The mediating role of energy intake on the relationship between screen time behaviour and body mass index in adolescents with obesity: The HEARTY study

Diet Quality and Its Association with Lifestyle and Dietary Behaviors among Croatian Students during Two COVID-19 Lockdowns

The present study aims to assess the diet quality, the relationship between diet quality and lifestyle, and the association of diet quality with body mass index and students' field of study during COVID-19 lockdown periods (spring and winter) in 2020. Datasets were collected via an anonymous online self-reported questionnaire distributed during two time periods using social media. A total of 1939 Croatian students (82.4% women and 17.6% men) completed the questionnaire. Diet quality was assessed using the pro-healthy diet index (pHDI) and non-healthy diet index (nHDI). An increase in diet quality was noted during both lockdown periods but was lower during the winter lockdown. Cooking for oneself was associated with a high level of pHDI, while ordering or buying ready-to-eat food was linked to a low level of pHDI. Additionally, a decrease in screen time and increased physical activity was associated with high pHDI values. Furthermore, during both lockdown periods, students with a BMI above 30 kg/m² had the highest nHDI values compared to other students. Although positive changes were found during both lockdown periods, they were less pronounced throughout the winter lockdown. Further studies are needed to elucidate the real impact of these changes in the post-COVID period.

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Aim

Few previous studies have investigated the impact of multiple types of electronic devices on health status, and the moderating effects of gender, age, and BMI. Our aim is to examine the relationships between the use of four types of electronics and three health status indicators in a middle-aged and elderly population, and how these relationships varied by gender, age, and BMI.

Subject and methods

Using data from 376,806 participants aged 40-69 years in the UK Biobank, we conducted a multivariate linear regression to estimate the association between electronic device use and health status. Electronics use was categorized as TV watching, computer use, computer gaming, and mobile phone use, and health status included self-rated health (SRH), multisite chronic pain (MCP), and total physical activity (TPA). Interaction terms were utilized to assess whether the above associations were modified by BMI, gender, and age. Further stratified analysis was performed to explore the role of gender, age, and BMI.

Results

Higher levels of TV watching (BSRH = 0.056, BMCP = 0.044, BTPA= -1.795), computer use (BSRH = 0.007, BTPA= -3.469), and computer gaming (BSRH = 0.055, BMCP = 0.058, BTPA= -6.076) were consistently associated with poorer health status (all P < 0.05). Contrastingly, earlier exposure to mobile phones (BSRH = -0.048, BTPA= 0.933, BMCP = 0.056) was inconsistent with health (all P < 0.05). Additionally, BMI (Bcomputer use-SRH= 0.0026, Bphone-SRH= 0.0049, BTV-MCP= 0.0031, and BTV-TPA= -0.0584) exacerbated the negative effects of electronics use, and male (Bphone-SRH = -0.0414, Bphone-MCP = -0.0537, Bphone-TPA= 2.8873) were healthier with earlier exposure to mobile phones (all P < 0.05).

Conclusion

Our findings suggest that the adverse health effects associated with watching TV, computer use, and computer gaming were consistent and were moderated by BMI, gender, and age, which advances a comprehensive understanding of the association between multiple types of electronic devices and health status, and provides new perspectives for future research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-023-01886-5.

Do dietary patterns differ with video game usage in college men?

Objective: To assess differences in dietary quality among college men reporting high, moderate, and non-video game usage. Participants: College men aged 18-24. Methods: Cross-sectional data were collected between 2012 and 2020. Participants (n = 1259) were categorized according to self-reported video game usage: non-users (NVG), <1 h/day (MVG), and ≥1 h/day (HVG). ANCOVA identified group differences in nutrient intake from 3-day food records. Results: College men reported 30% NVG, 39% MVG, and 31% HVG. Higher saturated fat (30.2 ± 0.4 g and 30.1 ± 0.3 g, vs. 28.5 ± 0.4 g, p < .01, p < .01) and lower fruit/vegetable intake (3.00 ± 0.1 cups and 2.91 ± 0.1 cups, vs. 3.45 ± 0.1 cups, p < .00, p < .00) was observed in HVG and MVG vs. NVG. Higher discretionary calories (750 ± 13 kcals, vs. 686 ± 13 kcals, p < .00) in HVG and sodium (3922 ± 44 mg, vs. 3860 ± 50 mg, p < .02) in MVG were reported vs. NVG. Conclusion: Video game usage was associated with higher saturated fat, sodium, discretionary calories, and lower F/V intake in college men.

Fright but not fight‐or‐flight: Violent video games elevated stress markers, but did not impact muscle function, memory recall or food intake, in a randomized trial in healthy young men

Objectives

Regular video game playing has been linked with obesity, but the underlying mechanisms remain unclear. Drawing on evolutionary life history theory, we hypothesized that playing violent video games, through activating the stress response, might increase the immediate demand for fuel by muscle and brain tissue, resulting in elevated appetite and food consumption.

Methods

We randomized 71 young adult men to play video games, involving either violent content or nonviolent puzzle‐solving, for 1 h. Over this period, we measured stress markers (blood pressure [BP], heart rate, visual‐analogue scale [VAS] self‐ratings), muscle function (handgrip strength) and cognitive function (memory recall test). Appetite was assessed by VAS, and by food intake using a test‐meal after the intervention. Linear mixed‐effects models were fitted to assess group effects and group:time effects.

Results

During the intervention, the violent video game group showed elevated systolic BP (∆ = 4.7 mm Hg, 95% CI 1.0, 8.4) and reported feeling more alert but less calm or happy. They showed no difference in grip strength or memory recall. They reported lower feelings of “fullness” but consumed similar food‐energy during the test‐meal.

Conclusions

Although playing a video game with violent content elevated physiological and perceived stress markers compared with a nonviolent game, this was not associated with markers of altered fuel distribution toward two tissues (muscle and brain) that contribute to the “fight‐or‐flight” response. Rather than more energy being allocated to the brain overall, energy may have been reallocated within the brain. This may explain why there was no compensatory increase in energy intake in the violent video game group.

Association of Night-Time Screen-Viewing with Adolescents' Diet, Sleep, Weight Status, and Adiposity

Night-time screen-viewing (SV) contributes to inadequate sleep and poor diet, and subsequently excess weight. Adolescents may use many devices at night, which can provide additional night-time SV. Purpose: To identify night-time SV patterns, and describe differences in diet, sleep, weight status, and adiposity between patterns in a cross-sectional and longitudinal manner. Methods: Adolescents (10–16 y) reported devices they viewed at night and completed food recalls. Accelerometry, anthropometrics, and imaging were conducted to measure sleep, weight status, and adiposity, respectively. Latent class analysis was performed to identify night-time SV clusters. Linear regression analysis was used to examine associations between clusters with diet, sleep, weight status, and adiposity. Results: Amongst 273 adolescents (12.5 ± 1.9 y, 54% female, 59% White), four clusters were identified: no SV (36%), primarily cellphone (32%), TV and portable devices (TV+PDs, 17%), and multiple PDs (17%). Most differences in sleep and adiposity were attenuated after adjustment for covariates. The TV+PDs cluster had a higher waist circumference than the no SV cluster in cross-sectional analysis. In longitudinal analysis, the primarily cellphone cluster had less change in waist circumference compared to the no SV cluster. Conclusions: Directing efforts towards reducing night-time SV, especially TV and PDs, may promote healthy development.

Contemporary screen time usage among children 9-10-years-old is associated with higher body mass index percentile at 1-year follow-up: A prospective cohort study

OBJECTIVE

There is a paucity of prospective research exploring the relationship among contemporary screen time modalities (e.g., video streaming, video chatting, texting and social networking) and body mass index (BMI) percentile. The objective of this study was to determine the prospective associations between screen time behaviours in a large and demographically diverse population-based cohort of 9-10-year-old children and BMI percentile at 1-year follow-up.

METHODS

We analyzed prospective cohort data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11 066). Multiple linear regression analyses were conducted to estimate associations between baseline screen time behaviours (exposure) and BMI percentile at 1-year follow-up, adjusting for race/ethnicity, sex, household income, parent education, depression, binge-eating disorder and baseline BMI percentile.

RESULTS

Each additional hour of total screen time per day was prospectively associated with a 0.22 higher BMI percentile at 1-year follow-up (95% CI 0.10-0.34) after adjusting for covariates. When examining specific screen time behaviours, each additional hour of texting (B = 0.92, 95% CI 0.29-1.55), video chat (B = 0.72, 95% CI 0.09-1.36) and video games (B = 0.42, 95% CI 0.06-0.78) was significantly prospectively associated with higher BMI percentile.

CONCLUSIONS

Screen time is prospectively associated with a higher BMI percentile 1 year later among children 9-10 years old.

Body Weight Perception and Health-Related Behaviors Among U.S. Adolescents: Mediating Effects of Body Weight Control Behaviors

This study examined mediating effects of body weight control behaviors in the relationship between body weight perception and health-related behaviors among 11,458 U.S. adolescents from the 2010 National Youth Physical Activity and Nutrition Survey. Parallel multiple mediation analysis was performed for the secondary data analysis. Nearly one third of adolescents (32.5%) had overweight or obesity; one quarter (25.0%) perceived themselves as slightly overweight and 5.1% thought they were very overweight. More girls (58.6%) had tried to lose weight than boys (32.3%), while boys were more physically active than girls. Healthy and unhealthy weight control behaviors significantly mediated the relationship between adolescents' body weight perception and health-related behaviors (physical activity and screen time). Teachers and parents should help adolescents have accurate weight perception and utilize reliable and healthy weight control strategies. Future studies should consider the intercorrelated relationships among adolescents' perceptions and behaviors regarding weight to provide successful weight control intervention programs.

Mediating role of disordered eating in the relationship between screen time and BMI in adolescents: longitudinal findings from the Research on Eating and Adolescent Lifestyles (REAL) study

OBJECTIVE

This study investigated whether the duration and type of screen time (ST) (TV viewing, recreational computer use, video gaming) is longitudinally associated with z-BMI and if these relationships are mediated by disordered eating (emotional, restrained).

DESIGN

At baseline, participants were n 1197 (T1; 60 % female) adolescents (mean age = 13·51 years) who completed surveys over 2 years. ST was assessed by a self-reported measure created by the investigative team, while emotional and restrained eating was measured by the Dutch Eating Behaviour Questionnaire (DEB-Q). Height and weight were objectively measured to quantify z-BMI.

SETTING

Thirty-one public and two private schools from the region of Ottawa, Canada.

PARTICIPANTS

Students in grades 7-12.

RESULTS

Parallel multiple mediation analyses revealed that more time spent watching TV at baseline is associated with higher z-BMI at T3 (total effect; B = 0·19, se = 0·07, P = 0·01, 95 % CI 0·05, 0·34), but no relationships were observed for total ST exposure or other types of ST and z-BMI. Disordered eating did not mediate the positive association between baseline TV viewing and z-BMI at T3.

CONCLUSIONS

TV viewing was longitudinally associated with higher z-BMI in a community-based sample of adolescents, but disordered eating behaviours did not mediate this relationship. However, other non-pathological eating behaviours may mediate the association between ST and obesity and warrant further investigation. Finding suggests that targeting reduction in youth's TV viewing may be an effective component in the prevention of childhood obesity.

Video Games, Obesity, and Children

PURPOSE OF REVIEW

To examine associations between video game play and obesity in children.

RECENT FINDINGS

Based on a scoping review of 26 studies (25 cross-sectional; 1 longitudinal) published in 2013-2018, 14 studies (53%) reported no association between video game play and obesity, and 12 studies reported positive associations. In a review of 8 systematic reviews, there was preliminary evidence on the effectiveness of exergame (physically active) play for weight reduction and to attenuate weight gain but little indication that interventions effectively reduced video game play or general screen time. This review found ambiguous evidence on the extent to which video game play is or is not significantly associated with obesity in children and preliminary evidence of exergame play as a tool for weight reduction and attenuation of weight gain. Several gaps existed in understanding the relationship between video game play and obesity, and prospective and interventional trials are needed.

Clustering of unhealthy behaviors in a nationally representative sample of U.S. children and adolescents

Poor diet, low physical activity, sedentary behavior and smoking are modifiable risk factors for chronic diseases that often develop early in life. An improved understanding of how unhealthy behaviors co-occur within individual children across childhood and adolescence could inform the development of more effective prevention approaches. Using data from the 2011-2016 National Health and Nutrition Examination Survey, we calculated weighted prevalence of five unhealthy behaviors - excessive screen time, poor diet quality, low physical activity, fast food consumption, and smoking (adolescents only) - alone and in combination among U.S. children and adolescents, stratified by age group (2-5, 6-11, 12-15, and 16-19 years). Multivariable logistic regression was used to estimate associations between health behavior clustering (≥2 unhealthy behaviors) and sociodemographic characteristics by age group. Among 7714 children and adolescents, the most prevalent behaviors were excessive screen time and poor diet quality. Unhealthy behavior clustering increased significantly with age (from 29.0% for ages 2-5 to 73.9% for ages 16-19 years, p-trend: <0.0001). The most common health behavior combination was excessive screen time and poor diet (from 14.4% prevalence for ages 2-5 to 45.3% for ages 16-19 years). Smoking prevalence was low, but 97% of smokers had ≥1 other unhealthy behavior. Unhealthy behavior clustering was significantly more prevalent among black than white children (ages 2-5 and 6-11) and less prevalent among Hispanic older adolescents (age 16-19). Associations with household characteristics varied by age group. These results provide a population-level understanding of the extent to which unhealthy behaviors co-occur in U.S. children and adolescents.

[Association of mobile phone overuse with sleep disorder and unhealthy eating behaviors in college students of a medical university in Guangzhou]

OBJECTIVE

To investigate the association of mobile phone use with sleep disorder and unhealthy eating behavior among college students of a medical university in Guangzhou.

METHODS

Mobile Phone Involvement Questionnaire (MPIQ), Pittsburgh Sleep Quality Index (PSQI) and the Three Factor Eating Questionnaire Revised 21 Item (TFEQ-R21) were used to survey 2122 undergraduates of the medical university. One-sample t test, One-way ANOVA and multiple linear regression analysis were used to analyze the data.

RESULTS

Age, body mass index (BMI), phone use before sleep, phone use frequency, sleep quality (assessed by total PSQI score) and the dimension scores of TFEQ-R21 for uncontrolled eating, cognitive restraint, and emotional eating were all significantly correlated with the total score of MPIQ (P < 0.05). Phone use before sleep, high frequency of mobile phone use, poor sleep quality and emotional eating were associated with high MPIQ scores, while lower cognitive restraint and emotional eating tendency were correlated with lower scores of MPIQ. Bivariate analysis revealed that age (r=0.088, P < 0.001), BMI (r=0.055, P < 0.05), PSQI scores (r=0.204, P < 0.001), TFEQ-UE scores (r=0.199, P < 0.001), TFEQ-CR scores (r=-0.076, P < 0.001), TFEQ-EE scores (r=0.170, P < 0.001), phone use before sleep (r=0.429, P < 0.001), and phone use frequency (r=0.316, P < 0.001) were all significantly correlated with MPIQ scores; multiple linear regression analysis showed that model 4 incorporating the scores of TFEQ-UE, TFEQ-CR, and TFEQ-EE explained up to 21.8% of the main effect (adjusted R2= 21.5%).

CONCLUSIONS

Mobile phone overuse is associated with poor sleep quality and unhealthy eating behaviors, and education and interventions for mobile phone use is essential among college students.

Associations of Sleep with Food Cravings, Diet, and Obesity in Adolescence

Background: Sleep and dietary intake/quality can contribute to excess weight gain, but food cravings may influence these relationships. This cross-sectional study examined the relationship of adolescents’ sleep characteristics with dietary intake/quality and obesity and whether food cravings mediated these relationships. Methods: Sleep measures were calculated based on 24-h accelerometry, and height and weight were directly measured to calculate body mass index (BMI) z-scores. Food cravings were assessed by the Food Craving Inventory (FCI). Dietary intake and quality were calculated based on dietary recalls. Multivariable linear regression was used to examine the associations among sleep, food cravings, dietary intake/quality, and obesity, adjusting for confounders. Results: In total, 256 adolescents (ages 10–16 years) had complete data; 42% were non-White and 45% were boys. Sleep efficiency was inversely associated with sweet cravings and FCI-28. Sleep duration, meeting the sleep duration guidelines, and fruit/vegetable cravings were each positively associated with dietary quality. Sleep duration was negatively associated with BMI z-score. Mediation models were not performed as no sleep parameter was associated with both cravings and dietary intake/quality or BMI z-score. Conclusions: Associations existed among poor sleep, quantity and quality, with more frequent food cravings and worse dietary quality. Sleep may underlie adolescent obesogenic behaviors.

The association between excessive screen-time behaviors and insufficient sleep among adolescents: Findings from the 2017 youth risk behavior surveillance system

Although studies have examined the association between television viewing and poor sleep quality, few studies have considered the association between excessive screen-time behaviors and insufficient sleep among adolescents drawing on a large nationally representative sample. The objective of this study was to examine the association between excessive screen-time behaviors and insufficient sleep among adolescents. Data for this study came from the 2017 Youth Risk Behavior Survey. A sample of 14,603 adolescents aged 14-18 years (51.5% female) was analyzed using logistic regression with insufficient sleep as the outcome variable and excessive screen-time behaviors as the main explanatory variable. Of the 14,603 adolescents, almost three out of four (74.8%) had less than 8 h of sleep on an average school night, and about 43% engaged in excessive screen-time behaviors on an average school day. Controlling for all other predictors, odds were 1.34 times higher for adolescents who engaged in excessive screen-time behaviors to have insufficient sleep when compared to adolescents who did not engage in excessive screen-time behaviors (AOR = 1.34, p < .001, 95% CI = 1.22-1.48). School-based behavior interventions that focus on reduction in excessive screen-time and sedentary behaviors might be beneficial in reducing excessive screen-time behaviors and consequently improve sleep quality among adolescents.

Digital Commensality: Eating and Drinking in the Company of Technology

Commensality is a key aspect of social dining. However, previous research has identified a number of pros and cons associated with the incorporation of digital technology into eating and drinking episodes. For instance, those who are distracted by digital technology may eat/drink more (that is, they may overconsume) as a result of their failure to attend to the food-related sensations that are thought to cue the termination of eating. Similarly, it has often been suggested that the use of mobile devices at mealtimes can disrupt the more commensal aspects of dining/drinking (at least among those who are physically present together). At the same time, however, looking to the future, it seems clear that digital technologies also hold the promise of delivering opportunities for enhanced multisensory experiential dining. For instance, they might be used to match the auditory, visual, or audiovisual entertainment to the eating/drinking episode (e.g., think only about watching a Bollywood movie while eating a home-delivery Indian meal, say). Indeed, given the growing societal problems associated with people dining by themselves, there are a number of routes by which digital technologies may increasingly help to connect the solo diner with physically co-located, remote, or even virtual dining partners. In this review of the literature, our focus is specifically on the role of technology in inhibiting/facilitating the more pleasurable social aspects of dining, what one might call "digital commensality." The focus is primarily on Westernized adults with reasonable access to, and familiarity with, digital technologies.

An examination of how age of onset for alcohol, cannabis, and tobacco are associated with physical activity, screen time and BMI as students are preparing to graduate from high school

Introduction

In this study we examined the co-occurrence of alcohol, cannabis, and tobacco among a large cohort of grade 12 students in Canada, and then explored if the age of initiation of these substances was associated with moderate-to-vigorous physical activity (MVPA), screen time, and BMI.

Methods

This cross-sectional study used student-level data from grade 12 students in years 1 to 5 (2012–2016) of the COMPASS study. Random intercept linear regression models were used to examine the impact of age of initiation of alcohol, cannabis, and tobacco use on student average daily physical activity, daily screen time and BMI.

Results

Twenty-eight percent of students had only tried one substance with alcohol being the most reported single substance used (25%). The most common co-occurrence was students reporting having tried all three substances (27%). Nineteen percent of students reported no substance use by grade 12.

Younger age of first use of alcohol was associated with increased MVPA in grade 12. Earlier initiation of cannabis and tobacco were associated with increased screen time in grade 12. Age of first use of alcohol, cannabis and tobacco were not associated with BMI in grade 12.

Conclusion

While no specific cut-off age was identified this study indicates that for every year tobacco and cannabis use are delayed among children, there are subsequent reductions to screen time in grade 12. Early initiation of alcohol was associated with increased MVPA in grade 12. Early initiation of alcohol, cannabis and tobacco were not associated with BMI in grade 12.

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Less than 1 in 5 students reported no substance use by grade 12.

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75% of students had tried alcohol by the end of high school.

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Initiating cannabis and tobacco earlier was associated with increased screen time.

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Age of first use of all substances not associated with BMI in grade 12.

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Initiating alcohol use at a younger age was associated with more MVPA in grade 12.

Effect of video game playing and a glucose preload on subjective appetite, subjective emotions, and food intake in overweight and obese boys

Video game playing (VGP) is associated with overweight/obesity (OW/OB). VGP and caloric preloads in the pre-meal environment influence short-term food intake (FI) in healthy-weight children. Therefore, the purpose of the present study was to examine the effect of pre-meal VGP and a glucose preload on subjective emotions, subjective appetite, and FI in boys with OW/OB. On 4 separate mornings, boys with OW/OB (n = 22; mean ± SD: age = 11.9 ± 1.6 years; body mass index percentile = 94.3 ± 3.9) participated in 4 test conditions. Two hours after a standardized breakfast, boys consumed equally sweetened preloads (250 mL) of sucralose (0 kcal) or glucose (200 kcal), with or without 30 min of subsequent VGP. Immediately after each test condition, FI was evaluated during an ad libitum pizza meal. Subjective appetite was measured at 0 (baseline), 15, and 30 min. Subjective emotions (aggression, anger, excitement, disappointment, happiness, upset, and frustration) were measured at 0 and 30 min. VGP did not affect FI, but the glucose preload decreased FI compared with the sucralose control (Δ = -103 ± 48 kcal, p < 0.01). However, cumulative FI (preload kcal + meal kcal) was 9% higher after the glucose preload (p < 0.01). Subjective appetite increased with time (p < 0.05) but was not influenced by preload or VGP. Frustration was the only subjective emotion that increased following VGP (p < 0.01). A glucose preload, but not VGP, suppressed FI in boys with OW/OB, suggesting a primary role of physiological factors in short-term FI regulation.

Impact of a Healthy Weight Intervention Embedded Within a National Home Visiting Program on the Home Food Environment

Purpose: To determine whether a lifestyle intervention embedded within Parents as Teachers (PAT), a national child development and parenting home visiting program, helped families make food-related home environment changes.

Design: Secondary data analysis of a stratified randomized pragmatic trial. (Trial Registration: This study is registered at www.clinicaltrials.gov NCT01567033).

Setting: Participant homes in St. Louis, Missouri.

Subjects: Women (n = 179 with pre-post data, of 230 with baseline) participating in standard PAT, with overweight or obesity, and at least one preschool child with BMI percentile ≥60%.

Intervention: PAT + Healthy Eating and Active Living Taught at Home (HEALTH), embedded elements of the Diabetes Prevention Program within the standard PAT curriculum. PAT + HEALTH addressed specific behaviors that impact caloric intake (e.g., sugar-sweetened beverages), focusing on behavioral and environmental strategies. Consistent with PAT practice, the frequency, number, and focus (i.e., time spent on intervention components) of home visits were determined by the family's needs; dose structure was flexible [on average intervention: 23 (SD = 9), usual care: 13 (SD = 6) visits].

Measures: Food availability/accessibility and distractions in the home were assessed with items drawn largely from the HomeSTEAD Survey.

Analysis: Generalized estimating equations (GEEs) were used to test equality of changes between baseline and 24 months in the intervention and usual care groups.

Results: The only significant difference in the pattern of change between usual care and intervention was soda availability/accessibility (p = 0.013).

Conclusion: This embedded intervention successfully reduced availability/accessibility of sugar-sweetened beverages in the home. However, given the limited impact on other food-related home environment factors, future interventions could seek to more effectively intervene on all aspects of the home environment.