International Journal of Mental Health & PsychiatryISSN: 2471-4372

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Research Article, Int J Ment Health Psychiatry Vol: 2 Issue: 4

The Effect of Mobile usage on Quality of Sleep and Health Related Quality of Life in Elderly

Wahba HMF1, Walaa W Aly1*, Salma MS Elsaid1 and Randa Ali-Labib2
1Department of Geriatrics and Gerontology, Ain Shams University, Egypt
2Department of Medical Biochemistry, Ain Shams University, Egypt
Corresponding author : Walaa W Aly
Ain Shams University Hospitals, Geriatric and Gerontology department, Abbassea square, Cairo, Egypt
Tel: +201005296077 E-mail: [email protected]
Received: April 28, 2016 Accepted: September 20, 2016 Published: September 24, 2016
Citation: Wahba HMF, Walaa W Aly, Salma MS Elsaid, Randa Ali-Labib (2016) The Effect of Mobile usage on Quality of Sleep and Health Related Quality of Life in Elderly. Int J Ment Health Psychiatry 2:4. doi:10.4172/2471-4372.1000133

Abstract

Objectives: To detect the levels of salivary amylase with mobile usage and its correlation with sleep deprivation and impaired Health related quality of life (HRQL) in a sample of Egyptian elderly. Methodology: This study was conducted on 100 elderly, all participants underwent comprehensive geriatric assessment. Sleep assessment was done using the ? Pittsburgh Sleep Quality Index (PSQI)? and assessment of QOL using The SF-12 and saliva was collected in a sterile suitable sampling devise for Salivary amylase measurement.

Results: Significant correlations were found between hours of mobile usage and age, both components of HRQL and quality of sleep but insignificant relation to salivary amylase, Yet, there was a significant correlation between absolute usage and non-usage of the mobile and salivary amylase level X2=0.901, p=0.036 (mean users=53.44, nonusers=37.97). There was significantly higher salivary amylase levels with poor quality of sleep (x2=13.873, p=0.001). Conclusion: Significant correlations were found between hours of mobile usage and age, both components of HRQL and quality of sleep.

Keywords: Mobile; Salivary amylase; Quality of sleep; HRQL

Keywords

Mobile; Salivary amylase; Quality of sleep; HRQL

Introduction

Aging is associated with psychobiological changes that could limit our ability to cope with stressors [1]. A review of the literature on psychological stress and disease concluded that there is considerable support for a link between stress and certain illnesses such as depression, cardiovascular disease and the progression of AIDS. There is also growing evidence for the role of stress in the incidence and progression of other diseases such as upper respiratory tract infections, asthma, autoimmune diseases and delayed wound healing. Research using animals provides strong evidence for a link between stress and cancer, but in humans this link is much weaker [2].
In order to better understand the role of stress, valid and reliable measurement of stress is of utmost importance [3]. Testing saliva is increasingly being used in research lately as it is easy to collect, doesn’t require a skilled person or any specific equipment [4] and painless [5]. A handy system for measuring salivary α-amylase activity was released in Japan at the end of 2005 [6], which raised interest in the testing saliva [7].
Researchers investigated the components of saliva in systemic diseases, infectious diseases, malignancy, and hormonal imbalances in attempt to isolate biomarkers [4]. Unfortunately despite many indicators highlighting the advantages of salivary testing studies are lacking [8].
Available research demonstrates salivary alpha-amylase as a useful biomarker that can be used in assessing psychological and behavioral processes [9]. The levels of salivary α-amylase are altered by the adrenergic and the hypothalamic-pituitary-adrenal axis [7].
Results of studies regarding the relationship between salivary amylase activity and age are discrepant: results of studies have shown that salivary amylase activity declines with aging [10,11], that salivary amylase activity does not differ with aging [12,13], and that salivary amylase activity is increased in the elderly [14]. The results of Strahler, et al 2010 implicate sAA as an alternative or additional sympathetic stress marker throughout the life span [15].
Globally, during the past few decades there has been a recognizable increase in the number of people using mobile phones [16,17]. Recently, research is directed to benefit from mobile phones for helping elderly in several clinical domains. The technologies can be used to help manage older adult health and to positively affect their quality of life and well-being [18]. Unfortunately, the radiofrequency radiation emitted from these devices has revealed the importance to investigate possible side effects of mobile phone use on health [19,20]. Research illustrates a variety of adverse effects of long term mobile phones usage on different body systems [20].
Similarly, insufficient sleep impairs several health domains, as well as an individual's general quality of life. The effect of insufficient sleep may include increased propensity to fall asleep, difficulty concentrating, impaired cognition, slowed reaction time, reduced vigilance, fatigue, mood changes, and headache [21,22]. Several studies have shown that the impairments demonstrated from acute and chronic sleep deprivation are comparable to those observed in individuals with high blood alcohol content [23-27]. According to Yogesh and colleagues, a significant association of hours of mobile usage and sleep indices were observed in their study in both genders [28]. The social and economic consequences associated with untreated sleep disorders are significant [1].
Despite the consequences of insufficient sleep that has been demonstrated in literature there are only a few objective assessment methods [29,30]. Currently, only subjective methods ad polysomnographs, which are expensive, are available [31]. Given the diversity of sleep disorders and the direct link to different diseases [30,32] it is vital to search for new objective assessment methods. In 2013 Michael et al, reported that physical fatigue changes the components of saliva and detected a salivary biomarker of physical fatigue that may help identify sleep deprived individuals [33].
Health-related quality of life [HRQL] is an individual's satisfaction or happiness with domains of life in so far as they affect or are affected by "health" [34]. In the past decade, HR-QOL has become of increasing interest in sleep medicine diagnosis and treatment. It is of growing importance toward improving health outcomes and is being taken into consideration in clinical care, health care utilization, and cost [35].
In view of the potential diagnostic applications of saliva, and due to the interplay of effects of the studied domains, this study was designed to detect the levels of salivary amylase with mobile usage and its correlation with sleep deprivation and impaired HRQL in a sample of Egyptian elderly.

Methodology

Study population
A cross sectional study was conducted on 100 elderly; all participants underwent comprehensive geriatric assessment. Sleep assessment was using the ―Pittsburgh Sleep Quality Index [PSQI]‖ [36] which assessed duration of sleep, sleep disturbance, sleep latency, day dysfunction due to sleep deprivation, sleep efficiency and a score of 5 or greater was indicative of poor sleep quality.
Assessment of QOL using The SF-12 [37] is a 12-item measure of subjective health. Widely used in many populations. The SF-12 contains two primary components, physical health (PHC) and mental health (MHC). Physical and Mental Health Composite Scores (PCS & MCS) are computed using the scores of twelve questions and range from 0 to 100, where a zero score indicates the lowest level of health measured by the scales and 100 indicates the highest level of health. For individual scores, those that score higher indicate a person has better health status. Conversely, scores that are lower indicate a person has poorer health.
Salivary amylase assay
Sample Preparation: The saliva is collected in a sterile suitable sampling devise (a minimum of 0.5 mL liquid) after considering the following precautions.
• Patients not eat, drink, and chew gums or brush teeth for 30 min before sampling. Otherwise they rinsed their mouth thoroughly with cold water 5 min prior to sample collection.
• Samples were not collected if there were oral diseases, inflammation or lesions exist (blood contamination).
• Samples were cooled to –20°C prior to laboratory testing.
• After thawing, they were mixed and centrifuged 10 min at 2000 – 3000 x g to remove particulate material.
Procedure method
The procedure used was as provided in the kit’s manual provided by IBL international GMBH for alpha-amylase salivary assay (enzymatic assay for determination of alpha amylase activity in human saliva.

Results

The sample included 100 elderly. Males and females were agematched and results were comparable (mental component of HRQL, salivary amylase levels and quality of sleep scores) except in the physical component of HRQL females had significantly lower scores.
Table 1 shows the distribution of the sample among males and females. Table 2 correlates hours of mobile usage with the other domains tested showing significant results with age, both components of HRQL and quality of sleep but insignificant relation to salivary amylase. Yet, there was a significant correlation between absolute usage and non-usage of the mobile and salivary amylase level X2=0.901, p=0.036 (mean: users=53.44, nonusers=37.97).
Table 1: Description of the sample.
Table 2: Correlation of mobile usage with other domains tested.
Table 3 shows significantly higher salivary amylase levels with poor quality of sleep (x2=13.873, p=0.001). HRQoL was correlated significantly to other domains tested.
Table 3: Correlation of mobile usage with other domains tested.

Discussion

In light of increasing use of cell phones, notably in elderly, and their reported side effects this study was planned to study the effect of cell phone usage on quality of sleep in elderly and HRQoL.
The study showed that the number of females using mobiles were more than males (57 and 24 respectively) and this could be explained by the fact that physical component of HRQoL in females had significantly lower scores.
HRQoL both the physical and mental components were positively correlated to mobile usage at all ranges of hours of mobile usage. Obviously mobile usage has helped elderly socialize and feel safe as they could easily seek help using mobile phones.
There was also a significant positive correlation between absolute usage and non-usage of the mobile and salivary amylase level. This indicates that stress levels, as measured by salivary amylase levels, are high with usage of mobiles when compared to nonusers. A previous study has reported increased levels of salivary cortisol and amylase on exposure to electromagnetic radiations from the Global System for Mobile Communication (GSM) mobile base station [8]. We have to consider that despite the fact that we are studying the effects of mobile usage on sleep the high stress levels could also indicate and mount to several other health dilemmas.
Unfortunately, as in other age groups [38-41] mobile usage negatively affected quality of sleep in all groups starting from the less than 1 hour usage, up to the more than 10 hour usage. Loughran et al. reported the adverse effects of electromagnetic fields emitted by mobile phones on sleep electroencephalograms [42].
Finally, as shown in Table 3, and as studies as Kim et al. have proven earlier, bad quality of sleep lead to worse HRQoL [43]. Unfortunately, this will put the elder in a vicious circle as we mentioned earlier as decline in physical and mental QoL components will intensify their mobile usage, and so on.
As new technologies are providing more and more services to the elderly to cover for the physical deficits and social isolation problems we have to consider the negative impact on general health and whether these risks are hazardous enough to put limitations on mobile usage in elderly or rather their benefits outweigh their detrimental effects.

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