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LACK OF SLEEP AND WEIGHT GAIN
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Running head: LACK OF SLEEP AND WEIGHT GAIN
EFFECT OF LACK OF SLEEP ON WEIGHT GAIN ON INDIVIDUALS
(Name)
(University)
INTRODUCTION
Background
Sleep is a restorative process which plays a vital role to balance the emotional, psychological and physical aspect of an individual. National sleep foundation indicates that a good night’s sleep for an adult should be between seven to nine hours every night. Nevertheless, studies have suggested that average American adults sleep far less than what is recommended sleeping for only six hours on average during workdays. Some signs which have been associated with sleep deprivation include feeling irritable, sluggish or fatigued. This deprivation has also linked to high to accidents and errors which occur either off or on the job. Considerably, of most importance as to why it is essential to have enough sleep is research studies which have shown that sufficient sleep plays a critical role in weight management.
In modern society, the quality and the duration of sleep have reduced significantly which have been attributed to socio-economic changes in the environment and the lifestyle. For instance, a study conducted among college students indicated chronic sleep deprivation had risen by 5%-10% as from 1995-2005 (Bayon et al., 2014). Coincidentally, a different study showed that during the same period, the prevalence of obesity had more than doubled. Recent studies have since then marked obesity as a global pandemic with statistics indicating that more than 25% of all Americans are obese or are in the risk of becoming obese (Patel, 2006). This parallelism has attracted interest from researcher s resulting in numerous studies to elucidate the relationship between the two. A National Health Interview Survey conducted between 2004-2007 indicated that more than 28.3% of adults slept for only 6 hours or less and had a body mass index(BMI) > 25kg/m 3 which would be marked as a precursor to obesity( Spaeth, 2013). A similar study carried out in 2008 found that worldwide, more than 1.46 billion adults had a BMI higher than 25kg/m 3 with 205 million of them b being men. Further, this study indicates that 75% of the 1.46 billion indicated as having the sleep of fewer than 7 hours per night (Spaeth, 2013).
Cross-sectional studies have also been conducted aimed at establishing if there is any relationship between sleeping and obesity. These studies have repeatedly concluded that it is a major association between reduced sleep and gaining weight. A cross-sectional survey conducted among adult men found that more than 80% of men who indicated sleeping less time than the recommended 9 hours were obese or had a high BMI indicating a high probability of being overweight ( Chaput et al., 2007). This data supported more 50 epidemiological studies which were conducted in various geographical regions to determine if there was an association between obesity and sleep among children and adults. Most of these studies had found a significant association.
Problem statement
However, besides having numerous studies conducted in this area, there has been no differentiation between causes from effect. Additionally, the studies have not been able to fully explain how lack of sleep affects or could affect weight gain on an individual thus making a significant topic to be researched on.
Purpose of the study
This study aims to add to the existing knowledge by explaining how lack of sleep affects weight gain on individuals. Further, the study will elucidate how weight gain depends on lack of sleep.
Research question
The study question to be addressed is what the effect of lack of sleep on weight gain by an individual.
Hypothesis
The study hypothesizes that weight gain depends on lack of sleep
Scope
This research study will only focus on the population of the United States.
Limitation
Some factors have been identified as possible limitations to the study.
Scope is the main limitation of this study. The population covered in this study and thus may not be able to entirely rule out variances that may result from the use of a large population.
Research method. The research will not involve conducting any primary research hence will be based on the use of secondary data sets. Thus the accuracy of the study results is subject to the accuracy of the data set that will be used.
Significance of the study
This study will serve to add to the existing knowledge about the topic under study. Further, they will provide more information about how weight gain depends on lack of sleep. The results of the study will be significant to individuals, health organization and the government by providing knowledge how weight gain and lack of sleep are related and thus could use this information to formulate strategies to address the rising prevalence of obesity.
LITERATURE REVIEW
Recent data has shown that there has been a dramatic increase in obesity for the past three decades with reaching an alarming rate. The increase has been concurrent to the reduction in sleeping time and thus has resulted in questions rising on the possibility of an association existing between sleep deprivation and obesity. Others have sought to understand whether sleep duration could be a cause of obesity. Despite the outburst of interest in this area, the studies have not elucidated on the factors which cause this secular reduction in sleeping time nor have the known factors been understood. Nevertheless, this decline has been described as a modern way of life (Chaput &Tremblay, 2012).
In recent times, social changes have been observed where for instance children have been subjected to sleep deprivation due to delayed bedtimes while the waking times have remained relatively unchanged. Some of the factors that have been associated with this disruptive behavior include activities which keep the children awake such as watching or another context such as school work and parent being part-time employees (Chaput &Tremblay, 2012). Additionally uses of caffeine, artificial light and parental attitude have also been attributed to sleeping late. The habit of declining sleep is not only a children’s problem but is more prevalent among adults. Recent studies indicate that over the past 40 years, there has been a sharp decline in the duration of sleep among adults in the United States. According to Chaput et al. (2007), the duration has declined by 2 to 2.5 hours.
Further, the proportion of young people who are sleeping less than 6 hours per night has nearly doubled between 1960 and 2002 jumping from 15.6% to 37.1%. Lack of sleep has become very widespread and has been blamed on the opportunities and demands of modern life which is termed as “24 hours”( Chaput et al., 2007). Studies conducted to investigate this problem found that more than a third of adults who participated in these studies indicated sleeping less than 6 hours per night (Spaeth et al., 2013). This has led to researchers concluding that we live in a society which is sleep-deprived. The term “sleep debt” has since then been coined to describe this situation.
Understanding sleep
The duration, quality, and timing of sleep have been found to affect the metabolic, endocrine and neurohormonal functions that are related to health. Rest is defined as a time when the brain is active in which distinct waves patterns in the brain are produced in a progressive series with the waves containing physiologic functions which are unique (Kondracki, 2015). According to research, sleep is a pattern of two cycles which keep on repeating. The rapid eye movement (REM) which is known as stage R is the first stage and accounts for 25% of sleep while the non-REM (NREM) accounts for 75% of sleep. The two cycles repeat alternatively after every 90 minutes.
The first stage of sleep begins with NREM which commences with stage N1, N2 and finally N3 which is also referred to as slow- wave sleep (SWS) (Kondracki, 2015). In stage N1 and N2, an individual becomes disengaged from the surrounding, and the body temperature falls resulting from slowing down of brain waves. After this, sleeping enters the SWS which mark the deepest part of sleep. This stage is associated with a decrease in heart rate, blood pressure, relaxation of muscle and reduction in breathing rate (Kondracki, 2015). Through SWS, the brain is restored with energy and the reason why individuals feel rejuvenated and energetic on waking up. More extended periods are experienced with progress into the night where longer periods of REM sleep are experienced as eyes dart back and forth, vitals decrease which results in brain becoming more active and dreams occur.
Although these stages are common for humans, it has been found that children spend more time in deeper stages of sleep as compared with adults. It has also been found that people have varying sleep requirements throughout the life cycle (Chaput et al., 2007). According to scientists, sleeping is regulated by both the circadian rhythm commonly called the biological clock and the physiological needs (Chaput et al., 2007). Circadian rhythm controls sleep by increasing the feeling of sleepiness from midnight to 7 AM and between 1 PM and 4 PM. Different factors have found to cause a shift in the biological clock including sleeping during the day, meal times, exogenous melatonin and light. Disruption in the biological clock has been found to cause metabolic and hormonal changes which could result in diabetes, decreased life expectancy and obesity (Chaput &Tremblay, 2012). Significant causes of hormonal and metabolic systems that have been identified include primary sleep disorder like Obstructive sleep apnea (OSA), restless leg syndrome (RLS) and narcolepsy. Other reasons for these disruptions include nicotine, caffeine, alcohol, shift work, and rheumatoid arthritis.
The connection between sleep and weight
Researchers have found that the quality and quantity of sleep affect weight gain and has associated it with gene connection. In a study conducted on fraternal and identical twins, it was found a deprivation of sleep could result in the genes which are related to obesity being promoted. Different studies have been carried out to explain the physiological and behavioral mechanism underlying the association between weight gain and sleep duration. An example is a laboratory study in which subjects underwent two nights of sleep deprivation sleeping for only 4 hours. Energy intake was also controlled with glucose being infused intravenously and it was observed that it caused ghrelin levels to increase (Patel et al., 2006). Ghrelin is an orexigenic hormone that is released in the stomach. It was also observed that the levels of leptin which is an anorexigenic hormone decreased and was followed by a consequent significant increase in self-reported rating of hunger and appetite with more specification for foods of high carbohydrate content (Patel et al., 2006).
Similar other experiments conducted indicated that a decline in sleeping time resulted in an increase of ghrelin levels and consequent reduction of leptin levels in humans who are calorically-restricted. Contrasting ad libitum experiment showed that sleep loss did not affect ghrelin or leptin in a simulated natural environment but instead resulted in an increased intake of calories (Spaeth et al., 2013). Thus these experiments concluded that by nature human beings would compensate for the loss of sleep by increasing energy intake. Further studies have found that deprivation of sleep affects the absorption of macronutrients and meal frequency which are highly associated with obesity.
Effects of Short sleep duration on energy intake
For weight gain to occur, sleep deprivation has to cause an increase in energy intake or reduction in energy expenditure (Chaput &Tremblay, 2012). There are various possible mechanism through which reduced sleeping time could cause the above and is shown in figure 1.
Figure 1: mechanisms through which insufficient sleep may result in weight gain (Source: Chaput & Tremblay, 2012)
The primary explanation as to why sleeping for short periods poses an obese risk is due to the increase in food intake. Short durations of sleep prevent the restoration of hormonal balance which is supposed to facilitate control of appetite through homeostasis. From earlier s discussion, the less sleeping time has been associated with a decrease in levels of leptin and consequent increase in cortisol and ghrelin levels. This alters glucose homeostasis activating the orexin system. For instance, in a study involving 14 men of healthy weight, it was that found that after they were sleep deprived, their food purchasing pattern changes dramatically opting to shop for food which had high-calorie content (Chaput et al., 2007). When the same experiment was conducted on the second day, it was observed that the same high-calorie food was bought but the quantity increased. After four days of 4-hour sleeping duration, it was noted that the energy intake rose by 22% while fat consumption increased by 98%. The study also indicated a significant increase in calorie intake more so fat without a change in expenditure on energy (Chaput et al., 2007). Short duration sleeping has also been associated with hedonic brain stimulus which drives individuals to consume food. In an experiment carried out by Hogenkamp, it was found that the morning following sleep deprivation; individuals were found to overeat with the preference being on snacks. Other studies have suggested that the intake of calorie is directly proportional to the duration of time spent awake. Thus the increased intake of energy with a resulting change in energy expenditure results to expenditure and which have been (KondrackiSleep&Weigh, 2015).
Effects of Short Sleep Duration on Energy Expenditure
Reduction in energy expenditure is another possible explanation of the obesity- short sleep connection. There are some possible explanations for this mechanism. The first one is that increase in tiredness and fatigue as a result of too little sleep lessens the probability of an individual participating in any physical activity(Beccuti&Pannan, 2013). This has been supported by recent studies which have shown that following short –term sleep restriction one the previous night, the next daytime is marked by spontaneous physical activity in men who are healthy. This study interestingly coincides with free-living conditions where a reduction in overall physical activity marks a shift towards less intense activities resulting in high-calorie retention (KondrackiSleep&Weigh, 2015).
Experimental Evidence
Many short term studies whose aim is to investigate the effects of sleep restriction on energy balance and deprivation of sleep have been published over the past 15 years. These studies have been contributed to understanding the potential relationship between short –sleep and obesity. In one experiment, it was found that restriction of sleeping time for two consecutive nights to 4h instead of 10 h led to an 18% decrease in leptin and 28% increase in orexigenic hormone followed by an increase in the sensation of appetite and hunger (Beccuti&Pannan, 2013). Similarly, another experiment indicated that the average weight gain for people who slept for short duration was 88% higher than what those who slept the recommended time gained. It was also found that the difference in waist circumference stood at 58% higher than the average sleeper and at 124% higher for percentage of body fat (Beccuti&Pannan, 2013).
METHODOLOGY
This chapter explains the methodology which was selected for the study that is in line with the research question what is the effect of lack of sleep on weight gain by an individual. It explains the research method, research design, validity of methodology and variable under research.
Research Method
The research method adopted in this study is secondary analysis. Secondary analysis is defined as the analysis of data that has already been collected by someone. The method is chosen due to the availability of a vast amount of data that a researcher can choose from. It is also saved on time since the study design and data collection are already completed. It is also justified by the minimal costs involved to access cross-historical and international data which would otherwise cost millions of dollars to collect through primary research. Furthermore, the data available is of high quality since most secondary data is from government-funded studies which usually involve larger samples which are more representative of the target population in addition to increased statistical precision which results from oversampling of low prevalence groups and behaviors.
Research design
The research design adopted was sampling design. The sampling research design was selected as the study aims to only use the most relevant data from the available collection of data.
Discussion of variables
The research question to be addressed is the effect of lack of sleep on weight gain by an individual. The variables under research are the weight of an individual and lack of sleep. The independent variable is the lack of sleep while the dependent variable is the weight of an individual.
RESULTS
Statistical results on sleep deprivation
Epidemiologic surveys suggest that the mean sleep duration among adults US adults has dramatically decreased over the past two decades according to a CDC unpublished data of 2007. The statistics estimate that more than 70 million Americans have wakefulness and chronic sleep disorders (US Department of Health and Human Services,2003). A 2006 analysis of Behavioral Risk Factor Surveillance System (BRFSS) by CDC in four states Delaware, Hawaii, New York, and Rhode Island sought to address was how many days throughout 30days respondents felt that had not gotten enough sleep. The resulting data were combined and was categorized in groups of a range of days. The ranges of the day were 0 days, 1-6 days, 7-13 days, 14-20 days, 21-29days and 30 days. The analysis of the result was also stratified in terms of race, sex, education level and age. The confidence level was at 95%.
The results indicated that 29.6% of all respondents in the states under study reported no days of insufficient sleeping. In specific states, the results were however different. In Delaware, only 27.7% indicated as having no sleep deprivation, 38.4% in Hawaii, and 29.2% in New York and 27.7% in Rhode Island (Morbidity and Mortality Weekly Report, 2008). On a stratified scale, sleep debt increased with increase in age with participants 44.7% of participants aged 55 years and above having no days of insufficient sleep. The number was much lower for working-age participants of between the ages of 18-45 years where only 21.9% indicated as not having had an inadequate sleep. 53.5% of retired participants reported no sleep deficiency (Morbidity and Mortality Weekly Report, 2008).
The study also found that the increase in educational level resulted in a decrease in the percentage of persons reporting no days of insufficient rest. 39.7% of participants who reported no days of insufficient rest had less than a high school diploma, 26.3% for those who had a college degree and 18.9% for participants who university tertiary education(Morbidity and Mortality Weekly Report, 2008). On average, the study found that 10.1% of respondent reported deprived sleeping daily during the preceding 30 days. Further, unemployed people had a higher probability of reporting 30 days of deprived sleep standing at 24.8% as compared to 9.9% for those who were employed (Morbidity and Mortality Weekly Report, 2008).
Similarly, another report in 2006 by the Institute of Medicine (IOM), titled Sleep Disorders and Sleep Deprivation reported that on average adults need approximately, adults need 7-8 hours of uninterrupted sleep while adolescents needed 9 hours per night (Perry et al., 2013). The report, however, found that 35% of all adults in the United States reported sleeping less than 7 hours per night while 70% of adolescents reported as not having an average of 8 hours rest time. The report approximated that in the US alone; more than 15 million children are sleep deprivation which translated to mean that nearly 39% of all children do not get enough sleep in the US(Perry et al., 2013). It was found that more than 20% of employed individuals reported having less 6 hours of sleep per day.
Data from a similar National Health Interview Survey in 2013-2014 tested the number of participants who indicated sleeping less than 7 hours per night based on various factors. The study found that 37.5% of parents with children aged less than 18 years reported sleeping less than 7 hours while those with children above the age of 18 were at 32.3% (Nugent& Black, 2016). The study also indicated that 17.3% who were single reported having sleeping problems, 13.1% who lived without children indicated having sleeping problems. 24.5% of single women indicated as having sleep deficits (Nugent& Black, 2016).
Statistical results on Weight Gain
A study by the CDC in collaboration with State Department of Agriculture to investigate the prevalence of obesity among the American population indicated that in overall, obesity in children had increased from 14.0% in 2000 to 15.5% in 2004. The figure had further increased to 15.9% in 2010. By 2014, the figure had dropped to 14.5% but rose sharply again to 15.6% in 2015.
A 2008 BFRSS survey in all states found that out of a population of 384,541 that participated in the research, only 1.8% was underweight. 35.1 % was normal, 36.4% were overweight, 17.1% had obesity class I and 6.1% had class II obesity while 3.5% had class III obesity (Wheaton et al., 2011). Similarly, a 2015-2016 National Health and Nutrition Examination Survey found that the prevalence of obesity in adults has risen to 39.8% and 18.5% in youth as compared to similar statistics from 2010 where adult prevalence stood at 35.7% and youth at 16.9% (Hales et al.,2017). The prevalence of obesity was found to be high among the middle-aged adults standing at 42.8% as compared to 35.7% in younger adults. Youth aged between 12-19 years had a higher prevalence of obesity standing at 20.6%, followed by those aged 6-11 years at 18.4% and lastly children aged 2-5 years at 13.9% (Hales et al., 2017).
DISCUSSION AND CONCLUSION
The prevalence of obesity remains very high in the United States if the above statistics are anything to go by. In parallel to the rise of obesity, there has been increasing in individuals who are sleep deprived. This has led to the postulation that weight gain is dependent on sleep deprivation. From the above results, this relationship seems to exist.
The results indicate that obesity prevalence among adults rose to 39.8% in 2016 from 35.7% in 2010. Accompanying this increase was the rising number of adults who reported having sleeping problems which resulted in sleep deprivation the figures standing at 35%. This concurrent rise indicates that when sleep deprivation sleep deprivation resulted in a consequent rise in obesity. Obesity was found to be high among the middle-aged adults standing at 42.8%. This group is associated with long hours and tight schedule which causes constant strain on their sleeping habit. A look at this work bracket indicates that 21.9% reported as having sleeping deprivation which would support the idea that obesity is related to lack of sleep.
Youths are known to spend most of their time engaged in different activities and more are highly associated with watching late into the night which leaves them with only a few hours to sleep. Statistics indicated that 70% of adolescents reported sleeping less than 7 hours per night. This figure coincides with the high prevalence rate of obesity which indicates that 20.6% of all youth in the US are obese. The main explanation for this association would be that youths consume a lot of energy foods during their long wake hours but there is no sequential increase in energy expenditure. Further as earlier explained, sleep deprivation reduces the impulse of an individual to participate in any physical activity resulting in rising in body mass index and eventually leading in obesity.
The number of parents with children below the age of 18 who indicated that they had sleep deprivation stood at 37.5% while that of children who were sleep deprived was at 39%. This shows there is a high association between the parents sleeping habits and those of their children. The patterns are closely related to the obesity rates among children which when combined for all children between the ages of 2-18 would result in nearly 50% obesity prevalence. Thus it can be argued that as sleep deprivation increases, the rate of obesity increases.
Conclusion
It is evident that there is an association between sleep duration and obesity. Statistical data proves that obesity depends on lack of sleep which agrees with the hypothesis of the study. However, the study identifies that although there seems to be an outright association between sleep and obesity, there are other factors which would affect the obesity prevalence such as health conditions of individuals, race and economic status. Nevertheless, these factors do not dilute the significance of the findings of this study.
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