Correlation of Screen Time With Eating Behavior Among School-Going Children Aged 8 to 10 Years in East Delhi,India

Abstract

Background and aim:

Excessive screen time (ST) negatively impacts physical activity and eating behavior among children <5 years. There is a dearth of data on older Indian children; hence, the present study aimed to assess the effect of ST on eating behavior among older children.

Methods:

The present cross-sectional study purposively recruited 100 school-going children. E-questionnaire was prepared to gather information regarding the demographic profile and self-reported weight and height. For the assessment of ST, the SCREENS questionnaire was used. Eating behavior was assessed using the Children Eating Behavior Questionnaire, and for physical activity, the PAQ-C was used. The nutrition status of children was assessed using body mass index (BMI) for age cut-offs.

Results:

The results revealed that 52% of the children were using screens for > 4 hours per day excluding school-related activities and online classes. ST of children was directly proportional to the parent’s ST (P < .05). There was a negative correlation between ST and the physical activity of children (P < .01). A positive correlation was observed between ST and emotional overeating, desire to drink, slow eating, satiety responsiveness, food fussiness, and emotional undereating (P < .01). BMI was positively associated with ST and negatively associated with physical activity, though the results were not significant. Satiety responsiveness (a food-avoiding subscale) was negatively associated with BMI (P < .05).

Conclusion:

The present study concludes that excessive ST among 8 to 10 years old school-going children has been associated with physical inactivity and poor eating behavior which could lead to an increased risk of being overweight and obese.

Keywords

Screen time children physical activity eating behavior BMI school-going children

Introduction

Digitalization of the world is making screen devices such as smart phones, tabs, laptops, etc, a necessity at a household level. Unfortunately, the usage of these screens is not restricted to any particular age group. With the COVID-19 pandemic, the practice of digital media devices has increased not only for leisure or professional work but also for academics.¹ Excessive screen time (ST) negatively impacts physical activity and eating behavior among children.²

According to the Indian Academy of Pediatrics (2020–2021), screens have become an important part of children’s daily lives. Children under the age of 2 should not exceed any type of ST, except for occasional video calls with relatives. ST for children aged 2 to 5 years should not exceed 1 hour. For children >5 years, it is critical to strike a balance between ST and other activities that are necessary for overall development. If physical activity/playtime, adequate sleep duration, schoolwork time, mealtime, hobbies, and family time are displaced due to the use of screens such as phones, laptops and television, etc, then it is considered excessive ST.³

Among children, excessive ST is linked to a variety of health risks such as the early onset of hypertension, heart problems, hyperlipidemia, and other health risks, which have direct associations with sedentary ST behavior as a result of lower physical activity and poor sleep quality.⁴ The longer the ST, leads to children’s engagement in unhealthy dietary habits such as skipping breakfast, eating fast food and sweets frequently, and less likely to engage in healthy dietary habits such as eating a second fruit every day, eating fresh or cooked vegetables or/and fish regularly.⁵ When compared to habits of moderate or vigorous physical exercise, screen-based sedentary behavior developed in childhood are more likely to persist into adulthood.⁶ Prolonged leisure ST is associated with greater media accessibility and less presence of parents/others. To avoid prolonged leisure ST, attention should be paid to mobile/small screen-based devices such as cell phones and pads/tablets, especially in boys and/or on weekends.⁷

Several studies have been conducted on children aged less than 5 years related to ST and eating habits but there is a lack of scientific evidence on the impact of ST on eating behavior and overall lifestyle among older children.^8-11 Considering the importance of establishing appropriate eating behavior among children, which will determine their future health/nutrition status, the present research aimed to study the association of ST on eating behavior among school-going children 8 to 10 years in East Delhi.

Methods

In the present cross-sectional study, the sample of 100 school-going children (8–10 years) of East Delhi was recruited using convenience sampling, after excluding the children having any kind of chronic disease. Four schools in East Delhi, India were approached. After taking due permission from the school authorities. Ethical clearance was obtained from the Institutional Ethics Committee, Lady Irwin College, on November 27, 2021. Since the target group was minors, parents were explained the purpose of the study and their online consent was undertaken. A study information sheet was shared providing detailed information regarding the research and researcher. The subjects were recruited for the study after taking informed consent. Data collection was done between January and March 2022.

The study was conducted using Google Forms. The following information was collected.

General and Anthropometric Information

A questionnaire was prepared to gather information regarding the demographic profile of the child. Anthropometric data like body weight and height of the children were asked and were compared to the WHO BMI cutoff (BMI for Age 5–19 Years, 2007).¹²

Screen Time

SCREENS is a questionnaire that covers the six domains that are validated to be important factors of screen media use in children.¹³ The six domains include screen media environment, child’s screen media use, context of screen media use, early exposure, parental perception of child’s media use, and parental media use. This questionnaire was adapted according to the Indian setup.

Child Eating Behavior Questionnaire

Child Eating Behavior Questionnaire (CEBQ) is a validated parent-rated instrument to assess 8 dimensions of eating style in children. There are total of 35 questions in CEBQ and each question contains 5 options “Never,” “Rarely,” “Sometimes,” “Often,” and “Always.” Each question relates to a particular dimension; responsiveness to food (FR), enjoyment of food (EF), satiety responsiveness (SR), slowness in eating (SE), fussiness (FF), emotional overeating (EOE), emotional under eating (EUE), and desire for drinks (DD).¹⁴ The above questionnaire was adapted in the present study to analyze children eating behavior.

Physical Activity Questionnaire—Child

Physical Activity Questionnaire (PAQ-C) was adapted according to the Indian setup. The PAQ-C is appropriate for school-aged children (grades 4–8; approximately ages 8–14). This tool was developed to assess general levels of physical activity among children.¹⁵

Pre-testing of the tools was performed; 10 parents of children in the same age group were asked to fill out the questionnaire. Minor changes were made like changing of language of some questions to make them understand easily.

Statistical Analysis

All the data was coded and entered into Microsoft excel sheets. Descriptive statistics of the participants’ baseline characteristics and responses were provided as frequency and percentage for categorical variables that were presented differently for males and females. Continuous variables such as age and BMI were reported as mean and standard deviation (SD).

The association between self-reported nutritional status and various parameters of eating behavior, physical activity, and ST was analyzed using Pearson’s chi-square test. For the association of all other parameters, the Pearson correlation test was performed. For all analyses, a P value < .05 was considered statistically significant. All statistical analyses were performed by using SPSS ver. 21.0 (IBM, Chicago, IL, USA).

Results

General Profile of Participants

The demographic profile of participants showed that the majority of the school-going children were girls and belonged to the middle-income group (Table 1).

All children were attending online classes because of the pandemic. The details of children’s online classes are depicted in Table 1. Indian Academy of Pediatrics (Guidelines for Normal Sleep and Physical Activity, 2020–2021) recommended 9 to 11 hours of sleep for 6 to 13 years old children.¹⁶ The majority of the children were having adequate sleep as per the guidelines. The data showed that 29% of the children were overweight and 18% were obese. The present study also showed that 27% of the children were involved in low physical activity (Table 1)

Table 1.

Demographic Profile of the Children.

S. No.	Category	N (%)
1.	Gender [boys/girls]	[27(27)/73(73)]
2.	Age [8 years/9 years/10 years]	[33(33)/41(41)/26 (26)]
3.	Parents qualification [high school/graduate/postgraduate]	[45 (45)/41 (41)/14 (14)]
4.	Children class standard [2nd/3rd/4th/5th]	[2 (2)/25(25)/56(56)/17(17)]
5.	Number of classes students attend per day [4/5/6]	[85 (85)/11(11)/4(4)]
6.	BMI for Age [underweight/normal/overweight/obese/severely malnourished]	[5(5)/46(46)/29 (29)/18(18)/2(2)]
7.	PAC-C [v. low PA/low PA/moderate PA/high PA]	[27 (27)/52 (52)/16(16)/5(5)]

Screen Time

Table 2 showed that the majority of the children were having 2 to 4 screen media devices in their households. 95% of the parents reported that their child uses screen media daily related to school activities and 85% for playing screen-based games. Parents (52%) reported that their child uses screen media (for YouTube, games, school-related tasks, video calls with relatives, etc) in their leisure time for more than 4 hours. Among 18% of the households, it was reported that television is very often switched on while no one is watching.

More than 90% of the parents agreed that the child must ask for permission to use screen media devices and boundaries should be fixed. The children were more prone to use screen media before half an hour of going to bed than after half an hour of waking up in the morning daily (58%). The parents disclosed that their children (15%) use more than one screen media at the same time (like watching TV and using their phone at the same time). The majority of the children used screen media with their siblings or alone (78%). About 22% of the children used screen media in the presence of an adult. 10% of the parents disagree that if the chance given, their child would spend his/her most of the time on screen media and 90% choose to agree strongly or partly the same (Table 2).

Table 2.

SCREENS Questionnaire.

S. No.	Question	n (%)
1.	How many of the following screen media devices are present in total at household where the child lives? (laptop, smart phones, iPad/tablets and TV)
	(a) 1–2	10 (10)
	(b) 2–3	40 (40)
	(c) 3–4	31 (31)
	(d) More than 4	19 (19)
2.	Does your child use a tablet, smart phone, laptop, or other screen media device connection to the school related activity?
	(a) Yes, daily	95 (95)
	(b) Yes, weekly	1 (1)
	(c) Yes, less often than weekly	3 (3)
	(d) No, never	1 (1)
3.	Does the child use a tablet, smartphone, laptop, or other screen media device during after-school care, for example, to play a screen-based game? (Do not include the use of smartphones to contact parents only)
	(a) Yes, daily	87 (87)
	(b) Yes, weekly	5 (5)
	(c) Yes, less often than weekly	4 (4)
	(d) No, never	2 (2)
	(e) Don’t know	2 (2)
4.	Within the past month, how much time has the child typically spent per day on the following screen-based activities during leisure time? (YouTube, games, school-related tasks, video calls with relatives, etc.)
	(a) Less than 1 hour	9 (9)
	(b) 1–2 hours	14 (14)
	(c) 2–4 hours	25 (25)
	(d) More than 4 hours	52 (52)
5.	Does it ever happen that the television is on while no one is watching?
	(a) Very often	18 (18)
	(b) Sometimes	53 (53)
	(c) Rarely	25 (25)
	(d) Never	4 (4)
6.	Indicate whether you agree or disagree with the statements below regarding the child’s screen media use at home	Agree	Disagree
	(a) The child must always ask for permission before using screen media	91 (91)	9 (9)
	(b) There are fixed boundaries for how much time the child may use screen media	93 (93)	7 (7)
	(c) There are fixed boundaries for when the child may use screen media during the day	93 (93)	7 (7)
	(d) There are fixed boundaries for what games the child is allowed to play	95 (95)	5 (5)
	(e) There are fixed boundaries for what movies, YouTube clips, TV shows, and entertainment programs the child may watch	95 (95)	5 (5)
7.	How many days in a typical week your child uses screen media within half an hour after he/she wakes up in the morning?
	(a) Daily	17 (17)
	(b) 3–6 days	41 (41)
	(c) 1–6 days	7 (7)
	(d) Never	35 (35)
8.	How many days in a typical week your child uses screen media within half an hour before he/she goes to sleep?
	(a) Daily	58 (58)
	(b) 3–6 days	8 (8)
	(c) 1–6 days	12 (12)
	(d) Never	22 (22)
9.	How much time does your child spend on screen in a day?	Weekdays	Weekends
	(a) Less than 3 hours	8 (8)	15 (15)
	(b) 4–5 hours	18 (18)	20 (20)
	(c) 5–7 hours	59 (59)	47 (47)
	(d) More than 7 hours	15 (15)	18 (18)
10.	How often does your child use more than one screen media device at a time? (like watching TV and using phone at the same time)
	(a) Very often	15 (15)
	(b) Sometimes	58 (58)
	(c) Rarely	15(15)
	(d) Never	12 (12)
11.	When your child uses screen media, it is usually with?
	(a) With you or other adults	22 (22)
	(b) With siblings	64 (64)
	(c) Alone	14 (14)
12.	If the child is given the choice, he/she will almost always choose to spend his/her time on screen-based activities
	(a) Strongly agree	40 (40)
	(b) Partly agree	50 (50)
	(c) Partly disagree	5 (5)
	(d) Strongly disagree	5 (5)
13.	Is your home your primary place of study or work?
	(a) Yes	26 (26)
	(b) No	24 (24)
	(c) I am neither working nor studying	50 (50)
14.	Within the past month, how much time have you typically spent on screen per day?
	(a) 2–4 hours	43 (43)
	(b) 4–6 hours	41 (41)
	(c) 6–8 hours	8 (8)
	(d) More than 8 hours	8 (8)
15.	If your child owns a smartphone/laptop/any other screen media, how old he/she was?
	(a) Less than 8	12 (12)
	(b) 8	6 (6)
	(c) 9	14 (14)
	(d) More than 9	68 (68)

Eating Behavior

The majority of the children were taking 3 (47%) to 4 (33%) meals a day. According to the Indian Academy of Pediatrics (2021–2022), children of 8 to 10 years should consume 3 meals and at least 2 snacks per day.³

The eating behavior of children can be broadly divided into 2 subscales. (a) Food Approaching Subscales: These consist of 4 scales—enjoyment of food, food responsiveness, emotional overeating, and desire to drink. (b) Food avoiding subscales: These consists of 4 scales—slowness in eating, satiety responsiveness, food fussiness, and emotional undereating. Data in Table 3 showed that majority of the children sometimes show the parameters of food avoiding and food approaching subscales.

Table 3.

Eating Behavior of School-Going Children.

Scale	Food Approaching Subscales (%)				Food Avoiding Subscales (%)
Scale	Enjoyment of Food	Food Responsiveness	Emotional Overeating	Desire to Drink	Slowness in eating	Satiety responsiveness	Food fussiness	Emotional Undereating
Never	0	5	13	8	2	1	1	2
Rarely	11	29	18	22	13	20	13	17
Sometimes	63	57	59	55	65	69	70	61
Often	20	7	9	14	19	10	16	20
Always	6	2	1	1	1	0	0	0

Association of Screen Time With Various Parameters Among School-Going Children

Screen time and physical activity

Pearson correlation reveals that there was a strong negative correlation between ST and the physical activity of children (r = –0.325, P < .01). It infers that children who used more screen media were less physically active. Almost half of the school-going children (51%) who used screen media for 5–7 hours are having low physical activity in this study.

Screen time and parent’s screen time

A strong positive significant difference is also seen between child’s ST and parent’s ST (r = 0.396, P < .01) as shown in Table 4. The data depicts that if the ST of parents is high then the ST of children is also high.

However, in the present study, no significant difference was found between gender and ST of children. Similarly, no significant difference was found in the ST of children and qualifications of parents, type of family, number of screens in the house, and socioeconomic status.

Screen time and eating behavior

A strong positive correlation (P < .01) was seen (Table 4) between ST and emotional overeating, desire to drink, slowness in eating, satiety responsiveness, food fussiness, and emotional undereating.

Table 4.

Association of Screen Time and Physical Activity.

Screen Time		Physical Activity
Parent’s screen time	r = 0.396 (P < .01)	–
Food responsiveness	–	–0.291 (P < .01)
Emotional overeating	r = 0.391 (P < .01)	–0.450 (P < .01)
Desire to drink	r = 0.398 (P < .01)	–0.219 (P < .05)
Slowness in eating	r = 0.340 (P < .01)	–0.247 (P < .05)
Satiety responsiveness	r = 0.267 (P < .01)	–0.201 (P < .05)
Food fussiness	r = 0.268 (P < .01)	–0.285 (P < .01)
Emotional undereating	r = 0.264 (P < .01)	–

Eating Behavior and Physical Activity

According to the present results, a negative significant correlation was found between physical activity and 6 subscales of CEBQ, namely food responsiveness, emotional overeating, desire to drink, slowness in eating, satiety responsiveness, and food fussiness as shown in Table 4. It showed that children with higher food responsiveness, emotional eating, desire to drink, slowness in eating, and food fussiness have low physical activity.

Association of Eating Behavior, Screen Time, and Physical Activity With and Body Mass Index for Age

A negative significant difference (P = .05) was found between satiety responsiveness and body mass index (BMI) through the Pearson correlation test (Table 5). It infers satiety responsiveness is indirectly proportional to the BMI of children. Children who are less responsive to satiety eat more which leads to increase BMI due to overeating.

The data also revealed a negative correlation between BMI and physical activity, though the result was not significant.

Discussion

Childhood is a crucial stage for the development of lifestyle practices. It is imperative to monitor children’s daily routines and control unsuitable practices such as improper sleep duration, personal hygiene, physical inactivity, higher ST, and improper eating habits. National and international guidelines have focused on controlling higher ST among children.

Numerous previous studies have focused on ST and its impact on eating behavior below 5 years. There is a dearth of data on older children related to ST and its impact on overall well-being. The present study tried to comprehend the correlation of ST on eating behavior among school-going children aged 8 to 10 years in East Delhi, India. The data showed that majority of participants were girls. All the students were learning through online mode. Table 1 showed that 29% and 18% of the children were overweight and obese, respectively. According to recent NFHS 5 data (2019–2020), the prevalence of overweight/ obesity has increased from 2.1% to 3.4%. The link between screen media exposure and obesity has received a lot of attention.¹⁷ Children with higher ST are generally more likely to overeat and they also learn unhealthy eating habits from advertisements and programs.¹⁸ In the present study over 19% of the parents reported that more than 4 screen devices are accessible to children at home. Around 90% reported regular use of these screen devices by children for school-related and leisure activities. Parents reported (52%) that children spent more than 4 hours in front of the screen in a day (Table 2).

ST and unhealthy eating habits are common in young children, and evidence suggests that they frequently co-occur and are linked. Early recognition of clusters of unhealthy habits and their influences can involve the development of targeted preventive interventions. The risk behavior combination of insufficient fruit and vegetable consumption, excessive ST, and high energy-dense snack consumption occurred more frequently than expected.¹⁹ The present data depicted that 29% and 22% of the children rarely showed food responsiveness and desire to drink. About 19% and 16% of the children showed slowness in eating and food fussiness and 20% of children showed emotional undereating (Table 3).

The present study revealed that ST was negatively associated with physical activity and positively associated with parent’s ST, emotional overeating, satiety responsiveness, food fussiness, and emotional undereating (Table 4). In line with the present findings, several studies have reported adverse consequences of ST on children’s overall development.^20–23 The data also revealed an association of eating behavior subscales with physical activity (Table 4), the results depicted a negative correlation of physical activity with food responsiveness, emotional overeating, desire to drink, slowness in eating, and satiety responsiveness. It has been seen that there were significant differences in eating behaviors among children who participated in 60 minutes of daily physical activity and those who are physically inactive.²⁴ A previous study,²⁵ also concludes that children who are overweight or obese are engaged in less physical activity. BMI of children was also associated with ST, that is, higher the BMI, higher is the ST of children, but the results were not significant. Some previous studies have also found a positive association between BMI and ST among children.^26,27 Table 5 also represented a significant and negative correlation of BMI with physical activity and satiety responsiveness and a positive association with ST. The present study has a few limitations like a smaller sample size and the finding of the study was based on self-reported information. But, the pernicious association of higher ST with eating behavior and physical inactivity among 8 to 10 years is crucial. Even so, the relevancy of the data has an imperative role in the comprehension of higher ST and its impact on children eating behavior, physical activity, and nutrition status which can be the leading factors for detrimental effects on the overall well-being of children.

Table 5.

Association of BMI with Satiety Responsiveness, Physical Activity, and Screen Time.

Satiety Responsiveness
Body mass index	–0.210 (P < .01)
Physical Activity
Body mass index	–0.004 (P > .05)
Screen Time
Body mass index	0.009 (P > .05)

Hence, this study concludes that excessive ST among school-going children has been associated with physical inactivity and poor eating behavior which could lead to an increased risk of being overweight and obesity.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Statement of Informed Consent and Ethical Approval

Necessary ethical clearances and informed consent were received and obtained from all participants before initiating the study.

References

Majumdar

, Biswas

, Sahu

. COVID-19 pandemic and lockdown: cause of sleep disruption, depression, somatic pain, and increased screen exposure of office workers and students of India. Chronobiol Int. 2020 Aug 2;37(8):1191–1200.

Finnane

, Jansen

, Mallan

, Daniels

. Mealtime structure and responsive feeding practices are associated with less food fussiness and more food enjoyment in children. J Nutr Educ Behav. 2017 Jan 1;49(1):11–18.

Indian Academy of Pediatrics Action Plan. Screen Time Guidelines for Parents 2020–2021. Indian Academy of Pediatrics Action Plan, 2021.

Ponti

, Bélanger

, Grimes

, . Screen time and young children: Promoting health and development in a digital world. Paediatr Child Health. 2017 Nov 27;22(8):461–477.

Tambalis

, Panagiotakos

, Psarra

, Sidossis

. Insufficient sleep duration is associated with dietary habits, screen time, and obesity in children. J Clin Sleep Med. 2018 Oct 15;14(10):1689–1696.

Smith

, Gardner

, Hamer

. Childhood correlates of adult TV viewing time: a 32-year follow-up of the 1970 British Cohort Study. J Epidemiol Community Health. 2015 Apr 1;69(4):309–313.

, Chen

, Wang

, Li

. Correlates of screen time among 8–19-year-old students in China. BMC Public Health. 2018 Dec;18(1):1–7.

Campbell

, Hesketh

, Silverii

, Abbott

. Maternal self-efficacy regarding children’s eating and sedentary behaviours in the early years: associations with children’s food intake and sedentary behaviours. Int J Pediatr Obes. 2010 Dec 1;5(6):501–508.

Rüger

, Scheer

. Effects of circadian disruption on the cardiometabolic system. Rev Endocr Metab Disord. 2009 Dec;10(4):245–260.

10.

Blissett

, Farrow

, Haycraft

. Relationships between observations and parental reports of 3–5 year old children’s emotional eating using the Children’s Eating Behaviour Questionnaire. Appetite. 2019 Oct 1;141:104323.

11.

Bocca

, Kuitert

, Sauer

, Corpeleijn

. Effect of a multidisciplinary treatment program on eating behavior in overweight and obese preschool children. J Pediatr Endocrinol Metab. 2018 May 1;31(5):507–513.

12.

WHO. Growth Reference data for 5–19 years. BMI for Age. WHO, 2007.

13.

Klakk

, Wester

, Olesen

, . The development of a questionnaire to assess leisure time screen-based media use and its proximal correlates in children (SCREENS-Q). BMC Public Health. 2020 Dec;20(1):1–2.

14.

Wardle

, Guthrie

, Sanderson

, Rapoport

. Development of the children’s eating behaviour questionnaire. J Child Psychol Psychiatry Allied Discip. 2001 Oct;42(7):963–970.

15.

Benítez-Porres

, Alvero-Cruz

, Sardinha

, López-Fernández

, Carnero

. Cut-off values for classifying active children and adolescents using the Physical Activity Questionnaire: PAQ-C and PAQ-A. Nutr Hosp. 2016;33(5): 1036–1044.

16.

Indian Academy of Pediatrics. Indian Academy of Pediatrics Action Plan: Guidelines for Normal Sleep and Physical Activity 2020–2021. Indian Academy of Pediatrics, 2021.

17.

Ministry of Health and Family Welfare. National Family Health Survey 2019–21 (NFHS-5). India Fact Sheet. 2019–2021. Ministry of Health and Family Welfare, 2021.

18.

Robinson

, Banda

, Hale

, . Screen media exposure and obesity in children and adolescents. Pediatrics. 2017 Nov;140(Supplement_2):S97–S101.

19.

Pearson

, Biddle

, Griffiths

, Johnston

, Haycraft

. Clustering and correlates of screen-time and eating behaviours among young children. BMC Public Health. 2018 Dec;18(1):1–9.

20.

Orben

, Przybylski

. Screens, teens, and psychological well-being: Evidence from three time-use-diary studies. Psychol Sci. 2019 May;30(5):682–696.

21.

Rosen

, Lim

, Felt

, . Media and technology use predicts ill-being among children, preteens and teenagers independent of the negative health impacts of exercise and eating habits. Comput Human Behav. 2014 Jun 1;35: 364–375.

22.

Hale

, Kirschen

, LeBourgeois

, . Youth screen media habits and sleep: sleep-friendly screen behavior recommendations for clinicians, educators, and parents. Child Adolesc Psychiatr Clin N Am. 2018 Apr 1;27(2):229–245.

23.

Tharner

, Jansen

, Kiefte-de

Jong JC

, . Toward an operative diagnosis of fussy/picky eating: a latent profile approach in a population-based cohort. Int J Behav Nutr Phys Act. 2014 Dec;11(1):1–1.

24.

Morin

, Turcotte

, Perreault

. Relationship between eating behaviors and physical activity among primary and secondary school students: results of a cross-sectional study. J Sch Health. 2013 Sep;83(9):597–604.

25.

Jago

, Stamatakis

, Gama

, . Parent and child screen-viewing time and home media environment. Am J Prev Med. 2012 Aug 1;43(2):150–158.

26.

Wethington

, Pan

, Sherry

. The association of screen time, television in the bedroom, and obesity among school-aged youth: 2007 national survey of children’s health. J Sch Health. 2013 Aug;83(8):573–581.

27.

Hands

, Chivers

, Parker

, Beilin

, Kendall

, Larkin

. The associations between physical activity, screen time and weight from 6 to 14 yrs: the Raine Study. J Sci Med Sport. 2011 Sep 1;14(5):397–403.