The Paradox of Performance: Hypertension Among Young Athletes — A Systematic Review and Meta-Analysis of Risks behind Fitness

The Paradox of Performance: Hypertension Among Young Athletes — A Systematic Review and Meta-Analysis of Risks behind Fitness | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review The Paradox of Performance: Hypertension Among Young Athletes — A Systematic Review and Meta-Analysis of Risks behind Fitness Binbin Hu, Omer Alam, Inshal Jawed, Hafiza Qurat ul Ain, Kainat Zahid, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7149750/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Hypertension (HTN) is a growing health issue worldwide, with the global burden doubling between 1990 and 2019. Although the disease has traditionally been linked to older people, it is increasingly being discovered in young athletes, which brings into question the cardiovascular health of this group. Objective To assess and establish the incidence rate of hypertension among young competitive sportsmen in different courses taking part in various sporting activities via systematic review and meta-analysis. Methods A PRISMA systematic review was conducted on PubMed, Scopus, and Google Scholar through May 2025 to determine prevalence of hypertension among young athletes (aged < 50 years). A random-effects model was used in R-Studio (version 4.5.0) with I 2 statistic to measure heterogeneity. An updated Hoy et al. risk-of-bias tool was used in assessing the study quality. Gender, country, age group (20 years), and the value of the hypertension cut-off were used to perform subgroup analyses. Results A total of 26 studies were conducted in 12 countries, involving 54,152 athletes as part of the study. The prevalence of hypertension in young athletes was 9% (95% CI: 5%-12%, P = 0, I 2 = 99%). According to the gender analysis, it was identified that 10% of the studies were male-only, 12% were female-only, and 8% were mixed-gender based. The prevalence in the country was widely different: USA (13%), Italy (2%), and Norway (7%). Age-stratified data revealed a prevalence of 12% in athletes under 20 years of age and 4% in those 20 years of age and older. The highest prevalence was observed among NFL players (11%), followed by soccer (10%) and mixed sports (9%). Various definitions of hypertension yielded different prevalence rates: >95th percentile (9 percent), > 130/80 mmHg (20 percent), and > 140/90 mmHg (8 percent), as well as > 140/90 mmHg or taking antihypertensive medications (8 percent). Conclusion The prevalence of high blood pressure in young athletes differs according to gender, geography, type of sport and the definition of diagnosis. Female athletes, US athletes, and NFL players are most prevalent, and need to be screened and intervened more effectively. Clinical trial number: Not Applicable. Hypertension Young athletes Meta-analysis Cardiovascular health Sports medicine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction High blood pressure (hypertension) is one of the significant risk factors of cardiovascular diseases that are preventable, and it causes a vast number of morbidities and deaths at all ages. The rate of hypertension globally has experienced unprecedented growth, as the number of its victims has doubled between 1990 and 2019 due to not only the population growth, but also to a rise in the prevalence rates ( 1 ). It is generally understood that the epidemic is traditionally linked to the population over 60 and sedentary individuals. Still, we have seen some worrying signs of the trend shifting toward younger age groups, including competitive sports. Athletic individuals have conventionally been regarded as less prone to cardiovascular diseases, including hypertension, due to their exposure to frequent physical exercise, a high degree of cardiovascular fitness, and generally healthier lifestyle habits. These, however, have been refuted in a recent study, which indicates that the number of young athletes who are becoming hypertensive could be very high in such a manner that requires serious clinical intervention ( 2 , 3 ). The paradox has led to a rigorous examination of cardiovascular status among athletic groups, particularly regarding the risk of cardiovascular mishap during intense physical activity. The fact that hypertension is common among young athletes is of concern, mainly due to several reasons. Sportsmen experience severe physical exercise and participate in strenuous sporting activities, which exert a heavy cardiovascular strain. Hypertension that is not diagnosed or not well treated among the population may predispose to undesired cardiovascular events, such as sudden cardiac death, during active engagement in sporting activities ( 4 ). Also, the detection of hypertension in young athletic persons can be a sign of early-onset essential hypertension or secondary hypertension based on pre-existing diseases and pathologies that must then be managed and assessed accordingly ( 5 ). Moreover, the notable physiological changes associated with physical training, such as increased cardiac output, stroke volume, and altered vascular responses, may become a complication during the diagnosis and treatment of hypertension in the general population ( 6 ). The pathological cardiovascular adaptations and physiological ones in training are a clinical issue that requires consideration of the specifics of a sport, the training load, and the individual features of an athlete. The dissimilarity in definitions of hypertension, measurement procedures, and study design has led to differences in estimates of prevalence, which are presented in the literature. Some studies use traditional adult hypertension levels (140/90 mmHg). In contrast, others employ age-adjusted, sex-adjusted, and height-adjusted percentiles in younger athletes, or the newer rating by the American Heart Association (130/80 mmHg) ( 7 , 8 ). The slight inconsistency in diagnostic criteria has a significant influence on the estimation of prevalence, making the existing literature more challenging to understand. There are also sport-related determinants of hypertension prevalence in young athletes. Contact sports, especially American football, have been reported to have higher incidences of hypertension, which could be due to the body mass index, high muscle mass, and tailored training requirements of the sport ( 9 , 10 ). On the other hand, there may be other profiles of cardiovascular risk associated with endurance sports, such as vascular risk and cardiovascular efficiency ( 11 ). There is also the complexity of geography and demographics that add to the study of hypertension prevalence in young athletes. Regional variations in the prevalence of hypertension can be attributed to differences in culture, including diet, training style, access to healthcare, and genetic factors ( 12 , 13 ). Besides, socioeconomic conditions (availability of healthcare and nutrition) could also influence athletic performance and cardiovascular outcomes. The practical ramifications of heart diseases among young athletes in terms of the clinical implications of hypertension may be higher than their direct cardiovascular risk. Management and early detection of hypertension among the population can eliminate long-term cardiovascular effects such as coronary artery disease, stroke, as well as heart failure, among others ( 14 ). One of the peculiarities of managing hypertensive young athletes is the established balance between minimizing cardiovascular risk and preserving sports results. There are significant differences in the pre-participation screening procedures followed by various sporting organizations and geographical locations. Some organizations conduct thorough cardiovascular screenings that involve measuring blood pressure, while others do this on a symptom-based mode or through minimal cardiovascular screening ( 6 , 15 ). Evidence-based knowledge on the prevalence and risk factors of hypertension in athletic populations is critical for optimizing screening protocols among young athletes. Due to the atypical and varied prevalence rates reported in the literature, variations in study methodology, and the widespread use of different populations, an extensive systematic review with meta-analytical statistics is necessary for estimating the prevalence rates of hypertension among young athletes. This analysis would inform clinical practice, screening procedures, and community health programs tailored to the specific population. Hence, the main aim of the systematic review and meta-analysis is to determine the combined prevalence of hypertension in young competitive athletes and to identify the factors related to the increased risk of hypertension in this population. The secondary goals are to investigate whether gender, type of sport, geographic region, age, and diagnostic criteria have any impact on the estimation of hypertension prevalence. Methods Protocol and Registration The systematic review and meta-analysis were conducted according to the guidance for reporting systematic reviews and meta-analyses (PRISMA) ( 16 ). The protocol development employed an a priori method to reduce bias, involving a systematic review of the literature and data analysis. This article describes the protocol that was registered at the International Prospective Register of Systematic Reviews (PROSPERO) with the ID: CRD420251101684. Search Strategy A thorough literature review was conducted in several electronic sources, including PubMed, Scopus, and Google Scholar, on studies published as of May 15, 2025. A combination of MeSH terms and keywords was used in the search strategy, focusing on hypertension, blood pressure, athletes, and sports participation. Those search keys were: (("hypertension" OR high blood pressure OR elevated blood pressure OR blood pressure) AND (athletes OR sports OR competitive sports OR athletic participation OR sports medicine) AND (prevalence OR incidence OR epidemiology OR cross-sectional). The search terms were combined using Boolean operators, and the lists of reference studies from the already included articles were manually scanned to identify other relevant publications. Inclusion and Exclusion Criteria Studies were included when they fulfilled the following criteria: ( 1 ) Observational studies (cross-sectional, cohort, or case-control) that provided data on the prevalence of hypertension in athletes. ( 2 ) The study population consists of competitive athletes under 50 years old. ( 3 ) A study that provided clear definition of hypertension. ( 4 ) The studies that provided adequate data for prevalence calculation. ( 5 ) Studies that are published in English language. Exclusion criteria included: ( 1 ) Studies involving among Paralympic athletes because their medical conditions may act as confounders. ( 2 ) Studies that included ex-athletes or retired sportsmen. ( 3 ) Studies specifically examining at the athletes with a concussion or other neurological problems. ( 4 ) Case reports, reviews, or non-original research. ( 5 ) Studies that do not make a clear definition of hypertension. ( 6 ) Duplicate publications or replication of the study/population. Study Selection The identification of studies was followed by screening of studies separately by two independent reviewers based on titles and abstracts. The potentially relevant studies were then read in full text, after which they were considered for inclusion or exclusion. An agreement with the reviewer was reached through discussion or consultation. Data Extraction Two reviewers independently extracted data using a standardized data extraction form. The enclosed information includes study features (author, year of publication, study design, country), participant features (number of participants, age, gender proportions, type of sport), definitions and measures of hypertension, as well as data on its prevalence. A special focus was placed on defining hypertension, with various cut-off values used to define it across the studies. The following definitions have been found: ( 1 ) > 140/90 mmHg. ( 2 ) > 95th percentile for gender, age, and height. ( 3 ) > 130/80 mmHg. ( 4 ) > 140/90 mmHg or consuming antihypertensive medication. ( 5 ) > 145/90 mmHg (used in only one study). Quality Assessment The quality of the studies was assessed using a modified version of the Hoy et al. risk-of-bias tool, which was developed explicitly for epidemiological studies of prevalence. The tool assesses both the external validity (representativeness of the target population, suitability of the sampling frame, methodology, and non-response effects) and the internal validity (data collection procedure, acceptability of the case definition, site consistency, tool porosity, and suitability of the statistical analysis). The level of risk of bias was assessed in each study as low, moderate, or high, based on whether it met one or more methodological limitations. Two independent reviewers determined the average study quality, and any disagreements were resolved through discussion. Statistical Analysis R Studio (version 4.5.0) and the meta package were used as tools for statistical analysis to run meta-analyses. The main effect was a cumulative rate of hypertension in young athletes. All analyses were conducted using a random-effects model, given the expected heterogeneity between studies. Pooled prevalence was estimated using the Raw proportion method with a 95 percent confidence interval. The I 2 statistic was used to measure heterogeneity; the percentages of low, moderate, and high population heterogeneity are 25%, 50%, or 75%. Assessment was also conducted using the Cochran Q test for statistical heterogeneity, where P < 0.10 was considered significant heterogeneity. Subgroup Analysis Hypotheses of possible heterogeneity were investigated through pre-planned subgroup analyses to identify factors associated with the prevalence of hypertension. Subgroup analyses were carried out on: Gender: Only men, only women, and both genders studies. Geographic location: Surveys carried out in various nations. Age groups: Age study means an age of < 20 years versus an age of ≥ 20 years. Type of sport: The analysis of particular sports (American football, sports, mixed sports). Hypertension definition: Studies based on varying diagnostic standards. Publication Bias Assessment The publication bias was estimated using funnel plots and a funnel regression test, as described by Egger. Funnel plot asymmetry and the significance of the Egger test (P < 0.05) were viewed to indicate possible publication bias. Sensitivity Analysis A sensitivity examination was conducted to assess the impact of pooled estimation on the exclusion of high-bias studies and its effects on overall prevalence estimates. Results Study Selection and Characteristics The initial search in databases retrieved 2,847 potentially relevant articles. Of the initial 189 articles derived after removing duplicate articles, titles, and abstracts, only 156 articles were selected for full-text review. Twenty-six out of these studies met the inclusion criteria and were therefore used in the final meta-analysis. The selection process is shown in PRISMA flow diagram below. The 26 studies considered were conducted in 12 countries and involved 54,152 young athletes (Table 1). They were published between 1987 and 2024, with most of them (n = 18, 69.2%) being published after 2010. The number of participants in the samples varied between 89 and 13,175, with a median of 847 athletes. The nature of all the included studies, such as sample size, the average ages, the proportions of males and females, the type of sports, the definitions of hypertension, and the prevalence rates, is specified in Table 1. ( Table 1 to be placed here) Study Quality Assessment The overall methodological quality of the included studies was of a sufficient level, as indicated by the quality rating based on the modified Hoy et al. risk-of-bias tool application. There were 20 studies (76.9%) with a low risk of bias and six studies (23.1%) with a moderate risk of bias among the 26 studies included in the meta-analysis. No researches were considered at high risk of bias. The methodological constraints most frequently noted comprised the convenience sampling procedures adopted in the majority of studies, insufficient accounts of non-response rates in certain studies, and, to a certain extent, a lack of exhaustive data concerning the representativeness of the sampling frame in some investigations. The sampling method used was primarily convenience sampling, which is characteristic of research involving the athletic population due to the unique nature of the research community. The pooled prevalence estimates have good reliability because the included studies are of relatively high quality, and this also supports the validity of the meta-analysis results. Detailed quality assessment results for each study are presented in Table 2. First Author, Year Quality Assessment Ashley, 2013 (3) Low risk Stiefel, 2016 (26) Low risk Stefano, 2017 (1) Low risk Maldanodo,2010 (27) Moderate risk Flavio ,2019 (5) Low risk Antonio,2017 (8) Low risk Daimee,2016 (6) Moderate risk Petek,2020 (28) Low risk Gioia, 2024 (2) Low risk Bullock et al 2021 (7) Moderate risk A.P. Deligiannis et al 2014 (10) Low risk Maron et al 1987 (12) Low risk Yevhen Mykhaliuk et al 2024 (21) Low risk Jill Kropa et al 2009–2012 (14) Low risk Berge et al 2013 (9) Low risk Cynthia, 2017 (13) Low risk Steffen, 2024 (25) Low risk Senka, 2010 (11) Low risk Georgeson, 2017 (15) Low risk Lively, 1999 (23) Low risk Andrew, 2009 (19) Low risk Tucker, 2015 (18) Low risk Yasmeen, 2022 (17) Low risk Adela, 2013 (22) Low risk Afrifa, 2019 (20) Low risk Saeed, 2019 (24) Low risk Table 2: Quality assessment of included studies using modified Hoy et al. tool ( Table 2 to be placed here) Overall Prevalence of Hypertension The overall prevalence rate of hypertension among the young sportspeople was 9% (95% CI: 5–12%); P = 0, I 2 = 99.6% (Fig. 2). A high level of I 2 indicated significant heterogeneity among trials, justifying the use of random-effects modeling and conducting a subgroup analysis to help identify the source of the heterogeneity. Gender-Specific Analysis The prevalence of hypertension differed significantly among men and women when subgroup analysis was done (Fig. 3). All studies in men (n = 12) had a pooled prevalence of 10% (95% CI: 6–15%, I 2 = 98.4%). The pooled prevalence was high at 12% (95% CI: 8%-17%, I 2 = 85.2%) when female-only studies (n = 4) were analyzed. Research involving both genders (n = 10) had a pooled prevalence of 8% (95% CI: 4–13%), with an I 2 value of 99.7. This increased frequency in female-exclusive studies was especially noteworthy, as it has long been challenging to establish gender differences in cardiovascular risk among athletic youth. The discovery indicates that there is a necessity for greater focus on the prevention and treatment of hypertension in women athletes. Geographic Variation A significant geographic difference was observed in the prevalence of hypertension among the 12 countries represented in the analysis (Fig. 4). The highest prevalence was observed in studies conducted in the United States (13%, 95% CI: 8%-19%, I 2 = 97.8%, n = 8 studies), followed by studies from several other countries with lower prevalence rates. Italian studies (n = 3) showed the lowest pooled prevalence of 2% (95% CI: 1–4%, I 2 = 78.9%), whereas a prevalence of 7% (95% CI: 5–10%, I 2 = 45.2%) was observed in Norwegian studies (n = 2). The high differences in prevalence among countries implied the role of genetic, environmental, diet, and healthcare system levels on the development of hypertension among young athletes. Sport-Specific Analysis Analysis by the type of sport showed significant discrepancies in the prevalence of hypertension (Fig. 5). Football (NFL) demonstrated the highest prevalence of 11% (95% CI: 7–16, I 2 = 95.7%, n = 5). The prevalence was found to be 10% (95% CI: 6%-15%, I 2 = 89.3%, n = 4 studies) in soccer, or 9% (95% CI: 5%-14%, I 2 = 99.2%, n = 17 studies) in studies involving mixed sports. Its higher rates in American football players might be correlated with sport-specific conditions in American football, such as elevated body mass indices, thicker muscles, and distinctive training requirements. The prevalence was high among soccer players, which was quite surprising and warrants further investigation. Age-Stratified Analysis In the age-stratified analysis, an unexpected inverse correlation was observed between age and the prevalence of hypertension (Fig. 6). On the one hand, the studies that included the mean participant age of < 20 years (n = 8) provided the pooled prevalence of 12% (95% CI: 7%-18%, I 2 = 97.9%); on the other hand, the studies where the mean age comprised 20 or more years (n = 18) presented the prevalence of 4% (95% CI: 2%-7%, I 2 = 98.8%). The counterintuitive observation in the finding implies that the prevalence of hypertension might be high among younger athletes, which could be attributed to developmental factors, screening, or age-specific patterns of sports participation. Impact of Hypertension Definition The Estimates of prevalence depended strongly on the definition of hypertension (Fig. 7). Research based on the threshold of > 130/80 mmHg (n = 3) showed the most significant prevalence of 20% (95% CI: 15%-26%, I 2 = 78.4%). Only one study with a sample size greater than the 95th percentile to derive the gender, age, and height (n = 6) reported a prevalence of 9 percent (95% CI: 5–14, I 2 = 96.8%). Research with the traditional cut-off > 140/90 mmHg (n = 12) had a prevalence of 8% (95% CI: 4%-13%, I 2 = 99.1%), whereas the studies with > 140/90 mmHg or antihypertensive medication (n = 4) also had a similar outcome with 8% (95% CI: 3%-15%, I 2 = 97.9%). A study with a threshold of > 145/90 mmHg was excluded from the analysis due to the occurrence of a unique level. Overall Subgroup Analysis The findings of all subgroup analyses are summarized in Table 3, which indicates the number of studies, sample sizes, pooled prevalence estimates with 95% confidence intervals, heterogeneity statistics (I 2 ), and p-values of any subgroup comparisons. Table 3 illustrates the significant correlation between the prevalence of hypertension in various subgroups, demonstrating that the observed difference is statistically significant. The overall prevalence of hypertension in young athletes was nine percent (95 percent CI: 5 percent to 12 percent, P < 0.001, I 2 = 99.6 percent). Subgroup Number of Studies Sample Size Pooled Prevalence (95% CI) I² (%) P-value Overall 26 54,152 9% (5-12%) 99.6 <0.001 Gender Male only 12 8,941 10% (6-15%) 98.4 <0.001 Female only 4 13,475 12% (8-17%) 85.2 <0.001 Mixed 10 31,736 8% (4-13%) 99.7 <0.001 Country USA 8 21,166 13% (8-19%) 97.8 <0.001 Italy 3 7,170 2% (1-4%) 78.9 0.008 Norway 2 1,059 7% (5-10%) 45.2 0.178 Sport Type American Football 5 2,814 11% (7-16%) 95.7 <0.001 Soccer 4 1,367 10% (6-15%) 89.3 <0.001 Mixed Sports 17 49,971 9% (5-14%) 99.2 <0.001 Age Group <20 years 8 21,445 12% (7-18%) 97.9 <0.001 ≥20 years 18 32,707 4% (2-7%) 98.8 130/80 mmHg 3 13,418 20% (15-26%) 78.4 0.009 >95th percentile 6 18,057 9% (5-14%) 96.8 140/90 mmHg 12 18,829 8% (4-13%) 99.1 140/90 or medication 4 1,988 8% (3-15%) 97.9 <0.001 HTN = Hypertension; CI = Confidence Interval Table 3: Summary of Subgroup Analysis ( Table 3 to be placed here) Publication Bias Assessment Examination of the funnel plot, as well as the Egger regression test (P = 0.0024), indicated possible publication bias (asymmetry in the funnel plot and a p-value of 0.002). Nonetheless, the assessment of publication bias is limited by the high number of studies and wide heterogeneity. Sensitivity Analysis The pattern of results remained the same when studies at high risk of bias were excluded in sensitivity analyses conducted to determine whether the primary findings were robust (prevalence estimate = 9%, 95% CI: 5%-13%). Individual studies were excluded one by one, and the overall calculation of the prevalence did not change significantly, indicating that no single study had an excessive influence on the estimate. Discussion The systematic review and meta-analysis of 26 studies involving a population of 54,152 young athletes provides strong evidence that a substantial percentage (9%, 95% CI: 5–12%) of competitive athletes have hypertension. Our data refute the accepted beliefs concerning cardiovascular health in young athletic populations and contribute to the future implementation of more effective screening strategies and management of cardiovascular health. The observed high heterogeneity between the studies (I 2 = 99.6%) indicates a complex nature of numerous factors that can affect hypertension prevalence in young athletes. We used subgroup analyses to identify the significant determinants of heterogeneity, which were successfully uncovered and revealed to be related to gender, geographic region, type of sport, age, and diagnostic criteria, as shown in Table 3 . The result that female-only studies found a higher prevalence of hypertension (12%) than male-only studies (10%) is quite specific and contradicts the general population data that a high incidence of hypertension was found in young men. Such trends may be an indication of several factors that are unique to female athletes. Women can also experience alternative physiological responses to exercise, which may affect their blood pressure. The possible factors contributing to such fluctuations in blood pressure include hormonal factors, such as fluctuations in estrogen levels during menstrual periods and potential menstrual irregularities, which are common in competitive female athletes ( 17 ). Moreover, the type of sport mainly engaged in by the women athletes in the studies mentioned is not necessarily the same as that engaged in by men athletes, which can affect cardiovascular adaptations. Gender disparity might be evident in cardiovascular screening, as females might undergo more blood pressure checks in certain circumstances than their male counterparts do. Nevertheless, this interpretation needs to be treated with skepticism because a large number of studies involved in the analysis had low representation of women, and the CI of sex-specific estimates overlap significantly. One of the clinical implications of these findings is that female athletes in particular need to be more aware of their risk of being hypertensive and the fact that cardiovascular screening needs to be thorough, irrespective of gender. The existing risk stratification models may need to be adjusted to account for the risk nature of young women who are athletes and individual athletes as a group. We report a 2–13% geographic variability in the prevalence of hypertension (Italian studies vs. US studies), based on our observations, and this suggests that both the environment and culture can play significant roles in cardiovascular well-being among young athletes. Such differences represent variations in dietary habits, especially the Mediterranean diet in Italy, which may protect cardiovascular status against common Western nutritional patterns that are more prevalent in the United States. There might also be an influence of genetic factors causing geographic variation, as some groups of people are more prone to the development of hypertension than others. Nevertheless, the level of variation encountered cannot be attributed to genetic factors, possibly pointing to considerable environmental influences. The differences between healthcare systems can interfere with both the detection and treatment of hypertension. The prevalence of hypertension may be found to be greater in countries with more complex pre-participation screening programs than in countries with only a few screening systems ( 10 ). The fact that screening protocols are not standardized across various countries remains a significant consideration among international sports organizations. There can also be differences in training and competition between countries, and variations in climate, altitude, and level of training may impact cardiovascular adaptation. Interaction between environmental and genetic predisposition is likely to be one of the reasons for the geographical distribution of hypertension. The high rate of hypertension among American football players (11%) is aligned with the studies conducted before, emphasizing the cardiovascular risks of the athletes ( 3 , 18 , 19 ). Some sport-related factors can be considered as leading to the elevated risk, such as the focus on gaining more body mass and muscle mass in the game of American football, which can predispose to developing hypertension. The very intensive, alternating manner of training and playing American football may also be related to cardiovascular load and an even development of high blood pressure. Moreover, cardiovascular risk profiles can be influenced by elements of American football culture, such as diet and supplement use. It is relatively surprising that the prevalence was so high in soccer players (10%); overall, soccer is a sport and activity that is fairly aerobic and related to cardiovascular conditioning ( 9 , 20 , 21 ). The observation suggests that studies of soccer players with varying rates of competition and training loads were included. The efforts of elite soccer players may result in other cardiovascular changes not observed in recreational or lower-level competitive players. The results obtained in this sport have significant implications for the intervention and screening processes. Sports in which hypertension is more prevalent may require more frequent and extended monitoring of cardiovascular health, and sport-specific treatment options may need to consider the unique characteristics and requirements of various athletic activities. Special attention should be paid to our counterintuitive piece of information that athletes younger than 20 years had a higher (12%) prevalence of hypertension than their older counterparts aged 20 years and over (4%). These trends are in contrast to other population rates of hypertension development with aging and indicate the existence of extraordinary phenomena in trend development among young athletic populations ( 6 , 14 , 22 ). Several reasons regarding the age-related paradox are worth considering. Younger sportspeople may be more inclined to engage in sports that are more physically intense and have higher cardiovascular requirements, which are likely to lead to an increase in blood pressure. Moreover, age differences may exist in cardiovascular training responses, where younger athletes may exhibit varying hemodynamic reactions. Depending on the age group, young athletes may undergo more thorough screening in certain practices. This explanation, however, is less probable, considering that pre-participation screening is usually mandatory in any competitive sport, regardless of age. The biological reason behind the discovery may be connected to the role of development as a factor in cardiovascular regulation in teenage and young adult athletes ( 11 ). The dependence of growth spurts on pubertal maturation, coupled with intensive training, may impart specific patterns of cardiovascular stress starting at an early age that predispose to hypertension. The results of our work, which reveal significant differences in the prevalence of hypertension using different diagnostic definitions (8–20 percent), underscore the importance of having standardized definitions in studies on the epidemiology of various health issues. Its most significant prevalence (20%) was observed in research on the utilization of the > 130/80 mmHg cut-off ( 13 , 17 ), which is attributed to the current American Heart Association guidelines' stage of lowering the threshold for diagnosing hypertension. Intermediate estimates of prevalence were obtained using age-, sex-, and height-adjusted percentiles (> 95th percentile) (9%) ( 6 , 10 , 15 ), which indicates that potentially more suitable measures should be used in younger athletes, i.e., pediatric and adolescent normative values. However, the ideal criteria of hypertension diagnosis among young athletes are still subject to trials and discussions. The implications of such differences in the diagnostic criteria are huge, clinically. The development of lower thresholds in diagnosis could yield a greater number of athletes with high blood pressure who could benefit from the intervention. However, it could also result in a larger number of false-positive diagnoses and the unwarranted exclusion of athletes who are not being harmed. On the other hand, the higher thresholds can also miss out sportsmen who have clinically significant hypertension and who might be helped by early treatment. Some of the implications of the results of this meta-analysis have clinical significance. It is supported by the high prevalence of hypertension in young athletes (9%), which confirms the importance of thorough cardiovascular screening as part of pre-participation medical evaluation ( 1 , 8 ). The present screening procedures might not be sufficient to detect hypertensive athletes, especially when it concerns some subgroups at high risk. The fact that high-risk groups have been identified (female athletes, American football players, younger individuals, and those with specific geographic locations) implies that special attention should be given to them in terms of screening and prevention. Transfused patients may benefit from increased blood pressure monitoring and earlier treatment. The difference in prevalence rates according to the diagnostic criteria highlights the need for a consistent definition of hypertension in young athletes. Professional bodies should strive to establish common standards that take into consideration the unique physiological characteristics of the athletic groups without compromising clinical significance. The high degree of heterogeneity observed in the studies underscores the importance of personalized cardiovascular risk assessment in young athletes. Besides measuring blood pressure, other factors such as the type of sport, level of training, and family history of cardiovascular diseases and other cardiovascular risks should also be considered. According to our findings, existing pre-participation screening schemes may need to be improved to ensure the appropriate identification of hypertensive young athletes ( 12 , 23 ). The screening practices must involve uniform methods of blood pressure measurement, meeting normal rates in young sports professionals, and proper follow-up on management practices. The creation of sport-specific screening recommendations may be necessary, especially when the sport, such as American football, is considered at risk. The guidelines are expected to take into account the different physiological requirements and risk patterns associated with various athletic activities. Education of healthcare professionals working in the sphere of athlete screening is necessary to ensure the proper assessment of blood pressure and the interpretation of results in terms of athletic activity. The distinction between physiological responses to training and pathological cardiovascular alterations requires specialized expertise and experience. Several critical research questions can be derived from this meta-study. Longitudinal studies should be implemented to define the natural history of hypertension among young athletes and to examine the factors associated with blood pressure changes over time. There is a need to study using intervention studies, the management options of hypertensive young athletes, to evaluate their effectiveness. Development of optimal diagnostic criteria of hypertension in young athletes under the consideration of sensitivity, specificity, and taking into account sport-specific factors. Theorized links between hypertension and poor cardiovascular outcomes in young athletes, and the observation of such a connection in studies is valuable in prognosis information. Further study of the actions that contribute to the identified gender, age, and sport-specific differences in hypertension prevalence would help clarify cardiovascular risk among young athletes ( 4 , 24 ). Research on the cost-effectiveness of proposed improvements in screening and management would inform health policy and decisions. This meta-analysis has several limitations that warrant mention. The high heterogeneity of research studies limits the accuracy of pooled prevalence data, suggesting that the reported overall prevalence may not accurately reflect the prevalence of all target young athletic groups. Observational studies included in these analyses restrain causal inferences about factors associated with hypertension. The inconsistency in the method of measuring blood pressure, definition, and the study participants in the included studies may be a source of bias, preventing the results from being generalized. We could be affected by the publication bias, which is reflected in the body of literature available. The findings may not be generalizable due to the limited representation of certain sports, geographic regions, and demographic groups in the literature ( 7 , 25 ). Most of the studies included are cross-sectional, so they do not allow making any inferences regarding the time relationship and causality. Based on our systematic review and meta-analysis, we have concluded that the prevalence rate of hypertension in young competitive athletes is high, at 9 per cent, in a manner that greatly varies depending on gender, geographical location, sport type, age, and diagnostic criteria. These results challenge the classical stereotypes regarding the cardiovascular health of young athletic populations and highlight the need for increased attention to screening, monitoring, and management. The determination of risks for specific groups, such as female athletes, American football players, younger athletes, and athletes residing in specific geographic regions, implies the possibility of direct interventions. Diagnostic criteria have widely been acknowledged to have substantial effects on prevalence estimates, thus necessitating uniformity in the definition of hypertension that applies to the young athletic population. These conclusions raise some significant expectations for clinical practice, screening, and sports medicine policy. Providers who work with young people involved in sports activities and athletes must have a more nuanced understanding of the impact of hypertension and introduce a comprehensive cardiovascular check to their battery of medical examinations. Sports associations must consider improving the screening of individuals at increased risk and developing evidence-based guidelines for managing hypertensive athletes. Longitudinal studies on the natural history of hypertension in young athletes, intervention studies to assess management methods, and the development of ideal diagnostic criteria for this special group of patients are needed in the future. The research will be crucial in optimizing the cardiovascular health outcomes of young competitive athletes and will serve as the basis for evidence-based clinical practice guidelines. The high prevalence of hypertension in young athletes unveiled in this meta-analysis is a significant public health issue that requires urgent attention by health care providers, sports medicine professionals, and health officers. Identification and proper treatment of hypertension in young athletes enable them to avoid long-term complications of cardiovascular diseases and maximize athletic performance and long-term health effects. Conclusion This systematic review and meta-analysis give strong evidence to show that the prevalence of hypertension among young competitive athletes is high at 9% and there is a considerable between-persons difference depending on gender, geographic location, type of sport, age, and diagnostic criteria. The results challenge conventional expectations regarding cardiovascular health within young athletic communities, highlighting the need for extended screening, tracking, and treatment solutions. The identification of high-risk populations, such as female athletes, American football players, younger athletes, and individuals in specific geographic areas, suggests the possibility of implementing targeted intervention methods. This is emphasized by the significant effects of the diagnostic criteria on the prevalence estimates, necessitating the need for standard definitions of hypertension that suit the young athletic population. These results are significant for clinical practice, screening programs, and policy in sports medicine. Physicians treating young athletes must be more aware of the risk of hypertension and incorporate extensive cardiovascular system screening procedures as a routine. Sports organizations are advised to put their screening procedures under the spotlight to identify and manage the high-risk group and create evidence-based management protocols on how to handle hypertensive athletes. In the future, longitudinal studies analyzing the natural history of hypertension in young athletes, studies aiming to assess management interventions, and the further development of optimal diagnostic criteria for this specific population must be considered. To enhance the performance of young competitive athletes in the field of cardiovascular health, such research will be indispensable for informing evidence-based clinical practice guidelines. The high prevalence of hypertension in young athletes found in this meta-analysis is more than a serious issue that concerns the healthcare professionals, sports medicine doctors, and community health authorities, since it is a dangerous health and public health problem, and as such, it undeniably needs urgent attention. During the development of young athletes, early diagnosis and treatment of hypertension are crucial in preventing long-term cardiovascular outcomes, which can lead to optimal athletic achievements and improved long-term health outcomes. Declarations Ethics approval and consent to participate This systematic review and meta-analysis utilized previously published data and did not involve direct human subject’s research. Therefore, ethics approval or consent to participate was not required. All included studies had appropriate ethics approvals as reported in their original publications. Consent for publication Not applicable Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding No specific funding was received for this research. Authors' contributions BH conceived and designed the study, developed the search strategy, conducted the statistical analysis using R-Studio, interpreted the results, and drafted the initial manuscript. MOA contributed to the study design, performed database searches, conducted study selection and quality assessment, and substantially revised the manuscript. IJ contributed to the study design, performed data extraction, conducted quality assessment using the modified Hoy et al. risk-of-bias tool, interpreted the data, and was a major contributor in writing and revising the manuscript. HQA contributed to the literature search, performed study selection and data extraction, assisted with quality assessment, and contributed to manuscript writing. KZ contributed to database searches, performed data extraction, assisted with statistical analysis interpretation, and contributed to manuscript revision. AK contributed to study selection, performed data extraction, assisted with subgroup analysis interpretation, and contributed to manuscript writing. WI contributed to literature search, performed quality assessment, assisted with data interpretation, and contributed to manuscript revision. MTA contributed to study design, assisted with statistical analysis, performed sensitivity analysis, and contributed to manuscript writing and revision. 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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-7149750","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":522076689,"identity":"7baaaed6-34f0-467d-9824-91fb53e67fb4","order_by":0,"name":"Binbin 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16:53:20","extension":"xml","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":158172,"visible":true,"origin":"","legend":"","description":"","filename":"9586adf8c9d5457f8a90a1d395902bc61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/37c4f28696fe5040b8a6a9e1.xml"},{"id":93256116,"identity":"e92a1d9f-afe1-41d9-92fe-aaabec6ed75e","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":167738,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/8703b4d56b03b72abb7ff218.html"},{"id":93256113,"identity":"c80bcbf5-e084-4b21-a00e-be13d5d15b71","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":343086,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA flow diagram of the article selection process\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/d5048332daa9e2f9645f4a34.png"},{"id":93256105,"identity":"11ca368b-e13a-446e-887e-70a2803aa404","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":137711,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall Prevalence of Hypertension in Young Athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/405e4529ca88f63771c5137b.png"},{"id":93256100,"identity":"a6ccda34-f558-4476-83c6-82acf2aca554","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":175785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGender-Specific Prevalence of Hypertension in Young Athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/20feef132cbfcb029d517d4e.png"},{"id":93256080,"identity":"7b1265ab-c5ef-49a7-b83c-57be0a75572a","added_by":"auto","created_at":"2025-10-10 16:53:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":130262,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCountry-Specific Prevalence of Hypertension in Young Athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/716a326393c1a52d513179bf.png"},{"id":93256101,"identity":"3a06a045-e7f5-4e4e-a0f5-b63bd7ce7166","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":182641,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSport-Specific Prevalence of Hypertension in Young Athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/03378af8c6ce9be4cf610e24.png"},{"id":93256110,"identity":"253eafe0-df69-49a4-a0c1-24cfb1e79cb5","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":154089,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge-Stratified Prevalence of Hypertension in Young Athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/538a0f65274efd538c905cb9.png"},{"id":93256093,"identity":"608a48be-9480-4502-abe2-2e33dbb91077","added_by":"auto","created_at":"2025-10-10 16:53:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":162617,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Hypertension Based on Different Diagnostic Criteria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/89a595d55bf9167b089e36c0.png"},{"id":93256107,"identity":"ad96eb5a-f400-4801-a1ff-838d1c7d7a92","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":33870,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunnel plot\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/bfcee79edc20b5b2ca134724.png"},{"id":93256978,"identity":"f894aa2f-8e65-4ac2-840d-3ebc919d61af","added_by":"auto","created_at":"2025-10-10 17:01:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2468035,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/57ec4f7d-f047-4b0a-9bc2-7f342b43eeca.pdf"},{"id":93256119,"identity":"94298c8d-bf61-42f1-bcf0-615a2b325f75","added_by":"auto","created_at":"2025-10-10 16:53:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":30219,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7149750/v1/c7893ea9b29e2a7a55b8bba1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Paradox of Performance: Hypertension Among Young Athletes — A Systematic Review and Meta-Analysis of Risks behind Fitness","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHigh blood pressure (hypertension) is one of the significant risk factors of cardiovascular diseases that are preventable, and it causes a vast number of morbidities and deaths at all ages. The rate of hypertension globally has experienced unprecedented growth, as the number of its victims has doubled between 1990 and 2019 due to not only the population growth, but also to a rise in the prevalence rates (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is generally understood that the epidemic is traditionally linked to the population over 60 and sedentary individuals. Still, we have seen some worrying signs of the trend shifting toward younger age groups, including competitive sports.\u003c/p\u003e\u003cp\u003eAthletic individuals have conventionally been regarded as less prone to cardiovascular diseases, including hypertension, due to their exposure to frequent physical exercise, a high degree of cardiovascular fitness, and generally healthier lifestyle habits. These, however, have been refuted in a recent study, which indicates that the number of young athletes who are becoming hypertensive could be very high in such a manner that requires serious clinical intervention (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The paradox has led to a rigorous examination of cardiovascular status among athletic groups, particularly regarding the risk of cardiovascular mishap during intense physical activity.\u003c/p\u003e\u003cp\u003eThe fact that hypertension is common among young athletes is of concern, mainly due to several reasons. Sportsmen experience severe physical exercise and participate in strenuous sporting activities, which exert a heavy cardiovascular strain. Hypertension that is not diagnosed or not well treated among the population may predispose to undesired cardiovascular events, such as sudden cardiac death, during active engagement in sporting activities (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Also, the detection of hypertension in young athletic persons can be a sign of early-onset essential hypertension or secondary hypertension based on pre-existing diseases and pathologies that must then be managed and assessed accordingly (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, the notable physiological changes associated with physical training, such as increased cardiac output, stroke volume, and altered vascular responses, may become a complication during the diagnosis and treatment of hypertension in the general population (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The pathological cardiovascular adaptations and physiological ones in training are a clinical issue that requires consideration of the specifics of a sport, the training load, and the individual features of an athlete.\u003c/p\u003e\u003cp\u003eThe dissimilarity in definitions of hypertension, measurement procedures, and study design has led to differences in estimates of prevalence, which are presented in the literature. Some studies use traditional adult hypertension levels (140/90 mmHg). In contrast, others employ age-adjusted, sex-adjusted, and height-adjusted percentiles in younger athletes, or the newer rating by the American Heart Association (130/80 mmHg) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The slight inconsistency in diagnostic criteria has a significant influence on the estimation of prevalence, making the existing literature more challenging to understand.\u003c/p\u003e\u003cp\u003eThere are also sport-related determinants of hypertension prevalence in young athletes. Contact sports, especially American football, have been reported to have higher incidences of hypertension, which could be due to the body mass index, high muscle mass, and tailored training requirements of the sport (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). On the other hand, there may be other profiles of cardiovascular risk associated with endurance sports, such as vascular risk and cardiovascular efficiency (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere is also the complexity of geography and demographics that add to the study of hypertension prevalence in young athletes. Regional variations in the prevalence of hypertension can be attributed to differences in culture, including diet, training style, access to healthcare, and genetic factors (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Besides, socioeconomic conditions (availability of healthcare and nutrition) could also influence athletic performance and cardiovascular outcomes.\u003c/p\u003e\u003cp\u003eThe practical ramifications of heart diseases among young athletes in terms of the clinical implications of hypertension may be higher than their direct cardiovascular risk. Management and early detection of hypertension among the population can eliminate long-term cardiovascular effects such as coronary artery disease, stroke, as well as heart failure, among others (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). One of the peculiarities of managing hypertensive young athletes is the established balance between minimizing cardiovascular risk and preserving sports results.\u003c/p\u003e\u003cp\u003eThere are significant differences in the pre-participation screening procedures followed by various sporting organizations and geographical locations. Some organizations conduct thorough cardiovascular screenings that involve measuring blood pressure, while others do this on a symptom-based mode or through minimal cardiovascular screening (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Evidence-based knowledge on the prevalence and risk factors of hypertension in athletic populations is critical for optimizing screening protocols among young athletes.\u003c/p\u003e\u003cp\u003eDue to the atypical and varied prevalence rates reported in the literature, variations in study methodology, and the widespread use of different populations, an extensive systematic review with meta-analytical statistics is necessary for estimating the prevalence rates of hypertension among young athletes. This analysis would inform clinical practice, screening procedures, and community health programs tailored to the specific population.\u003c/p\u003e\u003cp\u003eHence, the main aim of the systematic review and meta-analysis is to determine the combined prevalence of hypertension in young competitive athletes and to identify the factors related to the increased risk of hypertension in this population. The secondary goals are to investigate whether gender, type of sport, geographic region, age, and diagnostic criteria have any impact on the estimation of hypertension prevalence.\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eProtocol and Registration\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe systematic review and meta-analysis were conducted according to the guidance for reporting systematic reviews and meta-analyses (PRISMA) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The protocol development employed an a priori method to reduce bias, involving a systematic review of the literature and data analysis. This article describes the protocol that was registered at the International Prospective Register of Systematic Reviews (PROSPERO) with the ID: CRD420251101684.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSearch Strategy\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA thorough literature review was conducted in several electronic sources, including PubMed, Scopus, and Google Scholar, on studies published as of May 15, 2025. A combination of MeSH terms and keywords was used in the search strategy, focusing on hypertension, blood pressure, athletes, and sports participation.\u003c/p\u003e\u003cp\u003eThose search keys were: ((\"hypertension\" OR high blood pressure OR elevated blood pressure OR blood pressure) AND (athletes OR sports OR competitive sports OR athletic participation OR sports medicine) AND (prevalence OR incidence OR epidemiology OR cross-sectional). The search terms were combined using Boolean operators, and the lists of reference studies from the already included articles were manually scanned to identify other relevant publications.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion and Exclusion Criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStudies were included when they fulfilled the following criteria:\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Observational studies (cross-sectional, cohort, or case-control) that provided data on the prevalence of hypertension in athletes.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The study population consists of competitive athletes under 50 years old.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) A study that provided clear definition of hypertension.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) The studies that provided adequate data for prevalence calculation.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Studies that are published in English language.\u003c/p\u003e\u003cp\u003eExclusion criteria included:\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Studies involving among Paralympic athletes because their medical conditions may act as confounders.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Studies that included ex-athletes or retired sportsmen.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Studies specifically examining at the athletes with a concussion or other neurological problems.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Case reports, reviews, or non-original research.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Studies that do not make a clear definition of hypertension.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Duplicate publications or replication of the study/population.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Selection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe identification of studies was followed by screening of studies separately by two independent reviewers based on titles and abstracts. The potentially relevant studies were then read in full text, after which they were considered for inclusion or exclusion. An agreement with the reviewer was reached through discussion or consultation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo reviewers independently extracted data using a standardized data extraction form. The enclosed information includes study features (author, year of publication, study design, country), participant features (number of participants, age, gender proportions, type of sport), definitions and measures of hypertension, as well as data on its prevalence.\u003c/p\u003e\u003cp\u003eA special focus was placed on defining hypertension, with various cut-off values used to define it across the studies. The following definitions have been found:\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u0026gt; 140/90 mmHg.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u0026gt; 95th percentile for gender, age, and height.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) \u0026gt; 130/80 mmHg.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) \u0026gt; 140/90 mmHg or consuming antihypertensive medication.\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) \u0026gt; 145/90 mmHg (used in only one study).\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuality Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe quality of the studies was assessed using a modified version of the Hoy et al. risk-of-bias tool, which was developed explicitly for epidemiological studies of prevalence. The tool assesses both the external validity (representativeness of the target population, suitability of the sampling frame, methodology, and non-response effects) and the internal validity (data collection procedure, acceptability of the case definition, site consistency, tool porosity, and suitability of the statistical analysis).\u003c/p\u003e\u003cp\u003eThe level of risk of bias was assessed in each study as low, moderate, or high, based on whether it met one or more methodological limitations. Two independent reviewers determined the average study quality, and any disagreements were resolved through discussion.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eR Studio (version 4.5.0) and the meta package were used as tools for statistical analysis to run meta-analyses. The main effect was a cumulative rate of hypertension in young athletes. All analyses were conducted using a random-effects model, given the expected heterogeneity between studies. Pooled prevalence was estimated using the Raw proportion method with a 95 percent confidence interval.\u003c/p\u003e\u003cp\u003eThe I\u003csup\u003e2\u003c/sup\u003e statistic was used to measure heterogeneity; the percentages of low, moderate, and high population heterogeneity are 25%, 50%, or 75%. Assessment was also conducted using the Cochran Q test for statistical heterogeneity, where P \u0026lt; 0.10 was considered significant heterogeneity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSubgroup Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHypotheses of possible heterogeneity were investigated through pre-planned subgroup analyses to identify factors associated with the prevalence of hypertension. Subgroup analyses were carried out on:\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eGender: Only men, only women, and both genders studies.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eGeographic location: Surveys carried out in various nations.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAge groups: Age study means an age of \u0026lt; 20 years versus an age of ≥ 20 years.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eType of sport: The analysis of particular sports (American football, sports, mixed sports).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHypertension definition: Studies based on varying diagnostic standards.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003cb\u003ePublication Bias Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe publication bias was estimated using funnel plots and a funnel regression test, as described by Egger. Funnel plot asymmetry and the significance of the Egger test (P \u0026lt; 0.05) were viewed to indicate possible publication bias.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSensitivity Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA sensitivity examination was conducted to assess the impact of pooled estimation on the exclusion of high-bias studies and its effects on overall prevalence estimates.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy Selection and Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe initial search in databases retrieved 2,847 potentially relevant articles. Of the initial 189 articles derived after removing duplicate articles, titles, and abstracts, only 156 articles were selected for full-text review. Twenty-six out of these studies met the inclusion criteria and were therefore used in the final meta-analysis. The selection process is shown in PRISMA flow diagram below.\u003c/p\u003e\n\u003cp\u003eThe 26 studies considered were conducted in 12 countries and involved 54,152 young athletes (Table 1). They were published between 1987 and 2024, with most of them (n\u0026thinsp;=\u0026thinsp;18, 69.2%) being published after 2010. The number of participants in the samples varied between 89 and 13,175, with a median of 847 athletes. The nature of all the included studies, such as sample size, the average ages, the proportions of males and females, the type of sports, the definitions of hypertension, and the prevalence rates, is specified in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003eTable 1 \u003cstrong\u003eto be placed here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Quality Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall methodological quality of the included studies was of a sufficient level, as indicated by the quality rating based on the modified Hoy et al. risk-of-bias tool application. There were 20 studies (76.9%) with a low risk of bias and six studies (23.1%) with a moderate risk of bias among the 26 studies included in the meta-analysis. No researches were considered at high risk of bias. The methodological constraints most frequently noted comprised the convenience sampling procedures adopted in the majority of studies, insufficient accounts of non-response rates in certain studies, and, to a certain extent, a lack of exhaustive data concerning the representativeness of the sampling frame in some investigations. The sampling method used was primarily convenience sampling, which is characteristic of research involving the athletic population due to the unique nature of the research community. The pooled prevalence estimates have good reliability because the included studies are of relatively high quality, and this also supports the validity of the meta-analysis results. Detailed quality assessment results for each study are presented in Table 2.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"498\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Author, Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuality Assessment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAshley, 2013 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eStiefel, 2016 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eStefano, 2017 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eMaldanodo,2010 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eModerate risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eFlavio ,2019 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAntonio,2017 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eDaimee,2016 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eModerate risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003ePetek,2020 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eGioia, 2024 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eBullock et al 2021 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eModerate risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eA.P. Deligiannis et al 2014 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eMaron et al 1987 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYevhen Mykhaliuk et al 2024 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eJill Kropa et al 2009\u0026ndash;2012 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eBerge et al 2013 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eCynthia, 2017 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eSteffen, 2024 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eSenka, 2010 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eGeorgeson, 2017 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eLively, 1999 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAndrew, 2009 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eTucker, 2015 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eYasmeen, 2022 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAdela, 2013 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAfrifa, 2019 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 292px;\"\u003e\n \u003cp\u003eSaeed, 2019 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Quality assessment of included studies using modified Hoy et al. tool\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003eTable 2 \u003cstrong\u003eto be placed here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall Prevalence of Hypertension\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall prevalence rate of hypertension among the young sportspeople was 9% (95% CI: 5\u0026ndash;12%); P\u0026thinsp;=\u0026thinsp;0, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.6% (Fig.\u0026nbsp;2). A high level of I\u003csup\u003e2\u003c/sup\u003e indicated significant heterogeneity among trials, justifying the use of random-effects modeling and conducting a subgroup analysis to help identify the source of the heterogeneity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGender-Specific Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of hypertension differed significantly among men and women when subgroup analysis was done (Fig.\u0026nbsp;3). All studies in men (n\u0026thinsp;=\u0026thinsp;12) had a pooled prevalence of 10% (95% CI: 6\u0026ndash;15%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;98.4%). The pooled prevalence was high at 12% (95% CI: 8%-17%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;85.2%) when female-only studies (n\u0026thinsp;=\u0026thinsp;4) were analyzed. Research involving both genders (n\u0026thinsp;=\u0026thinsp;10) had a pooled prevalence of 8% (95% CI: 4\u0026ndash;13%), with an I\u003csup\u003e2\u003c/sup\u003e value of 99.7.\u003c/p\u003e\n\u003cp\u003eThis increased frequency in female-exclusive studies was especially noteworthy, as it has long been challenging to establish gender differences in cardiovascular risk among athletic youth. The discovery indicates that there is a necessity for greater focus on the prevention and treatment of hypertension in women athletes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeographic Variation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant geographic difference was observed in the prevalence of hypertension among the 12 countries represented in the analysis (Fig.\u0026nbsp;4). The highest prevalence was observed in studies conducted in the United States (13%, 95% CI: 8%-19%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;97.8%, n\u0026thinsp;=\u0026thinsp;8 studies), followed by studies from several other countries with lower prevalence rates.\u003c/p\u003e\n\u003cp\u003eItalian studies (n\u0026thinsp;=\u0026thinsp;3) showed the lowest pooled prevalence of 2% (95% CI: 1\u0026ndash;4%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;78.9%), whereas a prevalence of 7% (95% CI: 5\u0026ndash;10%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;45.2%) was observed in Norwegian studies (n\u0026thinsp;=\u0026thinsp;2). The high differences in prevalence among countries implied the role of genetic, environmental, diet, and healthcare system levels on the development of hypertension among young athletes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSport-Specific Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis by the type of sport showed significant discrepancies in the prevalence of hypertension (Fig.\u0026nbsp;5). Football (NFL) demonstrated the highest prevalence of 11% (95% CI: 7\u0026ndash;16, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;95.7%, n\u0026thinsp;=\u0026thinsp;5). The prevalence was found to be 10% (95% CI: 6%-15%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;89.3%, n\u0026thinsp;=\u0026thinsp;4 studies) in soccer, or 9% (95% CI: 5%-14%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.2%, n\u0026thinsp;=\u0026thinsp;17 studies) in studies involving mixed sports.\u003c/p\u003e\n\u003cp\u003eIts higher rates in American football players might be correlated with sport-specific conditions in American football, such as elevated body mass indices, thicker muscles, and distinctive training requirements. The prevalence was high among soccer players, which was quite surprising and warrants further investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge-Stratified Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the age-stratified analysis, an unexpected inverse correlation was observed between age and the prevalence of hypertension (Fig.\u0026nbsp;6). On the one hand, the studies that included the mean participant age of \u0026lt;\u0026thinsp;20 years (n\u0026thinsp;=\u0026thinsp;8) provided the pooled prevalence of 12% (95% CI: 7%-18%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;97.9%); on the other hand, the studies where the mean age comprised 20 or more years (n\u0026thinsp;=\u0026thinsp;18) presented the prevalence of 4% (95% CI: 2%-7%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;98.8%).\u003c/p\u003e\n\u003cp\u003eThe counterintuitive observation in the finding implies that the prevalence of hypertension might be high among younger athletes, which could be attributed to developmental factors, screening, or age-specific patterns of sports participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of Hypertension Definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Estimates of prevalence depended strongly on the definition of hypertension (Fig.\u0026nbsp;7). Research based on the threshold of \u0026gt;\u0026thinsp;130/80 mmHg (n\u0026thinsp;=\u0026thinsp;3) showed the most significant prevalence of 20% (95% CI: 15%-26%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;78.4%). Only one study with a sample size greater than the 95th percentile to derive the gender, age, and height (n\u0026thinsp;=\u0026thinsp;6) reported a prevalence of 9 percent (95% CI: 5\u0026ndash;14, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;96.8%).\u003c/p\u003e\n\u003cp\u003eResearch with the traditional cut-off \u0026gt;\u0026thinsp;140/90 mmHg (n\u0026thinsp;=\u0026thinsp;12) had a prevalence of 8% (95% CI: 4%-13%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.1%), whereas the studies with \u0026gt;\u0026thinsp;140/90 mmHg or antihypertensive medication (n\u0026thinsp;=\u0026thinsp;4) also had a similar outcome with 8% (95% CI: 3%-15%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;97.9%). A study with a threshold of \u0026gt;\u0026thinsp;145/90 mmHg was excluded from the analysis due to the occurrence of a unique level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall Subgroup Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings of all subgroup analyses are summarized in Table 3, which indicates the number of studies, sample sizes, pooled prevalence estimates with 95% confidence intervals, heterogeneity statistics (I\u003csup\u003e2\u003c/sup\u003e), and p-values of any subgroup comparisons. Table 3 illustrates the significant correlation between the prevalence of hypertension in various subgroups, demonstrating that the observed difference is statistically significant. The overall prevalence of hypertension in young athletes was nine percent (95 percent CI: 5 percent to 12 percent, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.6 percent).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePooled Prevalence (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u0026sup2; (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e54,152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e9% (5-12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e99.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMale only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8,941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e10% (6-15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003eFemale only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e13,475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e12% (8-17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e85.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e31,736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e8% (4-13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e99.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e21,166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e13% (8-19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e7,170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2% (1-4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e78.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1,059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e7% (5-10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e45.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSport Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eAmerican Football\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2,814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e11% (7-16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003eSoccer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1,367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e10% (6-15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e89.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003eMixed Sports\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e49,971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e9% (5-14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e99.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026lt;20 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e21,445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e12% (7-18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003e\u0026ge;20 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e32,707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e4% (2-7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHTN Definition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026gt;130/80 mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e13,418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e20% (15-26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e78.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026gt;95th percentile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e18,057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e9% (5-14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e96.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003e\u0026gt;140/90 mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e18,829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e8% (4-13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\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: 138px;\"\u003e\n \u003cp\u003e\u0026gt;140/90 or medication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1,988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e8% (3-15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHTN = Hypertension; CI = Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Summary of Subgroup Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003eTable 3 \u003cstrong\u003eto be placed here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublication Bias Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExamination of the funnel plot, as well as the Egger regression test (P\u0026thinsp;=\u0026thinsp;0.0024), indicated possible publication bias (asymmetry in the funnel plot and a p-value of 0.002). Nonetheless, the assessment of publication bias is limited by the high number of studies and wide heterogeneity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pattern of results remained the same when studies at high risk of bias were excluded in sensitivity analyses conducted to determine whether the primary findings were robust (prevalence estimate\u0026thinsp;=\u0026thinsp;9%, 95% CI: 5%-13%). Individual studies were excluded one by one, and the overall calculation of the prevalence did not change significantly, indicating that no single study had an excessive influence on the estimate.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe systematic review and meta-analysis of 26 studies involving a population of 54,152 young athletes provides strong evidence that a substantial percentage (9%, 95% CI: 5\u0026ndash;12%) of competitive athletes have hypertension. Our data refute the accepted beliefs concerning cardiovascular health in young athletic populations and contribute to the future implementation of more effective screening strategies and management of cardiovascular health. The observed high heterogeneity between the studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.6%) indicates a complex nature of numerous factors that can affect hypertension prevalence in young athletes. We used subgroup analyses to identify the significant determinants of heterogeneity, which were successfully uncovered and revealed to be related to gender, geographic region, type of sport, age, and diagnostic criteria, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe result that female-only studies found a higher prevalence of hypertension (12%) than male-only studies (10%) is quite specific and contradicts the general population data that a high incidence of hypertension was found in young men. Such trends may be an indication of several factors that are unique to female athletes. Women can also experience alternative physiological responses to exercise, which may affect their blood pressure. The possible factors contributing to such fluctuations in blood pressure include hormonal factors, such as fluctuations in estrogen levels during menstrual periods and potential menstrual irregularities, which are common in competitive female athletes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Moreover, the type of sport mainly engaged in by the women athletes in the studies mentioned is not necessarily the same as that engaged in by men athletes, which can affect cardiovascular adaptations.\u003c/p\u003e\u003cp\u003eGender disparity might be evident in cardiovascular screening, as females might undergo more blood pressure checks in certain circumstances than their male counterparts do. Nevertheless, this interpretation needs to be treated with skepticism because a large number of studies involved in the analysis had low representation of women, and the CI of sex-specific estimates overlap significantly. One of the clinical implications of these findings is that female athletes in particular need to be more aware of their risk of being hypertensive and the fact that cardiovascular screening needs to be thorough, irrespective of gender. The existing risk stratification models may need to be adjusted to account for the risk nature of young women who are athletes and individual athletes as a group.\u003c/p\u003e\u003cp\u003eWe report a 2\u0026ndash;13% geographic variability in the prevalence of hypertension (Italian studies vs. US studies), based on our observations, and this suggests that both the environment and culture can play significant roles in cardiovascular well-being among young athletes. Such differences represent variations in dietary habits, especially the Mediterranean diet in Italy, which may protect cardiovascular status against common Western nutritional patterns that are more prevalent in the United States. There might also be an influence of genetic factors causing geographic variation, as some groups of people are more prone to the development of hypertension than others. Nevertheless, the level of variation encountered cannot be attributed to genetic factors, possibly pointing to considerable environmental influences.\u003c/p\u003e\u003cp\u003eThe differences between healthcare systems can interfere with both the detection and treatment of hypertension. The prevalence of hypertension may be found to be greater in countries with more complex pre-participation screening programs than in countries with only a few screening systems (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The fact that screening protocols are not standardized across various countries remains a significant consideration among international sports organizations. There can also be differences in training and competition between countries, and variations in climate, altitude, and level of training may impact cardiovascular adaptation. Interaction between environmental and genetic predisposition is likely to be one of the reasons for the geographical distribution of hypertension.\u003c/p\u003e\u003cp\u003eThe high rate of hypertension among American football players (11%) is aligned with the studies conducted before, emphasizing the cardiovascular risks of the athletes (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Some sport-related factors can be considered as leading to the elevated risk, such as the focus on gaining more body mass and muscle mass in the game of American football, which can predispose to developing hypertension. The very intensive, alternating manner of training and playing American football may also be related to cardiovascular load and an even development of high blood pressure. Moreover, cardiovascular risk profiles can be influenced by elements of American football culture, such as diet and supplement use.\u003c/p\u003e\u003cp\u003eIt is relatively surprising that the prevalence was so high in soccer players (10%); overall, soccer is a sport and activity that is fairly aerobic and related to cardiovascular conditioning (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The observation suggests that studies of soccer players with varying rates of competition and training loads were included. The efforts of elite soccer players may result in other cardiovascular changes not observed in recreational or lower-level competitive players. The results obtained in this sport have significant implications for the intervention and screening processes. Sports in which hypertension is more prevalent may require more frequent and extended monitoring of cardiovascular health, and sport-specific treatment options may need to consider the unique characteristics and requirements of various athletic activities.\u003c/p\u003e\u003cp\u003eSpecial attention should be paid to our counterintuitive piece of information that athletes younger than 20 years had a higher (12%) prevalence of hypertension than their older counterparts aged 20 years and over (4%). These trends are in contrast to other population rates of hypertension development with aging and indicate the existence of extraordinary phenomena in trend development among young athletic populations (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Several reasons regarding the age-related paradox are worth considering. Younger sportspeople may be more inclined to engage in sports that are more physically intense and have higher cardiovascular requirements, which are likely to lead to an increase in blood pressure. Moreover, age differences may exist in cardiovascular training responses, where younger athletes may exhibit varying hemodynamic reactions.\u003c/p\u003e\u003cp\u003eDepending on the age group, young athletes may undergo more thorough screening in certain practices. This explanation, however, is less probable, considering that pre-participation screening is usually mandatory in any competitive sport, regardless of age. The biological reason behind the discovery may be connected to the role of development as a factor in cardiovascular regulation in teenage and young adult athletes (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The dependence of growth spurts on pubertal maturation, coupled with intensive training, may impart specific patterns of cardiovascular stress starting at an early age that predispose to hypertension.\u003c/p\u003e\u003cp\u003eThe results of our work, which reveal significant differences in the prevalence of hypertension using different diagnostic definitions (8\u0026ndash;20 percent), underscore the importance of having standardized definitions in studies on the epidemiology of various health issues. Its most significant prevalence (20%) was observed in research on the utilization of the \u0026gt;\u0026thinsp;130/80 mmHg cut-off (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), which is attributed to the current American Heart Association guidelines' stage of lowering the threshold for diagnosing hypertension. Intermediate estimates of prevalence were obtained using age-, sex-, and height-adjusted percentiles (\u0026gt;\u0026thinsp;95th percentile) (9%) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), which indicates that potentially more suitable measures should be used in younger athletes, i.e., pediatric and adolescent normative values. However, the ideal criteria of hypertension diagnosis among young athletes are still subject to trials and discussions.\u003c/p\u003e\u003cp\u003eThe implications of such differences in the diagnostic criteria are huge, clinically. The development of lower thresholds in diagnosis could yield a greater number of athletes with high blood pressure who could benefit from the intervention. However, it could also result in a larger number of false-positive diagnoses and the unwarranted exclusion of athletes who are not being harmed. On the other hand, the higher thresholds can also miss out sportsmen who have clinically significant hypertension and who might be helped by early treatment.\u003c/p\u003e\u003cp\u003eSome of the implications of the results of this meta-analysis have clinical significance. It is supported by the high prevalence of hypertension in young athletes (9%), which confirms the importance of thorough cardiovascular screening as part of pre-participation medical evaluation (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The present screening procedures might not be sufficient to detect hypertensive athletes, especially when it concerns some subgroups at high risk. The fact that high-risk groups have been identified (female athletes, American football players, younger individuals, and those with specific geographic locations) implies that special attention should be given to them in terms of screening and prevention. Transfused patients may benefit from increased blood pressure monitoring and earlier treatment.\u003c/p\u003e\u003cp\u003eThe difference in prevalence rates according to the diagnostic criteria highlights the need for a consistent definition of hypertension in young athletes. Professional bodies should strive to establish common standards that take into consideration the unique physiological characteristics of the athletic groups without compromising clinical significance. The high degree of heterogeneity observed in the studies underscores the importance of personalized cardiovascular risk assessment in young athletes. Besides measuring blood pressure, other factors such as the type of sport, level of training, and family history of cardiovascular diseases and other cardiovascular risks should also be considered.\u003c/p\u003e\u003cp\u003eAccording to our findings, existing pre-participation screening schemes may need to be improved to ensure the appropriate identification of hypertensive young athletes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The screening practices must involve uniform methods of blood pressure measurement, meeting normal rates in young sports professionals, and proper follow-up on management practices. The creation of sport-specific screening recommendations may be necessary, especially when the sport, such as American football, is considered at risk. The guidelines are expected to take into account the different physiological requirements and risk patterns associated with various athletic activities.\u003c/p\u003e\u003cp\u003eEducation of healthcare professionals working in the sphere of athlete screening is necessary to ensure the proper assessment of blood pressure and the interpretation of results in terms of athletic activity. The distinction between physiological responses to training and pathological cardiovascular alterations requires specialized expertise and experience.\u003c/p\u003e\u003cp\u003eSeveral critical research questions can be derived from this meta-study. Longitudinal studies should be implemented to define the natural history of hypertension among young athletes and to examine the factors associated with blood pressure changes over time. There is a need to study using intervention studies, the management options of hypertensive young athletes, to evaluate their effectiveness. Development of optimal diagnostic criteria of hypertension in young athletes under the consideration of sensitivity, specificity, and taking into account sport-specific factors. Theorized links between hypertension and poor cardiovascular outcomes in young athletes, and the observation of such a connection in studies is valuable in prognosis information.\u003c/p\u003e\u003cp\u003eFurther study of the actions that contribute to the identified gender, age, and sport-specific differences in hypertension prevalence would help clarify cardiovascular risk among young athletes (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Research on the cost-effectiveness of proposed improvements in screening and management would inform health policy and decisions.\u003c/p\u003e\u003cp\u003eThis meta-analysis has several limitations that warrant mention. The high heterogeneity of research studies limits the accuracy of pooled prevalence data, suggesting that the reported overall prevalence may not accurately reflect the prevalence of all target young athletic groups. Observational studies included in these analyses restrain causal inferences about factors associated with hypertension. The inconsistency in the method of measuring blood pressure, definition, and the study participants in the included studies may be a source of bias, preventing the results from being generalized. We could be affected by the publication bias, which is reflected in the body of literature available.\u003c/p\u003e\u003cp\u003eThe findings may not be generalizable due to the limited representation of certain sports, geographic regions, and demographic groups in the literature (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Most of the studies included are cross-sectional, so they do not allow making any inferences regarding the time relationship and causality.\u003c/p\u003e\u003cp\u003eBased on our systematic review and meta-analysis, we have concluded that the prevalence rate of hypertension in young competitive athletes is high, at 9 per cent, in a manner that greatly varies depending on gender, geographical location, sport type, age, and diagnostic criteria. These results challenge the classical stereotypes regarding the cardiovascular health of young athletic populations and highlight the need for increased attention to screening, monitoring, and management. The determination of risks for specific groups, such as female athletes, American football players, younger athletes, and athletes residing in specific geographic regions, implies the possibility of direct interventions. Diagnostic criteria have widely been acknowledged to have substantial effects on prevalence estimates, thus necessitating uniformity in the definition of hypertension that applies to the young athletic population.\u003c/p\u003e\u003cp\u003eThese conclusions raise some significant expectations for clinical practice, screening, and sports medicine policy. Providers who work with young people involved in sports activities and athletes must have a more nuanced understanding of the impact of hypertension and introduce a comprehensive cardiovascular check to their battery of medical examinations. Sports associations must consider improving the screening of individuals at increased risk and developing evidence-based guidelines for managing hypertensive athletes. Longitudinal studies on the natural history of hypertension in young athletes, intervention studies to assess management methods, and the development of ideal diagnostic criteria for this special group of patients are needed in the future. The research will be crucial in optimizing the cardiovascular health outcomes of young competitive athletes and will serve as the basis for evidence-based clinical practice guidelines.\u003c/p\u003e\u003cp\u003eThe high prevalence of hypertension in young athletes unveiled in this meta-analysis is a significant public health issue that requires urgent attention by health care providers, sports medicine professionals, and health officers. Identification and proper treatment of hypertension in young athletes enable them to avoid long-term complications of cardiovascular diseases and maximize athletic performance and long-term health effects.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis systematic review and meta-analysis give strong evidence to show that the prevalence of hypertension among young competitive athletes is high at 9% and there is a considerable between-persons difference depending on gender, geographic location, type of sport, age, and diagnostic criteria. The results challenge conventional expectations regarding cardiovascular health within young athletic communities, highlighting the need for extended screening, tracking, and treatment solutions.\u003c/p\u003e\u003cp\u003eThe identification of high-risk populations, such as female athletes, American football players, younger athletes, and individuals in specific geographic areas, suggests the possibility of implementing targeted intervention methods. This is emphasized by the significant effects of the diagnostic criteria on the prevalence estimates, necessitating the need for standard definitions of hypertension that suit the young athletic population.\u003c/p\u003e\u003cp\u003eThese results are significant for clinical practice, screening programs, and policy in sports medicine. Physicians treating young athletes must be more aware of the risk of hypertension and incorporate extensive cardiovascular system screening procedures as a routine. Sports organizations are advised to put their screening procedures under the spotlight to identify and manage the high-risk group and create evidence-based management protocols on how to handle hypertensive athletes.\u003c/p\u003e\u003cp\u003eIn the future, longitudinal studies analyzing the natural history of hypertension in young athletes, studies aiming to assess management interventions, and the further development of optimal diagnostic criteria for this specific population must be considered. To enhance the performance of young competitive athletes in the field of cardiovascular health, such research will be indispensable for informing evidence-based clinical practice guidelines.\u003c/p\u003e\u003cp\u003eThe high prevalence of hypertension in young athletes found in this meta-analysis is more than a serious issue that concerns the healthcare professionals, sports medicine doctors, and community health authorities, since it is a dangerous health and public health problem, and as such, it undeniably needs urgent attention. During the development of young athletes, early diagnosis and treatment of hypertension are crucial in preventing long-term cardiovascular outcomes, which can lead to optimal athletic achievements and improved long-term health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review and meta-analysis utilized previously published data and did not involve direct human subject\u0026rsquo;s research. Therefore, ethics approval or consent to participate was not required. All included studies had appropriate ethics approvals as reported in their original publications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBH conceived and designed the study, developed the search strategy, conducted the statistical analysis using R-Studio, interpreted the results, and drafted the initial manuscript. MOA contributed to the study design, performed database searches, conducted study selection and quality assessment, and substantially revised the manuscript. IJ contributed to the study design, performed data extraction, conducted quality assessment using the modified Hoy et al. risk-of-bias tool, interpreted the data, and was a major contributor in writing and revising the manuscript. HQA contributed to the literature search, performed study selection and data extraction, assisted with quality assessment, and contributed to manuscript writing. KZ contributed to database searches, performed data extraction, assisted with statistical analysis interpretation, and contributed to manuscript revision. AK contributed to study selection, performed data extraction, assisted with subgroup analysis interpretation, and contributed to manuscript writing. WI contributed to literature search, performed quality assessment, assisted with data interpretation, and contributed to manuscript revision. MTA contributed to study design, assisted with statistical analysis, performed sensitivity analysis, and contributed to manuscript writing and revision. All authors read and approved the final manuscript, agreed to be personally accountable for their contributions, and ensured that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCaselli S, Sequ\u0026igrave; AV, Lemme E, Quattrini F, Milan A, D\u0026apos;Ascenzi F, et al. Prevalence and management of systemic hypertension in athletes. The American Journal of Cardiology. 2017;119(10):1616-22.\u003c/li\u003e\n\u003cli\u003eDi Gioia G, Crispino SP, Maestrini V, Monosilio S, Squeo MR, Lemme E, et al. 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International Journal of Sport Studies for Health. 2019;2(2).\u003c/li\u003e\n\u003cli\u003eМихалюк Є, Гороховський Є, Босенко А, Базильчук О, Хорошуха М, Орлик Н, et al. Heart rate and blood pressure in soccer players differing in sports qualification. Wiadomości Lekarskie Medical Advances. 2024(77 (12)):2426-34.\u003c/li\u003e\n\u003cli\u003eSpoturno ACC, Paz-Sauquillo MT, L\u0026oacute;pez-Zea M, Fern\u0026aacute;ndez-Rostello EA. Cardiovascular risk factors encountered during medical examination in athletic children. Arch Argent Pediatr. 2013;111(6):472-5.\u003c/li\u003e\n\u003cli\u003eLively MW. Preparticipation physical examinations: a collegiate experience. LWW; 1999. p. 3-8.\u003c/li\u003e\n\u003cli\u003eSaeed SQ, Khalifa MF, Noaman MH. Screening of Obesity, Blood Pressure and Blood Glucose among Female Students Athletes at the College of Physical Education and Sport Sciences in the University of Baghdad. Indian Journal of Public Health Research \u0026amp; Development. 2019;10(6).\u003c/li\u003e\n\u003cli\u003eSteffen K. Comprehensive periodic health evaluations of 454 N. 2024.\u003c/li\u003e\n\u003cli\u003eStiefel EC, Field L, Replogle W, McIntyre L, Igboechi O, Savoie III FH. The prevalence of obesity and elevated blood pressure in adolescent student athletes from the state of Mississippi. Orthopaedic Journal of Sports Medicine. 2016;4(2):2325967116629368.\u003c/li\u003e\n\u003cli\u003eMaldonado J, Pereira T, Fernandes R, Santos R, Carvalho M. An approach of hypertension prevalence in a sample of 5381 Portuguese children and adolescents. The AVELEIRA registry.\u0026ldquo;Hypertension in Children\u0026rdquo;. Blood pressure. 2011;20(3):153-7.\u003c/li\u003e\n\u003cli\u003ePetek BJ, Drezner JA, Harmon KG. Prevalence of elevated blood pressure and risk factors for hypertension in college athletes. Clinical Journal of Sport Medicine. 2022;32(1):e74-e82.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hypertension, Young athletes, Meta-analysis, Cardiovascular health, Sports medicine","lastPublishedDoi":"10.21203/rs.3.rs-7149750/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7149750/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypertension (HTN) is a growing health issue worldwide, with the global burden doubling between 1990 and 2019. Although the disease has traditionally been linked to older people, it is increasingly being discovered in young athletes, which brings into question the cardiovascular health of this group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess and establish the incidence rate of hypertension among young competitive sportsmen in different courses taking part in various sporting activities via systematic review and meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA PRISMA systematic review was conducted on PubMed, Scopus, and Google Scholar through May 2025 to determine prevalence of hypertension among young athletes (aged \u0026lt; 50 years). A random-effects model was used in R-Studio (version 4.5.0) with I\u003csup\u003e2\u003c/sup\u003e statistic to measure heterogeneity. An updated Hoy et al. risk-of-bias tool was used in assessing the study quality. Gender, country, age group (\u0026lt; 20 vs. \u0026gt;20 years), and the value of the hypertension cut-off were used to perform subgroup analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 26 studies were conducted in 12 countries, involving 54,152 athletes as part of the study. The prevalence of hypertension in young athletes was 9% (95% CI: 5%-12%, P = 0, I\u003csup\u003e2\u003c/sup\u003e = 99%). According to the gender analysis, it was identified that 10% of the studies were male-only, 12% were female-only, and 8% were mixed-gender based. The prevalence in the country was widely different: USA (13%), Italy (2%), and Norway (7%). Age-stratified data revealed a prevalence of 12% in athletes under 20 years of age and 4% in those 20 years of age and older. The highest prevalence was observed among NFL players (11%), followed by soccer (10%) and mixed sports (9%). Various definitions of hypertension yielded different prevalence rates: \u0026gt;95th percentile (9 percent), \u0026gt; 130/80 mmHg (20 percent), and \u0026gt; 140/90 mmHg (8 percent), as well as \u0026gt; 140/90 mmHg or taking antihypertensive medications (8 percent).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of high blood pressure in young athletes differs according to gender, geography, type of sport and the definition of diagnosis. Female athletes, US athletes, and NFL players are most prevalent, and need to be screened and intervened more effectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number: \u003c/strong\u003eNot Applicable.\u003c/p\u003e","manuscriptTitle":"The Paradox of Performance: Hypertension Among Young Athletes — A Systematic Review and Meta-Analysis of Risks behind Fitness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 16:53:12","doi":"10.21203/rs.3.rs-7149750/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-09-08T05:59:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233159280547137932215305784732373350546","date":"2025-09-03T14:35:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-31T16:08:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44247851446177348781392741233675738134","date":"2025-08-31T15:24:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-30T03:51:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254321328599711525129339412940481615892","date":"2025-08-30T03:34:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-22T16:59:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-01T09:20:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-31T12:04:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-31T12:03:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-07-17T13:48:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e436854b-068f-499a-934e-fd801de81837","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-10T16:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-10 16:53:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7149750","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7149750","identity":"rs-7149750","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}