Prediction of sleep quality among university students after analyzing lifestyles, sports habits, and mental health

Abstract

The aim of this study was to develop and validate a prediction model to evaluate the risk of poor sleep quality. We performed a cross-sectional study and enrolled 1,928 college students from five universities between September and November 2021. The quality of sleep was evaluated using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a training (n = 1,555) group and a validation (n = 373) group. The training group was used to establish the model, and the validation group was used to validate the predictive effectiveness of the model. The risk classification of all participants was performed based on the optimal threshold of the model. Of all enrolled participants, 45.07% (869/1,928) had poor sleep quality (PSQI score ≧ 6 points). Multivariate analysis showed that factors such as older age, a higher grade, previous smoking, drinking, midday rest, chronic disease, anxiety, and stress were significantly associated with a higher rate of poor sleep quality, while preference for vegetables was significantly associated with better sleep quality, and all these variables were included to develop the prediction model. The area under the curve (AUC) was 0.765 [95% confidence interval (CI): 0.742–0.789] in the training group and 0.715 (95% CI: 0.664–0.766) in the validation group. Corresponding discrimination slopes were 0.207 and 0.167, respectively, and Brier scores were 0.195 and 0.221, respectively. Calibration curves showed favorable matched consistency between the predicted and actual probability of poor sleep quality in both groups. Based on the optimal threshold, the actual probability of poor sleep quality was 29.03% (317/1,092) in the low-risk group and 66.03% (552/836) in the high-risk group (P < 0.001). A nomogram was presented to calculate the probability of poor sleep quality to promote the applicationof the model. The prediction model can be a helpful tool to stratify sleep quality, especially among university students. Some intervention measures or preventive strategies to quit smoking and drinking, eat more vegetables, avoid midday rest, treat chronic disease, and alleviate anxiety and stress may be considerably beneficial in improving sleep quality.

Determinants of Sleep Quality: A Cross-Sectional Study in University Students

“…A considerable number of studies have been conducted among student cohorts across different socio-cultural regions [9,10,[29][30][31][32][33][34][35][36][37] using the well-established Pittsburgh Sleep Quality Index [38] which identifies good and poor sleepers. Results of these studies suggest that poor sleep quality is particularly common among university students, with between 30% and 70% of students classified as poor sleepers.…”

“…More recently, it has been proposed that pandemic-led restrictions were significant contributors to students sleep behavior, including bedtime schedules, sleep latency, and sleep duration, which caused a substantial worsening of their sleep quality [39]. Since the current literature is widely limited to US [10,30] and Chinese students [31,32,35], the findings may not reflect sleep quality rates among university students attending higher education in Europe, which has several different characteristics relating to living arrangements, tuition, enrollment, and infrastructure [40]. Additional studies are needed to characterize rates of poor sleep quality in students enrolled in European universities, particularly as the majority of previous research has examined medical [32,34] or undergraduate students [30,31,33] in other regions.…”

“…Thus, previous research in student populations has indicated that sleep quality varies by sex and age, though findings are inconsistent. Some studies [9,10,36,37] found that female students reported poorer sleep quality, while others found no significant sex differences [30,31,35]. Barriers to good sleep quality in female students might be relate to a greater prevalence of reduced sleep efficiency and sleep disturbances [10,37] as well as the menstrual cycle, which affects sleep in women [41].…”

“…Barriers to good sleep quality in female students might be relate to a greater prevalence of reduced sleep efficiency and sleep disturbances [10,37] as well as the menstrual cycle, which affects sleep in women [41]. Increased age was found to predict poor sleep quality [35] in some but not all studies [10,30,31] and was even found to be a protective factor in a sample of Jordanian university students [29]. In some studies [10,30,31] the age range of the university students was small, making it less likely to observe age-related effects on sleep quality.…”

“…According to the authors, these factors are in some way linked: Financial needs make it necessary for some students to take on a job while simultaneously attending university, which increases the challenge of balancing work schedules, academic workload, and sleep. Moreover, when entering the university environment, risk behaviors such as lack of physical activity [32], smoking [47], and frequent alcohol drinking [31,35] are highly prevalent and increase the likelihood of poor sleep quality in this population. Both quantitative and qualitative research has shown that students' dissatisfaction with their academic environment and demanding workloads have been linked to poor sleep quality in this population.…”