Association between problematic internet use, socio-demographic variables and obesity among European adolescents

Abstract

Background: Overweight of children and adolescents continues to be an important and alarming global public health problem. As the adolescent’s time spent online has increased, problematic internet use (PIU) potentially leads to negative health consequences. This study aimed to examine the relation between PIU and overweight/obesity among adolescents in seven European countries and assess the effect of demographic and lifestyle factors recorded in the European Network for Adolescent Addictive Behaviour (EU NET ADB) survey ( www.eunetadb.eu ). Methods: A cross-sectional school-based survey of 14- to 17-year-old adolescents was conducted in seven European countries: Germany, Greece, Iceland, the Netherlands, Poland, Romania and Spain. Anonymous self-completed questionnaires included sociodemographic data, internet usage characteristics, school achievement, parental control and the Internet Addiction Test. Associations between overweight/obesity and potential risk factors were investigated by logistic regression analysis, allowing for the complex sample design. Results: The study sample consisted of 10 287 adolescents aged 14–17 years. 12.4% were overweight/obese, and 14.1% presented with dysfunctional internet behavior. Greece had the highest percentage of overweight/obese adolescents (19.8%) and the Netherlands the lowest (6.8%). Male sex [odds ratio (OR) = 2.89, 95%CI: 2.46–3.38], heavier use of social networking sites (OR = 1.26, 95%CI: 1.09–1.46) and residence in Greece (OR = 2.32, 95%CI: 1.79–2.99) or Germany (OR = 1.48, 95%CI: 1.12–1.96) were independently associated with higher risk of overweight/obesity. A greater number of siblings (OR = 0.79, 95%CI: 0.64–0.97), higher school grades (OR = 0.74, 95%CI: 0.63–0.88), higher parental education (OR = 0.89, 95%CI: 0.82–0.97) and residence in the Netherlands (OR = 0.49, 95%CI: 0.31–0.77) independently predicted lower risk of overweight/obesity. Conclusions: The results indicate an association of overweight/obesity with PIU and suggest the importance of formulating preventive public health policies that target physical health, education and sedentary online lifestyle early in adolescence with special attention to boys.

Introduction

In our digitalized world, the internet has become a fundamental tool for information, entertainment and social communication. It has been widely adopted especially by adolescents, as a low-cost, easy-to-access platform for social interaction and leisure activities. Currently, 93% of adolescents and young adults go online in the USA ¹ and almost 70% adolescents in Europe spend 2–4 h daily on computer-games surfing and chatting via the internet. ^2,3

Given this high usage and amount of time spent on internet use, internet addiction, often referred to as ‘problematic internet use’ (PIU), is a growing concern. ^4,5 The reported prevalence of PIU varies widely, from 1% to 9% in Europe, ^5–7 1% to 12% in the Middle East and 2% to 18% in Asia. ¹ PIU in adolescents and young adults appears to be associated with negative health consequences, such as depression, Attention Deficit Hyperactivity Disorder, daytime sleepiness, alcohol abuse and injuries. ^8–10

In this article, we shall examine the association between PIU and being overweight or obese among adolescents. Our definitions of the terms ‘overweight’ and ‘obese’ will be given in the Methods section. When referring to other studies, we use the terminology employed by the original authors. Overweight or obesity among children and adolescents is a significant global public health concern with an already high prevalence which still continues to increase. ¹¹ The prevalence of obesity has doubled among children and trebled among adolescents in the past 30 years. ^12–14 Recent data have indicated that 22–25% of European adolescents were overweight or obese. ¹⁵

These figures are worrying, since obesity increases the risk of adverse psychosocial consequences, poor physical health outcomes and excessive weight during adulthood. ¹⁶ Risk factors that have been implicated in the development of obesity have encompassed genetic, lifestyle, socioeconomic and environmental parameters. ^15,17 Among sedentary behaviors a positive association between obesity and television viewing has been reported, as well as less consistent associations with computer use and video games. ^18–22

However, little is known about the role of PIU in the development of obesity among adolescents. ²³ At present, to our knowledge, a survey assessing overweight/obesity in association with PIU on a representative and multi-national basis is lacking. It is also necessary to increase knowledge of the distribution of adolescent overweight or obesity within different groups of adolescents and its relationship with sociodemographic and dysfunctional internet behavioral problems. The European Network for Adolescent Addictive Behaviour (EU NET ADB) project ²⁴ included among its aims the further extension of this body of research by investigating, via consistent methodological procedures across seven countries, whether being an overweight/obese adolescent is correlated with problematic internet use.

Therefore, the aim of the present study is to examine the relation between PIU and overweight/obesity among adolescents in seven European countries, taking demographic and lifestyle factors into account.

Methods

Participants and procedure

A cross-sectional school-based study was conducted in the seven countries participating in the EU NET ADB study: Germany, Greece, Iceland the Netherlands, Poland, Romania and Spain. The rationale for selecting these countries was to represent the economic, geographic and cultural diversity of European countries. Data collection took place between October 2011 and May 2012. The study protocol was approved by the respective Ethical Committees of each participating country. The parents or legal guardians of all participants were informed about the study objectives and were asked for their written consent.

Each participating country drew a school-based clustered probability sample, from the national official and complete school and class register. About 100 9th and 10th grade classes were sampled in order to obtain the target sample of 2000 adolescents per country. All students who attended the selected classes on the day of data collection day were eligible to participate. The methodological protocol of the EU NET ADB study has been described in detail elsewhere. ²⁴

In total, 13 708 students participated, representing 85% of those on the class registers participated. Participating adolescents answered a self-completed questionnaire in the classroom during school hours under the supervision of trained research assistants. An anonymous questionnaire was used in order to ensure confidentiality and to minimize reporting bias. Participants were excluded from the analysis if they were aged <14 or ≥18 ( n = 112), did not report either their gender or age ( n = 296), did not report either their weight or height [thus their body mass index (BMI) could not be calculated, n = 2936] or were categorized as underweight ²⁵ ( n = 77), leaving a total of 10 287 subjects for the analysis.

Measures

The questionnaires used in the study were developed by the EU NET ADB consortium. ²⁴ They were then tested and refined through a two-stage process of cognitive interviewing and pilot testing in each country. ²⁴

Socio-demographic variables

Gender and age were recorded. Parental education (highest qualification earned by either parent) was used as a proxy measure of socioeconomic status (SES).

Internet and social networking site use

Participants were asked about their daily frequency of internet use (‘How often do you use the internet?’). The precoded answers ranged from ‘<1 h’ to ‘>6 h’ in half-hour intervals. Adolescents were further asked whether they belonged to any social networking site (SNS) and for how long they used SNS on a typical weekday (‘normal school day’) and at weekends or in vacation (‘non-school day’) during the past 12 months. Possible answers ranged from ‘not at all’ to ‘>4 h’. A single estimate of daily SNS during the whole week was produced as the weighted average of weekday and weekend use. The frequency of SNS use was dichotomized into moderate (<2 h daily) and heavier (≥2 h daily) using the median response (‘2 h per day’).

The Internet Addiction Test (IAT) is a 20-item scale, which evaluates the degree of preoccupation, compulsive use, behavioral problems, emotional changes and impact of internet use upon the adolescent’s functioning. Response scores to each item range from 0 to 5, and the total score ranges between 0 and 100 points. ²⁶ The following cut-off scores were adopted in order to assess internet addictive behavior (IAB) ¹ : no signs of IAB (0–19); mild, yet non-problematic signs of IAB (20–39); at risk for IAB (40–69) IAB (70–100). Two missing values per subject were allowed and were replaced by the country-specific median during the calculation of the IAT score. The test had high internal reliability (Cronbach’s α = 0.92).

Overweight/obesity

BMI was calculated as weight/(height) ² . Each respondent was then characterized as either underweight, normal, overweight or obese according to the sex- and age-specific BMI cut-off values for adolescents, as proposed by Cole et al.^25,27 As noted above, underweight students were excluded. The categories of overweight and obese were combined for the analysis, which consequently examines overweight/obese vs. normal weight.

Statistical methods

Descriptive statistics were calculated for each country and for the total sample. To explore meaningful risk factors for overweight/obesity, a standard two-step approach was followed, comprising univariate and multivariate logistic regression analysis with overweight/obesity (vs. normal weight) as the dependent variable. Risk factors that were examined in the univariate analysis were: sex (male vs. female), age (≥15.75 vs <15.75 years), siblings (yes vs. no), parental education (ordinal variable: none = 1, primary = 2, secondary = 3, post-secondary or pre-vocational/vocational = 4, tertiary-university = 5), school grades (15–20 vs. 1–14.9), country (Germany, Greece, Iceland, Netherlands, Poland, Romania vs. Spain as the reference category as it had the median rate of overweight/obesity), SNS-use (≥2 h vs. <2 h), total daily hours of internet use (≥2 h vs. <2 h) and IAT score category. The variables that were significant in the univariate analysis were tested in the multivariate approach. Variables with P < 0.05 were retained in the final logistic regression model (backward selection of variables). An alternative approach, entering only one of the three internet-related indices (total internet use, IAT categories, SNS use) was also tried. All analyses were conducted using the Complex Samples procedure in SPSS version 22.0 statistical software (IBM Corp., Armonk, NY, USA) with countries as strata and classes as clusters so that the computation of all statistical tests and confidence intervals correctly took into account the complex sample design.

Results

The study sample consisted of 10 287 adolescents aged 14–17 years ( mean age = 15.8, SD = 0.7). Half of the subjects were males ( n = 5140, 50.0%). Participants were drawn from seven European countries: Germany ( N = 1845, 17.9%), Greece ( N = 1629, 15.8%), Iceland ( N = 1394, 13.6%), Netherlands ( N = 844, 8.2%), Poland ( N = 1437, 14.0%), Romania ( N = 1646, 16.0%) and Spain ( N = 1492, 14.5%). Table 1 shows the characteristics of the study sample 8972 participants (87.8%) had siblings (mean number of siblings = 1.9, SD = 1.3, median = 1); 1275 participants (12.4%) were overweight/obese whereas 9012 (87.6%) had normal BMI values [overall, the BMI of the study sample was 20.9 ± 3.1 kg/m ² (median: 20.4)]; 4868 participants (51.1%) used the internet ≥2 h per day. Regarding the adolescents’ IAB, 85.9% ( n = 8560) had functional internet behavior and the remaining 14.1% ( n = 1406) had dysfunctional internet behavior. The mean IAT score was 22.8 (SD = 15.8, median = 20.0). The mean duration of daily use of SNS was 5.6 h (SD = 2.7, median = 5.1); 36.9% of the study sample reported daily use ≥2 h.

Table 2 shows the distribution of adolescents’ BMI status by country and in total. Greece had the highest percentage of overweight/obese adolescents (19.8%) and the Netherlands the lowest (6.8%). The between-countries variability was statistically significant ( P < 0.001, Pearson’s χ ² test).

Table 3 shows the results of the complex-samples univariate logistic regression analysis examining the association between overweight/obesity and potential risk factors Overweight/obesity was significantly positively associated with male gender [odds ratio (OR) = 3.20, 95%CI: 2.79–3.67], heavier SNS use (OR = 1.15, 95%CI: 1.01–1.31), heavier internet use (OR = 1.14, 95%CI: 1.01–1.29) and IAB (OR = 1.70, 95%CI: 1.08–2.67, vs. no signs of IAB). On the other hand, overweight/obesity was inversely associated with older age (OR = 0.84, 95%CI: 0.73–0.95), number of siblings (OR = 0.80, 95%CI: 0.67–0.95), school grades (OR = 0.79, 95%CI: 0.69–0.90) and parental educational level (OR = 0.87, 95%CI: 0.82–0.93). Greece (OR = 2.08, 95%CI: 1.64–2.64) and Germany (OR = 1.44, 95%CI: 1.11–1.85) exhibited higher overweight/obesity rates than the reference country (Spain), whereas the Netherlands exhibited significantly lower rates (OR = 0.61, 95%CI: 0.41–0.91).

Table 4 shows the results of the complex-samples multivariate logistic regression analysis. Male sex (OR = 2.89, 95%CI: 2.46–3.38), heavier SNS use (OR = 1.26, 95%CI: 1.09–1.46) and residence in Greece (OR = 2.32, 95%CI: 1.79–2.99) or Germany (OR = 1.48, 95%CI: 1.12–1.96) were independently associated with higher risk of overweight/obesity. A greater number of siblings (OR = 0.79, 95%CI: 0.64–0.97), higher school grades (OR = 0.74, 95%CI: 0.63–0.88), higher parental education (OR = 0.89, 95%CI: 0.82–0.97) and residence in the Netherlands (OR = 0.49, 95%CI: 0.31–0.77) independently predicted lower risk for overweight/obesity. The alternative analysis, entering one of the three internet-related indices led to the same results, since the total daily internet use and IAT categories always lost their statistical significance in the multivariate approach.

Discussion

The present study is among the few of its kind that add to knowledge of the distribution of adolescent overweight/obesity among adolescents from various European countries and its relationship with socio-demographic factors and dysfunctional internet behaviors.

Results from earlier studies have already highlighted the alarming prevalence of overweight and obesity in children and adolescents worldwide. ^12–14 According to the HBSC study, ¹¹ the highest prevalence of overweight arises in the Southern European countries, compared to Central, Eastern and Northern Europe. In our study, findings are quite similar with 12.4% of the participants being overweight/obese. Greece had the highest percentage of overweight/obese adolescents (19.8%) and the Netherlands the lowest (6.8%). Significantly higher rates were observed in Greece (19.8%) and Germany (14.5%) compared with the reference country (Spain) and significantly lower rates in the Netherlands (6.8%). The significant between-countries variability may be related to differences in lifestyle factors including dietary habits, physical activity access and sedentary behavior across counties. ^11,28

A consistent pattern of boys being more frequently overweight than girls has been observed in most countries (29 out of 31) in the HBSC study, ^11,29 as well as in other studies. ^15,29–31 This gender difference was also observed as a risk factor in our study. Differences in the prevalence of overweight and obesity between genders have been attributed to geopolitical and cultural factors. ¹⁵ It seems that boys particularly suffer from obesogenic environmental influences and benefit less from preventive initiatives. ¹¹

Previous research has indicated a positive correlation between age and the prevalence of obesity among children and adolescents, although varying patterns have often been observed. ³¹ The interplay between obesity and age seems to vary regionally; in Eastern Europe, the prevalence of obesity appeared to decrease with age in both genders, whereas this was true only of girls in Southern Europe. However, a positive correlation between obesity and age was noted among boys in Central-European countries. ^15,29–31 The reasons for these differences are unclear although it has been suggested that environmental variables may operate in complex ways on adolescents who are either particularly susceptible or are selectively exposed to these influences at certain ages. ³² According to the findings of our study, overweight/obesity was associated with younger age.

Socioeconomic variables seem to increase the risk of childhood and adolescent obesity. Indeed, previous research suggests an inverse correlation between childhood obesity and parental occupation, education and income level. ^12,33 Also, some evidence supports an association between number of siblings and obesity in children and young adults. ^34,35 In our study, overweight/obesity was inversely associated with the number of siblings and parental educational level. Adolescents with parents from a lower SES and larger family size may have poorer diets and engage in less physical activity than their higher SES counterparts, ³⁶ a fact which may provide an explanation of this association.

Though the deleterious effects of academic achievement on students’ health status is well documented, ³⁷ less is known regarding its potential impact on adolescent BMI. Our study also expands on previous research ³⁸ by indicating a protective influence of adolescents’ academic achievement on overweight/obesity status.

Although previous research documents an association between Internet addiction and BMI among adolescents, ^23,39 a survey assessing overweight/obesity in association with PIU on a representative and multi-national basis was lacking. This study contributes to increasing knowledge in this field, as overweight/obesity was significantly positively associated with SNS use, total daily internet use and IAB. Since the time spent in sedentary behaviors such as internet use replaces physical activity and healthy dietary behavior it is likely to be implicated in the development of overweight and obesity among youth.

The primary strength of the present study is that it is one of the few studies of its kind conducted in order to evaluate the influence of internet use on the development of obesity among adolescents. Furthermore, the random sampling and anonymous self-reporting substantially restricted the potential for selection and reporting biases. The limitations of the study include the following. First, BMI based on self-reported data may yield lower estimates of the prevalence of overweight and obesity than those based on actual height and weight measurements. ^10,40 On the other hand, self-reported BMI based has been found to be fairly reliable ⁴¹ for the identification of valid associations in epidemiological studies. ⁴² Finally, the data are cross sectional and therefore cause-and-effect relationships cannot be established.

In conclusion, the results of this study indicate that overweight/obesity in European adolescents continues to be a public health concern. Furthermore, our findings reinforce previous research that has demonstrated the associations of obesity with PIU and certain socio-demographic factors. The results of the present study should also be considered as a pointer to public health policies to be formulated and strengthened in the future targeting physical health, education and online lifestyle early in adolescence, with special attention to boys.

Acknowledgements

Special thanks to all the participants in the EU NET ADB study for their contribution to the design, supervision and sampling procedure.

Implications

This study increases knowledge about the distribution of adolescent overweight/obesity among adolescents from different European countries and its relationship with socio-demographic factors and problematic internet use (PIU). Specifically, the findings reveal the effect of demographic and lifestyle factors that can be used to formulate preventive public health policies

Funding

This study is part of a larger mixed-methods project on IAB risk among minors in Europe (EU NET ADB) carried out in seven European countries and funded under the EU Safer Internet Programme (SI-2011-KEP-4101007).

Conflicts of interest : None declared.

References