Sleep hygiene mediates the association between sleep quality and symptoms of fatigue, anxiety and depression in prostate cancer patients

ABSTRACT

Introduction

Prostate cancer (PCa) treatment impairs sleep and psychological well-being. We aim to determine if sleep hygiene mediates the relationship between sleep quality, fatigue, anxiety and depression in PCa patients.

Methods

Fifty-one participants completed questionnaires on sleep, sleep hygiene and psychological well-being, and one-week sleep-wake measurement using actigraphy.

Results

Over 25% of participants frequently got out of bed at inconsistent times, used alcohol/tobacco/caffeine close to bed time, and used bed for activities other than sleeping or sex. Close to 40% frequently engaged in multiple poor sleep hygiene. Feeling stressed, angry, upset, or nervous while in bed partially mediated the relationships between insomnia symptoms and anxiety or depressive symptoms, and fully mediated the associations between: (1) wake after sleep onset (WASO) and fatigue symptoms, (2) insomnia symptoms and fatigue symptoms, and (3) WASO and depressive symptoms. Thinking, planning, or worrying while in bed partially mediated the relationships between number of awakening or insomnia symptoms and anxiety symptoms, and fully mediated the association between WASO and fatigue symptoms. Taking long daytime naps partially mediated the relationship between sleepiness and fatigue symptoms.

Conclusion

Sleep hygiene education may help PCa patients avoid behaviors that worsen their sleep and psychological well-being.

KEYWORDS:

• Prostate cancer
• sleep
• fatigue symptoms
• depressive symptoms
• anxiety symptoms

Introduction

Common treatments for prostate cancer (PCa) include the surgical removal of the prostate (prostatectomy), radiation therapy and androgen deprivation therapy (ADT) [1]. These treatments, however, may increase the risk of developing insomnia symptoms [2–6]. In previous studies, up to 60% of PCa patients reported insomnia symptoms [7], with some research suggesting that 31% experience moderate-to-severe insomnia symptoms [2]. Furthermore, Savard et al. showed that 29% of post-prostatectomy patients [6] and 42% of patients who received ADT as an adjuvant therapy to radiation therapy [4] had insomnia symptoms. Given the prevalence of insomnia symptoms in men with PCa, more research is needed to understand the factors that are associated with its presence and severity.

Insomnia symptoms are associated with a reduction in patients’ quality of life [3,7] and may be due to various factors. For example, ADT reduces gonadal hormone levels in men, and is known to worsen insomnia symptoms in PCa patients (2013). Furthermore, PCa patients on ADT have more severe insomnia symptoms than ADT-naïve patients, as early as at 6 months after treatment onset [8]. The same study also indicated that patients on ADT had longer periods of wake after sleep onset (WASO).

Sleep in PCa patients is a complex issue and is associated with many psychological and lifestyle factors. For example, insomnia symptoms are associated with worse daytime sleepiness, fatigue, anxiety, depressive symptoms, and sexual dysfunction in PCa patients [2,3,7]. In addition, PCa patients with worse insomnia symptoms more frequently show certain sleep-related habits, such as going to bed while distressed, or worrying while in bed [7].

Sleep hygiene includes lifestyle or behaviors which may potentially affect sleep [9]. Sleep hygiene education is a component of cognitive behavioral therapy (CBT), which also included sleep restriction, stimulus control, and cognitive restructuring [10]. However, changing sleep hygiene alone may not be sufficient to improve sleep. Considering that many PCa patients have treatment side effects (e.g. hot flashes, urinary symptoms), those side effects may also need to be treated in addition to CBT. PCa patients, however, may benefit from receiving sleep hygiene education as a pre-emptive strategy to lower the likelihood of developing insomnia or as a first-step in a stepped-care approach to managing sleep-related disturbances.

In the current study, we aim to: (1) describe sleep hygiene in men with PCa, (2) determine how sleep hygiene correlates with sleep and quality of life measures, and (3) investigate if sleep hygiene mediates the relationships between sleep measures and quality of life measures. Data from this study should help clinicians guide patients on how to avoid behaviors which may worsen their sleep and quality of life.

Methods

Using a cross-sectional approach, we recruited 52 PCa patients from the Otago region in Aotearoa New Zealand. One participant was removed from the analysis due to missing data (he did not return the actigraph), bringing the total for analysis to 51 patients. Patients were recruited using advertisements in local newspapers and promotion at a local PCa support group, as well as recruitment from clinicians who treat PCa in Dunedin (SC, AA). The recruitment took place over three periods from July 2019 to August 2020. The eligibility criteria included diagnosis of PCa, age over 18, fluency in English, not on chemotherapy, and not experiencing bone pain due to cancer metastasis. During the recruitment period, New Zealand went into a lockdown period for four weeks in March to April 2020. No recruitment occurred during this period. The study protocol was approved by the University of Otago Human Ethics Committee (Health) (H18/078).

Demographics

Standard demographic information on participant’s age, income, comorbidities, ethnicity, education, relationship status, job status and PCa treatment history was self-reported.

Objective sleep-wake patterns

The participants were given an Actiwatch Spectrum PRO (BMedical Pty Ltd) for recording sleep-wake parameters based on their wrist movement. The algorithm in its analysis software (Philips Actiware 6.0.9) was used in conjunction with the sleep diary data [11] to establish the rest periods for seven consecutive days. The objective parameters produced included sleep onset latency, total sleep duration, sleep efficiency, number of awakenings, and time spent awake after sleep onset (WASO).

Insomnia symptoms

The Insomnia Severity Index (ISI) [12] was used to assess the presence of insomnia associated symptoms. The ISI consists of seven items, and each item was measured on a scale of 0-4, with a higher score indicating worse insomnia severity. The internal consistency in our sample was 0.87.

Sleep hygiene index

The Sleep Hygiene Index (SHI) [9] was used to assess how frequently the participant engaged in 13 various behaviors that may influence their sleep quality. Each item can be rated from 0 (never) to 4 (always); with a higher score indicating worse sleep hygiene. Individual items of this scale are referred to SHI-1 to SHI-13 in this paper. Some of the items are linked to psychological distress (e.g. SHI-8 – going to bed feeling stressed, angry, upset, or nervous; SHI-13 – thinking, planning or worrying while in bed). Others are related to bedroom environment (e.g. SHI-10 – sleeping on an uncomfortable bed, SHI-11 – sleeping in an uncomfortable bedroom). Furthermore, there are sleep-related habits such as SHI-1 (taking daytime naps lasting two or more hours), SHI-2 (going to bed at different times from day to day), or SHI- 3 (getting out of bed at different times from day to day). The internal consistency in our sample was 0.67.

Epworth sleepiness scale

Sleepiness was measured by the Epworth Sleepiness Scale (ESS) [13] which asks participants to rate their likelihood of falling asleep in different daytime situations. Each item can be rated on a scale from 0 (would never dose) to 3 (high chance of dozing), with a higher score indicating a higher chance of dozing. The internal consistency in our sample was 0.77.

Anxiety symptoms

Generalised Anxiety Disorder (GAD7) screening questionnaire [14] was used to assess participants’ anxiety symptoms. This scale consists of questions about the frequency of seven symptoms related to anxiety during the last two weeks. Each item can be rated from 0 (not at all) to 3 (several days) with a higher total score indicating more severe anxious symptoms. The internal consistency in our sample was 0.93.

Depressive symptoms

The Center for Epidemiologic Studies Depression (CESD) scale [15] was used to measure depressive symptoms of participants. This questionnaire asks the frequency of 20 depressive symptoms within the last week. Each question was measured on a scale of 0 (rarely or none of the time (less than 1 d)) to 3 (most or all of the time (5-7 days)) with a higher total score indicating more severe depressive symptoms. The internal consistency in our sample was 0.78.

Fatigue symptoms

The Brief Fatigue Inventory (BFI) [16] consists of 9 items for assessing participants’ fatigue levels. Each item was rated on a scale of 0–10, with a higher score indicating a higher level of fatigue or interference due to fatigue. The internal consistency in our sample was 0.90.

Pain

Graded Chronic Pain Scale (GCPS) was used to assess pain symptoms [17]. This is a 7-item tool measuring self-reported levels of pain intensity (3 items) and pain interference (1 item) in daily activities and how much the pain changed (2 items) the ability to take part in work, recreational, social and family activities. An additional item recorded the number of days in disability due to pain. The 3 subscale scores (pain intensity, disability score, and the disability points score) were used to classify the pain symptoms experienced by participants.

Hormonal analyses

Participants were advised to have their blood sample collection before 10 am at the Southern Community Laboratory in the Otago and Southland areas. They were collected before 10 am because testosterone and cortisol levels are high in the morning [18]. Participants were advised to have blood sample collection within a week of starting sleep-wake recording.

Blood samples were assayed for testosterone, estradiol, and cortisol according to standard facility protocol. Testosterone levels were assessed using liquid chromatography tandem mass spectrometry. Estradiol levels were measured using the Elecsys Estradiol III immunoassay kit. Cortisol levels were measured using Elecsys Cortisol II immunoassay. The intra-assay coefficient of variations (CV) ranged from 1.9% to 2.4% for the testosterone assay, and the inter-assay CV was 2.2%. The intra-assay CV for the estradiol assay ranged from 1.9 to 7.6%, and cortisol was 2.9%. The inter-assay CVs for the estradiol and cortisol assays were 4.8% and 2.9% respectively.

Data analyses

SPSS software (IBM, version 25) was used for data analysis. Demographic data were summarized using descriptive statistics. The frequency of each sleep hygiene is summarized using descriptive statistics. Pearson’s correlation was used to determine the relationship between sleep hygiene with actigraphy data as well as quality of life measures. Significant findings from these correlations were used to guide variable selection in the mediation analyses. Mediation analyses were conducted, using the method outlined in Baron and Kenny [19] followed by the Sobel test. No covariates were included because of the small sample size. Sobel tests were conducted online at http://quantpsy.org/sobel/sobel.htm. P < .05 was considered significant.

Results

Demographic

Table 1 describes the demographic characteristics of our participants. Participants (n = 51) were 73.1 ± 5.8 (95% CI 71.5–74.7; ranging from 61 to 87) years old. The majority were NZ European (96.1%), in a relationship (88.2%), retired (68.0%), had a university education (45.1%), and had a combined household income of >$50,000 (56.0%). Three most common treatments were prostatectomy (35.4%), external beam radiation (56.3%), and ADT (34.7%). The average ADT duration was 11.9 ± 9.2 months (ranging from 2 to 36 months). The most commonly reported comorbidities were heart attack (20.4%), circulation problems (20.4%), breathing problems (10.2%), and stomach problems (10.2%). The majority had no (41.2%) or low intensity (41.2%) pain.

Table 1. Sociodemographic characteristics of participants.

Variables	N (%)	M (SD)
Age		73.1 (5.8)
Ethnicity
NZ European	49 (96.1%)
Māori	2 (3.9%)
In a relationship	45 (88.2%)
Employment
Full time	7 (14.0%)
Part time	8 (16.0%)
Looking for a job	1 (2.0%)
Retired	34 (68.0%)
Education
Some secondary school or polytechnic	10 (19.6%)
Secondary school or polytechnic graduate	18 (35.3%)
Some university	5 (9.8%)
Undergraduate/bachelors	5 (9.8%)
Graduate or professional degree	13 (25.5%)
Combined household income
$10,000 - $30,000	8 (16.0%)
$30,001 - $50,000	14 (28.0%)
$50,000- $100,000	20 (40.0%)
More than $100,000	8 (16.0%)
Treatment history
ADT	17 (34.7%)
Prostatectomy	17 (35.4%)
External beam radiation	27 (56.3%)
Brachytherapy	2 (4.2%)
Active surveillance	10 (20.4%)
Orchiectomy	1 (2.1%)
Other	4 (8.3%)
Comorbidities
Heart attack	10 (20.4%)
Circulation problems	10 (20.4%)
Stroke	3 (6.1%)
Amputation	1 (2.0%)
Breathing problems	5 (10.2%)
Stomach problems	5 (10.2%)
Kidney	3 (6.1%)
Depression	4 (8.2%)
Alcoholism	3 (6.1%)
Drug problems	2 (4.1%)
Pain characteristics
No pain	21 (41.2%)
Low disability – low intensity	21 (41.2%)
Low disability – high intensity	7 (13.7%)
High disability – moderately limiting	2 (3.9%)
High disability – severely limiting	0

In this study, 40 (80%) participants had their blood collected before 10 am. Twelve participants had testosterone levels under the normal range (median = .5 (95% CI 0.3–1.7; ranging from .17 to 3.3) nmol/L) and the remaining participants had a normal levels of testosterone (median = 12.8 (95% CI 12.4–15.7), ranging from 7.2–27.6 nmol/L). As shown on Supplementary Table 1, there was no significant difference in their bed time, get up time, and time from getting up to the blood collection time. Androgen-deprived participants also had significantly lower estradiol levels (U = 32.5, P < .001) but comparable cortisol levels to participants with normal testosterone levels. All patient-reported outcomes and actigraphy-derived parameters were comparable regardless of whether their testosterone levels were within or below normal levels. Similarly, all patient-reported outcomes and actigraphy-derived parameters were similar among participants who were recruited before and after the COVID-19 lockdown period.

Sleep hygiene

As shown on Figure 1, over 25% of participants in this sample frequently engaged in SHI-3 (get out of bed at different times from day to day), SHI-6 (using alcohol, tobacco, or caffeine within 4 h of going to bed or after going to bed), and SHI-9 (using bed for things other than sleeping or sex). Between 10-20% frequently engaged in SHI-2 (going to bed at different times from day to day), SHI-7 (doing something that may wake me up before bedtime), and SHI-13 (thinking, planning, or worrying while in bed). Less than 5% of participants engaged in the remaining SHI behaviors. Furthermore, Figure 2 shows that 39.2% of participants frequently did multiple poor sleep hygiene.

Figure 1. The proportions of participants who did various sleep-related habits at different frequencies. Numbers 1–13 on the x-axis represent the 13 sleep hygiene behaviors as described in the Sleep Hygiene Index [9]. Over 25% of participants frequently engaged in SHI-3, SHI-6, and SHI-9. Around 10-20% frequently engaged in SHI-2, SHI-7, and SHI-13. Less than 5% of participants engaged in the remaining sleep hygiene.

Figure 2. The proportions of participants with different numbers of poor sleep hygiene behaviors (i.e. those who frequently or always engaged in poor sleep hygiene). In this sample, 25.5% did not frequently engage in poor sleep hygiene, 35.3% frequently did one poor sleep hygiene, and 39.2% frequently did multiple poor sleep hygiene.

Correlates for sleep hygiene

Table 2 shows how sleep hygiene correlated with actigraphy-derived sleep measures, subjective sleep measures, and symptoms of fatigue, anxiety and depression. The total score of the SHI did not correlate with any measures, but some of the specific SHI item had significant correlations with certain variables. For example, SHI-1 (taking daytime naps lasting two or more hours) positively correlated with more sleepiness and fatigue. In addition, SHI-4 (exercising to the point of sweating within 1 h of going to bed) positively correlated with more fatigue, whereas SHI-5 (stay in bed longer than I should two or three times a week) positively correlated with longer total sleep time. Both SHI-8 (feeling stressed, angry, upset, or nervous while in bed) and SHI-13 (thinking, planning, or worrying while in bed) positively correlated with more WASO and symptoms of insomnia, fatigue, anxiety and depression. Furthermore, SHI-9 (using bed for things other than sleeping or sex) negatively correlated with depressive symptoms, but SHI-12 (doing important work before bedtime) positively correlated with anxiety symptoms. Lastly, SHI-11 (sleeping in an uncomfortable bedroom) positively correlated with longer total sleep time and more awakening.

Table 2. Correlation coefficients for the relationships between sleep hygiene and actigraphy data as well as self-report symptoms of insomnia, sleepiness, fatigue, anxiety and depression in PCa patients.

	Total sleep time	Sleep onset latency	Sleep efficiency	WASO	Number of awakening	ISI	ESS	BFI	GAD7	CESD
SHI score	0.14	0.12	−0.05	−0.03	0.07	0.13	0.17	0.244	0.179	0.173
SHI items
SHI-1	0.06	0.21	−0.01	0.00	−0.16	0.26	.32*	.37^	0.11	0.31
SHI-2	0.2	−0.08	0.08	−0.13	0.02	−0.12	0.23	0.26	−0.08	−0.02
SHI-3	0.23	0.23	−0.07	−0.09	0.02	0.03	−0.04	0.09	−0.04	0.02
SHI-4	−0.02	−0.15	0.11	0.03	0.18	−0.07	0.05	.28*	0.17	0.08
SHI-5	.31*	0.27	−0.08	−0.13	−0.13	−0.24	0.09	−0.02	−0.19	−0.12
SHI-6	0.27	−0.05	0.05	−0.02	0.23	−0.05	0.01	0.02	0.12	0.09
SHI-7	−0.13	0.05	−0.03	−0.07	−0.15	0.02	−0.06	−0.13	−0.02	−0.03
SHI-8	−0.16	−0.08	−0.18	.34*	0.26	.41^	0.27	.46^#	.59^#	.56^#
SHI-9	−0.12	0.22	−0.03	−0.2	−0.22	0.06	−0.02	−0.24	−0.28	-.29*
SHI-10	−0.12	0.05	−0.14	−0.07	0.13	−0.05	0.11	−0.12	−0.07	−0.05
SHI-11	.53^	0.01	−0.05	0.19	.36*	−0.08	0	0.27	0.06	0.18
SHI-12	−0.2	−0.16	−0.12	−0.15	0.07	0.06	−0.02	0.1	.37^	0.15
SHI-13	−0.08	0.03	−0.15	.31*	0.11	.51^#	0.17	.41^	.57^#	.42^

*Significant correlations, P < .05; ^P < .01, ^#P < .001

CES-D = Center for Epidemiologic Studies Depression Scale, ISI = Insomnia Severity Index, ESS = Epworth Sleepiness Scale, GAD7 = General Anxiety Disorders 7

SHI = Sleep Hygiene Index; BFI = Brief Fatigue Inventory; WASO = wakefulness after sleep­ onset

Mediation analyses for fatigue symptoms

As displayed on Table 3, the association between WASO and fatigue symptoms was mediated by sleep hygiene. The total effect of WASO on fatigue symptoms was .018 (95% CI: .001, .035). The direct effect of WASO on fatigue symptoms was .010 (95% CI: −.007, .026) after adjusting for going to bed feeling stressed, angry, upset, or nervous (SHI-8), and .011 (95% CI: −.005, .028) after adjusting for thinking, planning, or worrying in bed (SHI-13). The indirect effect of WASO on fatigue symptoms through going to bed feeling stressed, angry, upset, or nervous was .009 (95% CI: −.0004, .018) and through thinking, planning, or worrying in bed was .007 (95% CI: −.001, .015).

Table 3. Mediation analyses for sleep measures and sleep hygiene on fatigue, anxiety and depressive symptoms.

Variable	B	SE	P value	95% CI
				Lower	Upper
Effects on fatigue symptoms
WASO → SHI8 → Fatigue symptoms
Effect of WASO on SHI8	.011	.004	< .05	.002	.020
Effect of SHI8 on fatigue symptoms	.775	.254	< .01	.263	1.287
Total effect of WASO	.018	.008	< .05	.001	.035
Direct effect	.010	.008	.252	−.007	.026
Indirect effect	.009	.004	< .05	−.0004	.018
WASO → SHI13 → Fatigue symptoms
Effect of WASO on SHI13	.012	.005	< .05	.001	.022
Effect of SHI13 on fatigue symptoms	.599	.214	< .01	.168	1.030
Total effect of WASO	.018	.008	< .05	.001	.035
Direct effect	.011	.008	.183	−.005	.028
Indirect effect	.007	.004	.007	−.001	.015
Insomnia symptoms → SHI8 → Fatigue symptoms
Effect of insomnia symptoms on SHI8	.071	.022	< .01	.026	.116
Effect of SHI8 on fatigue symptoms	.729	.275	< .05	.175	1.282
Total effect of insomnia symptoms	.114	.044	< .05	.025	.203
Direct effect	.063	.046	.179	−.030	.155
Indirect effect	.052	.025	< .05	.001	.103
Sleepiness → SHI1 → Fatigue symptoms
Effect of sleepiness on SHI1	.083	.037	< .05	.008	.157
Effect of SHI1 on fatigue symptoms	.421	.209	< .05	.001	.842
Total effect of sleepiness	.179	.053	< .01	.072	.287
Direct effect	.144	.055	< .05	.035	.254
Effects on anxiety symptoms
Insomnia symptoms → SHI8 → Anxiety symptoms
Effect of insomnia symptoms on SHI8	.071	.022	< .01	.026	.116
Effect of SHI8 on Anxiety symptoms	2.166	.112	< .01	.825	3.506
Total effect of insomnia symptoms	.471	.109	< .001	.252	.691
Direct effect	.298	.112	< .05	.071	.524
Insomnia symptoms → SHI13 → Anxiety symptoms
Effect of insomnia symptoms on SHI13	.110	.024	< .001	.061	.159
Effect of SHI13 on anxiety symptoms	1.717	.599	< .01	.508	2.926
Total effect of insomnia symptoms	.471	.109	< .001	.252	.691
Direct effect	.281	.121	< .05	.037	.525
Effect on Depressive symptoms
WASO → SHI8 → Depressive symptoms
Effect of WASO on SHI8	.011	.004	< .05	.002	.020
Effect of SHI8 on depressive symptoms	4.514	1.071	< .001	2.355	.6.672
Total effect of WASO	.085	.037	< .05	.009	.160
Direct effect	.037	.034	.276	−.031	.106
Indirect effect	.050	.022	< .05	.001	.093
WASO → SHI13 → Depressive symptoms
Effect of WASO on SHI13	.012	.005	< .05	.001	.022
Effect of SHI13 on depressive symptoms	3.032	.972	< .01	1.074	4.990
Total effect of WASO	.085	.037	< .05	.009	.160
Direct effect	.052	.036	.150	−.020	.124
Indirect effect	.036	.019	.057	.002	.085
Insomnia symptoms → SHI8 → Depressive symptoms
Effect of insomnia symptoms on SHI8	.071	.022	< .01	.026	.116
Effect of SHI8 on depressive symptoms	3.640	.168	< .001	.251	.930
Total effect of insomnia symptoms	.828	.175	< .001	.476	1.181
Direct effect	.590	.168	< .01	.251	.930
Insomnia symptoms → SHI13 → Depressive symptoms
Effect of insomnia symptoms on SHI13	.110	.024	< .001	.061	.159
Effect of SHI13 on depressive symptoms	1.596	1.040	.132	−.502	3.693
Total effect of insomnia symptoms	.828	.175	< .001	.476	1.181
Direct effect	.665	.203	< .01	.256	1.073

Note: Indirect effect was only calculated when there was a full mediation. Only analyses showing full or partial mediation are shown.

SHI1 = taking daytime naps lasting two or more hours. SHI 8 = feeling stressed, angry, upset, or nervous while in bed; SHI13 = thinking, planning, or worrying while in bed.

In addition, going to bed feeling stressed, angry, upset, or nervous mediated the relationship between insomnia symptoms and fatigue symptoms. The total effect of insomnia symptoms on fatigue symptoms was .114 (95% CI: .025, .203). The direct effect of insomnia symptoms on fatigue symptoms was .063 (95% CI: −.030, .155) after adjusting for going to bed feeling stressed, angry, upset, or nervous. The indirect effect of insomnia symptoms on fatigue symptoms through going to bed feeling stressed, angry, upset, or nervous was .052 (95% CI: .001, .103).

Taking long daytime naps (SHI-1) partially mediated the relationship between sleepiness levels and fatigue symptoms. The direct effect of sleepiness levels on fatigue symptoms was .144 (95% CI: −.035, .254) after adjusting for taking long daytime naps.

Mediation analyses for anxiety symptoms

Both going to bed feeling stressed, angry, upset, or nervous and thinking, planning, or worrying in bed partially mediated the relationship between insomnia symptoms and anxiety symptoms. The direct effect of number awakening on anxiety symptoms was .298 (95% CI: .071, .524) after adjusting for going to bed feeling stressed, angry, upset, or nervous, and .281 (95% CI: .037, .525) after adjusting for thinking, planning, or worrying in bed.

Mediation analyses for depressive symptoms

The association between WASO and depressive symptoms was mediated by going to bed feeling stressed, angry, upset, or nervous. The total effect of WASO on depressive symptoms was .085 (95% CI: .009, .160). The direct effect of WASO on depressive symptoms was .037 (95% CI: −.031, .106) after adjusting for going to bed feeling stressed, angry, upset, or nervous, and .052 (95% CI: −.020, .124) after adjusting for thinking, planning, or worrying in bed. The indirect effect of WASO on depressive symptoms through going to bed feeling stressed, angry, upset, or nervous was .050 (95% CI: .001, .093) but the effect through thinking, planning, or worrying in bed was not significant.

Going to bed feeling stressed, angry, upset, or nervous, but not thinking, planning, or worrying in bed partially mediated the relationship between insomnia symptoms and depressive symptoms. The total effect of insomnia symptoms on depressive symptoms was .828 (95% CI: .476, 1.181). The direct effect of insomnia symptoms on depressive symptoms was .590 (95% CI: .251, .930) after adjusting for going to bed feeling stressed, angry, upset, or nervous.

Discussion

In this study, the sleep habits engaged in by over 25% of participants were getting out of bed at inconsistent times, using alcohol/tobacco/caffeine close to bed time or after going to bed, and using bed for activities other than sleeping or sex. In addition, close to 40% reported doing multiple poor sleep hygiene behaviors frequently. Some sleep hygiene also correlated with sleep and quality of life measures. For example, distress or being anxious while in bed correlated with more WASO and more severe symptoms of insomnia, fatigue, anxiety and depression. Furthermore, some sleep hygiene behaviors mediate, either fully or partially, the relationships between sleep, fatigue, and psychological well-being. More specifically, feeling stressed, angry, upset, or nervous while in bed fully mediated the associations: (1) between WASO and fatigue symptoms, (2) between insomnia symptoms and fatigue symptoms, and (3) between WASO and depressive symptoms. Thinking, planning, or worrying while in bed fully mediated the association between WASO and fatigue symptoms. Taking daytime naps partially mediated the relationship between sleepiness and fatigue symptoms. Feeling stressed, angry, upset, or nervous while in bed partially mediated the relationships between insomnia symptoms and anxiety symptoms or depressive symptoms. Thinking, planning, or worrying while in bed partially mediated the relationships between number of awakening or insomnia symptoms and anxiety symptoms. Our findings suggest poor sleep is associated with poor sleep hygiene in men with PCa, and these behaviors are linked to worse quality of life.

Mediating effect of sleep hygiene

Our data indicate the mediating effect of sleep hygiene on the relationship between sleep measures, fatigue, and psychological well-being in PCa patients. This finding suggests that poor sleep (e.g. long WASO, high number of awakening) is related to behaviors men with PCa engage in that worsen their sleep such as worrying or being stressed while in bed. Those behaviors are associated with lower quality of life including higher levels of fatigue, anxiety and depression. This finding stresses the importance of addressing cognitions and behaviors and as key part of comprehensive sleep treatment [10].

Our data support the existing data that behavioral adjustment may potentially improve sleep, fatigue, and psychological well-being in PCa patients. For example, if patients express that they wake up frequently or for a prolonged period of time, clinicians can advise them to avoid using this time to worry and get out of bed if they find themselves awake feeling stressed, angry, upset, or nervous while in bed. This is necessary to avoid conditioning the bed with wakefulness and perpetuating the problems.

Of note, however, sleep hygiene modification is not recommended as a mono-treatment. Patients with insomnia should be offered CBT as a first line treatment for insomnia. This may need to be coupled with other treatment to improve sleep because PCa patients often have treatment side effects which require separate treatment. For example, patients on ADT often experience hot flashes [20], and urinary symptoms are common in patients after prostatectomy and radiotherapy [21]. Thus, clinicians may need to manage these symptoms too, if they are present.

Impacts of ADT

Considering that some patients were on ADT, we compared their data based on testosterone levels. The sleep parameters we measured did not vary based on testosterone levels. These findings are inconsistent with past studies had used the ISI [4,5] and actigraphy [8,22] to compare sleep parameters between patients who were androgen-deprived or not. Insomnia severity, for example, was worse in patients on ADT than those who were not on ADT [4,5]. Furthermore, Gonzalez et al. [8] found that ADT recipients had significantly higher WASO than ADT-naïve participants at 6 months after ADT onset. In addition, Mondal et al. [22] showed that patients on ADT had longer total sleep time, more fragmented sleep and longer nap duration. These discrepancy in findings may be related to differences in sample size and study design. Our study has a smaller sample size than the other studies. Furthermore, most used longitudinal study design, thus they could determine the change in sleep over time after ADT treatment, but we are unable to determine such a change because we used a cross-sectional approach.

Quality of life measures were also comparable regardless of testosterone levels. However, these do not exclude the possibility that ADT increases the risks for fatigue, anxiety and depression, as previously shown in other studies [23–25]. Again, the lack of significant difference in our study may be related to the small sample size, and cross-sectional nature of the study design. Furthermore, the median scores for the symptoms of sleepiness, fatigue, depression and anxiety were all in the no or mild symptoms range.

Limitations

The primary limitation of our study is sample size which may have limited our data analyses. We also did not adjust our correlation or mediation analyses for any variable. In addition, the majority of the sample were New Zealand European, well-educated and of a high socio-economid background. We also did not access the participants’ clinical records because we mainly recruited from the community; thus, the clinical data were based on self-report and we did not collect information on cancer staging, and time since diagnosis or treatment. In addition, we did not screen participants for sleep disorder diagnosis. Actigraphy is also known to underestimate sleep latency and overestimate total sleep time [26], but this would not have impacted our between group comparisons. The use of self-report questionnaire data for some outcomes may have introduced recall bias; however, we used only validated questionnaires to minimize data inaccuracy. Furthermore, due to the cross-sectional design of this study, any causal inference of our findings is limited, and alternate temporal orders in the mediation model are possible. Lastly, the study was also advertised as a sleep study which may have caused some recruitment bias to those who were concerned of their sleep. There is also possible bias that men with better functioning are more likely to participate in our study, especially that their various psychological symptoms were mild.

Conclusion

Our findings show that poor sleep is associated with behaviors that further worsen their sleep, fatigue, and psychological well-being. Considering the risk of developing insomnia symptoms, men may benefit from having a pre-emptive sleep hygiene and sleep management education before starting on PCa treatment. This would equip men with PCa with tools to manage their sleep when their sleep worsen following PCa treatment. As noted above, patients may need to receive additional treatment because PCa treatment can lead to additional side effects which cannot be relieved by sleep hygiene education.

Ethical approval

The study protocol was approved by the University of Otago Human Ethics Committee (Health) (H18/078).

Acknowledgement

We thank the Dunedin prostate cancer support group, the University of Otago’s External Engagement team, and Rachel McLay-Barnes for their assistance with our study recruitment. We thank Roger Barton and his team at the Southern Community Laboratories for assisting in the hormone measurements.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project was supported by a funding from the Department of Anatomy at the University of Otago to Dr. Erik Wibowo.