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ORIGINAL RESEARCH article

Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1548056
This article is part of the Research Topic Holistically healthy humans: championing mental and physical wellbeing in education View all articles

Optimization of School Physical Education Schedules to Enhance Long-Term Public Health Outcomes

Provisionally accepted
SUN Tao SUN Tao 1*Sheng-Ping Zhu Sheng-Ping Zhu 2Wang Meng-Yuan Wang Meng-Yuan 2
  • 1 Hunan University of Arts and Science, Changde, China
  • 2 Xikou Middle School, Cili County, Zhangjiajie 427000, China

The final, formatted version of the article will be published soon.

    Optimizing school physical education (PE) schedules is crucial for enhancing public health outcomes, particularly among school-aged children. Therefore, in this study, a weighted fitness function is developed to evaluate health fitness scores. This function integrates multiple health metrics such as BMI reduction, fitness improvement, calories burned, and heart rate reduction.Six optimization algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Simulated Annealing (SA), Differential Evolution (DE), and Artificial Bee Colony (ABC) optimization algorithms are utilized to optimize PE schedules based on the designed weighted fitness function. Using a dataset of 1,360 student entries, the study incorporates health metrics such as BMI reduction, fitness score improvement, caloric expenditure, and heart rate reduction into a weighted fitness function for optimization. The results show that ACO achieved the highest allocation of PE time (9.91 hours / week), the most significant caloric expenditure (370 kcal / session) and the greatest reduction in heart rate (8.5 bpm). GA excelled in the reduction of BMI, achieving a decrease of 10.63 units. These analyses reveal the transformative potential of optimized PE schedules in reducing the burden of lifestyle-related diseases, promoting equitable health outcomes, and supporting cognitive and mental wellbeing. Finally, recommendations are provided for policy makers and stakeholders to implement data-driven PE programs that maximize long-term public health benefits.

    Keywords: Long-Term Public Health Outcomes, Digital Health, optimization, Physical Education Schedules, Fitness Improvement

    Received: 19 Dec 2024; Accepted: 16 Jan 2025.

    Copyright: © 2025 Tao, Zhu and Meng-Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: SUN Tao, Hunan University of Arts and Science, Changde, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.