Anxiety and depressive symptoms are associated with poor sleep health during a period of COVID-19-induced nationwide lockdown: a cross-sectional analysis of adults in Jordan

Abstract

Background

Jordan, a Middle Eastern country, declared a state of national emergency due to COVID-19 and a strict nationwide lockdown on 17 March 2020, banning all travel and movement around the country, potentially impacting mental health. This study sought to investigate the association between mental health (eg, anxiety and depressive symptoms) and sleep health among a sample of Jordanians living through a state of COVID-19-induced nationwide lockdown.

Methods

Using Facebook, participants (n=1240) in Jordan in March 2020 were recruited and direct to a web-based survey measuring anxiety (items from General Anxiety Disorder 7-item (GAD-7) scale instrument), depressive symptoms (items from Center for Epidemiologic Studies Depression Scale), sleep health (items from the Pittsburgh Sleep Quality Index) and sociodemographic. A modified Poisson regression model with robust error variance. Adjusted prevalence ratios (aPRs) and 95% CIs were estimated to examine how anxiety and depressive symptoms may affect different dimensions of sleep health: (1) poor sleep quality, (2) short sleep duration, (3) encountering sleep problems.

Results

The majority of participants reported having experienced mild (33.8%), moderate (12.9%) or severe (6.3%) levels of anxiety during lockdown, and nearly half of respondents reported depressive symptoms during lockdown. Similarly, over 60% of participants reported having experienced at least one sleep problem in the last week, and nearly half reported having had short sleep duration. Importantly, anxiety was associated with poor sleep health outcomes. For example, corresponding to the dose–response relationship between anxiety and sleep health outcomes, those reporting severe anxiety were the most likely to experience poor sleep quality (aPR =8.95; 95% CI=6.12 to 13.08), short sleep duration (aPR =2.23; 95% CI=1.91 to 2.61) and at least one problem sleep problem (aPR=1.73; 95% CI=1.54 to 1.95). Moreover, depressive symptoms were also associated with poor sleep health outcomes. As compared with scoring in the first quartile, scoring fourth quartile was associated with poor sleep quality (aPR=11.82; 95% CI=6.64 to 21.04), short sleep duration (aPR=1.87; 95% CI=1.58 to 2.22), and experiencing at least one sleep problem (aPR=1.90; 95% CI=1.66 to 2.18).

Conclusions

Increased levels of anxiety and depressive symptoms can negatively influence sleep health among a sample of Jordanian adults living in a state of COVID-19-induced nationwide lockdown.

Strengths and Limitations of this study.

• This study used a relatively large sample for a population that is heavily understudied in public health research, as well as an increased number of exposure and outcome measures compared with the existing research conducted in the region.

• To the best of our knowledge, this is the first study to examine this association among a Middle Eastern population and one of the first to investigate the impact of an extremely strict extended lockdown on health outcomes.

• The reliance of subjective measures for both the exposure and the outcome may have introduced bias.

• The generalisability of the results is an acknowledged concern given that participants were Jordanian using the social media platform, Facebook.

Introduction

On 31 December 2019, a pneumonia of unknown cause was first detected in Wuhan, the largest metropolitan area in China’s Hubei province, and was reported to the WHO Country Office in China. A month later, COVID-19 outbreak was declared as a public health emergency of international concern by WHO. On 2 March 2020, Jordan detected its first COVID-19 case in the country. On 11 March 2020, as the number of COVID-19 cases outside China continued to increase, resulting in over 4000 deaths at the time, WHO declared the COVID-19 a pandemic.1 2

As the COVID-19 pandemic continued to unfold across the world, Jordan began detecting tens of cases, and decided to impose some of the strictest measures to combat an outbreak. On 14 March 2020, a travel ban was issued, and all borders in Jordan were blocked. Few days after, a strict nationwide lockdown was implemented, and residents were not allowed on the streets.3 Although lockdown ended in Wuhan, China on 8 April 2020 after 76 days of being implemented,4 Jordanians continued to live under some of the strictest measures of a lockdown for nearly 2 months until early May 2020. This included allowing some movement outside households for some days of the week while completely disallowing such movement on other days. Additionally, all parks, restaurants, cafes and any public open spaces were shut down indefinitely. Groceries were only available through delivery to households, and no cars could be driven on the streets in all regions of the country.

While a lockdown is considered a recommended measure in combating an outbreak, an extended lockdown may have severe effects on people’s social lives, mobility and the overall economy.5 This includes influencing a set of health outcomes among the general population and could be an activator of stressors, such as anxiety, and several other symptoms of poor mental health.6–9 In the context of a prolonged strict lockdown measures, large-scale social isolation is also induced among the population. In Jordan, a large proportion of the population is employed in working-class jobs, such as those in the industrial or agricultural sectors, which require manual labour and typically offer low pay. The lockdown has left many Jordanians unemployed and without the daily income they depend on, imposing significant financial stress. For instance, in a report demonstrating the impact of lockdown in Jordan on households across the country, three-quarters of respondents (72.5%), among a sample of 12 084 Jordanian adults, indicated having difficulties covering basic needs (rent, food, heating and medicine) due to the lockdown measures.3 Additionally, 63.3% indicated that they did not have a source of support in case they run out of food and basic amenities required for survival.3

In general, previous research has consistently demonstrated that poor mental health is associated with multiple negative health outcomes, including poor sleep health.6–9 The Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, widely used by psychiatrists across the globe, lists sleep disturbance as one of the possible symptoms required for the diagnosis of both major depressive disorder and generalised anxiety disorder. Negative mental health outcomes may be heightened in epidemics, such as during the COVID-19 pandemic.10 For instance, Wang et al demonstrated that the COVID-19 pandemic and the restriction of freedom during lockdowns has been shown to have a significant psychological impact related to stress, depression and anxiety.11 Additionally, Brooks et al, reported that such psychosocial health outcomes (eg, stress, anger and fear) could be further increased during the state epidemic-induced lockdowns.12

Importantly, research has shown that sleep and the circadian system exert a strong regulatory influence on immune functions.13 Sleep and the circadian system cooperate bidirectionally at the systemic and cellular level to organise immune functions in time and space via neuroendocrine and sympathetic effector mechanisms.14–17 The relationship between sleep health and the immune system is particularly of importance during times of epidemics. For example, Prather et al showed that among a sample of 164 healthy men and women, shorter sleep duration, measured behaviourally using actigraphy prior to viral exposure, was associated with increased susceptibility to the common cold.18 While there is a literature on the prevalence of mental health issues during the times of epidemics,19–24 as well as its relationship with sleep health among various populations,6–10 25–27 few studies have investigated such an association during times of nationwide lockdowns,28–30 especially in the Middle East. Lockdown measures could be effective in controlling the transmission of infection, such measures could influence other health outcomes unrelated to their current outbreak, including sleep.

In this study, we sought to investigate the associations between mental health issues, namely anxiety and depressive symptoms, with poor sleep health among a sample of individuals residing in Jordan during a period of COVID-19 pandemic-induced lockdown. We hypothesised that anxiety and depressive symptoms will be associated with a higher risk of poor sleep health among a sample of Jordanians, after controlling for demographic covariates.

Methodology

Data and study sample

Facebook, a social media platform, was used to recruit a sample of individuals across Jordan during a period of nationwide lockdown put in place due to the COVID-19 pandemic outbreak in March 2020. Facebook was the platform of choice given its large spread among the Jordanian population, with approximately 83.21% of the population (9 903 802) being active users on Facebook in March 2020.31 An advertised post was placed on Facebook targeting Jordanians between the ages of 18 and 65 years who were in Jordan for the duration of the last 2 weeks of March 2020. The post was also placed by an independent researcher, and snowball sampling was also enabled by allowing the advertised post to be shared by individuals on Facebook. The survey was administered through Qualtrics, a platform for survey administration previously used in health research.32 The survey was available to participants in both English and Arabic languages. The survey was originally written in English, and then translated independently by three bilingual researchers to Arabic. The survey was then piloted for readability and clarity among both English and Arabic speakers. The post was advertised for a period of four consecutive days and included assessment of eligibility and a total of 30 items including sociodemographic and measures for various constructs. These included anxiety, depressive symptoms and sleep health. Measures were taken to avoid duplicate answers by using the ‘prevent ballot box stuffing’ feature on Qualtrics. Additionally, internal protocol addresses associated with responses were reviewed manually to ensure no duplicates were recorded. On average, the survey took 7 min for completion.

Overall, 3462 participants clicked on the link and were redirected to the survey, of which 2202 participants were eligible to participant. Twenty-two responses were excluded for being aged <18 years of age. Overall, a total of 1240 full responses were recorded, corresponding to a completion rate of 56.4% among those deemed eligible. Approximately two-thirds (67.4%) of the respondents completed the survey in Arabic. Overall, the completion rate of those who clicked the linked to the survey was 36.5%.

Patient and public involvement

No patient involved.

Measures

Anxiety

The General Anxiety Disorder 7-item (GAD-7) scale was used to measure anxiety among participants. The GAD-7 was developed to diagnose generalised anxiety disorders and has been validated in 2740 primary care patients.33 Seven items were included in the survey, and participants’ anxiety was determined according to their scoring on the item. A 7-item questionnaire was used where each item asked participants how often, during the last 2 weeks, they were bothered by a given symptom. Response options were ‘not at all’, ‘several days’, ‘more than half the days’ and ‘nearly every day’ scored as 0, 1, 2 and 3, respectively. Scores range from 0 to 21, with four categorisations of anxiety severity according to the score. Those who score between 0 and 4 were considered to have minimal anxiety, while those scoring between 5–9, 10–14 and 15–21 were noted to have mild, moderate and severe anxiety, respectively. Cronbach’s alpha was 0.87, indicating good internal consistency.

Depressive symptoms

Ten (10) items were adopted from the Center for Epidemiologic Studies Depression Scale. Those items were chosen to be consistent with cultural concerns regarding the topic of depression and to be appropriate when translated to the Arabic language. Response options were ‘rarely or none of the time (<1 day)’, ‘some or a little of the time (1–2 days)’, ‘occasionally or a moderate amount of time (3–4 days)’ and ‘most or all of the time (5–7 days)’, scored as 0, 1, 2 and 3, respectively. Three items worded in the positive direction were reverse coded and all items were summed for a total score, with a possible range of 0–30. During data analysis, the total scores were divided in quartiles: the first quartile (Q1: 0–3), the second quartile (Q2: 4–6), the third quartile (Q3: 7–11) and the fourth quartile (Q4: 12–27). Cronbach’s alpha was 0.8145, indicating good internal consistency.

Sleep health

Three items were adopted from the Pittsburgh Sleep Quality Index, a reliable and validated tool,34 and included in the survey to measure for sleep health outcomes: sleep quality, sleep duration and experiencing sleep problems. Sleep quality was measured using the item “During the past month, how would you rate your sleep quality overall?”35 Participants were asked to choose one of four options, including ‘very good’, ‘fairly good’, ‘fairly bad’ and ‘very bad’. Consistent with previous research on sleep health,36–39 the four response options were dichotomised in statistical analysis good sleep quality (eg, includes ‘very good’ and ‘fairly good’) and poor sleep quality (eg, includes ‘very bad’ and ‘fairly bad’). To measure sleep duration, we used the question asking, “During the past month, how many hours of actual sleep did you get each night? (This may be different from the number of hours you spent in bed.)”35 Participants then reported their response in hours as integers with one decimal place allowed (eg, halves). Short sleep duration was defined as 7 hours or less.36 40 41 Finally, sleep problems were assessed by asking the participants if they experienced any of three sleep-related problems in the past 2 weeks (eg, the period of lockdown). Three statements were presented, and participants were given a ‘yes’ or ‘no’ response options. These statements were (1) “I had trouble sleeping because I could not get to sleep within 30 min” (eg, problems falling asleep); (2) “I had trouble staying awake while driving, eating meals, or engaging in social activity” (eg, problems staying awake in the daytime also known as daytime sleepiness) and (3) “I took medicine (prescribed or ‘over the counter’) to help me sleep”.37

Physical activity

Two items were adopted from the International Physical Activity Questionnaire (IPAQ) and included in this study. The IPAQ is a well-used instrument in health research, and has been shown to be reliable and valid across different populations.42–44 The two items used measured the number of days in which moderate-to-vigorous physical activity (MVPA) was performed, as well as the duration of time in minutes spent in a given day, respectively. The reported answers for both items were then multiplied to calculate the MVPA variable, defined as the duration (in minutes) spent in MVPA per one full week. The participants were then grouped based on whether they met the WHO’s adults physical activity guidelines or not (eg, 150 min or more of MVPA per week).45 46

Sociodemographic

Four items were included to measure demographic variables among participants. Participants were asked to report their age (in years), gender (male or female), employment status (employed, self-employed, unemployed, student or retired) and the city they currently reside in within Jordan. Cities were grouped into the following regions: Northern region (Irbid, Jerash, Balqa’a, Zarqa, Ajloun and Mafraq), Central region (Amman, Madaba and Salt), Southern region (Tafila, Karak, Ma’an, Aqaba and Petra).

Statistical analysis

Descriptive statistics (frequencies, percentages) were calculated for sociodemographic characteristics, physical activity, anxiety and depression according to sleep health outcomes (eg, poor sleep quality, short sleep duration and experiencing sleep problems). Mann-Whitney U test or χ² test was used to examine the differences in demographic characteristics, physical activity, anxiety and depression between those with and without each sleep health outcome.

The association between anxiety, depression and each poor sleep outcome was assessed using a modified Poisson regression model with robust error variance47 due to the high prevalence of the sleep health outcomes.48–53 The multivariable analysis adjusted for age, gender, employment status, region and physical activity. Adjusted prevalence ratios (aPRs) and 95% CIs were estimated. Test for p-trend was calculated by treating the categories of anxiety and depression as continuous variables. Two-sided p<0.05 was considered statistically significant. Data were analysed using Stata V.16.0 (StataCorp, College Station, Texas, USA).

Results

Table 1 presents the participants’ sociodemographic characteristics, anxiety and depressive symptoms according to sleep health outcomes. The mean age was 37.35 (SD=11.01), with over 60% of our sample aged <40 years. The median age of the sample was 35.0. Approximately half of the sample (52.9%) were males. Additionally, more than three-quarters of the participants reported residing in the Central region (78.2%), followed by the Northern region (19.1%). Most of the participants were either employed (54.3%) or self-employed (16.5%), while 17.6% reported being unemployed or 4.6% were retired at the current time. Approximately a third of our sample (31.5%) met the WHO’s adults physical activity guidelines for MVPA of 150 min or more per week. In terms of anxiety, 53% of the participants reported symptoms for mild (33.8%), moderate (12.9%) or severe anxiety (6.3%) during the period of national lockdown. Furthermore, approximately a quarter of our sample scored in each of the four quartiles for the depressive symptoms measures (eg, 26.9% in the lowest quartile, 24.8% in the second quartile, 26.8% in the third quartile and 21.5% in the highest quartile). Finally, and when measuring for sleep health outcomes, 17.9% of the participants reported poor sleep quality, 46.8% reported short sleep duration (≤7 hours of sleep on average for every night over the past week), while 63.7% reported experiencing at least one sleep problem over the past week.

Table 1.

Participants’ characteristics, anxiety and depression by poor sleep health, n (%)

	Total	Sleep health, n (%)		Sleep duration, n (%)		Sleep problems, n (%)
		Poor	Good	≤7 hours	>6 hours	Yes	No
Total	1240 (100.0)	222 (17.9)	1018 (82.1)	580 (46.8)	660 (53.2)	790 (63.7)	450 (36.3)
Age, median (IQR)	35.0 (29.0–43.0)	34.0 (29.0–42.0)	36.0 (30.0–44.0)	37.0 (30.0–45.0)	35.0 (28.0–42.0)*	35.0 (29.0–43.0)	36.0 (29.0–44.0)
Age (years)
18–24	127 (10.2)	21 (9.5)	106 (10.4)	37 (6.4)	90 (13.6)*	77 (9.8)	50 (11.1)
25–29	188 (15.2)	46 (20.7)	142 (14.0)	82 (14.1)	106 (16.1)	126 (16.0)	62 (13.8)
30–39	471 (38.0)	82 (36.9)	389 (38.2)	226 (39.0)	245 (37.1)	303 (38.4)	168 (37.3)
40–49	271 (21.9)	47 (21.2)	224 (22.0)	134 (23.1)	137 (20.8)	172 (21.8)	99 (22.0)
≥50	172 (13.9)	26 (11.7)	146 (14.3)	96 (16.6)	76 (11.5)	106 (13.4)	66 (14.7)
Missing	11 (0.9)	0 (0.0)	11 (1.1)	5 (0.9)	6 (0.9)	6 (0.8)	5 (1.1)
Gender
Male	656 (52.9)	105 (47.3)	551 (54.1)	285 (49.1)	371 (56.2)*	404 (51.1)	252 (56.0)
Female	583 (47.0)	117 (52.7)	466 (45.8)	295 (50.9)	288 (43.6)	385 (48.7)	198 (44.0)
Missing	1 (0.1)	0 (0.0)	1 (0.1)	0 (0.0)	1 (0.2)	1 (0.1)	0 (0.0)
Employment
Employed	673 (54.3)	113 (50.9)	560 (55.0)	320 (55.2)	353 (53.5)*	418 (52.9)	255 (56.7)
Self-employed	205 (16.5)	36 (16.2)	169 (16.6)	85 (14.7)	120 (18.2)	131 (16.6)	74 (16.4)
Student	84 (6.8)	13 (5.9)	71 (7.0)	30 (5.2)	54 (8.2)	49 (6.2)	35 (7.8)
Unemployed/Retired	275 (22.2)	60 (27.0)	215 (21.1)	145 (25.0)	130 (19.7)	190 (24.1)	85 (18.9)
Missing	3 (0.2)	0 (0.0)	3 (0.3)	0 (0.0)	3 (0.5)	2 (0.3)	1 (0.2)
Region†
Northern	237 (19.1)	45 (20.3)	192 (18.9)	99 (17.1)	138 (20.9)	152 (19.2)	85 (18.9)
Central	970 (78.2)	170 (76.6)	800 (78.6)	461 (79.5)	509 (77.1)	614 (77.7)	356 (79.1)
Southern	33 (2.7)	7 (3.2)	26 (2.6)	20 (3.5)	13 (2.0)	24 (3.0)	9 (2.0)
Physical activity
MVPA ≥150 min	391 (31.5)	47 (21.2)	344 (33.8)	162 (27.9)	229 (34.7)*	216 (27.3)	175 (38.9)*
MVPA <150 min	849 (68.5)	175 (78.8)	674 (66.2)	418 (72.1)	431 (65.3)	574 (72.7)	275 (61.1)
Anxiety, median (IQR)	5.0 (3.0–8.0)	9.0 (6.0–14.0)	4.0 (2.0–7.0)*	6.0 (3.0–10.0)	4.0 (2.0–7.0)*	6.0 (3.0–9.0)	3.0 (1.0–6.0)*
Anxiety
Minimal anxiety (0–4)	583 (47.0)	37 (16.7)	546 (53.6)*	212 (36.6)	371 (56.2)*	292 (37.0)	291 (64.7)*
Mild (5–9)	419 (33.8)	80 (36.0)	339 (33.3)	205 (35.3)	214 (32.4)	301 (38.1)	118 (26.2)
Moderate (10–14)	160 (12.9)	60 (27.0)	100 (9.8)	100 (17.2)	60 (9.1)	128 (16.2)	32 (7.1)
Severe (15–21)	78 (6.3)	45 (20.3)	33 (3.2)	63 (10.9)	15 (2.3)	69 (8.7)	9 (2.0)
Difficulties caused by depression
Not at all	650 (52.4)	72 (32.4)	578 (56.8)*	267 (46.0)	383 (58.0)*	369 (46.7)	281 (62.4)*
Several days	432 (34.8)	91 (41.0)	341 (33.5)	222 (38.3)	210 (31.8)	305 (38.6)	127 (28.2)
Over half the days	96 (7.7)	34 (15.3)	62 (6.1)	53 (9.1)	43 (6.5)	69 (8.7)	27 (6.0)
Nearly everyday	58 (4.7)	25 (11.3)	33 (3.2)	36 (6.2)	22 (3.3)	46 (5.8)	12 (2.7)
Missing	4 (0.3)	0 (0.0)	4 (0.4)	2 (0.3)	2 (0.3)	1 (0.1)	3 (0.7)
Depression, median (IQR)	6.0 (3.0–11.0)	12.0 (8.0–16.0)	5.0 (3.0–9.0)*	8.0 (4.0–13.0)	5.0 (3.0–9.0)*	8.0 (4.0–12.0)	4.0 (2.0–8.0)*
Depression
Quartile 1 (0–3)	333 (26.9)	12 (5.4)	321 (31.5)*	117 (20.2)	216 (32.7)*	144 (18.2)	189 (42.0)*
Quartile 2 (4–6)	308 (24.8)	25 (11.3)	283 (27.8)	132 (22.8)	176 (26.7)	188 (23.8)	120 (26.7)
Quartile 3 (7–11)	332 (26.8)	65 (29.3)	267 (26.2)	159 (27.4)	173 (26.2)	234 (29.6)	98 (21.8)
Quartile 4 (12–27)	267 (21.5)	120 (54.1)	147 (14.4)	172 (29.7)	95 (14.4)	224 (28.4)	43 (9.6)

*Indicates that significant differences at the 5% (0.05) level using a χ² test or Mann-Whitney U test.

†Northern region includes Irbid (n=110), Jerash (n=10), Balqa’a (n=3), Zarqa (n=91), Ajloun (n=7), Mafrqa (n=16); Central region includes Amman (n=925), Madaba (n=19), Salt (n=26); Southern region includes Tafila (n=2), Karak (n=6), Ma’an (n=6), Aqaba (n=15) and Petra (n=4)

MVPA, moderate-to-vigorous physical activity.

Multivariable regressions with 95% CIs were calculated to investigate the relationship between anxiety, depressive symptoms and sleep health outcomes. The results, after adjusting for sociodemographic covariates, are presented in table 2. Anxiety was associated with poor sleep health outcomes. Results demonstrated a dose–response relationship, as the aPRs for poor sleep health increased with increasing levels of both anxiety and depressive symptoms. Compared with those who reported minimal anxiety, participants reporting mild anxiety were more likely to experience poor sleep quality (aPR = 3.01; 95% CI=2.07 to 4.35), short sleep duration (aPR = 1.35; 95% CI=1.17 to 1.56) and at least one problem sleep problem (aPR=1.41; 95% CI=1.27 to 1.56). Similarly, those reporting moderate anxiety were more likely to experience poor sleep quality (aPR=5.78; 95% CI=3.97 to 8.43), short sleep duration (aPR=1.73; 95% CI=1.47 to 2.04) and at least one problem sleep problem (aPR=1.56; 95% CI=1.39 to 1.75) compared with those reporting minimal anxiety. Similarly, and corresponding to the dose–response relationship between anxiety and sleep health outcomes, those reporting severe anxiety were the most likely to experience poor sleep quality (aPR = 8.954; 95% CI = 6.12 to 13.08), short sleep duration (aPR = 2.23; 95% CI=1.91 to 2.61) and at least one problem sleep problem (aPR =1.73; 95% CI=1.54 to 1.95). P-trend <0.001 for all sleep outcomes.

Table 2.

Multivariable association (aPRs)† between anxiety, depression and poor sleep health

	Poor sleep quality	Short sleep duration (≤7 hours)	Sleep problems
	aPR (95% CI)	aPR (95% CI)	aPR (95% CI)
Anxiety
Minimal anxiety (0–4)	Referent	Referent	Referent
Mild (5–9)	3.01 (2.07 to 4.35)**	1.35 (1.17 to 1.56)**	1.41 (1.27 to 1.56)**
Moderate (10–14)	5.78 (3.97 to 8.43)**	1.73 (1.47 to 2.04)**	1.56 (1.39 to 1.75)**
Severe (15–21)	8.95 (6.12 to 13.08)**	2.23 (1.91 to 2.61)**	1.73 (1.54 to 1.95)**
P for trend	<0.001	<0.001	<0.001
Depression
Quartile 1 (0–3)	Referent	Referent	Referent
Quartile 2 (4–6)	2.19 (1.12 to 4.27)*	1.21 (1.00 to 1.47)*	1.40 (1.20 to 1.63)**
Quartile 3 (7–11)	5.27 (2.89 to 9.61)**	1.41 (1.17 to 1.69)**	1.62 (1.40 to 1.87)**
Quartile 4 (12–27)	11.82 (6.64 to 21.04)**	1.87 (1.58 to 2.22)**	1.90 (1.66 to 2.18)**
P for trend	<0.001	<0.001	<0.001

*P<0.05; **p<0.001

†Adjusted for age, gender, region, employment and physical activity

aPR, adjusted prevalence ratio.

Depressive symptoms were also associated with poor sleep health outcomes. This association also demonstrated dose–response relationship. As compared with scoring in the first quartile, scoring in the second, third and fourth quartile was significantly associated with poor sleep quality (aPRs=2.19, 5.27 and 11.82, respectively), short sleep duration (aPRs=1.21, 1.41 and 1.87, respectively) and experiencing at least one sleep problem (aPRs=1.40, 1.62 and 1.90, respectively).

Discussion

This study is the first to empirically explore both mental health and sleep health measures during nationwide lockdown in response to the COVID-19 pandemic. It is also the first study to evaluate associations between mental health and sleep health in Jordan, and one of few studies to address the relationship between these measures among a severely understudied population; Middle Eastern adults. To the best of our knowledge, there is only one other study that has assessed sleep health in Jordan, which reported that poor sleep health, including a high risk of obstructive sleep apnoea, snoring and daytime sleepiness, was common among Jordanians attending primary care clinics.54

In our study, the majority of participants reported having experienced mild (33.8%), moderate (12.9%) or severe (6.3%) levels of anxiety during lockdown, and nearly half of respondents reported depressive symptoms during lockdown. Similarly, over 60% of participants reported having experienced at least one sleep problem in the last week, and nearly half reported having had short sleep duration. In addition, we found that increased levels of reported anxiety or depression were both significantly associated with an increase in poor sleep health outcomes among Jordanians during lockdown in response to the COVID-19 pandemic.

Our findings that increased levels of self-reported anxiety or depression were significantly associated with an increase in poor sleep health outcomes can potentially be explained by the relationship between mental health and sleep health. The pathway by which depression alters sleep is thought to be through the loss of deep, slow-wave sleep and an increase in nocturnal arousal. The combination of these two effects contributes to a decrease in non-REM sleep, which may subsequently result in reduced REM sleep latency.55 Several studies have shown the association between depression and the disruption of REM sleep.56 57 Furthermore, the cause of depression is most commonly attributed to the dysregulation of monoamines, such as serotonin, dopamine, norepinephrine and dopamine. An individual’s transition to REM sleep is typically accompanied by a rapid decrease in these monoamines,58 and such dysregulation may be associated with the disruption of REM sleep and the subsequent onset of depressive symptoms. Research has also demonstrated that depression is correlated with increased inflammatory markers and that depressive symptoms can be reduced by decreasing that inflammation.59 As such, sleep loss has been associated with the increased production of inflammatory markers, such as C reactive protein and interleukins.60 Although the exact mechanism is not fully understood, there appears to be a relationship between sleep disturbance, inflammation and depression.59 61 Another potential pathway by which depression and sleep disturbances interact is through alternations in one’s circadian rhythm. An individual’s circadian rhythm is crucial to maintaining the sleep-wake cycle, and it has been observed that depression disrupts circadian rhythm.62

Overall, our findings suggest the possible impact that economic, social or health-related circumstances caused by nationwide lockdown can have in exacerbating anxiety, depressive symptoms and poor sleep health among respondents in Jordan. Particular to the context of lockdown in response to the COVID-19 pandemic, the Jordanian government did not provide economic support, financial incentives (eg, stimulus) or loan forgiveness schemes to support individuals who may have lost significant portions of their income or faced additional financial obligations as a result of lockdown and their inability to engage with their given occupations consistently.3 As a result, these economic circumstances may have contributed to increased anxiety, reported depressive symptoms and poor sleep health. While it is expected that these economic circumstances would affect adult men in particular because they are typically considered financial providers for their families in the context of Jordanian culture,63 reported rates of anxiety, depressive symptoms and poor sleep health were comparable between male and female respondents. This is the case despite that within Jordan, a larger proportion of men work outside the home than women. That being said, because childcare, elderly care and housework are typically women’s responsibilities in this context, the lockdown restrictions would be expected to disproportionately affect women’s economic resilience, mental well-being and sleep health, especially given rising levels of domestic violence and reduced access to sexual and reproductive health services during lockdown.64 65 It should be noted that studies have shown that men tend to have a higher prevalence of sleep disorders such as obstructive sleep apnoea, other studies have found that women are more likely than men to report an increased burden of depressive symptoms as a result of poor sleep health.66

Other factors that have been found to affect sleep health and mental health outcomes that are also expected to be relevant or exacerbated during lockdown situations include tobacco or khat use, atypical work schedules and violent or poor familial environments in households.67–71 The increased recreational screen time during lockdown spent watching television, using a computer or using smartphones and the reality of isolation with limited social contact would also be expected to contribute to poor mental health outcomes, including anxiety and depressive symptoms, found in our study.71–73 In addition, unemployment has been noted to be associated with diminished mental health and is negatively correlated with sleep health measures.74 Approximately 25% of unemployed or retired respondents in our study reported having experienced at least one sleep problem in the last week and short sleep duration. These risk factors are expected to work in tandem and are expected to expose underlying vulnerabilities that also contribute to poor mental health and sleep health.74–76

When evaluating the potential consequences of lockdown during a pandemic such as COVID-19, it is critical to consider how lockdown may predispose individuals to risk factors that impact mental health and sleep health. Poor sleep habits, anxiety and depression are all recognised as affecting overall health and contributing to a number of risk factors for cardiovascular disease, obesity, hypertension, hyperlipidaemia and diabetes, among other chronic conditions that are increasingly prevalent in Jordan.77 Similarly, poor mental health and sleep health are also found to be associated with excessive alcohol use and substance use.6 78 Given that poor sleep habits, anxiety and depression are also associated with decreased immune responsiveness, it is especially important to consider how the impacts of nationwide lockdown on mental health and sleep health may make individuals particularly vulnerable to SARS-CoV-2, the causative agent of COVID-19, or other highly infectious pathogens.79

The study findings, the lack of interventions in place to support the population during strict lockdowns (eg, financial incentives, mental health resources), and the absence of discourse to address poor sleep health or mental health as a result of nationwide lockdown highlight a gap in policymaking and planning during health emergencies and disease outbreaks in Jordan and likely in other countries. While the impact of lockdown on mental health and sleep health is not expected to be unique to Jordan, future research should focus on further elucidating the determinants of mental health and poor sleep health during lockdown and exploring the potential interactive impacts of specific risk factors that are exacerbated during lockdown on mental health and sleep health and their subsequent effects on susceptibility to disease. Additionally, the mechanism(s) in which such association occurs should be investigated. Future attention should also focus on articulating policies and designing interventions to address identified determinants and risk factors and to uphold an international standard of individuals’ right to health,80 especially for vulnerable and disadvantaged populations.

Limitations

This study’s methodology is subject to several limitations. First, the sample population only includes individuals using one social media platform, which introduces self-selection and volunteer bias and limits the generalisability of this study. Second, the information collected using the online survey includes exclusively self-reported data. As a result, responses, especially those measuring sleep health and mental health, can be implicated with decreasing the reliability and/or the validity of the study findings. Third, because our analysis did not adjust for additional confounding factors, such as substance use, education and marital status, residual confounding may have been introduced. However, we note that we used a limited survey to increase the survey completion rate. Finally, given that this study uses a cross-sectional survey design, it cannot be used to analyse mental health and sleep health measures over an extended period of time. Consequently, causal inference is limited.

Conclusions

This study provides evidence of reported anxiety and depressive symptoms and their association with poor sleep health outcomes during lockdown in Jordan in the face of the COVID-19 pandemic. Our findings draw attention to the potential negative consequences of lockdown and their impact on sleep health, emphasising the need for public health professionals and governments to monitor health profiles during lockdown and to create interventions aimed at improving sleep health and well-being. More attention is required to investigate the impacts of lockdown in exacerbating risk factors for poor mental health and sleep health, and future interventions and policies should be tailored towards addressing identified risk factors and improving health outcomes in the context of a nationwide lockdown.