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Internet and computer use are increasingly common leisure-time sedentary behaviors, which have the potential to impact negatively on health outcomes. However, little is known about the extent to which adults’ Internet and computer use is associated with weight status and time spent in leisure-time physical activity.
The objective is to examine associations of leisure-time Internet and computer use with overweight and obesity, leisure-time physical activity, and other sedentary behaviors.
Participants (2650 adults living in Adelaide, Australia) completed a mail-back questionnaire including items on their height and weight, past seven day recall of leisure-time physical activity, Internet and computer use, and other leisure-time sedentary behaviors. Leisure-time Internet and computer use was categorized into no use, low use (less than three hours per week), or high use (three hours or more per week).
Participants with low leisure-time Internet and computer use had the highest levels of educational attainment and employment, and engaged in less other sedentary behaviors when compared to participants with no or high Internet and computer use. Multinomial logistic regression, adjusted for gender, age, employment, education, other sedentary behaviors and physical activity, determined that participants with a high leisure-time Internet and computer use were 1.46 (95% CI = 1.10 - 1.93) times more likely to be overweight (BMI≥25 and < 30 kg/m2) and 2.52 times more likely (95% CI = 1.82 - 3.52) to be obese (BMI≥30 kg/m2), compared to those who reported no Internet and computer use in their leisure-time. Adults with high leisure-time Internet and computer use were more likely to be overweight or obese even if they were highly active in their leisure time (OR = 1.86; 95% CI = 1.21 - 2.88), as compared to participants who did not use the Internet or computer. Leisure-time physical activity levels were largely independent of Internet and computer use.
These findings suggest that, apart from nutritional and physical activity interventions, it may also be necessary to decrease time spent in sedentary behaviors, such as leisure-time Internet and computer use, in order to reduce the prevalence of overweight and obesity. Future Internet interventions to reduce weight or increase physical activity may need to differentiate between participants with different levels of Internet use in order to increase their effectiveness. Longitudinal studies are required to examine further the potential causal relationships between the development of overweight and specific sedentary behaviors such as Internet and computer use.
Many studies have shown that physical inactivity is associated with higher levels of overweight and obesity and that physical activity is essential in the prevention and treatment of overweight and obesity [
There are strong adverse associations between time spent in sedentary behaviors and different health indicators [
However, most of the evidence on associations between sedentary behavior and health outcomes, such as weight status and levels of physical activity, is specific to time spent watching television [
Several studies have examined the associations between leisure-time Internet and computer use, physical activity, and levels of overweight/obesity in children and adolescents, with inconsistent outcomes. Some studies show that high leisure-time Internet and computer use is associated with higher Body Mass Index (BMI) and lower physical activity levels [
Further, little is known about how sedentary behaviors relate to each other. In relation to health outcomes, it is important to know whether high leisure-time Internet and computer use is a marker for high levels of other sedentary behaviors. It may be that leisure-time Internet and computer use is related to poor health outcomes due to its association with a broader pattern of sedentary behavior. A study by Sugiyama et al [
The aim of this study is to examine associations of Internet and computer use, specifically in leisure time (excluding occupational computer use), with overweight and obesity, leisure-time physical activity, and other sedentary behaviors, in a large socially-diverse sample of Australian adults.
This study is part of an observational epidemiological study (PLACE: Physical Activity in Localities and Community Environments) conducted in urban areas of Adelaide, Australia during 2003 - 2004. Detailed methods of the study have been described elsewhere [
Participants reported leisure-time Internet and computer use as part of a measurement tool assessing total leisure-time sedentary behavior in the last seven days. For each sedentary activity, the tool asks “How many days did you do this activity in the last 7 days”, followed by “On average, how many minutes did you do this activity on the days you did it”. This instrument has been shown to have acceptable reliability and validity, especially for Internet and computer use [
Body Mass Index (BMI; kg/m2) was calculated using self-reported height and weight and was categorized as either normal weight (< 25 kg/m2); overweight (≥ 25 and < 30 kg/m2) or obese (≥ 30 kg/m2). BMI was also used as a continuous variable.
Leisure-time physical activity was assessed using the long-form (31 items) International Physical Activity Questionnaire (IPAQ) [
The instrument applied to measure Internet and computer use [
One-way ANOVA and Chi-square tests were used for analysing differences in socio-demographic factors according to different categories of Internet and computer use. Multinomial logistic regression analyses were conducted to estimate associations of Internet and computer use with overweight and obesity (model 1), leisure-time physical activity (model 2), and other sedentary behaviors (model 3). The models were adjusted for age, gender, employment, level of education, overweight and obesity (only in models 2 and 3), other sedentary behaviors (only in models 1 and 2), and leisure-time physical activity (only in models 1 and 3). Binary logistic regression was conducted to estimate the odds ratios of being overweight or obese, comparing levels of Internet and computer use (no, low, and high Internet and computer use) and physical activity (low, medium, and high leisure-time physical activity). This model was adjusted for age, gender, education, employment, and other sedentary behaviors. Analyses were conducted using SPSS version 13.0. Significance was accepted at an alpha level of 0.05.
Sample size was 2532 (1554 women, 978 men), after excluding missing values for Internet and computer use (n = 118). Average leisure-time Internet and computer use was 125.3 minutes per week (SD: 273.3).
Sample characteristics for total group and according to computer and Internet use categories (mean ± SD or %)a
Total Sample |
No Internet or |
Low Internet and |
High Internet and |
|
|
Sex (% female) | 64.0 | 68.7 | 65.4 | 50.1 | < .001 |
Age (yr) | 44.5 ± 12.3 | 45.8 ± 11.8 | 42.8 ± 12.4 | 44.1 ± 12.7 | < .001 |
College or university degree (%) | 46.3 | 36.9 | 55.8 | 51.0 | < .001 |
Employed (%) | 69.2 | 62.9 | 77.0 | 67.6 | < .001 |
Leisure-time physical activity (hrs/week) | 3.3 ± 4.5 | 3.1 ± 4.7 | 3.6 ± 4.5 | 3.2 ± 4.3 | ns |
Body Mass Index (kg/m2) | 26.3 ± 6.4 | 25.9 ± 5.9 | 25.9 ± 5.6 | 27.5 ± 8.3 | < .001 |
Other sedentary behaviours (hrs/week) | 27.6 ± 16.9 | 27.5 ± 18.2 | 25.6 ± 14.3 | 32.2 ± 18.2 | < .001 |
aChi-squared and one-way ANOVA were used to examine differences between categories; ns is not significant.
As shown in
Leisure-time physical activity was largely independent of leisure-time Internet and computer use. However, participants with low Internet and computer use were 1.3 times more likely to do more than three hours of leisure-time physical activity, when compared to non-users.
Participants with low and high leisure-time Internet and computer use were respectively 1.8 and 2.5 times more likely to engage in more than five hours of other sedentary behaviors per day, when compared to participants that did not use the Internet and computer.
Multinomial logistic regression models predicting overweight or obesity, leisure-time physical activity, and other sedentary behaviors by computer and Internet usea
OR (95% CI) | OR (95% CI) | |||
Internet and computer use | ||||
No use | Reference | 1.00 | 1.00 | |
Low use | Category | 1.30 (1.01 - 1.56)b | 1.45 (1.10 - 1.92)c | |
High use | 1.46 (1.10 - 1.93)c | 2.52 (1.81 - 3.51)c | ||
Internet and computer use | ||||
No use | Reference | 1.00 | 1.00 | |
Low use | Category | 1.12 (0.87 - 1.44) | 1.28 (1.02 - 1.60)b | |
High use | 0.81 (0.60 - 1.12) | 0.83 (0.63 - 1.11) | ||
Internet and computer use | ||||
No use | Reference | 1.00 | 1.00 | |
Low use | Category | 1.24 (0.99 - 1.55) | 1.79 (1.30 - 2.46)c | |
High use | 0.99 (0.75 - 1.30) | 2.50 (1.75 - 3.57)c |
aRegression models were adjusted for gender, age, employment, educational attainment, other sedentary behaviors, leisure time physical activity, and BMI.
b
c
The odds ratios for being overweight or obese (BMI ≥ 25), according to combined categories of Internet and computer use (no, low, and high leisure-time Internet and computer use) and physical activity (low, medium, and high leisure-time physical activity). The reference category is having high leisure-time physical activity and not using the Internet and computer, for which the odds ratios are equal to 1. The significance levels on top of the figure bars are differences in relation to the reference category: ** P < .01; *** P < .001
The main finding of this study is that leisure-time Internet and computer use is strongly related to being overweight or obese, whereas it is largely independent of leisure-time physical activity. After adjusting for socio-demographic variables, leisure-time physical activity and other sedentary behaviors, participants who used the Internet and computer for three hours or more in the last seven days were 1.5 times more likely to be overweight and 2.5 times more likely to be obese compared to non-users. Although there are no direct comparisons with other studies for these outcomes in adults, they are in line with studies that report that higher amounts of time in sedentary behavior and television viewing are strongly associated with overweight and obesity [
The strong associations of leisure-time Internet and computer use with overweight and obesity may in part be explained by the association of leisure-time Internet and computer use with other leisure-time sedentary behaviors. Participants who had high Internet and computer use in their leisure time were 2.5 times more likely to engage in more than five hours of other sedentary behaviors per day. This is consistent with a study by Sugiyama et al [
Our results showed that leisure-time Internet and computer use was not strongly associated with leisure-time physical activity. Contrary to what might be expected, participants with low leisure-time Internet and computer use were slightly more likely to be in a higher leisure time physical activity category. While it is difficult to explain this outcome, it might be argued that it could be due to the higher socio-economic profile observed in participants with low Internet use. It is generally the case that those of higher socio-economic status are more physically active [
As may be seen in
As the level of Internet penetration increases, its users become more representative of the general population; thus, gender, age, and socio-economic differences are diminishing [
Given the high prevalence of Internet use, and its potential impact on health, it is important to address health issues for Internet users. Internet interventions to reduce weight or increase physical activity are likely to be more effective if they take differences among Internet users into account. Although a substantial number of these Internet interventions have been implemented, no studies reported that participants were targeted differently based on their level of Internet and computer use [
The major limitations of this study are that it relies on self-reported measures and a cross-sectional design which does not allow determination of the causal direction of the results. More research, using objective measures and prospective study designs, is needed to evaluate these associations. A further limitation is that this study only investigated leisure-time behaviors, this prevents evaluating the impact of using the Internet and computer at work on physical activity and overweight and obesity. Nevertheless, the associations observed in this study indicate that the impact of Internet and computer use, when only used in leisure time, is strong enough to have an influence on health, and that this impact should be taken into consideration when developing new interventions targeting these leisure-time behaviors.
In summary, high levels of leisure-time Internet and computer use were associated with a higher BMI (even among those engaging in a high level of leisure-time physical activity) and higher levels of other leisure-time sedentary behaviors. However, Internet and computer use was mostly unrelated to leisure-time physical activity. These findings suggest that, in addition to nutritional and physical activity interventions, it may also be necessary to decrease time spent in sedentary behaviors (including leisure-time Internet and computer use) in order to reduce the risk of overweight and obesity. Furthermore, future Internet interventions to reduce weight or increase physical activity may need to differentiate between participants with different levels of leisure-time Internet and computer use, in order to increase their effectiveness. Our study is the first to evaluate these specific associations; hence, more research is needed to confirm these findings. More specifically, longitudinal studies are required to examine further the potential causal relationships between specific sedentary behaviors, such as Internet and computer use, and weight gain.
The study was funded by the National Health and Medical Research Council of Australia (NHMRC) Project Grant (#213114) and NHMRC Program Grant (#301200). Vandelanotte is supported by a NHMRC (#519778) and the National Heart Foundation of Australia (NHF) (#PH 07B 3303) post-doctoral research fellowship. Sugiyama is supported by an NHMRC capacity building grant in population health (#252799). Gardiner is supported by a NHF postgraduate research scholarship (#PP 06B 2889).
None declared.
analysis of variance
body mass index
intra-class correlations
International Physical Activity Questionnaire
Physical Activity in Localities and Community Environments