Gandhi is a PhD student Anthropology at UNM.
This research was made possible in part by funding from the Latin American & Iberian Institute and Tinker Foundation Field Research Grant (FRG). For more information about the FRG, please visit the LAII website.
Courtesy of author. Tsimané family. I spent June to December of 2013 in the rainforest of Bolivia among an indigenous group known as the Tsimané. They live as hunter-horticulturalists in an environment with minimal market integration, no electricity, natural fertility, and a subsistence lifestyle. I studied their sleep patterns using wrist-worn sleep monitors and interviews. I hypothesize that their sleep duration is determined by a tradeoff between the need for rest and bodily repair and opportunity costs of sleep, as productive nighttime activity. The environment in which the Tsimané live is more similar to that in which humans evolved than that of contemporary US and western society where electricity and wage labor obscure the relationship between sleep and wake activity. The preliminary analysis of my dataset supports this tradeoff model, and when fully developed will become my dissertation.
Sleep is defined by three main criteria: relative inactivity; increased threshold for reaction to stimuli; and a “debt” accruing when organisms sleep for a shorter amount of time than “normal” (Campbell, 1984; McNamara et al. 2009). All animals tested thus far, from drosophila to all major vertebrate groups, exhibit behavior that match these criteria (Siegel, 2007; Hendricks, 2008). Despite this, the actual function and necessity of sleep are only beginning to be explored. Sleep deprivation studies have shown that a lack of sleep is associated with decreased energy levels, decreased insulin sensitivity, slower reaction time, impaired cognitive function, increased risk of obesity and heart disease, depression, and, in mice models, eventually death (St-Onge, 2011; Bonnet, 2000; Buxton, 2012; Knutson, 2007).
These provocative findings have fed into a paradigm shift away from common perceptions of sleep as a time wasting nuisance. There is mounting support for the view that sleep provides a vital function for healthy human and animal physiological maintenance (National Sleep Foundation, 2014a). Recent studies have focused on neurological mechanisms of sleep, circadian hormonal rhythms that regulate sleep, and the disruption of circadian hormonal rhythms by impaired sleep (Saper, 2005; Achermann & Borbely, 2003). One frustration many of these studies run into is the lack an objective measures of sleep for comparison. Most of these study samples are from US and other western societies where wage labor, television, and even electrical lighting may distract individuals thus impeding their ability to attain an appropriate or desirable amount of sleep. Indeed, there is still quite a bit of contention in the field about what the optimal sleep duration really is. This has been a source of frustration in the medical field where doctors lack a validated number of hours per night to recommend to their patients experiencing sleep disorders or any other of the above listed consequences of impaired sleep (National Sleep Foundation, 2014b).
A few studies, particularly in anthropology, are starting to expand their study sample to non-western cultures in an endeavor to alleviate this frustration (Worthman, 2013; Knutson, 2014). Cross-cultural comparison shows that the average number of hours of sleep per night is in the 7-8 hour range (Worthman, 2013; Knutson, 2014). While these studies have yielded some valuable insight, their findings would be greatly bolstered by studies conducted among subsistence populations, particularly those without electricity. It has been established that melatonin, which regulates our desire to sleep, is inhibited by exposure to electrical lighting and television after sunset (Wright, 2013). The effect of this hormonal change is that people stay awake much later into the night, and may be sleeping less as a result. In populations without electricity, natural lighting is hypothesized to strongly regulate circadian rhythms (Wright, 2013). Furthermore, the link between physical activity and work returns is less variable than in market-integrated populations. In the US, where there is a diverse division of labor, time spent working reflects differing levels of physical activity corresponding to vocation. By contrast, the Tsimané typically perform similar kinds of work such as hunting, fishing, planting, harvesting. Time spent working represents a particular profile of energy expenditure that is fairly consistent from one person to the next. Therefore, the hypothesis that sleep functions to maintain the body can thus be more precisely studied in these populations, since the need to provide food for oneself and one’s family will be balanced by the need to rest and recover from the tissue insult accrued by performing physical work. This approach also allows for a more effective examination of how tradeoffs between maintenance and work change throughout the course of life. Since humans evolved in subsistence environments, an examination of tradeoffs among living foragers and horticulturalists today can yield insight into sleep in western populations and aid the search for the target ‘normal’ amount of sleep people require on an average night.
Specific Aims:
To complement neurological lab studies and follow-up on recent cross-cultural studies on sleep, we undertake a new study to understand the environment in which human sleep evolved. A rich image of sleep within a subsistence population would be useful to frame other studies that explain why average sleep patterns may be observed to follow a certain pattern across the life course in men and women.
1. We aim to measure the age and sex profiles of average sleep duration. In order to get a reasonable profile and reduce error, both intra and inter individual measures will be recorded.
a. We hypothesize that the overall adult average sleep onset to be around 9PM and waking to be around dawn each morning. In comparison to other recent studies on populations with artificial lighting, this is expected to be an earlier average sleep onset and waking.
b. Based on preliminary data, we hypothesize that young women will sleep more than young men, but older women will sleep less than older men.
With this base profile established, a more in-depth analysis can be attempted to explain the variance seen within that profile. Age and sex trends suggest several hypotheses of potential drivers of increased or reduced sleep on a given night.
2. We aim to synthesize a multi-factor model that explains sleep duration on a given night.
a. We hypothesize that childcare is a significant predictor of reduced sleep on a given night. This hypothesis is motivated by prior observations of lower sleep duration in the age categories that tend to be associated with having young children in the family.
b. We hypothesize that daily work and energy expenditure will predict longer sleep duration, but nightly work and energy expenditure will predict shorter sleep duration. These hypotheses are supported by the general early-to-bed, early-to-rise rhythm seen in populations that lack electricity, as well as by observations of prevalent night hunting and fishing.
c. We hypothesize that impaired health will increase sleep duration on a given night. Large sample US studies have shown a U shaped mortality curve associated with sleep duration. The connection between long sleep duration and mortality may be driven by a spurious correlation, where impaired health and infection may lead to both higher mortality rate and longer sleep duration.
One complicating factor in studying sleep in this way is the cyclical nature of sleeping and waking, which creates bidirectional causality. Indeed, correlations observed in a non-experimental study are a serious concern in studies of this type. As such, an examination of downstream effects of variance in sleep may serve as a valuable compliment to the study already presented.
3. We aim to examine benefits and consequences of variance in sleep duration on a given night. This allows for an examination of the effects of sleep more or less than average for given age, sex, work, and health considerations.
a. We hypothesize that people who sleep less than predicted according to the considerations listed in aim 2 will show reduced productivity, higher fatigue, and higher rates of ill-health on a given day than people who sleep more than average according to these same considerations.
By studying sleep in this way, we hope to arrive at an ecological understanding of time allocation decisions and tradeoffs. Insight in this area will complement lab studies on how sleep affects physiological mechanisms and suggest some ways in which these biological consequences may end up impacting health in the short term. It may direct future hypotheses on how natural selection has shaped sleep in human evolution and serve as a foundation to understand how primate and mammalian sleep varies with ecology.
These provocative findings have fed into a paradigm shift away from common perceptions of sleep as a time wasting nuisance. There is mounting support for the view that sleep provides a vital function for healthy human and animal physiological maintenance (National Sleep Foundation, 2014a). Recent studies have focused on neurological mechanisms of sleep, circadian hormonal rhythms that regulate sleep, and the disruption of circadian hormonal rhythms by impaired sleep (Saper, 2005; Achermann & Borbely, 2003). One frustration many of these studies run into is the lack an objective measures of sleep for comparison. Most of these study samples are from US and other western societies where wage labor, television, and even electrical lighting may distract individuals thus impeding their ability to attain an appropriate or desirable amount of sleep. Indeed, there is still quite a bit of contention in the field about what the optimal sleep duration really is. This has been a source of frustration in the medical field where doctors lack a validated number of hours per night to recommend to their patients experiencing sleep disorders or any other of the above listed consequences of impaired sleep (National Sleep Foundation, 2014b).
A few studies, particularly in anthropology, are starting to expand their study sample to non-western cultures in an endeavor to alleviate this frustration (Worthman, 2013; Knutson, 2014). Cross-cultural comparison shows that the average number of hours of sleep per night is in the 7-8 hour range (Worthman, 2013; Knutson, 2014). While these studies have yielded some valuable insight, their findings would be greatly bolstered by studies conducted among subsistence populations, particularly those without electricity. It has been established that melatonin, which regulates our desire to sleep, is inhibited by exposure to electrical lighting and television after sunset (Wright, 2013). The effect of this hormonal change is that people stay awake much later into the night, and may be sleeping less as a result. In populations without electricity, natural lighting is hypothesized to strongly regulate circadian rhythms (Wright, 2013). Furthermore, the link between physical activity and work returns is less variable than in market-integrated populations. In the US, where there is a diverse division of labor, time spent working reflects differing levels of physical activity corresponding to vocation. By contrast, the Tsimané typically perform similar kinds of work such as hunting, fishing, planting, harvesting. Time spent working represents a particular profile of energy expenditure that is fairly consistent from one person to the next. Therefore, the hypothesis that sleep functions to maintain the body can thus be more precisely studied in these populations, since the need to provide food for oneself and one’s family will be balanced by the need to rest and recover from the tissue insult accrued by performing physical work. This approach also allows for a more effective examination of how tradeoffs between maintenance and work change throughout the course of life. Since humans evolved in subsistence environments, an examination of tradeoffs among living foragers and horticulturalists today can yield insight into sleep in western populations and aid the search for the target ‘normal’ amount of sleep people require on an average night.
Specific Aims:
To complement neurological lab studies and follow-up on recent cross-cultural studies on sleep, we undertake a new study to understand the environment in which human sleep evolved. A rich image of sleep within a subsistence population would be useful to frame other studies that explain why average sleep patterns may be observed to follow a certain pattern across the life course in men and women.
1. We aim to measure the age and sex profiles of average sleep duration. In order to get a reasonable profile and reduce error, both intra and inter individual measures will be recorded.
a. We hypothesize that the overall adult average sleep onset to be around 9PM and waking to be around dawn each morning. In comparison to other recent studies on populations with artificial lighting, this is expected to be an earlier average sleep onset and waking.
b. Based on preliminary data, we hypothesize that young women will sleep more than young men, but older women will sleep less than older men.
With this base profile established, a more in-depth analysis can be attempted to explain the variance seen within that profile. Age and sex trends suggest several hypotheses of potential drivers of increased or reduced sleep on a given night.
2. We aim to synthesize a multi-factor model that explains sleep duration on a given night.
a. We hypothesize that childcare is a significant predictor of reduced sleep on a given night. This hypothesis is motivated by prior observations of lower sleep duration in the age categories that tend to be associated with having young children in the family.
b. We hypothesize that daily work and energy expenditure will predict longer sleep duration, but nightly work and energy expenditure will predict shorter sleep duration. These hypotheses are supported by the general early-to-bed, early-to-rise rhythm seen in populations that lack electricity, as well as by observations of prevalent night hunting and fishing.
c. We hypothesize that impaired health will increase sleep duration on a given night. Large sample US studies have shown a U shaped mortality curve associated with sleep duration. The connection between long sleep duration and mortality may be driven by a spurious correlation, where impaired health and infection may lead to both higher mortality rate and longer sleep duration.
One complicating factor in studying sleep in this way is the cyclical nature of sleeping and waking, which creates bidirectional causality. Indeed, correlations observed in a non-experimental study are a serious concern in studies of this type. As such, an examination of downstream effects of variance in sleep may serve as a valuable compliment to the study already presented.
3. We aim to examine benefits and consequences of variance in sleep duration on a given night. This allows for an examination of the effects of sleep more or less than average for given age, sex, work, and health considerations.
a. We hypothesize that people who sleep less than predicted according to the considerations listed in aim 2 will show reduced productivity, higher fatigue, and higher rates of ill-health on a given day than people who sleep more than average according to these same considerations.
By studying sleep in this way, we hope to arrive at an ecological understanding of time allocation decisions and tradeoffs. Insight in this area will complement lab studies on how sleep affects physiological mechanisms and suggest some ways in which these biological consequences may end up impacting health in the short term. It may direct future hypotheses on how natural selection has shaped sleep in human evolution and serve as a foundation to understand how primate and mammalian sleep varies with ecology.
Courtesy of author. Reenactment of interview. Methods:
This project is conducted as an integrated part of the Tsimané Health and Life History Project (THLHP), directed by Dr. Hillard Kaplan of the University of New Mexico and Dr. Michael Gurven of the Univserity of California at Santa Barbara. It was designed and managed directly by the author, with the financial backing of LAII, GPSA, OGS, and the THLHP. Due to the multi-dimensional nature of the variables required to address the aims, several different methodologies are employed, some directly by the author and others by other THLHP personnel under direction and supervision of the author.
All sleep data is collected directly by the author, using a bipartite strategy of interview and wrist-worn digital accelerometry. Accelerometers are small, watch-like devices that record motion. For studying sleep, this method has been validated against the field’s ‘gold-standard’ methodology of electro encephalograms (EEG), which function by means of measuring electrical signals in the brain during sleep (Capellini, 2009). Due to the remote nature of the field site and the requirement of sleeping in a laboratory to conduct EEG, accelerometers are a more appropriate methodology for this project (de Souza, 2003). In addition, the accelerometers used also record ambient light during the observation period. Together, the accelerometers are recording both sleep vs. wake data as well as ambient light levels over 24 hours.
Interviews were devised in Bolivia while conducting two months of ethnographic background research on Tsimané sleep. After finalizing the interview form, interviews were performed three days in a row during the overall observation period of four days, three nights. These interviews also included questions about night-time childcare, night-time work, and fatigue.
Daily activity, productivity, energy expenditure, and medical data are all collected as parts of existing projects within the THLHP. All study participants are offered free doctor’s examinations during which time, if permission is given, data is recorded regarding symptoms, infection, and treatment of medical issues. For those who also volunteer blood, urine, and/or fecal samples are taken and used to improve diagnoses and recorded for analysis.
Daily activity, productivity, and energy expenditure are recorded as part of a separate anthropological project on sharing and energy expenditure, by means of accelerometry and extensive interviews. Accelerometers using energy expenditure algorithms assess calories burned per day. This has been validated against the field ‘gold-standard’ of doubly labeled water, which administers special water samples composed of hydrogen and oxygen isotopes. As the body burns calories, this water is metabolized, which results in a changing pattern of hydrogen and oxygen isotopes in urine, which indicate calories burned during the observation period. The doubly labeled water methodology is extremely expensive, but accelerometers have been validated and are used due to their inexpensive nature and accuracy in data collection on energy expenditure.
Study Population:
This study is being conducted with the Tsimané, a subsistence population living in lowland tropical Bolivia. This group has been studied extensively since 2004, when the THLHP began in Bolivia. Their economic system is best described as hunter-horticulturalist, where swidden planting occurs on a small scale. Their remote location lacks electricity in the vast majority of communities. Each planting field generally serves a single family or family cluster. Diet is primarily composed of corn, rice, manioc, and plantain grown in. Meat primarily comes from hunting and fishing. Both men and women work in the planting fields extensively, and both sexes fish regularly. Hunting is primarily conducted by men. Average fertility per woman is 8 children. Families build their own homes out of wood and woven leaves, and typically move once every 5-8 years. Rates of infectious disease are quite high, primarily due to parasite infested river water and mosquito-borne pathogens. The Tsimané speak their own indigenous language, though many within the study population have learned Spanish due to a higher degree of integration with the larger local Bolivian society. For this reason, the study is conducted with the aid of Tsimané-Spanish translators, and some parts are even conducted in Tsimané directly.
Conclusions:
While a complete data-analysis will require several months of careful examination to completely address all aims listed, some preliminary analyses suggest support for several of the hypotheses. It appears that young women (age range 13-25) tend to sleep more than young men, until they have a baby. Women with babies and young children sleep far fewer hours per night and wake up frequently. Young men tend to sleep less because frequently hunt, fish, or visit friends at night. Older women (age range 60-80) tend to sleep less than older men, largely due to their role in child care nocturnal work such as laundry, mending clothes, weaving roofing material for sale, or weaving mats and baskets for household use.
While statistical strength of the models proposed for aims 2 and 3 are as yet unanalyzed. Yet, qualitative preliminary analyses support the models, suggesting that illness, fatigue, and higher energy expenditure and productivity among older individuals leads to longer sleep duration. Shorter sleep duration appears to be associated with increased fatigue and reduced productivity the following day, especially among older individuals. Overall, the data appear promising and several of the listed hypotheses are supported.
References:
Achermann, P, and Borbely, A. 2003. Mathematical models of sleep regulation. Frontiers in Bioscience vol. 8:683-693.
Bonnet, M. 2000. Sleep deprivation. In: Kryger MH, Roth T, Dement WC, ed. Principles and practice of sleep medicine, 3rd ed. Philadelphia, PA: Saunders. 53-71.
Buxton, O., et al. 2012. Adverse metabolic consequences in humans of prolonged sleep restriction combined with circadian disruption. Science Translational Medicine vol. 4, no. 129.
Campbell, S., and Tobler, I. 1984. Animal sleep- a review of sleep duration across phylogeny. Neuroscience and Biobehavioral Reviews vol. 8: 269-300.
Capellini, I., et al. 2009. Ecological constraints on mammalian sleep architecture. In: The Evolution of Sleep, eds. McNamara, P., Barton, B., Nunn, C. Cambridge: Cambridge University Press.
de Souza, L., et al. 2003. Further validation of actigraphy for sleep studies. Sleep vol. 26, no. 1.
Hendricks, J.C. et al. 2000. Rest in Drosophila is a sleep-like state. Neuron vol. 25, 129–138.
Knutson, K. 2014. Sleep duration, quality, and timing and their associations with age in a community without electricity in Haiti. American Journal of Human Biology vol. 26: 80-86.
Knutson, K., et al. 2007. The metabolic consequences of sleep deprivation. Sleep Medicine Review vol. 11, no. 3: 163-178.
McNamara, P., Nunn, C., Barton, R. 2009. [Introduction] In: The Evolution of Sleep, eds. McNamara, P., Barton, B., Nunn, C. Cambridge: Cambridge University Press.
National Sleep Foundation. (2014a). What happens when you sleep? http://sleepfoundation.org/how-sleep-works/what-happens-when-you-sleep. Accessed 07.05.14.
National Sleep Foundation. (2014b). How much sleep do we really need?. http://www.sleepfoundation.org/article/how-sleep-works/how-much-sleep-do-wereally-need. Accessed 07.05.14.
Saper, C., et al. 2005. Homeostatic, circadian, and emotional regulation of sleep. Journal of Comparative Neurology vol. 493: 92-98.
Siegel, J. 2008. Do all animals sleep? Trends in neurosciences vol. 31, no. 4.
St-Onge, M. et al. 2011. Short sleep duration increases energy intake but does not change energy expenditure in normal-weight individuals. American Journal of Clinical Nutrition vol. 94: 410-416.
Worthman, C. and Brown, R. 2013. Sleep budgets in a globalizing world: biocultural interactions influence sleep sufficiency among Egyptian families. Social Science and Medicine vol. 79: 31-39.
Wright, K., et al. 2013. Entrainment of the human circadian clock to the natural light-dark cycle. Current Biology vol. 23, no. 16.
This project is conducted as an integrated part of the Tsimané Health and Life History Project (THLHP), directed by Dr. Hillard Kaplan of the University of New Mexico and Dr. Michael Gurven of the Univserity of California at Santa Barbara. It was designed and managed directly by the author, with the financial backing of LAII, GPSA, OGS, and the THLHP. Due to the multi-dimensional nature of the variables required to address the aims, several different methodologies are employed, some directly by the author and others by other THLHP personnel under direction and supervision of the author.
All sleep data is collected directly by the author, using a bipartite strategy of interview and wrist-worn digital accelerometry. Accelerometers are small, watch-like devices that record motion. For studying sleep, this method has been validated against the field’s ‘gold-standard’ methodology of electro encephalograms (EEG), which function by means of measuring electrical signals in the brain during sleep (Capellini, 2009). Due to the remote nature of the field site and the requirement of sleeping in a laboratory to conduct EEG, accelerometers are a more appropriate methodology for this project (de Souza, 2003). In addition, the accelerometers used also record ambient light during the observation period. Together, the accelerometers are recording both sleep vs. wake data as well as ambient light levels over 24 hours.
Interviews were devised in Bolivia while conducting two months of ethnographic background research on Tsimané sleep. After finalizing the interview form, interviews were performed three days in a row during the overall observation period of four days, three nights. These interviews also included questions about night-time childcare, night-time work, and fatigue.
Daily activity, productivity, energy expenditure, and medical data are all collected as parts of existing projects within the THLHP. All study participants are offered free doctor’s examinations during which time, if permission is given, data is recorded regarding symptoms, infection, and treatment of medical issues. For those who also volunteer blood, urine, and/or fecal samples are taken and used to improve diagnoses and recorded for analysis.
Daily activity, productivity, and energy expenditure are recorded as part of a separate anthropological project on sharing and energy expenditure, by means of accelerometry and extensive interviews. Accelerometers using energy expenditure algorithms assess calories burned per day. This has been validated against the field ‘gold-standard’ of doubly labeled water, which administers special water samples composed of hydrogen and oxygen isotopes. As the body burns calories, this water is metabolized, which results in a changing pattern of hydrogen and oxygen isotopes in urine, which indicate calories burned during the observation period. The doubly labeled water methodology is extremely expensive, but accelerometers have been validated and are used due to their inexpensive nature and accuracy in data collection on energy expenditure.
Study Population:
This study is being conducted with the Tsimané, a subsistence population living in lowland tropical Bolivia. This group has been studied extensively since 2004, when the THLHP began in Bolivia. Their economic system is best described as hunter-horticulturalist, where swidden planting occurs on a small scale. Their remote location lacks electricity in the vast majority of communities. Each planting field generally serves a single family or family cluster. Diet is primarily composed of corn, rice, manioc, and plantain grown in. Meat primarily comes from hunting and fishing. Both men and women work in the planting fields extensively, and both sexes fish regularly. Hunting is primarily conducted by men. Average fertility per woman is 8 children. Families build their own homes out of wood and woven leaves, and typically move once every 5-8 years. Rates of infectious disease are quite high, primarily due to parasite infested river water and mosquito-borne pathogens. The Tsimané speak their own indigenous language, though many within the study population have learned Spanish due to a higher degree of integration with the larger local Bolivian society. For this reason, the study is conducted with the aid of Tsimané-Spanish translators, and some parts are even conducted in Tsimané directly.
Conclusions:
While a complete data-analysis will require several months of careful examination to completely address all aims listed, some preliminary analyses suggest support for several of the hypotheses. It appears that young women (age range 13-25) tend to sleep more than young men, until they have a baby. Women with babies and young children sleep far fewer hours per night and wake up frequently. Young men tend to sleep less because frequently hunt, fish, or visit friends at night. Older women (age range 60-80) tend to sleep less than older men, largely due to their role in child care nocturnal work such as laundry, mending clothes, weaving roofing material for sale, or weaving mats and baskets for household use.
While statistical strength of the models proposed for aims 2 and 3 are as yet unanalyzed. Yet, qualitative preliminary analyses support the models, suggesting that illness, fatigue, and higher energy expenditure and productivity among older individuals leads to longer sleep duration. Shorter sleep duration appears to be associated with increased fatigue and reduced productivity the following day, especially among older individuals. Overall, the data appear promising and several of the listed hypotheses are supported.
References:
Achermann, P, and Borbely, A. 2003. Mathematical models of sleep regulation. Frontiers in Bioscience vol. 8:683-693.
Bonnet, M. 2000. Sleep deprivation. In: Kryger MH, Roth T, Dement WC, ed. Principles and practice of sleep medicine, 3rd ed. Philadelphia, PA: Saunders. 53-71.
Buxton, O., et al. 2012. Adverse metabolic consequences in humans of prolonged sleep restriction combined with circadian disruption. Science Translational Medicine vol. 4, no. 129.
Campbell, S., and Tobler, I. 1984. Animal sleep- a review of sleep duration across phylogeny. Neuroscience and Biobehavioral Reviews vol. 8: 269-300.
Capellini, I., et al. 2009. Ecological constraints on mammalian sleep architecture. In: The Evolution of Sleep, eds. McNamara, P., Barton, B., Nunn, C. Cambridge: Cambridge University Press.
de Souza, L., et al. 2003. Further validation of actigraphy for sleep studies. Sleep vol. 26, no. 1.
Hendricks, J.C. et al. 2000. Rest in Drosophila is a sleep-like state. Neuron vol. 25, 129–138.
Knutson, K. 2014. Sleep duration, quality, and timing and their associations with age in a community without electricity in Haiti. American Journal of Human Biology vol. 26: 80-86.
Knutson, K., et al. 2007. The metabolic consequences of sleep deprivation. Sleep Medicine Review vol. 11, no. 3: 163-178.
McNamara, P., Nunn, C., Barton, R. 2009. [Introduction] In: The Evolution of Sleep, eds. McNamara, P., Barton, B., Nunn, C. Cambridge: Cambridge University Press.
National Sleep Foundation. (2014a). What happens when you sleep? http://sleepfoundation.org/how-sleep-works/what-happens-when-you-sleep. Accessed 07.05.14.
National Sleep Foundation. (2014b). How much sleep do we really need?. http://www.sleepfoundation.org/article/how-sleep-works/how-much-sleep-do-wereally-need. Accessed 07.05.14.
Saper, C., et al. 2005. Homeostatic, circadian, and emotional regulation of sleep. Journal of Comparative Neurology vol. 493: 92-98.
Siegel, J. 2008. Do all animals sleep? Trends in neurosciences vol. 31, no. 4.
St-Onge, M. et al. 2011. Short sleep duration increases energy intake but does not change energy expenditure in normal-weight individuals. American Journal of Clinical Nutrition vol. 94: 410-416.
Worthman, C. and Brown, R. 2013. Sleep budgets in a globalizing world: biocultural interactions influence sleep sufficiency among Egyptian families. Social Science and Medicine vol. 79: 31-39.
Wright, K., et al. 2013. Entrainment of the human circadian clock to the natural light-dark cycle. Current Biology vol. 23, no. 16.
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