Changes in active travel of school children from 2004 to 2010 in New South Wales, Australia

YPMED-03175; No. of pages: 3; 4C: Preventive Medicine xxx (2011) xxx–xxx Contents lists available at SciVerse ScienceDirect Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed Changes in active travel of school children from 2004 to 2010 in New South Wales, Australia Dafna Meron 1, Chris Rissel ⁎, 2, Tracie Reinten-Reynolds 2, Louise L. Hardy 3 Prevention Research Collaboration, School of Public Health, University of Sydney 2006 NSW Australia a r t i c l e i n f o Article history: Received 24 May 2011 Received in revised form 1 September 2011 Accepted 1 September 2011 Available online xxxx Keywords: active travel fitness body mass index school students a b s t r a c t Purpose. To describe changes in mode of commuting to school among Australia students between 2004 and 2010 and in relation to body mass index (BMI) and cardio respiratory fitness. Methods. Representative cross-sectional survey of school children in grades 6, 8 and 10 in 2004 (n = 2750) and 2010 (n = 4273). Information on how many days students use active and passive travel modes to and from school and measured BMI and cardio-respiratory fitness test were collected as part of the New South Wales (NSW) Schools Physical Activity and Nutrition Surveys (SPANS). Results. Active travel to school remained stable between 2004 and 2010, although there was a small increase in minutes spent on active travel. There was no association between active travel and body mass index. In 2010 there was a significant association between frequent car use and low cardio-respiratory fitness (adjusted OR = 1.7, CI 1.3-2.1). Conclusion. It is a positive finding that the generational decline in active travel may have levelled out. Student inactivity associated with regular car use is plausibly related to lower cardio-respiratory fitness, but active commuting may not be of sufficient energy expenditure to impact upon BMI. © 2011 Elsevier Inc. All rights reserved. Introduction Cross sectional investigations have shown that children who actively commute to school tend to be more physically active than passive commuters (Cooper et al., 2003; Cooper et al., 2006), although the contribution of active commuting to children's body weight or fitness levels is still unclear (Faulkner et al., 2009; Lubans et al., 2011). Concurrently, a large body of research has focused on understanding the influences of children's travel behaviour to better direct promotional efforts (Davison et al., 2008; Panter et al., 2008). Social marketing campaigns (Merom et al., 2006) and communitybased interventions to promote active travel to school have been implemented and evaluated in many countries, with mixed success (Hinckson et al., 2011; McKee et al., 2007; Staunton et al., 2003; Wen et al., 2008). Population surveillance is critical for monitoring the long-term impact of active travel programs, but few routine data systems record school travel behavior (Buliung et al., 2009; Grize et al., 2010; McDonald, 2007; Van der Ploeg et al., 2008). The available reports ⁎ Corresponding author at: Prevention Research Collaboration, School of Public Health, University of Sydney 2006 NSW Australia. E-mail addresses: d.merom@uws.edu.au (D. Meron), Chris.Rissel@sydney.edu.au (C. Rissel), trein@doh.health.nsw.gov.au (T. Reinten-Reynolds), louise.hardy@sydney.edu.au (L.L. Hardy). 1 Fax: + 61 2 9036 3184. 2 Fax: + 61 2 9036 3184. 3 Fax: + 61 2 9036 3184. tend to be transportation surveys which rely on one day observations and lack information on health indicators such as physical activity, fitness or body mass index (BMI). In 2004 in New South Wales (NSW), Australia, the School Physical Activity and Nutrition Surveys (SPANS) incorporated a self-report measure of weekly travel patterns as well as health-related measurements. In this paper we describe changes in car use to school between 2004 and 2010 considering the regularity of this behaviour, and assess the associations between car use and cardio-respiratory fitness level and BMI. Methods Design SPANS are cross-sectional representative surveys of primary and high school students designed to monitor weight and weightrelated behaviours of school students in NSW, Australia. SPANS methods have been published elsewhere (Booth et al., 2005; Hardy et al., 2011). Briefly, 101 schools were selected using a stratified probability proportionate to size (PPS) methodology and invited to participate. The survey methodology, protocols and instruments were identical, each survey was conducted in summer/autumn and data were collected by trained field staff. Students in Years 6 (primary school), 8 and 10 (secondary school) and aged 12, 14 and 16 years respectively, provided demographic information. Informed consent by students and their carers was a requirement for participation. In 2010 the school and students’ response rates were 73% and 57%, 0091-7435/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2011.09.017 Please cite this article as: Meron, D., et al., Changes in active travel of school children from 2004 to 2010 in New South Wales, Australia, Prev. Med. (2011), doi:10.1016/j.ypmed.2011.09.017 2 D. Meron et al. / Preventive Medicine xxx (2011) xxx–xxx respectively. The University of Sydney Human Research Ethics Committee, the NSW Department of Education and Training, and the NSW Catholic Education Commission approved the surveys. Measures Socio-demographic information included the student's sex, date of birth, and postcode of residence as a proxy for socio-economic status (SES), to rank students in tertiles of SES (low, middle, or high). Height and weight were measured, BMI calculated and students’ categorized into overweight/obese or not according to international guidelines (Cole et al., 2000). The 20‐metre shuttle run test was used to assess cardio-respiratory fitness and the number of shuttles completed used to determine adequate fitness (Leger and Lambert, 1982). Daily time spent in moderate-to-vigorous physical activity (MVPA) was determined using the Adolescent Physical Activity Recall Questionnaire (Booth et al., 2005) and students categorized as sufficiently physically active if they spend at least 60 minutes every day in MVPA (Strong et al., 2005). Analysis Post stratification weights were calculated and the analyses accounted for the cluster design, and were performed using SAS version 9.2 (SAS Institute Inc., Cary, NC, USA). The proportion of students who were overweight/obese, with adequate fitness and the median time spent in MVPA (mins/day) were calculated for each travel group by survey year, sex and grade. The change between 2004 and 2010 and the differences between travel groups were tested for the proportions of overweight/obese, and adequate fitness using the Wald Chi-squared test. To test the difference in minutes MVPA over time and between travel groups we used non-parametric tests (Wilcoxon-Mann–Whitney) to deal with skewed data. To assess the association between fitness and car use, quartiles of fitness were constructed. As there were no differences between quartiles two through four, these groups were collapsed to compare the least fit with the rest in logistic regression models for each survey year, adjusted for sex, BMI category, SES, school year, and MVPA. Because there was no dose response relationship between category of car use and fitness, we used a dichotomous car use grouping combining occasional and no car use as the reference group. School travel Results Travel behaviour was collected only from Grade 6, 8 and 10 students in 2004 (n = 2750, student response rate 65%) and 2010 (n = 4273, student response rate 57%). Students were asked how they travelled to and from school on each day in a usual week, including walk, cycle, skateboard or scooter, driven by car, take the bus, or train or ferry/ boat with additional “other” options. Students could report more than one mode. For these analyses, data were reduced to three travel groups: 1. No car use; students who only reported active travel (walking, cycling, skateboard or scooter) and/or public transport (bus, train, ferry) on five school days. 2. Occasional car use; 1–5 trips to or from school on five school days 3. Frequent car use; 6 or more trips to or from school on five school days In 2004, 51.5% of the students were boys, 36%, 29% and 35% were from Years 6, 8 and 10 respectively, 14% were from rural NSW, and 29% and 35% were from low and middle SES tertiles. There were no significant differences in the sample distribution in all parameters. Table 1 shows that the proportion of children who do not use a car for school travel did not change between survey years, although there was a significantly (p b .05) higher proportion (+ 9%) of primary school girls who were frequent car users in 2010. About one third of primary and half of the secondary students travelled to and from school without using a car. Within this group, there was a nonsignificant increase (4%) in the proportion of primary school boys who used active modes on 10 trips (data not shown). Median time of active travel trips (data not shown) increased by up to 2 minutes, with greater gains in the 75 percentiles, which were 14, 13, and 14 Table 1 Changes in overweight/obesity, adequate fitness and moderate to vigorous physical activity (MVPA) between 2004 and 2010 by car use, sex and school level. Frequency of car use on school days (to and from) No car use Occasional 1–5 trips Frequent 6 or more trips ALL Number (n) Prevalence (%) Overweight/obese (%) Adequately fit (%) Median MVPA (mins/day) Number (n) Prevalence (%) Overweight/obese (%) Adequately fit (%) Median MVPA (mins/day) Number (n) Prevalence (%) Overweight/obese (%) Adequately fit (%) Median MVPA (mins/day) Number (n) Overweight/obese (%) Adequately fit (%) Median MVPA (mins/day) BOYS GIRLS Primary school High school Primary school High school 2004 2010 2004 2010 2004 2010 2004 2010 175 33.4 25.8 65.2 123.5 120 28.8 31.1 58.7 109.6 188 37.8 32.6 59.8 99.0 483 29.9 61.3 110.0 224 34.8 30.6† 69.0 75.4⁎ 167 26.9 17.7† 75.8 60.4⁎ 258 38.3 37.7† 65.4 66.1⁎ 522 52.7 26.7 61.7 105.1 278 31.2 29.6 62.7 112.6 163 16.1 19.7 71.7 118.7 963 26.5 63.6 109.9 889 52.9 22.6 68.2 87.4⁎ 460 27.4 21.3 66.5 86.6⁎ 312 19.6 32.4 62.1 86.4⁎ 155 30.9 30.1 72.6 82.3 153 31.4 18.3 77.5 93.6 188 37.7 18.9 80.4 81.8 496 22.2 77.2 85.4 198 30.0 25.5 79.5 69.1⁎ 152 23.3⁎ 397 47.6 15.7 71.3 78.0 245 31.7 23.2 62.4 77.7 166 20.6 16.4 68.0 76.1 808 18.2 67.8 77.2 617 47.0 21.5 68.7† 70.8⁎ 416 32.1 16.4 72.0† 75.2⁎ 299 20.9 20.6 53.2† 75.5 1332 19.7 66.5† 72.8⁎ 649 29.8 69.5 70.0⁎ 1661 24.2 66.6 87.0⁎ 22.2 74.2 59.9⁎ 281 46.8* 23.9 75.3 65.1⁎ 631 24.0 76.3 66.1⁎ ⁎ Statistically significant between 2004 and 2010 (p b 0.05). † Statistically significant difference in the proportion of overweight/obese children or proportion of children adequately fit or median daily MVPA between car usage groups by school level, sex and survey year. Please cite this article as: Meron, D., et al., Changes in active travel of school children from 2004 to 2010 in New South Wales, Australia, Prev. Med. (2011), doi:10.1016/j.ypmed.2011.09.017 3 D. Meron et al. / Preventive Medicine xxx (2011) xxx–xxx Table 2 Odds ratios (95% CI) from logistic regression of the frequency of car use for school travel on the outcome for least fit students (first quartile of fitness) by survey year. N 2004 2010 No or occasional car use Frequent car users No or occasional car use Frequent car users 1,805 630 2,957 1075 Outcome for least fit students (first quartile of fitness) n (weighted %) OR (95% CI) Adjusted† OR (95% CI) 414 146 638 315 1.0 0.9 (0.6,1.3) 1.0 1.7 (1.4,2.2)⁎ 1.0 1.0 (0.7,1.5) 1.0 1.7 (1.3,2.1)⁎ (80.6) (19.4) (68.4) (31.6) Regression was modelled on the first quartile (least fit) and ‘no and occasional car usage (0–5 trips/week)’ as the reference group. ⁎ statistically significant p b 0.05. † Values are adjusted for sex, school year, BMI category, whether they met the physical activity guideline and SES tertile. minutes in 2004 for primary school boys, girls and high-school boys, respectively, increasing to 17, 19, and 23 minutes in 2010. There was no association between car usage and being overweight/ obese (Table 1). Time spent in MVPA declined among all students, except high school girls who were occasional and frequent car users to and from school. The logistic regression models, shown in Table 2, found no association between the least fit quartile of fitness (laps) and frequent car usage in 2004, but significant associations in 2010. There was a significant association between frequent car use and least fit students (first quartile) compared with those in the combined higher quartiles of fitness. There was a large increase in the proportion of students reporting frequent car use among the least fit (first quartile) students in 2010 (19.4% in 2004 to 31.6% in 2010) but not among other students (see Table 2). Discussion In the context of a decline in active travel by school children from 1971–2003 (Van der Ploeg et al., 2008), that there was no change in active travel between 2004 and 2010 is a positive finding. This plateau of decline in active travel may be temporary, but may also reflect the cumulative effect of state and community level health promotion initiatives (Merom et al., 2005; Wen et al., 2008). Consistent with recent systematic reviews (Faulkner et al., 2009; Lubans et al., 2011), we found no association between school travel modes and overweight and obesity. For NSW students the predominant source of energy expenditure through active travel is walking (only 3.7% students cycled). Given the short duration of walking trips (median 9 minutes) and possible slow pace it may not be sufficient to impact upon weight status. Student‘s frequent car use was associated with low fitness in 2010 but not in 2004. Potentially, the combination of an increase in the proportion of students reporting frequent car use in 2010 among those least active students plus shifts in median and 75th percentile of active travel explain this association, whereas in 2004 the energy expenditure gained from active travel was not sufficient to impact fitness. This, in conjunction with substantial declines in MVPA between surveys, may have increased the prominence of no car use on the fitness of actively travelling children. If the overall amount of MVPA has declined then even small increases in active travel energy expenditure, as reported here, may be an important contributor to fitness. The strengths of this study include the representative sample of students, the consistent use of data collection methodologies across surveys, and objectively measured BMI and fitness and simultaneous adjustment for MVPA when the effect of active travel is explored. The self-report measurement of physical activity is a limitation of the data, and the possibility that some unmeasured artefact may explain lower MVPA in 2010 is a further limitation of this study. The cross sectional design limits our ability to make any causal inferences. Conflict of interest statement The authors declare no actual or potential conflict of interest relevant to this article. 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