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Adolescents’ physical activity (PA) is influenced by an interaction of individual, social and environmental factors.[[1]] Societal changes over recent decades have markedly reduced the need and opportunities for PA in daily life and imposed multiple barriers to PA across all PA domains: transport, leisure and recreation, school/workplace and household. In adolescents, PA has been associated with improved cardiorespiratory fitness, muscular endurance and strength and the prevention of non-communicable diseases.[[2]] To gain health benefits, adolescents need to accumulate at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily.[[2]] However, recent evidence suggests there are high rates of physical inactivity and time spent stationary among adolescents globally,[[3]] including New Zealand.[[4]] Worldwide, 81% of 11–17 year olds did not meet current guidelines for recommended levels of physical activity in 2016, while 89% of New Zealanders in this age group did not achieve recommended levels.[[3]]

Most studies examining adolescent PA have been conducted in urban areas. However, due to contextual differences (eg, population density, access to facilities, social and cultural norms), PA patterns observed among urban adolescents may not be generalisable to rural adolescents. Studies that compare device-measured PA in adolescents living in urban versus rural settings show inconsistent results. Although most report that urban adolescents accumulate more accelerometer-measured MVPA compared to rural adolescents,[[5,6]] one study in the United States found that PA was higher in adolescents living in rural compared to urban areas.[[7]] Similarly, inconsistent results have also been reported for time spent in sedentary pursuits. Compared to rural adolescents, urban adolescents spent more time being sedentary in Australia,[[8]] but less time in Kenya,[[9]] and no difference was reported for Canadian[[6]] and Portuguese adolescents.[[5]] These inconsistent findings may reflect urban–rural differences in social norms, recreational opportunities and infrastructure related to PA, country-specific PA characteristics and/or differences in how rurality is defined.

Understanding PA patterns in different geographical settings is necessary to inform country-specific initiatives and programmes aimed at increasing the low levels of PA among adolescents. New Zealand adolescents live in a range of settings,[[10]] and this study compared accelerometer-measured PA patterns in adolescents living in large, medium and small urban areas and rural settings in the Otago region.

Method

Study design

Secondary data were analysed from two cross-sectional studies conducted in the urban and rural areas of the Otago region, New Zealand. Dunedin city is the only large urban area, and the wider Otago region (population of approximately 225,186) consists of medium urban, small urban and rural areas.[[10]] The 2014–15 Built Environment and Active Transport to School (BEATS) Study was conducted in all 12 Dunedin secondary schools. The 2018 BEATS Rural Study (BEATS-R) was conducted in 11 of 15 regional secondary schools. Both studies used the BEATS research methodology, which has been described in detail elsewhere,[[11]] with data being collected throughout the school year. Both studies were approved by the University of Otago Human Ethics Committee (BEATS: 13/203; BEATS-R: 17/178).

Participants

Briefly, each participating secondary school invited adolescents from one to four classes from years 9 to 13 (ages 13 to 18 years) to participate in the study. In small schools of <100 students, all students were invited. Potential participants received information packages with parent and student information sheets and consents. In the BEATS Study, parental opt-in or parental opt-out consent was used depending on each school’s preference for adolescents aged 13 to 15 years, whereas for the BEATS-R Study no parental consent was required. In both studies, participants were required to sign an additional consent to wear an accelerometer. This analysis included data from 377 adolescents with valid survey and accelerometer data (Figure 1).

Given their school and home address location, participants were classified into four geographical setting categories using Stats NZ definitions:[[10]]

  • large urban area (30,000–99,999 residents; ie, Dunedin city excluding Mosgiel)
  • medium urban area (10,000–29,999 residents)
  • small urban area (1,000–9,999 residents)
  • rural setting (<1000 residents).

The BEATS and BEATS-R studies did not collect data from participants living in major urban areas (>100,000 residents).[[10]] Only participants residing and attending school in the same geographical setting were included in this analysis (ie, participants residing in rural areas but attending a boarding school were excluded) (Figure 1).

Figure 1: Flowchart of participant recruitment and selection for the final study sample.

Measurement procedures

Questionnaire

Participants completed an online survey during one school period (50–60 minutes) under the supervision of research staff. The survey included questions about sociodemographic characteristics, home address, number of vehicles and bicycles at home, transport-to-school habits and sport participation. Participants reported frequency of use of different modes of transport to school. The mode of transport used ‘most of the time’ and ‘all of the time’ informed their transport to school category: ‘active transport’, ‘motorised transport’ or ‘mixed transport’.[[11]] They also reported whether they participated in sports at school and outside school (eg, club sport) with ‘yes’/’no’ responses to each question. Neighbourhood-level socioeconomic status was determined by the home address data being matched with address codes from the New Zealand Index of Deprivation Study.[[12]] Geographic Information Science network analysis was used to calculate the shortest distance to school from each participant’s home address.[[11]]

Anthropometry

Research staff performed anthropometry measurements in a screened-off area of the classroom using standard procedures.[[11]] Height was measured using a stadiometer (BEATS: custom-made portable stadiometer; BEATS-R: portable (SECA213 stadiometer, SECA Corp)) and weight using an electronic scale (A&D scale UC321, A&D Medical).

Accelerometer-measured PA

Participants wore an accelerometer (ActiGraph, GT3XPlus, Pensacola, FL, USA) above their right hip for seven consecutive days, as described elsewhere.[[11,13]] Briefly, research staff instructed them to wear their device for ≥12 hours each day for seven days, and to take it off for sleep, water-based activities (eg, swimming) and contact sports (eg, rugby). To promote adherence, participants were given an activity log to record their accelerometer wear time, sent reminders by email or text and received a $10 book voucher.

Accelerometer data were downloaded in 10-second epochs for the BEATS Study and 15-second epochs for the BEATS-R Study using ActiGraph software and measured in average counts per minute (cpm).[[13]] The wear-time validity was set at ≥5 days, with ≥10 h/day (inclusive of three school days and one weekend day).[[13]] Accelerometer data were analysed by the MeterPlus data analysis service in San Diego, USA, using MeterPlus software (MeterPlus, San Diego, CA, USA) with Evenson’s cut-points.[[14]] Twenty-minute stationary bouts were classified as non-active periods. Processed accelerometer data included time spent in light, moderate, moderate-to-vigorous and vigorous intensity PA and sedentary time for an average day, a weekend day and a school day, as well as before school (08:00–09:00h), early after school (15:00–16:00h) and late after school (16:00–20:00h) on school days.[[13]]

Data analysis

Demographic characteristics were analysed using descriptive statistics. Continuous variables were checked for normality and showed skewness values ≤2 and kurtosis (excess) ≤4, which are indicative of considerable normality for sample sizes >300,[[15]] with the exception of only five variables (distance to school in the total sample; average daily sedentary time; average moderate PA before school; average vigorous PA before and late after school). For continuous variables, differences across geographical settings were compared using ANOVA with Scheffe post-hoc multiple comparisons (or Tamahane’s T2 test, when the assumption of homogeneity of variance was violated). Categorical variables were compared using χ[[2]]-test. Differences between school days versus weekend days were compared using paired t-test for continuous variables and McNemar test for categorical variables. Continuous variables are reported as means ± standard deviation, whereas categorical variables are reported as frequencies (n (%)). An alpha of less than 0.05 was considered statistically significant. Data were analysed using SPSS software (Version 24.0).

Results

Table 1 shows the sociodemographic characteristics of study participants. Among the 377 participants (age: 14.9±1.4 years), 66.8% were female and 75.5% were New Zealand European. Average distance to school was 4.5±5.1 km (median: 3.0km; interquartile range: 4.3km). Age, gender, ethnicity and sport participation rates were not statistically different between geographical settings. Neighbourhood-area deprivation level, car and bicycle ownership, home-to-school distance and rates of active transport to school varied across the geographical settings, with the longest median distance to school and lowest rates of active transport observed in rural settings.

Table 1: Sociodemographic characteristics of study participants.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.

Throughout the week, participants spent on average 9.5 hours (69.2%) of the daily accelerometer wear time in stationary pursuits, 3.5 hours (24.5%) in light intensity PA and 0.9 hours (6.6%) in MVPA per day (Table 2). Specifically, they participated in 54.4±21.0 minutes of MVPA daily (Table 2) and 35.0% met PA guidelines (Table 1). A greater proportion of participants met PA guidelines on school days (40.8%) versus weekend days (26.0%) (p<0.001). On school days, participants spent significantly more time in sedentary activities, moderate and vigorous PA as well as MVPA compared to weekend days (all p<0.05). 

Table 2: Physical activity levels throughout the week.

[[a]] p<0.05 vs. large urban area; [[b]] p<0.05 vs. medium urban area; [[c]] p<0.05 vs. small urban area; [[d]] p<0.05 vs. rural settlement or area. MVPA = moderate to vigorous physical activity; PA = physical activity.

A greater proportion of males, school-sport participants and users of active transport to school met PA guidelines on average school days, compared to their counterparts (Table 3). However, on an average weekend day, no differences were observed between participants who met PA guidelines and those who did not, except for sports participation at school (Table 3).

The average amount of daily MVPA (Table 3) or proportion of participants meeting PA guidelines (Table 1) did not differ across the four geographical setting categories. However, those living in rural areas spent more time in light PA compared to their counterparts from large and medium urban areas, and less time in stationary pursuits compared to those from large urban areas (Table 2). Similar patterns were observed on average school days. On weekend days, rural adolescents engaged in significantly more light PA compared to their urban counterparts, whereas no significant difference existed across geographical settings for the amount of time participants spent in stationary pursuits.

PA patterns on school days also varied across geographical settings. During the hour before school (8:00–9:00h), participants living in large and medium urban areas spent significantly more time in MVPA than those from small urban areas and rural settings (Table 4). In addition, participants from large and medium urban areas spent significantly more time in MVPA during early after school (15:00–16:00h) than those from rural areas; however, no difference was found for small urban areas (Table 4). During the late after school period (16:00–20:00h), participants living in urban areas spent significantly more time in stationary pursuits and less time in light PA compared to their rural counterparts (Table 4).  

Table 3: Characteristics of participants who met and did not meet physical activity recommendations.

Table 4: Physical activity levels throughout an average school day in participants across geographical settings.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.MVPA = moderate to vigorous physical activity; PA = physical activity.

Discussion

Key findings of this study are: (1) Less than half of Otago adolescents meet PA guidelines overall; (2) A greater proportions of adolescents meeting PA guidelines were male, participated in school sports and used active transport to school; (3) Although the proportion of adolescents meeting PA guidelines was not significantly different across geographical settings, those in large urban areas spent more time being stationary but accumulated more MVPA during the school commute time compared to their rural counterparts.

Taken together, these findings show that engagement in PA in Otago adolescents is lower than recommended for the majority and should be encouraged across all geographical settings, particularly during weekends.

Using device-measured PA, 35% of Otago adolescents met the PA guidelines and on average engaged in 54.4±21.0 minutes of MPVA per day with no significant differences by geographical setting. These findings are consistent with estimates of 27–33% of children and adolescents meeting recommended PA levels worldwide.[[4,16]] However, if these New Zealand adolescents as a group were to increase their daily PA by six minutes (approximately 10% of their daily activity), they would meet the guidelines. This seems like an achievable public health target.

Previous studies that compared PA across urbanisation settings reported higher levels of MVPA in urban compared to rural adolescents in Portugal,[[5]] Canada[[17]] and the United States.[[18,19]] Greater access to recreational facilities in urban compared to rural areas,[[20]] and consequently better access to organised sports and recreational activities,[[21]] may in part explain these findings. However, in the present study no difference in MVPA was observed among Otago adolescents living in the four geographical settings, although rural adolescents spent more time in light PA compared to their urban peers. It is highly likely that rural adolescents in New Zealand have more access to open green spaces and natural environments compared to their urban counterparts.[[22]] Greenness exposure has been associated with higher levels of MVPA among American children.[[23]] Nevertheless, the PA levels in Otago adolescents are low in both urban and rural areas, reinforcing the need for effective interventions to encourage PA in all New Zealand adolescents, irrespective of setting. In addition, given the limitations of self-reports,[[24,25]] more research employing direct measures (eg, accelerometers, pedometers, inclinometers) of the PA and sedentary behaviour of New Zealand youth will further contribute to understanding how patterns of such behaviour interact in diverse geographical locations across the country.

A greater proportion of adolescents who met PA guidelines in this study were male, used active transport to school and participated in school sports. These findings are consistent with those reported elsewhere.[[1,26]] In the Asia–Pacific region, rates of active transport to school vary by gender, with different patterns across countries.[[27]] Differences in active transport may also further contribute to gender differences in overall PA among adolescents observed in this and other studies.[[27]] As active-transport-to-school rates are lower than motorised-transport rates and continue to decline in New Zealand,[[4]] active transport should continue to be promoted as a way to increase PA among adolescents, particularly females. Possible ways to encourage active transport to school in diverse geographic settings include strong social support, creating safe walking and cycling routes to school through built environment changes and encouraging mixed transport for adolescents who live beyond walking and/or cycling distance to their school.

The finding that a greater proportion of adolescents who met PA guidelines participated in organised sports compared to their counterparts is also consistent with other studies.[[26]] Recent New Zealand data showed that 81% of 5–17 year olds participated in organised sports and 54% of those aged 13–18 years engaged in school sports.[[4]] Many factors contribute to adolescents’ sports participation, including individual characteristics, family socioeconomic status[[28]] and a supportive sport environment.[[26]] Previous Otago research showed that factors related to a supportive sport environment, such as provision of sport grounds at school, quality of sport management and availability of sports outside school, were associated with the time adolescents spent participating in sport.[[26]] Thus, future initiatives and programmes designed for promoting adolescents’ PA through organised sport participation should focus on providing well-organised and supportive sport environments in both urban and rural areas of New Zealand.

Adolescents in this study spent on average 9.5 hours being stationary. Those from large urban areas spent a significantly higher proportion of time in stationary pursuits (particularly in the time periods early after school and late after school) compared to their peers from rural areas. Given that light PA is considered the antidote to sedentary behaviour,[[29]] children in rural areas in New Zealand may be avoiding sedentary behaviour by engaging in more active and outdoor play than those in larger urban communities. Previous studies reported that adolescents from developed countries spend approximately 6–10 hours per day being sedentary.[[30,31]] Accelerometer-based studies that compared sedentary time between urban and rural adolescents reported inconsistent results.[[5,6,8,9]] Among Portuguese adolescents, urban female adolescents spent significantly more time in sedentary pursuits compared to their rural counterparts.[[5]] In the United Kingdom, technology-based sedentary behaviour was the most common after school activity among adolescents.[[32]] Among 9–16-year-old Australians, screen time was higher among urban males compared to rural males, but no difference was found among females.[[33]] The discrepancies between findings from studies could be due to different definitions of ‘rurality’: based on accessibility,[[8,9]] or population size,[[5,6]] or because of different availability of services, facilities and recreation spaces within urban and rural areas in New Zealand compared to other countries.[[34]] In addition, differences are likely to exist in what qualifies as sedentary behaviour. As Otago adolescents spend a significant amount of time in stationary pursuits, future interventions should focus on reducing sedentary time by reducing recreational screen time and encouraging outdoor activities[[4]] among New Zealand adolescents in both urban and rural areas. For adolescents living in large urban areas, such interventions should include efforts to increase active-transport-to-school rates and to reduce education-based sedentary time through the introduction of regular activity breaks.[[35]]

The strengths of this study include the device-based measurement of PA; the inclusion of participants living in different geographical settings with geographically matched participants’ home and school location; high school participation rates across the region; and PA being analysed at different times throughout the school day and on weekend days. However, there are limitations that should be acknowledged. Although accelerometers measure a range of movements in multiple planes, they cannot measure upper-body movements, movement on a graded terrain and movement in activities such as swimming and cycling, which may limit the validity of PA data among participants who regularly participate in those physical activities. Future research should improve the utility of accelerometers for assessing swimming, cycling, upper-body and graded-terrain PA. Additional limitations include the 3–4 year gap between the BEATS and BEATS-R studies data collection; the difference in length of epoch for accelerometer data collection between the two studies; a relatively small sample size in some geographical settings; and a lack of data on reasons for adolescents not consenting to participate in this assessment. Although the findings may not be generalisable to other geographical regions within New Zealand or to other countries, our results are consistent with international findings and provide further insight into understanding PA among adolescents in different environments.

The proportion of Otago adolescents meeting recommended PA levels was low. But a small increase in daily PA levels (eg, six minutes) would see most adolescents meeting current guidelines. Continuous encouragement of PA is needed for adolescents across urban and rural settings. New Zealand already provides substantial support for PA within school, community and environmental settings, as well as at the government/policy level.[[4]] Future initiatives to increase PA among New Zealand adolescents should focus on facilitating active transport to school (eg, through initiatives such as creating safe walking and cycling routes to school),[[36]] promoting inclusive sport participation[[26]] and increasing peer and family support for PA.[[4]]

Summary

Abstract

4AIM: This study compared accelerometer-measured physical activity (PA) patterns in adolescents living in diverse urban and rural areas of Otago, New Zealand. METHOD: Participants (n=377; age: 14.9±1.4 years; 66.8% female; 23 schools) completed an online school travel survey, anthropometry and seven-day PA accelerometer assessment. Participants resided in large (n=237), medium (n=45) and small (n=44) urban areas or rural settings (n=51). RESULTS: Overall, participants participated in 54.4±21.0 minutes of moderate-to-vigorous physical activity (MVPA) daily and 35.0% met PA guidelines (school day vs weekend day: 40.8% vs 26.0%; p<0.001) with no difference across geographical settings. A greater proportion of males (43.2% vs 31.9%; p=0.016), school sport participants (70.1% vs 54.0%; p=0.005) and active-transport-to-school users (40.2% vs 26.1%) met PA guidelines compared to their counterparts. Compared to rural adolescents, those from large urban areas accumulated more MVPA during the school commute time (before school: 8.3±6.7 vs 5.3±3.8 minutes, p<0.001; after school: 10.1±6.0 vs 7.7±4.3 min, p=0.003), but overall spent more time sedentary (584.9±84.7 vs 527.8±88.2 minutes/day; p<0.001). CONCLUSION: PA in Otago adolescents is low, with significant differences by gender, sport participation, mode of travel to school and geographical setting. Increased PA should be encouraged in both urban and rural adolescents.

Aim

Method

Results

Conclusion

Author Information

Brittany White: Master of Science Graduate, School of Physical Education, Sport and Exercise Sciences, University of Otago, Dunedin. Enrique García Bengoechea: Succeed & Lead Fellow, Physical Activity for Health, Health Research Institute, Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland. John C Spence: Professor, Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, Alberta, Canada. Kirsten J Coppell: Public Health Physician and Research Associate Professor, Department of Medicine, University of Otago, Dunedin. Sandra Mandic: Adjunct Professor, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Research Affiliate, Centre for Sustainability, University of Otago, Dunedin.

Acknowledgements

The BEATS Study was supported by the Health Research Council of New Zealand Emerging Researcher First Grant (14/565), National Heart Foundation of New Zealand (1602 and 1615), Lottery Health Research Grant (Applic 341129), University of Otago Research Grant (UORG 2014) and the Dunedin City Council. The BEATS Rural Study was supported by the University of Otago Research Grant (UORG 2018) and Otago Energy Research Centre Seed Grant. Brittany White was supported by the University of Otago Masters Scholarship. The authors would like to acknowledge BEATS investigators and Advisory Board members, research personnel (research assistants, students and volunteers) and all participating schools and adolescents.

Correspondence

Sandra Mandic, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand, +64 21 0902 0025

Correspondence Email

sandy.mandic@aut.ac.nz

Competing Interests

Nil.

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Adolescents’ physical activity (PA) is influenced by an interaction of individual, social and environmental factors.[[1]] Societal changes over recent decades have markedly reduced the need and opportunities for PA in daily life and imposed multiple barriers to PA across all PA domains: transport, leisure and recreation, school/workplace and household. In adolescents, PA has been associated with improved cardiorespiratory fitness, muscular endurance and strength and the prevention of non-communicable diseases.[[2]] To gain health benefits, adolescents need to accumulate at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily.[[2]] However, recent evidence suggests there are high rates of physical inactivity and time spent stationary among adolescents globally,[[3]] including New Zealand.[[4]] Worldwide, 81% of 11–17 year olds did not meet current guidelines for recommended levels of physical activity in 2016, while 89% of New Zealanders in this age group did not achieve recommended levels.[[3]]

Most studies examining adolescent PA have been conducted in urban areas. However, due to contextual differences (eg, population density, access to facilities, social and cultural norms), PA patterns observed among urban adolescents may not be generalisable to rural adolescents. Studies that compare device-measured PA in adolescents living in urban versus rural settings show inconsistent results. Although most report that urban adolescents accumulate more accelerometer-measured MVPA compared to rural adolescents,[[5,6]] one study in the United States found that PA was higher in adolescents living in rural compared to urban areas.[[7]] Similarly, inconsistent results have also been reported for time spent in sedentary pursuits. Compared to rural adolescents, urban adolescents spent more time being sedentary in Australia,[[8]] but less time in Kenya,[[9]] and no difference was reported for Canadian[[6]] and Portuguese adolescents.[[5]] These inconsistent findings may reflect urban–rural differences in social norms, recreational opportunities and infrastructure related to PA, country-specific PA characteristics and/or differences in how rurality is defined.

Understanding PA patterns in different geographical settings is necessary to inform country-specific initiatives and programmes aimed at increasing the low levels of PA among adolescents. New Zealand adolescents live in a range of settings,[[10]] and this study compared accelerometer-measured PA patterns in adolescents living in large, medium and small urban areas and rural settings in the Otago region.

Method

Study design

Secondary data were analysed from two cross-sectional studies conducted in the urban and rural areas of the Otago region, New Zealand. Dunedin city is the only large urban area, and the wider Otago region (population of approximately 225,186) consists of medium urban, small urban and rural areas.[[10]] The 2014–15 Built Environment and Active Transport to School (BEATS) Study was conducted in all 12 Dunedin secondary schools. The 2018 BEATS Rural Study (BEATS-R) was conducted in 11 of 15 regional secondary schools. Both studies used the BEATS research methodology, which has been described in detail elsewhere,[[11]] with data being collected throughout the school year. Both studies were approved by the University of Otago Human Ethics Committee (BEATS: 13/203; BEATS-R: 17/178).

Participants

Briefly, each participating secondary school invited adolescents from one to four classes from years 9 to 13 (ages 13 to 18 years) to participate in the study. In small schools of <100 students, all students were invited. Potential participants received information packages with parent and student information sheets and consents. In the BEATS Study, parental opt-in or parental opt-out consent was used depending on each school’s preference for adolescents aged 13 to 15 years, whereas for the BEATS-R Study no parental consent was required. In both studies, participants were required to sign an additional consent to wear an accelerometer. This analysis included data from 377 adolescents with valid survey and accelerometer data (Figure 1).

Given their school and home address location, participants were classified into four geographical setting categories using Stats NZ definitions:[[10]]

  • large urban area (30,000–99,999 residents; ie, Dunedin city excluding Mosgiel)
  • medium urban area (10,000–29,999 residents)
  • small urban area (1,000–9,999 residents)
  • rural setting (<1000 residents).

The BEATS and BEATS-R studies did not collect data from participants living in major urban areas (>100,000 residents).[[10]] Only participants residing and attending school in the same geographical setting were included in this analysis (ie, participants residing in rural areas but attending a boarding school were excluded) (Figure 1).

Figure 1: Flowchart of participant recruitment and selection for the final study sample.

Measurement procedures

Questionnaire

Participants completed an online survey during one school period (50–60 minutes) under the supervision of research staff. The survey included questions about sociodemographic characteristics, home address, number of vehicles and bicycles at home, transport-to-school habits and sport participation. Participants reported frequency of use of different modes of transport to school. The mode of transport used ‘most of the time’ and ‘all of the time’ informed their transport to school category: ‘active transport’, ‘motorised transport’ or ‘mixed transport’.[[11]] They also reported whether they participated in sports at school and outside school (eg, club sport) with ‘yes’/’no’ responses to each question. Neighbourhood-level socioeconomic status was determined by the home address data being matched with address codes from the New Zealand Index of Deprivation Study.[[12]] Geographic Information Science network analysis was used to calculate the shortest distance to school from each participant’s home address.[[11]]

Anthropometry

Research staff performed anthropometry measurements in a screened-off area of the classroom using standard procedures.[[11]] Height was measured using a stadiometer (BEATS: custom-made portable stadiometer; BEATS-R: portable (SECA213 stadiometer, SECA Corp)) and weight using an electronic scale (A&D scale UC321, A&D Medical).

Accelerometer-measured PA

Participants wore an accelerometer (ActiGraph, GT3XPlus, Pensacola, FL, USA) above their right hip for seven consecutive days, as described elsewhere.[[11,13]] Briefly, research staff instructed them to wear their device for ≥12 hours each day for seven days, and to take it off for sleep, water-based activities (eg, swimming) and contact sports (eg, rugby). To promote adherence, participants were given an activity log to record their accelerometer wear time, sent reminders by email or text and received a $10 book voucher.

Accelerometer data were downloaded in 10-second epochs for the BEATS Study and 15-second epochs for the BEATS-R Study using ActiGraph software and measured in average counts per minute (cpm).[[13]] The wear-time validity was set at ≥5 days, with ≥10 h/day (inclusive of three school days and one weekend day).[[13]] Accelerometer data were analysed by the MeterPlus data analysis service in San Diego, USA, using MeterPlus software (MeterPlus, San Diego, CA, USA) with Evenson’s cut-points.[[14]] Twenty-minute stationary bouts were classified as non-active periods. Processed accelerometer data included time spent in light, moderate, moderate-to-vigorous and vigorous intensity PA and sedentary time for an average day, a weekend day and a school day, as well as before school (08:00–09:00h), early after school (15:00–16:00h) and late after school (16:00–20:00h) on school days.[[13]]

Data analysis

Demographic characteristics were analysed using descriptive statistics. Continuous variables were checked for normality and showed skewness values ≤2 and kurtosis (excess) ≤4, which are indicative of considerable normality for sample sizes >300,[[15]] with the exception of only five variables (distance to school in the total sample; average daily sedentary time; average moderate PA before school; average vigorous PA before and late after school). For continuous variables, differences across geographical settings were compared using ANOVA with Scheffe post-hoc multiple comparisons (or Tamahane’s T2 test, when the assumption of homogeneity of variance was violated). Categorical variables were compared using χ[[2]]-test. Differences between school days versus weekend days were compared using paired t-test for continuous variables and McNemar test for categorical variables. Continuous variables are reported as means ± standard deviation, whereas categorical variables are reported as frequencies (n (%)). An alpha of less than 0.05 was considered statistically significant. Data were analysed using SPSS software (Version 24.0).

Results

Table 1 shows the sociodemographic characteristics of study participants. Among the 377 participants (age: 14.9±1.4 years), 66.8% were female and 75.5% were New Zealand European. Average distance to school was 4.5±5.1 km (median: 3.0km; interquartile range: 4.3km). Age, gender, ethnicity and sport participation rates were not statistically different between geographical settings. Neighbourhood-area deprivation level, car and bicycle ownership, home-to-school distance and rates of active transport to school varied across the geographical settings, with the longest median distance to school and lowest rates of active transport observed in rural settings.

Table 1: Sociodemographic characteristics of study participants.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.

Throughout the week, participants spent on average 9.5 hours (69.2%) of the daily accelerometer wear time in stationary pursuits, 3.5 hours (24.5%) in light intensity PA and 0.9 hours (6.6%) in MVPA per day (Table 2). Specifically, they participated in 54.4±21.0 minutes of MVPA daily (Table 2) and 35.0% met PA guidelines (Table 1). A greater proportion of participants met PA guidelines on school days (40.8%) versus weekend days (26.0%) (p<0.001). On school days, participants spent significantly more time in sedentary activities, moderate and vigorous PA as well as MVPA compared to weekend days (all p<0.05). 

Table 2: Physical activity levels throughout the week.

[[a]] p<0.05 vs. large urban area; [[b]] p<0.05 vs. medium urban area; [[c]] p<0.05 vs. small urban area; [[d]] p<0.05 vs. rural settlement or area. MVPA = moderate to vigorous physical activity; PA = physical activity.

A greater proportion of males, school-sport participants and users of active transport to school met PA guidelines on average school days, compared to their counterparts (Table 3). However, on an average weekend day, no differences were observed between participants who met PA guidelines and those who did not, except for sports participation at school (Table 3).

The average amount of daily MVPA (Table 3) or proportion of participants meeting PA guidelines (Table 1) did not differ across the four geographical setting categories. However, those living in rural areas spent more time in light PA compared to their counterparts from large and medium urban areas, and less time in stationary pursuits compared to those from large urban areas (Table 2). Similar patterns were observed on average school days. On weekend days, rural adolescents engaged in significantly more light PA compared to their urban counterparts, whereas no significant difference existed across geographical settings for the amount of time participants spent in stationary pursuits.

PA patterns on school days also varied across geographical settings. During the hour before school (8:00–9:00h), participants living in large and medium urban areas spent significantly more time in MVPA than those from small urban areas and rural settings (Table 4). In addition, participants from large and medium urban areas spent significantly more time in MVPA during early after school (15:00–16:00h) than those from rural areas; however, no difference was found for small urban areas (Table 4). During the late after school period (16:00–20:00h), participants living in urban areas spent significantly more time in stationary pursuits and less time in light PA compared to their rural counterparts (Table 4).  

Table 3: Characteristics of participants who met and did not meet physical activity recommendations.

Table 4: Physical activity levels throughout an average school day in participants across geographical settings.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.MVPA = moderate to vigorous physical activity; PA = physical activity.

Discussion

Key findings of this study are: (1) Less than half of Otago adolescents meet PA guidelines overall; (2) A greater proportions of adolescents meeting PA guidelines were male, participated in school sports and used active transport to school; (3) Although the proportion of adolescents meeting PA guidelines was not significantly different across geographical settings, those in large urban areas spent more time being stationary but accumulated more MVPA during the school commute time compared to their rural counterparts.

Taken together, these findings show that engagement in PA in Otago adolescents is lower than recommended for the majority and should be encouraged across all geographical settings, particularly during weekends.

Using device-measured PA, 35% of Otago adolescents met the PA guidelines and on average engaged in 54.4±21.0 minutes of MPVA per day with no significant differences by geographical setting. These findings are consistent with estimates of 27–33% of children and adolescents meeting recommended PA levels worldwide.[[4,16]] However, if these New Zealand adolescents as a group were to increase their daily PA by six minutes (approximately 10% of their daily activity), they would meet the guidelines. This seems like an achievable public health target.

Previous studies that compared PA across urbanisation settings reported higher levels of MVPA in urban compared to rural adolescents in Portugal,[[5]] Canada[[17]] and the United States.[[18,19]] Greater access to recreational facilities in urban compared to rural areas,[[20]] and consequently better access to organised sports and recreational activities,[[21]] may in part explain these findings. However, in the present study no difference in MVPA was observed among Otago adolescents living in the four geographical settings, although rural adolescents spent more time in light PA compared to their urban peers. It is highly likely that rural adolescents in New Zealand have more access to open green spaces and natural environments compared to their urban counterparts.[[22]] Greenness exposure has been associated with higher levels of MVPA among American children.[[23]] Nevertheless, the PA levels in Otago adolescents are low in both urban and rural areas, reinforcing the need for effective interventions to encourage PA in all New Zealand adolescents, irrespective of setting. In addition, given the limitations of self-reports,[[24,25]] more research employing direct measures (eg, accelerometers, pedometers, inclinometers) of the PA and sedentary behaviour of New Zealand youth will further contribute to understanding how patterns of such behaviour interact in diverse geographical locations across the country.

A greater proportion of adolescents who met PA guidelines in this study were male, used active transport to school and participated in school sports. These findings are consistent with those reported elsewhere.[[1,26]] In the Asia–Pacific region, rates of active transport to school vary by gender, with different patterns across countries.[[27]] Differences in active transport may also further contribute to gender differences in overall PA among adolescents observed in this and other studies.[[27]] As active-transport-to-school rates are lower than motorised-transport rates and continue to decline in New Zealand,[[4]] active transport should continue to be promoted as a way to increase PA among adolescents, particularly females. Possible ways to encourage active transport to school in diverse geographic settings include strong social support, creating safe walking and cycling routes to school through built environment changes and encouraging mixed transport for adolescents who live beyond walking and/or cycling distance to their school.

The finding that a greater proportion of adolescents who met PA guidelines participated in organised sports compared to their counterparts is also consistent with other studies.[[26]] Recent New Zealand data showed that 81% of 5–17 year olds participated in organised sports and 54% of those aged 13–18 years engaged in school sports.[[4]] Many factors contribute to adolescents’ sports participation, including individual characteristics, family socioeconomic status[[28]] and a supportive sport environment.[[26]] Previous Otago research showed that factors related to a supportive sport environment, such as provision of sport grounds at school, quality of sport management and availability of sports outside school, were associated with the time adolescents spent participating in sport.[[26]] Thus, future initiatives and programmes designed for promoting adolescents’ PA through organised sport participation should focus on providing well-organised and supportive sport environments in both urban and rural areas of New Zealand.

Adolescents in this study spent on average 9.5 hours being stationary. Those from large urban areas spent a significantly higher proportion of time in stationary pursuits (particularly in the time periods early after school and late after school) compared to their peers from rural areas. Given that light PA is considered the antidote to sedentary behaviour,[[29]] children in rural areas in New Zealand may be avoiding sedentary behaviour by engaging in more active and outdoor play than those in larger urban communities. Previous studies reported that adolescents from developed countries spend approximately 6–10 hours per day being sedentary.[[30,31]] Accelerometer-based studies that compared sedentary time between urban and rural adolescents reported inconsistent results.[[5,6,8,9]] Among Portuguese adolescents, urban female adolescents spent significantly more time in sedentary pursuits compared to their rural counterparts.[[5]] In the United Kingdom, technology-based sedentary behaviour was the most common after school activity among adolescents.[[32]] Among 9–16-year-old Australians, screen time was higher among urban males compared to rural males, but no difference was found among females.[[33]] The discrepancies between findings from studies could be due to different definitions of ‘rurality’: based on accessibility,[[8,9]] or population size,[[5,6]] or because of different availability of services, facilities and recreation spaces within urban and rural areas in New Zealand compared to other countries.[[34]] In addition, differences are likely to exist in what qualifies as sedentary behaviour. As Otago adolescents spend a significant amount of time in stationary pursuits, future interventions should focus on reducing sedentary time by reducing recreational screen time and encouraging outdoor activities[[4]] among New Zealand adolescents in both urban and rural areas. For adolescents living in large urban areas, such interventions should include efforts to increase active-transport-to-school rates and to reduce education-based sedentary time through the introduction of regular activity breaks.[[35]]

The strengths of this study include the device-based measurement of PA; the inclusion of participants living in different geographical settings with geographically matched participants’ home and school location; high school participation rates across the region; and PA being analysed at different times throughout the school day and on weekend days. However, there are limitations that should be acknowledged. Although accelerometers measure a range of movements in multiple planes, they cannot measure upper-body movements, movement on a graded terrain and movement in activities such as swimming and cycling, which may limit the validity of PA data among participants who regularly participate in those physical activities. Future research should improve the utility of accelerometers for assessing swimming, cycling, upper-body and graded-terrain PA. Additional limitations include the 3–4 year gap between the BEATS and BEATS-R studies data collection; the difference in length of epoch for accelerometer data collection between the two studies; a relatively small sample size in some geographical settings; and a lack of data on reasons for adolescents not consenting to participate in this assessment. Although the findings may not be generalisable to other geographical regions within New Zealand or to other countries, our results are consistent with international findings and provide further insight into understanding PA among adolescents in different environments.

The proportion of Otago adolescents meeting recommended PA levels was low. But a small increase in daily PA levels (eg, six minutes) would see most adolescents meeting current guidelines. Continuous encouragement of PA is needed for adolescents across urban and rural settings. New Zealand already provides substantial support for PA within school, community and environmental settings, as well as at the government/policy level.[[4]] Future initiatives to increase PA among New Zealand adolescents should focus on facilitating active transport to school (eg, through initiatives such as creating safe walking and cycling routes to school),[[36]] promoting inclusive sport participation[[26]] and increasing peer and family support for PA.[[4]]

Summary

Abstract

4AIM: This study compared accelerometer-measured physical activity (PA) patterns in adolescents living in diverse urban and rural areas of Otago, New Zealand. METHOD: Participants (n=377; age: 14.9±1.4 years; 66.8% female; 23 schools) completed an online school travel survey, anthropometry and seven-day PA accelerometer assessment. Participants resided in large (n=237), medium (n=45) and small (n=44) urban areas or rural settings (n=51). RESULTS: Overall, participants participated in 54.4±21.0 minutes of moderate-to-vigorous physical activity (MVPA) daily and 35.0% met PA guidelines (school day vs weekend day: 40.8% vs 26.0%; p<0.001) with no difference across geographical settings. A greater proportion of males (43.2% vs 31.9%; p=0.016), school sport participants (70.1% vs 54.0%; p=0.005) and active-transport-to-school users (40.2% vs 26.1%) met PA guidelines compared to their counterparts. Compared to rural adolescents, those from large urban areas accumulated more MVPA during the school commute time (before school: 8.3±6.7 vs 5.3±3.8 minutes, p<0.001; after school: 10.1±6.0 vs 7.7±4.3 min, p=0.003), but overall spent more time sedentary (584.9±84.7 vs 527.8±88.2 minutes/day; p<0.001). CONCLUSION: PA in Otago adolescents is low, with significant differences by gender, sport participation, mode of travel to school and geographical setting. Increased PA should be encouraged in both urban and rural adolescents.

Aim

Method

Results

Conclusion

Author Information

Brittany White: Master of Science Graduate, School of Physical Education, Sport and Exercise Sciences, University of Otago, Dunedin. Enrique García Bengoechea: Succeed & Lead Fellow, Physical Activity for Health, Health Research Institute, Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland. John C Spence: Professor, Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, Alberta, Canada. Kirsten J Coppell: Public Health Physician and Research Associate Professor, Department of Medicine, University of Otago, Dunedin. Sandra Mandic: Adjunct Professor, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Research Affiliate, Centre for Sustainability, University of Otago, Dunedin.

Acknowledgements

The BEATS Study was supported by the Health Research Council of New Zealand Emerging Researcher First Grant (14/565), National Heart Foundation of New Zealand (1602 and 1615), Lottery Health Research Grant (Applic 341129), University of Otago Research Grant (UORG 2014) and the Dunedin City Council. The BEATS Rural Study was supported by the University of Otago Research Grant (UORG 2018) and Otago Energy Research Centre Seed Grant. Brittany White was supported by the University of Otago Masters Scholarship. The authors would like to acknowledge BEATS investigators and Advisory Board members, research personnel (research assistants, students and volunteers) and all participating schools and adolescents.

Correspondence

Sandra Mandic, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand, +64 21 0902 0025

Correspondence Email

sandy.mandic@aut.ac.nz

Competing Interests

Nil.

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Adolescents’ physical activity (PA) is influenced by an interaction of individual, social and environmental factors.[[1]] Societal changes over recent decades have markedly reduced the need and opportunities for PA in daily life and imposed multiple barriers to PA across all PA domains: transport, leisure and recreation, school/workplace and household. In adolescents, PA has been associated with improved cardiorespiratory fitness, muscular endurance and strength and the prevention of non-communicable diseases.[[2]] To gain health benefits, adolescents need to accumulate at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily.[[2]] However, recent evidence suggests there are high rates of physical inactivity and time spent stationary among adolescents globally,[[3]] including New Zealand.[[4]] Worldwide, 81% of 11–17 year olds did not meet current guidelines for recommended levels of physical activity in 2016, while 89% of New Zealanders in this age group did not achieve recommended levels.[[3]]

Most studies examining adolescent PA have been conducted in urban areas. However, due to contextual differences (eg, population density, access to facilities, social and cultural norms), PA patterns observed among urban adolescents may not be generalisable to rural adolescents. Studies that compare device-measured PA in adolescents living in urban versus rural settings show inconsistent results. Although most report that urban adolescents accumulate more accelerometer-measured MVPA compared to rural adolescents,[[5,6]] one study in the United States found that PA was higher in adolescents living in rural compared to urban areas.[[7]] Similarly, inconsistent results have also been reported for time spent in sedentary pursuits. Compared to rural adolescents, urban adolescents spent more time being sedentary in Australia,[[8]] but less time in Kenya,[[9]] and no difference was reported for Canadian[[6]] and Portuguese adolescents.[[5]] These inconsistent findings may reflect urban–rural differences in social norms, recreational opportunities and infrastructure related to PA, country-specific PA characteristics and/or differences in how rurality is defined.

Understanding PA patterns in different geographical settings is necessary to inform country-specific initiatives and programmes aimed at increasing the low levels of PA among adolescents. New Zealand adolescents live in a range of settings,[[10]] and this study compared accelerometer-measured PA patterns in adolescents living in large, medium and small urban areas and rural settings in the Otago region.

Method

Study design

Secondary data were analysed from two cross-sectional studies conducted in the urban and rural areas of the Otago region, New Zealand. Dunedin city is the only large urban area, and the wider Otago region (population of approximately 225,186) consists of medium urban, small urban and rural areas.[[10]] The 2014–15 Built Environment and Active Transport to School (BEATS) Study was conducted in all 12 Dunedin secondary schools. The 2018 BEATS Rural Study (BEATS-R) was conducted in 11 of 15 regional secondary schools. Both studies used the BEATS research methodology, which has been described in detail elsewhere,[[11]] with data being collected throughout the school year. Both studies were approved by the University of Otago Human Ethics Committee (BEATS: 13/203; BEATS-R: 17/178).

Participants

Briefly, each participating secondary school invited adolescents from one to four classes from years 9 to 13 (ages 13 to 18 years) to participate in the study. In small schools of <100 students, all students were invited. Potential participants received information packages with parent and student information sheets and consents. In the BEATS Study, parental opt-in or parental opt-out consent was used depending on each school’s preference for adolescents aged 13 to 15 years, whereas for the BEATS-R Study no parental consent was required. In both studies, participants were required to sign an additional consent to wear an accelerometer. This analysis included data from 377 adolescents with valid survey and accelerometer data (Figure 1).

Given their school and home address location, participants were classified into four geographical setting categories using Stats NZ definitions:[[10]]

  • large urban area (30,000–99,999 residents; ie, Dunedin city excluding Mosgiel)
  • medium urban area (10,000–29,999 residents)
  • small urban area (1,000–9,999 residents)
  • rural setting (<1000 residents).

The BEATS and BEATS-R studies did not collect data from participants living in major urban areas (>100,000 residents).[[10]] Only participants residing and attending school in the same geographical setting were included in this analysis (ie, participants residing in rural areas but attending a boarding school were excluded) (Figure 1).

Figure 1: Flowchart of participant recruitment and selection for the final study sample.

Measurement procedures

Questionnaire

Participants completed an online survey during one school period (50–60 minutes) under the supervision of research staff. The survey included questions about sociodemographic characteristics, home address, number of vehicles and bicycles at home, transport-to-school habits and sport participation. Participants reported frequency of use of different modes of transport to school. The mode of transport used ‘most of the time’ and ‘all of the time’ informed their transport to school category: ‘active transport’, ‘motorised transport’ or ‘mixed transport’.[[11]] They also reported whether they participated in sports at school and outside school (eg, club sport) with ‘yes’/’no’ responses to each question. Neighbourhood-level socioeconomic status was determined by the home address data being matched with address codes from the New Zealand Index of Deprivation Study.[[12]] Geographic Information Science network analysis was used to calculate the shortest distance to school from each participant’s home address.[[11]]

Anthropometry

Research staff performed anthropometry measurements in a screened-off area of the classroom using standard procedures.[[11]] Height was measured using a stadiometer (BEATS: custom-made portable stadiometer; BEATS-R: portable (SECA213 stadiometer, SECA Corp)) and weight using an electronic scale (A&D scale UC321, A&D Medical).

Accelerometer-measured PA

Participants wore an accelerometer (ActiGraph, GT3XPlus, Pensacola, FL, USA) above their right hip for seven consecutive days, as described elsewhere.[[11,13]] Briefly, research staff instructed them to wear their device for ≥12 hours each day for seven days, and to take it off for sleep, water-based activities (eg, swimming) and contact sports (eg, rugby). To promote adherence, participants were given an activity log to record their accelerometer wear time, sent reminders by email or text and received a $10 book voucher.

Accelerometer data were downloaded in 10-second epochs for the BEATS Study and 15-second epochs for the BEATS-R Study using ActiGraph software and measured in average counts per minute (cpm).[[13]] The wear-time validity was set at ≥5 days, with ≥10 h/day (inclusive of three school days and one weekend day).[[13]] Accelerometer data were analysed by the MeterPlus data analysis service in San Diego, USA, using MeterPlus software (MeterPlus, San Diego, CA, USA) with Evenson’s cut-points.[[14]] Twenty-minute stationary bouts were classified as non-active periods. Processed accelerometer data included time spent in light, moderate, moderate-to-vigorous and vigorous intensity PA and sedentary time for an average day, a weekend day and a school day, as well as before school (08:00–09:00h), early after school (15:00–16:00h) and late after school (16:00–20:00h) on school days.[[13]]

Data analysis

Demographic characteristics were analysed using descriptive statistics. Continuous variables were checked for normality and showed skewness values ≤2 and kurtosis (excess) ≤4, which are indicative of considerable normality for sample sizes >300,[[15]] with the exception of only five variables (distance to school in the total sample; average daily sedentary time; average moderate PA before school; average vigorous PA before and late after school). For continuous variables, differences across geographical settings were compared using ANOVA with Scheffe post-hoc multiple comparisons (or Tamahane’s T2 test, when the assumption of homogeneity of variance was violated). Categorical variables were compared using χ[[2]]-test. Differences between school days versus weekend days were compared using paired t-test for continuous variables and McNemar test for categorical variables. Continuous variables are reported as means ± standard deviation, whereas categorical variables are reported as frequencies (n (%)). An alpha of less than 0.05 was considered statistically significant. Data were analysed using SPSS software (Version 24.0).

Results

Table 1 shows the sociodemographic characteristics of study participants. Among the 377 participants (age: 14.9±1.4 years), 66.8% were female and 75.5% were New Zealand European. Average distance to school was 4.5±5.1 km (median: 3.0km; interquartile range: 4.3km). Age, gender, ethnicity and sport participation rates were not statistically different between geographical settings. Neighbourhood-area deprivation level, car and bicycle ownership, home-to-school distance and rates of active transport to school varied across the geographical settings, with the longest median distance to school and lowest rates of active transport observed in rural settings.

Table 1: Sociodemographic characteristics of study participants.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.

Throughout the week, participants spent on average 9.5 hours (69.2%) of the daily accelerometer wear time in stationary pursuits, 3.5 hours (24.5%) in light intensity PA and 0.9 hours (6.6%) in MVPA per day (Table 2). Specifically, they participated in 54.4±21.0 minutes of MVPA daily (Table 2) and 35.0% met PA guidelines (Table 1). A greater proportion of participants met PA guidelines on school days (40.8%) versus weekend days (26.0%) (p<0.001). On school days, participants spent significantly more time in sedentary activities, moderate and vigorous PA as well as MVPA compared to weekend days (all p<0.05). 

Table 2: Physical activity levels throughout the week.

[[a]] p<0.05 vs. large urban area; [[b]] p<0.05 vs. medium urban area; [[c]] p<0.05 vs. small urban area; [[d]] p<0.05 vs. rural settlement or area. MVPA = moderate to vigorous physical activity; PA = physical activity.

A greater proportion of males, school-sport participants and users of active transport to school met PA guidelines on average school days, compared to their counterparts (Table 3). However, on an average weekend day, no differences were observed between participants who met PA guidelines and those who did not, except for sports participation at school (Table 3).

The average amount of daily MVPA (Table 3) or proportion of participants meeting PA guidelines (Table 1) did not differ across the four geographical setting categories. However, those living in rural areas spent more time in light PA compared to their counterparts from large and medium urban areas, and less time in stationary pursuits compared to those from large urban areas (Table 2). Similar patterns were observed on average school days. On weekend days, rural adolescents engaged in significantly more light PA compared to their urban counterparts, whereas no significant difference existed across geographical settings for the amount of time participants spent in stationary pursuits.

PA patterns on school days also varied across geographical settings. During the hour before school (8:00–9:00h), participants living in large and medium urban areas spent significantly more time in MVPA than those from small urban areas and rural settings (Table 4). In addition, participants from large and medium urban areas spent significantly more time in MVPA during early after school (15:00–16:00h) than those from rural areas; however, no difference was found for small urban areas (Table 4). During the late after school period (16:00–20:00h), participants living in urban areas spent significantly more time in stationary pursuits and less time in light PA compared to their rural counterparts (Table 4).  

Table 3: Characteristics of participants who met and did not meet physical activity recommendations.

Table 4: Physical activity levels throughout an average school day in participants across geographical settings.

[[a]] p<0.05 vs large urban area; [[b]] p<0.05 vs medium urban area; [[c]] p<0.05 vs small urban area; [[d]] p<0.05 vs rural settlement or area.MVPA = moderate to vigorous physical activity; PA = physical activity.

Discussion

Key findings of this study are: (1) Less than half of Otago adolescents meet PA guidelines overall; (2) A greater proportions of adolescents meeting PA guidelines were male, participated in school sports and used active transport to school; (3) Although the proportion of adolescents meeting PA guidelines was not significantly different across geographical settings, those in large urban areas spent more time being stationary but accumulated more MVPA during the school commute time compared to their rural counterparts.

Taken together, these findings show that engagement in PA in Otago adolescents is lower than recommended for the majority and should be encouraged across all geographical settings, particularly during weekends.

Using device-measured PA, 35% of Otago adolescents met the PA guidelines and on average engaged in 54.4±21.0 minutes of MPVA per day with no significant differences by geographical setting. These findings are consistent with estimates of 27–33% of children and adolescents meeting recommended PA levels worldwide.[[4,16]] However, if these New Zealand adolescents as a group were to increase their daily PA by six minutes (approximately 10% of their daily activity), they would meet the guidelines. This seems like an achievable public health target.

Previous studies that compared PA across urbanisation settings reported higher levels of MVPA in urban compared to rural adolescents in Portugal,[[5]] Canada[[17]] and the United States.[[18,19]] Greater access to recreational facilities in urban compared to rural areas,[[20]] and consequently better access to organised sports and recreational activities,[[21]] may in part explain these findings. However, in the present study no difference in MVPA was observed among Otago adolescents living in the four geographical settings, although rural adolescents spent more time in light PA compared to their urban peers. It is highly likely that rural adolescents in New Zealand have more access to open green spaces and natural environments compared to their urban counterparts.[[22]] Greenness exposure has been associated with higher levels of MVPA among American children.[[23]] Nevertheless, the PA levels in Otago adolescents are low in both urban and rural areas, reinforcing the need for effective interventions to encourage PA in all New Zealand adolescents, irrespective of setting. In addition, given the limitations of self-reports,[[24,25]] more research employing direct measures (eg, accelerometers, pedometers, inclinometers) of the PA and sedentary behaviour of New Zealand youth will further contribute to understanding how patterns of such behaviour interact in diverse geographical locations across the country.

A greater proportion of adolescents who met PA guidelines in this study were male, used active transport to school and participated in school sports. These findings are consistent with those reported elsewhere.[[1,26]] In the Asia–Pacific region, rates of active transport to school vary by gender, with different patterns across countries.[[27]] Differences in active transport may also further contribute to gender differences in overall PA among adolescents observed in this and other studies.[[27]] As active-transport-to-school rates are lower than motorised-transport rates and continue to decline in New Zealand,[[4]] active transport should continue to be promoted as a way to increase PA among adolescents, particularly females. Possible ways to encourage active transport to school in diverse geographic settings include strong social support, creating safe walking and cycling routes to school through built environment changes and encouraging mixed transport for adolescents who live beyond walking and/or cycling distance to their school.

The finding that a greater proportion of adolescents who met PA guidelines participated in organised sports compared to their counterparts is also consistent with other studies.[[26]] Recent New Zealand data showed that 81% of 5–17 year olds participated in organised sports and 54% of those aged 13–18 years engaged in school sports.[[4]] Many factors contribute to adolescents’ sports participation, including individual characteristics, family socioeconomic status[[28]] and a supportive sport environment.[[26]] Previous Otago research showed that factors related to a supportive sport environment, such as provision of sport grounds at school, quality of sport management and availability of sports outside school, were associated with the time adolescents spent participating in sport.[[26]] Thus, future initiatives and programmes designed for promoting adolescents’ PA through organised sport participation should focus on providing well-organised and supportive sport environments in both urban and rural areas of New Zealand.

Adolescents in this study spent on average 9.5 hours being stationary. Those from large urban areas spent a significantly higher proportion of time in stationary pursuits (particularly in the time periods early after school and late after school) compared to their peers from rural areas. Given that light PA is considered the antidote to sedentary behaviour,[[29]] children in rural areas in New Zealand may be avoiding sedentary behaviour by engaging in more active and outdoor play than those in larger urban communities. Previous studies reported that adolescents from developed countries spend approximately 6–10 hours per day being sedentary.[[30,31]] Accelerometer-based studies that compared sedentary time between urban and rural adolescents reported inconsistent results.[[5,6,8,9]] Among Portuguese adolescents, urban female adolescents spent significantly more time in sedentary pursuits compared to their rural counterparts.[[5]] In the United Kingdom, technology-based sedentary behaviour was the most common after school activity among adolescents.[[32]] Among 9–16-year-old Australians, screen time was higher among urban males compared to rural males, but no difference was found among females.[[33]] The discrepancies between findings from studies could be due to different definitions of ‘rurality’: based on accessibility,[[8,9]] or population size,[[5,6]] or because of different availability of services, facilities and recreation spaces within urban and rural areas in New Zealand compared to other countries.[[34]] In addition, differences are likely to exist in what qualifies as sedentary behaviour. As Otago adolescents spend a significant amount of time in stationary pursuits, future interventions should focus on reducing sedentary time by reducing recreational screen time and encouraging outdoor activities[[4]] among New Zealand adolescents in both urban and rural areas. For adolescents living in large urban areas, such interventions should include efforts to increase active-transport-to-school rates and to reduce education-based sedentary time through the introduction of regular activity breaks.[[35]]

The strengths of this study include the device-based measurement of PA; the inclusion of participants living in different geographical settings with geographically matched participants’ home and school location; high school participation rates across the region; and PA being analysed at different times throughout the school day and on weekend days. However, there are limitations that should be acknowledged. Although accelerometers measure a range of movements in multiple planes, they cannot measure upper-body movements, movement on a graded terrain and movement in activities such as swimming and cycling, which may limit the validity of PA data among participants who regularly participate in those physical activities. Future research should improve the utility of accelerometers for assessing swimming, cycling, upper-body and graded-terrain PA. Additional limitations include the 3–4 year gap between the BEATS and BEATS-R studies data collection; the difference in length of epoch for accelerometer data collection between the two studies; a relatively small sample size in some geographical settings; and a lack of data on reasons for adolescents not consenting to participate in this assessment. Although the findings may not be generalisable to other geographical regions within New Zealand or to other countries, our results are consistent with international findings and provide further insight into understanding PA among adolescents in different environments.

The proportion of Otago adolescents meeting recommended PA levels was low. But a small increase in daily PA levels (eg, six minutes) would see most adolescents meeting current guidelines. Continuous encouragement of PA is needed for adolescents across urban and rural settings. New Zealand already provides substantial support for PA within school, community and environmental settings, as well as at the government/policy level.[[4]] Future initiatives to increase PA among New Zealand adolescents should focus on facilitating active transport to school (eg, through initiatives such as creating safe walking and cycling routes to school),[[36]] promoting inclusive sport participation[[26]] and increasing peer and family support for PA.[[4]]

Summary

Abstract

4AIM: This study compared accelerometer-measured physical activity (PA) patterns in adolescents living in diverse urban and rural areas of Otago, New Zealand. METHOD: Participants (n=377; age: 14.9±1.4 years; 66.8% female; 23 schools) completed an online school travel survey, anthropometry and seven-day PA accelerometer assessment. Participants resided in large (n=237), medium (n=45) and small (n=44) urban areas or rural settings (n=51). RESULTS: Overall, participants participated in 54.4±21.0 minutes of moderate-to-vigorous physical activity (MVPA) daily and 35.0% met PA guidelines (school day vs weekend day: 40.8% vs 26.0%; p<0.001) with no difference across geographical settings. A greater proportion of males (43.2% vs 31.9%; p=0.016), school sport participants (70.1% vs 54.0%; p=0.005) and active-transport-to-school users (40.2% vs 26.1%) met PA guidelines compared to their counterparts. Compared to rural adolescents, those from large urban areas accumulated more MVPA during the school commute time (before school: 8.3±6.7 vs 5.3±3.8 minutes, p<0.001; after school: 10.1±6.0 vs 7.7±4.3 min, p=0.003), but overall spent more time sedentary (584.9±84.7 vs 527.8±88.2 minutes/day; p<0.001). CONCLUSION: PA in Otago adolescents is low, with significant differences by gender, sport participation, mode of travel to school and geographical setting. Increased PA should be encouraged in both urban and rural adolescents.

Aim

Method

Results

Conclusion

Author Information

Brittany White: Master of Science Graduate, School of Physical Education, Sport and Exercise Sciences, University of Otago, Dunedin. Enrique García Bengoechea: Succeed & Lead Fellow, Physical Activity for Health, Health Research Institute, Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland. John C Spence: Professor, Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, Alberta, Canada. Kirsten J Coppell: Public Health Physician and Research Associate Professor, Department of Medicine, University of Otago, Dunedin. Sandra Mandic: Adjunct Professor, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Research Affiliate, Centre for Sustainability, University of Otago, Dunedin.

Acknowledgements

The BEATS Study was supported by the Health Research Council of New Zealand Emerging Researcher First Grant (14/565), National Heart Foundation of New Zealand (1602 and 1615), Lottery Health Research Grant (Applic 341129), University of Otago Research Grant (UORG 2014) and the Dunedin City Council. The BEATS Rural Study was supported by the University of Otago Research Grant (UORG 2018) and Otago Energy Research Centre Seed Grant. Brittany White was supported by the University of Otago Masters Scholarship. The authors would like to acknowledge BEATS investigators and Advisory Board members, research personnel (research assistants, students and volunteers) and all participating schools and adolescents.

Correspondence

Sandra Mandic, School of Sport and Recreation, Faculty of Health and Environmental Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand, +64 21 0902 0025

Correspondence Email

sandy.mandic@aut.ac.nz

Competing Interests

Nil.

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