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Diabetes Care 27:2603-2609, 2004
© 2004 by the American Diabetes Association, Inc.

Epidemiology/Health Services/Psychosocial Research
Original Article

Physical Activity and Television Viewing in Relation to Risk of Undiagnosed Abnormal Glucose Metabolism in Adults

David W. Dunstan, PHD1, Jo Salmon, PHD2, Neville Owen, PHD3, Timothy Armstrong, PHD4, Paul Z. Zimmet, MD1, Timothy A. Welborn, PHD5, Adrian J. Cameron, MPH1, Terence Dwyer, PHD6, Damien Jolley, MSC2 and Jonathan E. Shaw, MD1 on behalf of the AusDiab Steering Committee

1 International Diabetes Institute, Melbourne, Australia
2 School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia
3 Cancer Prevention Research Centre, The University of Queensland, Brisbane, Australia
4 Australian Institute of Health and Welfare, Canberra, Australia
5 Departments of Medicine and Public Health, The University of Western Australia, Perth, Australia
6 Menzies Centre for Population Health Research, University of Tasmania, Tasmania, Australia

Address correspondence and reprint requests to Dr. David Dunstan, International Diabetes Institute, 250 Kooyong Rd., Caulfield, Victoria, Australia 3162. E-mail: ddunstan{at}idi.org.au


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
OBJECTIVE—The goal of this study was to assess the associations of physical activity time and television (TV) time with risk of "undiagnosed" abnormal glucose metabolism in Australian adults.

RESEARCH DESIGN AND METHODS—This population-based cross-sectional study using a stratified cluster design involving 42 randomly selected Census Collector Districts across Australia included 8,299 adults aged 25 years or older who were free from new type 2 diabetes and self-reported ischemic disease and did not take lipid-lowering or antihypertensive drugs. Abnormal glucose metabolism (impaired fasting glycemia [IFG], impaired glucose tolerance [IGT], or new type 2 diabetes) was based on an oral glucose tolerance test. Self-reported physical activity time and TV time (previous week) were assessed using interviewer-administered questionnaires.

RESULTS—After adjustment for known confounders and TV time, the odds ratio (OR) of having abnormal glucose metabolism was 0.62 (95% CI 0.41–0.96) in men and 0.71 (0.50–1.00) in women for those engaged in physical activity ≥2.5 h/week compared with those who were sedentary (0 h/week). The ORs of having abnormal glucose metabolism were 1.16 (0.79–1.70) in men and 1.49 (1.12–1.99) in women who watched TV >14 h/week compared with those who watched ≤7.0 h/week. Higher TV viewing (>14 h/week) was also associated with an increased risk of new type 2 diabetes in men and women and IGT in women compared with those watching <14 h/week. Total physical activity of ≥2.5 h/week was associated with a reduced risk of IFG, IGT, and new type 2 diabetes in both sexes; however, only the association with IGT in women was statistically significant.

CONCLUSIONS—These findings suggest a protective effect of physical activity and a deleterious effect of TV time on the risk of abnormal glucose metabolism in adults. Population strategies to reduce risk of abnormal glucose metabolism should focus on reducing sedentary behaviors such as TV time, as well as increasing physical activity.

Abbreviations: IFG, impaired fasting glycemia • IGT, impaired glucose tolerance • OGTT, oral glucose tolerance test


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
In Australia and elsewhere, increases in obesity (1) and declines in adult participation in physical activity have been reported (2,3). Physical activities and sedentary behaviors are two broad classes of behavior that may be clearly distinguished from each other and that have different patterns of determinants (4,5). They may also have independent effects on total energy expenditure, on weight gain, and on underlying metabolic parameters (6,7). In recent times, the importance of regular physical activity has been highlighted in public health guidelines adopted by several health agencies (8), whereby adults should engage in moderate-intensity physical activity for at least 30 min on ≥5 days/week or engage in vigorous physical activity ≥3 days/week for ≥20 min/occasion.

Prospective studies have consistently shown that physical activity reduces the risk of diabetes, with a recent meta-analysis of 23 studies showing that sedentary individuals have a 1.31–1.45 increase in risk compared with active individuals (9). Some population-based cross-sectional studies have also demonstrated an inverse association between physical activity and risk of impaired glucose tolerance (IGT) (10,11). However, most of this evidence has come from nonwhite populations (10–12). More recent studies in white populations have been limited to middle-aged or elderly subjects (13,14). Information on the associations of physical activity with categories of abnormal glucose metabolism (impaired fasting glycemia [IFG], IGT, and undiagnosed new type 2 diabetes) is needed from larger population-based studies.

Sedentary behaviors, as represented by television (TV) watching, have been linked to obesity and cardiovascular disease risk factors in children (15,16) and adults (17,18). Two longitudinal studies conducted in the U.S. (6,7) have reported an inverse relationship between risk of type 2 diabetes and physical activity and a positive association with TV time. In those studies, type 2 diabetes was, however, self-reported. There have been no large population-based studies that have simultaneously assessed the relationships between physical activity, TV time, and objectively measured precursors of type 2 diabetes (IFG, IGT, and new type 2 diabetes).

The recent Australian Diabetes, Obesity, and Lifestyle Study (AusDiab) included oral glucose tolerance tests (OGTTs), and this analysis evaluates the cross-sectional associations of physical activity and TV time with the presence of objectively determined indexes of abnormal glucose metabolism (IFG, IGT, new type 2 diabetes).


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
RESULTS
 CONCLUSIONS
 References
 
AusDiab was conducted during 1999–2000 and studied a representative national sample of adults aged 25 years and older from the six states of Australia and the Northern Territory. The methods and major findings have been reported (1,19,20). The sample of 11,247 adults represented 55% of those completing the initial household interview. The present analyses use data from the 8,299 adults who were not pregnant and did not have health conditions that may affect physical activity habits, including those with clinically diagnosed type 2 diabetes and those taking prescribed medication for hypertension or dyslipidemia. Those who reported a history of angina, stroke, or myocardial infarction were also excluded.

Measures and data management
Participants attended the local survey center after an overnight fast (minimum of 8 h). An OGTT was performed and interpreted using World Health Organization specifications (21). Blood specimens were centrifuged and transported daily to the central laboratory. Plasma glucose levels were determined using an Olympus AU600 automated analyzer. Abnormal glucose metabolism was defined as having IFG, IGT, or new type 2 diabetes.

Waist circumference was measured using a steel measuring tape, with duplicate measurements made halfway between the lower border of the ribs and the iliac crest on a horizontal plane. The mean of these measures was used in the analyses. Obesity was defined as a waist circumference of ≥102.0 cm in men and ≥88.0 cm in women (22). Height without shoes was measured to the nearest 0.5 cm using a stadiometer. Weight was measured with the subject wearing light clothes on a mechanical beam balance and was recorded to the nearest 0.1 kg. BMI was calculated as weight (kilograms)/height (meters squared). Those with a BMI of 25.0–29.9 kg/m2 were classified as overweight, whereas those with a BMI of ≥30.0 kg/m2 were classified as obese (22).

Demographic attributes, physical activity, and TV time were assessed using an interviewer-administered questionnaire. Participants reported their age, family history of diabetes (mother/father), current cigarette smoking status, and level of educational attainment (categorized as primary/never attended, some secondary, completed secondary, and university/further education).

Participants self-reported their frequency and duration of physical activity during the previous week using the Active Australia Survey questionnaire (23). Physical activity consisted of walking for recreation or transport, "other" moderate activity, and vigorous activity. These questions have been found to provide reliable and valid estimates of adult physical activity (23). Total physical activity time for the previous week was calculated as the sum of the time spent walking (if continuous and ≥10 min) or performing moderate physical activity plus double the time spent in vigorous physical activity. Australian public health guidelines (24) recommend a total physical activity time of at least 150 min/week. Because vigorous-intensity activity is commonly considered to contribute additional health benefits, we analyzed associations between abnormal glucose metabolism and walking plus moderate physical activity time (excluding those who reported any vigorous activity), and total physical activity time (including those who reported >0 min of vigorous activity) was assessed. Total physical activity categories were created to reflect current recommendations—those meeting the public health physical activity guidelines (≥2.5 h/week), those engaged in some physical activity but not meeting the public health guidelines (>0–2.49 h/week), and those reporting no activity (sedentary; 0 h/week). Walking plus moderate physical activity only was categorized according to those meeting the public health guidelines (≥2.5 h/week) and those not meeting the guidelines.

Participants also self-reported the total time they spent watching TV or videos in the previous week. This measure provides a reliable and valid estimate of TV time among adults (5). The average hours watching TV per week was used to create three categories of TV viewing (0–7, 7.01–14, and >14 h/week).

A self-administered validated food frequency questionnaire developed by the Anti-Cancer Council of Victoria (25) was used to assess nutrient intakes. Calculation of nutrient intake was achieved by multiplying the frequency of food consumption by standard portion weights to obtain weight of food consumed per day. These were then converted to nutrient intakes based on the NUTTAB95 nutrient composition data (26).

Statistical analysis
All analyses were conducted using Stata Statistical Software Release 8.0 (27) survey commands for analyzing complex survey data. Sample weights based on the 1998 estimated residential Australian were used to account for clustering and stratification in the survey design and for nonresponse. Odds ratios (ORs) (with 95% CI) for binary outcomes were estimated using forced entry logistic regression models. Regression models included the TV and physical activity categories and were adjusted for age, education level, cigarette smoking, parental history of diabetes, dietary covariates, and waist circumference. Associations of both total physical activity and TV viewing with IFG, IGT, and new type 2 diabetes were determined using separate models with the ORs calculated for the highest category of total physical activity (≥2.5 h/week) and TV viewing (>14 h/week).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
CONCLUSIONS
 References
 
Table 1 shows the demographic characteristics according to the mean hours spent in total physical activity time and the mean hours spent watching TV. Participants who spent more time engaged in physical activity were younger, were more likely to have completed university/further education, and were less likely to smoke cigarettes, be overweight, or have abnormal glucose metabolism. Those reporting more physical activity time had a lower intake of total fat and saturated fat and had a higher intake of carbohydrates, sugars, fiber, and alcohol. Participants who spent more time watching TV were older, were less likely to have completed university/further education, and were more likely to smoke cigarettes, be overweight, and have abnormal glucose metabolism. These participants also had a higher intake of total energy, total and saturated fats, total carbohydrates, and total sugars. However, there were no significant differences with respect to total physical activity. The correlation between TV watching and physical activity levels was negligible (r = –0.04).


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  		Table 1— Selected characteristics* according to categories of total physical activity time and television time in 8,299 adults aged 25 years or older in the AusDiab study

 
The risk of abnormal glucose metabolism was inversely associated with total physical activity in men and women (Table 2). The associations remained significant after further adjustment for education, family history of diabetes, smoking, dietary covariates, and TV time, but were no longer significant after adjustment for waist circumference. Women who engaged in ≥2.5 h/week of walking plus moderate activity only (excluding those who reported >0 min vigorous activity) were less likely to have abnormal glucose metabolism compared with those not achieving the public health recommendations. No significant associations for walking plus moderate activity only were observed in men.


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  		Table 2— Adjusted* ORs for the presence of abnormal glucose metabolism according to categories of physical activity

 
After adjusting for age, higher levels of TV time were positively associated with an increased risk of having abnormal glucose metabolism in women, but not in men (Table 3). Further adjustment for education, family history, smoking, dietary covariates, and physical activity did not appreciably alter the ORs. However, the inclusion of waist circumference into the model led to a larger attenuation in the association in both sexes.


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  		Table 3— Adjusted* ORs for the presence of abnormal glucose metabolism according to categories of TV

 
Separate logistic regression models (adjusted for the various confounders, except waist circumference) were applied to provide an estimate of the influence of each 1-h increment in daily TV viewing time and each 30-min/day increase in physical activity on the risk of abnormal glucose metabolism. For each 1-h/day increase in time spent watching TV, there was a 7% (95% CI –4 to 19%; P = 0.21) and 18% (9–29%; P = 0.001) increase in the risk of abnormal glucose metabolism in men and women, respectively. In contrast, each 30-min/day increase in physical activity was associated with an 11% (3–19%; P = 0.01) and 10% (–2 to 10%; P = 0.10) decrease in risk of abnormal glucose metabolism in men and women, respectively.

The associations of TV viewing and total physical activity with IFG, IGT, and new type 2 diabetes are shown in Fig. 1. Compared with those who watched TV 14 h/week or less (reference group), watching TV >14 h/week was associated with a significantly increased risk of having new type 2 diabetes in men (OR 2.4 [95% CI 1.41–4.12]) and women (2.2 [1.32–3.61]). TV viewing >14 h/week was also associated with an increased risk of IGT in women (1.34 [0.99–1.81]). No significant associations were observed between IFG and TV viewing. Women who engaged in ≥2.5 h/week of total physical activity were significantly less likely to have IGT than those who participated in physical activity <2.5 h/week. Reductions in risk for IFG, IGT, and new type 2 diabetes in men and IFG and new type 2 diabetes in women were not statistically significant.



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  		Figure 1— Adjusted ORs for the presence of IFG, IGT, and undiagnosed (new) type 2 diabetes (new DM) according to TV viewing (≥14 h/week vs. ≤14 h/week) and total physical activity (PA) (≥2.5 h/week vs. <2.5 h/week). ORs were adjusted for age, education, family history of diabetes, cigarette smoking, dietary covariates (total energy, total fat, total saturated fat, total carbohydrates, total sugars, fiber, and alcohol), and TV time/physical activity time.

 

   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
References
 
In this large cross-sectional study of Australian adults, compliance with the recommended public health guidelines for physical activity (≥2.5 h/week) was associated with a reduced risk of having abnormal glucose metabolism in men and women. The study also demonstrated that a sedentary lifestyle, characterized by time spent watching TV, was significantly associated with an increased risk for abnormal glucose metabolism in women, independent of the effects of physical activity. Greater TV time was also shown to more than double the risk of having new type 2 diabetes in men and women.

Few population-based studies have used an OGTT to determine the association between physical activity and abnormal glucose metabolism (10,11,13,14). Most previous studies that have reported a protective effect of physical activity on the prevalence of undiagnosed diabetes or IGT have followed-up middle-aged/elderly participants (13,14) or have sampled nonwhite populations (10,11). Our study covers a broad age range, and because individuals with IFG, IGT, or new type 2 diabetes were unaware of their condition, biased reporting of physical activity is no more likely in those with or without abnormal glucose metabolism. Although it is well accepted that physical activity reduces the risk of type 2 diabetes (6), our findings have extended this knowledge base by demonstrating an inverse association between physical activity and the presence of asymptomatic diabetes or its precursors.

The findings provide further support for current physical activity recommendations, suggesting that adults who adhere to the minimum physical activity guidelines could reduce their risk of having abnormal glucose metabolism irrespective of TV time and dietary intake. Although our results show that the beneficial effects of physical activity were partly mediated by body fat distribution (waist circumference), it has been argued that adjustment for waist circumference in regression models may constitute statistical overcorrection and lead to an underestimation of the true beneficial effect of physical activity (6). This is because physical activity has beneficial effects on weight loss and weight maintenance; therefore, increased physical activity may reduce body fat content (6).

Our finding of an independent association between TV time and new type 2 diabetes in men and women is consistent with recent cohort studies showing that increased TV time is associated with the incidence of self-reported type 2 diabetes, independent of physical activity (6,7). Our study produced mixed results with respect to other categories of abnormal glucose metabolism in that a positive association was observed between TV time and IGT in women but not in men, with no significant associations observed for IFG in either sex. Although the association between TV time and abnormal glucose metabolism in women was attenuated by the adjustment for waist circumference, the association was more pronounced in women than in men. An earlier population-based sample from the NHLBI (National Heart, Lung and Blood Institute) Family Heart Study showed that blood glucose concentrations were positively correlated with TV watching in both sexes (18). However, analyses included adjustments for occupational physical activity in that study. Sex differences in associations between TV time and abnormal glucose metabolism in the current study may be caused by limitations in the physical activity instrument, which excludes assessment of domestic and occupational physical activity. Furthermore, previous research has demonstrated that higher proportions of women underreport their dietary intake (28), which could also explain stronger associations between TV viewing and abnormal glucose metabolism among women even after adjusting for dietary intake.

The positive association observed between TV time and risk of abnormal glucose metabolism may be explained in a number of ways. It could be that TV viewing displaces physical activity. However, the two variables are poorly related in our own and in other studies (7). TV viewing has also been found to be associated with snacking behavior (29). Although the association between TV time and abnormal glucose metabolism was independent of dietary intake, our investigation shows that adults who watched more TV also had an unhealthy eating pattern, as evidenced by higher reported total energy, fat, and saturated fat intake compared with those watching less TV.

The major strengths of this study include its large sample size across a wide age range, measurement of glucose metabolism through blood collection, and measurement of several other covariates including body adiposity. Limitations of the study include assessment of just one aspect of sedentary living (TV viewing) and the cross-sectional study design. Therefore, it is difficult to determine the extent to which participants were in lower physical activity or higher TV time categories because of their health status. Longitudinal studies in this population should clarify the temporal associations between TV time, physical activity, and abnormal glucose metabolism. Furthermore, additional work is required to elucidate the potential behavioral and psychophysical mechanisms for the observed associations between physical activity and TV viewing with abnormal glucose tolerance. In particular, there is evidence that depression is associated with TV viewing (16) and type 2 diabetes (30). Future research should also aim to collect biomedical end points (such as an OGTT) when assessing abnormal glucose metabolism, and objective measures of physical activity such as accelerometers and pedometers should also be used.

In conclusion, this study provides further evidence that higher levels of physical activity are associated with a reduced risk of having "undiagnosed" abnormal glucose metabolism in adults. In contrast, prolonged TV watching increases the risk, especially in women. These findings suggest that the promotion of physical activity and encouragement of adults to watch less TV may be important dual public health strategies for the prevention of abnormal glucose metabolism and type 2 diabetes.


   Acknowledgments
 
D.D. is supported by a National Health and Medical Research Council (NHMRC) Post-Doctoral Research Fellowship. J.S. is supported by a Victorian Health Promotion Foundation Public Health Research Fellowship.

We are most grateful to the following for their support of the study: The Commonwealth Department of Health and Aged Care, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, Aventis Pharmaceutical, AstraZeneca, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly (Aust) Pty Ltd, GlaxoSmithKline, Janssen-Cilag (Aust) Pty Ltd, Merck Lipha s.a., Merck Sharp & Dohme (Aust), Novartis Pharmaceutical (Aust) Pty Ltd, Novo Nordisk Pharmaceutical Pty Ltd, Pharmacia and Upjohn Pty Ltd, Pfizer Pty Ltd, Roche Diagnostics, Sanofi Synthelabo (Aust) Pty Ltd, Servier Laboratories (Aust) Pty Ltd, BioRad Laboratories Pty Ltd, HITECH Pathology Pty Ltd, the Australian Kidney Foundation, Diabetes Australia, Diabetes Australia (Northern Territory), Queensland Health, South Australian Department of Human Services, Tasmanian Department of Health and Human Services, Territory Health Services, Victorian Department of Human Services, and Health Department of Western Australia.

Also, for their invaluable contribution to the field activities of AusDiab, we are enormously grateful to Annie Allman, Marita Dalton, Adam Meehan, Claire Reid, Alison Stewart, Robyn Tapp, and Fay Wilson.

The AusDiab Steering Committee consists of Dr. B. Atkins, Dr. S. Bennett, Dr. S. Chadban, Prof. S. Colagiuri, Dr. M. de Courten, Dr. M. D’Embden, Dr. D. Dunstan, Prof. T. Dwyer, Dr. D. Jolley, Dr. P. Magnus, Prof. J. Mathews, Dr. D. McCarty, Prof. K. O’Dea, Dr. P. Phillips, Dr. P. Popplewell, Mr. I. Kemp, Prof. H. Taylor, Prof. T. Welborn, and Prof. P. Zimmet.


   Footnotes
 
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

Received for publication April 14, 2004. Accepted for publication July 20, 2004.


   References
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 

  1. Cameron AJ, Welborn TA, Zimmet PZ, Dunstan DW, Owen N, Salmon J, Dalton M, Jolley D, Shaw JE: Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust 178:427–432, 2003[Medline]
  2. Bauman A, Armstrong T, Davies J, Owen N, Brown W, Bellew B, Vita P: Trends in physical activity participation and the impact of integrated campaigns among Australian adults, 1997–1999. Aust N Z J Public Health 27:76–79, 2003[Medline]
  3. Norman A, Bellocco R, Vaida F, Wolk A: Age and temporal trends of total physical activity in Swedish men. Med Sci Sports Exerc 35:617–622, 2003[Medline]
  4. Owen N, Leslie E, Salmon J, Fotheringham MJ: Environmental determinants of physical activity and sedentary behavior. Exerc Sports Sci Rev 28:153–158, 2000
  5. Salmon J, Owen N, Crawford D, Bauman A, Sallis JF: Physical activity and sedentary behavior: a population-based study of barriers, enjoyment, and preference. Health Psychol 22:178–188, 2003[Medline]
  6. Hu FB, Leitzmann MF, Stampfer MJ, Colditz GA, Willett WC, Rimm EB: Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med 161:1542–1548, 2001[Abstract/Free Full Text]
  7. Hu FB, Li TY, Colditz GA, Willett WC, Manson JE: Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. JAMA 289:1785–1791, 2003[Abstract/Free Full Text]
  8. U.S. Department of Health and Human Services: Physical Activity and Health: A Report of the Surgeon General. Washington, DC, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, 1996
  9. Bull F, Armstrong T, Dixon T, Ham S, Neiman A, Pratt M: Physical inactivity. In Comparative Quantification of Health Risks: Global and Regional Burden of Disease due to Selected Major Risk Factors. Ezzati M, Lopez A, Rodgers A, Murray C, Eds. Geneva, World Health Organization, 2003
  10. Dowse GK, Zimmet PZ, Gareboo H, George K, Alberti MM, Tuomilehto J, Finch CF, Chitson P, Tulsidas H: Abdominal obesity and physical activity as risk factors for NIDDM and impaired glucose tolerance in Indian, Creole, and Chinese Mauritians. Diabetes Care 14:271–282, 1991[Abstract]
  11. Kriska AM, LaPorte RE, Pettitt DJ, Charles MA, Nelson RG, Kuller LH, Bennett PH, Knowler WC: The association of physical activity with obesity, fat distribution and glucose intolerance in Pima Indians. Diabetologia 36:863–869, 1993[Medline]
  12. James SA, Jamjoum L, Raghunathan TE, Strogatz DS, Furth ED, Khazanie PG: Physical activity and NIDDM in African-Americans: the Pitt County Study. Diabetes Care 21:555–562, 1998[Abstract]
  13. Mooy JM, Grootenhuis PA, de Vries H, Valkenburg HA, Bouter LM, Kostense PJ, Heine RJ: Prevalence and determinants of glucose intolerance in a Dutch Caucasian population: the Hoorn Study. Diabetes Care 18:1270–1273, 1995[Abstract]
  14. Baan CA, Stolk RP, Grobbee DE, Witteman JC, Feskens EJ: Physical activity in elderly subjects with impaired glucose tolerance and newly diagnosed diabetes mellitus. Am J Epidemiol 149:219–227, 1999[Abstract/Free Full Text]
  15. Andersen RE, Crespo CJ, Bartlett SJ, Cheskin LJ, Pratt M: Relationship of physical activity and television watching with body weight and level of fatness among children: results from the Third National Health and Nutrition Examination Survey. JAMA 279:938–942, 1998[Abstract/Free Full Text]
  16. Sidney S, Sternfeld B, Haskell WL, Jacobs DR Jr, Chesney MA, Hulley SB: Television viewing and cardiovascular risk factors in young adults: the CARDIA study. Ann Epidemiol 6:154–159, 1996[Medline]
  17. Coakley EH, Rimm EB, Colditz G, Kawachi I, Willett W: Predictors of weight change in men: results from the Health Professionals Follow-up Study. Int J Obes Relat Metab Disord 22:89–96, 1998[Medline]
  18. Kronenberg F, Pereira MA, Schmitz MK, Arnett DK, Evenson KR, Crapo RO, Jensen RL, Burke GL, Sholinsky P, Ellison RC, Hunt SC: Influence of leisure time physical activity and television watching on atherosclerosis risk factors in the NHLBI Family Heart Study. Atherosclerosis 153:433–443, 2000[Medline]
  19. Dunstan DW, Zimmet PZ, Welborn TA, Cameron AJ, Shaw J, de Courten M, Jolley D, McCarty DJ: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab):methods and response rates. Diabetes Res Clin Pract 57:119–129, 2002[Medline]
  20. Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA, Dwyer T, Colagiuri S, Jolley D, Knuiman M, Atkins R, Shaw JE: The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study. Diabetes Care 25:829–834, 2002[Abstract/Free Full Text]
  21. World Health Organization: Definition, Diagnosis and Classification of Diabetes Mellitus and Its Complications. Geneva, World Health Org., 1999
  22. World Health Organization: Obesity. Preventing and Managing the Global Epidemic. Report of a WHO Consultation on Obesity. Geneva, World Health Org., 1998
  23. Australian Institute of Health and Welfare (AIHW): The Active Australia Survey: A Guide and Manual for Implementation, Analysis and Reporting. Canberra, Australia, AIHW, 2003
  24. Commonwealth Department of Health and Aged Care: National Physical Activity Guidelines for Australians: Active Australia. Canberra, Australia, Commonwealth Department of Health and Aged Care, 1999
  25. Ireland P, Jolley D, Giles G, O’Dea K, Powles J, Rutishauser I, Wahlqvist M, Williams J: Development of the Melbourne FFQ: a food frequency questionnaire for use in an Australian prospective study involving an ethnically diverse cohort. Asia Pacific J Clin Nutr 3:19–31, 1994
  26. Lewis J, Milligan G, Hunt A: NUTTAB95 Nutrient Data Table for Use in Australia. Canberra, Australia, Australian Government Publishing Service, 1995
  27. StataCorp: Stata Statistical Software. Release 8.0. College Station, TX, Stata Corporation, 2003
  28. Briefel RR, Sempos CT, McDowell MA, Chien S, Alaimo K: Dietary methods research in the third National Health and Nutrition Examination Survey: underreporting of energy intake. Am J Clin Nutr 65:1203S–1209S, 1997[Abstract/Free Full Text]
  29. Jeffery RW, French SA: Epidemic obesity in the United States: are fast foods and television viewing contributing? Am J Public Health 88:277–280, 1998[Abstract/Free Full Text]
  30. Carnethon MR, Kinder LS, Fair JM, Stafford RS, Fortmann SP: Symptoms of depression as a risk factor for incident diabetes: findings from the National Health and Nutrition Examination Epidemiologic Follow-up Study, 1971–1992. Am J Epidemiol 158:416–423, 2003[Abstract/Free Full Text]

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M. T. Hamilton, D. G. Hamilton, and T. W. Zderic
Role of Low Energy Expenditure and Sitting in Obesity, Metabolic Syndrome, Type 2 Diabetes, and Cardiovascular Disease
Diabetes, November 1, 2007; 56(11): 2655 - 2667.
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H. D. Margeirsdottir, J. R. Larsen, C. Brunborg, L. Sandvik, K. Dahl-Jorgensen, and for the Norwegian Study Group for Childhood Diabet
Strong Association Between Time Watching Television and Blood Glucose Control in Children and Adolescents With Type 1 Diabetes
Diabetes Care, June 1, 2007; 30(6): 1567 - 1570.
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G. N. Healy, D. W. Dunstan, J. Salmon, E. Cerin, J. E. Shaw, P. Z. Zimmet, and N. Owen
Objectively Measured Light-Intensity Physical Activity Is Independently Associated With 2-h Plasma Glucose
Diabetes Care, June 1, 2007; 30(6): 1384 - 1389.
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D. W. Dunstan, J. Salmon, G. N. Healy, J. E. Shaw, D. Jolley, P. Z. Zimmet, N. Owen, and on behalf of the AusDiab Steering Committee
Association of Television Viewing With Fasting and 2-h Postchallenge Plasma Glucose Levels in Adults Without Diagnosed Diabetes
Diabetes Care, March 1, 2007; 30(3): 516 - 522.
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C. Y. Jeon, R. P. Lokken, F. B. Hu, and R. M. van Dam
Physical Activity of Moderate Intensity and Risk of Type 2 Diabetes: A systematic review
Diabetes Care, March 1, 2007; 30(3): 744 - 752.
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G. N. Healy, D. W. Dunstan, J. E. Shaw, P. Z. Zimmet, and N. Owen
Beneficial Associations of Physical Activity With 2-h but Not Fasting Blood Glucose in Australian Adults: The AusDiab Study
Diabetes Care, December 1, 2006; 29(12): 2598 - 2604.
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