Research - International Journal of Medical Research & Health Sciences ( 2020) Volume 9, Issue 10
Association between Obesity and Sleep Duration in Young Adult Saudis: A Cross-Sectional Study
Abdelmarouf H. Mohieldein*Abdelmarouf H. Mohieldein, Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraidah, Saudi Arabia, Tel: 966 16 380 1580, Email: mabdelmarauf@hotmail.com
Received: 23-Sep-2020 Accepted Date: Oct 15, 2020 ; Published: 22-Oct-2020
Abstract
Objective: The study aimed to assess the relationship between nightly sleep duration and obesity in young adult Saudi citizens.
Methods: A cross-sectional study in which eighty-one healthy young adults were enrolled. Self-reported sleep duration per night was recorded from each participant. Sleep hours were categorized into three groups: normal (7-8 h), short (≤ 6 h), and long (>8 h). Weight, height, and waist circumference were measured for all participants. Body mass index was computed and WHO guidelines was used to estimate obesity. Venous blood samples were collected at fasting and 2-h after breakfast. Blood glucose and glycated hemoglobin were assayed by standard laboratory procedures. SPSS was used to analyze data.
Results: 69.6% of overweight/obese subjects reported sleeping less than 6 hours per night while 37.1% of normal weight subject did (p=0.008). 66.7% of all participants spent over three hours per day in front of screen i.e. spent watching TV, using computer, playing video games. Data analysis revealed an inverse significant correlation between duration of sleep per night and body mass index (r=-0.246, p=0.027).
Conclusion: Our findings collectively highlight the importance of having an adequate amount of sleep per night (7-8 hours) which could help in minimizing the epidemic of obesity and its associated co-morbidities. We should encourage young adults to create a positive behavioral change and improve their lifestyle choices by changing their delay in the timing of sleep onset.
Keywords
Overweight, Obesity, Sleep hours per night, Young adults, Risk factors
Introduction
Obesity is a condition of excessive fat accumulation in adipose tissue that adversely affect human health [1,2]. It is a public health concern worldwide with increased mortality and morbidity because of obesity associated co-morbidities like metabolic syndrome, type 2 diabetes, hypertension, cardiovascular disorders, some cancers [3,4]. The global economic impact of obesity in 2014 was 2.8% of the global gross domestic product which equivalents to US $2.0 trillion [5]. The prevalence of overweight and obesity has increased significantly in Arab Gulf Countries due to economic shifts toward greater gross domestic product [2]. A recent cross-sectional study in Southwestern Saudi Arabia reported that the overall prevalence of overweight and obesity was 38.3% and 27.6% respectively [6].
Researchers attribute body adiposity to multifactorial interactions including genetic, environmental, behavioral, and psychosocial factors [7,8]. These factors promote the intake of energy-dense food, sedentary lifestyle, and increasing urbanization [9]. Besides traditional lifestyle factors, sleep duration has been suggested to have a role in the obesity epidemic [10]. In our hectic modern society, sleep duration and patterns have been changed in both children and adults [11]. Television viewing, video gaming, computer and cellular phones use are associated with a reduction in sleep duration [12,13]. The prevalence of young adults who reported nightly sleep of ≤ 6 hours has significantly increased in recent decades [14,15].
To the best of our knowledge, no previous study has examined the association between sleep duration per night and obesity in a young adult Saudi population. Short sleep duration could be an additional risk factor to exaggerate obesity prevalence in the country. The aim of the study was to test the hypothesis of an inverse relationship between decreased sleep duration per night and increased Body mass index (BMI) in young adult Saudis. Also, we interested to examine the relationship between duration of using mobile phones and BMI.
Materials and Methods
Study Design and Participants
This was a cross-sectional study in which eighty-one apparently healthy subjects, aged between 18 to 46 years, were enrolled in this study. The inclusion criteria were: both sexes, Saudi citizen, BMI≥18.5 Kg/m2, fasting plasma glucose <100 mg/dl, 2-h plasma glucose<140 mg/dl. The exclusion criteria were: none Saudi, BMI<18.5 Kg/m2, fasting plasma glucose ≥ 100 mg/dl, 2-h plasma glucose ≥ 140 mg/dl, have diabetes or any chronic diseases. Data regarding each participant’s socio-demographic, physical activity, duration of sleep per night, screen time, duration talking in mobile were recorded by a questionnaire.
Sleep Duration
Self-reported sleep duration per night was recorded from each participant by the open-ended question, “How many hours of sleep do you get per night?” Based on sleeping 7-8 h per night is the optimal sleep duration for young [4,8,16], sleep hours were further categorized into three groups: 7-8 h (normal), ≤ 6 h (short), and>8 hours (long).
Assessment of Anthropometric Measures
Research assistants carried out anthropometric measurements including weight, height, and waist circumference for all participants. Weight and height were measured using electronic scales. We calculated Body mass index (BMI) as body weight (kilogram) divided by height (meter) squared. The WHO guidelines for BMI was used to estimate obesity: underweight (<18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 (kg/m2) and obese (≥ 30.0 kg/m2) [17]. Waist circumference (WC) was measured using an anthropo-metric tape at a level midway between the lower rib margin and iliac crest with the tape all around the body in a horizontal position.
Biochemical Analyses
Venous blood samples were drawn at fasting and 2-h after breakfast (postprandial) from each participant into heparinized tubes, centrifuged, separated to prepare plasma. Glucose was measured by glucose oxidase-glucose peroxidase method; glycated hemoglobin (HbA1c) was estimated from whole blood by fast ion-exchange separation method. Analyses were done using available commercial kits supplied by Human Diagnostics (Wiesbaden, Germany).
Statistics
Descriptive statistics were computed for all variables. All analyses were conducted using the SPSS software version 23.0 (SPSS Inc., IL, USA) for Windows, and a P value of<0.05 was used to indicate statistical significance. Results were reported as the mean (confidence interval) or number (%) where appropriate. Differences between normal weight group and overweight/obese group were tested for significance by a Student’s t-test (for continuous data) or chi-square test (for categorical data). Pearson’s correlation was conducted between the BMI, WC and sleep duration hours per night.
Ethical Consideration
Oral consent was obtained from all participants after a thorough explanation of the goals of the study. The protocol of this study conformed to the Declaration of Helsinki and all data were provided anonymously.
Results
Characteristics of Participants
Eighty-one healthy participants enrolled in this study were divided into two groups based on their BMI: normal weight group and overweight/obese group. There was no significant difference in the gender, height, 2-hour postprandial blood glucose, glycosylated hemoglobin. More than half of the participants (54.3%) were students and 72.8% of participants had university or higher education. Participants with normal weight were younger than overweight or obese subjects (p=0.031). Compared to overweight/obese subjects, more participants with normal weight significantly used to do physical exercise at least 30 minutes/day (p=0.01). Although the values within normal ranges, overweight/obese participants had higher fasting blood glucose and 2-hour postprandial blood glucose when compared to normal weight subjects (Table 1).
Characteristic | Overweight/Obesity (BMI ≥ 25 Kg/m2) | Normal weight (BMI=18.5-24.9 Kg/m2) | p-value |
---|---|---|---|
n=46 | n=35 | ||
Gender, Male | 31 (67.4%) | 28 (80.0%) | 0.206 |
Age, Years | 28.59 (25.65-31.53) | 24.83 (24.07-25.59) | 0.031* |
BW, Kg | 86.3 (82.5-90.1) | 65.6 (63.2-68.0) | 0.000* |
Height, cm | 164.7 (161.4-167.9) | 168.4 (165.7-171.0) | 0.087 |
BMI, Kg/m2 | 32.1 (30.3-33.9) | 22.6 (22.2-23.1) | 0.000* |
WC, cm | 96.2 (90.3-102.2) | 76.1 (73.9-78.3) | 0.000* |
Education, University or higher | 31 (67.4%) | 28 (80.0%) | 0.164 |
Occupation, Students | 29 (63.0%) | 15 (42.9%) | 0.036* |
Doing physical exercise at least 30min per day, Yes | 05 (10.9%) | 13 (37.1%) | 0.010* |
FPG, mg/dl | 84.7 (82.9 - 86.4) | 82.2 (80.7-83.6) | 0.036* |
2hr-PP, mg/dl | 117.5 (114.6 - 120.4) | 114.8 (111.5-118.1) | 0.217 |
HbA1c, % | 5.6 (5.2 - 6.0) | 5.7 (5.4-6.0) | 0.7 |
Values were expressed as mean (95% CI) or n (%) where appropriate; BW: Body Weight; BMI: Body Mass Index; WC: Waist Circumference; FPG: Fasting Plasma Glucose; 2hr-PP: 2 hours Post Prandial; HbA1c: Glycosylated hemoglobin; CI: Confidence Interval
Duration of Sleep/Night in Study Participants
Over two-third of subjects in the overweight/obese group reported sleeping less than 6 hours/night while around onethird of normal weight subjects did. Out of all participants, 66.7% spent more than three hours per day in front of screen i.e. spent watching TV, using computer, playing video games. 61.7% of participants reported talking less than one hour per day in mobile phones (Table 2).
Characteristic | Overweight/Obesity (BMI ≥ 25 Kg/m2) | Normal weight (BMI=18.5-24.9 Kg/m2) | p-value | |
---|---|---|---|---|
n=46 | n=35 | |||
Screen time, hours | <1 h/day | 00 (00%) | 01 (02.9%) | 0.463 |
1-3 h/day | 14 (30.4%) | 12 (34.3%) | ||
>3 h/day | 32 (69.6%) | 22 (62.9%) | ||
Talking on mobile | <60 min/day | 33 (71.7%) | 17 (48.6%) | 0.102 |
60-120 min/day | 07 (15.2%) | 09 (25.7%) | ||
>120 minutes/day | 06 (13.0%) | 09 (25.7%) | ||
Duration of sleep per night, hours | ≤ 6 hours | 32 (69.6%) | 13 (37.1%) | 0.008* |
7-8 hours | 14 (30.4%) | 20 (57.1%) | ||
>8 hours | 00 (00%) | 02 (5.7%) |
Values were expressed as n (%) where appropriate
Correlation between Duration of Sleep/Night and BMI and WC
Data analysis revealed an inverse significant relationship between duration of sleep per night and body mass index (r=-0.246, p=0.027). However, there was no significant correlation between waist circumference and duration of sleep per night (r=-0.155, p=0.166) (Table 3).
Duration of sleep per night | |
---|---|
BMI | r=-0.246 |
p=0.027 | |
WC | r=-0.155 |
p=0.166 |
BMI: Body Mass Index; WC: Waist Circumference
Discussion
Sleep is a restorative physiological process crucial for metabolic and endocrine homeostasis [9,18]. Sleep insufficiency is associated with chronic diseases, fatigue and hyperactivity, irritability and poor emotional regulation, poor academic performance, impaired immune function, and obesity [19,20].
The main finding of the current study was a higher percentage of overweight or obese participants who reported short sleep duration (less than 6 hours/night) as compared to normal weight subjects (69.6% vs. 37.1%, p=0.008). Our result is consistent with previous cross-sectional and longitudinal cohort studies. In a cross-sectional study conducted among suburban students, short sleep duration was associated with overweight. Authors confirmed a high prevalence of short sleep among suburban high school students [21]. In a prospective 10-year follow-up ‘Sleep and Health in women’ study (SHE study) to evaluate the consequences of sleep disturbances to obesity. Authors reported that younger women (aged<40 years) with short sleep duration (<6 h/night) had a higher prevalence of general obesity (BMI ≥ 30 kg/m2) and central obesity (waist circumference ≥ 88 cm) when compared with habitual normal sleepers (6-9 h/night). They concluded that a short sleep duration was a risk factor for obesity [22].
Our study showed an inverse significant correlation between duration of sleep per night and BMI (r=-0.246, p= 0.027). In agreement with our finding, Xiao, et al. [23], in a cohort longitudinal study over 7.5 years, observed an inverse association between sleep duration per night and weight gain in a sample of 83,377 US men and women aged 51-72 years. Weight gain was associated with subjects of short sleep (<5 hours or 5-6 hours) when compared with those 7-8 hours of sleep. The odd ratio for developing obesity was almost twice in participants with short sleep than those who reported 7-8 hours of sleep [23]. In line with these findings, a meta-analysis included 17 cross-sectional studies in adults from around the world (Spain, Japan, USA, France, Switzerland, Sweden, Brazil, Finland, Norway, Canada, Hong Kong, and United Kingdom) showed a consistent and significant negative association between hours of sleep and BMI. The authors suggested that a reduction in one hour of sleep per day would be associated with a 0.35 kg/m2 increase in BMI [24]. Another longitudinal prospective study over a 6-year follow-up period confirmed the association between short sleep duration (<6 hours of sleep/night) and increased abdominal adiposity in adults when compared to those who sleep on average ≥ 7 hours/night, over a 6-year follow-up period [25].
It is noteworthy that in this era most of young adults are engaged with electronic media which has its negative impact on other activities including sleep hours per night [26]. This study showed that two-third of participants spent more than three hours per day in front of screen engaged with late night activities such television, computer games, and the internet use. However, around the same percentage of participants reported talking less than one hour per day in mobile phones. This might point to the wide usage of mobile phones in social media applications rather than talking. We could expect study participants to use mobile phones during night since more than half of the participants were students who expected to have their daytime in schools or universities. Beside communication, mobile phones in recent years provide ubiquitous usage like interaction, searching for information, and passing time [27]. One study reported an association between the use of mobile phones after lights out and sleep disturbances including short sleep duration among Japanese adolescents [28].
The mechanism by which sleep curtailment leads to weight gain and obesity is thought to be related to hormonal alterations that control hunger and appetite. Short sleep duration alongside with greater awake time increase the opportunity to eat and then get more fatigue which leads to decease physical activity and basal metabolic rate; ultimately leads to significant weight gain [15]. Decreased sleep time creates alterations in levels of hormones that regulate appetite i.e., alteration of leptin (an appetite-inhibiting hormone) and ghrelin (an appetite-stimulating peptide) [29]. Taheri, et al. [30], confirmed an association of short sleep with low serum leptin and high serum ghrelin. The authors concluded that the differences in level of two hormones (leptin and ghrelin) could provide a powerful dual stimulus to food intake, which explain the increased weight gain for persons with short sleep duration.
Conclusion
The present study showed that subjects with short sleep duration per night were more overweight or obese than those with normal sleep duration. In this study, we found an inverse correlation between sleep duration per night and body weight (BMI). Our findings collectively highlight the importance of having an adequate amount of sleep per night (7-8 hours) which could help in minimizing the epidemic of obesity and its associated co-morbidities. We should encourage young adults to create a positive behavioral change and improve their lifestyle choices by changing their delay in the timing of sleep onset.
Limitations
The limitation of this study came from the limited number of sample size as well as the cross-sectional design in which we could not establish short sleep duration per night is a cause for body weight and obesity. However, person`s correlation showed the inverse relationship between sleep hours and body weight.
Declarations
Acknowledgement
The author is thankful for the help provided by Mr. Sami Al-Mushawwah for samples collection.
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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