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Why some do but too many don’t? Barriers and enablers to physical activity in regional Tasmania – an exploratory, mixed-methods study

Abstract

Background

The interconnectedness of physical inactivity and sedentarism, obesity, non-communicable disease (NCD) prevalence, and socio-economic costs, are well known. There is also strong research evidence regarding the mutuality between well-being outcomes and the neighbourhood environment. However, much of this evidence relates to urban contexts and there is a paucity of evidence in relation to regional communities. A better understanding of available physical activity (PA) infrastructure, its usage, and community perceptions regarding neighbourhood surroundings, could be very important in determining requirements for health improvement in regional communities. The aims of this research were to 1. Explore and evaluate the public’s perception of the PA environment; and 2. Evaluate the quantity, variety, and quality of existing PA infrastructure in regional Northwest (NW) Tasmania.

Methods

A mixed methods approach guided data collection, analysis, and presentation. Quality of PA infrastructure was assessed using the Physical Activity Resource Assessment (PARA) instrument and public perception about PA environment was evaluated using the International Physical Activity Questionnaire – Environmental (IPAQ-E) module. Quantitative data were analysed using descriptive summative methods and a team-based researcher triangulation approach was utilised for qualitative data.

Results

Overall, a wide array of high-quality PA infrastructure (with minimal incivilities such as auditory annoyance, litter, graffiti, dog refuse, and vandalism etc.) was available. Survey respondents rated neighbourhoods positively. The overall quality of PA infrastructure, rated on a scale from 0 to 3, was assessed as high (all rated between 2 to 3) with minimal incivilities (rated between 0 and 1.5). Of note, survey respondents confirmed the availability of numerous free-to-access recreational tracks and natural amenities across the 3 local government areas (LGAs) studied. Importantly, most respondents reported minimal disruption to their routine PA practices due to the COVID-19 pandemic.

Conclusion

This exploratory research confirmed the availability of a wide range of high-quality PA infrastructure across all three LGAs and there was an overwhelming public appreciation of this infrastructure. The challenge remains to implement place-based PA interventions that address extant barriers and further increase public awareness and utilisation of high-quality PA infrastructure.

Peer Review reports

Background

The interconnectedness of physical inactivity and sedentarism, obesity, non-communicable disease (NCD) prevalence, and socio-economic costs, are well documented [1, 2]. A range of approaches have been posited to thwart the inactivity pandemic, including the identification and management of ‘individual determinants.’ Considerable attention has also been paid to the ‘person-environment fit model’ [3] representative of the mutuality between well-being outcomes and the neighbourhood environment.

Empirical evidence has highlighted numerous features of neighbourhoods such as cost of access, safety supports, amenities, traffic conditions, transit access, aesthetics etc. and their potential impact on physical activity (PA) patterns [4, 5]. Neighbourhoods conducive to PA can directly influence communal activity and social engagement patterns [6, 7]. In urban contexts, access to PA facilities, convenient and proximate access to destinations, high residential density, land use, perceived safety and availability of exercise equipment, have all been cited as potential correlates (largely base on cross-sectional associations) [8]. In contrast, there is a paucity of evidence in regional communities [9,10,11]. The phrase, ‘rural and remote’, encompasses all regional areas outside Australia’s major cities, using the Australian Standard Geographical Classification System. Research suggests that compared with those living in urban settings, rural residents are likely to experience different challenges to maintain an active lifestyle [8, 9, 12]. Less than 50% of the Australian adult population meets the current recommendations for PA [13] and the prevalence of inactivity is higher amongst individuals living in rural settings, mainly due to lack of, or perceived lack of PA opportunities and poor functionality of available infrastructure [14, 15].

In addition, evidence, including in Australia, is replete with reports of negative associations between socio-economic status (SES) and population-wide PA levels (particularly leisure-time, and transport-related PA) [16, 17]. For example, Giles-Corti et al. indicated that people living in low-SES neighbourhoods were less likely to use recreational facilities and engage in adequate levels of PA [18]. Similar findings have been reported in other developed economies, including in the United States [19]. One of the reasons cited for lower engagement in PA in low-SES areas is lack of accessibility to infrastructure [18,19,20]. Rural and regional Tasmania, including the Northwest (NW), is characterised by areas of low-SES and has some of the poorest PA participation rates in the country [21, 22]. Environmental factors may also act as barriers or enablers to PA participation and whilst not exclusive to regional communities [23], could be a key factor regarding engagement in sufficient amounts of PA.

The availability of pertinent infrastructure, and perception of neighbourhood surroundings (e.g., quality and accessibility), can also impact participation in PA [24,25,26]. However, there is considerable conjecture pertaining to environmental perceptions and activity patterns [27]. As such, a better understanding of PA infrastructure availability, its usage, and community perceptions regarding neighbourhood characteristics could be very important to better understand how to improve the health status of residents in regional communities.]

Therefore, the aims of this research were to:

  1. 1.

    Explore and evaluate the public’s perception of the PA environment in rural/remote/regional communities.

  2. 2.

    Explore and evaluate the quantity, variety, and quality of existing PA infrastructure in NW Tasmania.

Methods

This study was part of a larger obesity prevention effort, the Critical Age Periods Impacting the Trajectory of Obesogenic Lifestyles (CAPITOL) Project, undertaken by the University of Tasmania in NW Tasmania across three regional Local Government Areas (LGAs), Burnie, Devonport, and Circular Head. Regional Australia includes all the towns, small cities and areas that lie beyond the major capital cities (Sydney, Melbourne, Brisbane, Perth, Adelaide, and Canberra) [28]. A LGA is an administrative division with responsibility vested in local government (Local Government Act 1993). Briefly, the selected LGAs are classified as Remoteness Area 2 (Inner Regional Australia) and 3 (Outer Regional Australia), according to the Australian Statistical Geography Standard classification system.

Study participants

Community members over 18 years of age residing in the Burnie, Devonport, or Circular Head LGAs were invited to participate in the research. Invitations were extended through a variety of web (e.g., University and local council web and social media pages) and print media (e.g., local newspapers), and surveys were made available in both print and online forms to optimize outreach. All procedures were approved by the Human Research Ethics Committee (Tasmania) Network; H0016117 and conformed to the guidelines of the National Health and Medical Research Council’s National Statement on Ethical Conduct in Human Research 2007 (Updated 2018). Submission/ return of completed surveys was contingent upon the provision of consent from all individuals.

Variety of physical activity infrastructure

A comprehensive list of the PA infrastructure across each LGA was generated by research staff from online search engines (e.g., Google, Bing), social media (Facebook), Yellow Pages and relevant LGA and State Government webpages (Fig. 1). This list was verified and checked via multiple sources including trained researchers and community champions. Infrastructure was added or subtracted based on initial screening, ground truthing where applicable, and consultation with Council staff. For the purposes of this research, only facilities and spaces with public access (not private homes and worksites), were considered as PA infrastructure. The infrastructure was then categorised into purpose-built outdoor recreation pathways, tracks or trails, natural amenities or green spaces, sporting venues used for community sport and recreation, multipurpose community centres, gyms, fitness centres and dance studios, and schools, based on previously published approaches [20, 29].

Fig. 1
figure 1

Physical activity infrastructure identification and assessment process

Quality of physical activity infrastructure

Quality of infrastructure was assessed using the Physical Activity Resource Assessment (PARA) instrument [30]. A four-person research team underwent training and pilot tested the PARA instrument prior to being deployed in the field, and all assessments were undertaken from June to July 2020. To minimise subjective bias, at least two persons independently assessed each infrastructure item.

Perceptions of the physical activity environment

Public perception of the PA environment was evaluated using the International Physical Activity Questionnaire – Environmental module (IPAQ-E) [31]. The IPAQ-E is a 17-item questionnaire (7 core and 10 optional items) that measures attributes of the built neighbourhood, and social environments hypothesized, or known, to be related to PA. These include, perceived safety of local surroundings, attractiveness, pleasantness of walking near home, proximity of shops, availability of walking and biking routes, and traffic patterns. Three additional open-ended questions were included to elicit further information about 1. Barriers to regular activity, 2. Impact of COVID-19 on activity patterns, and 3. Other location-specific challenges to being active (Table 1).

Table 1 Structure of IPAQ-E and open-ended questions

Participants were initially recruited via online invitations extended through LGA websites, their social media pages, local newspapers, and the University of Tasmania Facebook page. The online recruitment drive was supplemented with a targeted letterbox drop of paper surveys to the most populous suburbs in each LGA.

Quantitative data analysis

Thirty-seven elements (13 features, 12 amenities, and 12 incivilities) of each piece of infrastructure were coded for quality using a three-category quantitative system. Briefly, each resource was rated as 3 “good,” 2 “mediocre,” or 1 “poor,” in accordance with objective standards of quality. Additionally, each infrastructure item was rated on overall incivilities (i.e., auditory annoyance, broken glass, dog refuse, evidence of alcohol use, graffiti or tagging, litter, no grass, overgrown grass, and vandalism) using a 3-point scale (3 “high,” 2 “medium,” or 1 “low”) to derive an Incivility Score (IS) [29]. Feature and amenity scores were pooled to provide a ‘Quality Score’ (QS), with 3 being the highest quality. The QS was derived by calculating the mean of (rated) feature and amenity items for each infrastructure asset. The overall IS was derived by calculating the mean of (rated) incivility items for each infrastructure, again using the 3-point scale with 3 being the highest level of incivility.

Qualitative data analysis

Responses to the 17 IPAQ-E questions regarding the local physical environment (defined as a 10- to 15-min walk from the home) were collated and presented as percentages for each item using a four-point Likert scale. A team-based, researcher triangulation approach to qualitative thematic data analysis was used to manage and interpret answers to the open-ended questions [32]. Briefly, researchers read and re-read all answers, identified main themes, and refined them prior to generating the ‘summary table’. All transcripts of open-ended questions were deconstructed and distributed to analytical teams of at least 2 researchers (authors on this paper). Each researcher thematically analysed data independently, through familiarisation; searching for themes (meaning); refining themes; determining the story of each of them and documenting. Subsequently, the primary author, who analysed data across all questions, coordinated and arbitrated triangulation discussions with each analytical pair. Agreement between all members regarding the themes was attained through iterative, inductive, and reflexive means to maintain rigour [33, 34].

Results

Descriptive characteristics of the survey cohort are provided in Table 2. A total of 344 adults, with a mean age of 53 years, responded to the survey with nearly two-thirds being female. Most respondents lived in ‘detached single family homes’ and in most instances, owned 1 or 2 motor vehicles (Table 2). A wide variety of PA infrastructure is available to NW Tasmanian residents with ~ 30% of facilities incurring no usage costs (Recreation tracks and natural amenities; Table 2).

Table 2 Descriptive characteristics of survey respondents and LGAs

Quality of PA infrastructure

Despite subtle differences, the overall quality of available PA infrastructure was generally high (range 2–3; Fig. 2). In contrast, incivilities were low (range 0–1.5) with auditory annoyance, graffiti or tagging and litter being the most frequently recorded incivility type (Fig. 3). Overall perceptions of the PA settings across the three LGAs in NW Tasmania were positive (Fig. 4).

Fig. 2
figure 2

Quality of available physical activity infrastructure

Fig. 3
figure 3

Types (% of total) of incivilities observed

Fig. 4
figure 4

Public perception of physical activity environment in all 3 LGAs

Proximity

Two-thirds of survey respondents indicated they had easy access to shops and amenities and approximately 75% confirmed convenient proximity to other important services such as transit stops (Fig. 4).

Availability and safety

Over 80% of the respondents indicated adequate footpaths and more than 75% indicated adequate availability of free-to-access PA options. In contrast, some 40% of respondents indicated poor availability of bike paths. More than 75% of respondents had no safety concerns during daylight hours, but some (~ 33%) were more apprehensive at night (Fig. 4).

Traffic

Many (77%) did not view ‘traffic conditions while walking’ as an impediment to being active, in contrast to 52% of respondents who perceived traffic as an impediment while cycling (Fig. 4).

Visual aesthetics and maintenance

Almost 70% of respondents were satisfied with the maintenance and upkeep of their neighbourhoods with positive perceptions about the visual and aesthetic appeal.

Infrastructure preference and barriers to participation

Close to 70% of participants indicated outdoor recreation tracks and natural amenities or green space as their infrastructure of choice for regular PA (Fig. 5). Further, in response to open-ended survey questions, approximately 50% of respondents indicated there were no significant barriers to being physically active and that the COVID-19 pandemic did not have a significant impact on their PA habits (Table 3).

Fig. 5
figure 5

Public preference for different infrastructure types

Table 3 Barriers/challenges (% of total responses) to regular physical activity in NW Tasmania

Discussion

This exploratory research evaluated the quantity, variety, and quality of PA infrastructure in three LGAs with a concomitant evaluation of public perception of the neighbourhood PA environment. Overall, an array of high-quality PA infrastructure (with minimal incivilities) was available, and survey respondents rated neighbourhoods positively. The overall quality of PA infrastructure was assessed as high (all rated between 2 to 3) with minimal incivilities (rated between 0 and 1.5). This investigation confirmed the availability of numerous free-to-access recreational tracks and natural amenities across the 3 LGAs, and importantly, most respondents reported minimal disruption to their routine PA related to the COVID-19 pandemic.

The quality and usability of PA infrastructure, visual appeal, and perceptions of safety are all important elements [35]. Evidence indicates that people tend to be more active in neighbourhoods that are visually appealing with lower numbers of incivilities [36]. On the flipside, incivilities such as litter, graffiti, dog mess and vandalism can deter people from being physically active and collectively, contribute to negative perceptions about safety [35, 37, 38]. Lower incivility numbers may also impact PA involvement and consequential advantages including reductions in the prevalence of overweight and obesity [37]. Based on our observations, litter, auditory annoyances, dog refuse and graffiti were the most common incivilities. Although minimal in total, many of the incivilities reported were as a consequence of the geographical proximity of assets to industrial precincts or major roads. Overall, QS outweighed IS for 100% of PA infrastructure assessed reinforcing the level of attractiveness and visual appeal of the region. One would posit that this appeal should assist residents to be sufficiently motivated to engage in PA.

Greater anxiety about crime (perceived or real), and concerns regarding personal safety are important considerations in the PA participation patterns of many adults [35, 39, 40]. For example, adequate lighting (or lack thereof) can be a key component of perception of safety with the potential to impact PA behaviour [20]. In predominantly urban environments, presence of lighting has repeatedly been highlighted as the most important environmental feature that affects the perception of safety [41, 42].

Affordability of quality PA infrastructure and SES are intertwined, with previous research indicating that poorer neighbourhoods are usually the most affected [20, 43, 44]. One might contend that a regional area such as NW Tasmania may be particularly challenged in this context as socio-economic disparities are widespread, and the prevalence of several inactivity-related chronic conditions (including overweight and obesity), is high [22]. Our observations contradicted this notion with a total of 47 free-to-access recreation tracks and natural amenities with minimal incivilities available across the three LGAs. This is despite the SES level in the NW being lower than the country-wide average [45]. Our objective observations were further confirmed by survey respondents’ acknowledgement of the conduciveness of their ‘living environments’ to active recreation. These findings suggest that NW Tasmanian residents have ample opportunity (i.e., infrastructure) to be habitually physically active, in spite of socio-economic challenges. What might be done to assist these well-intentioned communities be more active?

One of the potential opportunities relates to the use of ‘social enterprises’ in each LGA, such as community sporting organisations, to progress local development agendas [46]. This is a potentially potent opportunity given that traditionally, engagement in community sport is an important element of the social fabric in NW Tasmania. The very low reported usage of (~ 20% of total responses) ‘sporting facilities’ is intriguing given the traditional interest in sport and activity (Fig. 4). Life-long health benefits of participation in sport are well documented [47] although engagement in sporting pursuits can depend on a myriad of factors, including gender, SES and geographical location [48, 49]. Australian data indicate a positive correlation between sport and PA participation and SES, and a negative association with remoteness and rurality [50]. Accordingly, initiatives to optimize the utilisation of community sporting facilities should be prioritised in this region.

Contrary to our expectations, most survey respondents reported uninhibited PA routines during the COVID-19 pandemic. It is difficult to predict the longer-term effects of the pandemic, however, significant concerns have been flagged regarding the effects of COVID-19 on existing levels of physical inactivity [51]. For instance, some of the pandemic mitigation measures (lockdowns, shelter in place, social distancing etc.) may impact accessibility to PA infrastructure, and therefore, levels of PA. The abundance of walkable areas, natural amenities, and green spaces in NW Tasmania may have enabled local residents to be relatively uninterrupted in recreation opportunities and is consistent with respondents’ perception of minimal disruption to routine habits during the pandemic (Table 2). However, some respondents were negatively impacted by social isolation due to COVID-19 restrictions (Table 2). As existing evidence highlights a strong association between isolation and lack of social interaction and inactivity across a wide age range, [52,53,54] concerted efforts are required to assist in the maintenance or improvement of the mental health of communities in the NW.

There are also numerous examples of associations between insufficient motivation and time with reductions in leisure-time PA [55, 56] and in particular, lack of social support [57]. The majority of survey respondents reported seeing ‘many people being physically active in their neighbourhood’, and ‘there being many interesting things to look at while walking in their neighbourhoods’. In summary, it appears there is adequate social and environmental supports for NW Tasmanian adults to be sufficiently physically active. It is noteworthy that a small number of residents perceived poor health and lack of infrastructure as barriers to PA. Both perceptions warrant further attention in larger scale future research. The use of validated (both construct and content) assessment tools is a significant strength of this study [20, 30, 58]. The use of open-ended questions to bookend the survey is also noteworthy and likely improved data quality as previously referenced [59]. Nevertheless, the generalisability of the findings to other regions may be limited due to the relatively low number of survey responses and potential lack of representativeness of the wider community. Conceptually, sample adequacy in qualitative research is an ongoing debate with epistemological, methodological, contextual, and practical necessities thought to affect the final size [60, 61]. Whilst larger sample sizes are invariably preferred, sample adequacy can also be reflected in any given cohort’s ability to yield richly textured information. Information redundancy and data saturation are also important considerations in this context [62,63,64].

Conclusions

The relationship between the built environment and PA is multifaceted and complex. As such, a better understanding of the physical characteristics of neighbourhoods may help us to better understand why a significant proportion of adults do not meet recommended levels of PA. In urban contexts, access to PA facilities, convenient and proximate access to destinations, high residential density, land use, perceived safety and availability of exercise equipment have all been cited as potential determinants of PA levels [8]. As outlined in the COM-B model of change, a particular behaviour will only occur when ‘an individual has the capability and opportunity to engage in the target behaviour and is more motivated to enact that behaviour than any other behaviours’ [65]. Evidence from this exploratory research confirms the availability of a wide variety of high-quality PA infrastructure across the three LGAs. Moreover, there was an overwhelming public appreciation of this infrastructure. As such, we postulate that neither capability nor opportunity, but rather motivation, may be a significant barrier influencing the low habitual PA engagement in these communities. As has been theorised, individual disposition to experience different motivations changes over time and with experience [66]. Therefore, a system-wide approach to promoting PA interventions through environmental, policy and legislative changes to make active choices easier for all, may be required.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CAPITOL:

Critical Age Periods Impacting the Trajectory of Obesogenic Lifestyles

IPAQ-E:

International Physical Activity Questionnaire – Environmental module (IPAQ-E)

IS:

Incivility score

LGA:

Local Government Area

NCD:

Non-communicable disease

NW:

Northwest

PA:

Physical activity

PARA:

Physical Activity Resource Assessment

QS:

Quality score

SES:

Socio-economic status

References

  1. Kohl HW 3rd, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. Group LPASW: the pandemic of physical inactivity: global action for public health. Lancet. 2012;380(9838):294–305.

    Article  PubMed  Google Scholar 

  2. Jayasinghe S, Byrne NM, Patterson KA, Ahuja KD, Hills AP. The current global state of movement and physical activity-the health and economic costs of the inactive phenotype. Prog Cardiovasc Dis. 2020;64:9–16.

  3. Stokols D. Translating social ecological theory into guidelines for community health promotion. Am J Health Promot. 1996;10(4):282–98.

    Article  CAS  PubMed  Google Scholar 

  4. Sallis JF, Cerin E, Conway TL, Adams MA, Frank LD, Pratt M, et al. Physical activity in relation to urban environments in 14 cities worldwide: a cross-sectional study. Lancet. 2016;387(10034):2207–17.

    Article  PubMed  Google Scholar 

  5. Sallis JF, Bowles HR, Bauman A, Ainsworth BE, Bull FC, Craig CL, et al. Neighborhood environments and physical activity among adults in 11 countries. Am J Prev Med. 2009;36(6):484–90.

    Article  PubMed  Google Scholar 

  6. Cerin E, Vandelanotte C, Leslie E, Merom D. Recreational facilities and leisure-time physical activity: an analysis of moderators and self-efficacy as a mediator. Health Psychol. 2008;27(2S):S126.

    Article  PubMed  Google Scholar 

  7. Chaudhury H, Campo M, Michael Y, Mahmood A. Neighbourhood environment and physical activity in older adults. Soc Sci Med. 2016;149:104–13.

    Article  PubMed  Google Scholar 

  8. Bauman A, Bull F. Environmental correlates of physical activity and walking in adults and children: a review of reviews. London: National Institute of Health and Clinical Excellence; 2007.

    Google Scholar 

  9. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet (London, England). 2012;380(9838):258–71.

    Article  Google Scholar 

  10. Castrillon CIM, Beckenkamp PR, Ferreira ML, Michell JA, de Aguiar Mendes VA, Luscombe GM, et al. Are people in the bush really physically active? A systematic review and meta-analysis of physical activity and sedentary behaviour in rural Australians populations. J Glob Health. 2020;10(1):010410.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Beck AM, Eyler AA, Aaron Hipp J, King AC, Tabak RG, Yan Y, et al. A multilevel approach for promoting physical activity in rural communities: a cluster randomized controlled trial. BMC Public Health. 2019;19(1):126.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Thornton LE, Crawford DA, Cleland VJ, Timperio AF, Abbott G, Ball K. Do food and physical activity environments vary between disadvantaged urban and rural areas? Findings from the READI study. Health Promot J Austr. 2012;23(2):153–6.

    Article  PubMed  Google Scholar 

  13. Statistics ABo. Australian health survey: physical activity, 2011–12. Canberra: Canberra Australian Bureau of Statistics; 2013.

  14. Rural A. Regional and remote health: indicators of health status and determinants of health. Rural health series. Canberra: Australian Institute of Health and Welfare; 2008.

  15. Cleland V, Hughes C, Thornton L, Squibb K, Venn A, Ball K. Environmental barriers and enablers to physical activity participation among rural adults: a qualitative study. Health Promot J Austr. 2015;26(2):99–104.

    Article  PubMed  Google Scholar 

  16. Wilson DK, Kirtland KA, Ainsworth BE, Addy CL. Socioeconomic status and perceptions of access and safety for physical activity. Ann Behav Med. 2004;28(1):20–8.

    Article  PubMed  Google Scholar 

  17. Cleland V, Cocker F, Canary J, Teychenne M, Crawford D, Timperio A, et al. Social-ecological predictors of physical activity patterns: a longitudinal study of women from socioeconomically disadvantaged areas. Prev Med. 2020;132:105995.

    Article  PubMed  Google Scholar 

  18. Giles-Corti B, Donovan RJ. Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment. Prev Med. 2002;35(6):601–11.

    Article  PubMed  Google Scholar 

  19. Parks S, Housemann RA, Brownson RC. Differential correlates of physical activity in urban and rural adults of various socioeconomic backgrounds in the United States. J Epidemiol Community Health. 2003;57(1):29–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Estabrooks PA, Lee RE, Gyurcsik NC. Resources for physical activity participation: does availability and accessibility differ by neighborhood socioeconomic status? Ann Behav Med. 2003;25(2):100–4.

    Article  PubMed  Google Scholar 

  21. Primary Health Tasmania: PHT 2020 Needs assessment in. Hobart Tasmanian Government 2020.

    Google Scholar 

  22. Public Health Services Tasmania. The state of public health Tasmania in. Edited by health do. Hobart: Tasmanian Government; 2019.

    Google Scholar 

  23. Jancey J, Lee AH, James AP, Howat P, Hills AP, Anderson AS, et al. Long-term sustainability of a physical activity and nutrition intervention for rural adults with or at risk of metabolic syndrome. Aust N Z J Public Health. 2020;44(5):421–6.

    Article  PubMed  Google Scholar 

  24. Edwards MB, Theriault DS, Shores KA, Melton KM. Promoting youth physical activity in rural southern communities: practitioner perceptions of environmental opportunities and barriers. J Rural Health. 2014;30(4):379–87.

    Article  PubMed  Google Scholar 

  25. Boehmer TK, Lovegreen SL, Haire-Joshu D, Brownson RC. What constitutes an obesogenic environment in rural communities? Am J Health Promot. 2006;20(6):411–21.

    Article  PubMed  Google Scholar 

  26. Alidoust S, Bosman C, Holden G. Talking while walking: an investigation of perceived neighbourhood walkability and its implications for the social life of older people. J Housing Built Environ. 2018;33(1):133–50.

    Article  Google Scholar 

  27. Ball K, Jeffery RW, Crawford DA, Roberts RJ, Salmon J, Timperio AF. Mismatch between perceived and objective measures of physical activity environments. Prev Med. 2008;47(3):294–8.

    Article  PubMed  Google Scholar 

  28. Rural & remote Australians [https://www.aihw.gov.au/rural-health-rrma-classification]. Accessed Mar-June 2021.

  29. Lee RE, Booth KM, Reese-Smith JY, Regan G, Howard HH. The physical activity resource assessment (PARA) instrument: evaluating features, amenities and incivilities of physical activity resources in urban neighborhoods. Int J Behav Nutr Phys Act. 2005;2(1):1–9.

    Article  Google Scholar 

  30. Lee RE, Booth KM, Reese-Smith JY, Regan G, Howard HH. The physical activity resource assessment (PARA) instrument: evaluating features, amenities and incivilities of physical activity resources in urban neighborhoods. Int J Behav Nutr Phys Act. 2005;2(1):13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.

    Article  PubMed  Google Scholar 

  32. Denzin N. The research act: a theoretical introduction to sociological methods. London: Routledge; 2009.

    Google Scholar 

  33. Byrne D. A worked example of Braun and Clarke’s approach to reflexive thematic analysis. Qual Quant. 2021:1–22. https://doi.org/10.1007/s11135-021-01182-y.

  34. Braun V, Clarke V, Hayfeld N, Terry G. Answers to frequently asked questions about thematic analysis; 2019.

    Google Scholar 

  35. Foster S, Giles-Corti B. The built environment, neighborhood crime and constrained physical activity: an exploration of inconsistent findings. Prev Med. 2008;47(3):241–51.

    Article  PubMed  Google Scholar 

  36. Foster S, Giles-Corti B, Knuiman M. Creating safe walkable streetscapes: does house design and upkeep discourage incivilities in suburban neighbourhoods? J Environ Psychol. 2011;31(1):79–88.

    Article  Google Scholar 

  37. Ellaway A, Macintyre S, Bonnefoy X. Graffiti, greenery, and obesity in adults: secondary analysis of European cross sectional survey. BMJ. 2005;331(7517):611–2.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Borst HC, Miedema HM, de Vries SI, Graham JM, van Dongen JE. Relationships between street characteristics and perceived attractiveness for walking reported by elderly people. J Environ Psychol. 2008;28(4):353–61.

    Article  Google Scholar 

  39. Caputo E, Rombaldi A, Hipólito T, Silva M. Perception of safety and physical activity in adults: a systematic review. Rev Bras Atividade Física Saúde. 2016;21(6):517–24.

    Google Scholar 

  40. de Almeida MM, da Silva ICM, Hallal PC, Tomasi E. Physical activity and perceived insecurity from crime in adults: a population-based study. PLoS One. 2014;9(9):e108136.

    Article  Google Scholar 

  41. Loewen LJ, Steel GD, Suedfeld P. Perceived safety from crime in the urban environment. J Environ Psychol. 1993;13(4):323–31.

    Article  Google Scholar 

  42. Fotios S, Unwin J, Farrall S. Road lighting and pedestrian reassurance after dark: a review. Light Res Technol. 2015;47(4):449–69.

    Article  Google Scholar 

  43. Bruton CM, Floyd MF. Disparities in built and natural features of urban Parks: comparisons by neighborhood level race/ethnicity and income. J Urban Health. 2014;91(5):894.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Crawford D, Timperio A, Giles-Corti B, Ball K, Hume C, Roberts R, et al. Do features of public open spaces vary according to neighbourhood socio-economic status? Health Place. 2008;14(4):889–93.

    Article  PubMed  Google Scholar 

  45. Statistics ABo: Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016 [webpage]. 2018.

    Google Scholar 

  46. Eversole R, Barraket J, Luke B. Social enterprises in rural community development. Commun Dev J. 2014;49(2):245–61.

    Article  Google Scholar 

  47. Eime RM, Young JA, Harvey JT, Charity MJ, Payne WR. A systematic review of the psychological and social benefits of participation in sport for children and adolescents: informing development of a conceptual model of health through sport. Int J Behav Nutr Phys Act. 2013;10(1):1–21.

    Google Scholar 

  48. Bauman A, Curac N, King L, Venugopal K, Merom D. Active, healthy cities–how does population physical activity vary between Australian cities? Health Promot J Austr. 2012;23(3):201–7.

    Article  PubMed  Google Scholar 

  49. Craike MJ, Symons C, Eime RM, Payne WR, Harvey JT. A comparative study of factors influencing participation in sport and physical activity for metropolitan and rural female adolescents. Ann Leisure Res. 2011;14(4):355–68.

    Article  Google Scholar 

  50. Eime RM, Charity MJ, Harvey JT, Payne WR. Participation in sport and physical activity: associations with socio-economic status and geographical remoteness. BMC Public Health. 2015;15(1):1–12.

    Article  Google Scholar 

  51. Hall G, Laddu DR, Phillips SA, Lavie CJ, Arena R. A tale of two pandemics: how will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another? Prog Cardiovasc Dis. 2021;64:108.

    Article  PubMed  Google Scholar 

  52. Elovainio M, Hakulinen C, Pulkki-Råback L, Virtanen M, Josefsson K, Jokela M, et al. Contribution of risk factors to excess mortality in isolated and lonely individuals: an analysis of data from the UK biobank cohort study. Lancet Public Health. 2017;2(6):e260–6.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Thompson T, Rodebaugh TL, Bessaha ML, Sabbath EL. The association between social isolation and health: an analysis of parent–adolescent dyads from the family life, activity, sun, health, and eating study. Clin Soc Work J. 2020;48(1):18–24.

    Article  PubMed  Google Scholar 

  54. Montgomery SC, Donnelly M, Bhatnagar P, Carlin A, Kee F, Hunter RF. Peer social network processes and adolescent health behaviors: a systematic review. Prev Med. 2020;130:105900.

    Article  PubMed  Google Scholar 

  55. Booth ML, Bauman A, Owen N, Gore CJ. Physical activity preferences, preferred sources of assistance, and perceived barriers to increased activity among physically inactive Australians. Prev Med. 1997;26(1):131–7.

    Article  CAS  PubMed  Google Scholar 

  56. Cerin E, Leslie E, Sugiyama T, Owen N. Perceived barriers to leisure-time physical activity in adults: an ecological perspective. J Phys Act Health. 2010;7(4):451–9.

    Article  PubMed  Google Scholar 

  57. Burton NW, Turrell G, Oldenburg B. Participation in recreational physical activity: why do socioeconomic groups differ? Health Educ Behav. 2003;30(2):225–44.

    Article  PubMed  Google Scholar 

  58. Alexander A, Bergman P, Hagströmer M, Sjöström M. IPAQ environmental module; reliability testing. J Public Health. 2006;14(2):76.

    Article  Google Scholar 

  59. Ogden J, Cornwell D. The role of topic, interviewee and question in predicting rich interview data in the field of health research. Sociol Health Illn. 2010;32(7):1059–71.

    Article  PubMed  Google Scholar 

  60. Baker SE, Edwards R. How many qualitative interviews is enough; 2012.

    Google Scholar 

  61. Vasileiou K, Barnett J, Thorpe S, Young T. Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Med Res Methodol. 2018;18(1):1–18.

    Article  Google Scholar 

  62. Lincoln YS, Guba EG. Naturalistic inquiry. UK: Sage; 1985.

  63. Glaser BG, Strauss AL, Strutzel E. The discovery of grounded theory; strategies for qualitative research. Nurs Res. 1968;17(4):364.

    Article  Google Scholar 

  64. Hennink MM, Kaiser BN, Marconi VC. Code saturation versus meaning saturation: how many interviews are enough? Qual Health Res. 2017;27(4):591–608.

    Article  PubMed  Google Scholar 

  65. Michie S, Van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6(1):1–12.

    Article  Google Scholar 

  66. West R, Michie S. A brief introduction to the COM-B model of behaviour and the PRIME theory of motivation [v1]. Qeios; 2020.

    Google Scholar 

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Acknowledgements

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Funding

This work was funded by a National Health & Medical Research Council (NHMRC) grant as part of the CAPITOL Project. The study funder had no role in study design, collection, analysis, or interpretation of the data, in writing the report, or in the decision to submit the article for publication. The contents of this article are the responsibility of the authors and do not reflect the views of the NHMRC.

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SJ, APH - Conceptualisation/design of the study, formulating research questions, writing, and editing drafts, data collection/analysis. RS, KAEP, KDKA, RH, TPH, NMB - Conceptualisation/design of the study, review and editing of the manuscript. The author(s) read and approved the final manuscript.

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Correspondence to Sisitha Jayasinghe.

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Jayasinghe, S., Soward, R., Holloway, T.P. et al. Why some do but too many don’t? Barriers and enablers to physical activity in regional Tasmania – an exploratory, mixed-methods study. BMC Public Health 22, 627 (2022). https://doi.org/10.1186/s12889-022-13001-6

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