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Review

Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review

1
Department of Educational Sciences, Psychology, Communication, University of Studies of Bari, 70122 Bari, Italy
2
Department of Agricultural and Environmental Sciences, University of Studies of Bari, 70126 Bari, Italy
3
Faculty of Law, Giustino Fortunato University, 82100 Benevento, Italy
4
Barcelona Institute for Global Health, 08003 Barcelona, Spain
5
Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
6
CIBER Epidemiologíay Salud Publica (CIBERESP), 28029 Madrid, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(18), 11700; https://doi.org/10.3390/ijerph191811700
Submission received: 8 August 2022 / Revised: 9 September 2022 / Accepted: 13 September 2022 / Published: 16 September 2022
(This article belongs to the Special Issue Methods and Techniques in Applied Psychology: Health and Well-Being)

Abstract

:
Recent advances in environmental psychology highlighted the beneficial role of greenspace exposure on cognition. We conducted a systematic review of the available studies on the association of long-term exposure to greenspace and cognitive functions across the lifespan. PRISMA guidelines and the PECOs method were applied to screen for eligible studies. Twenty-five studies from Scopus, PubMed, and PsycINFO met the inclusion criteria. Six studies were longitudinal and nineteen cross-sectional. Fifteen studies focused on schoolchildren, six studies on adults, and four on the elderly. Twenty studies used the NDVI to assess greenspace exposure and the remaining used other indexes. Eight studies employed academic achievement as the outcome, eight studies global cognition, six studies attention/executive functions, and three studies memory. The evidence was inconsistent but suggestive for a beneficial role of greenspace exposure on cognitive functions. Further studies are required, especially among adults and older people, by adopting longitudinal designs.

1. Introduction

Approximately 55% of the population lives in urban areas, and by 2050 it is predicted that this number will rapidly increase and about 85% of people in Europe will live in cities [1,2]. The growing urbanization influences greenspace fragmentation [3] and the spread of urban greenspace (UGS) as a part of green infrastructure (GI) which is increasing in the urban world [4]. The linking between presence and use of greenspace in urban contexts and human well-being has been of interest for a lot of studies in the field of environmental science [5,6]. Reviews and meta-analyses [7,8,9] have suggested the association of greenspace exposure with mental health in children and middle-aged and older adults. Davis et al. (2021) evaluated 45 studies and found evidence on the association between greenspace and emotional and behavioral well-being in children, such as reduction in anxiety, depression, and aggressive behavior. On the other hand, Gascon et al. (2015) found inadequate evidence for a relationship between greenspace and mental health among children and limited evidence among adults. Furthermore, Li et al. (2021), in their systematic review, found mixed results on the beneficial role of early nature exposure in mental health in later life. In addition, in a recent study, residential greenness was associated with fewer occurrences of problematic behavior in children [10]. Moreover, living in proximity to greenspace was found to be associated with a lower incidence of depressive symptoms in adolescents and young adults [11]. Other studies have shown an association between neighborhood greenness and a decrease in perceived stress [12], and residential greenness was positively associated with light-intensity physical activity among adults and older adults [13].
To explain the positive effect of greenspace on health and wellbeing, different biopsychosocial mechanisms could be hypothesized [14]. Specifically, air pollutant concentrations, such as traffic-related pollution exposure, are lower in green. The presence of greenspace has been reported to reduce levels of traffic noise, which in turn is associated with physical health, such as cognitive functions and the risk to develop neurodegenerative disorders [15,16]. Moreover, use of greenspace has also been reported to encourage physical activity [17] and social cohesion [18], which support the improvement of cognitive functioning [19,20]. Additionally, greenspaces have a restorative value, as proposed by the Stress Reduction Theory (SRT) [21,22] and by the Attention Restoration Theory (ART) [23,24,25]. The SRT suggest that exposure to the natural environment and greenspace encourages positive emotions and positive change in physiological arousal, which preserves sustained attention [21,22]. Instead, according to ART, since natural environments are sources of fascination, being in contact with the natural environment stimulates the use of involuntary attention. This could be an efficient way to recover depleted attention resources. Few studies have focused on the association between greenspace and attention or cognitive functioning in general. In a systematic review, de Keijzer et al. (2016) selected 13 studies on the relationship between long-term greenness exposure and cognition across the life course. Six studies focused on children, three on adults, and four on older adults. Studies on children highlighted the beneficial role of greenspace exposure and cognitive abilities, such as attention and working memory [26]. Moreover, studies reported a positive association of this exposure with cognitive function in adults as well [26]. Concerning older adults, results for associations between greenspace and cognitive functioning were limited and inconsistent [26]. Therefore, the authors concluded that evidence on the association between greenspace exposure and cognitive functioning were still inadequate but suggestive for potential association and are thus worthy of investigation. Since the publication of the aforementioned systematic review, several studies investigating the same association were published.
The overarching goal of this study was to systematically evaluate the body of evidence on the association between greenspace exposure and cognitive functioning. Specific aims were as follows: (a) to summarize studies on the topic including only objective measures of greenspace exposure and cognitive functioning; (b) to evaluate the beneficial role of greenspace in different age groups and for specific cognitive domains (e.g., attention, intelligent quotient (IQ), or global cognition); (c) to provide an explorative overview of intervening variables that could account for mediation or moderation effects on the association between greenspace exposure and cognitive functioning.

2. Methods

2.1. Eligibility Criteria

The PECO method [27] was used to define the selection criteria for the suitable studies: (a) P (Participants): no age, sex, or health condition restrictions were applied; (b) E (Exposure): long exposure to greenspace, assessed with objective measures; (c) C (Comparison): no comparison; (d) O (Outcome): global cognition, memory, attention/executive functions, visuospatial abilities, and language, as outcome, assessed with objective measures. Moreover, we only included original articles that were written in English and were based on human studies without any limitation with regards to the year of publication. Case studies, editorials, review articles, and conference abstracts were excluded from our review.

2.2. Search Strategy and Study Selection

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [28] was applied for reporting results of the present review. We queried PsychINFO, Scopus, and PubMed to search for the eligible studies. PsychINFO is considered the most used abstracts database of psychological sciences. Scopus is identified as a well-used electronic database of peer-reviewed research in several fields, such as medicine and life sciences. Instead, PubMed is considered to be an interface for searching MEDLINE, the most-used electronic database for health sciences.
The search strategy was defined using the following syntax terms based on title, abstract, and keywords: “greenness” OR “greenspace(s)” OR “urban forestry” AND “cogn *” OR “memory” OR “attent *” OR “lang *” OR “visuospatial” OR “exec *”. The search was conducted on 31 January 2022. The search syntax terms were adjusted to fit each database as presented in the Supplementary Materials (Table S1). Other studies were added by checking the reference list of the selected studies. From the resulting records, duplications were excluded. The articles were screened for the eligibility in three steps. Firstly, articles were screened for title and then for abstract. The final screening step was performed for the full text. The selected articles were consistent with the eligibility criteria.

2.3. Data Extraction and Manipulation

A datasheet from the electronic database was carried out by the authors to manage the large body of articles using R package “xlsx” [29,30]. For each selected study, the following information was extracted: authors, year, country, study design, study population, sample population, level of greenspace, greenspace indicator(s), outcome, outcome assessment, covariates, mediation and moderation variables, statistical analyses, and main study results. Associations found in each study included in the final dataset were assessed according to the Bayesian average method. It was used to avoid bias due to the discrepancy in the number of analyses performed in the included studies (e.g., using the percentage, the number of significant associations should be divided by the total number of analyses and multiplied by one hundred, and if ten analyses were performed and 5 significant associations were found, it should be attributed 50% of the associations to that study, but if 1 analysis was performed and 1 significant association was found, it should be attributed 100%). The Bayesian average was estimated considering (a) p (proportion of the significant analyses performed for each study), (b) c (the 25th percentile of the distribution of the number of analyses performed for each study), (c) m (mean of p), and (d) n (the total number of analyses performed for each study). The following formula was used:
(p × n + c × m)/(n + c)
Each study was classified as reporting a small association if the Bayesian average ranged between 0 and 0.33, medium association if it ranged between 0.33 and 0.66, and strong association if it ranged from 0.66 and 1.00.

2.4. Quality Assessment

Each article was evaluated for its quality. The score was based on 11 criteria for quality assessment of the studies that were adopted from similar previous systematic reviews of the health impacts of long-term exposure to green space (Table S2, Supplementary Materials) [8,26,31]. The quality score included a range from 0 to 1 for eight items of the checklist and from 0 to 2 for three items. The highest total score possible was 14; the total score for each article was converted to a percentage: it was divided by the maximum total score possible, and the result was multiplied by one hundred. The range quality was then labeled as excellent quality (score ≥ 81%), good quality (score between 61% and 80%), fair quality (score between 41% and 60%), poor quality (score between 21% and 40%), and very poor quality (score ≤ 20%). Two authors (ER and AOC) independently provided their quality score on each article. A third author (GSp) provided his quality score in case of disagreement. Cohen’s Kappa was then used to obtain a measure of inter-rater agreement. A value of K = 0.83 was found, thus indicating a good agreement between the two raters [32].

3. Results

3.1. Study Selection

Figure 1 presents the selection process of the articles. Initially, a total of 983 articles were found based on our systematic research, of which 169 studies were eliminated because they were duplicated. In addition, six studies from the references of the selected studies were identified. A further 734 articles were excluded after screening the titles and abstracts, because they did not meet our selection criteria. The remaining 86 articles were screened by full-text and 61 articles were excluded, of which 34 did not use objective measures of greenspace and/or cognitive functioning, 15 did not include relevant outcome for the present review, 3 were experiments, 2 were not written in English, 2 were case studies, 2 were editorials/commentaries, 1 was a review, 1 was a book chapter, and 1 was a dissertation. Therefore, 25 articles met the selection criteria and were included in this systematic review.

3.2. Study Characteristics

Table 1 shows the main characteristics of the selected studies. The most of studies (N = 27) were published after 2016, when the de Keijzer’s review was conducted. Among the selected articles, 6 studies were longitudinal [33,34,35,36,37,38] and 19 were cross-sectional studies [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57].
The selected studies were from the USA (N = 8) [37,45,48,49,50,52,53,55], Spain (N = 5) [33,34,35,36,42], England (N = 2) (Flouri et al., 2019; Lega et al., 2021), China (N = 3), Australia (N = 2) [40,41], Canada (N = 1) [46], New Zealand (N = 1) [54], and Bulgaria (N = 1) [43]. One study collected data from four European countries: Spain, England, Lithuania, and the Netherlands [57]. Fifteen studies were conducted among children [33,34,35,37,39,41,44,45,48,49,50,52,53,54,55], six on adults [40,42,43,46,51,57], and four among older adults [36,38,47,56]. The selected studies mainly assessed exposure to greenspace across buffers with a radius ranging from 25 m to 1000 m. Most of the studies (N = 17) [33,34,35,36,37,38,41,42,43,46,47,49,51,52,55,56,57] used the Normalized Differences Vegetation Index (NDVI). Two studies used also the Enhanced Vegetation Index (EVI) and Vegetation Continuous Field (VCF) [34,36], the additional indexes that, respectively, measure vegetation and tree cover [58,59]. Ten studies [39,40,44,45,48,49,50,52,53,54] also used other indicators of greenspace exposure as data from Multiple Environmental Deprivation Index (MEDIx), tree canopy cover, grass/shrub cover, and average percent impervious surfaces, and one study used the percentage of time spent in a greenspace. A deeper description of the characteristics of greenspace exposure assessment is in Table S3, Supplementary Materials.
Evaluated outcomes varied among the studies across the age groups: attention and executive functions among children, adolescents, and adults (N = 6) [33,34,35,39,46,57], memory among children and adults (N = 3) [40,44,51], global cognition among children, adults, and older adults (N = 8) [36,38,42,43,47,54,56,60], and academic achievement among children (N = 8) [41,45,48,49,50,52,53,55].
All studies, except for four [35,45,53,54], used more than three confounders in order to adjust their models. The most applied covariates were age, sex, and socioeconomic status. In some of studies on children, models were adjusted also for other confounders such as maternal or paternal education, maternal cognitive functioning, and maternal smoking during pregnancy. Among the studies on adults, smoking, alcohol, blood pressure, waist circumference, marital status, and employment were used as covariates as well. Instead, in the older adults’ studies, the models were adjusted also for financial support, physical activity, and social and leisure activities. Twelve studies [33,36,37,41,43,44,47,48,51,53,56,57] took into account mediation variables and effect modifiers.
Table 2 shows selected studies classified according to the Bayesian average method. Eight studies [39,42,45,46,47,53,57,60] showed a small association between greenspace exposure and cognitive functioning, eleven studies indicated medium association [33,36,38,41,44,48,49,50,51,54,56], and six studies revealed strong association [34,35,40,43,52,55].

3.3. Study Findings

3.3.1. Children and Adolescents

Fifteen studies investigated the association between exposure to green space at home, school, and/or on the commuting route between home and school and cognitive development in children. The studies were conducted in Europe (N = 5), America (N = 8), and Oceania (N = 2). Fourteen studies were classified as good quality, and one study as fair quality. Among the overall analyses and according to the Bayesian average, four studies [37,39,45,53] showed small association, seven studies [33,41,44,48,49,50,52] displayed medium association, and four studies [34,35,52,55] were evaluated as having a strong association (Table 3).
Eight of the selected studies on children considered academic achievement as an outcome; among these, three cross-sectional studies [41,52,55] found that a higher level of greenness surrounding primary schools was associated with higher academic achievements among schoolchildren. Specifically, Claesen et al. (2021) examined mean academic score in primary schools in Australia and found a significant and positive association between NDVI levels and the domains of reading, numeracy, and grammar/pronunciation. Wu et al. (2014) found a significant association between greenness of the school in spring and academic performances in math and English among children in elementary school in Massachusetts. Leung et al. (2017), as well, showed that the associations were positive for greenness around the school in Massachusetts and academic performances measured by composite performance index and percentage of students who scored as “proficient and higher”. Another two cross-sectional studies [49,50] highlighted that a higher percentage of tree cover in school surrounding was associated with better performance in math and reading tests. In one of these [49] conducted in Washington, greenness, in a buffer of 250 m, was associated with reading and math scores as well. Instead, Kuo et al. (2018) found a positive and significant association between school trees and math scores, but not for reading scores in public schools of Chicago. In contrast, Hodson and Sander (2017) reported an association between tree cover and reading performances in a sample of primary schools in Minnesota. For academic achievement as the outcome, Sivarajah et al. (2018) did not find any association between performance at elementary schools in Toronto (N = 387) and tree cover.
Two studies considered global cognition in children as the outcome. Especially, Jimenez et al. (2022), among the assessed cognitive domains, found an association between NDVI and visual memory in Massachusetts. On the contrary, Ward et al. (2016) did not find any association between time spent in greenspace and global cognition in children of Auckland [54].
Three longitudinal studies and two cross-sectional studies found an association between greenspace exposure and attention/executive functions and memory among children. In their Spanish study, Dadvand et al. (2015) found an association between 12-months progress in working memory and attention and greenness within school, surrounding school, or total surrounding greenness; commuting greenness, instead, was only associated with 12-months progress in working memory, but there was no association between residential surrounding greenness and working memory or attention at baseline or progress. Moreover, Dadvand et al. (2018) found an association between surrounding greenness and volumes in brain regions related to working memory and inattentiveness. In another study, in two cohorts of children in Spain, exposure to residential greenspace, measured as average NDVI, was associated with lower inattentiveness [34]. However, the associations between residential surrounding tree cover (i.e., based on VCF) and inattentiveness were not statistically significant. Bijnens et al., (2021) found that an increase in total greenspace (within 2000 m) was association with a better performance in attention and executive functions tasks in Belgian adolescents. Especially, vegetation higher than 3 m (high green) was associated with a shorter reaction time in attentional tasks. Lastly, the cross-sectional study conducted by Flouri et al. (2017) reported a significant association between neighborhood greenspace and spatial working memory in children in England.

3.3.2. Adults

Six studies investigated the association between residential greenness exposure and cognitive abilities among adults. All the studies were cross-sectional. The studies were conducted in Europe (N = 4), Oceania (N = 1), and North America (N = 1). Four studies were classified as good quality and two studies were classified as fair quality. Using the Bayesian average, three studies [42,46,57] were classified as small associations, one study [51] showed medium association, and two studies showed strong [40,43] association (Table 3).
Dzhambov et al. (2019), in a middle-aged population in Bulgaria, observed that living in neighborhoods with a higher ratio of greenspace (i.e., NDVI) was associated with better performance in general cognitive abilities. A cross-sectional study conducted in Spain did not find any association between residential surrounding greenness and global cognition, episodic memory, and executive functions [42]. Furthermore, another cross-sectional study in England [51] study reported a beneficial association of greenness surrounding home address on memory tasks. Specifically, residential surrounding greenness was significantly associated with forward digit span and total digit span, but there was no association with backward digit span. Concerning executive functions, in a sample of 1628 adults, an association between residential distance to natural outdoor environments and executive domains was found [57]. However, another study conducted in Canada by Hystad et al. (2019) did not find any associations between greenspace and executive functions among adults.

3.3.3. Older Adults

Four studies evaluated the relationship of greenspace exposure and risk of cognitive decline in older adults. Two studies were longitudinal and two were cross-sectional. The studies were conducted in Europe (N = 4), Oceania (N = 1), and North America (N = 1). All the studies on older adults were classified as good quality. One study showed a small association [47], and three studies [36,38,56] displayed a medium association according to the Bayesian average (Table 3).
In their longitudinal study in China, Zhu et al. (2019) showed that an increase in residential greenness exposure was associated with a better performance in Mini-Mental State Examination (MMSE) and a highest-odds ratio developing some cognition impairments. In addition, there was an association between residential greenness exposure and changes in MMSE score in the longitudinal analysis. The association between residential greenness exposure and odds of cognitive impairment was also found in another study [56], particularly in older adults aged from 65 to 79 years.
De Keijzer et al. (2017), in their longitudinal study, found that higher levels of greenspace (i.e., NDVI, EVI) in a 500 m and 1000 m buffer around the residential address were associated with slower cognitive decline in global cognition, reasoning, and fluency in older Spanish adults. Similarly, Jin et al. (2021) found that the highest contemporaneous NDVI (defined as a single measure of NDVI) was associated with lower odds of cognitive impairment, but no significant association was found between annual average of NDVI and odds in cognitive impairment in older Chinese adults.

3.3.4. Mediators and Effect Modifiers

Our reviewed studies considered the air pollution, stress, social interactions, blood pressure, physical activity, and obesity as potential mediators and sex, indicators of socioeconomic position learning opportunity index, and APOE ε4 as potential effect modifiers. Four studies tested the mediation role of air pollution. Specifically, Jimenez et al. (2022) reported a significant negative mediated effect of black carbon in the association between early childhood greenness and midchildhood cognitive development (except for verbal IQ). Dzhambov et al. (2019) did not find a mediating role of nitrogen dioxide in the association between residential surrounding greenness and cognitive abilities in adults. Dadvand et al. (2015) observed that the beneficial association of greenspace exposure with attention and working memory among children was partially mediated by reduction in TRAP. Furthermore, in another study by Cleasen et al., TRAP was reported to mediate the association between greenness around schools and academic achievement in terms of numeracy and grammar/punctuation [41]. Stress was evaluated as a mediator in the relationship between surrounding greenness and memory in only one study [51], which reported a partial mediation effect. Lastly, the mediation role of waist circumference, as an indicator of obesity, in the association between residential greenness and cognitive functions was found in a cross-sectional study among adults [43]. Other mediators were considered [36,37,43,57], such as social interaction/support/cohesion, blood pressure, and physical activity, but none of them showed a significant mediatory effect.
Four studies evaluated the effect modifiers. Flouri et al. (2019) investigated the modification of the association between greenness and cognitive functioning by the neighborhood deprivation and found that the association of greenness on spatial working memory did not change across different levels of neighborhood deprivation in a sample of children. In their study, Sivarajah et al. (2017) suggested that the association of tree cover with academic achievement changes across different levels of the learning opportunities index. Interaction between tree canopy cover and SES disadvantage in association with academic achievement was explored by Kuo et al. (2018). Their findings suggested that the association between school trees and academic achievement was modified by socioeconomic disadvantage (investigated by income and race/ethnicity). Lastly, Jin et al. (2021) found a significant interaction between residential greenness and AD Poligenetic Risk Score on cognitive functioning in older people. In addition, according to Zhu et al. (2020), the status of APOE ε4, considered to be a relevant risk factor in developing Alzheimer’s disease [61], was found to be a potential modifier of the association between greenspace exposure and cognitive impairment. Nevertheless, the interaction term between baseline annual average NDVI and APOE ε4 status on cognitive impairment was not significant.

4. Discussion

The purpose of this systematic review was to synthesize the available evidence on the association of greenspace exposure with cognitive function across the life course. Accordingly, we reviewed studies on this association across different age groups for different objective measures of greenspace exposure and cognitive domains (i.e., memory, attention, executive functions, visuospatial abilities, global cognition) and identified the reported potential mediators and modifiers of such associations.
The selected studies totaled 25. All the selected studies were published after 2016. A lot of studies on the beneficial role of the greenness exposure on the cognitive functioning were published over the past few years. This issue highlighted the need for an updated literature review. Moreover, differently from de Keijzer et al. (2016), all the selected studies used objective measures of greenspace exposure that are considered the better methods to explore the relationship between greenspace and health [14]. In addition, the selected studies were conducted mainly in Europe and North America: few studies were conducted in Asia and Oceania. Therefore, the selected studies were not conducted in many different climates and with different vegetation types. In addition, a lot of study were conducted especially in middle- and high-income countries.
The attempt to summarize findings on the association between greenspace exposure and cognitive functioning was difficult due to limitations of the available evidence, such as different study design, different number of analyses performed, and a great variety of predictors and outcomes. To overcome this, in our systematic review, we assessed each study based on the Bayesian average and each study was classified as small association, medium association, and strong association.

4.1. Age Groups

Among children, associations were found in attention/EF, memory, and academic achievement. This finding was consistent with previous reviews supporting the beneficial role of natural environment for schoolchildren [7,62]. For global cognition, the beneficial role of greenness exposure remains unclear. Within the adults’ age group, the trend is more blurred. Strong associations were found only for two of the four studies that investigated global cognition and memory. Therefore, among the selected evidence, all the studies investigating attention showed a small association. For older adults, few studies met our selection criteria, and all showed small or medium association between greenspace exposure and global cognition.
Overall, a general unclear trend on the relation between greenspace exposure and global cognition during the lifespan emerged, with studies on children and older adults lacking full associations for global cognition. A positive trend was found for attention and executive functions, which is in agreement with the ART. This trend was detectable exclusively across the children’s and adults’ age group. This finding was consistent with results from Jimenez et al. (2021). Indeed, their review suggested that the impact of greenspace exposure on cognitive functioning among adults was comparable with results obtained from children’s studies. A similar trend was not detectable across the older adults’ group due to a lack of studies on attention and executive functions in aging, even though recent studies suggested that the presence of greenspace could reduce the risk of developing dementia [16]. Furthermore, several studies were carried out on samples composed of children and few studies were available on the adults’ and older adults’ age groups. Nevertheless, consistent with the available literature [26,63,64], more studies on adults and older adults could be useful to explore the role of environment, especially of greenness exposure, in cognitively healthy aging and age-related cognitive decline.

4.2. Study Design

The present systematic review included 25 studies, and more than half of them were cross-sectional. Although cross-sectional designs are commonly adopted to explore the association between variables, their use leads to some methodological limits. The cross-sectional study implicates that all variables are assessed simultaneously. For this reason, the cross-sectional study has a predictive limitation, and no evidence on causal relationship between the variables could be deduced [65]. Longitudinal studies, instead, could overcome this limitation and provide reliable knowledge about the predictive conclusions.

4.3. Greenspace Exposure

In order to assess greenspace exposure and contact with greenspace, different methods are available. Surrounding greenness is the most-used. Almost all selected studies used the surrounding greenness to take account of greenness exposure. The most-used indicator of surrounding greenness was the NDVI. The NDVI is an efficient metric used to assess the presence of vegetation and is delivered from satellite images which quantify vegetation studying the difference between near-infrared vegetation minus visible radiation divided by near-infrared radiation plus visible radiation. It ranges from minus −1 to +1, with 0 indicating the absence of vegetation. Instead, if the index is close to +1, it indicates the presence of high density of green leaves [66]. The use of the NDVI allows a comparison among different studies. Nevertheless, the NDVI cannot evaluate the quality, typology, and biodiversity of greenspace and does not give information about structured greenspaces, such as parks, and unstructured vegetation, such as trees in the streets or yards [14]. To overcome the limits of NDVI, other indicators were used by the selected studies, such as EVI and VCF, two additional indexes useful, respectively, in monitoring vegetation and in measuring ground cover [58,59] and tree canopy cover, grass, and shrub. Using various indicators could make the comparison among different studies difficult and, as suggested by other authors [8,14], standardized tools to assess greenspace exposure could be useful in this research field. In addition, we detected that several selected studies used surrounding greenness focused on exposure at the home address or surrounding school, overlooking the exposure that can occur in other microenvironments such as workplace or commuting route, as suggested by a previous review [26]. Furthermore, most of the reviewed studies (except one: Hystad et al. (2019)) did not take into account changes in residential address.
Several studies measured greenness exposure within a buffer from 30 m to 5000 m, but it is not clear what buffer distance could be more usefully assessed [14]. Indeed, despite a large agreement on the use of specific buffer for NDVI (i.e., 100 m, 150 m, 300 m), official guidelines are still lacking. Best practices from previous studies should be considered in order to clarify which areas and buffer distances could be advantageous to measure [14,67,68].
Physical access to greenspace is a valid method to assess contact with greenspace as well. Few selected studies used it and quantified the distance between the address and the closest greenspace.
Visual access to greenspace and use of greenspace were never considered in our selected studies.
Lastly, in line with previous studies [26,64], we detected a few considerations of quality of greenspace that may play a key role in the association between greenspace and cognitive functioning, such as aesthetics, walkability, safety, biodiversity, and organized social activities [69].

4.4. Cognitive Functioning

Accounting for cognitive domains considered in the selected studies, cognitive domains were differentially measured through the age groups (i.e., children, adults, and older adults). Cognitive development in children was assessed considering different outcomes (e.g., attention/EF, memory, global cognition, academic achievement). All outcomes were assessed with a standardized cognitive test. Academic achievement was assessed with measures of school performance that may be influenced by other cognitive domains such as attention and executive functions.
Cognitive functioning in adults was assessed with standardized tests as well for each of the cognitive domains, such as the free recall test and S-words test. Instead, to evaluate cognitive functioning in older adults, the reviewed studies used a single screening test for global cognition (i.e., MMSE), making it difficult to have a clear overview for each specific cognitive domain. As suggested by ART, some proprieties of greenspace could be related with specific cognitive domain, not measurable with a single screening test. To overcome this, the Montreal Cognitive Assessment might be used, the most comprehensive available single screening test [70,71] to explore each cognitive domain separately. Therefore, well-established best practices to assess cognitive functioning among older adults could be used. This could provide a clear overview for each specific cognitive domain in older people, including spatial memory and orientation, which are sensitive to age and familiarity for places [72,73]. Lastly, computerized tools and evaluation by healthcare professional may provide a more accurate assessment of cognitive functioning across the age groups.

4.5. Role of Mediators and Modifiers

Few studies included in the present review explored the mediators of the association between greenspace exposure and cognitive function. TRAP, stress, and obesity were found to be potential mediators of this association; however, these observations were limited and in some cases were inconsistent. For example, the findings about the role of air pollution in the association between greenspace exposure and cognitive functioning were not consistent [37,43]. The mediation role of TRAP was not clear as well, but some studies highlighted that the association between greenspace exposure and cognitive functioning could be mediated by a reduction of TRAP in green areas [33,41].
Little evidence on the role of moderating variables was available as well. In spite of that, some studies suggested the modifying role of learning opportunities and socioeconomic status in the association between greenspace exposure and cognitive functioning [48,53]. No study investigated perceived restoration in this association. According to ART, it could be usefully introduced it in future models.

5. Limitations

The present review has some limitations. The variety of outcomes did not allow us to perform a formal meta-analysis. In addition, due to our limiting selection criteria, we excluded many studies evaluating the role of green exposure on cognitive functioning, since they used subjective measures of assessment.

6. Conclusions

The aim of the present work was to systematically review and summarize the available studies on the beneficial role of greenspace exposure on cognitive functioning. We found a limited number of available studies and most of them were cross-sectional. Cognitive domains were evaluated with different tools through the age groups and few studies explored intervening variables that could mediate or moderate the association between greenspace exposure and cognitive functioning. The available evidence is still limited, especially for adults and the elderly, but still is suggestive for a beneficial association between exposure to greenspace and cognitive function across the life-course. Further research could benefit from (a) longitudinal designs; (b) further focus on middle-aged and older adults; (c) the use of well-established practices to assess cognition; (d) the assessment of quality of greenspace; (e) the consideration of different climates with different vegetation types and in under-represented regions, especially in low- and middle-income countries; (f) a deeper investigation of mechanisms and potential effect modifiers.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph191811700/s1, Table S1, Search strategies on scientific database; Table S2, Quality assessment of the available evidence; Table S3, Characteristics of greenspace exposure assessment.

Author Contributions

Conceptualization, E.R. and A.O.C.; methodology, E.R. and A.O.C.; software, E.R. and A.O.C.; validation, E.R., G.S. (Giuseppina Spano) and A.O.C.; investigation, E.R. and A.O.C.; resources E.R. and A.O.C.; data curation, E.R., G.S. (Giuseppina Spano) and A.O.C.; writing original draft preparation, E.R., G.S. (Giuseppina Spano) and A.O.C.; writing—review and editing, E.R., A.O.C., G.S. (Giuseppina Spano), A.L., L.T., C.C., G.E., P.D., G.S. (Giovanni Sanesi) and A.B.; visualization, E.R. and A.O.C.; supervision, A.O.C.; project administration, A.O.C. and E.R.; funding acquisition, A.B. and E.R. All authors have read and agreed to the published version of the manuscript.

Funding

E.R. was supported by the project “EN.G.AGE.—The linking between ENvironment and coGnitive AGEing”. Action was cofunded by POR Puglia FESR FSE 2014–2020-Asse X-Azione 10.4. (CUP Code: H96D20000320008). G.Sp. was supported by the project “Role of PSychological and social factors in the conservation of biodivErsity and the ECOsystemic heritage for the fight against climate change (PsEEco)”, action was cofunded by Programma Operativo (PON) Ricerca E Innovazione 2014–2020-Azione IV.6 “Contratti di ricerca su tematiche Green” (CUP H95F21001420006). A.L. was supported by the project “A-WAND! Strengthening the skills of self-monitoring and preventing the risk of accidents in and outdoors in a population of elderly people in the South of Italy”. Action was funded by Research for Innovation (REFIN)-POR Puglia FESR FSE 2014-2020-Asse X-Azione 10.4. (Grant Code 8C40CDAA). P.D. was supported by the Spanish Ministry of Science and Innovation through the “Centro de Excelencia Severo Ochoa 2019–2023” Program (CEX2018-000806-S), and by the Generalitat de Catalunya through the CERCA Program to ISGlobal. G.S., A.B. and A.O.C. were supported by the project “GAME—Green, smArt and Mobile urban communitiEs: promotion of inclusive, equitable and integrated social policies for human well-being in cities”, funded by University of Studies of Bari.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of University of Bari “Aldo Moro”. (Protocol code ET-21-20, date of approval 28 November 2021).

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pesaresi, M.; Melchiorri, M.; Siragusa, A.; Kemper, T. Mapping Human Presence on Earth with the Global Human Settlement Layer. In The Atlas of the Human Planet 2016; Joint Research Centre: Ispra, Italy, 2016. [Google Scholar]
  2. Ritchie, H.; Roser, M. Urbanization. In Our World Data. 2018. Available online: https://ourworldindata.org/urbanization (accessed on 1 May 2021).
  3. Li, F.; Zheng, W.; Wang, Y.; Liang, J.; Xie, S.; Guo, S.; Li, X.; Yu, C. Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective. Forests 2019, 10, 333. [Google Scholar] [CrossRef]
  4. Escobedo, F.J.; Giannico, V.; Jim, C.Y.; Sanesi, G.; Lafortezza, R. Urban Forests, Ecosystem Services, Green Infrastructure and Nature-Based Solutions: Nexus or Evolving Metaphors? Urban For. Urban Green. 2019, 37, 3–12. [Google Scholar] [CrossRef]
  5. Giannico, V.; Spano, G.; Elia, M.; D’Este, M.; Sanesi, G.; Lafortezza, R. Green Spaces, Quality of Life, and Citizen Perception in European Cities. Environ. Res. 2021, 196, 110922. [Google Scholar] [CrossRef] [PubMed]
  6. Spano, G.; Giannico, V.; Elia, M.; Bosco, A.; Lafortezza, R.; Sanesi, G. Human Health–Environment Interaction Science: An Emerging Research Paradigm. Sci. Total Environ. 2020, 704, 135358. [Google Scholar] [CrossRef] [PubMed]
  7. Davis, Z.; Guhn, M.; Jarvis, I.; Jerrett, M.; Nesbitt, L.; Oberlander, T.; Sbihi, H.; Su, J.; van den Bosch, M. The Association between Natural Environments and Childhood Mental Health and Development: A Systematic Review and Assessment of Different Exposure Measurements. Int. J. Hyg. Environ. Health 2021, 235, 113767. [Google Scholar] [CrossRef]
  8. Gascon, M.; Triguero-Mas, M.; Martínez, D.; Dadvand, P.; Forns, J.; Plasència, A.; Nieuwenhuijsen, M.J. Mental Health Benefits of Long-Term Exposure to Residential Green and Blue Spaces: A Systematic Review. Int. J. Environ. Res. Public Health 2015, 12, 4354–4379. [Google Scholar] [CrossRef]
  9. Li, D.; Menotti, T.; Ding, Y.; Wells, N.M. Life Course Nature Exposure and Mental Health Outcomes: A Systematic Review and Future Directions. Int. J. Environ. Res. Public Health 2021, 18, 5146. [Google Scholar] [CrossRef]
  10. Lee, M.; Kim, S.; Ha, M. Community Greenness and Neurobehavioral Health in Children and Adolescents. Sci. Total Environ. 2019, 672, 381–388. [Google Scholar] [CrossRef]
  11. Bezold, C.P.; Banay, R.F.; Coull, B.A.; Hart, J.E.; James, P.; Kubzansky, L.D.; Missmer, S.A.; Laden, F. The Relationship between Surrounding Greenness in Childhood and Adolescence and Depressive Symptoms in Adolescence and Early Adulthood. Ann. Epidemiol. 2018, 28, 213–219. [Google Scholar] [CrossRef]
  12. Pun, V.C.; Manjourides, J.; Suh, H.H. Association of Neighborhood Greenness with Self-Perceived Stress, Depression and Anxiety Symptoms in Older U.S Adults. Environ. Health 2018, 17, 39. [Google Scholar] [CrossRef] [Green Version]
  13. Puhakka, S.; Lankila, T.; Pyky, R.; Kärmeniemi, M.; Niemelä, M.; Kangas, K.; Rusanen, J.; Kangas, M.; Näyhä, S.; Korpelainen, R. Satellite Imaging-Based Residential Greenness and Accelerometry Measured Physical Activity at Midlife—Population-Based Northern Finland Birth Cohort 1966 Study. Int. J. Environ. Res. Public Health 2020, 17, 9202. [Google Scholar] [CrossRef] [PubMed]
  14. 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]
  15. Wu, J.; Grande, G.; Stafoggia, M.; Ljungman, P.; Laukka, E.J.; Eneroth, K.; Bellander, T.; Rizzuto, D. Air Pollution as a Risk Factor for Cognitive Impairment No Dementia (CIND) and Its Progression to Dementia: A Longitudinal Study. Environ. Int. 2022, 160, 107067. [Google Scholar] [CrossRef]
  16. Zhao, Y.-L.; Qu, Y.; Ou, Y.-N.; Zhang, Y.-R.; Tan, L.; Yu, J.-T. Environmental Factors and Risks of Cognitive Impairment and Dementia: A Systematic Review and Meta-Analysis. Ageing Res. Rev. 2021, 72, 101504. [Google Scholar] [CrossRef] [PubMed]
  17. Astell-Burt, T.; Feng, X.; Kolt, G.S. Green Space Is Associated with Walking and Moderate-to-Vigorous Physical Activity (MVPA) in Middle-to-Older-Aged Adults: Findings from 203,883 Australians in the 45 and Up Study. Br. J. Sports Med. 2014, 48, 404–406. [Google Scholar] [CrossRef]
  18. Weinstein, N.; Balmford, A.; DeHaan, C.R.; Gladwell, V.; Bradbury, R.; Amano, T. Seeing Community for the Trees: Links Between Contact with Natural Environments, Community Cohesion, and Crime. BioScience 2015, 65, 1141–1153. [Google Scholar] [CrossRef]
  19. Cheval, B.; Csajbók, Z.; Formánek, T.; Sieber, S.; Boisgontier, M.P.; Cullati, S.; Cermakova, P. Association between Physical-Activity Trajectories and Cognitive Decline in Adults 50 Years of Age or Older. Epidemiol. Psychiatr. Sci. 2021, 30, e79. [Google Scholar] [CrossRef]
  20. Zhang, W.; Liu, S.; Sun, F.; Dong, X. Neighborhood Social Cohesion and Cognitive Function in U.S. Chinese Older Adults—Findings from the PINE Study. Aging Ment. Health 2019, 23, 1113–1121. [Google Scholar] [CrossRef]
  21. Ulrich, R.S. Aesthetic and Affective Response to Natural Environment. In Behavior and the Natural Environment; Altman, I., Wohlwill, J.F., Eds.; Springer: Boston, MA, USA, 1983; pp. 85–125. ISBN 978-1-4613-3541-2. [Google Scholar]
  22. Ulrich, R.S.; Simons, R.F.; Losito, B.D.; Fiorito, E.; Miles, M.A.; Zelson, M. Stress Recovery during Exposure to Natural and Urban Environments. J. Environ. Psychol. 1991, 11, 201–230. [Google Scholar] [CrossRef]
  23. Kaplan, S. The Restorative Benefits of Nature: Toward an Integrative Framework. J. Environ. Psychol. 1995, 15, 169–182. [Google Scholar] [CrossRef]
  24. Panno, A.; Theodorou, A.; Carrus, G.; Imperatori, C.; Spano, G.; Sanesi, G. Nature Reappraisers, Benefits for the Environment: A Model Linking Cognitive Reappraisal, the “Being Away” Dimension of Restorativeness and Eco-Friendly Behavior. Front. Psychol. 2020, 11, 1986. [Google Scholar] [CrossRef] [PubMed]
  25. Spano, G.; Dadvand, P.; Sanesi, G. Editorial: The Benefits of Nature-Based Solutions to Psychological Health. Front. Psychol. 2021, 12, 646627. [Google Scholar] [CrossRef] [PubMed]
  26. de Keijzer, C.; Gascon, M.; Nieuwenhuijsen, M.J.; Dadvand, P. Long-Term Green Space Exposure and Cognition Across the Life Course: A Systematic Review. Curr. Environ. Health Rep. 2016, 3, 468–477. [Google Scholar] [CrossRef]
  27. Morgan, R.L.; Whaley, P.; Thayer, K.A.; Schünemann, H.J. Identifying the PECO: A Framework for Formulating Good Questions to Explore the Association of Environmental and Other Exposures with Health Outcomes. Environ. Int. 2018, 121, 1027–1031. [Google Scholar] [CrossRef]
  28. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Linee guida per il reporting di revisioni sistematiche e meta-analisi: Il PRISMA Statement. PLoS Med 2015, 7, e1000097. [Google Scholar]
  29. R Core Team (2020)—European Environment Agency. Available online: https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006 (accessed on 19 November 2021).
  30. Dragulescu, A.; Arendt, C. Xlsx: Read, Write, Format Excel 2007 and Excel 97/20 0 0/XP/20 03 Files, R Package Version 0.6.5. 2020. Available online: https://CRAN.R-project.org/package=xlsx (accessed on 1 May 2021).
  31. de Keijzer, C.; Bauwelinck, M.; Dadvand, P. Long-Term Exposure to Residential Greenspace and Healthy Ageing: A Systematic Review. Curr. Environ. Health Rep. 2020, 7, 65–88. [Google Scholar] [CrossRef] [PubMed]
  32. Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159–174. [Google Scholar] [CrossRef]
  33. Dadvand, P.; Nieuwenhuijsen, M.J.; Esnaola, M.; Forns, J.; Basagaña, X.; Alvarez-Pedrerol, M.; Rivas, I.; López-Vicente, M.; De Castro Pascual, M.; Su, J.; et al. Green Spaces and Cognitive Development in Primary Schoolchildren. Proc. Natl. Acad. Sci. USA 2015, 112, 7937–7942. [Google Scholar] [CrossRef]
  34. Dadvand, P.; Tischer, C.; Estarlich, M.; Llop, S.; Dalmau-Bueno, A.; López-Vicente, M.; Valentín, A.; de Keijzer, C.; Fernández-Somoano, A.; Lertxundi, N.; et al. Lifelong Residential Exposure to Green Space and Attention: A Population-Based Prospective Study. Environ. Health Perspect. 2017, 125, 097016. [Google Scholar] [CrossRef]
  35. Dadvand, P.; Pujol, J.; Macià, D.; Martínez-Vilavella, G.; Blanco-Hinojo, L.; Mortamais, M.; Alvarez-Pedrerol, M.; Fenoll, R.; Esnaola, M.; Dalmau-Bueno, A.; et al. The Association between Lifelong Greenspace Exposure and 3-Dimensional Brain Magnetic Resonance Imaging in Barcelona Schoolchildren. Environ. Health Perspect. 2018, 126, 027012. [Google Scholar] [CrossRef]
  36. de Keijzer, C.; Tonne, C.; Basagaña, X.; Valentín, A.; Singh-Manoux, A.; Alonso, J.; Antó, J.M.; Nieuwenhuijsen, M.J.; Sunyer, J.; Dadvand, P. Residential Surrounding Greenness and Cognitive Decline: A 10-Year Follow-up of the Whitehall II Cohort. Environ. Health Perspect. 2017, 126, 077003. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Jimenez, M.P.; Shoaff, J.; Kioumourtzoglou, M.-A.; Korrick, S.; Rifas-Shiman, S.L.; Hivert, M.-F.; Oken, E.; James, P. Early-Life Exposure to Green Space and Mid-Childhood Cognition in the Project Viva Cohort, Massachusetts. Am. J. Epidemiol. 2022, 191, 115–125. [Google Scholar] [CrossRef] [PubMed]
  38. Zhu, A.; Wu, C.; Yan, L.L.; Wu, C.-D.; Bai, C.; Shi, X.; Zeng, Y.; Ji, J.S. Association between Residential Greenness and Cognitive Function: Analysis of the Chinese Longitudinal Healthy Longevity Survey. BMJ Nutr. Prev. Health 2019, 2, 72–79. [Google Scholar] [CrossRef] [PubMed]
  39. Bijnens, E.M.; Vos, S.; Verheyen, V.V.; Bruckers, L.; Covaci, A.; De Henauw, S.; Den Hond, E.; Loots, I.; Nelen, V.; Plusquin, M.; et al. Higher Surrounding Green Space Is Associated with Better Attention in Flemish Adolescents. Environ. Int. 2022, 159, 107016. [Google Scholar] [CrossRef] [PubMed]
  40. Cerin, E.; Barnett, A.; Shaw, J.E.; Martino, E.; Knibbs, L.D.; Tham, R.; Wheeler, A.J.; Anstey, K.J. From Urban Neighbourhood Environments to Cognitive Health: A Cross-Sectional Analysis of the Role of Physical Activity and Sedentary Behaviours. BMC Public Health 2021, 21, 2320. [Google Scholar] [CrossRef] [PubMed]
  41. Claesen, J.L.A.; Wheeler, A.J.; Klabbers, G.; Gonzalez, D.D.; Molina, M.A.; Tham, R.; Nieuwenhuijsen, M.; Carver, A. Associations of Traffic-Related Air Pollution and Greenery with Academic Outcomes among Primary Schoolchildren. Environ. Res. 2021, 199, 111325. [Google Scholar] [CrossRef]
  42. 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]
  43. 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]
  44. Flouri, E.; Papachristou, E.; Midouhas, E. The Role of Neighbourhood Greenspace in Children’s Spatial Working Memory. Br. J. Educ. Psychol. 2019, 89, 359–373. [Google Scholar] [CrossRef]
  45. Hodson, C.B.; Sander, H.A. Green Urban Landscapes and School-Level Academic Performance. Landsc. Urban Plan. 2017, 160, 16–27. [Google Scholar] [CrossRef]
  46. Hystad, P.; Payette, Y.; Noisel, N.; Boileau, C. Green Space Associations with Mental Health and Cognitive Function: Results from the Quebec CARTaGENE Cohort. Environ. Epidemiol. 2019, 3, e040. [Google Scholar] [CrossRef] [PubMed]
  47. Jin, X.; Shu, C.; Zeng, Y.; Liang, L.; Ji, J.S. Interaction of Greenness and Polygenic Risk Score of Alzheimer’s Disease on Risk of Cognitive Impairment. Sci. Total Environ. 2021, 796, 148767. [Google Scholar] [CrossRef] [PubMed]
  48. Kuo, M.; Browning, M.H.E.M.; Sachdeva, S.; Lee, K.; Westphal, L. Might School Performance Grow on Trees? Examining the Link Between “Greenness” and Academic Achievement in Urban, High-Poverty Schools. Front. Psychol. 2018, 9, 1669. [Google Scholar] [CrossRef]
  49. Kuo, M.; Klein, S.E.; HEM Browning, M.; Zaplatosch, J. Greening for Academic Achievement: Prioritizing What to Plant and Where. Landsc. Urban Plan. 2021, 206, 103962. [Google Scholar] [CrossRef]
  50. Kweon, B.-S.; Ellis, C.D.; Lee, J.; Jacobs, K. The Link between School Environments and Student Academic Performance. Urban For. Urban Green. 2017, 23, 35–43. [Google Scholar] [CrossRef]
  51. Lega, C.; Gidlow, C.; Jones, M.; Ellis, N.; Hurst, G. The Relationship between Surrounding Greenness, Stress and Memory. Urban For. Urban Green. 2021, 59, 126974. [Google Scholar] [CrossRef]
  52. Leung, W.; Yee Tiffany Tam, T.; Pan, W.-C.; Wu, C.-D.; Candice Lung, S.-C.; Spengler, J.D. How Is Environmental Greenness Related to Students’ Academic Performance in English and Mathematics? Landsc. Urban Plan. 2019, 181, 118–124. [Google Scholar] [CrossRef]
  53. Sivarajah, S.; Smith, S.M.; Thomas, S.C. Tree Cover and Species Composition Effects on Academic Performance of Primary School Students. PLoS ONE 2018, 13, e0193254. [Google Scholar] [CrossRef]
  54. Ward, J.S.; Duncan, J.S.; Jarden, A.; Stewart, T. The Impact of Children’s Exposure to Greenspace on Physical Activity, Cognitive Development, Emotional Wellbeing, and Ability to Appraise Risk. Health Place 2016, 40, 44–50. [Google Scholar] [CrossRef]
  55. Wu, C.-D.; McNeely, E.; Cedeño-Laurent, J.G.; Pan, W.-C.; Adamkiewicz, G.; Dominici, F.; Lung, S.-C.C.; Su, H.-J.; Spengler, J.D. Linking Student Performance in Massachusetts Elementary Schools with the “Greenness” of School Surroundings Using Remote Sensing. PLoS ONE 2014, 9, e108548. [Google Scholar] [CrossRef]
  56. Zhu, A.; Yan, L.; Shu, C.; Zeng, Y.; Ji, J.S. APOE Ε4 Modifies Effect of Residential Greenness on Cognitive Function among Older Adults: A Longitudinal Analysis in China. Sci. Rep. 2020, 10, 82. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Zijlema, W.L.; Triguero-Mas, M.; Smith, G.; Cirach, M.; Martinez, D.; Dadvand, P.; Gascon, M.; Jones, M.; Gidlow, C.; Hurst, G.; et al. The Relationship between Natural Outdoor Environments and Cognitive Functioning and Its Mediators. Environ. Res. 2017, 155, 268–275. [Google Scholar] [CrossRef] [PubMed]
  58. Carroll, M.; Townshend, J.; Hansen, M.; DiMiceli, C.; Sohlberg, R.; Wurster, K. MODIS Vegetative Cover Conversion and Vegetation Continuous Fields. In Land Remote Sensing and Global Environmental Change: NASA’s Earth Observing System and the Science of ASTER and MODIS; Ramachandran, B., Justice, C.O., Abrams, M.J., Eds.; Remote Sensing and Digital Image Processing; Springer: New York, NY, USA, 2010; pp. 725–745. ISBN 978-1-4419-6749-7. [Google Scholar]
  59. Huete, A.; Didan, K.; Miura, T.; Rodriguez, E.P.; Gao, X.; Ferreira, L.G. Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices. Remote Sens. Environ. 2002, 83, 195–213. [Google Scholar] [CrossRef]
  60. Jimenez, M.P.; DeVille, N.V.; Elliott, E.G.; Schiff, J.E.; Wilt, G.E.; Hart, J.E.; James, P. Associations between Nature Exposure and Health: A Review of the Evidence. Int. J. Environ. Res. Public Health 2021, 18, 4790. [Google Scholar] [CrossRef]
  61. Kim, J.; Basak, J.M.; Holtzman, D.M. The Role of Apolipoprotein E in Alzheimer’s Disease. Neuron 2009, 63, 287–303. [Google Scholar] [CrossRef]
  62. Mason, L.; Ronconi, A.; Scrimin, S.; Pazzaglia, F. Short-Term Exposure to Nature and Benefits for Students’ Cognitive Performance: A Review. Educ. Psychol. Rev. 2021, 34, 609–647. [Google Scholar] [CrossRef]
  63. Cassarino, M.; Setti, A. Environment as ‘Brain Training’: A Review of Geographical and Physical Environmental Influences on Cognitive Ageing. Ageing Res. Rev. 2015, 23, 167–182. [Google Scholar] [CrossRef]
  64. Chen, X.; Lee, C.; Huang, H. Neighborhood Built Environment Associated with Cognition and Dementia Risk among Older Adults: A Systematic Literature Review. Soc. Sci. Med. 2021, 292, 114560. [Google Scholar] [CrossRef]
  65. Carlson, M.D.A.; Morrison, R.S. Study Design, Precision, and Validity in Observational Studies. J. Palliat. Med. 2009, 12, 77–82. [Google Scholar] [CrossRef]
  66. Tucker, C.J. Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sens. Environ. 1979, 8, 127–150. [Google Scholar] [CrossRef]
  67. Huang, S.; Tang, L.; Hupy, J.P.; Wang, Y.; Shao, G. A Commentary Review on the Use of Normalized Difference Vegetation Index (NDVI) in the Era of Popular Remote Sensing. J. For. Res. 2021, 32, 1–6. [Google Scholar] [CrossRef]
  68. Reid, C.E.; Kubzansky, L.D.; Li, J.; Shmool, J.L.; Clougherty, J.E. It’s Not Easy Assessing Greenness: A Comparison of NDVI Datasets and Neighborhood Types and Their Associations with Self-Rated Health in New York City. Health Place 2018, 54, 92–101. [Google Scholar] [CrossRef] [PubMed]
  69. Knobel, P.; Dadvand, P.; Maneja-Zaragoza, R. A Systematic Review of Multi-Dimensional Quality Assessment Tools for Urban Green Spaces. Health Place 2019, 59, 102198. [Google Scholar] [CrossRef] [PubMed]
  70. Bosco, A.; Spano, G.; Caffò, A.O.; Lopez, A.; Grattagliano, I.; Saracino, G.; Pinto, K.; Hoogeveen, F.; Lancioni, G.E. Italians Do It Worse. Montreal Cognitive Assessment (MoCA) Optimal Cut-off Scores for People with Probable Alzheimer’s Disease and with Probable Cognitive Impairment. Aging Clin. Exp. Res. 2017, 29, 1113–1120. [Google Scholar] [CrossRef]
  71. Nasreddine, Z.S.; Phillips, N.A.; Bédirian, V.; Charbonneau, S.; Whitehead, V.; Collin, I.; Cummings, J.L.; Chertkow, H. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool for Mild Cognitive Impairment. J. Am. Geriatr. Soc. 2005, 53, 695–699. [Google Scholar] [CrossRef]
  72. Caffò, A.; Lopez, A.; Spano, G.; Stasolla, F.; Serino, S.; Cipresso, P.; Riva, G.; Bosco, A. The Differential Effect of Normal and Pathological Aging on Egocentric and Allocentric Spatial Memory in Navigational and Reaching Space. Neurol. Sci. 2020, 41, 1741–1749. [Google Scholar] [CrossRef]
  73. Lopez, A.; Germani, A.; Tinella, L.; Caffò, A.O.; Postma, A.; Bosco, A. The Road More Travelled: The Differential Effects of Spatial Experience in Young and Elderly Participants. Int. J. Environ. Res. Public Health 2021, 18, 709. [Google Scholar] [CrossRef]
Figure 1. Flowchart for selection process of articles.
Figure 1. Flowchart for selection process of articles.
Ijerph 19 11700 g001
Table 1. Main characteristics of the studies.
Table 1. Main characteristics of the studies.
Authors, YearStudy DesignCountryContinentStudy PopulationSample PopulationLevel of GreenspaceGreenspace IndicatorOutcomeOutcome AssessmentCovariatesMediation and Effect ModifiersStatistical AnalysesMain Result
Claesen et al., 2021 [41]Cross-sectionalAustraliaOceaniaChildren851 primary schoolsSchool surrounding greennessNDVIAcademic achievementNAPLAN scores
  • School sector
  • NAPLAN test format
  • Number of girls’ enrolments
  • Number of boys’ enrolments
  • FTE of enrolled students
  • FTE of teaching staff enrolments area
  • Level of socioeconomic status for each school
Mediating role of TRAPGeneralized linear modelsAssociation between NDVI and reading scores for students in years 3 and 5 in all buffers (except 2000 m, Year 3)
Association between NDVI and numeracy scores in years 3 and 5 for all buffers and grammar/punctuation scores in year 5 for all buffers
Inverse associations between NDVI and spelling scores in years 3 and 5 for all buffers (except the school polygon)

No association between NDVI and writing scores
Dadvand et al., 2015 [33]LongitudinalSpainEuropeChildren2593 childrenResidential surrounding greenness
Commuting greenness
School greenness
NDVIAttention/EFN-back task
ANT
  • Age
  • Sex
  • SES at individual level
  • SES at area level
Mediating role of TRAPLinear mixed-effect modelsAssociation between 12 mo progress in WM/superior WM/attention and greenness within school/surrounding school
Association between 12 mo progress in WM/superior WM/attention and total surrounding greenness
Association between 12 mo progress in WM and commuting greenness
No association between residential surrounding greenness and WM/superior WM/attention at baseline or progress
Dadvand et al., 2017 [34]LongitudinalSpainEuropeChildren1527 childrenResidential surrounding greennessNDVI
VFC
Attention/EFK-CPT
ANT
  • Age
  • Sex
  • Term birth
  • Maternal cognitive performance
  • Maternal smoking during pregnancy
  • Exposure to environmental tobacco smoke
  • SES at individual level
  • SES at area level
  • Urban vulnerability index
/Mixed-effect modelsIncreases in residential surrounding greenness (NDVI) were associated with lower K-CPT omission and HRT-SE at 4–5 y and lower ANT HRT-SE at 7 y
No association between K-CPT commission errors and ANT omission or commission errors
Dadvand et al., 2018 [35]LongitudinalSpainEuropeChildren253 childrenResidential surrounding greennessNDVIAttention/EF3D MRIs
ANT
2-back tasks
3-back tasks
  • Maternal education
  • SES
/Linear mixed-effects modelAssociation between residential surrounding greenness and volumes in several brain regions
Association between some of these regions and WM or superior WM or inattentiveness
Flouri et al., 2019 [44]Cross-sectionalEnglandEuropeChildren4758 childrenNeighborhood greenspaceData from Multiple Environmental Deprivation Index (MEDIx)MemoryCANTAB SWM task
  • SES
  • Neighborhood history
  • Neighborhood deprivation
  • Gender
  • Age
Neighborhood greenspace * Neighborhood deprivationMultilevel linear modelAssociation between neighborhood greenspace and SWM (b = 0.793; SE = 0.384; 95%; CI: −1.545, −0.041)
Hodson t al., 2017 [45]Cross-sectionalUSAAmericaChildren222 primary schoolsSchool greennessAverage percent canopy cover
Average percent impervious surfaces
Grass/Shrub cover
Academic achievementMCA
  • SES
  • ELL
  • Lunch
/Ordinary least squares regression modelsAssociation between canopy and reading (b = 0.26846; t-value = 2.572)
No association between canopy and mathematics score
No association between grass or shrub and reading or math score
Jimenez et al., 2022 [37]LongitudinalUSAAmericaChildren857 mother–child pairsResidential surrounding greennessNDVIGlobal cognitionPPVT-III
WRAVMA
WRAML2
KBIT-2
  • Sex
  • Race
  • Age
  • Mother’s intelligence
  • Parent’s education
  • Annual household income at enrollment
  • Neighborhood median annual income
  • Neighborhood population density
Air PollutionPhysical ActivityGeneralized additive modelsGreenness at early childhood was associated with visual memory (0.76; 95%; CI: 0.21–1.32)
Kuo et al., 2018 [48]Cross-sectionalUSAAmericaChildren318 public schools School and neighborhood greennessTree canopy cover
Grass/shrub cover
Academic achievementISAT assessment
  • Disadvantage
  • Bilingual
  • Number of students
  • % female
  • pupil/teacher ratio
School greenness * Disadvantage Neighborhood greenness * DisadvantageGeneralized linear modelsAssociation between school trees and math scores (b = 0.22; SE = 0.10)

Marginally significant association between school tree and reading scores
No association between neighborhood trees and math scores/reading scores
Kuo et al., 2021 [49]Cross-sectionalUSAAmericaChildren450 public schools School greennessNDVI
Tree canopy cover
Academic achievementWashington Measurements of Student Progress Assessment
  • Race/ethnicity
  • Poverty
  • Transitional bilingual status
  • Sex
  • Special education
  • Section 504 status
  • Students per teacher
  • Average years of educational experience among teachers
  • The percentage of teachers with master’s degrees
  • School enrollment and location (urban, suburban, or rural)
/Multivariate analysesTree canopy within 250 m of a school predicted better performance in both reading (coeff = 0.117, p = 0.000) and math (coeff = 0.134, p = 0.134), as well total greenness within 250 m (reading coeff = 0.131, p = 0.036; math coeff = 0.179, p = 0–0.39), and tree canopy within 1000 m (reading coeff = 0.068, p = 0.017; math coeff = 0.079, p = 0–0.47).
At the 1000 m buffer size, total greenness does not predict achievement
Tree canopy predict achievement when total greenness was controlled (reading coeff = 0.161, p = 0.001; math coeff = 0.153, p = 0.020)
Tree canopy at 250 m was significant for reading and math even when tree cover at 1000 m was controlled (reading coeff = 0.174, p = 0.001; math coeff = 0.187, p = 0.012)
Kweon et al., 2017 [50]Cross-sectionalUSAAmericaChildren219 public elementary and secondary schools and learning center School greennessLand cover variablesAcademic achievementDC Comprehensive Assessment System
  • SES
  • Enrollment
  • Student/Teacher Ratio
  • Race/Ethnicity
/Linear regression analysesAssociation between trees (%) and mathematics (b = 0.23; p = 0.005)/reading tests (b = 0.22; p = 0.006).
No association between grass or shrubs (%) and reading/mathematics
Leung et al., 2019 [52]Cross-sectionalUSAAmericaChildren2749 childrenGreenness surrounding schoolNDVI
Green land use
Academic achievementMCAS test
  • Sex
  • Student-teacher ratio
  • Financial status
  • Language ability
  • Race and ethnicity
/Generalized linear mixed modelsExcept the result of green land use of ELA in 250 m buffer, associations were all significantly (p < 0.05) positive for surrounding greenness and academic performance (AP%/CPI)
Ward et al., 2016 [54]Cross-sectionalNew ZealandOceaniaChildren108 childrenGreenspaceTime spent in GSGlobal cognitionCNS-VS
  • Sex
  • Age
  • School
/Generalized linear mixed modelsSignificant results not found
Wu et al., 2014 [55]Cross-sectionalUSAAmericaChildren905 schoolsGreenness of school surroundingNDVIAcademic achievementMCAS
  • Gender
  • Race
  • English as a second language
  • Family income level
  • Student/teacher ratio
  • School attendance
  • Country of schools
/Spatial Generalized linear mixed modelsSignificant association (p < 0.01) between surrounding greenness in March and academic achievement in English and math for all buffers.
Considering July and October, students with higher exposure to greenness for the balance of the year (even in summer) show better academic performance, too, with most of the estimates showing statistically significant results (p. 0.05)
Sivarajah et al., 2018 [53]Cross-sectionalUSAAmericaChildren387 elementary schoolsVegetation around schoolTotal land area (m2)
Total soft surface (m2)
Tree canopy cover (m2)
Percentage tree cover
Academic achievementStudent performance
  • Socio-demographic
  • Economic factors
tree cover * LOIGeneralized Linear ModelsSignificant results not found
Bijnens et al., 2022 [39]Cross-sectionalBelgiumEuropeAdolescents596 adolescentsResidential surrounding greenspace
School surrounding greenspace
Proximity to accessible greenspace
Land cover data from the Agency for Geographic Information FlandersAttention/EFStroop Test
Continuous Performance Test
  • Age
  • Sex
  • Education level mother
  • Area deprivation index
Multiple linear regressionLogistic regression modelThe association was found between the higher total and high greenspace (at 2000 m radius) with a shorter reaction time on Stroop Test and the CPT.
An increase of 13% in greenspace (within a 2000 m radius) is associated with a 35% lower risk of a mean reaction time longer than 536 ms on the Stroop Test and with a 24% lower risk of a mean reaction time longer than 1476 ms on the CPT
Cerin et al., 2021 [40]Cross-sectionalAustraliaOceaniaAdults4141 adultsParkland in residential bufferPercentage of parkland in residential bufferMemoryCVLT
SDMT
  • Age
  • Sex
  • English-speaking background
  • Educational attainment
  • Population density
  • Percentage of commercial land use
  • Land-use mix (five noncommercial land uses)
  • Area-level IRSAD
  • Residential self-selection related to recreational facilities
/Generalized additive mixed models The percentage of parkland in residential buffer was associated with better performance in memory and processing speed in total and direct-effect model
Lega et al., 2021 [51]Cross-sectionalEnglandEuropeAdults185 adultsResidential surrounding greennessNDVIMemoryFDS
BDS
TDS
  • Gender
  • Educational level
  • Deprivation
  • Frequency of visits to natural environments
  • Age
Mediating role of stressLinear univariate regressionAssociation between surrounding greenness and FDS (b = 0.45, 95% CI: 12.59, 21.10)
Association between surrounding greenness and TDS (b = 0.34, 95% CI: 10.50, 26.12)

No association between surrounding greenness and BDS
Dzhambov et al., 2019 [43]Cross-sectionalBulgariaEuropeAdults111 adultsResidential surrounding greennessNDVIGlobal cognitionCERAD-NB
MoCA
  • Sex
  • Age
  • Education
  • Smoking
  • Alcohol consumption
  • Waist circumference
  • Blood pressure
  • Road traffic day-evening-night noise
Mediating role of waist circumference, systolic blood pressure, total cholesterol, air pollution, glucose, NO2, and LdenMultivariate linear regression modelsAssociation between NDVI and CERAD-NB and MoCA, especially for NDVI 100 m
Zijlema et al., 2017 [57]Cross-sectionalSpain
Lithuania
Netherlands
England
EuropeAdults1628 adultsResidential surrounding greennessNDVI
Distance to NOE
Attention/EFCTT
  • Age
  • Sex
  • Educational level
  • Neighborhood socioeconomic status
  • Time spent away from home
  • CTT test quality
Mediating role of physical activity, social interaction, loneliness, neighborhood social cohesion, perceived mental health, traffic noise, worry about air pollutionLinear and logistic multilevel modelsAssociation between residential distance to NOE (per 100 m) and CTT time (b = 1.50; 95%, CI: 0.13–2.89)
No association between other indicators of NOE and CTT (time or errors)
Hystad et al., 2019 [46]Cross-sectionalCanadaAmericaAdults6658 adultsResidential surrounding greennessNDVIAttention/EFPaired associated learning
Reaction time
Verbal and numeric reasoning
  • Year and month of completion of baseline questionnaire
  • Age
  • Sex at birth (male/female)
  • Household income
  • Education level
  • White/nonwhite
  • Marital status
  • Population density
/Linear and logistic regression modelsSignificant results not found
Crous-Bou et al., 2020 [42]Cross-sectionalSpainEuropeAdults958 adultsResidential surrounding greennessNDVIGlobal cognitionMBT
WAIS-IV
PACC
  • Age
  • Gender
  • Years of education
/General linear modelsSignificant results not found
De Keijzer et al., 2017 [36]LongitudinalSpainEuropeOlder adults6506 older adultsResidential surrounding greennessNDVI
EVI
Global cognitionAlice Heim 4
S-words test
Animal names test
Free recall test
  • Age
  • Gender
  • Ethnicity
  • Alcohol use
  • Diet
  • Smoking
  • Education
  • IMD
  • IMD employment
  • SES
  • Socioeconomic status
  • Employment grade
Mediation role of physical activities, air pollution and social supportMixed-effects model with repeated measuresAn IQR increase in NDVI in a 500 m buffer was associated with a difference in the global cognition score of 0.020 (95% CI: 0.003, 0.037) over 10 years
An IQR increase in NDVI in the 500 m buffer was associated with a difference in the reasoning z-score of 0.022 (95% CI: 0.007, 0.038) and with a difference of 0.021 (95% CI: 0.002, 0.040) in the fluency z-score over 10 years
A positive baseline association between residential surrounding greenness and reasoning (b: 0.021; 95% CI: 0.003, 0.038)
Jin et al., 2021 [47]Cross-sectionalChinaAsiaOlder adults1349 older adultsResidential surrounding greennessNDVIGlobal cognitionChinese version of MMSE
  • Smoking
  • Drinking
  • Physical activities
  • Dietary diversity
  • ADL
  • Leisure activity score
  • Seven kinds of self-reported disease (diabetes, heart disease, stroke, hypertension, chronic obstructive pulmonary disease, tuberculosis, and cancer)
Interaction between NDVI and AD-PRS on cognitive functionMultivariate logistic regression Linear regression model Highest contemporaneous NDVI was associated with lower odds of cognitive impairment (Quartile 3: OR: 0.49, 95% CI: 0.31, 0.80, Quartile 4: OR: 0.62, 95% CI: 0.38, 0.99)
0.1-unit of contemporaneous average NDVI was associated with 9% lower odds (95% CI: 0.85, 0.99) of cognitive impairment and 0.28-point higher MMSE score (95% CI: 0.01, 0.56)
No significant association was found between annual average of NDVI and cognitive impairment or MMSE
Zhu et al., 2019 [38]LongitudinalChinaAsiaOlder adults19,726; 38,327 older adultsResidential surrounding greennessNDVIGlobal cognitionMMSE
  • Age
  • Gender
  • Ethnicity
  • Marital status
  • Urban/rural residence
  • Education
  • Occupation
  • Financial support
  • Social and leisure activity
  • Smoking status
  • Alcohol consumption
  • Physical activity
  • Time to reflect the number of years for each follow-up
/Linear regressionLogistic regression Linear mixed-effects regression Mixed-effects logistic regression modelsA 0.1-unit increase in NDVI was associated with a 0.23-point increase in MMSE score (95% CI 0.16 to 0.29) and an OR of 0.94 (95% CI 0.92 to 0.96) of having cognition impairment
Participants living in areas with a decrease in greenness had an OR of 1.25 (95% CI 1.18 to 1.34) of a decrease in MMSE, and an OR of 0.90 (95% CI 0.84 to 0.96) of an increase in MMSE in the longitudinal analysis
There was a significantly weak association (coefficient 0.069, 95% CI 0.0048 to 0.13) between NDVI and changes in MMSE
Zhu et al., 2020 [39]Cross-sectionalChinaAsiaOlder adults6994 older adultsResidential surrounding greennessNDVIGlobal cognitionMMSE
  • Age
  • Gender
  • Ethnicity
  • Marital status
  • Urban/rural residence
  • Education
  • Occupation
  • Financial support
  • Social and leisure activity
  • Smoking status
  • Alcohol consumption
  • Physical activity
Moderation role of APOEGeneralized estimating equations Older adults living in the highest quartile had 15% (95% CI: 0.75, 0.97) lower odds of cognitive impairment
The association between residential greenness and cognitive function also differed by the age group
The effect was significant only among the people aged 65 to 79 years (OR of the highest quartile of NDVI: 0.76, 95% CI: 0.62, 0.93)
Note: NDVI = Normalized Difference Vegetation Index; IQ = Intelligence Quotient; WISC III = Wechsler Intelligence Scale for Children-III; CI = Confidence Interval; IQR = Interquartile Range; NAPLAN score = National Assessment Program—Literacy and Numeracy score; FTE = Full Time Equivalent; TRAP = Traffic Related Air Pollution; ANT = Attentional Network Task; WM = Working Memory; VFC = Vegetation Continuous Field; K-CPT = Conners’ Kiddie Continuous Performance Test; SES = Socio-Economic Status; HRT-SE = Hit Reaction Time Standard Error; 3D-MRI = Three dimensional Magnetic Resonance Imaging; MEDIx = Multiple Environmental Deprivation Index; CANTAB = Cambridge Neuropsychological Test Automated Battery SWM task = Spatial Working Memory task; MCA = Minnesota Comprehensive Assessment; ELL = English language learners; PPVT-III = Peabody Picture Vocabulary Test; WEAVMA = Wide Range Assessment of Visual-Motor Abilities; WRAML2 = Wide Range Assessment of Memory and Learning; KBIT-2 = Kaufman Brief Intelligence Test; ISAT = Illinois State Board of Education’s Illinois Standardized Assessment Test; DC = District of Columbia; Kedi-WISC = Korean Educational Development Institute-Wechsler Intelligence Scale for Children; ETS = Exposure to Environmental Tobacco Smoke; NO2 = Nitrogen Dioxide; MCAS = Massachusetts Comprehensive Assessment System; AP = Proficient and Higher; CPI = Composite Performance Index; ELA = English Language Arts; WIPPSI-R = Wechsler Preschool and Primary Scale of Intelligence-Revised; WISC IV = Wechsler Intelligence Scale for Children-IV; WAIS IV = Wechsler Adults Intelligence Scale-IV; GS = Greenspace; CNS-VS = CNS visual signs; LOI = Learning Opportunity Index; CPT = Continuous Performance Test; CVLT = California Verbal Learning Test; SDMT = Symbol-Digit Modalities Test; FDS = Forward Digit Span; BDS = Backward Digit Span; TDS = Total Digit Span; CERAD-NB = Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Battery; MoCA = Montreal Cognitive Assessment; Lden = Road traffic day-evening-night noise; NOE = Natural Outdoor Environment; CTT = Color Trails Test; MBT = Memory Binding Test; PACC = Preclinical Alzheimer Cognitive Composite; EVI = Enhanced Vegetation Index; IMD = Index of Multiple Deprivation; MMSE = Mini Mental State Examination; OR = Odds Ratio; AD-PRS = Alzheimer Disease Polygenic Risk Score; APOE = Apolipoprotein E.
Table 2. Associations between greenness and cognitive functions classified according to the Bayesian average method.
Table 2. Associations between greenness and cognitive functions classified according to the Bayesian average method.
Authors, YearSignificant ResultTotal Number of ResultspnBayes
Average
Association
Claesen et al., 2021 [41]32500.64500.63Medium
Dadvand et al., 2015 [33]10300.33300.35Medium
Dadvand et al., 2017 [34]28360.78360.75Strong
Dadvand et al., 2018 [35]790.7890.68Strong
Flouri et al., 2019 [44]111.0010.58Medium
Hodson et al., 2017 [45]160.1760.29Small
Jimenez et al., 2022 [37]280.2580.32Small
Kuo et al., 2018 [48]140.2540.36Medium
Kuo et al., 2021 [49]10160.63160.59Medium
Kweon et al., 2017 [50]240.5040.49Medium
Leung et al., 2019 [52]31320.97320.91Strong
Ward et al., 2016 [54]010.0010.38Medium
Wu et al., 2014 [55]20240.83240.78Strong
Sivarajah et al., 2018 [53]040.0040.24Small
Bijnens et al., 2022 [39]5360.14360.17Small
Cerin et al., 2021 [40]441.0040.74Strong
Lega et al., 2021 [51]230.6730.55Medium
Dzhambov et al., 2019 [43]10101.00100.85Strong
Zijlema et al., 2017 [57]150.2050.32Small
Hystad et al., 2019 [46]030.0030.27Small
Crous-Bou et al., 2021 [42]030.0030.27Small
De Keijzer et al., 2017 [36]8160.50160.49Medium
Jin et al., 2021 [47]4160.25160.29Small
Zhu et al., 2019 [38]6160.38160.39Medium
Zhu et al., 2020 [39]240.5040.49Medium
Table 3. Frequencies of small association, medium association, and strong association for the age groups, and within each age group for each cognitive domain.
Table 3. Frequencies of small association, medium association, and strong association for the age groups, and within each age group for each cognitive domain.
Age Group: AllSmallMediumStrong
Children474
Adults312
Older adults130
Age Group: Children and AdolescentsSmallMediumStrong
Attention/EF112
Memory010
Global cognition110
Academic achievement242
Age Group: AdultsSmallMediumStrong
Global cognition101
Memory011
Attention/EF200
Age Group: Older adultsSmallMediumStrong
Global cognition130
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Ricciardi, E.; Spano, G.; Lopez, A.; Tinella, L.; Clemente, C.; Elia, G.; Dadvand, P.; Sanesi, G.; Bosco, A.; Caffò, A.O. Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review. Int. J. Environ. Res. Public Health 2022, 19, 11700. https://doi.org/10.3390/ijerph191811700

AMA Style

Ricciardi E, Spano G, Lopez A, Tinella L, Clemente C, Elia G, Dadvand P, Sanesi G, Bosco A, Caffò AO. Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review. International Journal of Environmental Research and Public Health. 2022; 19(18):11700. https://doi.org/10.3390/ijerph191811700

Chicago/Turabian Style

Ricciardi, Elisabetta, Giuseppina Spano, Antonella Lopez, Luigi Tinella, Carmine Clemente, Giuseppe Elia, Payam Dadvand, Giovanni Sanesi, Andrea Bosco, and Alessandro Oronzo Caffò. 2022. "Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review" International Journal of Environmental Research and Public Health 19, no. 18: 11700. https://doi.org/10.3390/ijerph191811700

APA Style

Ricciardi, E., Spano, G., Lopez, A., Tinella, L., Clemente, C., Elia, G., Dadvand, P., Sanesi, G., Bosco, A., & Caffò, A. O. (2022). Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review. International Journal of Environmental Research and Public Health, 19(18), 11700. https://doi.org/10.3390/ijerph191811700

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