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Physical Activity Affects the Sleep Quality of Women in Saudi Arabia: A Prospective Follow-up Study
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International Journal of Medical Research & Health Sciences (IJMRHS)
ISSN: 2319-5886 Indexed in: ESCI (Thomson Reuters)

2021 Conference Announcement - International Journal of Medical Research & Health Sciences ( 2024) Volume 9, Issue 7

Physical Activity Affects the Sleep Quality of Women in Saudi Arabia: A Prospective Follow-up Study

Huda Alraddadi*
 
Taibah University, Kingdom of Saudi Arabia
 
*Corresponding Author:
Huda Alraddadi, Taibah University, Kingdom of Saudi Arabia, Tel: 966 14 861 8888, Email: Huda.s.alradaay@hotmail.com

Received: 26-Sep-2022, Manuscript No. jbbs-23-87910; Editor assigned: 28-Sep-2022, Pre QC No. P-87910; Reviewed: 12-Oct-2022, QC No. Q-87910; Revised: 18-Oct-2022, Manuscript No. R-87910; Published: 26-Oct-2022, DOI: O

Abstract

1

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%)

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        

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*

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.

References

Citation: Imbalzano, Marco. �??Making Use of Machine Learning Algorithms for Multimodal Equipment to Assist in COVID-19's Assessment.�?� J Bioengineer & Biomedical Sci 12 (2022): 325.

Copyright: © 2022 Imbalzano M. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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