Is There an Association between Health Risk Behaviours and Academic Achievement among University Students?
Catriona Kar Yuen OngMelinda Jane HutchessonAmanda J PattersonMegan C WhatnallPublished in: International journal of environmental research and public health (2021)
University students have high rates of health risk behaviours, and these may be predictive of academic success. This cross-sectional study aimed to determine the association between individual and multiple health risk behaviours and academic achievement in a sample of Australian university students. Data from the University of Newcastle Student Healthy Lifestyle Survey 2019 were used. Health risk behaviours (diet, physical activity, sitting time, sleep, alcohol consumption, smoking) were assessed, and total number of risk factors calculated. Academic achievement was assessed using self-reported grade point average (GPA). The association between health risk behaviours and GPA was explored using linear regression, adjusted for socio-demographic and student characteristics. The sample included 1543 students (mean age 25.0 ± 7.9 years, 70.6% female). Lower GPA was associated with not meeting fruit consumption recommendations (β = -0.203), consuming >1 cup of soft drink/week (β = -0.307), having takeaway foods ≥1 time/week (β = -0.130), not consuming breakfast daily (β = -0.261), not meeting sleep recommendations (β = -0.163), exceeding single occasion alcohol consumption risk (β = -0.277), smoking (β = -0.393), and having a higher number of risk factors (β = -0.105). This study identified modest associations between GPA and health risk behaviours, suggesting that further research is warranted into whether strategies to improve university students' health could modestly improve their academic achievement.
Keyphrases
- health risk
- alcohol consumption
- physical activity
- heavy metals
- drinking water
- risk factors
- medical students
- healthcare
- weight loss
- metabolic syndrome
- public health
- body mass index
- clinical practice
- mental health
- smoking cessation
- cardiovascular disease
- clinical trial
- machine learning
- placebo controlled
- artificial intelligence
- double blind