A systematic review analyzing 40 articles found that a significant number of the studies reviewed indicated an 11% increased risk (odds ratio [OR], 1.766; 95% confidence interval [CI], 1.104–2.562, P=0.0001) between screen time and increased adiposity, body mass index (BMI), abdominal circumference, and body fat percentage [6]. Another meta-analysis found that screen time exceeding 2 hours/day was positively associated with the risk of overweight and obesity (OR, 1.67; 95% CI, 1.48–1.88, P<0.0001), indicating that the pediatric population exposed to more than 2 hours/day of screen time has a 67% higher risk of developing overweight/obesity compared to those with less exposure [7]. On the other hand, a meta-analysis that included 4 clinical trials showed that reducing TV time was associated with a decrease in BMI of -0.89 kg/m² (95% CI, -1.467 to 0.11; P=0.01), showing a significant association between screen exposure and BMI [2]. According to the evidence found, excessive screen time is associated with a higher risk of overweight and obesity in children and adolescents.

The use of screens in childhood, especially at early ages, has been shown to have a negative impact on physical activity by promoting sedentary routines, defined as time during which children remain seated or engage in no significant physical activity for more than 15 consecutive minutes [8]. These are activities that should elevate the heart rate to 70%–85% of the maximum heart rate and increase the respiratory rate [9,10]. A retrospective cohort study conducted in 2023 in Family Care Homes in the United States with 120 caregivers and 349 children, mostly Hispanic, analyzed the relationship between physical activity practices and screen time using questionnaires and accelerometers to measure the children's activity [11]. The authors found that 68.2% of children who spent more than 6 hours a day in front of screens showed more sedentary behavior, compared to 31.8% of children who spent 5 hours or less in front of electronic devices. A reduction in screen time was observed (β=-8.50; 95% CI, -11.50 to -5.51; P<0.001) while increasing moderate to vigorous physical activity time (β=3.16; 95% CI, 1.00–5.31; P=0.004), indicating the importance of limiting screen time [8].

The literature has observed that as screen time increases with activities such as watching television, using computers, and playing video games for more than 2 hours, there is an increase in depressive symptoms. This was highlighted by a 2020 study conducted by the University of Southern California, which evaluated 709 students from 4th to 6th grade to determine the relationship between depression (assessed using 4 questions selected from the Center for Epidemiologic Studies Depression Scale) and screen time (measured through computer use outside the school context, television, and video games). In particular, it was identified that boys spent more time on screens (M=2.954; standard deviation [SD]=0.75) compared to girls (M=2.171; SD=0.046; P<0.001) [12]. Additionally, a critical threshold was found with more than 4.5 hours of screen time per day, where the risk of depression through depressive symptoms increased (β=0.161, P<0.05) [12]. The most frequent symptom was anhedonia, which is defined as the inability to feel pleasure [13]. It was also noted that higher levels of anhedonia made children more prone to engaging in risky behaviors, as assessed through the use of substances at early ages [12].

Visual disturbances are a common issue in pediatric consultations, and evidence shows a positive association with screen use. One study showed the association of mobile device use with refractive errors in adolescents aged 12 to 16 years. It included 512 individuals, where an application was used to assess myopia development by measuring smartphone use and face-to-screen distance objectively [14]. The study found that continuous use, defined as 20-minute episodes without interruptions, had a significant association with refractive error (β=-0.07; 95% CI, -0.13 to -0.01) and with axial length (β=0.004; 95% CI, 0.001– 0.008) [15]. Another meta-analysis evaluated the relationship between screen time and myopia, finding a significant association with more than 2 hours/day of screen exposure (OR, 2.24; 95% CI, 1.47–3.42) [16]. Regarding cohort studies, it was found that continuous exposure to screens (>1 hr/day) is positively associated with the onset of myopia (OR, 1.07; 95% CI, 1.01–1.13) [16]. Subgroup analyses (by device type, study quality, and geographical region) showed that computer screens have a stronger impact on myopia (OR, 8.19; 95% CI, 4.78–14.04) [16]. Finally, a systematic review and meta-analysis of 268 studies, 59.2% of which showed a positive relationship between screen time and myopia, found that children and adolescents who spend more time on screens (more than 2 hr/day) have a 40% higher risk of developing myopia compared to those who spend less time (OR, 1.40; 95% CI, 1.31–1.50) [17].

The literature on behavioral changes has found evidence linking screen exposure with changes in emotional states, such as irritability, physical complaints, and mood in preadolescents. Irritability is defined as an emotional state in which a child experiences a low threshold for anger in response to negative emotional events [18]. In a multicenter study (CASPIAN-V) conducted on an Iranian population, the association between screen time and physical health complaints was investigated in 14,274 students aged 7–18 years. The results showed an average television use of 1.97 hr/day and computer use of 0.57 hr/day. Each additional hour of television use increased the risk of irritability by 14% (OR, 1.14; 95% CI, 1.07–1.22) [19]. On the other hand, each additional hour of computer use increased the risk of irritability by 12% (OR, 1.12; 95% CI, 1.04–1.19). The study also compared incidence rates in urban and rural populations, where it was found that children living in urban areas reported higher frequencies of symptoms such as irritability and sleep difficulties [19,20]. Additionally, a study by Lin et al. [21] in 2020, which examined 9,987 families with children aged 9–10 years, investigated the relationship between screen time and mood in preadolescents. They found that children who spent more time on screens, especially playing video games or watching restricted movies, showed increased irritability (P<0.001).

One of the aspects that has gained attention regarding screen exposure in children is its impact on sleep patterns. A study conducted on children aged 0–7 years in China found a positive relationship between screen exposure time and sleep duration disturbances. This study showed that more than 1 hr/day of screen time was associated with a higher risk of shorter sleep duration (OR, 1.42; 95% CI, 1.392–1.449; P≤0.009). Similarly, it was observed that children exposed to screens for more than 2 hours/day had a significantly higher risk of reduced sleep duration (OR, 2.283; 95% CI, 2.132–2.445; P<0.001) compared to those exposed for only 1 hr/day. On the other hand, a systematic review found a negative association in 39 of 43 studies between screen time and sleep duration, with more night awakenings, longer sleep latency, and poorer sleep quality in children aged 1 to 5 years. In the same study, a meta-analysis with 7 studies found a negative correlation (r=-0.07; 95% CI, -0.12 to -0.03, I²=0%, P=0.002) in infants (0 to 1 years) and children aged 1 to 2 years (r=-0.13; 95% CI, -0.21 to -0.04; I²=NA, P=0.004). However, in preschool children (3 to 4 years), no relationship was found between screen exposure time and sleep duration (r=0.10; 95% CI, -0.25 to 0.05; I²=93.5%; P=0.203). Overall, an inverse relationship was shown between screen time and sleep quality/duration in children under 5 years [22].

In the search for other outcomes, which were less frequently reported but still supported by analytical evidence, conditions such as attention deficit hyperactivity disorder (ADHD), impulsivity, neurodevelopmental disorders, bullying [23], low levels of physical activity, sleep problems, poor eating habits, headaches, and cancer were included. Meta-analyses have shown reciprocal associations between digital media use and ADHD symptoms, especially with problematic use rather than screen time alone [24]. Children with ADHD symptoms may be more vulnerable to high media use, while digital media may in turn worsen symptoms through effects on sleep, impulsivity, and social functioning [25]. Huber et al. [26] conducted a study with 96 children aged 2 to 3 years to assess the impact of screen use on working memory. The children were exposed to an educational app, an educational TV program, or a cartoon, and their ability to delay gratification was assessed. The results indicated that by controlling screen activity, the likelihood of not touching a candy for 3 minutes increased by 19% on average for each additional month of age (95% CI, 7%–32%; χ²(1)=10.49, P=0.001). Furthermore, when comparing screen conditions, it was observed that the probability of not touching the candy was, on average, 8% higher in the educational app condition compared to the cartoon, controlling for age (95% CI, 1.69–40.92; χ²(1)=6.80, P=0.009). The success percentages for delaying gratification were 84% for the educational app, 63% for the educational TV program, and 61% for the cartoon [26].

Studies regarding genetic predisposition and its association with various outcomes related to screen exposure in children are very limited. However, a relationship between single nucleotide polymorphisms (SNPs) and screen exposure outcomes such as obesity, hypertension, and ADHD was found (Table 2), the table shows the function, location, and variants of the genes. In 2007, an SNP, rs9939609 in the FTO gene (Alphaketoglutarate-dependent dioxygenase), was first described, with its role in obesity and its association with some phenotypes. A cross-sectional study conducted with children and adolescents aged 6 to 17 years in a city in Brazil found an inverse association between screen time and waist circumference (WC) (β=-0.013; CI, -0.023 to -0.004; P=0.005). Furthermore, a significant association was found between screen time and the presence of the rs9939609 polymorphism (allele A) (β=0.011; CI, 0.003 to 0.019; P=0.007) [27]. Additionally, a significant association was found between the AA genotype of the FTO polymorphism and WC in individuals who spent more than 3.8 hr/day on screens. However, no association was found in those who spent between 1 and 3 hr/day in front of screens. It was concluded that lifestyle modulates genetic predisposition to greater WC, acting as a moderating factor in the relationship between the FTO gene polymorphism and WC. It was also observed that an increase in sedentary behavior, especially in children and adolescents, was related to adverse health consequences such as body fat accumulation [27].

Yang et al. [28] conducted a case-control study to evaluate the association between the rs9810888 variant of the CACNA1D gene and blood pressure in 2,030 Chinese children aged 7 to 18 years, as well as its possible interaction with lifestyle factors. The CACNA1D gene encodes the α-1 subunit of voltage-dependent calcium channels expressed in neuroendocrine cells and electrically excitable cells, such as smooth and cardiac muscle. This variant (rs9810888) has been associated with the activation of voltage-dependent channels, leading to membrane hyperpolarization and increased calcium influx. In this study, it was found that children with screen exposure exceeding 2 hours per day and carrying the GG genotype had higher diastolic blood pressure (β=5.49, standard error [SE]=2.18, P=0.012) as well as higher mean arterial pressure (β=4.80, SE=1.70, P=0.017) [28]. In a cohort study with data collected between 2016 and 2019 as part of the Adolescent Brain Cognitive Development Study in the United States, researchers evaluated how genetic factors influence the associations between screen time and attention problems or internalizing behaviors in preadolescents aged 9 to 11 years. A polygenic risk score analysis, capable of indicating whether certain events are due to specific genetic variants, was performed. It was reported that screen time was associated with attention problems (β=0.10 SD; 95% CI, 0.07–0.13 SD) and internalizing problems (β=0.03 SD; 95% CI, 0.003–0.06 SD). Additionally, sensitivity analysis established that approximately 10% of the phenotypic association between exposure and outcome could be attributed to the presence of genetic factors [29]. Meanwhile, Meng et al. [30] conducted a Mendelian randomization study involving 225,534 children (186,843 healthy controls and 38,691 children with ADHD) to confirm the causal relationship between screen time and ADHD, using a set of SNP data previously linked to ADHD. The study found that prolonged mobile phone use (OR, 1.848; 95% CI, 1.336–2.555; P=2.07e-4) and time spent watching television (OR, 2.104; 95% CI, 1.395–3.170; P=3.8e-4) significantly increased the risk of pediatric ADHD, regardless of the presence of specific SNP variants [30]. The polymorphism of the DRD2 gene has been extensively studied in addiction disorders. The variation in this gene at the Taq1A1 locus (rs1800497) has been associated with reduced D2 receptor density in brain regions such as the caudate nucleus, thalamus, and hippocampus, making carriers more susceptible to impulsive-addictive-compulsive behaviors. A case-control study investigating reward dependence in adolescents with excessive internet video game use found that adolescents carrying this allele may use video games as a compensatory mechanism for deficiencies in the dopaminergic system [31]. In 2021, a hospital in Medellín, Colombia, conducted a cross-sectional study in children aged 4 to 8 years to examine the possible relationship between sleep bruxism and screen exposure time in pediatric populations. The study identified a statistically significant association (Rho=0.8; P=0.002). Furthermore, the DRD2 gene polymorphism was suggested to have an etiological relationship with certain bruxism phenotypes in children. The researchers proposed that future studies should investigate the presence of this polymorphism in these patients [32]. Although these findings suggest that screen exposure may interact with specific genetic variants to influence behavioral or physiological outcomes Fig. 2 is cited, it is important to note that these variants are not currently integrated into routine clinical diagnostics due to their nonspecific nature and the complexity of polygenic traits. Additionally, current clinical methodologies may not be able to capture the nuanced effects of such polymorphisms, particularly in the absence of clearly defined disease phenotypes. Therefore, the interpretation of these associations should remain within the scope of exploratory research and hypothesis generation, while their application to individualized clinical care remains premature at this time.