The relationship between youth sport participation, physical activity levels, and cardiovascular disease risk factors in 5- to 14-year-old children: a systematic review

The relationship between youth sport participation, physical activity levels, and cardiovascular disease risk factors in 5- to 14-year-old children: a systematic review | 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 Research Article The relationship between youth sport participation, physical activity levels, and cardiovascular disease risk factors in 5- to 14-year-old children: a systematic review Kyle A. Kercher, Janelle M. Goss, Paola A. Fernandez Sola, Annamaria Ebersole, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6762942/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Cardiovascular disease (CVD) causes approximately 18 million deaths annually, disproportionately affecting underrepresented racial and ethnic groups. Participation in youth sports has been suggested as a potential strategy to improve CVD-related risk factors, but studies on the topic have produced mixed results. The primary objective of this systematic review was to evaluate the relationship between youth sport participation, physical activity levels, and CVD risk factors, in children aged 5 to 14 years. A secondary objective was to investigate whether relationships differed across racial and ethnic groups. Methods The search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Eligible studies included experimental, quasi-experimental, or observational studies conducted on youth (5–14 years of age) from any health background. To be included, studies needed to report on the relationship of youth sport participation to at least one of the following outcomes: (a) physical activity levels, (b) blood pressure, (c) lipid fractions, (d) body mass index, (e) central adiposity, (f) systemic inflammation, or (g) glucose levels/insulin resistance. Primarily quantitative descriptive analyses were used to synthesize studies by outcome. Results We screened 12,286 studies; 379 underwent full text review, and 186 studies included in the final sample. The five most commonly reported CVD-risk related outcomes were: physical activity (119 studies), body mass index (117 studies), waist circumference (28 studies), blood pressure (27 studies), and lipid profiles (18 studies). 23 studies (12.4%) reported a definition of sport. Physical activity was measured primarily using MVPA (n = 65), sport participation (n = 30), or step counts (n = 8). Twenty-eight out of 65 studies (43.1%) that had a measure of MVPA demonstrated significant differences in MVPA. Out of 117 studies that assessed BMI, 75 studies (64.1%) assessed the significance of BMI-related relationships, and 41 studies (35.0%) reported statistically significant BMI-related relationships. 62 studies (33.3%) reported effect size estimates. Conclusions The present review indicated a need for more consistent and transparent methodology in youth sport research related to physical activity and CVD risk factors. Studies clearly stating the operationalized definition of youth sport and diverse and generalizable samples were lacking. Systematic Review Registration: PROSPERO CRD42023427219 public health sports medicine cardiovascular health sport-based youth development Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Cardiovascular disease (CVD), the leading global cause of mortality, accounts for 18 million deaths annually and disproportionately affects underrepresented racial and ethnic groups.( 1 – 4 ) Atherosclerosis, a major contributor to CVD, begins as early as childhood, with many health-related risk behaviors established during this time.( 5 – 8 ) Physical inactivity is a key modifiable lifestyle behavior that helps reduce CVD risk by lowering adiposity, improving blood pressure, and enhancing vascular and immune function.( 9 – 12 ) In line with supporting long-term health and wellness, the Department of Health and Human Services recommends that children engage in at least 60 minutes of moderate-to-vigorous physical activity per day.( 13 ) Despite this recommendation, fewer than 25% of U.S. youth meet the recommended physical activity guidelines, with the percentage being even smaller among the 12–17-year-olds compared to the 6–11-year-olds.( 14 ) Initiatives that support youth toward physical activity participation may subsequently reduce the risk of CVD. One potential way to support youth toward meeting physical activity guidelines is through sport. In line with previous literature ( 15 ), the present study defines youth sports as structured activities requiring physical effort or skill that include recreational programs, as well as development initiatives where sport is central. Sports based initiatives can provide sustained engagement in physical activity from a young age by focusing on more enjoyable activities than traditional exercise programs.( 16 – 18 ) Youth sports offer a potentially promising approach to reduce CVD risk factors like high blood pressure, cholesterol, and insulin resistance,( 19 ) but research results have been inconsistent.( 20 ) Some studies highlight physical benefits, while others show limited or no impact.( 20 – 22 ) For instance, a 2019 review of U.S. sport-based youth development programs found most interventions prioritized cognitive, social, or lifestyle outcomes over physical health.( 22 ) A review of the relationship between youth sport participation and cardiovascular health markers found potential benefits for cardiovascular function, but few studies met rigorous quality assessment criteria, and the review only included studies of intima-media thickness and blood pressure.( 23 ) Lastly, inconsistent definitions of "sport" across the studies complicate conclusions from existing research regarding the potential benefit of youth sport participation on CVD risk factors. Therefore, a comprehensive review that includes a broader range of cardiovascular health markers and a clear, robust definition of youth sports is needed to better understand the relationship between these factors and to guide future intervention research. Further, research rarely explores differences among racial and ethnic groups, despite disparities in prevalence of CVD( 1 , 2 ) and rates of sport participation.( 24 ) Youth from racial and ethnic minority backgrounds are at a higher risk of developing CVD and are less likely to meet recommended physical activity guidelines.( 1 , 2 ) Additionally, financial and logistical barriers often limit their access to sports programs. In fact, while over 50% of youth participate in a sports team or after school sport lesson, this percentage drops to 33% if the family is below the poverty level and 41% if the family is between 100% and 199% of the poverty level.( 25 ) Given these disparities, examining the impact of sports participation on physical activity and cardiovascular health outcomes in this population is advisable. A better understanding of these relationships can help inform the development of targeted interventions to improve health equity and guide culturally tailored health strategies for underrepresented populations. The present study uses a definition of youth sport from previously published research: physical exertion and/or physical skill in a structured or organized setting for training and/or competition.( 15 ) This definition includes competitive, recreational, sport-based youth development, and physical activity programs/interventions that have sport as a critical component of programming/intervention. The primary objective of this systematic review was to evaluate the association between youth sport participation and physical activity levels, as well as CVD risk factors, in children aged 5 to 14 years. A secondary objective was to investigate whether outcomes differed across racial and ethnic groups. CVD risk factors examined include activity intensity, duration, and frequency, as well as blood pressure, lipid profiles, BMI, waist circumference, inflammation, and glucose/insulin resistance. The findings from this systematic review may identify existing gaps in research, weaknesses in methodology, and opportunities for future research. METHODS This systematic review protocol is registered with PROSPERO (CRD42023427219) and follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (see Supplemental File 1 for the PRISMA checklist).(26) The search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Search development was conducted in collaboration with librarians from the Indiana University Bloomington Library. The study was conducted from September 2023 to April 2025, allowing sufficient time for literature review, eligibility assessment, quality evaluation, data synthesis, and manuscript preparation. The search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Eligible studies included observational, quasi-experimental, or experimental research conducted on youth (5-14 years of age) from any health background, examining the relationship between sport participation and either physical activity levels or CVD risk factors. To be included, studies needed to report on at least one of the following outcomes: (a) physical activity levels, (b) blood pressure, (c) lipid fractions, (d) body mass index, (e) central adiposity, (f) systemic inflammation, or (g) glucose levels/insulin resistance. For a full description and discussion of the search strategy (Supplemental File 2), initial title and abstract screening, full-text review, study selection, and amendments, please reference the published protocol paper.(27) Quality Assessment Four primary reviewers (JG, JW, JO, AE) conducted the initial quality assessments using Covidence systematic review management software. Each study was independently reviewed by two of our primary reviewers (JG, JW, JO, AE), with disagreements resolved by a third member. Study quality was assessed using a rating tool based on the Methods Guide for Effectiveness and Comparative Effectiveness Reviews developed by the Agency for Healthcare Research and Quality. This quality assessment tool was selected due to the broad study inclusion criteria of observational, quasi-experimental, and experimental studies, and the absence of a tool for comprehensively assessing the quality of observational studies that did not include direct group comparison or intervention. See Supplemental File 3 for the full quality assessment tool. Data Extraction The data extracted from each study included general information (e.g., author, funding, conflicts of interest, and data collection years), participant demographics (e.g., age, sex, race, and ethnicity), methods (e.g., groupings, timepoints, sport definition, and type of analysis), results (e.g., means, standard deviations, odds ratios, and hazard ratios), and conclusions. The primary outcomes of interest were physical activity levels, blood pressure, lipid fractions, body mass index, central adiposity, systemic inflammation, and glucose levels/insulin resistance. Data Synthesis This systematic review incorporated diverse research methods, including varying study designs, settings, measurement techniques, participant characteristics, and outcomes. A combined narrative approach with descriptive and limited inferential analysis was used to synthesize findings from heterogeneous studies. Results were presented either as the full sample or in two categories: (1) experimental and (2) non-experimental studies. This categorization was done to synthesize findings for the whole sample by grouping studies with limited internal validity (i.e., observational categorized as non-experimental) and another group as those with more robust internal validity (i.e., experimental and quasi-experimental). Meta-analyses were not conducted based on significant heterogeneity between study types, methodology in outcome reporting, and statistical reporting. Statistical analyses were performed in R (v4.2.2),(28) with significance set at p ≤ 0.05. KK, JG, and JW, and 4 other research assistants independently extracted data and each study required two independent extractions to be sent for consensus to ensure alignment. Disagreements were resolved by a third team member. Covidence software and Excel were used for data management. Racial and ethnic representation was summarized narratively and quantified where possible, contextualizing results within the quality of evidence. RESULTS Overview The literature search in this systematic review initially returned 13,674 publications. 12,286 studies were screened; 379 underwent full text review, and 186 studies included in the final sample. After the title, abstract, and full text review process, 186 studies were evaluated in the final sample. Sample sizes ranged from n =10 to n =35,367. An overview of the screening process is in Figure 1. See Supplemental File 4 for the full list of included studies. FIGURE 1. PRISMA DIAGRAM [INSERT FIGURE 1. PRISMA DIAGRAM] Results include a wide range of heterogeneous data across 7 CVD risk-related outcome categories. Due to the heterogeneity of the data, the majority of results below are descriptive rather than inferential. Results are organized and presented by CVD risk-related outcome. See Table 1 for a descriptive summary of included studies. See Figure 2 for the year of publication distribution. TABLE 1. Overall Descriptive Summary of Included Studies Total Studies n (%) Non-Experimental Studies n (%) Experimental Studies n (%) Included studies 186 (100.0) 106 (57.0) 80 (43.0) Country Study Was Conducted Australia 20 (10.8) 8 (40.0) 12 (60.0) Brazil 20 (10.8) 10 (50.0) 10 (50.0) Denmark 9 (4.8) 6 (66.7) 3 (33.3) Portugal 12 (6.5) 7 (58.3) 5 (41.7) United Kingdom 10 (5.4) 7 (70.0) 3 (30.0) USA 39 (21.0) 23 (59.0) 16 (41.0) Other 76 (40.9) 43 (56.6) 33 (43.4) Definition of Sport Reported Yes 23 (12.4) 18 (78.3) 5 (23.8) No 163 (87.6) 88 (54.5) 75 (45.4) Race Reported Yes 44 (23.7) 28 (63.6) 16 (36.4) No 142 (76.3) 78 (54.9) 64 (45.1) Races Reported & Included* Black or African American 26 (14.0) 15 (57.7) 11 (42.3) White 27 (14.5) 19 (70.4) 8 (29.6) Asian or Pacific Islander 11 (5.9) 5 (45.4) 6 (54.5) Hispanic or Latino 25 (13.4) 15 (60.0) 10 (40.0) American Indiana or Alaskan Native 9 (4.8) 4 (44.4) 5 (55.6) Other 22 (11.8) 14 (63.6) 8 (36.4) Sex Only Females 23 (12.4) 8 (34.8) 15 (65.2) Only Males 16 (8.6) 7 (43.8) 9 (56.3) Both 138 (74.2) 90 (65.2) 48 (34.8) Did Not Report 12 (6.5) 2 (16.7) 10 (83.3) CVD-Related Outcome Measure* Physical activity 119 (64.0) 73 (61.3) 46 (38.7) BMI 117 (62.9) 66 (56.4) 51 (43.6) Waist circumference 28 (15.1) 7 (25.0) 21 (75.0) Blood pressure 27 (14.5) 11 (40.7) 16 (59.3) Lipids 18 (9.7) 6 (33.3) 12 (66.7) Glucose / insulin resistance 11 (5.9) 2 (18.2) 9 (81.1) Systemic inflammation 7 (3.8) 2 (28.6) 5 (71.4) Effect Size Reported Yes 62 (33.3) 23 (37.1) 39 (62.9) No 124 (66.7) 83 (66.9) 41 (33.1) Note: The numbers in the table represent studies included in the final sample. The average age of the final sample was 11.48 (SD=2.20). The experimental group includes experimental and quasi-experimental studies. * = % will not equal 100% since not all studies reported on race. FIGURE 2. YEAR OF PUBLICATION FOR INCLUDED STUDIES [INSERT FIGURE 2] Physical Activity Out of 186 studies, 119 included a measure of physical activity. Of these 119 studies, 46 (38.7%) were experimental and 73 studies (61.3%) were non-experimental. Measures of physical activity included moderate-to-vigorous physical activity (MVPA), step counts, total physical activity levels, and participation in sports programs. Across the studies, MVPA was the most frequently reported physical activity measure, and it was typically reported as either minutes per day or as a percentage of participants who attained MVPA recommendations. Twenty-eight out of 65 studies (43.1%) that had a measure of MVPA demonstrated significant differences in MVPA. For instance, MVPA levels improved from 29.2 to 31.5 minutes/day and from 73.8 to 96.9 minutes/day following participation in organized sports programs.(29, 30) Sports participation often correlated with higher MVPA; for example, boys participating in sports reported 109 to 118 minutes/day compared to girls’ 75 to 84 minutes/day ( p = 0.001).(30, 31) Similarly, in a study measuring physical activity with step counts (used in 8 studies), higher levels of physical activity were found in boys, with boys achieving 11,898 steps/day compared to girls’ 10,068 steps/day.(32) Additionally, sport participation was used as a proxy measure for physical activity in 30 studies (16.1% of included studies). Effect sizes varied widely, and they were reported in 23 out of 119 studies (19.3%) that included physical activity as an outcome measure. Body Mass Index Out of 186 studies, 117 included BMI as an outcome measure (66 non-experimental and 51 experimental). Out of the 117 studies that assessed BMI, 75 studies (64.1%) assessed the significance of BMI-related relationships, and 41 studies (35.0%) reported statistically significant BMI-related relationships. The target population for these studies were primarily middle-school age children, with the experimental studies following pre- to post-test designs. Experimental designs varied in duration, with the shortest being 2 days and the longest being 621 days. Interventions included in-school settings, after-school settings, and a combination of in-school and at-home activities. Lipids Lipid profiles were reported in 18 (9.7%) out of 186 studies. Of these 18 studies, 12 (66.7%) were categorized as experimental and 6 (33.3%) were non-experimental. Various lipid measures were reported in the following numbers of studies: Total cholesterol ( n =9 studies; 2 were reported as a total cholesterol: high-density lipoprotein [HDL] ratios); HDL ( n =13), low-density lipoprotein (LDL) ( n =8), triglycerides ( n =13). Not all studies that assessed lipid profiles provided statistical analyses of each lipid variable (e.g., p -values, effect sizes). 11 out of 18 studies (61.1%) assessing lipid profiles reported p -values for the lipids. 8 out of 18 studies (44.4%) reported measures of effect size for lipids. Three of the 9 studies (33.3%) reporting on total cholesterol reported statistically significant p -values. For HDL, 3 reported statistically significant p -values (23.1%). For LDL, 3 of the 8 studies reporting statistically significant p -values (<0.05). For triglycerides, 3 of 13 studies (23.1%) found significant p -values. Blood Pressure Out of the 186 studies, 27 total studies (14.5%) had blood pressure as an outcome. Of these, 16 were experimental studies (59.3%), and 11 were non-experimental (40.7%). In addition, 23 measured both systolic and diastolic blood pressure. Among the 27 studies that assessed blood pressure, 25 reported p -values or specifically stated the p -values associated with blood pressure were not statistically significant. Of the 25 studies that reported on p -values, 8 (32%) demonstrated statistically significant differences ( p <0.05). Studies varied in length, from cross-section to up to 3-year studies. Sample sizes ranged from n =30 to n =2293. Waist Circumference Out of 186 studies, 28 (15.1%) included waist circumference as an outcome measure, comprising 7 (25.0%) non-experimental and 21 (75.0%) experimental studies. 9 (31.1%) out of 28 studies reported significant p -values for changes in waist circumference or its association with sport participation. Most studies focused on school children, with experimental studies primarily using pre-test and post-test designs ranging from 7 days to 3 years. Sample sizes ranged from n =25 to n =4033. Overall, the findings suggest a limited relationship between youth sport participation and waist circumference. Nine studies (32.1%) reported a reduction in waist circumference or significant relationship between sport participation and waist circumference among participants. As examples of these, one study used two volleyball sessions 2 times per week as an exercise intervention ( n =25),(33) while another focused exclusively on obese adolescents and used soccer training sessions 3 times per week for 12-weeks as the intervention ( n =30).(34) Despite 9 studies reporting significant reductions or relationships between sport participation and waist circumference, the majority of studies measuring waist circumference did not report significant relationships with sport participation (67.9%). One strength of the studies using this outcome was the greater emphasis on experimental and quasi-experimental designs rather than cross-sectional designs. Systemic Inflammation, Glucose Levels/Insulin Resistance Due to the lack of studies that included systemic inflammation ( n =7) and glucose level/insulin resistance ( n =11), these results will not be presented further. Study Quality and Summary Figures See Supplemental Table 1 for complete results of study quality for the final sample. See Figure 3 for studies reporting a definition of sport and Figure 4 for number of studies using experimental and non-experimental designs by outcome. FIGURE 3. STUDIES REPORTING A DEFINITION OF SPORT [INSERT FIGURE 3] FIGURE 4. STUDY DESIGN BY OUTCOME [INSERT FIGURE 4] DISCUSSION This study presents the results from a systematic review addressing this primary research question: How does youth sport participation improve physical activity levels and cardiovascular disease risk factors in 5- to 14-year-old children? The secondary research question was: Are the outcomes different in underrepresented racial and ethnic groups compared to White children? This systematic review intentionally included a wide range of study designs to gain a more comprehensive synthesis of how the relationship between youth sport participation and physical health outcomes, including physical activity and CVD risk factors, has been assessed. The findings from this systematic review may help guide the design, outcome, and variable selection for future research looking for more rigorous examination of the relationship between youth sport participation and physical activity and cardiovascular disease risk factors. The present study had 4 key outcomes. First, to answer our primary research question, there was significant heterogeneity in definition of sport and physical activity measurement which limited our ability to make definitive conclusions. Second, there is a need for more rigorous studies, particularly experimental designs, examining the relationship between youth sport participation and quantitative health outcomes (i.e., CVD-related risk factors). Third, to answer our secondary research question, there was limited racial and ethnic diversity in study samples, hindering the generalizability of findings. Lastly, small sample sizes and heterogeneity in study designs and methodology limited conclusions for other outcome measures (i.e., BMI, waist circumference, blood pressure, lipids, ). Our first key outcome was that there was significant heterogeneity in definition of sport and physical activity measurement. Overall, there was a lack of consistency and transparency for the definition of sport. Despite the importance of standardizing the definition of youth sport in research studies,( 20 ) only 23 (12.4%) studies reported a definition of sport. While it is true that sport can be used for a variety of purposes (e.g., participation, competition, fitness, socializing), transparency in reporting explicitly what definition was used could be a major step in the right direction for improving youth sport participation literature. Separate from the definition of sport, physical activity was measured primarily as MVPA, but also often as step counts, total physical activity, or meeting physical activity guidelines via using different assessment tools, including objective and subjective measurements. Concurrent assessment of physical activity both objectively and subjectively can lead to a more comprehensive description of children’s physical activity,( 35 ) but it also creates difficulties when not standardized and comparing across studies. Similar to our review, the inconsistency in physical activity assessments has been identified as a challenge in previous systematic reviews, making it difficult to draw definitive conclusions. Additionally, many of the included studies were non-experimental and measured physical activity at only one time point, which limits the ability to establish causality. Overall, future research on the relationship between youth sport participation and physical activity would benefit from more consistent methodologies applied in rigorous experimental study designs. For the second key outcome, the present systematic review provides a snapshot of the existing literature assessing youth sport participation and CVD-related risk factors, but more rigorous studies are needed. There is an opportunity for researchers to consider additional studies using experimental designs. This review identified n = 106 non-experimental studies compared to n = 80 experimental studies. Among those experimental studies, outcomes, designs, sample sizes, and populations varied widely. Only 46 experimental studies were identified for physical activity (i.e., met inclusion criteria and passed full-text review), and given the wide range of countries and publication years (1995–2024), there is opportunity for greater work to be done in this area. Researchers may also want to consider different levels of structure for sport and physical activity intervention strategies as more organized sport interventions may facilitate more regular participation.( 36 ) However, it is possible that organized sport interventions may fail to equally engage all youth, particularly females or those less inclined toward competitive or performance-based environments.( 37 ) This discrepancy suggests that the traditional format of organized sports may inadvertently favor certain groups while excluding others, thus potentially perpetuating inequities in physical activity participation.( 38 ) Therefore, researchers may strive to design tailored physical activity interventions that are inclusive and responsive to the diverse preferences and needs of their research context and youth populations. For example, incorporating non-competitive activities or providing options for individualized participation could help address barriers faced by groups with low physical activity adherence, thereby enhancing the overall effectiveness of such programs.( 39 ) Developing equitable strategies is essential for maximizing physical activity benefits and fostering lifelong engagement in physical activity across diverse groups. To answer our secondary research question, few studies included racially or ethnically diverse samples. Therefore, definitive conclusions about the relationship between youth sport participation and CVD risk outcomes among youth from racial and ethnic minority backgrounds cannot be made from the present review. This finding is similar to previous literature that found youth sport relies on fixed racial categories and faces challenges in recruiting diverse participants, reinforcing systemic barriers that limit the inclusion and representation of minority groups in both participation and research.( 40 , 41 ) Moreover, many studies were not transparent in reporting the racial and ethnic demographics of their study samples. Some research argues for always including race and ethnicity in scientific reporting, whereas others believe in only reporting on race and ethnicity if those variables are specifically relevant to the research question. The problem with the latter is that researchers want to avoid presuming generalizability of their findings to all races and ethnicities as there are important social, cultural, and contextual differences that need to be acknowledged between populations. Future research would be well served to include more diverse samples, and if not, at least report on the racial and ethnic demographics of their study samples. For our other outcome measures, such as BMI, waist, lipids, and blood pressure, quantitative analyses and narrative descriptions were provided. However, these analyses were limited by the smaller sample sizes. The findings from the studies that included BMI as an outcome measure suggest that while control and intervention groups may experience small decreases in BMI, the changes were often not significant, indicating that further research is needed to explore potential factors influencing BMI outcomes and the efficacy of the interventions. Overall, many of the studies that were included in this systematic review suggest that physical activity in youths may be associated with or decrease BMI. Current literature supports this trend that higher activity levels correlate with lower BMI.( 42 ) While BMI was cited more frequently, current literature supports waist circumference as a more accurate indicator of CVD risks.( 43 ) Future research should prioritize including waist circumference as an outcome measure, rather than relying on BMI alone. LIMITATIONS This systematic review has several limitations that should be considered. First, there is considerable heterogeneity in the definitions and measurement of sport and physical activity, which complicates comparisons across studies. Therefore, we purposely limited our inferential statistics to take a more conservative approach to interpretation. Second, the diverse study designs and methodological limitations, including small sample sizes for certain cardiovascular disease (CVD) outcome measures, restrict the ability to draw definitive conclusions. Third, meta-analyses were not conducted due to significant heterogeneity between study types, methodology in outcome reporting, and statistical reporting. Combining data in a meta-analyses with this high degree of heterogeneity could lead to misrepresenting the data and conclusions. Fourth, the equity challenges inherent in structured interventions and the lack of diversity in study samples further limit the generalizability of findings across diverse populations. Finally, contextual differences across studies reduce the applicability of the results to broader settings. Despite the methodological limitations of the evidence, presenting the results of the current state of research and associated gaps in this space is important to inform researchers planning future studies. Abbreviations BMI: body mass index MVPA: moderate-to-vigorous physical activity PROSPERO: international prospective roster of systematic reviews PRISMA: preferred reporting items for systematic review and meta-analyses CVD: cardiovascular disease Declarations ETHICAL APPROVAL AND CONSENT TO PARTICIPATE Due to the characteristics of this study design, ethical approval was not required. As this was a systematic review, informed consent was not required as no participants were recruited and no primary data were collected. AUTHOR CONTRIBUTIONS KK, PFS, MW, and VMK conceptualized the study. KK, JG, PFS, JW, JO, and JFK wrote the paper with valuable inputs from AE, JL, AC, MW, and VMK. KK, PFS, JG, JW, JO, AE, and JL contributed to the screening and extraction. AC, MW, and VMK provided critical review of the original manuscript. All authors have read and approved the final manuscript. COMPETING INTERESTS The authors declare that they have no competing interests. DATA AVAILABILITY No new data was generated as part of this review. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. FUNDING This work is supported by an American Heart Association Career Development Award (24CDA1038890). DOI: 10.58275/AHA.24CDA1038890.pc.gr.198245 ACKNOWLEDGEMENTS We would like to acknowledge the Indiana University librarians who assisted with the development of the initial search strategy, as well as other Hoosier Sport team members that contributed to the protocol development and publication. References Javed Z, Haisum Maqsood M, Yahya T, Amin Z, Acquah I, Valero-Elizondo J, et al. Race, racism, and cardiovascular health: Applying a social determinants of health framework to racial/ethnic disparities in cardiovascular disease. Circ Cardiovasc Qual Outcomes. 2022;15(1):e007917. World Health Organization. Global Health Estimates 2020: Deaths by Cause. 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Contribution of youth sport participation to physical activity levels and cardiovascular disease risk factors in 5-year-old to 14-year-old children: a study protocol for systematic review and meta-analysis. BMJ Open. 2024;14(5):e081524. R Core Team R. R: A language and environment for statistical computing. 2013. Basterfield L, Reilly JK, Pearce MS, Parkinson KN, Adamson AJ, Reilly JJ, et al. Longitudinal associations between sports participation, body composition and physical activity from childhood to adolescence. J Sci Med Sport. 2015;18(2):178-82. Machado-Rodrigues AM, Coelho e Silva MJ, Mota J, Santos RM, Cumming SP, Malina RM. Physical activity and energy expenditure in adolescent male sport participants and nonparticipants aged 13 to 16 years. J Phys Act Health. 2012;9(5):626-33. Guagliano JM, Rosenkranz RR, Kolt GS. Girls' physical activity levels during organized sports in Australia. Med Sci Sports Exerc. 2013;45(1):116-22. Domazet SL, Moller NC, Stockel JT, Ried-Larsen M. Objectively measured physical activity in Danish after-school cares: Does sport certification matter? Scand J Med Sci Sports. 2015;25(6):e646-54. Broglio LP, Gonelli PRG, Costa CdO, Sajorato TdC, Massarutto V, Cesar MdC. Volleyball as an exercise program for overweight and obese female adolescents. Rev Brasil Med Esporte. 2021;27(6):545-8. Vasconcellos F, Seabra A, Cunha F, Montenegro R, Penha J, Bouskela E, et al. Health markers in obese adolescents improved by a 12-week recreational soccer program: a randomised controlled trial. J Sport Sci. 2016;34(6):564-75. Marasso D, Lupo C, Collura S, Rainoldi A, Brustio PR. Subjective versus objective measure of physical activity: A systematic review and meta-analysis of the convergent validity of the physical activity questionnaire for children (PAQ-C). Int J Environ Res Public Health. 2021;18(7). Willinger N, Steele J, Atkinson L, Liguori G, Jimenez A, Mann S, et al. Effectiveness of structured physical activity interventions through the evaluation of physical activity levels, adoption, retention, maintenance, and adherence rates: A systematic review and meta-analysis. J Phys Act Health. 2021;18(1):116-29. Oja L, Piksoot J. Physical activity and sports participation among adolescents: Associations with sports-related knowledge and attitudes. Int J Environ Res Public Health. 2022;19(10). Tamura K, Martinez MF, Deng Y, Heneghan J, Weatherwax C, Velmurugan K, et al. Modeling health and economic outcomes of eliminating sex disparities in youth physical activity. JAMA Netw Open. 2024;7(11):e2446775. Hyde ET, Omura JD, Fulton JE, Lee SM, Piercy KL, Carlson SA. Disparities in youth sports participation in the U.S., 2017-2018. Am J Prev Med. 2020;59(5):e207-e10. Botchwey N, Conway TL, Floyd M, Hipp A, Kim A, Pollack Porter KM, et al. Challenges recruiting diverse youth for physical activity research. Prev Med. 2020;131:105888. Camiré M. Assemblage thinking as attunement to race, gender, and sexuality in youth sport research. J Sport Soc Issues. 2023;47(1):56-74. Ding C, Jiang Y, editors. The relationship between body mass index and physical fitness among Chinese university students: results of a longitudinal study. Healthcare; 2020: MDPI. Staiano AE, Reeder BA, Elliott S, Joffres MR, Pahwa P, Kirkland SA, et al. Body mass index versus waist circumference as predictors of mortality in Canadian adults. Int J Obes (Lond). 2012;36(11):1450-4. Supplementary Files SupplementalFile1PRISMA2020checklist.docx SupplementalFile2SearchStrategy.doc SupplementalFile3.TABLEStudyQualityTool.xlsx SupplementalFile4FullListofStudies.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 08 Oct, 2025 Reviewers invited by journal 08 Oct, 2025 Editor assigned by journal 11 Jun, 2025 First submitted to journal 27 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6762942","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":526502222,"identity":"ca04b1f5-30c1-4654-b7a7-ff4e853fcf69","order_by":0,"name":"Kyle A. 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review","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCardiovascular disease (CVD), the leading global cause of mortality, accounts for 18\u0026nbsp;million deaths annually and disproportionately affects underrepresented racial and ethnic groups.(\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Atherosclerosis, a major contributor to CVD, begins as early as childhood, with many health-related risk behaviors established during this time.(\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Physical inactivity is a key modifiable lifestyle behavior that helps reduce CVD risk by lowering adiposity, improving blood pressure, and enhancing vascular and immune function.(\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) In line with supporting long-term health and wellness, the Department of Health and Human Services recommends that children engage in at least 60 minutes of moderate-to-vigorous physical activity per day.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Despite this recommendation, fewer than 25% of U.S. youth meet the recommended physical activity guidelines, with the percentage being even smaller among the 12\u0026ndash;17-year-olds compared to the 6\u0026ndash;11-year-olds.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Initiatives that support youth toward physical activity participation may subsequently reduce the risk of CVD.\u003c/p\u003e\u003cp\u003e One potential way to support youth toward meeting physical activity guidelines is through sport. In line with previous literature (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), the present study defines youth sports as structured activities requiring physical effort or skill that include recreational programs, as well as development initiatives where sport is central. Sports based initiatives can provide sustained engagement in physical activity from a young age by focusing on more enjoyable activities than traditional exercise programs.(\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) Youth sports offer a potentially promising approach to reduce CVD risk factors like high blood pressure, cholesterol, and insulin resistance,(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) but research results have been inconsistent.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) Some studies highlight physical benefits, while others show limited or no impact.(\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) For instance, a 2019 review of U.S. sport-based youth development programs found most interventions prioritized cognitive, social, or lifestyle outcomes over physical health.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) A review of the relationship between youth sport participation and cardiovascular health markers found potential benefits for cardiovascular function, but few studies met rigorous quality assessment criteria, and the review only included studies of intima-media thickness and blood pressure.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) Lastly, inconsistent definitions of \"sport\" across the studies complicate conclusions from existing research regarding the potential benefit of youth sport participation on CVD risk factors. Therefore, a comprehensive review that includes a broader range of cardiovascular health markers and a clear, robust definition of youth sports is needed to better understand the relationship between these factors and to guide future intervention research.\u003c/p\u003e\u003cp\u003eFurther, research rarely explores differences among racial and ethnic groups, despite disparities in prevalence of CVD(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and rates of sport participation.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) Youth from racial and ethnic minority backgrounds are at a higher risk of developing CVD and are less likely to meet recommended physical activity guidelines.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Additionally, financial and logistical barriers often limit their access to sports programs. In fact, while over 50% of youth participate in a sports team or after school sport lesson, this percentage drops to 33% if the family is below the poverty level and 41% if the family is between 100% and 199% of the poverty level.(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) Given these disparities, examining the impact of sports participation on physical activity and cardiovascular health outcomes in this population is advisable. A better understanding of these relationships can help inform the development of targeted interventions to improve health equity and guide culturally tailored health strategies for underrepresented populations.\u003c/p\u003e\u003cp\u003eThe present study uses a definition of youth sport from previously published research: physical exertion and/or physical skill in a structured or organized setting for training and/or competition.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) This definition includes competitive, recreational, sport-based youth development, and physical activity programs/interventions that have sport as a critical component of programming/intervention. The primary objective of this systematic review was to evaluate the association between youth sport participation and physical activity levels, as well as CVD risk factors, in children aged 5 to 14 years. A secondary objective was to investigate whether outcomes differed across racial and ethnic groups. CVD risk factors examined include activity intensity, duration, and frequency, as well as blood pressure, lipid profiles, BMI, waist circumference, inflammation, and glucose/insulin resistance. The findings from this systematic review may identify existing gaps in research, weaknesses in methodology, and opportunities for future research.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis systematic review protocol is registered with PROSPERO (CRD42023427219) and follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (see Supplemental File 1 for the PRISMA checklist).(26) The search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Search development was conducted in collaboration with librarians from the Indiana University Bloomington Library. The study was conducted from September 2023 to April 2025, allowing sufficient time for literature review, eligibility assessment, quality evaluation, data synthesis, and manuscript preparation.\u003c/p\u003e\n\u003cp\u003eThe search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Eligible studies included observational, quasi-experimental, or experimental research conducted on youth (5-14 years of age) from any health background, examining the relationship between sport participation and either physical activity levels or CVD risk factors. To be included, studies needed to report on at least one of the following outcomes: (a) physical activity levels, (b) blood pressure, (c) lipid fractions, (d) body mass index, (e) central adiposity, (f) systemic inflammation, or (g) glucose levels/insulin resistance. For a full description and discussion of the search strategy (Supplemental File 2), initial title and abstract screening, full-text review, study selection, and amendments, please reference the published protocol paper.(27)\u003c/p\u003e\n\u003ch2\u003eQuality Assessment\u003c/h2\u003e\n\u003cp\u003eFour primary reviewers (JG, JW, JO, AE) conducted the initial quality assessments using Covidence systematic review management software. Each study was independently reviewed by two of our primary reviewers (JG, JW, JO, AE), with disagreements resolved by a third member. Study quality was assessed using a rating tool based on the Methods Guide for Effectiveness and Comparative Effectiveness Reviews developed by the Agency for Healthcare Research and Quality. This quality assessment tool was selected due to the broad study inclusion criteria of observational, quasi-experimental, and experimental studies, and the absence of a tool for comprehensively assessing the quality of observational studies that did not include direct group comparison or intervention. See Supplemental File 3 for the full quality assessment tool.\u003c/p\u003e\n\u003ch2\u003eData Extraction\u003c/h2\u003e\n\u003cp\u003eThe data extracted from each study included general information (e.g., author, funding, conflicts of interest, and data collection years), participant demographics (e.g., age, sex, race, and ethnicity), methods (e.g., groupings, timepoints, sport definition, and type of analysis), results (e.g., means, standard deviations, odds ratios, and hazard ratios), and conclusions. The primary outcomes of interest were physical activity levels, blood pressure, lipid fractions, body mass index, central adiposity, systemic inflammation, and glucose levels/insulin resistance.\u003c/p\u003e\n\u003ch2\u003eData Synthesis\u003c/h2\u003e\n\u003cp\u003eThis systematic review incorporated diverse research methods, including varying study designs, settings, measurement techniques, participant characteristics, and outcomes. A combined narrative approach with descriptive and limited inferential analysis was used to synthesize findings from heterogeneous studies.\u0026nbsp;Results were presented either as the full sample or in two categories: (1) experimental and (2) non-experimental studies. This categorization was done to synthesize findings for the whole sample by grouping studies with limited internal validity (i.e., observational categorized as non-experimental) and another group as those with more robust internal validity (i.e., experimental and quasi-experimental). Meta-analyses were not conducted based on significant heterogeneity between study types, methodology in outcome reporting, and statistical reporting. Statistical analyses were performed in R (v4.2.2),(28) with significance set at p \u0026le; 0.05.\u003c/p\u003e\n\u003cp\u003eKK, JG, and JW, and 4 other research assistants independently extracted data and each study required two independent extractions to be sent for consensus to ensure alignment. Disagreements were resolved by a third team member. Covidence software and Excel were used for data management. Racial and ethnic representation was summarized narratively and quantified where possible, contextualizing results within the quality of evidence.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003eOverview\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe literature search in this systematic review initially returned 13,674 publications.\u0026nbsp;12,286 studies were screened; 379 underwent full text review, and 186 studies included in the final sample.\u0026nbsp;After the title, abstract, and full text review process, 186 studies were evaluated in the final sample. Sample sizes ranged from \u003cem\u003en\u003c/em\u003e=10 to\u003cem\u003e\u0026nbsp;n\u003c/em\u003e=35,367. An overview of the screening process is in Figure 1. See Supplemental File 4 for the full list of included studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 1.\u0026nbsp;\u003c/strong\u003ePRISMA DIAGRAM\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e[INSERT FIGURE 1. PRISMA DIAGRAM]\u003c/p\u003e\n\u003cp\u003eResults include a wide range of heterogeneous data across 7 CVD risk-related outcome categories. Due to the heterogeneity of the data, the majority of results below are descriptive rather than inferential. Results are organized and presented by CVD risk-related outcome. See Table 1 for a descriptive summary of included studies. See Figure 2 for the year of publication distribution.\u003c/p\u003e\n\u003cp\u003eTABLE 1. Overall Descriptive Summary of Included Studies\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Studies\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Experimental Studies\u0026nbsp;\u003c/strong\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperimental Studies\u0026nbsp;\u003c/strong\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eIncluded studies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e186 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e106 (57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e80 (43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry Study Was Conducted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eAustralia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e20 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eBrazil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e20 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e10 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eDenmark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e6 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e3 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003ePortugal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e7 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eUnited Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e7 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e23 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e76 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e43 (56.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e33 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition of Sport Reported\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e23 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e18 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e163 (87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e88 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e75 (45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace Reported\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e44 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e28 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e142 (76.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e78 (54.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e64 (45.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRaces Reported \u0026amp; Included*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eBlack or African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e26 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e15 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e11 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e27 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e19 (70.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e11 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e5 (45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e6 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eHispanic or Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e25 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e15 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eAmerican Indiana or Alaskan Native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e4 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e22 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e14 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8 (36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eOnly Females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e23 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e8 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e15 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eOnly Males\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e7 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e9 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e138 (74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e90 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e48 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eDid Not Report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e2 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCVD-Related Outcome Measure*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e119 (64.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e73 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e46 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e117 (62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e66 (56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e51 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eWaist circumference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e28 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e7 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e21 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eBlood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e27 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e11 (40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eLipids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e18 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e6 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eGlucose / insulin resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e11 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e2 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e9 (81.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eSystemic inflammation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e7 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e2 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect Size Reported\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e62 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e23 (37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e124 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e83 (66.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e41 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 576px;\"\u003e\n \u003cp\u003eNote: The numbers in the table represent studies included in the final sample. The average age of the final sample was 11.48 (SD=2.20). The experimental group includes experimental and quasi-experimental studies. * = % will not equal 100% since not all studies reported on race.\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\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 2.\u0026nbsp;\u003c/strong\u003eYEAR OF PUBLICATION FOR INCLUDED STUDIES\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e[INSERT FIGURE 2]\u003c/p\u003e\n\u003ch2\u003ePhysical Activity\u003c/h2\u003e\n\u003cp\u003eOut of 186 studies, 119 included a measure of physical activity. Of these 119 studies, 46 (38.7%) were experimental and 73 studies (61.3%) were non-experimental. Measures of physical activity included moderate-to-vigorous physical activity (MVPA), step counts, total physical activity levels, and participation in sports programs. Across the studies, MVPA was the most frequently reported physical activity measure, and it was typically reported as either minutes per day or as a percentage of participants who attained MVPA recommendations. Twenty-eight out of 65 studies (43.1%) that had a measure of MVPA demonstrated significant differences in MVPA. For instance, MVPA levels improved from 29.2 to 31.5 minutes/day and from 73.8 to 96.9 minutes/day following participation in organized sports programs.(29, 30) Sports participation often correlated with higher MVPA; for example, boys participating in sports reported 109 to 118 minutes/day compared to girls\u0026rsquo; 75 to 84 minutes/day (\u003cem\u003ep\u003c/em\u003e = 0.001).(30, 31) Similarly, in a study measuring physical activity with step counts (used in 8 studies), higher levels of physical activity were found in boys, with boys achieving 11,898 steps/day compared to girls\u0026rsquo; 10,068 steps/day.(32) Additionally, sport participation was used as a proxy measure for physical activity in 30 studies (16.1% of included studies).\u0026nbsp;Effect sizes varied widely, and they were reported in 23 out of 119 studies (19.3%) that included physical activity as an outcome measure.\u003c/p\u003e\n\u003ch2\u003eBody Mass Index\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eOut of 186 studies, 117 included BMI as an outcome measure (66 non-experimental and 51 experimental). Out of the 117 studies that assessed BMI, 75 studies (64.1%) assessed the significance of BMI-related relationships, and 41 studies (35.0%) reported statistically significant BMI-related relationships. The target population for these studies were primarily middle-school age children, with the experimental studies following pre- to post-test designs. Experimental designs varied in duration, with the shortest being 2 days and the longest being 621 days. Interventions included in-school settings, after-school settings, and a combination of in-school and at-home activities.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eLipids\u003c/h2\u003e\n\u003cp\u003eLipid profiles were reported in 18 (9.7%) out of 186 studies. Of these 18 studies, 12 (66.7%) were categorized as experimental and 6 (33.3%) were non-experimental. Various lipid measures were reported in the following numbers of studies: Total cholesterol (\u003cem\u003en\u003c/em\u003e=9 studies; 2 were reported as a total cholesterol: high-density lipoprotein [HDL] ratios); HDL (\u003cem\u003en\u003c/em\u003e=13), low-density lipoprotein (LDL) (\u003cem\u003en\u003c/em\u003e=8), triglycerides (\u003cem\u003en\u003c/em\u003e=13). Not all studies that assessed lipid profiles provided statistical analyses of each lipid variable (e.g., \u003cem\u003ep\u003c/em\u003e-values, effect sizes). 11 out of 18 studies (61.1%) assessing lipid profiles reported \u003cem\u003ep\u003c/em\u003e-values for the lipids. 8 out of 18 studies (44.4%) reported measures of effect size for lipids. Three of the 9 studies (33.3%) reporting on total cholesterol reported statistically significant \u003cem\u003ep\u003c/em\u003e-values. For HDL, 3 reported statistically significant\u003cem\u003e\u0026nbsp;p\u003c/em\u003e-values (23.1%). For LDL, 3 of the 8 studies reporting statistically significant \u003cem\u003ep\u003c/em\u003e-values (\u0026lt;0.05). For triglycerides, 3 of 13 studies (23.1%) found significant \u003cem\u003ep\u003c/em\u003e-values.\u003c/p\u003e\n\u003ch2\u003eBlood Pressure\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eOut of the 186 studies, 27 total studies (14.5%) had blood pressure as an outcome. Of these, 16 were experimental studies (59.3%), and 11 were non-experimental (40.7%). In addition, 23 measured both systolic and diastolic blood pressure. Among the 27 studies that assessed blood pressure, 25 reported \u003cem\u003ep\u003c/em\u003e-values or specifically stated the \u003cem\u003ep\u003c/em\u003e-values associated with blood pressure were not statistically significant. Of the 25 studies that reported on \u003cem\u003ep\u003c/em\u003e-values, 8 (32%) demonstrated statistically significant differences (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Studies varied in length, from cross-section to up to 3-year studies. Sample sizes ranged from \u003cem\u003en\u003c/em\u003e=30 to \u003cem\u003en\u003c/em\u003e=2293.\u003c/p\u003e\n\u003ch2\u003eWaist Circumference\u003c/h2\u003e\n\u003cp\u003eOut of 186 studies, 28 (15.1%) included waist circumference as an outcome measure, comprising 7 (25.0%) non-experimental and 21 (75.0%) experimental studies.\u0026nbsp;9 (31.1%) out of 28 studies\u0026nbsp;reported\u0026nbsp;significant \u003cem\u003ep\u003c/em\u003e-values for changes in waist circumference or its\u0026nbsp;association with sport participation.\u0026nbsp;Most studies\u0026nbsp;focused on\u0026nbsp;school children, with experimental studies primarily using pre-test and post-test designs ranging from 7 days to 3 years. Sample sizes ranged from \u003cem\u003en\u003c/em\u003e=25 to \u003cem\u003en\u003c/em\u003e=4033.\u003c/p\u003e\n\u003cp\u003eOverall, the findings suggest a limited relationship between youth sport participation and waist circumference. Nine studies (32.1%) reported a reduction in waist circumference or significant relationship between sport participation and waist circumference among participants. As examples of these, one study used two volleyball sessions 2 times per week as an exercise intervention (\u003cem\u003en\u003c/em\u003e=25),(33) while another focused exclusively on obese adolescents and used soccer training sessions 3 times per week for 12-weeks as the intervention (\u003cem\u003en\u003c/em\u003e=30).(34)\u0026nbsp;Despite 9 studies reporting significant reductions or relationships between sport participation and waist circumference, the majority of studies measuring waist circumference did not report significant relationships with sport participation (67.9%). One strength of the studies using this outcome was the greater emphasis on experimental and quasi-experimental designs rather than cross-sectional designs.\u003c/p\u003e\n\u003ch2\u003eSystemic Inflammation, Glucose Levels/Insulin Resistance\u003c/h2\u003e\n\u003cp\u003eDue to the lack of studies that included systemic inflammation (\u003cem\u003en\u003c/em\u003e=7) and glucose level/insulin resistance (\u003cem\u003en\u003c/em\u003e=11), these results will not be presented further.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStudy Quality and Summary Figures\u003c/h2\u003e\n\u003cp\u003eSee Supplemental Table 1 for complete results of study quality for the final sample. See Figure 3 for studies reporting a definition of sport and Figure 4 for number of studies using experimental and non-experimental designs by outcome.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 3.\u003c/strong\u003e STUDIES REPORTING A DEFINITION OF SPORT\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e[INSERT FIGURE 3]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 4.\u003c/strong\u003e STUDY DESIGN BY OUTCOME\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e[INSERT FIGURE 4]\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study presents the results from a systematic review addressing this primary research question: \u003cem\u003eHow does youth sport participation improve physical activity levels and cardiovascular disease risk factors in 5- to 14-year-old children?\u003c/em\u003e The secondary research question was: \u003cem\u003eAre the outcomes different in underrepresented racial and ethnic groups compared to White children?\u003c/em\u003e This systematic review intentionally included a wide range of study designs to gain a more comprehensive synthesis of how the relationship between youth sport participation and physical health outcomes, including physical activity and CVD risk factors, has been assessed. The findings from this systematic review may help guide the design, outcome, and variable selection for future research looking for more rigorous examination of the relationship between youth sport participation and physical activity and cardiovascular disease risk factors.\u003c/p\u003e\u003cp\u003eThe present study had 4 key outcomes. First, to answer our primary research question, there was significant heterogeneity in definition of sport and physical activity measurement which limited our ability to make definitive conclusions. Second, there is a need for more rigorous studies, particularly experimental designs, examining the relationship between youth sport participation and quantitative health outcomes (i.e., CVD-related risk factors). Third, to answer our secondary research question, there was limited racial and ethnic diversity in study samples, hindering the generalizability of findings. Lastly, small sample sizes and heterogeneity in study designs and methodology limited conclusions for other outcome measures (i.e., BMI, waist circumference, blood pressure, lipids, ).\u003c/p\u003e\u003cp\u003eOur first key outcome was that there was significant heterogeneity in definition of sport and physical activity measurement. Overall, there was a lack of consistency and transparency for the definition of sport. Despite the importance of standardizing the definition of youth sport in research studies,(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) only 23 (12.4%) studies reported a definition of sport. While it is true that sport can be used for a variety of purposes (e.g., participation, competition, fitness, socializing), transparency in reporting explicitly what definition was used could be a major step in the right direction for improving youth sport participation literature. Separate from the definition of sport, physical activity was measured primarily as MVPA, but also often as step counts, total physical activity, or meeting physical activity guidelines via using different assessment tools, including objective and subjective measurements. Concurrent assessment of physical activity both objectively and subjectively can lead to a more comprehensive description of children\u0026rsquo;s physical activity,(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) but it also creates difficulties when not standardized and comparing across studies. Similar to our review, the inconsistency in physical activity assessments has been identified as a challenge in previous systematic reviews, making it difficult to draw definitive conclusions. Additionally, many of the included studies were non-experimental and measured physical activity at only one time point, which limits the ability to establish causality. Overall, future research on the relationship between youth sport participation and physical activity would benefit from more consistent methodologies applied in rigorous experimental study designs.\u003c/p\u003e\u003cp\u003eFor the second key outcome, the present systematic review provides a snapshot of the existing literature assessing youth sport participation and CVD-related risk factors, but more rigorous studies are needed. There is an opportunity for researchers to consider additional studies using experimental designs. This review identified \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;106 non-experimental studies compared to \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;80 experimental studies. Among those experimental studies, outcomes, designs, sample sizes, and populations varied widely. Only 46 experimental studies were identified for physical activity (i.e., met inclusion criteria and passed full-text review), and given the wide range of countries and publication years (1995\u0026ndash;2024), there is opportunity for greater work to be done in this area. Researchers may also want to consider different levels of structure for sport and physical activity intervention strategies as more organized sport interventions may facilitate more regular participation.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) However, it is possible that organized sport interventions may fail to equally engage all youth, particularly females or those less inclined toward competitive or performance-based environments.(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) This discrepancy suggests that the traditional format of organized sports may inadvertently favor certain groups while excluding others, thus potentially perpetuating inequities in physical activity participation.(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) Therefore, researchers may strive to design tailored physical activity interventions that are inclusive and responsive to the diverse preferences and needs of their research context and youth populations. For example, incorporating non-competitive activities or providing options for individualized participation could help address barriers faced by groups with low physical activity adherence, thereby enhancing the overall effectiveness of such programs.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) Developing equitable strategies is essential for maximizing physical activity benefits and fostering lifelong engagement in physical activity across diverse groups.\u003c/p\u003e\u003cp\u003eTo answer our secondary research question, few studies included racially or ethnically diverse samples. Therefore, definitive conclusions about the relationship between youth sport participation and CVD risk outcomes among youth from racial and ethnic minority backgrounds cannot be made from the present review. This finding is similar to previous literature that found youth sport relies on fixed racial categories and faces challenges in recruiting diverse participants, reinforcing systemic barriers that limit the inclusion and representation of minority groups in both participation and research.(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) Moreover, many studies were not transparent in reporting the racial and ethnic demographics of their study samples. Some research argues for always including race and ethnicity in scientific reporting, whereas others believe in only reporting on race and ethnicity if those variables are specifically relevant to the research question. The problem with the latter is that researchers want to avoid presuming generalizability of their findings to all races and ethnicities as there are important social, cultural, and contextual differences that need to be acknowledged between populations. Future research would be well served to include more diverse samples, and if not, at least report on the racial and ethnic demographics of their study samples.\u003c/p\u003e\u003cp\u003eFor our other outcome measures, such as BMI, waist, lipids, and blood pressure, quantitative analyses and narrative descriptions were provided. However, these analyses were limited by the smaller sample sizes. The findings from the studies that included BMI as an outcome measure suggest that while control and intervention groups may experience small decreases in BMI, the changes were often not significant, indicating that further research is needed to explore potential factors influencing BMI outcomes and the efficacy of the interventions. Overall, many of the studies that were included in this systematic review suggest that physical activity in youths may be associated with or decrease BMI. Current literature supports this trend that higher activity levels correlate with lower BMI.(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) While BMI was cited more frequently, current literature supports waist circumference as a more accurate indicator of CVD risks.(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) Future research should prioritize including waist circumference as an outcome measure, rather than relying on BMI alone.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eLIMITATIONS\u003c/h2\u003e\u003cp\u003eThis systematic review has several limitations that should be considered. First, there is considerable heterogeneity in the definitions and measurement of sport and physical activity, which complicates comparisons across studies. Therefore, we purposely limited our inferential statistics to take a more conservative approach to interpretation. Second, the diverse study designs and methodological limitations, including small sample sizes for certain cardiovascular disease (CVD) outcome measures, restrict the ability to draw definitive conclusions. Third, meta-analyses were not conducted due to significant heterogeneity between study types, methodology in outcome reporting, and statistical reporting. Combining data in a meta-analyses with this high degree of heterogeneity could lead to misrepresenting the data and conclusions. Fourth, the equity challenges inherent in structured interventions and the lack of diversity in study samples further limit the generalizability of findings across diverse populations. Finally, contextual differences across studies reduce the applicability of the results to broader settings. Despite the methodological limitations of the evidence, presenting the results of the current state of research and associated gaps in this space is important to inform researchers planning future studies.\u003c/p\u003e\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eMVPA:\u0026nbsp;moderate-to-vigorous physical activity\u003c/p\u003e\n\u003cp\u003ePROSPERO: international prospective roster of systematic reviews\u003c/p\u003e\n\u003cp\u003ePRISMA: preferred reporting items for systematic review and meta-analyses\u003c/p\u003e\n\u003cp\u003eCVD: cardiovascular disease\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eETHICAL APPROVAL AND CONSENT TO PARTICIPATE\u003c/p\u003e\n\u003cp\u003eDue to the characteristics of this study design, ethical approval was not required. As this was a systematic review, informed consent was not required as no participants were recruited and no primary data were collected.\u003c/p\u003e\n\u003cp\u003eAUTHOR CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003eKK, PFS, MW, and VMK conceptualized the study. KK, JG, PFS, JW, JO, and JFK wrote the paper with valuable inputs from AE, JL, AC, MW, and VMK. KK, PFS, JG, JW, JO, AE, and JL contributed to the screening and extraction. AC, MW, and VMK provided critical review of the original manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eCOMPETING INTERESTS\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eDATA AVAILABILITY\u003c/p\u003e\n\u003cp\u003eNo new data was generated as part of this review. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eFUNDING\u003c/p\u003e\n\u003cp\u003eThis work is supported by an American Heart Association Career Development Award (24CDA1038890). DOI: 10.58275/AHA.24CDA1038890.pc.gr.198245\u003c/p\u003e\n\u003cp\u003eACKNOWLEDGEMENTS\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the Indiana University librarians who assisted with the development of the initial search strategy, as well as other Hoosier Sport team members that contributed to the protocol development and publication.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJaved Z, Haisum Maqsood M, Yahya T, Amin Z, Acquah I, Valero-Elizondo J, et al. Race, racism, and cardiovascular health: Applying a social determinants of health framework to racial/ethnic disparities in cardiovascular disease. 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Int J Obes (Lond). 2012;36(11):1450-4.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"systematic-reviews","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sysr","sideBox":"Learn more about [Systematic Reviews](http://systematicreviewsjournal.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/sysr/default.aspx","title":"Systematic Reviews","twitterHandle":"@MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"public health, sports medicine, cardiovascular health, sport-based youth development","lastPublishedDoi":"10.21203/rs.3.rs-6762942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6762942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCardiovascular disease (CVD) causes approximately 18\u0026nbsp;million deaths annually, disproportionately affecting underrepresented racial and ethnic groups. Participation in youth sports has been suggested as a potential strategy to improve CVD-related risk factors, but studies on the topic have produced mixed results. The primary objective of this systematic review was to evaluate the relationship between youth sport participation, physical activity levels, and CVD risk factors, in children aged 5 to 14 years. A secondary objective was to investigate whether relationships differed across racial and ethnic groups.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe search encompassed studies published in English, Spanish, or Portuguese between January 1995 and April 2024, utilizing five databases: PubMed, Medline, EMBASE, Cochrane Library, and SPORTDiscus. Eligible studies included experimental, quasi-experimental, or observational studies conducted on youth (5\u0026ndash;14 years of age) from any health background. To be included, studies needed to report on the relationship of youth sport participation to at least one of the following outcomes: (a) physical activity levels, (b) blood pressure, (c) lipid fractions, (d) body mass index, (e) central adiposity, (f) systemic inflammation, or (g) glucose levels/insulin resistance. Primarily quantitative descriptive analyses were used to synthesize studies by outcome.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003e We screened 12,286 studies; 379 underwent full text review, and 186 studies included in the final sample. The five most commonly reported CVD-risk related outcomes were: physical activity (119 studies), body mass index (117 studies), waist circumference (28 studies), blood pressure (27 studies), and lipid profiles (18 studies). 23 studies (12.4%) reported a definition of sport. Physical activity was measured primarily using MVPA (n\u0026thinsp;=\u0026thinsp;65), sport participation (n\u0026thinsp;=\u0026thinsp;30), or step counts (n\u0026thinsp;=\u0026thinsp;8). Twenty-eight out of 65 studies (43.1%) that had a measure of MVPA demonstrated significant differences in MVPA. Out of 117 studies that assessed BMI, 75 studies (64.1%) assessed the significance of BMI-related relationships, and 41 studies (35.0%) reported statistically significant BMI-related relationships. 62 studies (33.3%) reported effect size estimates.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003e The present review indicated a need for more consistent and transparent methodology in youth sport research related to physical activity and CVD risk factors. Studies clearly stating the operationalized definition of youth sport and diverse and generalizable samples were lacking.\u003c/p\u003e\u003ch2\u003eSystematic Review Registration:\u003c/h2\u003e\u003cp\u003ePROSPERO CRD42023427219\u003c/p\u003e","manuscriptTitle":"The relationship between youth sport participation, physical activity levels, and cardiovascular disease risk factors in 5- to 14-year-old children: a systematic review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:18:12","doi":"10.21203/rs.3.rs-6762942/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-10-08T14:33:03+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-08T12:04:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-12T03:52:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Systematic Reviews","date":"2025-05-27T20:26:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"systematic-reviews","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sysr","sideBox":"Learn more about [Systematic Reviews](http://systematicreviewsjournal.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/sysr/default.aspx","title":"Systematic Reviews","twitterHandle":"@MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"afeaab48-8594-426d-9c8a-6c24dfc1ea7b","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-10T12:39:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 23:18:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6762942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6762942","identity":"rs-6762942","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}