Academic performance and its associated factors among degree students of faculty of sports sciences and recreations, UiTM, Shah Alam

As career competition grows more, the importance of students’ academic performance at university has caught the attention of parents, policy makers and Ministry of Education as well. Since academic performance is one of the key paths to success in the working world, much effort is made to identify, evaluate, track and encourage the progress of students at university. The relationship between personal attributes, health behaviours, health-related components of physical fitness and academic performance have not been thoroughly investigated simultaneously especially among Malaysian university students. The main objective of this study was to investigate the relationship between these factors and Cumulative Grade Point Average (CGPA), as an indicator of academic performance, among degree students. A total of 324 undergraduate students were randomly selected from the Faculty of Sports Sciences and Recreations of University Teknologi MARA (UiTM) in 2011. A pre-tested self-administered questionnaire was used to determine personal attributes (socio-demographic, health status and psychosocial factors) and health behaviours (smoking and alcohol consumption, diet, physical activity and sleep quality) of the subjects. Academic performance was measured by students’ current CGPA. Anthropometric measurements were used to measure body fat percentage by using BIA, height, weight and waist circumference. In addition, physical fitness tests (VO2max by using queen step box test, muscle strength and endurance using Camry Electronic Handgrip Dynamometer) and finger prick blood test (to measure random blood glucose, blood lipids and hemoglobin) by Reflotron® Plus instrument were used to determine health-related physical fitness of the subjects. The mean (S.D) age of subjects was 21.77±1.1 with almost half of them (50.1%) the age of 22 years old. Most of the students (49.5%) obtained second (upper) class followed by second (lower) (41.4%). Around 10.5% of the subjects were current smokers. Almost 92.3% of the subjects did not adhere to low fat eating. 67.9% of the subjects had high following by 23.1% moderate and 9.0% low physical activity level. Majority of (63.0%) the participants had normal body mass index. One-way ANOVA showed a significant difference in the mean CGPA between different entry levels (F (3, 316) = 33.56, p = 0.001). Independent sample t-test demonstrated that the mean CGPA of those who were living on-campus was significantly higher than those who were living off-campus (t (316) = 2.000, p = 0.046). In addition, the mean CGPA of those who had sufficient allowance was significantly higher than those who had insufficient allowance (t (317) = -2.062, p = 0.040). The mean CGPA of those whose fathers had higher education level was significantly higher than those whose fathers had lower (t (317) = -2.671, p = 0.008). There was a significant difference in the mean CGPA between different household income levels (F (3, 315) = 3.737, p = 0.012). The mean CGPA of current smokers was significantly lower than non-smokers (t (317) = -3.302, p = 0.001). The mean CGPA of supplement users was significantly higher than non-users (t (322) = 2.200, p = 0.029). There was a weak positive statistically significant relationship between low fat eating and CGPA (r = 0.162, p = 0.004). There was also a weak positive statistically significant relationship between total physical activity MET-minutes/week (r = 0.223, p = 0.003) and moderate MET-minutes/week (r = 0.120, p = 0.019) with CGPA. The mean CGPA of those who had never experienced sleep disturbance during the past month was significantly higher than those who had sometimes experienced sleep disturbance (p = 0.003). There was no significant relationship between body fat and academic performance (r = -0.041, p = 0.481). There was no significant relationship between BMI and academic performance (r = -0.092, p = 0.103). There was a weak, negative significant relationship between waist circumference and CGPA (r = -0.120, p = 0.034). There was a weak negative significant relationship between VO2max and CGPA (r = -0.128, p = 0.029). There was no statistically significant relationship between blood glucose, serum total cholesterol, HDL-cholesterol triglyceride, hemoglobin and academic performance. However, there was a negative medium significant relationship between LDL-cholesterol and CGPA (r = -0.505, p = 0.017). There was a weak negative significant relationship between muscle strength and CGPA (r = -0.143, p = 0.018). Overall, multivariate linear regression analysis showed that entry level, smoking, living, household income and sleep disturbance during the past year explained 22.8% of the variation in academic performance. Entry level contributed 16.0% of the variation in academic performance. Smoking contributed 3.2% of the variation in academic performance. Living contributed 1.5% of the variation in academic performance. Household income contributed 1.3% of the variation in academic performance. Finally, sleep disturbance during the past year contributed 0.8% of the variation in academic performance. In conclusion, entry level, smoking, living, household income and sleep disturbance during the past year contributed significantly towards academic performance. Results should be interpreted with caution. It cannot be inferred from these data that health behaviours and health-related components of physical fitness cause academic performance to improve. It is more likely that physical and mental processes influence each other in ways that are still being understood.

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