THE IMPACT OF SLEEP QUALITY ON ENERGY INTAKE, EATING BEHAVIOR, AND PHYSICAL ACTIVITY. A THESIS IN Psychology

Transcription

1 THE IMPACT OF SLEEP QUALITY ON ENERGY INTAKE, EATING BEHAVIOR, AND PHYSICAL ACTIVITY A THESIS IN Psychology Presented to the Faculty of the University of Missouri Kansas City in partial fulfillment of the requirements for the degree MASTER OF ARTS by ASHLEIGH ANNE PONA B.S., John Carroll University, 2013 Kansas City, Missouri 2015

2 2015 ASHLEIGH ANNE PONA ALL RIGHTS RESERVED

3 THE IMPACT OF SLEEP QUALITY ON ENERGY INTAKE, EATING BEHAVIOR, AND PHYSICAL ACTIVITY Ashleigh Anne Pona, Candidate for the Master of Arts Degree University of Missouri Kansas City, 2015 ABSTRACT Obesity is associated with numerous health risks and is prevalent across all stages of the lifespan, although it tends to increase with age. As such, the college years are an important time for the development of obesity. Sleep behavior is a possible factor that may contribute to obesity; however, most studies that have examined this relationship have focused on sleep duration and not on sleep quality. Because the restorative nature of sleep depends on its quality in addition to quantity, it is important to measure sleep quality. The purpose of this study was to examine the impact of sleep quality on energy intake, eating behavior, and physical activity in a college sample. Participants completed self-report questionnaires measuring their sleep quality, dietary intake, eating behaviors, and physical activity. It was hypothesized that poor-quality sleepers would consume less protein and more carbohydrates, fat, and total calories compared to good-quality sleepers. It was also predicted that poor-quality sleepers would demonstrate increased hunger, disinhibition, and dietary restraint compared to good-quality sleepers. Finally, it was hypothesized that poor-quality sleepers would demonstrate lower frequencies of moderate, hard, and very hard physical activity compared to good-quality sleepers. These findings will contribute to the existing literature on sleep and obesity and will be important in the development of health promotion programs for college students. iii

4 APPROVAL PAGE The faculty listed below, appointed by the Dean of the College of Arts and Sciences, have examined a thesis titled The Impact of Sleep Quality on Energy Intake, Eating Behavior, and Physical Activity, presented by Ashleigh A. Pona, candidate for the Master of Arts degree, and certify that in their opinion it is worthy of acceptance. Supervisory Committee Jennifer D. Lundgren, Ph.D., Committee Chair Department of Psychology Seung-Lark Lim, Ph.D. Department of Psychology Laura E. Martin, Ph.D. Department of Preventive Medicine and Public Health University of Kansas Medical Center iv

5 CONTENTS ABSTRACT... iii LIST OF TABLES... vii Chapter 1. INTRODUCTION REVIEW OF THE LITERATURE... 2 Obesity... 2 Excess Energy Intake... 4 Decreased Energy Expenditure... 5 Sleep... 7 Sleep and Obesity... 9 Neuroendocrine Hormones Eating Behavior and Energy Consumption Energy Expenditure Factors Confounded with Sleep Summary Study Aims METHODOLOGY Procedures and Participants Measures Statistical Analyses Power Analysis RESULTS v

6 Descriptive Statistics Hypothesis One Results Hypothesis Two Results Hypothesis Three Results DISCUSSION Appendix A. PITTSBURGH SLEEP QUALITY INDEX B. DIETARY RECALL C. THREE-FACTOR EATING QUESTIONNAIRE D. NIGHT EATING QUESTIONNAIRE E. SEVEN-DAY PHYSICAL ACTIVITY RECALL F. STATE TRAIT ANXIETY INVENTORY G. BECK DEPRESSION INVENTORY H. PERCEIVED STRESS SCALE REFERENCE LIST VITA vi

7 TABLES Table 1. Studies on sleep duration and obesity Studies on sleep duration and neuroendocrine hormones Studies on sleep and energy consumption Participant characteristics Global and component PSQI scores for poor- and good-quality sleep groups Global BDI, STAI, and PSS scores for poor- and good-quality sleep groups Average quantities of protein, carbohydrates, fat, and calories consumed Average scores on NEQ (re-scored) and TFEQ scales Average minutes of varying intensity weekly physical activity vii

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9 CHAPTER 1 INTRODUCTION Obesity is associated with numerous health risks and is prevalent across all stages of the lifespan, although it tends to increase with age. As such, the college years in particular are an important time for the development of obesity. During the college years, students often move away from home for the first time, and their diet quality, physical activity, and sleeping habits can change due to school, work, and social schedules. Indeed, factors such as excess energy intake and decreased energy expenditure are the most common reasons thought to contribute to weight gain in college students. However, sleep has also been found to play an important role in the development of obesity and research has repeatedly found an association between reduced sleep and increased weight. There are various pathways through which sleep loss might adversely affect energy balance and lead to weight gain, including factors such as alterations in appetite and glucose regulation, increased food intake, and reduced energy expenditure. In order to work towards the prevention and treatment of obesity, it is important to study the relationship between sleep and obesity especially within the college population. The majority of previous studies have focused on the role of sleep duration in this relationship, and relatively few have investigated the role of sleep quality. Because the restorative nature of sleep depends on its quality in addition to quantity, sleep quality is an important variable to study and may have unique effects on eating behavior. Thus, the collection of sleep quality data will contribute to the existing literature on sleep and obesity and will be important in the development of health promotion programs for college students. 1

10 CHAPTER 2 REVIEW OF THE LITERATURE Obesity Overweight is defined as a body mass index (BMI) of 25 to 29.9 kg/m 2, and obesity as a BMI of greater than or equal to 30 kg/m 2 (National Institutes of Health, 1998). Overweight and obesity are associated with numerous health risks and are among the most significant contributors to ill health (Kopelman, 2007). For example, increasing BMI raises the risk of morbidity from health risks such as hypertension, type 2 diabetes, coronary artery disease, stroke, metabolic syndrome, and liver and gall bladder disease, to name a few (Kopelman, 2007). The prevalence of overweight and obesity is also extremely high across stages of the lifespan, and tends to increase with age. Data from the National Health and Nutrition Examination Survey in indicated that 8.1% of infants and toddlers from birth to 2 years, 16.9% of children and adolescents aged 2-19 years, and 34.9% of adults aged 20 years and older were considered obese (Ogden, Carroll, Kit, & Flegal, 2014; Ogden, Carroll, Kit, & Flegal, 2013). Given the numerous risks associated with overweight and obesity, reducing the high prevalence of increasing body weight has become a public health priority (U.S. Department of Health and Human Services, 2010). Because the prevalence of obesity tends to increase with age, the college years in particular are an important time for the development of obesity. In fact, during the past two decades, there has been a significant increase in obesity and obesity-related disorders among individuals in their teens and 20s (U.S. Department of Health and Human Services, 2001; Sparling, 2007). During the college years, students often move away 2

11 from home for the first time, and their diet quality and physical activity can change. For example, the freshman 15 is a widespread belief that college students gain 15 pounds during their freshman year, and this idea has been investigated by several researchers. Butler et al. (2004) found that freshman women who left home to attend college had an average increase in body weight of 1.59 pounds over a 20-week period. During this time, dietary energy intake actually decreased, which suggests that a significant reduction in physical activity could be responsible for the change in body weight (Butler, Black, Blue, & Gretebeck, 2004). However, given that baseline weight measurements were taken at the beginning of the school year, and later measurements were taken 5 months after, the increase in weight could have been due to heavier winter clothes at the time of measurement. Levitsky et al. (2004) also found that freshman students gained an average of 4.2 pounds during their first 12 weeks of college, and that consumption of junk foods explained the most variance in weight gain (explained 24% out of a total of 71% explained variance) after controlling for initial body weight. A third study used a sample of 125 freshman and found that 30% gained 1-5 pounds, 17% gained 6-14 pounds, and 5% gained more than 15 pounds during the first 7 months of college, with an average weight gain of 2.7 pounds (Mihalopoulos, Auinger, & Klein, 2008). Morrow et al. (2006) found a significant body weight increase of 2.4 pounds in a sample of freshman females during their first year of college and reported that subjects who gained weight tended to be less active than those who lost weight. Finally, Racette et al. (2005) found that 70% of students gained approximately 9 pounds during their first two years of college. In sum, although 15 pounds seems to be an overestimate, these studies provide support for the idea that some degree of weight gain is common during the college years. 3

12 Research on the freshman 15 helps to demonstrate why the college years are an important developmental transition period in terms of weight gain and why obesity develops into adulthood. Indeed, many of the effects of students eating habits during college continue into adulthood. Although different studies suggest different weight gains, there is a trend for weight gain to occur in college. Thus, in order to work towards the prevention and treatment of obesity, it is important to understand what factors are thought to contribute to obesity in college students. These potential factors are reviewed below. Excess Energy Intake Overweight and obesity are most commonly caused by excess energy intake relative to energy expenditure. In other words, when a person takes in more calories than they lose via metabolic and physical activity, they are likely to gain weight (Wright & Aronne, 2012). Excess caloric consumption is likely to occur from unhealthy diets high in fat, sugar, and sodium, and low in fiber, fruits, and vegetables (Ludwig et al., 1999). Research has found that such unhealthy diets are especially present amongst college students (Anding, Suminski, & Boss, 2001; Brevard & Ricketts, 1996; Racette, Deusinger, Strube, Highstein, & Deusinger, 2005). Several studies have demonstrated that college students are likely to adopt diets high in fat, sugar, and sodium. For example, Anding and colleagues (2001) found that two-thirds (66%) of female participants exceeded recommended levels of saturated fat and 20% exceeded recommended levels of cholesterol. In terms of the Dietary Guidelines for Americans, 92% and 65% of the female students consumed a diet high in sugar and sodium, and 83% consumed a high-fat diet (Anding et al., 2001). Brevard et al. (1996) 4

13 also found that students consumed higher levels of total fat, saturated fat, and monounsaturated fat than recommended amounts. Racette et al. (2005) studied the dietary pattern changes of students from freshman to sophomore year and found that, during freshman year, almost half consumed three or more fried foods and high-fat fast foods during the previous week (54% and 50%, respectively). During their sophomore year, the students consumption of high-fat fast foods stayed the same (47%); however, their consumption of fried foods declined (43%). Moreover, Lazarevich et al. (2013), who evaluated eating behavior among college students in Mexico City, found that 75% reported carbohydrate craving and 41.4% reported constantly feeling hungry and overeating. Multiple studies have also suggested that college students are not likely to consume the recommended amount of fiber, fruits, and vegetables. For example, Huang et al. (2003) found that students demonstrated an unhealthy diet by not meeting the recommended intake of at least 5 servings of fruits and vegetables per day or a minimum of 20 grams of dietary fiber per day. On average, the students reported consuming only 4.2 servings of fruits and vegetables and only 18 grams of fiber per day (Huang et al., 2003). Racette et al. (2005) also found that 70% of freshman consumed less than 5 fruits and vegetables daily, and Anding et al. (2001) found that 95% of female students did not consume the recommended amount of grains, fruits, and vegetables daily. Finally, Ferrara et al. (2013) found that only 23% of their student sample consumed five or more servings of fruits and vegetables, while 40% consumed only two servings or less. Decreased Energy Expenditure In addition to excess energy intake, decreased energy expenditure resulting from 5

14 physical inactivity also plays an important role in the development of obesity. During the past several decades, physical activity levels have dramatically decreased among U.S. adults, primarily due to sedentary lifestyles (Racette et al., 2005). For example, more time is now spent watching television, surfing the internet, and playing video games (Wright & Aronne, 2012). Furthermore, college students are known to have busy lifestyles filled with school, work, and social responsibilities; thus, students may be too tired or too busy to engage in the recommended amount of exercise. Indeed, research has shown that lack of regular exercise appears to be common amongst college students. In a study conducted by Haberman et al. (1998), 39% of students reported that they exercised 3 or more times per week, and 12.3% reported not exercising at all. In addition, Anding et al. (2001) found that 75% of female participants did not comply with the Dietary Guidelines for Americans guideline of obtaining regular physical exercise and maintaining a healthy weight. Huang et al. (2003) also surveyed students and found that a high percentage engaged in low physical activity, in which students reported engaging in exercise on only 2.8 days in the previous 7 days. Racette et al. (2005) found that only about half (59%) of their student participants engaged in regular aerobic exercise, and 30% did not engage in any exercise. Ferrara et al. (2013) also found a lack of physical activity in their student sample, where only 18% reported engaging in vigorous to moderate aerobic exercise for at least 20 to 30 minutes on five or more days, 36% reported exercising on three or four days, and 46% reported exercising on two or less days during the past week. Similar findings have also been observed among ethnically diverse college students. For example, Suminski et al. (2002) examined physical activity levels among 6

15 ethnically diverse college students and found that 47% of the total sample did not engage in vigorous physical activity, and 17% were inactive during the month before the study. In addition, Kelley et al. (1994) inquired about the activity levels of African-American freshman and found that approximately 42% of males and 65% of females were considered low or very low with regard to their level of physical activity. Sleep In addition to energy intake and expenditure, sleep has also been found to play an important role in the development of obesity. Specifically, research has shown that sleep restriction may cause increases in hunger and appetite (Spiegel, Tasali, Penev, & van Cauter, 2004). Indeed, as the prevalence of obesity has risen, there has been a parallel increase in work hours and sleep deprivation (Gupta, Mueller, Chan, & Meininger, 2002; Lerger, 2000). Although sleep plays an especially fundamental role in college a time when good health, productivity, and performance are imperative research suggests that sleep problems are of concern in this population. For example, school, work, and social schedules are common to the lifestyle of college students and may potentially interfere with sleep needs (Wolfson & Carskadon, 1996; Wolfson & Carskadon, 1998). Moreover, the prevalence rates of sleep problems (i.e., poor sleep quality) among college students have ranged from 9.7% to 54.7% across studies (Fernández-Mendoza et al., 2009; Cheng et al., 2012). According to the national data of the spring 2008 American College Health Association National College Health Assessment, 25.6% of student participants experienced sleep difficulties. In addition, 30.3% of students reported having at least 5 7

16 days of feeling fully rested in a week, and only 6.9% reported feeling fully rested every day of the week (American College Health Association, 2008). Sleep can be defined as an active and reversible state of perceptual disengagement from and unresponsiveness to external stimuli. (Carskadon & Dement, 2005). There are two domains that are commonly used to describe sleep: sleep quality and sleep duration. Sleep duration is an objective sleep domain and refers to the actual time during which an individual is asleep. Sleep quality, on the other hand, refers to the subjective indices of how sleep is experienced, including feeling rested when waking up and satisfaction with sleep (Pilcher, Ginter, & Sadowsky, 1997). Furthermore, it is well known among health professionals that sufficient, restorative sleep has a fundamental and important role in the maintenance of physical and mental health (Lund, Reider, Whiting, & Prichard, 2010). Although adequate sleep is crucial for good health, productivity, and performance, recent statistics have shown that sleep debt is becoming prevalent in industrialized countries (Ohayon & Partinen, 2002). The National Sleep Foundation suggests that most adults need 7 to 9 hours of sleep per night; however, this is not always the case. For example, in 2009 a sleep module was added to the Behavioral Risk Factor Surveillance System and revealed that, among 74,571 adult respondents in 12 states, more than one-third (35.3%) reported getting less than 7 hours of sleep per night on average (Centers for Disease Control and Prevention, 2011). The National Sleep Foundation 2013 Bedroom Poll yielded similar results, with 21% of U.S. adults getting less than 6 hours, and 32% getting 6 to 7 hours, of sleep on a typical weekday (National Sleep Foundation, 2013). Shorter sleep duration, as demonstrated by these statistics, can have multiple 8

17 negative psychological consequences. For example, shorter sleep duration has been significantly associated with higher levels of stress (Galambos, Vargas Lascano, Howard, & Maggs, 2013) and depression (Hamilton, Nelson, Stevens, & Kitzman, 2007). Relatedly, poor sleep quality has revealed similar effects, such that individuals who report poorer sleep quality have been found to consistently report higher scores on depressive symptoms (Pilcher et al., 1997) and perceived stress (Galambos, Dalton, & Maggs, 2009; Lund et al., 2010). Furthermore, troubled sleep can also lead to increased body weight and obesity. However, it is important to note that the relationship between sleep and mood, stress, and weight variables may be bidirectional in nature. As such, it is possible that increased depression, stress, and body weight may lead to sleep problems, as well as sleep problems may lead to increased depression, stress, and body weight. In conclusion, sleep is a unique factor that could explain the increase in obesity during the college years; however, this relationship has not been adequately evaluated in the college weight gain literature. The next section will review the literature on the relationship between sleep and obesity, primarily in the child and adult populations. Sleep and Obesity Sleep behavior is a possible factor that may contribute to obesity. As the prevalence of obesity has risen, there has been a parallel increase in work hours and sleep deprivation (Gupta, Mueller, Chan, & Meininger, 2002; Lerger, 2000). In addition, crosssectional studies in both children (von Kries, Toschke, Wurmser, Sauerwald, & Koletzko, 2002; Sugimori et al., 2004) and adults (Vioque, Torres, & Quiles, 2000; Cournot et al., 2004; Gangwisch, Malaspina, Boden-Albala, & Heymsfield, 2005) have repeatedly found an association between reduced sleep and increased weight, with adult studies suggesting 9

18 that the risk for obesity is much higher for individuals who sleep less than 7 hours per night. Furthermore, in a systematic review and meta-analysis by Cappuccio and colleagues (2008), a pooled odds ratio of 1.89 in children and 1.55 in adults was found for short sleep duration and its relationship with obesity. Table 1 outlines several studies that have examined the association between sleep duration and obesity. These studies demonstrate that shorter sleep duration (e.g., less than 6 hours per night) is associated with increased risks for obesity. 10

19 Table 1 Studies on sleep duration and obesity 11 First author (year) Study details Participant characteristics Results Cappuccio (2008) Sleep duration, meta-analysis Reviewed studies of adults and children Pooled OR for association between short sleep duration and obesity: children=1.89, adults=1.55 Chen (2008) Sleep duration, meta-analysis Reviewed studies of children OR=1.58 for short sleep duration and overweight/obesity compared to children/adolescents Gangwisch (2005) Sleep duration, cross sectional 9,588 adults, ages: Gupta (2002) Sleep duration 383 adolescents, ages: Sekine (2002) Sleep duration 8274 children, ages: 6-7 van den Berg (2008) Sleep duration 983 adults, ages: >55 Vioque (2000) Sleep duration 814 males, 958 females, ages: 15+ with a recommended level of sleep ORs of obesity for different sleep durations: OR=2.35 (2-4 hours/night), OR=1.60 (5 hours/night), OR=1.27 (6 hours/night), ORs of different sleep durations are compared to 7 hours of sleep per night OR=.20 for every hour of increased sleep time, the odds of obesity decreases by 80% ORs of obesity for different sleep durations: OR=1.49 (9-10 hours/night), OR=1.89 (8-9 hours/night), OR=2.87 (<8 hours/night), ORs of different sleep durations are compared to >10 hours of sleep per night OR=2.76 for obesity with a short sleep duration of <5 hours/night compared to participants sleeping 7-<8 hours per night Prevalence OR=.76, for each additional hour spent sleeping per day, risk of obesity decreases by 24%

20 There are various pathways through which sleep loss might adversely affect energy balance and lead to weight gain, including factors such as alterations in appetite and glucose regulation, increased food intake, and reduced energy expenditure (van Cauter & Knutson, 2008). These factors are reviewed below. Neuroendocrine Hormones Numerous studies have found that insufficient sleep is associated with a dysregulation of the neuroendocrine control of appetite, with a decrease in levels of the satiety hormone, leptin, and an increase in levels of the hunger-stimulating hormone, ghrelin (Taheri, Lin, Austin, Young, & Mignot, 2004; Spiegel, Leproult, & van Cauter, 1999; Spiegel et al., 2004; Guilleminault et al., 2003). Leptin is an anorexigenic hormone that helps regulate energy intake and expenditure, including appetite and hunger, metabolism, and behavior; whereas ghrelin is an orexigenic hormone that stimulates hunger and food intake, induces appetite and feeding behaviors, and reduces energy expenditure and promotes retention of fat (Taheri et al., 2004). As such, it has been proposed that these two hormones work together as a regulatory system to inform the brain about the current state of energy balance (Muccioli et al., 2002). Several studies have demonstrated the effect of sleep on appetite hormones. For example, in a study conducted by Spiegel and colleagues (1999), healthy young men were subjected to 6 nights of 4 hours in bed followed by 7 nights of 12 hours in bed, and all participants had the same caloric intake and amount of physical activity. The results from this study showed that mean leptin levels were lower and mean ghrelin levels higher during sleep restriction compared to sleep extension. Glucose levels were also elevated 12

21 following breakfast on the last day of sleep restriction, and participants disposed of glucose at a slower rate in response to an intravenous glucose tolerance test (Spiegel, Leproult, & van Cauter, 1999). Furthermore, the insulin response to glucose was 30% lower after sleep restriction, which may be an early sign of diabetes (Spiegel et al., 1999; Kahn, 1995). Spiegel and colleagues (2004) conducted a second study with a similar design where participants were subjected to 2 days of 4 hours in bed and 2 days of 10 hours in bed. The results replicated those from the first study in that mean leptin levels were 18% lower during sleep restriction compared to sleep extension. In addition, mean ghrelin levels also differed between the two conditions, and were found to be 28% higher during sleep restriction compared to sleep extension. Guilleminault et al. (2003) conducted a similar study where healthy men, aged 18 to 25 years, were subjected to 7 nights of 4 hours in bed followed by 3 nights of sleep recovery. The yielded results were comparable to that of Spiegel et al. (1999; 2004), where mean leptin levels were 33% lower after sleep restriction compared to sleep recovery. Furthermore, Taheri et al. (2004) used data from the Wisconsin Sleep Cohort Study that included over 1000 subjects and also found that short sleep duration was associated with decreased leptin and increased ghrelin levels. Schmid et al. (2008) subjected male participants to one night of 7 hours of sleep, one night of 4.5 hours of sleep, and one night of total sleep deprivation. Results showed that ghrelin levels were 22% higher after total sleep deprivation compared to 7 hours of sleep with intermediate levels of ghrelin after 4.5 hours of sleep (Schmid, Hallschmid, Jauch-Chara, Born, & Shultes, 2008). Hogenkamp et al. (2013) subjected young men to 13

22 one night of 8 hours in bed and one night of total sleep deprivation and found that subjects had a 13% increase in ghrelin levels the morning after total sleep deprivation. Finally, Benedict et al. (2011) subjected health male participants to either normal sleep or a night of total sleep deprivation and found that glucose levels decreased and late nocturnal ghrelin levels increased the morning after sleep deprivation. Table 2 outlines the aforementioned studies that have examined the association between sleep duration and neuroendocrine hormones. Thus, the findings of these studies suggest that reduced sleep duration may increase the risk of obesity by increasing appetite via decreases in leptin and insulin sensitivity, and increases in ghrelin. Eating Behavior and Energy Consumption It has been demonstrated that insufficient sleep can alter appetite and glucose regulation; the next step would be for these alterations to affect eating behavior by increasing energy intake. This appears to be the most plausible explanation as to why and how sleep contributes to obesity, and this relationship has been studied extensively. In one study, poor subjective sleep quality (as measured with the Pittsburgh Sleep Quality Index) was associated with eating behaviors characterized by increased hunger, uncontrolled and emotional eating (disinhibition), and more cognitive restraint over eating in a sample of adults at risk for type 2 diabetes (Kilkus et al., 2012). Although this sample of young adults reported more cognitive restraint over eating, they may be susceptible to failure of restraint because they also exhibited potentially problematic eating behaviors, such as uncontrolled and emotional eating (Kilkus et al., 2012; van 14

23 Strien, 1997). Another study subjected participants to 2 days of 4 hours in bed and 2 days of 10 hours in bed and found that subjective appetite was 23% higher during sleep 15

24 Table 2 Studies on sleep duration and neuroendocrine hormones First author (year) Benedict (2011) Guilleminault (2003) Study details normal sleep (~8 hours), total sleep deprivation 7 nights of 4 hours in bed, 3 nights of sleep recovery Participant characteristics 14 healthy males, mean age: 22.6, mean BMI: 23.9 Results During the morning after sleep deprivation, participants reported greater hunger and exhibited increased late nocturnal ghrelin levels and decreased glucose levels 8 young adult males In the sleep dept condition (4 hours in bed) participants exhibited decreased leptin levels 16 Hogenkamp (2013) Schmid (2008) Spiegel (1999) Spiegel (2004) night 1: 8 hours sleep night 2: total sleep deprivation night 1: 7 hours sleep night 2: 4.5 hours sleep night 3: total sleep deprivation 16 consecutive nights, night 1-3: 8 hours sleep, night 4-9: 4 hours sleep, night 10-16: 12 hours sleep 2 days of 4 hours in bed, 2 days of 10 hours in bed 16 males, mean age: 23, mean BMI: healthy young men, mean age: 24.2, mean BMI: healthy young men, ages: healthy men, mean age: 22, mean BMI: 23.6 During the morning after sleep deprivation, participants exhibited increased ghrelin levels In the total sleep deprivation condition participants exhibited increased ghrelin levels In the 7 hours sleep and 4.5 hours sleep conditions participant ghrelin levels did not differ In the sleep debt condition (nights 4-9) participants exhibited decreased insulin response to glucose, decreased glucose tolerance, decreased leptin levels, and increased ghrelin levels In the sleep dept condition (4 hours in bed) participants exhibited decreased leptin levels and increased ghrelin levels Taheri (2004) Data were collected with self-report sleep measures, a 6-day sleep diary, and polysomnography 1,024 adults, mean age: 52.7, mean BMI: 29.7 Short sleep duration was associated with decreased leptin levels and increased ghrelin levels

25 restriction compared to sleep extension (Spiegel et al., 2004). In addition, during sleep restriction participants had a greater craving for foods that were high in calories and carbohydrates than for other food types. Taken together, these results suggest that both the quality and duration of sleep can have effects on subjective eating behavior. Moreover, the relationship between sleep and eating behavior can be examined more objectively by measuring energy intake. For example, McNeil and colleagues (2013) had participants complete three-day food records and found a difference in carbohydrate intake between poor and good sleepers, with good sleepers ( ± 68.43g) consuming significantly more carbohydrates than poor sleepers ( ± 81.03g); however, the authors did not find any differences between sleep duration groups. In addition, the authors did not breakdown carbohydrate intake into specific food groups; thus, it is unknown whether the sleepers differed on fruit/vegetable intake, breads/grains, and/or snack foods, for example. Furthermore, there were no differences between groups for total energy, fat, or protein intake (McNeil et al., 2013). A final study examined two groups of sleepers subjects who slept <7 hours per night and subjects who slept 7-8 hours per night and found that shorter sleepers demonstrated an increase in fast food and high-fat food consumption and a decrease in fruit and vegetable consumption (Stamatakis & Brownson, 2008). Because sleep is known to affect energy consumption, and college is a time when weight gain is common (i.e., the freshman 15 ), it is important to examine the relationship between sleep and energy consumption within the college population. However, there have been a limited amount of studies that have examined this relationship. Haghighatdoost and colleagues (2012) conducted a study with female 17

26 students, aged 18 to 28 years old, and found that subjects with a sleep duration of less than 6 hours a day had a higher intake of energy than those with a sleep duration of more than 8 hours a day (2406 ± 825 versus 2092 ± 700 kcal). In addition, the mean percentages of protein and carbohydrate intake were 14% and 58% for the short sleepers and 19% and 52% for the long sleepers; thus, short sleepers consumed significantly more carbohydrates and significantly less protein in comparison to long sleepers. In terms of food groups, short sleepers consumed significantly less fruits, whole grains, and beans than long sleepers. In terms of nutrients, short sleepers had a significantly lower mean intake of niacin, vitamin C, and vitamin B12 as compared to long sleepers (Haghighatdoost, Karimi, Esmaillzadeh, & Azadbakht, 2012). In a second study conducted by Hicks and colleagues (1986), college students responded to a sleep habits questionnaire and recorded the number and timing of all meals and snacks for a typical day. Results showed that short sleepers (6 or less hours of sleep per night) were more likely to deviate from the normal three meals a day pattern and ate more small meals and snacks as compared to long sleepers (8 or more hours of sleep per night) (Hicks, McTighe, & Juarez, 1986). Schmid et al. (2008) subjected male participants to one night of 7 hours of sleep, one night of 4.5 hours of sleep, and one night of total sleep deprivation and found that subjects perceived stronger feelings of hunger after total sleep deprivation than after 7 hours of sleep or 4.5 hours of sleep. Additionally, hunger feelings did not significant differ between 7 and 4.5 hours of sleep. Hogenkamp et al. (2013) subjected young men to one night of 8 hours in bed and one night of total sleep deprivation and found that subjects chose larger portion sizes during breakfast and their self-reported hunger was enhanced after total sleep deprivation. 18

27 Furthermore, Benedict et al. (2011) subjected male participants to either normal sleep or total sleep deprivation and found that participants reported greater levels of hunger on visual analogue scales during the morning following sleep deprivation. Table 3 outlines the aforementioned studies that have examined the association between sleep and energy consumption. In addition to energy consumption from food, research has also investigated the relationship between sleep and alcohol and caffeine intake. Research has demonstrated that consumption of alcohol and caffeine interferes with sleep quality. For example, in a study by Nakade and colleagues (2009), students who consumed more alcohol exhibited higher unhealthy sleep scores than those who did not drink. Moreover, Hicks and colleagues (1983) discovered an inverse relationship between caffeine use and sleep duration in college students. Although caffeine is thought to enhance performance, research suggests that under conditions of habitual sleep caffeine merely restores performance degraded by sleepiness, which may be due to basal sleep insufficiency and circadian sleep schedule reversals (Roehrs & Roth, 2008). However, Hicks and colleagues (1983) found no relationship between caffeine use and sleep satisfaction. Furthermore, Lund and colleagues (2010) found that alcohol and caffeine consumption were not significant predictors of sleep quality in a college population. Taken together, these findings suggest that sleep problems are common within the college population and that sleep deprivation does affect eating behavior and energy consumption. However, due to the limited amount of studies investigating this relationship in college students, further research is needed to replicate and extend these findings. 19

28 Energy Expenditure In addition to alterations in appetite and glucose regulation, sleep disturbance may also lead to reduced energy expenditure. Although there are no published studies on the relationship between sleep and energy expenditure in college students specifically, there is some research examining this relationship in the general child/adolescent and adult populations. Within the child/adolescent population, Gupta and colleagues (2002) found that the amount of daytime physical activity in adolescents was inversely associated with sleep disturbance time; where for every hour of sleep disturbance, there was a 3% decrease in daytime physical activity. The results also showed that for every hour of increased sleep time, the odds of obesity decreased by 80%. Garaulet et al. (2011) also found that adolescents who slept less than 8 hours per day were more sedentary as assessed by accelerometry. Wennman et al. (2014) investigated the relationship between physical activity and sleep in adults and found that the likelihood for high leisure time physical activity co- 20

29 Table 3 Studies on sleep and energy consumption 21 First author (year) Bosy-Westphal (2008) Brondel (2010) Study details One group design, long term study 2 nights: >8 hours sleep; 4 nights: sleep curtailment (7 hrs, 6 hrs, 6 hrs, 4 hrs), 2 nights: sleep recovery (>8 hrs) 2-condition crossover design, acute sleep deprivation (48 hour study), 8 hours of sleep, 4 hours of sleep, standardized meals Participant characteristics 14 healthy females, ages: 23-38, BMIs: male students, ages: 18-29, BMIs: normal ( ) Outcome measures Energy intake (self-report record), Body weight Energy intake (self-report record), Hunger Results During sleep loss period, energy intake increased by 20% (mean increase was 415 cal/day), mean body weight increased by 400 grams, and plasma leptin levels increased by 24% In the 4 hours of sleep condition, participants exhibited greater hunger before breakfast and dinner, had a greater total energy intake, and had an increased consumption of fats Calvin (2013) Parallel-group design, long-term study, experimental = 8 days/8 nights, recovery =4 days/3 nights, control = ad lib sleep duration, sleep deprivation = 2/3 of normal sleep time, food ad lib 17 adults (11 male, 6 female), ages: 18-40, BMIs: normal ( ) Energy intake (dieticians assessed using receipts of food and nutritional labels) During the sleep deprivation condition, participants exhibited an increase in total energy intake table continues

30 22 First author (year) Grandner (2013) Haghighatdoost (2012) Kilkus (2012) Study details Self-report measurements of sleep and energy intake: sleep: "how much sleep do you usually get at night on weekdays or workdays?" energy intake: 24 hour recall Sleep groups: very short (<5 hours), short (5-6 hours) normal (7-8 hours) long (9+ hours) Cross-sectional study, Self-report measurements of sleep and energy intake 14 days of sleep monitoring at home; 1 night of lab polysomnography (8.5 hours); used Pittsburgh Sleep Quality Index to assess subjective sleep quality Participant characteristics 4548 adults, mean age: 46.3, mean BMI: female students, ages: healthy adults, parental history of type-2 diabetes, ages: 21-40, BMIs: Outcome measures Total energy intake, Macronutrient intake Energy intake (food frequency questionnaire), Body weight Eating behavior (Three-Factor Eating Questionnaire) Results The short sleep group had the highest total energy intake and the highest intake for all fats (saturated, monounsaturated, polyunsaturated, cholesterol). The very short sleep group had the lowest total energy intake and the lowest consumption of protein and carbohydrates Subjects who slept <6 hours a night were more likely to be overweight and obese, consumed more dietary energy and carbohydrates, and consumed less fiber, protein, and fruits Reduced subjective sleep quality (higher Pittsburgh Sleep Quality Index score) was associated with increased hunger, uncontrolled and emotional eating, and more cognitive restraint table continues

31 23 First author (year) Markwald (2013) Nedeltcheva (2009) Schmid (2008) Study details 2-condition crossover design, long-term study: 14 days, 5 days in either 5-hour or 9-hour sleep condition 2-condition crossover design, long-term study (two 14-day periods), hours of sleep: 5.5 or 8.5, dietician made individual meal plans 3 nights: night 1: 7 hours of sleep night 2: 4.5 hours of sleep night 3: total sleep deprivation Participant Outcome characteristics measures 16 adults Ad libitum energy intake, Satiety and hunger hormones 11 sedentary adults (6 male, 5 female), ages: 34-49, BMIs: overweight (24-29) 9 healthy males, normal weight Energy intake (weighed food before and after) Feelings of hunger (self report Likert scale from 1-9) Results During the 5-hour condition: 24-hour food intake was 6% greater than in the 9-hour condition, subjects consumed more carbohydrates, subjects consumed 42% more calories as after dinner snacks (which contained more carbohydrates, protein, and fiber) than in the 9-hour condition, more calories were consumed at night after dinner than calories consumed for an individual meal, average 24-hour leptin levels increased by 22%, average 24-hour ghrelin levels decreased by 30% (and by 21% in 9-hour condition) During the 5.5 hours of sleep condition, participants showed an increased consumption of energy from snacks (late-night) and a greater total energy intake (due mostly to snacks, not meals) However, the difference in total energy intake was no longer significant after baseline weight was controlled Participants perceived stronger feelings of hunger after total sleep deprivation than after 7 or 4.5 hours of sleep Hunger feelings did not significantly differ between 7 and 4.5 hours of sleep. table continues

32 24 First author (year) Spaeth (2013) St-Onge (2011) Study details Repeated measures design, long-term study 2 baseline nights (10-12 hours of sleep), 5 experimental nights (4 or 10 hours of sleep), 2 recovery nights (12 hours of sleep) 2-condition crossover design, long-term (two 6-day periods), hours of sleep: ~4 or ~9, controlled food intake first 4 days, ad lib last 2 days Participant characteristics 37 adults, ages: 22-50, BMIs: adults (13 men, 13 women) ages: means 36.3 (5.6), 33.9 (4.3) BMIs: means 24.1 (1.1), 23 (1.1) Outcome measures Energy intake (weighed/recorded by study personnel), Macronutrients Ad lib energy intake weighed and recorded by personnel Results For the control participants (those who were assigned to the 10 hours of sleep experimental condition), caloric intake did not differ across protocol days. For participants who were assigned to the sleep restriction condition (4 hours of sleep), they consumed more calories during the experimental night than during baseline and recovery nights; they consumed more calories than control participants during experimental phase; they consumed more grams of protein, carbohydrates, and fats on experimental nights versus baseline or recovery nights; they consumed more meals during experimental nights than during baseline or recovery nights; and they consumed larger meals during experimental nights versus baseline or recovery nights During the short sleep (-4 hours) condition participants exhibited greater energy intake, greater fat and saturated fat intake, and ate more often (more eating occasions)

33 occurs with normal sleep range and subjective sleep satisfaction. Furthermore, their findings also suggested that risk factors for low physical activity included a subjective feeling of not sleeping enough, short sleep duration, and being an evening type (Wennman et al., 2014). In a study conducted by Schmid et al. (2009), 15 healthy men were subjected to 2 nights of 8.25 hours in bed and 2 nights of 4.25 hours in bed, and physical activity was measured by accelerometry. Results showed that sleep restriction significantly decreased physical activity after the first night of sleep manipulation, and the intensities of physical activity were also shifted towards lower levels, resulting in less time spend engaging in intense activities (Schmid et al., 2009). Factors Confounded with Sleep Several additional factors can affect weight gain and are often confounded with sleep. These factors will be controlled for in the analyses of this thesis and are described here. These include stress, mood/anxiety, and gender. For example, in a meta-analysis on the effect of stress on eating behavior, and how stress-induced eating may contribute to the development of obesity, researchers concluded that stress appears to both increase and decrease food intake (Torres & Nowson, 2007). Additionally, when individuals respond to stress by eating more, the authors state there is evidence that suggests the selected foods are usually high in sugar and fat (Torres & Nowson, 2007). Anxiety may also alter eating behavior by decreasing energy intake. For example, according to Herman and colleagues (1987), normal (i.e, nonobese and nondieting) individuals who are responsive to their physiological state, are expected to react to anxiety by eating less. 25

34 Mood has also been shown to affect eating behavior. One study induced either a depressed or nondepressed mood in obese and nonobese dieters and nondieters (Baucom & Aiken, 1981). Results showed that dieters ate more when depressed than when nondepressed, and nondieters ate less when depressed than when nondepressed. In other words, both groups reversed their typical eating patterns when depressed. The eating behaviors of depressed and nondepressed students were also examined. The authors found that, among depressed students, dieters ate more than nondieters; among nondepressed students, dieters ate less than nondieters. This pattern was found both for obese and nonobese students (Baucom & Aiken, 1981). In another study investigating mood, participants were asked to record everything they ate over a 2-week period, including their moods during the meals. Results showed that meals eaten in positive and negative moods were significantly larger than meals eaten in a neutral mood (Patel & Schlundt, 2001). Furthermore, gender differences in eating behavior are also commonly observed. For example, the energy needs of men continue to exceed those of women. In terms of food choices, men have been found to eat fewer fruits, vegetables, and low-fat foods compared to women (Li et al., 2000; Liebman, Cameron, Carson, Brown, & Meyer, 2001). Moreover, research has also found women to be more likely to diet and attach greater importance to healthy eating than men, which can influence their food choices and energy intake (Wardle, Haase, & Steptoe, 2004). Taken together, these findings suggest that other factors, such as stress, mood, anxiety, and gender, may affect eating behavior and, thus, should be taken into consideration when assessing the relationship between sleep and eating behavior. 26

35 Summary In summary, the prevalence of overweight and obesity is extremely high across stages of the lifespan, and tends to increase with age. As such, the college years in particular have been suggested to be an important time for the development of obesity. Factors that are thought to contribute to obesity in college students include excess energy intake, decreased energy expenditure, and sleep. The various pathways through which sleep loss might lead to weight gain include factors such as alterations in appetite and glucose regulation, increased food intake, and reduced energy expenditure. In order to work towards the prevention and treatment of obesity, it is important to study the relationship between sleep and obesity especially within the college population. Furthermore, while most studies have focused on the role of sleep duration in this relationship, relatively few have investigated the role of sleep quality. Study Aims There are two main rationales for conducting this study. First, not much is known about the relationship between sleep and obesity in the college population. The majority of studies investigating this relationship have focused on more general populations, such as child/adolescents and adults. It is important to take a closer look at this relationship in college students as the college years in particular have been suggested to be an important time for the development of obesity. The college years have been shown to be a critical period for weight gain. The second rationale for conducting this study is that most studies that have examined the link between sleep and obesity have focused on sleep duration and not on sleep quality. While sleep duration is an objective measure which refers to the actual time during which an individual is asleep, sleep quality is subjective and more 27

36 multi-dimensional, measuring how sleep is experienced, including feeling rested when waking up and satisfaction with sleep. As such, although an individual may get 8 hours of sleep a night which is the recommended duration they may not feel rested when waking up. This suggests that the restorative nature of sleep depends on its quality in addition to quantity and, thus, sleep quality may have unique effects on eating behavior. The purpose of the current study is to extend the existing literature on sleep and eating behavior by assessing sleep quality, rather than sleep duration alone, to a sample of college students. This study has three aims and three hypotheses: Aim 1: To compare the energy intake and macronutrients of poor- and goodquality sleepers, using dietary recall data. Hypothesis 1: Poor-quality sleepers will consume less protein and more carbohydrates, fat, total calories, alcohol, and caffeine compared to good-quality sleepers. Aim 2: To compare the eating attitudes and behaviors of poor- and good-quality sleepers, using the Three-Factor Eating Questionnaire and Night Eating Questionnaire. Hypothesis 2: Poor-quality sleepers will demonstrate increased hunger, disinhibition, and rigid control, and decreased flexible control, on the Three-Factor Eating Questionnaire, and will score higher on the Night Eating Questionnaire, compared to good-quality sleepers. Aim 3: To compare levels of physical activity of poor- and good-quality sleepers, using the Seven-Day Physical Activity Recall. Hypothesis 3: Poor-quality sleepers will demonstrate lower frequencies of moderate, hard, and very hard physical activity compared to good-quality sleepers. 28