Associations between Body Mass Index and Urban "Green" Streetscape in Cleveland, Ohio, USA

Neighbourhoods' social, built, and natural environment characteristics and body mass index in Latin American cities

BACKGROUND

Features of neighbourhoods affect body mass index (BMI) but this has been poorly acknowledged within the highly heterogeneous and unequal contexts of Latin American cities. We evaluated associations between social, built, and natural environment characteristics of neighbourhoods with BMI, and investigated whether these associations were modified by individual socioeconomic position (SEP).

METHODS

We linked individual data (n = 43 968) from national health surveys to data on neighbourhoods (n = 3428) and cities (n = 165) in Argentina, Chile, Colombia, and Mexico. Linear mixed models were used to estimate associations between neighbourhood education, intersection density, and greenness with BMI, adjusting for individual- and city-level characteristics.

RESULTS

Associations between neighbourhood education and BMI varied by country, in both magnitude and direction. In Argentina and Chile, higher neighbourhood education was associated with lower BMI. This negative association was also observed among women in Colombia and Mexico, although it was weaker. Among men in Colombia and Mexico, however, the association was positive. Associations of neighbourhood intersection density and greenness with BMI were less robust. In general, we did not find strong evidence of effect modification by individual SEP.

CONCLUSION

Neighbourhood education is associated with BMI beyond individual and city characteristics, although the associations are heterogenous across countries and by gender. Associations with built and natural features were less clear. Our results highlight the relevance of context-specific analysis for planning interventions that are aimed to reduce BMI and its unequal distribution in Latin American cities.

Association of greenspaces exposure with cardiometabolic risk factors: a systematic review and meta-analysis

BACKGROUND

Cardiometabolic conditions are major contributors to the global burden of disease. An emerging body of evidence has associated access to and surrounding public open spaces (POS) and greenspace with cardiometabolic risk factors, including obesity, body mass index (BMI), hypertension (HTN), blood glucose (BG), and lipid profiles. This systematic review aimed to synthesize this evidence.

METHODS

This systematic review was conducted based on the PRISMA guidelines. Four electronic databases including Web of Science, PubMed, Scopus, and Google Scholar were searched for eligible articles published until July 2023. All observational studies which assessed the association of greenspace and POS with cardiometabolic risk factors including obesity, BMI, HTN, BG, and lipid profiles were included and reviewed by two authors independently. Heterogeneity between studies was assessed using the I2 index and Cochrane's Q test. Random/fixed effect meta-analyses were used to combine the association between greenspace exposure with cardiometabolic risk factors.

RESULTS

Overall, 118 relevant articles were included in our review. The majority of the articles were conducted in North America or Europe. In qualitative synthesis, access or proximity to greenspaces or POS impacts BMI and blood pressure or HTN, BG, and lipid profiles via various mechanisms. According to the random effect meta-analysis, more access to greenspace was significantly associated with lower odds of HTN (odds ratio (OR): 0.81, 95% confidence intervals (CIs): 0.61-0.99), obesity (OR: 0.83, 95% CIs: 0.77-0.90), and diabetes (OR:0.79, 95% CI: 0.67,0.90).

CONCLUSIONS

Findings of this systematic review and meta-analysis suggested that greenspace accessibility is associated with some cardiometabolic risk factors. Improving greenspace accessibility could be considered as one of the main strategies to reduce cardiometabolic risk factors at population level.

The effect of seasonality and weather conditions on human perception of the urban-rural transitional landscape

Landscape perception research into the impact of seasonally changing landscape characteristics with the simultaneous influence of the weather are rare. Therefore, eye-tracking metrics were calculated (fixation and saccades) for the whole tested landscape, while its areas of interest (AOIs) were established based on clustering methods. Moreover, the gaze pattern was analysed using the Voronoi cells method. To identify significant differences in landscape perception according to various weather and seasonality, nonparametric tests were applied. The significant influence of weather/seasonality and their synergistic influence is noticed. The results indicate a rather complex influence of the types of weather in warmer and cooler seasons. Regardless of the weather type, seasonal changes cause greater visual span and shorter fixations in the warmer season. The fixations and saccades are shorter in the warmer season in two AOI's during positive weather, but are longer in negative weather during the colder season in most AOI's. The main reasons for the influence of weather and seasonality on the visual perception include seasonal changes in the landscape, resulting in the appearance of the landscape from more urban to natural and vice versa (phenological changes) as well as lighting changes (due to seasonality and type of weather).

Impacts of Urban Blue-Green Space on Residents' Health: A Bibliometric Review

Urban blue-green space (UBGS), as an important component of the urban environment, is found to closely relate to human health. An extensive understanding of the effects of UBGS on human health is necessary for urban planning and intervention schemes towards healthy city development. However, a comprehensive review and discussion of relevant studies using bibliometric methods is still lacking. This paper adopted the bibliometric method and knowledge graph visualization technology to analyze the research on the impact of UBGS on residents' health, including the number of published papers, international influence, and network characteristics of keyword hotspots. The key findings include: (1) The number of articles published between 2001 and 2021 shows an increasing trend. Among the articles collected from WoS and CNKI, 38.74% and 32.65% of the articles focus on physical health, 38.32% and 30.61% on mental health, and 17.06% and 30.61% on public health, respectively. (2) From the analysis of international partnerships, countries with high levels of economic development and urbanization have closer cooperation than other countries. (3) UBGS has proven positive effects on residents' physical, mental, and public health. However, the mediating effects of UBGS on health and the differences in the health effects of UBGS on different ages and social classes are less studied. Therefore, this study proposes several future research directions. First, the mediating effect of UBGS on health impacts should be further examined. Furthermore, the interactive effects of residents' behaviors and the UBGS environment should be emphasized. Moreover, multidisciplinary integration should be strengthened. The coupling mechanism between human behavior and the environment should also be studied in depth with the help of social perception big data, wearable devices, and human-computer interactive simulation. Finally, this study calls for developing health risk monitoring and early warning systems, and integrating health impact assessment into urban planning, so as to improve residents' health and urban sustainability.

Are yoga and physical activity determinants of quality of life in Polish adults? a cross-sectional study

OBJECTIVES

Yoga is an ancient form of physical activity (PA) that encompasses meditation, stretching and breathing techniques. Although the benefits of PA and associated lifestyle interventions are clear, we here addressed the paucity of evidence regarding the specific relationship between yoga and quality of life (QOL) in adults in Poland. We hypothesised that participation in PA and yoga could result in a positive impact on QOL.

DESIGN

Cross-sectional, self-administered questionnaire-based survey. Both the quantitative and qualitative variables were statistically compared. Multivariate analyses were performed using linear regression. Results were determined based on age, sex and education level; a p<0.05 was considered significant.

SETTING

Questionnaires were delivered to participants online, at high schools and universities, and in elderly communities in Poland.

PARTICIPANTS

714 polish citizens aged over 18 participated in the study; there are no specific entry and exclusion criteria besides age.

RESULTS

Statistically significant differences (p<0.05) were observed between the QOL of the physically active group (PAG) and non-PAG (N-PAG). Meanwhile, yoga practice was revealed to have a significant effect on QOL; QOL was found to be statistically higher (p<0.001) in the PAG with yoga (PAG-Y) (4.29±0.66) than in the N-PAG (3.83±0.92) and PAG without yoga (4.07±0.68).

CONCLUSIONS

The study shows that both regular PA and yoga practices could improve QOL; however, PAG-Y produced higher QOL scores than PA of other types. This outcome may be explained by the impact of physiological and psychological aspects within yoga practice. These results suggest that this unique combination impacts health more positively than other kinds of PA alone.

Inequality in urban green space benefits: Combining street greenery and park greenery

In this paper, we measured the amount of urban green space (UGS), defined here as park greenery and street greenery, in the Guangzhou Beltway region using remote sensing image data and the green view index (GVI) based on human visual images. We also evaluated the benefits of UGS comprehensively considering park greenery and street greenery within the Guangzhou Beltway region. We then calculated the urban green space score (UGSS) by assessing the amount of street greenery and park greenery and then juxtaposing the score with the population distribution of the region. The results show inequities in the spatial distribution of UGSS values within the Guangzhou Beltway region. The benefit score of street greenery is low. The service area of parks can't cover the whole study area. The comprehensive benefit score of UGS is composed of two parts, the park greenery score and the street greenery score, but the spatial distribution of UGSS values remains uneven. The UGS benefits enjoyed by one-half of the population of the study area are low, and the UGSS values of the more densely populated areas are not high.

Urban greenspace and mental health in Chinese older adults: Associations across different greenspace measures and mediating effects of environmental perceptions

This study aimed to contrast the associations of street view-, land use- and satellite-derived greenspace measures with older adults' mental health and to examine the mediating effects of neighborhood environmental perceptions (i.e., noise, aesthetics and satisfaction with recreational opportunities) to explain potential heterogeneity in the associations. Data of 879 respondents aged 60 or older in Dalian, China were used, and multilevel regression models were conducted in Stata. Results indicated that the Normalized Difference Vegetation Index (NDVI), vegetation coverage, park coverage and streetscape grasses were positively correlated with older adults' mental health. The associations of exposure metrics measured by overhead view were stronger than those measured by the street view. Streetscape grasses had a stronger association with older adults' mental health than streetscape trees. Noise, aesthetics and satisfaction with recreational opportunities mediated these associations, but the strength of the mediating effects differed across the greenspace measures. Our findings confirm the necessity of multi-measures assessment for greenspace to examine associations with older adults' mental health in Chinese settings and can contribute to the realization of health benefits of urban greenspace.

Do sex and gender modify the association between green space and physical health? A systematic review

A growing literature shows that green space can have protective effects on human health. As a marginalized group, women often have worse life outcomes than men, including disparities in some health outcomes. Given their marginalization, women might have "more to gain" than men from living near green spaces. Yet, limited research has deliberately studied whether green space-health associations are stronger for women or men. We conducted a systematic review to synthesize empirical evidence on whether sex or gender modifies the protective associations between green space and seven physical health outcomes (cardiovascular disease, cancer, diabetes, general physical health, non-malignant respiratory disease, mortality, and obesity-related health outcomes). After searching five databases, we identified 62 articles (including 81 relevant analyses) examining whether such effect modification existed. We classified analyses based on whether green space-health were stronger for women, no sex/gender differences were detected, or such associations were stronger for men. Most analyses found that green space-physical health associations were stronger for women than for men when considering study results across all selected health outcomes. Also, women showed stronger protective associations with green space than men for obesity-related outcomes and mortality. Additionally, the protective green space-health associations were slightly stronger among women for green land cover (greenness, NDVI) than for public green space (parks), and women were also favored over men when green space was measured very close to one's home (0-500 m). Further, the green space-health associations were stronger for women than for men in Europe and North America, but not in other continents. As many government agencies and nongovernmental organizations worldwide work to advance gender equity, our review shows that green space could help reduce some gender-based health disparities. More robust empirical studies (e.g., experimental) are needed to contribute to this body of evidence.

Residential Exposure to Urban Trees and Medication Sales for Mood Disorders and Cardiovascular Disease in Brussels, Belgium: An Ecological Study

BACKGROUND

The available evidence for positive associations between urban trees and human health is mixed, partly because the assessment of exposure to trees is often imprecise because of, for instance, exclusion of trees in private areas and the lack of three-dimensional (3D) exposure indicators (e.g., crown volume).

OBJECTIVES

We aimed to quantify all trees and relevant 3D structural traits in Brussels (Belgium) and to investigate associations between the number of trees, tree traits, and sales of medication commonly prescribed for mood disorders and cardiovascular disease.

METHODS

We developed a workflow to automatically isolate all individual trees from airborne light detection and ranging (LiDAR) data collected in 2012. Trait data were subsequently extracted for 309,757 trees in 604 census tracts. We used the average annual age-standardized rate of medication sales in Brussels for the period 2006 to 2014, calculated from reimbursement information on medication prescribed to adults (19-64 years of age). The medication sales data were provided by sex at the census tract level. Generalized log-linear models were used to investigate associations between the number of trees, the crown volume, tree structural variation, and medication sales. Models were run separately for mood disorder and cardiovascular medication and for men and women. All models were adjusted for indicators of area-level socioeconomic status.

RESULTS

Single-factor models showed that higher stem densities and higher crown volumes are both associated with lower medication sales, but opposing associations emerged in multifactor models. Higher crown volume [an increase by one interquartile range (IQR) of 1.4×104 m³/ha] was associated with 34% lower mood disorder medication sales [women, β=-0.341 (95% CI: -0.379, -0.303); men, β=-0.340 (95% CI: -0.378, -0.303)] and with 21-25% lower cardiovascular medication sales [women, β=-0.214 (95% CI: -0.246, -0.182); men, β=-0.252 (95% CI: -0.285, -0.219)]. Conversely, a higher stem density (an increase by one IQR of 21.8 trees/ha) was associated with 28-32% higher mood disorder medication sales [women, β=0.322 (95% CI: 0.284, 0.361); men, β=0.281 (95% CI: 0.243, 0.319)] and with 20-24% higher cardiovascular medication sales [women, β=0.202 (95% CI: 0.169, 0.236); men, β=0.240 (95% CI: 0.206, 0.273)].

DISCUSSION

We found a trade-off between the number of trees and the crown volumes of those trees for human health benefits in an urban environment. Our results demonstrate that conserving large trees in urban environments may not only support conservation of biodiversity but also human health. https://doi.org/10.1289/EHP9924.

Assessing streetscape greenery with deep neural network using Google Street View

The importance of greenery in urban areas has traditionally been discussed from ecological and esthetic perspectives, as well as in public health and social science fields. The recent advancements in empirical studies were enabled by the combination of 'big data' of streetscapes and automated image recognition. However, the existing methods of automated image recognition for urban greenery have problems such as the confusion of green artificial objects and the excessive cost of model training. To ameliorate the drawbacks of existing methods, this study proposes to apply a patch-based semantic segmentation method for determining the green view index of certain urban areas by using Google Street View imagery and the 'chopped picture method'. We expect that our method will contribute to expanding the scope of studies on urban greenery in various fields.

Association between eye-level greenness and lung function in urban Chinese children

BACKGROUND

Health effects of greenness perceived by residents at eye level has received increasing attention. However, the associations between eye-level greenness and respiratory health are unknown. The aim of the study was to investigate the associations between exposure to eye-level greenness and lung function in children.

METHODS

From 2012 to 2013, a total of 6740 school children in seven cities in northeast China were recruited into this cross-sectional study. Forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC), peak expiratory flow rate (PEF), and maximum mid expiratory flow rate (MMEF) were measured to evaluate lung function and to define lung impairment. Eye-level greenness was extracted from segmented Tencent Map street view images, and a corresponding green view index (GVI) was calculated. Higher GVIs mean more greenness coverage. Mixed-effects logistic regressions were used to estimate the health effects on lung impairment per interquartile range (IQR) increase in GVI. Linear regressions were used to estimate the associations between GVI and lung function. The health effects of ambient air pollutants were also assessed, including particulate matter with an aerodynamic diameter <1.0 μm (PM₁), <2.5 μm (PM_2.5), <10 μm (PM₁₀) as well as nitrogen dioxide (NO₂).

RESULTS

An increase of GVI_800m was associated with lung impairment in FEV₁, FVC, PEF and MMEF, with ORs ranging from 0.68 (95% CI: 0.59, 0.79) to 0.83 (95% CI: 0.74, 0.93). The associations between an IQR increase of GVI_800m and FEV₁ (48.15 ml, 95% CI: 30.33-65.97 ml), FVC (50.57 ml, 95% CI: 30.65-70.48 ml), PEF (149.59 ml/s, 95% CI: 109.79-189.38 ml/s), and MMEF (61.18 ml/s, 95% CI: 31.07-91.29 ml/s) were significant, and PM₁, PM_2.5, and PM₁₀ were found to be mediators of this relationship.

CONCLUSION

More eye-level greenness was associated with better lung function and reduced impairment. However, eye-level greenness associations with lung function became non-significant once lower particulate matter air pollution exposures were considered.

Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index

Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of overcoming the limitation of NDVI to determine the extent to which it was associated with asthma prevalence in Chinese children. During 2009-2013, a cross-sectional study of 59,754 children aged 2-17 years was conducted in northeast China. Tencent street view images surrounding participants' schools were segmented by a deep learning model, and streetscape greenness was extracted. The green view index (GVI) was used to assign exposure and higher value indicates more green coverage. Mixed-effects logistic regression models were used to calculate the adjusted odds of asthma per interquartile range (IQR) increase of GVI for trees and grass. Participants were further stratified to investigate whether particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) was a modifier. An IQR increase in GVI_800m for trees was associated with lower adjusted odds of doctor-diagnosed asthma (OR: 0.76; 95%CI: 0.72-0.80) and current asthma (OR: 0.82; 95%CI: 0.75-0.89). An IQR increase in GVI_800m for grass was associated with higher adjusted odds of doctor-diagnosed asthma (OR: 1.04; 95%CI: 1.00-1.08) and current asthma (OR: 1.08; 95%CI: 1.02-1.14). After stratification by PM_2.5 exposure level, the negative association between trees and asthma, and the positive association between grass and asthma were observed only in low PM_2.5 exposure levels (≤median: 56.23 μg/m³). Our results suggest that types of vegetation may play a role in the association between greenness exposure and childhood asthma. Exposure to trees may reduce the odds of childhood asthma, whereas exposure to grass may increase the odds. Additionally, PM_2.5 may modify the associations of trees and grass with childhood asthma.

Street view greenness is associated with lower risk of obesity in adults: Findings from the 33 Chinese community health study

BACKGROUND

Urban greenness may protect against obesity, but very few studies have assessed 'street view' (SV) greenness metrics, which may better capture people's actual exposure to greenness compared to commonly-used satellite-derived metrics. We aimed to investigate these associations further in a Chinese adult study.

METHODS

Our analysis included 24,845 adults in the 33 Chinese Community Health Study in 2009. SV images from Tencent Map, segmented by machine learning algorithms, were used to determine the average proportion of green vegetation in SV images at community level in 800m road network buffer. Sensitivity analyses were performed with an alternative buffer size. Overall greenness was assessed as normalized difference vegetation index (NDVI) in 800 m buffer. We used predicted PM_2.5 and monitored NO₂ as proxies of air pollution. Body mass index (BMI), waist circumference (WC) and hip circumference (HC) were regressed on SV greenness by generalized linear mixed models, with adjustment for covariates. Mediation analyses were performed to assess the mediation effects of air pollution.

RESULTS

Each interquartile range (IQR = 3.6%) increase in street view greenness was associated with a 0.15 kg/m² (95% CI: -0.22, -0.09) decrease in BMI and 0.23 cm (95% CI: -0.35, -0.11) reduction in HC, and was associated with 7% lower odds of overweight (OR = 0.93, 95% CI:0.90, 0.96) and 18% lower odds of obesity (OR = 0.82, 95% CI:0.76, 0.89). Similar effect estimation was observed compared with commonly-used NDVI measures. PM_2.5 and NO₂ mediated 15.5% and 6.1% of the effects of SV greenness with BMI, respectively.

CONCLUSIONS

Our findings suggest beneficial associations between community-level SV greenness and lower body weight in Chinese adults. The effects were observed in women but not in men. Air pollution may partially mediate the association. These findings may have implications to support efforts to promote greening in urban areas.

Obesity and Natural Spaces in Adults and Older People: A Systematic Review

BACKGROUND

Obesity is an important public health issue that has increased globally in the last decade and continues to be one of the main causes of morbidity and premature mortality. An accumulating body of evidence suggests that contact with nature is a valuable resource for the promotion of a more active lifestyle and seems to have a central role in maintaining a healthy weight. The authors conducted a systematic review to summarize the findings of studies that investigated the relationship between natural spaces and obesity.

METHODS

Following Primary Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a literature search was conducted using 11 databases for studies fully available in English and published between 2010 and 2020, with adults (18-64 y) and/or older people (≥65 y).

RESULTS

Fifty studies were found that met all the inclusion criteria. The majority (68%) of papers found that higher availability and less distance to green and blue spaces are associated with lower levels of adiposity. These associations were positive, even after adjusting for the demographic and socioeconomic factors.

CONCLUSIONS

Exploring the characteristics of green and blue spaces seems to be a promising tool for urban planning and health policies. The authors suggest the implementation of exercise programs in contact with nature for future interventions.

Virtual Reality Representations of Nature to Improve Well-Being amongst Older Adults: a Rapid Review

Poor well-being amongst older adults poses a serious health concern. Simultaneously, research shows that contact with nature can improve various facets of well-being, including physical, social, and mental well-being. However, nature is not always accessible for older adults due to mobility restrictions and related care needs that come with age. A promising strategy aims at bringing nature inside through pervasive technologies. However, so far, there is little academic understanding of essential nature characteristics, psychological processes involved, and means for implementation in practice. The current study used a three-folded rapid review to assess current understanding and strategies used for improving well-being for older adults through virtual reality representations of nature. Searches were performed across three databases, followed-up by content-based evaluation of abstracts. In total, a set of 25 relevant articles was identified. Only three studies specifically focus on digital nature as an intervention strategy for improving well-being amongst older adults. Although these studies provide useful starting points for the design and (technological) development of such environments, they do not generate understanding of how specific characteristics of virtual nature representations impact social well-being measures in particular, and of the underlying psychological processes involved. We conclude that follow-up research is warranted to close the gap between insights and findings from nature research, gerontology, health research, and human-technology interaction.

Near Real-Time Semantic View Analysis of 3D City Models in Web Browser

3D city models and their browser-based applications have become an increasingly applied tool in the cities. One of their applications is the analysis views and visibility, applicable to property valuation and evaluation of urban green infrastructure. We present a near real-time semantic view analysis relying on a 3D city model, implemented in a web browser. The analysis is tested in two alternative use cases: property valuation and evaluation of the urban green infrastructure. The results describe the elements visible from a given location, and can also be applied to object type specific analysis, such as green view index estimation, with the main benefit being the freedom of choosing the point-of-view obtained with the 3D model. Several promising development directions can be identified based on the current implementation and experiment results, including the integration of the semantic view analysis with virtual reality immersive visualization or 3D city model application development platforms.

Modelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions

The visibility of natural greenness is associated with several health benefits along multiple pathways, including stress recovery and attention restoration mechanisms. However, existing methodologies are inadequate for capturing eye-level greenness visibility exposure at high spatial resolutions for observers located on the ground. As a response, we developed an innovative methodological approach to model and map eye-level greenness visibility exposure for 5 m interval locations within a large study area. We used multi-source spatial data and applied viewshed analysis in conjunction with a distance decay model to compute a novel Viewshed Greenness Visibility Index (VGVI) at more than 86 million observer locations. We compared our eye-level visibility exposure map with traditional top-down greenness exposure metrics such as Normalised Differential Vegetation Index (NDVI) and a Street view based Green View Index (SGVI). Furthermore, we compared greenness visibility at street-only locations with total neighbourhood greenness visibility. We found strong to moderate correlations (r = 0.65-0.42, p < 0.05) between greenness visibility and mean NDVI, with a decreasing trend in correlation strength at increasing buffer distances from observer locations. Our findings suggest that top-down and eye-level measurements of greenness are two distinct metrics for assessing greenness exposure. Additionally, VGVI showed a strong correlation (r = 0.481, p < 0.01) with SGVI. Although the new VGVI has good agreement with existing street view based measures, we found that street-only greenness visibility values are not wholly representative of total neighbourhood visibility due to the under-representation of visible greenness in locations such as backyards and community parks. Our new methodology overcomes such underestimations, is easily transferable, and offers a computationally efficient approach to assessing eye-level greenness exposure.

Associations between the traditional and novel neighbourhood built environment metrics and weight status among Canadian men and women

OBJECTIVES

Neighbourhood characteristics can impact the health of residents. This study investigated associations between objectively derived neighbourhood characteristics, including novel space syntax metrics, and self-reported body mass index (BMI) among Canadian men and women.

METHODS

Our study included survey data collected from a random cross-section of adults residing in Calgary, Alberta (n = 1718). The survey, conducted in 2007/2008, captured participants' socio-demographic characteristics, health, and weight status (BMI). Participants' household postal codes were geocoded and 1600-m line-based network buffers estimated. Using a geographical information system, we estimated neighbourhood characteristics within each buffer including business destination density, street intersection density, sidewalk length, and population density. Using space syntax, we estimated street integration and walkability (street integration plus population density) within each buffer. Using adjusted regression models, we estimated associations between neighbourhood characteristics and BMI (continuous) and BMI categories (healthy weight vs. overweight including obese). Gender-stratified analysis was also performed.

RESULTS

Business destination density was negatively associated with BMI and the odds of being overweight. Among men, street intersection density and sidewalk length were negatively associated with BMI and street intersection density, business destination density, street integration, and space syntax walkability were negatively associated with odds of being overweight. Among women, business destination density was negatively associated with BMI.

CONCLUSION

Urban planning policies that impact neighbourhood design have the potential to influence weight among adults living in urban Canadian settings. Some characteristics may have a differential association with weight among men and women and should be considered in urban planning and in neighbourhood-focussed public health interventions.

Evaluating Street Greenery by Multiple Indicators Using Street-Level Imagery and Satellite Images: A Case Study in Nanjing, China

Street greenery plays an essential role in improving the street environment and residents’ health. The evaluation of street greenery is of great value to establish environmentally friendly streets. The evaluation indicators of present studies evaluating street greenery were relatively single, either the Green View Index (GVI) or Normalized Difference Vegetation Index (NDVI), which cannot describe the greenery condition in its entirety. The objective of this study is to assess the street greenery using multiple indicators, including GVI, NDVI, and Vegetation Structural Diversity (VSD). We combined street view images with a semantic segmentation method to extract the GVI and VSD and used satellite images to calculate the NDVI in the urban area of Nanjing, China. We found correlations and discrepancies of these indicators using statistical analyses in different urban districts, functional areas, and road levels. The results indicate that: (1) the GVI and NDVI are strongly correlated in open spaces, whereas weakly correlated in residential and industrial lands, (2) the areas with higher VSD are mainly located in the new city, whereas the VSD in the old city is lower, and a weak negative correlation exists between the GVI and VSD in the research area, and (3) the old city has a higher GVI level compared to the new city on the main road, whereas the new city has a higher GVI level than the old city on the branch road. Compared with the GVI, the trend of VSD in the old city and the new city is relatively consistent. Our findings suggest that considering multiple indicators of street greenery evaluation can provide a comprehensive reference for building more human-friendly and diversified street green belts.

Greenspace with overweight and obesity: A systematic review and meta-analysis of epidemiological studies up to 2020

Several reviews have been conducted to assess the association between greenspace and overweight or obesity, but the conclusions were inconsistent. However, an updated comprehensive review and meta-analysis is warranted, because several high-quality papers have been published more recently. The objectives of this study are to systematically and quantitatively assess the evidence for a link between greenspace with overweight/obesity and to make specific recommendations for further research. We searched three English language databases, four Chinese language databases and the reference lists of previously published reviews for epidemiological studies on greenspace and overweight/obesity published before January 2020. We developed inclusion criteria, screened the literature and extracted key data from selected papers. We assessed methodological quality and risk of bias, and we graded the credibility of the pooled evidence. We also performed sensitivity analyses. Fifty-seven records met our inclusion criteria and were included in the study. Most studies were cross-sectional designs (81%) and were from developed nations (88%). More than half (55%) of the included studies found beneficial associations between greenspace and overweight/obesity in overall or subpopulations. Our meta-analytical results showed that greater normalized difference vegetation index was associated with lower odds of overweight/obesity in a statistically significant fashion (odds ratio [OR]: 0.88; 95% CI: 0.84, 0.91) but not residential proximity to greenspace (OR: 0.99; 95% CI: 0.99, 1.00), proportion of greenspace (OR: 0.96; 95% CI: 0.85, 1.08) or number of parks in an area (OR: 0.99; 95% CI: 0.97, 1.01). However, we detected high between-study heterogeneity in two of the four meta-analyses, which reduced the credibility of the pooled evidence. Current evidence indicates that there might be an association between greater access to greenspace and lower odds of overweight/obesity. However, additional high-quality studies are needed to more definitively assess the evidence for a causal association.

Standardized Green View Index and Quantification of Different Metrics of Urban Green Vegetation

Urban greenery is considered an important factor in sustainable development and people’s quality of life in the city. To account for urban green vegetation, Green View Index (GVI), which captures the visibility of greenery at street level, has been used. However, as GVI is point-based estimation, when aggregated at an area-level by mean or median, it is sensitive to the location of sampled sites, overweighing the values of densely located sites. To make estimation at area-level more robust, this study aims to (1) propose an improved indicator of greenery visibility (standardized GVI; sGVI), and (2) quantify the relation between sGVI and other green metrics. Experiment on an hypothetical setting confirmed that bias from site location can be mitigated by sGVI. Furthermore, comparing sGVI and Normalized Difference Vegetation Index (NDVI) at the city block level in Yokohama city, Japan, we found that sGVI captures the presence of vegetation better in the city center, whereas NDVI is better at capturing vegetation in parks and forests, principally due to the different viewpoints (eye-level perception and top-down eyesight). These tools provide a foundation for accessing the effect of vegetation in urban landscapes in a more robust matter, enabling comparison on any arbitrary geographical scale.

Walkability Index for Elderly Health: A Proposal

Nowadays, the elderly tend to make more trips: Health benefits resulting from their daily walking routines are an important topic in the context of urban renewal processes. Many health organizations and researchers have demonstrated the influence of the urban environment on walkability levels. This article aims to design a multifactor Walkability Index for Elderly Health (WIEH), capable of associating both the adequacy level of public spaces to elderly walkability, and physical exercise benefits while walking. The methodological approach comprised two main parts: Firstly, a literature review of main reports, legislation, and scientific articles was conducted at the intersection of ‘gerontology and physical exercise’ with ‘urban design and mobility’, leading to the selection of four aging-related studies as main contributors to the design of the WIEH; and, secondly, the development of the WIEH was undertaken, based on two premises and designed according to four steps. The first premise defined three systematic areas (urban tissue, urban scene, and safety), variables, and criteria to classify the pedestrian network; and the second premise focused on slopes and stairs in public spaces. The WIEH is divided in four steps: (1) Analyzing public spaces and characterizing their quality for walking, (2) considering the existence of slopes and stairs, (3) calculating different routes for the elderly in their daily routines, or when going to points of interest, and (4) selecting the “heart-friendly route” for elderly people. Adequate walking paths for the elderly can be identified through this innovative approach, with the aim of achieving direct health benefits during their daily routines. Ultimately, the WIEH is capable of supporting decision makers and designers in creating inclusive and age-friendly spaces.

Does Green Space Really Matter for Residents' Obesity? A New Perspective From Baidu Street View

Despite a growing literature on the topic, the association between neighborhood greenness and body weight is inconsistent. The objective of this research is to examine the association between neighborhood greenness and residents' obesity levels in a high population density area. We accounted for three greenness features: green access, green exposure, and view-based green index. We used the novel technique of deep convolutional neural network architecture to extract eye-level information from Baidu Street View images to capture the urban vertical greenness level. The research involved a survey with 9,524 respondents from 40 communities in Shanghai. Generally, we found all aspects of horizontal greenery, vertical greenery, and proximity of green levels to be impactful on body weight; however, only the view-based green index consistently had an adverse effect on weight and obesity.

Associations between the neighbourhood characteristics and body mass index, waist circumference, and waist-to-hip ratio: Findings from Alberta's Tomorrow Project

This study estimated the associations between neighbourhood characteristics and self-reported body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) risk categories among Canadian men and women. Using data from the Alberta's Tomorrow Project (n = 14,550), we estimated 3- and 4-way intersections, business destinations, population count, and normalized difference vegetation index (NDVI) within a 400 m radius of participant's home. Intersections, business destinations, and population count (z-scores) were summed to create a walkability score. Four-way intersections and walkability were negatively associated with overweight and obesity. Walkability was negatively associated with obesity. NDVI was negatively associated with high-risk WHR and population count and walkability positively associated with high-risk WHR. Among men, population count and walkability were negatively associated with obesity, and business destinations and walkability were negatively associated with overweight and obesity. Among women, NDVI was negatively associated with overweight (including obesity), obesity, and high-risk WC. Interventions promoting healthy weight could incorporate strategies that take into consideration local built environment characteristics.

Spatial dimensions of the influence of urban green-blue spaces on human health: A systematic review

BACKGROUND

There is an increasing volume of literature investigating the links between urban environments and human health, much of which involves spatial conceptualisations and research designs involving various aspects of geographical information science. Despite intensifying research interest, there has been little systematic investigation of pragmatic methodological concerns, such as how studies are realised in terms of the types of data that are gathered and the analytical techniques that are applied, both of which have the potential to impact results. The aim of this systematic review is, therefore, to understand how spatial scale, datasets, methods, and analytics are currently applied in studies investigating the relationship between green and blue spaces and human health in urban areas.

METHOD

We systematically reviewed 93 articles following PRISMA protocol, extracted information regarding different spatial dimensions, and synthesised them in relation to various health indicators.

RESULTS AND DISCUSSION

We found a preponderance of the use of neighbourhood-scale in these studies, and a majority of the studies utilised land-use and vegetation indices gleaned from moderate resolution satellite imagery. We also observed the frequent adoption of fixed spatial units for measuring exposure to green and blue spaces based on physical proximity, typically ranging between 30 and 5000 m. The conceptual frameworks of the studies (e.g., the focus on physical vs. mental health or the definition of exposure to green space) were found to have an influence on the strength of association between exposure and health outcomes. Additionally, the strength and significance of associations also varied by study design, something which has not been considered systematically.

CONCLUSION

On the basis of our findings, we propose a set of recommendations for standardised protocols and methods for the evaluation of the impact of green-blue spaces on health. Our analysis suggests that future studies should consider conducting analyses at finer spatial scales and employing multiple exposure assessment methods to achieve a comprehensive and comparable evaluation of the association between greenspace and health along multiple pathways.

Translating Urban Walkability Initiatives for Older Adults in Rural and Under-Resourced Communities

The built environment can promote physical activity in older adults by increasing neighborhood walkability. While efforts to increase walkability are common in urban communities, there is limited data related to effective implementation in rural communities. This is problematic, as older adults make up a significant portion of rural inhabitants and exhibit lower levels of physical activity. Translating lessons from urban strategies may be necessary to address this disparity. This review examines best practices from urban initiatives that can be implemented in rural, resource-limited communities. The review of the literature revealed that simple, built environment approaches to increase walkability include microscale and pop-up infrastructure, municipal parks, and community gardens, which can also increase physical activity in neighborhoods for urban older adults. These simple and cost-effective strategies suggest great potential for rural communities.

Comfort and Time-Based Walkability Index Design: A GIS-Based Proposal

Encouraging people to walk as a means of transport throughout their daily lives has obvious benefits for the environment, the economy, and personal health. Specific features of the built environment have a significant influence on encouraging or discouraging walking. By identifying and quantifying these features we can design Walkability Indices (WI). The WI in the literature do not take factors related to comfort such as noise pollution and shade/sun conditions into account. Given the importance of these factors in walking, we decided to include them in our design of a new geographic information system (GIS)-based WI. The relative weight of each factor was determined by consulting experts. The proposed WI, computed for the entire city of Madrid, Spain, uses sections of the sidewalk as the spatial unit. The properties of this WI (based on secondary sources, spatially detailed, dynamic, weighted, and including comfort-related factors) fill a gap in previous WI proposals.

Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China

BACKGROUND

Residential green and blue spaces may be therapeutic for the mental health. However, solid evidence on the linkage between exposure to green and blue spaces and mental health among the elderly in non-Western countries is scarce and limited to exposure metrics based on remote sensing images (i.e., land cover and vegetation indices). Such overhead-view measures may fail to capture how people perceive the environment on the site.

OBJECTIVE

This study aimed to compare streetscape metrics derived from street view images with satellite-derived ones for the assessment of green and blue space; and to examine associations between exposure to green and blue spaces as well as geriatric depression in Beijing, China.

METHODS

Questionnaire data on 1190 participants aged 60 or above were analyzed cross-sectionally. Depressive symptoms were assessed through the shortened Geriatric Depression Scale (GDS-15). Streetscape green and blue spaces were extracted from Tencent Street View data by a fully convolutional neural network. Indicators derived from street view images were compared with a satellite-based normalized difference vegetation index (NDVI), a normalized difference water index (NDWI), and those derived from GlobeLand30 land cover data on a neighborhood level. Multilevel regressions with neighborhood-level random effects were fitted to assess correlations between GDS-15 scores and these green and blue spaces exposure metrics.

RESULTS

The average cumulative GDS-15 score was 3.4 (i.e., no depressive symptoms). Metrics of green and blue space derived from street view images were not correlated with satellite-based ones. While NDVI was highly correlated with GlobeLand30 green space, NDWI was moderately correlated with GlobeLand30 blue space. Multilevel regressions showed that both street view green and blue spaces were inversely associated with GDS-15 scores and achieved the highest model goodness-of-fit. No significant associations were found with NDVI, NDWI, and GlobeLand30 green and blue space. Our results passed robustness tests.

CONCLUSION

Our findings provide support that street view green and blue spaces are protective against depression for the elderly in China, yet longitudinal confirmation to infer causality is necessary. Street view and satellite-derived green and blue space measures represent different aspects of natural environments. Both street view data and deep learning are valuable tools for automated environmental exposure assessments for health-related studies.