Use of Caffeine-Containing Energy Drinks by Japanese Middle School Students: A Cross-Sectional Study of Related Factors
Abstract
Excessive consumption of caffeine negatively affects individuals’ health. Therefore, we studied the use of energy drinks and the conditions associated with it among Japanese secondary school students. Participants were 236 students in grades 7–9 who completed anonymous questionnaires at home in July 2018. We measured the basic attributes and dietary, sleeping, and exercise habits. We used Chi-squared tests to compare differences between users and non-users of energy drinks. Logistic regression analyses were used to elucidate the complex association between the variables. The results showed that boys were more willing to consume energy drinks than girls. The reasons were ‘feeling fatigued’, ‘needing to stay awake’, ‘for curiosity’, and ‘to quench one’s thirst’. Among boys, the following were associated with the use of EDs. Buying their own snacks , not understanding nutritional labels on foods, high caffeinated beverage intake, always waking up at about the same time, and weight. Health guidance is needed to prevent overconsumption and dependence on energy drinks. The cooperation of parents and teachers is needed to achieve these goals.
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.