Dunstan DW, Barr ELM, Healy GN, et al. Television viewing time and mortality: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab)

Baker IDI Heart and Diabetes Institute, 250 Kooyong Rd, Caulfield, Victoria, Australia 3162.
Circulation (Impact Factor: 14.43). 01/2010; 121(3):384-91. DOI: 10.1161/CIRCULATIONAHA.109.894824
Source: PubMed


Television viewing time, the predominant leisure-time sedentary behavior, is associated with biomarkers of cardiometabolic risk, but its relationship with mortality has not been studied. We examined the associations of prolonged television viewing time with all-cause, cardiovascular disease (CVD), cancer, and non-CVD/noncancer mortality in Australian adults.
Television viewing time in relation to subsequent all-cause, CVD, and cancer mortality (median follow-up, 6.6 years) was examined among 8800 adults > or =25 years of age in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). During 58 087 person-years of follow-up, there were 284 deaths (87 CVD deaths, 125 cancer deaths). After adjustment for age, sex, waist circumference, and exercise, the hazard ratios for each 1-hour increment in television viewing time per day were 1.11 (95% confidence interval [CI], 1.03 to 1.20) for all-cause mortality, 1.18 (95% CI, 1.03 to 1.35) for CVD mortality, and 1.09 (95% CI, 0.96 to 1.23) for cancer mortality. Compared with a television viewing time of <2 h/d, the fully adjusted hazard ratios for all-cause mortality were 1.13 (95% CI, 0.87 to 1.36) for > or =2 to <4 h/d and 1.46 (95% CI, 1.04 to 2.05) for > or =4 h/d. For CVD mortality, corresponding hazard ratios were 1.19 (95% CI, 0.72 to 1.99) and 1.80 (95% CI, 1.00 to 3.25). The associations with both cancer mortality and non-CVD/noncancer mortality were not significant.
Television viewing time was associated with increased risk of all-cause and CVD mortality. In addition to the promotion of exercise, chronic disease prevention strategies could focus on reducing sitting time, particularly prolonged television viewing.

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    • "that prolonged time spent sitting is an emerging health concern and increases the risk of all-cause mortality (Dunstan et al., 2010; Thorp, Owen, Neuhaus, & Dunstan, 2011) and of numerous other negative health conditions. However, sitting is ubiquitous for most adults in developed countries. "
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    ABSTRACT: Following contextual design, we identified motivational and social aspects, as well as environmental factors of desk-based office workplaces, that contribute to sedentary behavior in the workplace. Through 10 full-day work observations, we gathered detailed qualitative data on why and when workers sit and unveiled tacit knowledge about habits and physical workplace layouts that favor prolonged sitting, complementing the mostly quantitative research done in the field. Developing social motivations for standing and walking, distributing frequently used objects to require more walking, and reducing the attractiveness of sitting turned out to be key drivers for reducing and interrupting sedentary behavior.
    Ergonomics in Design The Quarterly of Human Factors Applications 07/2015; 23(3-3):31-35. DOI:10.1177/1064804615585409
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    • "There is growing concern that youth in developed countries spend a large portion of their leisure time engaged in sedentary pursuits (31, 32). Studies in adults have shown that prolonged time engaged in sedentary behavior contributes to increased risk of all-cause mortality and cardiovascular disease mortality independent of leisure time physical activity (33, 34). While cardiovascular disease may not manifest until later in life, biological precursors for these diseases due to sedentarism may develop in youth (35). "
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    ABSTRACT: Sedentary behavior is associated with overweight and obesity in children, and distance to school has been negatively associated with active commuting to school. It is not known how distance to school relates to sedentary behavior in children. The aim of this study was to investigate the association between distance to school and children's sedentary behavior during weekdays at times where children interact with the neighborhood environment. Children (5-13 years, n = 295) who participated in the understanding relationships between activity and neighborhoods study (2008-2010) across four New Zealand cities wore a hip-mounted accelerometer for 7 days. Minutes spent sedentary (accelerometer count <100 min(-1)) were derived for the school travel periods (0800-0859 and 1500-1559) and after school discretionary time (1600-1759). Shortest street network distance to school was calculated from residential addresses using geographical information systems and parsed into tertiles for analysis. Children completed a daily travel log including mode of transport to and from school, which was dichotomized into active (walking and cycling) and passive (motorized) modes. Children living in the second tertile of distance from school were the least sedentary during the school traveling periods (42 ± 10%, mean ± true between-child SD) compared to those living in the first or third distance tertiles (47 ± 10 and 49 ± 10%, respectively); the differences were clear and likely substantial (90% confidence limits ± 6%). Children who traveled by motorized transport were more sedentary for each of the distance tertiles (50 versus 44%, 46 versus 39%, and 54 versus 27% for first, second, and third tertiles, respectively; 90% confidence limits ± 7%). In the period of 1600-1759, girls in the third distance tertile were the most sedentary. The combined effects of 1-2 km distance from school and active commuting to school contributed to least sedentary time in children.
    Frontiers in Public Health 09/2014; 2:151. DOI:10.3389/fpubh.2014.00151
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    • "Sedentary behaviours—defined by low energy expenditure (ranging from 1.0 to 1.5 metabolic equivalents) in a sitting or reclining position (Owen, 2012; Sedentary Behaviour Research N, 2012)—have emerged as an additional element with concerns about physical activity and health. Television (TV) viewing time, a common leisure-time sedentary behaviour, has been associated with major chronic diseases and adverse cardio-metabolic health outcomes (Thorp et al., 2010; Wijndaele et al., 2010), decreased life expectancy (Veerman et al., 2011) and all-cause and cardiovascular mortality (Dunstan et al., 2010; Grontved and Hu, 2011; Wijndaele et al., 2011). Despite increasing evidence on the detrimental health consequences of high volumes of TV viewing time, little is known about the relationships of TV viewing time with health-related quality of life. "
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    ABSTRACT: Objective: Television (TV) viewing, a common leisure-time sedentary behaviour, is associated adversely with cardio-metabolic health, fatigue, depression and mental health. However, associations of TV viewing time with health-related quality of life attributes are less well understood. We examined associations of TV viewing time with physical well-being, mental well-being and vitality in a large population-based sample of Australian adults. Method: The study sample comprised 4,483 men and 5,424 women (mean age 51±14years) from the Australian Diabetes, Obesity and Lifestyle study (1999-2000). Multiple linear regressions examined associations of TV viewing time (h/day) with the SF-36v1 physical and mental health component summary scores and the vitality sub-score, adjusting for leisure-time physical activity and waist circumference. Results: Each 1-h/day increment in TV viewing time was associated with lower physical (-0.56 [95% CI: -0.77, -0.34]) and mental (-0.41 [-0.70, -0.12]) component summary scores and vitality (-0.51 [-0.81, -0.21]). Associations remained significant after adjustment for leisure-time physical activity and waist circumference. There was a gender interaction for the association of TV viewing time with vitality (significant in men only). Conclusions: TV viewing time is associated adversely with physical well-being, mental well-being and vitality. Further studies are required to better understand potential causal relationships and variations by gender and leisure-time physical activity.
    Preventive Medicine 09/2014; DOI:10.1016/j.ypmed.2014.09.007 · 3.09 Impact Factor
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