Sleep and quality of life in healthy people and people with depression

Abstract

Introduction All human beings require qualitatively and quantitatively good sleep, quality of sleep in terms of sound sleep and quantity in terms of sufficient duration. However, both quality and quantity of sleep in individual cases may be sub-optimal due to several factors related to physical health, mental health and sociological aspects. Several studies have been conducted to examine the effect of these factors on sleep quality and quantity. One of the less studied and important aspects is the effect of depression on temporal sleep quality and quantity. The relationship between sleep and depression is complex and maybe bi-directional. Sleep disturbances resulting from depression or vice versa can impact on the quality of life. A recognition of this importance prompted this research. As the first step towards assessment of this research, the methodology and the variables to be included, a review of available literature on various aspects of sleep quality and quantity was undertaken. The review provided an overview of most aspects of sleep and ranged from the medical definition of sleep, components of quality and quantity, measurement methods and factors affecting sleep. The methods and results of many studies were synthesised to obtain a cohesive picture. In the review process, depression was one of the factors that was considered along with other factors. Studies comparing sleep and quality of life characteristics between healthy and depressed groups were scarce. To study the differences in the sleep and quality of life characteristics between healthy and depressed groups was identified as the research gap to be addressed. It is well-recognised that healthy and depressed individuals differ in their mood state and other psychological health factors. The mood state can impact sleep parameters in different ways. Life quality is directly influenced by physical and psychosocial aspects of life and may contain as many as eight dimensions. It is clear that any one or more of the components of life quality is affected in more than one way if sleep is disturbed, especially, in depressed individuals. This is a matter worth detailed study and was included in this research. Therefore, this thesis explored qualitative and quantitative variables of sleep and life quality using scientifically validated methods. The thesis examined the following research questions: What are the differences between the temporal sleep patterns of healthy and depressed groups? (Chapter 4); What are the differences in the periodicity of sleep duration between healthy and depressed groups? (Chapter 5); and how does the relationship between quality of life and sleep compare between healthy and depressed groups? (Chapter 6). In chapter 7, the use of EEG spectral power to differentiate healthy and depressed groups more effectively has been examined. What are the elements of light therapy that contribute to successful treatment of depression? Although this question was raised, the study did not proceed as a similar clinical trial had already begun within the University. The completed comprehensive review of literature on all aspects of light therapy is published and presented in Chapter 9. Methods The research utilised a quantitative methodology to compare the differences between the sleep and quality of life characteristics of healthy and depressed groups. Objective sleep parameters were measured using the Actiwatch 2 (AW2) and sleep EEG. The subjective quality of sleep was measured using the Pittsburgh Sleep Quality Index (PSQI). The 8-dimensional Assessment of Quality of Life instrument (AQoL-8D) was applied to assess life quality on a group of 20 healthy and 20 depressed individuals. A Quick Inventory of Depressive Symptomatology (QIDS)-16 and Depressive Anxiety Stress Scales (DASS-D, DASS-S and DASS-S) were also administered to participants. The sleep and quality of life data were collected over a period of 4 weeks. Summary statistics and multivariate analysis were conducted. Significance of differences in the mean scores of variables between healthy and depressed groups were tested using t-tests. Multiple linear regression analyses to identify predictors of sleep, and the Cosinor analysis to measure sleep cycle periodicities were performed. Cluster analysis was done to group the temporal characteristics of sleep variables into healthy and depressed groups. A discrete time-frequency distribution definition method was used to calculate the average power spectra for the right and left brain hemispheres using MATLAB R2009 and its wavelet toolbox (MathWorks Inc., Natick, MA). The right-left asymmetry was calculated as the difference in the voltage between the Right and Left sides for each frequency band. All data were used to compare the EEG power for the different frequency bands between healthy participants and those with depression. Results and Conclusions Differences between the temporal sleep patterns of healthy and depressed groups were identified in Chapter 4. The depressed group had significantly higher levels of depression, stress and anxiety. Their level of physical activity was at a considerably lower level. Moreover, depressed people slept more (longer total sleep time) compared to healthy people. Association of both lower and higher sleep duration with depression are noted according to the American Psychiatric Association's 2013 update to the Diagnostic and Statistical Manual (DSM-5) suggesting that future research should aim to explore the differences in physical and psychological characteristics of short versus long sleepers who have depression. Delayed sleep onset was significantly correlated with anxiety and depression in the depressed group. Delayed sleep onset was also significantly correlated with activity levels of the depressed group. The positive association between activity level and SOL was anomalous, and did not reflect the expected pattern seen in healthy individuals. Cluster analysis revealed the potential of using the sleep variables of total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL) and wake after sleep onset (WASO) as predictors of depression when the sample size is large. The differences between the periodicity of sleep duration between healthy and depressed groups were reported in Chapter 5. The Cosinor analysis highlighted that the variability in sleep duration between nights was in the form of a cosine wave over time. The sleep parameters were more variable in the depressed group compared to the healthy group. High stress as measured by the depression, stress and anxiety scores (DASS) was associated with irregular total sleep time incurred by healthy individuals, whereas higher stress was noted among depressed individuals with the number of nights/days farther away from the longest night/day sleep (i.e. higher acrophase). Thus, healthy and depressed groups were differentiated by the effect of stress on total sleep time in the healthy group and how many nights/days away from their sleep peaks in the depressed group. The associations between quality of life and sleep in both the healthy and depressed groups were examined in Chapter 6. There were significant differences between depressed and healthy participants in the DASS scores, depressive symptoms (QIDS), sleep quality (PSQI), and all dimensions of AQoL-8D. The correlations between PSQI and the dimensions of AQoL-8D namely, independent living, happiness, self-worth, and quality of sleep were stronger in depressed people compared to healthy people with the exclusion of the association between PSQI and dimensions of mental health, relationships, pain, functioning of senses and coping and PSQI, which was similar or weaker in the depressed groups. Regression analysis of subjective sleep quality (PSQI) found mental health to be the only significant predictor of quality of sleep in healthy people, and happiness to be the only significant predictor of quality of sleep in depressed people. For objective sleep data, however, no quality of life dimensions were significant predictors of TST in both groups. Self-worth predicted three sleep variables: SE, SOL and WASO for the healthy group. Coping predicted SOL in the depressed group. The results of EEG studies described in chapter 7 failed to show any difference between depressed and healthy group, except for the delta frequency band which distinguished the groups. The systematic review, Chapter 9, examined the properties of light therapy: light specification, dose, timing and delivery that contribute to the effectiveness of light exposure based on the mood scores in major depressive disorder. The findings indicated that exposure duration between 30 min to 2 h per day, intensity range between 176 to 10,000 lux, in any of blue, green or white light colour and exposure during morning or evening mostly translated to a positive change in mood effects in people with major depressive disorders. Additionally, it was found that factors such as anti-depressant medication use, depression episodes and severity, natural light exposure and sleep deprivation may confound the effects of light therapy. Overall, it can be concluded from this research that, depression has a significant impact on both sleep and quality of life characteristics. This work has been successful in quantifying the association between depression, sleep and quality of life characteristics. The temporal characteristics of sleep variables may potentially be used to predict depression. This insight may be used to predict early onset of depression, which may be translated to better quality of life outcomes with early interventions, although more research is needed in the future.