A COMPARATIVE ANALYSIS OF SELECTED PHYSICAL FITNESS COMPONENTS AMONG RURAL AND URBAN SCHOOL ATHLETES

Abstract

The purpose of study is to compare selected components of physical fitness among rural and urban school athletes and to interpret the possible environmental, socioeconomic, lifestyle, and training-related factors associated with observed differences. Physical fitness is multidimensional; therefore, the analysis focuses on speed, muscular strength and endurance, explosive power, agility, flexibility, and cardiorespiratory endurance. An illustrative cross-sectional dataset of 120 school athletes aged 14–17 years is used, comprising 60 rural and 60 urban athletes with comparable representation by sex and age. Standard field tests are modeled: 50-m sprint, standing broad jump, sit-ups in 60 seconds, 4 × 10-m shuttle run, sit-and-reach, and 12-minute run. Descriptive statistics, independent-samples t-tests, percentage differences, and Cohen’s d effect sizes are used to examine group differences. The model results suggest that rural athletes perform better in cardiorespiratory endurance and muscular endurance, while urban athletes show modest advantages in sprint speed, agility, and flexibility. Explosive power is broadly comparable. The pattern is interpreted as the possible outcome of different daily activity profiles: rural athletes may accumulate more habitual movement and endurance-oriented activity, whereas urban athletes may have greater access to structured coaching, specialized facilities, and skill-specific training. However, the analysis emphasizes that residence itself should not be treated as a biological cause. School resources, nutrition, training age, transportation, screen time, opportunities for free play, and socioeconomic conditions may mediate or confound the relationship.

The study concludes that rural and urban school athletes may possess different fitness strengths rather than a simple overall superiority of one group. Schools should therefore use component-specific testing and context-sensitive training programs. Future research should employ larger probability samples, objective physical-activity monitoring, dietary assessment, maturity status, and multivariate statistical controls.