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

Associations between media parenting practices and early adolescent screen use

BACKGROUND

To assess the prevalence of various media parenting practices and identify their associations with early adolescent screen time and problematic social media, video game, and mobile phone use.

METHODS

Cross-sectional data from Year 3 of the Adolescent Brain Cognitive Development (ABCD) Study (2019-2022) that included 10,048 adolescents (12-13 years, 48.3% female, 45.6% racial/ethnic minorities) in the US were analyzed using multiple linear regression analyses adjusting for potential confounders.

RESULTS

Parent screen use, family mealtime screen use, and bedroom screen use were associated with greater adolescent screen time and problematic social media, video game, and mobile phone use. Parental use of screens to control behavior (e.g., as a reward or punishment) was associated with higher screen time and greater problematic video game use. Parental monitoring of screens was associated with lower screen time and less problematic social media and mobile phone use. Parental limit setting of screens was associated with lower screen time and less problematic social media, video game, and mobile phone use.

DISCUSSION

Parent screen use, mealtime screen use, and bedroom screen use were associated with higher adolescent problematic screen use and could be limited in a family media use plan. Parental monitoring and limiting of screen time are associated with less problematic screen use.

IMPACT STATEMENT

Although the American Academy of Pediatrics provides guidance for screen use for children 5-18 years, there is a paucity of evidence-based guidance for media parenting practices, specifically for early adolescents. In a diverse sample of 10,048 early adolescents across the US, we found cross-sectional associations between parent, mealtime, and bedroom screen use and higher adolescent problematic screen use. Parental monitoring and limiting of adolescent screen time were cross-sectionally associated with less problematic screen use in our analytic sample and may be incorporated into a family media use plan.

Association of physical activity and screen time with cardiovascular disease risk in the Adolescent Brain Cognitive Development Study

BACKGROUND

According to the Physical Activity Guidelines Advisory Committee Scientific Report, limited evidence is available on sedentary behaviors (screen time) and their joint associations with physical activity (steps) for cardiovascular health in adolescence. The objective of this study was to identify joint associations of screen time and physical activity categories with cardiovascular disease (CVD) risk factors (blood pressure, hemoglobin A1c, cholesterol) in adolescence.

METHODS

This study analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, comprising a diverse sample of 4,718 U.S. adolescents aged 10-15 years between 2018 and 2021. Steps were measured by a Fitbit wearable device and levels were categorized as low (1,000-6,000), medium (> 6,000-12,000), and high (> 12,000) averaged daily step counts. Self-reported recreational screen time hours per day were classified as low (0-4), medium (> 4-8), and high (> 8) hours per day. CVD risk factors including blood pressure, hemoglobin A1c, and cholesterol (total and HDL) were measured.

RESULTS

The analytical sample averaged 6.6 h of screen time per day and 9,722 steps per day. In models including both screen time and steps, the high screen time category was associated with a 4.27 higher diastolic blood pressure percentile (95% CI 1.83-6.73) and lower HDL cholesterol (B= -2.85, 95% CI -4.77 to -0.94 mg/dL) compared to the low screen time category. Medium (B = 3.68, 95% CI 1.24-6.11) and low (B = 7.64, 95% CI 4.07-11.20) step categories were associated with higher diastolic blood pressure percentile compared to the high step category. The medium step category was associated with lower HDL cholesterol (B= -1.99, 95% CI -3.80 to -0.19 mg/dL) compared to the high step category. Findings were similar when screen time and step counts were analyzed as continuous variables; higher continuous step count was additionally associated with lower total cholesterol (mg/dL).

CONCLUSIONS

Combinations of low screen time and high steps were generally associated with favorable cardiovascular health markers including lower diastolic blood pressure and higher HDL cholesterol, which can inform future adolescent health guidelines.

Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth

BACKGROUND

Youth use different forms of screen time (e.g., streaming, gaming) that may be related to body mass index (BMI). Screen time is non-independent from other behaviors, including physical activity and sleep duration. Statistical approaches such as isotemporal substitution or compositional data analysis (CoDA) can model associations between these non-independent behaviors and health outcomes. Few studies have examined different types of screen time, physical activity, and sleep duration simultaneously in relation to BMI.

METHODS

Data were baseline (2017-2018) and one-year follow-up (2018-2019) from the Adolescent Brain Cognitive Development Study, a multi-site study of a nationally representative sample of U.S. youth (N = 10,544, mean [SE] baseline age = 9.9 [0.03] years, 48.9% female, 45.4% non-White). Participants reported daily minutes of screen time (streaming, gaming, socializing), physical activity, and sleep. Sex-stratified models estimated the association between baseline behaviors and follow-up BMI z-score, controlling for demographic characteristics, internalizing symptoms, and BMI z-score at baseline.

RESULTS

In females, isotemporal substitution models estimated that replacing 30 min of socializing (β [95% CI] = -0.03 [-0.05, -0.002]), streaming (-0.03 [-0.05, -0.01]), or gaming (-0.03 [-0.06, -0.01]) with 30 min of physical activity was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing (-0.03 [-0.05, -0.01]), streaming (-0.02 [-0.03, -0.01]), or gaming (-0.02 [-0.03, -0.01]) with 30 min of sleep was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing with 30 min of gaming was associated with a lower follow-up BMI z-score (-0.01 [-0.03, -0.0001]). CoDA estimated that in males, a greater proportion of time spent in baseline socializing, relative to the remaining behaviors, was associated with a higher follow-up BMI z-score (0.05 [0.02, 0.08]). In females, no associations between screen time and BMI were observed using CoDA.

CONCLUSIONS

One-year longitudinal associations between screen time and BMI may depend on form of screen time, what behavior it replaces (physical activity or sleep), and participant sex. The alternative statistical approaches yielded somewhat different results. Experimental manipulation of screen time and investigation of biopsychosocial mechanisms underlying the observed sex differences will allow for causal inference and can inform interventions.

Differential associations between television viewing, computer use, and adiposity by age, gender, and race/ethnicity in United States youth: A cross-sectional NHANES analysis

BACKGROUND

Time spent on screens and adiposity change rapidly from childhood to adolescence, with differences by gender and race/ethnicity.

OBJECTIVE

Apply time-varying effect models (TVEMs) to a nationally representative sample of youth to identify the age ranges when the cross-sectional associations between television viewing, computer use, and adiposity are significant.

METHODS

Data from 8 to 15-year-olds (n = 3593) from the National Health and Nutrition Examination Survey (2011-2018) were extracted. TVEMs estimated the associations between television viewing, computer use, and fat mass index as dynamic functions of the participants' age, stratified by gender and race/ethnicity.

RESULTS

TVEMs revealed age-specific statistically significant associations that differed by gender and race/ethnicity. Notably, computer use was related to higher adiposity in non-Hispanic White females aged 9.3-11.4 years (slope β-range: 0.1-0.2) and in non-Hispanic Black females older than 14.8 years (β-range: 0.1-0.5). In males, these age windows were 13.5-15.0 years (non-Hispanic White, β-range: 0.1-0.2), 11.4-13.0 years (non-Hispanic Black, β-range: 0.1-0.14), and older than 13.0 years (Hispanic, β-range: 0.1-0.4).

CONCLUSIONS

More research during the specific age ranges in the demographic subgroups identified here could increase our understanding of tailored interventions in youth.

Screen use while eating is associated with lower intuitive eating and higher disordered eating in Chinese adult men and women

OBJECTIVE

We aimed to explore the potential associations between screen use while eating and intuitive eating and disordered (thinness-oriented and muscularity-oriented) eating behaviors.

METHODS

Analyses included 600 Chinese adults (50% women; Mage  = 30.67, SD = 8.08) recruited online. The use of four major screen devices was captured, including cell phones, tablets, computers, and TVs. Three types of eating behaviors were examined, namely intuitive eating, thinness-oriented disordered eating, and muscularity-oriented disordered eating. Pearson correlation and hierarchical regression analyses were conducted separately for men and women to examine the sex-specific associations between screen use while eating and intuitive eating, thinness-oriented disordered eating, and muscularity-oriented disordered eating.

RESULTS

In both men and women, more screen use while eating was significantly associated with lower intuitive eating, higher thinness-oriented disordered eating, and higher muscularity-oriented disordered eating, above and beyond total screen time and social media use.

DISCUSSION

We found preliminary evidence for the significant links between screen use while eating and intuitive eating and disordered eating. Given the global increases in screen use, continued research is warranted to further explore the role of screen use while eating in the development and maintenance of intuitive eating and disordered eating.

PUBLIC SIGNIFICANCE

Much remains unknown regarding screen use while eating and eating behaviors. We found that in both Chinese men and women, more screen use while eating was significantly and uniquely associated with lower intuitive eating, higher thinness-oriented disordered eating, and higher muscularity-oriented disordered eating. Findings highlight the importance of incorporating screen use while eating in future research on intuitive eating and disordered eating.

Associations between adverse childhood experiences and early adolescent problematic screen use in the United States

BACKGROUND

Problematic screen use, defined as an inability to control use despite private, social, and professional life consequences, is increasingly common among adolescents and can have significant mental and physical health consequences. Adverse Childhood Experiences (ACEs) are important risk factors in the development of addictive behaviors and may play an important role in the development of problematic screen use.

METHODS

Prospective data from the Adolescent Brain Cognitive Development Study (Baseline and Year 2; 2018-2020; N = 9,673, participants who did not use screens were excluded) were analyzed in 2023. Generalized logistic mixed effects models were used to determine associations with ACEs and the presence of problematic use among adolescents who used screens based on cutoff scores. Secondary analyses used generalized linear mixed effects models to determine associations between ACEs and adolescent-reported problematic use scores of video games (Video Game Addiction Questionnaire), social media (Social Media Addiction Questionnaire), and mobile phones (Mobile Phone Involvement Questionnaire). Analyses were adjusted for potential confounders including age, sex, race/ethnicity, highest parent education, household income, adolescent anxiety, depression, and attention-deficit symptoms, study site, and participants who were twins.

RESULTS

The 9,673 screen-using adolescents ages 11-12 years old (mean age 12.0) were racially and ethnically diverse (52.9% White, 17.4% Latino/Hispanic, 19.4% Black, 5.8% Asian, 3.7% Native American, 0.9% Other). Problematic screen use rates among adolescents were identified to be 7.0% (video game), 3.5% (social media), and 21.8% (mobile phone). ACEs were associated with higher problematic video game and mobile phone use in both unadjusted and adjusted models, though problematic social media use was associated with mobile screen use in the unadjusted model only. Adolescents exposed to 4 or more ACEs experienced 3.1 times higher odds of reported problematic video game use and 1.6 times higher odds of problematic mobile phone use compared to peers with no ACEs.

CONCLUSIONS

Given the significant associations between adolescent ACE exposure and rates of problematic video and mobile phone screen use among adolescents who use screens, public health programming for trauma-exposed youth should explore video game, social media, and mobile phone use among this population and implement interventions focused on supporting healthy digital habits.

Screen Time from Adolescence to Adulthood and Cardiometabolic Disease: a Prospective Cohort Study

BACKGROUND

Previous studies have analyzed the relationship between screen time and cardiometabolic disease risk factors among adolescents, but few have examined the longitudinal effects of screen time on cardiometabolic health into adulthood using nationally representative data.

OBJECTIVE

To determine prospective associations between screen time and later cardiometabolic disease over a 24-year period using a nationally representative adolescent cohort.

DESIGN

Longitudinal prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) collected from 1994 to 2018.

PARTICIPANTS

Adolescents aged 11-18 years old at baseline (1994-1995) followed for 24 years.

MAIN MEASURES

Predictors: screen time (five repeated measures of self-reported television and video watching from adolescence to adulthood).

OUTCOMES

Five repeated measures of body mass index (BMI); two repeated measures of waist circumference, hypertension, hyperlipidemia, and diabetes collected at 15- and 24-year follow-up exams.

KEY RESULTS

For the 7105 adolescents in the sample (49.7% female, 35.0% non-white), the baseline adolescent average screen time per day was 2.86 ± 0.08 hours per day, which generally declined through 24-year follow-up. Average BMI at baseline was 22.57 ± 0.13 kg/m2, which increased to 30.27 ± 0.18 kg/m2 through follow-up. By 24-year follow-up, 43.4% of participants had obesity, 8.4% had diabetes, 31.8% had hypertension, and 14.9% had hyperlipidemia. In mixed-effects generalized linear models, each additional hour of screen time per day was associated with 0.06 (95% CI 0.04-0.09) within-person increase in BMI. Each additional hour of screen time per day was associated with higher within-person odds of high waist circumference (AOR 1.17, 95% CI 1.09-1.26), obesity (AOR 1.09, 95% CI 1.03-1.15), and diabetes (AOR 1.17, 95% CI 1.07-1.28). Screen time was not significantly associated with hypertension or hyperlipidemia.

CONCLUSIONS

In this prospective cohort study, higher screen time in adolescence was associated with higher odds of select indicators of cardiometabolic disease in adulthood.

Excess BMI in early adolescence adversely impacts maturating functional circuits supporting high-level cognition and their structural correlates

BACKGROUND/OBJECTIVES

Adverse effects of excess BMI (affecting 1 in 5 children in the US) on brain circuits during neurodevelopmentally vulnerable periods are incompletely understood. This study investigated BMI-related alterations in maturating functional networks and their underlying brain structures, and high-level cognition in early adolescence.

SUBJECTS/METHODS

Cross-sectional resting-state fMRI, structural sMRI, neurocognitive task scores, and BMI from 4922 youth [median (IQR) age = 120.0 (13.0) months, 2572 females (52.25%)] from the Adolescent Brain Cognitive Development (ABCD) cohort were analyzed. Comprehensive topological and morphometric network properties were estimated from fMRI and sMRI, respectively. Cross-validated linear regression models assessed correlations with BMI. Results were reproduced across multiple fMRI datasets.

RESULTS

Almost 30% of youth had excess BMI, including 736 (15.0%) with overweight and 672 (13.7%) with obesity, and statistically more Black and Hispanic compared to white, Asian and non-Hispanic youth (p < 0.01). Those with obesity or overweight were less physically active, slept less than recommended, snored more frequently, and spent more time using an electronic device (p < 0.01). They also had lower topological efficiency, resilience, connectivity, connectedness and clustering in Default-Mode, dorsal attention, salience, control, limbic, and reward networks (p ≤ 0.04, Cohen's d: 0.07-0.39). Lower cortico-thalamic efficiency and connectivity were estimated only in youth with obesity (p < 0.01, Cohen's d: 0.09-0.19). Both groups had lower cortical thickness, volume and white matter intensity in these networks' constituent structures, particularly anterior cingulate, entorhinal, prefrontal, and lateral occipital cortices (p < 0.01, Cohen's d: 0.12-0.30), which also mediated inverse relationships between BMI and regional functional topologies. Youth with obesity or overweight had lower scores in a task measuring fluid reasoning - a core aspect of cognitive function, which were partially correlated with topological changes (p ≤ 0.04).

CONCLUSIONS

Excess BMI in early adolescence may be associated with profound aberrant topological alterations in maturating functional circuits and underdeveloped brain structures that adversely impact core aspects of cognitive function.

Contemporary screen use and symptoms of muscle dysmorphia among a national sample of Canadian adolescents and young adults

PURPOSE

Screen time has been previously linked to body dissatisfaction and eating disorder behaviors. However, less is known about whether use of common forms of screen technology is associated with symptoms of muscle dysmorphia (MD), which was the aim of this study.

METHODS

Data from the Canadian Study of Adolescent Health Behaviors (N = 2538) were analyzed. Associations between hours of use of six contemporary forms of recreational screen time, as well as total screen time, and symptoms of MD were determined using multiple linear regression models, stratified by gender, and adjusting for potential confounders.

RESULTS

Among both men and women, greater total screen time and texting were associated with greater symptoms of MD; however, differences emerged across the screen time modalities by gender. Among women, video chatting was most strongly associated with symptoms of MD, while social media use was most strongly associated with symptoms of MD among men.

CONCLUSION

Findings add to the growing literature documenting the potentially harmful correlates of screen time by including MD symptomatology. Findings have important implications for health care, public health, and policymaking professionals.

LEVEL OF EVIDENCE

Level V, cross-sectional descriptive study.

Contemporary screen time modalities and disruptive behavior disorders in children: a prospective cohort study

BACKGROUND

Cross-sectional studies have demonstrated associations between screen time and disruptive behavior disorders (conduct disorder and oppositional defiant disorder); however, prospective associations remain unknown. This study's objective was to determine the prospective associations of contemporary screen time modalities with conduct and oppositional defiant disorder in a national cohort of 9-11-year-old children.

METHODS

We analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,875). Modified Poisson regression analyses were conducted to estimate the associations between baseline child-reported screen time (total and by modality) and parent-reported conduct or oppositional defiant disorder based on the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) at 1-year follow-up, adjusting for potential confounders.

RESULTS

Participants reported an average of 4 hr of total screen time per day at baseline. Each hour of total screen time per day was prospectively associated with a 7% higher prevalence of conduct disorder (95% CI 1.03-1.11) and a 5% higher prevalence of oppositional defiant disorder (95% CI 1.03-1.08) at 1-year follow-up. Each hour of social media per day was associated with a 62% higher prevalence of conduct disorder (95% CI 1.39-1.87). Each hour of video chat (prevalence ratio [PR] 1.21, 95% CI 1.06-1.37), texting (PR 1.19, 95% CI 1.07-1.33), television/movies (PR 1.17, 95% CI 1.10-1.25), and video games (PR 1.14, 95% CI 1.07-1.21) per day was associated with a higher prevalence of the oppositional defiant disorder. When examining thresholds, exposure to >4 hr of total screen time per day was associated with a higher prevalence of conduct disorder (69%) and oppositional defiant disorder (46%).

CONCLUSIONS

Higher screen time was prospectively associated with a higher prevalence of new-onset disruptive behavior disorders. The strongest association was between social media and conduct disorder, indicating that future research and interventions may focus on social media platforms to prevent conduct disorder.

Associations Between Adverse Childhood Experiences, Adolescent Screen Time and Physical Activity During the COVID-19 Pandemic

OBJECTIVE

To determine the associations between Adverse Childhood Experiences (ACEs), adolescent screen time, and physical activity during the early COVID-19 pandemic.

METHODS

Data (2016-2020) from the Adolescent Brain Cognitive Development (ABCD) study were analyzed. Linear regression analyses estimated associations between ACE score and screen time and physical activity in May 2020, adjusting for potential confounders.

RESULTS

Of the 6749 adolescent respondents primarily aged 12-13, 81.6% reported a history of one ACE or more. In adjusted models, a higher ACE score was significantly associated with greater hours per day of screen time, with youth with ≥4 ACEs associated with 2.3 more hours of screen time per day compared to youth with 0 ACEs. In addition, the adjusted models found that a higher ACE score was associated with lower physical activity; youth with ≥4 ACEs averaged 0.8 fewer hours per week of physical activity and 0.5 fewer days per week of 60 minutes of physical activity compared to youth with 0 ACEs. Gender and race were also significantly associated with changes in screen time and physical activity.

CONCLUSIONS

ACEs are associated with higher adolescent sedentary behaviors, particularly greater screen time, during the early COVID-19 pandemic (May 2020). Clinicians caring for youth exposed to trauma in the postpandemic environment should explore screen time and physical activity behaviors.

Raising the Child-Do Screen Media Help or Hinder? The Quality over Quantity Hypothesis

Screen media are ubiquitous in human life across all age, cultural and socioeconomic groups. The ceaseless and dynamic growth of technological possibilities has given rise to questions regarding their effect on the well-being of children. Research in this area largely consists of cross-sectional studies; experimental and randomized studies are rare, which makes drawing causative conclusions difficult. However, the prevailing approach towards the use of screen media by children has focused on time limitations. The emerging evidence supports a more nuanced perspective. It appears that the older the child, the more important how the screen media are used becomes. Concentrating on the quality of the screen, time has become increasingly relevant in the recent COVID-19 pandemic, which necessitated a transfer of educational and social functioning from real-life to the digital world. With this review, we aimed at gathering current knowledge on the correlations of different screen media use and development outcomes, as well as providing an overview of potential benefits that new technologies may provide to the pediatric population. To summarize, if one cannot evade screen time in children, how can we use it for children's maximum advantage?

Parent-Adolescent Discrepancies in Adolescent Recreational Screen Time Reporting During the Coronavirus Disease 2019 Pandemic

OBJECTIVE

To describe the relationship between parent and adolescent reports of adolescent recreational screen time and to determine sociodemographic predictors of recreational screen time reporting differences during the coronavirus disease 2019 pandemic.

METHODS

We analyzed data from the Adolescent Brain Cognitive Development Study (N = 5335, ages 10-14) a national prospective cohort study in the United States collected in May 2020. We compared parent-reported, adolescent-reported, and a parent-adolescent differences in recreational screen time hours per day across 5 screen categories.

RESULTS

Adolescents' total recreational screen time per day was reported as 4.46 hours by parents and 3.87 hours by adolescents. Parents reported higher levels of their child's texting, video chatting, and total recreational screen time, while adolescents reported higher multiplayer gaming and social media use. Larger discrepancies in total recreational screen time were found in older, Black, and Latino/Hispanic adolescents. Larger discrepancies in total recreational screen time were also found among unmarried/unpartnered parents.

CONCLUSIONS

Given discrepancies in parent-adolescent recreational screen time reporting during the pandemic, a period of high screen use, pediatricians should encourage family discussions about adolescent media use through the development of a Family Media Use Plan. The digital media industry could provide more opportunities for parental monitoring of recreational screen time within product designs.

Digital technology use and muscle-building behaviors in young adults

OBJECTIVE

Digital technology use and muscle-building behaviors reflect a wide range of behaviors with associated health risks. However, links between digital technology use and muscle-building behaviors remain unknown and this study aimed to address this gap.

METHOD

Data were collected from a diverse sample of 1,483 young adults (mean age 22.2 ± 2.0 years) participating in the population-based Eating and Activity over Time 2018 study. Gender-stratified-modified Poisson regression models were used to determine cross-sectional associations between three types of digital technology use (screen time, social media, weight-related self-monitoring apps) and five types of muscle-building behaviors (changing eating, exercise, protein powders/shakes, pre-workout drinks, steroids/growth hormone/creatine/amino acids) in young adulthood, adjusted for sociodemographic characteristics and body mass index.

RESULTS

Screen time and social media were either not found to be associated with muscle-building behaviors or in a few instances, associated with less use of these behaviors (e.g., screen time and pre-workout drinks in men). In contrast, the use of weight-related self-monitoring apps was positively associated with all muscle-building behaviors, including steroids/growth hormone/creatine/amino acids in men (prevalence ratio [PR] = 1.83; 95% confidence interval [CI]: 1.13-2.97) and women (PR = 4.43; 95% CI: 1.68-11.68).

DISCUSSION

While most recreational screen time may represent sedentary behaviors not related to muscle-building behaviors, weight-related self-monitoring apps are highly associated with more muscle-building behaviors and could be a future target for interventions to discourage the use of steroids and other harmful muscle-building substances.

Social epidemiology of early adolescent problematic screen use in the United States

OBJECTIVE

To determine sociodemographic correlates of problematic screen use (social media, video games, mobile phones) among a racially/ethnically and socioeconomically diverse population-based sample of 10-14-year-old early adolescents.

STUDY DESIGN

We analyzed cross-sectional data from the Adolescent Brain Cognitive Development Study (Year 2, 2018-2020; N = 8753). Multiple linear regression analyses were used to estimate associations between sociodemographic factors (age, sex, race/ethnicity, primary language, household income, parental education) and adolescent-reported problematic video game (Video Game Addiction Questionnaire), social media (Social Media Addiction Questionnaire), and mobile phone use (Mobile Phone Involvement Questionnaire).

RESULTS

Boys reported higher problematic video game use while girls reported higher problematic social media and mobile phone use. Native American, black, and Latinx adolescents reported higher scores across all problematic screen measures compared to non-Latinx white adolescents. Having unmarried/unpartnered parents was associated with higher problematic social media use. Although higher household income was generally protective against problematic video game use, these associations were weaker for black than white adolescents (p for interaction <0.05).

CONCLUSIONS

Given the sociodemographic differences in problematic screen use, digital literacy education strategies can focus on at-risk populations, encourage targeted counseling by pediatricians, and adapt family media use plans for diverse backgrounds.

IMPACT

While sociodemographic differences in screen time are documented, we examined sociodemographic differences in problematic screen use in a large, diverse sample of early adolescents in the US. Boys reported higher problematic video game use while girls reported higher problematic social media and mobile phone use. Native American, black, and Latinx adolescents reported higher scores across all problematic screen measures compared to non-Latinx white adolescents. Although higher household income was generally protective against problematic video game use, these associations were weaker for black than white adolescents. Beyond time spent on screens, pediatricians, parents, and educators should be aware of sociodemographic differences in problematic screen use.

Sociodemographic Correlates of Contemporary Screen Time Use among 9- and 10-Year-Old Children

OBJECTIVE

To determine sociodemographic correlates of contemporary screen time use among a diverse population-based sample of 9- and 10-year-old children.

STUDY DESIGN

In 2021, we analyzed cross-sectional baseline (2016-2018) data from the Adolescent Brain Cognitive Development study (n = 10 755). Multiple linear regression analyses were conducted to estimate associations between sociodemographic factors (sex, race/ethnicity, country of birth, household income, parental education) and 6 contemporary forms of screen time (television, videos [eg, YouTube], video games, social networking, texting, and video chat).

RESULTS

On average, children reported 3.99 hours of screen time per day across 6 modalities, with the most time spent watching/streaming television shows/movies (1.31 hours), playing video games (1.06 hours), and watching/streaming videos (1.05 hours). On average, Black children reported 1.58 more hours of screen time per day and Asian children reported 0.35 less hours of screen time per day compared with White children (mean 3.46 hours per day), and these trends persisted across most modalities. Boys reported higher overall screen time (0.75 hours more) than girls, which was primarily attributed to video games and videos. Girls reported more time texting, social networking, and video chatting than boys. Higher income was associated with lower screen time usage across all modalities except video chat. However, in high-income households, Latinx children reported 0.65 more hours of screen time per day than White children.

CONCLUSIONS

Given the sociodemographic differences in child screen use, guideline implementation strategies can focus on key populations, encourage targeted counseling by pediatricians, and adapt Family Media Use Plans for diverse backgrounds.