Original Research Article

Are you still watching | Correlations between binge TV watching, diet and physical activity

Dr. Lori Andersen Spruance,

Lori Andersen Spruance 1 , Monita Karmakar 2 , Jessica Sloan Kruger 3 , J. Mitchell Vaterlaus 4
1. Department of Health Sciences, College of Life Sciences, Brigham Young University, LSB2149, provo, Utah, USA, 84602
2. Department of Neurology, The University of Toledo, 300 Arlington Avenue, Toledo, Ohio,USA, 43614
3. College of Population Health, The University of Toledo, 2801 W. Bancroft, Toledo, Ohio,USA, 43606
4. Department of Health & Human Development, College of Education, Health & Human
Development, Montana State University, 122 Herrick Hall, Bozeman, Montana, USA, 59717

Sedentary behavior can increase risk of chronic disease. Online streaming of television (TV) has increased in popularity, yet may increase a sedentary lifestyle among young adults. This study investigated self-reported demographic characteristics and obesogenic behaviors among college students who reported binge watching TV and those who did not.

*Corresponding author:


Dr. Lori Andersen Spruance
Lori.andersen@byu.edu

Keywords:

Binge Watching; College; Television; health; Diet; Physical Activity

Sedentary behavior can increase risk of chronic disease. Online streaming of television (TV) has increased in popularity, yet may increase a sedentary lifestyle among young adults. This study investigated self-reported demographic characteristics and obesogenic behaviors among college students who reported binge watching TV and those who did not. Five hundred young adults were randomly-sampled from a western public university in the United States in October 2015. Participants reported demographic information, health related details, and whether they binge watched TV weekly, monthly, or not at all through an online survey. Almost one-quarter of participant reported binge TV watching weekly and 72% did so monthly. Females had higher odds of binge TV watching (weekly and monthly) than males. Participants who reported eating out weekly had higher odds of weekly TV binge watching. Participants who were upperclassmen and did not consume fruit daily had higher odds of monthly TV binge watching. No relationship between self-reported Body Mass Index and TV binge watching was identified. TV binge watching is an understudied area that warrants more health research attention. These results identify the importance of reducing sedentary time activities among young adults, including binge TV watching, in order to prevent chronic disease in the future.

Young adulthood is a time marked by transition, increased autonomy, and regular media use (Coyne et al., 2013). With these notable markers, it has been proposed that young adulthood is an important time period for the development of enduring health behaviors (Nelson et al., 2008). Watching TV is one of the most prevalent sedentary behaviors (Winjndaele et al., 2011) and sedentary behavior is associated with increased risk for the top chronic diseases in the United States, including cardiovascular disease, cancer, and type 2 diabetes (Hu et al., 2001; Hu et al., 2003; Keadle et al., 2015). In the United States, the average American adult watches approximately four and half-hours of live television (TV) a day (The Nielsen Company, 2016).

Online, instant streaming platforms like Hulu, Amazon, and Netflix have changed the way many watch TV. Devices like laptops, smartphones, and tablets have made constant access to online TV streaming a possibility. Almost all young adults report using the internet (96%) (Pew Research Center, 2015). Because of the accessibility of instant streaming through the internet, the concept of binge TV watching has emerged. Binge TV watching is referred to as the act of watching consecutive hours of media content in a single sitting or viewing multiple episodes of the same TV show in the same sitting (Walton-Pattison et al., 2016). Currently, no standard definition of binge TV watching has been established (De Feijter et al., 2016; Khan and Gisbergen, 2016; Jenner, 2016; Spangler, 2013; Walton-Pattison et al., 2016), yet the most commonly used definition of binge TV watching is between two and six episodes in one sitting (Walton-Pattison et al., 2016). Because episodes vary in length, this can equate to be anywhere from 45 minutes to six hours.

TV and Physical Inactivity


While no research to date has specifically examined binge TV watching and physical inactivity, a large body of research has examined TV watching and physical inactivity. Experts assert that the number of hours spent in front of the TV displaces the time spent in physical activity (DuRant et al., 1994). Additionally, watching TV also has a relationship with obesity. Several researchers have identified a positive relationship between the number of hours of TV watched and obesity in young adults (Boone et al., 2007; Boulos et al., 2012). Thus suggesting that binge TV watching may negatively influence physical activity levels and obesity as well.

TV and Eating Habits


Another large body of evidence has examined the relationship between TV watching and diet. A well-established link between TV watching and a decreased consumption of fruits and vegetables has been established (Boynton-Jarrett et al., 2003; Coon et al., 2001; Crespo et al., 2001; Liang et al., 2009). Other research has recognized a strong relationship between TV watching and other unhealthy diet behaviors including increased sugar sweetened beverage consumption (Barr-Anderson et al., 2009), increased overall food intake (Bellisle et al., 2004; Blass et al., 2006; Jackson et al., 2009; Stroebele and de Castro, 2004), consumption of snacks that are high in calories, and fast food consumption (Cleland et al., 2008). Some hypothesize that eating while watching TV may interrupt one’s ability to respond to satiety cues (Wansink, 2010), thus contributing to one’s ability to regulate the number of calories consumed.

Purpose of the Current Study


Behaviors are best predicted through intention to perform a behavior, according to the theory of planned behavior (TPB) (Ajzen, 1975). Identity theory suggests that self-identity is a predictor to intention (Terry et al., 1999) and has been studied as a predictor to preform behavior for several decades. Researchers found that people were more likely to intend on engaging in a behavior if it was part of their self-identity for both health and non-health related behaviors (Charng et al., 1988; Granberg and Holmberg, 1990; Hagger et al., 2007; Sparks and Shepherd, 1992; Theodorakis, 1994). Therefore, there may be value in studying individuals who self-identify as binge TV watchers. According to identity theory and the TPB, individuals who self-identify as binge TV watcher are likely to spend hours of time in sedentary behavior each week and month, likely putting them at increased risk for the development of long-term chronic disease. Thus, identifying characteristics of young adults who are likely to self-identify as binge TV watchers may facilitate the development of targeted interventions to reduce time spent in sedentary activities.
Further, no research to date has examined binge TV watching and its relationship to obesogenic behaviors in young adults. Identifying relationships between diet and physical activity and binge TV watching may help prevent serious chronic disease in the future. The purpose of this study was to examine the correlations between consumption of fruits and vegetables, physical activity, self-reported Body Mass Index (BMI), and binge TV watching within a sample of young adults. We hypothesized that individuals who binge watched TV would have poorer diets, be less physically active, and have higher BMI values than those who do not binge watch TV.

Procedures and Sample


A random sample of young adults attending a university in northern Utah was determined by the university registrar’s office. A total of 1,995 students were invited to participate in an online survey, administered through Qualtrics. The survey consisted of questions from several previous studies (Centers for Disease Control and Prevention, 2002; Kruger and Karmarkar; Lorig et al., 1996) and was reviewed by a panel of health and media experts from several universities. Survey questions included demographic characteristics, typical TV use, physical activity, nutrition, and BMI. Prior to taking the survey, all respondents were asked to complete an online consent form. All data collection instruments, procedures, and protocols were approved by institution’s IRB.

Measures


Demographic variables. Respondents were asked to identify their race/ethnicity and were allowed to select more than one response option to classify their race/ethnicity. The majority of the sample selected Non-Hispanic, White; all other options, including those who selected multiple responses, were collapsed into other category to create a dichotomous variable. Participants were also asked to report their marital status and their responses were categorized as single or married.
Binge TV watching. Respondents were asked to identify how many consecutive hours of TV watching during one sitting they consider to be binge watching. Based on their description, respondents were asked if they binge watched in the last week and last month. These variables were used as the outcome variables for data analyses.
Diet. Several variables representing diet were examined. Respondents were asked to identify the number of times they ate or drank 100% pure fruit juice; fresh, frozen, or canned fruit; dark green vegetables; orange colored vegetables; and other vegetables in the last week. Seven response options were provided (i.e., I did not consume this food/drink in the past seven days, 1-3 times during the past 7 days, 4-6 times during the past 7 days, 1 time per day, 2 times per day, 3 times per day, and 4 or more times per day) and were collapsed into two categories: (a) less than once per day and (b) once or more per day for analysis. Respondents were also asked to report how frequently they eat out or get take out from a restaurant in a usual week (response options ranged from never to six or more times). Response options were collapsed to never, 1 time per week, 2-3 times per week, and 4 or more times per week.
Physical Activity. An established measure (Lorig et al., 1996) of total weekly time spent with different exercises was completed by respondents. Scoring following Stanford Patient Education Research Center (patienteducation.standford.edu) was used to define number of minutes spent on each exercise activity (Lorig et al., 1996). Each activity was classified into “moderate activity” and “vigorous activity” as defined by the CDC and American College of Sports Medicine (ACSM) guidelines (US Department of Health and Human Services, 1999). Relying on the PA requirements as defined by ACSM and the American Heart Association (Haskell et al., 2007), minutes of activity for “moderate” and “vigorous” were summed and the coded as one if they met PA recommendations and zero if they did not meet recommendations as.
Body mass index. BMI values were calculated using participant-reported measurements of height and weight in the formula (weight (lbs)/height (in)2) x 703. Two BMI variables were created; one capturing the previously established criteria for establishing obesity categories (Underweight= below 18.5; Normal/Healthy weight= 18.5-24.9; Overweight= 25.0-29.9; Obese= 30.0 and above) (Centers for Disease Control and Prevention, 2015), while the other was a continuous variable.

Analysis


Data analyses were conducted in SAS version 9.4. Descriptive statistics were calculated for each variable. To compare binge TV watchers to non-binge TV watchers, chi-square analysis and t-test analyses were used. For hypothesis testing, two separate logistic regression models were built. The first model examined correlates of weekly binge TV watching, while the second model examined associations with monthly binge TV watching. Unadjusted variables with a p-value of <0.20 and theoretical basis were considered for inclusion in the adjusted model; forward selection modeling strategy was used. Variables had to meet a minimum standard of p<0.05 to remain in the final multivariable model. For variables with high correlations (age and year in school, BMI and BMIcat), Aikake’s Information Criterion (AIC) values were examined and variables with smaller AIC values were selected for each model. A separate analysis, with the same modeling strategy, was used for respondents who defined binge TV watching as consecutively viewing between two and six hours of TV.

Weekly Binge TV Watchers


Over 20% of respondents identified as weekly binge TV watchers (Table 1). In a multivariate logistic regression, weekly binge TV watching was associated with gender and frequency of eating out (Table 2). Females had greater odds of being weekly binge TV watchers compared to males. While the relationship of gender to binge TV watching has not previously been explored, the finding is consistent with other literature stating that females are more likely to be sedentary and engage in physical activity less often than males (Chastin et al., 2015; Dumith et al., 2010; Frenn et al., 2005; Godfrey et al., 2014; Van Cauwenberg et al., 2014; Van Der Horst et al., 2007; Wenthe et al., 2009). There were no significant two-way interactions.

Table 1. Descriptive Characteristics for Emerging Adults Who Do and Do Not Self-Identify as Weekly Binge TV Watchers.

Variable

Does Not Binge; Frequency (%); Mean (SD); N=350 (76.59) 

Binge; Frequency (%); Mean (SD);  

N=107 (23.41)

Total

N= 457

Gender

                Male

                Female

 

145 (44.75) 

179 (55.25)

 

33 (34.74)

62 (65.26)

 

179 (42.62) 

241 (57.83)

Race

                White
                Other

 

284 (89.87)
32 (10.13)

 

77 (87.50)
11 (12.50)

 

361 (89.36)
43 (10.64)

Age

20.60 (2.07)

20.43 (1.86)

20.56 (2.02)

Year in School

                Freshman

                Sophomore

                Junior

                Senior

 

103 (31.79)

63 (19.44) 

78 (24.07)

80 (24.69)

 

29 (30.53) 

20 (21.05)

23 (24.21)

23 (24.21)

 

132 (31.50) 

83 (19.81) 

101 (24.11) 

103 (24.58)

Marital Status
                Single

                Married

260 (79.75) 

66 (20.25)

76 (81.72)

17 (18.28)

336 (80.19)

83 (19.81)

BMI

23.41 (4.13)

23.53 (3.59)

23.44 (4.01)

BMI Category

                Underweight

                Normal

                Overweight

                Obese

 

56 (16.00) 

210 (60.00)

61 (17.43)

23 (6.57)

 

16 (14.95) 

67 (62.62)

19 (17.76)

5 (4.67)

 

113 (22.69) 

277 (55.62)

80 (16.06)

28 (5.662)

100% Fruit Juice Consumption

                Less than once per day

               Once per day or greater    

 

326 (93.14) 

24 (6.86)

 

104 (97.20) 

3 (2.80)

 

471 (94.58) 

27 (5.42)

Fruit Consumption

                Less than once per day

                Once per day or greater

 

268 (76.57) 

82 (23.43)

 

91 (85.05) 

16 (14.95)

 

400 (80.32) 

98 (19.68)

Green Vegetable Consumption

                Less than once per day

                Once per day or greater

 

292 (83.43) 

58 (16.57)

 

96 (89.72) 

11 (10.28)

 

429 (86.14) 

69 (13.86)

Orange Vegetable Consumption

                Less than once per day

                Once per day or greater

 

307 (87.71) 

43 (12.29)

 

99 (92.52) 

8 (7.48)

 

447 (89.76)

51 (10.24)

Other Vegetable Consumption

                Less than once per day

                Once per day or greater

 

274 (78.29) 

76 (21.71)

 

91 (85.05) 

16 (14.95)

 

406 (81.53) 

92 (18.47)

Frequency of Eating Out**

                Never

                Once a week

                2-3 times per week

                4 or more times per week

 

89 (27.22)

146 (66.65) 

74 (22.63)

18 (5.50)

 

12 (12.63)

40 (42.11) 

36 (37.89)

7 (7.37)

 

101 (23.93)

186 (44.08)

110 (26.07)

25 (5.92)

Meets PA Recommendations

                No

                Yes

 

164 (46.86) 

186 (53.14)

 

58 (54.21) 

49 (45.79)

 

263 (52.81)

235 (47.19)


PA= Physical Activity, BMI= Body Mass Index
*indicates p<.05, **indicates p < .01, ***indicates p < .001


Table 2. Adjusted Effects Associated with Weekly Binge TV Watching 

Variable

Odds Ratio* 

Confidence Interval

p-value

Gender

            Male

            Female

 

Ref.

1.34

 

 

1.01-2.67

 

0.046

 

Frequency of Eating Out

            Never

            Once a week

            2-3 times per week

            4 or more times per week

 

Ref.

2.10

3.84

3.34

 

 

1.04-4.23

1.85-7.94

1.14-9.816

0.003

*Adjusted for other variables (gender, frequency of eating out) in the model.

Respondents who reported eating out one time or more per week also had greater odds of being weekly binge TV watchers compared to those who reported never eating out on an average week. Research has connected increased fast food consumption to TV viewing in adults (French et al., 2000; Hu et al., 2001; Hu et al., 2003; Panagiotakos et al., 2008) and food consumed that is prepared away from home contains more calories, is higher in fat and lower in calcium, iron, and fiber, than food prepared at home (Lin and Gutherie, 2012; Todd et al., 2010). While this study did not specifically examine fast food consumption, the association between young adults’ binge watching and frequency of eating out may be cause for concern.

In a separate analysis examining those who defined binging as watching between two to six hours of TV, eating out was the only variable related to weekly binge TV watching. Respondents who ate out one or more time per week had higher odds of being weekly binge TV watchers compared to those who did not eat out at all (once a week versus none adjusted Odds Ratio [aOR]: 1.2.35, Confidence Interval [CI]: 1.11-4.95; two or three times per week versus none aOR: 3.97, CI: 1.84-8.61; four or more times per week versus none aOR: 4.15, CI: 1.35-12.71) (data not shown).

Monthly Binge TV Watchers


Over 70% of respondents identified as monthly binge TV watchers (Table 3), which is consistent with the report that emerging adults are regular media users (Coyne et al., 2015). In a multivariate logistic regression, monthly binge watching was correlated with gender, year in school, and fruit consumption (Table 4). Again, females had higher odds of being monthly binge TV watchers compared to males. Upper classmen had higher odds of being monthly binge TV compared to freshmen. In Pittman and Sheehan’s (2015) binge TV watching study with adults they reported that people under age 40 were more likely to binge watch. The findings in this study suggest that there are differences in odds of binge watching among young adults.

Table 3. Descriptive Characteristics for Emerging Adults Who Do and Do Not Self-Identify as Monthly Binge TV Watchers

Variable

Do not Binge; Frequency (%);
Mean (SD); N=128 (28.01) 

Binge; Frequency (%)
Mean (SD); N=329 (71.99)

Total

N= 457

Gender

                Male

                Female

 

57 (48.72) 

60 (51.28)

 

121 (40.07) 

181 (59.93)

 

179 (42.62) 

241 (57.83)

Race

                White

                Other

 

102 (89.47)

12 (10.53)

 

259 (98.31)

31 (10.69)

 

361 (89.36) 

43 (10.64)

Age**

20.09 (2.00)

20.76 (2.00)

20.56 (2.02)

Year in School***

                Freshman

                Sophomore

                Junior

                Senior

 

57 (48.31)

25 (21.19)

24 (20.34) 

12 (10.17)

 

75 (24.92)

58 (19.27) 

77 (25.58)

91 (30.23)

 

132 (31.50)

83 (19.81)

101 (24.11) 

103 (24.58)

Marital Status*
                Single

                Married

103 (87.29) 

15 (12.71)

233 (77.41) 

68 (22.59)

336 (80.19) 

83 (19.81)

BMI

22.93 (4.35)

23.64 (3.85)

23.44 (4.01)

BMI Category

                Underweight

                Normal

                Overweight

                Obese

 

23 (17.97) 

79 (61.72)

17 (13.28)

9 (7.03)

 

49 (14.89)

198 (60.18) 

63 (19.15)

19 (5.78)

 

113 (22.69) 

277 (55.62)

80 (16.06)

28 (5.662)

100% Fruit Juice Consumption

                Less than once per day

                Once per day or greater

 

117 (91.41) 

11 (8.59)

 

313 (95.14) 

163 (4.86)

 

471 (94.58) 

27 (5.42)

Fruit Consumption*

                Less than once per day

                Once per day or greater

 

92 (71.88) 

36 (28.13)

 

267 (81.16) 

62 (18.84)

 

400 (80.32) 

98 (19.68)

Bean Consumption

                Less than once per day

                Once per day or greater

 

119 (92.97) 

9 (7.03)

 

311 (94.53)

18 (5.47)

 

471 (94.58) 

27 (5.42)

Green Vegetable Consumption

                Less than once per day

                Once per day or greater

 

109 (85.16) 

19 (14.84)

 

279 (84.80)

50 (15.20)

 

429 (86.14) 

69 (13.86)

Orange Vegetable Consumption

              Less than once per day

             Once per day or greater

 

112 (87.50)

16 (12.50)

 

294 (89.36) 

35 (10.64)

 

447 (89.76)

51 (10.24)

Other Vegetable Consumption

                Less than once per day

                Once per day or greater

 

95 (74.22) 

33 (25.78)

 

270 (82.07) 

59 (17.93)

 

406 (81.53) 

92 (18.47)

Frequency of Eating Out

                Never

                Once a week

                2-3 times per week

           4 or more times per week

 

38 (31.93) 

50 (42.02)

23 (19.33)

8 (6.72) 

 

63 (20.79)

136 (44.88)

87 (28.71)

17 (5.61)

 

101 (23.93)

186 (44.08)

110 (26.07)

25 (5.92)

Meets PA Recommendations

                No

                Yes

 

60 (46.88) 

68 (53.13)

 

162 (49.24) 

167 (50.76)

 

263 (52.81)

235 (47.19)

 

PA= Physical Activity, BMI= Body Mass Index
*indicates p<.05, **indicates p < .01, ***indicates p < .001

Table 4. Adjusted Effects Associated with Monthly Binge TV Watching 

Variable

Odds Ratio* 

Confidence Interval

p-value

Gender

            Male

            Female

 

Ref.

1.68

 

 

1.06-2.67

0.027

Year in School

            Freshman

            Sophomore

            Junior

            Senior

 

Ref.

2.17

3.14

7.54 

 

 

1.18-3.99

1.71-5.48

3.64-15.61 

<0.001

Fruit Consumption

            Less than once per day

            Once per day or greater

 

Ref.

0.43

 

 

0.25-0.72

0.001

*Adjusted for other variables (gender, year in school, fruit consumption) in the model 

Young adults who reported consuming fruit once per day or more had lower odds of being monthly binge TV watchers compared to those who reported consuming fruit less than once per day. Several studies established an inverse relationship between TV viewing and fruit consumption in adults (Hu et al., 2001; Hu et al., 2003; Panagiotakos et al., 2008); our study found similar results with monthly binge watching. There were no two-way interactions significantly related to monthly binge TV watching.

When examining only those who defined binging as watching between two to six hours of TV, a separate analysis yielded similar results. Females had higher odds of being monthly binge watchers compared to males (aOR: 1.65, CI: 1.01-2.67); upper classman had higher odds of being monthly binge TV watchers compared to freshman (sophomore versus freshman aOR: 2.06, CI: 1.09-3.91; junior versus freshman OR: 2.73, CI: 1.46-5.10; senior versus freshman aOR: 7.74, CI: 3.51-17.10), and those who reported consuming fruit once per day or more had lower odds of being monthly binge TV watchers compared to those who reported consuming fruit less than once per day (data not shown).

This study should be evaluated in light of its limitations and strengths. These data are subjected to the types of biases inherent with cross-sectional and self-reported data. Yet, many underreport perceived negative behaviors, including binge TV watching, so if this bias is present the magnitude of the relationships observed may be even larger in reality. The strengths of the study include a randomized sample design with a high percentage of male participants, where other self-selecting participation studies have seen lower rates of participation among males (Galea and Tracy, 2007).

The results of this exploratory study are an important first step in highlighting young adults’ reports of a newer media phenomenon and identifying important correlates between binge TV watching and young adult health behaviors. While the results from this study are not causal in nature, it is important to note that other research has identified that individuals have difficulty curbing their binge watching habits (de Feijter et al., 2016). Young adults are a particularly high-risk group of interest in this phenomenon because of their unmonitored time spent consuming media and because habits formed during young adulthood track into adulthood (Kvaavik et al., 2005; Steptoe et al., 2002). Additionally, these results identify the importance of reducing sedentary time activities among young adults, including binge TV watching, in order to prevent chronic disease in the future.

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Published: 14 July 2017

Reviewed By : Dr. Dayeon Shin.Dr. Nieves González Gómez.

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