Journal of Affective Disorders 352 (2024) 110–114

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Journal of Affective Disorders

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Short Communication

Associations between joint lifestyle behaviors and depression among

children and adolescents: A large cross-sectional study in China
Erliang Zhang a, 1, Jianchang Chen b, 1, Yujie Liu a, Huilun Li a, Yunfei Li c,
Keisuke Kuwahara d, e, f, *, Mi Xiang a, **
a
Ministry of Education—Shanghai Key Laboratory of Children's Environmental Health, School of Public Health, Shanghai Jiao Tong University School of Medicine,
Shanghai, China
b
Shanghai Educational Center of Science & Art, Shanghai, China
c
Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
d
Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Kanagawa, Japan
e
Department of Public Health, Yokohama City University School of Medicine, Kanagawa, Japan
f
Teikyo University Graduate School of Public Health, Tokyo, Japan

A R T I C L E I N F O A B S T R A C T

Keywords: Background: Lifestyles in children and adolescents are associated with mental health, yet the combined effects of
Joint lifestyle behaviors diet-related joint lifestyles on depression are unclear.
Children and adolescents Methods: A cross-sectional study was conducted in January 2020 in primary and secondary schools in Shanghai,
Depression
China, with 6478 participants in the analysis. Lifestyle behaviors (physical activity, sleep duration, screen time,
and diet quality) and depressive symptoms were measured using validated questionnaires. A series of multi­
variable logistic regressions were performed to examine the associations between lifestyle behaviors and their
combinations and depression.
Results: The prevalence of depressive symptoms 12.2 % (n = 788). Compared to those considered physically
active, physically inactive individuals showed higher odds of depression (adjusted odds ratio [aOR] = 1.206).
Similarly, insufficient sleep duration (aOR = 1.449), long screen time (aOR = 1.457) and poor diet quality (aOR
= 1.892) were all associated with higher odds of depression. Compared to participants with behaviors meeting
all guidelines, the odds of depression increased as the number of behaviors not meeting guidelines increased in a
dose-response relationship, with an average increase in depression odds of 49 % on average for each additional
unhealthy behavior. Moreover, different combinations of behaviors not meeting guidelines showed varied odds
of depression.
Conclusions: Our research suggests that lifestyle behaviors not meeting guidelines in children and adolescents are
associated with poorer mental health, and the risk varies with the number and specific combination of behaviors
not meeting guidelines. Diet-related joint behaviors may be overlooked, and practical measures targeting joint
lifestyles are needed to prevent and alleviate mental health problems among children and adolescents.

1. Introduction in 4 children and adolescents globally are experiencing clinically

elevated depression symptoms during COVID-19 (Racine et al., 2021).
Mental disorders are the primary cause of disease burden globally Nearly half of the global mental disorders first occur in childhood and
and increase with age among the younger generations (GBD 2019 adolescence, and thus interventions to prevent and treat adolescent
Mental Disorders Collaborators, 2022). Depression, the leading cause of mental disorders may have long-term benefits and will extend to the
mental disease burden and the major cause of disability globally, with 1 elderhood (Solmi et al., 2022; Nishida et al., 2016). However,

* Correspondence to: K. Kuwahara, Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Kanagawa, Japan.
** Corresponding author.
E-mail addresses: zhang_99@sjtu.edu.cn (E. Zhang), cjc6001@shec.edu.cn (J. Chen), kkuwahara@yokohama-cu.ac.jp (K. Kuwahara), xiangmi@sjtu.edu.cn
(M. Xiang).
1
Erliang Zhang and Jianchang Chen made equal contributions to this study and are the co-first authors.

https://doi.org/10.1016/j.jad.2024.02.032
Received 21 July 2023; Received in revised form 17 January 2024; Accepted 8 February 2024
Available online 13 February 2024
0165-0327/© 2024 Elsevier B.V. All rights reserved.
E. Zhang et al. Journal of Affective Disorders 352 (2024) 110–114

pharmacologic and psychotherapeutic treatments for depression only cell phones, for study or entertainment, with daily screen time >2 h per
decrease the burden of disease by 10–30 % and face the limitations of day defined as long screen time (Tremblay et al., 2016).
high costs and/or potential side effects (Chisholm et al., 2004; Marwaha
et al., 2023). Lifestyles, as contributing and treatable factors in several 2.2.2.2. Insufficient sleep duration. Sleep duration was obtained from
mental disorders, may need to be a central mental, medical, and public their reported wake and sleep time. The average sleep duration was
health focus (Walsh, 2011). A recent meta-review suggested a strong calculated using the following formula: (weekday sleep duration × 5 +
association between a range of mental conditions and adverse health weekend sleep duration × 2)/7. Sleep duration below 10 h per day for
behaviors, such as poorer diet, sleep patterns, and inadequate physical elementary school students and below 9 h per day for secondary school
activity. Therefore, these key modifiable health behaviors may be an students was defined as insufficient sleep duration (The Central People's
emerging prevention and treatment method for mental disorders (Firth Government of the People's Republic of China, 2019).
et al., 2020). However, such studies mainly focus on single lifestyle
behaviors, ignoring the fact that these behaviors are considered to be 2.2.2.3. Poor diet quality. The Chinese version of the quantitative food
interdependent and mutually influential, and thus should be regarded frequency questionnaire (FFQ) (Wen-peng et al., 2016) was used to
simultaneously (Liang et al., 2023; Rollo et al., 2020). Research on the examine possible food consumption in the past 30 days. The Chinese
associations between joint lifestyles and the mental health of children Children Dietary Index (CCDI) (Cheng et al., 2016) was calculated to
and adolescents is lacking, with existing studies focusing on only three measure dietary quality. Although the original CCDI included water and
health behaviors: physical activity, sleep time, and screen time (Sam­ vitamin A intake data, we did not include them due to a lack of data.
pasa-Kanyinga et al., 2020). However, the combined associations of diet Participants with the lowest third of CCDI scores were defined as having
and the other three behaviors on depression still remain unclear. This is poor diet quality (Cheng et al., 2016).
particularly important since diet, one of the most important behaviors in
children and adolescents, has also been associated with mental disorders
(Choi et al., 2020; Firth et al., 2020). Therefore, we investigated joint 2.3. Statistical analysis
key health-related behaviors, including diet, in Chinese children and
adolescents with the aim of examining the relationship between inte­ Descriptive statistics were expressed as median with interquartile
grated lifestyles and depression to fill the gap in the current literature. range (IQR) for continuous variables and as the frequency with per­
centage (%) for categorical variables. Chi-square tests were performed
2. Methods for differences in categorical variables between the depression and non-
depression groups, and Mann-Whitney U tests were used for continuous
2.1. Participants variables. Odds ratios (ORs) and 95 % confidence intervals (CI) were
obtained by logistic regression, adjusting for age, sex, weight status
A Web-based cross-sectional study among students aged 6–15 years (overweight or not), paternal education, maternal education, and family
in Shanghai, China, was conducted in January 2020 using multi-stage annual income. In addition, the definition of depression was changed
cluster sampling to recruit participants. Of the 14 districts in Shanghai from a CDI-S score of greater than or equal to 7 to a score of 4 (Allgaier
invited, seven agreed to participate in the survey. One to two schools et al., 2012) in sensitivity analyses to investigate the association be­
were randomly selected in each of the seven districts, and a total of ten tween behaviors not meeting guidelines and depression in different
schools participated in this survey. Children/adolescents in the 10 situations. IBM SPSS Statistics (version 25) was used for data analysis,
schools and their legal guardians were invited to participate in the and two-tailed P < 0.05 was considered statistically significant.
survey and informed consent was obtained before participation. A total
of 7544 students participated in the survey through web-based ques­ 3. Results
tionnaires (approximately 83 % participation rate) between January 3rd
and 21st, 2020. Participants with missing key data on lifestyles were A total of 6478 students were included in the analysis, of which 3335
excluded, and a total of 6478 children and adolescents were included in (51.5 %) were male, with a median age of 9 years. Overall, 788 (12.2 %)
the final analyses. This study was approved by the Ethics Committee of participants exhibited depression, 5092 (78.6 %) had insufficient sleep
Shanghai Jiao Tong University School of Medicine (SJUPN-201813). duration, 4627 (71.4 %) were physically inactive, 2159 (33.3 %) had
poor diet quality, and 2067 (31.9 %) had long screen time. In addition,
only 190 (2.9 %) of the participants met the guidelines for all the four
2.2. Measures behaviors, 1284 (19.8 %) had one, 2777 (42.9 %) had two, 1801 (27.8
%) had three, and 426 (6.6 %) had all four behaviors not meeting the
2.2.1. Outcome variables guidelines (Table 1).
The 10-item Children's Depression Inventory-short form (CDI-S) was As for the association of behaviors not meeting the guidelines and
used to measure depressive symptoms in children and adolescents. The depression, participants with each behavior not meeting the guidelines
Chinese version of CDI-S has been fully validated with satisfactory were more likely to exhibit depression (physically inactive: adjusted
psychometric properties (Yu and Li, 2000). The CDI-S had shown good odds ratio [aOR], 1.206; 95 % CI, 1.014, 1.434; insufficient sleep
internal consistency (Cronbach's α = 0.75) in the study of Chinese duration: aOR, 1.449; 95 % CI, 1.181–1.778; long screen time: aOR,
children, with depressive symptoms defined as a score greater than or 1.457; 95 % CI, 1.244–1.707; poor diet quality: aOR, 1.892; 95 % CI,
equal to 7 (Guo et al., 2012). 1.619–2.210) (Fig. 1A). Compared to participants with behaviors all met
the guidelines, participants with more behaviors not meeting the
2.2.2. Exposure variables guidelines were more likely to exhibit depression. The ORs increased
with the number of behaviors not meeting the guidelines, especially
2.2.2.1. Physically inactive and long screen time. The Chinese version of when participants with three (aOR, 4.661; 95 % CI, 2.249–9.661) and
the Global Physical Activity Questionnaire (GPAQ), which has good four (aOR, 6.301; 95 % CI, 2.961–13.408) behaviors not meeting the
reliability and validity among Chinese youth (Gao et al., 2022), was used guidelines (Fig. 1B). Furthermore, the prevalence of depression
to measure moderate and vigorous physical activity. Participants with increased from 12.2 % to 41.5 % after altering the definition of
<60 min of moderate to vigorous physical activity per day were defined depression in the sensitivity analyses, but these associations remained
as physically inactive (Chaput et al., 2020). Participants also reported significant (Supplementary Fig. 1). When behaviors not meeting
the time they spent using screens, such as computers, TVs, tablets and guidelines were considered as a continuous variable, the odds of

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E. Zhang et al. Journal of Affective Disorders 352 (2024) 110–114

Table 1 depression increased by an average of 49 % for each additional behavior

Characteristics of 6478 students according to depression.a not meeting guidelines (aOR: 1.488; 95 % CI, 1.366–1.621). In addition,
Variables Total (n = Depressionb P value associations between depression and multiple (two and three) different
6478) combinations of behaviors not meeting the guidelines are presented in
No (n = Yes (n =
5690) 788) Supplementary Fig. 2, suggesting that these combinations are signifi­
cantly but differentially associated with depression.
Age, median (IQR), years 9 (8–12) 9 (8–12) 11 (9–13) <0.001
Sex
Male 3335 2952 383 0.085 4. Discussion
(51.5) (51.9) (48.6)
Female 3143 2738 405 In this analysis of data from a large sample of 6478 children and
(48.5) (48.1) (51.4)
Weight status c
<0.001
adolescents, associations between joint key modifiable lifestyle behav­
Thin 575 (8.9) 511 (9.0) 64 (8.1) iors and depression were found. Single behaviors not meeting the
Normal 3811 3355 456 guidelines contributed to increased odds of depression ranging from 20
(58.8) (59.0) (57.9) % for physical inactivity to 90 % for poor diet quality. However, par­
Overweight 955 (14.7) 863 92 (11.7)
ticipants tended to have multiple unhealthy behaviors, which in turn
(15.2)
Obesity 1137 961 176 further increased the odds of depression, showing a dose-response
(17.6) (16.9) (22.3) relationship, with an average 49 % increased odds of depression for
Behaviors not meeting the each additional behavior not meeting the guidelines. Participants with
guidelines four behaviors not meeting the guidelines even had a more than six-fold
Insufficient sleep duration 5092 4437 655 0.001
increased risk of depression compared to participants without unhealthy
(78.6) (78.0) (83.1)
Physically inactive 4627 4051 576 0.268 behaviors. These associations remained significant in the sensitivity
(71.4) (71.2) (73.1) analysis.
Poor diet quality 2159 1790 369 <0.001 As stated earlier, a large body of high-quality research evidence has
(33.3) (31.5) (46.8)
pointed to the relationship between lifestyle behaviors such as physical
Long screen time 2067 1724 343 <0.001
(31.9) (30.3) (43.5)
activity, sleep, and eating patterns and depression (Firth et al., 2020).
Number of behaviors not <0.001 Inflammation, which has been linked to multiple mental disorders, is a
meeting the guidelines potential shared biological mechanism explaining the effect of adverse
None 190 (2.9) 182 (3.2) 8 (1.0) health behaviors on mental disorders. (Kuan et al., 2019). Previous
Any one only 1284 1179 105
studies have shown that exercise, sufficient sleep, and a high quality diet
(19.8) (20.7) (13.3)
Any two only 2777 2494 283 all have anti-inflammatory effects, which may partially explain the
(42.9) (43.8) (35.9) impact of lifestyle on mental health (Firth et al., 2020). Future mecha­
Any three only 1801 1505 296 nistic studies in intervention trials are needed to further explore the
(27.8) (26.4) (37.6)
neurobiological pathways by which various lifestyle factors influence
All four 426 (6.6) 330 (5.8) 96 (12.2)
Paternal education <0.001
mental health.
Junior middle school or 721 (11.1) 611 110 Previous studies focused mainly on single lifestyle behaviors,
below (10.7) (14.0) whereas according to Sampasa Kanyinga et al. and the present findings,
High school or equivalent 1497 1290 207 lifestyle behaviors not meeting the guidelines are always coexisting,
(23.1) (22.7) (26.3)
suggesting that measures should be focused on multiple lifestyles to
Bachelor or equivalent 3809 3392 417
(58.8) (59.6) (52.9) address persistently high rates of depression among children and ado­
Master or above 424 (6.5) 377 (6.6) 47 (6.0) lescents (Sampasa-Kanyinga et al., 2022). This is promising, as more
Unclear 27 (0.4) 20 (0.4) 7 (0.9) behaviors meeting the guidelines may reduce the population risk of
Maternal education <0.001
mental disorders. A systematic review revealed associations between
Junior middle school or 857 (13.2) 713 144
below (12.5) (18.3)
meeting more lifestyle guidelines (physical activity, sedentary time, and
High school or equivalent 1384 1192 192 sleep time) and better mental health indicators, even not including diet
(21.4) (20.9) (24.4) (Sampasa-Kanyinga et al., 2020). Although there may be a causal rela­
Bachelor or equivalent 3955 3539 416 tionship between dietary behaviors and depression (Choi et al., 2020),
(61.1) (62.2) (52.8)
attention to diet has not been received in current research on the com­
Master or above 250 (3.9) 221 (3.9) 29 (3.7)
Unclear 32 (0.5) 25 (0.4) 7 (0.9) bined effect of lifestyle on mental health. A recent study analyzing the
Family annual income, CNY <0.001 association of physical activity and diet quality with depression in na­
<100,000 901 (13.9) 726 175 tionally representative data from the National Health and Nutrition
(12.8) (22.2) Examination Survey showed that the risk of depression is further
100,000 to 200,000 2076 1831 245
(32.0) (32.2) (31.1)
reduced in individuals who have a high quality diet and are physically
>200,000 to 400,000 2012 1793 219 active, suggesting that there may be joint effects between lifestyle be­
(31.1) (31.5) (27.8) haviors on depressive symptoms (Liang et al., 2023). In this study, both
>400,000 857 (13.2) 774 83 (10.5) single dietary behavior and combinations with other behaviors tended
(13.6)
to exhibit higher odds of depression. Furthermore, the area under the
Unwilling to inform 632 (9.8) 566 (9.9) 66 (8.4)
curve (AUC) of Receiver operating characteristic (ROC) curves was
Abbreviations: IQR, Interquartile Range; CNY, Chinese Yuan. significantly greater with the addition of diet than with only physical
a
Data are presented as number (percentage) of study participants unless activity, sleep and screen time, showing better predictability of
otherwise indicated. Owing to rounding, some percentages may not total 100.
b depression, P < 0.001 (Supplementary Fig. 3). Given the potential for
Depression was defined as a score greater than or equal to 7 on the 10-item
additive effects between lifestyles, the synergistic effect of improving
children's depression inventory-short form scale.
c
Overweight/obesity was defined using age- and sex-specific BMI percentiles
depressive symptoms is enhanced by simultaneous exposure to the
according to Chinese reference values. lifestyles meeting the guidelines (Liang et al., 2023). Therefore, diet is a
key health behavior in children and adolescents, it is necessary and
effective to consider the combined effects of dietary behaviors and other
key behaviors on the mental health of children and adolescents, which

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E. Zhang et al. Journal of Affective Disorders 352 (2024) 110–114

Fig. 1. Associations between single behavior not meeting guidelines and their combinations and depression.
Note: The adjusted odds ratios (aORs) were adjusted for age, sex, weight status (overweight or not), paternal education, maternal education, and family annual
income.
a
Reference group for physical inactive was no physical inactive.
b
Reference group for insufficient sleep duration was no insufficient sleep duration.
c
Reference group for long screen time was no long screen time.
d
Reference group for poor diet quality was no poor diet quality.

provides an important reference on the national and school policies on submit the manuscript for publication.
depression prevention and control.
To our knowledge, our study is the first to investigate the relation­ CRediT authorship contribution statement
ship between the combinations of comprehensive lifestyle behaviors
(four key lifestyle behaviors) with mental health outcomes among Erliang Zhang: Writing – original draft, Visualization, Methodology,
children and adolescents. Nonetheless, the present study has several Formal analysis. Jianchang Chen: Writing – original draft, Data cura­
limitations. First, due to the cross-sectional design, it is possible that tion. Yujie Liu: Investigation, Data curation. Huilun Li: Writing – re­
poor mental health led to unhealthy lifestyles. Second, although vali­ view & editing, Data curation. Yunfei Li: Methodology, Data curation.
dated measurements were used, they were self-reported. Objective Keisuke Kuwahara: Writing – review & editing, Supervision, Concep­
measurements are needed. Finally, the study was conducted in tualization. Mi Xiang: Writing – review & editing, Supervision, Inves­
Shanghai, China. Caution should be exercised to generalize the present tigation, Funding acquisition, Data curation, Conceptualization.
finding to other locations.
Declaration of competing interest
5. Conclusion
The authors declare that they have no competing interests.
This large population-based cross-sectional study found that poor
diet quality, physical inactivity, prolonged screen use and inadequate
Acknowledgements
sleep were all associated with poorer mental health in children and
adolescents. Moreover, the prevalence of depression increased with
None.
unhealthy lifestyles in a dose-response pattern. The associations
depended on the number and specific combination of behaviors not
meeting guidelines. Governments, schools, health professionals, and Appendix A. Supplementary data
parents can use the current recommendations for targeted lifestyle in­
terventions to prevent and mitigate psychological problems in children Supplementary data to this article can be found online at https://doi.
and adolescents. org/10.1016/j.jad.2024.02.032.
Funding source
This study was supported by the National Natural Science Founda­ References
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