Associations of Cell Phone Use and Screen Viewing with Overweight in Children

Abstract

Background:

Effects of using mobile devices on childhood obesity have not been well studied. We aimed to ascertain whether cell phone use and screen viewing are associated with excess body weight in a cross-sectional study of Japanese school children.

Methods:

Subjects were 3141 students, ages 6 to 7 years, who participated in the Hekinan Children's Study conducted during 2011–2015. Participants were asked to submit a parent-administered questionnaire on child and parent demographics, health status, and lifestyles, including cell phone use and screen time. Heights and weights were measured at the schools. Being overweight was defined according to the cutoff point for children specified by the Extended International Obesity Task Force. Among 2596 analytic children, the odds ratios (ORs) for being overweight were estimated according to cell phone use, time spent watching television, and time spent on games and computers using the logistic regression models. Analyses were conducted after adjustments for potential confounders, including dietary intake, physical activities, sleep duration, and quality of sleep.

Results:

After multivariate adjustments, cell phone users were found to have an OR of 1.74 for being overweight compared with nonusers. Cell phone use of longer duration was associated with higher risk of being overweight (trend p = 0.018). Time spent watching television was positively associated with the risk of being overweight (trend p = 0.003).

Conclusions:

Just as earlier studies have shown for television viewing, cell phone use might be a risk factor related to being overweight among children.

Introduction

Obesity in childhood has been linked to adult obesity, which is often accompanied by hypertension, diabetes, and lipid abnormality.^1,2 These diseases are further recognized as potential risk factors for cardiovascular diseases and cancer, both major causes of death in Japan. In addition to physical health, childhood obesity has been associated with poor psychological well-being and lower academic performance.^3,4 So, elucidating the determinants of child obesity might suggest effective preventive strategies to improve public health.

Television viewing has been associated with obesity during childhood and adolescence.^5–8 Presumable pathways explaining screen media exposure effects on weight gain include increased dietary intake, increased sedentary activity, displacement of more physical pursuits, and sleep deprivation.⁵ In addition to television, children today spend increasingly large amounts of time using computers, video games, tablets, and cell phones. Especially, the use of portable devices among children has increased dramatically during the past two decades. Although these devices have some new features such as interactivity and mobility, which might not engender sedentary behaviors, effects of the use of mobile devices on childhood obesity have not been well studied.^9–15 Evidence is very limited for younger children, while more children start using cell phones at younger ages these days.

Furthermore, since the bright light emitted from the screen might adversely affect hormonal secretion such as melatonin,¹⁶ and reduced melatonin production has been reported as associated with obesity,^17,18 the use of electronic devices might be associated directly with obesity independent of dietary intake, physical activity, and sleep. However, earlier studies of electronic devices and obesity have not fully considered these potential confounders.^{6–8,10–15}

In this study of Japanese school children, ages 6 to 7 years, at first, we describe the associations of cell phone use and screen viewing with dietary intake, physical activity, sleep duration, and sleep quality. Then, we examine whether cell phone use and screen viewing are associated with excess body weight after considering these lifestyle behaviors. Because reading and listening to music, the other sedentary behaviors, may displace sleep time or physical activity in a similar way, we also compare the associations of these behaviors with excessive body weight.

Methods

Participants and Design

The Hekinan Children's Study is a prospective study that investigates the associations of lifestyle and environmental factors with surrogate markers of chronic diseases, such as cardiometabolic risk factors and cancer risk factors, and various health conditions, including allergies and pubertal development.¹⁹ The baseline survey was administered in Autumn from 2011 to 2015. Subjects were first-year elementary school students in Hekinan City, Aichi, Japan. Follow-up surveys are planned for the fourth grade of elementary school and the first grade of junior high school.

Among 3594 subjects at baseline, 3141 students (87.4%) participated in the study with informed consent written by at least one parent of each child. Participants were asked to submit a parent-administered questionnaire eliciting data of child and parent demographics, health status, and lifestyle. For non-Japanese parents, a different short version of the questionnaire was used. Each question was checked for implausible and missing values. Correct information was sought from parents whenever possible. The Ethics Board of the Gifu University Graduate School of Medicine, Gifu, Japan, approved the study protocol and informed consent procedures.

Of the total participants at baseline, we excluded 74 subjects whose parents were non-Japanese, 17 subjects without measured height and weight, and 454 subjects who did not have the reported height and weight of both parents. Finally, analyses were conducted among 2596 students. They were 1381 boys and 1215 girls, ages 6 to 7 years, with mean age of 7.0 years (Table 1). The mean (standard deviation) of BMI was 15.3 (1.7) kg/m². Children being overweight and with obesity were 157 (6.1%) and 42 (1.6%), respectively. Cell phone users were about 6.7%. Among cell phone users, 6.9% made or received a call once per day or more, 30.2% used the mail function, and 3.6% used cell phone Internet access. Mean times were 2.16 hours in watching television and 0.78 hour in spending on games and computers.

Table 1.

Characteristics of 2596 Study Participants

Variables
Sex (boys/girls), n	1381/1215
Age (years), mean (SD)	7.0 (0.3)
Height (cm), mean (SD)	118.1 (4.9)
Weight (kg), mean (SD)	21.4 (3.5)
BMI (kg/m²), mean (SD)	15.3 (1.7)
Sibling (yes: %)	91.2%
Feeding at 4 months (%)
Breastfed	55.7%
Mix-fed	26.8%
Bottle-fed	17.5%
Cell phone use (yes: %)	6.7%
Time spent watching television (hours/day), mean (SD)	2.16 (1.13)
Time spent on games and computers (hours/day), mean (SD)	0.78 (0.75)
Time spent reading books or comics (hours/day), mean (SD)	0.26 (0.33)
Listening to music (yes: %)	31.5%

SD, standard deviation.

Questionnaire

Questionnaire respondents provided data for birth size, number of siblings, feeding method during infancy, diet, physical activity, sedentary behavior, sleep habits, and cell phone use of children. Data of sociodemographic characteristics, medical histories, and smoking habits of parents and other cohabiters were also reported. Smokers were defined as persons who had smoked at least 20 packs of cigarettes during their lifetime. Using the age of initiation into smoking and the age at smoking cessation for parents and cohabiters and the child's birthday, we calculated the pack-years of household smoking to which the child had been exposed from birth.

Dietary intake was assessed using a validated food frequency questionnaire (FFQ).²⁰ The FFQ asked parents how often their children had consumed each of the 162 food items listed and what the usual serving size of each item was, on average, during the 6 months preceding the survey. Each intake of nutrients was estimated from the frequency of ingestion and portion size using the Japanese Standard Table of Food Composition (5th revised and enlarged edition), published by the Science and Technology Agency of Japan.²¹ When the FFQ validity was assessed by comparison with two 3-day diet records, the Spearman correlation coefficient for total energy intake was 0.34.²⁰

Questions about physical activity at playtime were based on an outdoor playtime checklist reported by Burdette et al.²² Parents were asked to report how long the child usually spent playing in the yard or street around the house before noon, from noon until 6 pm, and after 6 pm. Similarly, the duration the child spent playing in a park, playground, and outdoor recreation area was inquired. These questions were asked for both weekday and weekend activities. The sum of scores from these questions was regarded as the playtime score (range 0–40). Higher scores signified more physical activity. Details, including reproducibility, are described elsewhere.²³ Furthermore, information about child participation in organized sports, games, and other activities supervised by adults was sought based on a questionnaire by Booth et al.²⁴

Parents were asked to provide the approximate time when their children got up or went to bed on weekdays and weekends. Time in bed at night was calculated as the time from bedtime to wake-up time. The mean time was calculated by adding five-sevenths of the weekday time and two-sevenths of the weekend time. Information about the following three sleep problems was obtained: experiencing difficulties in falling asleep lasting for 30 minutes or longer, waking up frequently during the night, or waking up too early in the morning and being unable to go back to sleep. Those who had any of these complaints three times per week or more were defined as having insomnia.²⁵

Cell Phone Use, Screen Time, and Other Sedentary Behaviors

Students who owned a cell phone were regarded as cell phone users. For cell phone users, the usual duration of use and the mode of usage were inquired: making or receiving a call, sending a mail, and Internet use. Questions related to screen time specifically asked for the time children spent watching television or video and the time spent on games and computers. Time spent reading books or comics and listening to music was also reported. Respective times for weekdays and weekend days were asked. The mean time was calculated by adding five-sevenths of the weekday time and two-sevenths of the weekend time.

Overweight and Obesity

Data on child's heights and weights were obtained through anthropometric measurements taken at the schools. As a rule, measurements were taken with participants dressed in light indoor clothing after removing their shoes. Height was measured to the nearest 0.1 cm. Weight was measured to the nearest 0.1 kg. BMI was calculated as weight in kilograms divided by height in meters squared. The weight status was defined according to the age-specific and gender-specific BMI cutoff points for children specified by the Extended International Obesity Task Force.^26,27 Children with BMI values that corresponded to an adult BMI of ≥25 kg/m² were classified as being overweight (including obesity), because of a few children with obesity among our participants. The others were regarded as having normal weight (including thinness). The BMI cutoffs of being overweight are equivalent to z-scores by the World Health Organization growth standard reference of 1.45 for boys and 1.18 for girls at 7 years. Mother's and father's BMIs were calculated using the heights and weights reported in the questionnaire.

Statistical Analysis

Birth weight, lifestyles, passive smoking, and parents' characteristics were compared between children who were normal weight and overweight. One-way analysis of variance was used to test the associations of cell phone use (no, yes), time spent watching television (<1, 1–2, 2–3, ≥3 hours/day), time spent on games and computers (none, <0.5, 0.5–1, 1–1.5, ≥1.5 hours/day), time spent reading books or comics (none, <0.5, ≥0.5 hour/day), and listening to music (no, yes) with physical activity (playtime score and exercise and sports), total energy intake, and sleep time (time of waking, time for bed, and time in bed at night). Chi-squared tests were used to assess the associations with insomnia. In the logistic regression models with multivariate adjustments, the odds ratios (ORs) and 95% confidence intervals (CIs) for being overweight were estimated for the category of cell phone use, screen time, reading time, and listening to music. First, sex (boy, girl) and age (years) were inputted into the models (OR1). Second, the following potential confounders except for lifestyle behaviors were included (OR2): school (seven schools), mother's BMI (quartiles), father's BMI (quartiles), sibling (yes, no), birth weight (quartiles), feeding at 4 months (breastfed, mix-fed, bottle-fed), age of mother (<30, 30–35, 35–40, ≥40 years), mother's education (≤9, 10–12, 13–15, ≥16 years), and exposure to household smoking (0, ≤6, >6 pack-years). Last, the total energy intake (quartiles), playtime score (quartiles), time for bed (quartiles), and insomnia (yes, no) were additionally adjusted (OR3). The p-values for the Hosmer and Lemeshow goodness-of-fit tests showed >0.05 in all models. There were no strong correlations between any covariates inputted in the models.

All analyses were conducted using software (version 9.4; the SAS Institute, Inc.). All p-values were calculated using a two-sided test. For all analyses, a p-value of <0.05 was inferred as statistically significant.

Results

Children with being overweight had heavier birth weight, higher total energy intake, and higher playtime scores than children of normal weight (Table 2). Later time for bed, shorter time in bed at night, and insomnia were associated with being overweight. Children with being overweight were more likely to be exposed to household smoking. Higher BMIs of the mother and father were strongly associated with the child being overweight.

Table 2.

Birth Weight, Lifestyles, Passive Smoking, and Parents' Characteristics According to Weight Status

Variables	Normal weight	Overweight	p ^*
N	2397	199
Birth weight (g), mean (SD)	2968 (450)	3123 (402)	<0.001
Total energy intake (calorie), geometric mean (95% CI)	1569 (1217–2024)	1744 (1341–2268)	<0.001
Exercise and sports (yes: %)	64.6%	62.3%	0.52
Playtime score, mean (SD)	10.8 (6.0)	11.8 (6.4)	0.025
Time of waking (h:m), mean (SD)	6:44 (0:23)	6:44 (0:26)	0.99
Time for bed (h:m), mean (SD)	21:16 (0:33)	21:22 (0:37)	0.014
Time in bed at night (hours), mean (SD)	9.48 (0.49)	9.38 (0.55)	0.005
Insomnia (yes: %)	4.3%	8.5%	0.006
Exposure to household smoking (%)
None	44.7%	37.2%	0.001
≤6 pack-years	32.6%	28.2%
>6 pack-years	22.7%	34.6%
Age of mother (years), mean (SD)	36.6 (4.6)	36.5 (4.6)	0.69
Mother's education (%)
≤9 years	3.1%	5.2%	0.090
10–12 years	36.8%	35.2%
13–15 years	42.5%	36.8%
≥16 years	17.7%	22.8%
Mother's BMI (kg/m²), mean (SD)	21.0 (2.9)	23.0 (3.7)	<0.001
Father's BMI (kg/m²), mean (SD)	23.2 (3.2)	25.6 (3.9)	<0.001

Exercise and sports was defined as participating in organized physical activities supervised by adults.

t-Test or chi-squared test.

CI, confidence interval.

Time spent on games and computers, reading books or comics, and listening to music was positively associated with the total energy intake (Table 3). Cell phone users had a higher playtime score than nonusers. Students who usually listen to music also had a higher playtime score than those who do not listen to music. Children who spent watching television longer were unlikely to have exercise and sports.

Table 3.

Associations of Cell Phone Use, Screen Time, Reading, and Listening to Music with Physical Activity and Dietary Intake

	Total energy intake (kcal.)			Playtime score			Exercise and sport
	n	Geometric mean (95% CI)	p ^*	Mean	SD	p ^*	(Yes: %)	p ^**
Cell phone use
No	2397	1581 (1225–2040)	0.73	10.8	6.0	0.018	64.1	0.13
Yes	173	1592 (1208–2099)		11.9	6.8		69.8
Duration of cell phone use (years)
None	2397	1581 (1225–2040)	0.81	10.8	6.0	0.028	64.1	0.15
<1 year	108	1608 (1234–2094)		12.4	7.0		73.2
≥1 year	58	1585 (1180–2130)		11.0	6.3		63.2
Time spent watching television (hours/day)
<1 hour	245	1539 (1197–1978)	0.20	10.8	5.8	0.79	72.1	<0.001
1–2 hours	959	1577 (1228–2025)		11.0	5.9		67.7
2–3 hours	845	1587 (1231–2046)		11.0	6.1		65.0
≥3 hours	523	1598 (1218–2096)		10.7	6.4		53.9
Time spent on games and computers (hours/day)
None	504	1559 (1205–2017)	<0.001	11.0	6.2	0.50	65.7	<0.001
<0.5 hour	437	1566 (1252–1959)		10.8	5.8		68.4
0.5–1 hour	639	1546 (1196–2000)		10.9	6.0		65.2
1–1.5 hours	580	1609 (1247–2077)		11.1	6.1		64.5
≥1.5 hours	358	1656 (1250–2193)		10.4	6.1		54.5
Time spent reading books or comics (hours/day)
None	805	1548 (1195–2005)	<0.001	10.5	6.4	0.061	63.3	0.012
<0.5 hour	1347	1588 (1234–2043)		11.1	5.9		66.6
≥0.5 hour	293	1666 (1295–2144)		10.7	5.9		57.9
Listening to music
No	1648	1564 (1214–2016)	<0.001	10.5	6.0	<0.001	64.7	0.78
Yes	758	1624 (1259–2096)		11.6	6.1		64.1

Exercise and sports was defined as participating in organized physical activities supervised by adults.

Analysis of variance.

Chi-squared test.

Cell phone users went to bed at a later time than nonusers (Table 4). Longer duration of cell phone use was associated with later time of waking. Screen times allocated to television, games, and computers were associated with delayed time of waking and going to bed and shorter time in bed at night. Longer time spent on games and computers was related to insomnia. Longer time spent reading books or comics was associated with earlier time of waking. Listeners to music went to bed and got up at an earlier time than nonlisteners.

Table 4.

Associations of Cell Phone Use, Screen Time, Reading, and Listening to Music with Sleep Time and Insomnia

		Time in bed at night (hours)			Time of waking (h:m)			Time for bed (h:m)			Insomnia
	n	Mean	SD	p ^*	Mean	SD	p ^*	Mean	SD	p ^*	(Yes: %)	p ^**
Cell phone use
No	2397	9.47	0.49	0.41	6:44	0:23	0.054	21:16	0:34	0.042	4.69	0.46
Yes	173	9.44	0.60		6:48	0:21		21:21	0:37		3.47
Duration of cell phone use (years)
None	2397	9.47	0.49	0.55	6:44	0:23	0.024	21:16	0:34	0.11	4.69	0.64
<1 year	108	9.42	0.60		6:45	0:21		21:20	0:35		2.78
≥1 year	58	9.48	0.61		6:52	0:23		21:24	0:41		5.17
Time spent watching television (hours/day)
<1 hour	245	9.56	0.50	<0.001	6:36	0:25	<0.001	21:02	0:34	<0.001	4.51	0.81
1–2 hours	959	9.51	0.48		6:43	0:22		21:13	0:32		4.08
2–3 hours	845	9.47	0.50		6:46	0:22		21:18	0:33		4.99
≥3 hours	523	9.37	0.51		6:48	0:23		21:26	0:34		4.81
Time spent on games and computers (hours/day)
None	504	9.53	0.51	<0.001	6:40	0:23	<0.001	21:08	0:33	<0.001	3.19	<0.001
<0.5 hour	437	9.53	0.49		6:41	0:23		21:09	0:33		2.99
0.5–1 hour	639	9.48	0.48		6:44	0:21		21:15	0:31		4.70
1–1.5 hours	580	9.45	0.49		6:48	0:22		21:20	0:32		4.33
≥1.5 hours	358	9.32	0.52		6:52	0:25		21:32	0:37		8.94
Time spent reading books or comics (hours/day)
None	805	9.45	0.51	<0.001	6:48	0:23	<0.001	21:21	0:35	<0.001	4.98	0.41
<0.5 hour	1347	9.51	0.47		6:43	0:21		21:13	0:32		4.17
≥0.5 hour	293	9.33	0.57		6:37	0:27		21:17	0:38		5.80
Listening to music
No	1648	9.46	0.50	0.73	6:45	0:22	<0.001	21:18	0:34	0.008	5.18	0.060
Yes	758	9.47	0.49		6:42	0:25		21:14	0:34		3.44

Analysis of variance.

Chi-squared test.

After adjustments for potential confounders, cell phone users were found to have a relative risk of 1.74 for being overweight compared with nonusers (Table 5). Longer duration of cell phone use was associated with higher risk for being overweight (trend p = 0.018). Time spent watching television was positively associated with the risk of being overweight (trend p = 0.003). When we conducted the analyses separately for each sex, the OR3s of being overweight for cell phone users were 1.77 (95% CI: 0.71–4.38) in boys and 1.75 (95% CI: 0.84–3.66) in girls compared with nonusers. Compared with children who watched television for <1 hour/day, the OR3s of being overweight were 2.61 (95% CI: 0.59–11.49), 2.97 (95% CI: 0.67–13.10), and 5.61 (95% CI: 1.25–25.14), in those with 1–2, 2–3, and ≥3 hours/day of time spent watching television in boys (trend p = 0.006). The corresponding values were 0.67 (95% CI: 0.30–1.54), 0.79 (95% CI: 0.34–1.82), and 0.85 (95% CI: 0.35–2.10), respectively, in girls (trend p = 0.32). The effect modification by sex on the associations of cell phone use and television watching with overweight was not statistically significant (all p-values for interaction >0.05).

Table 5.

Odds Ratios for Being Overweight According to Cell Phone Use, Screen Time, Reading, and Listening to Music

	No. of subjects	No. of overweight	Sex and age adjusted	Multivariate adjusted	Multivariate adjusted
	No. of subjects	No. of overweight	OR1 (95% CI)	OR2^a (95% CI)	OR3^b (95% CI)
Cell phone use
No	2397	174	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
Yes	173	20	1.68 (1.02–2.74)	1.78 (1.04–3.07)	1.74 (1.00–3.02)
Duration of cell phone use (years)
None	2397	174	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
<1 year	108	13	1.79 (0.98–3.27)	1.83 (0.95–3.55)	1.74 (0.88–3.43)
≥1 year	58	7	1.68 (0.75–3.77)	1.85 (0.77–4.45)	1.88 (0.77–4.58)
Linear trend p			0.018	0.013	0.018
Time spent watching television (hours/day)
<1 hour	245	12	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
1–2 hours	959	63	1.36 (0.72–2.57)	1.08 (0.56–2.08)	0.97 (0.50–1.90)
2–3 hours	845	63	1.56 (0.83–2.94)	1.23 (0.63–2.40)	1.16 (0.59–2.29)
≥3 hours	523	56	2.28 (1.20–4.34)	1.86 (0.94–3.69)	1.73 (0.86–3.47)
Linear trend p			<0.001	0.003	0.003
Time spent on games and computers (hours/day)
None	504	39	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
<0.5 hour	437	26	0.74 (0.44–1.24)	0.81 (0.47–1.40)	0.80 (0.46–1.38)
0.5–1 hour	639	42	0.84 (0.53–1.33)	0.83 (0.51–1.35)	0.86 (0.52–1.41)
1–1.5 hours	580	50	1.14 (0.72–1.78)	1.08 (0.67–1.76)	1.06 (0.65–1.74)
≥1.5 hours	358	33	1.27 (0.76–2.13)	1.15 (0.66–2.01)	1.04 (0.58–1.85)
Linear trend p			0.010	0.065	0.14
Time spent reading books or comics (hours/day)
None	805	71	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
<0.5 hour	1347	89	0.73 (0.52–1.01)	0.77 (0.54–1.09)	0.73 (0.51–1.05)
≥0.5 hour	293	27	1.03 (0.65–1.65)	1.00 (0.60–1.64)	0.87 (0.52–1.46)
Linear trend p			0.99	0.80	0.51
Listening to music
No	1648	124	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
Yes	758	61	1.08 (0.78–1.49)	1.08 (0.76–1.52)	1.00 (0.70–1.42)
Linear trend p			0.38	0.73	0.91

Adjustments for school, sex, age (years), mother's BMI (quartiles), father's BMI (quartiles), sibling (yes, no), birth weight (quartiles), feeding at 4 months (breast-, mix-, bottle-fed), age of mother (<30, 30–35, 35–40, ≥40 years), mother's education (≤9, 10–12, 13–15, ≥16 years), and exposure to household smoking (0, ≤6, >6 pack-years).

Adjustments for total energy intake (quartiles), playtime score (quartiles), time for bed (quartiles), and insomnia (yes, no), in addition to the variables included in OR2.

OR, odds ratio.

Furthermore, after additional adjustments for time spent watching television, the OR of being overweight was 1.77 (95% CI: 1.02–3.08) for cell phone users compared with nonusers. Similarly, after additional adjustments for cell phone use, the ORs of being overweight were 0.99 (95% CI: 0.51–1.93), 1.20 (95% CI: 0.61–2.36), and 1.78 (95% CI: 0.89–3.59), in those with 1–2, 2–3, and ≥3 hours per day of time spent watching television, respectively, compared with children who watched television for <1 hour per day (trend p = 0.003).

Discussion

To date, a few cross-sectional studies have examined the association between the use of mobile devices and excessive body weight among children.^10–15 A Polish study of 340 students, ages 7–12 years, revealed that girls being overweight used cell phones longer than girls with normal weight.¹⁰ Among 315 Japanese students who were 12- to 13-year old, excess time spent by girls for electronic devices was positively correlated with being overweight.¹¹ Among 234 US children who were 8 to 17 years old, those who used their phones at bedtime were 2.3 times more likely to be overweight than those who did not.¹² A study of 3398 Canadian students who were 10 to 11 years old demonstrated that access to a cell phone in the bedroom was associated with higher risk of being overweight.¹³ Regarding television viewing, many studies, including prospective studies, have reported a positive association with obesity.^5–8 Earlier studies have concluded that the relationship between electronic device use and obesity is mediated by other lifestyle behaviors, including dietary intake, physical activities, and sleep. The present study found that positive associations of cell phone use and television viewing with being overweight are independent of such lifestyles.

Television watching was inversely associated with exercise and sports, and associated with a shift toward later times for sleeping and shorter sleep duration. These lifestyle behaviors might partially account for the increased risk of being overweight by television watching. Several earlier reports have also described that the use of electronic devices is associated with delayed bedtimes, reduced sleep duration, and poor sleep quality.^{13,14,28–30} Sleep deprivation has been implicated as a risk factor of childhood obesity.^31,32

Cell phone use was not as strongly associated with sleep variables as television watching was. It was associated with higher physical activity. Because of the low rate of cell phone use among participants, we were unable to identify which mode of usage was associated with being overweight. Internet access, online chat, and smart phones have become increasingly popular. Some applications have been developed to increase physical activity and to improve body composition. Future research might be desired for the specific examination of new ways of using electronic devices.

This study possibly missed significant associations between time spent on games and computers and being overweight, because time spent on games and computers was not so long among our participants (mean: 47 minutes/day).

Strengths of our study methods include the high response rate for school-based research, height and weight measurements, and data collection of various confounding factors. Nevertheless, our study has several limitations. Measures of cell phone use and screen time were based on parent reports. Because the errors on these reports would likely have occurred nondifferentially between parents of children who are overweight and of normal weight, the observed association might not be reported with a particular bias. Because our participants included a few children with obesity (1.6%), we were unable to assess the separate associations of electronic device use with being overweight or obesity. Last, because this study was cross-sectional, the direction of causality is indeterminate. Children with being overweight might have more sleep problems and stay up late, thereby spending more time with cell phones and in front of screens.

In conclusion, cell phone use and watching television were associated with increased risk of being overweight among Japanese children, ages 6 to 7 years. Reducing child's excessive exposure to cell phone in addition to screen may be important for prevention of obesity in childhood. Researchers should continue to figure out the effects of electronic devises on excess body weight, considering the usage pattern of electronic devices in a rapidly changing media environment.

Footnotes

Acknowledgments

We express our gratitude to all the participants of the study and to the staff of Hekinan City Health Division and School Education Division and Hekinan Medical Association. This work was supported by grants in aid from the Ministry of Education, Culture, Sports, Science, and Technology of Japan.

Author Disclosure Statement

No competing financial interests exist.

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