Behavioral Risk Factors Clusters and their Associations with Self-Reported Burdens Among University Students in Finland

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The current study undertook this task. Methods : Students (n=1169) at Turku University completed online questionnaire comprising sociodemographic variables (age, sex, income, social support), 18 burdens, and 5 BRFs (smoking, alcohol, drug use, food habits). Factor analysis reduced burdens into factors; cluster analysis of BRFs categorized students into clusters. Regression models appraised associations between sociodemographics and clusters with burdens. Results : Mean age was ≈23 years, with ≈70% females, 23.4% smokers, 28.8% problematic drinkers, 21% illicit drug/s users, and mean dietary guideline adherence=4.84±1.57. Factor analysis of burdens generated four factors: ‘Studies’=3 items; ‘Future’=3 items; ‘Relationships’=7 items; and ‘Needs’=5 items. Cluster analysis produced four BRFs clusters with significantly different BRFs and sociodemographics. Cluster 1 exhibited less risk-taking behaviors, Cluster 4 comprised more risk-taking, and the other two clusters fell in-between. Regression showed that females were more likely to report ‘Studies’+‘Relationships’ burdens; higher social support was associated with less burdens generally; older age was associated with less ‘Studies’+‘Future’+‘Relationships’ burdens; and sufficient income was associated with less ‘Studies’+‘Future’+‘Needs’ burdens. Compared to Cluster 1, Cluster 4 membership was more likely to feel ‘Needs’ burdens; Cluster 3 more likely to report ‘Relationships’+‘Needs’ burdens ( p range: <0.05 to <0.01 for all). Conclusion : Controlling for sociodemographics, cluster membership was more influenced by students’ perceptions of ‘Relationships’+‘Needs’, rather than academic difficulties of ‘Studies’ or unsecure ‘Future’. Risk taking was more likely with relationship difficulties, isolation, and day-to-day problems (housing, financial situation, health) rather than academic load or concerns for future prospects. Preventive and intervention efforts tackling students’ lifestyle behaviours need to consider programs aimed at better relationship building/maintenance to prevent isolation, while mitigating ‘on-the-ground’ everyday challenges that students face. behavioral risk factors burdens university students cluster analysis social support Figures Figure 1 Introduction University students face a range of burdens during transition from adolescence to adulthood, rendering them a particularly vulnerable group [ 1 ]. Moreover, their lifestyles are frequently characterized by unhealthy behaviors [ 2 ]. While young adulthood is a period for adopting and stabilizing lifelong healthy behavior, university life is independently associated with burdens that may further affect health and well-being [ 3 ]. In terms of burdens, across university students in Germany, Poland, and Bulgaria, students felt burdened by their course work, exams, uncertainty of the future, problems with relationships and feeling isolated [ 4 ]. Other significant burdens that students face include financial obligations, overwhelming workload, pressure to succeed, and work-life balance [ 5 ]. Studies found that 35.9%-60.4% of undergraduates felt burdened by studies, assignments, and presentations, lack of time for studies, and bad job prospects [ 6 ]. For instance, across 7 universities in Northern Ireland, Wales and England, one third of the students were highly burdened by finances [ 7 ], as well as exams, workload, and lack of time [ 8 ]. Likewise, in the USA, the cognitive burden created by student loans is significant [ 9 , 10 ]. Collectively, such burdens exert pressure on students, manifested as poor academic performance [ 11 ], depression [ 12 ], anxiety [ 13 ] or even suicidal thoughts [ 14 ]. Pertaining to behavioural risk factors (BRFs), unhealthy lifestyle behaviors are prevalent among university students. Many exihbit low rates of healthy nutrition, or dietary patterns that are below the recommended guidelines [ 15 – 17 ]. Likewise, cigarette smoking is frequently initiated as individuals transition from high school to university [ 18 ]. In addition, university students have been reported to be heavy drinkers [ 19 ], with higher consumption of alcohol than their non-university peers [ 20 ], and illicit drug use is common [ 21 – 23 ]. The congregation of unhealthy behaviors (smoking, alcohol consumption, illicit drug/s use, bad eating habits) influence students’ health and mortality risk [ 24 ], as unhealthy behaviors cluster together to generate multiplier effects. More than 65% of young fulltime female students at a USA university reported ≥ 2 unhealthy behaviors [ 25 ], and BRFs co-occur with each other [ 26 – 28 ]. Clustering of BRFs refers to an observed proportion of a combination of risk factors in excess of its expected proportion [ 29 ]. Other variables related to both burdens and BRFs play a confounding role. Among university students, differences related to sex [ 6 , 8 ], age or year of study [ 30 – 32 ] and income [ 33 , 34 ] have been observed in the levels of perceived burdens and in BRFs. Likewise, adequate social support, defined as supportive actions by others that facilitate one’s ability to cope with a stressful situation [ 35 ], may attenuate the burden of stressful events [ 36 , 37 ] and significantly buffer the effects of risky behaviour on physical and psychological health [ 38 ]. The literature reveals knowledge gaps. Despite the variety of burdens and BRFs characterizing this young adult population, surprisingly few studies have examined the range of student-related perceived burdens (categorized into factors) and the relationships of such burdens with a range of BRFs (categorized into clusters) [ 23 , 39 , 40 ]. We are not aware of any studies that undertook this task among Finnish university students. The current study bridges this knowledge gap by utilizing a cluster analysis approach [ 41 ], an increasingly popular method in the assessment of BRFs. We employed a large sample of students at a university in Finland in order to: (1) factor analyze 18 their self-reported burdens in components; (2) identify and describe the clustering of four major lifestyle BRFs [tobacco, alcohol, illicit drugs, nutrition behavior]; (3) characterize the student characteristics of each of the emerging clusters in terms of sociodemographics and BRF distribution; and (4) examine the associations between the emerging BRFs clusters and the groups of self-reported burdens, controlling for confounders (sex, age, income sufficiency, social support). University settings are important in shaping life-long health behaviors [ 42 ]. Hence, it is important to monitor students’ behavior at this young adulthood stage [ 43 , 44 ]. The current study adds new insights to the limited research on students’ self-reported burdens and their association with BRFs clusters. The findings would be useful for educators, policy makers, and other stakeholders to guide policies and approaches for prevention as well as tailoring intervention strategies aimed at university students’ wellbeing. Methods Ethics, Sample, Procedures The study was approved by the Research and Ethics Committee at the University of Turku in Finland. An online survey using an English-language questionnaire was used to collect data. An email invitation with the research objectives was sent to all (n = 4387) students enrolled in all faculties of the university, inviting them to participate. Students from all seven faculties of the University of Turku (Humanities, Mathematical and Natural Sciences, Medicine, Law, Social Sciences, Education and Economics) faculties were invited. Participation was voluntary and anonymous, and the data was kept confidential and protected (anonymous, no identifiers, strict access only for the research team, secure computer storage, passwords updated and changed monthly, no paper copies). Students were provided with information about the study and contact details for any questions. They were informed that by completing the questionnaire they were giving their consent to participate in the study. After completing the online questionnaire, the respondents' answers were automatically saved and forwarded to the university's student office. The total number of responses totaled 1169 (response rate: 27%). The average age of the students was ≈ 23 (SD 5) years and 823 (70.4%) were female. Research tool: Survey Questionnaire Socio-demographic information included students’ sex and age. Subjective financial situation was measured by a single item: “How sufficient is your income?”, with a 4-point response scale, subsequently dichotomized into (always /mostly sufficient vs always/mostly insufficient) [ 45 ]. Social support was measured by the item: “Are you on the whole satisfied with the support you get in such situations?” using a 5-point scale (1 = very satisfied, 5 = very dissatisfied) [ 46 ]. Perceived burdens associated with coursework and exams, relationships, isolation, and expectations regarding the future were assessed by asking the students: "To what extent do you feel burdened in the following areas?" (18 individual burdens). Responses were coded on a six-point scale from: “Not at all” to “Very strongly” [ 4 ]. Alcohol problem drinking was assessed using the 4 standard items that form the CAGE screening test for problem alcohol use with 2 response options (“Yes,” “No”) [ 47 ]. Two or three affirmative answers suggest problem drinking. We classified the respondents as non-problematic drinkers (less than two positive answers) and problematic drinkers (two or more positive answers). Smoking was measured with the item “Within the last 3 months, how often did you smoke (cigarettes, pipes, cigarillos, cigars)?” with response options “Daily,” “Occasionally,” and “Never” [ 48 ]. Illicit drug use (ecstasy, marijuana, cocaine, heroin, crack, LSD, amphetamines) was assessed by the question “Have you ever use/used drugs?” with response options “Yes, regularly,” “Yes but only a few times,” “Never” [ 49 ]. Dietary assessment (12 items) : respondents self-reported their dietary habits in a food frequency questionnaire, which included 12 variables assessing their consumption of sweets, cakes/crackers, fast food and canned foods, fresh fruit, raw and cooked vegetables and salads, meat and fish, dairy products and cereals. In the initial question "How often do you eat the following foods?" students were asked about the frequency of their usual consumption of each food group separately (5-point scale: "several times a day", "daily", "several times a week", "1–4 times a month", "never"). The question elicited information on the student's overall food consumption. The instrument was based on pre-existing food frequency questionnaires, adapted and used previous in studies [ 50 ]. Dietary guideline adherence score was calculated based on the student's answers to the frequency of food questionnaire. There are no specific guidelines for sweets, cakes/cookies, snacks, fast food/canned foods and sodas/soft drinks, so we used "1–4 times a month" and "never" as the recommended values. To assess sweets, cakes/cookies and snacks together, we used the above-combined food intake scores (sweets, cakes/cookies and snacks) and considered healthy eating to be present if this score was ≤ 6, which corresponds to three times the intake of these items to "< 1–4 times per month". Each of the fast food/canned snacks and soda/sweet drinks was included as a separate item in the calculation of the objective dietary adherence score. For other food groups, we used the WHO European Region recommendations [ 51 ]. A threshold of 'daily' or 'several times a day' was then set for the number of daily servings of fruit, and raw and cooked vegetables. For meat, the threshold was "less than daily" and for fish "several times a week". Milk and cereals were not included in the calculation of the compliance score because the information on milk and cereals was generally too non-specific to be classified as healthy/unhealthy. The maximum dietary adherence score is 8 points (8 recommendations), calculated from the recommendations of 8 food groups: (1) sweets, cookies, snacks, (2) fast food/canned food, (3) lemonade/soft drinks, (4) fruit, (5) salad, raw vegetables, (6) cooked vegetables, (7) meat, and (8) fish [ 50 , 51 ] Statistical Analysis We used independent samples t-test to compare quantitative variables, and Pearson chi-square, for qualitative variables. Exploratory factor analysis using principal component analysis with varimax rotation and Kaiser-Meyer-Olkin test for sampling adequacy was undertaken on the self-reported perceived burdens items. The internal consistency of the items that make up each of the factors was assessed by Cronbach’s alpha. Two-step cluster analysis was applied to 4 BRFs (tobacco smoking, alcohol drinking, illicit drug using, and eating behavior) to identify clusters that differed in criterion variables within the dataset, and the procedure combined pre-clustering and hierarchical methods. A log-likelihood distance measure was used in the two-step cluster analysis because the BRFs comprised continuous and categorical variables. Cluster number selection was automated using the Schwarz Bayesian criterion. Within each cluster, the frequency of categories and percentages were reported for categorical BRFs, whereas mean ± standard deviation was reported for continuous BRFs. Differences in the distribution of sociodemographic characteristics and BRFs across clusters were tested using Chi-square tests for categorical variables or analysis of variance for continuous variables. Multiple linear regression models examined the association between cluster membership and four perceived burdens factors while adjusting for participant’s gender, age, income sufficiency, and satisfaction with social support. We did not use any imputation for the missing values. The number of missing values was negligible, hence we decided to use complete case analysis which limits the analysis to respondents with complete data. Statistical analyses were performed using SPSS v25.0 and statistical significance was set at p < 0.05. Results Characteristics of the sample Table 1 shows that mean age was about 23 years, the majority of the sample always/ mostly had sufficient income during semesters, and about three-quarters of students never smoked. There were no sex differences in age, perceived income sufficiency, and smoking. Based on the CAGE score, significantly more males than females had problematic drinking. Conversely, although most respondents never used illicit drug/s, significantly more females (81.8%) reported it, and more females had better nutritional habits, scoring higher on the dietary guideline adherence index. Table 1 Sociodemographic and behavioral characteristics of the sample Variable Whole sample N = 1169 Male N = 346 Female N = 823 p-value Sociodemographic characteristics Age, years (M ± SD) 22.96 ± 5.21 22.83 ± 4.36 23.01 ± 5.55 0.59 Perceived income sufficiency n (%) 0.30 Always/ Mostly sufficient 675 (56.8) 207 (59.8) 466 (56.6) Always/ Mostly insufficient 487 (41) 135 (39) 348 (42.3) Behavioral risk factors Illicit drug/s (ever use), n (%) 0.001 Never 921 (79) 249 (73) 669 (81.8) Only few times 228 (19.6) 82 (24) 142 (17.4) Regularly 17 (1.5) 10 (2.9) 7 (0.9) Problematic drinking (CAGE score), n (%) 0.014 No 810 (71.2) 218 (66.1) 588 (73.3) Yes Smoking (past 3 months), n (%) Never Occasionally Daily 328 (28.8) 911 (76.6) 183 (15.7) 74 (6.3) 112 (33.9) 257 (74.9) 63 (18.4) 23 (6.7) 214 (26.7) 648 (79.2) 119 (14.5) 51 (6.2) 0.234 Nutrition habits* (M ± SD) Dietary guideline adherence index 4.84 ± 1.57 4.22 ± 1.54 5.10 ± 1.51 < 0.001 n (%) frequency (percent); M ± SD mean ± SD; italicized cells indicate statistical significance; numbers might not sum up to total because of missing values. * range: 1–8, each point increase represents an additional food group that shows adherence to dietary guidelines Factor analysis of 18 self-reported burdens Table 2 shows the exploratory factor analysis of the 18 self-reported burdens generated by four factors with eigenvalues of 5.6, 1.9, 1.4 and 1.1 that cumulatively explained 55.2% of the total variance. Kaiser–Meyer–Olkin measure of sampling adequacy was 0.87, and Bartlett’s test of sphericity was significant (Chi-square test = 6609, df = 153, p < 0.001). Table 2 also depicts the four factors, their items and factor loadings. They were broadly classified into: ‘Studies’ (3 items, Cronbach’s α = 0.74); ‘Future’ (3 items, Cronbach’s α = 0.63); ‘Relationships’ (7 items, Cronbach’s α = 0.81); and ‘Needs’ (5 items, Cronbach’s α = 0.7). Table 2 Factor analysis of 18 self-reported burdens into four factors Burden Subscale Studies Future Relationships Needs Cronbach’s alpha 0.74 0.63 0.81 0.70 Eigenvalue 1.1 1.4 5.6 1.9 Studies in general .826 Exams, assignments, presentations .829 Lack of time for studies .595 Lack of practical relevance of studies .627 Anonymity at university .679 Bad job prospects .670 Problems with parents .622 Problems with fellow students .750 Problems with friends .765 Relationship with significant other .454 Sexuality .556 Isolation at the university .585 Isolation in general .627 Housing .670 Health problems .540 Financial situation .626 Workload in addition to studying .569 Bad working conditions .607 Extraction Method: Principal Component Analysis; Varimax Rotation with Kaiser Normalization; Rotation converged in 9 iterations. Clustering of Behavioral risk factors among students Figure 1 depicts the silhouette measure of cohesion and separation of the clusters illustrating that four good-quality clusters were generated. At the two extremes, Cluster 1 (Lower Risk Takers) comprised students who generally exhibited less risk taking behaviors, while conversely, Cluster 4 (Higher Risk Takers) membership was characterized by more risk taking behaviors. The other two clusters fell in between, namely, Cluster 2 (Problem Drinkers) and Cluster 3 (Illicit Drug Takers). Table 3 shows that in terms of sociodemographics, across the clusters, there were no significant differences in age. Clusters 1 and 2 had more females and more income-sufficient respondents. There were also significant differences in satisfaction with social support across the four clusters, where Cluster 1 students reported the highest level of satisfaction with their social support and Clusters 3 and 4 the lowest. Pertaining to the BRFs, there were significant differences across all four BRFs between the clusters. Cluster 1 (Lower Risk Takers) was generally characterized by that none of the respondents ever smoked, had problematic drinking or used illicit drug/s, although they displayed the second lowest healthy eating score. On the other hand, Cluster 4 (Higher Risk Takers) members comprised all students who were occasional/daily smokers, half used illicit drug/s regularly or a few times, half were problematic drinkers, and they also exhibited the lowest healthy eating score. The other two clusters fell in between these two polars, where students exhibited some extent of “preference”. Cluster 2 students (Problem Drinkers) were characterized by their higher alcohol consumption, as all students were problem drinkers, despite that all never smoked, mostly all never used illicit drug/s, and were second highest in terms of their healthy eating habits. On the other hand, Cluster 3 (Illicit Drug Takers) was distinguished by a higher illicit drug/s use, where all students had used illicit drug/s regularly or a few times, more than a third were problem drinkers, despite that all were never-smokers, and they had the healthiest eating habits of all the clusters. Table 3 Comparison of sociodemographic characteristics and behavioral risk factors across four clusters of university students in Finland Characteristic Cluster 1 n = 574 Cluster 2 n = 161 Cluster 3 n = 121 Cluster 4 n = 249 p Risk taking behaviors Overall less Overall more ‘Preference’ Alcohol Illicit Drug/s Sociodemographic Age, years (M ± SD) 22.83 ± 5.83 22.77 ± 4.30 23.84 ± 4.42 22.98 ± 4.34 0.253 Sex, n (%) 0.003 Female 425 (74.0) 118 (73.3) 69 (57.0) 168 (67.5) Male 148 (25.8) 42 (26.1) 49 (40.5) 80 (32.1) Perceived income sufficiency, n (%) 0.001 Always/ Mostly sufficient 352 (61.3) 94 (58.4) 60 (49.6) 120 (48.2) Always/ Mostly insufficient 214 (37.3) 66 (41.0) 61 (50.4) 125 (50.2) Social support (M ± SD) a 1.96 ± 1.05 2.07 ± 1.13 2.17 ± 1.12 2.33 ± 1.26 < 0.001 Behavioral risk factors Smoking (past 3 months), n (%) Never 574 (100) 161 (100) 121 (100) 0 (0) < 0.001 Occasionally 0 (0) 0 (0) 0 (0) 175 (70.3) Daily 0 (0) 0 (0) 0 (0) 74 (29.7) Problematic drinking (CAGE score), n (%) < 0.001 No 574(100) 0 (0) 77 (63.6) 133 (53.9) Yes 0 (0) 161 (100) 44 (36.4) 116 (46.1) Illicit drug use, n (%) < 0.001 Never 574 (100) 158 (98.1) 0 (0) 133 (53.4) Yes, regularly 0 (0) 3 (1.9) 1 (0.8) 13 (5.2) Yes, only a few times 0 (0) 0 (0) 120 (99.2) 103 (41.4) Healthy eating* (points) Dietary guideline adherence score 4.77 ± 1.53 5.04 ± 1.48 5.12 ± 1.52 4.76 ± 1.65 0.04 n (%) frequency (percent); M ± SD mean ± SD; a higher score = higher dissatisfaction; italicized cells indicate statistical significance; numbers might not sum up to total because of missing values; * range: 1–8, each point increase represents an additional food group that shows adherence to dietary guidelines Associations between socio-demographic variables and behavioral risk factor clusters with self-reported burdens Table 4 shows the associations of the socio-demographic variables, social support, BRFs clusters with individual burdens components. For the socio-demographic variables, in terms of the number (breadth) of the associations, generally, sex and social support were significantly associated with all four burdens, whilst age and income sufficiency were significantly associated with three burdens. As for the direction of the associations, females were more likely to associate with the ‘Studies’ and ‘Relationships’ burdens, but less likely with the ‘Future’ and ‘Needs’ burdens. Higher satisfaction with social support was significantly associated with less burdens generally. Older age was significantly associated with less ‘Studies’, ‘Future’ and ‘Relationships’ burdens. Sufficient income was significantly associated with less ‘Studies’, ‘Future’ and ‘Needs’ burdens. Pertaining to the clusters, generally, there were differences in ‘Relationships’ and/or ‘Needs’ burdens rather than the ‘Studies’ and ‘Future’ burdens. For instance, compared to Cluster 1, Cluster 4 membership was significantly more likely to feel ‘Needs’ burdens, and Cluster 3 membership was significantly more likely to report ‘Relationships’ and ‘Needs’ burdens. Table 4 Association of behavioral risk factor cluster with individual burdens components Predictors Studies Future Relationships Needs Std-β β (95% CI) Std-β β (95% CI) Std-β β (95% CI) Std-β β (95% CI) Sex (female) 0.20 1.34 (1.72; 0.97) *** -0.11 0.66 (1.01; 0.31) *** -0.10 1.22 (1.88; 0.56) *** 0.21 1.88 (2.56;1.53) *** Age -0.09 -0.05 (-0.08; -0.02) ** -0.11 -0.06 (-0.09; -0.03) *** -0.10 -0.10 (-0.16; -0.05) *** -0.01 -0.01 (-0.05; 0.04) Income sufficiency (sufficient) -0.16 -0.98 (-1.33; -0.64) *** -0.08 -0.45 (-0.78; -0.13) ** -0.05 -0.52 (-1.13; 0.09) -0.26 -2.33 (-2.80; -1.85) *** Social support a 0.41 0.15 (0.26; 0.56) *** 0.18 0.44 (0.30; 0.59) *** 0.31 1.50 (1.24; 1.77) *** 0.20 0.79 (0.59; 1.00) *** Cluster 4 (vs Cluster 1) -0.01 -0.06 (-0.49; 0.39) -0.01 -0.07 (-0.48; 0.34) 0.04 0.49 (-0.28; 1.26) 0.09 0.96 (0.36; 1.56) ** Cluster 2 (vs Cluster 1) 0.04 0.39 (-0.16; 0.91) 0.05 0.36 (-0.11; 0.84) 0.05 0.86 (-0.04; 1.75) 0.03 0.41 (-0.29; 1.11) Cluster 3 (vs Cluster 1) 0.02 0.17 (-0.41; 0.75) 0.02 0.17 (-0.38; 0.71) 0.07 1.25 (0.24; 2.26) * 0.08 1.19 (0.39; 1.98) ** Std-ß: standardized beta coefficient; ß: beta coefficient; CI: confidence interval; all variables in the model adjusted for all the other variables; perceived social support * p < 0.05, ** p < 0.01, *** p < 0.001; a higher ratings of social support represent less satisfaction with social support Discussion The current study adds new insights to the limited research on lifestyle habits of university students pertaining to the clustering of BRFs (nutrition behavior, alcohol, tobacco, illicit drug/s use), and their association with self-reported burdens. To our knowledge, this is the first study of a large sample of university students in Finland to undertake such analysis. Our main findings were that there was four unique sets of burdens that students felt (Studies, Future, Relationships, Needs). The study also noted four distinct BRFs clusters that were significantly different from each other in terms of their relative configurations of the four risk factors (Lower Risk-Takers, Problem Drinkers, Illicit Drug Takers, Higher Risk Takers), and also significantly different in terms of their students’ sociodemographic characteristics. Collectively, these findings suggest several points regarding the characteristics of clusters of lifestyle habits. First, BRFs do not exist in a solitary fashion, rather they group together in constellations. Individuals engaging in one risky behavior probably engage in other risky behaviors; and conversely, students with healthier lifestyles are likely to maintain healthy diets, not smoke and be physically active. Second, despite this, such clusters do not represent clear-cut opposite-facing constellations of behaviors. Hence, we noted that although some clusters e.g., Cluster 4 Higher Risk−Takers was characterized by several unhealthy behaviors, the cluster still harbored healthy patterns of eating; and vice versa, where despite that some clusters were characterized by generally healthy behaviors e.g., Cluster 1 Lower Risk Takers , their members still engaged in unhealthy activities, reflected by less healthy nutritional habits. Such observed contrast or paradox might be explained by the principle of compensatory health beliefs, where individuals engage in risk behavior/s in one area of their lives, and attempt to balance it out by performing healthy behavior/s in another sphere of their life [ 52 ]. For example, individuals who drink alcohol on regular basis might also regularly exercise and eat healthy to feel like balancing out the health risks associated with the regular alcohol use. However, such proposed trade offs remain unclear. Whether any beneficiary effects accrued from exercise and a healthy diet actually counteract the negative health impacts of excessive alcohol consumption remain to be uncovered. Some propositions hold that improving physical fitness by working out and eating a healthier diet is one of the most effective ways to combat alcoholism and counteract the many negative health effects that it causes [ 53 ]. As for the prevalence of BRFs (unhealthy behaviors) within each cluster, we noted differences for three (alcohol consumption, illicit drug use, smoking) out of the four BRFs examined. Pertaining to alcohol consumption, with the exception of Cluster 1, the other three clusters represented students with 46%, 100% and 36% prevalence of problematic alcohol consumption. These findings support other studies in university settings that found that problematic drinking patterns characterized student life [ 54 , 55 ]. University life symbolises the transitions from the stricter parental control and structured high school environment to a more independent and less supervised lifestyle, with freedom, desires to explore boundaries, and peer social pressure to fit in the group [ 56 ]. These might contribute to a higher alcohol consumption. Others have also noted that students might consume alcohol as a mechanism to cope with academic stress, pressure and deadlines, or social anxiety [ 57 – 59 ]. Across our sample, 22% of the students regulary or occasionally used illicit drugs, with the highest prevalence observed in Cluster 3 Illicit Drug Takers and Cluster 4 Higher Risk−Takers . Compared with data from other countries and regions, a national survey of 2810 students in the UK reported that 56% of respondents had used drugs, and 39% currently used them [ 60 ]; and a large scale North American survey showed that the annual prevalence of illicit substance use among university student populations was 43% [ 61 ]. Interestingly, smoking was observed only in Cluster 4, characterized by members with more risky behavioral patterns as all students in this cluster smoked occasionally/regularly. More recent data from The 2021 Finnish Student Health and Wellbeing Survey observed that, among university students, 6% of women and 5% of men were daily smokers [ 62 ] suggesting a decreasing trend, a pattern observed globally and supported, for example, by data from USA [ 63 ]. Relationship between BRF cluster membership and specific burdens Using regression analyses that adjusted for sex, age, income sufficiency and social support, the current study appraised the relationships between the BRFs clusters and the four sets of self-reported burdens. Compared to Cluster 1 Lower Risk−Takers , Clusters 4 Higher Risk−Takers and 3 Illicit Drugs Takers were significantly more likely to report only one burden, namely the ‘Needs’ burdens, comprising elements related to housing, health problems, finances, and workloads. Such significant differences between the higher and lower risk takers in relation to the ‘Needs’ burdens might be partly attributed to the higher levels of illicit drug use and problematic drinking evident in Cluster 3, along with the additional smoking observed in Cluster 4, compared to Cluster 1. Multiple substance use (e.g., alcohol, tobacco, and other drugs, ATOD) is frequently associated with difficulties and negative life consequences, with higher likelihood of experiencing adverse outcomes, increased risk of physical and chronic health issues, as well as mental health conditions, all burdens that negatively impact well-being and render it harder to cope with daily challenges [ 64 – 67 ]. ATOD use is also costly, posing additional financial burdens on students already facing financial strains. Collectively, such features might lead to the burdens of meeting basic needs, fulfilling responsibilities and goals, and negatively impacting academic performance [ 68 ]. We also noted that Cluster 3 Illicit Drugs Takers students were significantly more likely to report ‘Relationship’ burdens compared to Cluster 1 Lower Risk−Takers . Again, alcohol and illicit drug use, characteristic of our Cluster 3 students may strain relationships with family, friends, and partners, potentially resulting in feelings of isolation and diminished support [ 69 ]. Indeed Cluster 3 students reported significantly lower satisfaction with the level of social support they receive compared to Cluster 1 students. In connection with links between sociodeomgraphics and social support on the one hand and burdens on the other, across the current sample, higher social support was significantly negatively associated with all the four burden components that were examined. Our findings support other research, where higher social support is viewed as a protective factor that can alleviate the burdens encountered in various aspects of life, and relieve emotional strains and stress [ 70 ] that are related to academic life and ‘Studies’ [ 71 – 73 ], basic ‘Needs’ [ 74 ] and ‘Relationships’ [ 75 ]. As for gender, across our smaple found that females were significantly more likely than males to be burdened by the ‘Studies’ and ‘Needs’ burdens. Although the precise reasons why females felt ‘Studies’ as a burden are difficult to speculate, however, generally, women value higher education and attach more attention and focus on their studies, possibly to the extent of feeling ‘burdened’ by ‘Studies’. Such propositions are in line with a number of studies that found higher general and academic stress levels among female students compared to their male counterparts [ 76 , 77 ]. The reasons why females felt the ‘Needs’ burden more than males are again difficult to pinpoint, but it is plausible that females value strongly the links between academic success and future financial stability, motivating them to focus on their future careers in order to satisfy needs. Conversly, in the current study, females were less likely to report ‘Relationship’ burdens than males, reflecting that for these young adults, it is frequently the males who seek out to initiate relationships [ 78 ]. In terms of age, we observed that older age was significantly associated with less ‘Studies’, ‘Future’ and ‘Relationships’ burdens. As younger university students progress in age and advance through their academic journey, they acquire more skills and life experience rendering them more adaptable to new situations, as well as effective strategies and better-coping mechanisms to navigate life challenges and stress. Pertaining to income sufficiency, across our sample, those with sufficient income were less likely to report ‘Studies’, ‘Future’ and ‘Needs’ burdens, congruent with research where perceived socioeconomic status predicted better well-being outcomes [ 33 , 79 ]. This study has limitations. Cross-sectional survey designs do not allow the confirmation of the direction associations. Data were self-reported, and we are unable to exclude recall and social desirability biases. The low response rate could have affected the sample's representativeness, and hence internal validity and generalizability. Our questionnaire focused on cigarette smoking rather than the use of electronic cigarettes, which are also prevalent among young adults. Future research would benefit from addressing these limitations. Despite these limtations, the study boasts many strengths, including a large sample of students from all the University’s departments and faculties, categorized into clusters that report on a wide range of health-related BRFs. To our knowledge, it is the first study among university students in Finland to evaluate and categorize students into BRF clusters and to explore the associations of these clusters with burdens, while controlling for multiple potential confounders. Conclusion Cluster analysis of BRFs can reveal high-risk groups. The current study identified four BRFs clusters, which, although distinct, do not represent clear-cut opposite-facing constellations of behaviors. Generally, substance users were significantly more likely to report ‘Needs‘, ‘Relationships’ and ‘Needs’ burdens. Higher social support was associated with fewer burdens. BRFs are products of lifestyle choices. Therefore, the identification of BRFs clusters as in the current study can guide health promotion prevention efforts to encourage regular PA, healthy eating habits and nutrition, as well as smoking cessation and responsible drinking programs, and effective behavioral modification interventions to protect the health of these young adults. Our findings can assist educators, policymakers and other stakeholders involved with similar student populations. Declarations Ethics approval and consent to participate This study has been reviewed and approved by the University Research and Ethics Committee (Approval # Lausunto 10/2010). Students were informed that by completing the survey, they agree to participate in the study. All methods were carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki) Consent for publication Not applicable. Availability of data and materials Data are available from the authors upon reasonable request to corresponding authors. Competing interests The authors declare no competing interests Funding This research received no external funding. Authors’ contributions Conceptualization, Walid El Ansari; methodology, Walid El Ansari, Rene Sebena; analyses, Rene Sebena; investigation, Walid El Ansari, Rene Sebena and Kareem El-Ansari; writing original draft preparation, Walid El Ansari, Rene Sebena and Kareem El-Ansari. All authors have read and agreed to the published version of the manuscript. Acknowledgements The authors thank the university and students who participated in the survey. Rene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284 References Islam A, Low WY, Tong WT, Choo C, Yuen W. Factors Associated with Depression among University Students in Malaysia: A Cross-sectional Study. KnE Life Sci 2018;415–27. Müller C, El-Ansari K, El Ansari W. Health-Promoting Behavior and Lifestyle Characteristics of Students as a Function of Sex and Academic Level. Int J Environ Res Public Health. 2022;19(12):7539. 10.3390/ijerph19127539 . PMID: 35742787; PMCID: PMC9224493. Wirnitzer KC, Motevalli M, Cocca A, Tanous DR, Wirnitzer G, Wagner KH, Schätzer M, Drenowatz C, Ruedl G, Kirschner W. Health behavior of Austrian tertiary students focusing on diet type linked to sports and exercise-first glimpse of results from the sustainably healthy-from science 2 high school and university study. Front Public Health. 2023;11:1129004. 10.3389/fpubh.2023.1129004 . PMID: 37533531; PMCID: PMC10392833. Mikolajczyk RT, Maxwell AE, Naydenova V, Meier S, El Ansari W. Depressive symptoms and perceived burdens related to being a student: Survey in three European countries. Clin Pract Epidemiol Ment Health. 2008;4:19. 10.1186/1745-0179-4-19 . PMID: 18598340; PMCID: PMC2483702. Hill MR, Goicochea S, Merlo LJ. In their own words: stressors facing medical students in the millennial generation. Med Educ Online. 2018;23(1):1530558. PMID: 30286698; PMCID: PMC6179084. El Ansari W, Stock C. Explaining the gender difference in self-rated health among university students in Egypt. Women Health. 2016;56(7):731–44. Epub 2016 Feb 17. PMID: 26886289. El Ansari W, Sebena R, Stock C. Socio-demographic correlates of six indicators of alcohol consumption: survey findings of students across seven universities in England, Wales and Northern Ireland. Arch Public Health. 2013;71(1):29. 10.1186/2049-3258-71-29 . PMID: 24196210; PMCID: PMC3923438. El Ansari W, Stock C, UK Student Health Group, Snelgrove S, Hu X, Parke S, Davies S, John J, Adetunji H, Stoate M, Deeny P, Phillips C, Mabhala A. Feeling healthy? A survey of physical and psychological wellbeing of students from seven universities in the UK. Int J Environ Res Public Health. 2011;8(5):1308–23. 10.3390/ijerph8051308 . Epub 2011 Apr 27. PMID: 21655121; PMCID: PMC3108111. Sinha GR, Larrison CR, Brooks I, Kursuncu U. Comparing Naturalistic Mental Health Expressions on Student Loan Debts Using Reddit and Twitter. J Evid Based Soc Work (2019). 2023;20(5):727–742. doi: 10.1080/26408066.2023.2202668. Epub 2023 Apr 16. PMID: 37461303. Hanson M. Average Medical School Debt. Education Data Initiatives. Updated December 9, 2021. https://educationdata.org/averagemedical-school-debt (Accessed 23 May, 2024). Wunsch K, Fiedler J, Bachert P, Woll A. The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2021;18(2):739. 10.3390/ijerph18020739 . PMID: 33467118; PMCID: PMC7830011. Pacheco JP, Giacomin HT, Tam WW, Ribeiro TB, Arab C, Bezerra IM, Pinasco GC. Mental health problems among medical students in Brazil: a systematic review and meta-analysis. Braz J Psychiatry. 2017 Oct-Dec;39(4):369–78. 10.1590/1516-4446-2017-2223 . Epub 2017 Aug 31. PMID: 28876408; PMCID: PMC7111407. Beiter R, Nash R, McCrady M, Rhoades D, Linscomb M, Clarahan M, Sammut S. The prevalence and correlates of depression, anxiety, and stress in a sample of college students. J Affect Disord. 2015;173:90–6. 10.1016/j.jad.2014.10.054 . Epub 2014 Nov 8. PMID: 25462401. Eskin M, Sun JM, Abuidhail J, Yoshimasu K, Kujan O, Janghorbani M, Flood C, Carta MG, Tran US, Mechri A, Hamdan M, Poyrazli S, Aidoudi K, Bakhshi S, Harlak H, Moro MF, Nawafleh H, Phillips L, Shaheen A, Taifour S, Tsuno K, Voracek M. Suicidal Behavior and Psychological Distress in University Students: A 12-nation Study. Arch Suicide Res. 2016;20(3):369–88. Epub 2016 Mar 8. PMID: 26954847. Wilson CK, Matthews JI, Seabrook JA, Dworatzek PDN. Self-reported food skills of university students. Appetite. 2017;108:270–276. 10.1016/j.appet.2016.10.011 . Epub 2016 Oct 11. PMID: 27742236. Abdel Sadek HA, Abu-Nazel MW, Shata ZN, Abd El-Fatah NK. The relationship between the BMI and the emotional status of Alexandria University students, Egypt. J Egypt Public Health Assoc. 2016;91(3):101–108. 10.1097/01.EPX.0000484542.88399.c7 . PMID: 27749640. Al-Sayegh N, Al-Shuwai N, Ramadan S, Al-Qurba T, Al-Obaidi SM, Dean E. Benchmarking the health of health sciences students at Kuwait University: towards a culture of health. East Mediterr Health J. 2016;22(8):619–627. 10.26719/2016.22.8.619 . PMID: 27834444. White HR, Labouvie EW, Papadaratsakis V. Changes in substance use during the transition to adulthood: A comparison of college students and their noncollege age peers. J Drug Issues. 2005;35(2):281–306. Wechsler H, Wuethrich B. Dying to drink: Confronting binge drinking on college campuses. Rodale Customer Service, 33 East Minor Street, Emmaus, PA 18098, 2002. Kypri K, Langley J, Stephenson S. Episode-centred analysis of drinking to intoxication in university students. Alcohol Alcohol. 2005 Sep-Oct;40(5):447 – 52. 10.1093/alcalc/agh178 . Epub 2005 Jul 4. PMID: 15996969. Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE, Miech RA. 1975–2014: Volume 2, College students and adults ages 19–55. Monitoring the Future national survey results on drug use. Ann Arbor: Institute for Social Research. The University of Michigan; 2015. Available at myumi.ch/J7G22. Jelagat J, Budambula NLM, Ngari M, Budambula V. Polydrug Use among Students in a Public University in a Lower Middle-Income Country. Biomed Res Int. 2023;2023:8085588. 10.1155/2023/8085588 . PMID: 37560202; PMCID: PMC10409583. El Ansari W, Ssewanyana D, Stock C. Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis. Front Public Health. 2018;6:120. 10.3389/fpubh.2018.00120 . PMID: 29868535; PMCID: PMC5950502. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2197–223. Quintiliani L, Allen J, Marino M, Kelly-Weeder S, Li Y. Multiple health behavior clusters among female college students. Patient Educ Couns. 2010;79(1):134–7. 10.1016/j.pec.2009.08.007 . Epub 2009 Sep 19. PMID: 19767168; PMCID: PMC5892440. Baskin-Sommers A, Sommers I. The co-occurrence of substance use and high-risk behaviors. J Adolesc Health. 2006;38(5):609 – 11. 10.1016/j.jadohealth.2005.07.010 . PMID: 16635777. Willoughby T, Chalmers H, Busseri MA. Where is the syndrome? Examining co-occurrence among multiple problem behaviors in adolescence. J Consult Clin Psychol. 2004;72(6):1022-37. 10.1037/0022-006X.72.6.1022 . PMID: 15612849. El Ansari W, Berg-Beckhoff G. Country and Gender-Specific Achievement of Healthy Nutrition and Physical Activity Guidelines: Latent Class Analysis of 6266 University Students in Egypt, Libya, and Palestine. Nutrients. 2017;9(7):738. 10.3390/nu9070738 . PMID: 28696407; PMCID: PMC5537852. Costa E, et al. Clustering of behavioural risk factors in the Portuguese population: Data from National Health Interview Survey. J Behav Health. 2014;3:205–11. Hudd S, Dumlao J, Erdmann-Sager D, Murray D, Phan E, Soukas N, Yokozuka N. Stress at college: Effects on health habits, health status and self-esteem. Coll Student J. 2000;34(2):217–27. Cheung DK, Tam DKY, Tsang MH, Zhang DLW, Lit DSW. Depression, anxiety and stress in different subgroups of first-year university students from 4-year cohort data. J Affect Disord. 2020;274:305–14. 10.1016/j.jad.2020.05.041 . Epub 2020 May 22. PMID: 32469820. Sebena R, Orosova O, Mikolajczyk RT, van Dijk JP. Selected sociodemographic factors and related differences in patterns of alcohol use among university students in Slovakia. BMC Public Health. 2011;11:849. 10.1186/1471-2458-11-849 . PMID: 22067135; PMCID: PMC3282827. Goodman E, Huang B, Schafer-Kalkhoff T, Adler NE. Perceived socioeconomic status: a new type of identity that influences adolescents' self-rated health. J Adolesc Health. 2007;41(5):479–87. 10.1016/j.jadohealth.2007.05.020 . Dougall I, Vasiljevic M, Kutlaca M, Weick M. Socioeconomic inequalities in mental health and wellbeing among UK students during the COVID-19 pandemic: Clarifying underlying mechanisms. PLoS ONE. 2023;18(11):e0292842. 10.1371/journal.pone.0292842 . PMID: 37910542; PMCID: PMC10619810. Lakey B, Sheldon C. Social support theory and measurement. In: Sheldon C, Underwood LG, Gottlieb BH, editors. Social Support Measurement and Intervention: A Guide for Health and Social Scientists. New York: Oxford University Press; 2000. pp. 29–52. Baqutayan S. Stress and Social Support. Indian J Psychol Med. 2011;33:29–34. Litwic-Kaminska K, Błachnio A, Kapsa I, Brzeziński Ł, Kopowski J, Stojković M, Hinić D, Krsmanović I, Ragni B, Sulla F, Limone P. Resilience, Positivity and Social Support as Perceived Stress Predictors among University Students. Int J Environ Res Public Health. 2023;20(19):6892. 10.3390/ijerph20196892 . PMID: 37835162; PMCID: PMC10572749. Szkody E, McKinney C. Appraisal and social support as moderators between stress and physical and psychological quality of life. Stress Health. 2020;36(5):586–95. 10.1002/smi.2957 . Epub 2020 Jun 12. PMID: 32419328. El Ansari W, Sebena R, El-Ansari K, Suominen S. Clusters of lifestyle behavioral risk factors and their associations with depressive symptoms and stress: evidence from students at a university in Finland. BMC Public Health. 2024;24(1):1103. 10.1186/s12889-024-18421-0 . PMID: 38649903; PMCID: PMC11034152. El Ansari W, Suominen S, El-Ansari K, Šebeňa R. Are behavioural risk factors clusters associated with self-reported health complaints? University students in Finland. Cent Eur J Public Health. 2023;31(4):248–255. 10.21101/cejph.a7916 . PMID: 38309702. Scott AJ, Knott M. A cluster analysis method for grouping means in the analysis of variance. Biometrics. 1974; 507–12. De Bourdeaudhuij I, Van Cauwenberghe E, Spittaels H, Oppert JM, Rostami C, Brug J, Van Lenthe F, Lobstein T, Maes L. School-based interventions promoting both physical activity and healthy eating in Europe: a systematic review within the HOPE project. Obes Rev. 2011;12(3):205 – 16. 10.1111/j.1467-789X.2009.00711.x . PMID: 20122137. Arnett JJ. Emerging adulthood. A theory of development from the late teens through the twenties. Am Psychol. 2000;55(5):469–80. PMID: 10842426. Aceijas C, Waldhäusl S, Lambert N, Cassar S, Bello-Corassa R. Determinants of health-related lifestyles among university students. Perspect Public Health. 2017;137(4):227–236. 10.1177/1757913916666875 . Epub 2016 Sep 5. PMID: 27597797. Sebena R, El Ansari W, Stock C, Orosova O, Mikolajczyk RT. Are perceived stress, depressive symptoms and religiosity associated with alcohol consumption? A survey of freshmen university students across five European countries. Subst Abuse Treat Prev Policy. 2012;7:21. 10.1186/1747-597X-7-21 . PMID: 22640549; PMCID: PMC3395565. Sarason IG, Levine HM, Basham RB, Sarason BR. Assessing social support: The social support questionnaire. J Pers Soc Psychol. 1983;44:127–30. Ewing JA. Detecting alcoholism. The CAGE questionnaire. JAMA. 1984;252:1905–7. El Ansari W, Salam A. Prevalence and predictors of smoking, quit attempts and total smoking ban at the University of Turku, Finland. Cent Eur J Public Health. 2021;29:45–55. El Ansari W, Vallentin-Holbech L, Stock C. Predictors of illicit drug/s use among university students in Northern Ireland, Wales and England. Glob J Health Sci. 2014;7(4):18–29. 10.5539/gjhs.v7n4p18 . PMID: 25946914; PMCID: PMC4802112. El Ansari W, Stock C, Mikolajczyk RT. Relationships between food consumption and living arrangements among university students in four European countries - a cross-sectional study. Nutr J. 2012;11:28. 10.1186/1475-2891-11-28 . World Health Organization. Regional Office for Europe. Food-based dietary guidelines in the WHO European Region. Copenhagen: WHO Regional Office for Europe. ‎2003; https://apps.who.int/iris/handle/10665/107490 . Knäuper B, Rabiau M, Cohen O, Patriciu N. Compensatory health beliefs: scale development and psychometric properties. Psychol Health. 2004;19(5):607–24. Cabé N, Lanièpce A, Pitel AL. Physical activity: A promising adjunctive treatment for severe alcohol use disorder. Addict Behav. 2021;113:106667. 10.1016/j.addbeh.2020.106667 . Epub 2020 Sep 29. PMID: 33074123. Hallett J, McManus A, Maycock B, Smith J, Howat P. Excessive Drinking—An Inescapable Part of University Life? A Focus Group Study of Australian Undergraduates. Open J Prev Med. 2014;4:616–29. https://doi.org/10.4236/ojpm.2014.47071 . Wicki M, Kuntsche E, Gmel G. Drinking at European universities? A review of students' alcohol use. Addict Behav. 2010;35:913–24. Schulenberg J, Wadsworth KN, O'Malley PM, Bachman JG, Johnston LD. Adolescent risk factors for binge drinking during the transition to young adulthood: Variable- and pattern-centered approaches to change. Dev Psychol. 1996;32(4):659–74. https://doi.org/10.1037/0012-1649.32.4.659 . Williams A, Clark D. Alcohol consumption in university students: the role of reasons for drinking, coping strategies, expectancies, and personality traits. Addict Behav. 1998 May-Jun;23(3):371-8. 10.1016/s0306-4603(97)80066-4 . PMID: 9668934. Douglass MA, Colley ML, Tyskiewicz AJ, Prince MA. Drinking to cope and college grade point average. Drugs Habits Social Policy. 2023;24(4):342–50. https://doi.org/10.1108/DHS-05-2023-0016 . Terlecki MA, Ecker AH, Buckner JD. College drinking problems and social anxiety: The importance of drinking context. Psychol Addict Behav. 2014;28(2):545–52. 10.1037/a0035770 . National Union of Students, Release. Taking the Hit: Student drug use and how Institutions respond. London. [online]. 2018. https://www.release.org.uk/publications/taking-hit-student-drug-use-and-how-institutions-respond (accessed 22 May 2024). Schulenberg JE, Johnston LD, O’Malley PM, Bachman JG, Miech RA, Patrick ME. Monitoring the Future national survey results on drug use, 1975–2019: Volume II, College students and adults ages 19–60. Ann Arbor: Institute for Social Research: The University of Michigan:; 2020. p. 7. Parikka S, Holm N, Ikonen J, Koskela T, Kilpeläinen H, Lundqvist A. May. KOTT 2021 -tutkimuksen perustulokset 2021. [online] (accessed 22 2024). Gallup. Cigarette Smoking Rates Down Sharply Among U.S. Young Adults.[online]. 2022. https://news.gallup.com/poll/405884/cigarette-smoking-rates-down-sharply-among-young-adults.aspx (accessed 23 May 2024). Hersh J, Curry JF, Becker SJ. The influence of comorbid depression and conduct disorder on MET/CBT treatment outcome for adolescent substance use disorders. Int J Cogn Ther. 2013;6:325–41. 10.1521/ijct.2013.6.4.325 . Scalco MD, Colder CR, Hawk LW, Read JP, Wieczorek WF, Lengua LJ. Internalizing and externalizing problem behavior and early adolescent substance use: a test of a latent variable interaction and conditional indirect effects. Psychol Addict Behav. 2014;28:828–40. 10.1037/a0035805 . Wu LT, Zhu H, Ghitza UE. Multicomorbidity of chronic diseases and substance use disorders and their association with hospitalization: Results from electronic health records data. Drug Alcohol Depend. 2018;192:316–23. 10.1016/j.drugalcdep.2018.08.013 . NIDA, Introduction. National Institute on Drug Abuse website. https://nida.nih.gov/publications/research-reports/common-comorbidities-substance-use-disorders/ . August 3, 2021. (Accessed April 20, 2024). Bugbee BA, Beck KH, Fryer CS, Arria AM, Substance, Use. Academic Performance, and Academic Engagement Among High School Seniors. J Sch Health. 2019;89(2):145–56. 10.1111/josh.12723 . PMID: 30604451; PMCID: PMC6373775. Copeland M, Fisher JC, Moody J, Feinberg ME. Different Kinds of Lonely: Dimensions of Isolation and Substance Use in Adolescence. J Youth Adolesc. 2018;47(8):1755–70. 10.1007/s10964-018-0860-3 . Epub 2018 May 17. PMID: 29774451; PMCID: PMC6045973. Kim B, Jee S, Lee J, An S, Lee SM. Relationships between social support and student burnout: A meta-analytic approach. Stress Health. 2018;34(1):127–34. 10.1002/smi.2771 . Epub 2017 Jun 22. PMID: 28639354. Szkody E, Stearns M, Stanhope L, McKinney C. Stress-Buffering Role of Social Support during COVID-19. Fam Process. 2021;60(3):1002–15. 10.1111/famp.12618 . Epub 2020 Nov 21. PMID: 33220082; PMCID: PMC7753728. Frazier P, Gabriel A, Merians A, Lust K. Understanding stress as an impediment to academic performance. J Am Coll Health. 2019 Aug-Sep;67(6):562–570. doi: 10.1080/07448481.2018.1499649. Epub 2018 Oct 4. PMID: 30285563. Muirhead V, Locker D. Canadian dental students' perceptions of stress and social support. Eur J Dent Educ. 2008;12(3):144-8. 10.1111/j.1600-0579.2008.00512.x . PMID: 18666895. Xin Z. Perceived social support and college student engagement: moderating effects of a grateful disposition on the satisfaction of basic psychological needs as a mediator. BMC Psychol. 2022;10(1):298. 10.1186/s40359-022-01015-z . PMID: 36503628; PMCID: PMC9743595. Stanton MV, Jones A, Shahani D. Relationship among interpersonal stressors in adolescence, social support buffers, and obesity in adulthood 14 years later. Health Psychol. 2022;41(12):904–11. 10.1037/hea0001223 . Epub 2022 Oct 13. PMID: 36227311. Backović DV, Živojinovic JI, Maksimović J, Maksimović M. Gender differences in academic stress and burnout among medical students in final years of education. Psychiatria Danubina. 2012;24(2):75–181. Graves BS, Hall ME, Dias-Karch C, Haischer MH, Apter C. Gender differences in perceived stress and coping among college students. PLoS ONE. 2021;16(8):e0255634. 10.1371/journal.pone.0255634 . PMID: 34383790; PMCID: PMC8360537. Schneider N. Gender Roles in Intimate Relationships: Who Initiates and Why? Can J Family Youth. 2022;14(2):11–20. Dougall I, Vasiljevic M, Kutlaca M, Weick M. Socioeconomic inequalities in mental health and wellbeing among UK students during the COVID-19 pandemic: Clarifying underlying mechanisms. PLoS ONE. 2023;18(11):e0292842. 10.1371/journal.pone.0292842 . PMID: 37910542; PMCID: PMC10619810. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4595741","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":316169989,"identity":"4aaa47af-59b9-418d-87a5-668e1133667d","order_by":0,"name":"Walid El Ansari","email":"","orcid":"","institution":"Hamad General Hospital, Hamad Medical Corporation","correspondingAuthor":false,"prefix":"","firstName":"Walid","middleName":"El","lastName":"Ansari","suffix":""},{"id":316169990,"identity":"a5120353-1d33-4bca-b924-0096776a99a7","order_by":1,"name":"Kareem El-Ansari","email":"","orcid":"","institution":"St. George’s University","correspondingAuthor":false,"prefix":"","firstName":"Kareem","middleName":"","lastName":"El-Ansari","suffix":""},{"id":316169991,"identity":"d9670025-6e09-499b-8d69-194d15340847","order_by":2,"name":"Rene Sebena","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBCDBCBmfMDAwMYAwURqYTYgWQubBIRNQIt5e+/BBwx/bPL4pZufVfPu4LNn4D+WgFeLzJlzyQaMbWnFknOOmd3mPcOW2CCRdgCvFgmJHDMJxobDiRtuJAC1tLElMEiwN+DXIv/G/AfDn/+J+2+kfysGagE67DgBLRI8ZkAPH0jcALSOGaiFsYGBkMN4cowlEtuSiyVu5BRLzgX6pU0iLQG/FvYzhh8+/LHL45+RvvHD2x3H7Pn5jxng1QIGcFMZG44RG5EILTWkaRgFo2AUjIIRAQAJPkCjuI3e8AAAAABJRU5ErkJggg==","orcid":"","institution":"PJ Safarik University","correspondingAuthor":true,"prefix":"","firstName":"Rene","middleName":"","lastName":"Sebena","suffix":""}],"badges":[],"createdAt":"2024-06-17 18:39:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4595741/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4595741/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59652724,"identity":"13be2c5d-139b-48b6-88a1-c90982d5e409","added_by":"auto","created_at":"2024-07-04 10:09:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8014,"visible":true,"origin":"","legend":"\u003cp\u003eCluster Quality of behavioral risk factors: Silhouette measure of cohesion and separation (Two-step algorithm, 4 inputs, 4 clusters)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4595741/v1/3e0e15afdf6aef2b14014459.png"},{"id":73516193,"identity":"0842dfb1-24bd-4aa4-82a2-369457e7fd46","added_by":"auto","created_at":"2025-01-10 17:46:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1098869,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4595741/v1/2b9cd015-767d-4e0c-8159-9f32892ae19d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Behavioral Risk Factors Clusters and their Associations with Self-Reported Burdens Among University Students in Finland","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUniversity students face a range of burdens during transition from adolescence to adulthood, rendering them a particularly vulnerable group [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Moreover, their lifestyles are frequently characterized by unhealthy behaviors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While young adulthood is a period for adopting and stabilizing lifelong healthy behavior, university life is independently associated with burdens that may further affect health and well-being [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of burdens, across university students in Germany, Poland, and Bulgaria, students felt burdened by their course work, exams, uncertainty of the future, problems with relationships and feeling isolated [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Other significant burdens that students face include financial obligations, overwhelming workload, pressure to succeed, and work-life balance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Studies found that 35.9%-60.4% of undergraduates felt burdened by studies, assignments, and presentations, lack of time for studies, and bad job prospects [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For instance, across 7 universities in Northern Ireland, Wales and England, one third of the students were highly burdened by finances [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], as well as exams, workload, and lack of time [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Likewise, in the USA, the cognitive burden created by student loans is significant [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Collectively, such burdens exert pressure on students, manifested as poor academic performance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], depression [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], anxiety [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] or even suicidal thoughts [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePertaining to behavioural risk factors (BRFs), unhealthy lifestyle behaviors are prevalent among university students. Many exihbit low rates of healthy nutrition, or dietary patterns that are below the recommended guidelines [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Likewise, cigarette smoking is frequently initiated as individuals transition from high school to university [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In addition, university students have been reported to be heavy drinkers [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], with higher consumption of alcohol than their non-university peers [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and illicit drug use is common [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe congregation of unhealthy behaviors (smoking, alcohol consumption, illicit drug/s use, bad eating habits) influence students\u0026rsquo; health and mortality risk [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], as unhealthy behaviors cluster together to generate multiplier effects. More than 65% of young fulltime female students at a USA university reported\u0026thinsp;\u0026ge;\u0026thinsp;2 unhealthy behaviors [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and BRFs co-occur with each other [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Clustering of BRFs refers to an observed proportion of a combination of risk factors in excess of its expected proportion [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOther variables related to both burdens and BRFs play a confounding role. Among university students, differences related to sex [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], age or year of study [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and income [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] have been observed in the levels of perceived burdens and in BRFs. Likewise, adequate social support, defined as supportive actions by others that facilitate one\u0026rsquo;s ability to cope with a stressful situation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], may attenuate the burden of stressful events [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and significantly buffer the effects of risky behaviour on physical and psychological health [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe literature reveals knowledge gaps. Despite the variety of burdens and BRFs characterizing this young adult population, surprisingly few studies have examined the range of student-related perceived burdens (categorized into factors) and the relationships of such burdens with a range of BRFs (categorized into clusters) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. We are not aware of any studies that undertook this task among Finnish university students. The current study bridges this knowledge gap by utilizing a cluster analysis approach [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], an increasingly popular method in the assessment of BRFs. We employed a large sample of students at a university in Finland in order to: (1) factor analyze 18 their self-reported burdens in components; (2) identify and describe the clustering of four major lifestyle BRFs [tobacco, alcohol, illicit drugs, nutrition behavior]; (3) characterize the student characteristics of each of the emerging clusters in terms of sociodemographics and BRF distribution; and (4) examine the associations between the emerging BRFs clusters and the groups of self-reported burdens, controlling for confounders (sex, age, income sufficiency, social support).\u003c/p\u003e \u003cp\u003eUniversity settings are important in shaping life-long health behaviors [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Hence, it is important to monitor students\u0026rsquo; behavior at this young adulthood stage [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The current study adds new insights to the limited research on students\u0026rsquo; self-reported burdens and their association with BRFs clusters. The findings would be useful for educators, policy makers, and other stakeholders to guide policies and approaches for prevention as well as tailoring intervention strategies aimed at university students\u0026rsquo; wellbeing.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics, Sample, Procedures\u003c/h2\u003e \u003cp\u003e The study was approved by the Research and Ethics Committee at the University of Turku in Finland. An online survey using an English-language questionnaire was used to collect data. An email invitation with the research objectives was sent to all (n\u0026thinsp;=\u0026thinsp;4387) students enrolled in all faculties of the university, inviting them to participate. Students from all seven faculties of the University of Turku (Humanities, Mathematical and Natural Sciences, Medicine, Law, Social Sciences, Education and Economics) faculties were invited. Participation was voluntary and anonymous, and the data was kept confidential and protected (anonymous, no identifiers, strict access only for the research team, secure computer storage, passwords updated and changed monthly, no paper copies).\u003c/p\u003e \u003cp\u003eStudents were provided with information about the study and contact details for any questions. They were informed that by completing the questionnaire they were giving their consent to participate in the study. After completing the online questionnaire, the respondents' answers were automatically saved and forwarded to the university's student office. The total number of responses totaled 1169 (response rate: 27%). The average age of the students was \u0026asymp;\u0026thinsp;23 (SD 5) years and 823 (70.4%) were female.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eResearch tool: Survey Questionnaire\u003c/h2\u003e \u003cp\u003eSocio-demographic information included students\u0026rsquo; sex and age. Subjective financial situation was measured by a single item: \u0026ldquo;How sufficient is your income?\u0026rdquo;, with a 4-point response scale, subsequently dichotomized into (always /mostly sufficient vs always/mostly insufficient) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eSocial support\u003c/em\u003e was measured by the item: \u0026ldquo;Are you on the whole satisfied with the support you get in such situations?\u0026rdquo; using a 5-point scale (1\u0026thinsp;=\u0026thinsp;very satisfied, 5\u0026thinsp;=\u0026thinsp;very dissatisfied) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003ePerceived burdens\u003c/em\u003e associated with coursework and exams, relationships, isolation, and expectations regarding the future were assessed by asking the students: \"To what extent do you feel burdened in the following areas?\" (18 individual burdens). Responses were coded on a six-point scale from: \u0026ldquo;Not at all\u0026rdquo; to \u0026ldquo;Very strongly\u0026rdquo; [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eAlcohol problem drinking\u003c/em\u003e was assessed using the 4 standard items that form the CAGE screening test for problem alcohol use with 2 response options (\u0026ldquo;Yes,\u0026rdquo; \u0026ldquo;No\u0026rdquo;) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Two or three affirmative answers suggest problem drinking. We classified the respondents as non-problematic drinkers (less than two positive answers) and problematic drinkers (two or more positive answers).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSmoking\u003c/em\u003e was measured with the item \u0026ldquo;Within the last 3 months, how often did you smoke (cigarettes, pipes, cigarillos, cigars)?\u0026rdquo; with response options \u0026ldquo;Daily,\u0026rdquo; \u0026ldquo;Occasionally,\u0026rdquo; and \u0026ldquo;Never\u0026rdquo; [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eIllicit drug use\u003c/em\u003e (ecstasy, marijuana, cocaine, heroin, crack, LSD, amphetamines) was assessed by the question \u0026ldquo;Have you ever use/used drugs?\u0026rdquo; with response options \u0026ldquo;Yes, regularly,\u0026rdquo; \u0026ldquo;Yes but only a few times,\u0026rdquo; \u0026ldquo;Never\u0026rdquo; [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eDietary assessment (12 items)\u003c/em\u003e: respondents self-reported their dietary habits in a food frequency questionnaire, which included 12 variables assessing their consumption of sweets, cakes/crackers, fast food and canned foods, fresh fruit, raw and cooked vegetables and salads, meat and fish, dairy products and cereals. In the initial question \"How often do you eat the following foods?\" students were asked about the frequency of their usual consumption of each food group separately (5-point scale: \"several times a day\", \"daily\", \"several times a week\", \"1\u0026ndash;4 times a month\", \"never\"). The question elicited information on the student's overall food consumption. The instrument was based on pre-existing food frequency questionnaires, adapted and used previous in studies [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e\u003cem\u003eDietary guideline adherence score\u003c/em\u003e was calculated based on the student's answers to the frequency of food questionnaire. There are no specific guidelines for sweets, cakes/cookies, snacks, fast food/canned foods and sodas/soft drinks, so we used \"1\u0026ndash;4 times a month\" and \"never\" as the recommended values. To assess sweets, cakes/cookies and snacks together, we used the above-combined food intake scores (sweets, cakes/cookies and snacks) and considered healthy eating to be present if this score was \u0026le;\u0026thinsp;6, which corresponds to three times the intake of these items to \"\u0026lt; 1\u0026ndash;4 times per month\". Each of the fast food/canned snacks and soda/sweet drinks was included as a separate item in the calculation of the objective dietary adherence score. For other food groups, we used the WHO European Region recommendations [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. A threshold of 'daily' or 'several times a day' was then set for the number of daily servings of fruit, and raw and cooked vegetables. For meat, the threshold was \"less than daily\" and for fish \"several times a week\". Milk and cereals were not included in the calculation of the compliance score because the information on milk and cereals was generally too non-specific to be classified as healthy/unhealthy. The maximum dietary adherence score is 8 points (8 recommendations), calculated from the recommendations of 8 food groups: (1) sweets, cookies, snacks, (2) fast food/canned food, (3) lemonade/soft drinks, (4) fruit, (5) salad, raw vegetables, (6) cooked vegetables, (7) meat, and (8) fish [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eWe used independent samples t-test to compare quantitative variables, and Pearson chi-square, for qualitative variables. Exploratory factor analysis using principal component analysis with varimax rotation and Kaiser-Meyer-Olkin test for sampling adequacy was undertaken on the self-reported perceived burdens items. The internal consistency of the items that make up each of the factors was assessed by Cronbach\u0026rsquo;s alpha.\u003c/p\u003e \u003cp\u003eTwo-step cluster analysis was applied to 4 BRFs (tobacco smoking, alcohol drinking, illicit drug using, and eating behavior) to identify clusters that differed in criterion variables within the dataset, and the procedure combined pre-clustering and hierarchical methods. A log-likelihood distance measure was used in the two-step cluster analysis because the BRFs comprised continuous and categorical variables. Cluster number selection was automated using the Schwarz Bayesian criterion. Within each cluster, the frequency of categories and percentages were reported for categorical BRFs, whereas mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation was reported for continuous BRFs. Differences in the distribution of sociodemographic characteristics and BRFs across clusters were tested using Chi-square tests for categorical variables or analysis of variance for continuous variables.\u003c/p\u003e \u003cp\u003e Multiple linear regression models examined the association between cluster membership and four perceived burdens factors while adjusting for participant\u0026rsquo;s gender, age, income sufficiency, and satisfaction with social support. We did not use any imputation for the missing values. The number of missing values was negligible, hence we decided to use complete case analysis which limits the analysis to respondents with complete data. Statistical analyses were performed using SPSS v25.0 and statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the sample\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that mean age was about 23 years, the majority of the sample always/ mostly had sufficient income during semesters, and about three-quarters of students never smoked. There were no sex differences in age, perceived income sufficiency, and smoking. Based on the CAGE score, significantly more males than females had problematic drinking. Conversely, although most respondents never used illicit drug/s, significantly more females (81.8%) reported it, and more females had better nutritional habits, scoring higher on the dietary guideline adherence index.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and behavioral characteristics of the sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhole sample\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1169\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;346\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;823\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.96\u0026thinsp;\u0026plusmn;\u0026thinsp;5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.83\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.01\u0026thinsp;\u0026plusmn;\u0026thinsp;5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived income sufficiency n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways/ Mostly sufficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e675 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207 (59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e466 (56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways/ Mostly insufficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e487 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIllicit drug/s (ever use), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e921 (79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e669 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly few times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegularly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblematic drinking (CAGE score), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e0.014\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e810 (71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e588 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eSmoking (past 3 months), n (%)\u003c/p\u003e \u003cp\u003eNever\u003c/p\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328 (28.8)\u003c/p\u003e \u003cp\u003e911 (76.6)\u003c/p\u003e \u003cp\u003e183 (15.7)\u003c/p\u003e \u003cp\u003e74 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (33.9)\u003c/p\u003e \u003cp\u003e257 (74.9)\u003c/p\u003e \u003cp\u003e63 (18.4)\u003c/p\u003e \u003cp\u003e23 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214 (26.7)\u003c/p\u003e \u003cp\u003e648 (79.2)\u003c/p\u003e \u003cp\u003e119 (14.5)\u003c/p\u003e \u003cp\u003e51 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutrition habits* (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary guideline adherence index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003en (%) frequency (percent); M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; italicized cells indicate statistical significance; numbers might not sum up to total because of missing values. * range: 1\u0026ndash;8, each point increase represents an additional food group that shows adherence to dietary guidelines\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFactor analysis of 18 self-reported burdens\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the exploratory factor analysis of the 18 self-reported burdens generated by four factors with eigenvalues of 5.6, 1.9, 1.4 and 1.1 that cumulatively explained 55.2% of the total variance. Kaiser\u0026ndash;Meyer\u0026ndash;Olkin measure of sampling adequacy was 0.87, and Bartlett\u0026rsquo;s test of sphericity was significant (Chi-square test\u0026thinsp;=\u0026thinsp;6609, df\u0026thinsp;=\u0026thinsp;153, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also depicts the four factors, their items and factor loadings. They were broadly classified into: \u0026lsquo;Studies\u0026rsquo; (3 items, Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.74); \u0026lsquo;Future\u0026rsquo; (3 items, Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.63); \u0026lsquo;Relationships\u0026rsquo; (7 items, Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.81); and \u0026lsquo;Needs\u0026rsquo; (5 items, Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.7).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactor analysis of 18 self-reported burdens into four factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurden\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eSubscale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFuture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelationships\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNeeds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEigenvalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudies in general\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExams, assignments, presentations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of time for studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of practical relevance of studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnonymity at university\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad job prospects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblems with parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblems with fellow students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblems with friends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelationship with significant other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexuality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolation at the university\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolation in general\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinancial situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorkload in addition to studying\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad working conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExtraction Method: Principal Component Analysis; Varimax Rotation with Kaiser Normalization; Rotation converged in 9 iterations.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eClustering of Behavioral risk factors among students\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the silhouette measure of cohesion and separation of the clusters illustrating that four good-quality clusters were generated. At the two extremes, Cluster 1 (Lower Risk Takers) comprised students who generally exhibited less risk taking behaviors, while conversely, Cluster 4 (Higher Risk Takers) membership was characterized by more risk taking behaviors. The other two clusters fell in between, namely, Cluster 2 (Problem Drinkers) and Cluster 3 (Illicit Drug Takers).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that in terms of sociodemographics, across the clusters, there were no significant differences in age. Clusters 1 and 2 had more females and more income-sufficient respondents. There were also significant differences in satisfaction with social support across the four clusters, where Cluster 1 students reported the highest level of satisfaction with their social support and Clusters 3 and 4 the lowest.\u003c/p\u003e \u003cp\u003ePertaining to the BRFs, there were significant differences across all four BRFs between the clusters. Cluster 1 (Lower Risk Takers) was generally characterized by that none of the respondents ever smoked, had problematic drinking or used illicit drug/s, although they displayed the second lowest healthy eating score. On the other hand, Cluster 4 (Higher Risk Takers) members comprised all students who were occasional/daily smokers, half used illicit drug/s regularly or a few times, half were problematic drinkers, and they also exhibited the lowest healthy eating score.\u003c/p\u003e \u003cp\u003eThe other two clusters fell in between these two polars, where students exhibited some extent of \u0026ldquo;preference\u0026rdquo;. Cluster 2 students (Problem Drinkers) were characterized by their higher alcohol consumption, as all students were problem drinkers, despite that all never smoked, mostly all never used illicit drug/s, and were second highest in terms of their healthy eating habits. On the other hand, Cluster 3 (Illicit Drug Takers) was distinguished by a higher illicit drug/s use, where all students had used illicit drug/s regularly or a few times, more than a third were problem drinkers, despite that all were never-smokers, and they had the healthiest eating habits of all the clusters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of sociodemographic characteristics and behavioral risk factors across four clusters of university students in Finland\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster 1\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;574\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCluster 2\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;161\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCluster 3\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;121\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCluster 4\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;249\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk taking behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOverall more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026lsquo;Preference\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIllicit Drug/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.83\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.77\u0026thinsp;\u0026plusmn;\u0026thinsp;4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.84\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.98\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.253\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.003\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e425 (74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e168 (67.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived income sufficiency, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways/ Mostly sufficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways/ Mostly insufficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125 (50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking (past 3 months), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e161 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e175 (70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74 (29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblematic drinking (CAGE score), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e133 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e161 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIllicit drug use, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (98.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e133 (53.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, regularly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes, only a few times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103 (41.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthy eating* (points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary guideline adherence score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003en (%) frequency (percent); M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e higher score\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;higher dissatisfaction; italicized cells indicate statistical significance; numbers might not sum up to total because of missing values; * range: 1\u0026ndash;8, each point increase represents an additional food group that shows adherence to dietary guidelines\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eAssociations between socio-demographic variables and behavioral risk factor clusters with self-reported burdens\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the associations of the socio-demographic variables, social support, BRFs clusters with individual burdens components. For the socio-demographic variables, in terms of the number (breadth) of the associations, generally, sex and social support were significantly associated with all four burdens, whilst age and income sufficiency were significantly associated with three burdens. As for the direction of the associations, females were more likely to associate with the \u0026lsquo;Studies\u0026rsquo; and \u0026lsquo;Relationships\u0026rsquo; burdens, but less likely with the \u0026lsquo;Future\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens. Higher satisfaction with social support was significantly associated with less burdens generally. Older age was significantly associated with less \u0026lsquo;Studies\u0026rsquo;, \u0026lsquo;Future\u0026rsquo; and \u0026lsquo;Relationships\u0026rsquo; burdens. Sufficient income was significantly associated with less \u0026lsquo;Studies\u0026rsquo;, \u0026lsquo;Future\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens.\u003c/p\u003e \u003cp\u003ePertaining to the clusters, generally, there were differences in \u0026lsquo;Relationships\u0026rsquo; and/or \u0026lsquo;Needs\u0026rsquo; burdens rather than the \u0026lsquo;Studies\u0026rsquo; and \u0026lsquo;Future\u0026rsquo; burdens. For instance, compared to Cluster 1, Cluster 4 membership was significantly more likely to feel \u0026lsquo;Needs\u0026rsquo; burdens, and Cluster 3 membership was significantly more likely to report \u0026lsquo;Relationships\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of behavioral risk factor cluster with individual burdens components\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eStudies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFuture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eRelationships\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eNeeds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStd-β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd-β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd-β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStd-β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (1.72; 0.97) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66 (1.01; 0.31)\u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.22 (1.88; 0.56) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.88 (2.56;1.53) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.05 (-0.08; -0.02) \u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.06 (-0.09; -0.03) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.10 (-0.16; -0.05) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.01 (-0.05; 0.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome sufficiency (sufficient)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.98 (-1.33; -0.64) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.45 (-0.78; -0.13) \u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.52 (-1.13; 0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.33 (-2.80; -1.85) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15 (0.26; 0.56) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44 (0.30; 0.59) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.50 (1.24; 1.77) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.79 (0.59; 1.00) \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster 4 (vs Cluster 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.06 (-0.49; 0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.07 (-0.48; 0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.49 (-0.28; 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.96 (0.36; 1.56) \u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster 2 (vs Cluster 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39 (-0.16; 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36 (-0.11; 0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.86 (-0.04; 1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41 (-0.29; 1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster 3 (vs Cluster 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17 (-0.41; 0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17 (-0.38; 0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25 (0.24; 2.26) \u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.19 (0.39; 1.98) \u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eStd-\u0026szlig;: standardized beta coefficient; \u0026szlig;: beta coefficient; CI: confidence interval; all variables in the model adjusted for all the other variables; perceived social support \u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e higher ratings of social support represent less satisfaction with social support\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study adds new insights to the limited research on lifestyle habits of university students pertaining to the clustering of BRFs (nutrition behavior, alcohol, tobacco, illicit drug/s use), and their association with self-reported burdens. To our knowledge, this is the first study of a large sample of university students in Finland to undertake such analysis.\u003c/p\u003e \u003cp\u003eOur main findings were that there was four unique sets of burdens that students felt (Studies, Future, Relationships, Needs). The study also noted four distinct BRFs clusters that were significantly different from each other in terms of their relative configurations of the four risk factors (Lower Risk-Takers, Problem Drinkers, Illicit Drug Takers, Higher Risk Takers), and also significantly different in terms of their students\u0026rsquo; sociodemographic characteristics.\u003c/p\u003e \u003cp\u003eCollectively, these findings suggest several points regarding the characteristics of clusters of lifestyle habits. First, BRFs do not exist in a solitary fashion, rather they group together in constellations. Individuals engaging in one risky behavior probably engage in other risky behaviors; and conversely, students with healthier lifestyles are likely to maintain healthy diets, not smoke and be physically active. Second, despite this, such clusters do not represent clear-cut opposite-facing constellations of behaviors. Hence, we noted that although some clusters e.g., Cluster 4\u003csub\u003eHigher Risk\u0026minus;Takers\u003c/sub\u003e was characterized by several unhealthy behaviors, the cluster still harbored healthy patterns of eating; and vice versa, where despite that some clusters were characterized by generally healthy behaviors e.g., Cluster 1\u003csub\u003eLower Risk Takers\u003c/sub\u003e, their members still engaged in unhealthy activities, reflected by less healthy nutritional habits.\u003c/p\u003e \u003cp\u003eSuch observed contrast or paradox might be explained by the principle of compensatory health beliefs, where individuals engage in risk behavior/s in one area of their lives, and attempt to balance it out by performing healthy behavior/s in another sphere of their life [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. For example, individuals who drink alcohol on regular basis might also regularly exercise and eat healthy to feel like balancing out the health risks associated with the regular alcohol use. However, such proposed trade offs remain unclear. Whether any beneficiary effects accrued from exercise and a healthy diet actually counteract the negative health impacts of excessive alcohol consumption remain to be uncovered. Some propositions hold that improving physical fitness by working out and eating a healthier diet is one of the most effective ways to combat alcoholism and counteract the many negative health effects that it causes [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs for the prevalence of BRFs (unhealthy behaviors) within each cluster, we noted differences for three (alcohol consumption, illicit drug use, smoking) out of the four BRFs examined. Pertaining to alcohol consumption, with the exception of Cluster 1, the other three clusters represented students with 46%, 100% and 36% prevalence of problematic alcohol consumption. These findings support other studies in university settings that found that problematic drinking patterns characterized student life [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. University life symbolises the transitions from the stricter parental control and structured high school environment to a more independent and less supervised lifestyle, with freedom, desires to explore boundaries, and peer social pressure to fit in the group [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. These might contribute to a higher alcohol consumption. Others have also noted that students might consume alcohol as a mechanism to cope with academic stress, pressure and deadlines, or social anxiety [\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcross our sample, 22% of the students regulary or occasionally used illicit drugs, with the highest prevalence observed in Cluster 3\u003csub\u003eIllicit Drug Takers\u003c/sub\u003e and Cluster 4\u003csub\u003eHigher Risk\u0026minus;Takers\u003c/sub\u003e. Compared with data from other countries and regions, a national survey of 2810 students in the UK reported that 56% of respondents had used drugs, and 39% currently used them [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]; and a large scale North American survey showed that the annual prevalence of illicit substance use among university student populations was 43% [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, smoking was observed only in Cluster 4, characterized by members with more risky behavioral patterns as all students in this cluster smoked occasionally/regularly. More recent data from The 2021 Finnish Student Health and Wellbeing Survey observed that, among university students, 6% of women and 5% of men were daily smokers [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] suggesting a decreasing trend, a pattern observed globally and supported, for example, by data from USA [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between BRF cluster membership and specific burdens\u003c/h2\u003e \u003cp\u003eUsing regression analyses that adjusted for sex, age, income sufficiency and social support, the current study appraised the relationships between the BRFs clusters and the four sets of self-reported burdens. Compared to Cluster 1\u003csub\u003eLower Risk\u0026minus;Takers\u003c/sub\u003e, Clusters 4\u003csub\u003eHigher Risk\u0026minus;Takers\u003c/sub\u003e and 3\u003csub\u003eIllicit Drugs Takers\u003c/sub\u003e were significantly more likely to report only one burden, namely the \u0026lsquo;Needs\u0026rsquo; burdens, comprising elements related to housing, health problems, finances, and workloads.\u003c/p\u003e \u003cp\u003eSuch significant differences between the higher and lower risk takers in relation to the \u0026lsquo;Needs\u0026rsquo; burdens might be partly attributed to the higher levels of illicit drug use and problematic drinking evident in Cluster 3, along with the additional smoking observed in Cluster 4, compared to Cluster 1. Multiple substance use (e.g., alcohol, tobacco, and other drugs, ATOD) is frequently associated with difficulties and negative life consequences, with higher likelihood of experiencing adverse outcomes, increased risk of physical and chronic health issues, as well as mental health conditions, all burdens that negatively impact well-being and render it harder to cope with daily challenges [\u003cspan additionalcitationids=\"CR65 CR66\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. ATOD use is also costly, posing additional financial burdens on students already facing financial strains. Collectively, such features might lead to the burdens of meeting basic needs, fulfilling responsibilities and goals, and negatively impacting academic performance [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also noted that Cluster 3\u003csub\u003eIllicit Drugs Takers\u003c/sub\u003e students were significantly more likely to report \u0026lsquo;Relationship\u0026rsquo; burdens compared to Cluster 1\u003csub\u003eLower Risk\u0026minus;Takers\u003c/sub\u003e. Again, alcohol and illicit drug use, characteristic of our Cluster 3 students may strain relationships with family, friends, and partners, potentially resulting in feelings of isolation and diminished support [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Indeed Cluster 3 students reported significantly lower satisfaction with the level of social support they receive compared to Cluster 1 students.\u003c/p\u003e \u003cp\u003eIn connection with links between sociodeomgraphics and social support on the one hand and burdens on the other, across the current sample, higher social support was significantly negatively associated with all the four burden components that were examined. Our findings support other research, where higher social support is viewed as a protective factor that can alleviate the burdens encountered in various aspects of life, and relieve emotional strains and stress [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] that are related to academic life and \u0026lsquo;Studies\u0026rsquo; [\u003cspan additionalcitationids=\"CR72\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], basic \u0026lsquo;Needs\u0026rsquo; [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] and \u0026lsquo;Relationships\u0026rsquo; [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs for gender, across our smaple found that females were significantly more likely than males to be burdened by the \u0026lsquo;Studies\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens. Although the precise reasons why females felt \u0026lsquo;Studies\u0026rsquo; as a burden are difficult to speculate, however, generally, women value higher education and attach more attention and focus on their studies, possibly to the extent of feeling \u0026lsquo;burdened\u0026rsquo; by \u0026lsquo;Studies\u0026rsquo;. Such propositions are in line with a number of studies that found higher general and academic stress levels among female students compared to their male counterparts [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. The reasons why females felt the \u0026lsquo;Needs\u0026rsquo; burden more than males are again difficult to pinpoint, but it is plausible that females value strongly the links between academic success and future financial stability, motivating them to focus on their future careers in order to satisfy needs. Conversly, in the current study, females were less likely to report \u0026lsquo;Relationship\u0026rsquo; burdens than males, reflecting that for these young adults, it is frequently the males who seek out to initiate relationships [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of age, we observed that older age was significantly associated with less \u0026lsquo;Studies\u0026rsquo;, \u0026lsquo;Future\u0026rsquo; and \u0026lsquo;Relationships\u0026rsquo; burdens. As younger university students progress in age and advance through their academic journey, they acquire more skills and life experience rendering them more adaptable to new situations, as well as effective strategies and better-coping mechanisms to navigate life challenges and stress. Pertaining to income sufficiency, across our sample, those with sufficient income were less likely to report \u0026lsquo;Studies\u0026rsquo;, \u0026lsquo;Future\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens, congruent with research where perceived socioeconomic status predicted better well-being outcomes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has limitations. Cross-sectional survey designs do not allow the confirmation of the direction associations. Data were self-reported, and we are unable to exclude recall and social desirability biases. The low response rate could have affected the sample's representativeness, and hence internal validity and generalizability. Our questionnaire focused on cigarette smoking rather than the use of electronic cigarettes, which are also prevalent among young adults. Future research would benefit from addressing these limitations. Despite these limtations, the study boasts many strengths, including a large sample of students from all the University\u0026rsquo;s departments and faculties, categorized into clusters that report on a wide range of health-related BRFs. To our knowledge, it is the first study among university students in Finland to evaluate and categorize students into BRF clusters and to explore the associations of these clusters with burdens, while controlling for multiple potential confounders.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCluster analysis of BRFs can reveal high-risk groups. The current study identified four BRFs clusters, which, although distinct, do not represent clear-cut opposite-facing constellations of behaviors. Generally, substance users were significantly more likely to report \u0026lsquo;Needs\u0026lsquo;, \u0026lsquo;Relationships\u0026rsquo; and \u0026lsquo;Needs\u0026rsquo; burdens. Higher social support was associated with fewer burdens. BRFs are products of lifestyle choices. Therefore, the identification of BRFs clusters as in the current study can guide health promotion prevention efforts to encourage regular PA, healthy eating habits and nutrition, as well as smoking cessation and responsible drinking programs, and effective behavioral modification interventions to protect the health of these young adults. Our findings can assist educators, policymakers and other stakeholders involved with similar student populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been reviewed and approved by the University Research and Ethics Committee (Approval # Lausunto 10/2010). Students were informed that by completing the survey, they agree to participate in the study. All methods were carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from the authors upon reasonable request to corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Walid El Ansari; methodology, Walid El Ansari, Rene Sebena; analyses, Rene Sebena; investigation, Walid El Ansari, Rene Sebena and Kareem El-Ansari; writing original draft preparation, Walid El Ansari, Rene Sebena and Kareem El-Ansari. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the university and students who participated in the survey. Rene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIslam A, Low WY, Tong WT, Choo C, Yuen W. Factors Associated with Depression among University Students in Malaysia: A Cross-sectional Study. KnE Life Sci 2018;415\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller C, El-Ansari K, El Ansari W. Health-Promoting Behavior and Lifestyle Characteristics of Students as a Function of Sex and Academic Level. Int J Environ Res Public Health. 2022;19(12):7539. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19127539\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19127539\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35742787; PMCID: PMC9224493.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWirnitzer KC, Motevalli M, Cocca A, Tanous DR, Wirnitzer G, Wagner KH, Sch\u0026auml;tzer M, Drenowatz C, Ruedl G, Kirschner W. Health behavior of Austrian tertiary students focusing on diet type linked to sports and exercise-first glimpse of results from the sustainably healthy-from science 2 high school and university study. Front Public Health. 2023;11:1129004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpubh.2023.1129004\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2023.1129004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37533531; PMCID: PMC10392833.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMikolajczyk RT, Maxwell AE, Naydenova V, Meier S, El Ansari W. Depressive symptoms and perceived burdens related to being a student: Survey in three European countries. Clin Pract Epidemiol Ment Health. 2008;4:19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1745-0179-4-19\u003c/span\u003e\u003cspan address=\"10.1186/1745-0179-4-19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 18598340; PMCID: PMC2483702.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHill MR, Goicochea S, Merlo LJ. In their own words: stressors facing medical students in the millennial generation. Med Educ Online. 2018;23(1):1530558. PMID: 30286698; PMCID: PMC6179084.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Stock C. Explaining the gender difference in self-rated health among university students in Egypt. Women Health. 2016;56(7):731\u0026ndash;44. Epub 2016 Feb 17. PMID: 26886289.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Sebena R, Stock C. Socio-demographic correlates of six indicators of alcohol consumption: survey findings of students across seven universities in England, Wales and Northern Ireland. Arch Public Health. 2013;71(1):29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/2049-3258-71-29\u003c/span\u003e\u003cspan address=\"10.1186/2049-3258-71-29\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 24196210; PMCID: PMC3923438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Stock C, UK Student Health Group, Snelgrove S, Hu X, Parke S, Davies S, John J, Adetunji H, Stoate M, Deeny P, Phillips C, Mabhala A. Feeling healthy? A survey of physical and psychological wellbeing of students from seven universities in the UK. Int J Environ Res Public Health. 2011;8(5):1308\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph8051308\u003c/span\u003e\u003cspan address=\"10.3390/ijerph8051308\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2011 Apr 27. PMID: 21655121; PMCID: PMC3108111.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSinha GR, Larrison CR, Brooks I, Kursuncu U. Comparing Naturalistic Mental Health Expressions on Student Loan Debts Using Reddit and Twitter. J Evid Based Soc Work (2019). 2023;20(5):727\u0026ndash;742. doi: 10.1080/26408066.2023.2202668. Epub 2023 Apr 16. PMID: 37461303.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanson M. Average Medical School Debt. Education Data Initiatives. Updated December 9, 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://educationdata.org/averagemedical-school-debt\u003c/span\u003e\u003cspan address=\"https://educationdata.org/averagemedical-school-debt\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Accessed 23 May, 2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWunsch K, Fiedler J, Bachert P, Woll A. The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2021;18(2):739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph18020739\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18020739\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 33467118; PMCID: PMC7830011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePacheco JP, Giacomin HT, Tam WW, Ribeiro TB, Arab C, Bezerra IM, Pinasco GC. Mental health problems among medical students in Brazil: a systematic review and meta-analysis. Braz J Psychiatry. 2017 Oct-Dec;39(4):369\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1590/1516-4446-2017-2223\u003c/span\u003e\u003cspan address=\"10.1590/1516-4446-2017-2223\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Aug 31. PMID: 28876408; PMCID: PMC7111407.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeiter R, Nash R, McCrady M, Rhoades D, Linscomb M, Clarahan M, Sammut S. The prevalence and correlates of depression, anxiety, and stress in a sample of college students. J Affect Disord. 2015;173:90\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.10.054\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2014.10.054\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2014 Nov 8. PMID: 25462401.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEskin M, Sun JM, Abuidhail J, Yoshimasu K, Kujan O, Janghorbani M, Flood C, Carta MG, Tran US, Mechri A, Hamdan M, Poyrazli S, Aidoudi K, Bakhshi S, Harlak H, Moro MF, Nawafleh H, Phillips L, Shaheen A, Taifour S, Tsuno K, Voracek M. Suicidal Behavior and Psychological Distress in University Students: A 12-nation Study. Arch Suicide Res. 2016;20(3):369\u0026ndash;88. Epub 2016 Mar 8. PMID: 26954847.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson CK, Matthews JI, Seabrook JA, Dworatzek PDN. Self-reported food skills of university students. Appetite. 2017;108:270\u0026ndash;276. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.appet.2016.10.011\u003c/span\u003e\u003cspan address=\"10.1016/j.appet.2016.10.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2016 Oct 11. PMID: 27742236.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdel Sadek HA, Abu-Nazel MW, Shata ZN, Abd El-Fatah NK. The relationship between the BMI and the emotional status of Alexandria University students, Egypt. J Egypt Public Health Assoc. 2016;91(3):101\u0026ndash;108. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.EPX.0000484542.88399.c7\u003c/span\u003e\u003cspan address=\"10.1097/01.EPX.0000484542.88399.c7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 27749640.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Sayegh N, Al-Shuwai N, Ramadan S, Al-Qurba T, Al-Obaidi SM, Dean E. Benchmarking the health of health sciences students at Kuwait University: towards a culture of health. East Mediterr Health J. 2016;22(8):619\u0026ndash;627. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.26719/2016.22.8.619\u003c/span\u003e\u003cspan address=\"10.26719/2016.22.8.619\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 27834444.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite HR, Labouvie EW, Papadaratsakis V. Changes in substance use during the transition to adulthood: A comparison of college students and their noncollege age peers. J Drug Issues. 2005;35(2):281\u0026ndash;306.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWechsler H, Wuethrich B. Dying to drink: Confronting binge drinking on college campuses. Rodale Customer Service, 33 East Minor Street, Emmaus, PA 18098, 2002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKypri K, Langley J, Stephenson S. Episode-centred analysis of drinking to intoxication in university students. Alcohol Alcohol. 2005 Sep-Oct;40(5):447\u0026thinsp;\u0026ndash;\u0026thinsp;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/alcalc/agh178\u003c/span\u003e\u003cspan address=\"10.1093/alcalc/agh178\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2005 Jul 4. PMID: 15996969.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnston LD, O\u0026rsquo;Malley PM, Bachman JG, Schulenberg JE, Miech RA. 1975\u0026ndash;2014: Volume 2, College students and adults ages 19\u0026ndash;55. Monitoring the Future national survey results on drug use. Ann Arbor: Institute for Social Research. The University of Michigan; 2015. Available at myumi.ch/J7G22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJelagat J, Budambula NLM, Ngari M, Budambula V. Polydrug Use among Students in a Public University in a Lower Middle-Income Country. Biomed Res Int. 2023;2023:8085588. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2023/8085588\u003c/span\u003e\u003cspan address=\"10.1155/2023/8085588\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37560202; PMCID: PMC10409583.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Ssewanyana D, Stock C. Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis. Front Public Health. 2018;6:120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpubh.2018.00120\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2018.00120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 29868535; PMCID: PMC5950502.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990\u0026ndash;2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2197\u0026ndash;223.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuintiliani L, Allen J, Marino M, Kelly-Weeder S, Li Y. Multiple health behavior clusters among female college students. Patient Educ Couns. 2010;79(1):134\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pec.2009.08.007\u003c/span\u003e\u003cspan address=\"10.1016/j.pec.2009.08.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2009 Sep 19. PMID: 19767168; PMCID: PMC5892440.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaskin-Sommers A, Sommers I. The co-occurrence of substance use and high-risk behaviors. J Adolesc Health. 2006;38(5):609\u0026thinsp;\u0026ndash;\u0026thinsp;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jadohealth.2005.07.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jadohealth.2005.07.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 16635777.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilloughby T, Chalmers H, Busseri MA. Where is the syndrome? Examining co-occurrence among multiple problem behaviors in adolescence. J Consult Clin Psychol. 2004;72(6):1022-37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/0022-006X.72.6.1022\u003c/span\u003e\u003cspan address=\"10.1037/0022-006X.72.6.1022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 15612849.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Berg-Beckhoff G. Country and Gender-Specific Achievement of Healthy Nutrition and Physical Activity Guidelines: Latent Class Analysis of 6266 University Students in Egypt, Libya, and Palestine. Nutrients. 2017;9(7):738. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu9070738\u003c/span\u003e\u003cspan address=\"10.3390/nu9070738\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 28696407; PMCID: PMC5537852.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCosta E, et al. Clustering of behavioural risk factors in the Portuguese population: Data from National Health Interview Survey. J Behav Health. 2014;3:205\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHudd S, Dumlao J, Erdmann-Sager D, Murray D, Phan E, Soukas N, Yokozuka N. Stress at college: Effects on health habits, health status and self-esteem. Coll Student J. 2000;34(2):217\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheung DK, Tam DKY, Tsang MH, Zhang DLW, Lit DSW. Depression, anxiety and stress in different subgroups of first-year university students from 4-year cohort data. J Affect Disord. 2020;274:305\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2020.05.041\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.05.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 May 22. PMID: 32469820.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSebena R, Orosova O, Mikolajczyk RT, van Dijk JP. Selected sociodemographic factors and related differences in patterns of alcohol use among university students in Slovakia. BMC Public Health. 2011;11:849. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2458-11-849\u003c/span\u003e\u003cspan address=\"10.1186/1471-2458-11-849\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 22067135; PMCID: PMC3282827.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodman E, Huang B, Schafer-Kalkhoff T, Adler NE. Perceived socioeconomic status: a new type of identity that influences adolescents' self-rated health. J Adolesc Health. 2007;41(5):479\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jadohealth.2007.05.020\u003c/span\u003e\u003cspan address=\"10.1016/j.jadohealth.2007.05.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDougall I, Vasiljevic M, Kutlaca M, Weick M. Socioeconomic inequalities in mental health and wellbeing among UK students during the COVID-19 pandemic: Clarifying underlying mechanisms. PLoS ONE. 2023;18(11):e0292842. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0292842\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0292842\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37910542; PMCID: PMC10619810.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLakey B, Sheldon C. Social support theory and measurement. In: Sheldon C, Underwood LG, Gottlieb BH, editors. Social Support Measurement and Intervention: A Guide for Health and Social Scientists. New York: Oxford University Press; 2000. pp. 29\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaqutayan S. Stress and Social Support. Indian J Psychol Med. 2011;33:29\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLitwic-Kaminska K, Błachnio A, Kapsa I, Brzeziński Ł, Kopowski J, Stojković M, Hinić D, Krsmanović I, Ragni B, Sulla F, Limone P. Resilience, Positivity and Social Support as Perceived Stress Predictors among University Students. Int J Environ Res Public Health. 2023;20(19):6892. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph20196892\u003c/span\u003e\u003cspan address=\"10.3390/ijerph20196892\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37835162; PMCID: PMC10572749.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzkody E, McKinney C. Appraisal and social support as moderators between stress and physical and psychological quality of life. Stress Health. 2020;36(5):586\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/smi.2957\u003c/span\u003e\u003cspan address=\"10.1002/smi.2957\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Jun 12. PMID: 32419328.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Sebena R, El-Ansari K, Suominen S. Clusters of lifestyle behavioral risk factors and their associations with depressive symptoms and stress: evidence from students at a university in Finland. BMC Public Health. 2024;24(1):1103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-024-18421-0\u003c/span\u003e\u003cspan address=\"10.1186/s12889-024-18421-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 38649903; PMCID: PMC11034152.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Suominen S, El-Ansari K, Šebeňa R. Are behavioural risk factors clusters associated with self-reported health complaints? University students in Finland. Cent Eur J Public Health. 2023;31(4):248\u0026ndash;255. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21101/cejph.a7916\u003c/span\u003e\u003cspan address=\"10.21101/cejph.a7916\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 38309702.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScott AJ, Knott M. A cluster analysis method for grouping means in the analysis of variance. Biometrics. 1974; 507\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Bourdeaudhuij I, Van Cauwenberghe E, Spittaels H, Oppert JM, Rostami C, Brug J, Van Lenthe F, Lobstein T, Maes L. School-based interventions promoting both physical activity and healthy eating in Europe: a systematic review within the HOPE project. Obes Rev. 2011;12(3):205\u0026thinsp;\u0026ndash;\u0026thinsp;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1467-789X.2009.00711.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1467-789X.2009.00711.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 20122137.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArnett JJ. Emerging adulthood. A theory of development from the late teens through the twenties. Am Psychol. 2000;55(5):469\u0026ndash;80. PMID: 10842426.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAceijas C, Waldh\u0026auml;usl S, Lambert N, Cassar S, Bello-Corassa R. Determinants of health-related lifestyles among university students. Perspect Public Health. 2017;137(4):227\u0026ndash;236. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1757913916666875\u003c/span\u003e\u003cspan address=\"10.1177/1757913916666875\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2016 Sep 5. PMID: 27597797.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSebena R, El Ansari W, Stock C, Orosova O, Mikolajczyk RT. Are perceived stress, depressive symptoms and religiosity associated with alcohol consumption? A survey of freshmen university students across five European countries. Subst Abuse Treat Prev Policy. 2012;7:21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1747-597X-7-21\u003c/span\u003e\u003cspan address=\"10.1186/1747-597X-7-21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 22640549; PMCID: PMC3395565.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarason IG, Levine HM, Basham RB, Sarason BR. Assessing social support: The social support questionnaire. J Pers Soc Psychol. 1983;44:127\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEwing JA. Detecting alcoholism. The CAGE questionnaire. JAMA. 1984;252:1905\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Salam A. Prevalence and predictors of smoking, quit attempts and total smoking ban at the University of Turku, Finland. Cent Eur J Public Health. 2021;29:45\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Vallentin-Holbech L, Stock C. Predictors of illicit drug/s use among university students in Northern Ireland, Wales and England. Glob J Health Sci. 2014;7(4):18\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5539/gjhs.v7n4p18\u003c/span\u003e\u003cspan address=\"10.5539/gjhs.v7n4p18\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 25946914; PMCID: PMC4802112.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Ansari W, Stock C, Mikolajczyk RT. Relationships between food consumption and living arrangements among university students in four European countries - a cross-sectional study. Nutr J. 2012;11:28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1475-2891-11-28\u003c/span\u003e\u003cspan address=\"10.1186/1475-2891-11-28\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Regional Office for Europe. Food-based dietary guidelines in the WHO European Region. Copenhagen: WHO Regional Office for Europe. \u0026lrm;2003; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/iris/handle/10665/107490\u003c/span\u003e\u003cspan address=\"https://apps.who.int/iris/handle/10665/107490\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKn\u0026auml;uper B, Rabiau M, Cohen O, Patriciu N. Compensatory health beliefs: scale development and psychometric properties. Psychol Health. 2004;19(5):607\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCab\u0026eacute; N, Lani\u0026egrave;pce A, Pitel AL. Physical activity: A promising adjunctive treatment for severe alcohol use disorder. Addict Behav. 2021;113:106667. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.addbeh.2020.106667\u003c/span\u003e\u003cspan address=\"10.1016/j.addbeh.2020.106667\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Sep 29. PMID: 33074123.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHallett J, McManus A, Maycock B, Smith J, Howat P. Excessive Drinking\u0026mdash;An Inescapable Part of University Life? A Focus Group Study of Australian Undergraduates. Open J Prev Med. 2014;4:616\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4236/ojpm.2014.47071\u003c/span\u003e\u003cspan address=\"10.4236/ojpm.2014.47071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWicki M, Kuntsche E, Gmel G. Drinking at European universities? A review of students' alcohol use. Addict Behav. 2010;35:913\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchulenberg J, Wadsworth KN, O'Malley PM, Bachman JG, Johnston LD. Adolescent risk factors for binge drinking during the transition to young adulthood: Variable- and pattern-centered approaches to change. Dev Psychol. 1996;32(4):659\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0012-1649.32.4.659\u003c/span\u003e\u003cspan address=\"10.1037/0012-1649.32.4.659\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams A, Clark D. Alcohol consumption in university students: the role of reasons for drinking, coping strategies, expectancies, and personality traits. Addict Behav. 1998 May-Jun;23(3):371-8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s0306-4603(97)80066-4\u003c/span\u003e\u003cspan address=\"10.1016/s0306-4603(97)80066-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 9668934.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDouglass MA, Colley ML, Tyskiewicz AJ, Prince MA. Drinking to cope and college grade point average. Drugs Habits Social Policy. 2023;24(4):342\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1108/DHS-05-2023-0016\u003c/span\u003e\u003cspan address=\"10.1108/DHS-05-2023-0016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTerlecki MA, Ecker AH, Buckner JD. College drinking problems and social anxiety: The importance of drinking context. Psychol Addict Behav. 2014;28(2):545\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0035770\u003c/span\u003e\u003cspan address=\"10.1037/a0035770\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Union of Students, Release. Taking the Hit: Student drug use and how Institutions respond. London. [online]. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.release.org.uk/publications/taking-hit-student-drug-use-and-how-institutions-respond\u003c/span\u003e\u003cspan address=\"https://www.release.org.uk/publications/taking-hit-student-drug-use-and-how-institutions-respond\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 22 May 2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchulenberg JE, Johnston LD, O\u0026rsquo;Malley PM, Bachman JG, Miech RA, Patrick ME. Monitoring the Future national survey results on drug use, 1975\u0026ndash;2019: Volume II, College students and adults ages 19\u0026ndash;60. Ann Arbor: Institute for Social Research: The University of Michigan:; 2020. p. 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParikka S, Holm N, Ikonen J, Koskela T, Kilpel\u0026auml;inen H, Lundqvist A. May. KOTT 2021 -tutkimuksen perustulokset 2021. [online] \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.terveytemme.fi/kott\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 22 2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGallup. Cigarette Smoking Rates Down Sharply Among U.S. Young Adults.[online]. 2022.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://news.gallup.com/poll/405884/cigarette-smoking-rates-down-sharply-among-young-adults.aspx\u003c/span\u003e\u003cspan address=\"https://news.gallup.com/poll/405884/cigarette-smoking-rates-down-sharply-among-young-adults.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 23 May 2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHersh J, Curry JF, Becker SJ. The influence of comorbid depression and conduct disorder on MET/CBT treatment outcome for adolescent substance use disorders. Int J Cogn Ther. 2013;6:325\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1521/ijct.2013.6.4.325\u003c/span\u003e\u003cspan address=\"10.1521/ijct.2013.6.4.325\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScalco MD, Colder CR, Hawk LW, Read JP, Wieczorek WF, Lengua LJ. Internalizing and externalizing problem behavior and early adolescent substance use: a test of a latent variable interaction and conditional indirect effects. Psychol Addict Behav. 2014;28:828\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0035805\u003c/span\u003e\u003cspan address=\"10.1037/a0035805\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu LT, Zhu H, Ghitza UE. Multicomorbidity of chronic diseases and substance use disorders and their association with hospitalization: Results from electronic health records data. Drug Alcohol Depend. 2018;192:316\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.drugalcdep.2018.08.013\u003c/span\u003e\u003cspan address=\"10.1016/j.drugalcdep.2018.08.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNIDA, Introduction. National Institute on Drug Abuse website. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nida.nih.gov/publications/research-reports/common-comorbidities-substance-use-disorders/\u003c/span\u003e\u003cspan address=\"https://nida.nih.gov/publications/research-reports/common-comorbidities-substance-use-disorders/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. August 3, 2021. (Accessed April 20, 2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBugbee BA, Beck KH, Fryer CS, Arria AM, Substance, Use. Academic Performance, and Academic Engagement Among High School Seniors. J Sch Health. 2019;89(2):145\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/josh.12723\u003c/span\u003e\u003cspan address=\"10.1111/josh.12723\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 30604451; PMCID: PMC6373775.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCopeland M, Fisher JC, Moody J, Feinberg ME. Different Kinds of Lonely: Dimensions of Isolation and Substance Use in Adolescence. J Youth Adolesc. 2018;47(8):1755\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10964-018-0860-3\u003c/span\u003e\u003cspan address=\"10.1007/s10964-018-0860-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2018 May 17. PMID: 29774451; PMCID: PMC6045973.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim B, Jee S, Lee J, An S, Lee SM. Relationships between social support and student burnout: A meta-analytic approach. Stress Health. 2018;34(1):127\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/smi.2771\u003c/span\u003e\u003cspan address=\"10.1002/smi.2771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Jun 22. PMID: 28639354.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzkody E, Stearns M, Stanhope L, McKinney C. Stress-Buffering Role of Social Support during COVID-19. Fam Process. 2021;60(3):1002\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/famp.12618\u003c/span\u003e\u003cspan address=\"10.1111/famp.12618\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Nov 21. PMID: 33220082; PMCID: PMC7753728.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrazier P, Gabriel A, Merians A, Lust K. Understanding stress as an impediment to academic performance. J Am Coll Health. 2019 Aug-Sep;67(6):562\u0026ndash;570. doi: 10.1080/07448481.2018.1499649. Epub 2018 Oct 4. PMID: 30285563.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuirhead V, Locker D. Canadian dental students' perceptions of stress and social support. Eur J Dent Educ. 2008;12(3):144-8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1600-0579.2008.00512.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1600-0579.2008.00512.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 18666895.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXin Z. Perceived social support and college student engagement: moderating effects of a grateful disposition on the satisfaction of basic psychological needs as a mediator. BMC Psychol. 2022;10(1):298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40359-022-01015-z\u003c/span\u003e\u003cspan address=\"10.1186/s40359-022-01015-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36503628; PMCID: PMC9743595.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStanton MV, Jones A, Shahani D. Relationship among interpersonal stressors in adolescence, social support buffers, and obesity in adulthood 14 years later. Health Psychol. 2022;41(12):904\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/hea0001223\u003c/span\u003e\u003cspan address=\"10.1037/hea0001223\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Oct 13. PMID: 36227311.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBacković DV, Živojinovic JI, Maksimović J, Maksimović M. Gender differences in academic stress and burnout among medical students in final years of education. Psychiatria Danubina. 2012;24(2):75\u0026ndash;181.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraves BS, Hall ME, Dias-Karch C, Haischer MH, Apter C. Gender differences in perceived stress and coping among college students. PLoS ONE. 2021;16(8):e0255634. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0255634\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0255634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 34383790; PMCID: PMC8360537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchneider N. Gender Roles in Intimate Relationships: Who Initiates and Why? Can J Family Youth. 2022;14(2):11\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDougall I, Vasiljevic M, Kutlaca M, Weick M. Socioeconomic inequalities in mental health and wellbeing among UK students during the COVID-19 pandemic: Clarifying underlying mechanisms. PLoS ONE. 2023;18(11):e0292842. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0292842\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0292842\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37910542; PMCID: PMC10619810.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"behavioral risk factors, burdens, university students, cluster analysis, social support","lastPublishedDoi":"10.21203/rs.3.rs-4595741/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4595741/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: No research among Finnish universities grouped students into clusters, based on their lifestyle behavioral risk factors (BRFs), and appraised relationships of the clusters with self-reported burdens, adjusting for confounders. The current study undertook this task.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Students (n=1169) at Turku University completed online questionnaire comprising sociodemographic variables (age, sex, income, social support), 18 burdens, and 5 BRFs (smoking, alcohol, drug use, food habits). Factor analysis reduced burdens into factors; cluster analysis of BRFs categorized students into clusters. Regression models appraised associations between sociodemographics and clusters with burdens.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Mean age was ≈23 years, with ≈70% females, 23.4% smokers, 28.8% problematic drinkers, 21% illicit drug/s users, and mean dietary guideline adherence=4.84±1.57. Factor analysis of burdens generated four factors: ‘Studies’=3 items; ‘Future’=3 items; ‘Relationships’=7 items; and ‘Needs’=5 items. Cluster analysis produced four BRFs clusters with significantly different BRFs and sociodemographics. Cluster 1 exhibited less risk-taking behaviors, Cluster 4 comprised more risk-taking, and the other two clusters fell in-between. Regression showed that females were more likely to report ‘Studies’+‘Relationships’ burdens; higher social support was associated with less burdens generally; older age was associated with less ‘Studies’+‘Future’+‘Relationships’ burdens; and sufficient income was associated with less ‘Studies’+‘Future’+‘Needs’ burdens. Compared to Cluster 1, Cluster 4 membership was more likely to feel ‘Needs’ burdens; Cluster 3 more likely to report ‘Relationships’+‘Needs’ burdens (\u003cem\u003ep\u003c/em\u003e range: \u0026lt;0.05 to \u0026lt;0.01 for all).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Controlling for sociodemographics, cluster membership was more influenced by students’ perceptions of ‘Relationships’+‘Needs’, rather than academic difficulties of ‘Studies’ or unsecure ‘Future’. Risk taking was more likely with relationship difficulties, isolation, and day-to-day problems (housing, financial situation, health) rather than academic load or concerns for future prospects. Preventive and intervention efforts tackling students’ lifestyle behaviours need to consider programs aimed at better relationship building/maintenance to prevent isolation, while mitigating ‘on-the-ground’ everyday challenges that students face.\u003c/p\u003e","manuscriptTitle":"Behavioral Risk Factors Clusters and their Associations with Self-Reported Burdens Among University Students in Finland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-04 10:09:31","doi":"10.21203/rs.3.rs-4595741/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1fed8102-7b9d-4ea8-a6a4-f64bfd4fea45","owner":[],"postedDate":"July 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-10T17:38:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-04 10:09:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4595741","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4595741","identity":"rs-4595741","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}