Biodiversity in Urban Green Spaces and Human Health: Systematic Review

BMC Public Health
https://doi.org/10.1186/s12889-026-28039-z
Article in Press
Does the biodiversity of urban green spaces
impact on human health? A systematic review of
literature
Nicola Pelizzari, Carlotta Alias, Michela Tiboni, Anna Bertolazzi & Claudia Zani
Received: 12 January 2026
Accepted: 29 May 2026
Cite this article as: Pelizzari N., Alias C.,
Tiboni M. et al. Does the biodiversity of
urban green spaces impact on human
health? A systematic review of literature.
BMC Public Health (2026). https://doi.
org/10.1186/s12889-026-28039-z
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Does the biodiversity of urban green spaces impact on human health?
A systematic review of literature
Nicola Pelizzari1, Carlotta Alias1, Michela Tiboni2, Anna Bertolazzi2, Claudia
Zani1*
1 Department of Medical and Surgical Specialties, Radiological Sciences and
Public Health, University of Brescia, Brescia, Italy.
2
Department of Civil, Environmental, Architectural Engineering and
Mathematics, University of Brescia, Brescia, Italy.
* Corresponding author ([email protected])
ABSTRACT
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Green spaces and their biodiversity seem to improve the urban life quality.
However, a wide range of descriptors were associated with multiple health
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outcomes, which limits the comparability of existing evidence.
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The objective of this systematic review was to organise this knowledge,
investigating the relationship between biodiversity in urban green spaces and
health outcomes in adults. Following PRISMA guidelines and a registered
protocol (PROSPERO: CRD42025636281), a search of PubMed, Scopus, Web
of Science identified studies published between January 2014 and July 2025.
The search strategy (“biodiversity” AND “human health” AND “urban green
space”) yielded 147 eligible studies. Most were published between 2017 and
2020 (57%) and predominantly relied on medium-sized cohorts of 101–10,000
participants (55%). Health outcomes fell into four categories: (i) general
health, mental health, and well-being; (ii) drug prescriptions; (iii) chronic
diseases (cardiovascular disease, T2 diabetes, obesity); and (iv) birth
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outcomes. Green exposure was primarily assessed through vegetation-based
indicators: 66.1% of studies used green-exposure metrics (tree canopy or
vegetation cover), 34.0% NDVI, and 22.4% percentage green area. Only a
minority incorporated composite ecological indices or fauna-based metrics
(bird or insect richness). Across all health domains, findings were
predominantly favourable. Between 70% and 90% of studies on general
health, mental health, and well-being reported beneficial associations with
green exposure, including improved self-rated health, reduced depressive
and anxiety symptoms, lower stress, and increased life satisfaction. All
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studies using drug prescription data found inverse associations between
green exposure and antidepressant or anxiolytic prescriptions. Evidence for
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chronic diseases consistently indicated protective associations: reduced
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cardiovascular and respiratory disease risk, prevalence of T2 diabetes, and
all-cause mortality. Birth outcomes demonstrated more variability, with half
of the studies reporting positive associations, largely influenced by
socioeconomic and contextual factors. Socioeconomic status frequently
modified associations, with stronger positive effects observed among lowerSES populations.
The overall evidence indicates that richness of urban green spaces is
associated with health benefits. However, the role of biodiversity remains
unclear and understudied, mostly due to inconsistent measurements and
ambiguous associations with health outcomes.
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Integrating ecological quality into urban planning may therefore represent
an important strategy for promoting healthier and more equitable urban
environments.
Keywords
Biodiversity; Well-being; Environmental quality; Urban green space; Human
health outcomes
1. Introduction
Current projections indicate that by the year 2050, approximately 70% of the
global population will be residing in urban areas [1]. There is broad
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consensus that the presence and creation of green spaces has the potential
to enhance the quality of life for citizens living in urban settings [2].
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Urban characteristics, such as the extent and accessibility of green areas,
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and the quantity and quality of tree cover have been demonstrated to be
associated with population health [3, 4]. Furthermore, there is a consistent
evidence base that suggests that spending time in urban green spaces has a
positive effect on well-being [5, 6]. However, several aspects of health
promotion
remain
insufficiently
addressed
within
urban
planning
frameworks, such as the enhancement of green spaces in terms of
biodiversity [7–9]. This constitutes a health-promoting characteristic of
natural environments and a key asset for urban public health [10–12]. Indeed,
the lack of biodiversity in green areas is a factor that may increase the risk
of disease transmission and other adverse health outcomes [2, 13].
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Several mechanisms may explain the health benefits of green areas, including
psychological restoration and stress reduction, increased levels of physical
activity among populations living near parks, reduced exposure to air
pollution, noise, and heat, and enhanced resilience to pollution and climate
change [8, 14]. Numerous studies show that higher biodiversity in urban
green spaces, whether plant or animal, has favourable effects on mental
health, inflammatory processes, several chronic degenerative diseases, and
birth outcomes [15–17].
Health effects of green spaces can be assessed using several methodological
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approaches. Surveys and interviews enable subjective evaluations, whereas
biological sampling (e.g., salivary cortisol) allows the measurement of
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physiological stress responses that may persist for hours after awakening in
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individuals exposed to green environments [18, 19]. Health-service indicators
such as antidepressant prescriptions have also been proposed as useful
population-level measures with implications for prevention and urban
planning [20].
A substantial body of research has examined the health effects of exposure
to green spaces or green areas biodiversity. These studies have utilised a
wide range of indicators (e.g., frequency of use, types of activities performed,
time spent in urban green areas and Normalized Difference Vegetation Index
(NDVI), plant or bird richness, respectively) and have been associated with
multiple health outcomes. This has limited the comparability of existing
evidence, as recently reviewed by Robinson and colleagues [21]. This
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variability underscores the need for a structured synthesis of current findings
that distinguishes biodiversity from green-space exposure and examines their
respective contributions to human health.
Based on these considerations, this systematic review aimed to: (i) ascertain
whether a relationship exists between urban green-space biodiversity and
human health outcomes in adults aged 18 years and older; (ii) identify the
parameters
of
biodiversity
(number
and
type
of
plants,
animals,
microorganisms) most strongly associated with these outcomes; and (iii)
determine whether specific health benefits, such as improvements in general
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and mental health, reductions in chronic disease burden, and maternal–fetal
outcomes, are linked specifically to the biodiversity of green spaces, to green
exposure more broadly, or to both.
2. Methods
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This systematic review was conducted and reported in accordance with the
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
(PRISMA 2020) statement [22] and followed a predefined protocol registered
in the International Prospective Register of Systematic Reviews (PROSPERO;
protocol number CRD42025636281). The review examines the relationship
between biodiversity within urban green spaces and human health outcomes
in adults aged 18 years and older, as well as the biodiversity indicators and
health domains most frequently investigated in the literature. The completed
PRISMA 2020 27-item checklist is provided in the supplementary materials.
2.1 Research questions and PECO framework
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The primary research question guiding this review was: is there a relationship
between urban green space biodiversity and human health outcomes in
adults? Secondary aims explored which biodiversity dimensions (e.g., plant,
animal, microbial) are most strongly associated with health outcomes and
which mechanisms (e.g., exposure to microbiota, ecosystem services, or
psychosocial benefits) mediate this relationship. The research was structured
according to the PECO framework [23] to ensure conceptual clarity and
methodological consistency. The population included adults (≥18 years)
residing in urban or peri-urban areas. The exposure was the biodiversity
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level in urban green spaces, measured quantitatively or qualitatively through
indices such as species richness, Shannon Index, vegetation diversity, or
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microbial composition. The comparator was lower or alternative levels of
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exposure to biodiversity in urban green spaces, where applicable. The
outcomes
comprised
human
health
indicators,
including
morbidity,
mortality, physiological, and psychological parameters. No restriction was
applied
to
study
design;
cross-sectional,
cohort,
case-control,
and
experimental or quasi-experimental designs were all eligible.
2.2. Information sources and search strategy
Three bibliographic databases — PubMed (U.S. National Library of
Medicine), Scopus (Elsevier), and Web of Science Core Collection (Clarivate;
SCIE, SSCI, A&HCI, ESCI indexes) were searched, covering the period from
January 2014 to July 2025. The last database search was run on 08 July 2025
across all three sources. Free-text terms were combined to capture studies
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addressing biodiversity, human health, and urban environments. The general
search string applied across databases was (“biodiversity” AND “human
health” AND “urban green space”), adapted to the field-tag syntax of each
database. Full search strings for each database are provided in the
supplementary materials.
Reference lists of included articles and relevant reviews were also screened
manually to identify additional studies. Only peer-reviewed publications
written in English and available in full text with an abstract were considered
eligible.
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2.3 Eligibility criteria, study selection, and data extraction
Studies were eligible if they included adult (>18 years old) human
populations, provided a biodiversity measure in urban or peri-urban green
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spaces, and reported at least one health outcome (i.e. physiological,
psychological, or disease-related parameters). Studies were excluded if they
(i) lacked a biodiversity and/or green exposure measurement, (ii) lacked
health outcomes, (iii) were conducted exclusively in rural or marine
ecosystems, (iv) analysed allergic diseases or allergic sensitization as primary
outcomes, or (v) were not published in English. No restrictions were applied
with regard to study design or geographical area. Duplicate entries were
identified using a two-step verification system. Initially, duplicates were
manually identified and annotated. Subsequently, a secondary review was
conducted using the Zotero software [24] for reference management and
duplicate removal. Two reviewers (CA and CZ) independently screened titles,
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abstracts, and full texts according to the predefined criteria. Disagreements
were resolved through discussion or, when necessary, adjudication by a third
reviewer (NP). No automation tools were used at any stage of the screening
process. The list of records excluded at the full-text stage, with reason of
exclusion, is provided in the supplementary materials. Data extraction was
performed independently by two reviewers (CA and CZ) using a structured
form developed a priori; discrepancies in extracted data were resolved by
discussion and, when necessary, adjudicated by a third reviewer (NP).
Extracted variables included author, year of publication, country, study
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design, population characteristics, biodiversity indicators, type of urban
green space, health outcomes, and main findings. All extracted data were
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cross-checked by all authors to ensure accuracy and completeness.
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2.4 Quality assessment and data synthesis
Methodological quality and risk of bias were independently assessed by two
reviewers (CA and NP) using the JBI Critical Appraisal Checklists [17]
appropriate to each study design [18]. Each item was rated as Yes, No,
Unclear, or Not applicable, and an overall score from 0 to 1 was calculated.
Studies scoring > 0.80 were considered high quality, 0.60–0.79 moderate
quality, and < 0.59 low quality. Inter-rater agreement between the two
reviewers was evaluated by comparing the JBI appraisal outcomes assigned
to each study independently prior to consensus discussion. For each of the
147 included studies, agreement was examined on the aggregated counts of
items rated as Yes, No, Unclear, and Not applicable across the relevant JBI
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checklist (8 items for the Analytical Cross-sectional checklist, 11 items for the
Cohort checklist, and 9 items for the Quasi-Experimental checklist). The two
reviewers reached identical appraisal profiles in 134 of the 147 studies,
corresponding to a study-level concordance of 91.2%. In the remaining 13
studies (8.8%), the reviewers' counts differed by one to three items, with most
discrepancies involving the classification of a single item as Yes versus
Unclear. These differences typically concerned items that require subjective
judgement, such as the appropriateness of confounder adjustment or the
reliability of outcome measurement. Based on the observed distribution of
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disagreements across 1,287 individual appraisal items, the estimated itemlevel Cohen's κ coefficient was approximately 0.78, corresponding to
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substantial agreement (full table reported in the supplementary materials).
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This value is consistent with inter-rater agreement levels reported in previous
methodological studies that applied the JBI checklists in systematic reviews.
All disagreements were resolved through structured discussion between the
two reviewers; when consensus could not be reached, the appraisal was
independently reassessed by a third investigator (CZ) to ensure final
adjudication. Results were grouped according to biodiversity indicators,
health domains, and population or geographic characteristics. Owing to
methodological and outcome heterogeneity among the included studies, a
meta-analysis was deemed inappropriate, and findings were synthesised
narratively. Because of the heterogeneity of exposure metrics and outcome
definitions across the included studies, effect measures varied widely. To
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allow a consistent summary across such heterogeneous measures, direction
of association (positive, neutral, or negative) was extracted for each study
and used as a summary indicator for the narrative synthesis. No formal
subgroup analyses or sensitivity analyses were pre-specified; exploratory
comparisons across outcome domains, biodiversity indicators, and population
subgroups are presented descriptively in the results section. A formal
assessment of publication or reporting bias was not feasible because no metaanalysis was performed; this aspect is discussed qualitatively among the
limitations of the review. Similarly, the certainty of the body of evidence was
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not formally graded because of the narrative nature of the synthesis and the
heterogeneity
of
exposure
and
outcome
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assessment;
study-level
methodological quality was instead appraised with the JBI checklists as
described above.
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3. Results
A total of 147 studies met the inclusion criteria and were included in the
review. A flow diagram of the study selection procedure is reported in Figure
1. The main characteristics, relevant data (such as study design, population
and exposure) and results of each study were extracted and reported in the
supplementary materials.
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Fig. 1 PRISMA flow diagram.
The methodological quality of the included studies was high overall, with JBI
scores ranging from 0.62 to 1.00 (median = 1.00). The large majority (93.2%,
137/147) were classified as high quality, while 10 studies (6.8%) reached a
moderate-quality
level;
none
fell
into
the
low-quality
category
(Supplementary Figure S1). Methodological differences emerged between
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high and moderate quality studies. Among high-quality studies, 86.3% used
objective greenness indicators derived from geographic information systems
(GIS) or satellite data, and 71.9% specifically employed the normalized
difference vegetation index (NDVI). Only one moderate-quality study used
NDVI [25], while the remaining nine relied on alternative greenness metrics
or did not report objective indices. Validated clinical or mental-health
outcomes were reported in 82.7% of high-quality studies, whereas at least
90% of moderate quality studies (9/10) employed non-validated or short-term
psychological measures. Adjustment for socioeconomic status was reported
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in 93.5% of high-quality studies. Environmental co-exposures such as air
pollution or noise were considered in 43.1% of high-quality studies but in
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none of the moderate-quality studies.
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Sample sizes varied considerably, ranging from large national health
databases or population-based surveys including tens of thousands of
individuals to smaller studies with biological or questionnaire-derived
measures (tens to hundreds of participants). Most studies were national-level
investigations (106/147; 72%), while others were carried out in more than
one country. Overall, 67 studies (45.6%) employed survey designs. In terms
of
study
design,
the
majority
were
cross-sectional
(71%),
showing
associations but not causal relationships, followed by cohort studies (24%)
and experimental studies (5%).
3.1 Chronological and geographical classification
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The temporal distribution of studies showed a clear increase in publication
volume over time, covering the period from 2014 to 2025. In the early phase
(2014–2016), 33 studies were published (22.4%); during the growth phase
(2017–2019), 62 studies (42.2%); and in the most recent period (2020–2025),
52 studies (35.4%) (Figure 2A).
The peak year was 2019, with 23 publications (15.6%). A gradual decline was
observed after 2020, with only three studies published in 2024 and none in
2025. Analysis by period also indicated shifts in research focus: mental health
and well-being outcomes predominated in the early phase (21/33, 63.6%) but
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decreased proportionally in later periods (27/62, 43.5% in 2017–2019; 23/52,
44.2% in 2020–2024). Birth-related outcomes emerged primarily during
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2017–2019 (8/62, 12.9%), while cardiovascular outcomes remained relatively
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stable across all phases (15–17%).
The geographical distribution of studies showed a predominance of research
conducted in Europe (n = 70), particularly in the United Kingdom (n = 22),
followed by the United States (n = 22) and China (n = 19) (Figure 2B).
The geographical composition of the literature also changed over time. In
2014–2016, Europe accounted for 63.6% of studies (21/33) and Asia for only
9.1% (3/33). By 2020–2024, the European contribution had declined to 34.6%
(18/52), while Asian output had risen to 30.8% (16/52). North American
output remained stable at approximately 21% across all periods. Regional
differences in outcome focus were observed: studies from the United
Kingdom concentrated heavily on mental health and well-being (20/25,
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80.0%), US studies showed a more diversified profile including mental health
(9/22, 40.9%), birth outcomes (5/22, 22.7%), and cardiovascular outcomes
(4/22, 18.2%), while Chinese studies placed relatively greater emphasis on
cardiovascular outcomes (5/19, 26.3%). Studies examining medication
consumption (e.g., antidepressant prescriptions) were almost exclusively
European (8/8, 100%).
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Fig 2. Chronological and geographical distribution of selected studies. (A)
Number of studies according to the year of publication (* up to July 2025);
(B) Countries involved in the studies and number of studies per country.
3.2 Assessment of biodiversity and green exposure
Our results showed that 66.1% of the studies (97/147) reported a measure of
green exposure to evaluate different health effects, mainly using plants or
trees as biodiversity markers. Some studies assessed tree richness (i.e., the
number of different tree species), while others measured canopy tree cover
using GIS or satellite-derived data. Additional studies quantified exposure
through the percentage of greenery or the overall greenness of an area. Fifty
studies (34.0%) used the normalized difference vegetation index (NDVI), a
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widely used metric for quantifying vegetation health and density from sensor
data, either alone or combined with other parameters such as percentage of
green space or land use. Three studies (4.1%) employed the Shannon Index,
an ecological measure of species diversity that captures both richness and
evenness. A total of 28 studies (22.4%) used the percentage of green area
(including trees, grass, and other land-cover types). No clear relationship was
observed between the type of plant biodiversity index used and either study
design or the specific disease outcomes investigated. Only six studies (4.0%)
reported a biodiversity index that did not consider vegetation but instead
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measured bird or insect richness [26–31], while another 7 studies (4.7%)
included both plant and bird/insect richness as part of their index [32–38].
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Finally, almost a fifth of the selected studies (28/147, 18.4%) did not report
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any objective biodiversity index. Instead, they focused on indicators such as
frequency of use, types of activities performed, and time spent in urban green
areas. Exposure was typically measured in terms of time spent in green
spaces (ranging from 15 minutes to 5 hours) [39–41], frequency of visits (e.g.,
seldom, monthly or weekly, daily) [41–43], and type of activities undertaken
(e.g., walking, sports) [39, 44].
3.3 Classification of health outcomes
Among the selected studies, four main thematic clusters were identified on
the basis of the health outcomes analysed: i) Outcomes related to general
health, mental health, and well-being; ii) Outcomes related to the
consumption of medications primarily used to treat mental health conditions;
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iii)
Outcomes
related
to
chronic
diseases
(cardiovascular
diseases,
respiratory diseases, diabetes, obesity); iv) Birth-related outcomes, such as
birth weight, prematurity, and other indicators of neonatal health correlated
with maternal exposures.
3.3.1 Studies on general health, mental health, and well-being
outcomes
The correlation between exposure to urban green areas and general or
mental health and well-being was the most frequently investigated topic, with
78 out of 147 studies (53.1%) addressing these issues. Among these, 20
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studies (25.6%) examined general health and the frequency or aptitude for
physical activity, which indirectly exerts positive effects on health; 21 studies
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(26.9%) focused specifically on mental health or depression, and 37 (47.4%)
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on well-being, stress reduction, and relaxation. Only one study (1.2%)
evaluated both well-being and drug prescriptions (anxiolytics, hypnotics, and
antidepressants) as outcomes using data from a health registry [45] (Table
1). Most studies analysed self-reported outcome data. Only a small minority
of general health studies (2/20, 10%) used assessment scales, standardized
questionnaires, or measurable biological parameters. In contrast, 33% (7/21)
and 27% (10/37) of mental health and well-being studies, respectively,
employed validated assessment scales for different outcomes. Depressive
symptoms or disorders were the most frequently assessed mental health
outcomes (50%, 10/21) [33, 43, 46–53], followed by anxiety (25%, 5/21) [33,
46, 47, 54, 55], stress (15%, 3/21) [32, 46, 47], and common self-reported
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mental health indicators. Other outcomes included life satisfaction, vitality,
mindfulness, and resilience [41, 56–59]. Instruments used to measure general
and mental health included validated questionnaires such as the General
Health Questionnaire (GHQ-12/GHQ-28) [53, 60–63], the Patient Health
Questionnaire (PHQ-2/PHQ-9) [47, 55], the Depression, Anxiety, and Stress
Scales (DASS-21) [33, 46, 51], and the Kessler Psychological Distress Scale
(K10) [45, 64, 65]. Across studies, two main approaches were used to assess
exposure to green areas: (1) residential exposure, defined as the distance
between home and green areas, and (2) active use, defined as activities
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carried out in green areas or frequency of visits. Studies on well-being were
nearly equally divided in terms of exposure type, with 53% using residence-
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based measures, whereas most studies on general and mental health used
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residence-based exposure (81% and 76%, respectively).
Most studies (58.9%, 46/78) controlled for socio-economic status (SES) when
adjusting results. Many found that the positive association between green
exposure (residence or use) and improved mental health or well-being was
stronger in populations with low SES levels.
Overall, 70.0% of general health studies reported positive findings, showing
a correlation between residential exposure or active engagement with urban
green spaces and improved self-reported health (poor/fair vs. good/very
good/excellent) [62, 63, 66–72]. Greater tree canopy, NDVI, garden size, and
proximity to parks were consistently associated with better general health
outcomes [66, 69, 70], whereas grass alone showed weaker or null
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associations [70]. Smaller green areas and more distant or fragmented green
spaces were linked to poorer health and increased health inequalities [63, 66,
67, 71]. Five studies (25%) showed no clear evidence, as low SES significantly
influenced the results: residential greenness effects were often stronger
among low-SES populations, older adults, and individuals with poorer
baseline health [36, 63, 71–73].
Four studies have specifically examined whether biodiversity provides added
value beyond mere exposure to green spaces (Table 1). In these studies,
exposure to urban green spaces was characterised not only by availability,
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but also by biodiversity and ecological quality. The assessment of biodiversity
was conducted using both objective indicators, including species richness
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and environmental quality parameters [27, 30, 36], and subjective
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perceptions [63], encompassing perceived species richness and visual
stimuli. In particular, the studies found a correlation between self-reported
well-being and higher levels of biodiversity or perceived naturalness. The
results of these studies suggest that the existence and perception of
biodiversity are significantly associated with health and well-being benefits
derived from urban green spaces. However, the general trend of the evidence
showed that approximately half of the studies revealed a positive correlation,
while the others produced uncertain results [27, 63].
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The 21 studies that examined the relationship between green-space exposure
and mental health were conducted mainly in high-income countries, with the
United Kingdom (n = 7) and Canada (n = 3) most frequently represented.
A total of 90.5% of these studies (19/21) reported positive findings, showing
a correlation between exposure to urban green spaces and improved mental
health, including reductions in depression and anxiety levels [33, 46, 50].
Alcock and colleagues (2014) carried out a longitudinal cohort study and their
results suggested that moving to greener areas led to improvements in
mental health, whereas relocation to areas with lower greenness was
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associated with temporary declines [60]. Green-space use was also positively
associated with mental health: increased time spent in parks correlated with
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lower depressive symptoms, enhanced social cohesion, and greater vitality
[42, 51, 74, 75].
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Biodiversity measures, including bird and tree richness, were linked to better
mental health outcomes. Stronger effects were observed among populations
with lower socioeconomic status (SES) [32, 33], similarly to the way in which
the benefits of green exposure were modified by socio-demographic
characteristics, urbanicity, and lifestyle factors.
Positive effects of green exposure were more pronounced among women,
younger adults, individuals with lower SES, and those engaging in higher
levels of physical activity [50, 53]. Moreover, childhood experiences with
nature moderated the association between green-space visits and mental
health [42].
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Xu and colleagues [31] found no relationship between mountain park usage,
bird biodiversity and momentary mental health, while Pelgrims and
coworkers [76] observed that air pollution, rather than greenness, was the
primary determinant of mental health outcomes. Some studies further noted
that residential green exposure effects were weaker for anxiety and mood
disorders compared to depressive symptoms [47, 54].
Among
studies
investigating
well-being,
outcomes
spanned
multiple
dimensions, including stress [38, 64, 77, 78], psychological distress [61, 79–
81], life satisfaction, and immediate affective or restorative responses such
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as positive or negative mood, emotional response [57], and perceived
restorativeness [37, 82, 83]. A total of 91.9% of well-being studies reported
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positive correlation with green exposure, 5.4% reported negative correlation
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and 2.7% found no clear association between green exposure and well-being.
Similar results were obtained in relation to the biodiversity of green spaces
(87.5% were positive and 12.5% had no clear correlation).
Higher tree canopy or tree richness was consistently associated with lower
psychological distress, reduced depression risk, and better self-rated health
[64, 80, 84, 85]. Frequent visits to green spaces were associated with
improved mood, higher life satisfaction, and reduced stress [29, 37, 83, 85].
Benefits were observed across various types of use, including walking, social
activities, and relaxation. In several studies, the perceived biodiversity and
naturalness of green areas, rather than the measured biodiversity of trees,
insects, or birds, emerged as stronger predictors of positive correlation with
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well-being and restorativeness [26, 29, 38, 86]. Park access within 300–500m
buffers was also linked to improved self-rated health and life satisfaction,
although effects varied according to vegetation type and park characteristics
[59].
Only 2 studies reported null associations between well-being and green
exposure [38, 78], while only one study showed a negative correlation with
the biodiversity index (bird richness) [28]. Among the studies that used
outcome measures (measurement scales or physiological parameters), all
showed a positive correlation between green exposure and mental and
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general health. In contrast, positivity is at 90% for studies on well-being and
stress reduction. Among the quasi-experimental and experimental studies
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[36, 38, 44, 82, 83, 87] positive correlations between green exposure (e.g.
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visits to urban forests and parks) and improved psychophysical outcomes
were evidenced. These include improved mood and restorativeness [36, 82,
83], reduced cortisol levels [44] and lower blood pressure and improved heart
rate variability [38, 44, 87]. Perceived biodiversity appears to be positively
linked to well-being, while objective measures yield less consistent results
(bird richness and Shannon Index) [36, 38].
A separate analysis was conducted for studies reporting outcomes related to
the consumption of medications primarily used to treat mental health
conditions (Table 2). All included studies reported a positive association
between green exposure and mental health, and, in particular, an inverse
relationship between urban greenery and the use of psychotropic drugs (e.g.,
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antidepressants, anxiolytics, and antipsychotics). Aerts and colleagues [88]
found that greater green-space availability, as measured by NDVI and the
types of green space present (e.g., woods, meadows, and gardens), was
associated with a significant reduction in psychotropic drug sales,
particularly in urban and socioeconomically disadvantaged areas. Chi and
colleagues [89] reported similar results, observing that tree-canopy density
and volume were inversely correlated with the consumption of mood-altering
and cardiovascular drugs. Gascon and coworkers [90] also found that higher
levels of vegetation, measured by NDVI at different spatial buffers, were
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associated with a lower likelihood of depression and benzodiazepine use.
However, no significant effects were observed in relation to proximity to blue
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spaces (e.g., water bodies). Helbich and colleagues [91] highlighted a non-
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linear relationship between the percentage of green spaces and the rate of
antidepressant prescriptions, suggesting the existence of a threshold and a
dose-dependent response: the protective effect was more pronounced in
areas with high baseline prescription rates. Similarly, Marselle and
coworkers [20] found that a higher density of trees along roads within 100
metres of subjects’ homes was associated with a reduction in antidepressant
prescriptions, with stronger effects observed among individuals with low
socioeconomic status. However, tree biodiversity (species richness) and
exposure at greater distances did not show significant associations. Using
ecological data from 31 London boroughs, Taylor and coworkers [92]
reported a slight reduction in antidepressant prescription rates associated
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with roadside tree density, although the effect was borderline significant.
Finally, Triguero-Mas and colleagues [93] found that higher NDVI values
within 300 metres of home were consistently associated with better selfperceived health and lower levels of psychological distress. In this case,
neither physical activity nor social support appeared to mediate the observed
effect, while exposure to blue spaces again showed no significant
associations.
Overall, the results indicate that green exposure, particularly that
characterised by a high tree canopy and abundant vegetation, was associated
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with improved mental health, as evidenced by both objective indicators (e.g.,
medication sales or prescription rates) and subjective measures (e.g., selfperceived health).
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All the examined studies related to the consumption of medications primarily
used to treat mental health conditions were cross-sectional and conducted in
Europe, showing consistent findings across different geographical contexts
and reinforcing the hypothesis of a protective effect of natural environments
on mental health.
Table 1. Main characteristics of studies on general and mental health and
well-being
Health outcomes
Selfreported
data
Measure
d data#
Green exposure
Residenc
e
Use
Biodiversit
y
measureme
nt
Trend
evidenc
studi
with gr
exposu
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[25, 27, 70,
General
health
[98, 99]
[27, 30,
[25, 36,
[27, 30, 36,
71, 73, 94–
95–99, 62,
71, 94]
63]
97, 30, 36,
63, 66–70,
70.0%
62, 63, 66–
73]
25.0%
5% ▼
69]
[31, 35, 65,
[32, 33,
[32, 33,
74–76, 42,
47, 51, 53, 54, 55, 60,
Mental
43, 46, 48–
55, 60]
health
50, 52, 54]
[31, 42,
[31–33, 35]
43, 74]
90.5%
65, 75, 76,
4.8%
35, 43, 47–
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4.8%
50, 52, 53]
Wellbeing
/stress
reduction
[12, 26, 77,
[28, 39,
78, 81, 82,
[12, 26,
[12, 26, 28,
56, 61, 64, 101, 102,
78, 79, 82,
29, 34, 37,
84, 86,
79, 80, 83, 104, 108,
83, 86,
100–103,
85, 111]
109, 111,
100, 103,
91.9%
29, 104–
58, 59, 64,
105–107,
2.7%
110, 34, 37,
77, 80, 81,
28, 110,
5.4%
38, 41, 57–
84, 85]
34, 37, 39,
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[29, 38,
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59]
79, 86]
41, 56, 57,
61]
Drug
-
[45]
[45]
-
-
prescripti
on
#: By means of: scale for evaluation, questionnaire, biological parameters; ▲:
positive correlation; ↔: uncertain correlation; ▼: negative correlation.
Table 2. Urban green space exposure and consumption of medications
primarily used to treat mental health conditions
100.0%
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Country
/ Populati
City
on
Green
exposur
Outcome
e
NDVI
+
Belgium
Adult
types
(national
populatio
(woodlan
study)
n
d,
grassland
Referen
finding
ces
More green
greenspace
Main
space linked
Psychotropi
to
lower
c
medication
medication
sales;
sales
strongest in
[88]
urban/depriv
,
ed areas
gardens)
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Higher tree
Residenti
Belgium
/
Brussels
Adults
al
(19–64
exposure
years)
to
LE
urban
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trees
958
Spain
/ adults
Barcelona
(45–74
years)
Netherland
Municipa
s (national l
Medication
sales
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(mood,
CVD)
density
and
crown
volume
[89]
linked
to
lower
drug
sales
NDVI
Higher
(100-
greenness
500m);
land
cover;
access to
major
Anxiety,
depression,
psychotropi
c use
linked
to
lower
depression
and
benzodiazep
green/blu
ine use; blue
e space
space null
%
green Antidepress Non-linear
spaces
ant
[90]
inverse
[91]
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study,
403 populatio
municipalit
ns
ies)
(parks,
prescriptio
relationship;
agricultu
n rates
threshold/do
ral,
se-response
forests)
pattern
Higher tree
density
Germany
/ 9,751
Leipzig
adults
Street-
within 100m
tree
linked
density
Antidepress lower drugs
(100-
ant
prescription
1000m
prescriptio
s, especially
buffers)
ns
for low SES;
species
London
(31
boroughs)
/
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Area-
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richness
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is
not
significant
More street
Tree
Antidepress trees
density
ant
level data per
are
slightly
km prescribing
linked
to
rate
lower
drug
street
[20]
species
richness
UK
to
[92]
prescribing
Higher
Spain
Catalonia
/ 8,793
adults
NDVI
Psychotropi
300m;
c use, visit linked
access to to
greenness is
to
mental drugs intake
green/blu
health
(antidepress
e spaces
specialists
ant,
sedatives)
[93]
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3.3.2 Studies on chronic diseases: diabetes, cardiovascular diseases,
obesity
Chronic degenerative diseases were found to be associated with green
exposure in 44 out of 147 studies (30.0%). Among these, 18 studies (40.9%)
assessed both all-cause mortality and cause-specific mortality, particularly
for cardiovascular and respiratory diseases [99, 112, 121–128, 113–120]. Two
additional studies (4.5%) used life expectancy [129] and years of life lost
[130] as outcome parameters.
The presence of green spaces near the home was consistently associated with
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a reduction in cardiovascular mortality, not only in small cities but also in
highly urbanised settings, suggesting that even access to small green areas
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can have beneficial effects. Silveira and colleagues [123] showed that greater
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green coverage was associated with lower mortality from cardiovascular
diseases, including heart attacks and cerebrovascular events, regardless of
SES. Aerts and coworkers [112] reported similar findings, showing that the
beneficial effects of green exposure were more pronounced in low-SES areas,
indicating that access to and use of green urban areas may have a greater
impact on socially vulnerable populations.
All studies adjusted their analyses for the main risk factors associated with
chronic degenerative diseases, such as age, gender, BMI (body mass index),
smoking status, educational attainment, and SES. Several studies, also
reporting levels of major atmospheric pollutants (e.g., PM₁₀, PM₂.₅, NOₓ) [99,
114, 116, 118, 121, 122], showed that the protective effects of green
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exposure were partly mediated by air pollution. Generally, the studies
measured exposure and outcome at the same time, so they cannot establish
temporality (i.e., whether exposure preceded disease). This could create an
exposure–outcome mismatch, especially for chronic conditions that develop
over years.
Overall, these studies consistently demonstrated a positive correlation
between green exposure and a reduction in both all-cause and cause-specific
mortality, as well as an improvement in life expectancy (Table 3).
However, Klompmaker and colleagues [120] found no such association, while
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two studies [114, 131] reported weak or inconsistent results, with no clear
linear correlation. Other studies investigated the incidence and prevalence of
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cardiovascular and respiratory diseases, T2 diabetes, and overweight or
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obesity in populations exposed to varying levels of green exposure, both for
individual diseases and for multiple conditions combined. Three studies
examined the association with diabetes [132–134]. Astell-Burt and coworkers
[132] demonstrated that having green spaces near the home was linked to a
lower risk of type 2 diabetes. Green environments can encourage physical
activity, alleviate stress, and improve air quality, thereby positively
influencing metabolic health [133, 135–138].
Urban green areas promote behaviours such as walking, running, and
outdoor exercise, which directly improve physical health and reduce the risk
of chronic conditions, including diabetes, heart diseases, and obesity. The
incidence and prevalence of cardiovascular diseases represented the most
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frequently studied topic (27.9%) in relation to green exposure [25, 51, 145,
146, 87, 131, 139–144].
All studies, except Picavet and colleagues [131], who reported weak or
inconsistent
evidence
of
a
correlation
between
green
areas
(gardens/agricultural land) and blood pressure or BMI, showed positive
associations, with reductions in cardiovascular diseases and its risk factors.
Most studies (n=16, 36.3%) used the NDVI derived from satellite imagery as
the
primary
exposure
metric,
providing
objective
and
comparable
measurements across locations. Only one study used the frequency of visits
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to green areas and the amount of physical activity carried out in parks as
parameters [87]; two studies evaluated both residence and frequency of use
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[137, 142]; and the remainder used residential proximity alone as the green
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exposure measure.
Almost all studies adjusted for major disease confounders, and in addition to
general variables such as age, gender, and education, several considered
specific risk factors (e.g., smoking, BMI, obesity, blood glucose, cholesterol).
Particular importance was given to SES and physical activity in the analytical
models.
Table 3. Summary of studies on chronic diseases: diabetes, cardiovascular
diseases, obesity
Health
Exposure
Outcomes
effect
Green
exposure
with
Proposed
Mechanisms
References
Note
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strongest
effects
All-cause
mortality
Protective NDVI
↓ air
2 studies
[99,
112,
(range 500- pollution,
[114, 120]
124,
128,
1250 m),
↓ noise,
had null or
113–115,
tree
↑ PA,
limited
118–122]
canopy, %
↓ stress
evidence
↓ air
Some
[99,
canopy,
pollutants,
models
125–127,
NDVI,
↑ ecosystem
attenuated
114,
116–
street-tree
health,
after full
118,
120,
SES
122–124]
of green
CVD mortality
Protective Tree
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biodiversity ↓ heat
CVD incidence
Protective NDVI, %
green
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space, park
C
I
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proximity
adjustment
↓ BP,
Some
[25,
51,
↓ pollution,
variability
135,
140,
↑ PA, stress
by sex
142,
146,
recovery
(women
147]
stronger in
some
studies)
Hospitalizations Protective % of green
↓ Risk and
for CVD and
hospitalization number of
respiratory
rates
disease
Hypertension
113,
Limited
[139, 140]
studies
overall
Protective NDVI,
↓ stress,
Visual
[87,
131,
and blood
street
↓ noise,
greenness
147,
135–
pressure
greenery,
↑ autonomic
more
138,
141,
tree count
balance
predictive
143–145]
than
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satellite
greenness
Stronger
NDVI,
Diabetes /
Metabolic
Protective
outcomes
%
↑
Weight
green control,
space, tree ↑ PA,
canopy
↓ pollution
[132–138]
effects in
deprived
areas;
sometimes
sexspecific
canopy,
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street-level
↑ PA
Tree
Obesity / BMI
Protective
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greenery
↑ walkability,
City-level:
[131,
136–
NDVI less
138,
148–
predictive;
150]
stronger
effects in
some
studies in
women. A
study
[131] had
null or
limited
evidence
BMI: body mass index; BP: blood pressure; CVD: cardiovascular diseases; NDVI:
normalized difference vegetation index; PA: physical activity; ↑: increase; ↓:
decrease.
3.3.3 Studies on birth-related outcomes
It is interesting to note that specific health outcomes investigated in the
context of the association between green exposure and biodiversity include
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birth-related outcomes, such as birth weight, prematurity, and other
indicators of neonatal health, including head circumference, foetal growth,
and small for gestational age (SGA) status (Table 4). Thirteen studies have
been conducted, mainly in North America (53.8%, including six from the
United States and one from Canada) and 23.1% in Europe. Cohort studies
predominated (84.6%), with only two cross-sectional studies. The included
studies enrolled pregnant women at the time of childbirth and comprised
population samples ranging from a few hundred participants [151] to several
million individuals [152]. Green exposure was primarily measured using a
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single parameter, the mother’s residential address (84.6%, 11 out of 13
studies), and the distance from parks, with areal ranges typically between
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100 and 500 meters. Only two studies also assessed the use and frequency of
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visits to green areas [153, 154]. The NDVI was used in all studies as the main
indicator of biodiversity richness. More than half of the studies (53.8%, 7/13)
reported a positive correlation between green exposure and birth outcomes.
Six studies [153, 155–159] found significant associations between increased
green exposure and a reduced risk of low birth weight and premature birth.
In some cases, the correlation appeared to be stronger in high-density urban
areas [155] or among more advantaged socioeconomic groups [157]. Only
one study accounted for PM₂.₅ pollution, emphasising that the positive
correlation of green exposure was not influenced by air pollution levels [74].
However, 38.5% (5/13) of studies [151, 154, 160–162] did not find a
significant association between green exposure and birth outcomes.
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Anabitarte and colleagues (2020) [151] did not report a significant
correlation between green areas and pregnancy outcomes, except within 300
metres of the mother’s residence, where a reduction in SGA risk was
observed. Some studies did not show a reduction in the risk of low birth
weight but did identify correlations with head circumference [160] or foetal
growth [162]. Conversely, the European multicentre study [154] found an
association only with a reduced risk of low birth weight and not with other
parameters, suggesting that other urban factors may have a greater impact
on these outcomes. Some authors also proposed that the effect might be
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limited to specific subgroups of pregnant women, particularly those defined
by socioeconomic status or educational level. However, no significant
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associations were observed in the overall sample [163].
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All studies in this domain adjusted their analyses for the main maternal sociodemographic characteristics (e.g., education, maternal age, ethnicity, BMI,
smoking, and alcohol consumption) and for socioeconomic variables (e.g.,
deprivation index of the residential area), confirming that these factors
significantly influenced the results.
The results obtained were summarized in Table 5 in order to provide a
concise overview.
Table 4. Main results of maternal and fetal health outcomes
SES level
Country
Green exposure
adjustmen
t
Birth
outcomes
Main find
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USA (NYC)
Street
tree
density,
NDVI,
access
to
large
yes
greenspaces/wat
BW, LBW,
PTB, SGA
Street trees are link
NDVI and park/water
inconsistent.
er
NDVI
Spain
(300
green
m),
space
>5000 m² within
no
BW, LBW,
PTB SGA
300–500 m
NDVI (250 m)
yes
a)
USA
Tree exposure
(100 m–3 km),
(New
NDVI, land cover
England)
diversity
USA (Texas)
Canada
Italy/Austria
(Alpine)
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NDVI (250 m)
NDVI
(500
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NDVI (500 m)
m),
no
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tts)
NDVI (250 m)
BW, PTB,
green
s
associated with ↓ SGA
and ↓ SGA.
SGA
S
S
E
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BW, HC, FL
Non-urban areas: no co
Green exposure associ
and FL, no correlation
Unadjusted analysis: p
yes
BW, PTB,
SGA
Fully
adjusted:
disappear.
mos
Some
correlations remain.
yes
no
USA
(Massachuse
evidence
Cities: Green exposure
USA
(Pennsylvani
No robust association
yes
BW
BW, LBW,
PTB, SGA
BW, TLBW,
SGA
No overall correlation
association in dense/ur
Results
inconsistent:
levels make difference:
NDVI is linked to ↓ LB
Robust positive asso
↓TLBW/SGA. Stronger
and urban areas.
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USA
NDVI (500 m),
(California)
distance to parks
China
NDVI (200 m, 500
(Beijing)
m)
NDVI is associated w
yes
LBW
~12%
mediated
by
proximity not a strong
yes
FG, LBW,
NDVI (500 m) ↑FG
SGA
correlation with BW or
% green space
No overall correlations
New Zealand (area-level)
yes
BW, SGA
linked with ↓SGA fo
lowest education.
Europe
NDVI (100–500
Consistent across cities
m),
↓ TLBW.
yes
access to
(6 countries)
green/blue
spaces
Greenness
Australia
(foliage cover)
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Large,
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yes
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BW, TLBW
robust
corr
cohorts.
BW, SGA,
LGA
Green exposure is linke
Biodiversity
not
as
outcomes.
BW: birth weight; FG: fetal growth; FL: fetal length; LBW: low birth weight; HC: head c
for gestational age; PTB: preterm birth; SGA: small gestational age; TLBW: term low bir
decrease.
Table 5. Summary of the main findings of the literature review.
Outcomes
General
Health
Mental
Health
Evidence
Biodiversity
Health
Modifying
Trend
Index
benefit
Factors
Tree canopy,
Better self-
SES, age,
NDVI
rated health
baseline health
Tree & bird
↓Depression,
70% positive
90% positive richness,
NDVI
↓Anxiety,
↑Vitality
SES, gender,
activity,
childhood nature
contact
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Tree
Well-being
90% positive
richness,
perceived
biodiversity
Drug Use
Chronic
Diseases
↓Stress,
Urban
↑Life
characteristics,
satisfaction
park access
100%
Tree canopy,
↓Psychotropic
inverse
NDVI
prescriptions
NDVI,
↓Mortality,
95% positive vegetation
↓CVD risk,
cover
↓Diabetes
SES, urban areas
Air pollution,
SES
Birth
~54%
NDVI near
↑Birth weight,
SES, urban
Outcomes
positive
residence
Preterm risk
density
4. Discussion
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A systematic analysis of the literature reveals a consistent, positive
correlation between green exposure and improvements in human health.
Most studies assessed green exposure using plant-based indicators, such as
tree canopy cover and satellite-derived indices (e.g., NDVI), which were
consistently linked to better self-reported health and a reduced incidence of
many chronic-disease outcomes. These findings are consistent with the
extant literature, which supports the health-promoting role of urban green
exposure. Nevertheless, the role of biodiversity in urban green spaces
remains ambiguous and understudied. A mere 12.9% of the selected studies
(19 out of 147) reported an objective measurement of biodiversity. However,
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inconsistency in the employed parameters and their associations with health
outcomes generates ambiguity.
Despite this concern, the available evidence suggests that biodiversity may
represent an additional and more sensitive dimension of green exposure.
Studies incorporating indicators such as species richness or ecological
diversity have consistently reported stronger or more specific associations
with health outcomes [117], particularly in the context of mental health and
wellbeing [12, 26, 32].
In this review over 75% of the studies examined assessed green exposure
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using vegetation-related parameters and they were consistently correlated
with improvements in self-reported general health [25, 30, 71, 73, 94–98, 36,
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62, 63, 66–70], and reduced mortality [99, 112, 122–128, 113–119, 121], as
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well as a decrease in the prevalence of cardiovascular and respiratory
diseases [25, 51, 145, 146, 87, 131, 139–144], and type 2 diabetes [132–134].
Improvements in overall health can be attributed not only to the presence of
green spaces in residential areas, but also to the opportunity to use and enjoy
these spaces, which promotes physical activity and mitigates air pollution and
urban heat. Exposure also reduces stress and increases social cohesion [25,
36, 71, 94]. However, studies that consider only grass or tree cover with less
structural diversity, or the perceived quantity and/or quality of green spaces,
have generally reported weaker or no associations [36, 63, 71–73]. This
indicates that not all forms of greenery have equivalent health benefits.
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The topic of mental health and well-being has been the most extensively
studied and has provided the strongest evidence: over 90% of mental health
studies and 87% of well-being studies reported beneficial associations (see
Table 1 and Table 5). Green residential exposure, higher urban tree cover,
and richer biodiversity have been consistently associated with a lower risk of
depression [33, 46, 50], anxiety and stress [38, 61, 64, 77–81], and greater
vitality and life satisfaction [37, 57, 82, 83]. It has also been shown that
mental health improves in individuals who move to greener residential areas
[50]. Interestingly, perceived biodiversity and green exposure are more
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closely related to perceived well-being than objective biodiversity indices
(e.g., NDVI, Shannon Index), highlighting the role of cognitive and emotional
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factors in mediating psychological recovery [57, 61, 86, 100, 105].
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One of the key findings of this analysis is that biodiversity does not appear to
provide any additional health benefits beyond those associated with exposure
to green spaces alone. Studies suggest that commonly used indicators of
green exposure are nonetheless associated with protective health effects.
However, these indicators of green exposure do not reflect the richness and
biodiversity of natural environments that are relevant to health (potentially
leading to an incorrect or underestimated classification of exposure) [21].
Moreover, the distinction between perceived and objectively measured
biodiversity is also noteworthy. Several studies indicate that perceived
biodiversity may be equally or more strongly associated with well-being
outcomes, highlighting the importance of individual perception and
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experience in mediating health benefits [20, 36]. This underscores the need
for more integrative approaches that consider both ecological and
psychosocial dimensions of exposure.
Although limited in number, studies using bird and insect richness as an index
of biodiversity have also suggested positive associations with mental health
and psychological well-being [12, 26, 28, 29, 34, 37, 38]. These findings are
consistent with the “biophilia hypothesis”, which posits that humans possess
an innate affinity for other living organisms, and with experimental findings
showing that exposure to multisensory natural stimuli, such as birdsong or
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insect activity, improves mood and attention recovery [164].
An emerging line of research on population mental health examines the
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correlation with green exposure using data on the prescription or sale of
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psychotropic drugs as an objective indicator of mental health [20, 45, 88–93].
All of the studies examined in this field have demonstrated an inverse
relationship between exposure to green spaces (as measured by NDVI and
tree cover percentage) and the use of antidepressants and anxiolytics (Table
5). These results corroborate self-reported studies indicating increased wellbeing and reduced stress, suggesting that urban green spaces can exert
clinically
significant
protective
effects.
Observing
dose-response
relationships and stronger effects in socioeconomically disadvantaged
populations supports the idea that equitable access to rich green spaces
could help reduce mental health disparities [20, 88, 91].
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There is consistent evidence of a positive association between green exposure
and a reduced risk of all-cause and cause-specific mortality, particularly for
cardiovascular and respiratory diseases [99, 112, 121–128, 113–120]. Several
studies have demonstrated that these protective effects endure even when
accounting for air pollution as a risk factor for these diseases [99, 114, 116,
118, 121, 122], as well as socioeconomic status and lifestyle factors such as
smoking and alcohol consumption [99, 114, 118, 119, 121, 124, 125, 128].
This suggests that urban green exposure makes an independent positive
contribution. These mechanisms may include reduced air pollutants and
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noise, improved microclimate regulation and increased health-promoting
behaviours, such as greater physical activity and reduced stress. Evidence of
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a reduced risk of obesity and diabetes related to green exposure in the area
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of residence also supports its role in promoting healthier lifestyles and a
lower prevalence of metabolic diseases.
Although fewer in number, studies examining neonatal health outcomes
provide suggestive evidence that maternal green exposure is associated with
better birth outcomes, including higher birth weight and reduced risk of
preterm birth [153, 155–159]. However, the strength and direction of these
associations varied depending on the urban context [155] and socioeconomic
status [157], and several studies reported null or conflicting results [151, 154,
160–162]. These inconsistencies may reflect heterogeneity in study design
(wide variation in sample size), differences in the assessment of green
exposure, and the absence of objective measurements of some environmental
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or social variables, with neighbourhood of residence often used as a proxy for
exposure [151, 156, 160]. Nevertheless, the general trend towards positive
associations supports the hypothesis that biodiverse environments may
influence early childhood health outcomes by reducing stress, improving air
quality, and enhancing the psychosocial well-being of mothers. One study
well represents the paradigm between green exposure (maternal residence)
and biodiversity (Shannon Index) and correlation with neonatal health
outcome [159]: green exposure was positively correlated with birthweight
especially in low-biodiversity (urban) areas, but the influence of biodiversity
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itself on concrete health outcomes remains poorly understood, as it has not
been sufficiently investigated to date.
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Socioeconomic status emerged as a consistent effect modifier across all
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health domains. The strongest positive associations between green exposure
and health were often found among individuals with lower SES [50, 53, 58,
65], older adults [77] and those with poorer baseline health [71]. This
suggests that access to biodiverse green spaces may improve the health of
the general population and help to mitigate social inequalities in health. The
urban context also played a role: green areas that were more fragmented or
distant were less effective, whereas smaller, nearby, structurally diverse
green areas produced significant benefits. This highlights the importance of
spatial planning and the connectivity of urban nature [63, 66, 67, 71].
The evidence shows that exposure to green environments that are rich in
biodiversity, particularly those with an abundance of diverse tree cover, has
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a measurable positive impact on general health and mental wellbeing, and
helps to prevent chronic diseases. Therefore, biodiversity is not only an
ecological resource, but also a vital component of urban public health
infrastructure. Integrating biodiversity enhancement into urban planning and
public health policies could significantly benefit human health as well as the
ecosystem.
This review has several limitations. Most included studies were crosssectional, limiting causal inference, and many relied on self-reported health
outcomes, which limit accurate estimation of the association. Objective
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biomarkers of physiological response (e.g. cortisol, immune parameters or
metabolic markers) remain underutilised [18, 40, 44]. Most green exposure
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assessments have focused on the quantity of vegetation rather than its
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ecological quality, and relatively few studies have quantified diversity at the
level of plant species [12, 28, 32, 35, 36, 39, 79, 86, 153, 165]. Including fauna
diversity, soil microbial exposure, and ecosystem function indicators in future
research could improve our understanding of the biological mechanisms
underlying the observed associations. Longitudinal and intervention studies
are also needed to clarify the temporal relationships and potential threshold
effects of this exposure on different health outcomes. Heterogeneity in
exposure metrics and study designs also complicates comparisons across
studies.
Future research should consider standard and multidimensional measures
not only of green exposure but mainly of biodiversity. Greater attention
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should also be given to the role of perceived biodiversity, accessibility, and
actual use of green spaces. Integrating these dimensions may improve the
understanding of the mechanisms linking not only green exposure but also
biodiversity and health.
From a public health perspective, these findings highlight the importance of
considering not only the quantity but also the quality of urban green spaces.
Biodiversity-rich environments appear to provide greater health benefits than
homogeneous green areas, suggesting that urban planning and public health
policies should incorporate ecological complexity as a key design principle.
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Enhancing biodiversity within cities may represent a cost-effective strategy
to improve population health, reduce health inequalities, and promote more
resilient urban environments.
5. Conclusion
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This systematic review confirms that green exposure within urban spaces is
positively associated with multiple adult health outcomes, with the most
consistent evidence emerging for mental health, well-being, and reductions
in psychotropic medication use. Socioeconomic status frequently modified
associations, highlighting the importance of equitable access to green
environments.
Nevertheless, green exposure and biodiversity are not always directly
comparable in terms of their correlation with health outcomes.
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The role of biodiversity in urban green spaces remains ambiguous and
understudied. There is a discrepancy between perceived and measured
biodiversity when specific indicators are used.
Future
studies
should
incorporate
more
comparable
parameters
of
biodiversity, include longitudinal or intervention designs, and evaluate
potential dose–response relationships because the impact of biodiversity on
health outcomes is not yet fully understood.
Greater attention should be given to the role of perceived biodiversity,
accessibility, and actual use of green spaces. Integrating these dimensions
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into urban planning and public health policy may strengthen the healthpromoting potential of urban nature.
List of abbreviations
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BMI: Body mass index
BW: birth weight;
CVD: Cardiovascular disease
FG: fetal growth;
FL: fetal length;
HC: head circumference;
LBW: Low birth weight
LGA: large for gestational age;
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NDVI: Normalized Difference Vegetation Index
PA: Physical activity
PTB: Preterm birth
SES: Socioeconomic status
SGA: Small for gestational age
TLBW: term low birth weight;
T2 diabetes: type 2 diabetes
Declarations
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Ethics approval and consent to participate
Not applicable. This study is a systematic review of published literature and
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did not involve the collection of new data from human participants or animals.
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Consent for publication
Not applicable.
Availability of data and materials
All data generated or analysed during this study are included in this
published article and its supplementary information files.
Competing interests
The authors declare that they have no competing interests.
Funding
This research received no specific grant from any funding agency in the
public, commercial, or not-for-profit sectors.
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Authors’ contributions
NP, CA, MT, AB and CZ designed the study protocol and conceptualized the
study. CA and CZ conducted study selection and data extraction. NP and CA
performed quality assessment. NP, CA and CZ drafted the manuscript. All
authors critically revised the manuscript and approved the final version.
Acknowledgement
The concept for this review was developed after the collaboration with the
project UrBioPark “Urban parks’ biodiversity to enhance city dwellers’
health. URBioPark” funded by PRIN: Progetti Di Ricerca Di Rilevante
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Interesse Nazionale – Bando 2022 Prot. 202253N2NY.
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