The Combined Effects of Television Viewing and Physical Activity on Cardiometabolic Risk Factors: The Kardiovize Study

. 2022 Jan 22 ; 11 (3) : . [epub] 20220122

Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid35159997

Grantová podpora
02.1.01/0.0/0.0/16_019/0000868 European Regional Development Fund - Project ENOCH

The aim of the present study was to evaluate the association between television viewing/physical activity (TVV/PA) interactions and cardiometabolic risk in an adult European population. A total of 2155 subjects (25-64 years) (45.2% males), a random population-based sample were evaluated in Brno, Czechia. TVV was classified as low (<2 h/day), moderate (2-4), and high (≥4). PA was classified as insufficient, moderate, and high. To assess the independent association of TVV/PA categories with cardiometabolic variables, multiple linear regression was used. After adjustments, significant associations were: High TVV/insufficient PA with body mass index (BMI) (β = 2.61, SE = 0.63), waist circumference (WC) (β = 7.52, SE = 1.58), body fat percent (%BF) (β = 6.24, SE = 1.02), glucose (β = 0.25, SE = 0.12), triglycerides (β = 0.18, SE = 0.05), and high density lipoprotein (HDL-c) (β = -0.10, SE = 0.04); high TVV/moderate PA with BMI (β = 1.98, SE = 0.45), WC (β = 5.43, SE = 1.12), %BF (β = 5.15, SE = 0.72), triglycerides (β = 0.08, SE = 0.04), total cholesterol (β = 0.21, SE = 0.10), low density protein (LDL-c) (β = 0.19, SE = 0.08), and HDL-c (β = -0.07, SE = 0.03); and moderate TVV/insufficient PA with WC (β = 2.68, SE = 1.25), %BF (β = 3.80, SE = 0.81), LDL-c (β = 0.18, SE = 0.09), and HDL-c (β = -0.07, SE = 0.03). Independent of PA levels, a higher TVV was associated with higher amounts of adipose tissue. Higher blood glucose and triglycerides were present in subjects with high TVV and insufficient PA, but not in those with high PA alone. These results affirm the independent cardiometabolic risk of sedentary routines even in subjects with high-levels of PA.

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Tremblay M.S., Aubert S., Barnes J.D., Saunders T.J., Carson V., Latimer-Cheung A.E., Chastin S.F., Altenburg T.M., Chinapaw M.J. Sedentary Behavior Research Network (SBRN)—Terminology Consensus Project process and outcome. Int. J. Behav. Nutr. Phys. Act. 2017;14:75. doi: 10.1186/s12966-017-0525-8. PubMed DOI PMC

López-Valenciano A., Mayo X., Liguori G., Copeland R.J., Lamb M., Jimenez A. Changes in sedentary behaviour in European Union adults between 2002 and 2017. BMC Public Health. 2020;20:1206. doi: 10.1186/s12889-020-09293-1. PubMed DOI PMC

Jochem C., Schmid D., Leitzmann M.F. Introduction to Sedentary Behaviour Epidemiology. In: Leitzmann M.F., Jochem C., Schmid D., editors. Sedentary Behaviour Epidemiology. Springer International Publishing; Cham, Switzerland: 2018. pp. 3–29.

Andrade-Gómez E., García-Esquinas E., Ortolá R., Martínez-Gómez D., Rodríguez-Artalejo F. Watching TV has a distinct sociodemographic and lifestyle profile compared with other sedentary behaviors: A nationwide population-based study. PLoS ONE. 2017;12:e0188836. doi: 10.1371/journal.pone.0188836. PubMed DOI PMC

Grøntved A., Hu F.B. Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: A meta-analysis. JAMA. 2011;305:2448–2455. doi: 10.1001/jama.2011.812. PubMed DOI PMC

Wansink B. From mindless eating to mindlessly eating better. Physiol. Behav. 2010;100:454–463. doi: 10.1016/j.physbeh.2010.05.003. PubMed DOI

Hamrik Z., Sigmundova D., Kalman M., Pavelka J., Sigmund E. Physical activity and sedentary behaviour in Czech adults: Results from the GPAQ study. Eur. J. Sport Sci. 2014;14:193–198. doi: 10.1080/17461391.2013.822565. PubMed DOI PMC

Pavlovska I., Polcrova A., Mechanick J.I., Brož J., Infante-Garcia M.M., Nieto-Martínez R., Maranhao Neto G.A., Kunzova S., Skladana M., Novotny J.S., et al. Dysglycemia and Abnormal Adiposity Drivers of Cardiometabolic-Based Chronic Disease in the Czech Population: Biological, Behavioral, and Cultural/Social Determinants of Health. Nutrients. 2021;13:2338. doi: 10.3390/nu13072338. PubMed DOI PMC

Directorate-General for Education, Youth, Sport and Culture, European Commission . Sport and Physical Activity Report. Publications Office of the European Union; Luxembourg: 2018.

Junová I. Contemporary Family Lifestyles in Central and Western Europe: Selected Cases. Springer International Publishing; Cham, Switzerland: 2020. Leisure Time in Family Life; pp. 65–86.

Stašová L. Contemporary Family Lifestyles in Central and Western Europe: Selected Cases. Springer International Publishing; Cham, Switzerland: 2020. Media in the Lives of Contemporary Families; pp. 87–109.

Hallal P.C., Andersen L.B., Bull F.C., Guthold R., Haskell W., Ekelund U. Global physical activity levels: Surveillance progress, pitfalls, and prospects. Lancet. 2012;380:247–257. doi: 10.1016/S0140-6736(12)60646-1. PubMed DOI

Suminski R.R., Patterson F., Perkett M., Heinrich K.M., Carlos Poston W.S. The association between television viewing time and percent body fat in adults varies as a function of physical activity and sex. BMC Public Health. 2019;19:736. doi: 10.1186/s12889-019-7107-4. PubMed DOI PMC

Movsisyan N.K., Vinciguerra M., Lopez-Jimenez F., Kunzová Š., Homolka M., Jaresova J., Cífková R., Sochor O. Kardiovize Brno 2030, a prospective cardiovascular health study in Central Europe: Methods, baseline findings and future directions. Eur. J. Prev. Cardiol. 2018;25:54–64. doi: 10.1177/2047487317726623. PubMed DOI

Ling C.H., de Craen A.J., Slagboom P.E., Gunn D.A., Stokkel M.P., Westendorp R.G., Maier A.B. Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Clin. Nutr. 2011;30:610–615. doi: 10.1016/j.clnu.2011.04.001. PubMed DOI

Hui D., Dev R., Pimental L., Park M., Cerana M.A., Liu D., Bruera E. Association between Multi-frequency Phase Angle and Survival in Patients with Advanced Cancer. J. Pain Symptom Manag. 2017;53:571–577. doi: 10.1016/j.jpainsymman.2016.09.016. PubMed DOI PMC

McLester C.N., Nickerson B.S., Kliszczewicz B.M., McLester J.R. Reliability and Agreement of Various InBody Body Composition Analyzers as Compared to Dual-Energy X-Ray Absorptiometry in Healthy Men and Women. J. Clin. Densitom. 2020;23:443–450. doi: 10.1016/j.jocd.2018.10.008. PubMed DOI

Khan S., Xanthakos S.A., Hornung L., Arce-Clachar C., Siegel R., Kalkwarf H.J. Relative Accuracy of Bioelectrical Impedance Analysis for Assessing Body Composition in Children with Severe Obesity. J. Pediatr. Gastroenterol. Nutr. 2020;70:e129–e135. doi: 10.1097/MPG.0000000000002666. PubMed DOI PMC

Yodoshi T., Orkin S., Romantic E., Hitchcock K., Clachar A.C.A., Bramlage K., Sun Q., Fei L., Trout A.T., Xanthakos S.A., et al. Impedance-based measures of muscle mass can be used to predict severity of hepatic steatosis in pediatric nonalcoholic fatty liver disease. Nutrition. 2021;91–92:111447. doi: 10.1016/j.nut.2021.111447. PubMed DOI PMC

Campos-Perez W., Perez-Robles M., Rodriguez-Echevarria R., Rivera-Valdés J.J., Rodríguez-Navarro F.M., Rivera-Leon E.A., Martinez-Lopez E. High dietary ω-6:ω-3 PUFA ratio and simple carbohydrates as a potential risk factors for gallstone disease: A cross-sectional study. Clin. Res. Hepatol. Gastroenterol. 2021:101802. doi: 10.1016/j.clinre.2021.101802. in press . PubMed DOI

Clark B.K., Sugiyama T., Healy G.N., Salmon J., Dunstan D.W., Shaw J.E., Zimmet P.Z., Owen N. Socio-demographic correlates of prolonged television viewing time in Australian men and women: The AusDiab study. J. Phys. Act. Health. 2010;7:595–601. doi: 10.1123/jpah.7.5.595. PubMed DOI

Dunstan D.W., Salmon J., Healy G.N., Shaw J.E., Jolley D., Zimmet P.Z., Owen N. AusDiab Steering Committee. Association of television viewing with fasting and 2-h postchallenge plasma glucose levels in adults without diagnosed diabetes. Diabetes Care. 2007;30:516–522. doi: 10.2337/dc06-1996. PubMed DOI

Eisenmann J.C., Bartee R.T., Smith D.T., Welk G.J., Fu Q. Combined influence of physical activity and television viewing on the risk of overweight in US youth. Int. J. Obes. 2008;32:613–618. doi: 10.1038/sj.ijo.0803800. PubMed DOI

Lemes I.R., Sui X., Fernandes R.A., Blair S.N., Turi-Lynch B.C., Codogno J.S., Monteiro H.L. Association of sedentary behavior and metabolic syndrome. Public Health. 2019;167:96–102. doi: 10.1016/j.puhe.2018.11.007. PubMed DOI

Dunstan D.W., Salmon J., Owen N., Armstrong T., Zimmet P.Z., Welborn T.A., Cameron A.J., Dwyer T., Jolley D., Shaw J.E. Associations of TV viewing and physical activity with the metabolic syndrome in Australian adults. Diabetologia. 2005;48:2254–2261. doi: 10.1007/s00125-005-1963-4. PubMed DOI

Mechanick J.I., Hurley D.L., Garvey W.T. Adiposity-Based Chronic Disease as a New Diagnostic Term: The American Association of Clinical Endocrinologists and American College of Endocrinology Position Statement. Endocr. Pract. 2017;23:372–378. doi: 10.4158/EP161688.PS. PubMed DOI

Mechanick J.I., Farkouh M.E., Newman J.D., Garvey W.T. Cardiometabolic-Based Chronic Disease, Addressing Knowledge and Clinical Practice Gaps: JACC State-of-the-Art Review. J. Am. Coll. Cardiol. 2020;75:539–555. doi: 10.1016/j.jacc.2019.11.046. PubMed DOI PMC

Sperling L.S., Mechanick J.I., Neeland I.J., Herrick C.J., Després J.P., Ndumele C.E., Vijayaraghavan K., Handelsman Y., Puckrein G.A., Araneta M.R.G., et al. The CardioMetabolic Health Alliance: Working Toward a New Care Model for the Metabolic Syndrome. J. Am. Coll. Cardiol. 2015;66:1050–1067. doi: 10.1016/j.jacc.2015.06.1328. PubMed DOI

Ekelund U., Steene-Johannessen J., Brown W.J., Fagerland M.W., Owen N., Powell K.E., Bauman A., Lee I.M., Series L.P.A. Lancet Sedentary Behaviour Working Group. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388:1302–1310. doi: 10.1016/S0140-6736(16)30370-1. PubMed DOI

Benatti F.B., Ried-Larsen M. The Effects of Breaking up Prolonged Sitting Time: A Review of Experimental Studies. Med. Sci. Sports Exerc. 2015;47:2053–2061. doi: 10.1249/MSS.0000000000000654. PubMed DOI

Frydenlund G., Jorgensen T., Toft U., Pisinger C., Aadahl M. Sedentary leisure time behavior, snacking habits and cardiovascular biomarkers: The Inter99 Study. Eur. J. Prev. Cardiol. 2012;19:1111–1119. doi: 10.1177/1741826711419999. PubMed DOI

Vos T., Lim S.S., Abbafati C., Abbas K.M., Abbasi M., Abbasifard M., Abbasi-Kangevari M., Abbastabar H., Abd-Allah F., Abdelalim A., et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2019;396:1204–1222. doi: 10.1016/S0140-6736(20)30925-9. PubMed DOI PMC

Lavie C.J., Ozemek C., Carbone S., Katzmarzyk P.T., Blair S.N. Sedentary Behavior, Exercise, and Cardiovascular Health. Circ. Res. 2019;124:799–815. doi: 10.1161/CIRCRESAHA.118.312669. PubMed DOI

Pinto Pereira S.M., Ki M., Power C. Sedentary behaviour and biomarkers for cardiovascular disease and diabetes in mid-life: The role of television-viewing and sitting at work. PLoS ONE. 2012;7:e31132. doi: 10.1371/journal.pone.0031132. PubMed DOI PMC

O’donoghue G., Perchoux C., Mensah K., Lakerveld J., Van Der Ploeg H., Bernaards C., Chastin S.F., Simon C., O’gorman D., Nazare J.A. A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: A socio-ecological approach. BMC Public Health. 2016;16:163. doi: 10.1186/s12889-016-2841-3. PubMed DOI PMC

Ofcom Media Nations 2020. [(accessed on 17 May 2021)]. Available online: https://www.ofcom.org.uk/research-and-data/tv-radio-and-on-demand/media-nations-reports/media-nations-2020.

Mechanick J.I., Rosenson R.S., Pinney S.P., Mancini D.M., Narula J., Fuster V. Coronavirus and Cardiometabolic Syndrome: JACC Focus Seminar. J. Am. Coll. Cardiol. 2020;76:2024–2035. doi: 10.1016/j.jacc.2020.07.069. PubMed DOI PMC

Movsisyan N.K., Sochor O., Kralikova E., Cifkova R., Ross H., Lopez-Jimenez F. Current and past smoking patterns in a Central European urban population: A cross-sectional study in a high-burden country. BMC Public Health. 2016;16:571. doi: 10.1186/s12889-016-3216-5. PubMed DOI PMC

City Population: Population Statistics for Countries. [(accessed on 30 November 2021)]. Available online: http://www.citypopulation.de/CzechRep-Cities.html.

Belohlavek R., Sigmund E., Zacpal J. Evaluation of IPAQ questionnaires supported by formal concept analysis. Inf. Sci. 2011;181:1774–1786. doi: 10.1016/j.ins.2010.04.011. DOI

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