Night-shift work and sleep quality: a cross-sectional survey study among Afghan healthcare workers

doi:10.21203/rs.3.rs-2782380/v1

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Night-shift work and sleep quality: a cross-sectional survey study among Afghan healthcare workers

https://doi.org/10.21203/rs.3.rs-2782380/v1

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Background

Sleep is a complex physiological process during which the body and mind enter a period of rest. For a healthy lifestyle, different cohort groups can be affected in different ways. One such cohort is healthcare workers (HCWs) – an unexplored group in Afghanistan. Therefore, the present study examined the association between a range of socio-demographic factors including having night shift work and sleep quality among Afghan HCWs.

Methods

A cross-sectional survey was administered in January 2023 among HCWs (N = 342) in the Herat province of Afghanistan. The survey examined sleep quality and its association with a range of socio-demographic factors among HCWs. Logistic regression models were used to examine the association of sleep quality with socio-demographic characteristics among HCWs.

Results

Of the 342 participants, 58.5% reported poor sleep quality. Married marital status, having higher number of children, not being a doctor, low economic status, working night shifts, and traumatic event occurring during past month were among the main variables associated with sleep quality among Afghan HCWs. Multiple regression analysis indicated having high income [negatively] (AOR = 4.132, p = 0.002), working night shifts [positively] (AOR = 0.288, p < 0.001), and traumatic event occurring during past month [positively] (AOR = 0.504, p = 0.007) were significantly associated with sleep quality.

Conclusion

The study suggests the need for Afghan health employers to create a healthy work environment that prioritizes the well-being of their employees by limiting overtime hours, providing rest breaks during long shifts, and ensuring that HCWs have access to necessary resources for coping with work-related stressors. These policies would promote the overall health and well-being of the workforce and would likely lead to better patient care outcomes.

Health sciences/Medical research/Epidemiology

Biological sciences/Neuroscience/Circadian rhythms and sleep

Sleep quality

healthcare workers

Afghanistan

Taliban

Sleep is defined as a complex physiological process during which the body and mind enter a period of rest (1). For a healthy lifestyle, different age groups need different amounts of sleep. More specifically, in a 24-hours period, infants (4–12 months) need 12 to 16 hours of sleep, 1-2-year-old children need between 11 to 14 hours, 3-5-year-old children need 10 to 13 hours, 6-12-year-old children need 9–12 hours, adolescents (13–18 years) need 8–10 hours, and adults need 7 or more hours (2). In addition to sleep quantity, sleep quality is also an important aspect of sleep (3). A person’s satisfaction with all elements of sleep experience defines their sleep quality (4). Sleep quality consists of four characteristics: sleep efficiency, sleep latency (the time it takes one to fall asleep after going to bed), sleep duration, and waking after sleep onset (the amount of time a person spends being awake after falling asleep) (4). It is important to recognize the signs of poor-quality sleep which include feeling drowsy despite getting enough sleep, waking up throughout the night and/or exhibiting signs of a sleep disorder such as snoring (5). Sleep quality impacts an individual’s body, memory, and learning (6). A good night’s sleep provides favorable impacts such as being well rested and maintaining positive relationships, whereas a poor sleep quality can make individuals irritable, drowsy, and slow in responses (4).

Sleep quality is associated with work performance such that better sleep at night leads to a more productive work the next day (7, 8). A study on employees in Saudi Arabia found that a highly significant outcome of poor-quality sleep was sleeping during work time. Moreover, the study found that those employees who took sleep medicines were more likely to be absent from work or make errors while working (9). In another study on the work performance of working mothers in Pakistan, researchers found that sleep deprivation not only negatively impacted work performance but was also in Pakistan associated with workplace deviance (10). Studies have shown that individuals with less sleep duration are prone to a faster global cognitive decline (11) while cognitive abilities are considered predictors of good job performance (12). Moreover, workers with insomnia are at a higher risk for injuries in the workplace and this outcome is mediated by workplace cognitive failure (13). In relation to shift work, studies have shown that night-shift workers are considerably more likely to report sleep disturbances, poorer sleep quality, shorter sleep latency, shorter sleep duration, and daytime dysfunction (14). Insufficient sleep can lead to complications such as high levels of cortisol which in turn can lead to high blood sugar, high blood pressure and weight gain, as well as anxiety, depression, and stroke (15).

Studies have also found an association between poor sleep quality and stressful life events such that the association of stressful events with poor sleep quality is mediated by concentrating on negative content or rumination (16). In a study among Chinese adolescents, researchers found that unpleasant life events are associated with sleep quality and that this association was mediated by negative coping styles (17). A common symptom of post-traumatic stress disorder (PTSD) is sleep disturbance. Moreover, women are more likely to experience insomnia and repeated nightmares after a traumatic event compared to men (18). Research has also shown that individuals with greater childhood trauma can experience poor sleep health in adulthood (19).

Research conducted on low-income adults in a rural area of China found that socio-demographic factors such as gender, marital status, and education level were associated with sleep quality (20). More specifically, the study showed that males reported better sleep quality compared to females and the researchers attributed this difference to female hormone secretions. As for marital status, the study showed that married women had better sleep quality compared to single women, but this association was not found in men. The results of the study also showed that a lower education level was associated with an increased likelihood of poor sleep quality, and that this could be due to individuals with lower education making “unhealthier lifestyle choices” that could disrupt sleep quality. Moreover, the study did not find any significant association between cigarette smoking/alcohol drinking and low sleep quality (20). However, according to another study, cigarette smokers in Korea reported higher daytime dysfunction and lower sleep quality compared to non-smokers (21). Research has found that poor socioeconomic status can reduce sleep quality and this association is mediated by depressive symptoms (22). Research has also shown that poverty negatively affects sleep duration and the ability to fall asleep (22).

A meta-analysis of observational studies has attested that insomnia is more prevalent among women compared to men (23). Moreover, an analysis of sleep and sociodemographic data showed that that (in general) married individuals experienced greater levels of REM (rapid eye movement) sleep compared to non-married individuals (24). In terms of sleep problems, women experience more sleep problems than men, and the results are consistent for divorced and widowed individuals compared to married ones (25). In relation to parenthood, new parents are often extremely sleep deprived if their only sleep time option is at night (26). After giving birth to a child, both mothers and fathers experience a decline in sleep duration and satisfaction, and this consequence does not recover for up to six years (27).

Other cohorts can also be more susceptible to sleep problems. In a cohort study among healthcare workers in the United States (US), data reported that 40.9% of hospital workers experienced sleep disorders, and consequently sleep disorders were found to be associated with adverse safety incidences (28). A study conducted in Turkey during the COVID-19 pandemic showed that those who worked in healthcare facilities had lower sleep quality compared to those working outside the healthcare field. (29) A review of sleep studies reported that sleep deprivation is common among healthcare workers and doctors (30).

Although there are many studies on the role of sleep and work performance, there are no data available regarding the association of sleep quality and daytime dysfunction among Afghan healthcare workers. The participants chosen for the present study were healthcare workers including doctors and other healthcare staff. The present study examined the association between a range of socio-demographic factors including having night shift work and sleep quality among HCWs.

Participants and procedure

A cross-sectional survey study was conducted among healthcare workers (HCWs) between January 29, 2022 and February 5, 2023 in Herat province of Afghanistan. The study’s participants were employees of Herat’s nine governmental Hospitals serving as the HCWs as well as those working in the management teams. A total of 342 HCWs participated and were recruited using a convenience sampling technique following the distribution on 600 surveys (response rate = 57%). The researchers personally approached the HCWs to participate in this study.

Measures

The survey used comprised two main sections: the socio-economic factors section, and the sleep quality assessment section. The socio-economic section of the survey included the following items: age (in years), gender (male, female), marital status (single, married), number of children (none, 1–5, 6–12), field of work (doctors, other), economic status (high-income, middle-income, low-income), worked night shifts (yes, no), cigarette smoker (non-smoker, ex-smoker, current-smoker), and traumatic event occurring during the past month (yes, no).

The sleep quality section included the Pittsburg Sleep Quality Index (PSQI) to assess the sleep quality of participants (31). The PSQI comprises 19 items which are self-rated and six items which are rated by bed-partner or roommate. However, only the self-rated items are considered in the scoring process. The 19 items of the PSQI form seven components (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction), and each item (e.g., “Cannot get to sleep within 30 minutes”) is rated from 0 (“not during the past month”) to 3 (“three or more times a week”). To calculate the global score, the scores of all of the seven components are summed together which results in a range from 0 (“indicating no difficulty”) to 21 (“indicating severe difficulty in all components”). Participants having a total score of 5 or less were considered as having good sleep quality, and participants with a total score of over 5 were considered to have poor sleep quality. The Cronbach’s alpha in the present study was 0.74.

Data analysis

The collected data were entered into the Microsoft Excel 2016. The statistical analysis was carried out using IBM SPSS version 26.0 software. Variables of each part were presented in category form with their frequency in number and percentage. Chi-square tests were performed to evaluate the association between the participants’ socio-economic characteristics and their sleep quality. A significant p-value was considered as less than 0.05.

Ethics

Ethical approval for the study was obtained from the Afghanistan Center for Epidemiological Studies (Ref: #22.006). The participants were briefed on the relevance and objectives of the study. The purpose of the study was explained to each participant. Confidentiality of information was maintained by omitting any personal identifier from the survey. Participants were aware that they could withdraw at any point in time from the study. All methods were carried out in accordance with relevant ethical guidelines and regulations. Informed consent was obtained from all the participants in the present study.

A total of 342 HCWs participated in the present study with an age range of 18 to 60 years. The mean age of the participants was 28.90 years (SD ± 8.10). Just over half of the participants were male (50.3%). Almost two-thirds of the participants were married (63.2%). Almost one-third of the participants were doctors or residents (36.8%). Almost three-quarters of the participants reported that they worked night-shifts (74.6%) [Table 1].

Table 1

Characteristics distribution of the study sample
Characteristic	Categories	Number (N)	Percentage (%)
Age group	18–29-years 30–60-years	253 89	74.0 26.0
Gender	Male Female	172 170	50.3 49.7
Marital status	Single Married	126 216	36.8 63.2
Number of children	None 1–5 children 6–12 children	180 149 13	52.6 43.6 3.8
Field of work	Doctors Other	126 216	36.8 63.2
Economic status	High income Middle income Low income	119 166 57	34.8 48.5 16.7
Working night shifts	Yes No	255 87	74.6 25.4
Cigarette smoking status	Non-smoker Smoker	312 30	91.2 8.8
Traumatic event occurred during past month	Yes No	142 200	41.5 58.5
Total		342	100.0

More than half of the participants’ sleep quality was found to be poor (58.5%). The mean value for subjective sleep quality was found to be 0.96 (SD ± 0.74) which was lower than 50%. The mean value for the habitual sleep efficiency component was found to be the lowest (0.10; SD ± 0.39) [Table 2].

Table 2

Prevalence of sleep quality and its components among participants
Components		Mean/SD
Subjective sleep quality		0.96 ± 0.74
Sleep latency		1.37 ± 0.97
Sleep duration		0.97 ± 0.92
Habitual sleep efficiency		0.10 ± 0.39
Sleep disturbances		1.25 ± .70
Use of sleep medication		0.24 ± 0.67
Daytime dysfunction		1.02 ± 0.93
Global score		5.91 ± 3.36
Sleep quality groups		N (%)
	Good	142 (41.5)
	Poor	200 (58.5)

Almost two-thirds of the married participants were found to have poor sleep quality (62.5%). More than half of participants with middle-income economic status were found to have poor sleep quality (60.2%) and two-thirds of participants who were not medical doctors (nurses, midwives, management team) had poor sleep quality (64.4%). There was a significant relationship between marital status (single participants had better sleep quality than the married participants), number of children (participants with no children had better sleep quality than those with children), field of work (participants who were doctors had better sleep quality than other HCWs), economic status (participants with high-income had better sleep quality), night-shift work (participants working night-shifts had poor sleep quality than those without nightshifts), and a traumatic event occurring during the past month (participants who experienced a traumatic event during the past month had poorer sleep quality than those who did not) with sleep quality of the participants [Table 3].

Table 3

Association of sleep quality with participants socio-demographic characteristics
Characteristic	Categories	Sleep quality		p-value
		Good	Poor
		N (%)	N (%)
Age group	18–29-years 30–60-years	111 (43.9) 31 (34.8)	142 (56.1) 58 (65.2)	.137
Gender	Male Female	74 (43.0) 68 (40.0)	98 (57.0) 102 (60.0)	.571
Marital status	Single Married	61 (48.4) 81 (37.5)	65 (51.6) 135 (62.5)	.048
Number of children	None 1–5 children 6–12 children	88 (48.9) 52 (34.9) 2 (15.4)	92 (51.1) 97 (65.1) 11 (84.6)	.006
Field of work	Doctor Other	65 (51.6) 77 (35.6)	61 (48.4) 139 (64.4)	.004
Economic status	High income Middle income Low income	67 (56.3) 66 (39.8) 9 (15.8)	52 (43.7) 100 (60.2) 48 (84.2)	< .001
Working night shifts	Yes No	84 (32.9) 58 (66.7)	171 (67.1) 29 (33.3)	< .001
Cigarette smoking status	Non-smoker Smoker	130 (41.7) 12 (40.0)	182 (58.3) 18 (60.0)	.860
Traumatic event occurred during past month	Yes No	42 (29.6) 100 (50.0)	100 (70.4) 100 (50.0)	< .001
Total		142 (41.5)	200 (58.5)

Multinomial logistic regression analysis was run to predict good sleep quality comprising the following variables: age group, gender, marital status, child group, field of work, economic status, working night shifts, cigarette smoking, and traumatic event occurring during the past month. High-income economic status (AOR = 4.132, p = 0.002), middle-income economic status (AOR = 2.385, p = 0.039), working night shifts (AOR = 0.288, p < 0.001), and traumatic event occurring during the past month (AOR = 0.504, p = 0.007) significantly contributed to the regression model [Table 4].

Table 4. Multinomial logistic regression analysis of sleep quality and participants’ characteristics

Characteristic

AOR [95% CI]

p-value

Age

0.978 [0.936, 1.023]

.339

Gender

Male

Female

1.586 [0.940, 2.677]

Reference

.084

Marital status

Single

Married

0.896 [0.433, 1.854]

Reference

.768

Number of children

None

1-5 children

6-8 children

1.626 [0.231, 11.453]

1.204 [0.198, 7.332]

Reference

.626

.841

Field of work

Doctor

Other

1.564 [0.913, 2.676]

Reference

.103

Economic status

High income

Middle income

Low income

4.132 [1.716, 9.945]

2.385 [1.043, 5.455]

Reference

.002

.039

Working night shifts

Yes

0.288 [0.165, 0.505]

Reference

<.001

Cigarette smoking

Non-smoker

Smoker

1.789 [0.732, 4.374]

Reference

.202

Traumatic event occurred during past month

Yes

0.504 [0.306, 0.828]

Reference

.007

The present study identified several socio-demographic factors that were significantly associated with sleep quality among healthcare workers (HCWs) in Afghanistan. The findings showed that being married, having children, being a healthcare worker other than a doctor, working night shifts, having low economic status, and experiencing a traumatic event in the past month were all significantly associated with sleep quality.

The present study found that married HCWs reported a significantly higher prevalence of poor sleep quality compared to single workers. This contrasts with a study conducted in Bahrain during the COVID-19 pandemic, which reported that single healthcare workers had a higher mean score on the Pittsburgh Sleep Quality Index (PSQI) than married workers, but the difference was not significant (32). Furthermore, a study of healthcare workers in Turkey during the COVID-19 pandemic found no significant relationship between poor sleep quality and marital status (33). The discrepancy in findings may be explained by work-family conflict (WFC), which has been found to be higher among married healthcare workers (nurses and paramedical staff) (34). WFC has been positively associated with emotional exhaustion (35), which in turn has been linked to sleep disturbances (36). Therefore, it is possible that the higher prevalence of poor sleep quality among married healthcare workers in the present study was due to the increased WFC and emotional exhaustion that often accompanies marriage and family responsibilities, particularly in healthcare settings where the demands of the job are high. Future studies could examine the impact of both marital quality and WFC on the quality of sleep among healthcare workers.

The present study found that the prevalence of poor sleep quality was highest among individuals with six to twelve children (84.6%), followed by those with one to five children (65.1%), and those with no children (51.1%). These findings highlight the significant impact of parenthood on sleep quality. Relatedly, another study involving nurses in the US showed that poorer-than-usual sleep quality was associated with more severe stressors the following day for parents with one child and those with two or more children, but not for non-parents. The study also found that the sleep-stressor association was stronger for those with two or more children compared to those with one child (37). Additionally, research conducted in the US, showed that on average, parents who raise children (from birth through to the age of 18 years) lose 645 hours of sleep time over this period when compared to those with no children (38).

The findings of the present study indicated that HCWs other than doctors were significantly more likely to experience poor sleep quality compared to doctors. These results are consistent with a study conducted in Bahrain, which found that being a non-physician HCW was a predictor of both poor sleep quality and high perceived stress levels (32). Similarly, a study in the US found a significant association between being a non-physician healthcare worker and the risk of moderate to severe insomnia (39). One possible explanation for this disparity could be the difference in pay scales between doctors and other HCWs, given that doctors are better paid than other HCWs.

In the present study, a significant association was found between working night-shifts and poor sleep quality among HCWs. The results showed that individuals who worked night-shifts were twice as likely to report poor sleep quality compared to those who did not. These findings are consistent with similar studies conducted in Malaysia and Saudi Arabia, which also reported higher rates of poor sleep quality among night-shift workers (14, 40). Furthermore, a study conducted in China demonstrated that nurses working consecutive or having night-shifts also experienced poor sleep quality. Additionally, the study found that participants who worked consecutive night-shifts showed a gradual decline in their sleep quality (41). These results are in line with the findings of the present study and suggest that poor sleep quality is a common problem among HCWs working night-shifts. This is also supported by other studies in Taiwan and Italy which found that poor sleep quality was associated with working night-shifts (42, 43). Moreover, the findings concur with all previously published reviews and worldwide meta-analyses showing that nurses and/or HCWs that work night shifts have poor sleep quality (e.g., 44–47).

In the present study, economic status was found to be another important factor linked to sleep quality. The findings indicated that 84.2% of participants with low income reported poor sleep quality, followed by 60.2% of those with middle income and 43.7% of those with high income. This result is consistent with the findings of a prior study conducted in the US (22) as well as a meta-analysis of observational studies showing that poverty and low socioeconomic levels negatively affect sleep quality (23).

Previous studies in China have shown that a traumatic or stressful event can disrupt sleep quality (16, 17). In the present study, 70.4% of individuals who experienced a traumatic event during the past month reported poor sleep quality, compared to 50.0% of individuals who did not experience a traumatic event in the past month. In relation to cigarette smoking, the findings did not indicate any significant association between cigarette smoking and sleep quality. This is consistent with a study conducted among Chinese adults (20). However, the results are different to a study conducted in Korea reporting that individuals who smoked cigarettes had lower sleep quality compared to those who did not (21).

Previous studies have shown that male participants generally experience better sleep quality compared to female participants (20, 23, 25). Additionally, a survey study conducted in the US found that female participants had higher odds of insomnia (39). However, the present study did not find any significant association between sleep quality and gender. Similarly, there was no significant association between age group and sleep quality, although a previous study in Egypt found that nurses younger than 30 years old were more likely to experience poor sleep quality. It is possible that other confounding variables, such as work schedule, work-family conflict, stress level, and job satisfaction may explain these differences. Future studies should consider a range of potential confounding factors that could influence sleep quality among HCWs.

Limitations and future directions

The present study has several limitations that should be considered when interpreting the findings. For example, the sample size of the study may be considered relatively small, given the complexity of the research question. Additionally, the study's sample was limited to HCWs from the province of Herat, which may not be representative of all HCWs in Afghanistan. The use of self-reported data may also introduce response bias into the results. Furthermore, the study only identified doctors and did not identify other HCWs by their specific roles, which is important because their sleep quality may vary based on their different job responsibilities and work-related stressors. Future research in Afghanistan should explore potential factors that may affect the sleep quality of HCWs including work-family conflict, job stressors, job satisfaction, and other potential variables to gain a more comprehensive understanding of the factors that influence sleep quality in this population.

The present study is the first attempt to evaluate the sleep quality of HCWs in Afghanistan. The findings provide valuable insights into sociodemographic factors associated with poor sleep quality among Afghan HCWs, including marital status, number of children, field of work, working night-shifts, economic status, and the experience of a traumatic event in the past month. The study recommends the need for Afghan health employers to create a healthy work environment that prioritizes the well-being of their employees by limiting overtime hours, providing rest breaks during long shifts, and ensuring that HCWs have access to necessary resources for coping with work-related stressors. These policies would promote the overall health and well-being of the workforce and would likely lead to better patient care outcomes.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files.

Conflict of interest

The authors declare no conflict of interest.

Funding

This research received no external funding.

Acknowledgement

We would like to express our sincere gratitude to all the participants who enrolled in this study

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Night-shift work and sleep quality: a cross-sectional survey study among Afghan healthcare workers

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