Document Type


Session Format

Graduate Research Poster (no oral presentation)


Magnolia Ballroom

Publication Date

Spring 3-27-2024

Faculty Advisor

Kevin Hunt

Start Date

27-3-2024 10:00 AM

End Date

27-3-2024 10:50 AM


Introduction: According to the spring 2023 American College Health Association health survey, 5.5%, 22.8%, and 16% of college students self-reported being underweight, overweight, and obese, respectively. These statistics align with CDC figures suggesting 35-40% of college students are overweight and/or obese. Unfortunately, the vast majority of college students are not meeting national physical activity or nutritional standards. This trend towards unhealthy body composition, a sedentary lifestyle, and poor dietary habits has the potential to promote the development of chronic health conditions such as heart disease, cancer, diabetes, and osteoporosis. These risk-factors are avoidable and hold substantial physical, social, and economic burdens. Methods: Researchers recruited undergraduate and graduate students at Georgia College & State University (GCSU) to participate in a voluntary dual x-ray absorptiometry (DEXA) scan to establish body composition through the measurement of fat mass and muscle mass across the arms, legs, and abdominal regions. Additional assessments were performed to measure blood pressure, blood glucose concentration, and cholesterol levels. A self-report survey was also distributed to students to collect data on variables of interest such as demographics, alcohol consumption, smoking status, dietary preferences, resistance training participation, cardiovascular training participation, and female contraception use. Data analysis: SPSS was utilized to analyze the data. Dependent Sample T-tests compared known healthy body composition values to the participants metrics; Paired Sample T-tests compared body composition data between current participants and participants from the previous year; and Independent Sample T-tests analyzed body composition variations based on gender. Descriptive statistics were generated to identify population characteristics.



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