SLJ is associated with multiple field-based fitness indicators in young adult males

Health data equity emphasizes the need for accessible, low-cost, and scalable indicators that can reduce barriers to health assessment when applied within clearly defined populations and contexts. However, many existing fitness and health evaluation methods rely on resource-intensive measurements, limiting their applicability in large-scale or under-resourced settings. The standing long jump (SLJ), a simple field-based test of lower-limb explosive power, may serve as a practical and scalable indicator of physical fitness among male college students.

This cross-sectional study included 7,842 male college students. SLJ performance was assessed alongside key health-related fitness indicators, including cardiorespiratory fitness (1000-m run), muscular endurance (pull-ups), flexibility (sit-and-reach), and body composition (BMI). Pearson correlation analysis was conducted to examine associations between SLJ and these variables.

SLJ performance was significantly associated with all measured variables (p < 0.01). It was negatively correlated with 1,000-m run time and BMI, suggesting associations with better cardiorespiratory fitness performance and lower BMI within this male college student sample. Positive correlations were observed between SLJ and both pull-up performance and flexibility. These findings indicate that SLJ is associated with multiple dimensions of physical fitness in young adult men.

As a low-cost, scalable, and easily implementable measure, SLJ has potential utility for large-scale fitness assessment among male college students. Its associations with multiple domains of physical fitness support its use as an accessible field-based assessment tool in university or resource-limited settings. Given that the present study included only male college students, the findings should not be generalized to female students, other age groups, or non-college populations without further validation. These findings contribute to the development of accessible and data-efficient strategies for context-specific health and fitness assessment.