

27 (24.77%)

103 (55.08%)

130 (43.92%)

 Industry

66 (60.55%)

50 (26.74%)

116 (39.19%)

 Other

16 (14.68%)

34 (18.18%)

50 (16.89%)

Time of professional activity (in years): mean ± standard deviation

12 ± 9.96

10 ± 7.72

11 ± 8.69

Type of work: n (%)

 Day work

23 (21.10%)

101 (54.01%)

124 (41.89%)

 Shift work

86 (78.90%)

86 (45.99%)

172 (58.11%)

Current shift time (in years): n (%)

 < 5

52 (47.7%)

91 (48.7%)

143 (48.3%)

 ≥ 5

57 (52.3%)

96 (51.3%)

153 (51.7%)

Known cardiovascular risk factor: n (%)

 Yes

51 (46.79%)

63 (33.69%)

114 (38.51%)

 No

58 (53.21%)

124 (66.31%)

182 (61.49%)

Type of cardiovascular risk factor (n = 114): n (%)

 Diabetes

4 (7.84%)

2 (3.17%)

6 (5.26%)

 Smoking

29 (56.86%)

36 (57.14%)

65 (57.02%)

 Hypertension

16 (31.37%)

11 (17.46%)

27 (23.68%)

 Dyslipidemia

2 (3.92%)

4 (6.35%)

6 (5.26%)

 Obesity

13 (25.49%)

18 (28.57%)

31 (27.19%)

 Other

22 (43,14%)

30 (47.62%)

52 (45.61%)

Diagnosed pathology (n = 87): n (%)

 Cardiovascular

4 (4.60%)

4 (4.60%)

8 (9.20%)

 Psychological

24 (27.60%)

43 (49.43%)

67 (77.01%)

 Other

2 (2.30%)

10 (11.49%)

12 (13.79%)

Sleep disorder: n (%)

 Yes

11 (10.09%)

13 (6.95%)

24 (8.11%)

 No

98 (89.91%)

10 (76.92%)

272 (91.89%)

Type of sleep disorder (n = 24): n (%)

 Insomnia

7 (63.64%)

10 (76.92%)

17 (70.83%)

 Restless legs syndrome

2 (18.18%)

2 (15.38%)

4 (16.67%)

 Excessive sleepiness

5 (45.45%)

6 (46.15%)

4 (16.67%)

 Obstructive sleep apnea syndrome

4 (36.36%)

2 (15.38%)

11 (45.83%)

 Parasomnias

1 (9.09%)

1 (7.69%)

2 (8.33%)


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Medication Use

Daily use of medications was reported by 87 (29.39%) subjects and it was slightly higher among female participants (32.09%). Concerning the person who recommended the use of the last medication, there was an expressive value referring to self-initiative (41.22%), even though physician's recommendation had the higher frequency (50.34%). Regarding the last drug used, there were no considerable differences in terms of the frequencies of drugs acting or not in the central nervous system (CNS). Most drugs used had no proven effects on sleep (72.30%), and 66.22% of the study participants stated that they did not take sleep medications ([Table 2]).

Table 2

Characterization of medication use.

Male: n (%)

Female n: (%)

Total: n (%)

Medication use

 Daily

27 (24.77%)

60 (32.09%)

87 (29.39%)

 Daily (contraceptive)

0 (0.00%)

6 (3.21%)

6 (2.03%)

 Sporadic

82 (75.23%)

121 (64.71%)

203 (68.58%)

Referring agent

 Family member

2 (1.83%)

0 (0.00%)

2 (0.68%)

 Pharmacy professional

8 (7.34%)

11 (5.88%)

19 (6.42%)

 Self-initiative

41 (37.61%)

81 (43.32%)

122 (41.22%)

 Physician

55 (50.46%)

94 (50.27%)

149 (50.34%)

 Friend

2 (1.83%)

0 (0.00%)

2 (0.68%)

 Other

1 (0.92%)

1 (0.53%)

2 (0.68%)

Direct action in the central nervous system

 Yes

41 (37.62%)

77 (41.18%)

118 (39.87%)

 No

49 (44.95%)

93 (49.73%)

142 (47.97%)

 Not applicable

19 (17.43%)

17 (9.09%)

36 (12.16%)

Proven effects on sleep

 Yes

16 (14.68%)

30 (16.04%)

46 (15.54%)

 No

74 (67.89%)

140 (74.87%)

214 (72.30%)

 Not applicable

19 (17.43%)

17 (9.09%)

36 (12.16%)

Sleep medication

 Yes

41 (37.61%)

59 (31.55%)

100 (33.78%)

 No

68 (62.39%)

128 (68.45%)

196 (66.22%)

A higher use of CNS-acting drugs was found among respondents with sleep disorders, but it was not statistically significant (p = 0.063). Regarding drugs with proven effects on sleep, there was an association between their use and the presence of sleep disorders (p < 0.001) ([Tables 3A] and [3B]).

Table 3A

Use of drugs acting in the central nervous system.

Direct action in the central nervous system

Yes: n (%)

No: n (%)

Not applicable: n (%)

p-value

Gender

 Male

41 (37.6%)

49 (45.0%)

19 (17.4%)

0.106

 Female

77 (41.2%)

93 (49.7%)

17 (9.1%)

Variables related to professional activity

Sector of activity

 Health

53 (40.8%)

67 (51.5%)

10 (7.7%)

 Industry

41 (35.3%)

57 (49.1%)

18 (15.5%)

0.129

 Other

24 (48.0%)

18 (36.0%)

8 (16.0%)

Time of professional activity (in years)

 < 5

48 (43.6%)

46 (41.8%)

16 (14.5%)

0.244

 ≥ 5

70 (37.6%)

96 (51.6%)

20 (10.8%)

Current type of work

 Day work

53 (42.7%)

61 (49.2%)

10 (8.1%)

0.178

 Shift work

65 (37.8%)

81 (47.1%)

26 (15.1%)

Time in the current work

 ≤ 5 years

61 (42.7%)

67 (46.9%)

15 (10.5%)

0.535

 > 5 years

57 (37.3%)

75 (49.0%)

21 (13.7%)

Variables related to comorbidities

Cardiovascular risk factor

 Yes

38 (33.3%)

59 (51.8%)

17 (14.9%)

0.158

 No

80 (44.0%)

83 (45.6%)

19 (10.4%)

Sleep disorders

 Yes

14 (58.3%)

6 (25.0%)

4 (16.7%)

0.063

 No

104 (38.2%)

136 (50.0%)

32 (11.8%)

Epworth Sleepiness Scale

 Normal

53 (41.7%)

56 (44.1%)

18 (14.2%)

 Moderate sleepiness

18 (39.1%)

24 (52.2%)

4 (8.7%)

0.762

 Abnormal sleepiness

47 (38.2%)

62 (50.4%)

14 (11.4%)

Table 3B

Use of drugs with proven effects on sleep.

Drugs with proven effects on sleep

Yes: n (%)

No: n (%)

Not available: n (%)*

p-value

Gender

 Male

16 (14.7%)

74 (67.9%)

19 (17.4%)

0.106

 Female

30 (16.0%)

140 (74.9%)

17 (9.1%)

Variables related to professional activity

Activity sector

 Health

23 (17.7%)

97 (74.6%)

10 (7.7%)

0.292

 Industry

15 (12.9%)

83 (71.6%)

18 (15.5%)

 Other

8 (16.0%)

34 (68.0%)

8 (16.0%)

Time of professional activity

 < 5 years

13 (11.8%)

81 (73.6%)

16 (14.5%)

0.298

 ≥ 5 years

33 (17.7%)

133 (71.5%)

20 (10.8%)

Current work

 Day wok

20 (16.1%)

94 (75.8%)

10 (8.1%)

0.187

 Shift work

26 (15.1%)

120 (69.8%)

26 (15.1%)

Time in the current work

 < 5 years

21 (14.7%)

107 (74.8%)

15 (10.5%)

0.603

 ≥ 5 years

25 (16.3%)

107 (69.9%)

21 (13.7%)

Variables related to comorbidities

Cardiovascular risk factor

 Yes

18 (15.8%)

79 (69.3%)

17 (14.9%)

 No

28 (15.4%)

135 (74.2%)

19 (10.4%)

0.499

Sleep disorders

 Yes

14 (58.3%)

6 (25.0%)

4 (16.7%)

< 0.001

 No

32 (11.8%)

208 (76.5%)

32 (11.8%)

Epworth Sleepiness Scale

 Normal

22 (17.3%)

87 (68.5%)

18 (14.2%)

 Moderate sleepiness

3 (6.5%)

39 (84.8%)

4 (8.7%)

0.283

 Excessive sleepiness

21 (17.1%)

88 (71.5%)

14 (11.4%)

Note: *Refers to named substances that are not actually considered medicines, such as multivitamins, for example.



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Sleep Quality Assessment

Male participants reported worse sleep quality (p = 0.005), such as shift workers (p < 0.001), and those who had been on the current shift for less than 5 years (p = 0.023).

The presence of CV risk factors was also associated with poor sleep quality (p < 0.001). Participants with a previously-diagnosed phycological pathology reported worse sleep quality (p < 0.001). All participants with sleep disorders had poor sleep quality (p < 0.001) ([Table 4]).

Table 4

Sleep quality according to the Pittsburgh Sleep Quality Index.

Sleep Quality

Good: n (%)

Poor: n (%)

p-value

Gender

 Male

31 (28.4%)

78 (71.6%)

0.005

 Female

84 (44.9%)

103 (55.1%)

Variables related to professional activity

Activity sector

 Health

70 (53.8%)

60 (46.2%)

< 0.001

 Industry

25 (21.6%)

91 (78.4%)

 Other

20 (40.0%)

30 (60.0%)

Time of professional activity

 < 5 years

36 (32.7%)

74 (67.3%)

0.096

 ≥ 5 years

79 (42.5%)

107 (57.5%)

Current work

 Day work

70 (56.5%)

54 (43.5%)

0.001

 Shift work

45 (26.2%)

127 (73.8%)

Time in the current work

 < 5 years

46 (32.2%)

97 (67.8%)

0.023

 ≥ 5 years

69 (45.1%)

84 (54.9%)

Variables related to comorbidities and preexisting pathologies

Cardiovascular risk factors

 Yes

27 (23.7%)

87 (76.3%)

< 0.001

 No

88 (48.4%)

94 (51.6%)

Previously diagnosed pathologies

 Cardiovascular

 Yes

2 (25.0%)

6 (75.0%)

0.415

 No

113 (39.2%)

175 (60.8%)

 Psychological

 Yes

13 (19.4%)

54 (80.6%)

< 0.001

 No

102 (44.5%)

127 (55.5%)

 Other

 Yes

4 (33.3%)

8 (66.7%)

0.689

 No

111 (39.1%)

173 (60.9%)

Existence of sleep disorders

 Yes

0 (0.0%)

24 (100.0%)

< 0.001

 No

115 (42.3%)

157 (57.7%)

Type of sleep disorder

 Insomnia

 Yes

0 (0.0%)

17 (100.0%)

Not applicable

 No

0 (0.0%)

7 (100.0%)

 Restless legs syndrome

 Yes

0 (0.0%)

4 (100.0%)

Not applicable

 No

0 (0.0%)

20 (100.0%)

 Excessive sleepiness

 Yes

0 (0.0%)

11 (100.0%)

Not applicable

 No

0 (0.0%)

13 (100.0%)

 Obstructive sleep apnea syndrome

 Yes

0 (0.0%)

6 (100.0%)

Not applicable

 No

0 (0.0%)

18 (100.0%)

 Parasomnias

 Yes

0 (0.0%)

2 (100.0%)

Not applicable

 No

0 (0.0%)

22 (100.0%)

When analyzing the association between medication use and sleep quality, no association was found regarding the daily or sporadic use of drugs and sleep quality. Participants with insomnia, a chronic disease or a psychological problem had worse sleep quality (p = 0.010), and the participants who were using sleeping drugs also reported worse sleep quality (p < 0.001). No association was found between sleep quality and the use of drugs acting on the CNS, although there was a tendency for worse sleep quality in participants using drugs with proven effects on sleep (p = 0.054) ([Table 5]).

Table 5

Medication use and sleep quality.

Sleep quality

Good: n (%)

Poor: n (%)

p-value

Medication use

 Daily

33 (35.5%)

60 (64.5%)

0.421

 Sporadic

82 (40.4%)

121 (59.6%)

Reason for last medication

 Unusual pain or symptoms

51 (42.1%)

70 (57.9%)

 Feeling weak

7 (36.8%)

12 (63.2%)

 Psychological problem

7 (35.0%)

13 (65.0%)

 Chronic disease

12 (34.3%)

23 (65.7%)

0.010

 Insomnia

1 (4.3%)

22 (95.7%)

 Health problem

18 (40.9%)

26 (59.1%)

 Other

19 (55.9%)

15 (44.1%)

Agent who indicated the last medication

 Familiar

0 (0.0%)

2 (100.0%)

 Pharmacy professional

4 (21.1%)

15 (78.9%)

 Self-initiative

53 (43.4%)

69 (56.6%)

0.280

 Medical doctor

57 (38.3%)

92 (61.7%)

 Friend

0 (0.0%)

2 (100.0%)

 Other

1 (50.0%)

1 (50.0%)

Sleeping medication

 Yes

14 (14.0%)

86 (86.0%)

< 0.001

 No

101 (51.5%)

95 (48.5%)

Drugs acting in the central nervous system

 Yes

49 (41.5%)

69 (58.5%)

 No

57 (40.1%)

85 (59.9%)

0.186

 Not applicable

9 (25.0%)

27 (75.0%)

Drugs with proven effects on sleep

 Yes

14 (30.4%)

32 (69.6%)

 No

92 (43.0%)

122 (57.0%)

0.054

 Not applicable

9 (25.0%)

27 (75.0%)

The use of stimulant drinks (p = 0.004) and stimulant medication (p = 0.044) were associated with decreasing sleep quality: as the frequency of consumption increases, sleep quality decreases. Excessive sleepiness was also associated with worse sleep quality (p < 0.001): the greater the degree of sleepiness, the worse the sleep quality ([Table 6]).

Table 6

Use of substances that can affect sleep, sleepiness, and sleep quality.

Sleep quality

Good: n (%)

Poor: n (%)

p-value

Coffee

 Never

13 (48.1%)

14 (51.9%)

 Rarely

9 (39.1%)

14 (60.9%)

0.107

 Sometimes

15 (25.4%)

44 (74.6%)

 Often

78 (41.7%)

109 (58.3%)

Alcohol

 Never

14 (31.1%)

31 (68.9%)

 Rarely

46 (38.0%)

75 (62.0%)

0.588

 Sometimes

48 (42.9%)

64 (57.1%)

 Often

7 (38.9%)

11 (61.1%)

Xanthines

 Never

12 (36.4%)

21 (63.6%)

 Rarely

36 (42.9%)

48 (57.1%)

0.797

 Sometimes

43 (38.7%)

68 (61.3%)

 Often

24 (35.3%)

44 (64.7%)

Stimulant drinks

 Never

71 (48.3%)

76 (51.7%)

 Rarely

39 (32.2%)

82 (67.8%)

0.004

 Sometimes

5 (20.8%)

19 (79.2%)

 Often

0 (0.0%)

4 (100.0%)

Stimulant medications

 Never

78 (44.6%)

97 (55.4%)

 Rarely

35 (33.0%)

71 (67.0%)

0.044

 Sometimes

2 (14.3%)

12 (85.7%)

 Often

0 (0.0%)

1 (100.0%)

Epworth Sleepiness Scale

 Normal

69 (54.3%)

58 (45.7%)

0.001

 Moderate sleepiness

17 (37.0%)

29 (63.0%)

 Excessive sleepiness

29 (23.6%)

94 (76.4%)

Finally, we developed a logistic regression model to adjust all the variables associated with sleep quality in the bivariate analysis, in order to determine the risk of having poor sleep quality. The model shows that, after adjustment, only time on current shift (p = 0.003) and the degree of excessive sleepiness (p = 0.043) are associated with sleep quality ([Table 7]).

Table 7

Risk factors for poor sleep quality.

Ajusted odds ratiob

p-value

 Gender

0.746

 Male

1.120 (0.563–2.227)

 Female

1

Age group

0.558

 < 45 years old)

0.558 (0.220–1.414)

 ≥ 45 years old)

1

Sector of activity

 Health

0.722 (0.298–1.751)

0.426

 Industry

1.181 (0.417–3.342)

0.471

 Other

1

0.754

Drugs with proven effect on sleep

0.954

 No effect

0.971 (0.360–2.622)

 Effect

1

Current work

0.064

 Day work

0.518 (0.258–1.039)

 Shift work

1

Time in current work

0.003

 < 5 years

2.737 (1.422–5.268)

 ≥ 5 years

1

Cardiovascular risk factor

0.061

 No

0.519 (0.262–1.030)

 Yes

1

Diagnosed psychological pathology

0.775

 No

0.866 (0.322–2.330)

 Yes

1

Daily use of medication

0.743

 No

1.133 (0.536–2.394)

 Yes

1

Epworth Sleepiness Scale

0.043

 Normal

0.527 (0.283–0.981)

 Excessive Sleepiness

1

Notes: aCalculated with a 95% confidence interval; blogistic regression model, including all studied covariates; 1= ref.



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Discussion

Sleep is fundamental for health, and it is closely interconnected with other diseases. A sleep disorder compromises an individual's quality of life. The use of medications to mitigate the consequences of sleep deprivation is increasingly common; however, the impact caused is not always positive, since medication interferes directly (through neurotransmitters with an impact on sleep) or indirectly on sleep, and it may potentiate the opposite effect.[9] In addition, it is known that shift work has a negative impact on sleep quality and, consequently, on quality of life.[8]

The aim of the present study was to evaluate the association between medication use and sleep quality in shift workers versus daytime workers. Our results revealed that, overall, there is no difference in sleep quality in those taking medication on a daily basis compared to those who do so sporadically. In the study conducted by Kumar et al.,[11] almost a third of the participants (who were taking medications) presented very poor sleep quality, and the authors stated that the use of medications with sedative and anticholinergic effects can contribute to an effect that is the opposite of its purpose, since they can cause sedation and excessive sleepiness during the day. In another study, Karami et al.[12] reported that the use of sedative medications improved sleep quality. In the present study, when we take into consideration the specific medications that the workers were taking, when such medications had a proven effect on sleep, in fact, sleep quality was worse. Additionally, for those who already have taken sleeping medications, sleep quality was worse. Although the directionality of this association is unclear (is poor sleep quality the consequence of the use of such drugs or are those drugs being used to improve poor sleep quality?), the fact remains that there was an association found between the use of drugs with proven effects on sleep and poor sleep quality. Fadhel[13] reported that individuals dependent on a medication presented more sleep problems, making this a two-way relationship, as each problem can be the cause and consequence of the other. Gordon[14] corroborates this idea, since in his study there was a higher prevalence of individuals who still experienced sleep disturbances a long time after they had stopped using medications with proven effects on sleep after other withdrawal symptoms had disappeared.

The use of substances such as stimulant drinks and stimulant medications have been associated with worse sleep quality, which worsens the more often those substances are consumed,[13] just like the results of the present study show. Some of these substances, such as coffee, alcohol, energy drinks and medications are often used by shift workers to improve the symptoms of sleepiness and poor sleep quality, as a consequence of the alteration in the circadian rhythm.[15]

Male workers presented worse sleep quality, which can be partially justified by the fact that, in the present study, men were older than women. Age has been described as a risk factor for poor sleep quality, with the occurrence of sleep disorders increasing with age, causing changes in sleep and affecting its quality.[10]

The preexistence of CV risk factors was also associated with poor sleep quality. This is also a two-way association, since sleep disorders can increase the risk of CV events,[16] [17] obesity, type-2 diabetes, and atherosclerosis.[18]

For those who were previously diagnosed with a psychological disorder, sleep quality was worse, which is aligned with the findings of Slaven et al.,[19] Kumar et al.,[11] and Kalmbach et al.,[20] in which sleep quality was associated with depressive symptoms and even depression. In fact, in the present study, all workers who had been diagnosed with a sleep disorder had poor sleep quality.

The results of the present study support the published evidence of the association between type of work and sleep quality, with shift workers presenting worse sleep quality. Kerkhof[21] reported a higher prevalence of general sleep disturbances in shift workers compared to day workers. Shift work, particularly night work, can have a negative impact on health and well-being, increasing the risk of sleep disorders,[22] [23] as well as that of various somatic and other psychological health conditions.[23] The impact of circadian rhythm disturbances (such as those caused by night work or shift work) on sleep quality is greater than that of non-modifiable factors such as age.[10] Shift time has also been described as an important risk factor for sleep disorders, since sustained or prolonged exposure to risk factors, whether biological, behavioral, individual or social, probably results in a higher risk of long-term adverse consequences compared to brief or short-term exposure.[24] However, the results of the present study showed that those who were working on the current shift for up to five years had worse sleep quality. This can imply some sort of adjustment in the sleeping habits of these workers, in which their experience helps them adjust their routines to reduce the impact that shift work can have on sleep quality, just like it was found by Costa.[25]

After adjusting all variables associated with sleep quality in the bivariate analysis, most variables did not increase the risk of having poor sleep quality, since the calculated odds ratio was not statistically significant, and this is the main finding and strength of the present study. The published literature on sleep quality mainly focuses on the individual effect of a specific variable on sleep, usually by conducting a bivariate analysis. But, since sleep quality is a multidimensional problem, influenced by multiple factors (related to the individual, to their working conditions, to the use of different substances, and others), it should be analyzed considering different factors, adjusted to one another, just we like did in the present study.

Of course, these results must be weighed against some limitations. First of all, the present was an observational study with no randomization of participants. Our results cannot be generalized to every activity sector. Secondly, the sampling method we used can lead to selection bias, since only those accessing their email or social media accounts could access the link to participate in the study. Also, the sample size may have influenced the results of our logistic model. Finally, in spite of the fact that the present study included a multiplicity of factors that can influence sleep quality, important factors, such as the time of exposure to light and/or the number of successive shifts without rest, and the use of light to stay awake were not addressed, since they were not collected for analysis.

Still, the current study presents some innovative features that should explored in other professional settings, with larger sample sizes and, preferably, under controlled conditions.


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Conclusion

Sleep quality is such a complex issue that its analysis should be multifactorial, not restricted to a simple association between a single variable and sleep quality.

Although there were several factors that individually negatively influenced sleep quality, when adjusted to one another, by using a logistic regression model, they did not increase the risk of having poor sleep quality. No differences were found regarding medication use, type of work, and sleep quality.

Understanding and promoting sleep quality and its underlying factors is a key factor to avoid pharmacological sleep iatrogenesis, encourage the rational and safe use of medications, and thereby improve overall health. Further research is necessary to confirm our findings, since they are restrained by the limitations pf the present study.


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Conflict of Interests

The authors have no conflict of interests to declare.

  • References

  • 1 Mukherjee S, Patel SR, Kales SN. et al; American Thoracic Society ad hoc Committee on Healthy Sleep. An Official American Thoracic Society Statement: The Importance of Healthy Sleep. Recommendations and Future Priorities. Am J Respir Crit Care Med 2015; 191 (12) 1450-1458
  • 2 Müller MR, Guimarães SS. Impacto dos transtornos do sono sobre o funcionamento diário e a qualidade de vida. Estud Psicol Camp. 2007; 24 (04) 519-528
  • 3 da Rocha MCP, De Martino MMF. [Stress and sleep quality of nurses working different hospital shifts]. Rev Esc Enferm USP 2010; 44 (02) 280-286
  • 4 CDC - Data and Statistics - Sleep and Sleep Disorders [Internet]. 2021 [citado 11 de Janeiro de 2022]. Disponível em: https://www.cdc.gov/sleep/data_statistics.html
  • 5 Mendes SS, Martino MM. [Shift work: overall health state related to sleep in nursing workers]. Rev Esc Enferm USP 2012; 46 (06) 1471-1476
  • 6 Costa G. Shift work and health: current problems and preventive actions. Saf Health Work 2010; 1 (02) 112-123
  • 7 De Martino MMF. Estudo comparativo de padrões de sono em trabalhadores de enfermagem dos turnos diurno e noturno. Rev Panam Salud Publica 2002; 12 (02) 95-100
  • 8 da Silva DB, Gabas DV, Omitto Rde F, da Silva Rde JP, Moreno Ade H. Benefícios do uso da melatonina no tratamento da insônia e qualidade do sono. Cuid Enferm 2020; 75-80
  • 9 Oliveira AV, Nunes PIG. Distúrbios do sono e a sua medicalização: uma revisão narrativa da literatura. Rev Interdiscip em Ciênc Saúde e Biológicas – RICSB 2020; 3 (02) 58
  • 10 Chang W-P, Peng Y-X. Meta-analysis of differences in sleep quality based on actigraphs between day and night shift workers and the moderating effect of age. J Occup Health 2021; 63 (01) e12262
  • 11 Kumar S, Wong PS, Hasan SS, Kairuz T. The relationship between sleep quality, inappropriate medication use and frailty among older adults in aged care homes in Malaysia. PLoS One 2019; 14 (10) e0224122
  • 12 Karami M, Dehdashti AR, Bahrami M. Prevalence of test anxiety among public health students at Semnan University of Medical Sciences in 2017: a short report. Journal of Rafsanjan University of Medical Sciences and Health Services. 2018; 17 (03) 275-282
  • 13 Fadhel FH. Exploring the relationship of sleep quality with medication use and substance abuse among university students: a cross-cultural study. Middle East Curr Psychiatry. 2020; 27 (01) 65
  • 14 Gordon HW. Differential Effects of Addictive Drugs on Sleep and Sleep Stages. J Addict Res (OPAST Group) 2019;3(02):
  • 15 Liira J, Verbeek JH, Costa G. et al. Pharmacological interventions for sleepiness and sleep disturbances caused by shift work. Cochrane Database Syst Rev 2014; 2014 (08) CD009776
  • 16 Bernardo VM, da Silva FC, Gonçalves E, Hernández SSS, Arancibia BAV, da Silva R. Effects of Shift Work on Sleep Quality of Policemen: A Systematic Review. Rev Cuba Med Mil 2015; 44 (03) 334-345
  • 17 Rajaratnam SMW, Barger LK, Lockley SW. et al; Harvard Work Hours, Health and Safety Group. Sleep disorders, health, and safety in police officers. JAMA 2011; 306 (23) 2567-2578
  • 18 Phoi YY, Keogh JB. Dietary Interventions for Night Shift Workers: A Literature Review. Nutrients 2019; 11 (10) 2276
  • 19 Slaven JE, Mnatsakanova A, Burchfiel CM. et al. Association of sleep quality with depression in police officers. Int J Emerg Ment Health 2011; 13 (04) 267-277
  • 20 Kalmbach DA, Arnedt JT, Song PX, Guille C, Sen S. Sleep Disturbance and Short Sleep as Risk Factors for Depression and Perceived Medical Errors in First-Year Residents. Sleep 2017; 40 (03) zsw073
  • 21 Kerkhof GA. Shift work and sleep disorder comorbidity tend to go hand in hand. Chronobiol Int 2018; 35 (02) 219-228
  • 22 Costa G. The impact of shift and night work on health. Appl Ergon 1996; 27 (01) 9-16
  • 23 Richter K, Peter L, Rodenbeck A, Weess HG, Riedel-Heller SG, Hillemacher T. Shiftwork and Alcohol Consumption: A Systematic Review of the Literature. Eur Addict Res 2021; 27 (01) 9-15
  • 24 Gurubhagavatula I, Barger LK, Barnes CM. et al. Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society. J Clin Sleep Med 2021; 17 (11) 2283-2306
  • 25 Costa G. Some considerations about aging, shift work and work ability. Int Congr Ser 2005; 1280: 67-72

Address for correspondence

André Coelho

Publication History

Received: 31 October 2022

Accepted: 31 May 2023

Article published online:
26 March 2024

© 2024. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 Mukherjee S, Patel SR, Kales SN. et al; American Thoracic Society ad hoc Committee on Healthy Sleep. An Official American Thoracic Society Statement: The Importance of Healthy Sleep. Recommendations and Future Priorities. Am J Respir Crit Care Med 2015; 191 (12) 1450-1458
  • 2 Müller MR, Guimarães SS. Impacto dos transtornos do sono sobre o funcionamento diário e a qualidade de vida. Estud Psicol Camp. 2007; 24 (04) 519-528
  • 3 da Rocha MCP, De Martino MMF. [Stress and sleep quality of nurses working different hospital shifts]. Rev Esc Enferm USP 2010; 44 (02) 280-286
  • 4 CDC - Data and Statistics - Sleep and Sleep Disorders [Internet]. 2021 [citado 11 de Janeiro de 2022]. Disponível em: https://www.cdc.gov/sleep/data_statistics.html
  • 5 Mendes SS, Martino MM. [Shift work: overall health state related to sleep in nursing workers]. Rev Esc Enferm USP 2012; 46 (06) 1471-1476
  • 6 Costa G. Shift work and health: current problems and preventive actions. Saf Health Work 2010; 1 (02) 112-123
  • 7 De Martino MMF. Estudo comparativo de padrões de sono em trabalhadores de enfermagem dos turnos diurno e noturno. Rev Panam Salud Publica 2002; 12 (02) 95-100
  • 8 da Silva DB, Gabas DV, Omitto Rde F, da Silva Rde JP, Moreno Ade H. Benefícios do uso da melatonina no tratamento da insônia e qualidade do sono. Cuid Enferm 2020; 75-80
  • 9 Oliveira AV, Nunes PIG. Distúrbios do sono e a sua medicalização: uma revisão narrativa da literatura. Rev Interdiscip em Ciênc Saúde e Biológicas – RICSB 2020; 3 (02) 58
  • 10 Chang W-P, Peng Y-X. Meta-analysis of differences in sleep quality based on actigraphs between day and night shift workers and the moderating effect of age. J Occup Health 2021; 63 (01) e12262
  • 11 Kumar S, Wong PS, Hasan SS, Kairuz T. The relationship between sleep quality, inappropriate medication use and frailty among older adults in aged care homes in Malaysia. PLoS One 2019; 14 (10) e0224122
  • 12 Karami M, Dehdashti AR, Bahrami M. Prevalence of test anxiety among public health students at Semnan University of Medical Sciences in 2017: a short report. Journal of Rafsanjan University of Medical Sciences and Health Services. 2018; 17 (03) 275-282
  • 13 Fadhel FH. Exploring the relationship of sleep quality with medication use and substance abuse among university students: a cross-cultural study. Middle East Curr Psychiatry. 2020; 27 (01) 65
  • 14 Gordon HW. Differential Effects of Addictive Drugs on Sleep and Sleep Stages. J Addict Res (OPAST Group) 2019;3(02):
  • 15 Liira J, Verbeek JH, Costa G. et al. Pharmacological interventions for sleepiness and sleep disturbances caused by shift work. Cochrane Database Syst Rev 2014; 2014 (08) CD009776
  • 16 Bernardo VM, da Silva FC, Gonçalves E, Hernández SSS, Arancibia BAV, da Silva R. Effects of Shift Work on Sleep Quality of Policemen: A Systematic Review. Rev Cuba Med Mil 2015; 44 (03) 334-345
  • 17 Rajaratnam SMW, Barger LK, Lockley SW. et al; Harvard Work Hours, Health and Safety Group. Sleep disorders, health, and safety in police officers. JAMA 2011; 306 (23) 2567-2578
  • 18 Phoi YY, Keogh JB. Dietary Interventions for Night Shift Workers: A Literature Review. Nutrients 2019; 11 (10) 2276
  • 19 Slaven JE, Mnatsakanova A, Burchfiel CM. et al. Association of sleep quality with depression in police officers. Int J Emerg Ment Health 2011; 13 (04) 267-277
  • 20 Kalmbach DA, Arnedt JT, Song PX, Guille C, Sen S. Sleep Disturbance and Short Sleep as Risk Factors for Depression and Perceived Medical Errors in First-Year Residents. Sleep 2017; 40 (03) zsw073
  • 21 Kerkhof GA. Shift work and sleep disorder comorbidity tend to go hand in hand. Chronobiol Int 2018; 35 (02) 219-228
  • 22 Costa G. The impact of shift and night work on health. Appl Ergon 1996; 27 (01) 9-16
  • 23 Richter K, Peter L, Rodenbeck A, Weess HG, Riedel-Heller SG, Hillemacher T. Shiftwork and Alcohol Consumption: A Systematic Review of the Literature. Eur Addict Res 2021; 27 (01) 9-15
  • 24 Gurubhagavatula I, Barger LK, Barnes CM. et al. Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society. J Clin Sleep Med 2021; 17 (11) 2283-2306
  • 25 Costa G. Some considerations about aging, shift work and work ability. Int Congr Ser 2005; 1280: 67-72