Background: Compliance with screen time guidelines among children worldwide remains low, and there is insufficient evidence on the current prevalence in China. This study aimed to investigate the prevalence of compliance with screen time guidelines among children under 3 years old in Fujian Province, East China, identify risk factors and their independent effects, and develop a risk discrimination model for targeted interventions.
Methods: A cross-sectional survey was conducted among low-income families recruited from welfare programs at 96 sites in both urban and rural areas of Fujian Province, China. Face-to-face interviews gathered sociodemographic data, lifestyle information, attitudes towards screen exposure, and details on screen media device ownership. A multivariable logistic regression model was employed to identify independent risk factors for compliance with screen time guidelines, while the area under the receiver operating characteristic curve (AUC) was used to evaluate the model's discrimination ability.
Results: A total of 4,707 children participated in the survey. The rates of compliance with screen time guidelines were 56.8% for children under 1 year old, 18.8% for those between 1 and 2 years old, and 81.9% for those between 2 and 3 years old. The multivariable regression analysis identified negative attitudes towards screen exposure, co-viewing and engagement, as well as single child, as significant positive independent factors for compliance with the guidelines. The risk discrimination model demonstrated good performance, with an AUC of 0.845 and 0.812 in the two younger age groups, but showed medium discrimination with an AUC of 0.691 for children between 2 and 3 years old.
Conclusions: Compliance with screen time guidelines among young children in Fujian Province, East China, is generally adequate, but notably low among children between 1 and 2 years old. Targeted interventions are needed to improve compliance, particularly for this age group.
Keywords: Children under 3 years; Risk discrimination model; Risk factors; Screen exposure; Targeted intervention.
© 2024. The Author(s).