051 - Associations between Parental Social Support and Early Childhood Screen-time in US Children

Publication Number: 51.3650

Elise Warda, New York University Grossman School of Medicine, New York, NY, United States; Suzy Tomopoulos, New York University Grossman School of Medicine, New York, NY, United States; Michelle W. Katzow, Cohen Children's Medical Center, Northwell Health, New Hyde Park, NY, United States; Nikita Nagpal, New York University Grossman School of Medicine, New York, NY, United States; Carol Duh-Leong, Hassenfeld Children's Hospital at NYU Langone, New York, NY, United States

Background: Early childhood studies in families with low-income have shown that social support, the perception of care or assistance from others, empowers parents with the self-efficacy to manage and monitor their children’s screen-time. Less is known as to which sources of support are associated with screen-time or influence these associations with income. Guidelines emphasize parental screen monitoring, so it is increasingly important to consider the factors that may predict screen co-engagement.

Objective: To examine if individual, family, and neighborhood levels of parental social support are associated with optimal screentime in early childhood.

Design/Methods: We performed a cross-sectional analysis of children aged 0-5 years from the 2022 National Survey of Children’s Health. Based on 2016 American Academy of Pediatrics recommendations for early childhood, we defined optimal screentime as one hour or less daily. Our predictors included three types of parental social support: 1) individual emotional support (day-to-day parenting support), 2) family support (a composite measure of family cohesion), and 3) neighborhood support (a composite measure of community support). We assessed cumulative support by summing the presence of each of type of social support, creating a score from 0 to 3. We performed weighted bivariate and multivariable analyses to examine associations between types of support and screentime, adjusting for race/ethnicity, maternal age, parental education, and income. We then stratified analyses by income, testing for interaction.

Results: We included 19,741 children (51% male; 65% White, 15% Hispanic, 5% Black). 5,894 (29.86%) had optimal screentime. Table 1 shows optimal screentime was associated with individual (OR 1.34, p=0.003), family (OR 1.37, p< 0.001), neighborhood (OR 1.16, p=0.02), and cumulative support (OR 2.24, p=0.006). Individual support was associated with optimal screentime in high-income families (OR 2.12, p< 0.001, Table 1). In low-income families, family (OR 1.39, p=0.014) and neighborhood support (OR 1.45, p< 0.001) were associated with optimal screentime. The association between cumulative support and optimal screentime was driven by low-income families (OR 2.46, p=0.002; Table 1).

Conclusion(s): All sources of parental social support are associated with optimal screentime, but associations varied by income status. Strengthening social support could facilitate healthy screen use, particularly in families with low-income. Further studies should investigate mechanisms of how each source of support may protect from excessive screentime to inform future interventions.

Logistic regression models for study predictors and low-screen time outcome (defined 1hr or less) with stratification by income level (low income <400% poverty line; high income >=400%).
PAS tables screentime_v4.pdfLogistic regression analyses modeled the association of various types of social support: individual, neighborhood, family, or cumulative support with the outcome of low screen-time separately in low-income and high-income families. We assessed moderation using an interaction term, which was calculated by multiplying the dichotomized income level (high or low) with each type of support. Models were either unadjusted or adjusted for maternal age, race/ethnicity, and parental education level. Models were weighted to represent the full US population (weighted n=21,470,296).

Logistic regression models for study predictors and low-screen time outcome (defined 1hr or less) with stratification by income level (low income <400% poverty line; high income >=400%).
PAS tables screentime_v4.pdfLogistic regression analyses modeled the association of various types of social support: individual, neighborhood, family, or cumulative support with the outcome of low screen-time separately in low-income and high-income families. We assessed moderation using an interaction term, which was calculated by multiplying the dichotomized income level (high or low) with each type of support. Models were either unadjusted or adjusted for maternal age, race/ethnicity, and parental education level. Models were weighted to represent the full US population (weighted n=21,470,296).