Nature Will Tell Us Again and Again

Abstract

Spending time in natural environments tin can benefit health and well-beingness, but exposure-response relationships are under-researched. We examined associations betwixt recreational nature contact in the last seven days and self-reported health and well-beingness. Participants (n = xix,806) were drawn from the Monitor of Engagement with the Natural Environs Survey (2014/fifteen–2015/16); weighted to be nationally representative. Weekly contact was categorised using 60 min blocks. Analyses controlled for residential greenspace and other neighbourhood and individual factors. Compared to no nature contact last calendar week, the likelihood of reporting good health or high well-being became significantly greater with contact ≥120 mins (e.grand. 120–179 mins: ORs [95%CIs]: Wellness = ane.59 [1.31–i.92]; Well-beingness = one.23 [1.08–i.40]). Positive associations peaked betwixt 200–300 mins per week with no further gain. The pattern was consistent beyond cardinal groups including older adults and those with long-term health issues. Information technology did not matter how 120 mins of contact a week was achieved (eastward.thousand. one long vs. several shorter visits/week). Prospective longitudinal and intervention studies are a critical next pace in developing possible weekly nature exposure guidelines comparable to those for physical activity.

Introduction

A growing trunk of epidemiological evidence indicates that greater exposure to, or 'contact with', natural environments (such every bit parks, woodlands and beaches) is associated with better health and well-being, at least amidst populations in high income, largely urbanised, societies¹. While the quantity and quality of show varies across outcomes, living in greener urban areas is associated with lower probabilities of cardiovascular disease², obesity³, diabetes⁴, asthma hospitalisation⁵, mental distress^half-dozen, and ultimately mortality^seven, among adults; and lower risks of obesity⁸ and myopia⁹ in children. Greater quantities of neighbourhood nature are besides associated with better self-reported health^x,11,12, and subjective well-being¹³ in adults, and improved birth outcomes^fourteen, and cognitive evolution¹⁵, in children.

Withal, the amount of greenspace in one's neighbourhood (e.yard. per centum of land cover in a 1 km radius from the home), or the distance of 1's home to the nearest publically attainable green space or park¹⁶ is but one way of assessing an private's level of nature exposure. An alternative is to measure the amount of time individuals actually spend outside in natural environments^17,18, sometimes referred to equally 'direct' exposure^xix. Both approaches are potentially informative. Residential proximity to nature may exist related to health promoting factors such equally reduced air and noise pollution (although the relationships are circuitous^xx); and may also provide 'indirect' exposure via views from the property²¹. Residential proximity is also generally positively related to 'direct' exposure; i.east. people in greener neighbourhoods tend to study visiting greenspace more often²². All the same many nature visits accept place outside of the local neighbourhood²³. Moreover, such visits may compensate for a lack of nature in the neighbourhood²⁴. In other words, straight exposure, or more specifically in the current context, recreational time spent in natural environments per week, cannot accurately be inferred from neighbourhood greenspace nearly the home.

Using data from a representative sample of the adult population of England, we aimed to better understand the relationships between time spent in nature per week and self-reported health and subjective well-existence. Our research builds direct on a small number of studies that have started to await at similar bug^17,18,25,26, and answers the call made in several recent reviews for more piece of work in this area^27,28. Quantification of these 'exposure-response' relationships can contribute to the policy procedure, for case by providing testify upon which to base recommendations regarding the amount of time required to be spent in nature per week to promote positive health and well-existence outcomes. A similar procedure was used to back up development of guidelines on the amount of recommended weekly concrete activity needed for health promotion and disease prevention²⁹.

The research advances previous work in three primal ways. First, to appointment, researchers have examined directly nature exposure-response relationships using either a specific visit duration¹⁷, or nature visit frequency over a prolonged period²⁶, or both independently¹⁸. By multiplying the elapsing of a representative visit within the final calendar week by the number of visits taken within the last week we were able to develop the first weekly exposure metric (i.due east. minutes per week) for nature exposure, like to those used in other health promotion contexts (e.g. physical activity²⁹). Second, by comparison the coefficients of other, well-established, predictors of health and well-beingness (e.1000. area deprivation) with those for average time spent in nature per week, we were able to assess the relative strength of whatever exposure-response human relationship. Third, previous studies were constrained in their ability to look at the generalisability of relationships across different socio-demographic groups due to relatively small, geographically constrained samples. In this report, the current, nationally representative sample enabled united states of america to stratify, a priori, on socio-demographic characteristics, such as age³⁰, gender³¹, ethnicity³² and area impecuniousness³³, which appeared to moderate the nature-health association in previous studies²².

Results

Models using elapsing categories

Descriptive information on the relationships between fourth dimension spent in nature in the last seven days (in 60 min categories) and self-reported wellness (Good vs. poor) and subjective well-being (Loftier vs. depression) are presented in Table ane. Percentages per category are presented for both the estimation sample (n = xix,806), and for the sample weighted to be representative of the developed population of England. Similar details for all covariates can exist institute in Appendix B, and relationships between our key predictor, fourth dimension in nature, and all other covariates in Appendix C.

Table i The frequency and percent of respondents in each category of each predictor who reported good/very proficient health and loftier well-beingness.

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The odds ratios (ORs) and 95% conviction intervals (CIs) for the survey weighted binomial logistic regressions predicting health and well-being are presented in Table ii (full models in Appendix D). In the unadjusted models the odds ratios for reporting 'good' health and 'high' well-being were significantly higher for all nature contact ≥60 mins per calendar week compared to 0 mins. Contact of 1–59 mins per week was not associated with ameliorate outcomes than 0 mins, and at that place was as well no linear increase above lx mins; longer durations were not associated with meliorate outcomes. In the adapted models, significance merely emerged at the ≥120 mins per week category; and again additional duration was not associated with improved outcomes. The human relationship appeared somewhat stronger for health than well-beingness (Fig. ane).

Table 2 The odds ratios (OR) and 95% confidence intervals (CIs) of reporting good health and loftier well-being as a function of nature visit elapsing in the last seven days.

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Effigy i

The odds ratios (OR) and 95% confidence intervals of reporting good health and loftier well-being as a part of nature visit duration in the terminal 7 days (0 mins = reference category). Note: Adjusted for urbanicity, neighbourhood greenspace, expanse deprivation, background PM10, sex, age, SES, restricted functioning, physical activity, employment status, human relationship status, ethnicity, children in household, canis familiaris ownership and yr.

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Sensitivity analysis

We conducted three types of sensitivity analysis. First we explored exposure-response relationships using time spent in nature as a continuous variable, and outcomes modelled equally binary variables using splines (Fig. ii). The figures suggested relatively steady increases in the positive relationships for both health and well-being up to effectually 120 mins, diminishing marginal returns from so until effectually 200 mins per calendar week for wellness and 300 mins for well-existence, and and so a flattening out or even decrease thereon (though note the very large CIs > 400 mins). Although Fig. two should be treated with caution, due to hourly clustering (see Methods, and Appendix A, Figure C), results broadly support the categorical analyses, with some suggestion that nature exposure beyond 120 mins a week may have some additional benefits that did non emerge when health and wellbeing were treated every bit binary variables.

Figure 2

The probability of reporting (a) good health and (b) high well-being (with 95% conviction intervals) equally a function of time spent in nature in the last 7 days using a generalised additive model (GAM) with a penalized cubic spline for nature contact. Note. The GAM is adapted for urbanicity, neighbourhood greenspace, expanse deprivation, groundwork PM10, sexual activity, age, SES, restricted performance, physical activity, employment status, relationship status, ethnicity, children in household, dog ownership and twelvemonth.

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Second, we explored exposure-response relationships using time spent in nature as a categorical variable and health and wellbeing modelled as ordinal variables. Results were once more very like (Appendix E). The merely slight change was significance at the threescore–119 min category for both outcomes, but this finding is non easily comparable to the binary logistic results for reasons explained in more detail in Appendix E.

Our final sensitivity assay modelled both fourth dimension and well-being as continuous variables (Appendix E, Figure D). Over again the results were very like to the original model (Fig. 2b). Due to the inherently ordinal structure of the general health variable, we were unable to conduct a comparable sensitivity model for health.

Contextualisation of results

To contextualise the magnitude of the relationship betwixt weekly nature contact and health and well-being, Fig. 3 presents the relevant ORs (CIs) aslope those for selected predictors including: neighbourhood greenspace and deprivation; physical exercise; individual SES; and relationship status (encounter Appendix D for details on all covariates). The effigy highlights that 120–179 mins vs. 0 mins of nature contact per week was associated with: (a) a similar likelihood of reporting adept health as, living in an expanse of low vs. high deprivation; meeting vs. non meeting physical activity guidelines, and (c) being in a loftier vs. low SES occupation. Although the association between nature contact at this level and wellbeing was similar to that betwixt high vs. low: greenspace, impecuniousness and physical activity; it was less important than SES and human relationship status.

Figure 3

The odds ratios (OR) and 95% conviction intervals of reporting practiced wellness and high well-being as a role of nature visits and selected covariates (controlling for all other covariates).

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Generalisability of results

Table iii shows results of analyses stratified on fundamental expanse and individual level factors (see Appendix F for full details). For these analyses, nature contact was reconfigured into iii duration levels reflecting: (a) 'no exposure' (0 minutes, ref); (b) 'depression exposure', non associated with significantly greater likelihood of skillful health and high wellbeing (i–119 mins); and (c) 'high exposure', i.e. all durations associated with significantly higher likelihood of proficient wellness and high well-being combined (≥120 mins). Estimates from the models of health showed that the positive relationship institute for 'high' merely not 'low' exposure, compared to 'no exposure', in the overall model was consistent across those living in urban and rural, and high and depression deprivation, areas. It was also consistent for: both males/females; those to a higher place/below 65years former; those of high/depression occupational social grade; those with/without a long-term disease/disability; and for those who did vs. did non see physical activity recommendations. Stratification on neighbourhood greenspace suggested those in areas of loftier (merely not low) greenspace also had greater odds of good wellness if they spent any time in nature per calendar week compared to 0 mins, possibly reflecting the importance of indirect exposure amongst this cohort. Stratification on ethnicity showed the threshold was maintained amongst white British, only not 'other' respondents. Stratified models of well-beingness showed that 'high' but not 'low' exposure was associated with significantly greater odds of high wellbeing in all cases.

Table 3 The odds ratios (OR) and 95% conviction intervals (CIs) of reporting expert wellness and high well-beingness as a function of the iii main categories of nature visit duration in the last vii days, stratified on central area and individual covariates.

Full size table

Additional analyses found no differences in health and well-beingness as a function of how 'loftier' exposure was achieved (a) one 120+ min visit; (b) 2 60+ min visits; or (c) or 3/more ≤ forty min visits (encounter Appendix G for details).

Discussion

Growing prove of a positive association between contact with natural environments and wellness and well-being has led to calls for improved agreement of whatever exposure-response relationships^27,28. The aim of the current study was to assess these relationships with a measure out based on direct exposure to natural environments, rather than residential proximity, using data from a large nationally representative sample in England. Exposure was defined in terms of the self-reported minutes spent in natural environments for recreation in the terminal seven days; and outcomes were cocky-reported health and subjective well-being.

After a range of covariates had been taken into account, individuals who spent between ane and 119 mins in nature in the last week were no more likely to report good health or high well-existence than those who reported 0 mins. Notwithstanding, individuals who reported spending ≥120 mins in nature concluding week had consistently college levels of both health and well-being than those who reported no exposure. Sensitivity analyses using splines to permit duration to be modelled as a continuous variable suggested that beyond 120 mins there were decreasing marginal returns until effectually 200–300 mins when the relationship flattened or fifty-fifty dropped. We tentatively suggest, therefore, that 120 mins contact with nature per week may reflect a kind of "threshold", below which there is insufficient contact to produce significant benefits to health and well-being, merely in a higher place which such benefits become manifest.

In terms of magnitude, the association between health, well-existence and ≥120 mins spent in nature a week, was like to associations between wellness, well-being and: (a) living in an expanse of low vs. high deprivation; (b) being employed in a high vs. depression social grade occupation; and (c) achieving vs. non achieving recommended levels of physical activity in the concluding calendar week. Given the widely stated importance of all these factors for health and well-being, we translate the size of the nature human relationship to be meaningful in terms of potential public wellness implications.

That the ≥120 mins "threshold" was present even for those who lived in low greenspace areas reflects the importance of measuring recreational nature contact directly when possible, rather than simply using residential proximity as a proxy for all types of nature exposure. People travel across their local neighbourhoods to access recreational nature experiences, and indeed in our ain information those who lived in the to the lowest degree green areas had higher odds of spending ≥120 mins in nature than those living in greener neighbourhoods (Appendix C). Impoverished local opportunities need not be a barrier to nature exposure^23,24. That the "threshold" was as well present for those with long-term illnesses/disability, suggests that the positive overall clan in the data was non just due to healthier people visiting nature more often.

Ane explanation for our findings might exist that time spent in nature is a proxy for physical activeness, and it is this which is driving the relationship, not nature contact per se. In England, for example, over three 1000000 adults accomplish recommended activity levels fully, or in role, in natural settings³⁴. Although: (a) we tried to command for this by including physical activeness over the last vii days in our models; and (b) the threshold applied to individuals who did not meet activity guidelines; we were unable to fully untangle these problems. Experimental enquiry, notwithstanding, indicates that some benefits cannot be due solely to physical activity. Research into shinrin-yoku (Japanese "forest bathing")³⁵, for instance, suggested that various psycho-physiological benefits can be gained from merely sitting passively in natural vs. urban settings. Moreover, physical activity conducted in nature may be more than psychologically beneficial than in other locations³⁶, suggesting a circuitous interaction between the two which requires further research to fully understand^xx.

The electric current results also suggested that information technology did non matter how the "threshold" was accomplished. This may exist considering individuals selected exposures to fit their personal preferences and circumstances. For case, some may adopt long walks on the weekend in locations farther from dwelling house; while others may prefer regular shorter visits to parks in the local surface area. To recommend the erstwhile blazon of person stops their long weekly visit in favour of several shorter trips or vice versa may be misguided.

Whilst this study deepens our understanding of the potential value of spending time outdoors in nature to wellness and well-being, it is too early on to make specific guidance due to several limitations. First, the data are observational and cantankerous-sectional; and thus, however the same pattern property for those with a long-term affliction/disability, we are unable to dominion out the possibility that the association is, at least in office, due to healthier, happier people spending more time in nature. Prospective longitudinal studies of the kind used to help develop physical activity guidelines²⁹, and nature-based intervention studies are needed to better sympathize causality. Cimprich and Ronis³⁷, for example, establish that women recently diagnosed with breast cancer scored higher on several attention tasks, compared to standard intendance controls, following a five-week period of spending 120 mins per week in 'natural restorative environments'. The authors argued that the 120 mins per week of nature exposure helped the women restore cognitive resources depleted past the stress of their diagnoses and early on handling. Although our sample was more than heterogeneous, weekly nature exposure may work in a similar mode by reducing generally loftier levels of stress³⁸. Similar studies are needed to come across how generalizable any potential "threshold" is across a range of situations, and to see how long an individual needs to maintain a certain corporeality of weekly exposure to achieve health and well-beingness gains. Although effects on attentional processes were observed after just 5 weeks in Cimprich and Ronis³⁷, health effects may demand longer; and it is also important to see whether different types of nature contact might confer different benefits.

Nosotros also notation that, although significant, time in nature explained relatively little variance in either health or wellbeing in these models based on cross-sectional data (approx. 1% in unadjusted models in both cases). It will therefore be of import to explore effect sizes in prospective/experimental studies to better understand the price/do good implications of any potentials interventions.

Another limitation concerned our gauge of weekly exposure. Every bit duration was asked well-nigh only a single randomly selected visit in the final week, nosotros assumed that at the population level this was representative of all visits. Although rigorous collection protocols meant that the effects of a typical visit selection are likely to abolish out over a sample of nearly xx,000, nosotros recognise that accuracy at the individual level would exist improved if duration were asked about all visits in the last week. We also acknowledge that our data rely on self-reports and thus results needed to be treated with circumspection. For instance, cocky-reported elapsing is likely to be less accurate than measures obtained from geo-tracking individuals during specific visits³⁹, or over several days^twoscore, and individuals may have been unsure about, or reluctant to hash out, certain bug which were included equally covariates (e.1000. long standing illness/disability). Future studies would ideally collate equally much data via non cocky-report measures as possible. We annotation, moreover, that unlike exposure to often invisible ecology factors such equally air pollution, we tin potentially 're-live' our experiences of the natural world in retentivity, for instance during periods of 'mind wandering', and derive benefits from these recollections independent of those experienced in situ ⁴¹. Thus, an exposure in this context may be considered equally the fourth dimension in situ plus all subsequent time spent thinking well-nigh the experience⁴². In short, we believe further work is needed to remember more critically and creatively about what the term 'exposure' ways in the current context.

We too remain cautious about whatever potential ≥120 mins "threshold". In office its emergence may be a consequence of the clustering of duration responses effectually the hour marking and subsequent stratification, rather than annihilation materially different occurring at this level of exposure. The spline models, for instance, suggested a more nuanced pattern. However, this smoothing of the data was notwithstanding reliant on a highly non-normal distribution, suggesting that we need to exist cautious most these analyses as well. Further piece of work is also needed to explore the 'peak' of returns at effectually 200–300 mins, to better understand why spending more fourth dimension in nature is associated with trivial marginal gain. Thus, nosotros run across the tentative "threshold" and "acme" discussed here more as a starting points for discussion and further investigation, than clearly established findings.

Finally, our results say fiddling virtually exposure 'quality'. Enquiry considering the quality of the natural environs in terms of plant and/or animal species richness suggests that experiences may be better in more biodiverse settings^25,43. Contact with nature is more than only a complex multi-sensory feel, to varying degrees personal histories and meanings, longstanding cultural practices, and a sense of identify play some part in the benefits realised^44,45,46, factors which may account for why we did not observe the aforementioned pattern for health individuals not identifying as White British. In the current inquiry, for instance, exposure estimates relied upon visits undertaken voluntarily, presumably because they had features important to those individuals⁴⁷ and these effects may not be found if individuals were to regularly spend 120 mins a week in a natural environment of less personal relevance (eastward.g. those who cocky-identified as 'White European'). Our estimates also explicitly excluded time spent in one's ain garden which tin be an important course of meaningful nature contact for many people⁴⁸. All of these issues will need greater consideration in futurity inquiry.

To conclude, although this inquiry suggests that spending ≥120 mins a week in nature may be an important "threshold" for health and well-being beyond a broad range of the developed population in England, we believe that more prospective accomplice, longitudinal, and experimental studies are required earlier any clear conclusions can be drawn. In addition to improving the duration-exposure estimates used here, more research is also needed to understand the touch on of different activities undertaken, as well as the effect of environmental quality and personal pregnant. Nevertheless, we see our findings as an important starting point for discussions around providing elementary, evidence-based recommendations most the corporeality of time spent in natural settings that could result in meaningful promotion of wellness and well-beingness.

Methods

Participants & process

Participants were drawn from Waves six and seven (2014–2015/2015–2016) of the Monitor of Engagement with the Natural Surroundings (MENE) survey (the only Waves where our central outcomes were consistently measured). The survey, which is office of the United kingdom of great britain and northern ireland authorities's National Statistics, is repeat cross-exclusive (different people take part in each moving ridge), and is conducted across the whole of England and throughout the twelvemonth (approx. 4,000 people per calendar week) to reduce potential geographical and seasonal biases⁴⁹. As part of the Uk's official statistics, sampling protocols are extensive, to ensure as representative a sample of the adult English language population as possible. Full details can exist found in the almanac MENE Technical Reports⁴⁹ with key features including: (a) "a computerised sampling system which integrates the Mail Part Address file with the 2001 Demography small expanse information at output area level. This enables replicated waves of multi-stage stratified samples"; (b) "the areas within each Standard Region are stratified into population density bands and within ring, in descending gild by percentage of the population in socio-economic Form I and Two"; (c) "[in lodge to] maximise the statistical accuracy of the sampling, sequential waves of fieldwork are allocated systematically across the sampling frame to ensure maximum geographical dispersion"; (d) "to ensure a balanced sample of adults within the constructive contacted addresses, a quota is set by sex (male, female housewife, female non-housewife); inside the female housewife quota, presence of children and working status and within the male quota, working status"; and (due east) "the survey data is weighted to ensure that the sample is representative of the UK population in terms of the standard demographic characteristics" (ref.⁴⁹, p.v). Data is collected using in-domicile face-to-face interviews with responses recorded using Computer Assisted Personal Interviewing (CAPI) software.

Although the full sample for these years was n = 91,190, the wellness and well-being questions were only asked in every fourth sampling week (i.e. monthly, rather than weekly) resulting in a reduced sample of n = 20,264. In social club to account for any residue biases in sampling at this monthly level, special 'calendar month' survey weights are included in the data set. These were applied in the current analysis to ensure that results remained generalisable to the unabridged adult population of England. All data were anonymised by Natural England and are publically accessible at: http://publications.naturalengland.org.uk/publication/2248731?category=47018. Upstanding blessing was not required for this secondary assay of publically available National Statistics.

Outcomes: Self-reported health & subjective well-existence

Self-reported health (henceforth: health) was assessed using the single-item: 'How is your health in general?' (sometimes referred to as 'SF1'). Response options were: 'Very bad', 'Bad', 'Fair', 'Good' and 'Very good'. Responses are robustly associated with utilise of medical services⁵⁰ and mortality⁵¹; and crucially, for current purposes, neighbourhood greenspace¹³. Following earlier work we dichotomised responses into 'Good' ('Practiced/very good', weighted = 76.5%) and 'Not good' ('Fair/bad/very bad', 23.five%)⁵². Subjective well-being (henceforth: well-being) was assessed using the 'Life Satisfaction' measure, one of the UK's national well-being measures⁵³: 'Overall how satisfied are you with life nowadays?' with responses ranging from 0 'Not at all' to 10 'Completely'. Again, post-obit earlier studies we dichotomised responses into 'High' (8–10, 60.2%) and Low (0–vii, 39.viii%) well-existence⁵⁴. Histograms of the (non-normal) distributions for both outcome variables are presented in Appendix A. Of note although the dichotomisation points were based on prior research, they are consistent with the current information; the 50^thursday percentile for health was in the 'good' response and for wellbeing in '8'. Sensitivity analyses conducted on ordinal (both health and wellbeing) and linear (wellbeing only) variations of these variables are presented in Appendix Eastward.

Exposure: Recreational nature contact in last 7 days

Recreational nature contact, or time spent in natural environments in the last calendar week, was derived by multiplying the number of reported recreational visits per week past the length of a randomly selected visit in the last week. Participants were introduced to the survey every bit follows: "I am going to ask you about occasions in the last week when you spent your time out of doors. By out of doors we mean open spaces in and around towns and cities, including parks, canals and nature areas; the coast and beaches; and the countryside including farmland, woodland, hills and rivers. This could be annihilation from a few minutes to all day. Information technology may include time spent close to your domicile or workplace, further afield or while on holiday in England. However this does not include: routine shopping trips or; time spent in your ain garden." And then they were asked "how many times, if at all, did yous brand this type of visit yesterday/on <Day> " for each of the previous seven days. Ninety-viii percent of respondents reported ≤7 visits last week. The remaining 2% were capped at 7 visits to avert dramatically skewing weekly duration estimates.

After bones details of each visit (up to 3 per day) were recorded, a unmarried visit was selected at random by the CAPI software, for the interviewer to inquire further questions virtually, including: "How long did this visit last altogether?" (Hours & Minutes). Due to random selection, even if the selected visit was not necessarily representative for any given individual, the randomisation procedure should reduce potential bias at the population level at which our analyses were conducted. Weekly duration estimates were thus derived past multiplying the duration for this randomly selected visit past the number of stated visits in the last vii days (capped at 7). Following the approach of earlier exposure-response studies in the field (e.k. Shanahan et al., 2016), duration was categorised into 7 categories: 0 mins (n = 11,668); 1–59 mins (north = 355); threescore–119 mins (n = ane,113); 120–179 mins (n = ane,290); 180–239 mins (n = 1,014); 240–299 mins (n = 882); ≥300 mins (n = 3,484). An culling banding at xxx minutes was problematic because of very low Ns for some bands (e.one thousand. 1–29 mins, n = 85), reflecting the fact that weekly elapsing estimates clustered around the hr marks, e.thousand. 78% of the unweighted observations within the 120–179 mins band were precisely 120 mins (See Appendix A, Figure C for duration histogram). The highest ring was capped at ≥300 mins due to the large positive skew of the information.

Command variables

Health and well-being are associated with socio-demographic and environmental characteristics at both neighbourhood (e.g. area impecuniousness) and individual (e.g. relationship status) levels⁵⁵. As many of these variables may also be related to nature exposure they were controlled for in the adjusted analyses.

Area level control variables

Expanse level covariate data was assigned on the spatial level of the Census 2001 Lower-layer Super Output Areas (LSOAs) in which individuals lived. There were 32,482 LSOAs in England, each containing approximately 1,500 people within a mean physical expanse of 4km².

Neighbourhood greenspace

In order to sympathise how much greenspace is in an individual'south neighbourhood, we derived an expanse density metric using the Generalised State Utilise Database (GLUD)⁵⁶. The GLUD provides, for each LSOA in England, the area covered by greenspace and domestic gardens. These were summed and divided by the total LSOA surface area to provide the greenspace density metric. This metric was allocated to each private in the sample, based on LSOA of residence. Following previous literature, individuals were assigned to one of five quintiles of greenspace based on this definition (ranging from least light-green to almost dark-green)³³. Rather than derive quintiles of greenspace from the current sample (i.e. divide the electric current sample into five equal parts based on the percentage of greenspace in their LSOA), we assigned individuals instead to one of five pre-determined greenspace quintiles based on the distribution of greenspace beyond all 32,482 LSOAs in England. Although this meant that nosotros did not get exactly equal 20% shares of our current sample across greenspace quintiles (although due to the sampling protocol we were nonetheless very shut to this, run across Appendix B) this arroyo allowed inferences to be made across the unabridged country, rather than simply to the current sample. In exploratory sensitivity analyses we defined greenspace every bit the GLUD category 'greenspace' merely, with the GLUD category 'gardens' excluded. This produced very similar results, so we focused on the more inclusive definition including both aspects. In further exploratory sensitivity analyses, we assigned individuals to five greenspace categories defined by equal ranges of greenspace coverage (e.g. 0–xx%, 21–40%, 41–60% etc.) rather than quintiles based on percentages of the population. This as well produced very similar results, so again nosotros decided to become with the nearly common approach. In subsequent analyses the least green quintile acted as the reference category.

Area deprivation

Each LSOA in England is assessed in terms of several parameters of deprivation, including unemployment and crime, levels of educational, income, health metrics, barriers to housing and services, and the living surroundings. A total Alphabetize of Multiple Deprivation (IMD) score is derived from these subdomains⁵⁷. Following previous studies⁵², we assigned individuals into deprivation quintiles based on the LSOA in which they lived. As with greenspace, the cutting points for expanse deprivation quintiles were also based on all LSOAs in England, rather than those in the electric current sample, to allow inference to the population every bit a whole (nigh deprived quintile =ref).

Air pollution

An indicative measure out of air pollution was operationalised as LSOA background PM₁₀ assigned to tertiles of all LSOAs in England (lowest particulate concentration =ref). PM10 concentrations, based on Pollution Climate Mapping (PCM) model simulations⁵⁸, were averaged over the period 2002–2012, and aggregated from 1 km square resolution to LSOAs.

Individual level controls

Individual level controls comparable to earlier studies in this expanse^{vi,vii,12,13,15} included: sex (male person =ref); age (categorised as 16–64 =ref; 65+); occupational social class (AB (highest, due east.g. managerial), C1, C2 and DE (lowest, e.thousand. unskilled labour, =ref) equally a proxy for individual socio-economic condition (SES); employment condition (full-fourth dimension, part-time, in educational activity, retired, not working/unemployed =ref); relationship condition (married/cohabiting; single/separated/divorced/widowed =ref); ethnicity (White British; other =ref); number of children in the household (≥1 vs. 0 =ref); and canis familiaris buying (Yes; No =ref).

2 further command variables were particularly important. First, the survey asked: 'Do you lot have any long standing illness, health problem or disability that limits your daily activities or the kind of piece of work you can do?' ('Restricted functioning': Yes; No =ref). Including this variable, at least in office, controls for contrary causality. If similar associations betwixt nature exposure and wellness and well-being are found for both those with and without restricted functioning, this would back up the notion that the associations are not merely due to healthier, more mobile people visiting nature more often.

We too controlled for the number of days per week people reported engaging in physical action >30 mins; in the current assay dichotomised equally either coming together or not meeting guidelines of 150 mins per week (i.east. five days in the week with concrete activity >30 mins). Some people achieve this guideline though concrete action in natural settings³⁵, thus, any association betwixt time spent in nature and health may only exist due to the physical activity engaged in these settings. Nosotros believe this is non the case in the current context because the (rank guild) correlation between weekly nature contact and the number of days a week an private engaged in >30 mins of concrete activity was just r_s = 0.27. All the same, past controlling for weekly activeness levels, modelled relationships between fourth dimension in nature and health take less bias from this source, and, therefore, improved estimates of association with nature exposure per se.

Temporal controls

Due to the multi-year pooled nature of the information, year/wave was also controlled for. Preliminary analysis found no effect of the season in which the data were collected so this was excluded from last analyses.

Analysis strategy

Survey weighted binomial logistic regressions were used to predict the relative odds that an individual would have 'Adept' wellness or 'High' well-being every bit a part of weekly nature exposure in terms of duration categories per week. Model fit was provided by pseudo R²; here the more conservative Cox and Snell judge. The consequence binary variables were kickoff regressed against the exposure elapsing categories to exam directly relationships; adjusted models were and then specified to include the private and area level control variables. Due to missing area level data for a small minority of participants (due north = 456), our interpretation samples for these adapted models were n = nineteen,808. Preliminary analysis found that the weighted descriptive proportions amid this reduced estimation sample differed only negligibly from those among all bachelor observations in the wider MENE sample, suggesting our consummate instance analysis approach did not misconstrue the population representativeness of the interpretation sample. The total n = 20,264 sample was maintained for the unadjusted model to provide the almost accurate, weighted representation of the information, equally reducing unadjusted models to n = 19,808 produced practically identical results. Although our primary analyses used elapsing categories of weekly nature contact, an exploratory analysis used generalized condiment models incorporating a penalized cubic regression spline of duration as a continuous variable (adjusting for the same set of covariates). This enabled us to produce a 'smoother' plot of the data. Analyses and plotting was done using R version iii.4.1, using packages mgcv and visreg ⁵⁹.

To explore the generalisability of any design across dissimilar socio-demographic groups, we also a priori stratified the analyses on several surface area and individual covariates (as divers above) which have been institute to exist important in previous studies: (a) Urbanicity; (b) Neighbourhood greenspace; (c) Area deprivation; (d) Sex; (e) Age; (f) Restricted functioning; (g) Private socio-economic status (SES); (f) Ethnicity; and (g) Physical activity. In the case of the three multi-category predictors (area greenspace/impecuniousness, individual SES), binary classifications were derived for the stratified analyses to maintain robust sample sizes in each category. In the case of LSOA greenspace and impecuniousness binary splits were made based on the median cut-betoken for all LSOAs in England; SES was dichotomised by collapsing the social grade categories in the standard mode, A/B/C1 vs. C2/D/E.

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Acknowledgements

This work was supported past the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Ecology Change and Wellness at the London School of Hygiene and Tropical Medicine in partnership with Public Health England (PHE), and in collaboration with the University of Exeter, University Higher London, and the Met Office. The funders had no role in the study blueprint, assay, interpretation of data, or decision to submit the article for publication. The views expressed are those of the writer(s) and not necessarily those of the NHS, the NIHR, the Department of Health, or Public Wellness England. Nosotros would similar thank an earlier reviewer and the editorial board squad for suggestions on how to improve an earlier version of this manuscript.

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Affiliations

1. European Centre for Surroundings and Human Health, University of Exeter Medical School, Exeter, UK

   Mathew P. White, Ian Alcock, James Grellier, Benedict W. Wheeler, Sara Fifty. Warber, Angie Bone, Michael H. Depledge & Lora Eastward. Fleming

2. Constitute for Housing and urban Research, Uppsala Academy, Box 514, SE-75120, Uppsala, Sweden

   Terry Hartig

3. Section of Family Medicine, University of Michigan Medical School, Ann Arbor, MI, Us

   Sara L. Warber

Contributions

Chiliad.W. conceived of the study in give-and-take with T.H., M.D. and Fifty.Due east.F.; M.West., I.A. and J.Yard. conducted the analyses; B.Westward., S.Westward. and A.B. made additional analysis suggestions and provided text/references on specific sections. All authors contributed to the text of the manuscript and reviewed the final submission.

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Correspondence to Mathew P. White.

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White, M.P., Alcock, I., Grellier, J. et al. Spending at least 120 minutes a week in nature is associated with good health and wellbeing. Sci Rep 9, 7730 (2019). https://doi.org/ten.1038/s41598-019-44097-three

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• Received: 08 May 2018

• Accepted: 08 May 2019

• Published: 13 June 2019

• DOI : https://doi.org/x.1038/s41598-019-44097-3

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