{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T14:05:21Z","timestamp":1789567521864,"version":"build-2803163510"},"reference-count":77,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Serious Games"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Exergaming, or active video gaming, may make physical activity more engaging for children and adolescents. Earlier reviews have focused on activity, adiposity, fitness, or psychosocial outcomes, leaving effects on glycemic and lipid biomarkers uncertain. Their cardiometabolic relevance warrants synthesis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review and meta-analysis evaluated the effects of exergaming on glucose and lipid metabolism in children and adolescents, and explored potential moderators.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), we searched PubMed, Embase, Scopus, Web of Science, the Psychology and Behavioral Sciences Collection, and CENTRAL from inception to April 27, 2026, with backward and forward citation searching. Eligible controlled interventions enrolled participants aged \u226418 years and compared exergaming with nonexergaming controls. Outcomes were glucose, insulin, total cholesterol (TC), triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Standardized mean differences (Hedges\n                      <jats:italic>g<\/jats:italic>\n                      ) were pooled with inverse-variance random-effects models and the Hartung-Knapp-Sidik-Jonkman adjustment. We reported 95% CIs, heterogeneity, 95% prediction intervals (PIs), risk of bias, and GRADE (Grading of Recommendations Assessment, Development and Evaluation) certainty; subgroup analysis, meta-regression, and leave-one-out sensitivity analyses explored moderators and estimate stability.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Ten controlled intervention studies involving 732 participants were included. Pooled effects were nonsignificant for glucose (9 studies, 528 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.16, 95% CI \u22120.57 to 0.24; PI \u22121.12 to 0.79), insulin (5 studies, 308 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.06, 95% CI \u22120.35 to 0.23; PI \u22120.39 to 0.27), TC (9 studies, 510 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.39, 95% CI \u22121.11 to 0.33; PI \u22121.70 to 0.93), triglycerides (9 studies, 510 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.17, 95% CI \u22120.50 to 0.17; PI \u22120.88 to 0.55), and HDL-C (9 studies, 510 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.14, 95% CI \u22120.34 to 0.06; PI \u22120.35 to 0.07; effect sizes were reverse-oriented so that negative values favored exergaming). LDL-C showed a small favorable pooled average reduction (9 studies, 510 participants; Hedges\n                      <jats:italic>g<\/jats:italic>\n                      =\u22120.29, 95% CI \u22120.55 to \u22120.04; PI \u22120.73 to 0.14), but its PI crossed the null. All PIs crossed the null; heterogeneity was substantial for glucose, considerable for TC, moderate for triglycerides, and low for insulin, HDL-C, and LDL-C. Subgroup signals were exploratory, no significant meta-regression moderators were identified, and leave-one-out analyses did not materially alter the glucose, TC, or triglycerides estimates. Most randomized trials had risk-of-bias concerns; the nonrandomized study had serious risk of bias. These limitations reduce confidence in the LDL-C signal. GRADE certainty was very low for glucose and TC and low for the remaining outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This review provides a synthesis of pediatric glycemic and lipid biomarkers and potential moderators, extending earlier broader exergaming reviews. Exergaming may be an engaging complementary strategy for physical activity and lipid health, including LDL-C, in schools, families, and community settings. However, heterogeneous protocols, risk-of-bias concerns, very low-to-low certainty, and PIs crossing the null mean that the magnitude and generalizability of any metabolic benefit remain uncertain.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/93610","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T06:35:09Z","timestamp":1785738909000},"page":"e93610-e93610","source":"Crossref","is-referenced-by-count":0,"title":["Effects and Moderators of Exergaming on Glucose and Lipid Metabolism in Children and Adolescents: Systematic Review and Meta-Analysis"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2761-945X","authenticated-orcid":false,"given":"Shuo","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8216-9485","authenticated-orcid":false,"given":"Yang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5387-949X","authenticated-orcid":false,"given":"Xiaoquan","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2210-5628","authenticated-orcid":false,"given":"Huakun","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3073-6644","authenticated-orcid":false,"given":"Lingyan","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"issue":"8","key":"R1","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1001\/jamapediatrics.2024.1576","article-title":"Global prevalence of overweight and obesity in children and adolescents: a systematic review and meta-analysis","volume":"178","author":"Zhang","journal-title":"JAMA Pediatr"},{"issue":"10431","key":"R2","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1016\/S0140-6736(23)02750-2","article-title":"Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults","volume":"403","author":"Phelps","journal-title":"The Lancet"},{"issue":"1","key":"R3","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1038\/s41572-023-00435-4","article-title":"Child and adolescent obesity","volume":"9","author":"Lister","journal-title":"Nat Rev Dis Primers"},{"issue":"1","key":"R4","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1038\/s41591-024-03279-x","article-title":"Lipid profiling identifies modifiable signatures of cardiometabolic risk in children and adolescents with obesity","volume":"31","author":"Huang","journal-title":"Nat Med"},{"issue":"1","key":"R5","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/S2352-4642(19)30323-2","article-title":"Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1\u00b76 million participants","volume":"4","author":"Guthold","journal-title":"Lancet Child Adolesc Health"},{"issue":"1","key":"R6","doi-asserted-by":"publisher","DOI":"10.1093\/abm\/kaaf031","article-title":"Screen time and allostatic load among youth: findings from the National Health and Nutrition Examination Survey, 2015-2018","volume":"59","author":"Chapman","journal-title":"Ann Behav Med"},{"issue":"24","key":"R7","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.1136\/bjsports-2020-102955","article-title":"World Health Organization 2020 guidelines on physical activity and sedentary behaviour","volume":"54","author":"Bull","journal-title":"Br J Sports Med"},{"issue":"9","key":"R8","doi-asserted-by":"publisher","first-page":"738","DOI":"10.1001\/jama.2024.11809","article-title":"Obesity in adolescents: a review","volume":"332","author":"Kelly","journal-title":"JAMA"},{"issue":"3","key":"R9","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1038\/s41581-022-00645-1","article-title":"Youth-onset type 2 diabetes mellitus: an urgent challenge","volume":"19","author":"Bjornstad","journal-title":"Nat Rev Nephrol"},{"issue":"11 Suppl 1","key":"R10","doi-asserted-by":"publisher","first-page":"S31","DOI":"10.1210\/jc.2008-1363","article-title":"Obesity in children and adolescents","volume":"93","author":"Cali","journal-title":"J Clin Endocrinol Metab"},{"issue":"7","key":"R11","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1111\/obr.12277","article-title":"What childhood obesity prevention programmes work? 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