The fault, dear viewer, lies not in the screens, but in ourselves: relationships between screen media and childhood overweight/obesity

Media use trajectories and risk of metabolic syndrome in European children and adolescents: the IDEFICS/I.Family cohort

Background

Media use may influence metabolic syndrome (MetS) in children. Yet, longitudinal studies are scarce. This study aims to evaluate the longitudinal association of childhood digital media (DM) use trajectories with MetS and its components.

Methods

Children from Belgium, Cyprus, Estonia, Germany, Hungary, Italy, Spain and Sweden participating in the IDEFICS/I.Family cohort were examined at baseline (W1: 2007/2008) and then followed-up at two examination waves (W2: 2009/2010 and W3: 2013/2014). DM use (hours/day) was calculated as sum of television viewing, computer/game console and internet use. MetS z-score was calculated as sum of age- and sex-specific z-scores of four components: waist circumference, blood pressure, dyslipidemia (mean of triglycerides and HDL-cholesterol⁻¹) and homeostasis model assessment for insulin resistance (HOMA-IR). Unfavorable monitoring levels of MetS and its components were identified (cut-off: ≥ 90^th percentile of each score). Children aged 2–16 years with ≥ 2 observations (W1/W2; W1/W3; W2/W3; W1/W2/W3) were eligible for the analysis. A two-step procedure was conducted: first, individual age-dependent DM trajectories were calculated using linear mixed regressions based on random intercept (hours/day) and linear slopes (hours/day/year) and used as exposure measures in association with MetS at a second step. Trajectories were further dichotomized if children increased their DM duration over time above or below the mean.

Results

10,359 children and adolescents (20,075 total observations, 50.3% females, mean age = 7.9, SD = 2.7) were included. DM exposure increased as children grew older (from 2.2 h/day at 2 years to 4.2 h/day at 16 years). Estonian children showed the steepest DM increase; Spanish children the lowest. The prevalence of MetS at last follow-up was 5.5%. Increasing media use trajectories were positively associated with z-scores of MetS (slope: β = 0.54, 95%CI = 0.20–0.88; intercept: β = 0.07, 95%CI = 0.02–0.13), and its components after adjustment for puberty, diet and other confounders. Children with increasing DM trajectories above mean had a 30% higher risk of developing MetS (slope: OR = 1.30, 95%CI = 1.04–1.62). Boys developed steeper DM use trajectories and higher risk for MetS compared to girls.

Conclusions

Digital media use appears to be a risk factor for the development of MetS in children and adolescents. These results are of utmost importance for pediatricians and the development of health policies to prevent cardio-metabolic disorders later in life.

Trial registration

ISRCTN, ISRCTN62310987. Registered 23 February 2018- retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01186-9.

Education, school type and screen time were associated with overweight and obesity in 2930 adolescents

AIM

This cross-sectional study analysed the influence of socio-economic factors on screen time, overweight and obesity.

METHODS

We asked adolescents aged 10, 14 and 17 from 10 school types in urban and rural regions in Upper Austria to complete questionnaires from December 2012 to February 2013. Their parents were also asked to complete questionnaires.

RESULTS

The questionnaires were completed by 2930 adolescents and 2209 parents. Total weekend screen time was significantly associated with a higher body mass index (BMI) in 10-year-old boys (p < 0.005) and 10-year-old girls (p = 0.002), and there were significant associations between higher BMI and television time and longer weekend video game use in subjects aged 10 and 14. Higher education levels were associated with shorter daily video game use and longer computer use. Males (p < 0.0001) and adolescents from immigrant families (p < 0.0001) reported longer screen times at all ages. Lower parental education and higher parental BMI correlated significantly with longer screen time and BMI in the youngest age group.

CONCLUSION

The greatest weight problems were in younger adolescents, despite shorter screen times, and boys and adolescents from immigrant families reported the longest screen times. Prevention strategies need to start early.

Reducing Recreational Sedentary Screen Time: A Community Guide Systematic Review

CONTEXT

Sedentary time spent with screen media is associated with obesity among children and adults. Obesity has potentially serious health consequences, such as heart disease and diabetes. This Community Guide systematic review examined the effectiveness and economic efficiency of behavioral interventions aimed at reducing recreational (i.e., neither school- nor work-related) sedentary screen time, as measured by screen time, physical activity, diet, and weight-related outcomes.

EVIDENCE ACQUISITION

For this review, an earlier ("original") review (search period, 1966 through July 2007) was combined with updated evidence (search period, April 2007 through June 2013) to assess effectiveness of behavioral interventions aimed at reducing recreational sedentary screen time. Existing Community Guide systematic review methods were used. Analyses were conducted in 2013-2014.

EVIDENCE SYNTHESIS

The review included 49 studies. Two types of behavioral interventions were evaluated that either (1) focus on reducing recreational sedentary screen time only (12 studies); or (2) focus equally on reducing recreational sedentary screen time and improving physical activity or diet (37 studies). Most studies targeted children aged ≤13 years. Children's composite screen time (TV viewing plus other forms of recreational sedentary screen time) decreased 26.4 (interquartile interval= -74.4, -12.0) minutes/day and obesity prevalence decreased 2.3 (interquartile interval= -4.5, -1.2) percentage points versus a comparison group. Improvements in physical activity and diet were reported. Three study arms among adults found composite screen time decreased by 130.2 minutes/day.

CONCLUSIONS

Among children, these interventions demonstrated reduced screen time, increased physical activity, and improved diet- and weight-related outcomes. More research is needed among adolescents and adults.

What are mothers doing while bottle-feeding their infants? Exploring the prevalence of maternal distraction during bottle-feeding interactions

The purpose of this study was to describe the extent to which mothers engage in distracting activities during infant feeding. Mothers reported engaging in other activities during 52% of feedings; television watching was the most prevalent activity reported. Further research on the impact of distraction on feeding outcomes is needed.

Mindless feeding: Is maternal distraction during bottle-feeding associated with overfeeding?

Mindless eating, or eating while distracted by surrounding stimuli, leads to overeating. The present study explored whether "mindless feeding," or maternal distraction during bottle-feeding, is associated with greater infant formula/milk intakes and lower maternal sensitivity to infant cues. Mothers and their ≤24-week-old bottle-feeding infants (N = 28) visited our laboratory for a video-recorded feeding observation. Infant intake was assessed by weighing bottles before and after the feedings. Maternal sensitivity to infant cues was objectively assessed by behavioral coding of video-records using the Nursing Child Assessment Feeding Scale. Maternal distraction was defined as looking away from the infant >75% of the feeding; using a mobile device; conversing with another adult; or sleeping. Twenty-nine percent (n = 8) of mothers were distracted. While differences in intakes for infants of distracted vs. not distracted mothers did not reach significance (p = 0.24), the association between distraction and infant intake was modified by two dimensions of temperament: orienting/regulation capacity (p = 0.03) and surgency/extraversion (p = 0.04). For infants with low orienting/regulation capacity, infants of distracted mothers consumed more (177.1 ± 33.8 ml) than those of not distracted mothers (92.4 ± 13.8 ml). Similar findings were noted for infants with low surgency/extraversion (distracted: 140.6 ± 22.5 ml; not distracted: 78.4 ± 14.3 ml). No association between distraction and intake was seen for infants with high orienting/regulation capacity or surgency/extraversion. A significantly greater proportion of distracted mothers showed low sensitivity to infant cues compared to not distracted mothers (p = 0.04). In sum, mindless feeding may interact with infant characteristics to influence feeding outcomes; further experimental and longitudinal studies are needed.

Bedroom media, sedentary time and screen-time in children: a longitudinal analysis

BACKGROUND

Having electronic media in the bedroom is cross-sectionally associated with greater screen-time in children, but few longitudinal studies exist. The aim of this study was to describe longitudinal patterns of ownership and examine cross-sectional and longitudinal associations of bedroom media with children's sedentary behaviour.

METHODS

Data are from the Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people (SPEEDY) study, collected at 3 time-points: baseline (2007, T0; age 10.3 ± 0.3 years), 1-year (T1y) and 4-year (T4y) follow-up. For each assessment, 1512 (44.9% male), 715 (41.0% male), and 319 (48.3% male) participants provided valid accelerometer data. Outcome variables were accelerometer-assessed sedentary time and self-reported screen-time. The presence of a television or computer in the bedroom was self-reported by participants and a combined bedroom media score calculated as the sum of such items. Cross-sectional and longitudinal associations between bedroom media and each outcome were examined using multi-level linear regression.

RESULTS

Bedroom TV ownership fell from 70.9% at T0 to 42.5% at T4y. Having a TV in the bedroom (beta; 95% CI*100, T0: -1.17; -1.88, -0.46. T1y: -1.68; -2.67, -0.70) and combined bedroom media (T0: -0.76; -1.26, -0.27. T1y: -0.79; -1.51, -0.07) were negatively associated with objectively measured weekly sedentary time at T0 and T1y. Having a computer in the bedroom (beta; 95% CI, T0: 0.15; 0.02, 0.29. T4y: 0.35; 0.10, 0.60) and combined bedroom media (T0: 0.09: 0.01, 0.18. T4y: 0.20; 0.05, 0.34) were positively associated with screen-time at T0 and T4y. Relative to participants without a computer throughout the study, children that had a computer in their bedroom at T0 but not at T4y (beta; 95% CI for change in screen-time: -8.02; -12.75, -3.29) reported smaller increases in screen-time.

CONCLUSIONS

The bedroom media environment changes with age and exhibits a complex relationship with children's sedentary behaviour. Modifying children's bedroom media environment may impact upon screen-time but appears unlikely to influence overall sedentary time.

mHealth approaches to child obesity prevention: successes, unique challenges, and next directions

Childhood obesity continues to be a significant public health issue. mHealth systems offer state-of-the-art approaches to intervention design, delivery, and diffusion of treatment and prevention efforts. Benefits include cost effectiveness, potential for real-time data collection, feedback capability, minimized participant burden, relevance to multiple types of populations, and increased dissemination capability. However, these advantages are coupled with unique challenges. This commentary discusses challenges with using mHealth strategies for child obesity prevention, such as lack of scientific evidence base describing effectiveness of commercially available applications; relatively slower speed of technology development in academic research settings as compared with industry; data security, and patient privacy; potentially adverse consequences of increased sedentary screen time, and decreased focused attention due to technology use. Implications for researchers include development of more nuanced measures of screen time and other technology-related activities, and partnering with industry for developing healthier technologies. Implications for health practitioners include monitoring, assessing, and providing feedback to child obesity program designers about users' data transfer issues, perceived security and privacy, sedentary behavior, focused attention, and maintenance of behavior change. Implications for policy makers include regulation of claims and quality of apps (especially those aimed at children), supporting standardized data encryption and secure open architecture, and resources for research-industry partnerships that improve the look and feel of technology. Partnerships between academia and industry may promote solutions, as discussed in this commentary.

Characteristics of screen media use associated with higher BMI in young adolescents

OBJECTIVES

This study investigates how characteristics of young adolescents' screen media use are associated with their BMI. By examining relationships between BMI and both time spent using each of 3 screen media and level of attention allocated to use, we sought to contribute to the understanding of mechanisms linking media use and obesity.

METHODS

We measured heights and weights of 91 13- to 15-year-olds and calculated their BMIs. Over 1 week, participants completed a weekday and a Saturday 24-hour time-use diary in which they reported the amount of time they spent using TV, computers, and video games. Participants carried handheld computers and responded to 4 to 7 random signals per day by completing onscreen questionnaires reporting activities to which they were paying primary, secondary, and tertiary attention.

RESULTS

Higher proportions of primary attention to TV were positively associated with higher BMI. The difference between 25th and 75th percentiles of attention to TV corresponded to an estimated +2.4 BMI points. Time spent watching television was unrelated to BMI. Neither duration of use nor extent of attention paid to video games or computers was associated with BMI.

CONCLUSIONS

These findings support the notion that attention to TV is a key element of the increased obesity risk associated with TV viewing. Mechanisms may include the influence of TV commercials on preferences for energy-dense, nutritionally questionable foods and/or eating while distracted by TV. Interventions that interrupt these processes may be effective in decreasing obesity among screen media users.