Problematic Internet Use and Video Gaming : Are They Emerging Risk Factors for Elevated Blood Pressure?

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Hande YETİŞGİN, Pervin DEMİR, Mihriban İNÖZÜ, Esra COP, Sare Gülfem ÖZLÜ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8182015/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2026 Read the published version in European Journal of Pediatrics → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Hypertension is an increasingly important health concern among children and adolescents. Beyond traditional risk factors such as obesity, sedentary behaviors including prolonged internet use and video gaming may contribute to elevated blood pressure. This study aimed to investigate the association between problematic internet use, video gaming, and ambulatory blood pressure parameters in adolescents. Methods: This prospective study included adolescents aged 12–18 years who were referred to a pediatric nephrology outpatient clinic for hypertension evaluation. Demographic, clinical, and laboratory data were obtained from medical records. Ambulatory blood pressure monitoring (ABPM) was performed to confirm hypertension. Internet use and gaming behaviors were assessed using the Young Internet Addiction Scale (YIA-SF) and the Internet Gaming Disorder Scale (IGDS9-SF). Scale scores were compared with ABPM parameters. Results: A total of 107 adolescents (40 girls, 67 boys) with a mean age of 14.9 ± 1.8 years were included. According to ABPM findings, 39.4% were normotensive, 17.8% prehypertensive, and 45.8% hypertensive. Although statistical significance was not reached, increasing internet addiction scores were associated with higher overall mean systolic blood pressure. Higher YIA-SF scores were particularly related to increased maximum and mean daytime systolic blood pressure. Conclusion: Excessive internet use and video gaming may contribute to elevated blood pressure in adolescents, independent of obesity. Problematic internet behavior should therefore be considered in the clinical evaluation of hypertensive children and adolescents. Adolescent Ambulatory Blood Pressure Monitoring Childhood Hypertension Problematic Internet Use Video Game What is Known Sedentary screen-based behaviors—particularly excessive internet use and video gaming—are linked to pediatric obesity and elevated blood pressure. Most prior research has relied on office blood pressure measurements rather than ambulatory blood pressure monitoring (ABPM). What is New This is the first study to investigate how problematic internet use and video gaming affect ABPM parameters in adolescents. Higher internet addiction scores were associated with elevated daytime systolic and maximum systolic blood pressure. These associations persisted even in non-obese adolescents, indicating an obesity-independent relationship. 1. Introduction Hypertension is an increasingly important public health problem among children and adolescents [ 1 ]. The rising prevalence of pediatric hypertension has been strongly linked to the global childhood obesity epidemic [ 1 – 3 ]. Numerous population-based studies have demonstrated that overweight and obese children have significantly higher blood pressure levels compared with their normal-weight peers [ 4 ]. Unhealthy lifestyle patterns—including fast food consumption, insufficient sleep, smoking, and sedentary behaviors—have been identified as major contributors to obesity [ 5 , 6 ]. More recently, emerging evidence suggests that excessive screen exposure, prolonged internet use, and video gaming may not only promote obesity by reducing physical activity, but may also be independently associated with elevated blood pressure in youth [ 2 , 7 – 11 ]. Although the underlying mechanisms are not fully understood, proposed pathways include sleep disturbance, inreased sympathetic nervous system activity, and sustained cognitive arousal during screen-based activities [ 12 , 13 ]. Importantly, most previous studies have relied on office-based or casual blood pressure measurements, which are less reliable than ambulatory blood pressure monitoring (ABPM) in detecting true hypertension and circadian blood pressure patterns. In this study, we aimed to evaluate the effects of problematic internet use and video gaming on ambulatory blood pressure parameters in adolescents aged 12–18 years. To our knowledge, this is the first study in the English literature to investigate the association between these screen-based behaviors and ABPM findings in this age group. 2. Patients and Methods This prospective observational study was carried out in our pediatric nephrology outpatient clinic between 1 September 2021 and 31 December 2021. Children who were referred for evaluation of hypertension and aged between 12 and 18 years were included in the study. Patients with known hypertension or patients who had chronic kidney diseases, chronic cardiac diseases, and endocrinologic diseases were excluded to rule out secondary hypertension. Additionally, children diagnosed with any psychiatric diseases were not included. Age, gender, family history, anthropometric measurements, body mass index (BMI), and physical examination findings were recorded. BMI values were calculated as kg/m 2 and classified according to age- and sex-specific BMI z-scores based on World Health Organization (WHO) growth standards. A BMI z-score +1 SD to + 2 SD were classified as overweight , and values > + 2 SD were considered obesity [ 14 ]. 2.1.Laboratory Investigations and Imaging Techniques Urine analysis, renal function tests (serum, blood urea nitrogen, creatinine, glomerular filtration rate according to the Schwartz formula), uric acid, electrolytes, venous blood gas, cholesterol, triglyceride, renin and aldosterone levels, thyroid function tests, urinary ultrasound and renal artery Doppler ultrasound were performed to detect the underlying etiology. Urine protein excretion, echocardiography and ophthalmological examination were carried out to identify end organ damage. 2.2.Blood Pressure Measurements: 2.2.1.Office Blood Pressure Measurements : Blood pressure was measured on three different occasions with an appropriate sphygmomanometer, and hypertension was defined as blood pressure greater than the 95th percentile for age, gender and height in children under the age of 13 years old and as > 130/80 mmHg in children ≥ 13 years of age, according to the American Academy of Pediatrics 2017 hypertension guideline [ 15 ]. 2.2.2.Ambulatory Blood Pressure Monitoring: All children underwent ambulatory blood pressure monitoring to confirm the diagnosis of hypertension with “Spacelabs Healthcare On Trak Ambulatory Blood Pressure Monitor”. To avoid artifacts, a nondominant arm was used for monitoring. An appropriate cuff size was selected according to the hypertension guidelines [ 15 ]. Blood pressure was recorded every twenty minutes for the awake period and for 30 minutes for the sleep period. Children were allowed to continue their daily activities during monitorization, including attending school, but heavy exercise, such as sports participation, was abstained. A diary to record wake and sleep periods, daily activities, and any medications during the 24-h period was requested from all of the participants. Valid measurements above 90% were considered significant. Incorrect and insufficient measurements were excluded from the study. Overall mean systolic and diastolic blood pressure (SBP/DBP); daytime and nighttime mean SBP and DBP; and daytime and nighttime SBP and DBP loads were evaluated. Maximum daytime and nighttime SBP and DBP measurements and systolic and diastolic dipping parameters were determined. Based on ambulatory blood pressure monitoring data, patients were divided into four categories as follows: i) normotensive; mean SBP/DBP < 95th percentile and blood pressure loads < 25%; ii) prehypertensive; mean SBP/DBP 95th percentile and BP loads between 25 and 50%; and iv) severe hypertensive; mean SBP/DBP > 95th and BP loads > 50% [ 16 ]. 2.3.Young Internet Addiction Short Form (YIA-SF) To evaluate problematic internet use, the Young Internet Addiction Short Form was administered to all participants. The YIA-SF consists of twelve questions evaluating the frequency and duration of internet use of the patients and the effect of the internet on daily social life and school life. It is a 5-point Likert type scale and is scored as 1 = never to 5 = always. There is no reverse-scored item in the scale. The minimum scale score is 12, the total scale score is 60, and higher scores indicate an increased risk of internet addiction [ 17 ]. In this study, we used the Turkish version of the test, which was generated and validated by Kutlu et al [ 18 ]. The validation of the test was performed among adolescents and university students. 2.4.Internet Gaming Disorder-Scale Short Form (IGDS9-SF): To determine the effects of video gaming, the Internet Gaming Disorder Scale Short Form (IGDS9-SF) was administered to all participants. This scale was developed by Pontes HM and Griffiths MD, and the first Turkish version was developed and applied by Günüç S and Kayri M in 2017 [ 19 , 20 ]. In 2018, Evren et al. demonstrated the validity and reliability of this scale among young Turkish adults [ 21 ]. The scale consists of nine questions about the time spent on computer game activities and electronic devices such as game consoles, mobile phones, tablets, and all kinds of games that can be played both on the Internet and without being connected to the Internet. The scale consists of nine items. Each item is rated on a 5-point Likert scale ranging from 1 = never to 5 = very often. The maximum and minimum scores of the IGDS9-SF are 9 and 45, respectively. Higher scores indicate higher levels of problematic internet gaming. 2.5.Ethical Issues: Ethical approval was obtained from the Research and Ethics Committee of Ankara Bilkent City Hospital (date: 02.12.2020 no: E2-20-14). Detailed information was given, and written informed consent was obtained from both children and parents who volunteered to participate in this study. 3. Statistical Analysis Statistical analyses were performed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Normality of continuous variables was assessed with the Kolmogorov–Smirnov and Shapiro–Wilk tests, supported by histogram and Q–Q plot inspection. Continuous variables were expressed as mean ± standard deviation or median (range), and categorical variables as frequencies and percentages. Between-group comparisons were conducted using the Student’s t-test or Mann–Whitney U test for continuous variables and the chi-square or Fisher’s exact test for categorical variables. For comparisons across more than two groups, one-way ANOVA or the Kruskal–Wallis test was applied, followed by Bonferroni-adjusted post-hoc analyses when appropriate. Correlations between behavioral scores and blood pressure parameters were evaluated using Pearson or Spearman coefficients. To determine independent predictors of ambulatory blood pressure category, an ordinal regression model (PLUM, logit link) including age, gender, BMI category, YIA-SF, and IGDS9-SF scores was performed. Additionally, two multiple linear regression models were used to identify predictors of maximum and mean daytime systolic blood pressure, with age, gender, and BMI group entered as independent variables. A post-hoc power analysis (G*Power 3.1) indicated adequate statistical power (1 − β = 0.84) for detecting a medium effect size in the regression models. A p-value < 0.05 was considered statistically significant. 4. Results 4.1. Demographic and Clinical Characteristics A total of 107 adolescents were included in the study, of whom 40 (37.4%) were girls and 67 (62.6%) were boys, with a mean age of 14.9 ± 1.8 years. Based on BMI classification, 29 (27.1%) were normal weight, 32 (29.9%) overweight, and 46 (43.0%) obese (Table 1 ). Table 1 Baseline characteristics of the study population (n = 107) Variable Category n (%) Gender Female 40 (37.4) Male 67 (62.6) BMI group Normal weight 29 (27.1) Overweight 32 (29.9) Obese 46 (43.0) BP status Normotensive 39 (36.4) Prehypertensive 19 (17.8) Hypertensive 49 (45.8) Age (years) Mean ± SD 14.9 ± 1.8 Median (min–max) 15.0 (12.0–17.5) BMI : Body Mass Index BP: Blood Pressure SD: Standart Deviation All adolescents diagnosed with hypertension on ABPM underwent laboratory and imaging evaluations, including thyroid function tests, renin–aldosterone levels, and renal Doppler ultrasonography. No secondary causes of hypertension were identified, and all cases were classified as primary hypertension. Left ventricular hypertrophy was detected in 23 hypertensive individuals, while ophthalmologic evaluations were normal in all participants. 4.2. Ambulatory Blood Pressure Categories According to ABPM results, 39 participants (36.4%) were normotensive, 19 (17.8%) prehypertensive, and 49 (45.8%) hypertensive. None met the criteria for severe hypertension (Table 1 ). 4.3. Relationship of BP Categories with Age, Gender, and BMI Gender distribution was similar across BP categories (Table 2 ; χ² = 0.080, p = 0.961). Table 2 Gender distribution across blood pressure categories BP status Female, n (%) Male, n (%) Total (n) Normotensive 14 (35.9) 25 (64.1) 39 Prehypertensive 7 (36.8) 12 (63.2) 19 Hypertensive 19 (38.8) 30 (61.2) 49 Total 40 (37.4) 67 (62.6) 107 Chi-square test: χ² = 0.080, df = 2, p = 0.961 BP: Blood pressure Age differed significantly among the groups (Table 3 ; Kruskal–Wallis H = 8.04, p = 0.018), while BMI categories were not significantly associated with BP status (Table 4 ; χ² = 3.891, p = 0.421). Table 3 Age comparison across blood pressure categories BP status Mean ± SD (years) Median (years) Range (years) Normotensive 15.13 ± 1.74 15.5 12–17.5 Prehypertensive 13.82 ± 1.79 13.5 12–17.5 Hypertensive 15.20 ± 1.80 15.5 12–17.5 Kruskal–Wallis H = 8.04, df = 2, p = 0.018 BP: Blood pressure Table 4 BMI distribution across blood pressure categories BP status Normal weight, n (%) Overweight, n (%) Obese, n (%) Normotensive 8 (20.5) 16 (41.0) 15 (38.5) Prehypertensive 6 (31.6) 4 (21.1) 9 (47.4) Hypertensive 15 (30.6) 12 (24.5) 22 (44.9) Chi-square test: χ² = 3.891, df = 4, p = 0.421 BMI: Body Mass Index BP : Blood pressure 4.4. Internet Use and Gaming Scores Within Demographic Subgroups YIA-SF scores did not differ significantly between boys and girls (p = 0.33), whereas IGDS9-SF scores were higher in boys (p = 0.02). Neither BMI category nor weight status was associated with YIA-SF or IGDS9-SF scores (p = 0.21 and p = 0.078, respectively). A weak negative correlation was observed between age and YIA-SF scores (r = − 0.200, p = 0.039). IGDS9-SF scores showed a similar, though non-significant, trend (p = 0.061). 4.5. Behavioral Scores and Blood Pressure Categories Mean YIA-SF and IGDS9-SF scores did not differ significantly across normotensive, prehypertensive, and hypertensive groups (p = 0.33 and p = 0.64, respectively). 4.6. Correlation Between Behavioral Scores and ABPM Parameters Higher YIA-SF and IGDS9-SF scores were associated with higher mean systolic BP, although these correlations did not reach statistical significance (YIA-SF: r = 0.168, p = 0.084; IGDS9-SF: r = 0.025, p = 0.80). No significant correlations were found between behavioral scores and diastolic BP (Supplementary Table 2). A significant positive correlation was detected between YIA-SF scores and mean daytime systolic BP (r = 0.191, p = 0.049). Nighttime systolic and daytime/nighttime diastolic pressures increased with higher YIA-SF scores, though not significantly. IGDS9-SF scores were not correlated with any ABPM parameter (Supplementary Table 2). When evaluated according to blood pressure loads, there were no significant associations between behavioral scores and systolic or diastolic BP loads (Supplementary Table 3). The only significant relationship was detected among YIA-SF scores and maximum daytime systolic BP load (r = 0.280, p = 0.021) (Supplementary Table 3). 4.7. Subgroup Analysis: Obese vs. Non-Obese Participants Among non-obese adolescents, higher YIA-SF scores were significantly associated with higher maximum systolic BP (r = 0.280, p = 0.019). This association was not observed among obese participants, suggesting a possible modifying role of BMI status. 4.8. Ordinal Regression Analysis Ordinal regression analysis was performed to determine whether YIA-SF and IGDS9-SF scores independently predicted BP category after adjusting for age, gender, and BMI. The overall model was not significant (Table 5 ; χ² = 16.466, p = 0.087). Table 5 Ordinal regression analysis of predictors of blood pressure categories Predictor Estimate SE Wald χ² df p-value BP = Normotensive 226.185 601.795 0.14 1 0.707 BP = Prehypertensive 416.602 915.296 0.21 1 0.649 Age 16.370 43.676 0.14 1 0.708 YIA-SF score 4.153 10.627 0.153 1 0.696 IGDS9-SF score 2.557 9.481 0.073 1 0.787 Gender (male) 37.772 121.762 0.096 1 0.756 BMI (normal) 41.227 119.948 0.118 1 0.731 BMI (overweight) -184.516 357.432 0.266 1 0.606 Age (scale factor) 0.389 0.125 9.735 1 *0.002 Model fit: χ² = 16.466, df = 10, p = 0.087. Only age was significantly associated with BP category. YIA-SF : Young Internet Addiction Short Form IGDS9: Internet Gaming Disorder-Scale Short Form BMI : Body Mass Index BP: Blood pressure Table 6A. Linear regression model for maximum daytime systolic blood pressure Predictor B SE β t p-value Constant 123.440 10.618 — 11.63 <0.001 Gender (male) 5.876 2.623 0.207 2.24 0.027 Age 0.917 0.694 0.122 1.32 0.189 BMI group 4.400 1.537 0.263 2.86 0.005 Model summary: R = 0.361; R² = 0.131; F(3,103) = 5.159; p = 0.002. Table 6B. Linear regression model for average daytime systolic blood pressure Predictor B SE β t p-value Constant 105.426 7.053 — 14.95 <0.001 Gender (male) 3.405 1.742 0.182 1.95 0.053 Age 0.961 0.461 0.195 2.09 0.040 BMI group 2.069 1.021 0.188 2.03 0.045 Model summary: R = 0.334; R² = 0.112; F(3,103) = 4.319; p = 0.007. BMI : Body Mass Index Among all predictors, only age was significantly associated with BP category (β = 0.389, p = 0.002). Neither YIA-SF nor IGDS9-SF scores predicted BP status (p = 0.696 and p = 0.787). 4.9. Linear Regression Analyses for Systolic BP Two multiple regression models were constructed for maximum and mean daytime systolic BP (Table 6 A- 6 B): Maximum daytime SBP: The model was significant (F = 5.159, p = 0.002; R² = 0.131). Male gender (p = 0.027) and BMI group (p = 0.005) were independent predictors, while age was not. Mean daytime SBP: The model was significant (F = 4.319, p = 0.007; R² = 0.112). Age (p = 0.040) and BMI group (p = 0.045) were significant predictors; male gender showed borderline significance (p = 0.053). Across both models, neither YIA-SF nor IGDS9-SF scores were independent predictors of maximum and mean daytime systolic BP. 5. Discussion In this study, we investigated the relationship between problematic internet use, video gaming behaviors, and ambulatory blood pressure parameters in adolescents. Although both YIA-SF and IGDS9-SF scores showed a trend toward higher systolic blood pressure, these associations did not reach statistical significance in general correlation analyses. However, we found that YIA-SF scores were positively and significantly associated with both mean daytime systolic blood pressure and maximum daytime systolic blood pressure. Importantly, this relationship persisted among non-obese adolescents, suggesting that problematic internet use may influence systolic blood pressure independently of obesity. Problematic internet use is increasingly recognized as a growing public health concern among adolescents, with documented associations with psychological, behavioral, and cardiometabolic risk factors [ 22 ]. Several studies have highlighted that excessive screen exposure, including prolonged internet use, may contribute to increased blood pressure, obesity, depression, anxiety, and unfavorable lipid profiles [ 12 , 23 ]. Cassidy-Bushrow et al. demonstrated that among 331 adolescents, time spent on the internet was positively correlated with blood pressure—particularly diastolic pressure—independent of BMI [ 11 ]. These findings align with our observation that internet use may exert physiological effects beyond weight-related mechanisms. The cardiovascular impact of video gaming has also been documented in the literature. Goldfield et al. reported that screen exposure, particularly video game playing, was independently associated with increased blood pressure and adverse lipid parameters in overweight and obese adolescents [ 24 ]. Similarly, Wang et al. observed acute increases in both systolic and diastolic blood pressure during video game play in younger boys [ 10 ]. In an interesting study by Siervo et al., authors evaluated the effect of violent video games on blood pressure [ 9 ]. The authors suggested that violent video games cause a high cardiac load, which is probably related to the activation of the stress response [ 9 ]. They found that diastolic blood pressure increased progressively during violent video games, and they stated that ongoing increases in blood pressure may cause significant cardiac problems.Although our study did not evaluate game content, the existing literature emphasizes that video games—especially competitive or violent content—may activate sympathetic nervous system pathways, thereby increasing blood pressure [ 9 ]. As has been demonstrated in many studies to date, a sedentary lifestyle may be associated with obesity and consequently hypertension. Considering this well-known finding, we tried to evaluate the effects of internet addiction and video games on ABPM parameters independent of obesity. As mentioned above, Siervo et al demonstrated that video games can increase diastolic blood pressure, especially in nonobese young men [ 9 ].In the comprehensive study of Gopinath et al. conducted with 2353 school children with a mean age of 12.7 years, it was determined that screen exposure was significantly associated with blood pressure, independent of BMI and other factors [ 8 ]. In line with these observations, our subgroup analysis revealed that non-obese adolescents exhibited a significant association between YIA-SF scores and maximum daytime systolic blood pressure. This suggests that sympathetic activation, arousal, or stress responses during internet use may contribute to elevated systolic blood pressure independently of adiposity. Despite these patterns, neither YIA-SF nor IGDS9-SF scores emerged as independent predictors of blood pressure categories in our adjusted ordinal regression model, in which only age remained significant. Additionally, in multivariate linear regression analyses, BMI group and male gender (for maximum SBP) or age (for mean SBP) were the only independent predictors of systolic blood pressure. These results indicate that while problematic internet use may be associated with certain systolic BP parameters, it does not independently predict hypertension category when demographic and anthropometric factors are simultaneously considered. The primary limitation of our study is the relatively small sample size, which may have limited the statistical power to detect weaker associations. Future studies with larger cohorts, objective measures of internet and gaming exposure, and longitudinal designs are needed to clarify the causal pathways linking digital behaviors to cardiovascular outcomes. 6. Conclusion In this study, we demonstrated that problematic internet use and video gaming behaviors are associated with certain systolic ambulatory blood pressure parameters in adolescents. Although these behaviors were not independent predictors of hypertension category after adjusting for age, gender, and BMI, higher YIA-SF scores showed significant correlations with mean and maximum daytime systolic blood pressure, particularly among non-obese adolescents. These findings suggest that internet-related behavioral patterns may influence systolic blood pressure through mechanisms other than obesity, potentially involving heightened sympathetic activation or stress responses. Given the increasing prevalence of excessive screen exposure in adolescents, clinicians should routinely inquire about internet use and gaming habits when evaluating patients with elevated blood pressure. Even in the presence of normal office measurements, ambulatory blood pressure monitoring may be warranted in adolescents with prolonged internet use. Interventions aimed at reducing daily screen time and promoting healthier digital habits should be emphasized as part of lifestyle modification strategies. Further studies with larger sample sizes and longitudinal designs are needed to clarify the causal pathways linking internet use, gaming behaviors, and cardiovascular risk. Declarations Ethical approval : This study was performed in line with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Research and Ethics Committee of Ankara City Hospital (date: 02.12.2020 no:E2-20-14). Funding: There is no funding for this study. Conflict of interest: None of the authors have any conflict of interest Author Contributions All authors contributed to the study conception and design. Material preparation, data collection was performed by HY and Mİ. Data analysis was performed by PD. The first draft of the manuscript was written by HY and SGÖ .All authors commented on previous versions of the manuscript. EC cirtically reviewed the manuscript. All authors read and approved the final manuscript. Data Availability Statement: This manuscript has no associated data References Din-Dzietham R, Liu Y, Bielo MV, Shamsa F (2007) High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation 116:1488–1496. 10.1161/CIRCULATIONAHA.106.683243 Falkner B (2017) Monitoring and management of hypertension with obesity in adolescents. Integr Blood Press Control 10:33–39. 10.2147/IBPC.S125094 Rao G, Diagnosis (2016) Epidemiology, and Management of Hypertension in Children. Pediatrics 138(2):e20153616. 10.1542/peds.2015-3616 Sorof JM, Lai D, Turner J, Poffenbarger T, Portman RJ (2004) Overweight, ethnicity, and the prevalence of hypertension in school-aged children. Pediatrics 113:475–482. 10.1542/peds.113.3.475 Kelishadi R, Poursafa P, Keramatian K (2011) Overweight, air and noise pollution: Universal risk factors for pediatric prehypertension. J Res Med Sci 16:1234–1250 Burke V, Beilin LJ, Simmer K et al Predictors of body mass index and associations with cardiovascular risk factors in Australian children: a prospective cohort study (2005). Int J Obes (Lond) 29:15–23. 10.1038/sj.ijo.0802750 Lissak G (2018) Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environ Res 164:149–157. 10.1016/j.envres.2018.01.015 Gopinath B, Baur LA, Hardy LL et al (2012) Relationship between a range of sedentary behaviors and blood pressure during early adolescence. J Hum Hypertens 26:350–356. 10.1038/jhh.2011.40 Siervo M, Sabatini S, Fewtrell MS, Wells JC (2013) Acute effects of violent video-game playing on blood pressure and appetite perception in normal-weight young men: a randomized controlled trial. Eur J Clin Nutr 67:1322–1324. 10.1038/ejcn.2013.180 Wang X, Perry AC (2006) Metabolic and physiologic responses to video game play in 7- to 10-year-old boys. Arch Pediatr Adolesc Med 160:411–415. 10.1001/archpedi.160.4.411 Cassidy-Bushrow AE, Johnson DA, Peters RM, Burmeister C, Joseph CL (2015) Time Spent on the Internet and Adolescent Blood Pressure. J Sch Nurs 31:374–384. 10.1177/1059840514556772 Bener A, Bhugra D (2013) Lifestyle and depressive risk factors associated with problematic internet use in adolescents in an Arabian Gulf culture. J Addict Med 7:236–242. 10.1097/ADM.0b013e3182926b1f Chaput JP, Visby T, Nyby S Astrup A, Sjödin A et al (2011) Video game playing increases food intake in adolescents: a randomized crossover study. Am J Clin Nutr 93:1196 – 203. 10.3945/ajcn.110.008680 Aronne LJ (2002) Classification of obesity and assessment of obesity-related health risks. Obes Res 10(Suppl 2):105S–115S. 10.1038/oby.2002.203 Flynn JT, Kaelber DC, Baker-Smith CM, SUBCOMMITTEE ON SCREENING AND MANAGEMENT OF HIGH BLOOD PRESSURE IN CHILDREN et al (2017) Clinical Practice Guideline for Screening and Management of High Blood Pressure in Children and Adolescents. Pediatrics 140(3):e20171904. 10.1542/peds.2017-1904 Flynn JT, Daniels SR, Hayman LL, Obesity in Youth Committee of the Council on Cardiovascular Disease in the Young (2014) American Heart Association Atherosclerosis, Hypertension and Update: ambulatory blood pressure monitoring in children and adolescents: a scientific statement from the American Heart Association. Hypertension 63:1116–1135. 10.1161/HYP.0000000000000007 Pawlikowski M, Altstötter-Gleich C, Brand M (2013) Validation and psychometric properties of a short version of Young's Internet Addiction Test. Comput Hum Behav 29:1212–1223 Kutlu M, Savcı M, Demir Y, Aysan F (2016) Turkish adaptation of Young’s Internet Addiction Test-Short Form: a reliability and validity study on university students and adolescents. Anatol J Psychiatry 17:69–76. 10.5455/apd.190501 Pontes HM, Griffiths MD (2016) Portuguese Validation of the Internet Gaming Disorder Scale-Short-Form. Cyberpsychol Behav Soc Netw 19:288–293. 10.1089/cyber.2015.0605 Günüç S, Kayri M (2010) The profıle of internet dependency in Turkey and development of internet addiction scale: study of validity & reliability. H. U. J Educ 39:220–232 Evren C, Dalbudak E, Topcu M, Kutlu N, Evren B, Pontes HM (2018) Psychometric validation of the Turkish nine-item Internet Gaming Disorder Scale-Short Form (IGDS9-SF). Psychiatry Res 265:349–354. 10.1016/j.psychres.2018.05.002 Király O, Griffiths MD, Urbán R et al (2014) Problematic internet use and problematic online gaming are not the same: findings from a large nationally representative adolescent sample. Cyberpsychol Behav Soc Netw 17:749–754. 10.1089/cyber.2014.0475 Marshall SJ, Biddle SJ, Gorely T, Cameron N, Murdey I (2004) Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis. Int J Obes Relat Metab Disord 28:1238–1246. 10.1038/sj.ijo.0802706 Goldfield GS, Kenny GP, Hadjiyannakis S et al (2011) Video game playing is independently associated with blood pressure and lipids in overweight and obese adolescents. PLoS ONE 6(11):e26643. 10.1371/journal.pone.0026643 Additional Declarations No competing interests reported. Supplementary Files SUpplementaryTable1.docx SupplementaryTable2.docx SupplementaryTable3.docx Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2026 Read the published version in European Journal of Pediatrics → Version 1 posted Editorial decision: Revision requested 15 Dec, 2025 Reviews received at journal 15 Dec, 2025 Reviews received at journal 27 Nov, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers invited by journal 26 Nov, 2025 Editor assigned by journal 26 Nov, 2025 Submission checks completed at journal 26 Nov, 2025 First submitted to journal 22 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8182015","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":552279622,"identity":"01213590-8ac7-4e13-a7e9-40f26a9366b1","order_by":0,"name":"Hande YETİŞGİN","email":"","orcid":"","institution":"Ankara Bilkent City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hande","middleName":"","lastName":"YETİŞGİN","suffix":""},{"id":552279623,"identity":"89181d30-6960-4ec1-a816-2d3c94c93c56","order_by":1,"name":"Pervin DEMİR","email":"","orcid":"","institution":"Ankara Yıldırım Beyazıt 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ÖZLÜ","email":"data:image/png;base64,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","orcid":"","institution":"Ankara Yıldırım Beyazıt University","correspondingAuthor":true,"prefix":"","firstName":"Sare","middleName":"Gülfem","lastName":"ÖZLÜ","suffix":""}],"badges":[],"createdAt":"2025-11-22 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15:37:20","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":15171,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8182015/v1/9186905ffa277c8970457911.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Problematic Internet Use and Video Gaming : Are They Emerging Risk Factors for Elevated Blood Pressure?","fulltext":[{"header":"What is Known","content":"\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eSedentary screen-based behaviors\u0026mdash;particularly excessive internet use and video gaming\u0026mdash;are linked to pediatric obesity and elevated blood pressure.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMost prior research has relied on office blood pressure measurements rather than ambulatory blood pressure monitoring (ABPM).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eWhat is New\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eThis is the first study to investigate how problematic internet use and video gaming affect ABPM parameters in adolescents.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHigher internet addiction scores were associated with elevated daytime systolic and maximum systolic blood pressure. These associations persisted even in non-obese adolescents, indicating an obesity-independent relationship.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eHypertension is an increasingly important public health problem among children and adolescents [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The rising prevalence of pediatric hypertension has been strongly linked to the global childhood obesity epidemic [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Numerous population-based studies have demonstrated that overweight and obese children have significantly higher blood pressure levels compared with their normal-weight peers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eUnhealthy lifestyle patterns\u0026mdash;including fast food consumption, insufficient sleep, smoking, and sedentary behaviors\u0026mdash;have been identified as major contributors to obesity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. More recently, emerging evidence suggests that excessive screen exposure, prolonged internet use, and video gaming may not only promote obesity by reducing physical activity, but may also be independently associated with elevated blood pressure in youth [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although the underlying mechanisms are not fully understood, proposed pathways include sleep disturbance, inreased sympathetic nervous system activity, and sustained cognitive arousal during screen-based activities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, most previous studies have relied on office-based or casual blood pressure measurements, which are less reliable than ambulatory blood pressure monitoring (ABPM) in detecting true hypertension and circadian blood pressure patterns. In this study, we aimed to evaluate the effects of problematic internet use and video gaming on ambulatory blood pressure parameters in adolescents aged 12\u0026ndash;18 years. To our knowledge, this is the first study in the English literature to investigate the association between these screen-based behaviors and ABPM findings in this age group.\u003c/p\u003e"},{"header":"2. Patients and Methods","content":"\u003cp\u003eThis prospective observational study was carried out in our pediatric nephrology outpatient clinic between 1 September 2021 and 31 December 2021. Children who were referred for evaluation of hypertension and aged between 12 and 18 years were included in the study. Patients with known hypertension or patients who had chronic kidney diseases, chronic cardiac diseases, and endocrinologic diseases were excluded to rule out secondary hypertension. Additionally, children diagnosed with any psychiatric diseases were not included.\u003c/p\u003e\u003cp\u003eAge, gender, family history, anthropometric measurements, body mass index (BMI), and physical examination findings were recorded. BMI values were calculated as kg/m\u003csup\u003e2\u003c/sup\u003e and classified according to age- and sex-specific BMI z-scores based on World Health Organization (WHO) growth standards. A BMI z-score \u0026lt; -2 SD was defined as underweight, values between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;1 as normal; \u0026gt;+1 SD to +\u0026thinsp;2 SD were classified as \u003cem\u003eoverweight\u003c/em\u003e, and values\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;2 SD were considered \u003cem\u003eobesity\u003c/em\u003e [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1.Laboratory Investigations and Imaging Techniques\u003c/h2\u003e\u003cp\u003eUrine analysis, renal function tests (serum, blood urea nitrogen, creatinine, glomerular filtration rate according to the Schwartz formula), uric acid, electrolytes, venous blood gas, cholesterol, triglyceride, renin and aldosterone levels, thyroid function tests, urinary ultrasound and renal artery Doppler ultrasound were performed to detect the underlying etiology. Urine protein excretion, echocardiography and ophthalmological examination were carried out to identify end organ damage.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2.Blood Pressure Measurements:\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e\u003cb\u003e2.2.1.Office Blood Pressure Measurements\u003c/b\u003e:\u003c/h2\u003e\u003cp\u003eBlood pressure was measured on three different occasions with an appropriate sphygmomanometer, and hypertension was defined as blood pressure greater than the 95th percentile for age, gender and height in children under the age of 13 years old and as \u0026gt;\u0026thinsp;130/80 mmHg in children\u0026thinsp;\u0026ge;\u0026thinsp;13 years of age, according to the American Academy of Pediatrics 2017 hypertension guideline [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2.Ambulatory Blood Pressure Monitoring:\u003c/h2\u003e\u003cp\u003eAll children underwent ambulatory blood pressure monitoring to confirm the diagnosis of hypertension with \u0026ldquo;Spacelabs Healthcare On Trak Ambulatory Blood Pressure Monitor\u0026rdquo;. To avoid artifacts, a nondominant arm was used for monitoring. An appropriate cuff size was selected according to the hypertension guidelines [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Blood pressure was recorded every twenty minutes for the awake period and for 30 minutes for the sleep period.\u003c/p\u003e\u003cp\u003eChildren were allowed to continue their daily activities during monitorization, including attending school, but heavy exercise, such as sports participation, was abstained. A diary to record wake and sleep periods, daily activities, and any medications during the 24-h period was requested from all of the participants. Valid measurements above 90% were considered significant. Incorrect and insufficient measurements were excluded from the study.\u003c/p\u003e\u003cp\u003eOverall mean systolic and diastolic blood pressure (SBP/DBP); daytime and nighttime mean SBP and DBP; and daytime and nighttime SBP and DBP loads were evaluated. Maximum daytime and nighttime SBP and DBP measurements and systolic and diastolic dipping parameters were determined.\u003c/p\u003e\u003cp\u003eBased on ambulatory blood pressure monitoring data, patients were divided into four categories as follows: i) normotensive; mean SBP/DBP\u0026thinsp;\u0026lt;\u0026thinsp;95th percentile and blood pressure loads\u0026thinsp;\u0026lt;\u0026thinsp;25%; ii) prehypertensive; mean SBP/DBP\u0026thinsp;\u0026lt;\u0026thinsp;95th percentile and BP loads\u0026thinsp;\u0026ge;\u0026thinsp;25%; iii) hypertensive; mean SBP/DBP\u0026thinsp;\u0026gt;\u0026thinsp;95th percentile and BP loads between 25 and 50%; and iv) severe hypertensive; mean SBP/DBP\u0026thinsp;\u0026gt;\u0026thinsp;95th and BP loads\u0026thinsp;\u0026gt;\u0026thinsp;50% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3.Young Internet Addiction Short Form (YIA-SF)\u003c/h2\u003e\u003cp\u003eTo evaluate problematic internet use, the Young Internet Addiction Short Form was administered to all participants.\u003c/p\u003e\u003cp\u003eThe YIA-SF consists of twelve questions evaluating the frequency and duration of internet use of the patients and the effect of the internet on daily social life and school life. It is a 5-point Likert type scale and is scored as 1\u0026thinsp;=\u0026thinsp;never to 5\u0026thinsp;=\u0026thinsp;always. There is no reverse-scored item in the scale. The minimum scale score is 12, the total scale score is 60, and higher scores indicate an increased risk of internet addiction [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this study, we used the Turkish version of the test, which was generated and validated by Kutlu et al [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The validation of the test was performed among adolescents and university students.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4.Internet Gaming Disorder-Scale Short Form (IGDS9-SF):\u003c/h2\u003e\u003cp\u003eTo determine the effects of video gaming, the Internet Gaming Disorder Scale Short Form (IGDS9-SF) was administered to all participants.\u003c/p\u003e\u003cp\u003eThis scale was developed by Pontes HM and Griffiths MD, and the first Turkish version was developed and applied by G\u0026uuml;n\u0026uuml;\u0026ccedil; S and Kayri M in 2017 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In 2018, Evren et al. demonstrated the validity and reliability of this scale among young Turkish adults [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The scale consists of nine questions about the time spent on computer game activities and electronic devices such as game consoles, mobile phones, tablets, and all kinds of games that can be played both on the Internet and without being connected to the Internet. The scale consists of nine items. Each item is rated on a 5-point Likert scale ranging from 1\u0026thinsp;=\u0026thinsp;never to 5\u0026thinsp;=\u0026thinsp;very often. The maximum and minimum scores of the IGDS9-SF are 9 and 45, respectively. Higher scores indicate higher levels of problematic internet gaming.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.5.Ethical Issues:\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003e was obtained from the Research and Ethics Committee of Ankara Bilkent City Hospital (date: 02.12.2020 no: E2-20-14). Detailed information was given, and written informed consent was obtained from both children and parents who volunteered to participate in this study.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Statistical Analysis","content":"\u003cp\u003eStatistical analyses were performed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Normality of continuous variables was assessed with the Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests, supported by histogram and Q\u0026ndash;Q plot inspection. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (range), and categorical variables as frequencies and percentages.\u003c/p\u003e\u003cp\u003eBetween-group comparisons were conducted using the Student\u0026rsquo;s t-test or Mann\u0026ndash;Whitney U test for continuous variables and the chi-square or Fisher\u0026rsquo;s exact test for categorical variables. For comparisons across more than two groups, one-way ANOVA or the Kruskal\u0026ndash;Wallis test was applied, followed by Bonferroni-adjusted post-hoc analyses when appropriate. Correlations between behavioral scores and blood pressure parameters were evaluated using Pearson or Spearman coefficients.\u003c/p\u003e\u003cp\u003eTo determine independent predictors of ambulatory blood pressure category, an ordinal regression model (PLUM, logit link) including age, gender, BMI category, YIA-SF, and IGDS9-SF scores was performed. Additionally, two multiple linear regression models were used to identify predictors of maximum and mean daytime systolic blood pressure, with age, gender, and BMI group entered as independent variables.\u003c/p\u003e\u003cp\u003eA post-hoc power analysis (G*Power 3.1) indicated adequate statistical power (1\u0026thinsp;\u0026minus;\u0026thinsp;β\u0026thinsp;=\u0026thinsp;0.84) for detecting a medium effect size in the regression models. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Demographic and Clinical Characteristics\u003c/h2\u003e\u003cp\u003eA total of 107 adolescents were included in the study, of whom 40 (37.4%) were girls and 67 (62.6%) were boys, with a mean age of 14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 years. Based on BMI classification, 29 (27.1%) were normal weight, 32 (29.9%) overweight, and 46 (43.0%) obese (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics of the study population (n\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40 (37.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67 (62.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (27.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32 (29.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46 (43.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormotensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39 (36.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrehypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (17.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49 (45.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian (min\u0026ndash;max)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.0 (12.0\u0026ndash;17.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eBMI :\u003c/em\u003e Body Mass Index\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBP:\u003c/em\u003e Blood Pressure\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSD:\u003c/em\u003e Standart Deviation\u003c/p\u003e\u003cp\u003eAll adolescents diagnosed with hypertension on ABPM underwent laboratory and imaging evaluations, including thyroid function tests, renin\u0026ndash;aldosterone levels, and renal Doppler ultrasonography. No secondary causes of hypertension were identified, and all cases were classified as primary hypertension. Left ventricular hypertrophy was detected in 23 hypertensive individuals, while ophthalmologic evaluations were normal in all participants.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Ambulatory Blood Pressure Categories\u003c/h2\u003e\u003cp\u003eAccording to ABPM results, 39 participants (36.4%) were normotensive, 19 (17.8%) prehypertensive, and 49 (45.8%) hypertensive. None met the criteria for severe hypertension (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Relationship of BP Categories with Age, Gender, and BMI\u003c/h2\u003e\u003cp\u003eGender distribution was similar across BP categories (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; χ\u0026sup2; = 0.080, p\u0026thinsp;=\u0026thinsp;0.961).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGender distribution across blood pressure categories\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal (n)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormotensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14 (35.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (64.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrehypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19 (38.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30 (61.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40 (37.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67 (62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eChi-square test: χ\u0026sup2; = 0.080, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.961 BP: Blood pressure\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAge differed significantly among the groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Kruskal\u0026ndash;Wallis H\u0026thinsp;=\u0026thinsp;8.04, p\u0026thinsp;=\u0026thinsp;0.018), while BMI categories were not significantly associated with BP status (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; χ\u0026sup2; = 3.891, p\u0026thinsp;=\u0026thinsp;0.421).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge comparison across blood pressure categories\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (years)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian (years)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRange (years)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormotensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e15.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u0026ndash;17.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrehypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e13.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u0026ndash;17.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e15.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u0026ndash;17.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eKruskal\u0026ndash;Wallis H\u0026thinsp;=\u0026thinsp;8.04, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.018 BP: Blood pressure \u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBMI distribution across blood pressure categories\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal weight, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverweight, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eObese, n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormotensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (41.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15 (38.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrehypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (47.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15 (30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (24.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22 (44.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eChi-square test: χ\u0026sup2; = 3.891, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;=\u0026thinsp;0.421\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eBMI:\u003c/em\u003e Body Mass Index\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBP\u003c/em\u003e: Blood pressure\u0026nbsp;\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Internet Use and Gaming Scores Within Demographic Subgroups\u003c/h2\u003e\u003cp\u003eYIA-SF scores did not differ significantly between boys and girls (p\u0026thinsp;=\u0026thinsp;0.33), whereas IGDS9-SF scores were higher in boys (p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e\u003cp\u003eNeither BMI category nor weight status was associated with YIA-SF or IGDS9-SF scores (p\u0026thinsp;=\u0026thinsp;0.21 and p\u0026thinsp;=\u0026thinsp;0.078, respectively).\u003c/p\u003e\u003cp\u003eA weak negative correlation was observed between age and YIA-SF scores (r = \u0026minus;\u0026thinsp;0.200, p\u0026thinsp;=\u0026thinsp;0.039). IGDS9-SF scores showed a similar, though non-significant, trend (p\u0026thinsp;=\u0026thinsp;0.061).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Behavioral Scores and Blood Pressure Categories\u003c/h2\u003e\u003cp\u003eMean YIA-SF and IGDS9-SF scores did not differ significantly across normotensive, prehypertensive, and hypertensive groups (p\u0026thinsp;=\u0026thinsp;0.33 and p\u0026thinsp;=\u0026thinsp;0.64, respectively).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Correlation Between Behavioral Scores and ABPM Parameters\u003c/h2\u003e\u003cp\u003eHigher YIA-SF and IGDS9-SF scores were associated with higher mean systolic BP, although these correlations did not reach statistical significance (YIA-SF: r\u0026thinsp;=\u0026thinsp;0.168, p\u0026thinsp;=\u0026thinsp;0.084; IGDS9-SF: r\u0026thinsp;=\u0026thinsp;0.025, p\u0026thinsp;=\u0026thinsp;0.80). No significant correlations were found between behavioral scores and diastolic BP (Supplementary Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eA significant positive correlation was detected between YIA-SF scores and mean daytime systolic BP (r\u0026thinsp;=\u0026thinsp;0.191, p\u0026thinsp;=\u0026thinsp;0.049). Nighttime systolic and daytime/nighttime diastolic pressures increased with higher YIA-SF scores, though not significantly. IGDS9-SF scores were not correlated with any ABPM parameter (Supplementary Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eWhen evaluated according to blood pressure loads, there were no significant associations between behavioral scores and systolic or diastolic BP loads (Supplementary Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003eThe only significant relationship was detected among YIA-SF scores and maximum daytime systolic BP load (r\u0026thinsp;=\u0026thinsp;0.280, p\u0026thinsp;=\u0026thinsp;0.021) (Supplementary Table\u0026nbsp;3).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.7. Subgroup Analysis: Obese vs. Non-Obese Participants\u003c/h2\u003e\u003cp\u003eAmong non-obese adolescents, higher YIA-SF scores were significantly associated with higher maximum systolic BP (r\u0026thinsp;=\u0026thinsp;0.280, p\u0026thinsp;=\u0026thinsp;0.019). This association was not observed among obese participants, suggesting a possible modifying role of BMI status.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.8. Ordinal Regression Analysis\u003c/h2\u003e\u003cp\u003eOrdinal regression analysis was performed to determine whether YIA-SF and IGDS9-SF scores independently predicted BP category after adjusting for age, gender, and BMI. The overall model was not significant (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; χ\u0026sup2; = 16.466, p\u0026thinsp;=\u0026thinsp;0.087).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOrdinal regression analysis of predictors of blood pressure categories\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWald χ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP\u0026thinsp;=\u0026thinsp;Normotensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e226.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e601.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.707\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP\u0026thinsp;=\u0026thinsp;Prehypertensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e416.602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e915.296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.649\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43.676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.708\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYIA-SF score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.627\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.696\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIGDS9-SF score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.481\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.787\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender (male)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37.772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e121.762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (normal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.731\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (overweight)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-184.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e357.432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.606\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (scale factor)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e*0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eModel fit: χ\u0026sup2; = 16.466, df\u0026thinsp;=\u0026thinsp;10, p\u0026thinsp;=\u0026thinsp;0.087. Only age was significantly associated with BP category.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eYIA-SF\u003c/em\u003e : Young Internet Addiction Short Form\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eIGDS9:\u003c/em\u003e Internet Gaming Disorder-Scale Short Form\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBMI\u003c/em\u003e: Body Mass Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBP:\u003c/em\u003e Blood pressure\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 6A. Linear regression model for maximum daytime systolic blood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e123.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e10.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e11.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eGender (male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e5.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBMI group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel summary: R = 0.361; R\u0026sup2; = 0.131; F(3,103) = 5.159; p = 0.002.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6B. Linear regression model for average daytime systolic blood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e105.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e14.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eGender (male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBMI group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel summary: R = 0.334; R\u0026sup2; = 0.112; F(3,103) = 4.319; p = 0.007.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBMI\u003c/em\u003e: Body Mass Index\u003c/p\u003e\u003cp\u003eAmong all predictors, only age was significantly associated with BP category (β\u0026thinsp;=\u0026thinsp;0.389, p\u0026thinsp;=\u0026thinsp;0.002). Neither YIA-SF nor IGDS9-SF scores predicted BP status (p\u0026thinsp;=\u0026thinsp;0.696 and p\u0026thinsp;=\u0026thinsp;0.787).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.9. Linear Regression Analyses for Systolic BP\u003c/h2\u003e\u003cp\u003eTwo multiple regression models were constructed for maximum and mean daytime systolic BP (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003eB):\u003c/p\u003e\u003cp\u003eMaximum daytime SBP:\u003c/p\u003e\u003cp\u003eThe model was significant (F\u0026thinsp;=\u0026thinsp;5.159, p\u0026thinsp;=\u0026thinsp;0.002; R\u0026sup2; = 0.131). Male gender (p\u0026thinsp;=\u0026thinsp;0.027) and BMI group (p\u0026thinsp;=\u0026thinsp;0.005) were independent predictors, while age was not.\u003c/p\u003e\u003cp\u003eMean daytime SBP:\u003c/p\u003e\u003cp\u003eThe model was significant (F\u0026thinsp;=\u0026thinsp;4.319, p\u0026thinsp;=\u0026thinsp;0.007; R\u0026sup2; = 0.112). Age (p\u0026thinsp;=\u0026thinsp;0.040) and BMI group (p\u0026thinsp;=\u0026thinsp;0.045) were significant predictors; male gender showed borderline significance (p\u0026thinsp;=\u0026thinsp;0.053).\u003c/p\u003e\u003cp\u003eAcross both models, neither YIA-SF nor IGDS9-SF scores were independent predictors of maximum and mean daytime systolic BP.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eIn this study, we investigated the relationship between problematic internet use, video gaming behaviors, and ambulatory blood pressure parameters in adolescents. Although both YIA-SF and IGDS9-SF scores showed a trend toward higher systolic blood pressure, these associations did not reach statistical significance in general correlation analyses. However, we found that YIA-SF scores were positively and significantly associated with both mean daytime systolic blood pressure and maximum daytime systolic blood pressure. Importantly, this relationship persisted among non-obese adolescents, suggesting that problematic internet use may influence systolic blood pressure independently of obesity.\u003c/p\u003e\u003cp\u003eProblematic internet use is increasingly recognized as a growing public health concern among adolescents, with documented associations with psychological, behavioral, and cardiometabolic risk factors [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Several studies have highlighted that excessive screen exposure, including prolonged internet use, may contribute to increased blood pressure, obesity, depression, anxiety, and unfavorable lipid profiles [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Cassidy-Bushrow et al. demonstrated that among 331 adolescents, time spent on the internet was positively correlated with blood pressure\u0026mdash;particularly diastolic pressure\u0026mdash;independent of BMI [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These findings align with our observation that internet use may exert physiological effects beyond weight-related mechanisms.\u003c/p\u003e\u003cp\u003eThe cardiovascular impact of video gaming has also been documented in the literature. Goldfield et al. reported that screen exposure, particularly video game playing, was independently associated with increased blood pressure and adverse lipid parameters in overweight and obese adolescents [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Similarly, Wang et al. observed acute increases in both systolic and diastolic blood pressure during video game play in younger boys [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In an interesting study by Siervo et al., authors evaluated the effect of violent video games on blood pressure [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The authors suggested that violent video games cause a high cardiac load, which is probably related to the activation of the stress response [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. They found that diastolic blood pressure increased progressively during violent video games, and they stated that ongoing increases in blood pressure may cause significant cardiac problems.Although our study did not evaluate game content, the existing literature emphasizes that video games\u0026mdash;especially competitive or violent content\u0026mdash;may activate sympathetic nervous system pathways, thereby increasing blood pressure [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs has been demonstrated in many studies to date, a sedentary lifestyle may be associated with obesity and consequently hypertension. Considering this well-known finding, we tried to evaluate the effects of internet addiction and video games on ABPM parameters independent of obesity. As mentioned above, Siervo et al demonstrated that video games can increase diastolic blood pressure, especially in nonobese young men [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].In the comprehensive study of Gopinath et al. conducted with 2353 school children with a mean age of 12.7 years, it was determined that screen exposure was significantly associated with blood pressure, independent of BMI and other factors [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In line with these observations, our subgroup analysis revealed that non-obese adolescents exhibited a significant association between YIA-SF scores and maximum daytime systolic blood pressure. This suggests that sympathetic activation, arousal, or stress responses during internet use may contribute to elevated systolic blood pressure independently of adiposity.\u003c/p\u003e\u003cp\u003eDespite these patterns, neither YIA-SF nor IGDS9-SF scores emerged as independent predictors of blood pressure categories in our adjusted ordinal regression model, in which only age remained significant. Additionally, in multivariate linear regression analyses, BMI group and male gender (for maximum SBP) or age (for mean SBP) were the only independent predictors of systolic blood pressure. These results indicate that while problematic internet use may be associated with certain systolic BP parameters, it does not independently predict hypertension category when demographic and anthropometric factors are simultaneously considered.\u003c/p\u003e\u003cp\u003eThe primary limitation of our study is the relatively small sample size, which may have limited the statistical power to detect weaker associations. Future studies with larger cohorts, objective measures of internet and gaming exposure, and longitudinal designs are needed to clarify the causal pathways linking digital behaviors to cardiovascular outcomes.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn this study, we demonstrated that problematic internet use and video gaming behaviors are associated with certain systolic ambulatory blood pressure parameters in adolescents. Although these behaviors were not independent predictors of hypertension category after adjusting for age, gender, and BMI, higher YIA-SF scores showed significant correlations with mean and maximum daytime systolic blood pressure, particularly among non-obese adolescents. These findings suggest that internet-related behavioral patterns may influence systolic blood pressure through mechanisms other than obesity, potentially involving heightened sympathetic activation or stress responses.\u003c/p\u003e\u003cp\u003eGiven the increasing prevalence of excessive screen exposure in adolescents, clinicians should routinely inquire about internet use and gaming habits when evaluating patients with elevated blood pressure. Even in the presence of normal office measurements, ambulatory blood pressure monitoring may be warranted in adolescents with prolonged internet use. Interventions aimed at reducing daily screen time and promoting healthier digital habits should be emphasized as part of lifestyle modification strategies.\u003c/p\u003e\u003cp\u003eFurther studies with larger sample sizes and longitudinal designs are needed to clarify the causal pathways linking internet use, gaming behaviors, and cardiovascular risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval :\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Research and Ethics Committee of Ankara City Hospital (date: 02.12.2020 no:E2-20-14).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e There is no funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eNone of the authors have any conflict of interest\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e \u003cem\u003eAll authors contributed to the study conception and design. Material preparation, data collection was performed by HY and Mİ. Data analysis was performed by PD. The first draft of the manuscript was written by HY and SG\u0026Ouml; .All authors commented on previous versions of the manuscript. EC cirtically reviewed the manuscript. All authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e This manuscript has no associated data\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDin-Dzietham R, Liu Y, Bielo MV, Shamsa F (2007) High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation 116:1488\u0026ndash;1496. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCULATIONAHA.106.683243\u003c/span\u003e\u003cspan address=\"10.1161/CIRCULATIONAHA.106.683243\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFalkner B (2017) Monitoring and management of hypertension with obesity in adolescents. Integr Blood Press Control 10:33\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/IBPC.S125094\u003c/span\u003e\u003cspan address=\"10.2147/IBPC.S125094\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRao G, Diagnosis (2016) Epidemiology, and Management of Hypertension in Children. Pediatrics 138(2):e20153616. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1542/peds.2015-3616\u003c/span\u003e\u003cspan address=\"10.1542/peds.2015-3616\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSorof JM, Lai D, Turner J, Poffenbarger T, Portman RJ (2004) Overweight, ethnicity, and the prevalence of hypertension in school-aged children. Pediatrics 113:475\u0026ndash;482. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1542/peds.113.3.475\u003c/span\u003e\u003cspan address=\"10.1542/peds.113.3.475\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKelishadi R, Poursafa P, Keramatian K (2011) Overweight, air and noise pollution: Universal risk factors for pediatric prehypertension. J Res Med Sci 16:1234\u0026ndash;1250\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBurke V, Beilin LJ, Simmer K et al Predictors of body mass index and associations with cardiovascular risk factors in Australian children: a prospective cohort study (2005). Int J Obes (Lond) 29:15\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.ijo.0802750\u003c/span\u003e\u003cspan address=\"10.1038/sj.ijo.0802750\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLissak G (2018) Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environ Res 164:149\u0026ndash;157. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envres.2018.01.015\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2018.01.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGopinath B, Baur LA, Hardy LL et al (2012) Relationship between a range of sedentary behaviors and blood pressure during early adolescence. J Hum Hypertens 26:350\u0026ndash;356. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/jhh.2011.40\u003c/span\u003e\u003cspan address=\"10.1038/jhh.2011.40\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiervo M, Sabatini S, Fewtrell MS, Wells JC (2013) Acute effects of violent video-game playing on blood pressure and appetite perception in normal-weight young men: a randomized controlled trial. Eur J Clin Nutr 67:1322\u0026ndash;1324. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ejcn.2013.180\u003c/span\u003e\u003cspan address=\"10.1038/ejcn.2013.180\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang X, Perry AC (2006) Metabolic and physiologic responses to video game play in 7- to 10-year-old boys. Arch Pediatr Adolesc Med 160:411\u0026ndash;415. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archpedi.160.4.411\u003c/span\u003e\u003cspan address=\"10.1001/archpedi.160.4.411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCassidy-Bushrow AE, Johnson DA, Peters RM, Burmeister C, Joseph CL (2015) Time Spent on the Internet and Adolescent Blood Pressure. J Sch Nurs 31:374\u0026ndash;384. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1059840514556772\u003c/span\u003e\u003cspan address=\"10.1177/1059840514556772\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBener A, Bhugra D (2013) Lifestyle and depressive risk factors associated with problematic internet use in adolescents in an Arabian Gulf culture. J Addict Med 7:236\u0026ndash;242. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ADM.0b013e3182926b1f\u003c/span\u003e\u003cspan address=\"10.1097/ADM.0b013e3182926b1f\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaput JP, Visby T, Nyby S Astrup A, Sj\u0026ouml;din A et al (2011) Video game playing increases food intake in adolescents: a randomized crossover study. Am J Clin Nutr 93:1196\u0026thinsp;\u0026ndash;\u0026thinsp;203. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3945/ajcn.110.008680\u003c/span\u003e\u003cspan address=\"10.3945/ajcn.110.008680\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAronne LJ (2002) Classification of obesity and assessment of obesity-related health risks. Obes Res 10(Suppl 2):105S\u0026ndash;115S. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/oby.2002.203\u003c/span\u003e\u003cspan address=\"10.1038/oby.2002.203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlynn JT, Kaelber DC, Baker-Smith CM, SUBCOMMITTEE ON SCREENING AND MANAGEMENT OF HIGH BLOOD PRESSURE IN CHILDREN et al (2017) Clinical Practice Guideline for Screening and Management of High Blood Pressure in Children and Adolescents. Pediatrics 140(3):e20171904. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1542/peds.2017-1904\u003c/span\u003e\u003cspan address=\"10.1542/peds.2017-1904\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlynn JT, Daniels SR, Hayman LL, Obesity in Youth Committee of the Council on Cardiovascular Disease in the Young (2014) American Heart Association Atherosclerosis, Hypertension and Update: ambulatory blood pressure monitoring in children and adolescents: a scientific statement from the American Heart Association. Hypertension 63:1116\u0026ndash;1135. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/HYP.0000000000000007\u003c/span\u003e\u003cspan address=\"10.1161/HYP.0000000000000007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePawlikowski M, Altst\u0026ouml;tter-Gleich C, Brand M (2013) Validation and psychometric properties of a short version of Young's Internet Addiction Test. Comput Hum Behav 29:1212\u0026ndash;1223\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKutlu M, Savcı M, Demir Y, Aysan F (2016) Turkish adaptation of Young\u0026rsquo;s Internet Addiction Test-Short Form: a reliability and validity study on university students and adolescents. Anatol J Psychiatry 17:69\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5455/apd.190501\u003c/span\u003e\u003cspan address=\"10.5455/apd.190501\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePontes HM, Griffiths MD (2016) Portuguese Validation of the Internet Gaming Disorder Scale-Short-Form. Cyberpsychol Behav Soc Netw 19:288\u0026ndash;293. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/cyber.2015.0605\u003c/span\u003e\u003cspan address=\"10.1089/cyber.2015.0605\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026uuml;n\u0026uuml;\u0026ccedil; S, Kayri M (2010) The profıle of internet dependency in Turkey and development of internet addiction scale: study of validity \u0026amp; reliability. H. U. J Educ 39:220\u0026ndash;232\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEvren C, Dalbudak E, Topcu M, Kutlu N, Evren B, Pontes HM (2018) Psychometric validation of the Turkish nine-item Internet Gaming Disorder Scale-Short Form (IGDS9-SF). Psychiatry Res 265:349\u0026ndash;354. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psychres.2018.05.002\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2018.05.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKir\u0026aacute;ly O, Griffiths MD, Urb\u0026aacute;n R et al (2014) Problematic internet use and problematic online gaming are not the same: findings from a large nationally representative adolescent sample. Cyberpsychol Behav Soc Netw 17:749\u0026ndash;754. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/cyber.2014.0475\u003c/span\u003e\u003cspan address=\"10.1089/cyber.2014.0475\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarshall SJ, Biddle SJ, Gorely T, Cameron N, Murdey I (2004) Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis. Int J Obes Relat Metab Disord 28:1238\u0026ndash;1246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.ijo.0802706\u003c/span\u003e\u003cspan address=\"10.1038/sj.ijo.0802706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoldfield GS, Kenny GP, Hadjiyannakis S et al (2011) Video game playing is independently associated with blood pressure and lipids in overweight and obese adolescents. PLoS ONE 6(11):e26643. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0026643\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0026643\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Adolescent, Ambulatory Blood Pressure Monitoring, Childhood Hypertension, Problematic Internet Use, Video Game","lastPublishedDoi":"10.21203/rs.3.rs-8182015/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8182015/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eHypertension is an increasingly important health concern among children and adolescents. Beyond traditional risk factors such as obesity, sedentary behaviors including prolonged internet use and video gaming may contribute to elevated blood pressure. This study aimed to investigate the association between problematic internet use, video gaming, and ambulatory blood pressure parameters in adolescents.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eThis prospective study included adolescents aged 12\u0026ndash;18 years who were referred to a pediatric nephrology outpatient clinic for hypertension evaluation. Demographic, clinical, and laboratory data were obtained from medical records. Ambulatory blood pressure monitoring (ABPM) was performed to confirm hypertension. Internet use and gaming behaviors were assessed using the Young Internet Addiction Scale (YIA-SF) and the Internet Gaming Disorder Scale (IGDS9-SF). Scale scores were compared with ABPM parameters.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eA total of 107 adolescents (40 girls, 67 boys) with a mean age of 14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 years were included. According to ABPM findings, 39.4% were normotensive, 17.8% prehypertensive, and 45.8% hypertensive. Although statistical significance was not reached, increasing internet addiction scores were associated with higher overall mean systolic blood pressure. Higher YIA-SF scores were particularly related to increased maximum and mean daytime systolic blood pressure.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003eExcessive internet use and video gaming may contribute to elevated blood pressure in adolescents, independent of obesity. Problematic internet behavior should therefore be considered in the clinical evaluation of hypertensive children and adolescents.\u003c/p\u003e","manuscriptTitle":"Problematic Internet Use and Video Gaming : Are They Emerging Risk Factors for Elevated Blood Pressure?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 15:37:15","doi":"10.21203/rs.3.rs-8182015/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-15T18:08:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T16:07:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-27T09:34:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238170478046931263462537038512088615866","date":"2025-11-26T20:07:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72953939293368165355393672011937021672","date":"2025-11-26T13:45:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-26T11:50:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-26T11:49:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-26T07:44:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2025-11-22T17:55:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cca2a03a-5c67-4f81-b023-f4a4c4f877e2","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:02:15+00:00","versionOfRecord":{"articleIdentity":"rs-8182015","link":"https://doi.org/10.1007/s00431-026-06817-6","journal":{"identity":"european-journal-of-pediatrics","isVorOnly":false,"title":"European Journal of Pediatrics"},"publishedOn":"2026-03-03 15:58:46","publishedOnDateReadable":"March 3rd, 2026"},"versionCreatedAt":"2025-12-01 15:37:15","video":"","vorDoi":"10.1007/s00431-026-06817-6","vorDoiUrl":"https://doi.org/10.1007/s00431-026-06817-6","workflowStages":[]},"version":"v1","identity":"rs-8182015","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8182015","identity":"rs-8182015","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}