Relationship of screen time and dietary behaviors with depressive symptoms in junior high school students in five provinces in China

doi:10.3969/j.issn.1674-8115.2024.03.008

Abstract

Abstract:

Objective ·To explore the relationship of screen time and dietary behaviors with depressive symptoms in junior high school students in 5 provinces in China. Methods ·A total of 1 067 junior high school students were selected from Zhejiang and Guangdong in the eastern region, Jiangxi in the central region, Sichuan and Guizhou in the western region of China by using stratified random cluster sampling method for a questionnaire survey, which included general demographic characteristics, health behaviors, diatery behaviors, and depressive symptoms. Univariate analysis was used to analyze the report rates of depressive symptoms, daily screen time and dietary behaviors of the students with variant demographic characteristics, and Logistic regression analysis was used to analyze the relationship of daily screen time and dietary behaviors with depressive symptoms and the interaction effects as well. Results ·The report rate of depressive symptoms was 12.9% in the junior high school students in 5 provinces. The students who were in the western region, were not only children, had a weekly allowance of over 100 yuan, had smoked or consumed alcohol, had daily screen time≥2 h, or had unhealthy dietary behaviors, had higher reporting rates of depressive symptoms (P<0.05). A total of 15.2% students had daily screen time≥2 h, who had a higher reporting rate of depressive symptoms than the others after the confounding factors being adjusted (OR=1.89, 95%CI 1.22?2.95). A total of 29.5% of students had unhealthy dietary behaviors, who had a higher reporting rate of depressive symptoms than the others after the confounding factors being adjusted (OR=2.16, 95%CI 1.47?3.19). A total of 6.4% of students had both daily screen time≥2 h and unhealthy dietary behaviors, who had a higher reporting rate of depressive symptoms than the students having daily screen time<2 h and healthy dietary behaviors after the confounding factors being adjusted (OR=4.26, 95%CI 2.24?7.56). After adjusting for the confounding factors, the analysis of the interaction between daily screen time and dietary behaviors showed an additive interaction with the relative excess risk due to interaction (RERI) of 1.21 (95%CI 1.02?1.51), the attributable proportion due to interaction (AP) of 0.19 (95%CI 0.13?0.31), and the synergy index (S) of 1.35 (95%CI 1.12?1.69). Conclusion ·The junior high school students with both long screen time and unhealthy dietary behaviors are more likely to suffer from depressive symptoms in China; long screen time and unhealthy dietary behaviors have an additive interactive effect on depressive symptoms.

Key words: middle school student, screen time, dietary behavior, depressive symptom

CLC Number:

R195.4

YANG Ruijun, LÜ Shuhong, LIU Zhiye, ZHANG Xin, LIU Zhihao. Relationship of screen time and dietary behaviors with depressive symptoms in junior high school students in five provinces in China[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2024, 44(3): 358-364.

Figures/Tables 3

TrendMD

References 27

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Factor	Sample size/n	Depressive symptoms/n(%)	χ² value	P value
Total	1 067	138 (12.9)
Area			18.177	0.000
East	406	34 (8.4)
Middle	283	34 (12.0)
West	378	70 (18.5)
Residence			2.469	0.116
Urban	422	63 (14.9)
Rural	645	75 (11.6)
Grade			0.008	0.930
7	252	33 (13.1)
8	815	105 (12.9)
Gender			0.426	0.514
Male	560	76 (13.6)
Female	507	62 (12.2)
Only child^①			4.291	0.038
Yes	319	31 (9.7)
No	737	106 (14.4)
Resident student^①			2.163	0.141
Yes	605	86 (14.2)
No	457	51 (11.2)
Weekly allowance^①			17.186	0.002
None	264	20 (7.6)
1‒10 yuan	209	20 (9.6)
11‒50 yuan	383	63 (16.4)
51‒100 yuan	156	24 (15.4)
>100 yuan	51	11 (21.6)
Smoking behavior^①			17.095	0.000
Yes	59	18 (30.5)
No	1 007	120 (11.9)
Drinking behavior^①			15.793	0.000
Yes	277	55 (19.9)
No	788	83 (10.5)
Daily screen time			18.783	0.000
<2 h	905	100 (11.1)
≥2 h	162	38 (23.5)
Healthy dietary behaviors			31.595	0.000
Yes	752	69 (9.2)
No	315	69 (21.9)
Daily exercise time			2.589	0.108
<1 h	428	64 (15.0)
≥1 h	639	74 (11.6)

Factor	Sample size/n	Depressive symptoms/n(%)	χ² value	P value
Total	1 067	138 (12.9)
Area			18.177	0.000
East	406	34 (8.4)
Middle	283	34 (12.0)
West	378	70 (18.5)
Residence			2.469	0.116
Urban	422	63 (14.9)
Rural	645	75 (11.6)
Grade			0.008	0.930
7	252	33 (13.1)
8	815	105 (12.9)
Gender			0.426	0.514
Male	560	76 (13.6)
Female	507	62 (12.2)
Only child^①			4.291	0.038
Yes	319	31 (9.7)
No	737	106 (14.4)
Resident student^①			2.163	0.141
Yes	605	86 (14.2)
No	457	51 (11.2)
Weekly allowance^①			17.186	0.002
None	264	20 (7.6)
1‒10 yuan	209	20 (9.6)
11‒50 yuan	383	63 (16.4)
51‒100 yuan	156	24 (15.4)
>100 yuan	51	11 (21.6)
Smoking behavior^①			17.095	0.000
Yes	59	18 (30.5)
No	1 007	120 (11.9)
Drinking behavior^①			15.793	0.000
Yes	277	55 (19.9)
No	788	83 (10.5)
Daily screen time			18.783	0.000
<2 h	905	100 (11.1)
≥2 h	162	38 (23.5)
Healthy dietary behaviors			31.595	0.000
Yes	752	69 (9.2)
No	315	69 (21.9)
Daily exercise time			2.589	0.108
<1 h	428	64 (15.0)
≥1 h	639	74 (11.6)

Factor	Sample size/n	Daily screen time≥2 h/n(%)	χ² value	P value	Unhealthy dietary behaviors/n(%)	χ² value	P value
Total	1 067	162 (15.2)			315 (29.5)
Area			18.551	0.000		90.119	0.000
East	406	40 (9.9)			63 (15.5)
Middle	283	43 (15.2)			77 (27.2)
West	378	79 (20.9)			175 (46.3)
Residence			5.201	0.023		27.806	0.000
Urban	422	51 (12.1)			163 (38.6)
Rural	645	111 (17.2)			152 (23.6)
Grade			5.116	0.024		1.089	0.297
7	252	27 (10.7)			81 (32.1)
8	815	135 (16.6)			234 (28.7)
Gender			2.905	0.088		0.969	0.325
Male	560	95 (17.0)			158 (28.2)
Female	507	67 (13.2)			157 (31.0)
Only child^①			0.310	0.578		19.389	0.000
Yes	319	51 (16.0)			64 (20.1)
No	737	108 (14.7)			247 (33.5)
Resident student^①			0.665	0.415		22.238	0.000
Yes	605	87 (14.4)			213 (35.2)
No	457	74 (16.2)			100 (21.9)
Weekly allowance^①			7.631	0.106		32.124	0.000
None	264	36 (13.6)			57 (21.6)
1‒10 yuan	209	28 (13.4)			41 (19.6)
11‒50 yuan	383	53 (13.8)			142 (37.1)
51‒100 yuan	156	34 (21.8)			57 (36.5)
>100 yuan	51	10 (19.6)			15 (29.4)
Smoking behavior^①			17.207	0.000		20.882	0.000
Yes	59	20 (33.9)			33 (55.9)
No	1 007	141 (14.0)			282 (28.0)
Drinking behavior^①			27.976	0.000		16.271	0.000
Yes	277	69 (24.9)			108 (39.0)
No	788	92 (11.7)			206 (26.1)
Daily exercise time			2.464	0.117		28.004	0.000
<1 h	428	74 (17.3)			165 (38.6)
≥1 h	639	88 (13.8)			150 (23.5)

Factor	Sample size/n	Daily screen time≥2 h/n(%)	χ² value	P value	Unhealthy dietary behaviors/n(%)	χ² value	P value
Total	1 067	162 (15.2)			315 (29.5)
Area			18.551	0.000		90.119	0.000
East	406	40 (9.9)			63 (15.5)
Middle	283	43 (15.2)			77 (27.2)
West	378	79 (20.9)			175 (46.3)
Residence			5.201	0.023		27.806	0.000
Urban	422	51 (12.1)			163 (38.6)
Rural	645	111 (17.2)			152 (23.6)
Grade			5.116	0.024		1.089	0.297
7	252	27 (10.7)			81 (32.1)
8	815	135 (16.6)			234 (28.7)
Gender			2.905	0.088		0.969	0.325
Male	560	95 (17.0)			158 (28.2)
Female	507	67 (13.2)			157 (31.0)
Only child^①			0.310	0.578		19.389	0.000
Yes	319	51 (16.0)			64 (20.1)
No	737	108 (14.7)			247 (33.5)
Resident student^①			0.665	0.415		22.238	0.000
Yes	605	87 (14.4)			213 (35.2)
No	457	74 (16.2)			100 (21.9)
Weekly allowance^①			7.631	0.106		32.124	0.000
None	264	36 (13.6)			57 (21.6)
1‒10 yuan	209	28 (13.4)			41 (19.6)
11‒50 yuan	383	53 (13.8)			142 (37.1)
51‒100 yuan	156	34 (21.8)			57 (36.5)
>100 yuan	51	10 (19.6)			15 (29.4)
Smoking behavior^①			17.207	0.000		20.882	0.000
Yes	59	20 (33.9)			33 (55.9)
No	1 007	141 (14.0)			282 (28.0)
Drinking behavior^①			27.976	0.000		16.271	0.000
Yes	277	69 (24.9)			108 (39.0)
No	788	92 (11.7)			206 (26.1)
Daily exercise time			2.464	0.117		28.004	0.000
<1 h	428	74 (17.3)			165 (38.6)
≥1 h	639	88 (13.8)			150 (23.5)

Factor	Model 1		Model 2		Model 3
Factor	OR (95%CI)	P value	OR (95%CI)	P value	OR (95%CI)	P value
Daily screen time
<2 h	1.00		1.00
≥2 h	2.47 (1.62‒3.75)	0.000	1.89 (1.22‒2.95)	0.005
Healthy dietary behaviors
Yes	1.00				1.00
No	2.78 (1.93‒4.01)	0.000			2.16 (1.47‒3.19)	0.000