Increased cardiometabolic risk is associated with increased TV viewing time.
OBJECTIVE
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.
Wijndaele
Katrien
K
Cancer Prevention Research Centre, School of Population Health, University of Queensland, Herston, Queensland, Australia.
Healy
Genevieve N
GN
Dunstan
David W
DW
Barnett
Adrian G
AG
Salmon
Jo
J
Shaw
Jonathan E
JE
Zimmet
Paul Z
PZ
Owen
Neville
N
D000328:Adult; D001315:Australia; D015415:Biomarkers; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D008076:Cholesterol, HDL / Q000097:blood; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005215:Fasting / Q000502:physiology; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000453:epidemiology*; D008875:Middle Aged; D011446:Prospective Studies; D012306:Risk; D057185:Sedentary Behavior; D013690:Television; D014280:Triglycerides / Q000097:blood; D055105:Waist Circumference
D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL; D014280:Triglycerides