Leisure time computer use and overweight development in young adults – a prospective study

BackgroundThe prevalence of overweight among Swedish young adults has nearly doubled since the 1980s. The weight increase has been paralleled by the increased use of computers at work, at school, and at leisure time. The aim was to examine leisure time computer use for gaming, and for emailing/chatting, in relation to overweight development in young adults.MethodsA prospective cohort study with Swedish young adults (20–24 years at baseline) who responded to a questionnaire at baseline (n = 6735), and after 1 year (n = 3928) and 5 years (n = 2593). Exposure variables were average daily time spent on leisure time computer gaming and emailing/chatting. Logistic regression was performed for cross-sectional analyses with overweight (BMI ≥ 25) and obesity (BMI ≥ 30) as the outcomes, and for prospective analyses with new cases of overweight at the 1- and 5-year follow-ups. Change in BMI from baseline to 5 year-follow-up was analyzed with linear regression.ResultsThere were cross-sectional and prospective associations between computer gaming and overweight (BMI ≥ 25) in women, after adjusting for age, occupation, physical activity, sleep, social support, and total computer use. For the men, only cross-sectional associations could be seen. Spending more than 2 h daily for emailing and chatting was related cross-sectionally to overweight in the women. No clear prospective associations were found for emailing/chatting and overweight development in either sex.ConclusionsWe have identified a new risk group for overweight development: young adult female computer gamers. Leisure time computer gaming was a prospective risk factor for overweight in women even after adjusting for demographic and lifestyle factors, but not in men. There were no clear prospective associations between computer use for emailing/chatting and overweight in either sex.

[1]  Sara Thomée,et al.  ICT use and mental health in young adults. Effects of computer and mobile phone use on stress, sleep disturbances, and symptoms of depression , 2012 .

[2]  B. Saltin,et al.  Physiological Analysis of Middle‐Aged and Old Former Athletes: Comparison with Still Active Athletes of the Same Ages , 1968, Circulation.

[3]  Aaron Delwiche,et al.  The Players They are A-Changin': The Rise of Older MMO Gamers , 2013 .

[4]  Kathryn H. Schmitz,et al.  Greater screen time is associated with adolescent obesity: a longitudinal study of the BMI distribution from ages 14 to 18 , 2012, Obesity.

[5]  Erica Scharrer,et al.  Active and Sedentary Video Game Time Testing Associations With Adolescents ’ BMI , 2014 .

[6]  F. Deane,et al.  Relationship between Self-Report and Log Data Estimates of Information System Usage. , 1998 .

[7]  R. Rhodes,et al.  Adult sedentary behavior: a systematic review. , 2012, American journal of preventive medicine.

[8]  J. Brug,et al.  Direction of the association between body fatness and self-reported screen time in Dutch adolescents , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[9]  G. Grimby,et al.  Self-reported leisure time physical activity: a useful assessment tool in everyday health care , 2012, BMC Public Health.

[10]  R. Callister,et al.  Effectiveness of weight loss interventions – is there a difference between men and women: a systematic review , 2014, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[11]  W. Ahrens,et al.  Young children’s screen activities, sweet drink consumption and anthropometry: results from a prospective European study , 2014, European Journal of Clinical Nutrition.

[12]  L. Moreno,et al.  Sedentary behaviour and obesity development in children and adolescents. , 2008, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[13]  C. Fernández-Rodríguez,et al.  Relationships between sleeping habits, sedentary leisure activities and childhood overweight and obesity , 2014, Psychology, health & medicine.

[14]  Natalie Pearson,et al.  Sedentary behavior and dietary intake in children, adolescents, and adults. A systematic review. , 2011, American journal of preventive medicine.

[15]  M. Hagberg,et al.  Computer use and stress, sleep disturbances, and symptoms of depression among young adults – a prospective cohort study , 2012, BMC Psychiatry.

[16]  M. Hagberg,et al.  Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults - a prospective cohort study , 2011, BMC public health.

[17]  L. Hale,et al.  Screen time and sleep among school-aged children and adolescents: a systematic literature review. , 2015, Sleep medicine reviews.

[18]  W. Willett,et al.  Adiposity and Different Types of Screen Time , 2013, Pediatrics.

[19]  Alain Guerrien,et al.  Quality of life in overweight and obese children and adolescents: a literature review , 2014, Quality of Life Research.

[20]  B M Slaney,et al.  Healthy at work? , 1970, Nursing times.

[21]  Natasha F. Veltri,et al.  Gender Differences in Online Gaming: A Literature Review , 2014, AMCIS.

[22]  Mari Hysing,et al.  Sleep and use of electronic devices in adolescence: results from a large population-based study , 2015, BMJ Open.

[23]  C. Vandelanotte,et al.  The association between short sleep and obesity after controlling for demographic, lifestyle, work and health related factors. , 2013, Sleep medicine.

[24]  K. Fox,et al.  Physical activity, screen time and obesity status in a nationally representative sample of Maltese youth with international comparisons , 2014, BMC Public Health.

[25]  A. S. Singh,et al.  Tracking of childhood overweight into adulthood: a systematic review of the literature , 2008, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[26]  D. Feeny,et al.  Bodyweight, gender, and quality of life: a population-based longitudinal study , 2012, Quality of Life Research.

[27]  A. Rissanen,et al.  Monitoring the Obesity Epidemic into the 21st Century – Weighing the Evidence , 2013, Obesity Facts.

[28]  Theo Stijnen,et al.  Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. , 2010, Archives of general psychiatry.

[29]  Mats Hagberg,et al.  Perceived connections between information and communication technology use and mental symptoms among young adults - a qualitative study , 2010, BMC public health.

[30]  G. Thomas,et al.  Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents , 2013, International Journal of Obesity.

[31]  W. Miller,et al.  A meta-analysis of the past 25 years of weight loss research using diet, exercise or diet plus exercise intervention , 1997, International Journal of Obesity.

[32]  Sanjay R. Patel,et al.  Short Sleep Duration and Weight Gain: A Systematic Review , 2008, Obesity.

[33]  Birgitte M Blatter,et al.  Test-retest reliability and validity of self-reported duration of computer use at work. , 2008, Scandinavian journal of work, environment & health.

[34]  R. Maddison,et al.  Comparative effects of TV watching, recreational computer use, and sedentary video game play on spontaneous energy intake in male children. A randomised crossover trial ☆ , 2014, Appetite.

[35]  S. Virtanen,et al.  Use of information and communication technology and prevalence of overweight and obesity among adolescents , 2005, International Journal of Obesity.

[36]  A. Okely,et al.  What factors are associated with excess body weight in Australian secondary school students? , 2012, The Medical journal of Australia.

[37]  Lindsay H. Shaw,et al.  Users Divided? Exploring the Gender Gap in Internet Use , 2002, Cyberpsychology Behav. Soc. Netw..

[38]  D. Moher,et al.  A comparison of direct vs. self‐report measures for assessing height, weight and body mass index: a systematic review , 2007, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[39]  D. Thelle,et al.  The validity of self-reported leisure time physical activity, and its relationship to serum cholesterol, blood pressure and body mass index. A population based study of 332,182 men and women aged 40–42 years , 2002, European Journal of Epidemiology.

[40]  J. Salmon,et al.  Mediators of the relationship between sedentary behavior and depressive symptoms amongst disadvantaged women , 2014 .

[41]  I. Pigeot,et al.  Socioeconomic factors and childhood overweight in Europe: results from the multi‐centre IDEFICS study , 2013, Pediatric obesity.

[42]  T. Lehtimäki,et al.  Sedentary behaviours and obesity in adults: the Cardiovascular Risk in Young Finns Study , 2013, BMJ Open.

[43]  D. Neumark-Sztainer,et al.  Sleep Duration and BMI in a Sample of Young Adults , 2012, Obesity.

[44]  M W Heymans,et al.  Association between TV viewing, computer use and overweight, determinants and competing activities of screen time in 4- to 13-year-old children , 2013, International Journal of Obesity.

[45]  C. Vandelanotte,et al.  Associations of Leisure-Time Internet and Computer Use With Overweight and Obesity, Physical Activity and Sedentary Behaviors: Cross-Sectional Study , 2009, Journal of medical Internet research.

[46]  Erica Scharrer,et al.  Active and Sedentary Video Game Time , 2014, J. Media Psychol. Theor. Methods Appl..

[47]  J. Lefevre,et al.  Patterns of physical activity and sedentary behavior in normal-weight, overweight and obese adults, as measured with a portable armband device and an electronic diary. , 2012, Clinical nutrition.