Research - International Journal of Medical Research & Health Sciences ( 2020) Volume 9, Issue 11
Physical Activity Affects the Sleep Quality of Women in Saudi Arabia: A Prospective Follow-up Study
Huda Alraddadi*Huda Alraddadi, Taibah University, Kingdom of Saudi Arabia, Tel: 966 14 861 8888, Email: Huda.s.alradaay@hotmail.com
Received: 19-Oct-2020 Accepted Date: Nov 23, 2020 ; Published: 30-Nov-2020, DOI: O
Abstract
Objectives: The prevalence rates of sleep insufficiency and physical inactivity are increasing worldwide. Accumulating evidence indicates a relationship between physical inactivity and sleep disturbance. This study aimed to determine the impact of physical activity on sleep quality and body mass index in women in Saudi Arabia. Methods: This prospective study included 63 women at sports clubs in Medina, Kingdom of Saudi Arabia. The study was conducted between June 2019 and September 2019. All participants were followed up for 3 months. Sleep quality was measured using the validated Pittsburgh sleep quality index, and physical activity was measured using the validated international physical activity questionnaire. Sleep quality and body mass index were compared at baseline and after 3 months using paired t-tests. Results: Physical activity showed a significant effect on sleep quality (p=0.034) and body mass index (p=0.002) among the participants. Conclusion: Physical activity improves sleep quality and decreases body mass index.
Keywords
Adult, Exercise, Physical activity, Saudi Arabia, Sleep quality, Women
Abbreviations
BMI: Body Mass Index; KSA: Kingdom of Saudi Arabia; PA: Physical Activity; SQ: Sleep Quality
Introduction
Current evidence suggests that regularly sleeping at least 7 hours per night is essential for good physical health of adults aged 18 to 60 years [1]. Sleep deprivation (failure to obtain adequate amount of sleep) has become a serious problem because of its negative impact on well-being [1,2]. The prevalence of sleep deprivation is approaching 33% in the Kingdom of Saudi Arabia (KSA) and is higher among Saudi women than Saudi men (37.3% versus 31.4%) [3].
In addition, nearly 23% of adults are physically inactive [4]. In KSA, the prevalence of physical inactivity ranges from 50% to 85% in men and from 73% to 91% in women [4-7]. According to the World Health Organization, adults aged 18-64 years should do at least 150 minutes of moderate-intensity physical activity throughout the week [8]. Recent studies have found a positive relationship between Physical Activity (PA) and sleep [9]. Notably, three studies in KSA showed that PA correlated significantly with sleep duration [10-12]. However, the associations of PA and physical fitness with Sleep Quality (SQ) remain unclear. Some studies showed no association [13], but others concluded the opposite [14-16].
This study aimed to investigate the impact of PA on SQ and Body Mass Index (BMI) in women aged >18 years in Medina, KSA. To the best of our knowledge, this is the first prospective study to investigate the effect of PA on SQ in Saudi women.
Materials and Methods
Study Setting and Participants
This prospective study was performed at four women sports clubs in Medina and included 63 women. The study was carried out between June 2019 and September 2019. Women who applied for new registration in the sports clubs were recruited until the target number of participants was reached. Each woman filled a self-administered questionnaire on the first day when she joined the sports club and then the same self-administered questionnaire 3 months later. The questionnaire was prepared in the Arabic language.
Women aged ≥18 years who spoke Arabic were included in the study. Pregnant women were excluded. The study sample size was calculated to be 53 with a power of 80%, 95% CI, and a level of significance of 5% (two-sided). To compensate for the non-response and loss to follow up, an additional 20% was added to the sample size [17]. Therefore, a total of 63 women were included in this study.
Ethical approval for this study was obtained from the Ethics Committee of the Directorate of Health in Al-Madinah. The benefits and objectives of the study were explained to the participants. Confidentiality and anonymity of the participants was assured. All participants signed an informed consent form. Contact information was provided by the participants, and data were collected from each participant at baseline and after 3 months.
Study Instruments
Sociodemographic variables and health status: Sociodemographic variables included age, marital status, number of children, family income, education level, employment status, chronic diseases (such as asthma and diabetes mellitus), shisha smoking, and cigarette smoking. Smoking was measured according to the Global Tobacco Surveillance System [18]. The participants rated their health by answering one question: How would you grade your health status? Answers were ranked based on a Likert-type scale as follows: (1) very bad, (2) bad, (3) fair, (4) good, and (5) excellent. Participants self-reported their height in centimeters (cm) and weight in kilograms (kg).
International physical activity questionnaire: To assess PA, we used the validated Arabic short version of the international physical activity questionnaire [19]. It collects information about the time and number of days spent in PA. Participants were categorized as high active, moderately active, or low active.
SQ assessment: The validated Arabic version of the Pittsburgh sleep quality index was used to measure the quality and pattern of sleep in adults. Cronbach’s alphas are 0.80 for the original English version and 0.65 for the Arabic version [20,21]. The scale examined SQ retrospectively over a 1-month period and assessed different SQ components, including subjective SQ, sleep latency, sleep duration, sleep efficiency, sleep troubles, use of sleeping pills, and daytime dysfunction. Each component was ranked from 0 to 3, with 3 indication the worst condition of that particular component. The sum of the scores of these seven components provides a single total SQ score. The highest possible Pittsburgh sleep quality index score is 21. High scores are suggestive of poor SQ. Scores less than or equal to 5 (0 to 5) indicate normal SQ, and scores above 5 indicate poor SQ.
Statistical Analysis
Each questionnaire received a unique code, and every answer was coded with numerical indicators. Descriptive & inferential data analysis was performed using SPSS Version 25. The normality test was conducted and showed that the data were normally distributed.
Continuous variables are presented as mean and standard deviation, and categorical variables are presented as frequency and percentage. T-test and ANOVA tests were used to compare mean SQ score across the study variables. A paired t-test was used to assess SQ and BMI before and after practicing exercise. Statistical significance was established at p<0.05.
Results
A total of 63 women participated in this study. Mean (SD) age was 25 (6.6) years, and mean (SD) BMI was 28.2 (8) (Table 1). Most of the participants were singles (71.4%), non-smokers (82.5%), and students (65.1%); did not have kids (90.5%); and had a university level of education (68.2%). Most of the participants worked during the daytime only (73.7%) and had a family income of less than 10000 Saudi riyals (65.2%). Approximately 22.2% of the participants had a chronic disease, and 3.2% were not satisfied with their health. More than 87% of the study participants claimed that they used smartphones during bedtime. The average smartphone use was above 7 hours per day. At the start of the study, 23.8% of the participants were physically inactive.
Variables | N (%) | Variables | N (%) |
---|---|---|---|
Age (years) | Shift work | ||
≤ 25 | 42 (66.7%) | Day shift | 28 (73.7%) |
≥ 26 | 21 (33.3%) | Night shift | 3 (7.9%) |
BMI (kg/m2) | Family income | ||
<18 | 5 (7.9%) | <3000 | 10 (15.9%) |
18-25 | 20 (31.7%) | 3000-5999 | 11 (17.5%) |
25.1-30 | 16 (25.4%) | 6000-9999 | 20 (31.8%) |
30.1-40 | 15 (23.8%) | 10000-18000 | 17 (27%) |
> 40 | 7 (11.1%) | >18000 | 5 (7.9%) |
Mean (SD) | 28.2 (8%) | ||
Marital status | Smoking cigarette | ||
Single | 45 (71.4%) | Yes | 8 (12.7%) |
Married | 13 (20.6%) | ||
Engaged | 3 (4.8%) | No | 55 (87.3%) |
Divorced or widowed | 2 (3.2%) | ||
Children | Smoking water pipe | ||
Yes | 6 (9.5%) | Yes | 6 (9.5%) |
No | 57 (90.5%) | No | 57 (91.5%) |
Education level | Chronic disease | ||
Less than university | 20 (31.8%) | Yes | 14 (22.2%) |
University | 43 (68.2%) | No | 49 (77.8%) |
Employment | Health satisfaction | ||
Student | 41 (65.1%) | Excellent | 16 (25.4%) |
Not employed | 8 (12.7%) | Very good | 20 (31.7%) |
Private sector | 8 (12.7%) | Good | 16 (25.4%) |
Government sector | 6 (9.5%) | Acceptable | 9 (14.3%) |
Bad | 2 (3.2%) | ||
Using smartphone at bedtime | Physical activity level | ||
Yes | 55 (87.3%) | Low | 15 (23.8%) |
No | 8 (12.7%) | Moderate | 23 (36.5%) |
High | 25 (39.7%) | ||
Smart phone use (hours per day) | |||
<6 | 19 (32.2%) | ||
6 h-10 h | 31 (52.5%) | ||
≥ 10 | 13 (15.3%) |
BMI: Body Mass Index
Table 1: Baseline sociodemographic and other health characteristics of participants
Table 2 describes sleep characteristics at baseline. More than half of the study participants (52%) had poor SQ. Mean (SD) sleep duration was 7 (2.6) hours per night, and the mean (SD) sleep onset latency was 25 (20.26) minutes. The mean sleep onset latency decreased from 25.2 minutes at baseline to 21.2 minutes at the end of the study. At the start of the study, 28.6% of the study participants claimed that they took sleep pills at least one time per month; this number was decreased to 20.6% at the end of the study.
Variables | Frequency (%) |
---|---|
Pittsburgh sleep scores | |
Good | 30 (47.6%) |
Bad | 23 (52.4%) |
Mean (SD) | 7.9 (4.5%) |
Sleep duration (hours) | |
≥ 7 | 32 (55.2%) |
<7 | 31 (44.8%) |
Mean (SD) | 7 (2.6%) |
Sleep efficiency | |
>85% | 26 (45.6%) |
75%-84% | 13 (22.8%) |
65%-74% | 10 (14%) |
<65% | 14 (17.5%) |
Sleep onset latency (minutes) | |
<15 | 27 (47.4%) |
16-30 | 13 (22.8%) |
31-60 | 17 (29.8%) |
Mean (SD) | 25.67 (20.26%) |
Sleep pills | |
Yes | 18 (28.6%) |
No | 45 (71.4%) |
Table 2: Sleep characteristics at baseline
Table 3 shows the association between the SQ score and participants’ characteristics at baseline. No significant association was found. Table 4 represents the results of the paired t-test. There were a significant improvement in SQ (p=0.034) and a significant decrease in BMI (p=0.002) after PA.
Variables | Mean | SD | p-value | Variables | Mean | SD | p-value |
---|---|---|---|---|---|---|---|
BMI (kg/m2) | Family income | ||||||
<18 | 8.8 | 4.7 | 0.34 | <3000 | 5.6 | 2.5 | 0.45 |
18-25 | 8.7 | 4.3 | 3000-5999 | 9.1 | 4 | ||
25.1-30 | 6.7 | 5.1 | 6000-9999 | 8.2 | 4.5 | ||
30.1-40 | 9.1 | 4.8 | 10000-18000 | 8.5 | 5.5 | ||
>40 | 5.7 | 1.8 | >18000 | 7 | 4.7 | ||
Marital status | Shift work | ||||||
Single | 8.2 | 4.8 | 0.48 | Day shift | 8.5 | 5.4 | 0.5 |
Married | 7.2 | 3.8 | Night shift | 11.6 | 2.5 | ||
Engaged | 5.3 | 1.5 | Both | 7.7 | 2.6 | ||
Kids | Educational Level | ||||||
Yes | 6.7 | 3.8 | 0.35 | Less than university | 7.4 | 3.8 | 0.14 |
No | 8 | 4.6 | University | 8.1 | 4.9 | ||
Health satisfaction | Employment | ||||||
Excellent | 6 | 4.8 | 0.07 | Student | 7.1 | 4.6 | 0.43 |
Very good | 8.6 | 4.2 | Not employed | 9.2 | 2.8 | ||
Good | 7.2 | 3.1 | Private sector | 8.4 | 3.8 | ||
Acceptable | 11.1 | 5.5 | Government sector | 9.8 | 5.7 | ||
Bad | 6.5 | 3.5 | |||||
Chronic diseases | Cigarette smoking | ||||||
Yes | 10.3 | 4.6 | 0.89 | Yes | 4.5 | 3.3 | 0.30 |
No | 7.6 | 4.5 | No | 8.3 | 4.5 | ||
Using smartphone at bedtime | Water pipe smoking | ||||||
Yes | 8 | 4.3 | 0.28 | Yes | 8.8 | 5.3 | 0.62 |
No | 6.8 | 5.7 | No | 7.8 | 4.5 | ||
Smartphone use (hours per day) | |||||||
<36 | 7 | 3.6 | 0.20 | ||||
6-10 | 7.9 | 5.2 | |||||
>10 | 10.2 | 4.1 |
BMI: Body Mass Index
Table 3: Relation between sleep quality and participants’ characteristics at baseline
Variables | At baseline | After 3 months | Mean differences | SD | CI 95% | p-value | ||
---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | |||||
SQ | 7.9 | 2.5 | 6.5 | 1.3 | 1.4 | 4.9 | 0.1-2.6 | 0.034* |
BMI (kg/m2) | 28.2 | 8 | 27.1 | 7.6 | 1.1 | 2.6 | 0.4-7.7 | 0.002* |
SQ: Sleep Quality; BMI: Body Mass Index; * Significant p-values
Table 4: Difference in SQ and BMI at baseline and after 3 months
Discussion
This study found that 52.4% of women had insufficient sleep, and the total sleeping time was much less than the recommended 7 hours per night [1]. This is not unexpected as the prevalence of poor SQ among the Saudi population is 33.8% [3], and it is higher among women than men (37.3% versus 31.4%) [3]. Women have a higher prevalence of poor SQ and physical inactivity. For instance, one study in Saudi Arabia showed that a great proportion of the females had insufficient sleep, and PA significantly correlated with sleep duration [10]; poor SQ was frequently observed among undergraduate female students (54%) in eastern Saudi Arabia, with a mean total sleep duration of 5 h/day, and was associated with low PA [11]. Similarly, the current study indicates that practicing PA improves SQ among women (p=0.034). However, the associations of PA and physical fitness with SQ remain controversial. Some studies showed no association [13], but a meta-analytical review found that regular PA had little effect on sleep efficiency, and moderate positive effect on sleep onset latency and SQ [22]. Indeed, exercise would promote cardiorespiratory fitness and thus solve sleep problems, including sleep apnea and insomnia [23]. The improvement of these disorders with exercise could then lead to a good metabolic control and physiological benefits, such as body temperature, heart rate, metabolic rate, blood pressure, and blood glucose control [23]. However, a recent randomized controlled trial found that a 1-week sedentary behavior-inducing intervention had a statistically significant, negative effect on overall SQ, indicating sedentary behavior worsened SQ [24]. In older adults, exercising for a long period leads to better SQ [25- 29]. In addition, Harp evaluated the effects of a 15-week aerobic exercise intervention on sleep in young adults [30]. The study showed improved SQ and BMI after the intervention [30]. Consistent with the findings of earlier research, the findings of our present research have demonstrated that PA improves SQ and BMI. Taken together, these findings indicate that regular exercise improves SQ.
There are some limitations to this study. First, a control group was not included in this study. This study only compared changes between pre- and post-exercises in one study group. Second, the sample size was relatively small. Third, we used the subjective measurement of PA and SQ in this study.
Conclusion
The present findings indicate that PA has an independent effect on the improvement of subjective SQ and BMI. Our findings on SQ and PA were mainly based on subjective estimates; thus, further studies are needed to determine objective measures of PA and sleep by polysomnography or ambulant sleep recording devices.
Declarations
Source of Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Conflicts of Interest
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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