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On the road to obesity: Television viewing increases intake of high-density foods
Abstract
Television viewing (TVV) has been linked with obesity, possibly through increased sedentary behavior and/or through increased ingestion during TVV. The proposition that TVV causes increased feeding, however, has not been subjected to experimental verification until recently. Our objective was to determine if the amount eaten of two familiar, palatable, high-density foods (pizza and macaroni and cheese) was increased during a 30-min meal when watching TV. In a within-subjects design, one group of undergraduates (n = 10) ate pizza while watching a TV show of their choice for one session and when listening to a symphony during the other session. A second group of undergraduates (n = 10) ate macaroni and cheese (M&C). TVV increased caloric intake by 36% (one slice on average) for pizza and by 71% for M&C. Eating patterns also differed between conditions. Although the length of time to eat a slice of pizza remained stable between viewing conditions, the amount of time before starting another slice was shorter during TVV. In contrast, M&C was eaten at a faster rate and for a longer period of time during TVV. Thus, watching television increases the amount eaten of high-density, palatable, familiar foods and may constitute one vector contributing to the current obesity crisis.
... One psychological factor that has received considerable research interest over the past few years is distraction during food intake [5][6][7][8]. Food intake is influenced by various distractions that require the use of cognitive functions, such as the auditory sense, audiovisual sense, and combined functions using the hands [9,10]; distraction may draw the attention away from the food being consumed and inhibit monitoring of food intake [6,7]. This could result in inaccurate evaluation of food intake and cause overeating when compared to non-distracting situation [8][9][10][11]. ...
... Food intake is influenced by various distractions that require the use of cognitive functions, such as the auditory sense, audiovisual sense, and combined functions using the hands [9,10]; distraction may draw the attention away from the food being consumed and inhibit monitoring of food intake [6,7]. This could result in inaccurate evaluation of food intake and cause overeating when compared to non-distracting situation [8][9][10][11]. Considering this, this study aimed to evaluate the effects of different levels of distraction on food intake. ...
... The reported effects of distraction on food intake are conflicting. Some studies have shown that distraction affects food intake amount and mealtime duration, while others point out that the effects of distraction may not be as clear as sometimes reported, or report no evidence of the effects of distraction on food intake [8][9][10][11]. Although there was no significant difference in food intake between the non-distraction and distraction situations, there was a trend of increasing food intake and mealtime duration in the distraction situations in this study. ...
... Eating environments have become of particular interest due to the role of environment on health and health behavior (6)(7)(8). ...
... Eating while watching the television is an example of an environmental stimulus, which has been shown to increase energy intake, and influences subsequent meals and snacking episodes (7). Watching screens while eating has also been shown to increase the rate of food consumption and reduce the time interval between eating types of food (8). Conversely, increasing the frequency of family mealtimes is positively associated with reduced energy consumption and increased intake of fruits, vegetables, whole grains, and decreased soft drink consumption (9). ...
... In a study from Tebar et al., increased screen time during the COVID-19 pandemic was associated with increased sweetened food consumption and increased desire to drink alcoholic beverages (35). Several pre-pandemic studies have shown that energy intake is increased while watching the television (8,36,37). Increased screen time during food consumption has been thought to reduce mindful eating. Mindful and intuitive eating constitute an awareness of the present moment while eating (38) and consists of making conscious food choices, an awareness of psychological vs. physical hunger, and eating healthfully in response to those cues (39,40). ...
Introduction
The aim of this feasibility and proof-of-concept study was to examine the use of a novel wearable device for automatic food intake detection to capture the full range of free-living eating environments of adults with overweight and obesity. In this paper, we document eating environments of individuals that have not been thoroughly described previously in nutrition software as current practices rely on participant self-report and methods with limited eating environment options.
Methods
Data from 25 participants and 116 total days (7 men, 18 women, Mage = 44 ± 12 years, BMI 34.3 ± 5.2 kg/mm²), who wore the passive capture device for at least 7 consecutive days (≥12h waking hours/d) were analyzed. Data were analyzed at the participant level and stratified amongst meal type into breakfast, lunch, dinner, and snack categories. Out of 116 days, 68.1% included breakfast, 71.5% included lunch, 82.8% included dinner, and 86.2% included at least one snack.
Results
The most prevalent eating environment among all eating occasions was at home and with one or more screens in use (breakfast: 48.1%, lunch: 42.2%, dinner: 50%, and snacks: 55%), eating alone (breakfast: 75.9%, lunch: 89.2%, dinner: 74.3%, snacks: 74.3%), in the dining room (breakfast: 36.7%, lunch: 30.1%, dinner: 45.8%) or living room (snacks: 28.0%), and in multiple locations (breakfast: 44.3%, lunch: 28.8%, dinner: 44.8%, snacks: 41.3%).
Discussion
Results suggest a passive capture device can provide accurate detection of food intake in multiple eating environments. To our knowledge, this is the first study to classify eating occasions in multiple eating environments and may be a useful tool for future behavioral research studies to accurately codify eating environments.
... [5][6][7] This relationship exists because of the sedentary nature of using media and the presence of food advertisements, which contributes to the increased risk for consuming unhealthy foods and drinks. 5,[8][9][10][11][12] In addition, prolonged media use has been associated with substance use and addictive behaviors. 6 In Saudi Arabia, a study reported that media use of > 2 h per day was positively associated with tobacco use and the use of legal and illegal substances. ...
... 15 Media use has been found to be associated with negative dietary behaviors, such as frequent fast-food consumption and sugary drinks as well as lower intake of healthy food items including fruits and vegetables. 5,8,[10][11][12] Due to the limited data available concerning the association between media use and diet in the region, the present study aimed to investigate the association between media use, dietary intake, and diet quality among adolescents in Saudi Arabia. ...
... In fact, media use may contribute to higher consumption of unhealthy foods through frequent exposure to advertisements of high-calorie foods (e.g., fast foods, candies, and sweetened cereals). 5,8,[10][11][12] A previous study conducted among children aged 3-5 years that aimed to explore the relationship between exposure to food advertisements and diet quality observed a negative association between exposure to food advertisements and children's diet quality (assessed by the Healthy Eating Index). 12 The major concern is that with the higher nutritional requirements for adolescents, low-quality diet on the long term may increase the risk for nutrient deficiencies. ...
Background: Excessive media use can affect diet of adolescents, but relevant data in Saudi Arabia are lacking. The present study aimed to explore the association between media use, dietary intake, and diet quality among adolescents.
Methods: This cross-sectional study included data of 631 adolescents (ages 11-18 years) who were randomly recruited from 16 schools located in two main cities in the Western region of Saudi Arabia (Madinah and Jeddah). Envelopes including a questionnaire were sent home to collect sociodemographic data. Students then completed the short-form food frequency questionnaire to assess diet quality. Data on media use, anthropometrics, and 24-h dietary recalls were also collected.
Results: A high proportion of adolescents (86.2%) exceeded media use recommendations of ≤2 hours per day. Significantly higher proportions of younger adolescents, males, and non-Saudis reported media use within the recommendation compared to their peers. Media use predicted lower diet quality score (B=-0.67 [95%CI:-1.09 to -0.28]) and lower intake of calcium, zinc, vitamin D, and vitamin C (B=-104 [95%CI:-203 to -5.24], B=-2.13 [95%CI:-4.15 to -0.11], B=-23.5 [95%CI:-41.3 to -5.65], B=-24.0 [95%CI:-45.1 to -2.96], respectively).
Conclusion: Interventions to limit media use are urgently needed for adolescents in Saudi Arabia to improve diet quality and overall nutritional health.
... Furthermore, many studies on adolescent technology and media use have focused on risk behaviors and negative outcomes. Previous studies have illustrated that digital technology and media use is associated with negative outcomes such as impaired sleep [4][5][6], decreased physical activity [5,7,8], problematic internet use (PIU) [9][10][11], and risk of depression [12]. Although several recent review articles have described both the benefits and risks of technology use [13,14], most individual studies take a risk-centered approach [15,16]. ...
... Furthermore, many studies on adolescent technology and media use have focused on risk behaviors and negative outcomes. Previous studies have illustrated that digital technology and media use is associated with negative outcomes such as impaired sleep [4][5][6], decreased physical activity [5,7,8], problematic internet use (PIU) [9][10][11], and risk of depression [12]. Although several recent review articles have described both the benefits and risks of technology use [13,14], most individual studies take a risk-centered approach [15,16]. ...
... There are several health concerns that have been associated with digital technology and media use influence and affect. First, technology and media use has been shown to negatively affect sleep by delaying bedtime as well as through exposure to light from screens disrupting melatonin levels [4][5][6]. Second, decreased physical activity has been associated with the sedentary nature of most media use [5,7,8]. Third, PIU is defined as "Internet use that is risky, excessive or impulsive in nature leading to adverse life consequences, specifically physical, emotional, social or functional impairment" [37]. ...
Background
Digital technology and media use is integral to adolescents’ lives and has been associated with both positive and negative health consequences. Previous studies have largely focused on understanding technology behaviors and outcomes within adolescent populations, which can promote assumptions about adolescent technology use as homogeneous. Furthermore, many studies on adolescent technology use have focused on risks and negative outcomes. To better understand adolescent digital technology use, we need new approaches that can assess distinct profiles within study populations and take a balanced approach to understanding the risks and benefits of digital technology use.
Objective
The purpose of this study was to identify profiles of adolescent technology use within a large study population focusing on four evidence-based constructs: technology ownership and use, parental involvement, health outcomes, and well-being indicators.
Methods
Adolescent-parent dyads were recruited for a cross-sectional web-based survey using the Qualtrics (Qualtrics International, Inc) platform and panels. Technology use measures included ownership of devices, social media use frequency, and the Adolescents’ Digital Technology Interactions and Importance scale. Parent involvement measures included household media rules, technology-related parenting practices, parent social media use frequency, and the parent-child relationship. Health outcome measures included physical activity, sleep, problematic internet use, and mental health assessments. Well-being indicators included mental wellness, communication, and empathy. We used latent class analysis (LCA) to identify distinct profile groups across the aforementioned 4 critical constructs.
Results
Among the 3981 adolescent-parent dyads recruited, adolescent participants had a mean age of 15.0 (SD 1.43) years; a total of 46.3% (1842/3981) were female, 67.8% (2701/3981) were White, and 75% (2986/3981) lived in a household with an income above the poverty line. The LCA identified 2 discrete classes. Class 1 was made up of 62.8% (2501/3981) of the participants. Class 1 participants were more likely than Class 2 participants to report family-owned devices, have lower technology importance scores, have household technology rules often centered on content, have positive parent relationships and lower parent social media use, and report better health outcomes and well-being indicators.
Conclusions
Findings from this national cross-sectional survey using LCA led to 2 distinct profile groups of adolescent media use and their association with technology use and parent involvement as well as health and well-being outcomes. The two classes included a larger Class 1 (Family-Engaged Adolescents) and a smaller Class 2 (At-Risk Adolescents). The findings of this study can inform interventions to reinforce positive technology use and family support.
... The fourth basic principle of mindful eating involves reducing distractions during eating. Research has demonstrated that watching television while eating increases consumption of high -fat foods, frequency of meals, and overall daily intake of calories [48,49,50]. Researchers investigated whether undergraduates would increase the amount of high -density foods (pizza or macaroni and cheese) consumed during television viewing versus listening to symphony music using a within -subject design [48]. ...
... Research has demonstrated that watching television while eating increases consumption of high -fat foods, frequency of meals, and overall daily intake of calories [48,49,50]. Researchers investigated whether undergraduates would increase the amount of high -density foods (pizza or macaroni and cheese) consumed during television viewing versus listening to symphony music using a within -subject design [48]. Students increased pizza consumption by 36% and macaroni and cheese by 71% during television viewing compared with listening to symphony music [48]. ...
... Researchers investigated whether undergraduates would increase the amount of high -density foods (pizza or macaroni and cheese) consumed during television viewing versus listening to symphony music using a within -subject design [48]. Students increased pizza consumption by 36% and macaroni and cheese by 71% during television viewing compared with listening to symphony music [48]. Being distracted while eating reduces the ability to assess internal sensory cues such as taste perception and satiation [51,52], which can lead to overeating. ...
In the last few years, great attention has been paid to the mindful eating technique as an approach derived from mindfulness to address unhealthy eating behavior among adults. Eating while distracted (television, conversation, etc.) or under cognitive stress (studying, reading, and writing) has shown to increase food consumption, which can result in overeating. Mindfulness-based approaches appear most effective in addressing binge eating, emotional eating and eating in response to external cues. Mindfulness encourages healthier weight and eating habits. Mindful eating can also help picky eaters overcome their poor eating by helping them enjoy more nutritious foods. Mindful eating has been utilized to reduce negative behaviors associated with overweight and obesity. Eating slowly and when hungry, stopping when full, reducing portion sizes, reducing distractions during meals, and savoring food are all principles of mindful eating. Each principle can be attempted individually or collectively with small, simple changes. Some practical ways of incorporating mindful eating include chewing food thoroughly before swallowing, drinking water between bites of food, savoring the aroma and taste of food, using smaller plates and bowls, turning off the television and computer while eating, and creating a pleasurable experience around food and eating. Present article describes mindful eating and offers ideas for how to teach the basics of this practice.
... Unhealthy food perception may lead to unhealthy food choices and eating behaviors [30]. Eating during screen time can also promote snacking, particularly the consumption of obesogenic, ultraprocessed foods (e.g., ready-meals, instant foods) [10,31], and "mindless eating" (eating without acknowledgement of the quantity and quality of foods) [32], leading to overeating and extra calorie consumption [33]. In addition, because screen devices are often used in lying or sitting positions, screen time may increase sedentary time, resulting in lower daily calorie expenditure and dysregulated metabolism [6,34]. ...
... Compared with other screen devices, smartphone is the most portable device and thus is more likely to be used during mealtime and before bedtime [41]. Smartphone use during mealtime can promote snacking and mindless eating, leading to consumption of extra calories [32,33]. Smartphone use before bedtime can disrupt sleep patterns [37], leading to hormone imbalance and appetite dysregulation [39]. ...
Background
We examined the associations between screen time and adolescent obesity and the associations of reallocating screen time to other activities using isotemporal substitution models. Understanding the association between screen time and obesity may provide additional insights into effective obesity prevention strategies in adolescents.
Methods
We conducted a cross-sectional analysis of 5,180 adolescents (4th and 7th grade students) from the Korean Children and Youth Panel Survey 2018. Participants reported their height, weight, and average time spent watching television, using computer, using smartphone, and other after-school activities. Obesity was defined as BMI-for-age and -sex ≥ 95th percentile based on the 2017 Korean National Growth Charts. We performed multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity prevalence, adjusting for potential confounders.
Results
Prolonged smartphone use (≥ 180 vs. <60 m/d: OR [95% CI] = 2.75 [2.06, 3.68]) was associated with a higher obesity prevalence. Television watching (≥ 120 vs. <60 min/d) was positively associated with obesity prevalence among 4th grade students (2.09 [1.51, 2.89]) but the association was not observed among 7th grade students (0.97 [0.63, 1.49]). One-hour increments of any non-screen time activities, with a simultaneous 1-hour decrease in combined screen time, were associated with a lower obesity prevalence (physical activity: 0.75 [0.65, 0.85]; sleeping: 0.69 [0.62, 0.78]; hanging out with friends: 0.80 [0.71, 0.89]; reading: 0.82 [0.69, 0.97]; studying: 0.84 [0.78, 0.90]; chatting with parents: 0.89 [0.88, 0.98]).
Conclusions
Our data suggest that public health strategies that reduce screen time and increase time for non-screen time activities, such as physical activity, may be effective in lowering adolescent obesity prevalence.
... Eating habits established in childhood and adolescence tend to be maintained into adulthood (14). In previous studies, eating while watching TV was found associated with unhealthy food preferences and food habits (8), increased energy intake (15) and obesity (10)(11)(12) in children. However, the effects of eating while watching TV on food preferences and overweight/obesity in Chinese adolescents are not clear. ...
... Another possible reason may be related to that the proportion of TV viewing during snacks ≥1 time/week (45.4%) was higher than the proportion of TV viewing during meals ≥1 time/week (30.7%) in the study. As eating while watching TV was found associated with unhealthy food preferences and food habits (8), increased energy intake (15), and obesity (10)(11)(12)34) in children and adolescents. Adolescents eating snacks while watching TV ≥1 time/week may have more chances to take unhealthy food and higher risk of being obesity than those eating meals while watching TV ≥1 time/week. ...
Background
Eating while watching TV was found associated with unhealthy food preferences and obesity in adolescents in foreign studies, which is not clear in China. The study aims to explore the influence of eating while watching TV on food preferences and overweight/obesity in Chinese adolescents.
Methods
Data from 1768 adolescents (aged 12–17 years) in the 2006, 2009, 2011, and 2015 China Health and Nutrition Survey (CHNS) was analyzed. The height and weight were measured. Mixed effect models were used to identify the associations between eating while watching TV and adolescents’ food preferences and overweight/obesity.
Results
Adolescents eating while watching TV ≥1 time/week were more likely to prefer fast food, salty snacks and soft drinks than those eating while watching TV <1 time/week. Adolescents eating meals while watching TV ≥1 time/week were less likely to prefer vegetables than those eating meals while watching TV <1 time/week. In addition, adolescents eating snacks while watching TV ≥1 time/week were more likely to be overweight/obesity than those eating meals while watching TV <1 time/week (odds ratio [OR] = 7.16; 95% confidence interval [CI] 1.39–36.93).
Conclusion
Eating snacks while watching TV was positively associated with adolescents’ unhealthy food preferences and overweight/obesity. Eating meals while watching TV was associated with adolescents’ unhealthy food preferences. Implementing web-based Community-based participatory research (CBPR) about reducing eating while watching TV may be a practical strategy to develop healthy food preferences and prevent overweight/obesity in Chinese adolescents.
... The most common cluster had a combination of high time in SB with high consumption of SSB foods. A possible explanation for this finding is that watching television makes individuals eat more because they are distracted, which reduces internal satiety due to the delay of normal mealtime satiety [73][74][75][76]. Another explanation is the high number of advertisements that screen users are exposed to, which may influence the type of food consumed [77]. ...
... Another explanation is the high number of advertisements that screen users are exposed to, which may influence the type of food consumed [77]. In addition, watching television is associated with poorer diet quality, including high consumption of SSB foods [73,78]. ...
Background:
The interaction between physical activity (PA), diet, and sedentary behavior (SB) plays an important role on health-related outcomes. This scoping review (Prospero CRD42018094826) aims to identify and appraise clusters of PA, diet, and SB among youth (0-19 years) according to country income.
Methods:
Five databases were searched. Fifty-seven articles met the inclusion criteria.
Results:
Fifty-five cluster types were identified, with greater variety in high-income than lower income countries. The most prevalent profiles were "High SB and consumption of sugar, salt, and beverages (SSB)" (n = 17) and "High PA" (n = 13-5), both of which presented in all income countries. The healthiest profile, "High PA and fruit and vegetables (F&V); Low SB and SSB" (n = 12), was present in upper-middle and high-income countries, while the unhealthiest "Low PA and F&V; High SB and SSB" (n = 6) was present only in high-income countries.
Conclusions:
High SB and unhealthy diet (SSB) were more prevalent in clusters, mainly in high-income countries. The results support the need for multi-component actions targeting more than one behavior at the same time.
... The most common cluster had a combination of high time in SB with high consumption of SSB foods. A possible explanation for this finding is that watching television makes individuals eat more because they are distracted, which reduces internal satiety due to the delay of normal mealtime satiety [73][74][75][76]. Another explanation is the high number of advertisements that screen users are exposed to, which may influence the type of food consumed [77]. ...
... Another explanation is the high number of advertisements that screen users are exposed to, which may influence the type of food consumed [77]. In addition, watching television is associated with poorer diet quality, including high consumption of SSB foods [73,78]. ...
Citation: Mello, G.T.d.; Lopes, M.V.V.; Minatto, G.; Costa, R.M.d.; Matias, T.S.; Guerra, P.H.; Filho, V.C.B.; Silva, K.S. Clustering of Physical Activity, Diet and Sedentary Behavior among Youth from Low-, Middle-, and High-Income Countries: A Scoping Review. Int. J. Environ. Res.
... Excessive binge watching has been correlated with neglect of duties, social problems, and negative health-related consequences including impaired sleep [6,7]. Further, binge watching can contribute to obesity, since it is a sedentary behavior and TV watching is often accompanied by eating [8,9]. Since stress and obesity often co-occur [10], and obesity is independently associated with TV viewing [11,12], it is possible that individuals with obesity are more vulnerable to stress-induced binge watching. ...
... Sedentary behaviors such as binge watching have been reinforced during the pandemic, with stay-at-home orders restricting opportunities for physical activity [30]. Furthermore, TV viewing is associated with increased food intake, especially of highly processed, high energy-density snack foods [9]. In accordance with this established phenomenon, 86.7% of our sample reported eating while binge watching. ...
Binge watching is becoming increasingly common and may impact energy balance and body weight. The COVID-19 pandemic has created conditions conducive to binge watching and increased stress. We investigated relationships between COVID-related stress and binge watching behaviors, and potential variation in this relationship by body weight. Adults (n = 466) completed a cross-sectional online survey assessing binge watching behaviors during and before the pandemic, COVID-related stress, and body weight. Participants reported an increase in binge watching frequency from before to during the pandemic (F1,401 = 99.970, p < 0.001), with rates of high binge watching (“3–4 times per week” to “3 or more times per day”) increasing from 14.6% to 33.0%. Binge watching episode duration increased from 3.26 ± 1.89 h to 3.92 ± 2.08 h (p < 0.001). The increase in binge watching frequency was greatest in individuals with obesity and high stress (F 4,401 = 4.098, p = 0.003). Participants reporting high stress reported higher frequency of eating while binge watching, as well as higher levels of negative emotional triggers, consequences to binge watching, and lack of control over binge watching (all p < 0.001). Our results show that binge watching increased during the pandemic, with greater increases among individuals reporting higher COVID-related stress, especially those with obesity, and concomitant effects on eating, and highlight a need for interventions to minimize the obesogenic impact of binge watching during the pandemic.
... A study showed that healthy-weight adolescents ate more while listening to music than when eating alone in the absence of stimuli (Mekhmoukh et al., 2012), while overweight adolescents ate more when watching TV than when eating in groups or listening to music. Another study showed that watching TV rather than listening to music (a symphony) increased food intake (Blass et al., 2006). These studies support the disruption effect; however, not all studies support it. ...
... Since mukbang includes live broadcasts of eating behavior using voice audio, we expect it to have a facilitation effect on solo dining. Although digital commensality helps maintain social bonds, especially during periods where social interactions are limited (e.g., social distancing during the COVID-19 pandemic), we need to be cautious about its negative effects; for example, the possibility that mukbang viewing may promote overconsumption and obesity, especially among children and adolescents (Blass et al., 2006;Crespo et al., 2001;Gore et al., 2003;Manios et al., 2009;Stroebele & de Castro, 2004a;Van Den Bulck & Van Mierlo, 2004;Yokum et al., 2015). Eating while watching mukbang requires careful planning to prevent excessive eating, especially for adolescents who regularly eat alone. ...
Food tastes better and people eat more when eating with others compared to eating alone. Although previous research has shown that watching television facilitates eating, the influencing factors regarding video content are unclear. We compared videos of a person speaking with those of only objects (food and a cell phone) in Experiment 1, and videos of groups of four people talking in Experiment 2. Half of these videos presented human voices (including the objects-only video), while the other half had no audio. Results showed participants rated the popcorn as tasting better and consumed more when eating alone while listening to someone talking, irrespective of whether the person was present or absent in the video in Experiment 1. A similar result was found in Experiment 2, irrespective of the increased number of people talking in the video. In Experiment 3, we assessed to what extent human voices contributed to an increase in food intake and the perceived taste of food by substituting sine-wave speech (SWS) for human voices used in Experiment 1 and found that the perceived taste of food and food intake were not facilitated when participants watched videos with SWS. The present study indicates that the human voice plays a crucial role in the perceived taste of food and consumption amount when people eat alone while watching television. Suggestions to improve food enjoyment when dining alone are discussed.
... Results from experimental studies typically show that when eating in front of the TV, people eat moreas demonstrated by a higher energy intakethan when eating without watching TV (6,(18)(19)(20) . This may be the result of several mechanisms, such as distraction (4)(5)(6) , learned associations between TV viewing and eating resulting from repeatedly pairing these two behaviours in the past (6,21) or a positive mood induced by TV viewing (6,22) . ...
... reading, social media use) was also related to an increased time spent on eating, but not as much as TV viewing. This finding, also reported in previous experimental research (19,50) , is further in line with this explanation of distraction. TV content is often narrative-based, and narrative media content more easily facilitates transportation (the experience of immersion in another world) compared with other, non-narrative media content (51) . ...
Objective:
One explanation for the relationship between TV viewing and obesity is that people may (over)eat while watching TV. The current study investigated associations between TV viewing and the time spent on (concurrent) eating in a naturalistic setting among a general population sample.
Design:
Preregistered secondary data analyses were performed of a diary survey in which respondents reported their time use in 10-min blocks for 7 d.
Setting:
Concurrent TV viewing and eating was operationalised as all blocks in which TV viewing and eating occurred simultaneously. Furthermore, the TV content respondents watched was coded as food-related (i.e. culinary content) or non-food related.
Participants:
The sample composed of 2292 adults (58·9 % female) in the Netherlands, aged ≥ 20 years, from all educational levels (18·1 % low, 29·8 % middle and 51·4 % high).
Results:
More than half of the respondents (51·3 %) reported concurrent TV viewing and eating at least once during the 7-d diary period. The average eating occasion was longer in duration while watching TV (v. without media use), and the total time spent on eating was longer on days of concurrent TV viewing and eating (v. days of eating without media use). The percentage of TV viewing time spent on concurrent eating did not differ between food-related and non-food-related TV content.
Conclusions:
Eating while watching TV was related to an increased time spent on eating. Even though energy intake was not assessed, these findings from a naturalistic setting provide further evidence that concurrent TV viewing and eating may contribute to overeating.
... Device usage during mealtimes is associated with an increased risk of obesity [40,41]. TV viewing, specifically during meals is related to less healthy eating [40,42] and, in our study, TV viewing intensified during the pandemic. ...
... Device usage during mealtimes is associated with an increased risk of obesity [40,41]. TV viewing, specifically during meals is related to less healthy eating [40,42] and, in our study, TV viewing intensified during the pandemic. Whereas TV viewing during mealtimes was high pre pandemic, the pandemic created conditions in which TV viewing became even more exaggerated. ...
Background:
The COVID-19 pandemic, with its cyclical lockdown restrictions and school closures, has influenced family life. The home, work, and school environments have collided and merged to form a new normal for many families. This merging extends into the family food environment, and little is known about how families are currently navigating this landscape. The objective of the present study was to describe families' adaptations in the family food environment during the COVID-19 pandemic.
Methods:
Parents participated in one of 14 virtual focus groups (conducted in English and Spanish between December 2020 and February 2021). Reflexive thematic analysis was used to analyze the transcripts.
Results:
Forty-eight parents (81% Hispanic and SES diverse) participated. Five themes and one subtheme were identified around changes in eating habits and mealtime frequency, increases in snacking, family connectedness at mealtimes, and use of screens at meals.
Conclusions:
The COVID-19 pandemic has influenced the family food environment. Families shared how their eating habits have changed and that device usage increased at mealtimes. Some changes (e.g., weight gain) may have lasting health implications for both children and parents. Public health officials, pediatricians, and schools should work with families to resume healthy habits post pandemic.
... When mothers were done feeding, they informed the research assistant, who then turned off the tablet. 2) During the Control condition, mothers were asked to listen to Rachmaninoff 's Second Symphony based on previous research illustrating that classical music is preferred to silence to prevent discomfort or boredom (Blass et al., 2006). The research assistant set the volume to 40 decibels, which is considered an ambient sound level (Mehta et al., 2012). ...
Introduction
Parents' sensitivity and responsiveness to their infants may be affected by the widespread availability and use of mobile devices. The present study examined the impact of maternal digital media use on maternal attention and the quality of mother-infant interaction during breastfeeding.
Methods
Mothers and infants ( n = 25 dyads) participated in a within-subject experiment. Mothers breastfed their infants under one experimental and one control condition, counterbalanced across two laboratory visits. During the Digital Media condition, mothers watched a television show on a tablet. During the Control condition, mothers listened to classical music at ambient levels. Video records were later coded to assess maternal attention to the infant, tablet, or elsewhere and evaluate the quality of mother-infant interaction.
Results
There were more disruptions in maternal attention to the infant during the Digital Media ( M = 3.7, S.E . = 0.2 per minute) vs. Control condition ( M = 1.7, S.E . = 0.2 per minute, p < 0.001). The proportion of the meal duration mothers spent focused on their infant was significantly lower during the Digital Media ( M = 52.5%, S.E . = 3.9) vs. Control condition ( M = 83.9%, S.E . = 4.0%, p < 0.001). Lower maternal attention to the infant was associated with lower maternal sensitivity to cues ( p = 0.03) and cognitive growth fostering ( p = 0.002), as well as lower infant clarity of cues ( p = 0.001). Lower maternal attention was also associated with less socioemotional growth fostering ( p < 0.001) and lower infant responsiveness to the mother ( p < 0.001) regardless of whether digital media was present or absent, but during the Digital Media condition, mothers engaged in more socioemotional growth fostering ( p = 0.004) and infants were more responsive to mothers ( p = 0.03).
Discussion
The presence of digital media during infant feeding led to more interruptions to mothers' attention to their infants and the time mothers spent focused on digital media displaced time spent focused on their infants. The degree to which mothers were attentive to their infants vs. digital media was a more important predictor of most aspects of interaction quality than the mere presence of digital media.
... Brunstrom & Shakeshaft, 2009 reported that healthy female participants who consumed sponge cake while playing a computer game were less satiated compared to a silent condition, indicating that arousal may be a factor. Blass et al. (2006) further reported that hunger ratings from pre-to post-meal were significantly higher in both normal and over-weight participants who consumed macaroni, pizza and cheese while watching TV than when listening to music. Oldham-Cooper et al. (2011) reported that participants who played computer games during lunch had significantly reduced post-meal fullness compared to a distraction-free condition. ...
Sensory cues like music can influence our behaviour towards food. In the present study, the effect of music on
hunger, fullness, desire to eat and liking of foods, while viewing real lunch food items, was investigated. To this
end, emotions and physiological measures were obtained to understand the changes in hunger, fullness, desire to
eat and liking. The study aimed to examine changes in hunger, fullness, desire to eat, and liking when viewing a
lunch meal under silent and varying music conditions. Additionally, the study explored the potential role of
emotions to explain these changes. A crossover experimental design was employed using 50 participants (17
males and 33 females) who observed lunch food items during a silent condition (control), or while listening to
either liked or disliked music. The findings demonstrate the cross-modal influence of music on hunger and food
liking ratings when viewing food. Hunger ratings were higher and more negative emotions were evoked while
viewing lunch food items and listening to disliked music. In contrast, in the silent and liked music conditions,
which elicited more positive emotions, there were increased ratings of healthy and unhealthy food pleasantness,
overall food liking, and food satisfaction. Electrophysiological measures of heart rate (HR) and skin conductance
(SC) were obtained while listening to music and viewing a lunch meal. Viewing food items while listening to
disliked music evoked negative emotions and significantly increased SC compared to liked music or silent
conditions. Viewing the food items under the silent condition evoked positive emotions and significantly
increased HR compared to listening to liked and disliked music. This study showed that the participants’ emo-
tions, hunger level, liking, and electrophysiological responses when viewing food are influenced by music that
varied with liking. Results from this study may assist in enhancing dining experiences, as well as influencing food
choices and satisfaction with meals.
... Especially when consumption takes place under cognitively taxing conditions, such as while driving, behind a computer, or while looking at one's smartphone, this practice is likely to increase the amount consumed. For example, children and adults that watch television during their meals have been found to consume more food during (Blass et al., 2006;Crespo et al., 2001;Dubois et al., 2008), and following (Higgs & Woodward, 2009) the consumption occasion. Likewise, eating while driving, and while listening to loud music, has been found to be less effective in reducing people's desire to eat (Ogden et al., 2016), and to promote overcon-sumption (Spence & Shankar, 2010;Stafford & Dodd, 2013;Stroebele & de Castro, 2006). ...
When individuals eat while distracted, they may compensate by consuming more afterwards. Here, we examined the effect of eating while driving, and explored potential underlying mechanisms. Participants (N = 116, 73.3% female) were randomly allocated to complete a driving simulation (distraction condition) or to watch someone else drive (control condition) while consuming 10g (50.8 kcal) of potato chips. Afterwards, participants rated the taste intensity and hedonic experience, reported stress levels, and were then given the opportunity to eat more chips. As hypothesized, participants consumed more chips after the driving simulation. Stress levels were higher in the driving compared to control condition, but were inversely related to consumption amount, ruling out stress as explanatory mechanism. Saltiness ratings differed between the driving and passive viewing condition, only when controlling for stress. The current findings converge with earlier work showing that distracted eating can drive overconsumption, which in turn can lead to long-term health implications. Limitations, implications and potential directions are discussed.
... 1.6 Fernsehen geht mit Steigerung der Kalorienzufuhr einher. (Adaptiert nachBlass et al. 2006) Davon abzugrenzen sind die monogenetischen Formen der Adipositas mit Mutationen hauptsächlich im Leptin-Melanocortin-Signalweg. Diese Adipositasformen stellen eine Rarität dar und treten bereits im Kindesalter auf. ...
Obesity has become a pandemic. More than 670 million people worldwide are obese. In Germany 24% of women and 23% of men have a BMI > 30 kg/m2. More than 2% of the people in Germany have a BMI > 40 kg/m2. Especially children and adolescents are increasingly affected by this metabolic disease. The increase in energy intake due to changes in food composition and eating habits and the reduction of energy consumption due to reduced physical activity are at the forefront. In addition, genetic, psychological, socioeconomic and endocrine causes must be taken into account.
... Time displacement hypothesized when adolescents spent more time on video/computer games, they may have less time available for PA (50), which is supported by Sandercock (49), and Biddle (51). Moreover, longer durations of ST are associated with decreased physical fitness (52), and decreased muscle strength (39), which may also affects the level of PA. Furthermore, the high prevalence of insufficient physical activity might influence this association. ...
Background
In adolescents, excessive screen time leads to many adverse health outcomes and is associated with a variety of lifestyle behaviors. This study was conducted to investigate the associations between the two types of screen time and a variety of lifestyle behaviors in American adolescents.
Methods
Based on the Youth Risk Behavior Surveillance System, this cross-sectional study was conducted. With the help of data collectors, participants self-reported screening time, lifestyle behaviors, and demographic data via well-validated tools.
Results
19% and 43.4% of the participants spent more than two hours a day watching television and using the computer, respectively, while the prevalence of physical inactivity and insufficient sleep was 75.1 and 74.4% respectively. Furthermore, 11.9, 7.3, 14.3, and 21.3% of the participants reported skipping fruits, vegetables, breakfast and milk, respectively. Moreover, the prevalence of alcohol and tobacco consumption and sexual activity was 26.8, 5.3, and 23.5% respectively. More than two hours of television time was significantly associated with high risks of fewer frequency for eating fruit (OR = 1.605, 95%CI: 1.308–1.970), vegetables (OR = 1.389, 95%CI: 1.029–1.873), and smoking (OR = 1.465, 95%CI: 1.088–1.972). Computer/video time for more than two hours was significantly associated with high risks of physical inactivity (OR = 1.724, 95%CI: 1.531–1.941), insufficient sleep (OR = 1.354, 95%CI: 1.151–1.592), and not eating fruit (OR = 1.434, 95%CI: 1.179–1.745).
Conclusion
Increased screen time may be associated with specific unhealthy lifestyle behaviors in adolescents. Furthermore, the associations between different types of screen time and various lifestyle behaviors varied.
... While watching TV programs of their choice, readings for energy intake, hunger, satiety, and palatability were taken. Results revealed 71% higher energy consumption from macaroni and cheese and 36% from pizza (60). Similarly, another study concluded that consuming a meal while watching TV not only enhanced energy intake at mealtime but also affected the normal mealtime satiation or satiety followed by reduced satiety signals from previously consumed foods (61). ...
Food intake and body weight regulation are of special interest for meeting today's lifestyle essential requirements. Since balanced energy intake and expenditure are crucial for healthy living, high levels of energy intake are associated with obesity. Hence, regulation of energy intake occurs through short- and long-term signals as complex central and peripheral physiological signals control food intake. This work aims to explore and compile the main factors influencing satiating efficiency of foods by updating recent knowledge to point out new perspectives on the potential drivers of satiety interfering with food intake regulation. Human internal factors such as genetics, gender, age, nutritional status, gastrointestinal satiety signals, gut enzymes, gastric emptying rate, gut microbiota, individual behavioral response to foods, sleep and circadian rhythms are likely to be important in determining satiety. Besides, the external factors (environmental and behavioral) impacting satiety efficiency are highlighted. Based on mechanisms related to food consumption and dietary patterns several physical, physiological, and psychological factors affect satiety or satiation. A complex network of endocrine and neuroendocrine mechanisms controls the satiety pathways. In response to food intake and other behavioral cues, gut signals enable endocrine systems to target the brain. Intestinal and gastric signals interact with neural pathways in the central nervous system to halt eating or induce satiety. Moreover, complex food composition and structures result in considerable variation in satiety responses for different food groups. A better understanding of foods and factors impacting the efficiency of satiety could be helpful in making smart food choices and dietary recommendations for a healthy lifestyle based on updated scientific evidence.
... Our findings are in line with previous studies showing that TV viewing presents a stronger association with negative health outcomes compared to other types of sedentary behaviors, such as sitting time 7 and PC use 6 . Possible explanations are related to enhances in food intake during TV viewing 21,22 and poor dietary habits 21 , such as snack consumption, which may elevate the probability for these health outcomes 23 . However, similar to the previous findings 7,9,24,25 , our findings were adjusted for a nutritional indicator (soft drinks). ...
We analyzed the associations of screen-based behaviors with obesity, hypertension, and diabetes, and the moderation of different physical activity (PA) domains in these associations. We used data from the 2019 Brazilian National Health Survey, including data from 80,940 adults (mean age of 32.6 years). TV viewing, other screens (PC, tablet, and cell phone), PA domains (leisure-time, occupational, and transport) were collected via interview. Logistic regression models were used. There was a dose–response association of higher TV viewing with diabetes. Within the groups with medium and higher time spent on other screens, those with < 150 min/week in leisure-time PA increased the odds for obesity [1–2.9 h/day: OR = 1.18 (1.01, 1.39)] and hypertension [1–2.9 h/day: OR = 1.29 (1.08, 1.53); ≥ 6 h/day: OR = 1.47 (1.03, 2.09)]. Likewise, among the participants who spent ≥ 6 h/day of TV viewing, those with < 150 min/week of occupational PA presented higher odds for hypertension [OR = 1.61 (1.03, 2.53)]. In the group with higher use of other screens, < 150 min per week of occupational PA was associated with lower odds for obesity [1–2.9 h/day: OR = 0.81 (0.68, 0.97)] and hypertension [≥ 6 h/day: OR = 0.65 (0.44, 0.98)]. In conclusion, the associations of other screens with obesity and hypertension were strongest among those without leisure-time PA, while the moderator role of occupational PA was not clear.
... Similar findings were reported for depression [3]; thus, people in a relationship could be more likely to have support during confinement and report fewer consequences. Concerning the role of television/computer, eating while watching television can lead to increased food intake among youths, because television watching might be associated with mindless eating [43,44]. Possibly, a similar relationship exists among adults and should be further investigated. ...
Objective
: This study aimed to explore the consequences of the lockdown among the Italian general population by focusing on depression and emotional overeating (EO).
Research
Methods & Procedures: QuarantEat was an Italian nationwide cross-sectional study conducted using a Computer-Assisted Web Interview method (6th-31st May 2020). The 40-item questionnaire included the 5-item World Health Organization Well-Being Index and the Emotional Overeating Questionnaire-5. Multivariable logistic regressions were performed.
Results
: A total of 1865 adults participated. Depression and EO were reported by 57.6% and 49.3% of the sample, respectively. Considering multivariable models, females, students, participants who smoked more/equal during lockdown and individuals with EO were more likely to report depression. Following a healthier diet or exercising during lockdown reduced the probability of depression. The likelihood of EO was higher for participants who were female, consumed more food, had a less healthy diet, were overweight and obese, consumed more chocolate, consumed more snacks between meals or before going to sleep/during the night, and were at risk for depression. Increasing age, having a relationship, and not having increased TV/computer watching time while eating reduced the odds of EO.
Conclusions
: QuarantEat highlighted high levels of depression and EO right after the end of lockdown measures. It also outlined the importance of the relationships between mental health and health risk behaviors, such as smoking, exercise, diet, and changes in eating behaviors due to lockdown. It is essential to plan interventions using a holistic approach and reach every individual overcoming the limits caused by the restrictive measures.
... It is known that distracting people while they are eating can divert their attention away from monitoring their intake and/or interfere with processing satiation cues (Stroebele & de Castro, 2006). It is therefore unsurprising that distraction during the meal, for instance watching TV, listening to music or listening to audiobooks, can result in an immediate increase in energy intake (Bellisle et al., 2004;Blass et al., 2006;Long et al., 2011;Stroebele & de Castro, 2006). In a meta-analysis of studies pertaining to the effects of attentive eating on intake, noted that while distraction increased immediate intake of food, it had a significantly greater effect on food consumed a few hours after the distracted meal. ...
The present thesis investigated the meal-recall effect, wherein remembering a recent meal reduces subsequent snack intake. A review of the literature suggested that the meal-recall effect might be driven by a temporary increase in interoceptive ability, which could then help individuals to perceive lingering satiety signals more strongly and to resolve ambiguous gastrointestinal signals (Chapter 2). A laboratory-based replication of the meal-recall effect was attempted, however, due to testing restrictions, data collection was prematurely ceased (Chapter 3). Instead, the effect was replicated online, with food photographs used as a proxy for intake (Chapter 4). The effect was not elicited in Experiment 1, potentially due to methodological issues, but changes to the design in Experiment 2 resulted in the meal-recall effect being successfully replicated. There was no evidence to support the idea that improved interoception was the mechanism underlying the meal-recall effect. Imagining a recent meal as bigger than in reality was shown to be an effective method of reducing biscuit intake, but visualising details of a previous meal disrupted the manifestation of the meal-recall effect (Chapter 5). Two weight loss interventions based on the meal-recall effect were tested for usability, by asking users for feedback (questionnaires and interviews) after using the interventions for a week (Chapter 6). Finally, the feasibility of a memory-based weight loss intervention was tested over a six-week period, and a number of potential improvements were identified (Chapter 7). The difference in weight loss between the intervention (1.81kg) and the control group (1.07kg) was not significant. The results suggest that a weight loss intervention based on the meal-recall effect has the potential to be feasible and acceptable to users, however more research is required to understand why the effect occurs and why it seems easily disrupted by contextual factors.
... Eating in front of a screen is not considered healthy eating behavior as this is associated with increased dietary intake and the inability to notice when you are full (41)(42)(43). For households of more than one person, screen use during mealtimes may be considered harmful as it creates a barrier to connect with others (44). ...
COVID-19 lockdown meant disruptions to daily routines for households in Aotearoa New Zealand. The research presented here investigates how mealtimes changed for people living in New Zealand during the first COVID-19 lockdown in mid-2020 and sought to determine if household composition type and psychological distress impacted the frequency of engaging in several mealtime behaviors. The COVID Kai Survey collected data using an anonymous, online survey and asked questions on sociodemographic characteristics including household composition, frequency of engaging in different mealtime behaviors before and during lockdown, and psychological distress, which was measured using the Kessler 6 screening tool. The findings of this study shows an increase in the perceived importance of mealtimes (n = 807, 26.9% before lockdown, n = 1,154, 38.5% during lockdown) and an increase in the proportion of the survey respondents who stated that they frequently ate meals at the dinner table (n = 1,343, 44.8% before lockdown, n = 1,481, 49.4% during lockdown). There was a decrease, across all household composition types, in the proportion of respondents who ate out frequently at a restaurant or café (n = 878, 29.3% before lockdown, n = 5, 0.2% during lockdown, P < 0.001). The use of meal kits, e-dining, and eating meals in front of screens is also presented and discussed. All results are discussed with reference to Aotearoa New Zealand’s stringent lockdown restrictions. Respondents who experienced psychological distress during lockdown were 1.47 times more likely to consider mealtimes an important part of their day and respondents living in households with one adult and at least one child who also experienced psychological distress were 5.95 times more likely to eat dinner at the dinner table than those who did not report psychological distress. Findings of this study further the understanding of the wider societal impact of COVID-19 lockdown on everyday life.
... Second, decreased physical activity has been associated with the sedentary nature of most media use (de Jong et al., 2013;Goris et al., 2010). Media use has also been attributed to increased obesity risk as adolescents often increase caloric intake while watching media (Blass et al., 2006). Third, problematic internet use (PIU) is defined as 'Internet use that is risky, excessive or impulsive in nature leading to adverse life consequences, specifically physical, emotional, social or functional impairment' . ...
Media use among early adolescents is nearly ubiquitous and has been associated with important health outcomes such as physical activity, sleep and problematic internet use (PIU). Parent involvement has been recommended as a prevention strategy; it remains unclear how it is associated with media use and health outcomes. The purpose of this study was to develop profiles of media use, parent involvement and health outcomes among adolescents. Early adolescents were recruited to a cross-sectional online survey using the Qualtrics platform and panels. Media use measures included ownership and bedroom use of devices, social media platforms and video games. Parent media involvement assessed media rules and role-modeling. Health measures included physical activity, sleep and PIU. We used latent class analysis (LCA) to identify distinct profile groups across these three areas. The 1155 participants had a mean age of 13.6 years (SD = 1.1), of whom 49.7% were female, 73.7% were White and 61.1% had parent education with a college degree. We found that most participants owned personal media devices, including smartphones (81.4%), computers (64.6%) and video game systems (58.9%). The LCA identified three distinct profile groups: (1) Active Autonomous Media Users, (2) Young Low-Tech Sleepers and (3) Risky Regulated Media Users. Findings support that media use patterns vary across adolescents, suggesting different education and prevention approaches may be needed. Targeting educational messages to different media profiles may be an effective strategy to optimize productive media use and health.
... The detrimental effects of screen time in general, and watching TV in particular, have been attributed to food advertisements and potential conditioning to eat while watching TV, as well as, distraction and disruption of food memory along with the interruption of physiological food regulation [42]. Food advertising not only influences food consumption but also affects food preference that can lead to a greater consumption of sweet and high-fat savory foods while decreasing the intake of fruits and vegetables [55,56]. Dietary intake also increases during screenbased activities, even in the absence of food advertisements [57,58]. ...
Poor lifestyle choices in adolescents, including low physical activity (PA), excess screen time, and unhealthy dietary habits, are major threats to their health in the future. Unhealthy behaviors such as insufficient PA, high TV time, and poor dietary choices also tend to cluster, but information on the combined association of screen time, sports participation, and dietary habits is limited in Austrian youth. To examine the association among these behaviors, 165 adolescents (74 girls and 91 boys) between 11 and 14 years of age completed a food frequency questionnaire during regular class hours. Additionally, participants reported whether they participated in club sports and whether they had a TV in the bedroom. The results showed that there were no interaction effects of club sports participation and TV in the bedroom on dietary habits. There were also no significant associations between participation in club sports and dietary habits. Having a TV in the bedroom, however, was associated with more frequent consumption of fast food and soft drinks. These results highlight the detrimental effects of unsupervised access to a TV on dietary habits in youth. As many lifestyle habits are established during adolescence and retained in adulthood, this age is important to develop a healthy lifestyle. Although club sports provide a viable setting to promote health, the results of this study indicate that the potential of club sports to educate children on nutrition is underused.
... While the environment can encourage food intake through food availability and exposure to food advertisements (Boswell & Kober, 2016;Swinburn et al., 2011), experimental evidence has shown that environmental factors not related to food may also influence variations in food intake, including auditory or audiovisual distractors (Long, Meyer, Leung, & Wallis, 2011). For example, some studies have shown that technology use, such as music, television, and video games, is associated with increased food intake (Bellisle, Dalix, & Slama, 2004;Blass et al., 2006;Cessna, Raudenbush, Reed, & Hunker, 2007;Hetherington, Anderson, Norton, & Newson, 2006;Stroebele & de Castro, 2006). ...
Nowadays people use screens, such as mobile phones, television, or tablets, more often during mealtimes, which may have an effect on intake. This review aims to analyze the effect of screen use, during food consumption, on intake. A systematic review was carried out, based on those protocols established by PRISMA. The Cochrane Library, PubMed, Web of Science and Scopus databases were consulted. Experimental studies, published between 2010 and 2021, that recorded individual intake while using screens such as television, cell phones, or tablets, were selected. A total of 7181 relevant articles were obtained, which were then assessed in accordance with predetermined inclusion and exclusion criteria. Finally, 35 studies were included in the complete review: 22 compared different kinds of television content (e.g., adverts), five which compared television versus the absence of screens, four which compared television versus video games, two which compared the use of simultaneous screens, and two studies which included cell phones. A total of 27 studies reported consumption increases related to the presence of advertisements and food signals on screens. No significant differences in intake were reported in the eight studies that reported design or sample size limitations, or lack of control of certain variables. It is thus concluded that screen use during food consumption may increase intake. Education is necessary to regulate the habit of consuming food in the presence of screens. Also, the creation of policies that regulate advertising and food cues on screens are justified and must be accompanied by strategies to monitor compliance. As a limitation, further evidence is necessary in order to determine the effect of mobile phone and tablet use while eating. This protocol was registered via PROSPERO, ID: CRD42020211797.
... As adolescents devote increasing amounts of time in front of computer monitors (in accumulation to the time spent in front of a television screen), they are probable to increase their risk of weight gain. (Blass, 2006) In the present study, this was inveterate, especially with regard to the time spent over the weekend. Consequently, the American Academy of Pediatrics recommends parents to limit the time their children spend with the media and to highlight alternative activities, such as sports events, physical conditioning, and imaginative play (American Academy of Pediatrics.2011) ...
... Indeed, eating in front of television have been reported to contribute to increased energy intake and could thereby be associated with increased body mass index. Another reason why television watching during meals might affect obesity status might be that TV watching may be associated with more 'mindless' eating, and may thus increase the amount of foods and thus the amount of calories consumed [36]. ...
Although poor eating habits and lifestyle factors have been reported to be associated with metabolic syndrome (MS), little is known about this association in Cameroonian pregnant women. The aim of this study was to describe lifestyle choices and eating habits in Cameroonian pregnant women, and determine their association with MS and its components. A hospital-based cross-sectional study was conducted on 859 participants aged 17-45 years (mean ± SD: 27.3±5.6) from the Littoral and Centre Regions of Cameroon. Height, weight, serum lipid profile, fasting blood glucose and arterial blood pressure were measured using standard procedures. Information concerning the lifestyle, eating habits and sociodemographic characteristics were recorded using structured questionnaire. Metabolic syndrome was diagnosed using a slightly modified of National Cholesterol Education Adult Treatment Panel III criteria. Statistical analysis was performed through descriptive statistics, including mean, standard deviation, frequency and logistic regression analysis in Statistical Package for Social Sciences (version 23) software. Statistical significance was set at p-value <0.05. The proportion of participants who reported eating fruits and vegetables occasionally, sugary foods and drinks ≥ 5 times a week and fatty foods ≥ 5 times a week were 77.4%, 23.7% and 22.8% respectively, 41.6% and 39.8% had unhealthy (long and short) sleeping duration and lack of physical exercise respectively. Also, 54.8% were alcohol consumers. Non-sedentary participants (OR: 0.49; 95% CI: 0.29-0.85) had lower odds to develop metabolic syndrome compared to sedentary participants. Participants with short sleep and long sleep duration were 5.1 and 2.4 times respectively more likely to have MS than those with normal sleep duration. Participants who had vigorous activities or physical exercise (OR: 0.39; 95% CI: 0.18-0.82; p: 0.014) where significantly less likely to experience MS than those with lack of physical exercise after controlling for potential covariates (age, parity, gravidity, BMI). Moreover, high consumption of sugary drinks, fatty foods, alcohol consumption (OR: 2.0; 95% CI: 1.12-3.58; p: 0.019) were associated with MS. Our findings suggest that, adoption of healthy lifestyle and dietary habits should be encouraged to reduce the prevalence of metabolic syndrome and its abnormal components. Further prospective studies are needed to consolidate our findings.
... 24 27 55 61 Watching TV was found to be associated with the urge to consume more savoury snacks and high-calorie drinks. 64 65 These unhealthy dietary practices, while watching TV, are hypothesised to be related to abdominal obesity in women. 55 One of the factors that might drive this tendency is the abundance of TV programmes with commercials or advertisements Open access for energy-dense foods, 66 67 which may determine dietary choices in other parts of the day. ...
Abstract
Objective This study aimed to assess the possible relationship between television viewing and overweight and obesity among Timorese women of reproductive age.
Methods This cross-sectional study analysed the Timor-Leste Demographic and Health Survey 2016 dataset. A weighted sample of 11 398 Timorese women aged 15–49 years was chosen using a two-stage stratified random sampling technique. Asian criteria-based body mass index (BMI) cut-offs were used to define overweight (BMI 23.0 to <27.5 kg/m2) and obesity (BMI ≥27.5 kg/m2). Frequency of TV viewing was categorised into three groups: (1) not at all, (2) less than once a week and (3) at least once a week. Multilevel ordered logistic regression was performed to identify the correlates of overweight and obesity. Both crude and adjusted odds ratios (AOR) along with a 95% CI were calculated to show the strength of association.
Results Among 11 398 respondents, 19.4% were overweight or obese (overweight: 15.7% and obese: 3.8%). Although about half of the respondents reportedly did not watch TV at all, just over two-thirds watched TV at least once a week. Women who watched TV at least once a week were found to have 1.3 times the odds of being overweight or obese compared with those who never watched TV (AOR: 1.3, 95% CI: 1.1 to 1.5; p<0.001). However, when stratified by settlement type, the statistical significance stood for the rural women only (AOR: 1.5, 95% CI: 1.2 to 1.8; p<0.001), after adjusting for the covariates.
Conclusion Watching TV at least once a week was found to be a significant correlate of overweight and obesity in rural Timorese women of reproductive age. Further studies need to be undertaken to assess physical activity, sedentary and dietary patterns to clarify the possible mechanism through which TV viewing may influence BMI in those groups.
... In my empirical analysis I am testing the effect of exposure to private television on food consumption patterns. The setup of this study does not allow for disentangling the impact of food advertisement on TV (Bagwell, 2007;Becker and Murphy, 1993;Braithwaite, 1928;Dixit and Norman, 1978;Nelson, 1974;Ozga, 1960;Stigler and Becker, 1977) from the effect of a more sedentary lifestyle and more time spent in front of the TV: Studies show that individuals eating in front of the TV are distracted and subsequently consume more calories (Blass et al., 2006;Higgs, 2015;Mekhmoukh et al., 2012;Péneau et al., 2009). Olken (2009) shows for individuals on the Indonesian island Java that each additional private TV Electricity is based on a retrospective information whether the household of the individual had access to electricity when she was 12 years old. ...
Using cross‐sectional survey data from Indonesia from 2007 and 2014, this study estimates the effect of the number of available television channels during childhood on food consumption later in life with a focus on unhealthy food items. To address endogeneity of television signal strength, I exploit exogenous variations in television signal quality due to random diffractions caused by topography within a small area. Using an instrumental variables approach the results suggest that exposure to television during youth of the household head has a positive effect on household‐level snack and soft drink expenditures. At the individual level I document more frequent consumption of soft drinks. Additional analysis suggests that households shift their consumption basket at the expense of vegetables and staples. Finally, heterogeneous effects analysis imply that results are driven by young individuals who are younger than 24 years old.
... Screen time while eating was directly associated with UPF intake in adults, a finding in accordance with prior evidence showing that TV watching possibly increases the amount eaten of high-density and palatable foods (46) , while in children and adolescents such association was not observed, likely because this behaviour in our young sample is underrepresented. ...
Objective
To assess ultra-processed food (UPF) consumption and its sociodemographic, psychosocial and behavioural correlates in a general population of Italian children, adolescents and adults.
Design
Cross-sectional telephone-based survey
Setting
Italy, 2010-2013
Participants
9,078 participants (5-97 y), from the Italian Nutrition & HEalth Survey (INHES). Dietary intakes were collected by a one-day 24-h dietary recall. UPF was defined by the NOVA classification and expressed as percentage of total calories.
Results
Average energy intake from UPF (95% confidence interval) was 17·3% (17·1%, 17·6%) among adults and 25·9% (24·8%, 27·0%) in children/adolescents.
Top sources of UPF were processed meats (32·5%) and bread substitutes (16·7%). Among adults, age (β=−3·10; 95%CI: −4·40, −1·80 for >65 y vs 20-40 y; βs are dimensionless) and residing in Southern Italy (β=−0·73; −1·32, −0·14 vs Northern) inversely associated with UPF. Screen view during meals was directly linked to UPF, as well as poor self-rated health (β=5·32; 2·66, 7·99), adverse life events (β=2·33; 1·48, 3·18) and low sleep quality (β=2·34; 1·45, 3·24). Boys consumed 2-point percent more UPF of the total energy than girls (β=2·01; 0·20, 3·82). For all ages, a Mediterranean diet was inversely associated with UPF (β=−4·86; −5·53, −4·20 for good vs poor adherence in adults and β=−5·08; −8·38, −1·77 for kids).
Conclusions
UPF contribute a modest proportion of energy to the diets of Italian adults while being one quarter of the total calories in children/adolescents. UPF was associated with several psychosocial factors and eating behaviours. Increased adherence to Mediterranean diet would possibly result in lower UPF consumption.
... Observational and experimental studies have linked ST to an increased risk of obesity, and increased energy intake has received support as an explanatory mechanism [19]. Snacking during television viewing is associated with an increased risk of obesity [20], which could be exacerbated during times of stress and magnified by preferences for comfort foods. One study found that youth who watch the television for more than 5 hours a day have 5-fold higher odds of being overweight than those who watch the television for less than 2 hours a day [21]. ...
Background:
Child screen time (ST) has soared during the COVID-19 pandemic as lockdowns and restrictions have forced changes to regular family routines. It is important to investigate how families are navigating ST.
Objective:
This study aimed to explore families' experiences of ST during the COVID-19 pandemic.
Methods:
Virtual focus group sessions were conducted between December 2020 and February 2021 in English and Spanish. Transcripts were analyzed using reflexive thematic analysis.
Results:
In total, 48 parents (predominantly Hispanic) residing in California participated in 1 of 14 focus group sessions. Children were attending school remotely at the time of the study. Six themes and one subtheme were identified: (1) total ST has increased; (2) children are too attached to screens; (3) ST has advantages and disadvantages, but parents perceive ST as mostly negative; (4) parents and children have limited options; (5) ST restrictions (subtheme: children react negatively when ST is restricted); and (6) parents are concerned that children are not getting enough exercise.
Conclusions:
This study provides a cross-sectional insight into how family life has changed with regard to ST during the COVID-19 pandemic. Parents expressed concerns about the total ST, the addictive nature of it, and the lack of physical activity. It is important that future studies examine the long-term effects of heavy ST and preemptively introduce ways to redirect children's ST habits as the country attempts to establish a new normal.
... 11 Watching movies/TV while eating food may expose them to overeating; while the children attention is on screen, they are encouraged to eat more. 28 It is also expected that, children may learn unhealthy dietary behavior due to the reason that, most advertisement are dominated by high calorie products which promote eating fast foods, processed, packed, sweets and sweet drinks. It is not only predisposing them to unhealthy dietary behavior but also make them adapt sedentary behavior thereby resulting in less energy expenditure. ...
Background
Although overweight/obesity is becoming a public health issue in low income countries, there is a paucity of evidence concerning overweight/obesity in Ethiopia. The aim of the study was to assess the magnitude of overweight/obesity and associated factors among second cycle primary school children in Kirkos Sub-City, Addis Ababa, Ethiopia.
Methods
A school based cross-sectional study was conducted among 482 children from May to June, 2019. Data were collected using a questionnaire and checklist. Data were entered using EpiData version 3.1 and exported into SPSS version 22.0. Bivariable and multivariable logistic regression analyses were done to identify factors associated with overweight/obesity. Level of statistical significance was declared at p ≤ 0.05.
Results
The overall magnitude of overweight/obesity was 21.2%. The magnitude of overweight was 13.7% while obesity was 7.5%. Vehicle availability, being from private school, not having friend(s), preferring sweet foods, eating breakfast irregularly, watching movies/Television while eating and physical inactivity were the factors significantly associated with overweight/obesity among second cycle primary school children.
Conclusions
The magnitude of overweight/obesity was high in the study area. Therefore, health and education sectors should promote healthy lifestyle to curb child overweight/obesity.
... There is little evidence to suggest that more food is consumed while watching TV compared with while doing other activities in a laboratory setting (figure 2 and online supplemental file 3). Seven studies compared food consumption while watching TV with consumption while doing other tasks, including listening to audio stories, 20 23 listening to classical music, 29 reading, 25 simulated driving, 27 playing video games, 30 eating with a researcher or strangers 22 27 and eating with friends. 22 Five of these studies reported no differences in the amount of food consumed between the TV condition and the other experimental condition they tested. ...
Objective:
To improve our understanding of how television (TV) time is linked to cardiometabolic health among adults by systematically and critically evaluating the evidence that watching TV is associated with increased food consumption, lack of movement or negative affect or affects subsequent sleep.
Design:
Systematic review.
Data sources:
Web of Science and PubMed.
Eligibility criteria:
Studies that provided quantitative evidence on short-term associations of watching TV with dietary intake, characteristics of sitting, affect and sleep among samples of healthy adults (≥18 years old).
Data extraction and synthesis:
Study quality was assessed using the National Heart, Lung, and Blood Institute Quality Assessment Tools; studies deemed to be of low quality were excluded from the review. Due to heterogeneity of study designs and measurements, the findings were synthesised using narrative summary accompanied by custom plots.
Results:
We identified 31 studies that met the inclusion criteria. Most of the associations reported by the studies included in this review were weak or inconsistent. There was no strong evidence to suggest that food consumption is higher while watching TV than in other contexts or that TV is a particularly 'sedentary' behaviour. Affect was less likely to be positive while watching TV than in other contexts but was not more likely to be negative. Two small studies suggest that TV may impact sleep via suppressing melatonin and delaying bedtime.
Conclusion:
There is currently no strong evidence to suggest that TV might impact cardiometabolic health via increasing food consumption, being linked with prolonged/inactive sitting, affect or subsequent sleep. Additional research is required to understand how TV fits within everyday lives and relates to eating, sitting, affect and sleep to improve our understanding of how it might impact cardiometabolic health.
... Mindless eating was associated with consumption of significantly larger meals in those that consumed their meals while watching television or listening to an auditory recording, as compared with controls. This is not surprising since previous research has reported that people tend to consume sweet and high-calorie snacks while watching TV (Blass et al., 2006). This research is the first to document positive associations between emotional eating (Model 1 and Model 2) and mindless (Model 1) and dental caries. ...
Dental caries is a chronic oral condition that disproportionately affects low-income women. The aim of this research was to investigate relationships between dental nutrition knowledge, socioecological factors, and prevalence of dental caries in low-income women. This quantitative cross-sectional study involved 220 women who were recruited from Central Texas. Participants completed demographics, the Dental Nutrition Knowledge Competency Scale, United States Adult Food Security Survey Module, and the Multidimensional Home Environment Scale. Two dentists measured dental caries via the Decayed, Missing, Filled Teeth Index. Regression models were conducted to test the effects of dental nutrition knowledge and Multidimensional Home Environment Scale factors on dental caries. Finally, mediation analysis explored relationships between dental nutrition knowledge and dental caries, adjusting for Multidimensional Home Environment Scale scores. Results showed that dental nutrition knowledge and Multidimensional Home Environment Scale score were significantly associated with dental caries. Subscales of self-efficacy for eating healthy, oral hygiene practices, emotional eating, availability of unhealthy foods at home, and social support were related to dental caries. The relationship between dental nutrition knowledge and caries was mediated by Multidimensional Home Environment Scale scores. This research emphasizes the role of dental nutrition knowledge and socio-ecological factors on prevalence of dental caries. Public health interventions to reduce dental caries should involve strategies that increase dental nutrition knowledge and encourage behavior change in low-income populations.
... Snacking and unhealthy eating have been associated with time watching television [29] and playing video games [28], which may be explained by mental stress and cognitive processes related to reward systems [28]. Additionally, experimental studies have shown that eating while watching television may cause a delay in satiation and a reduction in internal satiety signals [46,47]. Another possible explanation is that depending on the content and quantity of meals, postprandial sleepiness may occur, and adolescents may opt to engage in sedentary activities rather than physical activities if they are feeling tired or somnolent [48]. ...
We aimed to identify sociodemographic, dietary, and substance use factors associated with self-reported sleep duration, physical activity (PA), and sedentary behavior (SB) indicators in a sample of Brazilian adolescents. Adolescents (n = 731, 51% female, mean age: 16.4 years) answered a questionnaire. The volume of total PA, sports, non-sports, total SB, leisure-time SB, involuntary SB, sleep duration, dietary behaviors, sociodemographic, and substance use indicators were self-reported. Multilevel linear models were fitted. Females engaged in less total PA, sports, total SB, and leisure-time SB, but in more involuntary SB than males. Age was positively associated with non-sports and involuntary SB. Socioeconomic status was positively associated with total PA. Adolescents who lived with the mother only practiced more sports compared to those living with two parents. Unprocessed food was positively associated with total PA and sports. Processed food was inversely associated with total PA and non-sports, and positively associated with total SB and leisure-time SB. Alcohol use was positively associated with total PA, and tobacco smoking was negatively associated with total PA. No associations were observed for sleep duration. In conclusion, sociodemographic, dietary, and substance use factors are associated with the 24 h movement behaviors among Brazilian adolescents, and some associations are type specific.
... In contrast, an increased number of daily hours spent watching television was associated with a higher prevalence of a "high risk for OSA" in the current report, even after adjusting for potential confounding factors, including obesity status. Increased television viewing is probably a surrogate marker of a sedentary lifestyle and unhealthy dietary intake (35,36). Interestingly, we observed a positive association between the average number of daily hours spent working and a high risk for OSA, where those reporting at least nine daily hours of work had the highest prevalence of OSA risk. ...
Background: Obstructive sleep apnea (OSA) affects a considerable proportion of adults globally and is associated with elevated morbidity and mortality. Given the lack of epidemiologic data on the burden of OSA in Kuwait, this study sought to estimate its prevalence, associated risk factors, and comorbid conditions among a working population in Kuwait.
Methods: This was a cross-sectional study of a sample of working adults (n = 651) from public institutions in Kuwait. High/low risk for OSA was ascertained according to the Berlin Questionnaire criteria. Participants self-reported their coexisting health conditions. Associations were assessed using Poisson regression with robust variance estimation; adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) were estimated.
Results: Overall, 20.0% (130/651) of participants were classified as being at high risk for OSA, with more male than female subjects being at high risk (24.0% [56/233] vs. 17.7% [74/418], P = 0.053), though this difference did not gain statistical significance. Moreover, a high risk for OSA was more common among older and obese subjects. Factors associated with increased prevalence of a high risk for OSA included current smoking status (aPR = 1.58, 95% CI: 1.02–2.06), longer hours spent watching television (1.76, 1.10–2.81), and lower self-perceived physical health (2.11, 1.15–3.87). However, decreasing trends in the prevalence of high risk for OSA were observed with frequent engagement in vigorous physical activity and longer nightly sleep duration. Compared to those at a low risk for OSA, the subjects at high risk for OSA were more likely to have insomnia disorder (2.83, 1.81–4.41), diabetes (1.94, 1.15–3.27), hypertension (3.00, 1.75–5.16), and depression (4.47, 1.80–11.08).
Conclusion: This study estimated that 1/5 of working adults in Kuwait were at high risk for OSA, and the prevalence varied according to personal characteristics and lifestyle factors. Also, a high risk for OSA classification was associated with multiple comorbid health conditions.
Binge-watching has become one of the most popular ways for people to spend their free time.
Binge-watching refers to watching more than two episodes of a television show in a single sitting.
This pattern of behavior can be seen in people of a wide range of ages, but it is particularly
widespread among people of millennial age and younger. In this study, we propose a model that
explains binge-watching engagement by theorizing and testing the association of social influence
on perceived usefulness, regret on the continuous intention of binge-watching, and habit on
continuous intention and binge-watching engagement. The authors evaluated the model using
data collected from 225 respondents. The results supported the proposed hypotheses and
confirmed that regret does not neutralize the positive – and strong – effect of perceived usefulness
and habit on binge-watching.
Purpose
Swallowing has previously been characterized as consisting of four phases; however, it has become apparent that these four phases are not truly discrete and may be influenced by factors occurring prior to bolus entrance into the oral cavity (i.e., preoral factors). Still, the relationship between these factors and swallowing remains poorly understood. The aim of this review was to synthesize and characterize the literature pertaining to the influence of preoral factors on swallowing and nutritional outcomes in healthy individuals.
Method
We performed a scoping review, searching the databases of PubMed, CINAHL, Cochrane, and Scopus. Search terms included those related to swallowing, experience of preoral factors, and exclusionary terminology to reduce animal and pediatric literature. Our initial search revealed 5,560 unique articles, of which 153 met our inclusionary criteria and were accepted into the review.
Results
Of the accepted articles, 78% were focused exclusively on nutritional outcomes, 17% were focused on both swallowing and nutritional outcomes, and 5% were focused on solely swallowing outcomes. Of the preoral factors examined, 99% were exteroceptive in nature (17% olfactory, 44% visual, 21% auditory, 7% tactile, 11% other), while 1% were proprioceptive in nature.
Conclusions
This review supports the influence of preoral factors on swallowing and nutritional outcomes. However, there is a large emphasis on the visual modality and on nutritional outcomes. Nearly none of the literature found in this review directly measured swallowing safety, efficiency, or physiology. Future work will benefit from a larger focus on proprioceptive preoral factors as they relate to swallowing outcomes.
Background
Technology and digital media (TDM) use is integral to modern adolescence; adolescents have been labeled as “digital natives,” since they have had exposure to digital technology for their entire lives. Previous evidence has illustrated TDM’s connections with adolescent risk behaviors such as increased alcohol use and social media exposure, as well as relationships with adolescent well-being such as improved socioemotional health and social media connections with peers. Although several recent review articles have described both the benefits and risks of technology use, most individual studies adopt a singular risk-centered approach. In addition, reviews suggest that little evidence exists on the potential mediating and moderating factors between TDM use and well-being and health outcomes, which limits our understanding of what influences the outcomes of interest. Therefore, there is an urgent need to fill these gaps.
Objective
This protocol addresses the need to understand how TDM exposure and use affect multiple developmental domains and health outcomes. We address the fragmented nature of previous research, the common focus on single behaviors or conditions, and the typical narrow lens on risks. Our approach further aligns with reviews that called for studies identifying and investigating the factors that moderate the relationships between social media and health behaviors and outcomes.
Methods
We will address our objective by longitudinally examining over a 2-year period a common set of adolescent participants (N=400, aged 13-15 years) across 3 studies that adopt a multimethodological approach. Study 1 will use TDM to understand the mechanisms behind adolescent health and risk behaviors. Study 2 will use functional magnetic resonance imaging to understand how positive and negative TDM experiences relate to mental and behavioral health in a subsample of 150 adolescents. Study 3 will use a mixed methods design to evaluate self- and other-generated TDM content as the predictors of socioemotional well-being in sexual and gender minority and non–sexual and gender minority adolescents.
Results
Recruitment is ongoing, and the initial results from the first wave of recruitment are expected in 2024.
Conclusions
This integrated approach to longitudinal data collection from a shared adolescent participant pool will lead to novel analyses and findings, allowing for the examination of the health and well-being risks and benefits associated with TDM use and factors that moderate these relationships. The findings from this study will advance conceptual models and inform new interventions to improve adolescent health.
International Registered Report Identifier (IRRID)
DERR1-10.2196/50984
Digital media, including social media, has fundamentally changed how the human species communicates with, relates to, and influences one another. Adolescents use digital media extensively. Researchers, scholars, teachers, parents, and teens themselves have many questions about the effects of digital media on young people's psychological development. This handbook offers a comprehensive synthesis of scientific studies that explain what we know so far about digital media and its effects on youth mental health. With chapters from internationally renowned experts in the fields of psychology, psychiatry, media, and communications, the book offers a broad overview of the positive and negative implications of youths' engagement with digital media for brain development, relationships, identity exploration, daily behaviors, and psychological symptoms. Chapters include a discussion of the current state of knowledge, directions for future research, and practical suggestions for parents, educators, and teens themselves. This title is also available as Open Access on Cambridge Core.
The rapidly increasing prevalence of overweight and obesity has heightened the need for a better understanding of obesity-related eating patterns and dietary behaviours. Recent work suggests that distracted eating is causally related to increased immediate and later food, pushing the need for a better understanding of the prevalence of distracted consumption and how this relates to body weight. To extract insights in the relationship between demographics, daily consumption settings, and BMI, we performed secondary data analyses on data from 1011 individuals representative of the Dutch population (adults, 507F, BMI 17–50kg/m²). The most commonly reported distractions were talking to others (32.7%) and watching television (21.7%). Only 18.4% of respondents reported no distractions during meals. To examine how different distractions related to BMI, we performed OLS regression which showed, among other things, that watching tv while eating lunch (η² = 0.37) and working during dinner were associated with a higher BMI (η² = 1.63). To examine the robustness of these findings, machine learning techniques were used. A random forest analysis (RMSE = 4.09) showed that next to age and education level, distraction during lunch and snack was amongst the largest predictors of BMI. Multiple linear regression with lasso penalty (RMSE = 4.13) showed that specifically watching tv while eating lunch or snacks was associated with a higher BMI. In conclusion, our analyses confirmed the assumption that people are regularly distracted during their daily meals, with distinct distractors relating to BMI. These findings provide a starting point for evidence-based recommendations on which consumption settings are associated with healthier eating patterns and body weight.
Consumers’ lives are filled with myriad behaviors that can be successfully executed with minimal attention. Many such low-attention behaviors benefit from persistence but are often not performed long enough (e.g., hygiene, exercise). The current work examines consumer persistence-failures through an attentional lens. Specifically, drawing on boredom and resource-matching frameworks, we suggest one key driver of poor consumer persistence is that many behaviors demand less attention than consumers have available, leaving excess attention that leads to boredom and premature abandonment. The current research thus proposes an attention-matching framework for persistence and suggests that concurrently performing a task that engages excess attention will improve the match between attentional demands and available resources, thereby increasing persistence. Five experiments across a range of low-attention behaviors (e.g., toothbrushing, coordination exercise) demonstrate that concurrently performing a task that occupies excess attention (e.g., reading, listening), delays boredom and increases persistence. Moreover, two important boundary conditions arise. First, the focal behavior must require minimal attention, leaving excess attention available to attend to the tangential task. Second, the tangential task must engage excess attention without exceeding attentional capacity. This research provides important theoretical and practical contributions, offering the potential to improve consumer well-being by increasing persistence in low-attention behaviors.
Previous research has established that eating while viewing television is related to increased calorie consumption. However, despite the growing prevalence of smartphone use, very little research has investigated the relationship between phone use and eating behavior. Moreover, what little research exists has all been laboratory-based. The present study sought to fill this research gap by investigating smartphone use and eating behavior in everyday life. One hundred and thirty eight participants logged all foods and drinks consumed using MyFitnessPal and submitted smartphone screen time data for three consecutive days (Thursday through Saturday). Results revealed no significant associations between smartphone use and calorie consumption on any of the three study days. Additionally, morning phone use did not predict calories eaten in subsequent meals on any day. The type of phone use (e.g., social networking, reading, etc.) was also not related to total daily calorie intake. These findings tracking eating behavior in daily life contradict laboratory research, suggesting that smartphone use may not promote increased calorie intake in the same way that television viewing does.
Although television viewing during mealtime has been shown to associate with greater consumption of energy-dense foods, little is known about how new technological devices may influence children's food consumption. Because the number and type of media accessible to children continue to increase, this study examines the association between the presence of various media (TVs, mobile devices, video games, laptops) during mealtime and the healthfulness of children's meals. In this study, 61 primary caregivers of children ages 3–5 years and 10–13 years old participated in video-recorded dinner meals, which were reliably coded for media use, including number of media present. The overall healthfulness of the meals was coded using the Healthy Meal Index (HMI). Linear regression models were used to examine associations between number of media devices present during the meal and HMI, adjusting for parental education, income-to-needs ratio, and child race. Results indicate that the number of media present during the meal is inversely associated with HMI Total scores (B = -.29, p < .01; F(4, 53) = 9.97, p < .01). In other words, as the number of mealtime media devices increases, the healthfulness of children's meals decreases. These results suggest that media and device use during mealtime may be an additional childhood risk factor for poor meal quality, and parents should make efforts to limit mealtime media and device use.
Background
Despite a large volume of research on the impact of other digital screens (eg, televisions) on eating behavior, little is known about the nature and impact of mealtime smartphone use.
Objective
We investigated how smartphones are used in everyday meals, whether phone users differ according to mealtime phone use patterns, and whether specific phone functions (particularly food photography) would affect the amount and enjoyment of food eaten.
Methods
Across 2 studies, we used the experience sampling method to track 1780 meals in situ. In study 1, a total 137 young adults reported on their mealtime smartphone use 3 times per day over 7 consecutive days. This corresponded to each main meal, with participants recording whether they used their phones and what phone functions they engaged in while eating. In study 2, a total of 71 young adults were similarly tracked for 3 meals per day over 7 days. Across the week, participants’ meals were randomized to 1 of 3 smartphone conditions: food photography while eating, nonfood photography while eating, or no phone use. As the outcome measures, participants reported on the amount and enjoyment of food they ate.
Results
During the week-long tracking, most participants (110/129, 85.3%) recorded at least one instance of mealtime smartphone use, with an average frequency of 1 in 3 meals where phones were used (27.1%; 95% CI 23.6-30.6). Unlike traditional digital screens, mealtime phone use encompassed a wide range of social and nonsocial activities. Further, specific forms of phone use behaviors influenced food intake in different ways. Specifically, in study 2, participants showed the typical pattern of increased food intake across the day when they engaged in nonfood photography during a meal (P<.001); however, this pattern was disrupted when they engaged in food photography (P=.73).
Conclusions
Our findings underscore the prevalence and multifaceted nature of mealtime phone use, distinguishing mobile phones from traditional forms of digital screens.
Trial Registration
ClinicalTrials.gov NCT03299075; https://www.clinicaltrials.gov/ct2/show/NCT03299075 and ClinicalTrials.gov NCT03346785; https://clinicaltrials.gov/ct2/show/NCT03346785
This study aimed to evaluate the association between eating context patterns and ultra-processed food consumption at two main meal occasions in a representative sample of UK adolescents. Data was acquired from four-day food records of adolescents aged 11–18 years, who participated in the 2014–2016 UK National Diet and Nutrition Survey (n=542). The eating context was assessed considering the location of the meal (lunch and dinner) occasion, the individuals present, whether the television was on and if the food was consumed at a table. Ultra-processed foods were identified using the NOVA classification. Exploratory factor analysis was used to identify eating context patterns for lunch and dinner. Linear regression models adjusted for the covariates were utilised to test the association between eating context patterns and the proportion of total daily energy intake derived from ultra-processed foods. Their contribution was about 67% to total energy intake. Three patterns were retained for lunch (‘At school with friends’, ‘TV during family meal’, and ‘Out-of-home (no school)’); and three patterns were retained for dinner (‘Watching TV alone in the bedroom’, ‘TV during family meal’, and ‘Out-of-home with friends’). At lunch, there was no significant association between any of the three patterns and ultra-processed food consumption. At dinner, the patterns ‘Watching TV alone in the bedroom’ (coeff: 95%CI 4.95: 1.87–8.03) and ‘Out-of-home with friends’ (coeff: 95%CI 3.13: 0.21–6.14) were associated with higher consumption of ultra-processed food. Our findings suggest a potential relationship between the immediate eating context and ultra-processed food consumption by UK adolescents.
What is the role played by attentional load in eating? Does attending to an unrelated task generally lead to overeating, perhaps by preventing individuals from focusing on a goal to limit consumption? Or does such attentional diversion typically lead to reductions in eating, perhaps by preventing people from noticing tempting features of relevant food cues? Past research has supported each of these two propositions, but comparisons between existing studies have been hampered to the extent that various experimental manipulations differ in the degree to which they occupy attention, as well as differing in the particular type of attentional resources they exploit. To resolve existing discrepancies in the literature, in a series of studies, we made use of a working memory manipulation, the n-back task (Kirchner, 1958), that can be systematically modified to induce varying levels of cognitive load, allowing for rigorous comparisons of the effects of different levels of attentional load on eating. These studies revealed a complex pattern of results. Analysis of findings from three studies employing within-subjects designs documented a linear relationship, in that participants consumed less food when completing a higher cognitive-load task than when completing a lower cognitive-load task. Three studies employing between-subjects designs highlighted a less consistent pattern of results, but when combined in a mini-meta-analysis, suggested the opposite linear relationship, with participants assigned to higher cognitive-load conditions generally consuming more food than participants assigned to lower cognitive-load conditions. We conducted two additional studies to reconcile these conflicting patterns of data. Neither finding received unequivocal support, although both studies found that participants ate less when engaged in higher cognitive-load tasks than lower cognitive-load tasks. The precise nature of the relationship between attentional load and eating remains elusive.
The current epidemic of obesity is caused largely by an environment that promotes excessive food intake and discourages physical
activity. Although humans have evolved excellent physiological mechanisms to defend against body weight loss, they have only
weak physiological mechanisms to defend against body weight gain when food is abundant. Control of portion size, consumption
of a diet low in fat and energy density, and regular physical activity are behaviors that protect against obesity, but it
is becoming difficult to adopt and maintain these behaviors in the current environment. Because obesity is difficult to treat,
public health efforts need to be directed toward prevention.
To examine reproducibility and validity of visual analogue scales (VAS) for measurement of appetite sensations, with and without a diet standardization prior to the test days.
On two different test days the subjects recorded their appetite sensations before breakfast and every 30 min during the 4.5 h postprandial period under exactly the same conditions.
55 healthy men (age 25.6+/-0.6 y, BMI 22.6+/-0.3 kg¿m2).
VAS were used to record hunger, satiety, fullness, prospective food consumption, desire to eat something fatty, salty, sweet or savoury, and palatability of the meals. Subsequently an ad libitum lunch was served and energy intake was recorded. Reproducibility was assessed by the coefficient of repeatability (CR) of fasting, mean 4.5 h and peak/nadir values.
CRs (range 20-61 mm) were larger for fasting and peak/nadir values compared with mean 4.5 h values. No parameter seemed to be improved by diet standardization. Using a paired design and a study power of 0.8, a difference of 10 mm on fasting and 5 mm on mean 4.5 h ratings can be detected with 18 subjects. When using desires to eat specific types of food or an unpaired design, more subjects are needed due to considerable variation. The best correlations of validity were found between 4.5 h mean VAS of the appetite parameters and subsequent energy intake (r=+/-0.50-0.53, P<0.001).
VAS scores are reliable for appetite research and do not seem to be influenced by prior diet standardization. However, consideration should be given to the specific parameters being measured, their sensitivity and study power. International Journal of Obesity (2000)24, 38-48
It is widely believed that body fatness (and hence total body mass) is regulated by a lipostatic feedback system. This system is suggested to involve at least one peripheral signalling compound, which signals to the brain the current size of body fat stores. In the brain the level of the signal is compared with a desirable target level, and food intake and energy expenditure are then regulated to effect changes in the size of body fat stores. There is considerable support for this theory at several different levels of investigation. Patterns of body-mass change in subjects forced into energy imbalance seem to demonstrate homeostasis, and long-term changes in body mass are minor compared with the potential changes that might result from energy imbalance. Molecular studies of signalling compounds have suggested a putative lipostatic signal (leptin) and a complex network of downstream processing events in the brain, polymorphisms of which lead to disruption of body-mass regulation. This network of neuropeptides provides a rich seam of potential pharmaceutical targets for the control of obesity. Despite this consistent explanation for the observed phenomena at several different levels of enquiry, there are alternative explanations. In the present paper we explore the possibility that the existence of lipostatic regulation of body fatness is an illusion generated by the links between body mass and energy expenditure and responses to energy imbalance that are independent of body mass. Using computer-based models of temporal patterns in energy balance we show that common patterns of change in body mass following perturbation can be adequately explained by this 'non-lipostatic' model. This model has some important implications for the interpretations that we place on the molecular events in the brain, and ultimately in the search for pharmaceutical agents for alleviation of obesity.
The authors review the effect of the presence of others on food intake. In social facilitation studies, people tend to eat more in groups than when alone. In modeling studies, the presence of others may facilitate or inhibit intake, depending on how much these other people eat. Studies of impression management demonstrate that people tend to eat less in the presence of others than when alone. The authors attempt to reconcile these divergent literatures by reference to a model of inhibitory norms that govern eating. In the presence of palatable food, and in the absence of clear signals of satiety, people look outward to cues from the environment to determine when to stop eating. Socially derived inhibitory norms can account for either increased or decreased intake in the presence of others, depending on how much the others eat and the extent to which one is eager to impress them.
Package size, plate shape, lighting, socializing, and variety are only a few of the environmental factors that can influence the consumption volume of food far more than most people realize. Although such environmental factors appear unrelated, they generally influence consumption volume by inhibiting consumption monitoring and by suggesting alternative consumption norms. For researchers, this review suggests that redirecting the focus of investigations to the psychological mechanisms behind consumption will raise the profile and impact of research. For health professionals, this review underscores how small structural changes in personal environments can reduce the unknowing overconsumption of food.
The association of television viewing and obesity in data collected during cycles II and III of the National Health Examination Survey was examined. Cycle II examined 6,965 children aged 6 to 11 years and cycle III examined 6,671 children aged 12 to 17 years. Included in the cycle III sample were 2,153 subjects previously studied during cycle II. These surveys, therefore, provided two cross-sectional samples and one prospective sample. In all three samples, significant associations of the time spent watching television and the prevalence of obesity were observed. In 12- to 17-year-old adolescents, the prevalence of obesity increased by 2% for each additional hour of television viewed. The associations persisted when controlled for prior obesity, region, season, population density, race, socioeconomic class, and a variety of other family variables. The consistency, temporal sequence, strength, and specificity of the associations suggest that television viewing may cause obesity in at least some children and adolescents. The potential effects of obesity on activity and the consumption of calorically dense foods are consistent with this hypothesis.
Objective:
To examine prevalence of overweight and trends in overweight for children and adolescents in the US population.Design:
Nationally representative cross-sectional surveys with an in-person interview and a medical examination, including measurement of height and weight.Participants:
Between 3000 and 14000 youths aged 6 through 17 years examined in each of five separate national surveys during 1963 to 1965, 1966 to 1970, 1971 to 1974, 1976 to 1980, and 1988 to 1991 (Cycles II and III of the National Health Examination Survey, and the first, second, and third National Health and Nutrition Examination Surveys, respectively).Main Outcome Measures:
Prevalence of overweight based on body mass index and 85th or 95th percentile cutoff points from Cycles II and III of the National Health Examination Survey.Results:
From 1988 to 1991, the prevalence of over-weight was 10.9% based on the 95th percentile and 22% based on the 85th percentile. Overweight prevalence increased during the period examined among all sex and age groups. The increase was greatest since 1976 to 1980, similar to findings previously reported for adults in the United States.Conclusions:
Increasing overweight among youths implies a need to focus on primary prevention. Attempts to increase physical activity may provide a means to address this important public health problem.(Arch Pediatr Adolesc Med. 1995;149:1085-1091)
Although we are just beginning to understand how environmental factors such as portion size affect eating behavior, the available data suggest that large portions of energy-dense foods are contributing to the obesity epidemic. Several possible strategies for adjusting portions to bring intake back in line with energy requirements are discussed. The continuing rise in the rates of obesity calls for urgent action.
Objective.
—To examine trends in overweight prevalence and body mass index of the US adult population.Design.
—Nationally representative cross-sectional surveys with an in-person interview and a medical examination, including measurement of height and weight.Setting/Participants.
—Between 6000 and 13000 adults aged 20 through 74 years examined in each of four separate national surveys during 1960 to 1962 (the first National Health Examination Survey [NHES I]), 1971 to 1974 (the first National Health and Nutrition Examination Survey [NHANES I]), 1976 to 1980 (NHANESII), and 1988 to 1991 (NHANES III phase 1).Results.
—In the period 1988 to 1991,33.4% of US adults 20 years of age or older were estimated to be overweight. Comparisons of the 1988 to 1991 overweight prevalence estimates with data from earlier surveys indicate dramatic increases in all race/sex groups. Overweight prevalence increased 8% between the 1976 to 1980 and 1988 to 1991 surveys. During this period, for adult men and women aged 20 through 74 years, mean body mass index increased from 25.3 to 26.3; mean body weight increased 3.6 kg.Conclusions.
—These nationally representative data document a substantial increase in overweight among US adults and support the findings of other investigations that show notable increases in overweight during the past decade. These observations suggest that the Healthy People 2000 objective of reducing the prevalence of overweight US adults to no more than 20% may not be met by the year 2000. Understanding the reasons underlying the increase in the prevalence of overweight in the United States and elucidating the potential consequences in terms of morbidity and mortality present a challenge to our understanding of the etiology, treatment, and prevention of overweight.(JAMA. 1994;272:205-211)
Objective: This study examined the effects of physical activity, television viewing, video game play, socioeconomic status (SES), and ethnicity on body mass index (BMI).
Research Methods and Procedures: The sample was 2389 adolescents, 10 to 16 years of age (12.7 ± 1.0 years); 1240 (52%) females and 1149 (48%) males; 77% white and 23% African American; from rural (77%) and urban (23%) settings. BMI and skinfolds were directly assessed. All other data were obtained from questionnaires.
Results: Watching television on non-school days was related to being overweight (p < 0.005). However, when BMI analyses were adjusted for ethnicity and SES, there were no significant effects of television viewing on BMI (p > 0.061). Increased hours of video game play enhanced the risk of being overweight for both genders when analyses were adjusted for ethnicity and SES (p < 0.019). In males, participation in as little as one high-intensity physical activity 3 to 5 days a week decreased the ethnic- and SES-adjusted relative risk of being overweight (RR = 0.646; CI: 0.427 to 0.977). For females, the ethnic- and SES-adjusted relative risk for being overweight was not significantly altered by physical activity. The logistic analyses further indicated the influence of low SES and African American ethnicity overshadowed any direct effect of television or videos.
Discussion: Because weight status of male adolescents appears to be more related to exercise habits than to television or video game habits, increased participation in high-intensity exercise appears to be important. For females, neither videos nor exercise habits appear to be related to risk of being overweight. However, ethnicity and SES may be important factors that can influence body weight status, while television viewing may be of some importance. Thus, programs to reduce obesity in female adolescent should focus their efforts in lower SES communities.
We tested the effects of 3 mood inductions (neutral, positive, and negative) on food intake in 91 women of varying degrees of dietary restraint. Mood induction was accomplished by exposure to 1 of 3 film segments: a travelogue (neutral affect), a comedy film (positive affect), and a horror film (negative affect). In subjects exposed to the neutral film, food intake decreased with increasing levels of dietary restraint. Among subjects who viewed either the comedy film or the horror film, however, food intake increased with increasing restraint. Although the horror film appeared to be more disinhibiting than the comedy film, this effect may have resulted from a difference in the intensity of the emotions induced rather than from their valence. These results suggest that emotional arousal, regardless of valence, may trigger overeating among restrained eaters.
The association of television viewing and obesity in data collected during cycles II and III of the National Health Examination Survey was examined. Cycle II examined 6,965 children aged 6 to 11 years and cycle III examined 6,671 children aged 12 to 17 years. Included in the cycle III sample were 2,153 subjects previously studied during cycle II. These surveys, therefore, provided two cross-sectional samples and one prospective sample. In all three samples, significant associations of the time spent watching television and the prevalence of obesity were observed. In 12- to 17-year-old adolescents, the prevalence of obesity increased by 2% for each additional hour of television viewed. The associations persisted when controlled for prior obesity, region, season, population density, race, socioeconomic class, and a variety of other family variables. The consistency, temporal sequence, strength, and specificity of the associations suggest that television viewing may cause obesity in at least some children and adolescents. The potential effects of obesity on activity and the consumption of calorically dense foods are consistent with this hypothesis.
This report describes the construction of a questionnaire to measure three dimensions of human eating behavior. The first step was a collation of items from two existing questionnaires that measure the related concepts of 'restrained eating' and 'latent obesity', to which were added items newly written to elucidate these concepts. This version was administered to several populations selected to include persons who exhibited the spectrum from extreme dietary restraint to extreme lack of restraint. The resulting responses were factor analyzed and the resulting factor structure was used to revise the questionnaire. This process was then repeated: administration of the revised questionnaire to groups representing extremes of dietary restraint, factor analysis of the results and questionnaire revision. Three stable factors emerged: (1) 'cognitive restraint of eating', (2) 'disinhibition' and (3) 'hunger'. The new 51-item questionnaire measuring these factors is presented.
To investigate the specificity of satiety in man, subjects (n=32) rated the pleasantness of the taste of eight foods, were then given one of the foods to eat for lunch, and re-rated the pleasantness of the taste of the eight foods 2 and 20 min after the end of the meal. The pleasantness of the food eaten decreased more than that of the foods not eaten (p<0.001). In a second experiment it was shown that this relative specificity of satiety influenced subsequent food intake. Before a first course, subjects (n=24) rated their liking for the taste of eight foods, were then given one of the foods to eat for lunch, and 2 min after finishing eating re-rated their liking for the taste of the eight foods. Again liking decreased more for the food eaten than for foods not eaten. These changes in liking for the foods eaten and not eaten were highly correlated (p<0.001) with the amounts of those foods eaten in an unexpected second course. Thus in man satiety can be partly specific to foods eaten and this specificity may be an important determinant of the foods selected for consumption.
To examine prevalence of overweight and trends in overweight for children and adolescents in the US population.
Nationally representative cross-sectional surveys with an in-person interview and a medical examination, including measurement of height and weight.
Between 3000 and 14,000 youths aged 6 through 17 years examined in each of five separate national surveys during 1963 to 1965, 1966 to 1970, 1971 to 1974, 1976 to 1980, and 1988 to 1991 (Cycles II and III of the National Health Examination Survey, and the first, second, and third National Health and Nutrition Examination Surveys, respectively).
Prevalence of overweight based on body mass index and 85th or 95th percentile cutoff points from Cycles II and III of the National Health Examination Survey.
From 1988 to 1991, the prevalence of overweight was 10.9% based on the 95th percentile and 22% based on the 85th percentile. Overweight prevalence increased during the period examined among all sex and age groups. The increase was greatest since 1976 to 1980, similar to findings previously reported for adults in the United States.
Increasing overweight among youths implies a need to focus on primary prevention. Attempts to increase physical activity may provide a means to address this important public health problem.
This study examined the association between TV viewing, fast food eating, and body mass index.
Associations between hours of TV viewing, frequency of eating at fast food restaurants, body mass index, and behaviors were assessed cross sectionally and longitudinally over 1 year in 1059 men and women.
Fast food meals and TV viewing hours were positively associated with energy intake and body mass index in women but not in men. TV viewing predicted weight gain in high-income women.
Secular increases in fast food availability and access to televised entertainment may contribute to increasing obesity rates in the United States.
The relationship of moods and social context to energy and nutrient intakes was examined to ascertain if these variables interact or function independently. The subjects were 78 predominantly white, obese women participating in weight-loss studies. Mean age was 36.7 (SD=7.6) and mean Body Mass Index was 32.1 (SD=3.6). Subjects completed 2-week baseline food diaries recording everything they ate, including moods and people present during the meals. Meals eaten in positive and negative moods were significantly larger than meals eaten in a neutral mood. Meals eaten with other people were significantly larger than meals eaten alone. There were no significant moods by social context interactions for total energy intake. Moods and social context functioned additively to increase the risk of over-eating. Macro nutrient analysis revealed only a main effect for social context. Percentage of calories from fat and protein were greater, whereas the percentage of carbohydrate was less in social context meals compared to meals eaten alone. Clinicians should conduct a functional analysis to assess exposure to the frequency and types of risky situations. Teaching people to cope more effectively with social situations and moods may increase the efficacy of weight loss and maintenance programs.
To examine the relationship between physical activity, TV watching, and weight in U.S. youth ages 14 to 18 years.
Data from a nationally representative sample of 15,143 U.S. high-school students participating in the 1999 Centers for Disease Control and Prevention (CDC) Youth Risk Behavior Survey were examined. Prevalence rates of participation in moderate physical activity (MPA), vigorous physical activity (VPA), and television watching (TV) were determined. The association between MPA, VPA, TV and the body mass index (BMI) and overweight status (BMI > or =85th percentile of age- and sex-specific CDC/National Center for Health Statistics reference values) were examined by analysis of covariance and logistic regression.
Overall, 45% reported participating in MPA > or =3 d/wk, 65% reported participating in VPA > or =3 d/wk, and 25% reported watching TV > or =4 h/school day. Boys reporting six to seven bouts of MPA had a significantly lower BMI compared with boys reporting three to five or less than two. The mean BMI differed significantly between the lowest and highest levels of MPA groups in girls. The mean BMI was significantly lower in the highest VPA group compared with the other two groups in both sexes. There was a significant graded response for BMI across all levels of TV. Decreased levels of MPA and 3 to 4 days of VPA were significantly associated with an increased risk of overweight in boys when compared with those engaging in 6 to 7 d/wk (odds ratio = 1.26 to 1.37). A graded response existed between TV and overweight in both sexes. Boys and girls were approximately 20% to 25% less likely to be classified as overweight if they reported 2 to 3 hours of TV per day and approximately 40% less likely to be classified as overweight if they reported < or =1 hour of TV per day compared with those who watched > or =4 hours of TV. In general, youth who engaged in less physical activity watched more TV per week.
Increased levels of physical activity are associated with a lower BMI and less TV watching. However, the relationship between TV watching and weight status is more pronounced.
In sample of 76 undergraduate students (mostly female) in the USA, television viewing was associated with increased meal frequency and as a result with increased daily intake of energy.
Television viewing is associated with childhood obesity. Eating during viewing and eating highly advertised foods are 2 of the hypothesized mechanisms through which television is thought to affect children's weight.
Our objectives were to describe the amounts and types of foods that children consume while watching television, compare those types with the types consumed at other times of the day, and examine the associations between children's body mass index (BMI) and the amounts and types of foods consumed during television viewing.
Data were collected from 2 samples. The first sample consisted of ethnically diverse third-grade children, and the second consisted predominantly of Latino fifth-grade children. Three nonconsecutive 24-h dietary recalls were collected from each child. For each eating episode reported, children were asked whether they had been watching television. Height and weight were measured by using standard methods and were used to calculate BMI.
On weekdays and weekend days, 17-18% and approximately 26% of total daily energy, respectively, were consumed during television viewing in the 2 samples. Although the fat content of the foods consumed during television viewing did not differ significantly from that of the foods consumed with the television off, less soda, fast food, fruit, and vegetables were consumed with the television on. The amount of food consumed during television viewing was not associated with children's BMI, but in the third-grade sample, the fat content of foods consumed during television viewing was associated with BMI.
A significant proportion of children's daily energy intake is consumed during television viewing, and the consumption of high-fat foods on weekends may be associated with BMI in younger children.
The objective of the present study, performed under laboratory conditions, was to assess the impact of two non food-related environmental stimuli (television and auditory stimulus) on meal intake. Normal weight women (N = 48) ate lunch in the laboratory once a week for four weeks. All lunches were identical and included popular traditional foods, of which participants could eat ad libitum. The first and last lunches were eaten in the absence of the environmental stimuli (control conditions); in the other two tests, presented in random order, subjects ate while either watching television or listening to a recorded story. Energy intakes were determined for each meal, as were ratings of hunger, satiety and meal palatability. Subjects filled out the Three Factor Eating Questionnaire at the end of the meal series. Meal size was significantly larger in the presence of both environmental stimuli than in both control conditions (+11.6%, 280 kJ, p < 0.01). Television viewing induced a significant stimulation of intake, equal to, but not greater than the effect of the auditory stimulus. Ratings of hunger, satiety, and palatability were not significantly different between conditions, despite the differences in intake. These results suggest that environmental, non food-related stimuli could stimulate intake regardless of hunger-satiety or palatability conditions. Environmental stimulation of eating should be tested in other populations, eg subjects with weight control problems, and other conditions, e.g. free-living.
This study examined the links between childhood obesity, activity participation and television and video game use in a nationally representative sample of children (N = 2831) ages 1-12 using age-normed body mass index (BMI) ratings. Results indicated that while television use was not related to children's weight status, video game use was. Children with higher weight status played moderate amounts of electronic games, while children with lower weight status played either very little or a lot of electronic games. Interaction analyses revealed that this curvilinear relationship applied to children under age 8 and that girls, but not boys, with higher weight status played more video games. Children ages 9-12 with lower weight status used the computer (non-game) for moderate amounts of time, while those with higher weight status used the computer either very little or a lot. This was also true for the relationship between print use and weight status for children of all ages. Results also indicated that children with higher weight status spent more time in sedentary activities than those with lower weight status.
The objective was to examine the extent to which overfeeding reduces spontaneous food intake in humans. Twelve normal-weight adults participated in the three stage study. During the 14 day baseline period and 21 day recovery period, food intake was consumed ad libitum, beyond a minimum 5 MJ (1200 kcal) basal diet. During the 13 day period of overfeeding, each subject consumed 35% more energy than they consumed at baseline. Overfeeding resulted in a weight gain of 2.3+/-0.37 kg, (p<0.0001), approximately half the weight gain was determined to be fat (1.2+/-0.19 kg, p<0.0001) by underwater densitometry. Following overfeeding, mean daily caloric intake was not significantly suppressed returning immediately to baseline values. Despite normal energy intake, participants lost 1.3+/-0.24 kg of body weight (p<0.0001), of which 0.75+/-0.15 kg (p<0.0001) was fat. These results indicated that (1) the physiological control of eating behavior in humans is not the major mechanism responsible for the recovery of body weight following a period of overfeeding and (2) an increase in energy expenditure of 1.28 MJ (307 kcal)/day or about 14% was required to account for the weight loss following overfeeding.
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