Next Article in Journal
From Isolated Valves to a Potential Marine Living Resource: History, Documented Distribution and Sustainable Population Enhancement Possibilities of the Smooth Scallop (Flexopecten glaber) on the Romanian Coast
Previous Article in Journal
Numerical Simulation of the Density Effect on the Macroscopic Transport Process of Tracer in the Ruhrstahl–Heraeus (RH) Vacuum Degasser
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 10
10.3390/su16103925
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Urban Green Spaces’ Influence on Civilization Diseases—Meta-Analysis and Critical Review

by
Małgorzata Kaczyńska
Department of Landscape Art, Institute of Environmental Engineering, Warsaw University of Life Sciences-SGGW, Nowoursynowska Street 166, 02-787 Warsaw, Poland
Sustainability 2024, 16(10), 3925; https://doi.org/10.3390/su16103925
Submission received: 12 April 2024 / Revised: 26 April 2024 / Accepted: 2 May 2024 / Published: 8 May 2024
(This article belongs to the Section Health, Well-Being and Sustainability)
Browse Figures
Versions Notes

Abstract

:
This study investigates the influence of urban green spaces on the prevalence of overweight/obesity, diabetes, and hypertension. The search was run in the PUBMED database, using the search algorithm including combinations of keywords associated with the two concepts: civilization health problems and urban green spaces. A meta-analysis (for 48 studies) and critical review (for 26 studies) were performed. The meta-analysis results show that the presence, accessibility, and quality of green spaces are associated with the decreased prevalence of overweight/obesity (OR 0.86 (95% CI 0.77–0.95), p < 0.001, I2 99.7%), diabetes (OR 0.83 (95% CI 0.79–0.87), p < 0.001, I2 67.5%), and hypertension (OR 0.77 (95% CI 0.63–0.92), p < 0.001, I2 84.9%). In the children population, the influence of green spaces on overweight is unequivocal (OR 0.88 (95% CI 0.72–1.03), p < 0.001, I2 99.6%) and there is no influence on diabetes control. A green space’s direct influence on systolic or diastolic blood pressure is unequivocal. A green space is associated with a decreased prevalence of civilization diseases. Its positive influence, however, is not so strong in children. The short-term influence of green spaces on blood pressure (e.g., taken as a proxy for mental stress) is unequivocal.

1. Introduction

Chronic diseases, commonly known as non-communicable diseases (NCDs), are one of the biggest challenges currently facing humanity worldwide. They are the result of not only genetic and physiological but also environmental and behavioral factors. Among the major diseases related to lifestyle are diabetes, hypertension, and obesity. These diseases severely affect quality of life and well-being. Furthermore, healthcare costs associated with the treatment of NCDs impose a considerable economic burden on health services. Changes in lifestyle could prevent many of these chronic diseases, improve health, and reduce the need for expensive treatments. To lessen the impact of NCDs on individuals and society, a comprehensive approach is needed.
Sustainable development of an urban environment may reduce risks to human well-being. Many researchers indicate a positive correlation between access to green spaces in urban areas and public health. Exposure to green spaces may reduce the risk of several health problems for many reasons, including the ability to perform physical activity (e.g., [1,2,3]). Although studies on the impact of urban green spaces on the health of people suffering from civilization diseases are numerous, most of them were performed on a local scale (within one city or country). There is a lack of research that tackles this subject on a global scale. It is difficult to assess the impact of green spaces on health because existing research results are often difficult to compare. The main reason can be attributed to the use of different green space measures [2]. Some researchers focus on quantity of green space (e.g., green space area as a proportion of the total area within a community, number of green spaces per 10,000 residents [4], the total number of green spaces within 1600 m network buffer from residents’ homes [5], parkland density, parkland per 1000 residents [6], amount of green vegetation around the residential address [7]), while others focus on green space quality (e.g., the number, type, and quality of park features and amenities, and overall incivilities [8], access amenities, park facilities, aesthetics features, park quality concerns [9]) and the use of green space (e.g., time spent on walking and moderate and vigorous physical activity in the last seven days [10]).
Also, the definition of green space within an urban area varies considerably in the existing studies. As well, the range of different types of urban green spaces included in a study can vary. Some researchers took into account only natural elements that exist in urban areas, such as street trees, neighborhood parks, and open spaces [11]; others took into account very vast land-use categories, such as gardens, zoos, parks, cemeteries, suburban natural areas, sports fields, golf courses, amusement parks, and allotment gardens [12]; or such as community parks, farms, gardens, nurseries, linear parks, parkways, metropolitan parks, neighborhood parks, regional parks, squares, etc. [13]; or all types of formal, informal, natural, and young people’s sports green spaces [1]. Some researchers included in their analysis only areas with a limited size, for example: parks larger than 1 hectare, with at least 65% of the land covered with trees [14]; parks of at least 2 hectares in size [1], or 1 hectare [10] or 1 acre [15]; while others defined as a green space any park or garden that was freely accessible to the public, ranging between a regional park (over 400 hectares) and a pocket park (smaller than 0.4 hectares) [16]. The smallest green space unit that was included in the study was 19 square meters in size [17].
A frequent measure used to assess a green space’s accessibility is the distance to the closest green space from home. The recommended distance to a green space is usually based on the concept of having a green space within a 15-min walk from home [18]. Distance buffers used to assess a green space’s impact on health within an urban neighborhood vary considerably in different studies. According to some research, buffers reflecting a range of reasonable walking distances are half a mile, one mile [9], and two miles’ distance from home [19]. Half a mile’s distance can be comparable with 800 m of street network buffer (roughly a half-mile distance) and 1 km [17,20,21,22], which, according to some studies, represents an area that can be accessed in approximately 10–15 min of walking time. In other studies, a 500-m buffer [23] or 400-m buffer [21,24] (roughly a quarter-mile distance) were analyzed. According to several studies, a distance below or equal to a 300-m radius [25], or even a 250-m street network buffer [26], are used.
So far, there is a lack of systematic overview concerning the types of greenery available for urban dwellers and their association with civilization diseases. This study investigates the influence of urban green spaces on the prevalence of three civilization diseases: overweight/obesity, diabetes, and hypertension. Its aim is to summarize the state of this knowledge globally, as well as to identify topics that require further research.

2. Materials and Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in this meta-analysis and systematic review [27].

2.1. Data Source and Study Strategy

The search was run in the PUBMED database from the inception to 1 February 2024. The search algorithm included all possible combinations of keywords associated with the two concepts: civilization health problems and urban green spaces.
A combination of the following Medical Subject Heading (MeSH) terms indexed within the database comprised the search strategy: ‘obesity’ or ‘overweight*’ or ‘body mass index’ or ‘body weight’ or ‘obese’ or ‘body mass gain*’ or ‘body mass loss*’ or ‘hypertension’ or ‘hypertensive’ or ‘blood pressure’ or ‘diabetes’ or ‘diabetic’ or ‘prediabetes’ or ‘prediabetic’ or ‘high blood sugar’ or ‘insulin resistance’ or ‘metabolic syndrome’ or ‘diabetes risk’ or ‘blood sugar control’ or ‘impaired glucose tolerance’ and ‘community garden*’ or ‘urban green space’ or ‘park’ or ‘public garden’ or ‘recreational space’ or ‘local green space’ or ‘residential green space’ or ‘inner city green space’ or ‘green land cover’.
Also, the reference list search was conducted based on the full-text articles meeting the study selection criteria that were identified from the keyword search.
Experimental studies (randomized or controlled trials) published in English were ultimately included in the review, as presented in Figure 1. The publications presenting results from the same intervention or from the same sample were reported together.
All records were also reviewed by an MD, PhD, specialist in internal medicine and cardiology (A. I. K.) with experience in clinical trials to further consider their relevance for inclusion.
The required data were extracted and recorded, including the authors’ names, publication year, location, sample size, and study outcome (with 95% CI, SE, and p-value, respectively).

2.2. Statistical Analysis

The JASP 0.18.3.0 software package was used for the analysis. The results are shown as forest plots with 95% confidence intervals.
To quantify the degree of heterogeneity between studies, the I2 statistic was calculated. The analysis used a random-effects model, which is thought to be a more conservative approach suitable for cases of high heterogeneity. A p-value ≤ 0.05 was considered significant.

3. Results

3.1. Defining Green Space

Apart from reporting the presence/absence of a green space, in some studies, quantitative methods to assess greenery are used.
The most popular are: park space (area), tree canopy cover (and their percentage share in an area examined), number of parks in an examined area and Normalized Difference Vegetation Index (NDVI) [25,28,29,30,31,32,33] and Enhanced Vegetation Index (EVI) [34].
NDVI is a proxy for overall vegetation level, taking values from −1 to +1, where the positive values indicate higher greenness. EVI is similar to NDVI with a corrected atmospheric and soil background.
A green space’s accessibility is described using: the distance to a green space, measured in a straight line or along a street network, or as the presence of a green space in a buffer zone constructed around one’s home with various radii, ranging from 100 m to 3200 m (2 miles).
In studies where the participants self-reported having an accessible park in their neighborhood, the walking distance to the green space was defined as taking less than 15 min to walk to [22,35].

3.2. Overweight/Obesity

The most common way to diagnose overweight and obesity is to calculate a Body Mass Index (BMI), which is calculated by dividing the height by the weight of an individual. These parameters are self-reported by the participants of a study or taken by a medical professional. For children, a BMI z-score is used (BMI adjusted for age and sex) and BMIp95 (actual BMI divided by 95th percentile of BMI for specific age and sex).
Overweight is defined in adults as BMI > 25 kg/m2 and obesity as BMI > 30 kg/m2, while in children, these are defined as BMI > 85 percentile and > 95 percentile, respectively.
In some studies, the waist-to-hip circumference ratio (WHR) [11], percentage of body fat, or skinfold thickness [36] are used as overweight/obesity proxy.

3.2.1. Characteristics of the Included Studies

Thirty studies provided quantitative data adequate to be included in the meta-analysis—17 of them investigated the adult population, while 13 considered children. The fifteen studies remaining (6 in the adult population, 9 in the children population) are included in the review (Table 1).

3.2.2. Key Findings

A green space’s presence, accessibility, and quality are linked to the prevalence of overweight/obesity. The meta-analysis results show that green spaces are associated with a decreased prevalence of overweight/obesity—OR 0.86 (95% CI 0.77–0.95); p < 0.001; I2 99.7% (Figure 2).
The number of studies also allows the performance of separate analyses for the adult and children population, and the results are similar in the adults—OR 0.85 (95% CI 0.75–0.96); p < 0.001; I2 99.4% (Figure 3) but not in the children population—OR 0.88 (95% CI 0.72–1.03); p < 0.001; I2 99.6% (Figure 4).
Interestingly, in 1 study of the adult population [1] and 2 studies of the children population [47,52], the proximity of green space is associated with a higher probability of overweight/obesity.
In the adult population, BMI negatively correlates with a green space in 4 studies [17,42,44,46], while in 2 studies, no difference is observed [43,45].
In the children population, however, BMI negatively correlates with green space only in 3 studies [23,24,56], while in 5 studies, no difference is observed.
In the study concerning maintaining healthy body mass [20], having a green recreational space near the home increases the probability of success.

3.3. Diabetes

For the purpose of the review, type 2 diabetes (this type being a civilization disease) is taken into consideration.
In the chosen studies, an individual with diabetes self-reports a diagnosis, and medication or data are retrieved from medical reports. It is newly diagnosed when glucose concentration in a blood sample exceeds 7 mmol/L after overnight fasting.
To assess the severity of metabolic problems in diabetes, a percentage of glycated hemoglobin (HbA1c) is used [21].
As a proxy for prediabetes, a homeostatic model assessment of insulin resistance (HOMA-IR) is used [7,57].

3.3.1. Characteristics of the Included Studies

Thirteen studies provide quantitative data adequate to be included in the meta-analysis. The four studies remaining are included in the review (Table 2).

3.3.2. Key Findings

A green space’s presence, accessibility, and quality are linked to the prevalence of diabetes. The meta-analysis results show that green space is associated with decreased prevalence of diabetes—OR 0.83 (95% CI 0.79–0.87); p < 0.001; I2 67.5% (Figure 5).
There is an observed negative correlation between green space and HOMA results in children, suggesting a lower risk of diabetes development [7,57] but no difference in the percent of HbA1c, suggesting the lack of green space’s influence on diabetes control [21].

3.4. Hypertension

In the chosen studies, an individual with hypertension self-reports a diagnosis, and medication or data are retrieved from medical reports, and is newly diagnosed when the blood pressure (BP) measured by a medical professional exceeds 140/90 mmHg or 95th percentile adjusted for sex, age, and height in children. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) are reported.

3.4.1. Characteristics of the Included Studies

Five studies provide quantitative data adequate to be included in the meta-analysis. The seven remaining studies are included in the review (Table 3).
Four studies [65,66,67,68] are experimental studies investigating a green space’s short-term influence on blood pressure.

3.4.2. Key Findings

A green space’s presence, accessibility, and quality are linked to the prevalence of hypertension. The meta-analysis results show that green space is associated with a decreased prevalence of hypertension—OR 0.77 (95% CI 0.63–0.92); p < 0.001; I2 84.9% (Figure 6).
As for adults, a green space does not directly influence the systolic nor the diastolic measured BP [13]. In children, however, the results are unequivocal—in one study, there lower SBP associated with green space is reported [69], while the other reported no difference [21].
As for the studies investigating a short-term green space influence on blood pressure, 2 studies report a reduction of DBP [65] or both systolic and diastolic BP [67], and 2 studies do not report differences [66,68].

4. Discussion

The presented review includes highly heterogeneous studies, which allows a wide perspective of the problem to be assessed. However, it should be noted that there is an over-representation of studies from Europe and North America, especially those concerning obesity. This may present some limitations in translating the results to the global population. It is worth noting that 80% of the studies based on green space accessibility directly assessed by the authors are less prone to error than the self-declaration of study participants. Unfortunately, the overweight/obesity prevalence is largely based on self-reported weight and height (53% of the studies), which may not be fully reliable.
As far as NCDs having a complex cause, in the reviewed studies, other factors of possible contribution have been assessed, namely: age, gender, educational level, employment status, and personal income. Some studies also investigated: race [6,15,35,52,56,63], marital status, smoking status [6,12,14], diet [28], food resources in neighborhood [19,45], breastfeeding duration [25], participation in physical activity—usually self-declared [6,26], TV viewing time [5,25], mobility impairments and household ownership of cars [46], type of medical coverage [9,12], neighborhood crime [41], park quality [8,54], and satisfaction with the park [38,45].
It seems that the possibility of =contact with nature, even limited to an urban green space only, is associated with the reduced prevalence of NCDs. However, an urban environment is a very complex system. Some authors claim that modern, more expensive districts usually offer more green spaces of better quality. Yet, they attract tenants with higher incomes, which allows them to follow a well-balanced diet and gives them better healthcare possibilities. On the other hand, there are also districts devoid of green spaces but with high-income tenants who adhere to a healthy lifestyle.
There is also a problem with the interpretation of self-reported access to green space that is of low quality or is in a dangerous neighborhood. Probably, its protective effect will be considerably reduced.
In some studies, the effect of income level on NCDs is more prominent than that of green space. It poses the question of whether it is green space that has a mitigating effect on civilization diseases, or if it is rather a proxy for social status.
A recommended concept of urban planning is having green space within a 15-min walk from home. However, in some studies [1,47,52], the proximity of green space does not prevent obesity. Apart from the quality of green space, this phenomenon may be explained by an assessment of motivation. A good quality, well-equipped park not within walking distance may be frequented by better-motivated users, who, if they already have made the time to get there, stay there for longer and commit more to their exercises.
Interesting is the question of the lack of protective effect of green spaces on overweight prevalence in the children population. Apart from the quality and safety of green spaces and a possible motivation factor, this observation may be explained by the fact that, nowadays, children may need more structured recreational green spaces, as well as the encouragement of parents, to perform physical activities outdoors.
This review helps to outline the problem of urban green spaces and their influence on NCDs. Further, more uniformly and well-designed studies are necessary to determine the qualitative and quantitative need for greenery in a sustainable urban environment, taking into account area per capita, plant composition, and distance from residence.

5. Conclusions

Green spaces are associated with a decreased prevalence of overweight/obesity. Its positive influence, however, is not so strong on children’s BMI, and some studies even report negative influence.
Green space is associated with a decreased prevalence of type 2 diabetes. A green space may prevent the development of type 2 diabetes in children. However, green space does not improve diabetes control.
Green space is associated with a decreased prevalence of hypertension, but no relationship is observed between green space and blood pressure as a continuous variable. The short-term influence of green space on blood pressure (e.g., taken as a proxy for mental stress) is unequivocal.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Coombes, E.; Jones, A.P.; Hillsdon, M. The relationship of physical activity and overweight to objectively measured green space accessibility and use. Soc. Sci. Med. 2010, 70, 816–822. [Google Scholar] [CrossRef] [PubMed]
  2. Klompmaker, J.O.; Hoek, G.; Bloemsma, L.D.; Gehring, U.; Strak, M.; Wijga, A.H.; van den Brink, C.; Brunekreef, B.; Lebret, E.; Janssen, N.A.H. Green space definition affects associations of green space with overweight and physical activity. Environ. Res. 2018, 160, 531–540. [Google Scholar] [CrossRef] [PubMed]
  3. Tsai, W.L.; Davis, A.J.S.; Jackson, L.E. Associations between types of greenery along neighborhood roads and weight status in different climates. Urban For. Urban Green. 2019, 41, 104–107. [Google Scholar] [CrossRef] [PubMed]
  4. Potestio, M.L.; Patel, A.B.; Powell, C.D.; McNeil, D.A.; Jacobson, R.D.; McLaren, L. Is there an association between spatial access to parks/green space and childhood overweight/obesity in Calgary, Canada? Int. J. Behav. Nutr. Phys. Act. 2009, 6, 77. [Google Scholar] [CrossRef] [PubMed]
  5. Veitch, J.; Abbott, G.; Kaczynski, A.T.; Wilhelm Stanis, S.A.; Besenyi, G.M.; Lamb, K.E. Park availability and physical activity, TV time, and overweight and obesity among women: Findings from Australia and the United States. Health Place 2016, 38, 96–102. [Google Scholar] [CrossRef] [PubMed]
  6. West, S.T.; Shores, K.A.; Mudd, L.M. Association of available parkland, physical activity, and overweight in America’s largest cities. J. Public Health Manag. Pract. 2012, 18, 423–430. [Google Scholar] [CrossRef] [PubMed]
  7. Jimenez, M.P.; Oken, E.; Gold, D.R.; Luttmann-Gibson, H.; Requia, W.J.; Rifas-Shiman, S.L.; Gingras, V.; Hivert, M.F.; Rimm, E.B.; James, P. Early life exposure to green space and insulin resistance: An assessment from infancy to early adolescence. Environ. Int. 2020, 142, 105849. [Google Scholar] [CrossRef] [PubMed]
  8. Hobbs, M.; Green, M.A.; Griffiths, C.; Jordan, H.; Saunders, J.; Grimmer, H.; McKenna, J. Access and quality of parks and associations with obesity: A cross-sectional study. SSM Popul. Health 2017, 3, 722–729. [Google Scholar] [CrossRef] [PubMed]
  9. Jiang, Q.; Carlson, J.A.; Kaczynski, A.T.; Shook, R.P.; Besenyi, G.M.; Steel, C.; Moon, M.; Hampl, S.E.; Wilhelm Stanis, S. Neighborhood park access and park characteristics are associated with weight status in youth. Health Place 2023, 83, 103116. [Google Scholar] [CrossRef]
  10. Knobel, P.; Maneja, R.; Bartoll, X.; Alonso, L.; Bauwelinck, M.; Valentin, A.; Zijlema, W.; Borrell, C.; Nieuwenhuijsen, M.; Dadvand, P. Quality of urban green spaces influences residents’ use of these spaces, physical activity, and overweight/obesity. Environ. Pollut. 2021, 271, 116393. [Google Scholar] [CrossRef]
  11. Suppakittpaisarn, P.; Charoenlertthanakit, N.; Yaipimol, E.; Surinseng, V.; Wanitchayapaisit, C.; Kim, G. Relationship between the Duration of Urban Nature and a Lower Waist-Hip Ratio. Int. J. Environ. Res. Public Health 2022, 19, 11606. [Google Scholar] [CrossRef] [PubMed]
  12. Dempsey, S.; Lyons, S.; Nolan, A. Urban green space and obesity in older adults: Evidence from Ireland. SSM Popul. Health 2018, 4, 206–215. [Google Scholar] [CrossRef]
  13. Koh, C.; Kondo, M.C.; Rollins, H.; Bilal, U. Socioeconomic Disparities in Hypertension by Levels of Green Space Availability: A Cross-Sectional Study in Philadelphia, PA. Int. J. Environ. Res. Public Health 2022, 19, 2037. [Google Scholar] [CrossRef]
  14. Tamosiunas, A.; Grazuleviciene, R.; Luksiene, D.; Dedele, A.; Reklaitiene, R.; Baceviciene, M.; Vencloviene, J.; Bernotiene, G.; Radisauskas, R.; Malinauskiene, V.; et al. Accessibility and use of urban green spaces, and cardiovascular health: Findings from a Kaunas cohort study. Environ. Health 2014, 13, 20. [Google Scholar] [CrossRef]
  15. Ohri-Vachaspati, P.; Lloyd, K.; Delia, D.; Tulloch, D.; Yedidia, M.J. A closer examination of the relationship between children’s weight status and the food and physical activity environment. Prev. Med. 2013, 57, 162–167. [Google Scholar] [CrossRef] [PubMed]
  16. Hajna, S.; Nafilyan, V.; Cummins, S. Associations between residential greenspace exposure and mortality in 4 645 581 adults living in London, UK: A longitudinal study. Lancet Planet. Health 2023, 7, e459–e468. [Google Scholar] [CrossRef]
  17. Müller, G.; Harhoff, R.; Rahe, C.; Berger, K. Inner-city green space and its association with body mass index and prevalent type 2 diabetes: A cross-sectional study in an urban German city. BMJ Open 2018, 8, e019062. [Google Scholar] [CrossRef] [PubMed]
  18. Dadvand, P.; Villanueva, C.; Font-Ribera, L.; Martinez, D.; Basagaña, X.; Belmonte, J.; Vrijheid, M.; Grazuleviciene, R.; Kogevinas, M.; Nieuwenhuijsen, M.J. Risks and Benefits of Green Spaces for Children: A Cross-Sectional Study of Associations with Sedentary Behavior, Obesity, Asthma, and Allergy. Environ. Health Perspect. 2014, 122, 1329–1335. [Google Scholar] [CrossRef]
  19. Hsieh, S.; Klassen, A.C.; Curriero, F.C.; Caulfield, L.E.; Cheskin, L.J.; Davis, J.N.; Goran, M.I.; Weigensberg, M.J.; Spruijt-Metz, D. Built environment associations with adiposity parameters among overweight and obese Hispanic youth. Prev. Med. Rep. 2015, 2, 406–412. [Google Scholar] [CrossRef]
  20. Fiechtner, L.; Cheng, E.R.; Lopez, G.; Sharifi, M.; Taveras, E.M. Multilevel Correlates of Healthy BMI Maintenance and Return to a Healthy BMI among Children in Massachusetts. Child Obes. 2017, 13, 146–153. [Google Scholar] [CrossRef]
  21. Ribeiro, A.I.; Tavares, C.; Guttentag, A.; Barros, H. Association between neighbourhood green space and biological markers in school-aged children. Findings from the Generation XXI birth cohort. Environ. Int. 2019, 132, 105070. [Google Scholar] [CrossRef] [PubMed]
  22. Frank, L.D.; Adhikari, B.; White, K.R.; Dummer, T.; Sandhu, J.; Demlow, E.; Hu, Y.; Hong, A.; Van den Bosch, M. Chronic disease and where you live: Built and natural environment relationships with physical activity, obesity, and diabetes. Environ. Int. 2022, 158, 106959. [Google Scholar] [CrossRef] [PubMed]
  23. Wolch, J.; Jerrett, M.; Reynolds, K.; McConnell, R.; Chang, R.; Dahmann, N.; Brady, K.; Gilliland, F.; Su, J.G.; Berhane, K. Childhood obesity and proximity to urban parks and recreational resources: A longitudinal cohort study. Health Place 2011, 17, 207–214. [Google Scholar] [CrossRef] [PubMed]
  24. White, M.J.; McClure, E.; Killeen, J.; Howard, J.; Skinner, A.C.; Spears, T.; Perrin, E.M. Changes in the recreational built environment and youth body mass index. Acad. Pediatr. 2021, 21, 76–83. [Google Scholar] [CrossRef] [PubMed]
  25. Petraviciene, I.; Grazuleviciene, R.; Andrusaityte, S.; Dedele, A.; Nieuwenhuijsen, M.J. Impact of the Social and Natural Environment on Preschool-Age Children Weight. Int. J. Environ. Res. Public Health 2018, 15, 449. [Google Scholar] [CrossRef] [PubMed]
  26. Molina-García, J.; Menescardi, C.; Estevan, I.; Queralt, A. Associations between Park and Playground Availability and Proximity and Children’s Physical Activity and Body Mass Index: The BEACH Study. Int. J. Environ. Res. Public Health 2022, 19, 250. [Google Scholar] [CrossRef] [PubMed]
  27. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ 2009, 339, b2535. [Google Scholar] [CrossRef] [PubMed]
  28. Zhou, W.; Wang, Q.; Kadier, A.; Wang, W.; Zhou, F.; Li, R.; Ling, L. The role of residential greenness levels, green land cover types and diversity in overweight/obesity among older adults: A cohort study. Environ. Res. 2023, 217, 114854. [Google Scholar] [CrossRef] [PubMed]
  29. Clark, C.; Sbihi, H.; Tamburic, L.; Brauer, M.; Frank, L.D.; Davies, H.W. Association of Long-Term Exposure to Transportation Noise and Traffic-Related Air Pollution with the Incidence of Diabetes: A Prospective Cohort Study. Environ. Health Perspect. 2017, 125, 087025. [Google Scholar] [CrossRef]
  30. Doubleday, A.; Knott, C.J.; Hazlehurst, M.F.; Bertoni, A.G.; Kaufman, J.D.; Hajat, A. Neighborhood green space and risk of type 2 diabetes in a prospective cohort: The Multi-Ethncity Study of Atherosclerosis. Environ. Health 2022, 21, 18. [Google Scholar] [CrossRef]
  31. Fan, S.; Xue, Z.; Yuan, J.; Zhou, Z.; Wang, Y.; Yang, Z. Associations of Residential Greenness with Diabetes Mellitus in Chinese Uyghur Adults. Int. J. Environ. Res. Public Health 2019, 16, 5131. [Google Scholar] [CrossRef]
  32. Li, R.; Chen, G.; Jiao, A.; Lu, Y.; Guo, Y.; Li, S.; Wang, C.; Xiang, H. Residential Green and Blue Spaces and Type 2 Diabetes Mellitus: A Population-Based Health Study in China. Toxics 2021, 9, 11. [Google Scholar] [CrossRef]
  33. Dzhambov, A.M.; Markevych, I.; Lercher, P. Greenspace seems protective of both high and low blood pressure among residents of an Alpine valley. Environ. Int. 2018, 121 Pt 1, 443–452. [Google Scholar] [CrossRef]
  34. Khan, J.R.; Sultana, A.; Islam, M.M.; Biswas, R.K. A negative association between the prevalence of diabetes and urban residential area greenness detected in the nationwide assessment of urban Bangladesh. Sci. Rep. 2021, 11, 19513. [Google Scholar] [CrossRef] [PubMed]
  35. Melius, J. Overweight and obesity in minority children and implications for family and community social work. Soc. Work Public Health 2013, 28, 119–128. [Google Scholar] [CrossRef]
  36. Lovasi, G.S.; Jacobson, J.S.; Quinn, J.W.; Neckerman, K.M.; Ashby-Thompson, M.N.; Rundle, A. Is the environment near home and school associated with physical activity and adiposity of urban preschool children? J. Urban Health 2011, 88, 1143–1157. [Google Scholar] [CrossRef] [PubMed]
  37. Cunningham-Myrie, C.A.; Theall, K.P.; Younger, N.O.; Mabile, E.A.; Tulloch-Reid, M.K.; Francis, D.K.; McFarlane, S.R.; Gordon-Strachan, G.M.; Wilks, R.J. Associations between neighborhood effects and physical activity, obesity, and diabetes: The Jamaica Health and Lifestyle Survey 2008. J. Clin. Epidemiol. 2015, 68, 970–978. [Google Scholar] [CrossRef]
  38. Fermino, R.; Reis, R.; Hallal, P.C.; Kaczynski, A.T. Who are the users of urban parks? A study with adults from Curitiba, Brazil. J. Phys. Act. Health 2015, 12, 58–67. [Google Scholar] [CrossRef] [PubMed]
  39. Mathis, A.L.; Rooks, R.N.; Tawk, R.H.; Kruger, D.J. Neighborhood Influences and BMI in Urban Older Adults. J. Appl. Gerontol. 2017, 36, 692–708. [Google Scholar] [CrossRef]
  40. Prince, S.A.; Kristjansson, E.A.; Russell, K.; Billette, J.M.; Sawada, M.C.; Ali, A.; Tremblay, M.S.; Prud’homme, D. Relationships between neighborhoods, physical activity, and obesity: A multilevel analysis of a large Canadian city. Obesity 2012, 20, 2093–2100. [Google Scholar] [CrossRef]
  41. Sullivan, S.M.; Brashear, M.M.; Broyles, S.T.; Rung, A.L. Neighborhood environments and obesity among Afro-Caribbean, African American, and Non-Hispanic white adults in the United States: Results from the National Survey of American Life. Prev. Med. 2014, 61, 1–5. [Google Scholar] [CrossRef] [PubMed]
  42. Gilbert, A.S.; Salvo, D.; Tabak, R.G.; Haire-Joshu, D. Does the neighborhood built environment moderate the effectiveness of a weight-loss intervention for mothers with overweight or obesity? Findings from the Healthy Eating and Active Living Taught at Home (HEALTH) study. Int. J. Behav. Nutr. Phys. Act. 2022, 19, 130. [Google Scholar] [CrossRef] [PubMed]
  43. Omodior, O.; Ramos, W.D. Social Determinants of Health-Related Quality of Life: A Recreation Setting Analysis. Health Promot. Pract. 2020, 21, 952–961. [Google Scholar] [CrossRef] [PubMed]
  44. Rundle, A.; Quinn, J.; Lovasi, G.; Bader, M.; Yousefzadeh, P.; Weiss, C.; Neckerman, K. Associations between Body Mass Index and Park Proximity, Size, Cleanliness, and Recreational Facilities. Am. J. Health Promot. 2013, 27, 262–269. [Google Scholar] [CrossRef] [PubMed]
  45. Tseng, M.; Thornton, L.E.; Lamb, K.E.; Ball, K.; Crawford, D. Is neighborhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighborhoods. Health Place 2014, 30, 20–27. [Google Scholar] [CrossRef] [PubMed]
  46. Xiaohelaiti, X.; Liu, X.; Li, C.; Wang, T.; Wu, J.; Peng, B.; Zhang, Y. Neighborhood environment and body mass index in community-dwelling older adults in China: The mediating role of transport-related physical activity. Geriatr. Nurs. 2023, 55, 304–310. [Google Scholar] [CrossRef] [PubMed]
  47. Bloemsma, L.D.; Wijga, A.H.; Klompmaker, J.O.; Janssen, N.A.H.; Smit, H.A.; Koppelman, G.H.; Brunekreef, B.; Lebret, E.; Hoek, G.; Gehring, U. The associations of air pollution, traffic noise and green space with overweight throughout childhood: The PIAMA birth cohort study. Environ. Res. 2019, 169, 348–356. [Google Scholar] [CrossRef] [PubMed]
  48. Pereira, M.; Nogueira, H.; Padez, C. The role of urban design in childhood obesity: A case study in Lisbon, Portugal. Am. J. Hum. Biol. 2019, 31, e23220. [Google Scholar] [CrossRef]
  49. Reuben, A.; Rutherford, G.W.; James, J.; Razani, N. Association of neighborhood parks with child health in the United States. Prev. Med. 2020, 141, 106265. [Google Scholar] [CrossRef]
  50. Schalkwijk, A.A.H.; van der Zwaard, B.C.; Nijpels, G.; Elders, P.J.M.; Platt, L. The impact of greenspace and condition of the neighbourhood on child overweight. Eur. J. Public Health 2018, 28, 88–94. [Google Scholar] [CrossRef]
  51. Schüle, S.A.; Fromme, H.; Bolte, G. Built and socioeconomic neighborhood environments and overweight in preschool aged children. A multilevel study to disentangle individual and contextual relationships. Environ. Res. 2016, 150, 328–336. [Google Scholar] [CrossRef] [PubMed]
  52. Sánchez-Valdivia, N.; Pérez-del-Pulgar, C.; de Bont, J.; Anguelovski, I.; López-Gay, A.; Pistillo, A.; Triguero-Mas, M.; Duarte-Salles, T. Residential Proximity to Urban Play Spaces and Childhood Overweight and Obesity in Barcelona, Spain: A Population-Based Longitudinal Study. Int. J. Environ. Res. Public Health 2022, 19, 13676. [Google Scholar] [CrossRef] [PubMed]
  53. Yang, Y.; Jiang, Y.; Xu, Y.; Mzayek, F.; Levy, M. A cross-sectional study of the influence of neighborhood environment on childhood overweight and obesity: Variation by age, gender, and environment characteristics. Prev. Med. 2018, 108, 23–28. [Google Scholar] [CrossRef] [PubMed]
  54. Bird, M.; Datta, G.D.; van Hulst, A.; Cloutier, M.S.; Henderson, M.; Barnett, T.A. A park typology in the QUALITY cohort: Implications for physical activity and truncal fat among youth at risk of obesity. Prev. Med. 2016, 90, 133–138. [Google Scholar] [CrossRef] [PubMed]
  55. Goldsby, T.U.; George, B.J.; Yeager, V.A.; Sen, B.P.; Ferdinand, A.; Sims, D.M.T.; Manzella, B.; Cockrell Skinner, A.; Allison, D.B.; Menachemi, N. Urban Park Development and Pediatric Obesity Rates: A Quasi-Experiment Using Electronic Health Record Data. Int. J. Environ. Res. Public Health 2016, 13, 411. [Google Scholar] [CrossRef] [PubMed]
  56. Hughey, M.S.; Kaczynski, A.T.; Child, S.; Moore, J.B.; Porter, D.; Hibbert, J. Green and lean: Is neighborhood park and playground availability associated with youth obesity? Variations by gender, socioeconomic status, and race/ethnicity. Prev. Med. 2017, 95, S101–S108. [Google Scholar] [CrossRef]
  57. Astell-Burt, T.; Feng, X.; Kolt, G.S. Is neighborhood green space associated with a lower risk of type 2 diabetes? Evidence from 267,072 Australians. Diabetes Care 2014, 37, 197–201. [Google Scholar] [CrossRef]
  58. Dalton, A.M.; Jones, A.P.; Sharp, S.J.; Cooper, A.J.; Griffin, S.; Wareham, N.J. Residential neighborhood green space is associated with reduced risk of incident diabetes in older people: A prospective cohort study. BMC Public Health 2016, 16, 1171. [Google Scholar] [CrossRef]
  59. Lee, J.J.; Hwang, S.J.; Mutalik, K.; Corey, D.; Joyce, R.; Block, J.P.; Fox, C.S.; Powell-Wiley, T.M. Association of built environment characteristics with adiposity and glycaemic measures. Obes. Sci. Pract. 2017, 3, 333–341. [Google Scholar] [CrossRef]
  60. Yang, T.; Gu, T.; Xu, Z.; He, T.; Li, G.; Huang, J. Associations of residential green space with incident type 2 diabetes and the role of air pollution: A prospective analysis in UK Biobank. Sci. Total Environ. 2023, 866, 161396. [Google Scholar] [CrossRef]
  61. Hsieh, S.; Klassen, A.C.; Curriero, F.C.; Caulfield, L.E.; Cheskin, L.J.; Davis, J.N.; Goran, M.I.; Weigensberg, M.J.; Spruijt-Metz, D. Fast-food restaurants, park access, and insulin resistance among Hispanic youth. Am. J. Prev. Med. 2014, 46, 378–387. [Google Scholar] [CrossRef] [PubMed]
  62. Abbasi, B.; Pourmirzaei, M.; Hariri, S.; Heshmat, R.; Qorbani, M.; Dadvand, P.; Kelishadi, R. Subjective Proximity to Green Spaces and Blood Pressure in Children and Adolescents: The CASPIAN-V Study. J. Environ. Public Health 2020, 2020, 8886241. [Google Scholar] [CrossRef] [PubMed]
  63. Adhikari, B.; Delgado-Ron, J.A.; Van den Bosch, M.; Dummer, T.; Hong, A.; Sandhu, J.; Demlow, E.; Hu, Y.; Frank, L.D. Community design and hypertension: Walkability and park access relationships with cardiovascular health. Int. J. Hyg. Environ. Health 2021, 237, 113820. [Google Scholar] [CrossRef] [PubMed]
  64. Kjelstrom, S.; Hass, R.W.; McIntire, R.K. Association Between Lack of Access to a Neighborhood Park and High Blood Pressure in the Philadelphia Metropolitan Area. Prev. Chronic Dis. 2023, 20, 230098. [Google Scholar] [CrossRef] [PubMed]
  65. Grazuleviciene, R.; Vencloviene, J.; Kubilius, R.; Grizas, V.; Danileviciute, A.; Dedele, A.; Andrusaityte, S.; Vitkauskiene, A.; Steponaviciute, R.; Nieuwenhuijsen, M.J. Tracking Restoration of Park and Urban Street Settings in Coronary Artery Disease Patients. Int. J. Environ. Res. Public Health 2016, 13, 550. [Google Scholar] [CrossRef] [PubMed]
  66. Lanki, T.; Siponen, T.; Ojala, A.; Korpela, K.; Pennanen, A.; Tiittanen, P.; Tsunetsugu, Y.; Kagawa, T.; Tyrväinen, L. Acute effects of visits to urban green environments on cardiovascular physiology in women: A field experiment. Environ. Res. 2017, 159, 176–185. [Google Scholar] [CrossRef] [PubMed]
  67. Pratiwi, P.I.; Xiang, Q.; Furuya, K. Physiological and Psychological Effects of Viewing Urban Parks in Different Seasons in Adults. Int. J. Environ. Res. Public Health 2019, 16, 4279. [Google Scholar] [CrossRef]
  68. Tsao, T.-M.; Hwang, J.-S.; Lin, S.-T.; Wu, C.; Tsai, M.-J.; Su, T.-C. Forest Bathing Is Better than Walking in Urban Park: Comparison of Cardiac and Vascular Function between Urban and Forest Parks. Int. J. Environ. Res. Public Health 2022, 19, 3451. [Google Scholar] [CrossRef]
  69. Dzhambov, A.M.; Lercher, P.; Markevych, I.; Browning, M.H.E.M.; Rüdisser, J. Natural and built environments and blood pressure of Alpine schoolchildren. Environ. Res. 2022, 204 Pt A, 111925. [Google Scholar] [CrossRef]
Sustainability 16 03925 g001
Figure 1. Review process diagram.
Figure 1. Review process diagram.
Sustainability 16 03925 g001
Sustainability 16 03925 g002
Figure 2. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity [1,2,3,4,5,6,8,9,10,11,12,14,15,18,22,25,28,35,37,38,39,40,41,47,48,49,50,51,52,53].
Figure 2. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity [1,2,3,4,5,6,8,9,10,11,12,14,15,18,22,25,28,35,37,38,39,40,41,47,48,49,50,51,52,53].
Sustainability 16 03925 g002
Sustainability 16 03925 g003
Figure 3. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity in the adult population [1,2,3,5,6,8,10,11,12,14,22,28,37,38,39,40,41].
Figure 3. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity in the adult population [1,2,3,5,6,8,10,11,12,14,22,28,37,38,39,40,41].
Sustainability 16 03925 g003
Sustainability 16 03925 g004
Figure 4. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity in the children population [4,9,15,18,25,35,47,48,49,50,51,52,53].
Figure 4. Forest plot showing the influence of green spaces on the prevalence of overweight/obesity in the children population [4,9,15,18,25,35,47,48,49,50,51,52,53].
Sustainability 16 03925 g004
Sustainability 16 03925 g005
Figure 5. Forest plot showing the influence of green spaces on the prevalence of diabetes [14,17,22,29,30,31,32,34,37,58,59,60,61].
Figure 5. Forest plot showing the influence of green spaces on the prevalence of diabetes [14,17,22,29,30,31,32,34,37,58,59,60,61].
Sustainability 16 03925 g005
Sustainability 16 03925 g006
Figure 6. Forest plot showing the influence of green spaces on the prevalence of hypertension [14,33,62,63,64].
Figure 6. Forest plot showing the influence of green spaces on the prevalence of hypertension [14,33,62,63,64].
Sustainability 16 03925 g006
Table 1. Summary of the characteristics of the 45 included studies.
Table 1. Summary of the characteristics of the 45 included studies.
Author, Publication YearLocationSample SizeDescriptionStudy Outcome 1
Coombes E., 2010 [1]United Kingdom6803green space < 100 m from home—overweight/obesity (self-reported BMI)OR 1.2 (95% CI 1.04–1.39)
Cunningham-Myrie L.A., 2015 [37] Jamaica2848recreational space in walking distance (self-reported)—overweight/obesity (measured BMI)OR 1.03 (95% CI 0.86–1.23)
Dempsey S., 2018 [12]Ireland5783% of green space in buffer zone 1600 m from home—obesity (measured BMI)OR 0.356 (SE 0.103)
Fermino R., 2015 [38]Brazil1461regular user of park < 500 m from home (self-reported)—overweight/obesity (self-reported BMI)PR 0.89 (95% CI 0.79–1.0)
Hobbs M., 2017 [8]United Kingdom4723access to park—obesity (self-reported BMI)OR 1.37 (95% CI 0.78–2.36)
Klompmaker J.O., 2018 [2]Netherlands354,827distance to park 500–1000 m—overweight (self-reported BMI)OR 0.95 (95% CI 0.92–0.98)
Knobel P., 2021 [10]Spain2053access to park in buffer zone 300 m from home—overweight/obesity (self-reported BMI)OR 0.92 (95% CI 0.82–1.03)
Mathis A.L., 2017 [39]USA217 (>65 years old)park in neighborhood (self-reported)—obesity (self-reported BMI)OR 0.37 (95% CI 0.14–0.98)
Prince S.A., 2012 [40]Canada4727park area per 1000 residents—overweight/obesity (self-reported BMI)OR 0.97 (95% CI 0.78–1.2)
Sullivan S.M., 2014 [41]USA6082green space in neighborhood (self-reported)—obesity (self-reported BMI)OR 0.68 (95% CI 0.47–0.98)
Suppakittpaisarn P., 2022 [11]Thailand111short distance to green space (self-reported)—waist-hip ratio (self-reported)OR 0.82 (95% CI 0.48–1.47)
Tamosiunas A., 2014 [14]Lithuania5112regular user of park in neighborhood (self-reported)—overweight (measured BMI)OR 0.99 (95% CI 0.85–1.16)
Tsai W-L., 2019 [3]USA1,429,946green space in buffer zone 500 m from home—overweight (self-reported BMI)OR 0.86 (95% CI 0.86–0.87)
West S.T., 2012 [6]USA99,534park density—overweight (self-reported BMI)OR 0.85 (95% CI 0.76–0.95)
Zhou W., 2023 [28]China8318NDVI—overweight/obesity (measured BMI)HR 0.74 (95% CI 0.63–0.88)
Frank L.D., 2022 [22]Canada34,390park available in walking distance—obesity (self-reported BMI)OR 0.57 (95% CI 0.48–0.68)
Veitch J., 2016 [5]Australia1848, femalesnumber of parks in buffer zone 1600 m from home—overweight/obesity (self-reported BMI)OR 0.98 (95% CI 0.97–0.99)
Gilbert A.S., 2022 [42]USA 151, femalesshort distance to park—BMI; low park density BMI—(measured)Β = −2.23, SE 0.71, p < 0.01;
β = −2.08, SE 0.61, p < 0.01
Müller S., 2018 [17]Germany1312BMI (measured)—with access to green space < 800 m vs. >800 m27.1 (26.7–27.5) vs. 27.8 (27.5–28.2) kg/m², p = 0.01
Omodior O., 2020 [43]USA169BMI of frequent park users vs. non-users (self-reported)26.61 +/− 8.99 vs. 26.06 +/− 7.05 kg/m², p = 0.7
Rundle A., 2013 [44]USA13,102% parks in buffer zone 0.5 miles from home—BMI (self-reported) Β = −1.67 (95% CI from −2.74 to −0.61)
Tseng M., 2014 [45]Australia3786, femalesurban park space—BMI (self-reported)Β = −0.24, SE 0.36, p = 0.47
Xiaohelaiti X., 2023 [46]China197park accessibility in buffer zone 1000 m from home—BMI (self-reported)Β = −0.242, p < 0.05
Bloemsma L.D., 2019 [47]Netherlands3680, childrendistance to park—obesity (self-reported BMI)OR 1.49 (95% CI 1.17–1.92)
Dadvand P., 2014 [18]Spain3178, childrenpark < 300 m from home—overweight/obesity (self-reported BMI)OR 0.94 (95% CI 0.77–1.13)
Jiang Q., 2023 [9]USA20,638, childrennumber of parks in buffer zone 0.5 miles from home—overweight/obesity (measured BMI)OR 0.97 (95% CI 0.95–0.99)
Melius J., 2013 [35]USA6669, childrenpark/playground in walking distance (self-reported)—overweight/obesity (self reported BMI)OR 0.82 (95% CI 0.68–0.99)
Ohri-Vachaspati P., 2013 [15]USA702, childrenpark in buffer zone 0.5 miles from home—overweight/obesity (self-reported BMI)OR 0.41 (95% CI 0.21–0.81)
Pereira M., 2019 [48]Portugal929, childrenurban green space in neighborhood—overweight/obesity (measured BMI)OR 0.44 (95% CI 0.25–0.8)
Petraviciene I., 2018 [25]Lithuania1489, childrenNDVI > median+ distance to park < 300 m—overweight/obesity (self-reported BMI)OR 0.48 (95% CI 0.24–0.95)
Potestio M.L., 2009 [4]Canada6772, children% of park area in buffer zone 800 m from home—overweight/obesity (measured BMI)OR 1.35 (95% CI 0.82–2.22)
Reuben A., 2020 [49]USA3790, childrenpark in neighborhood (self-reported)—overweight/obesity (self-reported BMI)OR 0.8 (95% CI 0.73–0.88)
Schalkwijk A., 2018 [50]United Kingdom6467, childrenhighest vs. lowest tertile of green space—overweight/obesity (measured BMI)OR 0.88 (95% CI 0.79–0.98)
Schüle S.A., 2016 [51]Germany3499, childrenpark space per resident high vs. low—overweight (measured BMI) OR 0.82 (95% CI 0.66–1.02)
Sanchez-Valdivia N., 2022 [52]Spain75,608, childrengreen play space < 300 m from home—overweight/obesity (measured BMI)HR 1.01 (95% CI 1.0–1.03)
Yang Y., 2018 [53]USA41,283, childrenshort distance to park—overweight/obesity (measured BMI)OR 0.99 (95% CI 0.99–1.0)
Bird M., 2016 [54]Canada380, childrenpark in buffer zone 500–1000 m from home—% of over-weight/obesity (measured BMI)41.3% vs. 43.6%, p = 0.6
Fiechtner L., 2017 [20]USA33,272, childrenrecreational space in buffer zone 800 m from home—maintaining healthy body mass (measured BMI)OR 1.2 (95% CI 1.1–1.31)
Goldsby T.U., 2016 [55]USA1443, childrendistance to a new park—BMI z-score (measured BMI)Β = 0.04, SE 0.025, p = 0.4
Hsieh S., 2015 [19]USA576, childrenpark area in buffer zone 0.5 miles from home—BMI z-score (measured BMI)R = 0.024, p = NS
Hughey S.M., 2017 [56]USA13,469, childrennumber of parks in neighborhood—BMI percentile (measured BMI)females: β = −2.2, p < 0.05
males: β = 1.5, p = 0.08
Lovasi G.S., 2011 [36]USA428, childrenpark accessible in buffer zone 500 m from home—BMI z-score and skinfold thickness (measured)Β = −0.04 (95% CI from—0.19 to 0.11) and β = −1.0 (95% CI from −1.9 to −0.1)
Molina-Garcia J., 2022 [26]Spain83, childrenpark area and number of parks in buffer zone 500 m from home—BMI percentile (measured BMI)β = 0 and β = 0.01, p = NS
White M.J., 2021 [24]USA8282, childrenpark in buffer zone 400 m from home—decrease in BMIp95 (measured BMI)Β = −2.85 (95% CI from −5.47 to −0.24), p = 0.032
Wolch J., 2011 [23]USA3173, childrenpark space in buffer zone 500 m from home—overweight/obesity (measured BMI)Β = −0.0094, p < 0.005
1 Values in bold are statistically significant.
Table 2. Summary of the characteristics of the 17 included studies.
Table 2. Summary of the characteristics of the 17 included studies.
Author, Publication YearLocationSample SizeDescriptionStudy Outcome
Astell-Burt T., 2014 [58]Australia267,072% of green space in buffer zone 1000 m from home—diabetes OR 0.87 (95% CI 0.83–0.92)
Clark Ch., 2017 [29]Canada380,738NDVI in buffer zone 100 m from home—diabetes OR 0.83 (95% CI 0.81–0.85)
Cunningham-Myrie L.A., 2015 [37]Jamaica2848recreational space in walking distance (self-reported)—diabetes OR 0.99 (95% CI 0.74–1.32)
Dalton AM., 2016 [59]United Kingdom25,865green space in buffer zone 800 m from home Q4 vs. Q1—diabetesHR 0.81 (95% CI 0.67–0.99)
Doubleday A., 2022 [30]USA5574NDVI in buffer zone 1000 m from home—diabetes HR 0.79 (95% CI 0.63–0.99)
Fan S., 2019 [31]China4670NDVI in buffer zone 1000 m from home—diabetes OR 0.93 (95% CI 0.87–1.00)
Frank L.D., 2022 [22]Canada34,390park available in walking distance—diabetes OR 0.63 (95% CI 0.47–0.84)
Khan J.R., 2021 [34]Bangladesh2367EVI in buffer zone 2000 m from home—diabetes OR 0.806 (95% CI 0.694–0.936)
Lee J.J., 2017 [60]USA4010% green space in census block group—diabetes OR 0.7 (95% CI 0.41–1.19)
Li R., 2021 [32]China39,019NDVI in neighborhood—diabetesOR 0.81 (95% CI 0.78–0.84)
Müller S., 2018 [17]Germany1312access to green space < 800 m—diabetes OR 0.51 (95% CI 0.33–0.79)
Tamosiunas A., 2014 [14]Lithuania5112regular use of park in neighborhood (self-reported)—diabetes OR 0.72 (95% CI 0.58–0.90)
Yang T., 2023 [61]United Kingdom379,238% green space in buffer zone 300 m from home—diabetes OR 0.86 (95% CI 0.8–0.92)
Hajna S., 2023 [16]United Kingdom4,645,581distance to the nearest green space—mortality due to diabetesHR 1.0001 (95% CI 0.993–1.0073)
Hsieh S., 2014 [57]USA453, childrenpark area in buffer zone 0.5 miles from home—HOMA females: r = −0.153, p < 0.05
Jimenez M.P., 2020 [7]USA460, childrenliving in the highest tertile of green space at infancy—HOMA in adolescence0.15 U lower HOMA-IR (95% CI from −0.23 to −0.06)
Ribeiro AI., 2019 [21]Portugal 3108, childrengreen space in buffer zone 400 m from home—HbA1c 5.22% vs. 5.23%, p = 0.8
Table 3. Summary of the characteristics of the 12 included studies.
Table 3. Summary of the characteristics of the 12 included studies.
Author, Publication YearLocationSample SizeDescriptionStudy Outcome
Abbasi B., 2020 [62]Iran12,340, childrengreen space at <15 min from home (self-reported)—hypertension OR 0.8 (95% CI 0.82–1.16)
Adhikari B., 2021 [63]Canada11,972park availability in walking distance—hypertension OR 0.75 (95% CI 0.64–0.88)
Dzhambov A., 2018 [33]Austria555NDVI in buffer zone 500 m from home—hypertension OR 0.64 (95% CI 0.52–0.78)
Kjelstrom S., 2023 [64]USA3605park in neighborhood (self-reported)—hypertension OR 0.6 (95% CI 0.5–0.7)
Tamosiunas A., 2014 [14]Lithuania5112regular user of park in neighborhood (self-reported)—hypertension OR 0.92 (95% CI 0.81–1.04)
Grazuleviciene R., 2016 [65]Lithuania2030-min walk on 7 consecutive days in park and urban space—BP DBP reduction in park by 6 mmHg, p < 0.01; by 2 mmHg in urban space p = NS
Koh C., 2022 [13]USA3887NDVI low/medium/high—hypertension 39% vs. 50% vs. 40%, p = NS
Lanki T., 2017 [66]Finland40, females15-min sitting and 30-min walk in park—BP ΔSBP 0.44 +/− 1.23 mmHg; ΔDBP 0.39 +/− 0.9 mmHg, p = NS
Pratiwi P.I., 2019 [67]Japan1215-min sitting in park vs. city centrum—BP129.1/76.0 mmHg vs. 142.1/83.6 mmHg, for SPB p = 0.0017 and for DBP p = 0.0044
Tsao T-M., 2022 [68]Taiwan251.5 h in park—BP SBP before 113.82 mmHg and after 114.11 mmHg; DBP before 72.72 mmHg and after 73.06 mmHg, p = NS
Dzhambov AM., 2022 [69]Austria/Italy1251, childrenNDVI in buffer zone 450 m from home—BP for SBP β = −0.69 (95% CI from −1.32 to −0.05), p < 0.05; for DBP β = −0.5 (95% CI from −1.08 to 0.08), p = NS
Ribeiro AI., 2019 [21]Portugal 3108, childrengreen space in buffer zone 400 m from home—BP SBP 105.05 vs. 105.71 mmHg, p = 0.1; DBP 69.75 vs. 70.30 mmHg, p = 0.2
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kaczyńska, M. Urban Green Spaces’ Influence on Civilization Diseases—Meta-Analysis and Critical Review. Sustainability 2024, 16, 3925. https://doi.org/10.3390/su16103925

AMA Style

Kaczyńska M. Urban Green Spaces’ Influence on Civilization Diseases—Meta-Analysis and Critical Review. Sustainability. 2024; 16(10):3925. https://doi.org/10.3390/su16103925

Chicago/Turabian Style

Kaczyńska, Małgorzata. 2024. "Urban Green Spaces’ Influence on Civilization Diseases—Meta-Analysis and Critical Review" Sustainability 16, no. 10: 3925. https://doi.org/10.3390/su16103925

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

Article Metrics

Back to TopTop