Causes of Death Associated With Prolonged TV Viewing

NIH-AARP Diet and Health Study

      Introduction

      TV viewing is the most prevalent sedentary behavior and is associated with increased risk of cardiovascular disease and cancer mortality, but the association with other leading causes of death is unknown. This study examined the association between TV viewing and leading causes of death in the U.S.

      Methods

      A prospective cohort of 221,426 individuals (57% male) aged 50–71 years who were free of chronic disease at baseline (1995–1996), 93% white, with an average BMI of 26.7 (SD=4.4) kg/m2 were included. Participants self-reported TV viewing at baseline and were followed until death or December 31, 2011. Hazard ratios (HRs) and 95% CIs for TV viewing and cause-specific mortality were estimated using Cox proportional hazards regression. Analyses were conducted in 2014–2015.

      Results

      After an average follow-up of 14.1 years, adjusted mortality risk for a 2-hour/day increase in TV viewing was significantly higher for the following causes of death (HR [95% CI]): cancer (1.07 [1.03, 1.11]); heart disease (1.23 [1.17, 1.29]); chronic obstructive pulmonary disease (1.28 [1.14, 1.43]); diabetes (1.56 [1.33, 1.83]); influenza/pneumonia (1.24 [1.02, 1.50]); Parkinson disease (1.35 [1.11, 1.65]); liver disease (1.33 [1.05, 1.67]); and suicide (1.43 [1.10, 1.85]. Mortality associations persisted in stratified analyses with important potential confounders, reducing causation concerns.

      Conclusions

      This study shows the breadth of mortality outcomes associated with prolonged TV viewing, and identifies novel associations for several leading causes of death. TV viewing is a prevalent discretionary behavior that may be a more important target for public health intervention than previously recognized.

      Trial Registration

      ClinicalTrials.gov number, NCT00340015

      Introduction

      TV viewing is the most prevalent leisure-time behavior in the U.S. and an estimated 289 million Americans (92%) have a TV at home. On a given day, 80% of American adults watch TV for an average of 3.5 hours per day, which is more than half (55%) of their available leisure time.

      Bureau of Labor Statistics. American time use survey. 2012. www.bls.gov/tus/tables/a1_2013.pdf. Accessed June 8, 2015.

      In the past 10 years, a growing body of evidence has linked prolonged TV viewing to poor health. A 2011 meta-analysis showed that each 2-hour increase in TV viewing was associated with a 13% increased risk of all-cause mortality.
      • Grontved A.
      • Hu F.B.
      Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis.
      To date, TV viewing and mortality studies have focused on the two leading causes of death, cardiovascular disease (CVD) and cancer, which account for only half of all deaths in the U.S.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      TV viewing has consistently been linked with increased risk of CVD mortality,
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      • Dunstan D.W.
      • Barr E.L.
      • Healy G.N.
      • et al.
      Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
      • Seguin R.
      • Buchner D.M.
      • Liu J.
      • et al.
      Sedentary behavior and mortality in older women: the Women’s Health Initiative.
      • Warren T.Y.
      • Barry V.
      • Hooker S.P.
      • Sui X.
      • Church T.S.
      • Blair S.N.
      Sedentary behaviors increase risk of cardiovascular disease mortality in men.
      even among individuals exceeding current recommendations for moderate to vigorous physical activity (MVPA).
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      Associations with cancer mortality have been less consistent.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      • Dunstan D.W.
      • Barr E.L.
      • Healy G.N.
      • et al.
      Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
      • Seguin R.
      • Buchner D.M.
      • Liu J.
      • et al.
      Sedentary behavior and mortality in older women: the Women’s Health Initiative.
      Whether TV viewing is associated with causes of death other than CVD and cancer is not yet established. The displacement of physical activity by prolonged TV viewing has been hypothesized to explain the positive association between TV and diabetes and cardiometabolic biomarkers.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing and incident cardiovascular disease: prospective associations and mediation analysis in the EPIC Norfolk Study.
      • Dunstan D.W.
      • Salmon J.
      • Healy G.N.
      • et al.
      Association of television viewing with fasting and 2-h postchallenge plasma glucose levels in adults without diagnosed diabetes.
      • Smith L.
      • Hamer M.
      Television viewing time and risk of incident diabetes mellitus: the English Longitudinal Study of Ageing.
      TV viewing has also been prospectively associated with poor mental health
      • Hamer M.
      • Poole L.
      • Messerli-Burgy N.
      Television viewing, C-reactive protein, and depressive symptoms in older adults.
      and depression.
      • Lucas M.
      • Mekary R.
      • Pan A.
      • et al.
      Relation between clinical depression risk and physical activity and time spent watching television in older women: a 10-year prospective follow-up study.
      • Mekary R.A.
      • Lucas M.
      • Pan A.
      • et al.
      Isotemporal substitution analysis for physical activity, television watching, and risk of depression.
      Quite plausibly, TV viewing may be linked to other leading causes of death, though this has not, to the authors’ knowledge, been examined.
      The present study examined the association between TV viewing and the leading causes of death in the U.S. A better understanding of the causes of death associated with prolonged TV viewing may suggest new hypotheses related to the deleterious health effects of sedentary behavior and may help inform future public health recommendations.

      Methods

      The NIH-AARP Health Study (ClinicalTrials.gov number, NCT00340015) has been described previously.
      • Schatzkin A.
      • Subar A.F.
      • Thompson F.E.
      • et al.
      Design and serendipity in establishing a large cohort with wide dietary intake distributions: the National Institutes of Health-American Association of Retired Persons Diet and Health Study.
      In 1995–1996, 3.5 million AARP members aged 50–71 years who lived in one of six states (California, Florida, Louisiana, New Jersey, North Carolina, and Pennsylvania) or two metropolitan areas (Atlanta, Georgia and Detroit, Michigan) were mailed a questionnaire asking about their medical history, diet, and demographic characteristics. Of the 566,401 participants who initially responded, those who did not report colon, breast, or prostate cancer were asked to complete a second questionnaire 6 months later that asked about TV viewing and other health behaviors. Completion of the questionnaires was considered to imply informed consent. The Special Studies IRB of the U.S. National Cancer Institute approved the study.
      Eligible participants were those who responded to both questionnaires, were alive, and had not moved from the study area before returning the second questionnaire (N=334,921). Those who indicated they were proxies for the intended respondents (n=10,383); a prior history of cancer (n=18,863), heart disease or stroke (n=45,752), or emphysema (n=5,709); missing or extreme BMI values (≤18.5 or ≥60 kg/m2; n=7,874); missing TV viewing or MVPA (n=4,103); or had extreme log-transformed energy intake values (n=1,844) were excluded. To further address reverse causation concerns those who reported “poor” or “fair” health (n=18,951) were eliminated, resulting in a final analytic cohort of 221,426.

      Measures

      TV viewing was assessed using a questionnaire that asked: During a typical 24-hour period over the past 12 months, how much time did you spend watching television or videos? Responses were categorized as 0–1, 1–2, 3–4, 5–6, and ≥7 hours/day. Validity of this question has not been evaluated, but it is similar to questions that have acceptable validity compared to behavioral logs (r =0.61)
      • Marshall A.L.
      • Miller Y.D.
      • Burton N.W.
      • Brown W.J.
      Measuring total and domain-specific sitting: a study of reliability and validity.
      and an electronic TV monitor (r =0.51).
      • Otten J.J.
      • Jones K.E.
      • Littenberg B.
      • Harvey-Berino J.
      Effects of television viewing reduction on energy intake and expenditure in overweight and obese adults: a randomized controlled trial.
      Follow-up of participants was completed via annual linkage to the U.S. Postal Service’s National Change of Address database, through processing undeliverable mail and using address change services and participant notifications. Vital status ascertainment was performed by annual linkage of the cohort to the Social Security Administration Death Master File. Verification of vital status and cause of death were obtained by searches of the National Death Index (NDI) Plus and was available for >95% of the cohort.
      The leading causes of death in the U.S. were categorized using the same classification approach employed by the National Center for Health Statistics for vital status reporting
      • Murphy S.L.
      • Xu J.Q.
      • Kochanek K.D.
      Deaths: final data for 2010.
      based on the causes of death provided by the NDI. The specific ICD-9 and ICD-10 codes used to classify each outcome are provided in Appendix Table 1 (available online): malignant neoplasms (cancer); diseases of the heart (CHD); chronic obstructive pulmonary disease and allied conditions (COPD); cerebrovascular disease (stroke); accidents and adverse effects (accidents); Alzheimer disease; diabetes mellitus (diabetes); nephritis, nephrotic syndrome, and nephrosis (kidney disease); influenza and pneumonia; intentional self-harm (suicide); septicemia (sepsis); chronic liver disease and cirrhosis (liver disease); essential hypertension and hypertensive renal disease (hypertension); and Parkinson disease.
      Numerous self-reported covariates were evaluated as potential confounders and are listed and defined in Table 1. Diet was assessed using a 124-item food frequency questionnaire,
      • Thompson F.E.
      • Kipnis V.
      • Midthune D.
      • et al.
      Performance of a food-frequency questionnaire in the U.S. NIH-AARP (National Institutes of Health-American Association of Retired Persons) Diet and Health Study.
      and the Healthy Eating Index 2005 (HEI-2005) was used as a measure of overall diet quality.
      • Guenther P.M.
      • Reedy J.
      • Krebs-Smith S.M.
      Development of the Healthy Eating Index-2005.
      Table 1Baseline Participant Characteristics According to TV Viewing Category, Among 221,426 Participants at Baseline: NIH-AARP Diet and Health Study
      TV viewing
      <1 h/d1-2h/dcategory 3-4h/d5-6h/d≥7 h/d
      N16,79867,65797,25530,7918,925
      Age (years)60.8 ± 5.461.9 ± 5.462.8 ± 5.363.5 ± 5.163.2 ± 5.2
      BMI (kg/m2)25.3 ± 4.026.2 ± 4.126.9 ± 4.427.6 ± 4.828.2 ± 5.3
      Female (%)4741424652
      White (%)9594939288
      Black (%)12357
      Some college or college graduate (%)8475645547
      Married or living as married (%)6671706558
      Obesity, BMI >30 (%)1115202530
      Current smoker (%)68111418
      Dietary intake
       Calories (kcal/day)1739.8 ± 7021779 ± 7371820 ± 7611875 ± 8171931 ± 900
       Alcohol intake (g/day)11.0 ± 24.212.3 ± 28.512.8 ± 30.613.3 ± 34.213.6 ± 38.9
       HEI-2005 total score69.7 ± 10.468.3 ± 10.866.9 ± 11.265.3 ± 11.764.1 ± 12.2
      Physical activity and sleep (%)
       MVPA>7h/wk3032272624
       Sleep<7 h/day3032333641
      Health status at baseline (%)
       Excellent3827201614
       Hypertension2531353942
       High cholesterol5651474443
       Diabetes34689
       Bone fracture after 45 y66677
       Osteoporosis33334
      d, day; g, gram; kcal, kilocalorie; kg, kilogram; h, hours; HEI-2005, Healthy Eating Index 2005; MVPA, moderate to vigorous physical activity; wk, week; y, years.

      Statistical Analysis

      Covariates that changed the magnitude of associations by at least 10% with all-cause mortality were retained in the fully adjusted models.
      Model 1 adjusted for age (years), sex (male or female), race (white, black, other, or missing), education (<12 years, high school graduate, some college, college graduate, or missing), smoking history (never; quit, ≤20 cigarettes/day; quit, >20 cigarettes/day; current, ≤20 cigarettes/day; current, >20 cigarettes/day; or missing), and diet quality (HEI-2005 score quintiles) and MVPA (never or rarely, 1, 1–3, 4–7, or ≥7 hours/week).
      Model 2 included covariates from Model 1 plus two variables that may could be considered confounders or potential causal intermediaries between TV viewing and morality: BMI (18.5 to <25, 25 to <30, 30–35, or >35 kg/m2) and self-reported health status (good, very good, or excellent).
      For each of the mortality outcomes, Cox proportional hazards regression was used to obtain the adjusted hazard ratios (HRs) and 95% CIs for each of the five categories of TV viewing using the lowest category as the referent. Given the higher proportion of the population in the 1–2 hour/day category, a sensitivity analysis was conducted with that group as the referent. To test for linear trend, the categorical responses were translated to hours/day using the midpoints of the duration interval indicated for each response option. These values were then divided by two and this version of the response was used as a continuous variable in the models. The regression coefficients were then in units that are interpreted as a 2-hour/day increase in risk. The underlying time variable was calculated from the scan date on the second questionnaire until death from any cause or the end of the follow-up on December 31, 2011. The proportional hazards assumption was tested by examining the interaction between follow-up time and TV viewing.
      Additional analyses examined effect modification of TV viewing by strata of sex, age quartiles, BMI, education, MVPA, diet quality, smoking, marital status, diabetes, hypertension, cholesterol, and health status for the 11 other causes of death (excluding CVD and cancer). To assess whether the associations for TV and mortality persisted in physically active individuals, multiplicative interactions for MVPA (active ≥4 hours/week and inactive <4 hours/week) and TV viewing (low, <2 hours/day; medium, 3–4 hours/day, and high, >5 hours/day) and joint effects by setting a common referent group (i.e., low TV and active) were performed. Statistical significance of the interactions for subgroups and activity status was assessed using likelihood ratio tests comparing Cox proportional hazards models with and without cross-product terms for each level of the baseline stratifying variable, with TV viewing as a continuous variable. Sensitivity analyses were completed excluding deaths in the first 3 years of follow-up and among never smokers. SAS, version 9.3, was used for all analyses and statistical significance was set at p<0.05. Analyses were conducted in 2014–2015.

      Results

      At baseline, those who watched more TV were less likely to have attended college, sleep at least 7 hours/night, or have high cholesterol. Higher TV viewers tended to consume more calories and alcohol, were more likely to be obese (BMI >30 kg/m2), smokers, and have diabetes or hypertension (Table 1). The Spearman correlation between TV viewing (hours/day) and MVPA (hours/week) was 0.06. During a mean of 14.1 (SD=2.2) years of follow-up, there were 36,590 deaths (Table 2). All-cause mortality risk was increased by 14% per 2-hour/day increase in TV viewing (p<0.001). The average age of death for <1 hour/day (73.9 [SD=6.4] years) was similar to the >7 hours/day category (74.8 [SD=6.0] years). There was a modest violation of the proportional hazards assumption, indicating a difference in the association between TV viewing and all-cause mortality at different follow-up times, although risk was significantly elevated at both time points (p<0.001). The deviation occurred at 6 years of follow-up, with risk estimates (HR [95% CI]) <6 years of 1.21 (1.16, 1.28) and 6 years of 1.12 (1.09, 1.15). Additional information can be found in the Appendix (available online).
      Table 2Association of TV Viewing and Cause-Specific Mortality: NIH-AARP Diet and Health Study
      Television viewing
      <11–2(h/day) 3–45–6>7p-value for trend
      All participants (N)17,03568,28197,99331,0038,990
      All causesNo. of deaths36,5901,8519,36816,7226,4522,197
      Model 1ref1.06 (1.00, 1.11)1.15 (1.09, 1.20)1.25 (1.19, 1.32)1.47 (1.38, 1.56)<0.001
      Model 2ref1.02 (0.97, 1.07)1.08 (1.03, 1.14)1.15 (1.09, 1.21)1.33 (1.25, 1.41)<0.001
      CancerNo. of deaths15,161854402669332555793
      Model 1ref1.00 (0.93, 1.07)1.05 (0.98, 1.13)1.10 (1.02, 1.19)1.17 (1.06, 1.29)<0.001
      Model 2ref0.98 (0.91, 1.06)1.03 (0.96, 1.10)1.06 (0.98, 1.15)1.12 (1.02, 1.24)<0.01
      CHDNo. of deaths7,340319180533741328514
      Model 1ref1.17 (1.04, 1.32)1.33 (1.19, 1.50)1.50 (1.32, 1.69)2.02 (1.75, 2.33)<0.001
      Model 2ref1.09 (0.97, 1.23)1.19 (1.06, 1.33)1.26 (1.11, 1.43)1.64 (1.42, 1.90)<0.001
      StrokeNo. of deaths1,74810046179231085
      Model 1ref0.97 (0.78, 1.20)1.01 (0.81, 1.24)1.10 (0.87, 1.38)1.04 (0.78, 1.40)0.19
      Model 2ref0.94 (0.76, 1.17)0.96 (0.78, 1.19)1.03 (0.82, 1.30)0.97 (0.72, 1.30)0.54
      COPDNo. of deaths1,52249304706341122
      Model 1ref1.13 (0.84, 1.53)1.35 (1.01, 1.81)1.55 (1.15, 2.10)1.72 (1.23, 2.41)<0.001
      Model 2ref1.08 (0.80, 1.46)1.26 (0.94, 1.68)1.42 (1.05, 1.92)1.54 (1.10, 2.16)<0.001
      AccidentsNo. of deaths9196127639015240
      Model 1ref0.97 (0.74, 1.28)0.87 (0.66, 1.15)1.02 (0.75, 1.38)0.98 (0.65, 1.47)0.95
      Model 2ref0.97 (0.71, 1.31)0.97 (0.70, 1.36)1.12 (0.75, 1.67)1.01 (0.62, 1.64)0.62
      Alzheimer diseaseNo. of deaths7963623535413635
      Model 1ref1.36 (0.96, 1.94)1.27 (0.90, 1.80)1.43 (0.99, 2.08)1.39 (0.87, 2.23)0.27
      Model 2ref1.37 (0.97, 1.95)1.29 (0.91, 1.83)1.48 (1.01, 2.15)1.46 (0.91, 2.34)0.17
      DiabetesNo. of deaths7673013836516470
      Model 1ref0.98 (0.66, 1.45)1.59 (1.09, 2.32)2.05 (1.38, 3.04)2.95 (1.91, 4.57)<0.001
      Model 2ref0.84 (0.57, 1.25)1.24 (0.85, 1.80)1.41 (0.95, 2.10)1.93 (1.24, 2.98)<0.001
      Influenza/ pneumoniaNo. of deaths550221492449243
      Model 1ref1.36 (0.87, 2.12)1.33 (0.86, 2.06)1.42 (0.89, 2.28)2.41 (1.43, 4.06)0.01
      Model 2ref1.30 (0.83, 2.04)1.25 (0.80, 1.94)1.30 (0.81, 2.10)2.18 (1.29, 3.69)0.03
      Parkinson diseaseNo. of deaths513291252527928
      Model 1ref0.91 (0.60, 1.36)1.19 (0.81, 1.76)1.17 (0.76, 1.80)1.70 (1.00, 2.88)0.01
      Model 2ref0.92 (0.61, 1.38)1.22 (0.83, 1.81)1.21 (0.78, 1.87)1.77 (1.04, 3.02)0.00
      Kidney diseaseNo. of deaths42922872107634
      Model 1ref0.78 (0.49, 1.25)1.08 (0.69, 1.68)1.04 (0.64, 1.69)1.54 (0.89, 2.66)0.01
      Model 2ref0.72 (0.45, 1.15)0.94 (0.60, 1.47)0.85 (0.52, 1.38)1.22 (0.70, 2.11)0.13
      SepsisNo. of deaths39513861986830
      Model 1ref1.33 (0.74, 2.38)1.76 (1.00, 3.11)1.64 (0.90, 3.00)2.40 (1.24, 4.66)<0.01
      Model 2ref1.23 (0.68, 2.20)1.53 (0.87, 2.70)1.32 (0.72, 2.42)1.85 (0.95, 3.59)0.09
      Liver diseaseNo. of deaths37419921597529
      Model 1ref1.04 (0.63, 1.70)1.12 (0.69, 1.81)1.52 (0.91, 2.54)2.04 (1.13, 3.67)<0.01
      Model 2ref0.96 (0.59, 1.58)0.99 (0.61, 1.60)1.27 (0.76, 2.13)1.65 (0.91, 2.99)0.02
      SuicideNo. of deaths29214701405513
      Model 1ref1.07 (0.60, 1.91)1.40 (0.80, 2.44)1.70 (0.93, 3.09)1.48 (0.69, 3.18)0.01
      Model 2ref1.10 (0.62, 1.96)1.46 (0.83, 2.55)1.79 (0.98, 3.27)1.55 (0.72, 3.36)0.01
      HypertensionNo. of deaths26712631215615
      Model 1ref1.13 (0.61, 2.09)1.31 (0.72, 2.39)1.67 (0.89, 3.16)1.52 (0.70, 3.29)0.03
      Model 2ref1.04 (0.56, 1.93)1.14 (0.62, 2.08)1.38 (0.73, 2.62)1.22 (0.56, 2.65)0.18
      Note: Values are Hazard Ratio (95% CI). p-value for trend was determined by entering the mid-point of each category and model as a continuous variable.
      Model 1 was adjusted for age (years), sex, race (white, black, other, missing), education (<12 years, high school graduate, some college, college graduate, missing), smoking history (never; quit, ≤20 cigarettes/day; quit, >20 cigarettes/day; current, ≤20 cigarettes/day; current, >20 cigarettes/day; unknown), MVPA (never or rarely, 1, 1–3, 4–7, ≥7 h/wk) and diet quality (quintiles).
      Model 2 was adjusted for the above plus BMI categories (18.5 to <25, 25 to <30, 30–35 and >35 kg/m2) and health status (good, very good, excellent).
      CHD, coronary heart disease; COPD, chronic obstructive pulmonary disease; h, hours; MVPA, moderate to vigorous physical activity.
      When examined on a continuous basis, each 2-hour/day increase in TV viewing was significantly associated with an increased risk of mortality for eight causes of death after adjusting for covariates in Model 2 (HR [95% CI]): cancer (1.07 [1.03, 1.11]); CHD (1.23 [1.17, 1.29]); COPD (1.28 [1.14, 1.43]); diabetes (1.56 [1.33, 1.83]); influenza/pneumonia (1.24 [1.02, 1.50]); Parkinson disease 1.35 [1.11, 1.65]); liver disease (1.33 [1.05, 1.67]); and suicide (1.43 [1.10, 1.85]) (Figure 1). Results for five causes of death were nonsignificant: sepsis (1.22 [0.97, 1.52]); kidney disease (1.18 [0.95, 1.47]); hypertension (1.21 [0.92, 1.59]); Alzheimer disease (1.12 [0.95, 1.31]); accidents (0.96 [0.83, 1.12]); and stroke (1.03 [0.93, 1.15]). There was no cause of death where TV viewing was protective. In the model without potential causal intermediaries (health status and BMI, Model 1), mortality risk was significantly increased for three additional causes of death (kidney, hypertension, and sepsis, Table 2), and the associations tended to be stronger. Influenza/pneumonia was the only cause of death where the mortality risk from TV viewing differed by sex (pint= 0.03), with stronger associations in women (Appendix Figure 1, available online). In the categorical analyses, elevation in risk was initially observed for most outcomes at 3–4 hours/day of TV viewing (Table 2), compared with those watching <1 hour/day. When the 1–2 hours/day category was set as referent, the results were similar, though the precision of the estimates was improved (Appendix Table 2, available online). Age- and sex-adjusted models are shown in Appendix Table 3 (available online).
      Figure thumbnail gr1
      Figure 1Association for a 2 hour/day increase in TV viewing and the leading causes of death in the U.S.: NIH-AARP Diet and Health Study.
      Note: Values are hazard ratios and 95% CIs, fully adjusted for covariates in Model 2. COPD, chronic obstructive pulmonary disease.
      To investigate potential confounding and reverse causation, stratified analyses were conducted for the combined mortality outcome for other causes of death (i.e., excluding CVD and cancer), which included 6,824 (18.5%) deaths. The positive association between TV viewing and the combined causes of death was consistent across relevant subgroups (Figure 2). There was no interaction between TV viewing and age, MVPA, education, diet quality, or marital, health, smoking, hypertension, or diabetes status. Risk estimates for TV viewing were higher in leaner individuals (p=0.03) and those without high cholesterol (p=0.01). Excluding the first 3 years of follow-up and limiting the sample to never smokers resulted in similar risk estimates (Appendix Table 4, available online).
      Figure thumbnail gr2
      Figure 2Associations for a 2 hour/day increase in TV viewing for other causes of death by baseline characteristics: NIH-AARP Diet and Health Study.
      Note: Values are hazard ratios and 95% CIs. Other causes of death included deaths due to chronic obstructive pulmonary disease, diabetes, sepsis, hypertension, pneumonia and influenza, liver disease, kidney disease, suicide, accidents, Alzheimer disease, and Parkinson disease. Models were fully adjusted for covariates in Model 2, unless they were the comparator of interest. Diet quality is based on the Healthy Eating Index-2005, “low” included bottom two quintiles and “high” included top two quintiles. MVPA, moderate to vigorous physical activity.
      There was no significant interaction between MVPA and TV viewing (all p>0.05), indicating the detrimental effects of TV viewing were similar in active and inactive individuals. The joint effects of TV viewing and MVPA are shown Figure 3 for nine causes of death where a significant main effect of TV viewing was found. For the four leading causes (cancer, CHD, diabetes, and COPD), the estimates in the active/high TV group were equivalent to the inactive/low TV group. For example, for CHD the active/high TV HR (95% CI) was 1.21 (1.11, 1.34) and inactive/low TV was 1.08 (0.99, 1.17) (Figure 3).
      Figure thumbnail gr3
      Figure 3Joint effects of MVPA and TV viewing on selected mortality outcomes: NIH-AARP Diet and Health Study.
      Note: Values are hazard ratios and 95% CIs. Moderate to vigorous physical activity (MVPA) was categorized as active (≥4h/wk) or inactive (<4h/wk). TV viewing was categorized as low (<2h/day), medium (3h–4h/day), or high (≥5h/day). High active and low TV were set as referent group. Models were fully adjusted for covariates in Model 2. h, hours; MVPA, moderate to vigorous physical activity.

      Discussion

      In this large prospective study of adults aged 50–71 years who were free of major chronic illness and reported good health, prolonged TV viewing was significantly associated with greater risk for eight of 14 leading causes of death in the U.S., including CHD, cancer, COPD, diabetes, influenza/pneumonia, Parkinson disease, liver disease, and suicide. There was evidence for a dose–response relationship for the majority of outcomes and the associations remained significant after adjustment for relevant confounders, including BMI, health status, and MVPA. Although the relations between TV viewing and CHD and cancer have been examined previously,
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      • Dunstan D.W.
      • Barr E.L.
      • Healy G.N.
      • et al.
      Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
      • Seguin R.
      • Buchner D.M.
      • Liu J.
      • et al.
      Sedentary behavior and mortality in older women: the Women’s Health Initiative.
      the finding of elevated risk for other leading causes of death are novel and demonstrate for the first time the breadth of mortality outcomes that may be linked to prolonged TV viewing. Results from this study suggest that interventions targeting reductions in TV viewing, a single health behavior, have the potential to efficiently leverage a variety of health benefits and yield clinical and public health impact that is more expansive than previously known.
      There are several plausible explanations for these results, and our central hypothesis is that physical inactivity resulting from prolonged TV viewing is a primary mechanism. On average, TV viewing consumes 55% of leisure time

      Bureau of Labor Statistics. American time use survey. 2012. www.bls.gov/tus/tables/a1_2013.pdf. Accessed June 8, 2015.

      and has been associated with lower levels of leisure-time and total physical activity
      • Sugiyama T.
      • Healy G.N.
      • Dunstan D.W.
      • Salmon J.
      • Owen N.
      Is television viewing time a marker of a broader pattern of sedentary behavior?.
      • Tucker L.A.
      • Tucker J.M.
      Television viewing and obesity in 300 women: evaluation of the pathways of energy intake and physical activity.
      and lower cardiorespiratory fitness,
      • Tucker L.A.
      Television viewing and physical fitness in adults.
      • Tucker L.A.
      • Arens P.J.
      • Lecheminant J.D.
      • Bailey B.W.
      Television viewing time and measured cardiorespiratory fitness in adult women.
      an important determinant of which is inactivity. Conversely, a randomized trial that reduced TV viewing by 50% among adults who watched for at least 3 hours/day resulted in an increase of physical activity of 100 kcal/day,
      • Otten J.J.
      • Jones K.E.
      • Littenberg B.
      • Harvey-Berino J.
      Effects of television viewing reduction on energy intake and expenditure in overweight and obese adults: a randomized controlled trial.
      which is roughly equivalent to a mile of walking. A growing body of research indicates that displacement of physical activity with sedentary behavior, including TV viewing, can have adverse effects on energy balance and metabolic health. Experimental studies have shown that prolonged sitting increases postprandial glucose and insulin levels.
      • Dunstan D.W.
      • Kingwell B.A.
      • Larsen R.
      • et al.
      Breaking up prolonged sitting reduces postprandial glucose and insulin responses.
      Observational studies indicate that prolonged TV viewing is associated with weight gain,
      • Mitchell J.A.
      • Bottai M.
      • Park Y.
      • Marshall S.J.
      • Moore S.C.
      • Matthews C.E.
      A prospective study of sedentary behavior and changes in the BMI distribution.
      poor metabolic health,
      • Grontved A.
      • Hu F.B.
      Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis.

      Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. Am J Prev Med. 2011;41(2):207-215. http://dx.doi.org/10.1016/j.amepre.2011.05.004

      and increased risk for developing diabetes.
      • Smith L.
      • Hamer M.
      Television viewing time and risk of incident diabetes mellitus: the English Longitudinal Study of Ageing.
      This is the first study to report the association between TV viewing and diabetes mortality. Mortality from liver disease,
      • Smith B.W.
      • Adams L.A.
      Nonalcoholic fatty liver disease and diabetes mellitus: pathogenesis and treatment.
      infection,
      • Bertoni A.G.
      • Saydah S.
      • Brancati F.L.
      Diabetes and the risk of infection-related mortality in the U.S.
      and COPD
      • Agusti A.
      • Calverley P.M.
      • Celli B.
      • et al.
      Characterisation of COPD heterogeneity in the ECLIPSE cohort.
      • Decramer M.
      • Janssens W.
      • Miravitlles M.
      Chronic obstructive pulmonary disease.
      • Seshasai S.R.
      • Kaptoge S.
      • Thompson A.
      • et al.
      Emerging Risk Factors Collaboration
      Diabetes mellitus, fasting glucose, and risk of cause-specific death.
      have also been linked to obesity and poor metabolic health, providing a plausible biological mechanism for these associations.
      By contrast, for some of the novel mortality outcomes the explanations are less clear and this study presents intriguing hypothesis-generating results that should stimulate future research. For example, TV viewing has been associated with a prothombotic/inflammatory state (i.e., interleukin 6, C-reactive protein, and endothelial function)
      • Hamer M.
      • Poole L.
      • Messerli-Burgy N.
      Television viewing, C-reactive protein, and depressive symptoms in older adults.
      • Allison M.A.
      • Jensky N.E.
      • Marshall S.J.
      • Bertoni A.G.
      • Cushman M.
      Sedentary behavior and adiposity-associated inflammation: the Multi-Ethnic Study of Atherosclerosis.
      • Henson J.
      • Yates T.
      • Edwardson C.L.
      • et al.
      Sedentary time and markers of chronic low-grade inflammation in a high risk population.
      which, in turn, has been linked with progression of COPD,
      • Fabbri L.M.
      • Luppi F.
      • Beghe B.
      • Rabe K.F.
      Complex chronic comorbidities of COPD.
      Parkinson disease,
      • Pessoa Rocha N.
      • Reis H.J.
      • Vanden Berghe P.
      • Cirillo C.
      Depression and cognitive impairment in Parkinson’s disease: a role for inflammation and immunomodulation?.
      and sepsis mortality,
      • Bertoni A.G.
      • Saydah S.
      • Brancati F.L.
      Diabetes and the risk of infection-related mortality in the U.S.
      perhaps due to inactivity associated with prolonged TV viewing. Similarly, TV viewing has been associated with lower cardiorespiratory fitness
      • Tucker L.A.
      • Arens P.J.
      • Lecheminant J.D.
      • Bailey B.W.
      Television viewing time and measured cardiorespiratory fitness in adult women.
      and muscle strength.
      • Hamer M.
      • Stamatakis E.
      Screen-based sedentary behavior, physical activity, and muscle strength in the English longitudinal study of ageing.
      Thus, prolonged TV time may adversely affect functional health and reduce one’s ability to withstand acute health events later in life (e.g., influenza/pneumonia, sepsis). More research is needed to fully understand the relations between TV viewing, inflammation, functional health, and mortality from these outcomes. The finding of a link between TV viewing and suicide was also novel and should be interpreted cautiously. Although there is an established relationship between physical activity and reduced risk of depression,
      • Dunn A.L.
      • Trivedi M.H.
      • O’Neal H.A.
      Physical activity dose-response effects on outcomes of depression and anxiety.
      and prolonged TV viewing has been prospectively associated with increased risk of depression,
      • Hamer M.
      • Poole L.
      • Messerli-Burgy N.
      Television viewing, C-reactive protein, and depressive symptoms in older adults.
      • Lucas M.
      • Mekary R.
      • Pan A.
      • et al.
      Relation between clinical depression risk and physical activity and time spent watching television in older women: a 10-year prospective follow-up study.
      • Mekary R.A.
      • Lucas M.
      • Pan A.
      • et al.
      Isotemporal substitution analysis for physical activity, television watching, and risk of depression.
      • Hamer M.
      • Stamatakis E.
      • Mishra G.D.
      Television- and screen-based activity and mental well-being in adults.
      depression may also lead to prolonged TV viewing. Future studies are needed to clarify the temporal relation between prolonged TV viewing, depression, and suicide and to elucidate whether depression resides in the causal pathway for the observed TV–suicide mortality association, or simply acts as a confounder.
      Prolonged TV viewing has also been associated with increased mortality from all-causes and cardiovascular disease
      • Grontved A.
      • Hu F.B.
      Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      • Dunstan D.W.
      • Barr E.L.
      • Healy G.N.
      • et al.
      Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
      • Ford E.S.
      Combined television viewing and computer use and mortality from all-causes and diseases of the circulatory system among adults in the United States.
      but less is known about the relation with the individual components of CVD mortality, such as stroke. Seguin et al.
      • Seguin R.
      • Buchner D.M.
      • Liu J.
      • et al.
      Sedentary behavior and mortality in older women: the Women’s Health Initiative.
      reported a stronger association between TV viewing and mortality from CHD than for overall CVD in women, consistent with the present finding of a null association for TV viewing and stroke mortality. Previous studies of TV viewing and cancer mortality have been mixed.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Dunstan D.W.
      • Barr E.L.
      • Healy G.N.
      • et al.
      Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
      • Seguin R.
      • Buchner D.M.
      • Liu J.
      • et al.
      Sedentary behavior and mortality in older women: the Women’s Health Initiative.
      • George S.M.
      • Smith A.W.
      • Alfano C.M.
      • et al.
      The association between television watching time and all-cause mortality after breast cancer.
      • Lee I.M.
      • Shiroma E.J.
      • Lobelo F.
      • et al.
      Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy.
      The present results, derived from double the number of deaths of the largest previous study, suggest a modest increase in cancer mortality with prolonged TV viewing, even among never smokers. In this study, the adverse effect of TV viewing was evident in both active and inactive individuals. This is consistent with several studies showing that prolonged sedentary behavior displaces primarily light and intermittent MVPA
      • Healy G.N.
      • Matthews C.E.
      • Dunstan D.W.
      • Winkler E.A.
      • Owen N.
      Sedentary time and cardio-metabolic biomarkers in U.S. adults: NHANES 2003-06.
      and associations between TV and health mortality remain after adjustment for structured MVPA.
      • Wijndaele K.
      • Brage S.
      • Besson H.
      • et al.
      Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk study.
      • Matthews C.E.
      • George S.M.
      • Moore S.C.
      • et al.
      Amount of time spent in sedentary behaviors and cause-specific mortality in U.S. adults.
      • Matthews C.E.
      • Moore S.C.
      • Sampson J.
      • et al.
      Mortality benefits for replacing sitting time with different physical activities.
      These results suggest both active and inactive individuals would benefit from interventions that reduce prolonged TV viewing.

      Limitations

      This study has limitations that should be noted. The cohort was primarily composed of white, educated older adults who were free of major chronic disease at baseline; hence, the generalizability of these results may be limited to similar populations. TV viewing was self-reported and assessed at a single time point, which may not adequately account for within-person variation in TV viewing and introduces measurement error that probably underestimates (attenuates) the strength of the observed associations. Results for a 2-hour/day increase in risk are only valid throughout the range of the highest response option (9 or more hours/day) on the TV viewing questions. Some of the causes of death associated with TV viewing are also chronic conditions, and information derived from death certificates may not always reflect the actual underlying cause of death. In particular, hypertension and diabetes mortality are typically associated with a cardiovascular event.
      • Cheng T.J.
      • Lin C.Y.
      • Lu T.H.
      • Kawachi I.
      Reporting of incorrect cause-of-death causal sequence on death certificates in the USA: using hypertension and diabetes as an educational illustration.
      • Cheng T.J.
      • Lu T.H.
      • Kawachi I.
      State differences in the reporting of diabetes-related incorrect cause-of-death causal sequences on death certificates.
      There is the potential for residual confounding and may be error associated with self-reported covariates. Increased dietary intake may confound or mediate associations with TV viewing owing to increased snacking behavior,
      • Harris J.L.
      • Bargh J.A.
      • Brownell K.D.
      Priming effects of television food advertising on eating behavior.
      • Thorp A.A.
      • McNaughton S.A.
      • Owen N.
      • Dunstan D.W.
      Independent and joint associations of TV viewing time and snack food consumption with the metabolic syndrome and its components; a cross-sectional study in Australian adults.
      and though adjustment for and stratification by BMI and diet quality had minimal effect on risk estimates, it is possible that residual confounding persists. Depression has been associated with increased risk of suicide and early mortality
      • Cuijpers P.
      • Vogelzangs N.
      • Twisk J.
      • Kleiboer A.
      • Li J.
      • Penninx B.W.
      Comprehensive meta-analysis of excess mortality in depression in the general community versus patients with specific illnesses.
      and this analysis was unable to control for mental health status. Similarly, the primary indicator of SES (educational attainment) may not have completely adjusted for all of the socioeconomic determinants of mortality. Strengths of this study include a large sample size and long follow-up, which allowed the investigation of many causes of death that are difficult to evaluate in smaller studies. The large sample also allowed for exclusion of individuals with major chronic diseases and poor/fair health at baseline to minimize concerns about reverse causality. Furthermore, stratified analyses revealed that risk associated with prolonged TV viewing persisted among individuals with and without comorbid conditions, with excellent self-reported health, and in smokers and non-smokers, suggesting these results are robust.

      Conclusions

      Older adults watch the most TV of any demographic group in the U.S.

      Bureau of Labor Statistics. American time use survey. 2012. www.bls.gov/tus/tables/a1_2013.pdf. Accessed June 8, 2015.

      In this large cohort of older adults, prolonged TV viewing was associated with higher risk for eight of 14 leading causes of death in the U.S. Given the increasing age of the population, the high prevalence of TV viewing in leisure time, and the broad range of mortality outcomes for which risk appears to be increased, prolonged TV viewing may be a more important target for public health intervention than previously recognized.

      Acknowledgments

      We are indebted to the participants in the NIH-AARP Diet and Health Study for their outstanding cooperation. This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute. The funder did not play any role in study design; collection, analysis, and interpretation of data; writing the report; or the decision to submit the report for publication.
      No financial disclosures were reported by the authors of this paper.

      Appendix. Supplementary Materials

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