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Journal of Public Health (Oxford, England) logoLink to Journal of Public Health (Oxford, England)
. 2010 Nov 3;33(3):392–402. doi: 10.1093/pubmed/fdq087

Sociodemographic and home environment predictors of screen viewing among Spanish school children†

Itziar Hoyos Cillero 1,✉, Russell Jago 2
PMCID: PMC3307230  PMID: 21047871

Abstract

Background

Higher screen-viewing levels increase the risk of obesity. Understanding the correlates of screen viewing is an important first step in designing interventions but there is lack of information on the correlates among Spanish children. This study examined associations among environmental, sociocultural, age variables and screen viewing among Spanish children.

Methods

Children completed a questionnaire about time spent in screen viewing. BMI was assessed and children were classified into obesity groups using International Obesity Task Force cut-off points. Parents completed a questionnaire about sociodemographic, environmental and sociocultural variables.

Results

Participants were 247 primary and 256 secondary school-aged children and their parents. Time spent in screen viewing increased with age. Males spent more time than females in screen viewing. Greater access to bedroom media sources was associated with higher screen viewing. Younger children from single-parent households and older children having a younger parent, siblings and a father who was not working were higher screen-viewers on weekends and weekdays, respectively. For older children parental TV viewing time appeared to be a significant correlate, while parental rules was a determinant predictor for younger children on weekdays.

Conclusions

Environmental and sociocultural factors influence the time children spend in screen viewing. Parents play a central role in child's screen viewing; therefore, interventions that target environmental and family TV viewing practices are likely to be effective.

Keywords: children, obesity and health promotion

Introduction

The prevalence of overweight and obesity among children and adolescents has increased in many European countries.1,2 A number of studies have reported that high levels of screen viewing increase the risk of obesity.3–6 Moreover, a small number of interventions that have focussed on reducing screen viewing have yielded reductions in adiposity.7–9 The American Academy of Paediatrics (AAP) suggest that parents should limit their child's total media time (i.e. television and electronic games) to no more than 1–2 h per day.10 As evidence indicates that many children exceed this threshold,11 there is a need to develop interventions to reduce screen viewing. The mediating variable model12 suggests that changes in screen-viewing behaviours will be achieved by understanding the mediators and moderators of behaviours. Thus, in order to reduce screen viewing, we need to understand the correlates of screen viewing and how they may differ by participant characteristics. Although sociodemographic variables of screen viewing have been more routinely assessed in the literature, few studies have examined modifiable environmental and sociocultural variables. This absence is important because it has also been suggested that there is a need to identify and focus interventions on strong and consistent modifiable correlates.12

Middle childhood and early adolescence period (ages 5–13) are transition periods of interest when social skills such as learning to make choices13 are developed and long-term pathways of behaviours are established.14,15 A peak in television (TV) usage emerges between 9 and 12 years of age16 and patterns of screen viewing from this age track into later life.15 Thus, if the correlates that influence screen viewing for school-aged children are known more sophisticated interventions can be developed.

Research on media technology in Spain has highlighted that children's media viewing time has increased in recent years.17,18 Data from the Spanish National Health Survey showed that 53.2% of Spanish adolescents aged 10–14 years old watched more than 2 h of TV per day with this figure increasing to 70.9% for weekend days.18 There is lack of information on the correlates of screen viewing among Spanish school-aged children. To the best of our knowledge, there is no Spanish study that compares correlates of screen viewing in primary and secondary school-aged children. This paper aims to: (i) describe patterns of screen viewing (TV watching, computer and console playing and overall screen viewing); and (ii) to identify sociodemographic, environmental and sociocultural correlates of screen viewing in a sample of primary and secondary Spanish school-aged children.

Methods

Sample and procedures

The schools were recruited to approximate the economic diversity of the local area based on an assessment of the economic activity that includes assessment of employment, establishments, business density and commercial establishments in Bilbao (Biscay, Spain).19 The economic activity rates for the areas where schools were located were obtained. Although this approach only provides information on the school and not where the children live it was intended to provide a reasonable range of participants from different economic neighbourhoods within the city. We invited 19 public schools (six from the highest, eight from the middle and five from the lowest economic activity level) to participate but three (one from each economic activity level) declined to participate. From the 16 schools which participated, six had only primary school-aged children (two from the highest, two from the lowest and two from the middle economic activity level), six only secondary school-aged children (two from the highest, three from the lowest and one from the middle economic activity level) and four both primary and secondary school-aged children (three from the middle and one from the highest economic activity level). This study was carried out between November 2009 and January 2010. It was approved by the University of the Basque Country Ethics Committee and written informed parental consent was obtained for all participants.

Measures

Children completed a self-administered questionnaire at school that assessed their TV viewing, computer games-playing and console games-playing hours for an average weekday and average weekend day. Six-point ordinal response scales were used with options of ‘none’, ‘1–2 h’, ‘2–3 h’, ‘3–4 h, ‘4–5 h’ and ‘more than 5 h’. Children were assisted with the completion of the questionnaire by teachers and the first author. Daily TV viewing time and daily computer games-playing and console games-playing time were summed to create an overall screen-viewing variable. In addition, children were classified as not meeting TV and electronic media use guidelines for a usual weekday and for a usual weekend day in accordance with suggested screen-viewing guidelines by the AAP (≥2 h/day).10 They were also asked about the presence of a TV, computer or console in their bedroom (yes/no). The questions were based on a published scale that has been shown to have good reliability.20 Children's height and weight were assessed using a Seca portable scale and stadiometer. Body mass index (BMI) was calculated [weight (kg)/height(m2)] and the International Obesity Task Force (IOTF) cut-off points were used to classify participants as normal weight, overweight and obese.21

Parents completed a self-administered questionnaire reporting standard sociodemographic (gender, children and parental age, parental education, family structure, presence of siblings and employment), environmental (number of household TV sets) and sociocultural information (daily parental TV viewing time and presence of TV and computer playing time rules). Parents reported their weight and height. BMI was calculated and they were classified in accordance with IOTF BMI cut-off points (underweight: <18.5, normal range: 18.5–24.99, overweight: 25–29.99 and obese: ≥30).22 All items were Spanish translations of widely used English language scales that have been shown to have good internal consistency and validity.23,24

Analysis

Participants' characteristics were compared using independent sample t-tests for continuous variables and chi-square statistics for categorical variables. Associations were assessed separately by age, gender and for a usual weekday and a usual weekend day. A logistic regression model with whether participants exceed the AAP guideline (≥2 h/day of watching TV) as the outcome was estimated with environmental (household TV set and presence of TV, computer and console in child's bedroom), sociocultural (parental TV viewing, and parental rules for TV and computer playing) and sociodemographic variables (parental age, family structure, presence of siblings, mother employment and father employment) as variable exposures. The model was adjusted for child's BMI group, parental BMI group and parental education, which were treated as confounders with all variables entered into the model in one step. The process was then repeated with ≥2 h/day engaged in overall screen viewing (i.e. TV and electronic games use combined with entertainment media) as the outcome. Robust standard errors were used to take account of the clustering of participants in schools. Alpha was set at <0.05. All analyses were performed using STATA (version 11.0, 2009; Stata Corporation, College Station, TX, USA).

Results

Descriptive data

Analyses included volunteers from 10, fifth year primary schools (10–11 years old) and 10, first year secondary schools (12–13 years old) groups. Three hundred and ninety-seven primary school-aged children were invited to participate and 247 agreed (response rate 65.1%), while 457 secondary school-aged children were invited and 256 participated (response rate 57.9%). Five hundred and nine parents (247 from the primary group and 262 from the secondary group) completed the questionnaire. Six secondary school-aged children were absent on the day of data collection due to illness.

Participant and parent characteristics are summarized by age and by gender within age group in Table 1. There were no differences in parental age between the two groups but parents of the primary school group were more educated than those of the secondary school group (P = 0.01). The children in the secondary school group had more TV sets in their homes (P = 0.01) and they also had more TV sets in their bedroom (34.6%) than the children in the primary school group (20.2%) (P < 0.01). The number of parents who spent ≥2 h/day watching TV was higher in the secondary school group (29.5%) than in the primary school group (21.6%) (P = 0.04). The number of single parents was higher in the secondary school group than in the primary school group (P = 0.04). There were no differences between genders within each age group, except that more males in the secondary school group than females had a console in their bedroom (P < 0.01)

Table 1.

General characteristics of children and family by age group and by gender within age group

Primary school children
 Secondary school children
Female Male Inline graphic Female Male Inline graphic Inline graphic
Age (mean ± SD) 10.09 ± 0.8 10.08 ± 0.6 0.9 12.27 ± 0.5 12.30 ± 0.5 0.6 0.00
Parental age (mean ± SD) 43.7 ± 4.4 43.47 ± 3.9 0.6 44.35 ± 6.3 44.35 ± 5.3 1.0 0.1
Female Male Inline graphic Female Male Inline graphic Inline graphic
Gender n (%) 132 (53.4) 115 (46.6) 120 (46.9) 136 (53.1) 0.1
Parental education
 Secondary school 25 (18.9) 21 (18.3) 0.7 44 (36.7) 32 (23.5) 0.07 0.01
 High school 32 (24.2) 33 (28.7) 26 (21.6) 34 (25)
 University 75 (56.8) 61 (53) 50 (41.6) 70 (51.5)
Children BMI group
 Non-overweight/obese 96 (72.7) 80 (70.2) 0.5 75 (63) 93 (68.4) 0.3 0.2
 Overweight 32 (24.2) 27 (23.7) 38 (31.9) 40 (29.4)
 Obese 4 (3) 7 (6.1) 6 (5) 3 (2.2)
Parental BMI group
 Underweight 1 (0.8) 2 (1.9) 0.9 1 (0.9) 3 (2.5) 0.2 0.3
 Norm weight 85 (67.5) 71 (67) 66 (57.4) 73 (60.8)
 Overweight 32 (25.4) 26 (24.5) 35 (30.4) 38 (31.7)
 Obese 8 (6.3) 7 (6.6) 13 (11.3) 6 (5)
House TV set
 1 37 (28) 26 (22.6) 0.6 19 (15.8) 20 (14.7) 0.7 0.01
 ≥2 52 (39.4) 49 (42.6) 54 (45) 56 (41.2)
 ≥3 43 (32.6) 40 (34.8) 47 (39.2) 60 (44.1)
TV set bedroom
 Yes 29 (22.3) 20 (17.7) 0.3 35 (29.2) 53 (39.6) 0.08 0.00
 No 101 (77.7) 93 (82.3) 85 (70.8) 81 (60.4)
Computer bedroom
 Yes 48 (37.2) 43 (38.1) 0.8 52 (43.3) 56 (41.8) 0.8 0.2
 No 81 (62.8) 70 (61.9) 68 (56.7) 78 (58.2)
Console bedroom
 Yes 55 (42.6) 57 (50.4) 0.2 32 (26.9) 65 (48.9) 0.00 0.08
 No 74 (57.4) 56 (49.6) 87 (73.1) 68 (51.1)
Parental TV viewing
 <2 h/day 99 (77.3) 86 (79.6) 0.6 82 (70.1) 88 (71) 0.8 0.04
 ≥2 h/day 29 (22.7) 22 (20.4) 35 (29.9) 36 (29)
Parental TV rules
 Yes 119 (92.2) 97 (91.5) 0.8 103 (89.6) 111 (91.7) 0.5 0.6
 No 10 (7.8) 9 (8.5) 12 (10.4) 10 (8.3)
Parental computer rules
 Yes 120 (93.8) 101 (95.3) 0.6 108 (93.1) 115 (93.5) 0.9 0.6
 No 8 (6.2) 5 (4.7) 8 (6.9) 8 (6.5)
Family structure
 Single parent 16 (12.5) 15 (14.3) 0.6 24 (20.9) 24 (19.5) 0.7 0.04
 Two parents 112 (87.5) 90 (85.7) 91 (79.1) 99 (80.5)
Presence of siblings
 Yes 100 (76.9) 78 (72.9) 0.4 56 (47.5) 54 (43.5) 0.5 0.00
 No 30 (23.1) 29 (27.1) 62 (52.5) 70 (56.5)
Mother employment
 Non-working 26 (20.5) 24 (23.1) 0.6 30 (26.8) 34 (28.6) 0.7 0.1
 Working 101 (79.5) 80 (76.9) 82 (73.2) 85 (71.4)
Father employment
 Non-working 7 (6.2) 6 (6.5) 0.9 8 (8.5) 7 (6.9) 0.6 0.6
 Working 106 (93.8) 86 (93.5) 86 (91.5) 95 (93.1)
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Inline graphic: by sex within age group t-test, Inline graphic: by age group t-test, Inline graphic: by sex within age group chi-square test, Inline graphic: by age group chi-square test.

Screen-viewing time

Child's TV viewing, computer games-playing, console games-playing and overall screen viewing are shown by age group and gender for a usual weekday and for a usual weekend day in Table 2. For all children more time was spent engaged in screen-viewing behaviours on weekend days than on weekdays (all P < 0.01). When children's screen-viewing behaviours were analysed separately by day of the week, more older children spent ≥2 h/day engaged in all analysed screen-viewing behaviours in comparison to younger children on a weekday and on a weekend day.

Table 2.

Time spend in screen-viewing behaviours by age group, by gender within age group and by day of the week

Primary school children
 Secondary school children
Female Male P* Female Male P* P**
Weekday n (%)
 TV viewing
  <2 h/day 109 (83.2) 76 (67.9) 0.00 81 (67.5) 88 (64.7) 0.6 0.01
  ≥2 h/day 22 (16.8) 36 (32.1) 39 (32.5) 48 (35.3)
 Computer playing
  <2 h/day 120 (93) 112 (98.2) 0.05 103 (85.8) 116 (85.3) 0.9 0.00
  ≥2 h/day 9 (7) 2 (1.8) 17 (14.2) 20 (14.7)
 Console playing
  <2 h/day 122 (93.1) 101 (87.8) 0.1 109 (90.8) 105 (77.2) 0.00 0.01
  ≥2 h/day 9 (6.9) 14 (12.2) 11 (9.2) 31 (22.8)
Overall media use
  <2 h/day 100 (75.8) 66 (57.4) 0.00 63 (52.5) 52 (38.2) 0.02 0.00
  ≥2 h/day 32 (24.2) 49 (42.6) 57 (47.5) 84 (61.8)
Weekend day n (%)
 TV viewing
  <2 h/day 68 (54) 51 (44.7) 0.1 36 (30.2) 46 (34.3) 0.4 0.00
  ≥2 h/day 58 (46) 63 (55.2) 83 (69.8) 88 (65.7)
 Computer playing
  <2 h/day 114 (87.7) 101 (87.8) 0.9 72 (60.5) 85 (63) 0.6 0.00
  ≥2 h/day 16 (12.3) 14 (12.2) 47 (39.5 ) 50 (37)
 Console playing
  <2 h/day 118 (91.5) 83 (72.2) 0.00 99 (82.5) 80 (59.3) 0.00 0.00
  ≥2 h/day 11 (8.5) 32 (27.8) 21 (17.5) 55 (40.7)
 Overall media use
  <2 h/day 58 (46) 31 (27.2) 0.00 17 (14.2) 17 (12.7) 0.7 0.00
  ≥2 h/day 68 (54) 83 (72.8) 103 (85.8) 117 (87.3)
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P*: by sex within age group chi-square test and P**: by age group chi-square test.

A greater proportion of males in primary (P < 0.01) and in secondary schools (P = 0.02) spent ≥2 h/day in overall screen viewing on a weekday. For a weekend day, only primary school-aged males (P < 0.01) spent ≥2 h/day in overall screen viewing than primary school-aged females. More primary school-aged males (P < 0.01) exceeded TV viewing guidelines than primary school-aged females on a weekday. More males reported spending ≥2 h/day engaged in console games than females.

Relationships between screen-viewing behaviours and variables

Table 3 presents logistic regression models (odds ratios and 95% confidence intervals) for analysed environmental, sociocultural and sociodemographic variables by age group, by gender within age group and by day of the week for watching TV ≥2 h/day. Statistically significant predictors for younger females exceeding TV guidelines on a weekday were having ≥2 TV sets in the household [OR: 3.20 (1.15–8.90), P < 0.05] and not having parental rules regarding computer playing [OR: 0.19 (0.05–0.72), P < 0.05]. Not having parental screen-viewing rules [for TV viewing OR: 0.07 (0.01–0.42), P < 0.01 and for computer playing OR: 0.19 (0.04–0.82), P < 0.05], and living in single-parent households [OR: 0.47 (0.24–0.92), P < 0.05] were also predictors for young males exceeding TV guidelines on a weekday and on a weekend day, respectively. For older females, the presence of TV [OR: 0.25 (0.09–0.68), P < 0.01] and console in the bedroom [OR: 0.14 (0.04–0.50), P < 0.01], having a parent <40 years of age [OR: 0.09 (0.03–0.23), P < 0.01] and having siblings [OR: 2.76 (1.67–4.57), P < 0.01] were significant correlates for spending ≥2 h/day watching TV on a weekday. On a weekend day, having two or more TV sets in the household [OR: 1.94 (1.06–3.56), P < 0.05] and not having parental TV rules [OR: 0.16 (0.03–0.87), P < 0.05] were also associated in this subgroup. Higher parental TV viewing [for a weekday OR: 4.22 (1.95–9.12), P < 0.01; and for a weekend day OR: 10.5 (2.74–40.8), P < 0.01] was associated with secondary school-aged males watching TV ≥2 h/day. Not having parental TV rules [OR: 0.28 (0.08–0.88), P < 0.05] and having a father that was not working [OR: 0.13 (0.03–0.51), P < 0.01] were also associated with an increased of exceeding TV guidelines on a weekday for older males.

Table 3.

Logistic regression model analysis (odds ratios and 95% confidence intervals) for analysed environmental, sociocultural and sociodemographic variables by age group, by gender within age group and by day of the week for watching TV ≥2 h/day

TV viewing
Primary school children
 Secondary school children
Female
 Male
 Female
 Male
Weekday
 Weekend day
 Weekday
 Weekend day
 Weekday
 Weekend day
 Weekday
 Weekend day
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Household TV set
 ≥2 3.20 1.15–8.90* 1.51 0.44–5.09 1.01 0.40–2.54 1.10 0.49–2.47 6.17 0.85–44.3 1.94 1.06–3.56* 1.18 0.47–2.95 1.88 0.33–10.7
 ≥3 1.07 0.25–4.46 1.10 0.25–4.72 2.36 0.67–8.26 2.69 0.91–7.94 3.82 0.43–33.5 1.73 0.62–4.84 0.86 0.25–2.89 1.52 0.24–9.37
TV bedroom 0.85 0.25–2.89 2.08 0.64–6.74 0.46 0.11–1.94 0.88 0.24–3.15 0.25 0.09–0.68** 1.32 0.43–4.03 0.78 0.24–2.54 0.73 0.24–2.17
Computer bedroom 0.85 0.39–1.84 1.09 0.31–3.87 0.77 0.26–2.28 1.28 0.53–3.07 1.25 0.54–2.84 1.22 0.67–2.22 1.57 0.81–3.07 0.89 0.37–2.14
Console bedroom 0.46 0.20–2.06 1.40 0.71–2.76 0.34 0.10–1.12 1.12 0.44–2.81 0.14 0.04–0.50** 0.37 0.08–1.76 1.38 0.72–2.67 1.12 0.55–2.26
Parental TV viewing 1.59 0.27–9.37 0.97 0.34–2.80 0.32 0.05–1.91 2.32 0.83–6.53 3.11 0.88–10.9 1.73 0.79–3.81 4.22 1.95–9.12** 10.5 2.74–40.8**
Parental rules TV 0.35 0.08–1.46 0.94 0.31–2.83 0.07 0.01–0.42** 0.57 0.12–2.61 0.59 0.17–2.01 0.16 0.03–0.87* 0.28 0.08–0.88* 0.47 0.11–2.03
Parental rules computer playing 0.19 0.05–0.72* 0.93 0.32–2.67 0.19 0.04–0.82* 1.17 0.22–6.26 1.37 0.22–8.57 0.75 0.19–2.86 0.28 0.04–1.92 0.32 0.03–2.87
Parental age 0.43 0.08–2.07 0.28 0.07–1.10 0.99 0.33–2.90 1.10 0.42–2.88 0.09 0.03–0.23** 0.60 0.16–2.23 0.39 0.15–1.00 0.50 0.16–1.56
Family structure 0.89 0.09–7.96 0.42 0.16–1.12 0.42 0.09–1.97 0.47 0.24–0.92* 0.31 0.09–1.01 0.61 0.18–1.99 0.51 0.24–1.08 0.87 0.28–2.70
Presence of siblings 1.50 0.62–3.63 0.56 0.25–1.25 0.72 0.26–2.02 0.94 0.43–2.05 2.76 1.67–4.57** 1.14 0.62–2.11 0.66 0.35–1.24 0.47 0.19–1.14
Mother employment 0.75 0.31–1.81 0.67 0.23–1.95 1.72 0.62–4.77 0.62 0.17–2.18 0.65 0.26–1.58 0.68 0.22–2.06 0.69 0.32–1.51 1.45 0.54–3.84
Father employment 0.43 0.09–1.91 3.81 0.39–36.5 1.46 0.50–4.27 1.86 0.18–18.6 1.61 0.27–9.55 1.22 0.29–5.16 0.13 0.03–0.51** 0.27 0.03–2.51
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Household TV set (ref. 1); TV bedroom (ref. yes); computer bedroom (ref. yes); console bedroom (ref. yes); parental TV viewing (ref. <2 h/day); parental TV rules (ref. no); parental age (ref. ≤40 years old); family structure (ref. single parents); presence of siblings (ref. no); mother employment (ref. non-working); father employment (ref. non-working). Model adjusted for parental BMI group, children BMI group and parental education and clustering by school. *P < 0.05, **P < 0.01.

The logistic regression models for whether participants exceeded the 2 h per day of overall screen viewing (i.e. TV and electronic games use combined with entertainment media) are presented in Table 4. Living in a single-parent household [OR: 0.26 (0.12–0.53), P < 0.01] and not having parental TV rules [OR: 0.12 (0.02–0.67), P < 0.05] were associated with not meeting overall screen-viewing guidelines for young females on a weekend day and young males on a weekday, respectively. For older females, having a TV [OR: 0.32 (0.10–0.97), P < 0.05] and a console in the bedroom [OR: 0.26 (0.08–0.84), P < 0.05], living in higher parental TV viewing households [OR: 2.74 (1.06–7.10), P < 0.05] and having a parent <40 years of age [OR: 0.11 (0.02–0.51), P < 0.01] were associated with spending ≥2 h/day engaged in overall screen-viewing time on a weekday. For older males, parental TV viewing was associated with exceeding overall recommended screen-viewing guidelines [weekday OR: 5.89 (1.15–30.1), P < 0.05; and weekend day OR: 6.83 (1.02–45.4), P < 0.05]. Having a parent <40 years of age [OR: 0.15 (0.03–0.64), P < 0.05] and a father who was not working [OR: 0.15 (0.02–0.88), P < 0.05] were also associated with not meeting overall recommended screen-viewing guidelines in this subgroup on a weekday.

Table 4.

Logistic regression model analysis (odds ratios and 95% confidence intervals) for analysed environmental, sociocultural and sociodemographic variables by age group, by gender within age group and by day of the week for spending ≥2 h/day in overall screen viewing

Overall screen viewing
Primary school children
 Secondary school children
Female
 Male
 Female
 Male
Weekday
 Weekend day
 Weekday
 Weekend day
 Weekday
 Weekend day
 Weekday
 Weekend day
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Household TV set
 ≥2 2.34 0.56–9.79 1.18 0.35–3.89 1.27 0.63–2.58 0.75 0.27–2.08 3.99 0.75–20.9 1.89 0.96–3.70 1.34 0.64–2.79 5.85 0.99–34.5
 ≥3 2.06 0.45–9.26 1.11 0.32–3.82 1.52 0.40–5.76 1.33 0.26–6.69 3.62 0.81–16.1 1.38 0.61–3.10 1.68 0.66–4.27 7.72 0.87–68.5
TV bedroom 1.08 0.38–3.05 2.43 0.86–6.84 0.44 0.08–2.20 0.71 0.10–5.05 0.32 0.10–0.97* 0.87 0.24–3.15 0.40 0.15–1.03 1.09 0.38–3.05
Computer bedroom 0.97 0.41–2.30 1.00 0.29–3.41 0.56 0.18–1.72 0.43 0.17–1.04 0.94 0.34–2.61 1.20 0.53–2.70 1.30 0.55–3.05 0.53 0.25–1.09
Console bedroom 0.60 0.19–1.89 1.08 0.47–2.49 0.51 0.21–1.23 0.56 0.29–1.08 0.26 0.08–0.84* 0.84 0.11–6.23 0.60 0.34–1.05 1.44 0.43–4.84
Parental TV viewing 1.90 0.39–9.05 1.60 0.44–5.77 0.95 0.37–2.46 1.59 0.32–7.73 2.74 1.06–7.10* 0.67 0.27–1.63 5.89 1.15–30.1* 6.83 1.02–45.4*
Parental rules TV 0.45 0.07–2.62 1.35 0.41–4.45 0.12 0.02–0.67* 0.91 0.20–4.04 0.52 0.22–1.20 Omitted 0.34 0.07–1.56 1.84 0.29–11.5
Parental rules computer playing 0.31 0.04–2.08 1.48 0.47–4.59 0.84 0.12–5.95 0.99 0.10–9.79 2.49 0.29–20.8 0.86 0.12–5.88 0.59 0.08–3.99 Omitted
Parental age 0.34 0.07–1.53 0.34 0.08–1.38 0.42 0.15–1.15 1.21 0.37–4.01 0.11 0.02–0.51** 0.45 0.11–1.79 0.15 0.03–0.64* 1.24 0.32–4.74
Family structure 0.42 0.08–2.05 0.26 0.12–0.53** 0.62 0.13–2.93 0.54 0.17–1.71 0.42 0.16–1.13 Omitted 0.97 0.35–2.64 1.06 0.17–6.35
Presence of siblings 1.40 0.45–4.36 0.73 0.33–1.60 1.38 0.39–4.87 0.87 0.39–1.97 1.22 0.52–2.88 1.27 0.39–4.16 0.92 0.46–1.85 1.20 0.49–2.89
Mother employment 1.33 0.40–4.41 0.53 0.21–1.29 0.98 0.40–2.41 0.49 0.12–1.93 0.67 0.28–1.58 0.61 0.12–3.18 1.89 0.52–6.81 1.25 0.25–6.13
Father employment 0.32 0.06–1.68 1.14 0.19–6.87 0.87 0.21–3.52 5.90 0.49–70.4 2.67 0.42–16.9 1.33 0.24–7.36 0.15 0.02–0.88* Omitted
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Household TV set (ref. 1); TV bedroom (ref. yes); computer bedroom (ref. yes); console bedroom (ref. yes); parental TV viewing (ref. <2 h/day); parental TV rules (ref. no); parental age (ref. ≤40 years old); family structure (ref. single parents); presence of siblings (ref. no); mother employment (ref. non-working); father employment (ref. non-working). Model adjusted for parental BMI group, children BMI group and parental education and clustering by school. *P < 0.05, **P < 0.01.

Discussion

Main findings of this study

In this sample of Spanish youth, 32.8% of primary and 55.1% of secondary school-aged children exceeded the AAP total screen-viewing time recommendation on weekdays. On weekend days these figures were higher with 62.9% in primary and 86.6% in secondary school-aged children exceeding the guidelines. There were also gender differences in TV viewing and console games-playing. Males watched more TV than females, although it was only in primary school-aged children and on weekdays. Males also spent more time playing games-consoles than females. Overall, males engaged more time than females in all screen-viewing behaviours.

Older children with greater access to media sources in their bedrooms spent more time engaged in screen-viewing behaviours. The higher levels of TV and screen viewing by older children could be at least partially explained by increased access to media equipment as our results showed that they had more TV sets in their bedrooms than younger children and that having a TV and a console in the bedroom were significant factors for not meeting screen-viewing guidelines on weekdays.

Familial screen-viewing factors such as parental TV viewing and rules were correlates of screen viewing, although influences differed depending on children's age and day of the week. For older children, parental TV viewing time appeared to be associated with children's TV viewing on weekdays and weekend days, while parental rules was associated among younger children on weekend days. Some family factors are also likely to be key predictors of youth screen viewing. Younger children living in single-parent households were more likely to exceeded recommended screen-viewing guidelines on weekend days, while older children with a younger parent, with siblings and having a father that was not working were more likely to exceeded recommended screen-viewing guidelines on weekdays.

What is already known on this topic

Previous research has established that adolescents spend more time in screen-based activities than their younger counterparts25–32 and that TV usage peak emerges between 9 and 12 years of age.16 Several studies have also described that adolescents spent more time in screen-viewing behaviours on weekend days than on weekdays.18,25,26–28,33–35 Two reviews of correlates of screen viewing and TV viewing in youth have reported no gender differences in TV viewing,16,34 while males spent more time engaged in console games-playing than females.16,25,29,35–37 Several studies have also reported that youth in single-parent families consistently watch more TV than those from two-parent families34,38 and that TV viewing appears unrelated to being an only child.34,39

In relation to environmental and sociocultural variables, the presence of a TV in the bedroom has been suggested to be an important correlate of TV viewing in youth.34 Several studies have described a positive association between young people and parental TV viewing habits.33,34,39,40 The home media environment including rules41–43 and whether TV is left on in home44,45 has been also associated with children's screen viewing.

What this study adds

This study makes an important contribution to the limited research that has examined correlates of screen viewing among Spanish children. We focused on environmental and sociocultural variables as a way to identify modifiable correlates that might help to develop future effective interventions. Overall our results support previous findings on screen-viewing correlates, although they may operate at different time during childhood and associations may also differ depending on the day of the week. However, in contrast with previous review studies16,34 males in this study spent more time in TV viewing than females. Older children had more media devices in their bedrooms and they also spent more time in screen viewing. This might be at least partially explained because as they get older they might have greater access and spend more time engaged in independent activities in their bedrooms.

Weekday and weekend TV and screen viewing are separate behaviours, so the variables associations would not be expected to be the same. Family characteristics (parental age and employment) were significant variables for not meeting screen-viewing guidelines on weekdays for older children, while time rules and family structure were significant variables for not meeting screen-viewing guidelines on weekdays and weekend days, respectively, for younger children. Changes in time and family structures might have a stronger effect on younger children as consistent time schedules and habits help them to form a healthy lifestyle.

Parental TV viewing for older children was associated with child TV viewing in this study. Parents' lifestyles might have a strong influence on their children's lifestyles from early stages. These influences might be more notable as children age and parental rules become more relaxed as they have more opportunities to make their own choices. It has been reported that parents tend to increase co-viewing as children move into early adolescence, while less time is spent together in other social contexts (eating together, going out, etc.).46 In this context, co-viewing can be considered as a familial social activity that may serve as a means of bonding between young adolescents and parents.39 When combined with our data, these results might suggest that parents influence their child's screen viewing via role modelling and therefore interventions that target child and parent TV viewing together may be useful.

Sociodemographic correlates might highlight key groups that could be the target for future interventions, while environmental and sociocultural correlates might reflect potential mediators and targets for future interventions that should be developed to change these variables. However, more research is needed to both corroborate these findings and to better understand correlates' influences by children's characteristics and time periods.

Limitations of this study

The strengths of this study include heterogeneity across different socioeconomic strata and the examination of a great variety of different screen-viewing behaviours and variables included. Previous studies of electronic media use have focused mostly on the description of sociodemographic characteristics and on TV viewing as a highly prevalent sedentary behaviour. This study included the analysis of sociocultural and environmental factors and captured the diversity of screen-viewing behaviours. This study has some limitations. The cross-sectional nature of this study makes it unable to infer causality. We know that the use of self-reported questionnaires can be problematic, particularly among children. Finally, this sample comprised children living in a single city and this might result in limited generalizability of the results, even if they were from different socioeconomic strata.

Conclusions

There are important associations between environmental and sociocultural factors and screen-viewing behaviours, although they may operate at different time during childhood. Parents are a key influence on children's screen-viewing behaviours and therefore interventions that target environmental and family TV viewing practices are likely to be effective.

Contributors

The authors developed the hypothesis, analysed the data, developed statistical analyses and interpreted the data. The authors contributed to various drafts and approved the final draft.

Ethics approval

This study was approved by the University of the Basque Country Ethics Committee.

Funding

This work is research arising from a Career Development Fellowship (to Dr. Jago) supported by the National Institute for Health Research. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the National Institute for Health Research or the Department of Health.

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