Hành vi ít vận động có liên quan với tăng nguy cơ bệnh mãn tính và hành vi ít vận động đang gia tăng trong thanh thiếu niên. Dữ liệu về những thay đổi trong hành vi định canh định cư ở các nước đang phát triển bị hạn chế. Mục đích Để mô tả 5 năm thay đổi theo chiều dọc trong giờ ít vận động nonschool trong thanh thiếu niên đô thị tại thành phố Hồ Chí Minh, và để xác định mối tương quan với sự thay đổi này. Phương pháp Đây là 5 năm nhóm theo chiều dọc với lấy mẫu ngẫu nhiên hệ thống của 759 sinh viên đến từ 18 trường trung học cơ sở. Tất cả các biện pháp đã được thực hiện hàng năm từ năm 2004 đến năm 2009. Hành vi Định canh định cư được đánh giá bằng tự báo cáo và accelerometry. Mô hình tiềm ẩn và hỗn hợp tuyến tính tổng quát được sử dụng để phân tích dữ liệu trong năm 2011. Kết quả Từ năm 2004 đến năm 2009, thời gian tự báo cáo chi tiêu trong hành vi ít vận động nonschool tăng 498603 phút ngày. Trong năm khảo sát lần thứ 5, nam và nữ (từ 16 tuổi) tương ứng là 3,6 lần (95% CI = 2.3, 6.0) và 3,1 lần (95% CI = 1,8, 5,0) nhiều khả năng dành ≥ 2 giờ ngày vào thời gian màn hình so với ban đầu (từ 12 tuổi). Dữ liệu tốc điều chỉnh cho thời gian mặc tiết lộ rằng nam và nữ từ 16 tuổi có, tương ứng, ở phút thứ 78 ngày (95% CI = 48, 104) và 69 phút ngày (95% = 34, 95) nonschool nhiều thời gian ít vận động hơn những người có đánh giá tốc đầu tiên (ở tuổi 13 năm). Cô gái trong tứ phân vị kinh tế xã hội cao nhất dành một 90 phút bổ sung ngày trong hành vi ít vận động so với các cô gái trong tứ phân vị thấp nhất (95% CI = 52, 128). Kết luận Hành vi ít vận động Nonschool tăng trong thanh thiếu niên Việt Nam có độ tuổi. Sự gia tăng lớn nhất là trong thời gian màn hình giải trí (28%), đó sẽ là mục tiêu rõ ràng nhất cho các chiến lược y tế dự phòng.
Longitudinal Sedentary Behavior Changes in Adolescents in Ho Chi Minh City Nguyen H.H.D. Trang, MD, MSc, Tang K. Hong, MD, PhD, Hidde P. van der Ploeg, PhD, Louise L. Hardy, PhD, Patrick J. Kelly, PhD, Michael J. Dibley, MBBS, MPH This activity is available for CME credit. See page A4 for information. Background: Sedentary behavior is associated with increased risk of chronic disease and sedentary behavior is increasing among adolescents. Data on changes in sedentary behavior in developing countries are limited. Purpose: To describe 5-year longitudinal changes in nonschool sedentary hours among urban adolescents in Ho Chi Minh City, and to identify correlates with this change. Methods: This is a 5-year longitudinal cohort with systematic random sampling of 759 students from 18 junior high schools. All measures were taken annually between 2004 and 2009. Sedentary behavior was assessed by self-report and accelerometry. Generalized linear latent and mixed models were used to analyze the data in 2011. Results: Between 2004 and 2009, self-reported time spent in nonschool sedentary behavior increased from 498 to 603 minutes/day. In the 5th survey year, boys and girls (aged 16 years) were, respectively, 3.6 times (95% CIϭ2.3, 6.0) and 3.1 times (95% CIϭ 1.8, 5.0) more likely to spend Ն2 hours/day on screen time compared with baseline (aged 12 years). Accelerometer data adjusted for wearing time revealed that boys and girls aged 16 years had, respectively, 78 minutes/day (95% CIϭ48, 104) and 69 minutes/day (95% CIϭ34, 95) more nonschool sedentary time than those at the fırst accelerometer assessment (at age 13 years). Girls in the highest socioeconomic quartile spent an additional 90 minutes/day in sedentary behavior compared with girls in the lowest quartile (95% CIϭ52, 128). Conclusions: Nonschool sedentary behavior increased among Vietnamese adolescents with age. The largest increase was in recreational screen time (28%), which would be the most obvious target for preventive health strategies. (Am J Prev Med 2013;44(3):223–230) © 2013 American Journal of Preventive Medicine Introduction S edentary behaviors increase the risk of obesity 1–3 and the development of a range of chronic dis- eases. 4–6 In children and adolescents, leisure-time sedentary behaviors, such as TV viewing, have been associated with metabolic risk factors, independent of physical activity levels. 4,7 In recent decades, the oppor- tunities to be sedentary have increased, and young people tend to be more sedentary than those in previ- ous generations. 8,9 Although much is known about correlates of physical activity, 10 little is known about correlates of sedentary be- haviors among adolescents, despite the belief that the deter- minants of sedentary behavior are distinct from those of physical activity. 11,12 In addition, sedentary behavior ap- pears to carry over more than physical activity from child- hood to adolescence, 13 and may even have a greater influ- ence on the development of overweight and obesity than physical activity. 14,15 Data on sedentary behaviors are available for devel- oped countries, 16–20 but they are lacking for develop- ing nations. 21 Moreover, current studies are mostly cross-sectional and focused on only screen time (i.e., TV, videos/DVDs, recreational computer use), which has been used widely as a proxy measure of sedentary behavior among youth. 7,22,23 Few studies have exam- From the Department of Community Health (Trang, Hong), Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam; Sydney School of Public Health (Trang, Kelly, Dibley), and Prevention Research Collabo- ration (van der Ploeg, Hardy), The University of Sydney, New South Wales, Australia; and the Department of Public and Occupational Health (van der Ploeg), VU University Medical Center Amsterdam, the Netherlands Address correspondence to: Nguyen H.H.D. Trang, MD, MSc, Pham Ngoc Thach University of Medicine, 86/2 Thanh Thai Street, District 10, Ho Chi Minh City, Vietnam. E-mail: nguyenhoang_doantrang@yahoo. com. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2012.10.021 © 2013 American Journal of Preventive Medicine. All rights reserved. Am J Prev Med 2013;44(3):223–230 223 ined a broad range of sedentary behaviors longitudi- nally among adolescents. 24 Identifıcation of the correlates of a full range of seden- tary behaviors in adolescents is needed to develop more- effıcient preventive action to decrease sedentary behavior and risk of chronic disease including excess adiposity in developing countries, such as Vietnam. The purpose of the current study was to describe the longitudinal changes in sedentary behavior among adolescents in ur- ban Vietnam who participated in the Ho Chi Minh City Youth Cohort study between 2004 and 2009, and to iden- tify individual, family, and environmental factors associ- ated with screen time and sedentary behavior over this 5-year period. Methods Study Design The Ho Chi Minh City (Vietnam) Youth Cohort study was a 5-year longitudinal study that began in 2004 from a multistage cluster cross-sectional survey. The study examined the weight status and weight-related behaviors among adolescents in this city. The sur- vey covered 140 junior high schools from which 31 clusters (schools) were selected. Systematic random sampling was used to select 18 junior high schools, of which 11 were from wealthy districts and seven were from less-wealthy districts for the cohort. 25 In each school, one class was taken from two classes (one from Grade 6 and one from Grade 7) combined. The two classes were selected by simple random sampling in the cross-sectional study. All stu- dents in the selected classes were invited to participate in the study (Nϭ784), and 759 students consented to participate in the cohort. Data were collected by trained fıeld staff on fıve occasions, 1 year apart, on adolescents who consented to take part in the study. Consent, from both the adolescents and their parents, was required for participation in the cohort study. The study was approved by the Research Ethics Committee, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, and the Human Research Ethics Committee of the University of Newcastle, Australia. Data Collection Information on sedentary behaviors was measured using the Ado- lescent Sedentary Activity Questionnaire (ASAQ), 26 validated in Vietnamese adolescents, 27 which asked students to report the time spent outside of school hours for each day of the week in a range of sedentary activities. Daily time spent in sedentary behavior was com- puted as the total of all recorded sedentary activities, categorized by sedentary domains: screen time (watching TV/video, playing com- puter games, using computer for fun); educational time (using com- puter for study, studying at home, studying in afterschool class); other leisure time (reading books, chatting with friends, talking on phone, doing hobbies, music or painting lesson/practice); and passive com- muting to school (i.e., by car, bus, motorbike). One year after baseline (Year 2005), students’ sedentary behav- ior also was assessed objectively for 7 days with an Actigraph accelerometer (model GT1M) worn on the right hip. 28 Sedentary time was defıned as Ͻ100 counts per minute. 29,30 Nonwear time was defıned as 10 minutes of consecutive zeroes. 31 Only partici- pants who wore the accelerometer for Ն8 hours per day on at least 4 days were included in the analysis. Physical activity was assessed using the Vietnamese Adolescent Physical Activity Recall Ques- tionnaire (V-APARQ). 32 The Spearman and intraclass correla- tion coeffıcients showed this questionnaire to be valid and reli- able, with a weighted kappa of 0.75, indicating that the V-APARQ is useful for monitoring change in physical activity among Vietnamese adolescents. Anthropometric measurements were taken by trained fıeld staff. Participant weight (in kilograms; without shoes or heavy clothing) was measured using a Tanita BF 571 electronic scale and recorded to the nearest 100 g. Standing height (in centimeters) was measured with a suspended Microtoise tape to the nearest 0.1 cm. BMI was calculated, and overweight and obesity were defıned using the International Obesity Task Force cutpoint values. 33 In a confıden- tial setting, the adolescents self-reported their pubertal status using Tanners’ fıve stages of pubertal development for pubic hair, and male genitalia or female breasts; for female students, the date of menarche also was recorded. 34 The student’s parents also completed a questionnaire provid- ing information on household SES, and their personal charac- teristics. SES was assessed through questions on ownership of 14 assets that were used to construct a household wealth index. Responses were ranked and divided into quartiles of SES. Par- ents also reported on the availability of computer game stores, home rules on playing computer games, presence of a TV in the child’s room, and frequency of the parents’ doing exercises with their child. Data Analysis Analyses were conducted using Stata, version 11. Models were fıtted using the generalized linear latent and mixed models (GLLAMM) package in Stata. 35 Multilevel models were used to take account of the clustering of observations within schools and for repeated student observations. Data were weighted according to school size. Screen time was categorized according to recom- mended guidelines (Ͻ2 and Ն2 hours/day). 36 To determine fac- tors that could predict the change in the prevalence of Ն2 hours/ day screen time, multilevel multivariable logistic regression models were used,and multilevelmultivariable linearmodels wereused for continuous data. Results were stratifıed by gender because participation in seden- tary behaviors differed between boys and girls, 37 and an interaction was found between gender and sedentary time (pϭ0.004). Vari- ables with a univariate p-value Ͻ0.25 were entered into the multi- variable model. 38 Stepwise backward elimination was used, and variables were removed from the model if their adjusted p-value was Ͼ0.05. Only signifıcant factors were presented. Results At baseline, 759 adolescents consented to participate in the study, and complete data from the 5 survey years were available for 585 (77%) adolescents. At baseline, the mean age of the students was 11.8 years (Ϯ0.6). The baseline characteristics of the students (Table 1) showed that 14.2% of students were overweight or obese. The majority of students did not have a TV in their bedroom (92%); 224 Trang et al / Am J Prev Med 2013;44(3):223–230 www.ajpmonline.org had a computer game store nearby (95%); and had paren- tal rules limiting screen time (95%). Self-reported time spent in various domains of seden- tary behaviors by survey year is shown in Table 2. Over the 5-year period, sedentary behavior increased by 21% (pϽ0.001; from an average of 498 minutes/day to 603 minutes/day). At each survey year, the most common sedentary domain was afterschool educational activities, Table 1. Baseline characteristics of adolescents, M (SD) or % (95% CI) Boys (nϭ364) Girls (nϭ395) Total (Nϭ759) Age (years) 11.8 (0.6) 11.9 (0.7) 11.8 (0.6) Height (cm) 155.7 (9.7) 153.4 (8.1) 154.5 (9) Weight (kg) 44.6 (9.6) 41 (7.4) 42.7 (8.7) BMI 20.1 (3.9) 18.1 (3.1) 19.1 (3.7) BMI status a Not overweight/obese 78.2 (73.7, 82.7) 86.5 (82.9, 90.0) 82.5 (79.7, 85.4) Overweight/obese 21.8 (17.3, 26.3) 13.5 (9.9, 17.1) 17.4 (14.6, 20.3) Pubertal status Prepubescent 45.9 (40.6, 51.2) 22.1 (18.0, 26.3) 33.6 (29.9, 36.8) Pubescent and postpubescent 54.1 (48.8, 59.4) 77.9 (73.7, 82.0) 66.6 (63.2, 70.1) Maternal education (nϭ329) (nϭ367) (nϭ696) Did not complete junior high school 24.6 (19.9, 29.3) 26.7 (22.2, 31.2) 25.7 (22.5, 29.0) Did not complete high school 21.6 (17.1, 26.0) 22.3 (18.1, 26.6) 22.0 (18.9, 25.1) Completed high school or higher 53.8 (48.4, 59.2) 50.9 (45.8, 56.1) 52.3 (48.6, 56.0) Paternal education (nϭ329) (nϭ367) (nϭ696) Did not complete junior high school 19.1 (14.9, 23.4) 22.6 (18.3, 26.9) 21.0 (17.9, 24.0) Did not complete high school 20.1 (15.7, 24.4) 21.0 (16.8, 25.2) 20.5 (17.5, 23.6) Completed high school or higher 60.8 (55.5, 66.1) 56.4 (51.3, 61.5) 58.5 (54.8, 62.1) BMI status of parents (nϭ291) (nϭ326) (nϭ617) Both not overweight/obese 71.1 (65.9, 76.4) 72.1 (67.2, 77.0) 71.6 (68.1, 75.2) Father overweight/obese 7.6 (4.5, 10.6) 7.1 (4.3, 9.8) 7.3 (5.2, 9.4) Mother overweight/obese 17.9 (13.4, 22.3) 16.6 (12.5, 20.6) 17.2 (14.2, 20.2) Both overweight/obese 3.4 (1.3, 5.5) 4.3 (2.1, 6.5) 3.9 (2.3, 5.4) SES quartile b (nϭ364) (nϭ395) (nϭ759) 1st (poorest) 26.1 (21.6, 30.6) 25.3 (21.0, 29.6) 25.7 (22.6, 28.8) 2nd 22.5 (18.2, 26.8) 26.3 (22.0, 30.7) 24.5 (21.4, 27.6) 3rd 25.8 (21.3, 30.3) 27.1 (22.7, 31.5) 26.5 (23.3, 29.6) 4th (richest) 25.5 (21.1, 30.0) 21.3 (17.2, 25.3) 23.3 (20.3, 26.3) TV in child’s bedroom (nϭ360) (nϭ391) (nϭ751) No 88.9 (87.4, 90.3) 94.1 (93.1, 95.2) 91.6 (90.7, 92.5) Easy access to computer game store (nϭ278) (nϭ371) (nϭ649) Yes 94.4 (91.0, 97.8) 94.7 (91.3, 98.1) 94.5 (92.2, 96.9) Rules for computer games at home (nϭ337) (nϭ351) (nϭ688) Yes 95.0 (92.6, 97.3) 94.0 (91.5, 96.5) 94.5 (92.8, 96.2) a Defined by using International Obesity Task Force cutpoint b Based on household wealth index Trang et al / Am J Prev Med 2013;44(3):223–230 225 March 2013 accounting for 38%– 40% of total sedentary time, followed by screen time (30%–34%) and other leisure activities (17%–20%). Over the 5-year period, screen time increased by 28% (pϽ0.001); afterschool educational ac- tivities increased by 27% (pϽ0.001); and other sedentary leisure-time activities increased by 14% (pϽ0.01). At baseline, 81.5% students have more than 2 hours of screen time/day, increasing to 86.4% in 5 years (pϭ0.01). Figure 1 shows the median time (minutes/day) spent in three main domains of sedentary behavior outside of school hours by gender and survey year. For both boys and girls, time spent in afterschool educational activities and screen time increased at each survey year. Boys con- sistently engaged in more screen time than girls across survey years (pϽ0.001). At baseline, screen time was 160 minutes/day and 144 minutes/day and increasedover the 5-year period to 215 minutes/day and 190 minutes/ day, for boys and girls respectively. In contrast, girls spent signifıcantly more time in afterschool educational activi- ties than boys, especially in the third survey year when students transitioned into high school, although educa- tional time did increase in both boys and girls. The correlates of screen time of Ն2 hours/day by gen- der show that in the 5th survey year, boys (mean age 16 years) were 3.6 times (ORϭ3.6, 95% CIϭ2.3, 6.0) as likely to spend Ն2 hours/day on screen time compared with baseline screen time (mean age 12 years). Similarly, in the 5th survey year, girls(mean age 16 years) were three times (ORϭ3.1, 95% CIϭ1.8, 5.0) as likely to spend Ն2 hours/day on screen time compared with baseline screen time (mean age 12 years). Girls from the highest SES quartile were also twice as likely to spend Ն2 hours/ day on screen time than their counterparts from the low- est SES quartile (ORϭ2.1, 95% CIϭ1.3, 3.4). The correlates of time in total sedentary behavior (Table 3) show that in the 5th survey year (mean age 16 years), boys had increased their daily sedentary time by 121 minutes/day (95% CIϭ98, 160) compared with baseline, whereas sedentary behavior among girls in- creased 115 minutes/day (95% CIϭ96, 163) over the 5-year period. Girls in the highest SES quartile had an additional 90 minutes of daily sedentary time compared with peers in the lowest SES quartile (95% CIϭ52, 128). Table 2. Sedentary behavior time (minutes/day) outside of school hours, by categories and survey year 2004/2005 nϭ759 2005/2006 nϭ740 2006/2007 nϭ712 2007/2008 nϭ630 2008/2009 nϭ585 Age (years) 11.8 (0.66) 12.8 (0.65) 13.9 (0.64) 14.8 (0.71) 15.8 (0.61) Accelerometry time (minutes) — 445 (118) 463 (114) 498 (92) 482 (90) Wearing time, accelerometry (minutes) — 787 (134) 779 (134) 734 (127) 705 (117) Self-reported time (ASAQ; minutes) 498 (180) 558 (201) 601 (210) 604 (215) 603 (212) Screen time 158 (102, 243) 165 (114, 283) 172 (163, 287) 205 (156, 275) 203 (157, 264) TV 75 (43, 129) 86 (51, 137) 94 (78, 136) 103 (69, 146) 99 (60, 137) Video 34 (17, 62) 39 (19, 69) 34 (20, 60) 43 (19, 69) 36 (17, 69) Using computer for fun/games 31 (17, 60) 40 (27, 69) 50 (34, 114) 63 (44, 89) 72 (46, 120) Ն2 hours screen time/day, % (95% CI) 81.5 (78.9, 84.2) 82.8 (80.0, 85.1) 83.2 (80.6, 85.8) 85.7 (83.2, 88.4) 86.4 (83.5, 89.2) Total afterschool educational time 191 (148, 236) 196 (150, 244) 244 (192, 309) 240 (184, 321) 242 (197, 326) Computer use for education 21 (14, 34) 26 (16, 39) 27 (21, 43) 30 (19, 51) 35 (18, 56) Noncomputerized study 101 (60, 146) 110 (70, 139) 125 (94, 174) 118 (69, 154) 120 (80, 164) Afterschool class 62 (41, 95) 64 (39, 90) 96 (57, 132) 92 (71, 137) 98 (64, 133) Total other leisure-time sedentary behavior 108 (65, 143) 116 (75, 211) 103 (85, 148) 120 (114, 175) 123 (112, 160) Sitting chatting with friends/talking on phone 26 (14, 49) 40 (10, 76) 36 (11, 72) 50 (30, 83) 45 (29, 77) Reading 25 (13, 43) 26 (13, 43) 21 (10, 39) 25 (16, 43) 30 (17, 51) Hobbies/music/recreational practices 56 (34, 90) 51 (29, 84) 45 (28, 88) 50 (29, 95) 52 (43, 105) Passive travel 41 (22, 80) 60 (47, 137) 70 (34, 116) 45 (30, 98) 40 (30, 103) Note: Values are M (SD) or median (25th percentile, 75th percentile), unless otherwise noted; — ϭ no observation. ASAQ, Adolescent Sedentary Activity Questionnaire 226 Trang et al / Am J Prev Med 2013;44(3):223–230 www.ajpmonline.org Accelerometer data, adjusted for wearing time, showed that sedentary behavior increased by 78 minutes/day (95% CIϭ48, 104) among boys and 69 minutes/day (95% CIϭ34, 95) among girls between the 2nd and 5th survey year. Physical activity and environmental factors were not associated with the changes in screen time and sedentary behavior. Changes in BMI were not associated with changes in sedentary behavior (data not shown). Discussion This is the fırst study to present longitudinal changes across a broad range of sedentary behaviors and to pro- vide a better understanding of relevant correlates of screen time and sedentary behavior among Vietnamese adolescents. The study fındings are important to the de- sign of interventions designed to decrease the sedentary lifestyles that are becoming increasingly common in de- veloping countries such as Vietnam. This study showed an increase in nonschool sedentary time in a representa- tive sample of adolescents aged 12–16 years in urban Ho Chi Minh City. Afterschool educational sedentary time and screen time accounted for more than two thirds to three quarters of total sedentary time, respectively, out- side school hours. Age, gender, and SES were related to screen time and total sedentary time. The increase in screen time with age found in the present study is similar to increases reported by longi- tudinal studies in developed countries. 13,39,40 This fınding may be due to the substantial amount of free- dom adolescents have in Vietnam to engage in screen time and the increased access and availability of screen technologies. Ownership of a TV among those in ur- ban areas in Vietnam has increased from 77% in 1999 to 91.3% in 2009. 41 Likewise, Internet usage has increased signifıcantly from 12.8% to 25.7% from 2005 to 2009. 42 Among all screen behaviors, TV time only increased slightly, a fınd- ing in accordance with previous studies that reported the stability of TV time. 43 The median screen time of Viet- namese adolescents was above the recommended level of Ͻ2 hours/day in all 5 survey years (2.5–3.5 hours per day). This is higher than the level found in a study in urban Chinese adolescents in 2004–2006 that reported 1.2–1.7 hours/day of screen time, 44 and it is more closely aligned with fındings of adolescents’ screen time in the U.S. and Canada, where daily screen time exceeds 4 hours/day. 45 The present fınding that Vietnamese youth report a large amount of time in afterschooleducational sedentary behaviors is similar to results reported among Chinese adolescents. 44 This result may be due to the high priority placed on education in Asian cultures, where academic pressure is put on the students by their parents and schools. The time spent in sedentary educational activi- ties increased steeply after 3 years of follow-up in both boys and girls, corresponding to the time when students are preparing for junior high school graduation exams, followed by entry into high school. During this time, students often spend more time on extracurricular tutor- ing in addition to homework, including evening classes in private institutions and private classes preparing students for the fınal junior high school examination. In the present study, time spent hanging out chatting with friends increased substantially and is also an impor- tant sedentary leisure-time activity for Vietnamese ado- lescents. During adolescence, teenagers begin to spend increasingly more time away from their parents and are more exposed to schools, peers, and other socialization agents. Time spent hanging out and socializing therefore increased correspondingly. 46 Consistent with other studies, 37,44,47,48 boys reported higher screen time than girls. This may be because girls take part in more activities other than screen time, such as housework and extracurricular cultural activities. In Vietnamese culture, girls are expected to help their moth- ers with household activities, especially cooking, prepar- ing the table for dinner, and cleaning; boys may follow their fathers’ behavioral patterns, which allow for more screen time. In the present study, older children were more likely to have 2 or more hours of daily screen time as well as total sedentary time. These fındings are in agreement with other studies that focused on screen time. 13,49,50 The present study showed that screen time was higher among 0 100 200 300 400 500 600 700 2004/2005 2005/2006 2006/2007 2007/2008 2008/2009 Other leisure time Afterschool educational time Screen time Minutes/day Boys Boys Boys Boys BoysGirls Girls Girls Girls Girls Figure 1. Median (minutes/day) self-reported screen time, afterschool educational time, and other leisure sedentary time Trang et al / Am J Prev Med 2013;44(3):223–230 227 March 2013 high-SES adolescents, especially girls, which is in contrast to that reported among developed countries wherehigher SES is associated with lower screen time. 51 Similarly, this study also found a negative association between total nonschool sedentary time and SES,which is also in contrast with fındings reported by developed countries. 52–54 Various explanations are possible for the higher rates of screen time and total sedentary time among higher-SES adolescents. Higher-SES families may have greater access to sedentary technologies, their chil- dren might be more likely to engage in study outside school hours, and their children might be more likely to spend time helping with housework. No association was found between screen time or total nonschool sedentary behavior and physical activity. This fınding supports results of a recent review of the corre- lates of physical activity in children and adolescents, 10 which concluded that there was no relationship between TV/video games and physical activity among those aged 13–18 years. Similarly, sedentary time and physical activ- ity have been suggested as being independent behaviors in school children. 18 Strengths and Limitations The strength of this study was its longitudinal design with repeated measures and a good retention rate over the 5-year period (77%). The prospective cohort study design allowed examination of changes in a large variety of sed- entary behaviors and relevant sociodemographic factors during adolescence. Another strength of the study was the use of accelerometers to objectively measure seden- tary time. In contrast to self-report, accelerometers pro- vide very precise information on movement patterns; Table 3. Correlates of total sedentary behavior (minutes/day) by gender, mean change (95% CI) Boys Girls Univariate Adjusted a Univariate Adjusted a ADOLESCENT SEDENTARY ACTIVITY QUESTIONNAIRE Year of follow-up (ref: Year 1—baseline) 2 30 (16, 61) 30 (16, 61) 27 (12, 53) 27 (12, 53) 3 70 (35, 106) 70 (35, 106) 66 (39, 110) 66 (39, 110) 4 118 (96, 153) 118 (96, 153) 113 (79, 158) 113 (79, 158) 5 121 (98, 160) 121 (98, 160) 115 (96, 163) 115 (96, 163) Pubertal status (ref: prepubescent) Postpubescent 45 (10, 59) — 66 (27, 106) — Maternal education (ref: did not complete junior high school) Did not complete high school — — 55 (18, 90) — High school or higher — — 50 (19, 71) — SES quartile (ref: 1st—the poorest) 2nd 35 (15, 84) — 72 (32, 119) 69 (31, 109) 3rd 39 (16, 85) — 81 (36, 116) 76 (35, 114) 4th 45 (11, 92) — 97 (48, 125) 90 (52, 128) ACCELEROMETER Year of follow-up (ref: Year 2) 3 21 (12, 47) 21 (12, 47) 37 (13, 60) 37 (13, 60) 4 65 (43, 88) 65 (43, 88) 58 (28, 78) 58 (28, 78) 5 78 (48, 104) 78 (48, 104) 69 (34, 95) 69 (34, 95) Pubertal status (ref: prepubescent) Postpubescent 37 (16, 58) — 39 (12, 66) — Note: SES is based on household wealth index. a Adjusted for pubertal status, maternal education, SES, and wearing time (from accelerometry data) 228 Trang et al / Am J Prev Med 2013;44(3):223–230 www.ajpmonline.org however, because accelerometers provide no contextual information, both methods are required. The fındings showed that irrespective of the mea- surement instrument, sedentary behavior among Viet- namese adolescents has increased over time. The study design, a multistage cluster, random sampling of urban adolescents from Ho Chi Minh City, provides strong external validity of the results. Thus, the results are likely to be representative of other adolescent popula- tions in large cities in Vietnam and possibly other South East Asian cities, which are going through rapid economic transition. One of the limitations is the substantial amount of missing accelerometer data, especially in the later survey years. The main reason for the missing data was that many of the participating adolescents did not comply with wearing instructions. This lack of compliance may have led to an underestimation of sedentary time mea- sured by the accelerometer. Similarly, given the large number of prompts in the questionnaire for various kinds of sedentary behavior, it seems that total sedentary time might have been overes- timated by the questionnaire. This also would help ex- plain partly the discrepancy between the accelerometer and questionnaire. However, there is no indication sug- gesting that such overestimation of sedentary time would be different across age categories. Accelerometer results also suggested an increase in sedentary time with age, although a smaller increase than those reported in the questionnaire. Conclusion The present study showed an increase in daily nonschool sedentary behavior among Vietnamese youth as they progress through adolescence. Information on correlates given can be used to plan evidence-based strategies that are age-tailored and targeted to differences between gen- ders, and to high-risk groups, such as students in high- SES families. Strategies to reduce excessive educational sitting include more active classes that incorporate stand- ing time into the educational process, an increase in re- cess and break times, 55,56 and active homework. 57 Other promising strategies include encouraging adolescents to switch from passive to active screen time, 58,59 and to exchange sitting and chatting during leisure time with walking and chatting. Decreasing sedentary behavior has an important role in prevention strategies aimed at tackling emerg- ing obesity and chronic diseases in Vietnamese adoles- cents. Intervention strategies in Ho Chi Minh City will need to have multidisciplinary approaches and sup- port from a range of communication channels to in- crease awareness of the positive effects of decreasing sedentary time for both adolescents and their parents. The survey was funded by a grant from the Nestlé Foundation, Switzerland. Nguyen H.H.D. 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