Next Article in Journal
Enhanced Automatic Identification of Urban Community Green Space Based on Semantic Segmentation
Next Article in Special Issue
Change of Residents’ Attitudes and Behaviors toward Urban Green Space Pre- and Post- COVID-19 Pandemic
Previous Article in Journal
The Functional Value Evolution of Rural Homesteads in Different Types of Villages: Evidence from a Chinese Traditional Agricultural Village and Homestay Village
Previous Article in Special Issue
Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Perceived Qualities, Visitation and Felt Benefits of Preferred Nature Spaces during the COVID-19 Pandemic in Australia: A Nationally-Representative Cross-Sectional Study of 2940 Adults

1
School of Population Health, University of New South Wales, Sydney, NSW 2052, Australia
2
Population Wellbeing and Environment Research Lab (PowerLab), NSW, Australia
3
School of Health and Society, University of Wollongong, Wollongong, NSW 2522, Australia
*
Author to whom correspondence should be addressed.
Land 2022, 11(6), 904; https://doi.org/10.3390/land11060904
Submission received: 11 May 2022 / Revised: 10 June 2022 / Accepted: 10 June 2022 / Published: 14 June 2022

Abstract

:
We investigated how the perceived quality of natural spaces influenced levels of visitation and felt benefits during the COVID-19 pandemic in Australia via a nationally representative online and telephone survey conducted on 12–26 October (Social Research Centre’s Life in AustraliaTM panel aged > 18 years, 78.8% response, n = 3043). Our sample was restricted to those with complete information (n = 2940). Likert scale responses to 18 statements regarding the quality of local natural spaces that participants preferred to visit were classified into eight quality domains: access; aesthetics; amenities; facilities; incivilities; potential usage; safety; and social. These domains were then summed into an overall nature quality score (mean = 5.8, range = 0–16). Associations between these quality variables and a range of nature visitation and felt benefits were tested using weighted multilevel models, adjusted for demographic and socioeconomic confounders. Compared with participants in the lowest perceived nature quality quintile, those in the highest quality quintile had higher odds of spending at least 2 h in their preferred local nature space in the past week (Odds Ratio [OR] = 3.40; 95% Confidence Interval [95%CI] = 2.38–4.86), of visiting their preferred nature space almost every day in the past four weeks (OR = 3.90; 2.77–5.47), and of reporting increased levels of nature visitation in comparison with before the COVID-19 pandemic (OR = 3.90; 2.54–6.00). Participants in the highest versus lowest perceived nature quality quintile also reported higher odds of feeling their visits to nature enabled them to take solace and respite during the pandemic (OR = 9.49; 6.73–13.39), to keep connected with their communities (OR = 5.30; 3.46–8.11), and to exercise more often than they did before the pandemic (OR = 3.88; 2.57–5.86). Further analyses of each quality domain indicated time in and frequency of visiting nature spaces were most affected by potential usage and safety (time in nature was also influenced by the level of amenity). Feelings of connection and solace were most affected by potential usage and social domains. Exercise was most influenced by potential usage, social and access domains. In conclusion, evidence reported in this study indicates that visits to nature and various health-related benefits associated with it during the COVID-19 pandemic were highly contingent upon numerous qualities of green and blue spaces.

1. Introduction

Epidemiological, experimental and ethnographic research accumulated over many decades indicates that contact with nature (i.e., green and blue spaces) can provide relief from stress and restore depleted cognitive resources, enrich lives with more socially and physically active recreational pursuits, and endow communities with cleaner and cooler microclimates [1,2,3]. The net-health benefits of these entwined pathways include lower risks of cardiovascular diseases [4,5,6,7,8,9,10,11], diabetes [12,13,14] and death [15], while a smaller number of studies also identify lower risks of loneliness [16,17], cognitive decline and dementia [18,19,20,21,22,23,24,25,26,27].
Numerous studies around the world have shone a light on how contact with nature has played an important role in coping with protracted socioeconomic upheaval and significant emotional distress during the COVID-19 pandemic [28]. Many have zeroed in on the mental health benefits of nature during this difficult period [29]. Some work has focused on the inequalities that were exacerbated by lockdowns [30] and the compensation of private gardens for a lack of access to public green spaces [31,32]. Others have shown how the rapid transition to ‘remote work’ in some countries enabled more people to benefit from spending time in nature [33]. Notable for its absence from current research, however, was the critical issue of green and blue space quality, which was not mentioned once in a comprehensive narrative review of studies published [28]. To our knowledge, only one study has examined the role of green space quality during the pandemic [29].
Green and blue space quality is a critical issue for health and mental health in particular, as many previous studies conducted before the COVID-19 pandemic demonstrate [34,35,36,37]. Qualitative evidence bears this out in ways that are largely absent from the epidemiological literature [38,39]. For example, many people will visit natural settings that they identify as providing sources of non-judgmental, ego-free and dependable support [40]; it would be erroneous to consider all green and blue spaces as affording such precious experiences. Meanwhile, some natural settings can, as a result of regular visitation over time and over generations, become invested with individual and shared meanings that (re)generate feelings of connection and belonging within and between nearby communities [41]. Clearly, not all green and blue spaces share equal value. If a nearby green or blue space has a deficit of what people might need or desire (i.e., ‘good’ qualities) and/or an abundance of things they might seek to avoid (i.e., ‘bad’ qualities), a situation may transpire where there are lots of nature spots nearby but this does not necessarily translate into better health.
Accordingly, we sought to look beyond the sole issues of availability and accessibility to investigate more holistically the degree to which the nature–health association during the COVID-19 pandemic was dependent upon the various qualities of the nearby natural settings that people prefer to visit. We examined the extent to which different aspects of visitation and contrasting health benefits were contingent upon the presence of a range of specific qualities, both good and bad. We hypothesized that people tended to visit and benefit more from green and/or blue spaces that they felt had more of the qualities they value.

2. Materials and Methods

2.1. Data

A nationally-representative survey of the Australian adult population aged ≥ 18 years was conducted between 12 and 26 October 2020 via the Social Research Centre’s Life in AustraliaTM panel. Participation was in the English language only. Panel members were recruited in 2016 via their landline or cell phone using a dual-frame random digit dialling design (RDD) with a 30:70 split between landline and cell phone sample frames. Respondents in households were selected using an alternating next or last birthday approach via the landline method wherein households were occupied by at least two residents in scope. The phone answerer was the selected respondent via the cell phone method. In each case, invitation to join the panel was for one member per household only. The panel was refreshed in 2018 using mobile phone RDD only and again in 2019 with online-only participants using a G-NAF (Geocoded National Address File) sample frame and push-to-web methodology. In each of these cases, refreshment was required to balance demographics of the panel with respect to the Australian population. Online panel members were invited to participate in the survey via email and SMS, followed by emails, telephone calls, voicemails and SMS in week 2 of the survey period to encourage completion. The Social Research Centre’s interviewers and supervisors had received training in the Life in AustraliaTM panel, survey procedures and sample management protocols, respondent liaison procedures, strategies to maintain cooperation, and detailed examination of the survey questionnaire developed by the researchers. An incentive of a supermarket or department store gift card, direct payment into a PayPal account, or donation to a designated charity was offered to all panel members to the value of AUD 10.00 each. Ethical approval for the survey was granted by the University of Wollongong HREC.
Approximately 78.8% (n = 3043) of the Life in AustraliaTM panel participated in our survey (95.0% completing online, 5.0% completing via telephone). A total of 19.9% of panel members could not be contacted during the survey period and 1.3% of invited members declined to participate. Response propensity weights were constructed by the Social Research Centre using logistic regression to limit the impact of non-participation on sample representativeness, taking into account geography, age group, gender, annual household income, citizenship status, language(s) spoken other than English, country of birth, Aboriginal or Torres Strait Islander status, number of adults and children in the household, employment status, marital status, highest education, television viewing and internet browsing habits, smoking and drinking status, general health, life satisfaction, early adopter status, caregiving, disability status, volunteer status, concession card status, and telephony status. Our sample focussed on people with full outcome data (n = 2940; 96.6%).

2.2. Outcomes: Nature Space Visitation and Felt Benefits

Six binary outcomes describing participants’ visitation of, and felt benefits from nearby natural settings during the COVID-19 pandemic were examined. Given evidence indicating at least 120 min of time in nature may support general health, we used this as a cut-point for responses to the question: “Approximately how many hours did you spend in green spaces and/or blue spaces in total over the last 7 days?” We allowed for the possibility that for some people, the natural setting(s) they would prefer to visit might not be accessible for multiple reasons and so responses to the following question were also examined: “In the past four weeks (including the weekends), how often have you visited your preferred local green space and/or blue space?” Responses were classified as ‘at least once a week’ (combining ‘almost daily’ and ‘1–4 times weekly’) or ‘less than once a week’ (combining ‘2–3 times in the past month’, ‘once or less in the past month’, and ‘never’). The third visitation-focussed outcome was used to determine if participants had increased their visit frequency since the pandemic began with the following question: “Since the COVID-19 pandemic and social distancing began in Australia, to what extent, if at all, do you agree or disagree with each of the following statements? (A) I now visit green spaces and/or blue spaces more often than before the COVID-19 pandemic”. This question set also included three statements pertaining to felt benefits, as follows: “(B) Green spaces and/or blue spaces have helped me to stay connected with my neighbours during the COVID-19 pandemic. (C) Green spaces and/or blue spaces have brought me solace and respite in these challenging times. (D) I now walk and/or exercise in green spaces and/or blue spaces more frequently than before the COVID-19 pandemic”.

2.3. Qualities of Nearby Natural Spaces

Eighteen different quality indicators on the nearby natural setting participants preferred to visit were measured in the survey (Table 1). These indicators were used to construct eight different quality domains adopted from a published green space quality auditing tool [42]. The survey question was “Thinking of the green space and/or blue space you prefer to visit most often and your experiences in it, how much do you agree or disagree with the following statements?” The first domain was “access”, for which participants were asked whether their preferred nature spaces were well-connected by public transport, footpaths and road crossing points. The second domain, “aesthetics”, examined views concerning potential for exploration and interesting discoveries, as well as pleasant natural vistas and biodiverse soundscapes. “Amenities” were the third domain to permit acknowledgement of adjacent reasons people might visit the natural setting for, such as before or after shopping and dining out. The amenities domain also included a separate question on provision of shade along footpaths from tree canopy cover. The fourth domain described “facilities”, including those used for physical activity, public bathrooms, and seating. “Incivilities” were the fifth domain and were measured by a single item pertaining to perception of quality and maintenance of the natural space. The sixth domain described various types of “usage” including breaks from day-to-day routines, opportunities to feel some distance from cognitive demands, and spaces that children can play outdoors and/or that a participant feels they can walk and/or exercise in. The seventh domain attended to “safety”, with specific focus on safety during the evening/night. The eighth and final domain considered “social” factors, such as whether the green/blue space was viewed as a shared setting for neighbours, friends and/or family to meet. Where possible, these questions were derived from existing literature. For instance, “there is much to explore and discover there” in the aesthetics domain was drawn from Hartig’s perceived restorativeness scale [43]. The answer set to all eighteen quality indicators was a five-point Likert scale.
We classified each indicator to “disagree/ambivalent” (scoring zero, combining “strongly disagree”, “disagree”, and “neither agree nor disagree”), “agree” (scoring 1) and “strongly agree” (scoring 2). Participants’ mean scores across all quality indicators within each domain were calculated. Degree of correlation between domain means was assessed using Pearson’s correlation coefficients (Table 2), from which it was evident that most domains were weak-to-moderately correlated (e.g., the only correlation >0.6 was for the aesthetics and usage domains: coefficient = 0.619, p-value < 0.001). Those domain means were then summed across all domains to give a total quality score for nearby green and blue spaces. This total quality score was normally distributed with an overall mean of 5.84 (standard deviation = 3.05) and ranged from zero to 16. We classified it into quintiles, for which the interval means and other parameters are reported in Table 3.

2.4. Confounders

Variables that denote factors known to influence both human behaviour and psychological and social wellbeing, and also where people live and access to green and/or blue space, were measured using survey responses. These included gender, age, country of birth, language spoken at home, relationship status, highest educational qualification, annual household income, economic status (e.g., employed, retired, unemployed), perceived financial difficulties, housing type (e.g., house, flat), and urban/rural. The urban/rural variable was extended to 15 categories to account for substantial geographical variations across the states and territories of Australia, differentiating between participants living in major cities (e.g., Sydney, Melbourne) from those living in regional and rural areas of the same states (e.g., Rest of New South Wales, Rest of Victoria).

2.5. Statistical Analysis

Cross-tabulations, percentages and means were used to describe the study sample and the patterning of the total nature space quality scores across participants’ characteristics. Weighted linear regressions were used to assess associations between the total nature space quality scores and participants’ characteristics. Separate weighted logistic regressions were then used to examine associations between each of the nature space visitation and felt benefit outcomes with the quality scores, adjusting for confounding variables. All analyses were conducted in Stata V.14 (StataCorp., College Station, TX, USA).

3. Results

3.1. Sample Description and Differences in Nature Space Total Quality Scores

Weighted descriptive statistics of the study sample are reported in Table 4, as well as unadjusted mean nature space total quality scores and adjusted coefficients from a weighted multiple linear regression. The ratio of females to males is almost equal. About 53% of the sample was aged between 25 years and 54 years. About two-thirds of the sample were born in Australia and nearly four-fifths did not speak a language other than English at home. Approximately 71% of the sample were in a couple with or without children, whereas just over 15% were living in single-person households. University degrees were held by 27.6% of participants whereas the highest qualification for 13.2% was fewer than 12 years of education. In total, 59% of the sample had annual household incomes up to AUD 100 k, whereas 34.6% had incomes greater than or equal to AUD 101 k per year. Unemployment was at 9.5%, retirement at 20.7%, employment at 61.1% and those living with disability at 2.6%. Employment varied with respect to remote work, with 29.7% having no remote work option whereas 13.9% working remotely full-time. Nearly 10% of the sample reported financial difficulty relative to 26.5% who were comfortable. Approximately 37.6% of the sample was resident in the cities of Sydney or Melbourne, with 66.7% living in major cities.
The mean nature quality scores tended to be higher among males in comparison with females (Table 4). Mean nature quality scores also tended to be higher among participants aged 25–54 years in comparison to those aged 18–24 years, participants who felt their financial circumstances were comfortable relative to those who were not, and those in houses or flats relative to a farmhouse. Variations in mean nature space quality scores between other demographic and socioeconomic groups were small and not statistically significant.

3.2. Associations between Nature Space Quality Scores and Visitation and Felt Benefits

Higher quintiles of nature space total quality scores were consistently and positively associated with each of the visitation and felt benefit outcome variables, after adjustment for confounding variables and weighted for national representativeness (Figure 1).
In comparison with quintile 1 (i.e., lowest quality), participants in quintile 5 (i.e., highest quality) had 3.4 times greater odds of spending two hours or more in nature a week (odds ratio [OR] 3.40, 95% confidence interval [95%CI] 2.38–4.86), 3.9 times greater odds of visiting their nearby preferred nature setting at least once a week for the last four weeks (OR 3.90, 95%CI 2.77–5.47), and 3.9 times greater odds of reporting that they visit green and blue spaces more often now than before the COVID-19 pandemic (OR 3.90, 95%CI 2.54–5.99). In order of magnitude, participants in quintile 5 compared with quintile 1 for nature space total quality scores had 9.5 times greater odds of reporting that time in nature had been a source of solace during the pandemic (OR 9.49, 95%CI 6.73–13.39; wider confidence intervals are in part indicative of smaller sample sizes), 5.3 times greater odds of reporting that green and blue spaces had enabled them to stay connected with their neighbors (OR 5.30, 95%CI 3.46–8.11), and 3.9 times greater odds of reporting more engagement in physical activity now than before the pandemic (OR 3.88, 95%CI 2.57–5.86).
Associations between each nature space quality domain and the six visitation and felt benefit outcome variables are reported in Table 5. Models were initially fitted for each outcome and quality domain score separately, followed by models that adjusted for all quality domain scores simultaneously. Every quality domain score was associated with more favorable outcomes when analyzed in isolation and adjusted for confounding. Many domains were no longer statistically significantly associated with the outcomes after adjusting for other domains. Potential usage was the only domain that was consistently associated with increased odds of all outcomes. The magnitude of odds ratios for potential usage were also consistently larger than in other domains. The access domain was only associated with taking exercise in nature more often than before the COVID-19 pandemic. Aesthetics, facilities and incivilities were not associated with any of the outcomes, while amenities were only associated—negatively—with the odds of spending at least two hours a week in nature. Higher levels of safety were important for both achieving at least two hours a week in nature and for visiting the preferred nearby natural setting at least once a week for the last four weeks, but not for any of the other outcomes. The social domain was positively associated with staying connected, finding solace, and taking more physical activity in nature, but none of the visitation-focused outcomes.

4. Discussion

Key findings from this study affirm our hypothesis on the importance of having higher quality green and blue spaces nearby and their positive role in enabling people to keep connected with their neighbours, feel a sense of solace and maintain or increase their level of physical activity during the COVID-19 pandemic. These results present a major advance in research on nature and various aspects of mental, physical and social health experienced during the pandemic that has largely ignored the issue of quality [28]. Our results show—as many already suspected—that simply having green and/or blue space nearby is not always sufficient to elicit favorable outcomes [38,44]. This is perhaps no more vividly illustrated than the over nine-fold increase in the odds of finding solace through nature during the pandemic where those natural settings were of the highest quality quintile versus the lowest. The dose–response patterns for each of the outcomes with respect to the overall quality of nearby nature spaces demonstrate how this is not a curvilinear effect, with higher quality scores and odds of favorable outcomes following positive linearity.
Analyzing separate domains of nature space quality revealed which ones appeared to be of greater importance to specific outcomes. This is important as a common policy-relevant area for improvement with current research on perceived green space quality and various health outcomes is that data are often insufficient to discern which qualities matter most and least [45,46]. It was notable that the domain describing potential usage was consistently and positively associated with visitation and felt benefits. This is expected, as indicators in this domain emphasized nature as a setting for rest, recuperation, restoration of depleted cognitive resources, physical activity and as a play space for children. These indicators might attend more to some participants’ intrinsic motivations for seeking time in nature in comparison to other domains where descriptive elements are present, but might not necessarily be of fundamental importance to the individual responding. This domain and others that were associated with some outcomes but not all, such as the safety and social domains, appeared to be more important than others, such as incivilities, facilities and aesthetics that were no longer statistically significant in multi-domain models. To some extent, this will be due to partial overlap between each of the domains, most notably for the aesthetics and potential usage domains; the presence of wildlife and other cues that prompt interest and exploration in the aesthetic domain are concomitant with the desire to feel away from the day-to-day routine of cognitive demands.
Our survey included a partial assessment of biodiversity through a single indicator. This is important as there are now several studies indicating how objective and subjectively-measured biodiversity of green spaces (e.g., presence of birds and species diversity indicators) may be an important conduit by which some mental health benefit occurs [47,48,49,50], not least through attending to people’s preferences [51]. However, the present indicator likely only grazes the surface of this concept and this is an area in need of further research. Similarly, it is also plausible that some of the domains, such as incivilities, might be underpowered, given its current single-item focus on quality and maintenance, wherein specific issues might resonate strongly with some people (e.g., the presence of dog feces on grass). So too might be the access domain, with its focus more on getting to the natural space, rather than the accessibility within it, which might be especially important for people with physical limitations or disabilities [52,53,54]. Curiously, the amenities domain was statistically significantly and negatively associated with time in nature and non-significantly negatively associated with all other outcomes after adjusting for other domains. Caution is needed in interpreting this result. On one hand, it may be driven by multicollinearity, but on the other, negative association may be due to some people actively avoiding natural settings that are within close proximity to retail strips and similar that may attenuate their restorative experiences while in nature. For instance, while some work indicates that non-natural sounds emanating from automobiles, trucks and other elements concomitant with commercial (and industrial) landscapes may be soothed by being in nature via psychoacoustic pathways [55,56], it is unclear if such annoyances are ameliorated entirely. Furthermore, other physical cues that are either located nearby or encroach within natural settings, such as neon signage to advertise workplaces and fast-food restaurants, may also be a source of distraction (perhaps, even irritation) for many people when visiting nature for rest and escape from the day-to-day demands in life.
A third key finding was that the degree of the socioeconomic gradient in the availability of quality nature spaces was atypical, with total quality scores being only slightly higher on average for people with university-level qualifications or annual household incomes over AUD 150 k. These differences were not statistically significant in fully adjusted models. However, importantly, there was a somewhat greater gap in mean total quality scores between people whose financial situation was difficult, in comparison with those whose situation was more comfortable. These differences remained statistically significant after adjustment. How a person feels about their financial situation is important and often overlooked in epidemiological studies of person-level data that tend to rely on education, income, and in some contexts, occupational class [57,58]. While difficult financial circumstances were more common in participants with less than 12 years of education versus those with a bachelor’s degree (9.9% vs. 6.7%) or among those with AUD 50 k per annum or less versus those with AUD 151 k per annum or greater (17.8% vs. 2.63%), clearly there are situations in which those with higher qualifications and income categories may also be living under major financial strain and vice versa. This variable, therefore, provides more incisive utility for accounting for socioeconomic circumstances than other more routinely-used variables. However, it is also worth noting that how people perceive the quality of their nearby green and blue spaces may be, in part, influenced by the levels of financial and psychological strain under which they are presently living. Accordingly, further work might examine to what extent changes in perceived financial circumstances among people whose socioeconomic circumstances remain consistent, as measured by income and education (etc.), may influence how they perceive the natural spaces they have nearby.
It is worthwhile noting that although our survey was able to measure time spent in nature, which is important as previous studies have indicated [59,60], we did not have information on what survey participants did in those spaces specifically beyond the outcomes already analyzed. For instance, some people may have visited specific parks on Saturdays to engage with other local community members in the Parkrun movement, which various studies indicate provides opportunities for volunteering and social connection, as well as physical activity [61,62,63]. For many people, especially during the COVID-19 pandemic, cemeteries may have played a key role in giving people opportunities to be outdoors and connect, if not with each other, then with loved ones no longer around [64]. Others may have visited natural settings they regard as special places, perhaps due to childhood memories [65,66] or as providing opportunities to do things they feel unable to at home, such as connecting with peers through allotment gardens [67,68]. Further qualitative research and maybe further survey analysis are needed to better understand the roles in which specific types of green space and their qualities have aided coping and restoration through the pandemic.
An additional layer to this research is the well-reported socioeconomic inequities in green space and blue space availability and qualities are likely to reflect, in part, personal preferences, financial capacities and willingness to pay to live near these health-promoting resources. The intersection between these economic issues and the epidemiological literature remains a gap in knowledge, though research was carried out on these aspects. For example, Johnson and Thomassin [69] provided a model to estimate the willingness to pay for surface water quality improvements by recreational users. Further investigation utilizing longitudinal data capable of tracking changes in the qualities of green and blue spaces that occur and impacts on both the health of local residents and on population flows in and out of the areas nearby is warranted.
Beyond the strengths and limitations already discussed, this study benefits from a large and nationally representative sample of the Australian adult population, covering all states and territories. The survey contained a large range of variables used to describe green and blue spaces, permitting the identification of nature space qualities and the development of an overall score from domains established by a published study that focused on in-person auditing of parks [42]. All descriptive statistics and models were adjusted using a comprehensive set of confounding variables and also weighted to ensure parameter estimates that can be extrapolated to the adult population of Australia. The analyses use data of cross-sectional design and so the associations reported should not be interpreted as definitively revealing cause and effect. Follow-up of the same individuals over time will enable stronger epidemiological study designs with which to minimize the potential for reverse causation, wherein individuals more prone to poorer health are socioeconomically disadvantaged in part because of their circumstances and move into areas with poorer quality green and blue spaces as a result. These data and follow-up of the same individuals will also permit opportunities to study the longer-term impacts of the COVID-19 pandemic and to identify the extent to which different types of nature, preferential elements of it and ways in which people interact with it have supported recovery and flourishing.

Author Contributions

Conceptualization, X.F. and T.A.-B.; methodology, X.F. and T.A.-B.; software, T.A.-B.; validation, T.A.-B.; formal analysis, X.F. and T.A.-B.; investigation, X.F. and T.A.-B.; resources, X.F. and T.A.-B.; data curation, X.F. and T.A.-B.; writing—original draft preparation, X.F. and T.A.-B.; writing—review and editing, X.F. and T.A.-B.; visualization, X.F. and T.A.-B.; project administration, X.F. and T.A.-B.; funding acquisition, X.F. and T.A.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Hort Frontiers Green Cities Fund, part of the Hort Frontiers strategic partnership initiative developed by Hort Innovation, with co-investment from the University of Wollongong (UOW) Faculty of Arts, Social Sciences and Humanities, the UOW Global Challenges initiative and contributions from the Australian Government (project number #GC15005). T.A.-B. was supported by a National Health and Medical Research Council Boosting Dementia Research Leader Fellowship (#1140317). X.F. was supported by a National Health and Medical Research Council Career Development Fellowship (#1148792). All aspects related to the conduct of this study including the views stated and the decision to publish the findings are that of the authors only.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of the University of Wollongong (protocol code 2020/343, 14 September 2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data are not publically available.

Acknowledgments

We thank the Social Research Centre and the Life in AustraliaTM panel members. We thank Richard Mitchell (University of Glasgow) for sharing ideas on survey questions.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Markevych, I.; Schoierer, J.; Hartig, T.; Chudnovsky, A.; Hystad, P.; Dzhambov, A.M.; de Vries, S.; Triguero-Mas, M.; Brauer, M.; Nieuwenhuijsen, M.J.; et al. Exploring pathways linking greenspace to health: Theoretical and methodological guidance. Environ. Res. 2017, 158, 301–317. [Google Scholar] [CrossRef] [PubMed]
  2. Hartig, T. Restoration in nature: Beyond the conventional narrative. In Nature and Psychology: Biological, Cognitive, Developmental, and Social Pathways to Well-Being, Proceedings of the 67th Annual Nebraska Symposium on Motivation, Lincoln, NE, USA, 21–22 April 2021; Schutte, A.R., Torquati, J., Stevens, J.R., Eds.; Springer Nature: Cham, Switzerland, 2021; Volume 67. [Google Scholar]
  3. Hartig, T.; Mitchell, R.; de Vries, S.; Frumkin, H. Nature and Health. Annu. Rev. Public Health 2014, 35, 207–228. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Liu, X.-X.; Ma, X.-L.; Huang, W.-Z.; Luo, Y.-N.; He, C.-J.; Zhong, X.-M.; Dadvand, P.; Browning, M.H.; Li, L.; Zou, X.-G.; et al. Green space and cardiovascular disease: A systematic review with meta-analysis. Environ. Pollut. 2022, 301, 118990. [Google Scholar] [CrossRef] [PubMed]
  5. Astell-Burt, T.; Feng, X. Urban green space, tree canopy and prevention of cardiometabolic diseases: A multilevel longitudinal study of 46 786 Australians. Int. J. Epidemiol. 2020, 49, 926–933. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Kardan, O.; Gozdyra, P.; Misic, B.; Moola, F.; Palmer, L.; Paus, T.; Berman, M.G. Neighborhood greenspace and health in a large urban center. Sci. Rep. 2015, 5, 11610. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Moreira, T.C.L.; Polizel, J.L.; Santos, I.S.; Filho, D.F.S.; Bensenor, I.; Lotufo, P.A.; Mauad, T. Green Spaces, Land Cover, Street Trees and Hypertension in the Megacity of São Paulo. Int. J. Environ. Res. Public Health 2020, 17, 725. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Dzhambov, A.M.; Markevych, I.; Lercher, P. Greenspace seems protective of both high and low blood pressure among residents of an Alpine valley. Environ. Int. 2018, 121, 443–452. [Google Scholar] [CrossRef]
  9. Tamosiunas, A.; Grazuleviciene, R.; Luksiene, D.; Dedele, A.; Reklaitiene, R.; Baceviciene, M.; Vencloviene, J.; Bernotiene, G.; Radisauskas, R.; Malinauskiene, V.; et al. Accessibility and use of urban green spaces, and cardiovascular health: Findings from a Kaunas cohort study. Environ. Health 2014, 13, 20. [Google Scholar] [CrossRef] [Green Version]
  10. Yeager, R.; Riggs, D.W.; DeJarnett, N.; Tollerud, D.J.; Wilson, J.; Conklin, D.J.; O’Toole, T.E.; McCracken, J.; Lorkiewicz, P.; Xie, Z.; et al. Association Between Residential Greenness and Cardiovascular Disease Risk. J. Am. Heart Assoc. 2018, 7, e009117. [Google Scholar] [CrossRef]
  11. Yitshak-Sade, M.; James, P.; Kloog, I.; Hart, J.E.; Schwartz, J.D.; Laden, F.; Lane, K.J.; Fabian, M.P.; Fong, K.C.; Zanobetti, A. Neighborhood Greenness Attenuates the Adverse Effect of PM2.5 on Cardiovascular Mortality in Neighborhoods of Lower Socioeconomic Status. Int. J. Environ. Res. Public Health 2019, 16, 814. [Google Scholar] [CrossRef] [Green Version]
  12. Twohig-Bennett, C.; Jones, A. The health benefits of the great outdoors: A systematic review and meta-analysis of greenspace exposure and health outcomes. Environ. Res. 2018, 166, 628–637. [Google Scholar] [CrossRef] [PubMed]
  13. Dalton, A.M.; Jones, A.P.; Sharp, S.J.; Cooper, A.J.; Griffin, S.; Wareham, N.J. Residential neighbourhood greenspace is associated with reduced risk of incident diabetes in older people: A prospective cohort study. BMC Public Health 2016, 16, 1171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Bodicoat, D.H.; O’Donovan, G.; Dalton, A.M.; Gray, L.J.; Yates, T.; Edwardson, C.; Hill, S.; Webb, D.R.; Khunti, K.; Davies, M.J.; et al. The association between neighbourhood greenspace and type 2 diabetes in a large cross-sectional study. BMJ Open 2014, 4, e006076. [Google Scholar] [CrossRef] [Green Version]
  15. Rojas-Rueda, D.; Nieuwenhuijsen, M.J.; Gascon, M.; Perez-Leon, D.; Mudu, P. Green spaces and mortality: A systematic review and meta-analysis of cohort studies. Lancet Planet. Health 2019, 3, e469–e477. [Google Scholar] [CrossRef] [Green Version]
  16. Astell-Burt, T.; Hartig, T.; Eckermann, S.; Nieuwenhuijsen, M.; McMunn, A.; Frumkin, H.; Feng, X. More green, less lonely? A longitudinal cohort study. Int. J. Epidemiol. 2022, 51, 99–110. [Google Scholar] [CrossRef]
  17. Maas, J.; van Dillen, S.M.E.; Verheij, R.A.; Groenewegen, P.P. Social contacts as a possible mechanism behind the relation between green space and health. Health Place 2009, 15, 586–595. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Astell-Burt, T.; Navakatikyan, M.A.; Feng, X. Urban green space, tree canopy and 11-year risk of dementia in a cohort of 109,688 Australians. Environ. Int. 2020, 145, 106102. [Google Scholar] [CrossRef]
  19. Paul, L.A.; Hystad, P.; Burnett, R.T.; Kwong, J.C.; Crouse, D.L.; van Donkelaar, A.; Tu, K.; Lavigne, E.; Copes, R.; Martin, R.V.; et al. Urban green space and the risks of dementia and stroke. Environ. Res. Lett. 2020, 186, 109520. [Google Scholar] [CrossRef]
  20. Astell-Burt, T.; Feng, X. Greener neighbourhoods, better memory? A longitudinal study. Health Place 2020, 65, 102393. [Google Scholar] [CrossRef]
  21. Brown, S.C.; Perrino, T.; Lombard, J.; Wang, K.; Toro, M.; Rundek, T.; Gutierrez, C.M.; Dong, C.; Plater-Zyberk, E.; Nardi, M.I.; et al. Health Disparities in the Relationship of Neighborhood Greenness to Mental Health Outcomes in 249,405 U.S. Medicare Beneficiaries. Int. J. Environ. Res. Public Health 2018, 15, 430. [Google Scholar] [CrossRef] [Green Version]
  22. Cherrie, M.P.; Shortt, N.K.; Mitchell, R.J.; Taylor, A.M.; Redmond, P.; Thompson, C.W.; Starr, J.M.; Deary, I.J.; Pearce, J.R. Green space and cognitive ageing: A retrospective life course analysis in the Lothian Birth Cohort. Soc. Sci. Med. 2018, 196, 56–65. [Google Scholar] [CrossRef] [PubMed]
  23. Cherrie, M.P.; Shortt, N.K.; Thompson, C.W.; Deary, I.J.; Pearce, J.R. Association Between the Activity Space Exposure to Parks in Childhood and Adolescence and Cognitive Aging in Later Life. Int. J. Environ. Res. Public Health 2019, 16, 632. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Crous-Bou, M.; Gascon, M.; Gispert, J.D.; Cirach, M.; Sánchez-Benavides, G.; Falcon, C.; Arenaza-Urquijo, E.M.; Gotsens, X.; Fauria, K.; Sunyer, J.; et al. Impact of urban environmental exposures on cognitive performance and brain structure of healthy individuals at risk for Alzheimer’s dementia. Environ. Int. 2020, 138, 105546. [Google Scholar] [CrossRef] [PubMed]
  25. De Keijzer, C.; Tonne, C.; Basagaña, X.; Valentín, A.; Singh-Manoux, A.; Alonso, J.; Antó, J.M.; Nieuwenhuijsen, M.J.; Sunyer, J.; Dadvand, P.; et al. Residential Surrounding Greenness and Cognitive Decline: A 10-Year Follow-Up of the Whitehall II Cohort. Environ. Health Perspect. 2018, 126, 077003. [Google Scholar] [CrossRef] [Green Version]
  26. Dzhambov, A.M.; Bahchevanov, K.M.; Chompalov, K.A.; Atanassova, P.A. A feasibility study on the association between residential greenness and neurocognitive function in middle-aged Bulgarians. Arch. Ind. Hyg. Toxicol. 2019, 70, 173–185. [Google Scholar] [CrossRef] [Green Version]
  27. Ho, H.C.; Fong, K.N.K.; Chan, T.-C.; Shi, Y. The associations between social, built and geophysical environment and age-specific dementia mortality among older adults in a high-density Asian city. Int. J. Health Geogr. 2020, 19, 1–13. [Google Scholar] [CrossRef]
  28. Labib, S.; Browning, M.H.; Rigolon, A.; Helbich, M.; James, P. Nature’s contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID. Sci. Total Environ. 2022, 833, 155095. [Google Scholar] [CrossRef]
  29. Reid, C.E.; Rieves, E.S.; Carlson, K. Perceptions of green space usage, abundance, and quality of green space were associated with better mental health during the COVID-19 pandemic among residents of Denver. PLoS ONE 2022, 17, e0263779. [Google Scholar] [CrossRef]
  30. Burnett, H.; Olsen, J.R.; Nicholls, N.; Mitchell, R. Change in time spent visiting and experiences of green space following restrictions on movement during the COVID-19 pandemic: A nationally representative cross-sectional study of UK adults. BMJ Open 2021, 11, e044067. [Google Scholar] [CrossRef]
  31. Ribeiro, A.I.; Triguero-Mas, M.; Santos, C.J.; Gómez-Nieto, A.; Cole, H.; Anguelovski, I.; Silva, F.M.; Baró, F. Exposure to nature and mental health outcomes during COVID-19 lockdown. A comparison between Portugal and Spain. Environ. Int. 2021, 154, 106664. [Google Scholar] [CrossRef]
  32. Poortinga, W.; Bird, N.; Hallingberg, B.; Phillips, R.; Williams, D. The role of perceived public and private green space in subjective health and wellbeing during and after the first peak of the COVID-19 outbreak. Landsc. Urban Plan. 2021, 211, 104092. [Google Scholar] [CrossRef]
  33. Astell-Burt, T.; Feng, X. Time for ‘green’ during COVID-19? Inequities in green and blue space access, visitation and felt benefits. Int. J. Environ. Res. Public Health 2021, 18, 2757. [Google Scholar] [CrossRef] [PubMed]
  34. Feng, X.; Astell-Burt, T. Residential Green Space Quantity and Quality and Child Well-being: A Longitudinal Study. Am. J. Prev. Med. 2017, 53, 616–624. [Google Scholar] [CrossRef] [PubMed]
  35. Feng, X.; Astell-Burt, T. Residential green space quantity and quality and symptoms of psychological distress: A 15-year longitudinal study of 3897 women in postpartum. BMC Psychiatry 2018, 18, 348. [Google Scholar] [CrossRef] [Green Version]
  36. Van Dillen, S.M.; de Vries, S.; Groenewegen, P.P.; Spreeuwenberg, P. Greenspace in urban neighbourhoods and residents’ health: Adding quality to quantity. J. Epidemiol. Community Health 2012, 66, e8. [Google Scholar] [CrossRef] [Green Version]
  37. Francis, J.; Wood, L.J.; Knuiman, M.; Giles-Corti, B. Quality or quantity? Exploring the relationship between Public Open Space attributes and mental health in Perth, Western Australia. Soc. Sci. Med. 2012, 74, 1570–1577. [Google Scholar] [CrossRef]
  38. Astell-Burt, T.; Feng, X. Paths through the woods. Int. J. Epidemiol. 2022, 51, 1–5. [Google Scholar] [CrossRef]
  39. Holland, I.; DeVille, N.V.; Browning, M.H.; Buehler, R.M.; Hart, J.E.; Hipp, J.; Mitchell, R.; Rakow, D.; Schiff, J.; White, M.; et al. Measuring Nature Contact: A Narrative Review. Int. J. Environ. Res. Public Health 2021, 18, 4092. [Google Scholar] [CrossRef]
  40. Birch, J.; Rishbeth, C.; Payne, S.R. Nature doesn’t judge you—How urban nature supports young people’s mental health and wellbeing in a diverse UK city. Health Place 2020, 62, 102296. [Google Scholar] [CrossRef]
  41. Graham, T.M.; Glover, T.D. On the Fence: Dog Parks in the (Un)Leashing of Community and Social Capital. Leis. Sci. 2014, 36, 217–234. [Google Scholar] [CrossRef]
  42. Knobel, P.; Dadvand, P.; Alonso, L.; Costa, L.; Español, M.; Maneja, R. Development of the urban green space quality assessment tool (RECITAL). Urban For. Urban Green. 2021, 57, 126895. [Google Scholar] [CrossRef]
  43. Hartig, T.; Korpela, K.; Evans, G.W.; Gärling, T. A measure of restorative quality in environments. Scand. Hous. Plan. Res. 1997, 14, 175–194. [Google Scholar] [CrossRef]
  44. Nguyen, P.-Y.; Astell-Burt, T.; Rahimi-Ardabili, H.; Feng, X. Green Space Quality and Health: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 11028. [Google Scholar] [CrossRef] [PubMed]
  45. Feng, X.; Astell-Burt, T.; Standl, M.; Flexeder, C.; Heinrich, J.; Markevych, I. Green space quality and adolescent mental health: Do personality traits matter? Environ Res. 2022, 206, 112591. [Google Scholar] [CrossRef]
  46. Feng, X.; Astell-Burt, T. Can green space quantity and quality help prevent postpartum weight gain? A longitudinal study. J. Epidemiol. Community Health 2019, 73, 295–302. [Google Scholar] [CrossRef] [Green Version]
  47. Aerts, R.; Honnay, O.; Van Nieuwenhuyse, A. Biodiversity and human health: Mechanisms and evidence of the positive health effects of diversity in nature and green spaces. Br. Med. Bull. 2018, 127, 5–22. [Google Scholar] [CrossRef] [Green Version]
  48. Marselle, M.R.; Hartig, T.; Cox, D.T.; de Bell, S.; Knapp, S.; Lindley, S.; Triguero-Mas, M.; Böhning-Gaese, K.; Braubach, M.; Cook, P.A.; et al. Pathways linking biodiversity to human health: A conceptual framework. Environ. Int. 2021, 150, 106420. [Google Scholar] [CrossRef]
  49. Rook, G.A. Regulation of the immune system by biodiversity from the natural environment: An ecosystem service essential to health. Proc. Natl. Acad. Sci. USA 2013, 110, 18360–18367. [Google Scholar] [CrossRef] [Green Version]
  50. Fuller, R.A.; Irvine, K.N.; Devine-Wright, P.; Warren, P.H.; Gaston, K.J. Psychological benefits of greenspace increase with biodiversity. Biol. Lett. 2007, 3, 390–394. [Google Scholar] [CrossRef]
  51. Harris, V.; Kendal, D.; Hahs, A.K.; Threlfall, C.G. Green space context and vegetation complexity shape people’s preferences for urban public parks and residential gardens. Landsc. Res. 2018, 43, 150–162. [Google Scholar] [CrossRef]
  52. Perry, M.; Cotes, L.; Horton, B.; Kunac, R.; Snell, I.; Taylor, B.; Wright, A.; Devan, H. “Enticing” but Not Necessarily a “Space Designed for Me”: Experiences of Urban Park Use by Older Adults with Disability. Int. J. Environ. Res. Public Health 2021, 18, 552. [Google Scholar] [CrossRef] [PubMed]
  53. Corazon, S.S.; Gramkow, M.C.; Poulsen, D.V.; Lygum, V.L.; Zhang, G.; Stigsdotter, U.K.; Gramkov, M.C. I Would Really like to Visit the Forest, but it is Just Too Difficult: A Qualitative Study on Mobility Disability and Green Spaces. Scand. J. Disabil. Res. 2019, 20, 1–13. [Google Scholar] [CrossRef]
  54. Wojnowska-Heciak, M.; Suchocka, M.; Błaszczyk, M.; Muszyńska, M. Urban Parks as Perceived by City Residents with Mobility Difficulties: A Qualitative Study with In-Depth Interviews. Int. J. Environ. Res. Public Health 2022, 19, 2018. [Google Scholar] [CrossRef] [PubMed]
  55. Dzhambov, A.M.; Dimitrova, D.D. Green spaces and environmental noise perception. Urban For. Urban Green. 2015, 14, 1000–1008. [Google Scholar] [CrossRef]
  56. Dzhambov, A.M.; Dimitrova, D.D. Urban green spaces’ effectiveness as a psychological buffer for the negative health impact of noise pollution: A systematic review. Noise Health 2014, 16, 157–165. [Google Scholar] [CrossRef]
  57. Galobardes, B.; Shaw, M.; Lawlor, D.; Lynch, J.; Davey Smith, G. Indicators of socioeconomic position (part 2). J. Epidemiol. Community Health 2006, 60, 95. [Google Scholar] [CrossRef] [Green Version]
  58. Galobardes, B.; Shaw, M.; Lawlor, D.A.; Lynch, J.W.; Davey Smith, G. Indicators of socioeconomic position (part 1). J. Epidemiol. Community Health 2006, 60, 7–12. [Google Scholar] [CrossRef] [Green Version]
  59. Shanahan, D.F.; Bush, R.; Gaston, K.J.; Lin, B.B.; Dean, J.; Barber, E.; Fuller, R.A. Health Benefits from Nature Experiences Depend on Dose. Sci. Rep. 2016, 6, 28551. [Google Scholar] [CrossRef] [Green Version]
  60. White, M.P.; Alcock, I.; Grellier, J.; Wheeler, B.W.; Hartig, T.; Warber, S.L.; Bone, A.; Depledge, M.H.; Fleming, L.E. Spending at least 120 minutes a week in nature is associated with good health and wellbeing. Sci. Rep. 2019, 9, 7730. [Google Scholar] [CrossRef] [Green Version]
  61. Wiltshire, G.; Stevinson, C. Exploring the role of social capital in community-based physical activity: Qualitative insights from parkrun. Qual. Res. Sport Exerc. Health 2018, 10, 47–62. [Google Scholar] [CrossRef] [Green Version]
  62. Morris, P.; Scott, H. Not just a run in the park: A qualitative exploration of parkrun and mental health. Adv. Ment. Health 2019, 17, 110–123. [Google Scholar] [CrossRef]
  63. Hindley, D. “More than just a run in the park”: An exploration of parkrun as a shared leisure space. Leis. Sci. 2020, 42, 85–105. [Google Scholar] [CrossRef]
  64. Swensen, G.; Skår, M. Urban cemeteries’ potential as sites for cultural encounters. Mortality 2019, 24, 333–356. [Google Scholar] [CrossRef]
  65. Rishbeth, C.; Powell, M. Place Attachment and Memory: Landscapes of Belonging as Experienced Post-migration. Landsc. Res. 2013, 38, 160–178. [Google Scholar] [CrossRef]
  66. Sobel, D. A place in the world: Adults’ memories of childhood’s special places. Child. Environ. Q. 1990, 7, 5–12. [Google Scholar]
  67. Kingsley, J.; Foenander, E.; Bailey, A. “It’s about community”: Exploring social capital in community gardens across Melbourne, Australia. Urban For. Urban Green. 2020, 49, 126640. [Google Scholar] [CrossRef]
  68. Kingsley, J.; Foenander, E.; Bailey, A. “You feel like you’re part of something bigger”: Exploring motivations for community garden participation in Melbourne, Australia. BMC Public Health 2019, 19, 745. [Google Scholar] [CrossRef] [Green Version]
  69. Johnston, R.J.; Thomassin, P.J. Willingness to Pay for Water Quality Improvements in the United States and Canada: Considering Possibilities for International Meta-Analysis and Benefit Transfer. Agric. Resour. Econ. Rev. 2010, 39, 114–131. [Google Scholar] [CrossRef]
Figure 1. Adjusted associations between nature space total quality scores and visitation and felt benefits, weighted for national representativeness.
Figure 1. Adjusted associations between nature space total quality scores and visitation and felt benefits, weighted for national representativeness.
Land 11 00904 g001
Table 1. Eighteen nature space quality indicators nested within eight quality domains.
Table 1. Eighteen nature space quality indicators nested within eight quality domains.
Thinking of the green space and/or blue space you prefer to visit most often and your experiences in it, how much do you agree or disagree with the following statements?
[strongly disagree, disagree, neither agree nor disagree, agree, strongly agree]

Domain 1: Access
“It is well connected by footpaths and safe road crossing points”
“Public transport is available nearby”

Domain 2: Aesthetics
“There is much to explore and discover there”
“My attention is drawn to many interesting things there”
“It is a place I can enjoy watching and/or listening to wildlife (e.g., birds)”

Domain 3: Amenities
“There are cafes, and/or shops, and/or supermarkets and/or restaurants nearby”
“There is lots of tree canopy along footpaths that provide shade from heat and direct sunlight”

Domain 4: Facilities
“There are free or low cost recreation facilities, such as outdoor gyms, sports grounds and/or swimming pools in it or nearby”
“There are public toilets available in it or nearby”
“There are benches in it or nearby on which I can sit and relax”

Domain 5: Incivilities
“I consider it to be high quality and well maintained”

Domain 6: Potential usage
“Spending time there gives me a break from my day-to-day routine”
“This is a place to get away from the things that usually demand my attention”
“It is a good place for children to play outdoors”
“I go there for walks and/or to exercise”

Domain 7: Safety
“This is a place I feel safe to visit during the evening/night”

Domain 8: Social
“It is a social hub for the local community”
“This is a place to spend time with friends and/or family”
Table 2. Pearson’s correlation coefficients for quality domains of natural settings.
Table 2. Pearson’s correlation coefficients for quality domains of natural settings.
AccessAestheticsAmenitiesFacilitiesIncivilitiesPotential UsageSafetySocial
Access1
Aesthetics0.1641.000
p-value<0.001
Amenities0.4620.3541.000
p-value<0.001<0.001
Facilities0.5200.2820.5071.000
p-value<0.001<0.001<0.001
Incivilities0.4250.3380.4270.5201.000
p-value<0.001<0.001<0.001<0.001
Potential Usage0.3750.6190.4410.4240.4831.000
p-value<0.001<0.001<0.001<0.001<0.001
Safety0.1240.2570.1470.1620.2150.2731.000
p-value<0.001<0.001<0.001<0.001<0.001<0.001
Social0.3960.3960.4500.5590.4770.4940.2161
p-value<0.001<0.001<0.001<0.001<0.001<0.001<0.001
Table 3. Description of the nature space total quality score quintile intervals.
Table 3. Description of the nature space total quality score quintile intervals.
QuintilesMeanStandard DeviationQuintile Bounds
1 (low)2.021.000.003.30
24.110.453.334.83
35.530.394.876.17
47.080.576.208.03
5 (high)10.531.838.0716.00
Table 4. Sample description, mean quality of preferred nearby natural setting, and adjusted differences, weighted for national representativeness.
Table 4. Sample description, mean quality of preferred nearby natural setting, and adjusted differences, weighted for national representativeness.
Total Sample n = 2940n (%)Mean (SE)Coef (95%CI) [p-Value]
Gender (ref: Female)49.4%5.6 (0.1)
 Male50.5%6.0 (0.1)0.432 (0.138, 0.726) [0.004]
 Other0.2%6.9 (1.2)0.950 (−1.091, 2.990) [0.361]
Age group (ref: 18–24 years)10.0%5.2 (0.3)
 25–34 years18.5%6.2 (0.2)0.977 (0.225, 1.729) [0.011]
 35–44 years18.1%6.2 (0.2)0.834 (0.105, 1.563) [0.025]
 45–54 years16.3%5.9 (0.2)0.764 (0.036, 1.491) [0.040]
 55–64 years15.1%5.5 (0.1)0.515 (−0.192, 1.222) [0.153]
 65–74 years14.0%5.4 (0.2)0.604 (−0.231, 1.440) [0.156]
 ≥75 years6.9%5.4 (0.2)0.588 (−0.321, 1.496) [0.205]
 Undetermined1.1%6.9 (0.9)1.792 (−0.046, 3.630) [0.056]
Country of birth (ref: Australia)66.1%5.7 (0.1)
 Overseas, not English-speaking19.1%5.8 (0.2)−0.392 (−0.946, 0.162) [0.165]
 Overseas, English-speaking14.7%5.9 (0.2)0.161 (−0.296, 0.618) [0.489]
 Undetermined0.2%7.6 (1.5)0.638 (−2.987, 4.263) [0.730]
Language other than English at home (ref: Yes)20.1%6.1 (0.2)
 No79.9%5.7 (0.1)−0.375 (−0.946, 0.196) [0.198]
Relationship status (ref: Living alone)15.2%5.5 (0.2)
 Alone with kids6.9%5.6 (0.3)0.232 (−0.426, 0.890) [0.489]
 Couple without kids27.7%5.6 (0.1)0.139 (−0.287, 0.565) [0.521]
 Couple with kids43.4%6.0 (0.1)0.413 (−0.037, 0.864) [0.072]
 Cohabiting, unrelated2.7%6.3 (0.4)0.592 (−0.212, 1.397) [0.149]
 Other4.1%4.9 (0.4)−0.576 (−1.380, 0.228) [0.160]
Highest educational qualification (ref: <Year 12)13.2%5.5 (0.2)
 Year 1219.0%5.6 (0.2)−0.020 (−0.574, 0.533) [0.943]
 Advanced diploma/certificate37.2%5.7 (0.1)0.069 (−0.385, 0.522) [0.767]
 Bachelor degree18.8%6.2 (0.1)0.334 (−0.182, 0.850) [0.204]
 Postgraduate degree8.8%6.1 (0.1)0.195 (−0.360, 0.751) [0.491]
 Undetermined3.0%5.0 (0.3)−0.310 (−1.008, 0.388) [0.384]
Annual household income (ref: ≤50 K)27.1%5.5 (0.1)
 AUD 51 K–AUD 100 K31.9%5.7 (0.1)−0.135 (−0.530, 0.259) [0.501]
 AUD 101 K–AUD 150 K18.0%6.1 (0.2)−0.115 (−0.627, 0.396) [0.658]
 ≥AUD 151 K16.6%6.1 (0.2)−0.136 (−0.776, 0.503) [0.675]
 Undetermined6.4%5.4 (0.3)−0.337 (−0.996, 0.322) [0.316]
Economic status (ref: Employed, never remotely)29.7%5.8 (0.2)
 Employed, work remotely sometimes11.0%6.0 (0.2)0.091 (−0.469, 0.650) [0.751]
 Employed, work remotely often6.5%6.2 (0.3)0.228 (−0.386, 0.842) [0.466]
 Employed, work remotely always13.9%6.3 (0.2)0.210 (−0.281, 0.701) [0.402]
 Unemployed9.5%5.3 (0.3)−0.377 (−0.993, 0.239) [0.231]
 Retired20.7%5.4 (0.1)−0.183 (−0.758, 0.393) [0.534]
 Disabled2.6%4.9 (0.3)−0.636 (−1.325, 0.053) [0.070]
 Other5.3%5.9 (0.3)0.121 (−0.505, 0.747) [0.705]
 Undetermined0.9%6.6 (0.7)0.812 (−0.615, 2.238) [0.265]
Economic difficulty (ref: Comfortable)26.5%6.2 (0.1)
 Doing ok44.2%5.7 (0.1)−0.460 (−0.809, −0.111) [0.010]
 Getting by19.3%5.6 (0.2)−0.560 (−0.990, −0.131) [0.011]
 Difficult9.9%5.3 (0.2)−0.801 (−1.398, −0.205) [0.009]
 Undetermined0.2%3.8 (0.5)−2.308 (−3.715, −0.902) [0.001]
Housing (ref: House)75.0%5.8 (0.1)
 Flat17.7%6.0 (0.2)0.335 (−0.089, 0.760) [0.122]
 Farmhouse5.2%4.8 (0.3)−0.936 (−1.470, −0.403) [0.001]
 Retirement village0.9%5.4 (0.5)−0.202 (−1.300, 0.895) [0.718]
 Other1.2%5.3 (0.7)−0.044 (−1.305, 1.217) [0.945]
Geographic area (ref: Greater Sydney)18.8%5.8 (0.2)
 Rest of New South Wales13.2%5.4 (0.2)−0.072 (−0.603, 0.459) [0.790]
 Greater Melbourne18.8%6.2 (0.2)0.352 (−0.141, 0.845) [0.162]
 Rest of Victoria7.4%5.5 (0.3)0.006 (−0.610, 0.623) [0.984]
 Greater Brisbane11.1%5.6 (0.2)−0.106 (−0.699, 0.487) [0.726]
 Rest of Queensland8.9%5.8 (0.2)0.182 (−0.387, 0.752) [0.530]
 Greater Adelaide5.7%5.6 (0.3)−0.016 (−0.649, 0.617) [0.960]
 Rest of South Australia1.3%6.1 (0.5)0.508 (−0.588, 1.604) [0.363]
 Greater Perth10.3%6.0 (0.2)0.173 (−0.407, 0.752) [0.559]
 Rest of Western Australia1.5%5.1 (0.5)−0.319 (−1.362, 0.724) [0.549]
 Greater Hobart0.7%6.6 (0.6)1.027 (−0.191, 2.245) [0.098]
 Rest of Tasmania1.0%5.8 (0.5)0.372 (−0.632, 1.377) [0.467]
 Greater Darwin0.2%5.0 (1.0)−0.763 (−2.610, 1.083) [0.418]
 Rest of Northern Territory0.0%5.4 (1.1)−0.533 (−2.139, 1.072) [0.515]
 Australian Capital Territory1.1%5.3 (0.4)−0.140 (−1.060, 0.779) [0.765]
Constant 5.330 (4.178, 6.482) [<0.001]
SE: Standard Error; 95%CI: 95% Confidence Interval; Note: all means, standard errors, regression coefficients and 95% confidence intervals are weighted for national representativeness.
Table 5. Adjusted associations between qualities of nearby natural settings and visitation and felt benefits, weighted for national representativeness.
Table 5. Adjusted associations between qualities of nearby natural settings and visitation and felt benefits, weighted for national representativeness.
Single Quality Domain ModelMulti Quality Domain Model
Visitation and felt benefitOdds Ratio (95% Confidence Interval) [p-value]
≥120 min a week in nature
 Access1.408 (1.145, 1.732) [0.001]0.864 (0.652, 1.145) [0.310]
 Aesthetics1.921 (1.594, 2.314) [<0.001]1.062 (0.838, 1.345) [0.619]
 Amenities1.391 (1.121, 1.727) [0.003]0.721 (0.540, 0.962) [0.026]
 Facilities1.610 (1.299, 1.997) [<0.001]0.926 (0.670, 1.278) [0.639]
 Incivilities1.524 (1.302, 1.785) [<0.001]1.029 (0.825, 1.285) [0.797]
 Potential usage3.631 (2.803, 4.704) [<0.001]3.510 (2.434, 5.062) [<0.001]
 Safety1.759 (1.464, 2.114) [<0.001]1.402 (1.143, 1.719) [0.001]
 Social1.823 (1.491, 2.230) [<0.001]1.242 (0.943, 1.634) [0.122]
Visited preferred nearby natural setting at least once a week for the last 4 weeks
 Access2.067 (1.491, 2.864) [<0.001]1.235 (0.814, 1.876) [0.321]
 Aesthetics2.156 (1.600, 2.904) [<0.001]0.974 (0.679, 1.397) [0.887]
 Amenities1.730 (1.203, 2.489) [0.003]0.748 (0.493, 1.135) [0.172]
 Facilities1.913 (1.387, 2.638) [<0.001]0.930 (0.601, 1.437) [0.742]
 Incivilities1.499 (1.192, 1.886) [0.001]0.798 (0.599, 1.064) [0.125]
 Potential usage5.399 (3.408, 8.553) [<0.001]5.521 (3.020, 10.094) [<0.001]
 Safety2.255 (1.649, 3.082) [<0.001]1.782 (1.268, 2.506) [0.001]
 Social1.988 (1.425, 2.773) [<0.001]1.108 (0.726, 1.693) [0.634]
Visited nature more often since the onset of the COVID-19 pandemic than before
 Access1.683 (1.352, 2.095) [<0.001]1.148 (0.876, 1.505) [0.317]
 Aesthetics1.685 (1.398, 2.031) [<0.001]1.039 (0.811, 1.330) [0.764]
 Amenities1.599 (1.274, 2.008) [<0.001]0.964 (0.723, 1.285) [0.802]
 Facilities1.729 (1.378, 2.171) [<0.001]1.043 (0.759, 1.433) [0.795]
 Incivilities1.373 (1.159, 1.627) [<0.001]0.868 (0.699, 1.079) [0.203]
 Potential usage2.821 (2.205, 3.611) [<0.001]2.405 (1.695, 3.412) [<0.001]
 Safety1.359 (1.137, 1.624) [0.001]1.071 (0.886, 1.294) [0.480]
 Social1.792 (1.476, 2.176) [<0.001]1.248 (0.964, 1.615) [0.092]
Nature has helped me stay connected with my neighbours during the COVID-19 pandemic
 Access1.819 (1.492, 2.216) [<0.001]1.191 (0.921, 1.539) [0.182]
 Aesthetics1.913 (1.599, 2.290) [<0.001]1.188 (0.944, 1.495) [0.142]
 Amenities1.697 (1.370, 2.102) [<0.001]0.907 (0.694, 1.186) [0.476]
 Facilities1.840 (1.486, 2.279) [<0.001]0.877 (0.656, 1.173) [0.377]
 Incivilities1.688 (1.434, 1.986) [<0.001]1.084 (0.882, 1.330) [0.444]
 Potential usage2.863 (2.279, 3.598) [<0.001]1.699 (1.227, 2.351) [0.001]
 Safety1.515 (1.280, 1.793) [<0.001]1.147 (0.956, 1.377) [0.139]
 Social2.304 (1.897, 2.798) [<0.001]1.670 (1.285, 2.171) [<0.001]
Nature has helped me to find solace during the COVID-19 pandemic
 Access2.200 (1.804, 2.682) [<0.001]1.134 (0.864, 1.489) [0.365]
 Aesthetics2.698 (2.258, 3.224) [<0.001]1.124 (0.892, 1.416) [0.322]
 Amenities2.193 (1.784, 2.696) [<0.001]0.885 (0.667, 1.175) [0.398]
 Facilities2.215 (1.804, 2.720) [<0.001]0.805 (0.588, 1.101) [0.174]
 Incivilities2.039 (1.757, 2.366) [<0.001]1.112 (0.904, 1.370) [0.315]
 Potential usage8.275 (6.330, 10.816) [<0.001]6.358 (4.494, 8.996) [<0.001]
 Safety1.792 (1.519, 2.114) [<0.001]1.205 (0.998, 1.456) [0.053]
 Social2.583 (2.137, 3.122) [<0.001]1.311 (1.008, 1.705) [0.044]
I visit nature to walk and exercise more often during the COVID-19 pandemic than before
 Access2.001 (1.605, 2.494) [<0.001]1.418 (1.081, 1.860) [0.012]
 Aesthetics1.805 (1.502, 2.170) [<0.001]1.120 (0.875, 1.432) [0.369]
 Amenities1.706 (1.361, 2.137) [<0.001]0.952 (0.715, 1.267) [0.736]
 Facilities1.819 (1.452, 2.278) [<0.001]0.948 (0.689, 1.304) [0.743]
 Incivilities1.441 (1.218, 1.706) [<0.001]0.860 (0.693, 1.068) [0.172]
 Potential usage2.966 (2.336, 3.765) [<0.001]2.163 (1.534, 3.051) [<0.001]
 Safety1.427 (1.193, 1.707) [<0.001]1.100 (0.910, 1.330) [0.325]
 Social1.980 (1.629, 2.407) [<0.001]1.363 (1.047, 1.774) [0.021]
SE: Standard Error; 95%CI: 95% Confidence Interval; All models weighted for national representativeness and adjusted for gender, age group, country of birth, language spoken at home, relationship status, highest educational qualification, annual household income, economic status, perceived financial difficulty, housing status, and geographic region.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Feng, X.; Astell-Burt, T. Perceived Qualities, Visitation and Felt Benefits of Preferred Nature Spaces during the COVID-19 Pandemic in Australia: A Nationally-Representative Cross-Sectional Study of 2940 Adults. Land 2022, 11, 904. https://doi.org/10.3390/land11060904

AMA Style

Feng X, Astell-Burt T. Perceived Qualities, Visitation and Felt Benefits of Preferred Nature Spaces during the COVID-19 Pandemic in Australia: A Nationally-Representative Cross-Sectional Study of 2940 Adults. Land. 2022; 11(6):904. https://doi.org/10.3390/land11060904

Chicago/Turabian Style

Feng, Xiaoqi, and Thomas Astell-Burt. 2022. "Perceived Qualities, Visitation and Felt Benefits of Preferred Nature Spaces during the COVID-19 Pandemic in Australia: A Nationally-Representative Cross-Sectional Study of 2940 Adults" Land 11, no. 6: 904. https://doi.org/10.3390/land11060904

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop