Association of Trajectory and Covariates of Children’s Screen Media Time

Trinh, Mai-Han; Sundaram, Rajeshwari; Robinson, Sonia L.; Lin, Tzu-Chun; Bell, Erin M.; Ghassabian, Akhgar; Yeung, Edwina

doi:10.1001/jamapediatrics.2019.4488

Cited by 57 publications

(50 citation statements)

References 51 publications

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“…These family stressors may also contribute to OWOB among children on Guam. With respect to OWOB prevention guidance, the study found evidence supporting previous studies' findings that traditional or low acculturation to be protective against obesity [39,59,60]. Healthy cultural behaviors, both unique to and shared across ethnic group(s), should be incorporated in future obesity interventions by highlighting healthy cultural values, practices and traditional foods.…”

Section: Discussionsupporting

confidence: 72%

“…The proportion of children exceeding screen-time recommendation in this study (83%) was comparable to the 87% reported among a prospective birth cohort of children born in New York led by researchers from the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development [60]; however, the birth cohort included children below two years of age, which is an age group not represented in the Guam study. Additionally, while screen-time increased with preschool age in the birth cohort, the total hours decreased to below the recommended two hours by 7-8 years old possibly due to school activities [60].…”

Section: Discussionsupporting

confidence: 71%

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Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam

et al. 2020

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This study is part of the Children’s Healthy Living program in U.S. Affiliated Pacific region. The objectives were to estimate overweight and obesity (OWOB) prevalence and identify possible related risk factors among ethnic groups in Guam. In 2013, 865 children (2–8 years) were recruited via community-based sampling from select communities in Guam. Children’s demographic and health behavior information; dietary intake; and anthropometric measurements were collected. Logistic regression, odds ratio, t-tests, and chi-square tests were used to determine differences and assess covariates of OWOB. The results indicate that 58% of children were living below the poverty level, 80% were receiving food assistance, and 51% experienced food insecurity. The majority of children surveyed did not meet recommendations for: sleep duration (59.6%), sedentary screen-time (83.11%), or fruit (58.7%) and vegetable (99.1%) intake, and consumed sugar sweetened beverages (SSB) (73.7%). OWOB affected 27.4% of children. Children affected by OWOB in this study were statistically more likely (p = 0.042) to suffer from sleep disturbances (p = 0.042) and consume marginally higher amounts (p value = 0.07) of SSB compared to children with healthy weight. Among Other Micronesians, children from families who considered themselves ‘integrated’ into the culture were 2.05 (CI 0.81–5.20) times more likely to be affected by OWOB. In conclusion, the OWOB prevalence among 2–8-year-olds in Guam was 27.4%; and compared with healthy weight children, children with OWOB were more likely to have educated caregivers and consume more SSBs. Results provide a basis for health promotion and obesity prevention guidance for children in Guam.

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Section: Discussionsupporting

confidence: 72%

Section: Discussionsupporting

confidence: 71%

Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam

et al. 2020

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“…In previous studies, conflicting results were reported about the relationship between maternal education, paternal education, gender of the child, and screen time. 26,27 Similar to Trinh and his colleagues, 28 the present study demonstrated an inverse relationship between parental education level and screen time of children and also found that male gender was associated with increased screen time. In addition, Maatta et al, 29 showed that parents with high education have lower descriptive norms, use fewer screens in front of children, and place greater importance on limiting children's screen time compared to parents with low education.…”

Section: Di̇scussi̇onsupporting

confidence: 88%

“…Findings related to maternal occupation, presence of siblings and the child's screen time differed in past studies. 28 Hinkley et al, 30 identified no association between maternal employment, the presence of siblings, and screen time for preschool children. On the contrary, Wu et al, 31 reported that screening devices were used more frequently in children whose mothers were housewives compared to working mothers.…”

Section: Di̇scussi̇onmentioning

confidence: 99%

Excessive screen time is associated with emotional lability in preschool children

et al. 2021

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Introduction. Previous studies have found that excessive screen time or early screen exposure is associated with poor attention, lack of behavioral control, delayed language and deficit in executive functions. The aim of this study was to investigate the relationship between screen time and emotion regulation skills, which is one of the important life components affecting the social relations of children aged 2 to 5 years. Population and methods. This cross-sectional descriptive study was carried out in a university hospital between January 1, 2018 and March 1, 2018. Mothers of healthy children aged 2-5 years with a daily screen time of less than 1 hour or over 4 hours were included in the study. A structured survey and the Emotion Regulation Checklist for parents were applied to the mothers who agreed to participate. Results. Of 240 children participating in the study, 98 (40.8 %) had ≥4 hours of screen time. Caring by mother, age at first screen exposure 12 months and older, not co-viewing with parents were found to be associated with ≥ 4 hours of screen time (p = 0.002, p = 0.002, p = 0.012, respectively). The ratio of participants with highlability/negativity (L/N) score was significantly higher in children with screen time of ≥ 4 hours and not co-viewing with parents (p = 0.004, p = 0.033, respectively). Conclusions. This study investigating the relationship between the emotion regulation skill and screen time revealed that excessive screen time is associated with emotional lability in this early childhood period.

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“…Exploratory subgroup analyses revealed a small but significant effect in reducing BMI in interventions in which a screen time component was present (g = 0.23, 95% CI = 0.10-0.36) versus absent (g = 0.05, 95% CI = -0.02 to 0.12) relative to the control or comparison group [Q B (1) = 11.24, p = <0.001]. This is an important finding given that screen time habits in children younger than the age of three are associated with increased screen use at 8 years of age, 67 and the robustness of research showing that screen time exposure is associated with an increased risk of obesity. 68 This also highlights the critical role of parents in reducing childhood obesity, 69 and the need to identify specific strategies and provide skills-training to support parents of preschoolers who often find it challenging to limit screen time exposure 70 These findings are consistent with the Community Preventive Services Task Force, which found strong evidence supporting the efficacy of interventions addressing screen time reduction to promote healthy weight in children aged 13 and younger.…”

Section: Childhood Obesity September 2020mentioning

confidence: 71%

Childhood Obesity Evidence Base Project: A Systematic Review and Meta-Analysis of a New Taxonomy of Intervention Components to Improve Weight Status in Children 2–5 Years of Age, 2005–2019

et al. 2020

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Objective: To evaluate the efficacy of childhood obesity interventions and conduct a taxonomy of intervention components that are most effective in changing obesity-related health outcomes in children 2-5 years of age. Methods: Comprehensive searches located 51 studies from 18,335 unique records. Eligible studies: (1) assessed children aged 2-5, living in the United States; (2) evaluated an intervention to improve weight status; (3) identified a same-aged comparison group; (4) measured BMI; and (5) were available between January 2005 and August 2019. Coders extracted study, sample, and intervention characteristics. Effect sizes [ESs; and 95% confidence intervals (CIs)] were calculated by using random-effects models. Metaregression was used to determine which intervention components explain variability in ESs. Results: Included were 51 studies evaluating 58 interventions (N = 29,085; mean age = 4 years; 50% girls). Relative to controls, children receiving an intervention had a lower BMI at the end of the intervention (g = 0.10, 95% CI = 0.02-0.18; k = 55) and at the last follow-up (g = 0.17, 95% CI = 0.04-0.30; k = 14; range = 18-143 weeks). Three intervention components moderated efficacy: engage caregivers in praise/encouragement for positive health-related behavior; provide education about the importance of screen time reduction to caregivers; and engage pediatricians/health care providers.

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Association of Trajectory and Covariates of Children’s Screen Media Time

Cited by 57 publications

References 51 publications

Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam

Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam

Excessive screen time is associated with emotional lability in preschool children

Childhood Obesity Evidence Base Project: A Systematic Review and Meta-Analysis of a New Taxonomy of Intervention Components to Improve Weight Status in Children 2–5 Years of Age, 2005–2019

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