Movement and Dietary Behaviours and Mental Health among University Students: The Health@NUS Study

doi:10.21203/rs.3.rs-5042499/v1

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Movement and Dietary Behaviours and Mental Health among University Students: The Health@NUS Study

https://doi.org/10.21203/rs.3.rs-5042499/v1

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Introduction

University is a crucial time when students face mounting pressures on their mental health and are establishing health behaviours that may persist in later life. This study investigated the associations between movement and dietary behaviours and mental health among university students. It further explored the potential role of sex differences in these associations.

Methods

This cross-sectional study used data (2020–2022) from the Health@NUS prospective cohort study. Six behaviours—moderate-to-vigorous physical activity (MVPA), sedentary time, sleep duration, and intake of fruit, vegetables, and unhealthy food—were assessed and classified as either healthy or unhealthy based on established recommendations. Mental health was measured using the 6-item Kessler Psychological Distress scale and the 5-item World Health Organization Well-being Index. Multivariable linear regression was used to investigate the associations between the behaviours and mental health, and to evaluate effect modification by sex.

Results

Among 773 students (mean age 22.7 years, 56.8% female), 23.3% practiced 4–6 healthy behaviours; 14.1% and 37.7% reported high distress and poor well-being, respectively. Compared to students engaging in 0–1 healthy behaviour, those engaging in 2 or more healthy behaviours reported less distress and greater well-being. Students who practiced 4–6 behaviours reported lowest distress (females: -1.51, 95% CI -2.75, -0.27; males: -1.72, 95% CI -3.06, -0.39) and the best well-being (females: 10.66, 95% CI 6.04, 15.23; males: 9.98, 95% CI 6.04, 15.23). For individual behaviours, more sleep and less intake of unhealthy foods were associated with less distress, whereas more MVPA and sleep were associated with better well-being. Additionally, among female students, less sedentary time and unhealthy food intake were associated with better well-being.

Conclusions

The more healthy movement and dietary behaviours that students practiced, the better their reported mental health outcomes. The type of behaviour and sex also appear to play a role. These findings highlight the need for interventions addressing both lifestyle behaviours and mental health in students concurrently, potentially using sex-tailored strategies.

University Students

Mental Health

Lifestyle Behaviours

Behavioural Risk Factors

University students not only represent a key workforce demographic but also central in the development of health and well-being capabilities.^1,2 They are poised to contribute significantly to economic growth and societal advancement.^1,2 During the crucial transition from adolescence to adulthood, typically between ages 18 and 29 years, students often face significant developmental tasks, such as achieving independence, completing their education, transitioning to employment, and forming lifelong relationships.^1,2,3 These developmental tasks can be challenging and potentially lead to higher levels of psychological distress and depression, making this group more vulnerable than the general population.^4,5,6,7 A large international study of 14,000 university students across eight countries found that 35% met the diagnostic criteria for at least one common mental health condition.⁸ This may potentially lead to adverse outcomes in both personal and professional spheres and impaired functioning later in life.⁹

During the transition to adulthood, unhealthy lifestyle behaviours such as physical inactivity, inadequate sleep, poor nutrition, excessive alcohol consumption, and smoking tend to emerge.^10,11 These behaviours often persist and cluster over time, synergistically amplifying the risks for mental health conditions.^12,13,14,15 The recent COVID-19 pandemic has further challenged ongoing efforts to improve mental health for young adults.¹⁶ Therefore, it is urgent to intervene and interrupt the trajectory towards poor mental health in later life.^17,18 Evidence has shown that prioritising multiple healthy lifestyle behaviours, including physical activity, diet, smoking, and alcohol consumption, could prevent or mitigate mental health conditions.^19,20,21 Targeting multiple modifiable lifestyle behaviours is a fundamental strategy for mental health prevention and long-term healthy ageing promotion.¹⁹

To create effective public health promotion strategies for mental health, it is important to understand behaviours in the local context because young adult behaviour profiles differ greatly between countries and within nation-states.¹ For example, Singapore prohibits smoking and alcohol consumption in most educational institutions.²² The regulations are associated with a low prevalence of these behaviours among university students (1.4% for smoking and 7.1% for binge drinking) compared to Western countries.^{23,24,25,26,27} Given these unique circumstances and the low prevalence rates, this study will focus on physical activity and diet, two other key factors for mental health prevention, which are potentially more universally applicable in similar university settings.^22,28,29 Recent research has broadened its scope to embrace a holistic perspective on 24-hour movement behaviours, integrating the impacts of sedentary behaviour and sleep duration in addition to physical activity.^30,31,32,33 Furthermore, these movement and dietary behaviours appear to be closely related and positively influence each other.³⁴ A broader and integrated approach may be more efficient at improving mental health than a segmented or siloed approach that considers each component individually.^{24,25,34,35,36,37,} However, the relationship between these behaviours and mental health among university students remains unclear.^34,38

There are also sex differences in mental health and behaviours.¹ For example, women tend to experience higher rates of depression, anxiety, and psychological distress, while men typically exhibit higher levels of physical activity and poor diet habits.^39,40,41 Sex-specific biological factors and sex-related social factors may interact to influence behaviours and health status.⁴² Therefore, it is crucial to explore the sex roles in the relationships between movement and dietary behaviours and mental health. Another research gap is that existing research often limits its scope to negative mental health outcomes such as psychological distress, depression, or anxiety, overlooking the broader mental health spectrum.^24,25,26,43 Mental health is more than the mere absence of mental illness; it includes positive aspects such as subjective well-being.⁴⁴ To address existing gaps in the evidence, this study aims to evaluate relationships between the number and type of movement and dietary behaviours and both the positive and negative facets of mental health (psychological distress and mental well-being), with a special focus on sex differences.

Study design and setting

Health@NUS is a prospective cohort study conducted at the National University of Singapore (NUS) in partnership with the Singapore Government’s Health Promotion Board (HPB).²⁷ This study is based on Health@NUS baseline data collected from 2020 to 2022. Eligible participants for the study included citizens or permanent residents of Singapore, aged 18 to 26 years, who were studying full-time at NUS. Participants also had to have a Singapore registered mobile number and a mobile phone with an operating system compatible with the study app (Health Insights SG (hiSG) and the Fitbit app.

The reporting of this study follows the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) statement.⁴⁵ The study has been approved by the National Healthcare Group Domain Specific Review Board (NHG DSRB, Ref: 2019/00285).

Data collection

After obtaining written informed consent, students completed baseline self-administrated questionnaires via REDCap and underwent anthropometric assessments conducted by trained research assistants at NUS.^46,47

Key variables of interest

Movement and dietary behaviours

Movement behaviours, which include moderate-to-vigorous physical activity (MVPA),⁴⁸ sedentary behaviour,⁴⁹ sleep duration,⁵⁰ and dietary behaviours–fruit and vegetable intake,⁵¹ and unhealthy food intake,⁵¹–were assessed using validated measures. The details of the measurement for each behaviour and the coding are provided in Table 1. Students were categorised as “engaging in the healthy lifestyle behaviour” if they met international or Singapore recommendations (coding = Yes).^52,53,54 To account for the low percentage of participants meeting the recommended fruit intake of 2 servings/day, we used an alternative cut-off of 1 serving/day for a more robust analysis. The cut-off of 1 serving/day was also applied to unhealthy food intake, as it was recommended that less is better.⁵⁵ To explore the relationships between the number of healthy movement and dietary behaviours and mental health outcomes, students were further classified into three groups based on the number of healthy behaviours they engaged in: those who engaged in 0–1, 2–3, and 4–6 healthy lifestyle behaviour(s).

Table 1

Measurements and coding criteria of lifestyle behaviors
Behaviors	Measurements	Engaged in healthy lifestyle behavior
Moderate-to-vigorous physical activity (mins/week)	Modified Singapore Prospective Study Program Physical Activity Questionnaire⁴⁸	Yes, sufficient MVPA(≥ 150 mins/week) No, insufficient MVPA (< 150 mins/week)
Sedentary behavior (hours/day)	Modified Domain-Specific Adult Sedentary Behavior Questionnaire⁴⁹	Yes, less sedentary behavior/time (≤ 8hrs/day) No, prolonged sedentary behavior (> 8hrs/day)
Sleep duration (hours/day)	Pittsburgh Sleep Quality Index: sleep duration⁵⁰	Yes, adequate sleep ( 7–9 hours) No, inadequate sleep (< 7 hours or > 9 hours)
Vegetable intake (servings/day)	37-item Food Frequency Questionnaire (FFQ): green leafy; carrots; other vegetables⁵¹	Yes, recommended vegetable intake (≥ 2 servings/day) No, low vegetable intake (< 2 servings/day)
Fruit intake (servings/day)	37-item FFQ: citrus fruits; other fresh fruits; pure fruit juices⁵¹	Yes, more fruit intake (≥ 1 serving/day) No, low fruit intake (< 1 serving/day)
Unhealthy food intake (servings/day)	37-item FFQ: sweet and desserts; malted drinks; sweetened beverages; Western fast food; deep-fried meals/snacks⁵¹	Yes, more unhealthy food intake (≥ 1 serving/day) No, limited unhealthy food intake (< 1 serving/day)

Mental health

Mental health was assessed using two indicators: psychological distress measured by the 6-item Kessler Psychological Distress Scale (K6)⁵⁶ and mental well-being by the 5-item World Health Organization Well-Being Index (WHO-5).⁵⁷

The K6 asked participants how often they felt nervous, hopeless, restless or fidgety, so depressed that nothing could cheer them up, felt that everything was an effort, and felt worthless during the past 30 days. Each question is rated on a scale of 0 (None of the time) to 4 (All of the time), with a total score ranging from 0 to 24. Low scores indicate low levels of psychological distress, while high scores indicate high levels of psychological distress. A score of 13 or above indicates “serious psychological distress”.⁵⁶

The WHO-5 consists of 5 positively phrased items: 1) I have felt cheerful and in good spirits, (2) I have felt calm and relaxed, (3) I have felt active and vigorous, (4) I woke up feeling fresh and rested, and (5) My daily life has been filled with things that interest me. Students were asked to rate each item based on their experience in the past 14 days, using a scale from 0 (None of the time) to 5 (All of the time). The total raw score ranges from 0 to 25, which is then multiplied by 4 to obtain the final score ranging from 0 to 100. High scores indicate better mental well-being, whilst low scores indicate poorer mental well-being. A score of 50 or below indicates “poor mental well-being”.⁵⁷

Statistical analysis

We analysed the socio-demographic characteristics, movement and dietary behaviours, and mental health of the students. Continuous data following a normal distribution were reported as mean (standard deviation, SD), and the Student t-test was used to compare differences between groups. Continuous and skewed data were reported as median (Interquartile range [IQR], IQ1–IQ3), and the Mann-Whitney U test was used for the group comparison. Categorical data were reported as number (percentage), and the Chi-square test was used for the group comparison.

Multiple linear regressions with robust standard error were used to examine the relationships between 1) the number of healthy behaviours and mental health outcomes; and 2) the type of healthy behaviours and mental health outcomes. Covariates were selected based on literature, including age, sex, financial factors (weekly allowance and part-time job, academic factors (study year, weekly time in class, and weekly study time), and social factors (weekly time with friends and weekly time on extracurricular classes).^58,59,60 The models investigating relationships between specific type of movement and dietary behaviours and mental health were also mutually adjusted for the other five behaviours.

To explore whether sex modifies these relationships, we introduced interaction terms between exposures (i.e. number of behaviours or type of behaviour) and sex into our models. F-tests were also performed to confirm the significant interaction effects and to validate the necessity of a stratified analysis for sex. The regression results were reported as crude beta coefficients, fully adjusted coefficients, and coefficients in female and male strata from fully adjusted models, each with a 95% confidence interval (CI). All data analyses were conducted using Stata/SE 16.0.

Characteristics of Students

Out of 1556 students screened, 776 enrolled in the study, and 773 were included in the final analysis (Fig. 1). Among these participants, 56.8% were female and 43.2% were male, with an average age of 22.70 years (SD = 1.69). The majority (92.1%) were of Chinese ethnicity. Approximately half of the students were in their 4th or 5th year of study (52.1%), spent more than 15 hours per week in classes (47.3%), dedicated over 15 hours to studying outside of class (56.7%), engaged in social activities with friends for more than 4 hours each week (44.4%), and received more than 50 SGD allowance a week (45.5%). Additionally, 29.8% of the students worked part-time. Significant differences were observed between female and male students in terms of age and part-time employment: male students were older and less likely to have part-time jobs. Table 1 provides more details on students’ characteristics.

For movement behaviours, students reported engaging in a median of 240 minutes MVPA per week, an average of 10.87 hours of sedentary behaviour per day, and an average of 6.84 hours of sleep per day. Regarding dietary behaviours, the median daily intake was were 0.58 servings of fruit, 1.71 servings of vegetables, and 1.01 servings of unhealthy food. Male students reported significantly more minutes of MVPA per week compared to female students. Students reported an average psychological distress score of 8.07 (SD = 4.15) and the average mental well-being score was 54.92 (SD = 17.10). Notably, 14.1% of students reported serious psychological distress, whilst 37.7% reported poor mental well-being. Female students reported significantly higher psychological distress and lower mental well-being compared to male students.

Table 1

Descriptive analysis of individual lifestyle behaviours and mental health outcome by sex
	Overall (n = 773)	Female (n = 439, 56.8%)	Male (n = 334, 43.2%)	P-value
Age	22.70 ± 1.69	22.03 ± 1.43	23.57 ± 1.60	< 0.001
Ethnicity
Chinese	711 (92.1)	406 (92.9)	304 (91.0)
Malay	24 (3.1)	11 (2.5)	13 (3.9)
Indians	20 (2.6)	10 (2.3)	10 (3.0)
Others	17 (2.2)	10 (2.3)	7 (2.1)	0.650
Study year
1–3	369 (47.9)	206 (47.0)	163 (48.9)
4–5	402 (52.1)	232 (53.0)	170 (51.1)	0.598
Hours of classes/week
≤ 15	406 (52.7)	235 (53.8)	171 (51.2)
> 15	365 (47.3)	202 (46.2)	163 (48.8)	0.477
Hours of studying/week
≤ 15	341 (45.4)	206 (48.6)	135 (41.2)
> 15	411 (56.7)	218 (51.4)	193 (58.8)	0.042
Hours of extracurricular/week
≤ 4	612 (79.4)	356 (81.5)	256 (76.7)
> 4	159 (20.6)	81 (18.5)	78 (23.4)	0.100
Hours with friends/week
≤ 4	429 (55.6)	248 (56.8)	181 (54.2)
> 4	342 (44.4)	189 (43.3)	153 (45.8)	0.480
Part-time job
Yes	230 (29.8)	151 (34.6)	79 (23.7)
No	542 (70.2)	286 (65.4)	255 (76.4)	0.001
Allowance/week (SGD)
≤ 50	420 (54.5)	233 (53.3)	187 (56.0)
> 50	351 (45.5)	204 (46.7)	147 (44.0)	0.460
Individual behaviours
MVPA, mins/week	240.00 (117.50–450.00)	185.00 ( 85.00–375.00)	315.62 (165.00–540.00)	< 0.001
Sedentary behaviour, hours/day	10.87 ± 3.60	10.91 ± 3.58	10.82 ± 3.63	0.732
Sleep, hours/day	6.84 ± 1.08	6.89 ± 1.13	6.78 ± 3.63	0.146
Fruit intake, servings/day	0.58 (0.26–1.03)	0.53 (0.25– .07)	0.64 (0.26–1.00)	0.746
Vegetable intake, servings/day	1.71 (1.00–3.21)	1.71 (0.88–3.21)	1.71 (1.10–3.21)	0.350
Unhealthy food intake, servings/day	1.01 (0.54–1.58)	1.02 (0.54–1.58)	1.00 (0.56–1.58)	0.952
mental health outcomes
Psychological distress	8.07 ± 4.15	8.47 ± 4.23	7.54 ± 3.97	0.002
Serious (score ≥ 13)	109 (14.1)	74 (16.9)	35 (10.5	0.016
Mental well-being	54.92 ± 17.10	52.85 ± 16.89	57.64 ± 17.02	< 0.001
Poor (score ≤ 50)	291 (37.7)	181 (41.3)	110 (32.9)	0.023
The data was reported as mean ± standard deviation, number (percentage), median (Interquartile [IQR], IQ1–IQ3); MVPA: moderate-to-vigorous physical activity

Figure 2 shows that 17.7% students engaged in 0–1 healthy behaviour and over half of the students practiced 2–3 healthy behaviours (56.0%). Only 23.3% reported engaging in at least 4 healthy behaviours. In terms of individual behaviour (Fig. 3), 68.6% students reported sufficient MVPA. Approximately half reported having adequate sleep (54.6%) and consuming fewer than 1 serving of unhealthy food per day (49.6%). Less than one third of the students adhered to recommended sedentary time (20.2%) and consumed at least 1 serving of fruit daily (27.6%).

Significant gender differences were observed in the engagement of healthy behaviours. Compared to male students, a higher proportion of female students engaged in 0–1 healthy behaviour and fewer engaged in 4–6 behaviours (Fig. 2). A significant difference was also found between female and male students in engaging in sufficient MVPA (Fig. 3).

Figure 2. Frequency of the number of healthy movement and dietary behaviours among students

Associations between movement and dietary behaviours and mental health outcomes

Table 3 describes results from multivariable linear regression analyses examining the associations between students' healthy movement and dietary behaviours and mental health outcomes. After adjusting for covariates, we found statistically significant associations between the number of healthy behaviours and psychological distress. Students who engaged in 2–3 and 4–6 healthy behaviours, as compared to those who engaged in 0–1, reported lower levels of psychological distress. Regarding the type of lifestyle behaviours, adequate sleep and limited intake of unhealthy food were significantly associated with lower levels of psychological distress. The results for healthy behaviours and mental well-being were similar. After adjusting for covariates, students who engaged in 2–3 and 4–6 healthy behaviours reported significantly higher mental well-being scores compared to those who engaged in 0–1. Among the six behaviours, movement behaviours including sufficient MVPA, less sedentary behaviour, and adequate sleep–as well as limited unhealthy food intake were significantly associated with better mental well-being.

Table 3

The associations between movement and dietary behaviours and mental health outcomes
Variables	Psychological distress (n = 749) Coefficient (95% CI)		Mental well-being (n = 749) Coefficient (95% CI)
Number of healthy behaviours	Crude	Adjusted overall association ^a	Crude	Adjusted overall association ^a
0–1	Ref	Ref	Ref	Ref
2–3	-1.19 (-1.98, -0.40)^**	-1.17 (-1.97, -0.37)^**	6.02 (2.83, 9.22)^***	5.77 (2.72, 8.82)^***
4–6	-1.83 (-2.75, -0.92)^***	-1.72 (-2.63, -0.81)^***	12.40 (8.68, 16.11)^***	10.46 (6.97, 13.95)^***
Type of healthy behaviours	Crude	Adjusted overall association ^b	Crude	Adjusted overall association ^b
MVPA	-0.29 (-0.92, 0.34)	-0.16 (-0.83, 0.52)	8.21 ( 5.66, 10.75)^***	5.85 (3.21, 8.49)^***
Sedentary behaviour	-0.23 (-0.96, 0.50)	-0.15 (-0.87, 0.57)	4.44 (1.44, 7.43)^**	3.50 (0.72, 6.29)^*
Sleep	-1.04 (-1.62, -0.46)^***	-1.08 (-1.67, -0.49)^***	4.49 (2.09, 6.90)^***	4.86 (2.54, 7.19)^***
Fruit intake	-0.19 (-0.84, 0.47)	-0.06 (-0.72, 0.60)	2.79 (0.09, 5.48)^*	0.89 (-1.78, 3.55)
Vegetable intake	0.17 (-0.44, 0.75)	0.20 (-0.41, 0.80)	-0.13 ( -2.57, 2.31)	-1.08 (-3.51, 1.35)
Unhealthy food intake	-1.42 (-2.00, -0.85)^***	-1.38 (-1.95, -0.80)^***	3.65 (1.25, 6.06)^**	3.80 (1.50, 6.09)^**
^a full models were adjusted for sex, age, weekly allowance, part-time job, study year, weekly time spent on classes/studying/ classes and weekly time spent with friends. The Global p-values of number of healthy behaviours for psychological distress and mental well-being were 0.001 and less than 0.001, respectively. ^b The models were mutually adjusted for six individual lifestyle behaviours as well as for sex, age, weekly allowance, part-time job status, study year, weekly time spent on classes/studying/ classes and weekly time spent with friends. ^* p < 0.05, ^ p < 0.01, and ^* p < 0.001

Associations between movement and dietary behaviours and mental health outcomes by sex

Significant interaction effects of exposures and sex were observed. Table 4 shows the associations between healthy behaviours and mental health outcomes, stratified by sex. Engagement in 4–6 healthy movement and dietary behaviours was significantly associated with lower levels of psychological distress and better well-being in both sexes. For female students, significant associations were also found between 2–3 healthy behaviour engagement and two mental health outcomes.

Similar patterns were found for the type of behaviours, with associations varying between sex. In both sexes, adequate sleep and limited unhealthy food intake were associated with lower levels of psychological distress, whilst sufficient MVPA and adequate sleep were found to be associated with better mental well-being. Significant associations were also found for less sedentary behaviour and limited unhealthy food intake among female students, but not among male students.

Table 4

The associations between movement and dietary behaviours and mental health outcomes by sex
Variables	Psychological distress (n = 749) Coefficient (95% CI)		Mental well-being (n = 749) Coefficient (95% CI)
Number of healthy behaviours ^a	Female	Male	Female	Male
0–1	Ref	Ref	Ref	Ref
2–3	-1.67 (-2.71, -0.62)^**	-0.40 (-1.67, 0.86)	6.32 (2.42, 10.22)^**	4.89 (-0.12, 9.90)
4–6	-1.51 (-2.75, -0.27)^*	-1.72 (-3.06, -0.39)^*	10.66 (6.04, 15.23)^***	9.98 (4.64, 15.32)^***
Type of behaviours ^b	Female	Male	Female	Male
MVPA	0.04 (-0.77, 0.85)	-0.53 (-1.69, 0.64)	6.52 (3.31, 9.74)^***	4.58 (0.22, 8.93)^*
Sedentary behaviour	-0.10 (-1.07, 0.88)	-0.21 (-1.26, 0.85)	3.71 (0.05, 7.36)^*	3.27 (-0.96, 7.49)
Sleep	-0.99 (-1.78, -0.19)^*	-1.20 (-2.08, -0.32)^**	3.31 (0.23, 6.38)^*	6.87 (3.33, 10.42)^***
Fruit intake	-0.19 (-1.08, 0.70)	0.10 (-0.83, 1.03)	1.01 (-2.48, 4.49)	0.73 (-3.22, 4.68)
Vegetable intake	-0.04 (-0.86, 0.78)	0.48 (-0.39, 1.35)	0.65 (-2.55, 3.85)	-3.20 (-6.77, 0.36)
Unhealthy food intake	-1.45 (-2.22, -0.65)^***	-1.30 (-2.14, -0.45)^**	4.31 (1.25, 7.37)^**	3.13 (-0.34, 6.61)
^a The models were adjusted for sex, age, weekly allowance, part-time job, study year, weekly time spent on classes/studying/extracurricular classes and weekly time spent with friends. The Global p-values of number of healthy behaviours for psychological distress and mental well-being were 0.020 and 0.002, respectively. ^b The models were mutually adjusted for six lifestyle behaviours as well as for sex, age, weekly allowance, part-time job status, study year, weekly time spent on classes/studying/extracurricular classes and weekly time spent with friends. ^* p < 0.05, ^ p < 0.01, and ^* p < 0.001

Our study showed high levels of psychological distress and poor mental well-being in university students in Singapore, with female students reporting poorer mental health than their male counterparts. Students demonstrated low engagement in healthy movement and dietary behaviours, with particular concern for females students. Additionally, there was very low adherence to recommended sedentary behaviour and fruit intake. We found that engaging in a greater number of healthy behaviours was associated with lower psychological distress and better well-being. Female students who engaged in at least 2 or more healthy behaviours reported better mental health, whilst among male students, a significant association was found between 4–6 behaviours and mental health. Regarding specific type of behaviours, in both sexes, adequate sleep and limited unhealthy food intake were associated with lower psychological distress, and sufficient MVPA and adequate sleep were associated higher mental well-being. In addition, more MVPA and less sedentary behaviour were associated with better well-being in female students.

University students in our study reported higher levels of psychological distress than the general Singapore population.⁶¹ However, these levels appeared better than those reported by university students internationally.^62,63,64 The mental well-being scores in our study population, collected during the COVID-19 pandemic, were also higher than those from other studies conducted in similar periods.^65,66 Alarmingly, only 2% of students met the recommended fruit intake of two servings per day, which was lower than both local and international evidence.^67,68 Similarly, low adherence to recommended sedentary behaviour was also observed.^69,70 These findings resonate with global observations that cultivating multiple healthy lifestyle behaviours is a widespread challenge—only a minority of students managed to engage in multiple healthy behaviours.^22,71,72,73

Our findings indicate that engaging in more healthy movement and dietary behaviours is associated with better mental health. Although a direct comparison with other studies is challenging due to differences in included behaviors and study populations, our results are consistent with the broader body of research.^74,75,76 Movement and dietary behaviours appear to be closely related and positively influence each other.³⁴ For instance, engaging in physical activity may have positive effects on sleep; shorter sleep duration is associated with unhealthy dietary behaviours; and sedentary behaviours may encourage passive snacking and overeating.^28,77 It is plausible that these behaviours create a cumulative or synergistic relationship with mental health, where engaging in more healthy movement and dietary behaviours is associated with lower psychological distress and better mental well-being. Also, the problem behaviour theory posits that engaging in one unhealthy behaviour increases the likelihood of participating in another unhealthy behaviour.^28,78 Addressing multiple behaviours simultaneously may be more efficient at improving mental health than a segmented approach that considers each behaviour individually.^{24,25,34,35,36,37}

Whilst engaging in more healthy movement and dietary behaviours is strongly associated with better mental health outcomes, our findings suggest that the type of behaviours students engage in appears to play a role, too. Adequate sleep and limited unhealthy food intake were significantly associated with both mental health outcomes, aligning with findings from other studies.^{68,79,80,81,82} Evidence suggests that adherence to sleep guidelines was more strongly associated with reduced depression and anxiety than meeting the guidelines for sedentary behaviour or MVPA.^{33, 83} This could be due to the fact that sleep disturbance are often key symptoms of mental health conditions.⁸⁴ Moreover, unhealthy food choices frequently serve as an accessible means to reduce stress through sensory pleasure, distraction, or escapism.⁷⁹ Interestingly, our study found that sufficient MVPA was associated only with better mental well-being. This might be because persistent stressors such as academic performance pressure and concerns about future employment still maintain a certain level of psychological distress in this study population, despite engagement in physical activity. Contrary to some previous studies, our study did not find direct associations between fruit and vegetable intake and either of the two mental health outcomes.^81,82,85 These discrepancies might be attributed to variations in measurements across studies. It's also plausible that fruit and vegetable consumption, as individual behaviours, may not be directly associated with mental health outcomes in our study population. However, when combined with other dietary or movement behaviours, they could contribute to better mental health.

Our study adds another dimension to the existing literature by considering sex differences. Overall, female students engaged in fewer healthy movement and dietary behaviours compared to male students. While the directions of the observed associations between the number of healthy behaviours and mental health outcomes were consistent for both sexes, the strength of associations appeared to be greater in female students.^86,87,88,89 This may be due to the low engagement in healthy behaviours and poorer mental health in female students, potentially making them more responsive. Evidence also suggests a bi-directional relationship between movement and dietary behaviours and mental health: individuals with poor mental health reported more unhealthy movement and dietary behaviours.^{81,86, 90,91} This highlights the potential interplay of these aspects and the importance of addressing mental health conditions when promoting healthy lifestyle behaviours.⁹² An additional factor to consider is the mandatory two-year national service for Singaporean male citizens or permanent male residents at the age of 18.⁹³ This service, including physical training and a regimented lifestyle, could influence health behaviours and potentially lead to greater mental resilience among male students. This unique contextual factor may contribute to the observed sex differences in our study and warrants future investigation in future research.

This study is among the first to explore the combination of movement and dietary behaviours and their associations with both positive and negative mental health outcomes. It contributes to our understanding of mental health promotion among university students in Asia. University students are at risk, as mental disorders have become one of the leading causes of morbidity, mortality, and dysfunction among young people worldwide.¹⁶ Whilst prevention and early intervention can be implemented throughout the lifespan, the potential benefits are substantial when targeting young people, an area currently lacking sufficient attention.^16,18

As we strive to better promote mental health, several aspects worth considering for future research have emerged from our findings. First, our results provide insights into the potential interplay between movement and dietary behaviours and mental health. Recognising this interrelation underscores the need for interventions addressing both lifestyle behaviours and mental health holistically. Future interventions could benefit from adopting multi-faceted approaches that not only improve movement and diet behaviours but also incorporate components directly targeting mental health, such as stress management skills.⁹² Second, our findings support the importance of sex-tailored strategies when adopting a multi-faceted approach. Interventions are needed to exploit the responsiveness in females and acknowledge that males may need to engage in a higher level of health-promoting behaviours for comparable benefits. Lastly, the varying degrees of associations found between healthy behaviours and two mental health outcomes in this study advocate for future research to capture the broader spectrum of mental health.

Despite the novelty and strengths of the study, several limitations need to be acknowledged. First, as a cross-sectional study, it limits the ability to establish causality and reverse causality is possible. However, it does provide insights into the potential interplay and clustering of mental health outcomes and multiple health behaviours. Given that a cross-sectional study provides only a snapshot of the situation, future studies should leverage longitudinal designs with multiple data points to confirm the observed associations. Second, the use of self-report questionnaires introduces potential recall bias. Future research could benefit from including device-measured variables, particularly for assessing movement behaviours. Third, there remains a risk of residual confounding due to factors that our study may not have fully accounted for.

In conclusion, this study demonstrated that university students in Singapore reported poor mental health and low engagement in movement and dietary behaviours, with a particular concern on female students. Engaging in more healthy movement and dietary behaviours was associated with better reported mental health outcomes, with the type of behaviours playing a role. There were also sex differences among these relationships. Together, these findings emphasise the need for future longitudinal studies and interventions that address both lifestyle behaviours and components to improve mental health holistically, coupled with sex-tailored strategies.

Ethic declarations

Participation in this study was voluntary and written informed consent was obtained. The study was approved by the National Healthcare Group Domain Specific Review Board (NHG DSRB, Ref: 2019/00285).

Competing interest

All authors declare no competing financial interest relating to this paper, but the following competing non-financial interests: Janelle Chia and Daphne Koek are current employees at Health Promotion Board Singapore Government.

Competing Interests

Funding

This study received funding from the Physical Activity and Nutrition Determinants in Asia (PANDA) research programme at the Saw Swee Hock School of Public Health, National University of Singapore, and the Health Promotion Board, Singapore. Additionally, the first author, Shenglin Zheng, was supported by the Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore.

Author Contribution

Conceptualization: S.Z., F.M-R. Methodology: S.Z., F.M-R.,B.C.T. Formal analysis: S.Z. Data collection: X.H.C. Data curation: C.M., J.C. Writing-original draft: S.Z. Writing-review & editing: X.H.C., S.M.E., C.M., B.C.T., J.C., D.K., R.M.v.D., F.M-R. Supervision: F.M-R. Funding acquisition: J.C., D.K., F.M-R. All authors have read and agreed to the published version of the manuscript.

Acknowledgement

We would also like to thank the Singapore Population Health Studies team at the National University of Singapore for their assistance to recruit and guide participants through the study procedures.

Data Availability

The datasets used/or analysed during the current study are available from the corresponding author on reasonable request.

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Competing interest reported. All authors declare no competing financial interest relating to this paper, but the following competing non-financial interests: Janelle Chia and Daphne Koek are current employees at the Health Promotion Board Singapore Government.

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Movement and Dietary Behaviours and Mental Health among University Students: The Health@NUS Study

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Abstract

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INTRODUCTION

METHOD

Study design and setting

Data collection

Movement and dietary behaviours

Mental health

Statistical analysis

RESULTS

Characteristics of Students

Associations between movement and dietary behaviours and mental health outcomes

Associations between movement and dietary behaviours and mental health outcomes by sex

DISCUSSION

CONCLUSIONS

Declarations

Ethic declarations

Competing interest

Competing Interests

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1