The prevalence of adult overweight and obesity has increased to 68% in the United States (9). One contributor to weight gain and obesity may be the increased amount of time spent in sedentary behaviors. Both sedentary leisure time pursuits like watching television (TV) (21) and seated occupations (14,27) may be contributing to the high obesity prevalence. TV viewing has increased dramatically since 1965, making it the most prominent leisure time activity in the United States (23,24). American adults spend almost 38 h·wk−1 watching TV (21).
Cross-sectional studies have demonstrated that TV viewing is linked to weight status in children (11) and adults (10,29). This sedentary leisure time activity is hypothesized to influence weight status and the risks of chronic diseases by reducing energy expenditure (4,12) and increasing energy intake (15,29). The time spent engaging in TV watching may displace time spent in other activities that require greater energy expenditure such as moderate- to vigorous-intensity leisure activities (3,4,26) and other light-intensity activities (12). TV viewing may result in increased dietary intake through prompting and distraction (29). In intervention studies, reducing TV viewing has decreased sedentary behaviors and energy intake (7) and increased moderate-intensity physical activity in children and adolescents (6). In adults, restricting TV viewing resulted in an increase in estimated total daily energy expenditure and a decrease in sedentary time but no change in time spent in light activity or total physical activity (22). Because of the large amount of TV most Americans watch and their reluctance to permanently give up screen time, the long-term sustainability of reducing TV viewing is doubtful (8). An alternative to asking individuals to give up their screen time is to convert sedentary TV time into active TV time.
Encouraging adults to exercise during their leisure time is one approach to counter the obesity epidemic, but getting adults to maintain their increased levels of physical activity continues to be challenging (16). Small changes in physical activity behaviors may be a method for increasing daily physical activity in sedentary individuals (2,13,18,25). Incorporating physical activity into a traditionally sedentary leisure time activity (TV viewing) may be a method to increase energy expenditure and prevent weight gain. Encouraging a small behavior change by having individuals step in place during TV commercials (TV commercial stepping) could be one strategy to modify sedentary TV viewing. A former president of the American Dietetic Association has advocated this approach (Jane White, personal communication, March 31, 2009); however, no research examining the energy cost that results from adults changing their sedentary TV watching behaviors to active behaviors (stepping in place during commercials) has been conducted. Before this strategy can be tested as an effective method to reduce sedentary behavior and increase physical activity in an intervention, it must be determined whether this activity substantially increases the energy expenditure of watching TV. We hypothesize that modifying TV watching behaviors by stepping in place during commercial breaks will enable individuals to increase their energy expenditure and physical activity.
Therefore, the objectives of this two-part laboratory-based pilot study were 1) to evaluate the energy cost of stepping in place at a self-selected pace compared with the energy cost at rest (lying in a reclined position), sitting, standing, and walking at 3.0 mph on a treadmill (a moderate-intensity physical activity) and 2) to evaluate the energy cost of 1 h’s worth of TV commercial stepping in comparison with 1 h of TV viewing while seated. During the 1 h of TV commercial stepping, the number of steps taken and total physical activity time were also evaluated.
Twenty-three volunteers (11 males and 12 females) between 18 and 65 yr and across a wide range of body mass indexes (BMI) (19–37 kg·m−2, average = 27 kg·m−2) were recruited from the University of Tennessee and the surrounding community. Participants for this study were recruited by word of mouth and posted flyers. The Physical Activity Readiness Questionnaire was used to screen out individuals with contraindications to exercise. Participants did not regularly participate in exercise. Participants were excluded if they reported not being able to walk a quarter of a mile without difficulty or taking any medication that would influence metabolic rate. Participants were asked to arrive in the morning after 10 h of fasting and having refrained from exercise for at least 12 h. Participants were asked to read and sign an informed consent, which was approved by the University of Tennessee Institutional Review Board, before taking part in the study.
Participants arrived at the Applied Physiology Laboratory between the hours of 6 and 11 a.m. dressed in comfortable clothing and shoes. Their height and weight were measured (in light clothing, without shoes) with a wall-mounted stadiometer and a Tanita bioelectrical impedance analyzer (model BC-418; Tokyo, Japan), respectively. BMI was calculated by dividing weight (kg) by height (m) squared. Percent body fat was determined using the Tanita BC-418 bioelectrical impedance analyzer. Using a Gulick spring-loaded tape measure (Patterson Medical, Bolingbrook, IL), waist circumference was measured to the nearest 0.1 cm over bare skin at the narrowest portion of the torso (above the umbilicus and below the xiphoid process). Hip measurements were taken at the maximal circumference of the buttocks, above the gluteal fold.
Part 1: energy cost of stepping in place compared with other activities
Energy expenditure was measured using a TrueMax 2400 metabolic measurement system (Parvo Medics, Salt Lake City, UT) (1). In preparation for the resting metabolic rate (RMR) measurement, participants lay awake and motionless in a reclined position for 5 min in a quiet, dimly lit room. While still lying in a reclined position, participants were fitted with a face mask used for indirect calorimetry metabolic measurements. They breathed through this face mask for the next 30 min, during which time their expired air was analyzed and their RMR was measured. The last 10 min of the measurement period was used to determine RMR.
After a 5-min break, the participants were again fitted with the face mask to measure the energy expenditure. Participants then completed a protocol that involved sitting, standing, stepping in place, and treadmill walking at 3.0 mph. Each stage lasted 5 min, and there was a 1-min transition period between stages. When sitting in a standard office chair, subjects sat with their feet on the floor and their ankles, knees, and hips at right angles. They sat with relaxed arms and their hands rested in their lap. When standing, the subjects stood facing forward, feet shoulder-width apart, with their arms hanging relaxed by their sides. For the stepping-in-place condition, participants were instructed to stand and step in place continuously for the duration of that 5-min condition. Participants stepped in place at a self-selected “moderate pace” (e.g., 100–120 steps per minute), with each foot stepping up off the ground about 15–20 cm as demonstrated by the investigator. Before the data collection, participants were given the opportunity to practice an appropriate stepping-in-place technique. Finally, participants performed treadmill walking at 3 mph. All participants completed the four conditions in the same order (sitting, standing, stepping in place, and walking at 3.0 mph on the treadmill). The metabolic cart measured the energy cost of each condition. The researcher counted actual steps with a hand tally counter during the stepping-in-place and 3.0-mph–walk conditions. In each condition, the first 3 min were allotted for the attainment of a steady state. Metabolic data from minutes 4 and 5 were averaged and used for subsequent analysis.
Part 2: energy cost and steps during 1 h of TV commercial stepping
After completing the four activity conditions, participants were given the opportunity to remove the face mask, rest for a period of 5 min, and take a drink of water. Participants were refitted with the face mask before the start of watching 2 h’s worth of video-recorded TV programming with commercials. During 1 h of programming, participants remained seated for the entire hour of programming. They sat in a standard office chair, with their feet on the floor and their ankles, knees, and hips at right angles. They sat with arms relaxed and hands resting on their lap. During the other hour of TV watching, participants engaged in TV commercial stepping. Participants were instructed to rise from their chair and to step in place at a self-selected moderate pace for the duration of each commercial break. When the regular TV program resumed, participants returned to their seated position until the next commercial break. The order of the two TV watching conditions (seated TV and TV commercial stepping) was counterbalanced. There was a 5-min break between each hour of TV viewing to allow participants to remove the face mask and return to RMR. Energy expenditure was measured during the entire 60 min of both seated TV and TV commercial stepping. The investigator counted the number of steps taken during the hour of TV commercial stepping using a hand tally counter. Participants were observed during all conditions to ensure compliance with the study protocol.
SPSS version 17.0.0 for Windows (SPSS, Inc., Chicago, IL) was used for statistical analysis. Height, weight, BMI, body fat percentage, hip and waist circumference, age, and energy expenditure were calculated for each individual and expressed as mean ± SD. One-way ANOVAs tested the effect of BMI category (normal weight, overweight, obese) on energy cost of each condition and again to determine whether there were differences in actual steps of each ambulatory condition among the BMI categories. To compare the differences in energy cost, repeated-measures ANOVAs were used. To compare the differences in actual steps between 5 min of stepping in place and 5 min of walking at 3.0 mph, paired-sample t-tests were used. For all statistical analyses, an α level of 0.05 was used to show significant differences, and all values were shown as mean ± SD.
Twenty-three healthy adults (11 men and 12 women) aged 21–48 yr ranging from normal weight to obese participated in this study. Their physical characteristics are shown in Table 1. Nine adults were of normal weight (BMI = 19–24.9 kg·m−2), 10 were overweight (BMI = 25–29.9 kg·m−2), and four were obese (BMI > 30 kg·m−2). There were significant differences among groups for all indicators of adiposity (body weight, BMI, waist circumference, and hip circumference).
Part 1: energy cost of stepping in place compared with other activities
When expressing energy cost as kilocalories per hour, there was a significant BMI group × activity interaction (P < 0.001) (Fig. 1, top). When at rest (P = 0.037) and while sitting (P = 0.037), the obese group expended a significantly greater number of total calories per minute than the normal-weight group. Likewise, the obese group expended more calories per minute than the normal-weight and overweight categories during standing (P = 0.003 and 0.026), stepping in place (P < 0.001 and 0.016), and walking at 3 mph on the treadmill (P < 0.001 and P < 0.001). The normal-weight and overweight categories did not differ from one another for any activity. All activities differed in energy cost except for the reclining rest and seated conditions (P < 0.001). The energy cost of treadmill walking at 3.0 mph (304.3 ± 71.5 kcal·h−1) was greater than that of stepping in place (257.7 ± 76.1 kcal·h−1) (P = 0.006). The energy cost of stepping in place was significantly greater (P < 0.001) than that of standing (94.0 ± 22.3 kcal·h−1), and the energy cost of standing was greater than that of seated rest (P < 0.001) (89.4 ± 17.9 kcal·h−1) or reclining rest (P < 0.001) (78.9 ± 15.5 kcal·h−1).
When the energy cost was expressed as kilocalories per kilogram per hour, there was no longer an effect of BMI category on energy cost (P = 0.058) (Fig. 1, bottom). However, there were still significant differences between all of the activities (P < 0.05), except between reclining and sitting rest (P = 0.21). The energy cost of treadmill walking at 3.0 mph (3.65 ± 0.32 kcal·kg−1·h−1) was greater than that of stepping in place (3.14 ± 0.53 kcal·kg−1·h−1) (P < 0.001). The energy cost of stepping in place was significantly greater (P < 0.001) than that of standing (1.13 ± 0.13 kcal·kg−1·h−1), and the energy cost of standing was greater than that of sitting (P = 0.008) (1.02 ± 0.17 kcal·kg−1·h−1) or rest (P < 0.001) (0.95 ± 0.14 kcal·kg−1·h−1). Stepping in place (3.14 ± 0.53 METs) was classified as a moderate-intensity activity (3–5 METs).
Steps taken while stepping in place versus treadmill walking at 3 mph
The obese participants took fewer steps during the 5 min of stepping in place than the other two groups (normal weight = 542 ± 50, overweight = 547 ± 80, obese = 445 ± 81) (P = 0.041). The groups did not differ in the number of steps taken during treadmill walking at 3 mph (normal weight = 564 ± 22, overweight = 562 ± 45, obese = 552 ± 36). During 5 min of stepping in place, participants accumulated an average of 528 ± 77 steps (106 steps per minute), compared with 561 ± 35 steps (112 steps per minute) from treadmill walking at 3 mph (P = 0.022).
Part 2: energy cost of 1 h of TV commercial stepping
When the energy cost was expressed as kilocalories per hour, there was a significant BMI group × activity interaction (Fig. 2, top). The obese group expended more calories than the normal-weight (P = 0.001) and overweight (P = 0.01) groups during 60 min of TV commercial stepping. The normal-weight and overweight groups did not differ from one another (P = 0.58). As expected, the total number of calories expended during 60 min of TV commercial stepping (148 ± 40 kcal·h−1) was greater than the total number of calories expended during 60 min of seated TV viewing (81 ± 19 kcal·h−1) (P < 0.001).
When energy cost was expressed as kilocalories per kilogram per hour, there was no interaction between BMI group and activity on energy cost (P = 0.116) (Fig. 2, bottom). There was also no overall effect of BMI (P = 0.429). However, the main effect of “activity” remained significant (P = 0.001). The energy cost per kilogram was greater for 60 min of TV commercial stepping (1.77 ± 0.27 kcal·kg−1·h−1) than for 60 min of seated TV viewing (0.97 ± 0.13 kcal·kg−1·h−1).
Steps taken during 1 h of TV commercial stepping
During the 60 min of TV commercial stepping, subjects were physically active for an average of 21 ± 2 min, and they accumulated 2111 ± 253 steps (103 steps per minute) during commercial breaks. Subjects in all BMI categories took a similar number of steps (P = 0.98) while performing TV commercial stepping, during the 60 min of TV programming (normal weight = 2125 ± 244 steps, overweight = 2098 ± 319 steps, obese = 2109 ± 72 steps).
The present study quantified the difference in energy cost and steps between sedentary TV viewing and active TV viewing achieved with TV commercial stepping. Participants in all BMI categories expended more energy when engaged in TV commercial stepping than while watching TV in the seated position. The energy cost of TV commercial stepping was 67 kcal·h−1 or 55% greater compared with seated TV viewing. During 1 h of TV commercial stepping, participants were physically active for 41% of the time and took approximately 2000 steps (similar to the quantity accumulated in 1 mile of walking at 3.0 mph). We suggest that TV commercial stepping results in substantial increases in energy expenditure, steps, and physical activity as compared with usual TV watching. Given the large number of hours American adults watch TV, we suggest that TV commercial stepping is one potential approach for reducing sedentary behavior and increasing physical activity.
According to the American Time Use Survey conducted by the US Bureau of Labor Statistics, TV watching accounts for 2.8 h·d−1 or approximately 55% of available leisure time (28). In 2009, the results of the Video Consumer Mapping Study conducted by Ball State University’s Center for Media Design reported that Americans watch 5.9 h·d−1 of TV and view 72 min·d−1 of commercials (5). According to the 2010 Nielsen Three Screen Report, Americans currently spend almost 38 h·wk−1 (about 5.4 h·d−1) watching TV (21). A standard half-hour TV show contains about 8–12 min of commercials (5). Thus, for the average adult who watches 3 to 5 h·d−1 of TV (5,21,28), this could represent 48 to 120 min of commercials per day. This represents periods during which individuals are not “watching” their program and could be encouraged and cued to do some alternative behavior (physical activity), which would increase the energy cost of watching TV. Given the poor adherence/maintenance to many physical activity interventions, the use of “cueing” to prompt TV watchers to be active during commercials may be an instrumental component for ensuring greater success of this strategy in the future.
The conversion of sedentary screen time to active time could be an effective approach to promote physical activity (17). On the basis of these findings, we propose that the energy expenditure of TV commercial stepping at a pace of approximately 100 steps per minute during 1.5 h of TV programming would be approximately equivalent to 30 min of continuous walking at 3 mph. Taking the energy cost data from the present study, we estimate that the average number of calories (165 kcal) for 1.5 h of TV viewing with TV commercial stepping (∼38 min of actual stepping) is roughly equivalent to the number of calories expended during 30 min of walking at a pace of 3 mph (150 kcal). These findings suggest that people can expend as much energy through 1.5 h of TV commercial stepping as that expended if they performed 30 min of continuous walking. Over time, this could have an important effect on energy balance (assuming that “compensation,” i.e., reduced activity during other times or increased calorie intake, does not cancel out the effect). A daily positive energy balance of 15–50 kcal·d−1 is enough to result in creeping weight gain in adults (14,19,20). It is estimated that individuals who engage in TV commercial stepping for 1.5 h would expend an additional 100 kcal·d−1, which could be helpful in restoring energy balance.
The current study has both strengths and weaknesses. We used indirect calorimetry, which is considered a “gold standard” for assessing energy expenditure in humans. Furthermore, participants in this study performed each activity in a controlled laboratory setting, so the results should be reproducible. However, several limitations should also be noted. In the 5-min sitting condition and 60 min of seated TV viewing, participants sat in an office chair, in an upright position, with their hips, knees, and ankles bent at 90 degrees so their feet rested flat on the floor and hands rested on their lap. If participants were permitted to sit with a self-selected posture, alter their sitting position, or fidget, the energy cost of these sitting conditions might have been different. In a real-life situation, when watching TV for a 60-min period, most individuals do not remain in the same posture for the entire time. Also, not all TV programming contains the same number or length of commercials, and individuals with digital video recorder technology have the ability to fast-forward through commercial breaks. Each 1-h segment of TV programming used in the present study consisted of two 30-min prime-time programs. Lastly, it is necessary to clarify that the findings of our study only apply to US adults.
In conclusion, our data clearly indicate that TV commercial stepping increased energy expenditure to moderate levels, nearly as high as walking at 3.0 mph. During 1 h, the energy cost of intermittent TV commercial stepping was nearly twice that of viewing TV in a seated position. Because adults are spending more time than ever in front of the TV screen and only a small percentage of American adults engage in adequate amounts (30 min·d−1) of physical activity using standard approaches, we believe that modifying TV-viewing behaviors by having adults step in place during commercial breaks could be useful in promoting physical activity. Theoretically, the advantage of TV commercial stepping is that it is a relatively small behavior change that could be achieved by most adults. Moreover, it does not require any reallocation of leisure time, nor does it take any additional time out of the day to perform. However, asking people to adhere to a plan that requires them to perform the same activity repeatedly may result in boredom and could cause people to discontinue. We have to find alternatives for those who have difficulty with the standard approaches. It may be necessary to include some behavioral prompting or incentives to ensure adherence to this behavior change. Nonetheless, by modifying a behavior that is very common in this population and allowing the activity to be performed at home, it could remove some of the barriers that prevent sedentary adults from being physically active. Experimental research investigating this strategy as an intervention is needed before it can be labeled a simple, realistic strategy for increasing physical activity in sedentary adults who watch TV.
No funding was received for this study.
The authors report no conflicts of interest.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Bassett DR Jr, Howley ET, Thompson DL, et al.. Validity of inspiratory and expiratory methods of measuring gas exchange with a computerized system. J Appl Physiol. 2001; 91 (1): 218–24.
2. Boreham CA, Wallace WF, Nevill A. Training effects of accumulated daily stair-climbing exercise in previously sedentary young women. Prev Med. 2000; 30 (4): 277–81.
3. Buchowski MS, Sun M. Energy expenditure
, television viewing and obesity
. Int J Obes Relat Metab Disord. 1996; 20 (3): 236–44.
4. Buckworth J, Nigg C. Physical activity
, exercise, and sedentary behavior
in college students. J Am Coll Health. 2004; 53 (1): 28–34.
5. Council for Research Excellence Web site [Internet]. New York (NY): Council for Research Excellence. Video Consumer Mapping Study: Key Finding Report 2009; [cited 2011 Jan 8]. Available from http://www.researchexcellence.com/vcmstudy.php
6. Epstein LH, Paluch RA, Gordy CC, Dorn J. Decreasing sedentary behaviors in treating pediatric obesity
. Arch Pediatr Adolesc Med. 2000; 154 (3): 220–6.
7. Epstein LH, Roemmich JN, Paluch RA, Raynor HA. Influence of changes in sedentary behavior
on energy and macronutrient intake in youth. Am J Clin Nutr. 2005; 81 (2): 361–6.
8. Faith MS, Berman N, Heo M, et al.. Effects of contingent television on physical activity
and television viewing in obese children. Pediatrics. 2001; 107 (5): 1043–8.
9. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity
among US adults, 1999–2008. JAMA. 2010; 303 (3): 235–41.
10. Foster JA, Gore SA, West DS. Altering TV viewing habits: an unexplored strategy for adult obesity
intervention? Am J Health Behav. 2006; 30 (1): 3–14.
11. Gortmaker SL, Must A, Sobol AM, Peterson K, Colditz GA, Dietz WH. Television viewing as a cause of increasing obesity
among children in the United States, 1986–1990. Arch Pediatr Adolesc Med. 1996; 150 (4): 356–62.
12. Healy GN, Dunstan DW, Salmon J, et al.. Objectively measured light-intensity physical activity
is independently associated with 2-h plasma glucose. Diabetes Care. 2007; 30 (6): 1384–9.
13. Hill J. Can a small-changes approach help address the obesity
epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. Am J Clin Nutr. 2009; 89 (2): 477–84.
14. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity
and the environment: where do we go from here? Science. 2003; 299 (5608): 853–5.
15. Jeffery RW, French SA. Epidemic obesity
in the United States: are fast foods and television viewing contributing? Am J Public Health. 1998; 88 (2): 277–80.
16. King AC, Kiernan M, Oman RF, Kraemer HC, Hull M, Ahn D. Can we identify who will adhere to long-term physical activity
? Signal detection methodology as a potential aid to clinical decision making. Health Psychol. 1997; 16 (4): 380–9.
17. Lanningham-Foster L, Jensen TB, Foster RC, et al.. Energy expenditure
of sedentary screen time compared with active screen time for children. Pediatrics. 2006; 118 (6): e1831–5.
18. Levine JA, Miller JM. The energy expenditure
of using a “walk-and-work” desk for office workers with obesity
. Br J Sports Med. 2007; 41 (9): 558–61.
19. Levine JA, Vander Weg MW, Hill JO, Klesges RC. Non-exercise activity thermogenesis: the crouching tiger hidden dragon of societal weight gain. Arterioscler Thromb Vasc Biol. 2006; 26 (4): 729–36.
20. Levitsky DA, Halbmaier CA, Mrdjenovic G. The freshman weight gain: a model for the study of the epidemic of obesity
. Int J Obes Relat Metab Disord. 2004; 28 (11): 1435–42.
21. Nielsen Company Web site [Internet]. New York (NY): The Nielsen Company. Three Screen Report Q1 2010; [cited 2011 Jan 1]. Available from: http://www.nielsen.com/us/en/insights/reports-downloads/2010/three-screen-report-q1-2010.html
22. Otten JJ, Jones KE, Littenberg B, Harvey-Berino J. Effects of television viewing reduction on energy intake and expenditure in overweight and obese adults: a randomized controlled trial. Arch Intern Med. 2009; 169 (22): 2109–15.
23. Robinson J, Godbey G. Busyness as usual. Soc Res. 2005; 72 (2): 407–26.
24. Robinson J, Godbey G. Time in our hands: most people in industrialized societies feel time-pressured. The problem isn’t how much time we have, but rather how we use it. Futurist. 2005; 39 (5): 18–22.
25. Rodearmel SJ, Wyatt HR, Barry MJ, et al.. A family-based approach to preventing excessive weight gain. Obesity
(Silver Spring). 2006; 14 (8): 1392–401.
26. Sugiyama T, Healy GN, Dunstan DW, Salmon J, Owen N. Is television viewing time a marker of a broader pattern of sedentary behavior
? Ann Behav Med. 2008; 35 (2): 245–50.
27. Trust for America’s Health Web site [Internet]. Washington (DC): Trust for America’s Health. F as in fat: how obesity
policies are failing in America 2009; [cited 2010 Dec 19]. Available from: http://healthyamericans.org/reports/obesity2009/
28. US Department of Labor, Bureau of Labor Statistics Web site [Internet]. Washington (DC): US Department of Labor, Bureau of Labor Statistics. America Time Use Survey-2010 Results; [cited 2011 July 1]. Available from: http://www.bls.gov/news.release/pdf/atus.pdf
29. Williams DM, Raynor HA, Ciccolo JT. A review of TV viewing and its association with health outcomes in adults. Am J Lifestyle Med. 2008; 2 (3): 250–59.