Television Viewing Time, Overweight, Obesity, and Severe COVID-19: A Brief Report From UK Biobank

in Journal of Physical Activity and Health

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Malik HamrouniNational Center for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom

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Matthew J. RobertsNational Center for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom

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Nicolette C. BishopNational Center for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom

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Background: Overweight and obesity are well-established risk factors for COVID-19 severity; however, less is known about the role of sedentary behaviors such as television (TV) viewing. The purpose of this brief report was to determine whether lower TV viewing time may mitigate the risk of severe COVID-19 in individuals with excess weight. Methods: We analyzed 329,751 UK Biobank participants to investigate the independent and combined associations of BMI and self-reported TV viewing time with odds of severe COVID-19 (inpatient COVID-19 or COVID-19 death). Results: Between March 16 and December 8, 2020, there were 1648 instances of severe COVID-19. Per 1-unit (hours per day) increase in TV viewing time, the odds of severe COVID-19 increased by 5% (adjusted odds ratio = 1.05, 95% confidence interval = 1.02–1.08). Compared with normal-weight individuals with low (≤1 h/d) TV viewing time, the odds ratios for overweight individuals with low and high (≥4 h/d) TV viewing time were 1.17 (0.89–1.55) and 1.66 (1.31–2.11), respectively. For individuals with obesity, the respective ORs for low and high TV viewing time were 2.18 (1.61–2.95) and 2.14 (1.69–2.73). Conclusion: Higher TV viewing time was associated with higher odds of severe COVID-19 independent of BMI and moderate to vigorous physical activity. Additionally, low TV viewing time may partly attenuate the elevated odds associated with overweight, but not obesity.

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  • 1.

    Hamer M, Gale CR, Kivimäki M, Batty GD. Overweight, obesity, and risk of hospitalization for COVID-19: a community-based cohort study of adults in the United Kingdom. Proc Natl Acad Sci. 2020;117(35):2101121013. doi:10.1073/pnas.2011086117

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Yates T, Razieh C, Zaccardi F, et al. Obesity, walking pace and risk of severe COVID-19 and mortality: analysis of UK Biobank. Int J Obes. 2021;45(5):11551159. doi:10.1038/s41366-021-00771-z

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Hamrouni M, Roberts MJ, Thackray A, Stensel DJ, Bishop N. Associations of obesity, physical activity level, inflammation and cardiometabolic health with COVID-19 mortality: a prospective analysis of the UK Biobank cohort. BMJ Open. 2021;11(11):e055003. doi:10.1136/bmjopen-2021-055003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Rowlands AV, Dempsey PC, Gillies C, et al. Association between accelerometer-assessed physical activity and severity of COVID-19 in UK Biobank. Mayo Clin Proc Innov Qual Outcomes. 2021;5(6):9971007. doi:10.1016/j.mayocpiqo.2021.08.011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Sallis R, Young DR, Tartof SY, et al. Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients. Br J Sports Med. 2021;55(19):10991105. doi:10.1136/bjsports-2021-104080

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Hamer M, Yates T, Demakakos P. Television viewing and risk of mortality: exploring the biological plausibility. Atherosclerosis. 2017;263:151155. doi:10.1016/j.atherosclerosis.2017.06.024

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    van der Ploeg HP, Hillsdon M. Is sedentary behaviour just physical inactivity by another name? Int J Behav Nutr Phys Act. 2017;14(1):142. doi:10.1186/s12966-017-0601-0

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Wijndaele K, Brage S, Besson H, et al. Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study. Int J Epidemiol. 2011;40(1):150159. doi:10.1093/ije/dyq105

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    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. 2001;161(12):15421548. doi:10.1001/archinte.161.12.1542

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Grøntved A, Hu FB. Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality a meta-analysis. JAMA. 2011;305(23):24482455. doi:10.1001/jama.2011.812

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11.

    Aadahl M, Kjaer M, Jørgensen T. Influence of time spent on TV viewing and vigorous intensity physical activity on cardiovascular biomarkers. The Inter 99 study. Eur J Cardiovasc Prev Rehabil. 2007;14(5):660665. doi:10.1097/HJR.0b013e3280c284c5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    O’Hearn M, Liu J, Cudhea F, Micha R, Mozaffarian D. Coronavirus disease 2019 hospitalizations attributable to cardiometabolic conditions in the United States: a comparative risk assessment analysis. J Am Heart Assoc. 2021;10(5):e019259. doi:10.1161/JAHA.120.019259

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Morys F, Dagher A. Poor metabolic health increases COVID-19-related mortality in the UK biobank sample. Front Endocrinol. 2021;12:652765. doi:10.3389/fendo.2021.652765

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. doi:10.1371/journal.pmed.1001779

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Craig CL, Marshall AL, Sjöström M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):13811395. doi:10.1249/01.MSS.0000078924.61453.FB

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Bohannon RW. Grip strength: an indispensable biomarker for older adults. Clin Interv Aging. 2019;14:16811691. doi:10.2147/CIA.S194543

  • 17.

    Kunzmann AT, Mallon KP, Hunter RF, et al. Physical activity, sedentary behaviour and risk of oesophago-gastric cancer: a prospective cohort study within UK Biobank. United Eur Gastroenterol J. 2018;6(8):11441154. doi:10.1177/2050640618783558

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Morris JS, Bradbury KE, Cross AJ, Gunter MJ, Murphy N. Physical activity, sedentary behaviour and colorectal cancer risk in the UK biobank. Br J Cancer. 2018;118(6):920929. doi:10.1038/bjc.2017.496

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Cassidy S, Chau JY, Catt M, Bauman A, Trenell MI. Cross-sectional study of diet, physical activity, television viewing and sleep duration in 233 110 adults from the UK biobank; the behavioural phenotype of cardiovascular disease and type 2 diabetes. BMJ Open. 2016;6(3):e010038. doi:10.1136/bmjopen-2015-010038

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Armstrong J, Rudkin JK, Allen N, et al. Dynamic linkage of COVID-19 test results between Public Health England’s second generation surveillance system and UK Biobank. Microb Genomics. 2020;6(7):mgen.0.000397. doi:10.1099/mgen.0.000397

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Tarp J, Fagerland MW, Dalene KE, et al. Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies. Br J Sports Med. 2021;56(13):725732. doi:10.1136/bjsports-2021-104827

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Chen X, Hong X, Gao W, et al. Causal relationship between physical activity, leisure sedentary behaviors and COVID-19 risk: a Mendelian randomization study. J Transl Med. 2022;20(1):216. doi:10.1186/s12967-022-03407-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Davies NM, Holmes MV, Smith GD. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601. doi:10.1136/bmj.k601

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Burgess S, Malarstig A. Using Mendelian randomization to assess and develop clinical interventions: limitations and benefits. J Comp Eff Res. 2013;2(3):209212. doi:10.2217/cer.13.14

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Damiot A, Pinto AJ, Turner JE, Gualano B. Immunological implications of physical inactivity among older adults during the COVID-19 pandemic. Gerontology. 2020;66(5):431438. doi:10.1159/000509216

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26.

    Dunstan DW, Salmon J, Owen N, et al. Physical activity and television viewing in relation to risk of undiagnosed abnormal glucose metabolism in adults. Diabetes Care. 2004;27(11):26032609. doi:10.2337/diacare.27.11.2603

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Chang PC, Li TC, Wu MT, et al. Association between television viewing and the risk of metabolic syndrome in a community-based population. BMC Public Health. 2008;8(1):193. doi:10.1186/1471-2458-8-193

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Holtermann A, Krause N, van der Beek AJ, Straker L. The physical activity paradox: six reasons why occupational physical activity (OPA) does not confer the cardiovascular health benefits that leisure time physical activity does. Br J Sports Med. 2018;52(3):149150. doi:10.1136/bjsports-2017-097965

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Gupta N, Dencker-Larsen S, Lund Rasmussen C, et al. The physical activity paradox revisited: a prospective study on compositional accelerometer data and long-term sickness absence. Int J Behav Nutr Phys Act. 2020;17(1):93. doi:10.1186/s12966-020-00988-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Holtermann A, Schnohr P, Nordestgaard BG, Marott JL. The physical activity paradox in cardiovascular disease and all-cause mortality: the contemporary Copenhagen General Population Study with 104 046 adults. Eur Heart J. 2021;42(15):14991511. doi:10.1093/eurheartj/ehab087

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Depp CA, Schkade DA, Thompson WK, Jeste DV. Age, affective experience, and television use. Am J Prev Med. 2010;39(2):173178. doi:10.1016/j.amepre.2010.03.020

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Aghababian AH, Sadler JR, Jansen E, Thapaliya G, Smith KR, Carnell S. Binge watching during COVID-19: associations with stress and body weight. Nutrients. 2021;13(10):3418. doi:10.3390/nu13103418

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Werneck AO, Silva DR, Malta DC, et al. Physical inactivity and elevated TV-viewing reported changes during the COVID-19 pandemic are associated with mental health: a survey with 43,995 Brazilian adults. J Psychosom Res. 2021;140:110292. doi:10.1016/j.jpsychores.2020.110292

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Batty GD, Gale CR, Kivimäki M, Deary IJ, Bell S. Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis. BMJ. 2020;368:m131. doi:10.1136/bmj.m131

    • Crossref
    • Search Google Scholar
    • Export Citation
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