The purpose of this study was to examine the longitudinal association between television (TV) viewing and all-cause mortality in older adults with hypertension. Sedentary behavior, physical activity, hypertension, and other chronic diseases were assessed by face-to-face interviews and confirmed by medical history. Mortality was reported by relatives and confirmed in medical records of the National Health System. The fully adjusted model showed a direct association between high TV viewing time and all-cause mortality; hazard ratio: 1.65 (95% confidence interval [1.02–2.68]). Women with high TV viewing were more likely to die than men. Higher TV viewing time was associated with all-cause mortality among those with diabetes and hypertension; hazard ratio: 3.54 (95% confidence interval [1.64–7.66]). The findings from this longitudinal study show that higher TV viewing time is associated with higher risk for all-cause mortality among older adults with hypertension, independently of physical activity, and other potential confounders.

Hypertension is a known risk factor for cardiovascular disease (CVD) and mortality (Lotfaliany et al., 2015; Mills et al., 2016). Despite the efforts of health professionals, the prevalence of hypertension is high worldwide, with 29% in the United States (Fryar, Ostchega, Hales, Zhang, & Kruszon-Moran, 2017), 30% in England, 59.5% in China, 77.9% in South Africa (Lloyd-Sherlock, Beard, Minicuci, Ebrahim, & Chatterji, 2014), and 30% in Brazil (Picon, Fuchs, Moreira, Riegel, & Fuchs, 2012). Globally, it is estimated that 1.39 (31%) billion people have hypertension. Considering that the definition of hypertension has changed (Whelton et al., 2018), these rates can be underestimated. Therefore, reducing and controlling blood pressure levels may lead to a significantly reduced risk of CVD and mortality (Bundy et al., 2017).

Sedentary behavior, defined as any waking behavior characterized by an energy expenditure ≤1.5 metabolic equivalents while in a sitting or reclining posture (Sedentary Behaviour Research Network, 2012; Tremblay et al., 2017), has been linked to poor health outcomes and mortality (Biswas et al., 2015; Chau et al., 2013; Proper, Singh, van Mechelen, & Chinapaw, 2011). It can be commonly interpreted as physical inactivity; however, sedentary behavior is not physical inactivity by a different name (van der Ploeg & Hillsdon, 2017).

Although television (TV) viewing may not be considered a proxy of overall sedentary behavior, it is the most common sedentary activity among adults (Mielke, da Silva, Owen, & Hallal, 2014). Previous studies have demonstrated that 49% of adults spend more than 4.5 hr/day watching TV (Mielke et al., 2014), while time spent watching TV may vary based on the method used to assess this behavior. Finally, TV viewing has been associated with Type 2 diabetes (Goldfield et al., 2013; Grøntved & Hu, 2011), depression (Zhai, Zhang, & Zhang, 2015), hypertension (Shiue, 2015), CVD (Grøntved & Hu, 2011), and mortality (Grøntved & Hu, 2011; Turi et al., 2018). A recent meta-analysis found a dose–response association between sitting time with CVD, mainly in people with low levels of physical activity (PA). However, there was no increased risk among the most active quartile (Ekelund et al., 2018).

Epidemiological evidence has clearly demonstrated that hypertension and TV viewing, as independent risk factors, have a negative impact on health outcomes including mortality (Dempsey, Howard, Lynch, Owen, & Dunstan, 2014; Gorgui, Gorshkov, Khan, & Daskalopoulou, 2014; Hadgraft et al., 2015; Schmid & Leitzmann, 2014; Whelton et al., 2018). However, many questions remain. People with hypertension and longer TV viewing time might be at the greatest risk of poor health and needs special attention from public efforts. From a public health perspective, the combination of these two independent risk factors, hypertension and TV viewing, may lead to an increased risk of CVD and mortality.

Data regarding behavioral variables and health outcomes are scarce in developing countries, such as Brazil (the biggest Latin-American nation), which can be considered an important gap in the literature. In addition, to the best of our knowledge, there is no prospective study investigating the association of TV viewing and mortality in a specific population (hypertension) from an emerging country. It is not clear how transferable findings are from developed countries to emerging nations. Therefore, this study aims to investigate the association of TV viewing with all-cause mortality in a hypertensive population from the Brazilian National Health System (NHS).

Methods

Participants

Participants were part of an ongoing cohort study with users of the Brazilian NHS in the city of Bauru. Bauru is a city (∼367,000 inhabitants) located in the central region of São Paulo state. This study began in 2010 with men and women from five basic health care units. Basic health care units are small primary health care facilities, in which health professionals (e.g., general practitioners, gynecologists, obstetricians, psychiatrists, dentists, and nurses) offer free low-complex health services (e.g., medical consultations, medicine prescription, vaccinations) to the population that lives in that specific region of the city. More complex cases and examinations are directed to hospitals linked to the NHS. Only men and women with a diagnosis of hypertension were included in this study (n = 747).

The recruitment process was described previously (Turi, Codogno, Fernandes, & Monteiro, 2016; Turi et al., 2015, 2017). Briefly, inclusion criteria were age ≥50 years, registered for at least 1 year at the basic health care unit, and active health care service registration (at least one medical visit in the previous 6 months). The Ethics Board Committee of the São Paulo State University (UNESP), Bauru, Brazil, reviewed and approved the study protocol and all participants included in the study signed a consent form.

TV Viewing and Physical Activity

Television viewing and PA were assessed through a validated questionnaire (Baecke, Burema, & Frijters, 1982) for epidemiological studies in the Brazilian population (Florindo, Latorre, Jaime, Tanaka, & Zerbini, 2004). This questionnaire provides questions regarding domains of PA: occupational, sports/exercise and leisure-time. The overall score was calculated following the questionnaire by combining the three domains. Participants classified in the top quartile (25% more active) were identified as “physically active” (Codogno, Fernandes, Sarti, Freitas Júnior, & Monteiro, 2011; Turi et al., 2017). TV viewing was assessed using one question of the Baecke et al. (1982) questionnaire: “During leisure time I watch television,” with the following possibilities of answer: (a) “never,” (b) “seldom,” (c) “sometimes,” (d) “often,” or (e) “very often.” Due to our limited sample size, the answers 1, 2, and 3 (“never,” “seldom,” and “sometimes”) were grouped as “low frequency” of TV viewing (score 0 has been attributed to this group), and the answers 4 and 5 (“often” and “very often”) were grouped as “high frequency” of TV viewing (score 1 has been attributed to this group) (Turi et al., 2018).

Mortality Follow-Up

The present mortality data were obtained by April 1, 2016. Researchers registered the occurrence of death by contacting relatives of participants and ascertaining the information in the records of the NHS. There were 74 deaths during the period. The most prevalent causes of death were cardiovascular, neoplasms, respiratory, and gastrointestinal.

Covariates

Information on health (body mass index [BMI], hypercholesterolemia, diabetes, history of arrhythmia or myocardial infarction), sociodemographic (sex, age, and economic status), and behavioral status (smoking and PA) were collected.

Statistical Analysis

Continuous variables were summarized using M ± SD, and categorical variables were summarized using frequency (percentage). Group comparisons were performed using the independent Student t test, and categorical variables were compared using the chi-square test (χ2). Cox proportional hazards regression analysis was used to calculate hazard ratios and its 95% confidence intervals for all-cause mortality according to TV viewing categories (high vs. low frequency) aiming to quantify the strength of this association. Adjusted models were used to control the main analysis for potential confounding factors. Model 1 was adjusted by age and sex. Model 2 was adjusted by Model 1 plus smoking status, economic status, history of arrhythmia and acute myocardial infarction, and PA. Model 3 was adjusted by Model 2 plus BMI, hypercholesterolemia, and diabetes mellitus. Kaplan–Meier survival analyses were performed using a log-rank p value to compare the curves. Finally, we performed stratified analyses according to sex, age, economic status, diabetes, and hypercholesterolemia to assess whether these factors may influence the association between TV viewing and all-cause mortality. Significance was set at p < .05 for all analyses. All analyses were performed using SPSS (version 18.0; SPSS Inc., Chicago, IL).

Results

At baseline, the mean age of the study sample was 65.36 ± 8.99 years, with a BMI of 30.21 ± 5.95 kg/m2. Overall, 23.3% of our sample was physically active, and 84.3% was considered overweight or obese. Differences between exposure groups were found for economic status, hypercholesterolemia, and PA. People in the high TV viewing group were more likely to have higher economic status (p = .024), hypercholesterolemia (p = .028), and be physically inactive (p < .01) (Table 1).

Table 1

Baseline Characteristics of the Sample According to TV Viewing Frequency

Leisure-Time TV Viewing

(frequency)
VariablesOverall sample

(n = 747)
Low

(never/seldom/sometimes)

(n = 568)
High

(often/very often)

(n = 179)
p-value
Age (years), M ± SD65.36 ± 8.9965.08 ± 9.0366.23 ± 8.86.135
WC (cm), M ± SD101.26 ± 12.64101.06 ± 12.87101.88 ± 11.87.456
Weight (kg), M ± SD74.92 ± 15.9074.69 ± 15.8775.67 ± 16.02.476
Height (cm), M ± SD157.41 ± 8.52157.35 ± 8.57157.61 ± 8.38.728
BMI (kg/m2), M ± SD30.21 ± 5.9530.16 ± 6.1330.36 ± 5.34.696
BMI (overweight/obesity), n (%)627 (84.3)477 (84.3)150 (84.3).998
ES score, M ± SD17.69 ± 5.5017.43 ± 5.4118.50 ± 5.71.024
Current smoker, n (%)92 (12.3)65 (11.4)27 (15.1).196
Diabetes mellitus, n (%)230 (30.8)182 (32.0)48 (26.8).187
Hypercholesterolemia, n (%)254 (30.0)181 (31.9)73 (40.8).028
Physically active, n (%)174 (23.3)153 (26.9)21 (11.7).000

Note. TV = television; WC = waist circumference; BMI = body mass index; ES = economic status.

A total of 74 deaths occurred after 6 years of follow-up. The fully adjusted model (age, sex, smoking status, economic status, history of arrhythmia and acute myocardial infarction, PA, BMI, hypercholesterolemia, and diabetes mellitus) across ascending categories of TV viewing (low TV viewing as reference) showed significant association between high TV viewing and all-cause mortality (1.65 [1.02–2.68]) (Table 2).

Table 2

Adjusted HR and 95% CI for All-Cause Mortality by TV Viewing Categories

TV Viewing Frequency
CharacteristicsLowHighp
All-cause mortality 
 deaths, n4727 
 death ratea140.8242.2 
HR [95% CI] 
 model 11.001.70 [1.06, 2.74].028
 model 21.001.57 [0.97, 2.54].066
 model 31.001.65 [1.02, 2.68].042

Note. Model 1: adjusted by age and sex. Model 2: adjusted by Model 1, smoking status, economic status, history of arrhythmia and acute myocardial infarction, and physical activity. Model 3: adjusted by Model 2, body mass index, hypercholesterolemia, and diabetes mellitus. TV = television; HR = hazard ratio; CI, confidence interval.

aAge-adjusted death rate per 10,000 person-years.

Further analysis showed a crude Kaplan–Meier survival curve favorable to the low TV viewing group (p = .007) (Figure 1). The stratified analysis showed that women with high TV viewing were more likely to die than men. In addition, longer TV viewing time was strongly associated with all-cause mortality among those with diabetes and hypertension (3.54 [1.64–7.66]), while there were no associations among those with hypertension and hypercholesterolemia (1.91 [0.71–5.15]) (Figure 2).

Figure 1
Figure 1

—Kaplan–Meier survival curves for all-cause mortality by TV viewing frequency among hypertensive adults. TV = television.

Citation: Journal of Aging and Physical Activity 27, 3; 10.1123/japa.2018-0094

Figure 2
Figure 2

—Adjusted hazard ratios and 95% CIs of all-cause mortality according to TV viewing frequency (high vs. low) across characteristics variables. Adjusted for all variables in the figure plus body mass index, smoking status, history of arrhythmia and acute myocardial infarction, and physical activity. The low frequency group is the reference for all analysis. CI = confidence interval; TV = television.

Citation: Journal of Aging and Physical Activity 27, 3; 10.1123/japa.2018-0094

Discussion

This study showed a positive association between longer TV viewing time and a higher risk of all-cause mortality among men and women with hypertension. Even after adjustments for confounders, including BMI, hypercholesterolemia, diabetes, history of CVD, and PA, their associations remained significant. Women and people with combined hypertension and diabetes presented higher risk of mortality. These results suggest that public health efforts should target the reduction of sedentary behavior in this population, especially among women and those with combined chronic diseases.

Sedentary behavior has been studied as an independent risk factor for several health outcomes including mortality. Previous large prospective cohort studies have found associations between sitting time and all-cause, CVD and cancer mortality (Matthews et al., 2012; van der Ploeg, Chey, Korda, Banks, & Bauman, 2012). The authors found that even among adults reporting high levels of PA, higher TV viewing time was associated with increased all-cause and CVD mortality risk (Matthews et al., 2012). Moreover, the population-attributable fraction of sedentary behavior suggested that it was responsible for 6.9% of deaths (van der Ploeg et al., 2012). Furthermore, a recent meta-analysis with over a million people reported that high levels of PA may attenuate, but not eliminate, the association of TV viewing time with increased risk of mortality (Ekelund et al., 2016).

Our study shows an association of TV viewing with increased all-cause mortality risk in hypertensive people. Previous research found positive association of sedentary activities with blood pressure in hypertensive patients (Gerage et al., 2015). Hypertension is already known as a strong risk factor for CVD and mortality (Lotfaliany et al., 2015; Mills et al., 2016) and its combination with increased sitting time might be even harmful to general health. Although PA is recommended for preventing and controlling blood pressure levels (Diaz & Shimbo, 2013), the best intervention to reduce sedentary behavior and/or replace it by PA is still unclear. Indeed, to eliminate the detrimental effect of sedentary behavior, people would have to do four to five times more PA than the recommended guidelines (van der Ploeg & Hillsdon, 2017; World Health Organization, 2010). From a public health perspective, it does not seem feasible for the majority of the population (van der Ploeg & Hillsdon, 2017).

The TV viewing has been found to be the most common sedentary activity. In fact, the complexity of the relationship between TV viewing and mortality can be partially explained by health status linked to this behavior. Previous studies have found that TV viewing stimulates consumption of unhealthy foods, independent of hunger in children and adults (Harris, Bargh, & Brownell, 2009). This change in diet combined with the low energy expenditure during this sedentary activity (TV viewing) increases body weight and, consequently, the development of obesity (Sun et al., 2015), obesity-related diseases, and mortality (Veerman et al., 2012). Moreover, experimental studies have investigated the pathophysiology of sedentary time on health. For example, previous research had noted adverse changes to glucose tolerance and suggested that loss of muscle contraction had been shown to suppress lipoprotein lipase activity (Dunstan, Howard, Healy, & Owen, 2012; Hamilton, Hamilton, & Zderic, 2007; Thyfault & Krogh-Madsen, 2011). This activity is necessary for the uptake of the constituents of triglyceride-rich lipoproteins by skeletal muscle. Finally, time spent watching TV has been linked to reduced time spent in PA (Touvier et al., 2010), increased body weight and waist circumference (Menai et al., 2016; Shuval, Gabriel, & Leonard, 2013), and hypertension (Thorp, McNaughton, Owen, & Dunstan, 2013). These factors, associated with a preexistent condition (hypertension), might increase the detrimental effects of sedentary behavior in this population.

In this study, people with combined diabetes mellitus and hypertension presented higher risk of all-cause mortality. This can be partially explained by the fact that diabetes and hypertension are both independent risk factors for CVD and mortality (Lotfaliany et al., 2015; WHO, 2009). Women also presented higher risk of all-cause mortality. Although mortality causes may be similar between men and women, there are specific risk factors that affect only women, such as preeclampsia, gestational diabetes, and menopause (Appelman, van Rijn, ten Haaf, Boersma, & Peters, 2015).

Our sample is composed of adults aged 50 years and older, and a significant proportion of the participants are retired or in the retirement process. As time spent watching TV and in other sedentary activities increase with retirement (Touvier et al., 2010), interpretation and generalizability of our results require caution. Our limited sample size and lack of information about diet can also be considered an important limitation. However, there is no previous study investigating the association of TV viewing with mortality in Brazilian adults with hypertension, which reinforce the originality of our study. Analyses of more robust longitudinal data from Brazil and other emerging nations should be developed shortly to evaluate our findings. Another limitation is the self-reporting of TV viewing time and the categories used. Unfortunately, the questionnaire did not allow us to create categories based on time spent watching TV (e.g., hours/day), limiting any link with current guidelines for TV viewing (or other sorts of sedentary behavior) based on time per day. Objective measures should be considered in future studies to address the real effect of sedentary activities on health outcomes (Lee et al., 2018).

In summary, our results show a positive association between TV viewing and all-cause mortality in men and women with hypertension, independent of PA, and other potential confounders. PA interventions to prevent and control hypertension can also be used to stimulate changes in behavioral activities, such as TV viewing. From a public health point of view, reducing time spent in sedentary activities and/or replacing this time by PA is a potential target for future interventions in developing countries.

Acknowledgments

The authors acknowledge the Coordination for the Improvement of Higher Education Personnel (CAPES), the Health Secretary of Bauru and the health professionals of primary care units. Í. R. Lemes is supported by a scholarship from São Paulo Research Foundation (FAPESP) grants #2015/17777-3 and #2016/11140-6. The authors declare no conflict of interest.

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  • Shiue, I. (2015). Duration of daily TV/screen watching with cardiovascular, respiratory, mental and psychiatric health: Scottish Health Survey, 2012–2013. International Journal of Cardiology, 186, 241246. PubMed ID: 25828126 doi:10.1016/j.ijcard.2015.03.259

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  • Shuval, K., Gabriel, K.P., & Leonard, T. (2013). TV viewing and BMI by race/ethnicity and socio-economic status. PLoS ONE, 8(5), e63579. PubMed ID: 23691070 doi:10.1371/journal.pone.0063579

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  • Sun, J.-W., Zhao, L.-G., Yang, Y., Ma, X., Wang, Y.-Y., & Xiang, Y.-B. (2015). Association between television viewing time and all-cause mortality: A meta-analysis of cohort studies. American Journal of Epidemiology, 182(11), 908916. PubMed ID: 26568572 doi:10.1093/aje/kwv164

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  • Thorp, A.A., McNaughton, S.A., Owen, N., & Dunstan, D.W. (2013). 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. The International Journal of Behavioral Nutrition and Physical Activity, 10(1), 96. doi:10.1186/1479-5868-10-96

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  • Thyfault, J.P., & Krogh-Madsen, R. (2011). Metabolic disruptions induced by reduced ambulatory activity in free-living humans. Journal of Applied Physiology, 111(4), 12181224. PubMed ID: 21636564 doi:10.1152/japplphysiol.00478.2011

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  • Touvier, M., Bertrais, S., Charreire, H., Vergnaud, A.-C., Hercberg, S., & Oppert, J.-M. (2010). Changes in leisure-time physical activity and sedentary behaviour at retirement: A prospective study in middle-aged French subjects. The International Journal of Behavioral Nutrition and Physical Activity, 7(1), 14. doi:10.1186/1479-5868-7-14

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  • Tremblay, M.S., Aubert, S., Barnes, J.D., Saunders, T.J., Carson, V., Latimer-Cheung, A.E., . . . SBRN Terminology Consensus Project Participants. (2017). Sedentary Behavior Research Network (SBRN)—Terminology Consensus Project process and outcome. The International Journal of Behavioral Nutrition and Physical Activity, 14(1), 75. PubMed ID: 28599680 doi:10.1186/s12966-017-0525-8

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  • Turi, B.C., Codogno, J.S., Fernandes, R.A., & Monteiro, H.L. (2016). Low levels of physical activity and metabolic syndrome: Cross-sectional study in the Brazilian public health system. Ciência & Saúde Coletiva, 21(4), 10431050. PubMed ID: 30320880 doi:10.1590/1413-81232015214.23042015

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  • Turi, B.C., Codogno, J.S., Fernandes, R.A., Sui, X., Lavie, C.J., Blair, S.N., & Monteiro, H.L. (2015). Accumulation of domain-specific physical inactivity and presence of hypertension in Brazilian public healthcare system. Journal of Physical Activity and Health, 12(11), 15081512. PubMed ID: 25710729 doi:10.1123/jpah.2014-0368

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  • Turi, B.C., Codogno, J.S., Fernandes, R.A., Sui, X., Lavie, C.J., Blair, S.N., & Monteiro, H.L. (2017). Association of different physical activity domains on all-cause mortality in adults participating in primary care in the Brazilian National Health System: 4-Year follow-up. Journal of Physical Activity & Health, 14(1), 4551. PubMed ID: 27775469 doi:10.1123/jpah.2016-0067

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  • Turi, B.C., Monteiro, H.L., Lemes, Í.R., Codogno, J.S., Lynch, K.R., Asahi Mesquita, C.A., & Fernandes, R.A. (2018). TV viewing time is associated with increased all-cause mortality in Brazilian adults independent of physical activity. Scandinavian Journal of Medicine & Science in Sports, 28(2), 596603. PubMed ID: 28329411 doi:10.1111/sms.12882

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  • van der Ploeg, H.P., Chey, T., Korda, R.J., Banks, E., & Bauman, A. (2012). Sitting time and all-cause mortality risk in 222 497 Australian adults. Archives of Internal Medicine, 172(6), 494500. PubMed ID: 22450936 doi:10.1001/archinternmed.2011.2174

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  • van der Ploeg, H.P., & Hillsdon, M. (2017). Is sedentary behaviour just physical inactivity by another name? International Journal of Behavioral Nutrition and Physical Activity, 14(1), 142. PubMed ID: 29058587 doi:10.1186/s12966-017-0601-0

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  • Veerman, J.L., Healy, G.N., Cobiac, L.J., Vos, T., Winkler, E.A.H., Owen, N., & Dunstan, D.W. (2012). Television viewing time and reduced life expectancy: A life table analysis. British Journal of Sports Medicine, 46(13), 927930. PubMed ID: 23007179 doi:10.1136/bjsports-2011-085662

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  • Whelton, P.K., Carey, R.M., Aronow, W.S., Casey, D.E., Collins, K.J., Dennison Himmelfarb, C., . . . Wright, J.T. (2018). 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension, 71(6), e13e115. PubMed ID: 29133356 doi:10.1161/HYP.0000000000000065

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  • WHO. (2009). Global health risks: Mortality and burden of disease attributable to selected major risks. Bulletin of the World Health Organization, 87, 646. doi:10.2471/BLT.09.070565

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  • World Health Organization. (2010). Global recommendations on physical activity for health. Geneva: WHO.

  • Zhai, L., Zhang, Y., & Zhang, D. (2015). Sedentary behaviour and the risk of depression: A meta-analysis. British Journal of Sports Medicine, 49(11), 705709. PubMed ID: 25183627 doi:10.1136/bjsports-2014-093613

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Lemes is with the Dept. of Physical Therapy, São Paulo State University (UNESP), Presidente Prudente, Brazil. Sui and Blair are with the Dept. of Exercise Science, University of South Carolina, Columbia, SC, USA. Turi-Lynch is with the Dept. of Physical Education, Faculty of Dracena (UNIFADRA), Dracena, Brazil. Fernandes and Codogno are with the Dept. of Physical Education, São Paulo State University (UNESP), Presidente Prudente, Brazil. Monteiro is with the Dept. of Physical Education, São Paulo State University (UNESP), Bauru, Brazil.

Address author correspondence to Ítalo Ribeiro Lemes at itolemes@hotmail.com.
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    —Kaplan–Meier survival curves for all-cause mortality by TV viewing frequency among hypertensive adults. TV = television.

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    —Adjusted hazard ratios and 95% CIs of all-cause mortality according to TV viewing frequency (high vs. low) across characteristics variables. Adjusted for all variables in the figure plus body mass index, smoking status, history of arrhythmia and acute myocardial infarction, and physical activity. The low frequency group is the reference for all analysis. CI = confidence interval; TV = television.

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  • Shiue, I. (2015). Duration of daily TV/screen watching with cardiovascular, respiratory, mental and psychiatric health: Scottish Health Survey, 2012–2013. International Journal of Cardiology, 186, 241246. PubMed ID: 25828126 doi:10.1016/j.ijcard.2015.03.259

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shuval, K., Gabriel, K.P., & Leonard, T. (2013). TV viewing and BMI by race/ethnicity and socio-economic status. PLoS ONE, 8(5), e63579. PubMed ID: 23691070 doi:10.1371/journal.pone.0063579

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J.-W., Zhao, L.-G., Yang, Y., Ma, X., Wang, Y.-Y., & Xiang, Y.-B. (2015). Association between television viewing time and all-cause mortality: A meta-analysis of cohort studies. American Journal of Epidemiology, 182(11), 908916. PubMed ID: 26568572 doi:10.1093/aje/kwv164

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thorp, A.A., McNaughton, S.A., Owen, N., & Dunstan, D.W. (2013). 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. The International Journal of Behavioral Nutrition and Physical Activity, 10(1), 96. doi:10.1186/1479-5868-10-96

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thyfault, J.P., & Krogh-Madsen, R. (2011). Metabolic disruptions induced by reduced ambulatory activity in free-living humans. Journal of Applied Physiology, 111(4), 12181224. PubMed ID: 21636564 doi:10.1152/japplphysiol.00478.2011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Touvier, M., Bertrais, S., Charreire, H., Vergnaud, A.-C., Hercberg, S., & Oppert, J.-M. (2010). Changes in leisure-time physical activity and sedentary behaviour at retirement: A prospective study in middle-aged French subjects. The International Journal of Behavioral Nutrition and Physical Activity, 7(1), 14. doi:10.1186/1479-5868-7-14

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tremblay, M.S., Aubert, S., Barnes, J.D., Saunders, T.J., Carson, V., Latimer-Cheung, A.E., . . . SBRN Terminology Consensus Project Participants. (2017). Sedentary Behavior Research Network (SBRN)—Terminology Consensus Project process and outcome. The International Journal of Behavioral Nutrition and Physical Activity, 14(1), 75. PubMed ID: 28599680 doi:10.1186/s12966-017-0525-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turi, B.C., Codogno, J.S., Fernandes, R.A., & Monteiro, H.L. (2016). Low levels of physical activity and metabolic syndrome: Cross-sectional study in the Brazilian public health system. Ciência & Saúde Coletiva, 21(4), 10431050. PubMed ID: 30320880 doi:10.1590/1413-81232015214.23042015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turi, B.C., Codogno, J.S., Fernandes, R.A., Sui, X., Lavie, C.J., Blair, S.N., & Monteiro, H.L. (2015). Accumulation of domain-specific physical inactivity and presence of hypertension in Brazilian public healthcare system. Journal of Physical Activity and Health, 12(11), 15081512. PubMed ID: 25710729 doi:10.1123/jpah.2014-0368

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turi, B.C., Codogno, J.S., Fernandes, R.A., Sui, X., Lavie, C.J., Blair, S.N., & Monteiro, H.L. (2017). Association of different physical activity domains on all-cause mortality in adults participating in primary care in the Brazilian National Health System: 4-Year follow-up. Journal of Physical Activity & Health, 14(1), 4551. PubMed ID: 27775469 doi:10.1123/jpah.2016-0067

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    • Export Citation
  • Turi, B.C., Monteiro, H.L., Lemes, Í.R., Codogno, J.S., Lynch, K.R., Asahi Mesquita, C.A., & Fernandes, R.A. (2018). TV viewing time is associated with increased all-cause mortality in Brazilian adults independent of physical activity. Scandinavian Journal of Medicine & Science in Sports, 28(2), 596603. PubMed ID: 28329411 doi:10.1111/sms.12882

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van der Ploeg, H.P., Chey, T., Korda, R.J., Banks, E., & Bauman, A. (2012). Sitting time and all-cause mortality risk in 222 497 Australian adults. Archives of Internal Medicine, 172(6), 494500. PubMed ID: 22450936 doi:10.1001/archinternmed.2011.2174

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van der Ploeg, H.P., & Hillsdon, M. (2017). Is sedentary behaviour just physical inactivity by another name? International Journal of Behavioral Nutrition and Physical Activity, 14(1), 142. PubMed ID: 29058587 doi:10.1186/s12966-017-0601-0

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Veerman, J.L., Healy, G.N., Cobiac, L.J., Vos, T., Winkler, E.A.H., Owen, N., & Dunstan, D.W. (2012). Television viewing time and reduced life expectancy: A life table analysis. British Journal of Sports Medicine, 46(13), 927930. PubMed ID: 23007179 doi:10.1136/bjsports-2011-085662

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Whelton, P.K., Carey, R.M., Aronow, W.S., Casey, D.E., Collins, K.J., Dennison Himmelfarb, C., . . . Wright, J.T. (2018). 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension, 71(6), e13e115. PubMed ID: 29133356 doi:10.1161/HYP.0000000000000065

    • Search Google Scholar
    • Export Citation
  • WHO. (2009). Global health risks: Mortality and burden of disease attributable to selected major risks. Bulletin of the World Health Organization, 87, 646. doi:10.2471/BLT.09.070565

    • Search Google Scholar
    • Export Citation
  • World Health Organization. (2010). Global recommendations on physical activity for health. Geneva: WHO.

  • Zhai, L., Zhang, Y., & Zhang, D. (2015). Sedentary behaviour and the risk of depression: A meta-analysis. British Journal of Sports Medicine, 49(11), 705709. PubMed ID: 25183627 doi:10.1136/bjsports-2014-093613

    • Crossref
    • Search Google Scholar
    • Export Citation
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