Effects of gender differences and lifestyle factors on depression among Chinese children and adolescents

doi:10.21203/rs.3.rs-4276145/v1

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Effects of gender differences and lifestyle factors on depression among Chinese children and adolescents

https://doi.org/10.21203/rs.3.rs-4276145/v1

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Purpose

This study aims to investigate the variations in the prevalence of depressive symptoms among Chinese children and adolescents with different lifestyles, including Internet use, breakfast, exercise, sleep and homework, and to further explore the impact of gender on the relationship between lifestyles and depressive symptoms.

Methods

The cross-sectional study recruited school-based students (8–18 years) throughout Chongqing, China. The Center for Epidemiological Studies Depression Scale for Children (CES-DC) was utilized to assess depressive symptoms. Binary logistic regression was employed to identify the factors significantly contributing to the prevalence of depressive symptoms. The Analyses were stratified by gender.

Results

A total of 22,373 children and adolescents were recruited from February 2019 to December 2019, comprising 11,141 boys (49.80%) and 11,232 girls (50.20%). Among them, 2922 (13.06%) participants reported experiencing depressive symptoms, with a prevalence rate of 10.56% for boys and 15.54% for girls. The binary logistic regression analysis revealed that spending more than 2 hours on the Internet, skipping breakfast, and spending more than 1.5 hours on homework were risk factors for depressive symptoms. Conversely, exercising for 3 to 5 hours and sleeping for 6 to 10 hours were protective factors of depressive symptoms. Notably, Internet use and exercise were gender-related predictors of depressive symptoms and were only significant in girls.

Conclusions

The insights gained from this study may assist in raising awareness among families and schools about the need to focus on the lifestyles of children and adolescents, particularly these gender-related lifestyle factors, when implementing preventive measures for depression.

Child

Adolescent

Depressive symptom

Lifestyle

Cross-sectional analysis

Mental disorders affect nearly 30% of individuals worldwide in their lifetime, accounting for 32% of all years lived with disability and 13% of disability-adjusted life years[1]. Among mental disorders in adolescents, unipolar depressive disorder stands out as a common problem worldwide [2], often persisting into adulthood [3].

Depression in young people has garnered widespread concern [4]. This is not only due to the enormous social and economic burden associated with depression [5], but also because it occurs during a period of rapid emotional and cognitive development, coupled with crucial life transitions [4]. In the past two decades, depressive symptoms appear to be increasing in prevalence among the younger generations [6], rising from 9.5% in 1995 to 11.6% in 2018 [7]. Despite the early onset of depressive symptoms and the urgent need for government and community support [8], there remains a significant gap between needs and resource availability [9]. In developed countries, such as the United States, only 1% of children and adolescents can access depression treatment in outpatient clinics annually[10]. Furthermore, in China, over 90% of children individuals suffering from depression have never received any professional help [11].

Traditionally, lifestyle factors such as exercise [12], breakfast [13], and sleep [14] have been predominantly associated with physical health. However, in recent years, these factors have increasingly been linked to the onset and symptoms of various mental disorders, leading to the emergence of “lifestyle psychiatry” [15, 16]. In reality, unhealthy lifestyles such as insufficient exercise [17] or sleep [18], excessive Internet use [19], skipping breakfast [20], and heavy homework loads [21], particularly prevalent in China [22], were common among children and adolescents.

Previous studies have shown that unhealthy lifestyles [15, 23, 24] were related to depressive symptoms, Additionally, positive health behaviors could improve depressive symptoms in children and adolescents [25, 26]. However, these behaviors were often considered separately from each other [27]. Furthermore, recent studies have indicated differences in the prevalence of depressive symptoms between boys and girls [28, 29]. Therefore, this study was designed to investigate the variations in the prevalence of depressive symptoms among Chinese children and adolescents with different lifestyles, including Internet use, breakfast, exercise, sleep, and homework, and to further explore the impact of gender on the relationship between lifestyles and depressive symptoms.

Participants and procedure

The data in this study were derived from a large cross-sectional epidemiological study [30], specifically designed to investigate the prevalence of depressive symptoms. The study was conducted among 22,373 school-based individuals in Chongqing, China, spanning from February 2019 to December 2019. To assess depressive symptoms, a structured questionnaire, the Centre for Epidemiological Studies Depression Scale for Children (CES-DC), was employed[31]. CES-DC scores ≥ 28 were considered indicative of a significant level of depressive symptoms [32]. The rationale and design of the epidemiological study have been detailed elsewhere [30]. This study was approved by the Ethics Committee of Chongqing Medical University.

Measures

Personal factors

We have previously considered the personal factors assumed to be associated with our exposures and outcomes of interest based on theory and prior research. Continuous variables included age, Body Mass Index (BMI), and Connor-Davidson Resilience Scale (CD-RISC). Gender was considered as a categorical variable. BMI was calculated using weight and height (kg/m²), both measured by the research assistants.

Lifestyle factors

Lifestyle factors included in the self-administered questionnaire were as follows.

Internet use. Children and adolescents reported their average daily Internet use time in response to the following question: ‘How many hours do you spend using a mobile phone or computer for non-study purposes each day on average?’ The present study categorized the variable as ‘< 0.5 hour’, ‘0.5-2 hours’, ‘2–4 hours’, and ‘>4 hours’.

Breakfast. We assessed how often the participants ate breakfast each week with the question: ‘How often do you eat breakfast?’ The frequency of breakfast was divided into five categories: ‘never’, ‘seldom/1–2 times per week’, ‘often/3–4 times per week’, ‘usually/ 5–6 times per week and every day’.

Exercise. Participants' average weekly exercise time was evaluated with the question: ‘How many hours do you exercise each week on average?’ The options included: ‘<1 hour’, ‘1–3 hours’, ‘3–5 hours’, and ‘>5 hours’.

Sleep. Sleep duration was ascertained with the question: ‘How many hours do you sleep each day on average?’ The response options were: ‘< 6 hours’, ‘6–8 hours’, ‘8–10 hours’, and ‘>10 hours’.

Homework. Average daily homework time was gauged with the following question: ‘How many hours do you spend doing homework after school each day on average?’ The answering alternatives were: ‘<0.5 hour’, ‘0.5-1 hour’, ‘1-1.5 hours’, ‘1.5-2 hours’, and ‘>2 hours’.

Statistical analysis

Statistical analyses were performed using SPSS, version 25.0 for Windows (IBM Corp, Armonk, NY, USA). First, descriptive statistics for continuous variables were expressed as mean with standard deviation (SD), and categorical variables were expressed as numbers with percentages. Then, the Mann-Whitney U test was employed for analyzing continuous data, and chi-square analysis was performed on categorical data. Next, a binary stepwise logistic regression analysis was conducted to identify the factors significantly contributing to the prevalence of depressive symptoms. Two models were tested: The unadjusted model only included the lifestyle factors for depressive symptoms; While the adjusted model accounted for personal factors as well. In addition, associations between these lifestyle factors and depressive symptoms were stratified for the gender groups. Adjusted odds ratio (AOR) was reported with 95% confidence intervals (CI). The Nagelkerke R square value was used as the coefficient of determination. The Hosmer and Lemeshow test was utilized to assess the goodness-of-fit of the model and p > 0.05 indicated an acceptable fitness. A value of p < 0.05 was considered to be statistically significant.

Personal factors

The characteristics of the responding individuals were summarized in Table 1. Out of the 22,373 eligible participants, the number of boys (49.80%) and girls (50.20%) was roughly equal. The mean age for boys was 13.42 (2.44), and girls have an mean age of 13.47 (2.42). Futhermore, boys exhibited a BMI of 19.65 (4.10), and girls had a BMI of 18.95 (3.21). Additionally, the CD-RISC was 65.13 (15.69) for boys and 64.66 (16.29) for girls. The results of the univariate analysis showed significant differences in depressive symptoms among different groups of participants including age, BMI, and CD-RISC in both boys and girls (Table 2). These factors were adjusted for in subsequent analyses.

Table 1

General characteristics of the 22,373 eligible participants.
	Total	Boys	Girls
Variable	M (SD) / N (%)	M (SD) / N (%)	M (SD) / N (%)
Total	22373 (100.00)	11141 (49.80)	11232 (50.20)
Personal factors
Age	13.44 (2.43)	13.42 (2.44)	13.47 (2.42)
BMI	19.29 (3.73)	19.65 (4.10)	18.95 (3.21)
CD-RISC	64.89 (15.99)	65.13 (15.69)	64.66 (16.29)
Lifestyle factors
Average daily Internet use
< 0.5h	11733 (52.44)	5670 (50.89)	6063 (53.98)
0.5-2h	6298 (28.15)	3163 (28.39)	3135 (27.91)
2-4h	2459 (10.99)	1267 (11.37)	1192 (10.61)
>4h	1883 (8.42)	1041 (9.34)	842 (7.50)
Breakfast frequency
Never	258 (1.15)	144 (1.29)	114 (1.01)
Sometimes	944 (4.22)	455 (4.08)	489 (4.35)
Often	1950 (8.72)	878 (7.88)	1072 (9.54)
Usually	4330 (19.35)	1969 (17.67)	2361 (21.02)
Everyday	14891(66.56)	7695 (69.07)	7196 (64.07)
Average weekly exercise time
<1h	5378 (24.04)	2190 (19.66)	3188 (28.38)
1-3h	10156 (45.39)	4899 (43.97)	5257 (46.80)
3-5h	3652 (16.32)	2048 (18.38)	1604 (14.28)
> 5h	3187 (14.24)	2004 (17.99)	1183 (10.53)
Average daily sleep duration
< 6h	5398 (24.13)	2318 (20.81)	3080 (27.42)
6-8h	10621 (47.47)	5356 (48.07)	5265 (46.88)
8-10h	5843 (26.12)	3150 (28.27)	2693 (23.98)
>10h	511 (2.28)	317 (2.85)	194 (1.73)
Average daily homework time
< 0.5h	2745 (12.27)	1579 (14.17)	1166 (10.38)
0.5-1h	6580 (29.41)	3281 (29.45)	3299 (29.37)
1-1.5h	5694 (25.45)	2847 (25.55)	2847 (25.35)
1.5-2h	3589 (16.04)	1650 (14.81)	1939 (17.26)
> 2h	3765 (16.83)	1784 (16.01)	1981 (17.64)
Abbreviations: BMI, Body Mass Index; CD-RISC, Connor-Davidson Resilience Scale; M, Mean; SD, Standard Deviation; N, Number.

Table 2

Prevalence of depressive symptoms of lifestyle subgroups stratified by gender.
	Total	Boys	girls
Variable	M(SD) / N (%)	M (SD) / N (%)	M (SD) / N (%)
Total	2922 (13.06)	1176 (10.56)	1746 (15.54)
Personal factors
Age	14.28 (2.02)***	14.21 (2.15)***	14.34 (1.93)***
BMI	19.93 (3.72)***	20.34 (4.31)***	19.66 (3.24)***
CD-RISC	47.69 (11.67)***	49.10 (11.43)***	46.73 (11.73)***
Lifestyle factors
Average daily Internet use	***	***	***
< 0.5h	1174 (10.01)	476 (8.40)	698 (11.51)
0.5-2h	796 (12.64)	310 (9.80)	486 (15.50)
2-4h	451 (18.34)	181 (14.29)	270 (22.65)
> 4h	501 (26.61)	209 (20.08)	292 (34.68)
Breakfast frequency	***	***	***
Never	108 (41.86)	45 (31.25)	63 (55.26)
Sometimes	338 (35.81)	137 (30.11)	201 (41.10)
Often	475 (24.36)	172 (19.59)	303 (28.26)
Usually	816 (18.85)	320 (16.25)	496 (21.01)
Everyday	1185 (7.96)	502 (6.52)	683 (9.49)
Average weekly exercise time	***	***	***
< 1h	1029 (19.13)	364 (16.62)	665 (20.86)
1-3h	1224 (12.05)	469 (9.57)	755 (14.36)
3-5h	369 (10.10)	174 (8.50)	195 (12.16)
> 5h	300 (9.41)	169 (8.43)	131 (11.07)
Average daily sleep duration	***	***	***
< 6h	1335 (24.73)	503 (21.70)	832 (27.01)
6-8h	1243 (11.70)	482 (9.00)	761 (14.45)
8-10h	290 (4.96)	158 (5.02)	132 (4.90)
< 10h	54 (10.57)	33 (10.41)	21 (10.82)
Average daily homework time	***	***	***
< 0.5h	368 (13.41)	183 (11.59)	185 (15.87)
0.5-1h	675 (10.26)	244 (7.44)	431 (13.06)
1-1.5h	653 (11.47)	259 (9.10)	394 (13.84)
1.5-2h	486 (13.54)	187 (11.33)	299 (15.42)
> 2h	740 (19.65)	303 (16.98)	437 (22.06)
Abbreviations:BMI, Body Mass Index; CD-RISC, Connor-Davidson Resilience Scale; M, Mean; SD, Standard Deviation; N, Number.
Chi-squared tests for categorical variables; Mann-Whitney U tests for continuous variables.
***p < 0.001

Lifestyle factors

The data from Table 1 indicated that the distribution of various lifestyle factors appeared to be similar between boys and girls. Approximately half of the participants spent less than 0.5 hour a day on average using the Internet. Two-thirds of participants ate breakfast every day. Nearly half of the participants spent an average of 1 hour to 3 hours exercising per week. Participants sleeping 6 hours to 8 hours per day comprised almost half. About one-third of participants took 0.5 hour to 1 hour per day to complete homework after school.

The prevalence rate of depressive symptoms was summarized in Table 2. Out of the 22,373 responding participants, 2922 (13.06%) children and adolescents had depressive symptoms. The results indicated that depressive symptoms were significantly different among different groups of lifestyles including average daily Internet use, breakfast frequency, average weekly exercise time, sleep duration, and average daily homework time. The prevalence of depressive symptoms for five lifestyle factors was compared by gender, as shown in Fig. 1. Overall, girls had a higher prevalence of depressive symptoms than boys across all lifestyles.

Results for the unadjusted model and a model adjusting for potentially confounding factors were reported in Table 3. The Nagelkerke R square values for the unadjusted and adjusted models were 0.163 and 0.404, respectively. The HosmerLemeshow test showed that the adjusted (χ2 = 3.774, p = .877) model (χ2 = 10.51, p = 0.231) had adequate fitness compared with the unadjusted model (χ2 = 25.64, p = 0.001).

Table 3

The association between lifestyle factors and depressive symptoms.
	Unadjusted	Adjusted
Variables	OR(95% CI)	AOR (95% CI)
Personal factors
Age		1.060 (1.035–1.085)***
CD-RISC		0.895 (0.891–0.899) ***
BMI
Gender
Girls vs. boys		1.475 (1.341–1.622) ***
Lifestyle factors
Average daily Internet use	***	***
> 4h vs. < 0.5h	2.038 (1.791–2.318) ***	1.416 (1.224–1.639) ***
2-4h vs. < 0.5h	1.518 (1.338–1.723) ***	1.168 (1.011–1.348)*
0.5-2h vs. < 0.5h	1.105 (0.998–1.223)	1.075 (0.959–1.205)
Breakfast frequency	***	***
Never vs. everyday	4.675 (3.570–6.122) ***	2.893 (2.121–3.946) ***
Sometimes vs. everyday	4.493 (3.855–5.237) ***	2.383 (1.998–2.841) ***
Often vs. everyday	2.702 (2.384–3.062) ***	1.659 (1.439–1.912) ***
Usually vs. everyday	2.064 (1.865–2.284) ***	1.509 (1.347–1.691) ***
Average weekly execise time	***	**
> 5h vs. < 1h	0.682 (0.589–0.790) ***	1.130 (0.958–1.334)
3-5h vs. < 1h	0.630 (0.551–0.721) ***	0.798 (0.685–0.930)**
1-3h vs. < 1h	0.735 (0.667–0.809) ***	0.937 (0.840–1.045)
Average daily sleep duration	***	***
> 10h vs. < 6h	0.502 (0.371–0.679) ***	0.719 (0.513–1.008)
8-10h vs. < 6h	0.253 (0.220–0.290) ***	0.406 (0.346–0.477) ***
6-8h vs. < 6h	0.477 (0.436–0.522) ***	0.612 (0.552–0.678) ***
Average daily homework time	***	***
> 2h vs. < 0.5h	1.572 (1.359–1.819) ***	1.751 (1.487–2.062) ***
1.5-2h vs. < 0.5h	1.154 (0.988–1.348)	1.334 (1.119–1.590) **
1-1.5h vs. < 0.5h	1.006 (0.869–1.165)	1.164 (0.988–1.373)
0.5-1h vs. < 0.5h	0.900 (0.779–1.041)	1.066 (0.906–1.255)
Abbreviations: BMI, Body Mass Index; CD-RISC, Connor-Davidson Resilience Scale; OR, Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval.
Unadjusted: Unadjusted binary logistic regression model. Including lifestyle factors (Internet use, breakfast, exercise, sleep and homework).
Adjusted: Adjusted binary logistic regression model. The model were adjusted for age, BMI, CD-RISC and gender.
95% CI: If the 95% CI contains 0 then estimate is nonsignificant at 0.05 level.
p < 0.05;p < 0.01; **p < 0.001

After adjusting for the potential confounders, spending too much time using the internet (more than 2 hours per day), skipping breakfast, and spending too much doing homework (more than 1.5 hours) were found to be significantly associated with a higher risk of depressive symptoms in binary logistic regression analysis. Protective factors independently associated with depressive symptoms included proper sleep duration (6 hours to 10 hours per day) and exercise (3 hours to 5 hours per week). In more detail, if participants spent more than 2 hours online, the risk of depressive symptoms increased with time. The odds of having depressive symptoms were 41.6% higher among participants using the Internet for more than 4 hours (AOR = 1.416, 95%CI = 1.224–1.639), as compared with participants using the Internet for less than 0.5 hour. Skipping breakfast was a strong risk factor for depressive symptoms and the risk increased with the frequency of skipping. The odds of having depressive symptoms were 1.893 times higher among participants who never had breakfast (AOR = 2.893, 95%Cl = 2.121–3.946) than participants who ate breakfast every day. It is worth mentioning that exercising for 3 hours to 5 hours (AOR = 0.798, 95%Cl = 0.685–0.930) per week was a protective factor for depressive symptoms in comparison to only exercising for 1 hour. As for sleep duration per day, compared with sleeping more than 6 hours, participants sleeping 8 hours to 10 hours (AOR = 0.406, 95%CI = 0.346–0.477) were the least likely to experience depressive symptoms. When spending more than 1.5 hours on homework, the risk of depressive symptoms increased with longer periods of daily average time to complete homework after school.

Gender differences in the risk of depressive symptoms by lifestyle were demonstrated in Fig. 2, additional data was given in Online Resource 1. All five lifestyle factors were significant in girls, while only three factors (including sleep, breakfast, and homework) were significant in boys. Therefore, exercise and Internet use were considered to be gender-dependent relative risk factors. In particular, only 3 hours to 5 hours of exercise (AOR = 0.803, 95%CI = 0.648–0.996) was a protective factor for girls. Additionally, daily homework time of more than 1.5 hours was a risk factor for depressive symptoms in girls, while spending more than 2 hours on homework was associated with depressive symptoms in boys. Thus, girls were more likely to be influenced by the time they spent doing homework.

In our study, after controlling for potential confounding factors, lifestyle factors including Internet use, breakfast, exercise, sleep, and homework were significantly associated with depressive symptoms. Internet use and exercise were gender-related predictors of depressive symptoms, being significant only in girls. These findings implied that possibly complex mechanisms may exist between lifestyle and depressive symptoms in children and adolescents.

Skipping breakfast was the most meaningful impact factor of depressive symptoms in this study. The prevalence of depressive symptoms in children and adolescents increased with breakfast skipping frequency. Recent studies also reported a similar positive association between skipping breakfast and depressive symptoms [33, 34]. Moreover, Lars Lien found that the association was stronger for boys than girls, even after adjusting for possible confounding factors [35]. The observed gender disparities might be attributed to variations in breakfast quality, sample size, and environmental or cultural influences. It was well known that girls tended to show more body image distortions than boys in children and adolescents [36]. The heightened self-consciousness about their body shape in girls led them to intentionally reduce the quantity and quality of food [37]. In fact, consuming a nutritious breakfast containing grain-based and dairy products have shown to be associated with lower scores of depressive symptoms [38]. Differences in the results highlighted the need for further research in this area to shed light on the relationship between breakfast consumption and depressive symptoms, and why gender differences existed. Although there were no well-established mechanisms to explain why breakfast frequency may affect depression, having a healthy and regular breakfast might be considered an effective approach to prevent depression [39].

Internet use was pervasive among teenagers. This study demonstrated the risk of developing depressive symptoms increased with time spending more than 2 hours on the internet. The result was consistent with the research conducted by Mingli Liu et al [40]. Recently, in a longitudinal study of adolescents, researchers found that high use of mobile phones at baseline was correlated with a high level of depression at one year [41]. Excessive use of mobile phones replaced face-to-face contact would inevitably lead to subsequent social isolation and ultimately have depressive symptoms [42]. However, results from studies investigating the effect of internet use on mental health have been inconclusive [43]. Thom et al. found no relationship between internet use and depression in healthy adolescents [44]. The difference in findings could be illustrated by the fact that the authors' data were collected in 2009. In the past few years, due to the increasing popularity and affordability of handheld devices such as smartphones and tablets, internet use has become more common than ever before. Furthermore, the reliability and generality of the results were also limited by the small sample size. Given the differences in research results and quality, further research on the relationship and potential mechanisms of Internet use and depressive symptoms must be done.

Our study found that about a quarter of children and adolescents slept less than 6 hours per day on average, and 24.73% of them developed depressive symptoms. Due to the decreasing sleep time of children and adolescents worldwide [45], a series of negative consequences brought out by the lack of sleep have aroused widespread concern. 6 hours of sleep or less was defined as short sleep duration or deprivation in earlier studies [46] and would increase the risk of depressive symptoms significantly [47]. The possible mechanism for the relationship between short sleep duration and depressive symptoms was that short sleep duration led to alterations in the hypothalamic-pituitary-adrenal (HPA) axis [48], and sensitization of the HPA axis would contribute to the onset of depression [49]. Notably, a large cross-sectional study from Japan also found a U-shaped relationship between sleep duration and depressive symptoms in adolescents [50], suggesting that an optimal sleep duration against depressive symptoms may exist. In Japan, the lowest risk of depression was 7.5 to 8.5 hours of sleep for girls and 8. 5 to 9.5 hours of sleep for boys [51]. Similarly, in our study, the lowest risk of having depressive symptoms was found in both girls and boys who slept 8 hours to 10 hours.

Approximately 80% of adolescents worldwide had not met the minimum recommended guidelines for moderate-to-vigorous physical exercise [52]. Additionally, girls were less physically active than boys [53, 54]. Our study confirmed the gender differences in exercise levels and further found that engaging in exercise for 3 hours to 5 hours per day was a protective factor for depressive symptoms. There was also promising evidence that exercise could be utilized for the prevention and treatment of depressive symptoms [55]. A study found that any level of physical activity, even low levels such as walking less than 2.5 hours per week, could prevent future depression [56]. Furthermore, findings from some other studies suggested that increasing levels of physical activity may have beneficial effects on depressive symptoms in children and adolescents [57, 58]. Interestingly, in our study, girls who exercised for more than 5 hours had an increased risk of depressive symptoms, while there was no significant difference between exercise duration and depressive symptoms in boys. Besides, research had shown that physical activity, especially organized team sports, had a greater relief on depressive symptoms in girls [59] and was able to provide more mental health benefits [57]. This suggested that girls, in particular, should be encouraged to participate in appropriate levels of physical activity.

Spending excessive time on homework was also considered as a risk factor for depressive symptoms. When homework lasted longer than 1.5 hours, the likelihood of developing depressive symptoms increased with time. Asian countries placed a greater emphasis on academic achievement, resulting in children and adolescents in Asia facing higher academic pressure and exhibiting higher rates of depressive symptoms [60]. Particularly in China, children and adolescents encountered intense academic pressure [61] and were burdened with heavy homework loads [62]. The excessive academic load led to emotional changes in students, which in turn easily contributed to the development of depressive symptoms in the long term [63]. Previous studies have demonstrated that adolescents who spent longer time on homework tended to have later bedtimes and shorter nocturnal sleep [64–66], ultimately experiencing more school-related stress [67]. In this study, it was found that spending more than 1.5 hours and 2 hours on homework respectively posed a risk for depressive symptoms in girls and boys. Therefore, more attention should be paid to children and adolescents, especially girls, to avoid these negative outcomes. To alleviate the academic burden on these students, the Chinese government has implemented the “double reduction” policy since September 1st, 2021, which has reduced the prevalence of depressive symptoms to a certain extent [68].

In summary, this study provided additional evidence on the impact of gender differences and lifestyle factors on depression in Chinese children and adolescents. We not only observed a significant association between unhealthy lifestyles and depressive symptoms, but we also identified two gender-related lifestyle factors including Internet use and time spent on exercise. In light of the above findings and to prevent the occurrence of depressive symptoms, we recommend that schools, families, and public health institutions implement effective multidisciplinary health interventions to increase their awareness, especially among girls, about the adverse effects of unhealthy lifestyles and depressive symptoms.

Strengths and Limitations

Strengths of the study include a large number of participants recruited at random and assessed using standardized diagnostic and symptom rating tools. We considered the lifestyle as a whole to explore its impact on depressive symptoms. This provided new insights for the prevention of depressive symptoms and new evidence for the improvement of depressive symptoms through adopting a healthy lifestyle in the future.

However, this study has several limitations. Firstly, due to the nature of our variables, we did not further verify the interrelationships between the five factors we studied. Additionally, we did not explore how Internet use, breakfast, exercise, sleep, and homework combined to correlate with better mental health. Secondly, we only conducted a preliminary study on the five lifestyle factors in terms of time or frequency, without a comprehensive examination of detailed study on each factor to reflect the relationship comprehensively and systematically between different lifestyles and depressive symptoms. For instance, in addition to breakfast frequency, breakfast quality was also an important factor affecting depressive symptoms [38]. We plan to include more lifestyle factors that may affect depressive symptoms in our future studies and use more comprehensive questionnaires or scales to collect a broader range of information about participants' daily lifestyles, so as to further study the relationship between lifestyle and mental health.

We found that skipping breakfast, spending more than 2 hours on the Internet, and spending more than 1.5 hours on homework were risk factors for depressive symptoms. Sleeping 6 hours to 10 hours and exercising 3 hours to 5 hours, on the other hand, were protective factors for depressive symptoms. In general, girls exhibited a higher prevalence of depressive symptoms compared to boys in all lifestyle factors. Additionally, exercise and internet use were gender-related predictors of depressive symptoms and were significant in girls. In order to prevent depression, families and schools should attach great importance to these lifestyles.

Ethics approval

This study have been approved and consented by the Ethics Committee of Chongqing Medical University and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments..

Conflict of interest

The authors declare that they have no conflict of interest.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish

Patients signed informed consent regarding publishing their data.

Funding

The work was supported by the STI2030-Major Projects (2022ZD0212900) and National Natural Science Foundation of China (83371565).

Availability of data and materials

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

Authors' contributions

Rong Liu designed the study, analyzed and interpreted the data and was a major contributor in writng the manuscript. Qian LYU designed the study, interpreted the data and drafted the manuscript. Xinyue Liu visualized the data and reviewed the manuscript. Yaru Zou collected and collated the data and reviewd the manuscript. Jiaxiu Liu analysed the data and reviewed the manuscript. Yanjie Yu designed the study and made a critical revision of manuscript for intellectual content. Xinyu Zhou made a critical revision of manuscript for intellectual content. All authors read and approved the final manuscript.

Acknowledgments

The authors thank all the children and adolescents who participated in the study sincerely.

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Online Resource 1 Risk of depressive symptoms in boys and girls in five different lifestyle factors. Abbreviations: BMI, Body Mass Index; CD-RISC, Connor-Davidson Resilience Scale; AOR, Adjusted Odds Ratio; CI, Confidence Interval; VIF, Variance Inflation Factor. 95% CI: If the 95% CI contains 0 then estimate is nonsignificant at 0.05 level. Logistic models were adjusted for age, BMI, and CD-RISC.

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Effects of gender differences and lifestyle factors on depression among Chinese children and adolescents

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