Examining Sleep Habits and Associated Lifestyle Factors in Adolescents: A Population‐Based Study

Introduction This study aimed to examine the associations between adolescent characteristics and sleep habits in Hong Kong. Methods A cross‐sectional study was conducted among secondary school students in Hong Kong. Data on sociodemographics, health behaviors, mental toughness, and sleep patterns were collected. Univariable and multivariable logistic regression analyses were used to identify factors associated with late bedtime, insufficient sleep duration, and late wake‐up time. Results Among 1345 adolescents surveyed, 60.1% reported late bedtime, 56.6% experienced insufficient sleep duration (<8 h), and 34.1% reported late wake‐up time. In multivariable models, older age was consistently associated with adverse sleep habits (aOR late wake‐up = 1.64, 95% CI: 1.23–2.18, p = 0.001; aOR late bedtime = 2.69, 95% CI: 1.98–3.64, p < 0.001; aOR insufficient duration = 1.74, 95% CI: 1.31–2.31, p < 0.001). Exceeding recommended screen time was linked to later bedtimes (aOR video = 1.46, 95% CI: 1.14–1.88, p = 0.003; aOR game = 1.42, 95% CI: 1.10–1.84, p = 0.007; aOR social media = 1.78, 95% CI: 1.38–2.29, p < 0.001) and insufficient sleep duration (aOR social media = 1.87, 95% CI: 1.46–2.39, p < 0.001). Daily breakfast consumption was consistently associated with lower odds of late bedtime (aOR = 0.49, 95% CI: 0.39–0.63, p < 0.001), insufficient sleep duration (aOR = 0.56, 95% CI: 0.44–0.71, p < 0.001), and late wake‐up time (aOR = 0.69, 95% CI: 0.54–0.88, p = 0.002). Alcohol consumption was associated with higher odds of insufficient sleep duration (aOR = 1.80, 95% CI: 1.10–2.96, p = 0.020) and lower odds of late wake‐up (aOR = 0.60, 95% CI: 0.37–0.96, p = 0.032). Male students had lower odds of insufficient sleep (aOR = 0.69, 95% CI: 0.54–0.87, p = 0.002) but higher odds of waking up late (aOR = 1.75, 95% CI: 1.37–2.24, p < 0.001). Conclusion This study identified high rates of adverse sleep habits among Hong Kong adolescents and demonstrated strong associations with age, screen use, dietary behavior, and other lifestyle factors. These findings highlight the need for targeted interventions—such as digital use guidelines and school‐based breakfast programs—to promote healthy sleep patterns during adolescence.