Sustainable UNiversity Life (SUN) Study
Sustainable UNiversity Life (SUN) Study
In 2017, Socialstyrelsen reported that mental ill-health in young adults had increased by
 almost 70% in the previous10 years. A 2014 report showed that 5% of men and 11% of women
 18-24 years were diagnosed with depression or anxiety in Stockholm County. Furthermore, 41%
 of women 21-24 years have self reported psychological distress. Regarding pain, 28% of men
 and 36% of women 16-24 years have disabling neck pain. Little is known about the etiology and
 prognosis of poor mental health in university students.

 The aim is to advance knowledge about the etiology of depression, anxiety, stress and pain in
 undergraduate university students. The investigators will study a cohort of students at
 full-year programs at universities in the Stockholm area. Primary research questions are
 whether modifiable factors such as sleep quality, lifestyle, screen time and work environment
 are independent risk factors for incident episodes or unfavorable trajectories of depression,
 anxiety and pain in men and women? To be able to answer these research questions we designed
 a prospective cohort study targeting 5000 university students.
Study objectives:

 The overall study aim is to advance the knowledge about the etiology and prognosis of common
 mental health problems (depression, anxiety and stress) and musculoskeletal pain experienced
 by undergraduate university students in Sweden.

 Specific research questions:

 Are modifiable factors as bad sleep quality, meal patterns, low physical activity/sedentary
 lifestyle, pain conditions and bad study environment independent risk factors of incident
 episodes of troublesome depressive and anxiety symptomatology and musculoskeletal pain and of
 unfavorable trajectories of depressive, anxiety, stress and pain symptoms? Are modifiable
 factors as bad sleep quality, meal patterns, low physical activity/sedentary lifestyle, pain
 conditions and bad study environment independent prognostic factors for recovery from
 troublesome depressive and anxiety symptomatology and musculoskeletal pain? Do such potential
 risk factors and trajectories vary between men and women? What are the trajectories of sleep
 quality, meal patterns, physical activity/sedentary lifestyle, pain and substance use during
 one academic year (describe the fluctuations of risk factors)?

 Study design:

 Cohort study of undergraduate full time program students followed-up four times during an
 academic year.

 Source populations:

 The source populations for this project are undergraduate full-time program students at
 universities in the Stockholm area.

 Data collection:

 Data collection will be performed with questionnaires through a link sent to students e-mail
 address, provided by the participating universities. The students will be able to access the
 questionnaire for a four-week period at baseline and each follow-up.

 Exposures:

 Sleep quality, physical activity and sedentary behavior, substance use in the past three
 months (non-medical use), study environment, body image, perfectionism, gambling, compulsive
 exercise, social media use, cyberbullying, procrastination and loneliness.

 Outcomes:

 Outcomes will be measured with the Depression Anxiety Stress Scales-21 (DASS-21). The DASS-21
 includes three subscales designed to measure depression, anxiety and stress symptoms in
 non-clinical populations with response alternatives on a Likert scale ranging from 0-3.
 Higher scores indicate more severe symptoms. Musculoskeletal pain will be measured with the
 The Nordic Musculoskeletal pain Questionnaire (NMQ) that cover most potential musculoskeletal
 pain sights. The questionnaire measure musculoskeletal symptoms, and pain intensity in nine
 body areas: the neck, shoulder, elbow, wrists/hands, upper back, lower back,
 hips/thighs/buttocks, knees and ankle/feet. The questions were modified to ask about the
 previous month rather than the previous 12 months as per the original NMQ. Those reporting no
 symptoms were assigned a pain score of zero, while those who reported having musculoskeletal
 symptoms were also asked to report how intense pain was on average over the last month, on a
 scale from zero, which refers to no complaints, to nine, which refers to the pain 'as bad as
 it can be'.

 Potential confounders:

 The investigators will collect the following variables as potential confounders of the
 association between the exposures and the outcomes. These confounders were selected based on
 our review of the literature.

 Sociodemographic variables: age, gender, citizenship, marital status, number of dependents,
 parents' marital status, parents' employment status, annual personal and household income,
 hours of work per week, living arrangement, and commute time.

 Academic variables: Overall average in the past year (first year students will provide the
 average for the final year of high school), program of study, year of study.

 General health and medically diagnosed comorbidities: The investigators will ask participants
 to rate their general health and comorbidities diagnosed by a health care provider in the
 past year. We will selected comorbidities that are reported by > 5% of the sample in our
 pilot study. In the Canadian pilot study, these include: allergies, arthritis, asthma,
 attention disorder/learning disability, eating disorder, hypertension, intestinal or stomach
 ulcers, migraine headaches, mood disorder, scoliosis, and sexually transmitted infections.

 Data analysis and statistics:

 Definition of trajectories: Trajectories of the outcomes depression, anxiety, stress symptoms
 and pain will emerge by latent class growth mixture models (LCGMM) that allows for the
 identification of multiple underlying trajectories within a defined population. In LCGMM,
 each trajectory is defined by its own growth parameters (intercept, linear slope), which are
 assumed to be latent. We will use the Baysian Information Criteria (BIC), Bootstrap
 Likelihood Ratio Test (BLRT) and entropy (measure of uncertainty) to determine whether our
 4-trajactory hypothesis offers the best fitting solution for the data. Also trajectories of
 sleep quality, food insecurity, physical activity/sedentary lifestyle, and substance use will
 be identified with this method.

 Associations between exposures and trajectories: The investigators will use multinomial
 logistic regression analyses to determine the associations between each of the exposures and
 trajectories of outcomes. The investigators will report the associations as odds ratios (OR)
 and 95% confidence intervals (95% CI). The investigators will first build bivariate models to
 measure the crude associations between the exposures and trajectories. To identify
 confounders, the investigators will build models to test whether the inclusion of each
 potential confounder produced a ≥ 10% change in any of the associations.

 Associations between exposures and incident cases of depression, anxiety, stress symptoms and
 pain: At baseline, the investigators will identify a sub-cohort of students at risk of
 developing troublesome depressive and anxiety symptoms and pain respectively. The
 investigators will use Kaplan-Meier estimates to describe the incidence and discrete time
 survival analysis to measure the associations between the exposures and the outcome. In all
 models, the reference category will be the level of exposure hypothesized to be associated
 with the lowest risk of the outcome. ORs and 95% CIs will be used to describe the strength
 and direction of association. The same approach as described above will be used to identify
 prognostic factors (starting with a sub-cohort under "risk" of recovery) and for control for
 confounding.

 Sample size: The investigators estimated the number of parameters that could be included in
 the multinomial logistic regression models based on distributions of participants across the
 four hypothesized trajectories (no symptoms; improvement; worsening; and persistent) using
 two diverse distribution scenarios. In scenario 1, we hypothesized that 70% have no symptoms,
 13% experience worsening, 10% improve and 7% have persistent symptoms. In scenario 2, the
 investigator hypothesized equal distribution (25%) across trajectories. Based on these
 assumptions, the investigators estimated that the models could accommodate between 32
 parameters if the investigators recruit 1000 students (scenario 1) to as many as 234
 parameters if the investigators recruit 5000 participants (scenario 2).

 Covid-19 sub-study:

 The recruitment and data collection for the cohort study took place before and during the
 Covid-19 pandemic.Therefore, the investigators started a more fequent recording of levels of
 pain, axiety and depression from May 2020 with weekly text messages. The data Collection
 before and during the pandemic provide a chance to investigate the change in symptoms of
 depression, anxiety and stress and lifestyle behaviors in relation to the pandemic. The
 specific research questions with regards to this Covid-19-related sub-study are: 1) Are there
 any changes regarding symptoms of mental health problems during the first month of the
 pandemic? 2) Will students display changes in healthy lifestyle behaviors such as sleep
 patterns and quality, meal pattern, exercise and substance use during the first month of the
 pandemic and 3) Different trajectories of symptoms of low mood, worry and pain during the
 course of the pandemic will be measured weekly with the aim of identifying factors related to
 unfavorable trajectories.
Inclusion Criteria:

 The inclusion criteria are students at selected universities/colleges in the Stockholm
 attending selected educational programs with at least one remaining academic year before
 graduating. Students from matriculation to master level studies are invited to participate.
 Participants need to be 18 years of age or older, have access to a smart phone, laptop or
 tablet and speak sufficient Swedish or English.