GAMES FOR HEALTH JOURNAL: Research, Development, and Clinical Applications Volume 4, Number 4, 2015 ª Mary Ann Liebert, Inc. DOI: 10.1089/g4h.2014.0126
Active Gaming Among High School Students—United States, 2010 MinKyoung Song, PhD, RN, FNP-BC,1–3 Dianna D. Carroll, PhD,4,5 Sarah M. Lee, PhD,6 and Janet E. Fulton, PhD 3
Abstract
Objectives: Our study is the first to describe the prevalence and correlates (demographics, body mass index [BMI], sedentary behaviors, and physical activity) of high school youth who report active videogame playing (active gaming) in a U.S. representative sample. Materials and Methods: The National Youth Physical Activity and Nutrition Study of 2010 provided data for this study. Active gaming was assessed as the number of days in the 7 days prior to the survey that students in grades 9–12 (14–18 years of age) reported participating in active videogames (e.g., ‘‘Wii Fit’’ [Nintendo, Kyoto, Japan], ‘‘Dance Dance Revolution’’ [Konami, Osaka, Japan]). Students reporting q1 days were classified as active gamers. Logistic regression was used to examine the association among active gaming and demographic characteristics, BMI, sedentary behaviors, and physical activity. Results: Among 9125 U.S. high school students in grades 9–12 surveyed, 39.9 percent (95 percent confidence interval = 37.9 percent, 42.0 percent) reported active gaming. Adjusting for covariates, the following characteristics were positively associated (P < 0.05) with active gaming: being in 9th and 10th grades compared with being in 12th grade; being of black, non-Hispanic race/ethnicity; being overweight or obese; watching DVDs > 0 hours/day; watching TV > 0 hours/day; and meeting guidelines for aerobic and muscle-strengthening physical activity. Conclusions: Four out of 10 U.S. high school students report participating in active gaming. Active gamers tend to spend more time watching DVDs or TV, meet guidelines for physical activity, and/or be overweight or obese compared with nonactive gamers. These findings may serve to provide a baseline to track active gaming in U.S. youth and inform interventions that target sedentary behaviors and/or physical activity.
Introduction
T
here has been increasing concern about the excessive amount of time children and adolescents spend in sedentary behaviors.1 On average, American children (10–16 years of age) are sedentary for more than 10 hours/day.2 This estimate includes about 4.5 hours at school, with much of the remaining time spent in screen-based sedentary activities such as watching TV, playing videogames, and using computers. A recent report indicated that there has been a significant increase over the last decade in the time children spend in screen-based sedentary activities: currently about 7½ hours on a typical day, compared with approximately 6
hours in 1999.3 The American Academy of Pediatrics recommends youth not exceed 2 hours of ‘‘quality screen time’’ (screen time that has some educational or developmental value) per day,4 yet more than half of U.S. youth exceed the screen-time recommendation.5 This finding is concerning, as excessive sedentary time is associated with having greater fat mass as well as being overweight or obese among youth.6–9 Not all screen time is necessarily sedentary. ‘‘Active gaming’’ is considered nonsedentary (or active) screen time.10 Active gaming (examples include ‘‘Wii Fit’’[Nintendo, Kyoto, Japan] and ‘‘Dance Dance Revolution’’ [Konami, Osaka, Japan]11) was originally created as an entertainment product, but it is differentiated from other videogaming
1
School of Nursing, University of Michigan, Ann Arbor, Michigan. Epidemic Intelligence Service and Divisions of 3Nutrition, Physical Activity, and Obesity, 4Human Development and Disability, and 6 Population Health, Centers for Disease Control and Prevention, Atlanta, Georgia. 5 Commissioned Corps, U.S. Public Health Service, Atlanta, Georgia. The conclusions in this report are the authors and do not represent the official position or views of the Centers for Disease Control and Prevention. 2
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entertainment because it combines screen time with physical movement.12 Energy expenditure during active gaming averages about 3.2 metabolic equivalents, equivalent to ‘‘moderate-intensity’’ physical activities such as brisk walking.13–16 Thus, if future research shows that youths’ participation in active gaming replaces sedentary screen time and does not come at the expense of other forms of physical activity, it may present a new pathway for increasing energy expenditure. Although little is known about how many U.S. youth participate in active gaming, three studies examined prevalence and correlates of active gaming in youth in non-U.S. populations.17–19 A Canadian study reported that approximately 25 percent of 10th and 11th graders engaged in active gaming (based on responses to the question ‘‘Do you play active videogames?’’) and that active gamers were more likely to be girls, to also play nonactive videogames, to watch q2 hours of TV/day, and to be concerned about weight.17 There have also been two surveys conducted with Dutch adolescents 12–16 years of age: One was conducted via a survey where the source population was from a Dutch Internet panel, and the other was via a school-based survey. The Internetbased study found that regular active gamers were younger than nonactive gamers.18 In the school-based survey, approximately 43 percent of adolescents participated in active gaming q1 hour/week, and rates of active gaming were higher in youth attending prevocational levels of schooling compared with those at higher levels.19 This study used a nationally representative sample to help gain understanding of the current status of active gaming among U.S. youth. The two primary objectives of this study were to examine the prevalence of high school students participating in active gaming and the directly associated correlates (demographics, body mass index [BMI], sedentary behaviors, and physical activity) of active gamers. This information will provide baseline data to monitor active gaming among U.S. youth. In addition, because active gaming can potentially replace sedentary screen time with active behaviors, this information may be useful for designing targeted interventions that use active gaming as a strategy to reduce passive screen time and/or increase physical activity. Materials and Methods Survey design
Data from the National Youth Physical Activity and Nutrition Study (NYPANS), conducted in Spring 2010, were used in this study. NYPANS includes a school-based survey (120 items in total, which takes about 45 minutes to complete [available online20]) on behaviors and behavioral determinants related to nutrition and physical activity, as well as measurements of height and weight. Items developed for NYPANS were subjected to cognitive testing, which resulted in the revision or deletion of problematic questions. Several of the NYPANS questions were based on questions from the Youth Risk Behavior Survey; psychometrics have been published elsewhere.21 The study used a three-stage cluster sample design that oversampled African American/black and Hispanic/Latino students to obtain a nationally representative sample of public and private school students in grades 9–12 in the 50 states and the District of Columbia. Specifically, the target population consisted of all public, Catholic, and other private school students in grades 9–12. In each
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participating school, one or two classrooms in each grade from either a required subject (e.g., English) or a required period (e.g., second period) were randomly selected. Lastly, all students in selected classes were eligible to participate. During a regular class session, students voluntarily completed an anonymous, self-administered questionnaire. Additionally, each student’s height and weight were measured by trained study personnel using standard protocol. School response rate was 82 percent; student response rate was 88 percent, and the overall response rate was 73 percent. The Institutional Review Board of the study contractor approved the NYPANS protocol. More detailed information about the study methods has been published previously.22 Participants
Data from 11,429 NYPANS students were available for analyses. We excluded students from the analyses with missing data on active gaming (n = 668), physical activity and sedentary behaviors (n = 253), or BMI or demographic characteristics (sex, grade, and/or race/ethnicity) (n = 1,383). The final analytical sample included 9,125 U.S. high school students in grades 9–12. Measurements Active gaming. The NYPANS survey includes a question to assess types of physical activities: ‘‘For each of the following activities, please mark on how many of the past 7 days you did this activity. Think about activities you did before and after school, in the evenings, and on the weekends, by yourself or with others. Do not include PE [physical education] or gym class. Include activities you did just for fun or in competition.’’ Response options ranged from 0 to 7 days for each activity. Active gaming was listed as one of the 35 physical activities. We classified students reporting q1 day/week as active gamers. Physical activity and sedentary behaviors. Several physical activity variables—sport team participation, participation in PE class, and meeting aerobic and musclestrengthening physical activity guidelines—were also included. Sedentary behaviors, including watching DVDs and other videos and watching TV, were obtained from the questionnaire. (The questionnaire is available online at www.cdc .gov/healthyyouth/yrbs/nypans.htm). Sports team participation was grouped into four categories: no team, one team, two teams, and three or more teams. PE class participation was grouped into three categories: per week, 0 days, 1–4 days, and 5 days. Students who reported participating in q60 minutes of aerobic physical activity/day during the past 7 days were characterized as meeting the aerobic physical activity guideline. Students who reported participating in q3 days of muscle-strengthening activities per week were characterized as meeting the musclestrengthening physical activity guideline.23 Sedentary behavior was grouped into three categories: 0 hours/day, > 0 and p2 hours/day, and > 2 hours/day (exceeding daily restricted hours). The cutoff for sedentary behavior reflected the American Academy of Pediatrics screen-time guideline.4 BMI. BMI (weight [in kg]/height2 [in m2]) was calculated using height and weight measurements. Students were
ACTIVE GAMING AMONG U.S. HIGH SCHOOL STUDENTS
Table 1. Weighted Sample Characteristics: National Youth Physical Activity and Nutrition Study, 2010 Characteristic
n
Percentage 95 percent CI
Sex Male Female
4567 4558
50.6 49.4
48.9, 52.2 47.8, 51.1
Grade 9 10 11 12
2345 2303 2233 2244
28.5 25.4 23.8 22.3
27.2, 23.9, 22.7, 21.1,
29.9 26.8 25.0 23.6
Race/ethnicity White, non-Hispanic 3694 Black, non-Hispanic 1961 Hispanic 2796 Other, non-Hispanic 674
58.7 13.7 18.9 8.7
52.4, 10.6, 14.8, 7.2,
64.6 17.6 23.9 10.4
5690
63.4
61.0, 65.7
1673 1762
17.6 19.0
16.6, 18.7 17.3, 20.9
Sports team participation None 3699 1 team 2499 2 teams 1722 3 or more teams 1205
38.7 26.5 20.2 14.7
35.7, 24.8, 18.3, 12.5,
BMIa Underweight or normal weight Overweight Obese
41.8 28.2 22.2 17.2
Physical education class participation 0 days 4056 45.4 1–4 days 1955 17.5 5 days 3114 37.1
39.3, 51.6 12.9, 23.4 31.1, 43.5
Meeting aerobic physical activity guidelineb Yes 1310 15.1 No 7815 85.0
13.4, 17.0 83.1, 86.6
Meeting muscle-strengthening guidelinec Yes 4593 50.8 No 4532 49.2
48.3, 53.2 46.8, 51.7
Watching DVDs or videos 0 hours/day 1980 > 0 and p2 4904 hours/day > 2 hours/day 2241
23.6 56.2
21.9, 25.3 54.3, 58.1
20.3
18.0, 22.8
863 5309
10.1 61.9
8.9, 11.5 58.7, 64.9
2953
28.0
25.5, 30.7
Active gaming participation Yes 3704 No 5421
39.9 60.1
37.9, 42.0 58.0, 62.1
Watching TV 0 hours/day > 0 and p2 hours/day > 2 hours/day
Total percentages may not add to 100% because of rounding. a Body mass index (BMI) estimates were calculated from measured weight and height (weight [kg]/height2 [m2]) and classified based on sex- and age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts. b Defined as performing at least 1 hour of aerobic physical activity daily. c Defined as performing muscle-strengthening activities q3 days/ week. CI, confidence interval.
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categorized into three BMI groups (underweight or normal weight [ < 85th percentile], overweight [q85th and < 95th percentile], and obese [q95th percentile]), according to sexand age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts.24 Data analyses
We calculated percentage and 95 percent confidence interval of U.S. high school students who were active gamers and examined the distribution of the reported number of days of active gaming in the 7 days immediately prior to the survey. We also assessed active gaming by demographic characteristics, BMI, sedentary behaviors, and physical activity. To assess associations between select characteristics and active gaming, we used logistic regression analysis to determine unadjusted and multivariable adjusted odds ratios and 95 percent confidence intervals. Adjusted odds ratios simultaneously controlled for demographic characteristics, BMI, and other correlates directly related to active gaming. Statistical significance was determined at P < 0.05. SAS callable SUDAAN (version 10.0.1) software (Research Triangle Institute, Research Triangle Park, NC) was used to account for the complex sample design. To produce nationally representative estimates of youth, sample weights were applied to all analyses to adjust for nonresponse and oversampling of black and Hispanic students. Results
Approximately half of the students were male, about 30 percent were in 9th grade and 25 percent were in 10th grade, 60 percent were non-Hispanic white, and 37 percent were overweight or obese. Also, 40 percent reported no participation in team sports during the past 12 months, and almost half reported no participation in PE during an average week. Approximately 15 percent met the aerobic physical activity guideline, and half of the students met the muscle-strengthening guideline. Approximately 20 percent reported watching DVDs or videos for > 2 hours/day, and 28 percent reported watching TV for > 2 hours/day. Overall, 40 percent of the students reported active gaming in the 7 days immediately prior to taking the survey (Table 1). Figure 1 presents frequency of active gaming. About 14 percent of all students reported active gaming 1 day/week, and nearly 3 percent reported active gaming 7 days/week. The percentage of students reporting active gaming generally decreased as the frequency of active gaming (days/week) increased. Adjusting for all covariates, active gaming was positively associated with 9th and 10th grade versus 12th grade, race/ ethnicity of black, non-Hispanic versus white, non-Hispanic, being overweight or obese versus underweight/normal weight, engaging in any TV or video watching versus none, and meeting aerobic physical activity and muscle-strengthening physical activity guidelines versus not (Table 2). Discussion
Our findings show that 40 percent of U.S. high school students participate in active gaming. This finding is generally consistent with other studies.17,25 In a Canadian study17 active gaming prevalence (25 percent) in 10th and 11th grade
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FIG. 1.
Prevalence of active gaming. Color images available online at www.liebertonline.com/g4h
adolescents was lower than we report (40 percent). The difference might be due to nationality and sampling method (convenience sample from the Montreal area versus U.S. nationally representative sample). A previous study reported active gaming as one of the five most frequently reported activities during the previous 7 days among U.S. youth,25 and although it remains unclear whether all active gaming activity is intense enough to contribute to meeting physical activity guidelines, it does appear that active gaming represents a popular youth pastime that is on average a moderateintensity level of physical activity.13–16 Thus, active gaming should be included when evaluating overall youth aerobic physical activity and considered alongside other activities when planning programs to improve youth physical activity.11,12,26,27 Our data show that non-Hispanic blacks were more likely to participate in active gaming, which is an interesting finding in that another study with the NYPANS showed that overall physical activity levels were lower in non-Hispanic black youth.28 To the best of our knowledge, other examinations of the demographic correlates of active gaming either have not included race/ethnicity variables,29 included nonspecific race/ethnicity variables17–19 (e.g., Caucasian versus non-Caucasian), or were conducted with samples composed of white students, predominantly.15 Further investigation with diverse race/ethnicity groups is warranted to determine if active gaming is a promising intervention for specific racial/ethnic groups. Our data further show that students who watch DVDs/ videos or TV were more likely to participate in active gaming. This finding is consistent with another study that reported that students who watched TV or engaged in nonactive videogaming were more likely to be active gamers.17 These findings, however, do not show any causal relationship and/or direction of causality with respect to that association. Given that an association was shown in both studies, we feel further investigation is warranted to see whether active gaming might be a particularly useful tool for those youth who are particularly likely to spend time watching DVDs/ videos or TV—by changing ‘‘passive screen time’’ to ‘‘active screen time.’’30
The current finding that students who met aerobic or muscle-strengthening physical activity guidelines were more likely to be active gamers is consistent with one previous study and inconsistent with other previous studies.10,17,29,31 Wethington et al.10 showed that youth who participate more in vigorous physical activity were more likely to report ‘‘active’’ screen time. However, O’Loughlin et al.17 reported that active gamers were no more likely to meet moderate to vigorous physical activity guideline than nonactive gamers. Recently, Baranowski et al.31 reported no difference in physical activity over a 12-week period when comparing a group of children who received a new videogame console along with two active videogames and a group who received the same console and two inactive videogames. Finally, in a recent study with young adults, Kakinami et al.29 reported that female active gamers reported approximately 45 more minutes/week of moderate-intensity physical activity than female nonactive gamers but were no more likely to meet the physical activity guidelines than nonactive gamers. Pending further investigation to confirm an association between active gaming and meeting physical activity guidelines, our findings raise some questions related to any such association: (1) Do youth who are more physically active participate in higher levels of active gaming? or (2) Does time spent active gaming increase overall physical activity levels, perhaps to the point where some active gamers go from not meeting the guidelines to meeting the guidelines? Laboratory research shows active gaming, on average, represents moderate-intensity activity—similar to walking briskly.32 A recent systematic review of active gaming,11 however, cautions that not all active gaming involves moderate- to vigorous-intensity physical activity. Intensity levels of physical activity during active gaming depend to a large extent on the game played, with a higher intensity resulting from games that include lower-body movement.15,32 Further longitudinal, experimental design studies would help clarify the underlying relationship among participation in active gaming, intensity of physical activity, and contribution of active gaming toward meeting physical activity guidelines.23 The examination of long-term health outcomes of habitual active gaming is still in its infancy. A randomized controlled
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Table 2. Prevalence and Odds Ratios of Active Gaming Participation, National Youth Physical Activity and Nutrition Study, 2010
Characteristic Sex Male Female Grade 9 10 11 12 Race/ethnicityb Black, non-Hispanic Hispanic White, non-Hispanic BMIc Underweight or normal weight Overweight Obese Sports team participation None 1 team 2 teams 3 or more teams Physical education class participation 0 days 1–4 days 5 days Meeting aerobic physical activity guidelined Yes No Meeting muscle-strengthening guidelinee Yes No Watching DVD or videos 0 hours/day > 0 and p2 hours/day > 2 hours/day Watching TV 0 hours/day > 0 and p2 hours/day > 2 hours/day
Odds ratio (95 percent CI)
Active gamers (percent)
Unadjusted
Adjusted a
40.4 39.4
1.04 (0.91, 1.19) 1.00
0.93 (0.82, 1.06) 1.00
46.3 39.7 36.3 35.7
1.56 (1.34, 1.81) 1.19 (1.05, 1.34) 1.03 (0.89, 1.18) 1.00
1.44 (1.24, 1.66) 1.15 (1.01, 1.31) 1.02 (0.88, 1.17) 1.00
47.8 38.4 38.1
1.48 (1.24, 1.78) 1.01 (0.84, 1.22) 1.00
1.32 (1.13, 1.56) 0.94 (0.78, 1.15) 1.00
37.6 43.3 44.5
1.00 1.27 (1.07, 1.52) 1.33 (1.15, 1.55)
1.00 1.22 (1.03, 1.45) 1.34 (1.14, 1.58)
35.9 42.9 41.2 43.1
1.00 1.34 (1.17, 1.55) 1.25 (1.04, 1.50) 1.35 (1.13, 1.62)
1.00 1.33 (1.15, 1.54) 1.23 (1.01, 1.50) 1.26 (1.04, 1.51)
36.9 42.7 42.2
1.00 1.27 (1.06, 1.52) 1.25 (1.05, 1.49)
1.00 1.12 (0.95, 1.32) 1.04 (0.88, 1.24)
45.8 38.8
1.33 (1.12, 1.58) 1.00
1.22 (1.01, 1.46) 1.00
42.9 36.8
1.29 (1.15, 1.44) 1.00
1.23 (1.10, 1.38) 1.00
28.3 41.6 48.6
1.00 1.81 (1.55, 2.10) 2.39 (1.95, 2.93)
1.00 1.74 (1.49, 2.03) 2.44 (1.93, 3.08)
28.6 41.2 41.2
1.00 1.74 (1.36, 2.23) 1.74 (1.32, 2.30)
1.00 1.48 (1.14, 1.92) 1.22 (0.93, 1.60)
Estimates are weighted to account for survey nonresponse and oversampling of certain populations. a Adjusting for demographic characteristics (sex, grade, race/ethnicity), body mass index (BMI), and physical activity and sedentary behaviors (sports team participation, physical education class participation, meeting the aerobic and muscle-strengthening guidelines). b Because the numbers of students from non-Hispanic other and non-Hispanic multiracial groups were too small for meaningful analysis, race/ethnicity is presented only for non-Hispanic white, non-Hispanic black, and Hispanic students (who might be of any race). c BMI estimates were calculated from measured weight and height (weight [kg]/height2 [m2]) and classified based on sex- and age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts. d Defined as performing at least 1 hour of aerobic physical activity daily. e Defined as performing muscle-strengthening activities q3 days per week. CI, confidence interval.
trial with a 24-week follow-up by Maddison et al.33 showed that home-based active gaming intervention had a positive influence on BMI and body composition in 10–14-year-old overweight/obese children. A systematic review reported that active gaming may attenuate weight gain in overweight and obese youth.11 Our finding that overweight and obese youth are more likely to be active gamers than normal or
underweight youth has an interesting implication when combined with the findings of Maddison et al.33 and the systematic review11; there might be value in examining whether encouraging active gaming could be an effective way to reach youth who are the most in need for obesity interventions and/or youth who are already overweight. One longitudinal study currently being conducted by Simons
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et al.34 is examining the impact of a 10-month active gaming intervention on weight gain, BMI, other measures of adiposity, and physical activity/sedentary behaviors in normalweight and obese youth 12–16 years of age. The findings of Simons et al.34 may shed light on the potential contribution of active gaming to prevent obesity among adolescents. Our findings have several public health implications. First, our results might have public health implications regarding current efforts underway aimed at reducing ‘‘screen time.’’ Not all screen time is sedentary. Because our results show an association between active gaming and meeting physical activity guidelines, care should be taken to ensure that initiatives aimed at reducing overall screen time do not have an unintended consequence of reducing physical activity benefits from active gaming.11,35,36 Second, and relatedly, our data suggest or support the idea that encouraging active gaming may be a viable strategy for getting youth to substitute physical activity for sedentary screen time. In fact, Straker et al.37 reported that replacing ‘‘passive’’ videogames with active games led to increases in physical activity and decreases in sedentary time among children. Future research would enable us to explore the potential contribution of active gaming to increase youth energy expenditure. Third, active gaming may be a particularly effective strategy for increasing physical activity in youth who spend time watching DVDs or TV, or who are overweight or obese—as those youth already participate in active gaming at higher rates. These potential benefits, however, come some caveats: It is not yet clear whether and/or how much active gaming reduces passive screen time, and it is also not yet clear whether/how much youth participation in active gaming meaningfully increases energy expenditure or improves BMI/adiposity-related outcomes. It is possible that many youth play active games at low-intensity levels without expending much energy, and it is possible that any effects of increased energy expenditure might be mediated by changes in energy intake. It should be noted here that Maddison et al.33 did find an association between active gaming and reduced BMI without significant changes in self-reported energy intake, but further research that accounts for energy intake is needed to fully understand the direct relationship between active gaming and BMI/adiposity-related outcomes. The present study has several limitations. First, we did not assess the intensity level of physical activity, the duration of participation, or the body part involved during active gaming (e.g., upper or lower extremity). Acquiring more information about some component parts of physical activity, including intensity, duration, and types of body movement, would provide useful information to evaluate active gaming benefits. Second, through the NYPANS we obtained information on active gaming and physical activity through self-reports; thus, the frequency of active gaming might have been underor over-reported. However, at the current time, these data are the best available measure. Third, questions used to assess active gaming in the NYPANS dataset only identified the Wii and ‘‘Dance Dance Revolution’’ as specific active screen time activities and did not list other consoles (e.g., Xbox Kinect [Microsoft, Redmond, WA], PlayStation Move [Sony, Tokyo, Japan]), games, or other active screen-time activities. Thus, we cannot interpret whether they were answering the question with reference to all active videogames or to the Wii and ‘‘Dance Dance Revolution’’ only, and, as a
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result, our findings might be underestimating the prevalence of active gaming. In future active gaming assessments, other consoles or different forms of active screen time need to be included. Fourth, this study relied on self-reported data, which may be influenced by recall bias or social-desirability bias. Finally, this study was a cross-sectional analysis; thus we cannot determine any causal relationships. Nonetheless, the associations presented may prove useful for further research into the potential benefits of active gaming, and ultimately in designing interventions that incorporate active gaming to reduce sedentary behavior. Conclusions
Our findings show 40 percent of U.S. high school students are active gamers, and they tend to meet national physical activity guidelines, despite spending more time watching DVDs or TV and/or being overweight or obese. These baseline data can be used to inform researchers, educators, parents, and decision-makers who are interested in using active gaming as a way to help youth become less sedentary and more physically active. Author Disclosure Statement
No competing financial interests exist. References
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36.
37.
healthykids.ca/active-video-games-position.aspx (accessed December 15, 2012). Physical activity levels of high school students—United States, 2010. MMWR Morb Mortal Wkly Rep 2011; 60: 773–777. Kakinami L, O’Loughlin EK, Dugas EN, et al. The association between exergaming and physical activity in young adults. J Phys Act Health 2014 August 15 [Epub ahead of print]. doi: http://dx.doi.org/10.1123/jpah.2013-0447. Lu AS, Kharrazi H, Gharghabi F, Thompson D. A systematic review of health videogames on childhood obesity prevention and intervention. Games Health J 2013; 2:131– 141. Baranowski T, Abdelsamad D, Baranowski J, et al. Impact of an active video game on healthy children’s physical activity. Pediatrics 2012; 129:e636–e642. Barnett A, Cerin E, Baranowski T. Active video games for youth: A systematic review. J Phys Act Health 2011; 8: 724–737. Maddison R, Foley L, Ni Mhurchu C, et al. Effects of active video games on body composition: A randomized controlled trial. Am J Clin Nutr 2011; 94:156–163. Simons M, Chinapaw MJM, van de Bovenkamp M, et al. Active video games as a tool to prevent excessive weight gain in adolescents: Rationale, design and methods of a randomized controlled trial. BMC Public Health 2014; 14:275. Peng W, Crouse JC, Lin JH. Using active video games for physical activity promotion: A systematic review of the current state of research. Health Educ Behav 2013; 40:171– 192. Physical Activity Guidelines for Americans Midcourse Report Subcommittee of the President’s Council on Fitness, Sports & Nutrition. Physical Activity Guidelines for Americans Midcourse Report: Strategies to Increase Physical Activity Among Youth. Washington, DC: U.S. Department of Health and Human Services; 2012. Straker LM, Abbott RA, Smith AJ. To remove or to replace traditional electronic games? A crossover randomised controlled trial on the impact of removing or replacing home access to electronic games on physical activity and sedentary behaviour in children aged 10–12 years. BMJ Open 2013; 3(6). pii: e002629. doi: 10.1136/bmjopen-2013-002629.
Address correspondence to: MinKyoung Song, PhD, RN, FNP-BC School of Nursing University of Michigan 400 North Ingalls, Suite 2172 Ann Arbor, MI, 48109-5482 E-mail: [email protected]
Active Gaming Among High School Students—United States, 2010 MinKyoung Song, PhD, RN, FNP-BC,1–3 Dianna D. Carroll, PhD,4,5 Sarah M. Lee, PhD,6 and Janet E. Fulton, PhD 3
Abstract
Objectives: Our study is the first to describe the prevalence and correlates (demographics, body mass index [BMI], sedentary behaviors, and physical activity) of high school youth who report active videogame playing (active gaming) in a U.S. representative sample. Materials and Methods: The National Youth Physical Activity and Nutrition Study of 2010 provided data for this study. Active gaming was assessed as the number of days in the 7 days prior to the survey that students in grades 9–12 (14–18 years of age) reported participating in active videogames (e.g., ‘‘Wii Fit’’ [Nintendo, Kyoto, Japan], ‘‘Dance Dance Revolution’’ [Konami, Osaka, Japan]). Students reporting q1 days were classified as active gamers. Logistic regression was used to examine the association among active gaming and demographic characteristics, BMI, sedentary behaviors, and physical activity. Results: Among 9125 U.S. high school students in grades 9–12 surveyed, 39.9 percent (95 percent confidence interval = 37.9 percent, 42.0 percent) reported active gaming. Adjusting for covariates, the following characteristics were positively associated (P < 0.05) with active gaming: being in 9th and 10th grades compared with being in 12th grade; being of black, non-Hispanic race/ethnicity; being overweight or obese; watching DVDs > 0 hours/day; watching TV > 0 hours/day; and meeting guidelines for aerobic and muscle-strengthening physical activity. Conclusions: Four out of 10 U.S. high school students report participating in active gaming. Active gamers tend to spend more time watching DVDs or TV, meet guidelines for physical activity, and/or be overweight or obese compared with nonactive gamers. These findings may serve to provide a baseline to track active gaming in U.S. youth and inform interventions that target sedentary behaviors and/or physical activity.
Introduction
T
here has been increasing concern about the excessive amount of time children and adolescents spend in sedentary behaviors.1 On average, American children (10–16 years of age) are sedentary for more than 10 hours/day.2 This estimate includes about 4.5 hours at school, with much of the remaining time spent in screen-based sedentary activities such as watching TV, playing videogames, and using computers. A recent report indicated that there has been a significant increase over the last decade in the time children spend in screen-based sedentary activities: currently about 7½ hours on a typical day, compared with approximately 6
hours in 1999.3 The American Academy of Pediatrics recommends youth not exceed 2 hours of ‘‘quality screen time’’ (screen time that has some educational or developmental value) per day,4 yet more than half of U.S. youth exceed the screen-time recommendation.5 This finding is concerning, as excessive sedentary time is associated with having greater fat mass as well as being overweight or obese among youth.6–9 Not all screen time is necessarily sedentary. ‘‘Active gaming’’ is considered nonsedentary (or active) screen time.10 Active gaming (examples include ‘‘Wii Fit’’[Nintendo, Kyoto, Japan] and ‘‘Dance Dance Revolution’’ [Konami, Osaka, Japan]11) was originally created as an entertainment product, but it is differentiated from other videogaming
1
School of Nursing, University of Michigan, Ann Arbor, Michigan. Epidemic Intelligence Service and Divisions of 3Nutrition, Physical Activity, and Obesity, 4Human Development and Disability, and 6 Population Health, Centers for Disease Control and Prevention, Atlanta, Georgia. 5 Commissioned Corps, U.S. Public Health Service, Atlanta, Georgia. The conclusions in this report are the authors and do not represent the official position or views of the Centers for Disease Control and Prevention. 2
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entertainment because it combines screen time with physical movement.12 Energy expenditure during active gaming averages about 3.2 metabolic equivalents, equivalent to ‘‘moderate-intensity’’ physical activities such as brisk walking.13–16 Thus, if future research shows that youths’ participation in active gaming replaces sedentary screen time and does not come at the expense of other forms of physical activity, it may present a new pathway for increasing energy expenditure. Although little is known about how many U.S. youth participate in active gaming, three studies examined prevalence and correlates of active gaming in youth in non-U.S. populations.17–19 A Canadian study reported that approximately 25 percent of 10th and 11th graders engaged in active gaming (based on responses to the question ‘‘Do you play active videogames?’’) and that active gamers were more likely to be girls, to also play nonactive videogames, to watch q2 hours of TV/day, and to be concerned about weight.17 There have also been two surveys conducted with Dutch adolescents 12–16 years of age: One was conducted via a survey where the source population was from a Dutch Internet panel, and the other was via a school-based survey. The Internetbased study found that regular active gamers were younger than nonactive gamers.18 In the school-based survey, approximately 43 percent of adolescents participated in active gaming q1 hour/week, and rates of active gaming were higher in youth attending prevocational levels of schooling compared with those at higher levels.19 This study used a nationally representative sample to help gain understanding of the current status of active gaming among U.S. youth. The two primary objectives of this study were to examine the prevalence of high school students participating in active gaming and the directly associated correlates (demographics, body mass index [BMI], sedentary behaviors, and physical activity) of active gamers. This information will provide baseline data to monitor active gaming among U.S. youth. In addition, because active gaming can potentially replace sedentary screen time with active behaviors, this information may be useful for designing targeted interventions that use active gaming as a strategy to reduce passive screen time and/or increase physical activity. Materials and Methods Survey design
Data from the National Youth Physical Activity and Nutrition Study (NYPANS), conducted in Spring 2010, were used in this study. NYPANS includes a school-based survey (120 items in total, which takes about 45 minutes to complete [available online20]) on behaviors and behavioral determinants related to nutrition and physical activity, as well as measurements of height and weight. Items developed for NYPANS were subjected to cognitive testing, which resulted in the revision or deletion of problematic questions. Several of the NYPANS questions were based on questions from the Youth Risk Behavior Survey; psychometrics have been published elsewhere.21 The study used a three-stage cluster sample design that oversampled African American/black and Hispanic/Latino students to obtain a nationally representative sample of public and private school students in grades 9–12 in the 50 states and the District of Columbia. Specifically, the target population consisted of all public, Catholic, and other private school students in grades 9–12. In each
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participating school, one or two classrooms in each grade from either a required subject (e.g., English) or a required period (e.g., second period) were randomly selected. Lastly, all students in selected classes were eligible to participate. During a regular class session, students voluntarily completed an anonymous, self-administered questionnaire. Additionally, each student’s height and weight were measured by trained study personnel using standard protocol. School response rate was 82 percent; student response rate was 88 percent, and the overall response rate was 73 percent. The Institutional Review Board of the study contractor approved the NYPANS protocol. More detailed information about the study methods has been published previously.22 Participants
Data from 11,429 NYPANS students were available for analyses. We excluded students from the analyses with missing data on active gaming (n = 668), physical activity and sedentary behaviors (n = 253), or BMI or demographic characteristics (sex, grade, and/or race/ethnicity) (n = 1,383). The final analytical sample included 9,125 U.S. high school students in grades 9–12. Measurements Active gaming. The NYPANS survey includes a question to assess types of physical activities: ‘‘For each of the following activities, please mark on how many of the past 7 days you did this activity. Think about activities you did before and after school, in the evenings, and on the weekends, by yourself or with others. Do not include PE [physical education] or gym class. Include activities you did just for fun or in competition.’’ Response options ranged from 0 to 7 days for each activity. Active gaming was listed as one of the 35 physical activities. We classified students reporting q1 day/week as active gamers. Physical activity and sedentary behaviors. Several physical activity variables—sport team participation, participation in PE class, and meeting aerobic and musclestrengthening physical activity guidelines—were also included. Sedentary behaviors, including watching DVDs and other videos and watching TV, were obtained from the questionnaire. (The questionnaire is available online at www.cdc .gov/healthyyouth/yrbs/nypans.htm). Sports team participation was grouped into four categories: no team, one team, two teams, and three or more teams. PE class participation was grouped into three categories: per week, 0 days, 1–4 days, and 5 days. Students who reported participating in q60 minutes of aerobic physical activity/day during the past 7 days were characterized as meeting the aerobic physical activity guideline. Students who reported participating in q3 days of muscle-strengthening activities per week were characterized as meeting the musclestrengthening physical activity guideline.23 Sedentary behavior was grouped into three categories: 0 hours/day, > 0 and p2 hours/day, and > 2 hours/day (exceeding daily restricted hours). The cutoff for sedentary behavior reflected the American Academy of Pediatrics screen-time guideline.4 BMI. BMI (weight [in kg]/height2 [in m2]) was calculated using height and weight measurements. Students were
ACTIVE GAMING AMONG U.S. HIGH SCHOOL STUDENTS
Table 1. Weighted Sample Characteristics: National Youth Physical Activity and Nutrition Study, 2010 Characteristic
n
Percentage 95 percent CI
Sex Male Female
4567 4558
50.6 49.4
48.9, 52.2 47.8, 51.1
Grade 9 10 11 12
2345 2303 2233 2244
28.5 25.4 23.8 22.3
27.2, 23.9, 22.7, 21.1,
29.9 26.8 25.0 23.6
Race/ethnicity White, non-Hispanic 3694 Black, non-Hispanic 1961 Hispanic 2796 Other, non-Hispanic 674
58.7 13.7 18.9 8.7
52.4, 10.6, 14.8, 7.2,
64.6 17.6 23.9 10.4
5690
63.4
61.0, 65.7
1673 1762
17.6 19.0
16.6, 18.7 17.3, 20.9
Sports team participation None 3699 1 team 2499 2 teams 1722 3 or more teams 1205
38.7 26.5 20.2 14.7
35.7, 24.8, 18.3, 12.5,
BMIa Underweight or normal weight Overweight Obese
41.8 28.2 22.2 17.2
Physical education class participation 0 days 4056 45.4 1–4 days 1955 17.5 5 days 3114 37.1
39.3, 51.6 12.9, 23.4 31.1, 43.5
Meeting aerobic physical activity guidelineb Yes 1310 15.1 No 7815 85.0
13.4, 17.0 83.1, 86.6
Meeting muscle-strengthening guidelinec Yes 4593 50.8 No 4532 49.2
48.3, 53.2 46.8, 51.7
Watching DVDs or videos 0 hours/day 1980 > 0 and p2 4904 hours/day > 2 hours/day 2241
23.6 56.2
21.9, 25.3 54.3, 58.1
20.3
18.0, 22.8
863 5309
10.1 61.9
8.9, 11.5 58.7, 64.9
2953
28.0
25.5, 30.7
Active gaming participation Yes 3704 No 5421
39.9 60.1
37.9, 42.0 58.0, 62.1
Watching TV 0 hours/day > 0 and p2 hours/day > 2 hours/day
Total percentages may not add to 100% because of rounding. a Body mass index (BMI) estimates were calculated from measured weight and height (weight [kg]/height2 [m2]) and classified based on sex- and age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts. b Defined as performing at least 1 hour of aerobic physical activity daily. c Defined as performing muscle-strengthening activities q3 days/ week. CI, confidence interval.
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categorized into three BMI groups (underweight or normal weight [ < 85th percentile], overweight [q85th and < 95th percentile], and obese [q95th percentile]), according to sexand age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts.24 Data analyses
We calculated percentage and 95 percent confidence interval of U.S. high school students who were active gamers and examined the distribution of the reported number of days of active gaming in the 7 days immediately prior to the survey. We also assessed active gaming by demographic characteristics, BMI, sedentary behaviors, and physical activity. To assess associations between select characteristics and active gaming, we used logistic regression analysis to determine unadjusted and multivariable adjusted odds ratios and 95 percent confidence intervals. Adjusted odds ratios simultaneously controlled for demographic characteristics, BMI, and other correlates directly related to active gaming. Statistical significance was determined at P < 0.05. SAS callable SUDAAN (version 10.0.1) software (Research Triangle Institute, Research Triangle Park, NC) was used to account for the complex sample design. To produce nationally representative estimates of youth, sample weights were applied to all analyses to adjust for nonresponse and oversampling of black and Hispanic students. Results
Approximately half of the students were male, about 30 percent were in 9th grade and 25 percent were in 10th grade, 60 percent were non-Hispanic white, and 37 percent were overweight or obese. Also, 40 percent reported no participation in team sports during the past 12 months, and almost half reported no participation in PE during an average week. Approximately 15 percent met the aerobic physical activity guideline, and half of the students met the muscle-strengthening guideline. Approximately 20 percent reported watching DVDs or videos for > 2 hours/day, and 28 percent reported watching TV for > 2 hours/day. Overall, 40 percent of the students reported active gaming in the 7 days immediately prior to taking the survey (Table 1). Figure 1 presents frequency of active gaming. About 14 percent of all students reported active gaming 1 day/week, and nearly 3 percent reported active gaming 7 days/week. The percentage of students reporting active gaming generally decreased as the frequency of active gaming (days/week) increased. Adjusting for all covariates, active gaming was positively associated with 9th and 10th grade versus 12th grade, race/ ethnicity of black, non-Hispanic versus white, non-Hispanic, being overweight or obese versus underweight/normal weight, engaging in any TV or video watching versus none, and meeting aerobic physical activity and muscle-strengthening physical activity guidelines versus not (Table 2). Discussion
Our findings show that 40 percent of U.S. high school students participate in active gaming. This finding is generally consistent with other studies.17,25 In a Canadian study17 active gaming prevalence (25 percent) in 10th and 11th grade
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FIG. 1.
Prevalence of active gaming. Color images available online at www.liebertonline.com/g4h
adolescents was lower than we report (40 percent). The difference might be due to nationality and sampling method (convenience sample from the Montreal area versus U.S. nationally representative sample). A previous study reported active gaming as one of the five most frequently reported activities during the previous 7 days among U.S. youth,25 and although it remains unclear whether all active gaming activity is intense enough to contribute to meeting physical activity guidelines, it does appear that active gaming represents a popular youth pastime that is on average a moderateintensity level of physical activity.13–16 Thus, active gaming should be included when evaluating overall youth aerobic physical activity and considered alongside other activities when planning programs to improve youth physical activity.11,12,26,27 Our data show that non-Hispanic blacks were more likely to participate in active gaming, which is an interesting finding in that another study with the NYPANS showed that overall physical activity levels were lower in non-Hispanic black youth.28 To the best of our knowledge, other examinations of the demographic correlates of active gaming either have not included race/ethnicity variables,29 included nonspecific race/ethnicity variables17–19 (e.g., Caucasian versus non-Caucasian), or were conducted with samples composed of white students, predominantly.15 Further investigation with diverse race/ethnicity groups is warranted to determine if active gaming is a promising intervention for specific racial/ethnic groups. Our data further show that students who watch DVDs/ videos or TV were more likely to participate in active gaming. This finding is consistent with another study that reported that students who watched TV or engaged in nonactive videogaming were more likely to be active gamers.17 These findings, however, do not show any causal relationship and/or direction of causality with respect to that association. Given that an association was shown in both studies, we feel further investigation is warranted to see whether active gaming might be a particularly useful tool for those youth who are particularly likely to spend time watching DVDs/ videos or TV—by changing ‘‘passive screen time’’ to ‘‘active screen time.’’30
The current finding that students who met aerobic or muscle-strengthening physical activity guidelines were more likely to be active gamers is consistent with one previous study and inconsistent with other previous studies.10,17,29,31 Wethington et al.10 showed that youth who participate more in vigorous physical activity were more likely to report ‘‘active’’ screen time. However, O’Loughlin et al.17 reported that active gamers were no more likely to meet moderate to vigorous physical activity guideline than nonactive gamers. Recently, Baranowski et al.31 reported no difference in physical activity over a 12-week period when comparing a group of children who received a new videogame console along with two active videogames and a group who received the same console and two inactive videogames. Finally, in a recent study with young adults, Kakinami et al.29 reported that female active gamers reported approximately 45 more minutes/week of moderate-intensity physical activity than female nonactive gamers but were no more likely to meet the physical activity guidelines than nonactive gamers. Pending further investigation to confirm an association between active gaming and meeting physical activity guidelines, our findings raise some questions related to any such association: (1) Do youth who are more physically active participate in higher levels of active gaming? or (2) Does time spent active gaming increase overall physical activity levels, perhaps to the point where some active gamers go from not meeting the guidelines to meeting the guidelines? Laboratory research shows active gaming, on average, represents moderate-intensity activity—similar to walking briskly.32 A recent systematic review of active gaming,11 however, cautions that not all active gaming involves moderate- to vigorous-intensity physical activity. Intensity levels of physical activity during active gaming depend to a large extent on the game played, with a higher intensity resulting from games that include lower-body movement.15,32 Further longitudinal, experimental design studies would help clarify the underlying relationship among participation in active gaming, intensity of physical activity, and contribution of active gaming toward meeting physical activity guidelines.23 The examination of long-term health outcomes of habitual active gaming is still in its infancy. A randomized controlled
ACTIVE GAMING AMONG U.S. HIGH SCHOOL STUDENTS
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Table 2. Prevalence and Odds Ratios of Active Gaming Participation, National Youth Physical Activity and Nutrition Study, 2010
Characteristic Sex Male Female Grade 9 10 11 12 Race/ethnicityb Black, non-Hispanic Hispanic White, non-Hispanic BMIc Underweight or normal weight Overweight Obese Sports team participation None 1 team 2 teams 3 or more teams Physical education class participation 0 days 1–4 days 5 days Meeting aerobic physical activity guidelined Yes No Meeting muscle-strengthening guidelinee Yes No Watching DVD or videos 0 hours/day > 0 and p2 hours/day > 2 hours/day Watching TV 0 hours/day > 0 and p2 hours/day > 2 hours/day
Odds ratio (95 percent CI)
Active gamers (percent)
Unadjusted
Adjusted a
40.4 39.4
1.04 (0.91, 1.19) 1.00
0.93 (0.82, 1.06) 1.00
46.3 39.7 36.3 35.7
1.56 (1.34, 1.81) 1.19 (1.05, 1.34) 1.03 (0.89, 1.18) 1.00
1.44 (1.24, 1.66) 1.15 (1.01, 1.31) 1.02 (0.88, 1.17) 1.00
47.8 38.4 38.1
1.48 (1.24, 1.78) 1.01 (0.84, 1.22) 1.00
1.32 (1.13, 1.56) 0.94 (0.78, 1.15) 1.00
37.6 43.3 44.5
1.00 1.27 (1.07, 1.52) 1.33 (1.15, 1.55)
1.00 1.22 (1.03, 1.45) 1.34 (1.14, 1.58)
35.9 42.9 41.2 43.1
1.00 1.34 (1.17, 1.55) 1.25 (1.04, 1.50) 1.35 (1.13, 1.62)
1.00 1.33 (1.15, 1.54) 1.23 (1.01, 1.50) 1.26 (1.04, 1.51)
36.9 42.7 42.2
1.00 1.27 (1.06, 1.52) 1.25 (1.05, 1.49)
1.00 1.12 (0.95, 1.32) 1.04 (0.88, 1.24)
45.8 38.8
1.33 (1.12, 1.58) 1.00
1.22 (1.01, 1.46) 1.00
42.9 36.8
1.29 (1.15, 1.44) 1.00
1.23 (1.10, 1.38) 1.00
28.3 41.6 48.6
1.00 1.81 (1.55, 2.10) 2.39 (1.95, 2.93)
1.00 1.74 (1.49, 2.03) 2.44 (1.93, 3.08)
28.6 41.2 41.2
1.00 1.74 (1.36, 2.23) 1.74 (1.32, 2.30)
1.00 1.48 (1.14, 1.92) 1.22 (0.93, 1.60)
Estimates are weighted to account for survey nonresponse and oversampling of certain populations. a Adjusting for demographic characteristics (sex, grade, race/ethnicity), body mass index (BMI), and physical activity and sedentary behaviors (sports team participation, physical education class participation, meeting the aerobic and muscle-strengthening guidelines). b Because the numbers of students from non-Hispanic other and non-Hispanic multiracial groups were too small for meaningful analysis, race/ethnicity is presented only for non-Hispanic white, non-Hispanic black, and Hispanic students (who might be of any race). c BMI estimates were calculated from measured weight and height (weight [kg]/height2 [m2]) and classified based on sex- and age-specific reference data from the 2000 Centers for Disease Control and Prevention growth charts. d Defined as performing at least 1 hour of aerobic physical activity daily. e Defined as performing muscle-strengthening activities q3 days per week. CI, confidence interval.
trial with a 24-week follow-up by Maddison et al.33 showed that home-based active gaming intervention had a positive influence on BMI and body composition in 10–14-year-old overweight/obese children. A systematic review reported that active gaming may attenuate weight gain in overweight and obese youth.11 Our finding that overweight and obese youth are more likely to be active gamers than normal or
underweight youth has an interesting implication when combined with the findings of Maddison et al.33 and the systematic review11; there might be value in examining whether encouraging active gaming could be an effective way to reach youth who are the most in need for obesity interventions and/or youth who are already overweight. One longitudinal study currently being conducted by Simons
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et al.34 is examining the impact of a 10-month active gaming intervention on weight gain, BMI, other measures of adiposity, and physical activity/sedentary behaviors in normalweight and obese youth 12–16 years of age. The findings of Simons et al.34 may shed light on the potential contribution of active gaming to prevent obesity among adolescents. Our findings have several public health implications. First, our results might have public health implications regarding current efforts underway aimed at reducing ‘‘screen time.’’ Not all screen time is sedentary. Because our results show an association between active gaming and meeting physical activity guidelines, care should be taken to ensure that initiatives aimed at reducing overall screen time do not have an unintended consequence of reducing physical activity benefits from active gaming.11,35,36 Second, and relatedly, our data suggest or support the idea that encouraging active gaming may be a viable strategy for getting youth to substitute physical activity for sedentary screen time. In fact, Straker et al.37 reported that replacing ‘‘passive’’ videogames with active games led to increases in physical activity and decreases in sedentary time among children. Future research would enable us to explore the potential contribution of active gaming to increase youth energy expenditure. Third, active gaming may be a particularly effective strategy for increasing physical activity in youth who spend time watching DVDs or TV, or who are overweight or obese—as those youth already participate in active gaming at higher rates. These potential benefits, however, come some caveats: It is not yet clear whether and/or how much active gaming reduces passive screen time, and it is also not yet clear whether/how much youth participation in active gaming meaningfully increases energy expenditure or improves BMI/adiposity-related outcomes. It is possible that many youth play active games at low-intensity levels without expending much energy, and it is possible that any effects of increased energy expenditure might be mediated by changes in energy intake. It should be noted here that Maddison et al.33 did find an association between active gaming and reduced BMI without significant changes in self-reported energy intake, but further research that accounts for energy intake is needed to fully understand the direct relationship between active gaming and BMI/adiposity-related outcomes. The present study has several limitations. First, we did not assess the intensity level of physical activity, the duration of participation, or the body part involved during active gaming (e.g., upper or lower extremity). Acquiring more information about some component parts of physical activity, including intensity, duration, and types of body movement, would provide useful information to evaluate active gaming benefits. Second, through the NYPANS we obtained information on active gaming and physical activity through self-reports; thus, the frequency of active gaming might have been underor over-reported. However, at the current time, these data are the best available measure. Third, questions used to assess active gaming in the NYPANS dataset only identified the Wii and ‘‘Dance Dance Revolution’’ as specific active screen time activities and did not list other consoles (e.g., Xbox Kinect [Microsoft, Redmond, WA], PlayStation Move [Sony, Tokyo, Japan]), games, or other active screen-time activities. Thus, we cannot interpret whether they were answering the question with reference to all active videogames or to the Wii and ‘‘Dance Dance Revolution’’ only, and, as a
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result, our findings might be underestimating the prevalence of active gaming. In future active gaming assessments, other consoles or different forms of active screen time need to be included. Fourth, this study relied on self-reported data, which may be influenced by recall bias or social-desirability bias. Finally, this study was a cross-sectional analysis; thus we cannot determine any causal relationships. Nonetheless, the associations presented may prove useful for further research into the potential benefits of active gaming, and ultimately in designing interventions that incorporate active gaming to reduce sedentary behavior. Conclusions
Our findings show 40 percent of U.S. high school students are active gamers, and they tend to meet national physical activity guidelines, despite spending more time watching DVDs or TV and/or being overweight or obese. These baseline data can be used to inform researchers, educators, parents, and decision-makers who are interested in using active gaming as a way to help youth become less sedentary and more physically active. Author Disclosure Statement
No competing financial interests exist. References
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Address correspondence to: MinKyoung Song, PhD, RN, FNP-BC School of Nursing University of Michigan 400 North Ingalls, Suite 2172 Ann Arbor, MI, 48109-5482 E-mail: [email protected]
