Van Dyck et al. BMC Public Health 2011, 11:668 http://www.biomedcentral.com/1471-2458/11/668 been identified in cross-sectional and longitudinal studies addressing specific behaviors like television (TV) viewing, other screen-based entertainment and time spent sitting in cars, as well as in studies examining overall sitting time [4-11]. Because most adults spend more than 50% of their waking hours sedentary [12], interventions should not only aim at increasing PA, but also at decreas- ing SB in order to obtain optimal health effects. Domestic screen time (TV viewing and leisure-time Internet use at home) has been related to negative health outcomes [7-9] and is one of the most prominent non- work related SBs of adults in developed countries [13]. Moreover, TV viewing and leisure-time computer use have been associated with higher levels of other leisure- time sedentary behavior [14,15]. Approximately 20% of the Belgian adults can be categorized as ‘heavy TV watchers’ (> three hours/day of TV viewing) [16] and 77.8% of the Belgian adult population has Internet access at home (http://www.internetworldstats.com 2010, Miniwatts Marketing Group; accessed June 13, 2011). Furthermore, changing these types of leisure-time SB might be more susceptible to individuals’ own choice compared to for example occupational sitting. Therefore, TV viewing and leisure-time Internet use are target behaviors of interest when developing SB-reducing interventions. Nonetheless, before interventions can be developed, the crucial determi- nants of these behaviors need to be understood. When investigating determinants and correlates of SB, ecological models of health behaviors can be used as a the- oretical basis. However, since socio-demographic, psycho- social and physical environmental correlates of PA are poorly associated with SB, the PA-related ecological mod- els should be adjusted, using SB-specific variables [17-19]. To our knowledge, very few studies have investigated pos- sible specific correlates of TV viewing time and leisure- time Internet use in adults, so this type of research is still in an exploratory phase and the most important correlates remain to be clarified. Moreover, no studies have yet explored individual, psychosocial and environmental factors concurrently for associations with adults’ SB. Consequently the main aim of this study was to examine the associations of socio-demographic and sedentary-spe- cific home-environmental and psychosocial factors with TV viewing time and leisure-time Internet use in Belgian adults. Moreover, since behavioral correlates can differ between men and women, younger and older adults and those of higher and lower educational attainment [20-22], an additional aim was to examine gender, age and educa- tional level as potential moderators of these associations. Methods Participants and procedures The present study was conducted in Ghent (237,000 inhabitants, 165.18 km2, 1468 inhabitants/km2), Belgium. Page 2 of 10 Data were collected between March and May 2010. In total, 419 adults (20-65 years) participated in the study. To recruit participants, a questionnaire on SB and possi- ble correlates and a letter explaining the purpose of the study were mailed to 1200 randomly selected (based on publicly available population data) urban and suburban adults. A prepaid and preaddressed envelope was pro- vided to return the questionnaire. Fifty-three question- naires (4.4%) were returned because people no longer lived at the address. After six weeks, 347 completed ques- tionnaires were received and a second letter was sent to non-responders to ask for participation. After another six weeks, a total of 419 completed questionnaires (response rate 36.5%) was sent back. Informed consent was obtained from all participants and the study protocol was approved by the ethics committee of Ghent University Hospital. Measures Self-reported domestic screen time Domestic screen time included self-reported TV viewing time (min/day) and leisure-time internet use at home (min/day). Leisure-time internet use included visiting web- sites, emailing, and Facebook, Twitter, Netlog at home during leisure-time. These behaviors were determined using an adjusted version of the leisure-time SB question- naire developed by Salmon and colleagues [23]. The origi- nal English-language questionnaire was translated into Dutch and instead of assessing the amount of SB during the last seven days, a ‘usual week’ version was used in this study. Assessing ‘usual’ behavior offers a more stable mea- sure compared to assessing behaviors undertaken during the last seven days [24]. The English-language version of the questionnaire has fair to excellent reliability (intra- class-range from 0.56 to 0.82). Concurrent validity, assessed against a three-day behavioral log was fair-to- moderate with rho’s ranging from 0.20 to 0.60 [23]. Dura- tion (hours and minutes) of TV viewing and leisure-time Internet use on a regular weekday and weekend day was assessed. Daily means were calculated by the following for- mula: (weekday min/day*5 + weekend day min/day*2)/7. Socio-demographic variables These included self-reported gender, age, educational attainment (primary, secondary, tertiary education), employment status (employed, not employed/retired), and body mass index (BMI; calculated using self-reported height and weight). For the analyses, education was dichotomized into having college/university degree (yes/ no). Home-environmental variables To assess the number of TVs and computers in the home, questions were derived from a previously validated home electronic equipment scale [25]. All participants recorded the number of TVs and computers (with Internet