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Physical activity among indigenous Australian children and youth in remote and non-remote areas
Accepted Manuscript Physical activity among indigenous Australian children and youth in remote and nonremote areas John Robert Evans, Rachel Wilson, Clare Coleman, Wing Man, Tim Olds PII:
S0277-9536(18)30185-0
DOI:
10.1016/j.socscimed.2018.04.018
Reference:
SSM 11698
To appear in:
Social Science & Medicine
Received Date: 16 November 2017 Revised Date:
12 March 2018
Accepted Date: 13 April 2018
Please cite this article as: Evans, J.R., Wilson, R., Coleman, C., Man, W., Olds, T., Physical activity among indigenous Australian children and youth in remote and non-remote areas, Social Science & Medicine (2018), doi: 10.1016/j.socscimed.2018.04.018. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas John Robert Evans,
Rachel Wilson,
Clare Coleman,
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University of Sydney
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University of Technology Sydney
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University of Sydney
Wing Man,
University of Sydney
Tim Olds,
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University of South Australia
Corresponding Author:
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Dr. Rachel Wilson
Sydney School of Education & Social Work
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Faculty of Arts and Social Sciences Building A35, Manning road. University of Sydney
Camperdown, NSW 2600 Australia
Email: [email protected] Ph: + 61 2 93516390 1
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas Abstract
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Sport and physical activity (PA) hold particular significance in Australian Indigenous communities, and have the potential to address many of the health and education
challenges faced by Indigenous communities. Optimal levels of PA are an important
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foundation in efforts to build healthy communities and reduce social disadvantage experienced to date. Yet little evidence relating to the current levels of PA within
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these communities, or the relationship between PA and outcomes, has been available.
Drawing on national survey data from the Australian Bureau of Statistics, we examine levels of PA in the Australian Aboriginal and Torres Strait Islander Health
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Survey 2012-13. These data describe PA levels among Indigenous Australians, aged 5 to 17 years, in remote and non-remote communities. We also examine the relationship between PA and participation in education and self-reported health among 15-17 year
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olds.
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Overall, participation rates appear to be high, with 64-84% of youth reporting at least 60 min of PA on the previous day. A gender gap was also evident, with lower levels of activity among girls. PA decreased with age, particularly at or around the age of puberty. There were no significant associations between PA and either self-reported health or engagement in study. There was a relationship between high PA and low
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ACCEPTED MANUSCRIPT area-level socio-economic status in remote areas, but no association in non-remote areas.
The differences between remote and non-remote areas highlight the importance of
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disaggregated analysis of Indigenous populations and are consistent with qualitative
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studies identifying locally contextualised factors influential in promoting PA.
KEYWORDS: physical activity; Indigenous; Australia; sport; health; education;
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remote; community
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ACCEPTED MANUSCRIPT Introduction There is now an emerging international focus on the role of physical activity (PA) and sport in the broader public health context. In 2012 as part of the London Olympics, The Lancet Medical Journal established The Lancet Physical Activity Observatory
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(LPAO) to examine worldwide trends in physical activity and its repercussions. They found that:
“One third of adults and 80% of adolescents around the world do not reach
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recommended levels for daily physical activity (30 min and 60 min of physical activity of moderate-to-vigorous intensity per day for adults and adolescents,
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respectively). Physical inactivity was shown to be responsible for 5.3 million deaths per year worldwide. If inactivity decreased by only 10%, half a million deaths could be averted every year” (Hallal, Martins, & Ramírez, 2014, p. 471).
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Many factors contribute to population levels of physical activity. One important factor is place of residence, and conditions can vary widely within a country. Internationally, countries appear to be situated at different points on a common
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developmental trajectory (Zuckerman, 2014), marked by an “epidemiological
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transition” which occurs at a point characterised by decreasing physical activity associated with increasing automation and motorisation, and a switch from unprocessed to highly processed foods (Popkin, 1994). The transition is marked by a reversal of associations between socio-economic status (SES) and fatness and PA: in pre-transition areas, low SES individuals are leaner and more active; in posttransition areas, low SES individuals — including children — tend to be fatter and
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ACCEPTED MANUSCRIPT less active (Broyles et al., 2015). In this paper we explore these issues in relation to Indigenous Australian communities in remote and non-remote locations.
Sport and physical activity together with healthy outdoor pursuits continue to define
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Australia’s place in the world (Light, 2006; Tatz, 2009). They also have a history as
important activities that bind communities especially in urban, rural and remote areas (Light, 2006; Spaaij, 2009a, 2009b; Tonts & Atherley, 2010). Sport is a central
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cultural practice in Australia where it holds unusual significance and symbolic
meaning (Stoddart, 1986) and has played an important role in shaping our national
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identity. Australia is one of a few countries which has a highly sophisticated government-funded sports program which serves both community and elite interests (Crawford, 2004; Phillips, 2000).
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The particular importance of sport to Indigenous Australian communities and the success of Indigenous elite athletes in the Australian sporting landscape has been well documented (Tatz 1995, Hallinan & Judd 2009; Norman 2012). Sports, such as rugby
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league and Australian Rules football, form important mechanisms for promoting
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community identity and cohesion in Indigenous communities (Bamblett, 2013; Norman, 2006). Indigenous athletes have made an outstanding contribution to Australia’s national and international sporting success for a very long time, often against a backdrop of racism and limited opportunity (Klugman & Osmond, 2013; Tatz, 2009; Tatz & Adair, 2009). Yet, while Australia’s Indigenous athletes have been glorified for their success in sport, it has been suggested that this has diverted attention from broader community-level participation in physical activity, and also 4
ACCEPTED MANUSCRIPT under-achievement in other areas of life such as education, employment and access to adequate housing and health, perpetuating an enduring inequality of Australian life (Altman, Biddle, & Hunter, 2009; Evans, Wilson, Dalton & Georgakis, 2015;
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Marmot, 2011; Marmot, Friel, Bell, Houweling, & Taylor, 2008).
Sport, physical activities and recreational activities were established as pedagogical
and life learning endeavours for Indigenous communities prior to colonisation and the
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introduction of Anglo-Celtic games (Edwards, 1999; Maynard, 2011; Whimpress,
1999). For many Indigenous children and young adults sport is a vital vehicle through
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which they socialise and also find opportunities to overcome social inequities through opportunities to participate and excel (Veal, Lynch, & Darcy, 2013). In rural areas PA and sport may be the only avenue for Indigenous Australians to be involved in the
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wider community (Tonts & Atherley, 2010), as Tatz’s points out:
Sport is a major element in contemporary Aboriginal life: it provides meaning, a sense of purpose and belonging; it is inclusive and embracing in a world
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where most Aboriginal youth feel alienated, disempowered, rejected and
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excluded (p.922).
Over the last two decades ‘sport as development’ has emerged on the global stage and sport is often seen as a tool that can be used to improve outcomes in areas where there is significant disadvantage (Carson, 2007), including Australian Indigenous communities (Evans, Wilson, Dalton, Georgakis, 2015). This has been matched by a growing realisation that Indigenous health is best understood within wider historical, 5
ACCEPTED MANUSCRIPT political, social, or psychological worlds (Le Grande, Ski, Thompson, Scuffham, Kularatna, Jackson & Brown, 2017) where sport and physical activity sit prominently.
Sport as a development activity has been viewed as a vehicle that transcends
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conservative traditional approaches, and that “reaches communities with messages in a way that politicians, multilateral agencies and NGOs cannot” (Levermore, 2008, p. 183). In Indigenous communities sport has also been identified as an area where
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community leadership has led to health- and education-related interventions, targeting outcomes as diverse as domestic violence, diabetes, smoking cessation and suicide
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prevention (Doyle, Firebrace, Reilly, Crumpen, & Rowley, 2013; Norman, 2012; Tatz, 2012). While remaining positive about sport, Levermore (2008) makes the point that further evaluation and empirical research is required to determine if the claims about development are in fact as plausible as many propose. He concludes by
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remarking; “The use of sport for developmental purposes should be considered in a more nuanced manner, and evaluated relative to other engines of development” (ibid
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p.189).
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At a national level in Australia, physical activity in Indigenous communities has been identified as a potential lever in the Closing the Gap approach outlined in strategies by the Council of Australian Governments (Ware & Meredith, 2013). These recognise that overcoming Indigenous disadvantage requires long-term generational commitment that will see major efforts directed across a number of strategic platforms or “Building Blocks including, Economic Participation (through employment opportunities for Indigenous people in sport), Education, Safe 6
ACCEPTED MANUSCRIPT Communities (by providing an alternative to anti-social behaviour, especially in schools) and Governance and Leadership” (Commonwealth of Australia, 2013, p. 9).
Yet, the evaluation of Aboriginal physical activity, sport and recreation programs has
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been limited and little data exists to contribute to an evidence base. Research carried out by Cunningham and Beneforti in (2005) indicated that this was a difficult and
problematic area, leading them to make the following comments in their discussion:
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It is evident from the literature review that indicator development relating to
outcomes from sport and recreation programs (for the general population and
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even more so for Indigenous populations) is in its infancy. Research evidence on the links between sport and recreation programs and various health and social outcomes is also limited. (p.96).
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Although much has been written on the role of sport among Indigenous Australians, little empirical research has explored the relationship between physical activity and related outcomes (Commonwealth of Australia, 2013). This research will make a
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small contribution to redressing this gap by providing foundational national analysis
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of 2012-13 participation in physical activity among children and youth, ages 5 to 17. Furthermore, one recommendation outlined in the Parliamentary Inquiry into the contribution of sport to Indigenous wellbeing was the need to establish an evaluation framework to assess the impact of sports programs in Indigenous communities (see page xiii Commonwealth of Australia, 2013). This clearly signals that previous efforts to evaluate and monitor outcomes have not been effective. As a preliminary step this
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ACCEPTED MANUSCRIPT study aims to identify the linkages between physical activity, education attainment and health outcomes.
Understanding Indigenous participation in physical activity and sport is bedevilled by
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complex intersections between Aboriginality, socio-economic status and remoteness. Across Australia Indigenous children and youth live in communities and
environments of great diversity. There are also sports participation dynamics linked to
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age and gender and that interact with these other complex contextual factors. Some of these relationships have been explored in the Commonwealth Government’s review
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of Indigenous sport, however there is to date no national profile of physical participation that takes geographical location into account.
National data are available reporting the levels of physical activity participation
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among all Australian children and youth. In the 2007 National Children’s Nutrition and Physical Survey (NCNPAS), the proportion of children meeting physical activity guidelines (operationalised as averaging at least 60 min/d across the four survey days)
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varied significantly with remoteness status, rising from 75% among children and
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adolescents living in major cities, to 85% for those living in remote areas using the ASGC remoteness classifications (Australian Bureau of Statistics, 2017). There were also large differences by age. While 94% of 9-10 year olds met the guidelines, only 57% of 16 years olds did. Furthermore the remoteness gradients were stronger in girls (p=0.006) than in boys (p=0.08). While there was no overall relationship between socio-economic status (SES), operationalised either as household income or as the Socio-Economic Indicators for Areas Index of Relative Social Disadvantage (IRSD), 8
ACCEPTED MANUSCRIPT in remote areas there was a clear inverse gradient, with 67% of children in the top IRSD quartile meeting the guidelines compared to 85% in the lowest quartile. In nonremote areas there was no socio-economic gradient (rates of compliance ranged from 77-82%) (Olds et al., 2008). These trends are evident among all Australian children
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and youth, and this paper will examine if similar trends are evident within Indigenous populations.
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In this study we report on a secondary data analysis of the Australian Bureau of
Statistics’ 2012-13 Australian Aboriginal and Torres Strait Islander Health Survey
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(AATSIHS). The survey has three elements: 1) the National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), 2) the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) and 3) the National Aboriginal and Torres Strait Islander Health Measures Survey
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(NATSIHMS). Drawing on the indicators available in these national data sets the analysis aims to: provide foundational understanding of the current levels of activity among Indigenous children and youth in diverse settings; and also contribute to an
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understanding of the role of physical activity and its relationship to health and
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education outcomes. More specifically, the available data allows us to answer the following research questions: 1.
What are the levels of physical activity in Indigenous children and youth aged
5-17 years of age in remote and non-remote areas; and how does PA vary in association with gender, age and SES?
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What association, if any, is evident between participation in physical activity
and reported general health and/or engagement in education among Indigenous children and youth aged 15-17 years of age in remote and non-remote areas?
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Methods
As part of a larger study, known as Foundations of Sport in Indigenous Communities, or the ‘FOSIC’ study, examining the place and role of sport and physical activity in
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Indigenous communities, this paper presents national data from the Australian Bureau of Statistics (ABS). The FOSIC study’s broad aims are to integrate insights from
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national data sets with local knowledge and qualitative data from the communities themselves. In this paper we present insights into patterns of Indigenous children and youth’s participation evident in the Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS). These findings will inform discussions and data gathering
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from local communities in the FOSIC study and also current debates in research,
Data
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policy and programs beyond the scope of the study.
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Data from the ABS AATSIHS, 2012-13, were used in this study. The AATSIHS comprises of two survey samples for children, one in the National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), and the other in the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS). The National Aboriginal and Torres Strait Islander Health Measures Survey (NATSIHMS) was also carried out for both survey samples on consenting survey participants aged 18 years and over. 10
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The main PA variable in both the remote and non-remote component for persons aged 5 to 17 years of age was whether the participant engaged in at least 60 minutes of physical activity yesterday. The survey questions on PA were designed to yield data
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based on Australia’s Physical Activity and Sedentary Behaviour Guidelines (Australian Government, 2017).
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The survey questionnaires were administered differently in the remote and non-
remote components and some survey questions were also different. In particular, the
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survey questions for deriving the main outcome variable were different for the remote and non-remote components, so they were analysed separately and the results cannot be directly compared.
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In the remote component, questions on physical activity yesterday were asked for survey participants aged 5 years and over and related to physical activity yesterday. In the non-remote component, questions on physical activity in the last seven days were
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asked for participants in the 5 to 17 years age group. The type of PA required recall of
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having performed the particular activity type and was entered by the interviewer using a trigram coder. The questions were asked in more detail in the non-remote component than in the remote component. A variable on whether the respondent did physical activity for at least 60 minutes yesterday was created by ABS for all those aged 5 to 17 years and it was analysed as the main outcome variable, nevertheless we report the remote and non-remote samples separately because of the substantial difference in the way the data was collected. 11
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Self-assessed health (excellent/very good/good/fair/poor) and whether studying fulltime (full-time v part-time/not studying) were also available and analysed for association with physical activity for persons aged 15-17 years old. The questions for
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these data items were not asked in the AATSIHS survey for the younger ages.
Factors associated with physical activity that were examined include: sex, age body
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mass index (BMI categorised into underweight, normal and overweight/obese) and socio-economic status (SES) as measured by the IRSD measure (Index of Relative
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Social Disadvantage) of SEIFA (Socio-Economic Index For Areas, and using the Index of Relative Socioeconomic Disadvantage) quintile (Biddle, 2009). And also: equivalised household income quintile; and whether household has salary or wage
Sample
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income as a source of income.
In Australia the Indigenous population comprises two distinct groups, Aboriginal and
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Torres Strait Islanders which together represent 3% of the Australian population
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(650,000 individuals). About two-thirds live in regional or remote areas, a rate twice that observed in the general Australian population. The research drew on a nationally representative sample of approximately 13,000 Indigenous participants as part of the Australian Health Survey. The sample was weighted by the ABS to represent the Aboriginal and Torres Strait Islander population on 30 June 2011 by age group, sex and geographical classification of area of usual residence, which is an independently estimated benchmark of the resident population from the 2011 Census of Population 12
ACCEPTED MANUSCRIPT and Housing. The first step to calculating the weighting applied to each person was to assign an initial weight, which is the inverse of the probability of being selected to the survey. The weights were then calibrated so that the weighted sample aligns with the population benchmark. The calibration of weights helps to compensate for over or
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under-enumeration of persons in the specified levels of disaggregation due to random sampling error and non-response. The weighted sample of 12,947 participants
represents 606,915 Aboriginal and Torres Strait Islander peoples in private dwellings.
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Numbers, proportions and odds ratios and their standard errors and 95% confidence intervals were estimated with the use of person-level jackknife replicate weights
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supplied in the files.
Four age groups were defined based on whether the person was at the approximate age for lower primary school (5-8 years old), upper primary school (9-11 years old),
Analysis
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old).
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lower secondary school (12-14 years old) or upper secondary school (15-17 years
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The Australian Bureau of Statistics Core Content release of Microdata in Expanded Confidentialised Unit Record Files (CURF) accessed via Remote Access Data Laboratory (RADL) (Australian Bureau of Statistics, 2006) was used in this analysis. The Core Content data combine both survey samples to yield a bigger combined sample but on the reduced question set that was administered to both survey samples.
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ACCEPTED MANUSCRIPT Statistical analyses were carried out using Stata version 10 on the RADL server. The level of statistical significance was set at p<0.05. Tests of association were performed as a logistic regression analysis to yield odds ratio (OR): unadjusted and adjusted for sex and age. Linear trend OR assumes that the ordinal variables — age group, SEIFA
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quintile and equivalised household income quintile — are continuous quantitative measures.
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Results
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PA in Indigenous children and youth aged 5-17 years and trends associated with gender, age and SES
In both the remote and non-remote samples PA was higher among males, but these
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groups show differing trends across age and region. Levels of PA, across age groups, were consistently higher among the remote sample. Where PA in remote areas was sustained at levels above 80% until 15 years of age, in non-remote areas there is a
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more gradual decline in participation rates from the peak at 5-8 years (approx. 80%)
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to substantially lower levels at 15-17 years (approx. 50%).
INSERT FIGURES 1 and 2 HERE
Although comparison of absolute levels of PA is not possible because of differences in data indicators we can see that the non-remote sample of Indigenous children 14
ACCEPTED MANUSCRIPT reflects the national trends, including the lower participation among girls and the decline with age. Greater detail on the PA trends is available in Tables 1 and 2.
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INSERT TABLES 1 AND 2 HERE
Tables 1 and 2 show the association between PA (those who reported having at least 60 minutes of physical activity yesterday) and some socio-demographic
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characteristics among Aboriginal and Torres Strait Islanders aged 5 to 17 years in non-remote and remote areas, respectively. While gender and age show clear and
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significant trends, socio-economic status, income factors and BMI do not show any discernible relationship with PA in the non-remote areas.
In the remote areas, children and youth in the lower SEIFA socio-economic quintiles
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were more likely to engage in at least 60 minutes of physical activity yesterday. There is also a discernible, but not statistically significant (p=0.066), pattern where those in a household without salary or wage as a source of income are also more likely to
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engage in PA. Overweight or obese children and youth in remote areas were less
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likely to engage in physical activity.
PA and reported general health and/or engagement in education in Indigenous children and youth aged 15-17 years Limited data were available to explore this question, particularly in the younger age cohort (5-15 years) where there were no data available on general health or educational participation or attainment. Among the 15 to 17 years cohort self-reported 15
ACCEPTED MANUSCRIPT general health was available and the only educational data available was whether they are participating in full time or part time study. No relationship between PA and study is evident in either the remote or non-remote youth. Neither is there a statistically
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significant relationship between PA and self-reported general health.
INSERT TABLES 3 AND 4 HERE
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Discussion
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Reported PA participation in Indigenous youth was high: 79-84% of participants in remote areas, and 64-74% in non-remote areas reported at least 60 min of PA on the day before the survey. While caution is required when making comparisons across surveys using different instruments, a Victorian study (Olds et al., 2007) found that the likelihood of a randomly chosen 16-year old child meeting the 60 minute
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guideline on a randomly chosen day was 57%. The corresponding figures in these datasets were 53% (non-remote) and 63% (remote), which are very comparable.
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Consistent with world literature, boys reported higher participation than girls, and there was a clear age gradient, with younger children reporting higher participation
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rates, and a marked drop-off around the secondary school/post-pubertal years.
In this sample, participation in PA was not significantly associated with engagement in study, self-reported health, body mass index, or equivalised household income. However, participation was significantly associated with area-level socio-economic status (SEIFA IRSD) in remote (but not in non-remote) areas. In remote areas, 16
ACCEPTED MANUSCRIPT participation in PA was inversely associated with IRSD (i.e. children from more advantaged families reported lower levels of PA), whereas in non-remote areas there was no gradient. Limitations
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There are very few data on participation in PA in Australian Indigenous communities, because of the triple measurement burdens of remoteness, small population size and
cultural impediments. This is the first attempt to interrogate national datasets to form
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a picture of participation patterns. This analysis has been useful in establishing some foundational understandings around how PA interacts with geography (remote vs
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non-remote), socio-economic status (SEIFA), gender and age.
However, the analysis here is based on self-report data, which are subject to recall and social desirability bias. More frustratingly, different instruments were used for
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remote and non-remote areas, precluding direct comparison. However, these differences are less likely to affect relational comparisons, between for example SES and participation across remote vs non-remote areas. Furthermore, the PA
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participation indicator for the remote component failed to capture compliance with
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national PA guidelines (≥60 min/day on each day of the week). Compliance is therefore certain to be much lower than the 64-84% reported (Olds et al., 2007). Similarly, the indicators for general health and education were suboptimal, being based on self-report rather than educational and health records, and only available for youth aged 15-17 years. The self-reported general health indicator was a single 5point Likert item. While the overall sample size was fairly large (n=3696), cell sizes
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ACCEPTED MANUSCRIPT became very small for some indicators, for example n<10 for the highest income quintile in remote areas.
The outcome measures in the AATSIHS data are also limited. In relation to
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engagement in study, for example, for this age group recently introduced legislation (Commonwealth of Australia, 2014) means that those who are not studying, or in
employment, are no longer eligible for Commonwealth unemployment benefits. In
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this new legislative context, this indicator will lose sensitivity. Ideally, future research would examine the relationship between education and PA using school attendance
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and educational attainment data, such as NAPLAN. Similarly, health data should be derived from linked PBS and Medicare records. Consideration should also be given to collecting biospecimens in the younger age groups.
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Implications
There is growing evidence that participation in PA is critical for physical and mental health, and social and academic outcomes. Participation tracks moderately from
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childhood to adulthood (Telama, Yang, Laakso & Viikari, 1997), so establishing
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participation patterns in childhood may be critical. While the AATSIHS dataset failed to reveal associations between PA participation and either health status or engagement in study, the data are not well suited for this type of analysis and further research with better instruments is needed.
From the few data available, it appears that PA participation rates among Indigenous youth are comparable to those of non-Indigenous youth, and the same age- and sex18
ACCEPTED MANUSCRIPT related patterns, which doubtless reflect both social and biological determinants (Sallis, 2000), are evident. The 5-10% lower participation rates for girls are concerning. While there are several programs encouraging Indigenous talent development in male-dominated sports, there are fewer for Indigenous girls. The
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characteristic drop-off in participation in both sexes after age 12 may be associated with the shift to secondary school or puberty. Assessment of pubertal status might
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help to shed light on this question.
In the general population in developed countries, especially among adults, PA
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participation is positively associated with SES: wealthier, better educated families are more likely to be physically active. A striking finding of this study was that in remote communities high levels of PA were associated with lower SES, while in non-remote communities there was no clear SES gradient. This contrasting dynamic has, to our
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knowledge, not been identified previously. Methodologically, this highlights the importance of disaggregated analysis of Indigenous populations and is consistent with
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qualitative studies identifying locally contextualised factors.
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This pattern of relationships between SES and PA in remote areas (higher PA among children from less advantaged families) is characteristic of countries which have not yet undergone the “epidemiological transition” (Katzmarzyk & Mason, 2009). In these areas, children are dependent on non-motorised transport, and sporting infrastructure is so rudimentary that most sport is played on an ad hoc basis, so that the financial differentials which characterise sports participation in urban areas may not come into play (Olds, Dolman & Maher, 2009). It is possible that cultural and 19
ACCEPTED MANUSCRIPT structural conditions in some Australian remote Indigenous communities resemble these countries. The flat PA-SES gradient in non-remote communities more resembles transitional countries like India (Katzmarzyk et al., 2015).
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Conclusions and further research
Monitoring PA levels, and their correlates and determinants, is of particular
importance for Indigenous youth. PA is a critical contributor to both physical and
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mental health, and sports participation can be a gateway for social inclusion and
academic engagement (Evans, Wilson, Dalton, & Georgakis, 2015). There has been
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substantial government investment in numerous sport-focused and physical activity programs for Indigenous communities and calls for increased data and evidence surrounding these.
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Unfortunately, the available PA data rely on subjective assessments, and are inconsistent and incommensurable both within the survey, and between the Indigenous-only and general population surveys. They fail to capture compliance
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with national PA guidelines. We strongly recommend that in the future objective
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measurements of PA be taken with the use of wearable accelerometers on the wider sample and that the recruitment process encourage its uptake. These devices quantify not only the duration of PA, but also timing, bout distribution and day-to-day variability. They have the advantage of also capturing sedentary behaviour and sleep, consistent with the international shift towards conceptualising the 24-hour day as a whole, rather than as separate domains for PA, sitting and sleep (Tremblay et al., 2016). Finally, objective data are comparable with general population data, such as 20
ACCEPTED MANUSCRIPT the CheckPoint survey associated with the Longitudinal Study of Australian Children (Wake et al., 2014)
Good quality data collected using high-tech, low-touch methods will allow
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researchers to explore relationships between lifestyle and health in Indigenous
children, and to close the research gap between Indigenous and non-Indigenous children. Potential areas to explore are the relationships between the activity
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composition (the whole 24-hour day) and outcomes such as weight status,
cardiovascular and metabolic health, well-being, and social outcomes such as
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interactions with the juvenile justice system, academic achievement, and peer relationships. Because of the special significance of sport to Indigenous communities and it’s identified potential to remediate entrenched disadvantage, there is a strong imperative for further research that explores not only physical activity and sport, but
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also more holistic perspectives on the communities in which these occur, to discover
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The social significance of sport in the moral governing of ‘good’ and ‘healthy’ citizens in Sweden, 1922–1998. Sport, Education and Society, 19(8), 973-990.
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Ryde, Mew South Wales: Angus & Robertson.
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Stoddart, B. (1986). Saturday afternoon fever: sport in the Australian culture. North
Tatz, C. (2009). Coming to Terms: 'Race', Ethnicity, Identity and Aboriginality in Sport. Australian Aboriginal Studies(2), 15-31.
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Tatz, C. (2012). Aborigines, sport and suicide. Sport in Society, 15(7), 922-935. doi:
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Tatz, C., & Adair, D. (2009). Darkness and a little light: 'race' and sport in Australia. Australian Aboriginal Studies, 2009(2), 1(14).
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ACCEPTED MANUSCRIPT behaviour, and sleep. Applied Physiology, Nutrition, and Metabolism. Accepted 5 Apr 2016. Veal, A. J., Lynch, R., & Darcy, S. (2013). Australian leisure. Frenchs Forest, N.S.W: Pearson Australia.
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Wake, M., Clifford, S., York, E., Olds, T., and Wong, T.Y. (2014). Introducing Growing Up In Australia’s Child Health Checkpoint: a physical and biomarkers module for the Longitudinal Study of Australian Children. Family
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Matters, 95, 14 et ss.
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1939. Sydney: Walla Walla Press.
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Supplementary Materials (for online publication only)
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Figure 1. Weighted and non-weighted sample data: Non-remote areas:
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proportion who had at least 60 minutes of physical activity yesterday
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Figure 2. Weighted and non-weighted sample data: Remote areas: proportion
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who had at least 60 minutes of physical activity yesterday
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ACCEPTED MANUSCRIPT Figure 3. Weighted and non-weighted sample data: Proportion who had at
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least 60 minutes of physical activity yesterday by SEIFA quintiles
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Figure 4: Percentage of youth reporting participating in at least 60 min of PA on the day before the interview in remote (filled circles) and non-remote areas (empty
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circles), by quintile of SEIFA IRSD.IRSD=Index of Relative Social Disadvantage
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ACCEPTED MANUSCRIPT Table 1: Proportion of Indigenous respondents, aged 5-17 years, in non-remote areas (n=2,207; N=155,950a) who reported at least 60 minutes of physical activity yesterday.
Weighted % (95% CI)
Unadjusted OR (95% CI)
OR adjusted for sex and age (95% CI)
Sex
Age (N=49,470) (N=34,410) (N=36,810) (N=35,260)
81.9 (78.4 - 85.5) 71.9 (66.7 - 77.1) 63.6 (57.7 - 69.4) 53.0 (47.6 - 58.3)
5th quintile High (N=8,080) 4th quintile (N=18,150) 3rd quintile (N=23,900) 2nd quintile (N=39,750) Low 1st quintile (N=66,070) b Equivalised household income
70.5 (58.7 - 82.2) 67.7 (60.7 - 74.7) 66.4 (59.7 - 73.1) 67.4 (62.7 - 72.2) 70.7 (66.4 – 75.0)
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[Ref] 0.61 (0.48-0.79) Linear trend: 0.63 (0.57-0.69)
0.41(0.32-0.51) Linear trend: 1.04 (0.94-1.15) [Ref]
1.16 (0.90-1.50) Linear trend: 1.01 (0.89-1.14)
--
-Linear trend: 1.03 (0.93-1.15) [Ref] 1.14 (0.87-1.49) Linear trend: 0.97 (0.86-1.09)
73.7 (61.0 - 86.4) 69.5 (59.9 - 79.2) 69.7 (63.2 - 76.2) 67.4 (61.9 - 72.9) 70.3 (66.0 - 74.6)
1.09 (0.83-1.42)
1.00 (0.76-1.31)
68.1 (64.9 - 71.3) 69.9 (65.7 - 74.1)
0.92 (0.71-1.18) [Ref]
1.01 (0.79-1.30) [Ref]
67.2 (54.3 - 80.2) 69.7 (66.0 - 73.3) 64.8 (59.2 - 70.4)
0.89 (0.48-1.65) [Ref] 0.80 (0.59-1.10)
0.92 (0.45-1.86) [Ref] 0.85 (0.61-1.18)
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5th quintile High (N=2,770) 4th quintile (N=9,250) 3rd quintile (N=20,180) 2nd quintile (N=38,270) 1st quintile Low (N=66,950) Household has salary/wage income Yes (N=90,850) No (N=65,110) c BMI Underweight (N=7,170) Normal (N=69,910) Overweight/Obese (N=40,380)
[Ref]
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5-8 years 9-11 years 12-14 years 15-17 years SEIFA (IRSD)
[Ref] 0.64 (0.60-0.67) Linear trend: 0.63 (0.57-0.70)
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73.6 (70.1 - 77.2) 63.8 (60.3 - 67.4)
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Males (N=79,770) Females (N=76,190)
[Ref]
[Ref]
Weighted number of persons, N, in the population is rounded to nearest ten. 259 out of the 2,207 persons had missing data on equivalised household income (not stated or not known). a Height and weight measurements were missing for 546 out of the 2,207 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 19 persons sampled in the more extreme classes (underweight class 2 and class 3). a
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ACCEPTED MANUSCRIPT Table 2: Proportion of Indigenous respondents, aged 5-17 years, in the remote areas (n=1,489;N=37,500d) who reported at least 60 minutes of physical activity yesterday Weighted % (95% CI)
Unadjusted OR (95% CI)
OR adjusted for age and sex (95% CI)
Sex 84.2 (80.3 - 88.0) 79.0 (74.3 - 83.7)
5-8 years (N=12,340) 9-11 years (N=9,600) 12-14 years (N=7,750) 15-17 years (N=7,810) SEIFA (IRSD)
86.0 (81.6 - 90.5) 87.0 (82.0 - 92.0) 83.8 (76.3 - 91.3) 66.0 (57.0 - 74.9)
5th quintile High (N=620) 4th quintile (N=2,170) 3rd quintile (N=3,230) 2nd quintile (N=3,900) Low (N=27,590) 1st quintile Equivalised household incomee
54.7 (21.3 - 88.1) 71.6 (57.1 - 86.1) 78.3 (65.8 - 90.7) 75.0 (61.7 - 88.4) 84.4 (80.3 - 88.5)
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a
[Ref] 0.69 (0.48-0.98) Linear trend: 0.67 (0.54-0.83)
0.32 (0.21-0.50) Linear trend: 1.33 (1.09-1.62) [Ref]
1.89 (1.14-3.14) Linear trend: 1.20 (0.98-1.46)
--
-Linear trend: 1.34 (1.09-1.65) [Ref]
1.94 (1.15-3.25) Linear trend: 1.18 (0.96-1.46)
73.0 (50.3 - 95.8) 83.5 (73.8 - 93.2) 74.4 (60.9 - 87.9) 77.1 (68.6 - 85.7) 85.1 (81.2 – 89.0)
1.68 (1.06-2.67)
1.60 (0.99-2.59)
79.0 (74.2 - 83.9) 85.7 (81.9 - 89.5)
0.63 (0.42-0.94) [Ref]
0.68 (0.45-1.03) [Ref]
83.8 (75.6 - 91.9) 83.3 (79.2 - 87.3) 74.9 (67.0 - 82.9)
1.04 (0.55-1.95) [Ref] 0.60 (0.37-0.98)
1.07 (0.56-2.07) [Ref] 0.67 (0.42-1.09)
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5th quintile High (N=640) 4th quintile (N=1,780) 3rd quintile (N=2,750) 2nd quintile (N=5,990) (N=18,020) 1st quintile Low Household has salary/wage income Yes (N=22,770) No (N=14,730) BMIf Underweight (N=4,660) Normal (N=17,100) Overweight / Obese (N=8,220)
[Ref]
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Age
[Ref] 0.71 (0.50-0.99) Linear trend: 0.68 (0.55-0.84)
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(N=19,160) (N=18,340)
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Males Females
[Ref]
[Ref]
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Weighted number of persons, N, in the population is rounded to nearest ten. 325 out of the 1,489 persons had missing data on equivalised household income (not stated or not known). a Height and weight measurements were missing for 321 out of the 1,489 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 68 persons sampled (though the sample numbers is more an issue in the non-remote component) in the more extreme classes (underweight class 2 and class 3). There were 182 overweight and 123 obese class 1 persons, but proportions undertaking at least 60 minutes of physical activity is relatively similar. a
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ACCEPTED MANUSCRIPT Table 3: Association of physical health and full-time study with having at least 60 minutes of physical activity yesterday among persons aged 15-17 years old in the non-remote component (n=482; N=35,260a)
54.1 (47.6 - 60.5)
1.12 (0.71-1.78)
1.17 (0.73-1.88)
51.1 (41.5 - 60.7)
[Ref]
[Ref]
54.6 (49.3 - 59.9)
36.9 (18.2 - 55.7)
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Fair / Poor (N=3,310)
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2.06 (0.90-4.67)
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Self-assessed health Excellent / Very good / Good (N=31,950)
OR adjusted for sex (95% CI)
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Studying part-time / Not studying (N=13,250)
Unadjusted OR (95% CI)
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Whether currently studying Studying full-time (N=22,020)
Weighted % (95% CI)
[Ref]
1.98 (0.85-4.62)
[Ref]
ACCEPTED MANUSCRIPT Table 4: Association of physical health and full-time study with having at least 60 minutes of physical activity yesterday among persons aged 15-17 years old in the remote component (n=275; N=7,810viii) Unadjusted OR (95% CI)
OR adjusted for sex (95% CI)
62.4 (48.5 - 76.4)
0.71 (0.32-1.59)
0.72 (0.31-1.66)
69.9 (59.1 - 80.7)
[Ref]
[Ref]
Self-assessed health Excellent / Very good / Good (N=7,080)
66.3 (57.0 - 75.6)
1.18 (0.23-6.06)
1.29 (0.22-7.59)
Fair / Poor (N=720)
62.6 (27.5 - 97.8)
[Ref]
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Weighted number of persons, N, in the population is rounded to nearest ten.
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Whether currently studying Studying full-time (N=4,110) Studying part-time / Not studying (N=3,700)
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Weighted % (95% CI)
4
[Ref]
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a
Weighted number of persons, N, in the population is rounded to nearest ten. 259 out of the 2,207 persons had missing data on equivalised household income (not stated or not known). c Height and weight measurements were missing for 546 out of the 2,207 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 19 persons sampled in the more extreme classes (underweight class 2 and class 3). d Weighted number of persons, N, in the population is rounded to nearest ten. e 325 out of the 1,489 persons had missing data on equivalised household income (not stated or not known). f Height and weight measurements were missing for 321 out of the 1,489 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 68 persons sampled (though the sample numbers is more an issue in the non-remote component) in the more extreme classes (underweight class 2 and class 3). There were 182 overweight and 123 obese class 1 persons, but proportions undertaking at least 60 minutes of physical activity is relatively similar.
Weighted number of persons, N, in the population is rounded to nearest ten.
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viii
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b
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas
Research Highlights Sport and physical activity (PA) hold significance in Indigenous communities
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Little data relating to PA, and outcomes, within these communities has been examined
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Nationally 64-84% of Indigenous youth report => 60 min of PA on the previous day
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Females and older youth participate less, with different patterns in remote areas
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Limitations in the available national data mean further research is needed
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S0277-9536(18)30185-0
DOI:
10.1016/j.socscimed.2018.04.018
Reference:
SSM 11698
To appear in:
Social Science & Medicine
Received Date: 16 November 2017 Revised Date:
12 March 2018
Accepted Date: 13 April 2018
Please cite this article as: Evans, J.R., Wilson, R., Coleman, C., Man, W., Olds, T., Physical activity among indigenous Australian children and youth in remote and non-remote areas, Social Science & Medicine (2018), doi: 10.1016/j.socscimed.2018.04.018. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas John Robert Evans,
Rachel Wilson,
Clare Coleman,
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University of Sydney
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University of Technology Sydney
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University of Sydney
Wing Man,
University of Sydney
Tim Olds,
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University of South Australia
Corresponding Author:
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Dr. Rachel Wilson
Sydney School of Education & Social Work
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Faculty of Arts and Social Sciences Building A35, Manning road. University of Sydney
Camperdown, NSW 2600 Australia
Email: [email protected] Ph: + 61 2 93516390 1
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas Abstract
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Sport and physical activity (PA) hold particular significance in Australian Indigenous communities, and have the potential to address many of the health and education
challenges faced by Indigenous communities. Optimal levels of PA are an important
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foundation in efforts to build healthy communities and reduce social disadvantage experienced to date. Yet little evidence relating to the current levels of PA within
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these communities, or the relationship between PA and outcomes, has been available.
Drawing on national survey data from the Australian Bureau of Statistics, we examine levels of PA in the Australian Aboriginal and Torres Strait Islander Health
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Survey 2012-13. These data describe PA levels among Indigenous Australians, aged 5 to 17 years, in remote and non-remote communities. We also examine the relationship between PA and participation in education and self-reported health among 15-17 year
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olds.
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Overall, participation rates appear to be high, with 64-84% of youth reporting at least 60 min of PA on the previous day. A gender gap was also evident, with lower levels of activity among girls. PA decreased with age, particularly at or around the age of puberty. There were no significant associations between PA and either self-reported health or engagement in study. There was a relationship between high PA and low
1
ACCEPTED MANUSCRIPT area-level socio-economic status in remote areas, but no association in non-remote areas.
The differences between remote and non-remote areas highlight the importance of
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disaggregated analysis of Indigenous populations and are consistent with qualitative
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studies identifying locally contextualised factors influential in promoting PA.
KEYWORDS: physical activity; Indigenous; Australia; sport; health; education;
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remote; community
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ACCEPTED MANUSCRIPT Introduction There is now an emerging international focus on the role of physical activity (PA) and sport in the broader public health context. In 2012 as part of the London Olympics, The Lancet Medical Journal established The Lancet Physical Activity Observatory
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(LPAO) to examine worldwide trends in physical activity and its repercussions. They found that:
“One third of adults and 80% of adolescents around the world do not reach
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recommended levels for daily physical activity (30 min and 60 min of physical activity of moderate-to-vigorous intensity per day for adults and adolescents,
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respectively). Physical inactivity was shown to be responsible for 5.3 million deaths per year worldwide. If inactivity decreased by only 10%, half a million deaths could be averted every year” (Hallal, Martins, & Ramírez, 2014, p. 471).
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Many factors contribute to population levels of physical activity. One important factor is place of residence, and conditions can vary widely within a country. Internationally, countries appear to be situated at different points on a common
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developmental trajectory (Zuckerman, 2014), marked by an “epidemiological
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transition” which occurs at a point characterised by decreasing physical activity associated with increasing automation and motorisation, and a switch from unprocessed to highly processed foods (Popkin, 1994). The transition is marked by a reversal of associations between socio-economic status (SES) and fatness and PA: in pre-transition areas, low SES individuals are leaner and more active; in posttransition areas, low SES individuals — including children — tend to be fatter and
3
ACCEPTED MANUSCRIPT less active (Broyles et al., 2015). In this paper we explore these issues in relation to Indigenous Australian communities in remote and non-remote locations.
Sport and physical activity together with healthy outdoor pursuits continue to define
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Australia’s place in the world (Light, 2006; Tatz, 2009). They also have a history as
important activities that bind communities especially in urban, rural and remote areas (Light, 2006; Spaaij, 2009a, 2009b; Tonts & Atherley, 2010). Sport is a central
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cultural practice in Australia where it holds unusual significance and symbolic
meaning (Stoddart, 1986) and has played an important role in shaping our national
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identity. Australia is one of a few countries which has a highly sophisticated government-funded sports program which serves both community and elite interests (Crawford, 2004; Phillips, 2000).
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The particular importance of sport to Indigenous Australian communities and the success of Indigenous elite athletes in the Australian sporting landscape has been well documented (Tatz 1995, Hallinan & Judd 2009; Norman 2012). Sports, such as rugby
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league and Australian Rules football, form important mechanisms for promoting
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community identity and cohesion in Indigenous communities (Bamblett, 2013; Norman, 2006). Indigenous athletes have made an outstanding contribution to Australia’s national and international sporting success for a very long time, often against a backdrop of racism and limited opportunity (Klugman & Osmond, 2013; Tatz, 2009; Tatz & Adair, 2009). Yet, while Australia’s Indigenous athletes have been glorified for their success in sport, it has been suggested that this has diverted attention from broader community-level participation in physical activity, and also 4
ACCEPTED MANUSCRIPT under-achievement in other areas of life such as education, employment and access to adequate housing and health, perpetuating an enduring inequality of Australian life (Altman, Biddle, & Hunter, 2009; Evans, Wilson, Dalton & Georgakis, 2015;
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Marmot, 2011; Marmot, Friel, Bell, Houweling, & Taylor, 2008).
Sport, physical activities and recreational activities were established as pedagogical
and life learning endeavours for Indigenous communities prior to colonisation and the
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introduction of Anglo-Celtic games (Edwards, 1999; Maynard, 2011; Whimpress,
1999). For many Indigenous children and young adults sport is a vital vehicle through
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which they socialise and also find opportunities to overcome social inequities through opportunities to participate and excel (Veal, Lynch, & Darcy, 2013). In rural areas PA and sport may be the only avenue for Indigenous Australians to be involved in the
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wider community (Tonts & Atherley, 2010), as Tatz’s points out:
Sport is a major element in contemporary Aboriginal life: it provides meaning, a sense of purpose and belonging; it is inclusive and embracing in a world
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where most Aboriginal youth feel alienated, disempowered, rejected and
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excluded (p.922).
Over the last two decades ‘sport as development’ has emerged on the global stage and sport is often seen as a tool that can be used to improve outcomes in areas where there is significant disadvantage (Carson, 2007), including Australian Indigenous communities (Evans, Wilson, Dalton, Georgakis, 2015). This has been matched by a growing realisation that Indigenous health is best understood within wider historical, 5
ACCEPTED MANUSCRIPT political, social, or psychological worlds (Le Grande, Ski, Thompson, Scuffham, Kularatna, Jackson & Brown, 2017) where sport and physical activity sit prominently.
Sport as a development activity has been viewed as a vehicle that transcends
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conservative traditional approaches, and that “reaches communities with messages in a way that politicians, multilateral agencies and NGOs cannot” (Levermore, 2008, p. 183). In Indigenous communities sport has also been identified as an area where
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community leadership has led to health- and education-related interventions, targeting outcomes as diverse as domestic violence, diabetes, smoking cessation and suicide
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prevention (Doyle, Firebrace, Reilly, Crumpen, & Rowley, 2013; Norman, 2012; Tatz, 2012). While remaining positive about sport, Levermore (2008) makes the point that further evaluation and empirical research is required to determine if the claims about development are in fact as plausible as many propose. He concludes by
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remarking; “The use of sport for developmental purposes should be considered in a more nuanced manner, and evaluated relative to other engines of development” (ibid
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p.189).
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At a national level in Australia, physical activity in Indigenous communities has been identified as a potential lever in the Closing the Gap approach outlined in strategies by the Council of Australian Governments (Ware & Meredith, 2013). These recognise that overcoming Indigenous disadvantage requires long-term generational commitment that will see major efforts directed across a number of strategic platforms or “Building Blocks including, Economic Participation (through employment opportunities for Indigenous people in sport), Education, Safe 6
ACCEPTED MANUSCRIPT Communities (by providing an alternative to anti-social behaviour, especially in schools) and Governance and Leadership” (Commonwealth of Australia, 2013, p. 9).
Yet, the evaluation of Aboriginal physical activity, sport and recreation programs has
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been limited and little data exists to contribute to an evidence base. Research carried out by Cunningham and Beneforti in (2005) indicated that this was a difficult and
problematic area, leading them to make the following comments in their discussion:
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It is evident from the literature review that indicator development relating to
outcomes from sport and recreation programs (for the general population and
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even more so for Indigenous populations) is in its infancy. Research evidence on the links between sport and recreation programs and various health and social outcomes is also limited. (p.96).
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Although much has been written on the role of sport among Indigenous Australians, little empirical research has explored the relationship between physical activity and related outcomes (Commonwealth of Australia, 2013). This research will make a
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small contribution to redressing this gap by providing foundational national analysis
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of 2012-13 participation in physical activity among children and youth, ages 5 to 17. Furthermore, one recommendation outlined in the Parliamentary Inquiry into the contribution of sport to Indigenous wellbeing was the need to establish an evaluation framework to assess the impact of sports programs in Indigenous communities (see page xiii Commonwealth of Australia, 2013). This clearly signals that previous efforts to evaluate and monitor outcomes have not been effective. As a preliminary step this
7
ACCEPTED MANUSCRIPT study aims to identify the linkages between physical activity, education attainment and health outcomes.
Understanding Indigenous participation in physical activity and sport is bedevilled by
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complex intersections between Aboriginality, socio-economic status and remoteness. Across Australia Indigenous children and youth live in communities and
environments of great diversity. There are also sports participation dynamics linked to
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age and gender and that interact with these other complex contextual factors. Some of these relationships have been explored in the Commonwealth Government’s review
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of Indigenous sport, however there is to date no national profile of physical participation that takes geographical location into account.
National data are available reporting the levels of physical activity participation
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among all Australian children and youth. In the 2007 National Children’s Nutrition and Physical Survey (NCNPAS), the proportion of children meeting physical activity guidelines (operationalised as averaging at least 60 min/d across the four survey days)
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varied significantly with remoteness status, rising from 75% among children and
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adolescents living in major cities, to 85% for those living in remote areas using the ASGC remoteness classifications (Australian Bureau of Statistics, 2017). There were also large differences by age. While 94% of 9-10 year olds met the guidelines, only 57% of 16 years olds did. Furthermore the remoteness gradients were stronger in girls (p=0.006) than in boys (p=0.08). While there was no overall relationship between socio-economic status (SES), operationalised either as household income or as the Socio-Economic Indicators for Areas Index of Relative Social Disadvantage (IRSD), 8
ACCEPTED MANUSCRIPT in remote areas there was a clear inverse gradient, with 67% of children in the top IRSD quartile meeting the guidelines compared to 85% in the lowest quartile. In nonremote areas there was no socio-economic gradient (rates of compliance ranged from 77-82%) (Olds et al., 2008). These trends are evident among all Australian children
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and youth, and this paper will examine if similar trends are evident within Indigenous populations.
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In this study we report on a secondary data analysis of the Australian Bureau of
Statistics’ 2012-13 Australian Aboriginal and Torres Strait Islander Health Survey
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(AATSIHS). The survey has three elements: 1) the National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), 2) the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) and 3) the National Aboriginal and Torres Strait Islander Health Measures Survey
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(NATSIHMS). Drawing on the indicators available in these national data sets the analysis aims to: provide foundational understanding of the current levels of activity among Indigenous children and youth in diverse settings; and also contribute to an
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understanding of the role of physical activity and its relationship to health and
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education outcomes. More specifically, the available data allows us to answer the following research questions: 1.
What are the levels of physical activity in Indigenous children and youth aged
5-17 years of age in remote and non-remote areas; and how does PA vary in association with gender, age and SES?
9
ACCEPTED MANUSCRIPT 2.
What association, if any, is evident between participation in physical activity
and reported general health and/or engagement in education among Indigenous children and youth aged 15-17 years of age in remote and non-remote areas?
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Methods
As part of a larger study, known as Foundations of Sport in Indigenous Communities, or the ‘FOSIC’ study, examining the place and role of sport and physical activity in
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Indigenous communities, this paper presents national data from the Australian Bureau of Statistics (ABS). The FOSIC study’s broad aims are to integrate insights from
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national data sets with local knowledge and qualitative data from the communities themselves. In this paper we present insights into patterns of Indigenous children and youth’s participation evident in the Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS). These findings will inform discussions and data gathering
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from local communities in the FOSIC study and also current debates in research,
Data
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policy and programs beyond the scope of the study.
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Data from the ABS AATSIHS, 2012-13, were used in this study. The AATSIHS comprises of two survey samples for children, one in the National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), and the other in the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS). The National Aboriginal and Torres Strait Islander Health Measures Survey (NATSIHMS) was also carried out for both survey samples on consenting survey participants aged 18 years and over. 10
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The main PA variable in both the remote and non-remote component for persons aged 5 to 17 years of age was whether the participant engaged in at least 60 minutes of physical activity yesterday. The survey questions on PA were designed to yield data
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based on Australia’s Physical Activity and Sedentary Behaviour Guidelines (Australian Government, 2017).
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The survey questionnaires were administered differently in the remote and non-
remote components and some survey questions were also different. In particular, the
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survey questions for deriving the main outcome variable were different for the remote and non-remote components, so they were analysed separately and the results cannot be directly compared.
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In the remote component, questions on physical activity yesterday were asked for survey participants aged 5 years and over and related to physical activity yesterday. In the non-remote component, questions on physical activity in the last seven days were
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asked for participants in the 5 to 17 years age group. The type of PA required recall of
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having performed the particular activity type and was entered by the interviewer using a trigram coder. The questions were asked in more detail in the non-remote component than in the remote component. A variable on whether the respondent did physical activity for at least 60 minutes yesterday was created by ABS for all those aged 5 to 17 years and it was analysed as the main outcome variable, nevertheless we report the remote and non-remote samples separately because of the substantial difference in the way the data was collected. 11
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Self-assessed health (excellent/very good/good/fair/poor) and whether studying fulltime (full-time v part-time/not studying) were also available and analysed for association with physical activity for persons aged 15-17 years old. The questions for
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these data items were not asked in the AATSIHS survey for the younger ages.
Factors associated with physical activity that were examined include: sex, age body
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mass index (BMI categorised into underweight, normal and overweight/obese) and socio-economic status (SES) as measured by the IRSD measure (Index of Relative
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Social Disadvantage) of SEIFA (Socio-Economic Index For Areas, and using the Index of Relative Socioeconomic Disadvantage) quintile (Biddle, 2009). And also: equivalised household income quintile; and whether household has salary or wage
Sample
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income as a source of income.
In Australia the Indigenous population comprises two distinct groups, Aboriginal and
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Torres Strait Islanders which together represent 3% of the Australian population
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(650,000 individuals). About two-thirds live in regional or remote areas, a rate twice that observed in the general Australian population. The research drew on a nationally representative sample of approximately 13,000 Indigenous participants as part of the Australian Health Survey. The sample was weighted by the ABS to represent the Aboriginal and Torres Strait Islander population on 30 June 2011 by age group, sex and geographical classification of area of usual residence, which is an independently estimated benchmark of the resident population from the 2011 Census of Population 12
ACCEPTED MANUSCRIPT and Housing. The first step to calculating the weighting applied to each person was to assign an initial weight, which is the inverse of the probability of being selected to the survey. The weights were then calibrated so that the weighted sample aligns with the population benchmark. The calibration of weights helps to compensate for over or
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under-enumeration of persons in the specified levels of disaggregation due to random sampling error and non-response. The weighted sample of 12,947 participants
represents 606,915 Aboriginal and Torres Strait Islander peoples in private dwellings.
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Numbers, proportions and odds ratios and their standard errors and 95% confidence intervals were estimated with the use of person-level jackknife replicate weights
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supplied in the files.
Four age groups were defined based on whether the person was at the approximate age for lower primary school (5-8 years old), upper primary school (9-11 years old),
Analysis
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old).
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lower secondary school (12-14 years old) or upper secondary school (15-17 years
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The Australian Bureau of Statistics Core Content release of Microdata in Expanded Confidentialised Unit Record Files (CURF) accessed via Remote Access Data Laboratory (RADL) (Australian Bureau of Statistics, 2006) was used in this analysis. The Core Content data combine both survey samples to yield a bigger combined sample but on the reduced question set that was administered to both survey samples.
13
ACCEPTED MANUSCRIPT Statistical analyses were carried out using Stata version 10 on the RADL server. The level of statistical significance was set at p<0.05. Tests of association were performed as a logistic regression analysis to yield odds ratio (OR): unadjusted and adjusted for sex and age. Linear trend OR assumes that the ordinal variables — age group, SEIFA
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quintile and equivalised household income quintile — are continuous quantitative measures.
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Results
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PA in Indigenous children and youth aged 5-17 years and trends associated with gender, age and SES
In both the remote and non-remote samples PA was higher among males, but these
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groups show differing trends across age and region. Levels of PA, across age groups, were consistently higher among the remote sample. Where PA in remote areas was sustained at levels above 80% until 15 years of age, in non-remote areas there is a
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more gradual decline in participation rates from the peak at 5-8 years (approx. 80%)
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to substantially lower levels at 15-17 years (approx. 50%).
INSERT FIGURES 1 and 2 HERE
Although comparison of absolute levels of PA is not possible because of differences in data indicators we can see that the non-remote sample of Indigenous children 14
ACCEPTED MANUSCRIPT reflects the national trends, including the lower participation among girls and the decline with age. Greater detail on the PA trends is available in Tables 1 and 2.
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INSERT TABLES 1 AND 2 HERE
Tables 1 and 2 show the association between PA (those who reported having at least 60 minutes of physical activity yesterday) and some socio-demographic
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characteristics among Aboriginal and Torres Strait Islanders aged 5 to 17 years in non-remote and remote areas, respectively. While gender and age show clear and
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significant trends, socio-economic status, income factors and BMI do not show any discernible relationship with PA in the non-remote areas.
In the remote areas, children and youth in the lower SEIFA socio-economic quintiles
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were more likely to engage in at least 60 minutes of physical activity yesterday. There is also a discernible, but not statistically significant (p=0.066), pattern where those in a household without salary or wage as a source of income are also more likely to
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engage in PA. Overweight or obese children and youth in remote areas were less
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likely to engage in physical activity.
PA and reported general health and/or engagement in education in Indigenous children and youth aged 15-17 years Limited data were available to explore this question, particularly in the younger age cohort (5-15 years) where there were no data available on general health or educational participation or attainment. Among the 15 to 17 years cohort self-reported 15
ACCEPTED MANUSCRIPT general health was available and the only educational data available was whether they are participating in full time or part time study. No relationship between PA and study is evident in either the remote or non-remote youth. Neither is there a statistically
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significant relationship between PA and self-reported general health.
INSERT TABLES 3 AND 4 HERE
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Discussion
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Reported PA participation in Indigenous youth was high: 79-84% of participants in remote areas, and 64-74% in non-remote areas reported at least 60 min of PA on the day before the survey. While caution is required when making comparisons across surveys using different instruments, a Victorian study (Olds et al., 2007) found that the likelihood of a randomly chosen 16-year old child meeting the 60 minute
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guideline on a randomly chosen day was 57%. The corresponding figures in these datasets were 53% (non-remote) and 63% (remote), which are very comparable.
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Consistent with world literature, boys reported higher participation than girls, and there was a clear age gradient, with younger children reporting higher participation
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rates, and a marked drop-off around the secondary school/post-pubertal years.
In this sample, participation in PA was not significantly associated with engagement in study, self-reported health, body mass index, or equivalised household income. However, participation was significantly associated with area-level socio-economic status (SEIFA IRSD) in remote (but not in non-remote) areas. In remote areas, 16
ACCEPTED MANUSCRIPT participation in PA was inversely associated with IRSD (i.e. children from more advantaged families reported lower levels of PA), whereas in non-remote areas there was no gradient. Limitations
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There are very few data on participation in PA in Australian Indigenous communities, because of the triple measurement burdens of remoteness, small population size and
cultural impediments. This is the first attempt to interrogate national datasets to form
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a picture of participation patterns. This analysis has been useful in establishing some foundational understandings around how PA interacts with geography (remote vs
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non-remote), socio-economic status (SEIFA), gender and age.
However, the analysis here is based on self-report data, which are subject to recall and social desirability bias. More frustratingly, different instruments were used for
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remote and non-remote areas, precluding direct comparison. However, these differences are less likely to affect relational comparisons, between for example SES and participation across remote vs non-remote areas. Furthermore, the PA
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participation indicator for the remote component failed to capture compliance with
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national PA guidelines (≥60 min/day on each day of the week). Compliance is therefore certain to be much lower than the 64-84% reported (Olds et al., 2007). Similarly, the indicators for general health and education were suboptimal, being based on self-report rather than educational and health records, and only available for youth aged 15-17 years. The self-reported general health indicator was a single 5point Likert item. While the overall sample size was fairly large (n=3696), cell sizes
17
ACCEPTED MANUSCRIPT became very small for some indicators, for example n<10 for the highest income quintile in remote areas.
The outcome measures in the AATSIHS data are also limited. In relation to
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engagement in study, for example, for this age group recently introduced legislation (Commonwealth of Australia, 2014) means that those who are not studying, or in
employment, are no longer eligible for Commonwealth unemployment benefits. In
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this new legislative context, this indicator will lose sensitivity. Ideally, future research would examine the relationship between education and PA using school attendance
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and educational attainment data, such as NAPLAN. Similarly, health data should be derived from linked PBS and Medicare records. Consideration should also be given to collecting biospecimens in the younger age groups.
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Implications
There is growing evidence that participation in PA is critical for physical and mental health, and social and academic outcomes. Participation tracks moderately from
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childhood to adulthood (Telama, Yang, Laakso & Viikari, 1997), so establishing
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participation patterns in childhood may be critical. While the AATSIHS dataset failed to reveal associations between PA participation and either health status or engagement in study, the data are not well suited for this type of analysis and further research with better instruments is needed.
From the few data available, it appears that PA participation rates among Indigenous youth are comparable to those of non-Indigenous youth, and the same age- and sex18
ACCEPTED MANUSCRIPT related patterns, which doubtless reflect both social and biological determinants (Sallis, 2000), are evident. The 5-10% lower participation rates for girls are concerning. While there are several programs encouraging Indigenous talent development in male-dominated sports, there are fewer for Indigenous girls. The
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characteristic drop-off in participation in both sexes after age 12 may be associated with the shift to secondary school or puberty. Assessment of pubertal status might
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help to shed light on this question.
In the general population in developed countries, especially among adults, PA
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participation is positively associated with SES: wealthier, better educated families are more likely to be physically active. A striking finding of this study was that in remote communities high levels of PA were associated with lower SES, while in non-remote communities there was no clear SES gradient. This contrasting dynamic has, to our
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knowledge, not been identified previously. Methodologically, this highlights the importance of disaggregated analysis of Indigenous populations and is consistent with
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qualitative studies identifying locally contextualised factors.
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This pattern of relationships between SES and PA in remote areas (higher PA among children from less advantaged families) is characteristic of countries which have not yet undergone the “epidemiological transition” (Katzmarzyk & Mason, 2009). In these areas, children are dependent on non-motorised transport, and sporting infrastructure is so rudimentary that most sport is played on an ad hoc basis, so that the financial differentials which characterise sports participation in urban areas may not come into play (Olds, Dolman & Maher, 2009). It is possible that cultural and 19
ACCEPTED MANUSCRIPT structural conditions in some Australian remote Indigenous communities resemble these countries. The flat PA-SES gradient in non-remote communities more resembles transitional countries like India (Katzmarzyk et al., 2015).
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Conclusions and further research
Monitoring PA levels, and their correlates and determinants, is of particular
importance for Indigenous youth. PA is a critical contributor to both physical and
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mental health, and sports participation can be a gateway for social inclusion and
academic engagement (Evans, Wilson, Dalton, & Georgakis, 2015). There has been
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substantial government investment in numerous sport-focused and physical activity programs for Indigenous communities and calls for increased data and evidence surrounding these.
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Unfortunately, the available PA data rely on subjective assessments, and are inconsistent and incommensurable both within the survey, and between the Indigenous-only and general population surveys. They fail to capture compliance
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with national PA guidelines. We strongly recommend that in the future objective
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measurements of PA be taken with the use of wearable accelerometers on the wider sample and that the recruitment process encourage its uptake. These devices quantify not only the duration of PA, but also timing, bout distribution and day-to-day variability. They have the advantage of also capturing sedentary behaviour and sleep, consistent with the international shift towards conceptualising the 24-hour day as a whole, rather than as separate domains for PA, sitting and sleep (Tremblay et al., 2016). Finally, objective data are comparable with general population data, such as 20
ACCEPTED MANUSCRIPT the CheckPoint survey associated with the Longitudinal Study of Australian Children (Wake et al., 2014)
Good quality data collected using high-tech, low-touch methods will allow
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researchers to explore relationships between lifestyle and health in Indigenous
children, and to close the research gap between Indigenous and non-Indigenous children. Potential areas to explore are the relationships between the activity
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composition (the whole 24-hour day) and outcomes such as weight status,
cardiovascular and metabolic health, well-being, and social outcomes such as
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interactions with the juvenile justice system, academic achievement, and peer relationships. Because of the special significance of sport to Indigenous communities and it’s identified potential to remediate entrenched disadvantage, there is a strong imperative for further research that explores not only physical activity and sport, but
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also more holistic perspectives on the communities in which these occur, to discover
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Wake, M., Clifford, S., York, E., Olds, T., and Wong, T.Y. (2014). Introducing Growing Up In Australia’s Child Health Checkpoint: a physical and biomarkers module for the Longitudinal Study of Australian Children. Family
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Matters, 95, 14 et ss.
Ware, V.-A., & Meredith, V. (2013). Supporting healthy communities through sports
Gap Clearinghouse.
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and recreation programs. Resource sheet no. 26 produced for the Closing the
Whimpress, B. (1999). Passport to nowhere: Aborigines in Australian cricket, 1850-
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1939. Sydney: Walla Walla Press.
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Supplementary Materials (for online publication only)
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Figure 1. Weighted and non-weighted sample data: Non-remote areas:
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proportion who had at least 60 minutes of physical activity yesterday
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Figure 2. Weighted and non-weighted sample data: Remote areas: proportion
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who had at least 60 minutes of physical activity yesterday
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ACCEPTED MANUSCRIPT Figure 3. Weighted and non-weighted sample data: Proportion who had at
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least 60 minutes of physical activity yesterday by SEIFA quintiles
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Figure 4: Percentage of youth reporting participating in at least 60 min of PA on the day before the interview in remote (filled circles) and non-remote areas (empty
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circles), by quintile of SEIFA IRSD.IRSD=Index of Relative Social Disadvantage
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ACCEPTED MANUSCRIPT Table 1: Proportion of Indigenous respondents, aged 5-17 years, in non-remote areas (n=2,207; N=155,950a) who reported at least 60 minutes of physical activity yesterday.
Weighted % (95% CI)
Unadjusted OR (95% CI)
OR adjusted for sex and age (95% CI)
Sex
Age (N=49,470) (N=34,410) (N=36,810) (N=35,260)
81.9 (78.4 - 85.5) 71.9 (66.7 - 77.1) 63.6 (57.7 - 69.4) 53.0 (47.6 - 58.3)
5th quintile High (N=8,080) 4th quintile (N=18,150) 3rd quintile (N=23,900) 2nd quintile (N=39,750) Low 1st quintile (N=66,070) b Equivalised household income
70.5 (58.7 - 82.2) 67.7 (60.7 - 74.7) 66.4 (59.7 - 73.1) 67.4 (62.7 - 72.2) 70.7 (66.4 – 75.0)
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[Ref] 0.61 (0.48-0.79) Linear trend: 0.63 (0.57-0.69)
0.41(0.32-0.51) Linear trend: 1.04 (0.94-1.15) [Ref]
1.16 (0.90-1.50) Linear trend: 1.01 (0.89-1.14)
--
-Linear trend: 1.03 (0.93-1.15) [Ref] 1.14 (0.87-1.49) Linear trend: 0.97 (0.86-1.09)
73.7 (61.0 - 86.4) 69.5 (59.9 - 79.2) 69.7 (63.2 - 76.2) 67.4 (61.9 - 72.9) 70.3 (66.0 - 74.6)
1.09 (0.83-1.42)
1.00 (0.76-1.31)
68.1 (64.9 - 71.3) 69.9 (65.7 - 74.1)
0.92 (0.71-1.18) [Ref]
1.01 (0.79-1.30) [Ref]
67.2 (54.3 - 80.2) 69.7 (66.0 - 73.3) 64.8 (59.2 - 70.4)
0.89 (0.48-1.65) [Ref] 0.80 (0.59-1.10)
0.92 (0.45-1.86) [Ref] 0.85 (0.61-1.18)
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5th quintile High (N=2,770) 4th quintile (N=9,250) 3rd quintile (N=20,180) 2nd quintile (N=38,270) 1st quintile Low (N=66,950) Household has salary/wage income Yes (N=90,850) No (N=65,110) c BMI Underweight (N=7,170) Normal (N=69,910) Overweight/Obese (N=40,380)
[Ref]
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5-8 years 9-11 years 12-14 years 15-17 years SEIFA (IRSD)
[Ref] 0.64 (0.60-0.67) Linear trend: 0.63 (0.57-0.70)
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73.6 (70.1 - 77.2) 63.8 (60.3 - 67.4)
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Males (N=79,770) Females (N=76,190)
[Ref]
[Ref]
Weighted number of persons, N, in the population is rounded to nearest ten. 259 out of the 2,207 persons had missing data on equivalised household income (not stated or not known). a Height and weight measurements were missing for 546 out of the 2,207 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 19 persons sampled in the more extreme classes (underweight class 2 and class 3). a
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ACCEPTED MANUSCRIPT Table 2: Proportion of Indigenous respondents, aged 5-17 years, in the remote areas (n=1,489;N=37,500d) who reported at least 60 minutes of physical activity yesterday Weighted % (95% CI)
Unadjusted OR (95% CI)
OR adjusted for age and sex (95% CI)
Sex 84.2 (80.3 - 88.0) 79.0 (74.3 - 83.7)
5-8 years (N=12,340) 9-11 years (N=9,600) 12-14 years (N=7,750) 15-17 years (N=7,810) SEIFA (IRSD)
86.0 (81.6 - 90.5) 87.0 (82.0 - 92.0) 83.8 (76.3 - 91.3) 66.0 (57.0 - 74.9)
5th quintile High (N=620) 4th quintile (N=2,170) 3rd quintile (N=3,230) 2nd quintile (N=3,900) Low (N=27,590) 1st quintile Equivalised household incomee
54.7 (21.3 - 88.1) 71.6 (57.1 - 86.1) 78.3 (65.8 - 90.7) 75.0 (61.7 - 88.4) 84.4 (80.3 - 88.5)
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[Ref] 0.69 (0.48-0.98) Linear trend: 0.67 (0.54-0.83)
0.32 (0.21-0.50) Linear trend: 1.33 (1.09-1.62) [Ref]
1.89 (1.14-3.14) Linear trend: 1.20 (0.98-1.46)
--
-Linear trend: 1.34 (1.09-1.65) [Ref]
1.94 (1.15-3.25) Linear trend: 1.18 (0.96-1.46)
73.0 (50.3 - 95.8) 83.5 (73.8 - 93.2) 74.4 (60.9 - 87.9) 77.1 (68.6 - 85.7) 85.1 (81.2 – 89.0)
1.68 (1.06-2.67)
1.60 (0.99-2.59)
79.0 (74.2 - 83.9) 85.7 (81.9 - 89.5)
0.63 (0.42-0.94) [Ref]
0.68 (0.45-1.03) [Ref]
83.8 (75.6 - 91.9) 83.3 (79.2 - 87.3) 74.9 (67.0 - 82.9)
1.04 (0.55-1.95) [Ref] 0.60 (0.37-0.98)
1.07 (0.56-2.07) [Ref] 0.67 (0.42-1.09)
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5th quintile High (N=640) 4th quintile (N=1,780) 3rd quintile (N=2,750) 2nd quintile (N=5,990) (N=18,020) 1st quintile Low Household has salary/wage income Yes (N=22,770) No (N=14,730) BMIf Underweight (N=4,660) Normal (N=17,100) Overweight / Obese (N=8,220)
[Ref]
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Age
[Ref] 0.71 (0.50-0.99) Linear trend: 0.68 (0.55-0.84)
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(N=19,160) (N=18,340)
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Males Females
[Ref]
[Ref]
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Weighted number of persons, N, in the population is rounded to nearest ten. 325 out of the 1,489 persons had missing data on equivalised household income (not stated or not known). a Height and weight measurements were missing for 321 out of the 1,489 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 68 persons sampled (though the sample numbers is more an issue in the non-remote component) in the more extreme classes (underweight class 2 and class 3). There were 182 overweight and 123 obese class 1 persons, but proportions undertaking at least 60 minutes of physical activity is relatively similar. a
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ACCEPTED MANUSCRIPT Table 3: Association of physical health and full-time study with having at least 60 minutes of physical activity yesterday among persons aged 15-17 years old in the non-remote component (n=482; N=35,260a)
54.1 (47.6 - 60.5)
1.12 (0.71-1.78)
1.17 (0.73-1.88)
51.1 (41.5 - 60.7)
[Ref]
[Ref]
54.6 (49.3 - 59.9)
36.9 (18.2 - 55.7)
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Fair / Poor (N=3,310)
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2.06 (0.90-4.67)
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Self-assessed health Excellent / Very good / Good (N=31,950)
OR adjusted for sex (95% CI)
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Studying part-time / Not studying (N=13,250)
Unadjusted OR (95% CI)
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Whether currently studying Studying full-time (N=22,020)
Weighted % (95% CI)
[Ref]
1.98 (0.85-4.62)
[Ref]
ACCEPTED MANUSCRIPT Table 4: Association of physical health and full-time study with having at least 60 minutes of physical activity yesterday among persons aged 15-17 years old in the remote component (n=275; N=7,810viii) Unadjusted OR (95% CI)
OR adjusted for sex (95% CI)
62.4 (48.5 - 76.4)
0.71 (0.32-1.59)
0.72 (0.31-1.66)
69.9 (59.1 - 80.7)
[Ref]
[Ref]
Self-assessed health Excellent / Very good / Good (N=7,080)
66.3 (57.0 - 75.6)
1.18 (0.23-6.06)
1.29 (0.22-7.59)
Fair / Poor (N=720)
62.6 (27.5 - 97.8)
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Weighted number of persons, N, in the population is rounded to nearest ten.
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Whether currently studying Studying full-time (N=4,110) Studying part-time / Not studying (N=3,700)
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Weighted % (95% CI)
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[Ref]
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a
Weighted number of persons, N, in the population is rounded to nearest ten. 259 out of the 2,207 persons had missing data on equivalised household income (not stated or not known). c Height and weight measurements were missing for 546 out of the 2,207 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 19 persons sampled in the more extreme classes (underweight class 2 and class 3). d Weighted number of persons, N, in the population is rounded to nearest ten. e 325 out of the 1,489 persons had missing data on equivalised household income (not stated or not known). f Height and weight measurements were missing for 321 out of the 1,489 persons (not taken because of refusal or other reasons). There are 3 underweight classes, but there were only 68 persons sampled (though the sample numbers is more an issue in the non-remote component) in the more extreme classes (underweight class 2 and class 3). There were 182 overweight and 123 obese class 1 persons, but proportions undertaking at least 60 minutes of physical activity is relatively similar.
Weighted number of persons, N, in the population is rounded to nearest ten.
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Physical Activity among Indigenous Australian children and youth in remote and non-remote areas
Research Highlights Sport and physical activity (PA) hold significance in Indigenous communities
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Little data relating to PA, and outcomes, within these communities has been examined
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Nationally 64-84% of Indigenous youth report => 60 min of PA on the previous day
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Females and older youth participate less, with different patterns in remote areas
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Limitations in the available national data mean further research is needed
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•