Introduction

The ongoing COVID-19 pandemic has impacted billions of children’s and adolescents’ lives in an unprecedented manner [1–3]. To limit the spread of the virus, stringent preventative measures were imposed worldwide. Countries around the globe announced complete lockdown which included school closures for the most part of the year 2020 and extended partially into the following years. Around 1.5 billion children (aged 5–12 year) and youths (aged 13–17 year) were transitioned into virtual learning [4, 5]. Disruption of daily routines, limited mobility and social constraints have considerably increased engagement in sedentary activities especially screen time (ST) [6, 7]. Available evidence indicates that screen-based sedentary behaviours have been associated with unhealthy dietary habits [6], interrupted sleep patterns [8] and limited opportunities for children and adolescents to engage in physical activity [9], all of which comprise a combination of risk factors for metabolic syndrome.

Given the revolutionary advances in digital technologies, the question of how to adequately classify ST remains a challenge [10]. The World Health Organization (WHO) defines ST as “Time spent passively watching screen-based entertainment (TV, computers, mobile devices),” excluding other innovative and modern forms of virtual realities, interactive video-gaming where physical activity or movement is required [11].

The COVID-19 pandemic has caused a marked increase in ST across the globe. A large observational study (n = 8395) in 10 European countries revealed that 69.5% [95%CI: 68.5–70.5] of young adolescents aged 6–18 years have exceeded the recommended limit of ST (>2 h/day) during weekdays and 63.8% during weekend [95%CI: 62.7–64.8]. Children residing in mildly affected countries and those in countries with lower level of restrictions were less likely to exceed that limit (OR = 3.25 [95%CI: 2.38–4.45) and OR = 1.42 [95% CI: 1.07–1.90], respectively) [12]. Similarly, findings from (ABCD) study during the early stages of the pandemic reported a mean (SD) of 7.70 (5.74) h/day of screen use, a more than twofold increase as compared to the pre-pandemic figure [13].

MetS is defined as a set of cardio-metabolic risk factors that includes glucose intolerance, central obesity, hypertension, and dyslipidaemia [14]. Lifestyle factors such as insufficient moderate-to-vigorous physical activity (MVPA), low cardiorespiratory fitness, smoking, and sedentary behaviour are amongst the various possible predictors of MetS in adolescents [15]. According to the American Heart Association (AHA), National Heart, Lung and Blood Institute (NHLBI) and International Diabetes Federation (IDF), the diagnosis of MetS is based on the presence of three of the followings: waist circumference (WC) indicative of central obesity (at least 102 cm in men and 89 cm in women), raised triglyceride (<40 mg/dl) in males, <50 mg/dl in females), raised blood pressure (systolic BP≥ 130 or diastolic BP ≥ 85 mmHg or receiving treatment for hypertension), and raised fasting glucose level (≥100 mg/dL, or diagnosed with type 2 diabetes) [16]. The diagnosis of MetS is usually established after the age of 10 years. In older children and adolescents aged 10–16 years, MetS is diagnosed in the presence of central adiposity (≥90th) and two of the following: triglycerides (TG)≥ 150 mg/dl, HDL-C <40 mg/dl, systolic blood pressure (SBP) ≥ 130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg, fasting plasma glucose (FG) ≥ 100 mg/dl or previously diagnosed type 2 diabetes [17].

MetS in children and adolescents has become a major public health concern, with prevalence reaching as high as 38.9% in the general population and relatively higher in overweight/obese children [18]. Numerous studies [19–21] have suggested that metabolic risk factors in childhood are associated with an increased risk of type 2 diabetes, subclinical atherosclerosis, and cardiovascular disease in adulthood. The pathological process underlying MetS begins in childhood with complex interrelated genetic and environmental factors [22]. Screen-based behaviours and physical inactivity are linked to higher levels of inflammatory biomarkers like interleukin-6 (IL-6) and tumour necrosis factor- (TNF-), which stimulate C-reactive protein (CRP), an important causative pathway leading to dyslipidaemia, insulin resistance, and cardiovascular disease [23]. A study by Strizich et al. showed that lower levels of MVPA were associated with higher glucose/lipid profiles and increased inflammatory biomarkers [24].

According to the current physical activity (PA) guidelines, children and adolescents should be engaged in at least 60 minutes of MVPA and no more than two hours of sedentary recreational ST daily [25]. Nevertheless, restrictions imposed due to the COVID-19 pandemic as well as prolonged missed opportunities in physical education due to school closures are foreseeable to profoundly limit the ability to meet these recommendations.

The association between ST and MetS among adolescents has been investigated in several studies prior to the declaration of the COVID-19 pandemic [26, 27]. However, results were found inconclusive for the most part owing to limited data and generalizability of findings to different types of ST considering the duration, content, and context of exposure [28, 29]. In a recent systematic review, authors pointed out limitations in approving the direct cause and effect relationship between excessive ST and MetS in adolescents [30]. For instance, de Oliveira RG et al. [31] revealed that ST of more than 2h/day during the weekend was significantly associated with a twofold increased risk of MetS, while insignificant association was observed concerning other days of the week. Khan et al. [32], however, observed a positive linear correlation between ST and MetS in children and adolescents, indicating a dose-response relationship for every 2 hours/day increase in ST (OR: 1.29, 95 percent CI 1.12–1.46) [32]. Stiglic and Viner [33] in their review found inadequate and unreliable evidence of association between ST and MetS, though, higher levels of ST were related significantly to an increased caloric intake, lower nutritional food, being obese, and having an overall reduced quality of life.

In light of the evolving pandemic, the prolonged screen-based sedentary behaviour exacerbated by remote learning remains a particular cause of concern. The emergence of MetS in earlier life indicates a serious risk of persistence into adulthood. Identification of contributing risk factors is of a great importance to planning for cost-effective prevention strategies. Therefore, an updated evaluation of available evidence is needed to examine the association between ST and MetS (with dose-response gradient) among adolescents, taking into consideration adjustment of potential confounders such as PA and dietary behaviour.

Thus, the aim of the current systematic review was to summarise the findings of studies that have looked at the quantifiable association between various forms of ST and MetS in adolescents aged 12 to 18 years.

Methods

Quality assessment

The National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to evaluate the risk of bias [35]. The checklist comprised 14 items for longitudinal research, of which only 11 could be applied to cross-sectional studies. Each item of methodological quality was classified as yes, no, or not reported and based on number of yes as total score, studies were classified according to quality rating: Poor<50%, Fair 50–75% and good >75%. Possible disagreements on the final score were resolved by consensus among the authors. Studies met from 73% to 91% of the quality criteria, with 9 studies (9/10, 90%) meeting good scoring indicating low risk of bias. All studies clearly stated the main aim, population and definition of exposure/outcome. However, two studies (2/10, 20%) did not use key potential confounders in the analysis. Eleven items were applicable to nine studies due to cross-sectional nature of these studies and one perspective cohort study where all 14 items were applicable (Table 1). Details of the NHL Quality assessment questions (Q1-14) are shown in S2 Table.

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Table 1. Study quality assessed by the quality assessment tool for observational cohort and cross-sectional studies.

https://doi.org/10.1371/journal.pone.0265560.t001

Data analysis

Synthesis began by summarizing review results and conclusions in note form. Reviews were then grouped by the exposure, which is screen time, and the outcome of interest was measured, which is the MetS and related risk factors. Moreover, we examined the conclusions of the included studies to decide which article came out as plausible. However, we did not enumerate the findings across studies as quantitative summaries should be undertaken at an individual study level rather than at a review level. A descriptive analysis of each included publication was conducted. ST exposure in hrs/day or week and the observed prevalence of MetS in percentages were specified. Adjusted estimates of OR or MetS z-score for the association between ST and MetS with a corresponding 95% CI were obtained. The OR of the dose-response gradient effect was also extracted.

Result

Flow of the studies

Fig 1 displays a flow chart of study identification and selection. Systematic search on database identified 3521 abstracts; of these, 2137 were excluded during initial screening for unrelated topics, meeting the exclusion criteria and duplicate studies from different databases. Totally, 62 full text articles were assessed to examine their eligibility for inclusion in the current review, and finally, after review of the full texts, ten studies were included in the data extraction.

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Fig 1. PRISMA flowchart for review.

https://doi.org/10.1371/journal.pone.0265560.g001

Overview of studies

Table 2 presents the general characteristics of the eligible studies. Most studies (9/10, 90%) employed a cross-sectional study design, except for one that implemented a prospective cohort design. In total, data from 41,687 participants was included in this review. The sample size ranged from 474 to 33,900 and the mean age of participants ranged from 12–18 years. Six of the studies have utilized school-based setting [31, 32, 36, 40–42], while the remaining 4 were part of national surveys. The primary objective of included studies was to establish significant association between ST (of any type) and MetS among adolescents, with all studies considering single or multiple exposures like PA, dietary habit or sleep duration associated with ST. Although the scope of the review focused on adolescents at the age of (12–18) year, studies that had a range of below 12 or above 18 were not excluded if the mean age was between 12–18 years. All the studies used subjective measures of daily/weekly hours ST including parental report, self-reported interview questionnaires. The main modalities of ST were TV viewing, computers, videogames, internet, tablets, and smartphones. Nine of the studies (9/10, 90%) utilized multivariable analysis to adjust for covariates [31, 32, 36–40, 42, 43], 8 of which (8/10, 80%) [31, 32, 36–38, 40, 42, 43], found a positive association between ST and MetS. Seven studies (7/10, 70%) proved a dose-response gradient for that association [29, 30, 34–36, 40, 41]. Two studies by Fadzlina et al. [41] and Siwarom et al. [39] found no significant association between ST and MetS. Exposure to ST prior to the age of 2 years was significantly associated with MetS in one of the included studies [39].

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Table 2. Summary of characteristics of included studies showing relation between screen time (ST) and Metabolic syndrome (MetS).

https://doi.org/10.1371/journal.pone.0265560.t002

Discussion

Public health measures related to the COVID-19 pandemic have led to a critical increase in the use of digital screen devices and reliance on remote learning. Screen-based sedentary behaviour is linked to physical inactivity and increased caloric consumption, which are important contributors to obesity and cardio-metabolic risk. Taken together, a better understanding of the association between ST (of different types) and MetS among vulnerable populations i.e., adolescents, is necessary to target preventable causes of premature mortality in later adulthood.

The present systematic review provides a narrative synthesis of data concerning the relationship between ST and MetS among adolescents. The majority of studies indicate a positive and dose-response association between exposure and the outcome of interest. Based on Quality Assessment Tool for Observational and Cross-Sectional Studies, 90 percent of included studies indicated low risk of bias, demonstrating good quality score.

Findings from this review confirm that adolescents engaged in screen-based sedentary behaviour have an increased likelihood of developing MetS. Multivariate analysis demonstrated that ST was a significant independent predictor of MetS. These findings are consistent with Tremblay et al. [44], who reported in their systematic review and meta-analysis of 232 publications a positive correlation between increased levels of sedentary behaviour (especially TV viewing> 2h/day) and cardiometabolic illnesses among children and youth. A notable link was observed between ST and adverse body composition, poor fitness, and low self-esteem [44]. Contrarily, some scholars have argued that ST in adolescents is irrelevant to future health risks. A systematic review [31] showed weak evidence of an association between ST and poor cardiorespiratory fitness, poorer cognitive development, lower educational attainments, poor sleep outcomes, or risk of MetS. However, it is important to note that weak association does not imply absence of correlation. For instance, the authors have reported a lack of literature as the probable cause of such an observation.

Time spent in front of screens (of different types), whether at home or school-based, was obtained as a self-reported measure based on daily/weekly hours. Longitudinal studies [42, 45] established that longer duration or more frequent TV viewing was associated with a higher clustering cardio-metabolic risk score, particularly elevated systolic blood pressure. In contrast, computer-based ST was associated with higher diastolic blood pressure, while a lower level of HDL was objectively associated with longer-accelerometer-derived sedentary time [46]. Sedentary behaviour was not found to be associated with other cardiometabolic risk factors such as triglycerides, HOMA-IR, or glucose level [42].

This systematic review indicates a linear association between ST and MetS, meaning that MetS risk increased in tandem. For instance, spending more than two hours of daily ST triggered an increased risk of MetS in a dose-response manner, with the most harmful effect noted at 5–6 hours per day. Consistent with our findings, longitudinal studies have shown that higher cholesterol levels [47] and higher blood pressure [48] were associated with watching more than two hours of television per day, as compared to those who watch less. Similarly, high levels of self-reported sedentary behaviour including ST were associated with an increased risk of elevated systolic and diastolic blood pressure [48–51], higher glycated haemoglobin (HbA1C) [52], fasting insulin [50, 53], insulin resistance [54], and MetS [55]. With reference to the dose-response gradient, longer duration of TV viewing was significantly correlated with increased risk of MetS/cardiovascular disease risk factors, whether a 2-h cut-point [56, 57], a 3-h [58] or a 4-h [59] cut-point [60] was utilized. Accordingly, adolescents should be urged to limit their daily recreational ST to less than 2 hours per day, as recommended by the American Academy of Paediatrics and the World Health Organization (WHO). This is especially crucial given the likelihood of such a risk persisting into adulthood.

Several studies have conveyed a rising trend of ST and digital technology use during the pandemic [33, 61]. Children and adolescents are considered amongst the most susceptible groups due to their limited self-regulation and liability to peer pressure. For instance, Xiang et al. [62], illustrated a considerable increase in ST during the pandemic among 6–17 years old in Shanghai (+1730 minutes or nearly 30 hours in total). More than a quarter of students revealed an increase in leisure-based ST in addition. Comparably, the median time spent in PA was shown to be reduced from, 540 minutes per week (prior to the pandemic) to 105 minutes per week, with an average reduction of 435 minutes. The prevalence of physical inactivity was almost tripled as compared to the pre-pandemic period (21.3 vs. 65.6%). Another study [63] conducted in Canada exhibited a significant decline of adherence into PA and ST guidelines among 5–17-year-old during the pandemic (PA; from 18% to 35% [64] and ST: from 64% to 11.2% [65], subsequently).

Despite the well-established harmful effects of ST, several academic studies have indicated possible benefits (especially educational outcomes) of ST among younger generations. According to several studies, children and teenagers frequently lack the discipline and insight to limit ST on their own [65]. Thus, taking into account the current challenging crisis [66], it becomes critically vital to address mitigation strategies and encourage a family-centred media use plan that allows us to balance the risks and benefits. Despite the fact that ST has been traditionally linked to sedentary behaviour and increases the risk of negative health outcomes [67], there are always alternative positive ways around the corner. Appropriately used, ST can promote PA during a shelter-in-place [68], such as online PA classes, workout apps for mobile devices or active video games [68]. In this way, a recent systematic review among adolescents found that digital interventions incorporating educational activities, goal setting, self-monitoring, and parental involvement have led to a significant increase in PA [69].

Evidence is validating the role of opportunistic behaviour change counselling by clinical practitioners in the management of sedentary behaviour. A key mitigative strategy is to identify correlates of sedentary time, such as sociodemographic attributes, accessibility, parental behaviour, psychological, PA, and dietary behaviour [70]. Engaging adolescents, families, schools, and social workers in healthy lifestyle choices provides an enabling environment that supports behavioural change. School could be an ideal setting for encouraging physical activity and reducing sedentary behaviour. For instance, Verloigne et al. [71] acclaimed the placing of standing desks in classrooms and promoting stand-up bouts as an interventional approach to increase pupils’ self-efficacy and reduce sedentary behaviour in a pleasurable manner.

It may be possible to use a holistic method that looks at all three levels of the socio-ecological model (intra-individual, inter-individual, physical environment, and policy) to help people move more and make healthy food choices [72]. Effective communication with adolescents and their families enhances digital literacy related to screen types, content, and setting screen limits. A systematic review and meta-analysis on the effect of behavioural interventions in reducing ST revealed that smaller sample sizes and shorter intervention durations were associated with greater impact. Involvement of healthcare professionals in setting goals, feedback, and planning clusters yielded better outcomes in ST reduction [73].

Healthcare workers are advised to initiate early prevention strategies tackling the associated risk factors of NCDs among adolescents. Given the challenging period of COVID-19 [74–78], it has become increasingly important to integrate lifestyle education, health promotion, and community awareness within the management. Screening for early identification of behavioural and metabolic risk factors will help reduce the burden of NCDs later in adulthood. Tools such as screening of baseline PA, ST, Body Mass Index (BMI) and psychological assessment are essential to identify modifiable risk factors and ‘at risk’ children. Accordingly, replacement strategies, weight loss programs, and exercise prescriptions are recommended, taking into account the importance of continuous monitoring and evaluation. Evidence from this study can guide national and public health efforts in planning accessible multisectoral prevention and intervention strategies to tackle the determinants of MetS and NCDs.

Limitations

The evidence in this review was dependent on peer-reviewed journals via scientific databases, not accessing data from unpublished reports from educational institutions, non-profit data, or community services, and maybe subject to publication bias. Due to the apparent high risk of bias (ROB) attributable to clinical and methodological heterogeneity, meta-analysis of data was not performed. Moreover, undefined information in any of the included studies was not confirmed by the related authors, jeopardizing their quality, if any important details were missed. Furthermore, our research was limited to studies published only in English, and the cross-sectional design of the majority of included studies prevented inference of causality, thereby limiting the conclusion drawn regarding the temporal relationship between ST and MetS. Data were gathered by one researcher, and even though the data were carefully checked back to the publication by the second researcher, we did not use two separate extractions. In our narrative synthesis of findings, we aimed to avoid vote-counting of numbers of positive or negative studies to judge the strength of evidence. However, it is possible that our findings reflect methodological or conceptual biases in our included reviews. Finally, the search did not extend to all existing databases. Nonetheless, we performed searches in two primary databases and one secondary database.

Conclusion

The COVID-19 pandemic has resulted in children and adolescents spending more time on digital screen devices, eliciting a profound effect on their cardio-metabolic health and NCDs burden. In brief, our review demonstrated that independent of PA, significant association between ST and MetS was noted among adolescents. This observation has significant public health and clinical implications that demand urgent prevention initiatives targeting young people and their parents. Such interventions aim to enhance early screening of behavioural and metabolic risk factors and increase awareness of potential adverse health impacts related to NCDs. Healthcare providers should consider a promotive, holistic approach, taking into consideration the international recommendation of ST and PA across different age groups. Further community-based research, including longitudinal and RCTs are needed to confirm this primarily observational evidence.

Supporting information