The study titled Sweat Based Biomarkers Profiling Among Recreational Athletes A Cross Sectional Study is designed as a prospective cross sectional study with a duration of six months. A total of 61 participants will be recruited, with the sample size determined using G Power software. The aim of the study is to profile sweat based biomarkers in recreational athletes, with the objective of collecting sweat samples and analyzing them using gas chromatography mass spectrometry.

The study is justified on the basis that very few investigations have focused on sweat biomarkers in recreational athletes in India. Current approaches rely largely on invasive sampling methods such as blood or urine, which limit real time monitoring. Sweat analysis provides a non invasive alternative that can offer valuable insights. Additionally, there is a gap in literature on recreational athletes aged 18 to 28 years, which this study seeks to address.

The study will be conducted jointly by the Department of Physiotherapy, Manipal College of Health Professions, and the Department of Biotechnology, Manipal Institute of Technology, under Manipal Academy of Higher Education. Participants will be men and women aged 18 to 28 years who have been engaged in structured training at least three to five days per week for the last three months, with training sessions lasting more than 60 minutes and including aerobic, anaerobic, strength or skill based exercises. Individuals with cardiovascular, respiratory or neurological conditions, recent musculoskeletal injury, active pain, or illness that may worsen with exercise will be excluded.

Sweat collection will be performed using sterile patches placed on the forearm both before and after a shuttle run test. The samples will be transported under controlled conditions and analyzed using GCMS in a certified laboratory. Demographic details including age, sex, height, weight and BMI will be recorded. Pre participation screening with PARQ 2024 plus will be conducted, and vitals such as heart rate, blood pressure, oxygen saturation and perceived exertion will be monitored. Additional tools include bioelectrical impedance analysis for body composition and pulse oximetry.

Outcome measures will include electrolytes such as sodium, calcium, potassium and chloride, metabolites such as lactate, glucose and urea, hormonal markers like cortisol, as well as neuropeptides and cytokines. Statistical analysis will be carried out using Jamovi software, with Shapiro Wilk test and descriptive statistics applied to the biomarker data. Results will be reported in SI units. The study does not require external funding and will be supported with existing laboratory resources.