The DOI matches its Crossref record; 42 of the 43 references it cites were found in a registry or an index.
Relationship of Television Time with Accelerometer-Derived Sedentary Time: NHANES
Open accessAbstract
PURPOSE: To examine the relationship of self-reported television (TV) viewing time with accelerometer-derived total sedentary time and to determine whether it differs by subgroup. METHODS: Using data for adults (≥20 yr) from the 2003-2004 and 2005-2006 nationally representative US National Health and Nutrition Examination Surveys (NHANES; n=5738), linear regression models examined the associations of categories of self-reported TV viewing time (<1, 1, 2, 3, 4, and >5 h·d) with accelerometer-derived sedentary time (<100 counts per minute; h·d). Spearman ρ assessed the correlation between participants' rankings on the two measures. Analyses were stratified by gender, age, race/ethnicity, and, in the 2003-2004 NHANES cycle, by work status among working-aged adults (20-65 yr, n=2069). RESULTS: TV viewing time was significantly associated with sedentary time, with positive associations for all gender, age, race/ethnicity groups, and for those not working or working part-time, but not for those in full-time work. However, correlations between rankings of the measures were only "fair" overall (ρ=0.22) and were similar for all gender and racial/ethnic groups and for those of mid- and older age but not for those of younger age (20-39 yr, ρ=0.05). In the working-aged subgroup, there was also a fair correlation between the measures for those not working (ρ=0.22) but no significant correlation for those in part-time (ρ=0.14) or full-time work (ρ=0.03). CONCLUSIONS: Associations of TV viewing time with accelerometer-derived total sedentary time were statistically significant, but correlations were of only fair magnitude, and the strength of the relationship was not consistent across all population subgroups. These findings suggest that TV viewing time has an influence on overall sedentary time at a population level; however, measurement of sedentary time in other domains is also important.
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
“Fifty six percent of the older population report watching over 2 h of TV per day, 54.2% report over 3 h and 15.1% report over 4 h.”
From Prevalence of Sedentary Behavior in Older Adults: A Systematic Review (2013) · cites this paper as [34]
In the citing paper
“Fifty six percent of the older population report watching over 2 h of TV per day, 54.2% report over 3 h and 15.1% report over 4 h.”
From Prevalence of Sedentary Behavior in Older Adults: A Systematic Review (2013) · cites this paper as [34]
In the citing paper
“Fifty six percent of the older population report watching over 2 h of TV per day, 54.2% report over 3 h and 15.1% report over 4 h.”
From Prevalence of Sedentary Behavior in Older Adults: A Systematic Review (2013) · cites this paper as [34]
In the citing paper
“A study comparing self-reported TV viewing time with accelerometer-assessed sedentary time among a representative sample of US adults in the National Health and Nutrition Examination Survey yielded a correlation of only 0.22, indicating low agreement.[22]”
From Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges (2014) · cites this paper as [22]
In the citing paper
“It is unclear how well self-reported TV/screen time reflects total sedentary time.”
From Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges (2014) · cites this paper as [22]
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
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
International physical activity questionnaire: 12-country reliability and validity
CRAIG, C. L., MARSHALL, A. L., SJ??STR??M, M., BAUMAN, A. E., BOOTH, M. L., AINSWORTH, B. E., PRATT, M., EKELUND, U., YNGVE, A., SALLIS, J. F., et al. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000078924.61453.fb · Cited by 21,619 · cited 2×
“It is also a specific behavior that may be recalled relatively accurately (9, 26), thus has an advantage over using more-imprecise overall measures (11).”
Physical Activity in the United States Measured by Accelerometer
TROIANO, R. P., BERRIGAN, D., DODD, K. W., MÂSSE, L. C., TILERT, T., & MCDOWELL, M. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31815a51b3 · Cited by 7,638 · cited 8×
“citizens aged six years and older (7, 25, 37).”
InfluentialTotal energy intake: implications for epidemiologic analyses.
WILLETT, W., & STAMPFER, M. J. (1986) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114366 · Cited by 2,751 · cited 1×
“Sedentary time (hours per day) was corrected for monitor wear time using the residuals method (39).”
MethodRE: “TOTAL ENERGY INTAKE: IMPLICATIONS FOR EPIDEMIOLOGIC ANALYSES”
Palmgren, J., & Kushi, L. H. (1991) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115841 · Cited by 2,712
Amount of Time Spent in Sedentary Behaviors in the United States, 2003-2004
Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwm390 · Cited by 2,631 · cited 10×
“This cut point has previously been shown to approximate sitting time (25), however, as accelerometers are not able to discriminate between sitting and standing very still, time recorded as sedentary will not strictly represent sitting time.”
InfluentialSelf-citationToo 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 · cited 1×
“Paragraph 1 There is a growing body of evidence on the detrimental associations of sedentary behavior (prolonged sitting time) with cardio-metabolic risk biomarkers and health outcomes (28).”
Self-citationHu, 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 · cited 1×
“TV viewing is a highly prevalent leisure-time behavior (4, 12, 36) and has been shown to have strong and consistent detrimental associations with cardio-metabolic risk biomarkers and health outcomes, including premature mortality (13-15, 19-22).”
The evolving definition of “sedentary.”
Pate, R. R., O'Neill, J. R., & Lobelo, F. (2008) · Exercise and Sport Sciences Reviews · doi:10.1097/jes.0b013e3181877d1a · Cited by 1,280 · cited 1×
“In this context, Pate and colleagues (29) highlight inconsistencies in studies on sedentary behavior that report findings solely on TV viewing time, yet discuss these findings in terms of overall sedentary behavior.”
Salmon, 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-citation
Flagged first, then by citations
1 of the 43 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 101–137 of 137
Longitudinal Sedentary Time Among Females Aged 17 to 23 Years
Young, D. R., Sidell, M. A., Koebnick, C., Saksvig, B. I., Mohan, Y. D., Cohen, D. A., & Wu, T. T. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2018.11.021 · Cited by 6
Jean, N. P. (2014) · Journal of Child and Adolescent Behaviour · doi:10.4172/2375-4494.1000124 · Cited by 5
“Sedentary time has been shown to be affected by monitor wear time [42].”
BackgroundYu, L., Guo, Z., Long, Q., Zhao, X., Liu, Y., Cao, X., Zhang, Y., Yan, W., Qian, Q. Q., Chen, J., et al. (2024) · Advanced Biology · doi:10.1002/adbi.202400052 · Cited by 3
Keadle, S. K., Hasanaj, K., Leonard, K. S., Tolas, A., Crosley‐Lyons, R., Pfisterer, B., Legato, M., Fernandez, A., Lowell, E., Hollingshead, K. E., et al. (2023) · Contemporary Clinical Trials · doi:10.1016/j.cct.2023.107402 · Cited by 3
Minton, H. A. M., Thevenet-Morrison, K. N., & Fernandez, I. D. (2016) · American Journal of Lifestyle Medicine · doi:10.1177/1559827616680584 · Cited by 3
Papadimitriou, N., Kazmi, N., Dimou, N. L., Tsilidis, K. K., Martin, R. M., Lewis, S. J., Lynch, B. M., Hoffmeister, M., Kweon, S., Li, L., et al. (2023) · Cancer Medicine · doi:10.1002/cam4.6732 · Cited by 2
“3,48 Therefore, our results cannot be generalised to overall sedentary behaviour.”
BackgroundMaltagliati, S., Aslan, D. H., Sayre, M. K., Bharadwaj, P. K., Ally, M., Lai, M. H. C., Wilcox, R. R., Klimentidis, Y. C., Alexander, G. E., & Raichlen, D. A. (2025) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbaf071 · Cited by 3
Leung, K. M., & Wong, M. Y. C. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19105958 · Cited by 2
“, 2011 [21] 552 <100 counts/min Bankoski et al.”
MethodKeadle, S. K. (2019) · Scholarworks (University of Massachusetts Amherst) · doi:10.7275/xfd1-4h10 · Cited by 2
“However, when a previously non-exercising individual initiates an exercise training program, there is remarkable variability in the response to training (2).”
BackgroundInfluentialMarchant, G., Chevance, G., Ladino, A., Lefèvre, B., & Jacquemond, N. (2025) · F1000Research · doi:10.12688/f1000research.117843.3 · Cited by 1
Objectively Measured Sedentary Behavior and Cardiovascular Disease Risk Factors
Sung, H., Lim, J., Mun, J., & Kim, Y. S. (2020) · The Korean Journal of Sports Medicine · doi:10.5763/kjsm.2020.38.3.143 · Cited by 1
Longitudinal Study of Adjustable Workstations
Sandy, M. E. (2016) · Digital Commons - University of South Florida (University of South Florida) · Cited by 1
Papadimitriou, N., Kazmi, N., Dimou, N. L., Tsilidis, K. K., Martin, R. M., Lewis, S. J., Lynch, B. M., Hoffmeister, M., Kweon, S., Li, L., et al. (2023) · medRxiv · doi:10.1101/2023.03.01.23286492 · Cited by 1
INTERRELATIONSHIPS AMONG SEDENTARY BEHAVIOUR, SHORT SLEEP, AND THE MEBAOLIC SYNDROME IN ADULTS
Saleh, D., & Janssen, I. (2014) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2014-205217.9
Christifano, D. N. (2014) · KU ScholarWorks (University of Kansas)
McGuire, K. A. (2011) · QSpace (Queen's University Library)
Correlates of sedentary behaviour in mid-age and older adults
Chen, Y. (2016) · Loughborough University Institutional Repository (Loughborough University)
Objectively measured sedentary behaviour, physical activity and health in adolescent females
Dowd, K. (2012) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/7228
Kaseva, K. (2017) · Työväentutkimus Vuosikirja
Marchant, G., Chevance, G., Ladino, A., Lefèvre, B., & Jacquemond, N. (2022) · F1000Research · doi:10.12688/f1000research.117843.1
Mayo, N. L., Lopez, D. A., Block, R., Shi, H., Bertoni, A. G., Diaz, K. M., Ding, J., Post, W. S., Liu, Y., & Li, D. (2023) · medRxiv · doi:10.1101/2023.06.27.23291977
“9 Potential confounders identified from the literature included age, race/ethnicity, sex, study 224 site, education, smoking status, waist circumference, and MVPA MET hours per week (26-28).”
BackgroundMarchant, G., Chevance, G., Ladino, A., Lefèvre, B., & Jacquemond, N. (2024) · F1000Research · doi:10.12688/f1000research.117843.2
Chen, X., Hong, X., Gao, W., Luo, S., Cai, J., Liu, G., & Huang, Y. (2022) · Figshare · doi:10.6084/m9.figshare.19766063
Hasanaj, K., Leonard, K. S., Sears, D. D., Yu, F., Petrov, M. E. R., Keadle, S. K., & Buman, M. P. (2025) · Research Square · doi:10.21203/rs.3.rs-6803906/v1
Rockette‐Wagner, B. (2013) · D-Scholarship@Pitt (University of Pittsburgh)
Dickie, K. (2013) · Open University of Cape Town (University of Cape Town)
Dillon, K., Morava, A., Harry Prapavessis, A., Grigsby‐Duffy, L., Nović, A., & Gardiner, P. A. (2022) · Figshare · doi:10.6084/m9.figshare.21321641
Chen, X., Hong, X., Gao, W., Luo, S., Cai, J., Liu, G., & Huang, Y. (2022) · Figshare · doi:10.6084/m9.figshare.19766066
Dillon, K., Morava, A., Harry Prapavessis, A., Grigsby‐Duffy, L., Nović, A., & Gardiner, P. A. (2022) · Figshare · doi:10.6084/m9.figshare.21321647
Chen, L., You, G., Yang, Z., Shen, R., Zhang, R., Zhu, D., Wang, L., Lin, S., Lv, L., & Huang, K. (2023) · Figshare · doi:10.6084/m9.figshare.23707036
Dillon, K., Morava, A., Harry Prapavessis, A., Grigsby‐Duffy, L., Nović, A., & Gardiner, P. A. (2022) · Figshare · doi:10.6084/m9.figshare.21321644
Hasanaj, K., Leonard, K. S., Sears, D. D., Yu, F., Petrov, M. E. R., Keadle, S. K., & Buman, M. P. (2026) · Journal of Activity Sedentary and Sleep Behaviors · doi:10.1186/s44167-026-00096-0 · Cited by 1
“Several studies [58, 60, 61, 69] have suggested that greater rSST is associated with increased sedentary time, which can lead to poor health outcomes.”
Han, X., Han, Z., Wang, S., Zhang, Y., Liu, Y., Zhang, J., Yu, J., Cui, D., Ma, X., Jin, J., et al. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2026.1774582
“Television viewing stands out as a predominant sedentary behavior due to its passive nature, leading to reduced energy expenditure and often increased caloric intake, particularly from snacking (Clark et al., 2011).”
Niu, H.-G., Li, T., Gao, H.-Y., Liu, X., Wen, S.-M., & Gao, W. (2026) · Journal of Orthopaedics · doi:10.25259/joo_16_2026
Seasonal variations in lifestyle behaviours and their relationship with indicators for poor health
O'Connell, S. E. (2013) · Loughborough University Institutional Repository (Loughborough University)
Physical Activity and Eating Behaviour Changes in Patients with Obstructive Sleep Apnea Syndrome
Igelström, H. (2013) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Metadata
- Authors
- CLARK, B. K., HEALY, G. N., WINKLER, E. A. H., GARDINER, P. A., SUGIYAMA, T., DUNSTAN, D. W., MATTHEWS, C. E., & OWEN, N.
- Affiliations
- The University of Queensland (AU)
- Baker Heart and Diabetes Institute (AU)
- Edith Cowan University (AU)
- National Institutes of Health (US)
- ORCID
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2011-05
- Volume
- 43
- Issue
- 5
- Pages
- 822-828
- ISSN
- 0195-9131 (ISSN-L)
- PMC
- PMC8477752
- OpenAlex
- W2028234299
- Cited by
- 136
- References
- 43
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 4 · 2023: 9 · 2022: 11 · 2021: 6 · 2020: 9 · 2019: 7 · 2018: 7 · 2017: 6 · 2016: 12 · 2015: 8 · 2014: 16 · 2013: 18 · 2012: 10
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Edith Cowan University Research Online (Edith Cowan University) (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- eSpace (Curtin University) (submittedVersion)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Funders
- National Institutes of Health (Z99 CA999999)
- 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
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Keywords
- television viewing time, sedentary behavior, accelerometer-measured sedentary time, measurement agreement, subgroup differences, working-age adults, part-time work, full-time employment, gender differences, age differences, racial and ethnic differences
- MeSH terms
- Adult, Aged, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Nutrition Surveys, Television, United States, Linear Models, Young Adult, Actigraphy, 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
