El Ansari Walid, Sebena Rene, El-Ansari Kareem, Suominen Sakari
Department of Surgery, Hamad General Hospital, Hamad Medical Corporation, 3050, Doha, Qatar.
College of Medicine, Qatar University, 3050, Doha, Qatar.
BMC Public Health. 2024 Apr 22;24(1):1103. doi: 10.1186/s12889-024-18421-0.
No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task.
Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester.
Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms or stress; (2) those living with parents/partner were significantly less likely to experience depressive symptoms; (3) compared to Cluster 1, students in the two other clusters were significantly more likely to report higher depressive symptoms; and (4) only students in Cluster 2 were more likely to report higher stress.
BRFs cluster together, however, such clustering is not a clear-cut, all-or-none phenomenon. Students with BRFs consistently exhibited higher levels of depressive symptoms and stress. Educational and motivational interventions should target at-risk individuals including those with insufficient income or living with roommates or alone.
此前芬兰没有针对大学生的研究评估生活方式行为风险因素(BRF),将学生分组,评估这些组与他们心理健康的关系,同时控制混杂因素。本研究承担了这项任务。
图尔库大学的学生(n = 1177,年龄22.96±5.2岁)完成了一份在线问卷,该问卷收集了社会人口统计学变量(年龄、性别、收入充足情况、学期期间的住宿情况)、四种BRF[问题饮酒、吸烟、饮食习惯、中度至剧烈身体活动(MVPA)]以及抑郁症状和压力方面的信息。使用对数似然距离度量对BRF进行两步聚类分析,将学生分为明确的几类。两个回归模型评估了类别归属与抑郁症状和压力之间的关联,同时控制了性别、收入充足情况和学期期间的住宿情况。
略多于一半的研究参与者(56.8%)收入一直/大多充足,33%与父母/伴侣同住。BRF的聚类分析确定了三个不同的学生类别,即类别1(健康组)、类别2(吸烟者)和类别3(不吸烟者但有问题饮酒者)。各聚类在年龄、性别和MVPA方面没有差异,但类别1和类别3中收入一直/大多充足且在学期期间与父母/伴侣同住的受访者明显更多。类别1和类别3的所有成员都不吸烟,而类别2的所有成员都是偶尔/每天吸烟者。有问题饮酒在各聚类之间有显著差异(类别1 = 0%,类别2 = 54%,类别3 = 100%)。类别3的营养习惯明显比其他两个类别更健康。回归分析表明:(1)男性和收入充足的人报告抑郁症状或压力的可能性显著更低;(2)与父母/伴侣同住的人经历抑郁症状的可能性显著更低;(3)与类别1相比,其他两个类别的学生报告更高抑郁症状的可能性显著更高;(4)只有类别2的学生报告更高压力的可能性更大。
BRF会聚集在一起,然而,这种聚集并非是一种明确的、非此即彼的现象。有BRF的学生始终表现出更高水平的抑郁症状和压力。教育和激励干预应针对有风险的个体,包括收入不足或与室友同住或独自居住的人。