Television viewing is a dominant sedentary pastime at all ages. Data from a study involving 28 European countries showed that the prevalence of children aged 11–15 years who watched television for 4 h or more per day ranged from 26.5% to 49.2% (3). In adults, a recent study showed that 58.9% watch television for more than 2 h per day in the USA (4). The seminal study by Dietz and Gortmaker (5) was the first to place the relationship linking high television viewing with a higher risk of overweight and obesity on the map; since then, the evidence has expended to support this association throughout the lifespan (6–9). There are also consistent relationships of high television viewing with low levels of fitness and high blood cholesterol in adulthood (10,11). Several potential mechanisms have been proposed to explain the link between television viewing and obesity, including reduced time available for physical activity (12), reduced resting metabolic rate (5,8), increased energy intake (13,14), and the influence of food and beverage advertisements (15).
In addition to being a sedentary activity, television viewing seems to exert certain negative effects on food intake and appetite control. Epidemiological studies have consistently reported that television viewing is associated with increased meal frequency and food intake (16–19). Current estimates suggest that 20–25% of daily energy is consumed in front of the television (17), as depicted in Fig. 1. Recent experimental data have also showed that watching television increases the simultaneous intake of high-density, palatable, familiar foods (20). Using a within-subject design, the authors observed that caloric intake increased by 36% for pizza (one slice on average) and by 71% for macaroni and cheese during a 30-min meal when watching television (20). They concluded that based on the mean increase of 288 kcal (1206 kJ) per energy-dense meal during television viewing, eating two such meals weekly in front of the television would cause an annual weight gain of 3.6 kg if we assume no compensatory changes. This observation concurs with a number of other laboratory studies in adults and children showing that television viewing acts as a ‘distractor’ at meal times and induces an increase in caloric intake (21,22).
Figure 1. Percentage of total energy intake consumed during television viewing on weekdays and weekend days in children. Values are expressed as mean ± standard error of the mean. For the third-grade sample, n = 91 for weekdays and 89 for weekend days. For the fifth-grade sample, n = 129 for weekdays and 122 for weekend days. *Significantly different from weekdays (P < 0.05). Figure adapted from Matheson et al. (17).
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In contrast to previous studies, television viewing has not been reported to influence energy intake in a recent laboratory-based study involving healthy adults (23). However, the authors observed that memory for advertisements was associated with energy intake and body weight. Additionally, distractibility was associated with body weight and accounted for 13% of the variance in men's energy intake. These novel results suggest that individual characteristics may play an important role in the effect that environmental stimuli like television viewing have on energy intake; future research is needed to determine whether these characteristics help explain energy intake mechanisms.
Based on the available literature, it is increasingly recognized that people snack more when watching television, and they do so even if they are not hungry. Recent experimental results are concordant with the latter observation and have showed that watching television stimulates food intake regardless of hunger–satiety or palatability conditions (21). In another recent experimental study, television watching has been shown to disrupt habituation to food cues, resulting in increased motivated responding for food and increased energy intake (24). Watching television is a distracting activity that makes the eater ignore the sensations of satiety and fullness, which often leads to overconsumption of food. Consistent with this theory, the more attention people pay to the movie at the movie theatre, the more they eat (25). Television may also influence eating through associative learning. Indeed, people may elect to snack in front of the television screen because such eating is part of a habitual consumption pattern and not because they are necessarily hungry (18). For some people, turning the TV set on signals it is time to eat. Furthermore, obese people have a greater tendency to be distracted than non-obese people (26), and may eat even more than do normal-weight people in identical distracting circumstances such as watching a television program. In a media-rich and food-rich environment, distraction-prone people might not be able to accurately monitor their consumption and are likely to overeat.
Video game playing
Video games have enormous mass appeal and are omnipresent in the daily schedule of most children and teenagers. As of 1999, video games comprised 30% of the US toy market, which helped the video game industry to earn between $6 billion and $9 billion, outselling even the motion picture industry (27,28). A 2004 estimate of media consumption revealed that video game play and non-school-related computer access occupies approximately 2 h of a typical child's day (29). The increased prevalence of electronic game play (computer and video games) has prompted researchers to examine the impact of this medium on various aspects of health (30). Because electronic games are relatively new devices, older epidemiological studies had lower prevalent usage and generally found no association with obesity (31,32). Recent observational studies are, however, more consistent in showing a direct connection between electronic games and overweight as well as obesity (33–36). In particular, a recent study has found a nearly twofold increased risk of obesity for every hour spent playing electronic games daily (37). An inverse relationship between time spent using video games and daily physical activity has also been reported (38). Additionally, playing computer games has been shown to displace the amount of time that teenagers need to spend on meals (39).
Studies that examined the link between electronic games and obesity are limited by their observational design and mainly aimed to link the sedentary nature of this activity with the increased risk of being overweight or obese. Until very recently, no experimental study had examined the potential of video games to induce an increased spontaneous energy intake. Using a randomized cross-over design, preliminary data from an ongoing research project are indicating that an 1-h video game played by male adolescents is accompanied by increased caloric intake at a following ad libitum meal compared with the control condition consisting of being sat on a comfortable chair (see Fig. 2). Moreover, the overconsumption of food after playing video games has been observed without increased sensations of hunger and appetite, as previously reported with television watching (21). It is, however, unknown for the moment if the ‘eating in the absence of hunger’ is more related to impairment of satiety signals capacity or to the mental-stress-induced reward system.
Figure 2. Energy expenditure of rest (control) and video game play and spontaneous energy intake in an ad libitum meal offered after the completion of each task. Values are expressed as mean ± standard error of the mean. n = 12 healthy male adolescents between 15 and 19 years of age. *P < 0.05. Preliminary results from an ongoing research project (JP Chaput et al., unpublished data).
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With the advent of new generation active video games, future research will have to distinguish video games as active or passive. Manufacturers have produced games that require players to dance, play the guitar or drums and replicate the actions used in athletic competition. Not surprisingly, such active gaming has been shown to result in meaningful increases in energy expenditure and heart rate compared with the seated screen environment (40,41). Manipulating the gaming environment offers an appealing alternative, and testing whether active gaming interventions can provide sustainable increases in physical activity is needed. The net impact on energy balance of this active gaming is, however, unknown and it cannot be excluded that children may compensate the increased energy expenditure by increasing their energy intake more than after a comparable traditional physical activity. This might particularly be the case with the increase of online gaming laden with targeted advertising for high-caloric beverages and food.
Mental work has progressively replaced physical work and has become an important modality of human activity. Technological changes, particularly the appearance of computers, have not only increased mental activity but have also redefined the notion of ‘fatigue at work’, which is now more of a psychosomatic nature (such as a ‘burnout’) than physical exhaustion (42). With the continuing decline in costs of technology, programs are proliferating worldwide to put networked laptop computers into the hands of millions of students on a routine basis (43). However, evidence on the effects of computer-related activities on energy balance and appetite control is scarce.
From a physiological standpoint, a comparison of mental and physical work reveals that mental work has to deal with some metabolic limitations that may affect appetite control. Indeed, physical exertion relies on skeletal muscle, which is the main site of free fatty acid utilization of the body, whereas mental work solicits brain, which only oxidizes glucose under normal feeding conditions (44). Furthermore, if one considers that free fatty acids cannot be converted into glucose, this means that mental work essentially relies on the small body carbohydrate stores and on carbohydrate intake. This switch in the macronutrient oxidation profile can be realistically considered as a potential cause of the suspected effects of mental work on energy intake. This expected effect is concordant with the glucostatic theory of appetite control (45), which stipulates that variations in one or several variables related to carbohydrate metabolism can be sensed by the brain, which could affect food intake.
In a recent randomized cross-over study (46), we have found that the energy expenditure of being sat in a comfortable chair or performing a reading–writing task for 45 min was almost the same (difference of 13 kJ only) whereas the ad libitum energy intake after the reading–writing condition exceeded that measured after rest by 959 kJ (see Fig. 3). This agrees with the results of a study involving scientists from the University of Washington who increased their energy and fat intake at the time of the preparation of National Institutes of Health grant applications (47). We also reported in another experimental study that cognitive work acutely induced an increase in spontaneous food intake and promoted increased fluctuations in plasma glucose and insulin levels compared with a control, resting condition (48). In accordance with the glucostatic theory of appetite control, the increased variability of glycaemia was related to a compensatory increase in energy intake (49). Interestingly, we also observed that mental work solicited by computer-related activities produced an increase in cortisol levels, which was related to a compensatory increase in energy intake (2). This observation is in line with the results from Epel et al. (50) who found that high cortisol responders (defined as the increase from baseline to stress levels of salivary cortisol) consumed significantly more calories and more high-fat sweet foods on the stress day compared with low responders, but consumed similar amounts on the control day.
Figure 3. Energy expenditure of rest (control) and mental work (reading–writing) and spontaneous energy intake in a buffet-type meal offered after the completion of each condition. Values are expressed as mean ± standard error of the mean. n = 15 healthy female students between 20 and 30 years of age. *Significantly different from control value (P < 0.05). Figure adapted from Chaput and Tremblay (46).
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Some researchers also reported that the overconsumption of food may be perceived as a reaction for which eating serves as a consolation and/or compensation to stress. Indeed, Dallman et al. (51) proposed that people eat ‘comfort food’ in an attempt to reduce the activity in the stress-response network. This suggests that the overconsumption of food in response to computer-related activities could be seen as a psychobiological problem, involving both homeostatic and non-homeostatic feeding behaviours. Apart from perturbations in key appetite hormones, the overconsumption of food in response to computer-related activities was observed without increased sensations of hunger and appetite in previous experiments (46,48,49). This observation is concordant with results from a recent randomized cross-over study showing that acute psychological stress (mental arithmetic task) was associated with eating in the absence of hunger (52). The disconnection between subjective appetite sensations (as measured by visual analogue scales) and objective markers of appetite (e.g. key appetite-related hormones and substrates) is very interesting and suggests that intellectual work impairs satiety signal capacity.
All together, these observations raise the possibility that mental workload adds a new component to the notion of ‘sedentariness’, which might increase the positive energy balance that is more likely to occur when one is inactive. As recently reported, computer-related activities represent a particular type of sedentary activities – they are stressful, biologically demanding for the body and deserve to be counterbalanced by an adequate physical activity regimen (53). With the advent of computers and new technologies, mental activities have become excessive as opposed to physical activities. This has obviously led to several positive changes, e.g. gains in labour efficiency and productivity, but also to some side effects associated to sedentariness and weight gain. Future work will be needed to assess the overall impact of computer-related activities on energy balance and appetite control before definitive conclusions can be drawn.
The mounting interest in portable media players that has been observed in the last decade is a worldwide phenomenon. In particular, the iPod (Apple Inc.) has revolutionized the MP3 player market since its initial release in 2001 and has continued to do so. On average, it has been reported that people in the group aged 14–20 years listen to over 3 h of music per day (54). The portable media player occupies an integral part of the everyday life for most teenagers and the market for these devices is growing.
As shown in Fig. 4, a recent study involving college students has reported that listening to music while eating is related to higher food intake and longer meal duration (55). Consumption of soft drinks has also been reported to increase by exposing students to loud music (56). Other researchers reported an increase in the disposition to consume alcohol by continuous exposure to rock-type music (57). The pace of music is also known to be effective in enhancing both food and fluid intake. A laboratory experiment with college students have showed that participants drink faster when exposed to fast music (58). Music tempo can also affect chewing intensity, with an increased number of bites associated with an increased amount of beats per minute in the piece of music (59). Likewise, a high music sound level in bars has been shown to increase alcohol consumption and decrease the amount of time spent by customers to drink their glass (60). Conversely, slower music has been reported to be accompanied by a slower rate of eating, but, unfortunately, higher bar bills for customers (61,62). Background music generally decreases customers' dining speed significantly; however, the slower tempo encourages customers to drink more. It thus appears that both extremes (soft, comforting music as well as loud, fast music) increase consumption, but they do so in different ways.
Figure 4. Comparison of food intake and meal duration associated with meals eaten with and without music. Values are expressed as mean ± standard error of the mean. n = 55 undergraduate college students. *Significantly different from meals eaten without music (P < 0.05). Figure adapted from Stroebele and de Castro (55).
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Consumer reports state that over 50% of drivers listen to music while driving (63). Interestingly, results from a recent study showed that over all meals with music on, one-third were consumed while driving (55), highlighting the need for future research examining eating behaviours in the car. This is particularly the case in the USA, where it is a common behaviour to consume food and beverages in the car. However, cultural differences need to be addressed as this might not be the case in other countries.
On the other side of the energy balance equation, listening to music has been shown not to be more energy demanding than complete silence (64). However, music can have positive effects when played at the same time as physical activity is being performed, particularly fast music (65). Music has been used by athletes during submaximal and maximal exercise, as well as in their pre-competition preparations, to increase motivation and improve performance (66). Music could enable a particular workload to be more acceptable and perceived as less arduous, but it could also mean that individuals choose to do more work without an increased sense of effort.
With the massive spread in the popularity of portable MP3 players, a better understanding of the net impact this stimulus can have on energy balance is needed. Here again, listening to music could facilitate hyperphagia by distracting people from their internal sensations of hunger and satiety, as well as from their habitual deliberate control over intake. Future experimental studies should include hormonal measurements and novel brain imaging techniques while listening to music in an attempt to identify some key biological markers that could be linked to increased spontaneous food intake.
Sleep curtailment has become an endemic condition of modern societies, with population statistics revealing that sleep duration has decreased by more than 1 h over the last few decades (67). Factors responsible for this situation include, but are not limited to, extended work schedules, jet lag or shift work, resulting in irregular sleep patterns, and lifestyle choices, including late-night television viewing, Internet use, or consumption of caffeine and/or other stimulants (68). Furthermore, common sleep disorders, such as insomnia, sleep-disordered breathing, sleep apnoea, restless legs syndrome, narcolepsy and circadian rhythm disorders, can cause sleep loss (69). A growing body of epidemiological evidence supports that lack of sleep is associated with obesity (70,71), type 2 diabetes (72,73), coronary heart disease (74,75), hypertension (76,77) and all-cause mortality (78,79).
Recent experimental studies have shown that short-term partial sleep restriction leads to striking alterations in metabolic and endocrine functions, including decreased glucose tolerance, increased sympathetic tone, elevated cortisol concentrations, elevated levels of pro-inflammatory cytokines, and decreased leptin and increased ghrelin levels (80,81). Thus, one could speculate that chronic lack of sleep represents a stress factor stimulating appetite, promoting weight gain and impairing glycaemic regulation, with a subsequently increased risk of type 2 diabetes.
In contrast, the positive impact of a good night's sleep is well demonstrated. From a physiological standpoint, it has been known for several decades that sleep exerts profound modulatory effects on hormones and metabolism. For example, decreased core body temperature, decreased heart rate, decreased blood pressure, decreased sympathetic nerve activity, increased vagal tone and decreased cerebral glucose utilization are all observed during sleep (82). Sleep is not a waste of time – its beneficial effects far exceed the restoration and maintenance of tissue structure and function.
It may seem paradoxical that short sleep duration predicts an increased risk of being overweight or obese. Indeed, a reduced time allocated to the most sedentary activity, i.e. sleep, should normally be expected to result in a negative energy balance if one essentially focuses on energy expenditure. This apparent paradox was clarified several years ago, when Spiegel et al. (83) experimentally tested the short-term effects of partial sleep restriction (two nights of 4 h in bed) on feeding behaviour and key appetite-related hormones. Using a randomized cross-over study, sleep restriction in young men was associated with reductions in the anorexigenic hormone leptin, elevations in the orexigenic hormone ghrelin, and increased hunger and appetite, especially for calorie-dense foods. This is concordant with recent results showing that recurrent bedtime restriction over 14 d is accompanied by increased intake of calories from snacks (84), as depicted in Fig. 5. Likewise, shorter sleep duration during school nights in school children has also been reported to be associated with higher consumption of energy-rich foods (85).
Figure 5. Comparison of energy intake from snacks between the 5.5-h and 8.5-h bedtime conditions. Values are expressed as mean ± standard deviations. n = 11 healthy volunteers (six men and five women). *Significantly different from 8.5-h bedtime condition (P < 0.05). Figure adapted from Nedeltcheva et al. (84).
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Based on the available literature, lack of sleep is stressful, biologically demanding and should be avoided in order to maintain a healthy lifestyle (2,86). Recent results indicate that 5–13% of the total proportion of obesity in children and 3–5% in adults could be attributable to short sleep (87). Short sleep duration is probably related to a greater risk of being overweight because it does not allow the recovery of a hormonal profile facilitating appetite control. Furthermore, when we sleep less, we simply have more time and more opportunities for eating (including late-night snacking), and the resulting increased fatigue often leads to reductions in physical activity (88). Future studies will need to address whether increasing sleep time in sleep-deprived obese individuals can reduce the amount of body fat and/or influence the level of hormones that help to control appetite. Whether people can voluntarily change their sleeping hours is also unknown; therefore, the causes of sleep curtailment should be investigated. Furthermore, the advent of functional magnetic resonance imaging will open new research avenues and allow a better understanding of food-related reward activation in the brain after sleep restriction. In particular, more knowledge is needed about the contribution of homeostatic (hormonal signals that increase appetite) vs. non-homeostatic (eating in the absence of hunger) factors, and their potential interactions, in short sleepers' feeding behaviour.