The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Increased Cardiometabolic Risk Is Associated with Increased TV Viewing Time
Open accessAbstract
PURPOSE: Television viewing time, independent of leisure time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and 5-yr changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardiometabolic risk (waist circumference, triglycerides, HDL-cholesterol, systolic and diastolic blood pressure, fasting plasma glucose, and a clustered cardiometabolic risk score) in Australian adults. METHODS: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999-2000 and 2004-2005. Noninstitutionalized adults aged > or =25 yr were measured at baseline (11,247; 55% of those completing an initial household interview); 6400 took part in the 5-yr follow-up biomedical examination, and 3846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used, and unstandardized B coefficients (95% confidence intervals (CI)) are provided. RESULTS: Baseline television viewing time (10 h.wk-1 unit) was not significantly associated with change in any of the biomarkers of cardiometabolic risk. Increases in television viewing time over 5 yr (10 h.wk-1 unit) were associated with increases in waist circumference (men: 0.43 cm, 95% CI = 0.08-0.78 cm, P = 0.02; women: 0.68 cm, 95% CI = 0.30-1.05, P < 0.001), diastolic blood pressure (women: 0.47 mm Hg, 95% CI = 0.02-0.92 mm Hg, P = 0.04), and the clustered cardiometabolic risk score (women: 0.03, 95% CI = 0.01-0.05, P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. CONCLUSIONS: These findings indicate that an increase in television viewing time is associated with adverse cardiometabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The importance of long sleepers reporting significantly more television viewing time lies in the fact that sedentary behavior is an independent risk factor for cardiovascular disease [71, 72].”
From Smoking, screen-based sedentary behavior, and diet associated with habitual sleep duration and chronotype: data from the UK Biobank (2016) · cites this paper as [72]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,385
Blood pressure, stroke, and coronary heart disease
Collins, R., Peto, R., MacMahon, S., Godwin, J., Qizilbash, N., Collins, R., MacMahon, S., Hebert, P., Eberlein, K. A., Taylor, J. O., et al. (1990) · The Lancet · doi:10.1016/0140-6736(90)90944-z · Cited by 4,491
MACMAHON, S. (1990) · The Lancet · doi:10.1016/0140-6736(90)90878-9 · Cited by 4,253 · cited 1×
“Measurement error in explanatory variables biases associations toward the null because of the regression dilution bias, and the greater the measurement error, the greater the bias toward the null (22).”
BackgroundHu, F. B., Li, T. Y., Colditz, G. A., Willett, W. C., & Manson, J. E. (2003) · JAMA · doi:10.1001/jama.289.14.1785 · Cited by 1,892
Hamilton, M. T., Hamilton, D. G., & Zderic, T. W. (2007) · Diabetes · doi:10.2337/db07-0882 · Cited by 1,655
Healy, G. N., Dunstan, D. W., Salmon, J., Cerin, E., Shaw, J. E., Zimmet, P. Z., & Owen, N. (2008) · Diabetes Care · doi:10.2337/dc07-2046 · Cited by 1,465
Self-citationObjectively Measured Sedentary Time, Physical Activity, and Metabolic Risk
Healy, G. N., Wijndaele, K., Dunstan, D. W., Shaw, J. E., Salmon, J., Zimmet, P. Z., & Owen, N. (2008) · Diabetes Care · doi:10.2337/dc07-1795 · Cited by 1,100
Self-citationSalmon, J., Owen, N., Crawford, D., Bauman, A., & Sallis, J. F. (2003) · Health Psychology · doi:10.1037/0278-6133.22.2.178 · Cited by 915
Self-citationHancox, R. J., Milne, B. J., & Poulton, R. (2004) · The Lancet · doi:10.1016/s0140-6736(04)16675-0 · Cited by 872
Physical Activity and Television Watching in Relation to Risk for Type 2 Diabetes Mellitus in Men
Hu, F. B., Leitzmann, M. F., Stampfer, M. J., Colditz, G. A., Willett, W. C., & Rimm, E. B. (2001) · Archives of Internal Medicine · doi:10.1001/archinte.161.12.1542 · Cited by 828
Cited by
Sorted by citations
Garber, C. E., Blissmer, B., Deschenes, M. R., Franklin, B. A., Lamonte, M. J., Lee, I.-M., Nieman, D. C., & Swain, D. P. (2011) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318213fefb · Cited by 9,319
Too Much Sitting: The Population Health Science of Sedentary Behavior
Owen, N., Healy, G. N., Matthews, C. E., & Dunstan, D. W. (2010) · Exercise and Sport Sciences Reviews · doi:10.1097/jes.0b013e3181e373a2 · Cited by 2,202
Self-citationSedentary Behaviors and Subsequent Health Outcomes in Adults
Thorp, A. A., Owen, N., Neuhaus, M., & Dunstan, D. W. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2011.05.004 · Cited by 1,455
Self-citationTreatment of NAFLD with diet, physical activity and exercise
Romero-Gómez, M., Zelber-Sagi, S., & Trenell, M. (2017) · Journal of Hepatology · doi:10.1016/j.jhep.2017.05.016 · Cited by 1,347
OECD (2019) · OECD health policy studies · doi:10.1787/67450d67-en · Cited by 1,227
Metadata
- Authors
- WIJNDAELE, K., HEALY, G. N., DUNSTAN, D. W., BARNETT, A. G., SALMON, J., SHAW, J. E., ZIMMET, P. Z., & OWEN, N.
- Affiliations
- The University of Queensland (AU)
- Baker Heart and Diabetes Institute (AU)
- Queensland University of Technology (AU)
- Deakin University (AU)
- ORCID
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2010-08
- Volume
- 42
- Issue
- 8
- Pages
- 1511-1518
- ISSN
- 0195-9131 (ISSN-L)
- OpenAlex
- W2098669683
- Cited by
- 161
- References
- 24
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 5 · 2023: 5 · 2022: 6 · 2021: 9 · 2020: 5 · 2019: 11 · 2018: 6 · 2017: 16 · 2016: 10 · 2015: 17 · 2014: 19 · 2013: 18 · 2012: 12
- FWCI
- 10.83
- Type
- journal article
- Language
- en
- Open access
- green
- eprints.qut.edu.au
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- eSpace (Curtin University) (submittedVersion)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Funders
- Sanofi
- Queensland Health
- National Heart Foundation of Australia
- Medical Research Council
- National Health and Medical Research Council (569861, 233200, 301200)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- television viewing, sedentary behavior, cardiometabolic risk, metabolic syndrome, waist circumference, diastolic blood pressure, triglycerides, HDL cholesterol, fasting blood glucose, physical activity, AusDiab, sex differences, adults, lifestyle risk factors, obesity, cardiovascular risk, diabetes risk, lifestyle intervention
- MeSH terms
- Adult, Australia, Blood Glucose, Blood Pressure, Cross-Sectional Studies, Fasting, Female, Follow-Up Studies, Humans, Cholesterol, HDL, Male, Middle Aged, Prospective Studies, Risk, Television, Triglycerides, Cohort Studies, Biomarkers, Metabolic Syndrome, Waist Circumference, Sedentary Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review