Association of screen time-based sedentary behavior and the risk of depression in children and adolescents: Dose-response meta-analysis

Zou, Zhichun; Xiang, Jianfeng; Wang, Huimin; Wen, Quan; Luo, Xiao

doi:10.15761/0101-60830000000314

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Original Article • Arc. Clin. Psychiatr. 48 (6) • Nov-Dec 2021 • https://doi.org/10.15761/0101-60830000000314 linkcopy

Association of screen time-based sedentary behavior and the risk of depression in children and adolescents: Dose-response meta-analysis

Authorship SCIMAGO INSTITUTIONS RANKINGS

Purpose: We aimed to find the association between screen time (ST)-based sedentary behavior and depression in children and adolescents.

Methods: PubMed, Embase, and Web of science database were searched to find eligible studies until April 25, 2021. Data extraction was conducted by two investigators independently, followed by quality assessment for included studies. Odd ration (OR) and 95% confidence intervals (CI) were regarded as effect size index. Heterogeneity test was conducted using Cochran’ s Q test and I² test. Least squares trend estimation method was used for dose-response meta-analysis. All statistical analyses were conducted using Stata12.0 software.

Results: Totally 22 articles containing 197,673 cases were included. The pooled results displayed that there was a significant positive correlation between ST and depression [OR (95%CI) = 1.24 (1.11, 1.38), P < 0.001]. Similar results were observed for watching television (TV), computer use (CU), computer game (CG)/video game (VG) and internet use (IU)/mobile phone (MP) time. Dose-response meta-analysis showed that take 1 hour/day as control, the risk of depression went down and then went up as sedentary time increased for ST (P > 0.05). The risk of depression was significantly increased when TV time beyond 4.5 hours/day (P < 0.05), or CU time beyond 0.5 hours/day (P < 0.05), or CG/VG time beyond 2 hours/day (P < 0.05), or IU/MP time beyond 0.5 hours/day (P < 0.05).

Conclusion: ST-based sedentary behavior was associated with the risk of depression in a non-linear dose–response manner for children and adolescents.

Keywords:
Depression; screen time; children and adolescents; dose-response meta-analysis

Study	Area, Survey time	Type of study	n, M/F	Age, years	Screen-time (hrs/day): style; categories	Depression measure; cutoff	Adjustment for confounders
Bélanger et al. [²⁴]	Switzerland, 2002	CSS	7211, 3905/3306	17.91±2.11	CU; 0, 0-<1, 1-≤2, >2	DTS. Cutoff: NR	Age; academic track; socioeconomic status; chronic condition; PA
Cao et al. [²⁵]	China, 2010	CSS	5003, 2606/2397	13.2±1.0	ST (TV/CU); <2, >2	DSRSC. Cutoff : 15	Gender, grade, family type, perceived socioeconomic status, BMI, fruit and vegetable intake, and fizzy drinks intake
Cao et al. [²⁶]	China, 2018	CSS	4178, 1946/2232	14.25±1.77	ST (TV/VG/CU/MP); <2, >2	CES-D. Cutoff: 16	Gender, age, living in school dormitory accommodation, school type and perceived socioeconomic status
Casiano[¹⁶]	Canada, 2000-2001	CSS	9137, 4544/4593	12-19	TV, VG, CU; 0, <1/7, <1/3, 0.4-0.7, 0.8-1.4, 1.5-2, 2-3, ≥3	CIDI short form. Cutoff: 0.90	Household income; gender
da Costa, et al. [²⁷]	Brazil, 2019	CSS	610, 295/315	16.33±1.4	TV, VG, MP; <2, 2-4, ≥4	CES-D. Cutoff: 20	Sex, age, weight status, and socioeconomic status
Godinho, et al. [²⁸]	Portugal, 2003-2004	CSS	1680, 796/884	13	ST (≤2, 2-3, >3); TV (≤1, 1-2, >2); CU (≤2, >2)	BDI-II. Cutoff: 13	Living with both parents, Parents’ age, Type of school, Repeated school year, Sleep duration, Ever smoke, Frequency of PA, BMI
Grøntved et al. [²⁹]	Denmark, 2009-2010	PCS	435, 203/232	15.6±0.4	ST, TV (0-1, 1-3, >3); CU (0-1, 1-3)	MDI scale. Cutoff: 20	Age, BMI and CRF, follow-up time, sex, parental education level, parentalmarital status, smoking status, and alcohol intake in adolescence
Hoare et al. [³⁰]	Australia, 2012	CSS	800, 360/440	13.1±0.6	ST (TV/VG/CU); ≤2, >2	SMFQ. Cutoff: 10.	Age, PA, weight status, fruit and vegetable, sweet drink, takeaway food consumption over a month period, parents’ level of education, and school
Hoare, et al. [³¹]	Australia, 2013-2014	CSS	2967, 1530/1437	14.6±2.0	IU; ≤2, 2-6, ≥7	DISC-IV. Cutoff: NR	Age, relative level of socio-economic disadvantage and BMI
Hong et al. [³²]	China, 2004	CSS	2444, 1180/1264	13.85±1.04	TV; Low, middle, high	CDI. Cut-off: 20	Age; gender; school grade; BMI; study time; sleep time; smoking; alcohol; unintentional injuries; parents’ education, parents’ job; family structure
Hrafnkelsdottir et al. [³³]	Iceland, 2015	CSS	244, 100/144	15.8±0.3	ST (CG,TV, IU, CU) <5.3, ≥5.3	SCL-90. Cut-off: 30	Sex, body fat percentage and maternal education
Kim et al. [³⁴]	Korea, 2009	CSS	75066, 39612/35454	12-18	CU; 0, 0-<1, 1-≤2, >2	Self-reported	Age, residing region, type of school, subjective academic performance status, subjective economic status, presence of parents, family lives together and sedentary behavior in weeks and weekend
Kremer et al. [³⁵]	Australia, 2006	CSS	8029, 3852/4177	11.5±0.8	ST (TV/VG/CU): <2, ≥2	SMFQ. Cut-off: ≥8	Location and area- socioeconomic status
Lee et al. [³⁶]	USA, 2015	CSS	15624, 8015/7609	High school students	VG; 0, <1, 1, 2, 3, 4, ≥5	Self-reported	Crude
Leung et al. [³⁷]	USA, 2018	CSS	10794, 5710/5084	13-17	TV; <1, 1, 2, 3, ≥4	Doctor or health professional	Sex, age, poverty level, insurance type, parent education, language spoken at home, race/ethnicity, household generation, family structure, comorbid conditions, and emotional/behavior medications
Lim et al. [³⁸]	Korea, 2008	CSS	920, 633/287	15-17	IU; 0-1, 1-3, >3	CES-D. Cutoff: 24	Sex, age, PA, BMI, Perception on body image, Figure satisfaction
Liu et al. [³⁹]	China, 2015	CSS	11831, 5813/6018	15.0±1.5	MP; <1, 1-2, ≥2 (weekday)/<2, 2-<4, 4-<5, ≥5 (weekend)	CES-D. Cut-off:>90th percentile	Age, gender, chronic disease, smoking, alcohol use, school, family factors, weekday sleep duration, and insomnia
Mridha et al. [¹⁸]	Bangladesh, 2018-2019	CSS	9569, 4761/4808	10-19	TV; 0, 0-<1, 1-≤2, >2	PHQ-9. Cut-off: ≥5	Age, residence, educational status, maternal/paternal education and occupation, religion, household size, household member, tobacco use, Fruits and vegetables intake, Processed food intake, Consumption of fortified oil, Consumption of iodised salt, PA, Weight.
Primack et al. [²²]	USA, 1994-2002	PCS	4142, 2145/1967	Grade 7-12	TV, CG; hours per day	CES-D; Cut-off: 24 (F), 22 (M).	Baseline CES-D score; age; gender; race/ethnicity; socioeconomic status; ever married; educational achievement of at least graduation from high school
Twenge et al. [¹⁷]	UK, 2015	CSS	11427, 5720/5707	13.77±0.45	TV, CG, IU; <1, 1-<2, 2-<5, ≥5	SMFQ. Cut-off: 12.	Age, family income, natural father present, ethnicity, the age the primary caregiver left formal education, primary caregiver’s employment, number of siblings in household, longstanding illness, and the primary caregiver’s vocabulary word score
Wang et al. [²³]	China, 2017	CSS	1062, 576/486	15.38±1.74	ST (TV/VG/CU); ≤2, >2	SDS. Cutoff: 0.6	Grade, health status, family economic situation
Xu et al. [⁴⁰]	China, 2017-2018	CSS	14500, 7347/7153	14.9±1.8	ST (TV/CU/MP); 0, <1, 1-2, 2-3, 3-4, 4-5, >5	CDI. Cut-off: 19.	Age, Grade, Residence, The only child in the family, Boarding school, Father/mother's education level, Self-perceived socioeconomic status, The number of close friend

Study	Type of study	Source of population	Measurement for screen time	Measurement for depression	Methods to control confounding	Deal with any design-specific issues#	Appropriate statistical methods (excluding control of confounding)	Quality score
Bélanger et al. [²⁴]	CSS	1	1	1	0	0	1	4
Cao et al. [²⁵]	CSS	1	1	1	1	0	1	5
Cao et al. [²⁶]	CSS	1	1	1	0	0	1	4
Casiano [¹⁵]	CSS	1	1	1	0	1	1	5
da Costa, et al. [²⁷]	CSS	0	1	1	1	0	1	4
Godinho, et al. [²⁸]	CSS	0	1	1	1	0	1	4
Grøntved et al. [²⁹]	PCS	1	1	1	1	0	1	5
Hoare et al. [³⁰]	CSS	0	1	1	1	0	1	4
Hoare et al. [³¹]	CSS	0	1	1	1	0	1	4
Hong et al. [³²]	CSS	1	1	1	0	1	1	5
Hrafnkelsdottir et al. [³³]	CSS	1	1	1	0	0	1	4
Kim et al. [³⁴]	CSS	1	1	0	1	0	1	4
Kremer et al. [³⁵]	CSS	0	1	1	1	0	1	4
Lee et al. [³⁶]	CSS	0	1	1	0	0	1	3
Leung et al. [³⁷]	CSS	0	1	1	1	0	1	4
Lim et al. [³⁸]	CSS	1	1	1	0	0	1	4
Liu et al. [³⁹]	CSS	1	1	1	1	0	1	5
Mridha et al. [¹⁸]	CSS	1	1	1	1	0	1	5
Primack et al. [²²]	PCS	1	1	1	1	1	1	6
Twenge et al. [¹⁷]	CSS	1	1	1	1	0	1	5
Wang et al. [²³]	CSS	0	1	1	0	1	1	4
Xu et al. [⁴⁰]	CSS	1	1	1	0	0	1	4

Model			No. of studies	Heterogeneity test		Effect size
Model			No. of studies	I² (%)	P_H	OR (95% CI)	P value
ST			11	72.4	<0.001	1.24 (1.11: 1.38)	<0.001
Area
		Asian	4	87.7	<0.001	1.28 (1.05: 1.56)	0.013
	Australia		3	0	0.636	1.15 (1.06: 1.24)	0.001
	European		4	67.2	0.027	1.71 (0.91: 3.22)	0.096
Study design
	CSS		10	73.0	<0.001	1.23 (1.10: 1.37)	<0.001
	PCS		1	NA	NA	3.46 (0.96: 12.47)	0.058
Gender
	Mixed		7	81.8	<0.001	1.34 (1.11: 1.63)	0.03
	Female		2	0	0.344	1.11 (1.01: 1.22)	0.26
	Male		2	0	0.466	1.24 (1.07: 1.43)	0.05
Multivariate analysis
		Yes	10	74.6	<0.001	1.26 (1.13: 1.41)	<0.001
	No		1	NA	NA	0.91 (0.59: 1.39)	0.656
TV			12	87.5	<0.001	1.38 (1.16: 1.64)	<0.001
Area
		Asian	3	70.3	0.035	1.72 (1.31: 2.25)	<0.001
	American		4	82.2	0.001	1.12 (0.94: 1.34)	0.195
	European		5	58.3	0.048	1.30 (0.97: 1.74)	0.074
Study design
	CSS		10	89.0	<0.001	1.40 (1.10: 1.79)	0.006
	PCS		2	78.2	0.032	1.86 (0.49: 7.07)	0.360
Gender
	Mixed		6	78.9	<0.001	1.19 (1.00: 1.41)	0.050
	Female		3	85.8	0.001	1.37 (0.92: 2.05)	0.122
	Male		3	41.7	0.180	1.61 (1.23: 2.11)	0.001
Multivariate analysis
		Yes	11	88.3	<0.001	1.44 (1.20: 1.72)	<0.001
	No		1	NA	NA	0.78 (0.49: 1.23)	0.283
CU			8	80.9	<0.001	1.41 (1.14: 1.74)	0.002
Area
		Asian	2	76.6	0.039	1.55 (1.11: 2.16)	0.010
	European		5	0	0.449	1.51 (1.25: 1.82)	<0.001
	American		1	NA	NA	1.03 (0.96: 1.10)	0.395
Study design
	CSS		7	83.5	<0.001	1.41 (1.13: 1.76)	0.002
	PCS		1	NA	NA	1.42 (0.56: 3.59)	0.459
Gender
	Mixed		2	0	0.499	1.03 (0.96: 1.10)	0.366
	Female		3	0	0.938	1.83 (1.51: 2.22)	<0.001
	Male		3	0	0.699	1.32 (1.14: 1.52)	<0.001
Multivariate analysis
		Yes	8	80.9	<0.001	1.41 (1.14: 1.74)	0.002
	No		0	NA	NA	NA	NA
CG/VG			7	96.2	<0.001	1.44 (1.02: 2.05)	0.038
Area
		European	2	68.1	0.077	1.57 (1.15: 2.14)	0.004
	American		5	97.4	<0.001	1.39 (0.88: 2.19)	0.154
Study design
	CSS		6	96.7	<0.001	1.53 (1.01: 2.31)	0.044
	PCS		1	NA	NA	1.04 (0.89: 1.22)	0.626
Gender
	Mixed		3	60.0	0.082	0.97 (0.82: 1.15)	0.723
	Female		2	94.8	<0.001	1.82 (1.04: 3.16)	0.035
	Male		2	0	0.963	1.86 (1.59: 2.17)	<0.001
Multivariate analysis
		Yes	5	88.5	<0.001	1.21 (0.93: 1.58)	0.151
	No		2	78.1	0.033	2.12 (1.65: 2.73)	<0.001
IU/MP			7	36.9	0.147	1.90 (1.62: 2.21)	<0.001
Area
		Asian	2	0	0.488	1.73 (1.53: 1.96)	<0.001
	European		2	73.6	0.052	2.19 (1.45: 3.29)	<0.001
	Australia		2	0	0.733	1.75 (1.27: 2.42)	0.001
		American	1	NA	NA	1.67 (1.10: 2.54)	0.016
Study design
	CSS		7	36.9	0.147	1.90 (1.62: 2.21)	<0.001
	PCS		0	NA	NA	NA	NA
Gender
	Mixed		3	0	0.775	1.73 (1.54: 1.94)	<0.001
	Female		2	57.1	0.127	2.28 (1.59: 3.27)	<0.001
	Male		2	0	0.823	1.72 (1.30: 2.27)	<0.001
Multivariate analysis
		Yes	7	36.9	0.147	1.90 (1.62: 2.21)	<0.001
	No		0	NA	NA	NA	NA

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[TFN1] NR: not reported; CSS: cross-sectional study; PCS: prospective cohort study; ST: screen time; VG: video game; TV: television viewing; IU: internet use; CU: computer use; CG: computer game; MP: mobile phone; F: female; M: male; BM: body mass index; CRF: cardiorespiratory fitness; PA: Physical activity.

[TFN2] DSRSC: Depression Self-rating Scale for Children; CES-D: the Center for Epidemiologic Studies Depression Scale; CIDI: Composite International Diagnostic Interview; MDI: Major Depression Inventory; SMFQ: moods and feelings questionnaire; DTS: Depressive Tendencies Scale; DISC-IV: the Diagnostic and Statistical Manual of Mental Disorders Version IV; SCL-90: Subscales of the Symptom Checklist 90; PHQ-9: The nine-item adolescent Patient Health Questionnaire; SDS: Self-rating depressive scale; CDI: The Children's Depression Inventory.