دورية أكاديمية
Benefits of Meeting the Healthy People 2030 Youth Sports Participation Target.
| العنوان: | Benefits of Meeting the Healthy People 2030 Youth Sports Participation Target. |
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| المؤلفون: | Martinez MF; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Weatherwax C; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Piercy K; Office of Disease Prevention and Health Promotion, U.S. Department of Health and Human Services (HHS), Rockville, Maryland., Whitley MA; Ruth S. Ammon College of Education and Health Sciences, Adelphi University, Garden City, New York; Stellenbosch University, Maties Sport, Centre for Sport Leadership, Stellenbosch, South Africa., Bartsch SM; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Heneghan J; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Fox M; Project Play, Sports & Society Program, The Aspen Institute, Washington, District of Columbia., Bowers MT; Department of Kinesiology and Health Education, College of Education, The University of Texas at Austin, Austin, Texas., Chin KL; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Velmurugan K; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Dibbs A; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Smith AL; Emma Eccles Jones College of Education and Human Services, Utah State University, Logan, Utah., Pfeiffer KA; Department of Kinesiology, College of Education, Michigan State University, East Lansing, Michigan., Farrey T; Project Play, Sports & Society Program, The Aspen Institute, Washington, District of Columbia., Tsintsifas A; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Scannell SA; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York., Lee BY; Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, New York; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, New York. Electronic address: bruceleemdmba@gmail.com. |
| المصدر: | American journal of preventive medicine [Am J Prev Med] 2024 May; Vol. 66 (5), pp. 760-769. Date of Electronic Publication: 2024 Feb 27. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S. |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 8704773 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2607 (Electronic) Linking ISSN: 07493797 NLM ISO Abbreviation: Am J Prev Med Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Amsterdam : Elsevier Science Original Publication: [New York, NY] : Oxford University Press, [c1985- |
| مواضيع طبية MeSH: | Youth Sports* , Healthy People Programs*, Humans ; Adolescent ; Child ; United States ; Male ; Female ; Mental Health ; Overweight/epidemiology ; Overweight/prevention & control |
| مستخلص: | Introduction: Healthy People 2030, a U.S. government health initiative, has indicated that increasing youth sports participation to 63.3% is a priority in the U.S. This study quantified the health and economic value of achieving this target. Methods: An agent-based model developed in 2023 represents each person aged 6-17 years in the U.S. On each simulated day, agents can participate in sports that affect their metabolic and mental health in the model. Each agent can develop different physical and mental health outcomes, associated with direct and indirect costs. Results: Increasing the proportion of youth participating in sports from the most recent participation levels (50.7%) to the Healthy People 2030 target (63.3%) could reduce overweight/obesity prevalence by 3.37% (95% CI=3.35%, 3.39%), resulting in 1.71 million fewer cases of overweight/obesity (95% CI=1.64, 1.77 million). This could avert 352,000 (95% CI=336,200, 367,500) cases of weight-related diseases and gain 1.86 million (95% CI=1.86, 1.87 million) quality-adjusted life years, saving $22.55 billion (95% CI=$22.46, $22.63 billion) in direct medical costs and $25.43 billion (95% CI= $25.25, $25.61 billion) in productivity losses. This would also reduce depression/anxiety symptoms, saving $3.61 billion (95% CI=$3.58, $3.63 billion) in direct medical costs and $28.38 billion (95% CI=$28.20, $28.56 billion) in productivity losses. Conclusions: This study shows that achieving the Healthy People 2030 objective could save third-party payers, businesses, and society billions of dollars for each cohort of persons aged 6-17 years, savings that would continue to repeat with each new cohort. This suggests that even if a substantial amount is invested toward this objective, such investments could pay for themselves. (Copyright © 2023 American Journal of Preventive Medicine. All rights reserved.) |
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| معلومات مُعتمدة: | P01 AI172725 United States AI NIAID NIH HHS; R01 GM127512 United States GM NIGMS NIH HHS; R01 HS028165 United States HS AHRQ HHS; U54 TR004279 United States TR NCATS NIH HHS |
| تواريخ الأحداث: | Date Created: 20240228 Date Completed: 20240423 Latest Revision: 20240822 |
| رمز التحديث: | 20240822 |
| مُعرف محوري في PubMed: | PMC11034834 |
| DOI: | 10.1016/j.amepre.2023.12.018 |
| PMID: | 38416089 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1873-2607 |
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| DOI: | 10.1016/j.amepre.2023.12.018 |