Sleep Problems and Their Associations with Digital Screen Exposure Among 2 to 5 Years Old Children in Chandigarh,a North Indian Union Territory

Abstract

Background:

Watching television and other electronic devices can adversely affect children’s sleep. This study aims to ascertain the association of sleep problems with digital screen exposure (DSE) among 2- to 5-year-old children in Chandigarh, India.

Methods:

A cross-sectional study was conducted among 400 randomly selected families having 2- to 5-year-old children, using a validated DSE questionnaire and the standard child’s sleep habits questionnaire abbreviated, from October 2017 to March 2018. The American and Indian Academy of Pediatrics guidelines were used to define higher DSE as more than 1 h per day. The multivariate binary logistic regression analysis was performed using IBM SPSS Statistics for Macintosh, Version 26.0 (IBM Corp., New York, USA), to identify significant predictors of sleep problems.

Results:

Boys (51.5%) and girls (48.5%) were equally represented. On average, children (3.5 ± 0.9 years) slept for 10 ± 1.6 h per day. Bedtime sleep resistance (15.1% vs 11%) and sleep behavior problems (11.8% vs 5.6%) were significantly (P < .05) higher among children with higher DSE than children having DSE of less than 1 h per day. The significant predictors of sleep problems were children living in a nuclear family (adjOR = 2.4, CI [1.1, 5.3]), watching non-educational digital media content (adjOR = 2.6, 2.36, CI [1.1, 6.2]), and absence of digital media rules at home (adjOR = 3.9, CI [1.3, 12]). In the subgroup analysis, children having higher DSE (adjOR = 2.4, CI [1.1, 4.9]) had a significantly greater probability of bedtime resistance, and those living in a nuclear family (adjOR = 1.7, CI [1.1, 2.7]) had a significantly greater probability of morning waking-up problems.

Conclusion:

Sleep problems were significantly associated with higher DSE among young children in Chandigarh, India.

Keywords

Sleep behaviors digital screen exposure screen-time sleep problems sleep duration

Introduction

Adequate sleep is critical for day-to-day functioning and mental and physical well-being. Digital screen exposure (DSE), including television (TV) viewing or other digital screens, can cause sleep problems, especially among young and vulnerable children.¹ These sleep problems and the DSE might have further increased significantly during the COVID-19 pandemic because of lockdowns, closure of open spaces for outdoor activities, school closures, and online learning modes. Several sleep problems are associated with impaired cognitive functioning, learning, attention, and poor school performance.²

There are reports of a significant association between using electronic media in bed before going to sleep and sleep behaviors and problems among 1 and a half to 3-year-old children.³ Vandewater et al (2005) reported that 35% of American children (0 to 6 years) live in homes where the TV was switched on in the background while they play.⁴ A TV switched on in the background and uncontrolled digital media content, directly and indirectly, affects a child’s sleep behavior.^5,6 A Spanish study conducted among 2 to 4 and 6 to 9-year-olds reported that every hour per day of TV viewing decreased sleep duration and led to lower well-being among children.⁷ As TV viewing adversely influences the balance of biological, psychological, and sleep mechanisms,^1,8 there has been a global increase in sleep problems among children aged 6 to 8.⁹

TV viewing lessens parents’ engagement with their children and makes them more vulnerable to digital media content, eventually leading to sleep problems.¹⁰ This reduced parent-child interaction might lead to multiple adverse health and behavioral outcomes. The social and physical environment at home could increase DSE among children.⁵ Although the Indian Academy of Pediatrics, 2020,¹¹ and American Academy of Pediatrics, 2016,¹² recommend only 1 h per day of age-appropriate, interactive digital media exposure for a 2 to 5 years old child under adult supervision, 6 in 10 Indian children (2 to 5 years old) have been found to have DSE higher than that recommended for their age in a study.⁶ The associations of sleep problems with DSE are unexplored among young children, especially in India.⁶ This paper presents the findings on the prevalence of sleep problems and their association with DSE. The results of this study might be helpful to guide future research, especially in the Southeast Asian Region and formulate clinical practice guidelines or recommendations for safe and healthy digital media usage among young children.

Methods

A cross-sectional study was conducted among 400 children aged 2 to 5 years old in Chandigarh, a Union Territory in the north of India from October 2017 to March 2018. The sample size “n” was calculated using the formula “n = 4pq/l²,” where “p” is the prevalence and assumed as 50% of higher DSE, “q” is “p-1,” and “l” is the precision assumed 8.¹³ We had assumed a nonresponse rate of 15% and design effect of 2 to counter cluster effect to have a final sample size of 360. Nearly 48 families (12%) refused to participate in this study during household visits. As we had estimated the sample assuming a nonresponse rate of 15%, hence refusal rate was being taken care of at the time of sample size calculations. Also, we recruited more (n = 400) participants than the calculated sample size (n = 360).

A multistage cluster random sampling technique was used to select the households/families from the study area. A cluster was assumed to be a catchment area catered to by an auxiliary nurse midwife (ANMs) in Chandigarh. Generally, she caters to a population of 4000 to 10,000. The list of all the ANMs (n = 219) enrolled under the Reproductive and Child Health (RCH) program in Chandigarh was obtained from the program officer. In the first stage, we selected 10 such clusters (9 urban and 1 rural) to represent Chandigarh’s population as per probability proportion to size by a simple random sampling technique through generating random numbers on Microsoft Excel, version 2019. The first 9 clusters of ANMs for urban and 1 rural cluster were chosen. In the second stage, the annual health registers of the selected ANMs were obtained to identify and list the households with a 2-to-5-year-old child in their catchment area. 36 households from this list were selected by simple random sampling from each cluster to meet the desired sample size by computer-generated random numbers. If a family was not available, they were contacted over the phone and revisited if they had given consent to participate in study. Eligibility criteria were family having at least 1 electronic device. Each family was visited at their homes to obtain data from the principal caregiver of the child. The younger child was recruited from families with 2 or more children. Only children previously diagnosed with long-term or chronic, or congenital illnesses were excluded. The detailed methodology of the study has been described elsewhere.⁶

Data Collection Methods

The lead author visited the selected household and interviewed the primary caregivers of the children face-to-face by using the following questionnaires.

Digital Screen Exposure Questionnaire (DSEQ)

A validated, pretested, semi-structured, and bilingual (in English and Hindi) DSEQ was used to assess the DSE duration and behaviors.¹⁵ The DSEQ had good internal consistency (Cronbach’s α = 0.73-0.82) and good interrater agreement (Kappa 0.75, 95% CI [0.72, 0.78]).^6,14,15 DSEQ was also used to obtain background information from the primary caregivers of the children, media rules at home, media literacy of the parents, and level of physical activity. The information regarding the digital media content watched by the children was obtained by asking 12 questions included in the pretested and validated digital screen exposure questionnaire (DSEQ).¹⁵ It was segregated into educational and non-educational digital media content. Educational content included using media devices for completing homework assignments, learning poems, rhymes, ABC, etc, learning math, numbers, tables, to recognize shapes/sounds/colors, to learn letters, words, vocabulary, language, to draw, write, to watch stories, etc. Non-educational media content included video calling applications to talk to family/friends, watch adult programs (soap opera, news, sports, movies, etc), and watch random things for enjoyment (music, advertisements, baby TV, click photos, etc).

Child’s Sleep Habits Questionnaire-Abbreviated (CHSQ-A)

A standard Child’s Sleep Habits Questionnaire-Abbreviated (CHSQ-A) version was used for measuring the child’s sleep problems. It was validated in Asian settings and comprised of 22 items.¹⁶ The items of the questionnaire are rated on a 5-point Likert-type scale where “always” signifies a sleep problem that occurred 7 times in the past week, “usually” if the behavior occurred 5 to 6 times in the past week, “sometimes” for 2 to 4 times that week, “rarely” for 1 time that week, and “never” for zero times that week.¹⁷

Data Management and Analyses

The statistical analyses and management were done using the IBM SPSS Statistics for Macintosh, version 25.0. The list of dependent and independent variables and analyses performed is presented in supplementary Table S1.

The cumulative DSE was calculated from all electronic devices viewed by the child separately on weekdays and weekends, as the child’s DSE is different on the weekdays and weekends.¹⁸ We calculated the average DSE per day in minutes based on the weighted DSE average of the weekday (5 weekdays [Monday to Friday]) and weekend (2 weekend [Saturday and Sunday]) using the formula:

\begin{matrix} A v e r a g e D S E p e r d a y (\min u t e s) = \\ (\begin{array}{l} [W e e k d a y D S E i n \min u t e s \times 5] + \\ [W e e k e n d D S E i n \min u t e s \times 2] \end{array}) / 7 \end{matrix}

We considered DSE for 2 to 5 years old children to be of more than 1 h per day as high level, based on the Indian Academy of Pediatrics guidelines, 2020, and American Academy of Pediatrics guidelines, 2016.^11,12 Accordingly, the average DSE of the child was expressed as a categorical variable with 2 categories, ie, the proportion of children having DSE of “more than 1 h” and “less than 1 h” per day.

The scores for considering the sleep behaviors as problematic were based on the results of an Indonesian study.¹⁶ The sleep problems were dichotomized as per the scores given in the CHSQ into “present” or “absent” based upon the cutoff scores in each subcategory, ie, “total sleep problems” at 41.12 (standard deviation (SD) = 5.49), “total sleep behaviors” at 12.36 (SD = 2.2), “total waking during the night” at 2.76 (SD ± 1), “total morning wake-up problems” at 7.12 (SD = 1.7), and “total bedtime resistance” at 18.8 (SD = 3).¹⁸ Sleep duration was considered normal between 7 h and 10 h per day for 2 to 5-year-olds and categorized into “low” at less than 7 h per day, “normal” at 7 h to 10 h per day, and “high” more than 10 h per day.¹⁷

In the bivariate analyses, the chi-square test was applied to test the significance (P < .05) of the difference in proportions between the various groups. The significance level was considered to be significant at 95% confidence intervals (CI). The intra-class correlation of the scores of individual sleep problems was estimated with the weighted average of DSE in minutes.

We performed binary multivariate logistic regression analysis as we were interested in examining the likelihood of the “presence” of sleep problems and its subcategories influenced by different predictor variables. Because the dependent variable, ie, sleep problems and its subcategories, were dichotomized, the application of the linear regression model was redundant.¹⁹ The data were analyzed for the subcategories of sleep problems, which were computed as categorical variables (supplementary Table S1). The independent variables were child, caregiver, and home-related variables.

Ethical Considerations

The Postgraduate Institute of Medical Education and Research’s Ethics Committee permitted to conduct the study. (INT/IEC/2019/000711). The Director of Health Services, Chandigarh, Union Territory, permitted us to conduct the study in the community setting. (VO/FW/17/1894, Dated August 30, 2017). The participant information sheet was given to the study participants, and they were explained the study objectives and procedures in their preferred language (English/Hindi/Punjabi). Written informed consent was obtained from the parents/legal guardian of the children before collecting the study information. Participation in the study was voluntary, and all the participant’s information was kept confidential.

Results

Background Characteristics

The mean age of the children was 3.5 (SD ± 0.9) years old. The boys (51.5%) and girls (48.5%) were almost equally represented in this study. A majority (55.8%) of the families belonged to the higher socioeconomic status, and mostly (56%) lived as nuclear families. The TV was mostly (80%) placed in the parents’ bedroom. Almost all the children (97%) were co-sleeping with their parents at home. More than half (53.8%) of the families kept the TV switched on while the child played or slept in the room (Table 1). In 95.3% of cases, mothers provided data, and in 4.9% cases, by fathers, grandparents, or paternal aunts.

Prevalence

Sleep Problems

The prevalence of total nighttime waking-up problems was at 23.8%, total morning waking-up problems at 23.3%, total bedtime resistance at 11.8%, total sleep behavior problems at 9.3%, and total sleep problems was at 7.8% Figure 1. The average sleep duration of the children was 10 ± 1.5 h per day.

Figure 1.

Note: * Multiple options might have been chosen; # The sleep problems were dichotomized into “present” or “absent” based upon the cutoff scores in each subcategory, ie, “total sleep problems” at 41.12 (standard deviation (SD) = 5.49), “total sleep behaviors” at 12.36 (SD = 2.2), “Nighttime waking” at 2.76 (SD ± 1), “total morning wake-up problems” at 7.12 (SD = 1.7), and “total bedtime resistance” at 18.8 (SD = 3).

DSE

About 59.5% of children watched TV for more than 1 h (high level; Table 1). The average DSE was 1.9 h per day (interquartile range = 0.6-2.6).

Table 1.

Background Characteristics of the Children

Characteristics of the Children	Mean	–
Mean age of the children in years	3.45	SD 0.9
Average DSE in hours per day	1.9	IQR 0.6-2.6
Sleep duration in hours per day	10	SD 1.5
–	Total (N = 400)	Percentage (%)
Sex of the child	–	–
Boys	206	51.5
Girls	194	48.5
Age of the child	–	–
2 to 3 years	167	41.8
3 to 4 years	109	27.3
4 to 5 years	124	31
Socioeconomic status^¥	–	–
Higher (above $393)	223	55.8
Middle and lower (below $393)	177	44.3
Type of family	–	–
Nuclear	224	56
Joint or extended	176	44
TV switched on in the background while the child is playing there	215	53.8
Digital screen exposure	–	–
<1 h per day	162	40.5
1 h to 2 h per day	108	27
2 h to 3 h per day	60	15
>3 h per day	70	17.5
Child falls asleep with the following members*	–	–
Parents	388	97
Other family members	12	3
Siblings	4	1
TV placement*	–	–
Parents’ bedroom	320	80
Living room	68	17
Dining room	9	2.3
Other rooms (lobby, child’s bedroom, etc)	23	5.6

Note: * Multiple responses might be possible so the percentage might not add up to 100%.

Abbreviations: TV, television; SD, standard deviation; IQR, inter-quartile range; < less than; >more than

¥ As per B.G. Prasad scale 2016 classification at United States $1 = ₹74.3 on June 23, 2021.

Association of Individual Sleep Problems with DSE

The bivariate analysis showed that total bedtime sleep resistance (15.1% vs 11%) and total sleep behavior problems (11.8% vs 5.6%) were significantly (P < .05) higher among children with higher DSE (more than 1 h per day) as compared to children watching electronic devices up to 1 h per day (Table 2).

Correlation of Individual Sleep Problems with DSE

The total sleep problems score (r = + 0.142), total bedtime resistance’s score (r = + 0.146), and the total sleep behaviors’ score (r = + 0.1) had significant (P < .05) positive correlations with the DSE of the child (supplementary Table S2).

Correlation of Children’s Sleep Duration and Problems with Level of Physical Activity

The total sleep problems’ score had insignificant positive correlations with the average physical activity of the child (supplementary Table S3).

Predictors

Total Sleep Problems

The significant predictors of having total sleep behavioral problems among the children as per multivariate binary logistic regression analysis were living in a nuclear family (adjusted odds ratio (adjOR) = 2.4, CI [1.1, 5.3], P = .03), watching non-educational digital media content (adjOR = 2.6, CI [1.1, 6.2], P = .03), and absence of digital media rules at home (adjOR = 3.9, CI [1.3, 12], P = .01; Table 3).

Table 2.

Associations of Digital Screen Exposure with Sleep Problems Among Children Aged 2 to 5 Years

Variables Related to Sleep	–	Screen Time			P Value
–	Scores (standard deviation)	<1 h per day N = 162 (40.5%)	>1 h per day N = 238 (59.5%)	Total N = 400 (100%)	–
Total sleep duration	–	–	–	–	.88
<7 h per day	–	10 (6.2)	12 (5)	22 (5.5)	–
7 h to 10 h per day	–	82 (50.6)	123 (51.7)	205 (51.2)	–
>10 h per day	–	70 (43.2)	103 (43.3)	173 (43.3)	–
Total sleep problems	41.12 (5.49)	–	–	–	.08
Absent	–	154 (95.1)	215 (90.3)	369 (92.2)	–
Present	–	8 (4.9)	23 (9.7)	31 (7.8)	–
Bedtime sleep resistance	18.8 (3)	–	–	–	.01
Absent	–	151 (93.2)	202 (84.9)	353 (88.3)	–
Present	–	11 (6.8)	36 (15.1)	47 (11.8)	–
Sleep behavior problems	12.36 (2.2)	–	–	–	.03
Absent	–	153 (94.4)	210 (88.2)	363 (90.8)	–
Present	–	9 (5.6)	28 (11.8)	37 (9.3)	–
Morning waking-up problems	7.12 (1.7)	–	–	–	.52
Absent	–	127 (78.4)	180 (75.6)	307 (76.8)	–
Present	–	35 (21.6)	58 (24.4)	93 (23.3)	–
Night time waking-up	2.76 (1)	–	–	–	.41
Absent	–	127 (78.4)	178 (74.8)	305 (76.3)	–
Present	–	35 (21.6)	60 (25.2)	95 (23.8)	–

Note: * < less than; > more than.

Individual Sleep Problems

The child’s average DSE exceeding the guidelines (adjOR = 2.4, CI [1.1, 4.9], P = .02) was a significant predictor of total bedtime resistance problems. Also, living in a nuclear family (adjOR = 1.7, CI [1.1, 2.7], P = .03) was a significant predictor of difficulties with morning waking up problems (Table 3).

Table 3.

Predictors of Sleep Problems Among Children 2 to 5 Years as per Multivariate Binary Logistic Regression Model in Chandigarh

–	Comparative Group (Reference)	Total Sleep Problems adjOR, (CI)	Bedtime Resistance adjOR, (CI)	Morning Wake-up Problems adjOR, (CI)	Night Time Wakings adjOR, (CI)	Sleep Behavioral Problems adjOR, (CI)	Sleep Duration adjOR, (CI)
Age	Less than 3.5 years	0.8 (0.3, 1.9)	1 (0.5, 2)	1 (0.6, 1.7)	0.7 (0.4, 1.2)	0.8 (0.4, 1.7)	0.6 (0.2, 1.8)
–	(More than 3.5 years)	1	1	1	1	1	1
Gender	Boys	1.1 (0.5, 2.5)	1 (0.6, 2)	0.8 (0.5, 1.3)	1.4 (0.8, 2)	0.9 (0.5, 1.9)	0.5 (0.2, 1.2)
–	(Girls)	1	1	1	1	1	1
Daycare services	Not attending	1 (0.4, 2.7)	0.9 (0.4, 2)	0.9 (0.5, 1.5)	0.9 (0.5, 1.6)	1.3 (0.6, 3)	1 (0.3, 2.9)
–	(Attending)	1	1	1	1	1	1
Family type	Nuclear	2.4* (1.1, 5.3)	2.1 (1.1, 4.1)	1.7* (1.1, 2.7)	0.9 (0.5, 1.4)	1.1 (0.5, 2.1)	1.7 (0.7, 4.2)
–	(Joint/extended)	1	1	1	1	1	1
Socioeconomic status	Above middle-class	0.6 (0.2, 1.4)	0.8 (0.4, 1.5)	0.7 (0.5, 1.2)	1 (0.6, 1.6)	0.6 (0.3, 1.2)	2.5 (0.9, 6.7)
–	(Middle-class and below)	1	1	1	1	1	1
Average DSE	Above 1 h	2 (0.8, 5)	2.4* (1.1, 4.9)	1.2 (0.7, 2)	1.2 (0.7, 2)	2.2 (0.9, 4.9)	1.7 (0.7, 4.4)
–	(Below 1 h)	1	1	1	1	1	1
Media content watched	Random	2.6* (1.1, 6.2)	1.7 (0.8, 3.6)	1.7 (1, 3)	1 (0.5, 1.7)	0.9 (0.4, 2.1)	3.9 (0.8, 17.8)
–	(Educational)	1	1	1	1	1	1
Media rules at home	Absent	3.9^¥ (1.3, 12)	2.7 (1, 7.3)	1.6 (0.6, 4)	1.1 (0.4, 2.9)	1.3 (0.4, 4.2)	1.7 (0.2, 14.4)
–	(Present)	1	1	1	1	1	1
TV in the background	Switched off	0.7 (0.3, 1.5)	0.7 (0.4, 1.4)	0.7 (0.5, 1)	1 (0.6, 1.5)	0.8 (0.4, 1.6)	0.5 (0.2, 1.1)
–	(Switched on)	1	1	1	1	1	1

Note:^*Level of significance = <0.05; ¥ the level of significance = <0.01.

$ Dependent variables were the presence and absence of sleep problems (the subcategories of sleep problems included average sleep duration, “total sleep problems” at 41.12 (standard deviation (SD) = 5.49), “total sleep behaviors” at 12.36 (SD = 2.2), “total waking during the night” at 2.76 (SD ± 1), “total morning wake-up problems” at 7.12 (SD = 1.7), and “total bedtime resistance” at 18.8 (SD = 3).

Abbreviations: adjOR, adjusted odds ratio; CI, confidence interval; DSE, digital screen exposure.

Discussion

This study has provided evidence that a higher DSE (more than 1 h per day) might be associated with children’s (2 to 5 years) sleep problems in Chandigarh, North India. The total sleep problems, bedtime resistance, and sleep behaviors were significantly positively correlated with the child’s DSE. The significant predictors of having sleep problems were children living in a nuclear family, watching non-educational digital media content, and living in homes where digital media rules were absent.

Children were primarily co-sleeping with their parents in the parents’ bedroom in this study, which is similar to Japanese and other Indian studies.^16,20 The prevalence of co-sleeping in this study was considerably higher than that reported among American children (5%–52%) but similar to another Indian study (93%).^21,22 A higher (51.5%) proportion of American parents used electronic devices to help their children (0 to 5 years) sleep as compared to only one-third of caregivers in the present study.²³ Caregivers also reported keeping their children occupied with electronic devices to watch their favorite shows or work in America,²³ in contrast to the American Academy of Pediatrics guidelines strictly prohibiting DSE before sleep for children.¹²

Existing evidence suggests that TV in the bedroom could reduce sleep time because of the displacement of the child’s circadian rhythm by watching bright electronic devices before bedtime.²⁴ A Chilean study reported that nearly half of the families (51%) have a TV in the bedroom,²⁵ which was distinctly lesser than in the present study (75%). A Japanese study suggested that having a device like a TV or a videogame in the bedroom increased the child’s (6-12 years) activity before sleep time.²⁶ However, our results did not show any association with the TV switched on in the room where the child slept or played with the sleep problems. Most of the mothers in our study were homemakers (86%) and primary caregivers (95.3%). So, probably the mothers engaged the child in other activities even when the TV was on in the background or controlled the electronic devices at home.⁶

A Swedish study in 2001 observed that 4.9% of children (6-8 years) suffer from sleep problems,⁹ and our research, conducted almost after 2 decades, estimated that the sleep problems in children (2-5 years) have nearly doubled (7.8%). However, the sleep problems observed in this study (7.8%) were lesser than those observed among American kindergarteners to fourth graders (37%) and among 3 to 10 years old Indian children (42.7%).^1,20 These dissimilarities might be because of the inclusion of older children in these studies.

The present study’s average sleep duration of 10 ± 1.5 h per day was well within the recommended range for this age group.¹⁷ These results are comparable to another Indian study among children aged 3 to 10 years who slept for 10.32 ± 1.18 h per day.²⁰ Warren et al (2016) concluded that the average sleep duration was significantly associated with sedentary behaviors among American fourth to sixth graders.²⁷ But, the relationship of sleep duration with DSE was negative and significant in our study. A multicenter birth cohort study demonstrated that every 1 h per day increase in the DSE decreased the sleep duration at follow-up visits and was associated with 3 to 8 lesser minutes of nighttime sleep and significantly reduced sleeping consistently.⁷ Children who complied with the American Academy of Pediatrics guidelines slept for an additional 20 min to 26 min.²⁸ Also, another Indian study observed a reduction in sleep duration with an increase in the DSE’s duration, which was not observed in this study.²⁹ This difference could be because of the total duration of sleep (day time and nighttime) calculated as a cumulative score in the present study, the difference in study design (cohort),²⁸ and the inclusion of older children (up to 15 years).²⁹

A national survey of American children’s (6 months to 16 years) health concluded that DSE had a modest effect on their sleep. However, other social and contextual factors may have a more prominent influence, similar to the present study’s findings.²⁸ A meta-analysis highlighted the impact of digital media content on the child’s fears and anxiety.³⁰ Similarly, studies from America and India have reported bedtime resistance, behavioral problems, reduced bedtime sleep behaviors, excessive daytime sleepiness, awakening during the night, regularity and duration of sleep, and sleep-disordered breathing in children (under 15 years).^9,29 The Indian and American Academy of Pediatrics advises only adult-supervised, age-appropriate, and high-quality media content specifically for children 2 to 5 years old.^11,12

A longitudinal Californian study among fourth to sixth graders predicted that nightly sleep duration was significantly associated with sedentary digital media viewing and the presence/absence of parental DSE rules at home.²⁷ Likewise, in the present study, sleep problems among children were related to the lack of DSE rules at home. Our data concluded that children whose caregivers established digital media rules at home generally slept more and engaged in less sedentary behaviors than children whose caregivers did not impose such restrictions. Nevertheless, there were very few families with any digital media rules at home, so the results might not significantly affect sleep problems in our study. The prevalence of a high level of DSE (59.5%) in our study can be compared to a Malaysian study (63.05%), including children aged 0.5 to 12 years.³¹ However, the prevalence of DSE is notably lower than in Canadian children (82%) aged 3 to 5 years old.³²

Warren et al, in 2016, concluded that sex and age-related differences existed in sleep behaviors among American children (fourth through sixth grade).²⁷ Younger American children studying in grades 1 to 2 were more likely to have sleep problems than the older children studying in grades 3 to 4.¹ However, in this study, sleep problems were not related to age, sex, and socioeconomic status, also supported by another Indian study.²⁰ Similar to our findings, an Indian study indicated that sleep-related problems were significantly higher if the child lived in a nuclear family (adjOR 2.41; CI [1.04, 5.57]).²⁰ As per our understanding, parents usually have a smaller accommodation with easy access to electronic devices in a nuclear family. In addition, when the parent has to work, they allow the child to watch electronic devices without supervision. This unsupervised and nonspecific content watched by the child leads to a higher DSE. While in a joint or an extended family, other family members might aid in caretaking, have other screen-free rooms, and siblings to play with that might act as distractions. The American Academy of Pediatrics explicitly mentions content-specific supervised DSE in 2 to 5 years old.¹²

This study’s major strength is that this is one of the first extensive community-based studies on this topic and age group in North India. Moreover, this study measures the DSE from all devices used by the child, unlike previous studies, allowing a consolidated measurement of DSE. It also highlighted sleep problems (bedtime resistance, nighttime waking, sleep behaviors, morning wake-up, and sleep duration) among young children. We performed advanced statistical analysis to interpret individual factors affecting various categories of sleep problems in children. This study’s results might reinforce the role of primary caregivers or parents in limiting the DSE at home as per the recommended guidelines.^5,12 The cross-sectional analyses and dichotomized variables might not examine all the potential explanatory factors. The CHSQ-A version for children above 4 years of age was used. Hence, results need to be interpreted carefully regarding sleep habits for children 2 to 5 years old. However, the questionnaire was pretested and modified before data collection. Also, there might be recall bias as the questionnaire was proxy-reported by caretakers or parents. Lastly, the present study could not explore the underlying causes for parents not seeking consultation despite confronting sleep problems in their children.

Conclusion

We conclude that sleep problems were significantly associated with higher DSE (more than 1 h per day) among children aged 2 to 5 years old in Chandigarh, a North Indian Union Territory.

Supplemental Material

Supplemental material for this article is available online.

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

We received the funding from Indian Council of Medical Research, New Delhi, for supporting Dr Nimran Kaur (first author) in pursuing her Ph.D. (3/1/3/Next-100/JRF-2015/HRD-SS/03/10451/135); and Research Grant Cell, PGIMER, Chandigarh, India, as intramural funds (71/2-Edu-16/92, Dated August 1, 2018). The funding agencies did not sanction the publication cost of the manuscript. The funders had no role in designing the study, data collection, analysis, interpretation, report writing, and submitting the paper for publication.

Statement of Informed Consent and Ethical Approval

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

Lay Summary

What Is Already Known: ·     TV viewing can cause sleep problems, bedtime resistance, delayed sleep onset, sleep anxiety, nighttime waking, and reduced sleep duration in preschool children.
·           TV viewing reduces parents’ engage- ment with the child, making the children more vulnerable to digital media content leading to sleep problems. What This Study Adds: ·     This is the first community-based study that provides evidence on the associations of sleep problems with excessive digital screen exposure among children aged 2 to 5 years in an Indian city.
· The average digital screen exposure among children was measured with a validated digital screen exposure questionnaire in the Indian settings from all types of devices used.
·                The significant predictors of sleep problems among children aged 2 to 5 years were living in a nuclear family, watching non-educational digital media content, and absence of digital media rules at home.

References

Owens

, Spirito

, McGuinn

, Nobile

. Sleep habits and sleep disturbance in elementary school-aged children. J Dev Behav Pediatr. 2000;21(1):27–36. 10.1097/00004703-200002000-00005.PMID:10706346.

Sadeh

. Consequences of sleep loss or sleep disruption in children. Sleep Med Clin. 2007;2:513–520. 10.1016/j.jsmc.2007.05.012

Fossum

, Nordnes

, Storemark

, Bjorvatn

, Pallesen

. The association between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chronotype. Behav Sleep Med. 2014;12(5):343–357. 10.1080/15402002.2013.819468. Epub 2013 Oct 24. PMID: 24156294.

Vandewater

, Bickham

, Lee

, Cummings

, Wartella

, Rideout

. When the television is always on: Heavy television exposure and young children’s development. Am Behav Sci. 2005;48:562–577. 10.1177/0002764204271496.

Kaur

, Gupta

, Malhi

, Grover

. Screen time in under-five children. Indian Pediatrics. 2019;56:773–788. 10.1007/s13312-019-1638-8.

Kaur

, Gupta

, Malhi

, Grover

. prevalence of screen time among children aged 2 to 5 years in Chandigarh, a North Indian Union Territory. J Dev Behav Pediatr. 2021. 10.1097/DBP.0000000000000964. Epub ahead of print. PMID: 34016828.

Marinelli

, Sunyer

, Alvarez-Pedrerol

, Iñiguez

, Torrent

, Vioque

, Turner

, Julvez

. Hours of television viewing and sleep duration in children: a multicenter birth cohort study. JAMA Pediatr. 2014;168(5):458–464. 10.1001/jamapediatrics.2013.3861. PMID: 24615283.

Gandolphi

, Okazaki

, Nozoe

, Polesel

, Andersen

, Tufik

. Influence of sleep disorders on television viewing time, diabetes and obesity. Diabet Med. 2015;32(1):141–142. 10.1111/dme.12603. PMID: 25307170.

Smedje

, Broman

, Hetta

. Associations between disturbed sleep and behavioural difficulties in 635 children aged six to eight years: a study based on parents’ perceptions. Eur Child Adolesc Psychiatry. 2001;10(1):1–9. 10.1007/s007870170041. PMID: 11315530.

10.

Wright

, Huston

, Vandewater

, Bickham

, Scantlin

, Kotler

. American children’s use of electronic media in 1997: evidence from a national survey. J. Appl. Dev. Psychol. 2001;22:31–47.

11.

Nemours KidsHealth. Screen time guidelines for teens (for parents) 2020:1–12. https://kidshealth.org/en/parents/screentime-teens.html (April 24, 2021).

12.

Reid Chassiakos

, Radesky

, Christakis

, Moreno

, Cross

. Children and adolescents and digital media. Pediatrics. 2016;138(5):e20162593. 10.1542/peds.2016-2593. PMID: 27940795.

13.

Kirkwood

, Sterne

JAC

. Essential medical statistics. 2nd ed. Massachusetts, USA: Wiley/Blackwell (10.1111); 2003.

14.

Kaur

, Gupta

, Malhi

, Grover

. A multicomponent intervention to reduce screen time among children aged 2-5 years in Chandigarh, North India: protocol for a randomized controlled trial. JMIR Res Protoc. 2021;10(2):e24106. 10.2196/24106.

15.

Kaur

, Gupta

, Kiran

, Malhi

, Grover

. Development and evaluation of the digital-screen exposure questionnaire (DSEQ) for young children. PLoS One. 2021;16(6):e0253313. 10.1371/journal.pone.0253313.

16.

Irwanto Rehatta

, Hartini

, Takada

. Sleep problem of children with autistic spectrum disorder assessed by children sleep habits questionnaire-abbreviated in Indonesia and Japan. Kobe J Med Sci. 2016;62(2):E22–E26.

17.

Owens

, Spirito

, McGuinn

. The Children’s Sleep Habits Questionnaire (CSHQ): psychometric properties of a survey instrument for school-aged children. Sleep. 2000;23(8):1043–1051.

18.

Chang

, Park

, Yoo

, Lee

, Shin

. Electronic media exposure and use among toddlers. Psychiatry Investig. 2018;15(6):568–573. 10.30773/pi.2017.11.30.2. Epub 2018 May 24.

19.

Gujarati

, Porter

DC.

Gunasekar

Basic econometrics. 5th ed. New Delhi: Tata McGraw-Hill Education Private Ltd.; 2009:784.

20.

Murthy

, Bharti

, Malhi

, Khadwal

. Sleep habits and sleep problems in healthy preschoolers. Indian J Pediatr. 2015;82(7):606–611.

21.

Lozoff

, Wolf

, Davis

. Cosleeping in urban families with young children in the United States. Pediatrics. 1984;74:171–182.

22.

Bharti

, Malhi

, Kashyap

. Patterns and problems of sleep in school going children. Indian Pediatr. 2006;43:35–38.

23.

Taveras

, Hohman

, Price

, Gortmaker

, Sonneville

. Televisions in the bedrooms of racial/ethnic minority children: how did they get there and how do we get them out? Clin Pediatr (Phila). 2009 Sep;48(7):715–719. 10.1177/0009922809335667.

24.

LeBourgeois

, Hale

, Chang

, Akacem

, Montgomery-Downs

, Buxton

. Digital media and sleep in childhood and adolescence. Pediatrics. 2017;140(Suppl 2):S92–S96. 10.1542/peds.2016-1758J.

25.

Marinelli

. Impact of television on the quality of sleep in preschool children. Sleep Med. 2016;20:138–139. 10.1016/j.sleep.2015.07.011.

26.

Oka

, Suzuki

, Inoue

. Bedtime activities, sleep environment, and sleep/wake patterns of Japanese elementary school children. Behav Sleep Med. 2008;6(4):220–233. 10.1080/15402000802371338.

27.

Warren

, Riggs

, Pentz

. Executive function mediates prospective relationships between sleep duration and sedentary behavior in children. Prev Med. 2016;91:82–88. 10.1016/j.ypmed.2016.07.024.

28.

Przybylski

. Digital screen time and pediatric sleep: evidence from a preregistered cohort study. J Pediatr. 2019;205:218–223.e1. 10.1016/j.jpeds.2018.09.054.

29.

Bansal

, Mahajan

. Impact of mobile use amongst children in rural area of Marathwada region of Maharashtra, India. Int. J. Contemp. Pediatr. 2017;5:50. 10.18203/2349-3291.ijcp20175138.

30.

Laura

Pearce

Andy P.

Field, The impact of “scary” TV and film on children’s internalizing emotions: a meta-analysis. Hum. Commun. Res. 2016;42(1):98–121. 10.1111/hcre.12069

31.

Lee

, Wong

, Ong

, Ismail

, Deurenberg

, Poh

. Physical activity pattern of malaysian preschoolers: environment, barriers, and motivators for active play. Asia Pac J Public Health. 2016;28(5 Suppl):21S–34S. 10.1177/1010539516638155.

32.

Colley

, Garriguet

, Adamo

, Carson

, Janssen

, Timmons

, Tremblay

. Physical activity and sedentary behavior during the early years in Canada: a cross-sectional study. Int J Behav Nutr Phys Act. 2013;10:54. 10.1186/1479-5868-10-54.

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