Screen time, physical activity, and health-related quality of life in early childhood: a cross-sectional study of Spanish preschoolers

Abstract

Background

There is evidence of a negative association between excessive screen time and health-related quality of life (HRQoL), and a positive association between higher levels of physical activity (PA) and HRQoL. However, research focusing on early childhood, a crucial period of development, and the formation and reinforcement of habits for long-term health outcomes remains scarce. This study examined the relationship between screen time and PA with HRQoL, after controlling for relevant confounders such as socioeconomic status (SES) and weight status in Spanish preschoolers.

Methods

A cross-sectional analysis was conducted using baseline data from the MOVI-HIIT study, which included 494 children aged 4–5 years from 9 schools in Ciudad Real, Spain. HRQoL was assessed using KINDL-R questionnaires completed by both children and parents. Screen time and PA were estimated through parental questionnaires and categorized according to international guidelines. Body mass index (BMI) and SES were included as covariates. Partial correlations and covariance analyses were performed.

Results

Among the participants, 68.6% adhered to the recommendation of ≤ 1 h/day of screen time, while 87.2% met the PA guideline of ≥ 180 min/day. Children exceeding screen time recommendations reported lower overall HRQoL, particularly among girls, even after adjusting for BMI, SES, and PA. Conversely, children meeting PA guidelines exhibited higher parent-reported overall HRQoL scores.

Conclusions

Meeting recommendations of ≤ 1 h/day of screen time and ≥ 180 min/day of PA is associated with better HRQoL scores in 4- to 5-year-olds, with gender-specific differences. Interventions should promote healthy habits from early childhood, incorporating a gender perspective and emphasizing equitable physical activities and digital content monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-23429-1.

Background

In an era of rapid technological expansion, multimedia content is becoming an integral part of children’s daily lives and plays a crucial role in their development [1]. Sedentary behaviour, often measured as screen time, is defined as the time spent passively engaging with screen-based entertainment, such as watching television, using computers, or browsing mobile devices, excluding interactive screen-based games that involve physical activity (PA) or movement [2]. In contrast, PA refers to any bodily movement produced by skeletal muscles that results in energy expenditure [3].

Although major international organizations recommend that children under the age of 5 limit sedentary behaviour as screen time to no more than one hour and engage in at least 180 min of PA per day [2], many children do not adhere to these guidelines [4–6]. The increasing prevalence of screen time [7] has raised significant concerns about its potential association with children’s development in the early years of life [8]. Thus, excessive screen time has been associated with poorer mental and emotional health, impaired cognitive development [9], and lower levels of self-esteem, prosocial behaviour, and academic performance in children [10]. Furthermore, the use of electronic devices often displaces important protective behaviours or lifestyles such as PA [11], which has been consistently linked to numerous physical, emotional, mental, and social health benefits in youths [12].

Health-Related Quality of Life (HRQoL), which encompasses experiences, beliefs, and perceptions related to physical, psychological, and social aspects of health, is currently regarded as an important global health outcome [13]. In children, HRQoL reflects their ability to perform age-appropriate activities, their perceptions of their own lives, and how they value their functioning and well-being [14]. Consequently, examining the factors influencing HRQoL could help identify at-risk children and inform the development of lifestyle intervention programs aimed at improving their quality of life from a public health perspective [15].

Studies examining the relationship between screen time and HRQoL has predominantly focused on adolescents and children over five years old, providing moderate evidence regarding a negative association between screen time and HRQoL [16]. Conversely, higher levels of PA have been linked to better HRQoL in schoolchildren and adolescents [17]. Similarly, in this age group, meeting the 24-hour movement guidelines has been associated with better HRQoL [18]. In preschoolers, however, the evidence is limited and inconclusive [19]. To our knowledge, only 5 studies analysed compliance with recommendations on healthy behaviours (PA and screen time) and quality of life in children under 5 years of age. Previous studies suggest that those with lower screen time and higher PA levels tend to have higher HRQoL scores compared to those with low PA and low screen time, or low PA and high screen time [20–22], particularly in terms of physical health score [23]. On the other hand, other studies did not observe associations between health-related lifestyle behaviours and HRQoL in preschoolers [24] or no significant association was found between 24-h movement behaviours and HRQoL in preschool girls [23]. Furthermore, according to the multidimensional model of HRQoL proposed by Wilson and Cleary [25], in addition to health-related behaviours (such as screen time and PA), other factors such as socioeconomic status (SES) [26] and health conditions such as overweight/obesity [27], influence HRQoL outcomes. In particular, children with lower SES or higher body mass index (BMI) often face systemic barriers that affect both their lifestyle choices and their perceived well-being. These elements underscore the complexity of isolating causal relationships in HRQoL research in young populations. On the other hand, parents tend to perceive their children’s HRQoL as higher than the children do themselves, making it important to consider both perspectives [28].

This complex relationship between these factors remains underexplored in children aged 4 to 5 years, a critical developmental stage where foundational habits for long-term health are established and reinforced. Addressing this gap, the present study examined the association between screen time and PA with HRQoL (self-reported and parent-reported) by sex, after controlling for relevant confounders such as SES and weight status, in a sample of 4- and 5-year-old Spanish schoolchildren. Therefore, based on previous studies, we hypothesized that: (1) children who meet the screen time recommendation (≤ 1 h/day) will report higher HRQoL scores compared to those exceed this threshold; (2) children who meet the PA recommendation (≥ 180 min/day) will have better HRQoL than those with lower PA levels; and (3) the associations between screen time, PA, and HRQoL will differ by sex.

Materials and methods

This research presents a cross-sectional analysis of baseline data derived from the MOVI-HIIT study, a cluster-randomized controlled trial registered in clinicaltrials.gov (NCT04863040, 2021-04-28). The study included 494 children aged 4–5 years, recruited from 9 schools in Ciudad Real, Spain. The assessments were conducted between September and November 2022 by trained personnel who adhered to standardized procedures. Informed consent was obtained from the School Board, parents or guardians, and verbal assent was acquired from the children before conducting each test. Ethical approval for the MOVI-HIIT study was granted by the Clinical Research Ethics Committee of the University General Hospital in Ciudad Real (REG: C-254).

Health-related quality of life (HRQoL) was assessed using the Spanish versions of the KINDL-R self-report and parent’s proxy-report questionnaires [29], which asks about the previous week. The KINDL-R children’s self-report consists of 12 items, with the average score transformed into a scale from 0 to 100, resulting in a total HRQoL score. The KINDL-R parent’s proxy-report is organized into six dimensions (physical well-being, emotional well-being, self-esteem, family, friends, and school), in addition to a total HRQoL score. The average scores for each dimension were also transformed into a 0 to 100 scale, allowing for the calculation of a total HRQoL score. Higher scores indicate better HRQoL.

Screen time was assessed using a parent-reported questionnaire based on previous studies conducted in Spain [30]. Parents reported the duration of their child’s leisure activities involving electronic devices–such as television, computers, tablets, smartphones, and video games–on both weekdays and weekends, referring to time spent outside preschool hours. The weekly frequency and duration (in hours) were averaged and divided by seven to calculate the daily screen time. Based on established guidelines, screen time was classified as either compliant (≤ 1 h/day) or non-compliant (> 1 h/day).

Physical activity was measured using a parent-reported questionnaire based on population studies to assess compliance with PA recommendations [31], where parents recorded the duration (in minutes) of their children’s daily PA on weekdays and weekends. The questionnaire included the following question: “In the past 7 days, outside of school hours, on how many days was your child physically active for a total of at least 60 minutes per day? Please consider both moderate activities (such as walking or playing outdoors) and vigorous activities (such as running or sports like swimming, soccer, or judo).” Weekly frequency and duration were averaged and divided by seven to calculate the daily average PA minutes. Following established guidelines, PA was categorized as compliant (≥ 180 min/day) or non-compliant (< 180 min/day) based on the daily average.

Socioeconomic status was evaluated through self-reported parental occupation and education levels. A socioeconomic status index was computed based on these factors, following the procedures outlined by the Spanish Society of Epidemiology scale [32]. This scale categorizes family socioeconomic status into five levels; however, for our analyses, these were condensed into three categories due to the small number of individuals in the extreme categories: lower-upper lower, lower-middle, and upper middle-upper.

The weight and height of the participants were measured twice using a SECA-821 scale and a SECA-222 stadiometer (Vogel & Halke, Hamburg, Germany) according to standardized procedures. Body mass index (BMI) was calculated by dividing the mean weight (in kilograms) by the square of the height (in meters).

Statistical analysis. The normality of all variables was evaluated using graphical methods and the Kolmogorov-Smirnov test and all variables fitted to a normal distribution. Descriptive characteristics of the study sample were expressed as means and standard deviations for continuous variables or percentages for categorical variables. The independent samples t-test was used to assess differences for continuous variables, while the chi-square test was used for categorical variables in the descriptive analyses. Cronbach’s alpha for the dimensions of the KINDL-R was calculated at 0.80, indicating high internal consistency. The analysis of covariance (ANCOVA) with Bonferroni post hoc was used to assess differences in HRQoL according to screen time and PA categories, controlling for BMI, SES, and PA when the factor was screen time categories, and by screen time when the factor was PA categories. Partial eta squared () for the ANCOVA test were calculated indicating small effect (0.01–0.06), intermediate effect (≥ 0.06–0.14) and strong effect (≥ 0.14) sizes [33]. Radar diagrams were plotted using the R package ggplot2 [34]. Statistical analyses were performed using IBM SPSS Statistics Statistical v28 (IBM Corp., Armonk, NY, USA), and the statistical significance was set at p < 0.05.

Results

Table 1 presents the descriptive characteristics of the study participants. 68.6% of the total sample spent ≤ 60 min on screen time (64.8% boys; 72.4% girls), and 87.2% were involved in ≥ 180 min of PA (88.1% boys; 86.4% girls). Significant sex differences in HRQoL were observed, in KINDLp Self-esteem (p < 0.001) and KINDLp School (p = 0.041), with girls showing lower scores in both self-esteem and school perception. No significant differences were found in the other HRQoL dimensions.

Table 1.

Characteristics of the study sample

	N Total	Value	N ♂	Value	N ♀	Value
Age (years)	494	4.81 (0.56)	244	4.82 (0.58)	250	4.82 (0.54)
Socioeconomic status
Lower-Upper lower	91	21.5	43	19.7	48	23.4
Lower-Middle	233	55.1	123	56.4	110	53.7
Upper middle-Upper	99	23.4	52	23.9	47	22.9
Anthropometry
Weight (kg)	488	18.20 (3.54)	233	18.58 (3.58)	255	17.86 (3.47)*
Height (m)	494	1.08 (0.06)	236	1.09 (0.06)	258	1.07 (0.05)*
BMI (kg/m2)	487	15.48 (2.03)	232	15.56 (1.96)	255	15.41 (2.09)
Screen time (min/day)	472	53.84 (30.70)	233	55.16 (29.98)	239	52.56 (31.39)
Screen time (> 60 min)†	148	31.4	82	35.2	66	27.6
Physical activity (min/day)	478	298.74 (115.77)	235	304.34 (115.94)	243	293.33 (115.58)
Physical activity (≤ 180 min)†	61	12.8	28	11.9	33	13.6
Health-related quality of life
Physical well-being	469	84.16 (13.60)	234	85.03 (13.16)	235	83.29 (14.00)
Emotional well-being	470	89.08 (10.71)	234	89.41 (10.36)	236	88.75 (11.05)
Self-esteem	469	82.10 (14.40)	234	79.41 (14.76)	235	84.78 (13.55)*
Family	477	85.96 (11.35)	237	85.63 (11.07)	240	86.29 (11.65)
Friends	476	88.16 (11.84)	236	88.00 (11.74)	240	88.32 (11.95)
School	451	85.20 (12.86)	222	83.94 (13.96)	229	86.43 (11.60)*
Total score parents	474	85.72 (8.61)	236	85.18 (8.59)	238	86.25 (8.61)
Total score children‡	486	80.40 (12.16)	231	79.79 (12.92)	255	80.95 (11.43)

Data are presented as means and standard deviations, except for socioeconomic status categories, screen time (>60 min) and physical activity (≤180 min) which is shown as quantity and percentage. BMI: body mass index

* Indicate differences between boys and girls

^† Screen time was classified as either compliant (≤1 h/day) or non-compliant (>1 h/day) and physical activity was categorized as compliant (≥180 min/day) or non-compliant (<180 min/day) based on the recommendations

^‡ Health-related quality of life children self-report

Partial correlation coefficients between screen time, PA and HRQoL for the total sample as well as by sex controlling by BMI and SES are presented in Table 2. PA showed a negative association with screen time during the week for the total sample (r = -0.218, p < 0.01) and for boys (r = -0.318, p < 0.01). Additionally, PA was positively associated with school-related HRQoL and parents’ perception of total HRQoL in the whole sample (r = 0.108, p < 0.05 and r = 0.130, p < 0.05), as well as in boys (r = 0.179, p < 0.05 and r = 0.188, p < 0.05). For physical well-being, a positive association was observed in boys (r = 0.197, p < 0.05). Screen time was negatively associated with physical well-being, school-related HRQoL, and total HRQoL in children’s self-reports for the total sample (r = -0.131, r = -0.108, and r = -0.190; p < 0.05), as well as in boys (r = -0.142, r = -0.175, and r = -0.163; p < 0.05). For girls, screen time was also negatively associated with total HRQoL in their self-reports (r = -0.211, p < 0.01).

Table 2.

Pearson partial correlation coefficients (r) between physical activity, screen time and health-related quality of life by sex, controlling by body mass index and socioeconomic status

		Screen time min/day	Physical well-being	Emotional well-being	Self-esteem	Family	Friends	School	Total score parents	Total score children‡
Physical activity min/day	Total	-0.218**	0.098	0.095	0.082	0.077	0.078	0.108*	0.130*		0.068
	♂	-0.318**	0.197*	0.068	0.094	0.113	0.091	0.179*	0.188*		0.105
	♀	-0.145	0.007	0.116	0.116	0.049	0.072	0.051	0.094		0.049
Screen time min/day	Total	-	-0.131*	-0.038	-0.082	-0.027	-0.036	-0.108*	-0.105		-0.190**
	♂	-	-0.142	-0.070	-0.082	-0.052	0.002	-0.175*	-0.135		-0.163**
	♀	-	-0.142	-0.020	-0.043	-0.006	-0.066	-0.015	-0.071		-0.211**

*p<0.05; **p<0.001

^‡ Health-related quality of life children self-report

Figure 1 illustrates the mean differences in HRQoL across screen time categories, controlling for BMI, SES, and PA by sex. Children and girls who spent ≤ 60 min of screen time per day reported better total quality of life in self-reports, with a small effect size (children: X̅ = 82.40 ± 0.73 vs. X̅ = 77.91 ± 1.19, p = 0.002, = 0.026; girls: X̅ = 83.50 ± 0.89 vs. X̅ = 77.89 ± 1.62, p = 0.003, = 0.047). No statistically significant differences were found in the means of the other dimensions of the HRQoL according to screen time categories. In Additional file 1, all complete data can be found.

Fig. 1.

Differences in health-related quality of life (HRQoL) by screen time categories, controlling for confounders. The more prominently coloured data points and solid lines represent statistically significant differences (p < 0.05). ^‡ Health-related quality of life children self-report

Figure 2 presents the mean differences in HRQoL across PA categories, controlling for BMI, SES, and screen time by sex. Boys who engaged in ≥ 180 min of PA per day showed better total quality of life in parents’ proxy reports with a small effect size (X̅= 85.58 ± 0.58 vs. X̅ = 81.49 ± 1.92, p = 0.045, = 0.022). No statistically significant differences were found in the means of the other dimensions of the HRQoL according to PA categories. In Additional file 2, all complete data can be found.

Fig. 2.

Differences in health-related quality of life (HRQoL) by physical activity categories controlling for confounders. The more prominently coloured data points and solid lines represent statistically significant differences (p < 0.05). ^‡ Health-related quality of life children self-report

Discussion

The results of this study suggest that children aged 4 and 5 years who did not meet the recommendation of one hour or less screen time per day scored lower self-reported overall HRQoL than children who meet this recommendation, even after controlling for SES, BMI and PA, particularly among girls. Furthermore, adherence to PA recommendations (≥ 180 min per day) was associated with better parents-reported overall HRQoL in boys after controlling for SES, BMI and screen time.

Our findings align with previous studies that have demonstrated a significant association between excessive screen time and lower HRQoL scores in both children and adolescents [16, 17]. For children aged 3 to 6 years, excessive screen time has been suggested to correlate with lower HRQoL scores across all dimensions [35] and with overall HRQoL score [23]. However, our results show that the relationship is only significant for the total HRQoL scores reported. The lack of association in other domains of the HRQoL in our sample in comparison to previous studies could be explained by several factors. First, our study includes healthy children with high quality of life scores on most dimensions, it is likely that if the sample were more heterogeneous the results would be different. Second, parental responses regarding screen time and PA may not be free of subjectivity and social desirability bias, as screen time of less than one hour per day seems unrealistic given other current Spanish studies where higher data are reported [36]. Finally, the cutoff score of 60 min of screen time per day may not capture meaningful differences given the homogeneity of screen time exposure, with most children likely clustered around one hour per day.

Previous studies have found that excessive screen time is primarily associated with socioemotional aspects [9], as well as lower prosocial behaviour and academic performance in school-aged children [37]. In line with these findings, our study shows a declining trend, although without reaching statistical significance, in scores related to the school environment for boys and emotional well-being and family relationships for girls as screen time increases. These observed gender differences may be attributed to family context [21] and its influence on the type of content consumed, such as television in girls and video games in boys, being associated with poorer HRQoL [38]. For girls, screen time has also been associated with lower self-esteem [39], with evidence of a consistent dose-response relationship [40], which may affect their emotional well-being. The observed decline in physical well-being with increasing screen time might be explained by the association of high levels of sedentary behaviour with higher BMI [37] and unfavourable measures of adiposity [9].

Regarding the decrease in HRQoL scores related to the school environment, previous studies have reported that screen use in school-aged children is associated with physiological responses such as central nervous system arousal, disruption of sleep patterns [41], and greater school disengagement [42]. Furthermore, excessive television viewing at a very early age may be associated with and increased risk of peer victimization during the early school years and decrease attention skills [43].

In our study, we also found that engaging in more than 180 min of PA per day was associated with higher overall HRQoL scores only in boys, with an upward trend across all dimensions, although these did not reach statistical significance. Previous findings suggest that more active children tend to scored better HRQoL [44]. Consistent with our results, Christian et al. found in a study with preschoolers that meeting 24-hour movement guidelines in the early years was associated with socioemotional development in boys, but not in girls [45]. In contrast, in our study, PA was not associated with any aspect of HRQoL in girls, a finding consistent with a recent study that reported no significant associations between 24-hour movement behaviours and HRQoL in preschool girls [23]. However, comparisons are challenging due to the limited number of studies involving such young children. The differences observed between boys and girls may be due to the fact that preschool boys are generally more active than girls [45, 46], and that not all types of PA are equally associated with children’s HRQoL [38].

Several mechanisms could help explain the associations observed between screen time, PA, and HRQoL. First, time spent in sedentary activities might reduce the time available for physically or intellectually stimulating activities [47, 48]. Second, PA has been associated with improved brain health by enhancing nutrient transport to neurons, increasing endorphin secretion, and providing opportunities for better social interaction among peers [49]. These factors could influence psychophysiological responses to screen exposure and potentially reduce the risk of adverse psychological effects [41]. Furthermore, recent evidence suggests that self-esteem, self-concept, and self-efficacy are key psychosocial factors through which PA may contribute to improved psychological well-being and reduced distress [50]. These factors have been identified as potential mediators in the association between PA and mental health, particularly in youths.

Even considering the valuable data provided in this study, due to lack of studies in this age-range, our study has several limitations that should be acknowledged. First, the cross-sectional design of the analysis does not allow us to infer causal relationships between screen time, PA levels, and HRQoL. The cross-sectional design of the studies offers a limited basis for establishing the direction of the associations. For instance, sedentary time may be associated with physical and psychological symptoms rather than preceding them. Future studies should collect longitudinal data at different time points. Second, although the questionnaires used have demonstrated high validity and reliability, we relied on parent-reported measures of PA and screen time rather than objective measures, which may not accurately reflect actual values. Thus, the results of this study may be biased by the instrument used for data collection and by the fact that parents only reported screen time and PA occurring outside preschool hours. In addition, we were unable to conduct a reliability analysis of the KINDL-R in our sample; however, the original instrument shows a good reliability [51]. Third, the type of content consumed and the context in which it is consumed were not considered. Viewing educational content in the company of parents could mitigate the negative health effects of screen time [52] and have positive effects on cognitive development [53]. Future research should include 24-hour accelerometery data and examine the impact of specific types of screen use on children’s socioemotional development, as well as the specific circumstances in which preschoolers access different content. Likewise, the influence of other factors not evaluated in this study, such as the children’s health status or other behavioural factors such as sleep, should be analysed. Finally, although a sample size calculation was not performed specifically for this study, as it uses baseline data from a cluster-randomised controlled trial, the sample size is comparable to similar published studies [20–23]. In addition, exploratory post-hoc analyses showed adequate statistical power (> 85%) for most statistically significant associations. However, power was low (53.2%) in the comparison by physical activity levels among boys, likely due to small subgroup size (n = 16). This increases the risk of a Type II error (failing to detect a true effect) and warrants cautious interpretation. We highlight the need for replication in larger, adequately powered studies, especially for sex-stratified analyses, in line with current recommendations on post-hoc power interpretation [54, 55].

In conlusion, the results of this study indicate that, after adjusting for confounding variables, exceeding the recommendation of one hour of screen time per day is associated with poorer overall HRQoL in Spanish girls aged 4 and 5 years. In addition, a negative trend was observed in different HRQoL dimensions with increasing screen time in both boys and girls. Conversely, adherence to PA recommendations was associated with better HRQoL in boys.

Institutional recommendations should focus on encouraging parents to limit their children’s screen time from an early age, spend as much of that time as possible with their children, and use parental controls to regulate the type of content consumed. Additionally, schools should integrate PA during the school day by encouraging active commuting (e.g., walking or biking to school), active recess, or active breaks, with or without curricular content, during the school day. Public policies should also encourage active commuting and incorporate educational programs on screen use and the benefits of PA. PA initiatives should be introduced in preschool, incorporating a gender perspective to ensure that both boys and girls can participate equally, fostering long-term healthy habits that can be integrated into children’s daily routines.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

A.B-C.: Conceptualization, investigation, formal analysis, writing– original draft; Y.S.: Investigation, writing– review and editing; A.R-T.: Conceptualization, investigation, formal analysis, data curation, writing– original draft; A.D-F.: Funding acquisition, project administration, investigation, writing– review and editing; M.E.V-A.: Investigation, writing– review and editing; M.S-L.: Conceptualization, funding acquisition, project administration, investigation, writing– review and editing, supervision.

Funding

This study was funded by the Spanish Ministry of Science, Innovation, and Universities (MCIN/AEI/10.13039/501100011033; ref. PID2019-104160RB-I00).

Data availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Declarations

Ethics approval and consent to participate

Ethical approval for the MOVI-HIIT study was granted by the Clinical Research Ethics Committee of the University General Hospital in Ciudad Real (REG: C-254). The study was conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from the School Board, parents or guardians, and verbal assent was acquired from the children before conducting each test.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.