Eye-Level Street Greenery and Walking Behaviors of Older Adults

Exploring the Relationship between Built Environment Attributes and Physical Activity in Lower-Income Aging Adults: Preliminary Insights from a Multi-Level Trial

The built environment has been linked to physical activity (PA) behaviors, yet there is limited knowledge of this association among lower-income midlife and older adults who are insufficiently active. The present cross-sectional study utilized baseline data collected between October 2017 and November 2019 from a clustered randomized controlled trial to determine how built environment attributes were associated with PA behaviors among midlife and older adults (n = 255) residing in or near affordable housing sites (n = 10). At each site, perceptions of the built environment were collected and scored at the participant level via the abbreviated Neighborhood Environment Walkability Survey (NEWS-A), while objective built environment attributes were measured and scored by trained research staff using the Physical Activity Resource Assessment (PARA). Multiple PA behaviors-walking, total PA, and moderate-to-vigorous PA (MVPA) (min/wk)-were measured using the validated Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. Adjusted linear regression models examined associations between NEWS-A measures and PA behaviors, and site-level correlations between PARA measures and PA behaviors were examined using Spearman's rank correlations. At the participant level, adjusted models revealed that a one point increase in the NEWS-A aesthetics score was associated with a 57.37 min/wk increase in walking (β = 57.37 [95% CI: 20.84, 93.91], p = 0.002), with a similar association observed for street connectivity and MVPA (β = 24.31 min/wk [95% CI: 3.22, 45.41], p = 0.02). At the site level, MVPA was positively correlated with the quality of the features of local, PA-supportive environmental resources (ρ = 0.82, p = 0.004). Findings indicate that participant- and site-level measures of the built environment may play a role in promoting PA behavior among this demographic and similar populations. Results also suggest that improvements in aesthetic attributes and street connectivity, along with enhancing the quality of local, PA-supportive environmental resources, may be effective strategies for promoting physical activity among lower-income midlife and older adults.

The impact of street greenery on active travel: a narrative systematic review

Background

Street greenery may have a profound effect on residents' active travel (AT), a mode of transportation involving walking and cycling. This study systematically reviewed the scientific evidence on the effects of street greenery on active travel.

Methods

A comprehensive search was performed using keywords and references in PubMed, Web of Science, Scopus, and Cochrane Library. The review included studies that met the following criteria: (1) Study design: experimental studies, cross sectional studies, (2) Participants: individuals of all ages, (3) Exposure variables: street greenery, including street vegetation (e.g., trees, shrubs, and lawns), (4) Outcomes: active travel behaviors (walking, cycling), (5) Article type: peer-reviewed articles, (6) Search time window: from the inception of relevant electronic literature database until 21 June 2023, (7) Geographic scope: worldwide; (8) Language: articles in English.

Results

Twenty-six cross-sectional studies met the inclusion criteria and were analyzed. These studies employed objective metrics for assessing street greenery and varied methodologies to measure AT, including 14 using subjective measurements (like self-reported surveys), 10 using objective data (such as mobile app analytics), and two studies combined both approaches. This review identifies a generally positive impact of street greenery on active travel in various aspects. However, the extent of this influence varies with factors such as temporal factors (weekdays vs. weekends), demographic segments (age and gender), proximity parameters (buffer distances), and green space quantification techniques. Street greenness promotes active travel by enhancing environmental esthetics, safety, and comfort, while also improving air quality, reducing noise, and fostering social interactions. In addition, the study suggests that variables like weather, seasonality, and cultural context may also correlate with the effectiveness of street greenery in encouraging active travel.

Conclusion

Street greenery positively influences active travel, contributing to public health and environmental sustainability. However, the findings also indicate the need for more granular, experimental, and longitudinal studies to better understand this relationship and the underlying mechanisms. These insights are pivotal for urban planners and policymakers in optimizing green infrastructure to promote active transportation, taking into account local demographics, socio-economic factors, and urban design.

A Scoping Review of Personal, Financial, and Environmental Determinants of Mobility Among Older Adults

OBJECTIVE

To synthesize available evidence of factors comprising the personal, financial, and environmental mobility determinants and their association with older adults' self-reported and performance-based mobility outcomes.

DATA SOURCES

PubMed, EMBASE, PsychINFO, Web of Science, AgeLine, Sociological Abstract, Allied and Complementary Medicine Database, and Cumulative Index to Nursing and Allied Health Literature databases search for articles published from January 2000 to December 2021.

STUDY SECTION

Using predefined inclusion and exclusion criteria, multiple reviewers independently screened 27,293 retrieved citations from databases, of which 422 articles underwent full-text screening, and 300 articles were extracted.

DATA EXTRACTION

The 300 articles' information, including study design, sample characteristics including sample size, mean age and sex, factors within each determinant, and their associations with mobility outcomes, were extracted.

DATA SYNTHESIS

Because of the heterogeneity of the reported associations, we followed Barnett et al's study protocol and reported associations between factors and mobility outcomes by analyses rather than by article to account for multiple associations generated in 1 article. Qualitative data were synthesized using content analysis. A total of 300 articles were included with 269 quantitative, 22 qualitative, and 9 mixed-method articles representing personal (n=80), and financial (n=1), environmental (n=98), more than 1 factor (n=121). The 278 quantitative and mixed-method articles reported 1270 analyses; 596 (46.9%) were positively and 220 (17.3%) were negatively associated with mobility outcomes among older adults. Personal (65.2%), financial (64.6%), and environmental factors (62.9%) were associated with mobility outcomes, mainly in the expected direction with few exceptions in environmental factors.

CONCLUSIONS

Gaps exist in understanding the effect of some environmental factors (eg, number and type of street connections) and the role of gender on older adults' walking outcomes. We have provided a comprehensive list of factors with each determinant, allowing the creation of core outcome set for a specific context, population, or other forms of mobility, for example, driving.

Effects of green space on physical activity and body weight status among Chinese adults: a systematic review

Background

Green space may provide many benefits to residents' health behaviors and body weight status, but the evidence is still relatively scattered among Chinese adults. The purpose of this study was to review the scientific evidence on the effects of green space on physical activity (PA) and body weight status among Chinese adults.

Methods

A keyword and reference search was conducted in Pubmed, Web of Science, MEDLINE, and PsycINFO. Studies examining the associations between green space and PA, body mass index (BMI) among Chinese adults were included. The quality of the included literature was evaluated using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool.

Results

A total of 31 studies were included that met the inclusion criteria, including 25 studies with a cross-sectional design, 3 studies with a longitudinal design, and 3 studies with an experimental design. Street-level green view index and green space accessibility were found to be positively associated with PA, but negatively associated with BMI. In most studies, there was a correlation between green space ratio in local areas and BMI. In addition, green space interventions were effective in increasing PA and decreasing BMI among Chinese adults. In contrast, further evidence is needed to support the association between the design characteristics of green space and PA and BMI.

Conclusion

Preliminary evidence suggests that green space has a positive effect on PA and BMI among Chinese adults. However, there are contradictory findings, and future studies adopting longitudinal and quasi-experimental studies are needed to further explore the causal relationship between green space and PA and BMI to provide a relevant theoretical basis for policymakers.

Effect of built environment on BMI of older adults in regions of different socio-economic statuses

Background

Numerous studies have ignored the influence of underdeveloped urban surroundings on the physical health of China's ageing population. Lanzhou is a typical representative of a less developed city in China.

Methods

This study investigated the relationship between body mass index (BMI) and built environment amongst older adults in regions of different socio-economic statuses (SES) using data from medical examinations of older adults in Lanzhou, as well as calculating community built environment indicators for regions of different SES based on multiple linear regression models.

Results

Results showed that age and underlying disease were negatively associated with overall older adult BMI in the study buffer zone. Land use mix, number of parks and streetscape greenery were positively associated with older adult BMI. Street design and distance to bus stops were negatively connected in low SES regions, but population density and street design were negatively correlated in high SES areas.

Conclusion

These findings indicate that the built environment of SES regions has varying impacts on the BMI of older persons and that planners may establish strategies to lower the incidence of obesity amongst older adults in different SES locations.

The built environment’s nonlinear effects on the elderly’s propensity to walk

The increased ageing of the population is a vital and upcoming challenge for China. Walking is one of the easiest and most common forms of exercise for older people, and promoting walking among older people is important for reducing medical stress. Streetscape green visibility and the normalised difference vegetation index (NDVI) are perceptible architectural elements, both of which promote walking behaviour. Methodologically we used Baidu Street View images and extracted NDVI from streetscape green visibility and remote sensing to scrutinize the nonlinear effects of streetscape green visibility and NDVI on older people’s walking behaviour. The study adopted a random forest machine learning model. The findings indicate that the impact of streetscape green visibility on elderly walking is superior to NDVI, while both have a favourable influence on senior walking propensity within a particular range but a negative effect on elderly walking inside that range. Overall the built environment had a non-linear effect on the propensity to walk of older people. Therefore, this study allows the calculation of optimal thresholds for the physical environment, which can be used by governments and planners to formulate policies and select appropriate environmental thresholds as indicators to update or build a community walking environment that meets the needs of local older people, depending on their own economic situation.

Spatially varying associations between the built environment and older adults' propensity to walk

Population aging has become a severe issue facing most nations and areas worldwide-with Hong Kong being no exception. For older adults, walking is among the most well-liked travel modes, boosting their overall health and wellbeing. Some studies have confirmed that the built environment has a significant (spatially fixed) influence on older adults' walking behavior. However, little consideration has been given to the potential spatial heterogeneity in such influences. Hence, this study extracted data on older adults' (outdoor) walking behavior from the 2011 Hong Kong Travel Characteristics Survey and measured a series of built environment attributes based on geo-data (e.g., Google Street View imagery). Logistic regression and geographically weighted logistic regression models were developed to unveil the complicated (including spatially fixed and heterogeneous) association between the built environment and older adults' propensity to walk. We show that population density, land-use mix, street greenery, and access to bus stops are positively connected with the propensity to walk of older adults. Intersection density seems to impact walking propensity insignificantly. All built environment attributes have spatially heterogeneous effects on older adults' walking behavior. The percentage of deviance explained is heterogeneously distributed across space.

Nonlinear Effects of the Built Environment on Light Physical Activity among Older Adults: The Case of Lanzhou, China

The aging of the population is increasing the load on the healthcare system, and enhancing light physical activity among older adults can alleviate this problem. This study used medical examination data from 1773 older adults in Lanzhou city (China) and adopted the random forest model to investigate the effect of the built environment on the duration of light physical activity of older adults. The results showed that streetscape greenery has the most significant impact on older adults' light physical activity; greenery can be assessed in a hierarchy of areas; population density and land-use mix only have a positive effect on older adults' light physical activity up to a certain point but a negative effect beyond that point; and a greater distance to the park within 1 km is associated with a longer time spent on light physical activity. Therefore, we conclude that the built environment's impact is only positive within a specific range. Changes in the intervention of environmental variables can be observed visually by calculating the relative importance of the nonlinearity of built environment elements with partial dependency plots. These results provide a reasonable reference indicator for age-friendly community planning.

Research on the Difference Between Recreational Walking and Transport Walking Among the Elderly in Mega Cities With Different Density Zones: The Case of Guangzhou City

Walking is the easiest method of physical activity for older people, and current research has demonstrated that the built environment is differently associated with recreational and transport walking. This study modelled the environmental characteristics of three different building density zones in Guangzhou city at low, medium, and high densities, and examined the differences in walking among older people in the three zones. The International Physical Activity Questionnaire (IPAQ) was used to investigate the recreational and transport walking time of older people aged 65 years and above for the past week, for a total of three density zones (N = 597) and was analysed as a dependent variable. Geographic Information Systems (GIS) was used to identify 300, 500, 800, and 1,000 m buffers and to assess differences between recreational and transport walking in terms of the built environment [e.g., land-use mix, street connectivity, Normalised Difference Vegetation Index (NDVI) data]. The data were processed and validated using the SPSS software to calculate Pearson's correlation models and stepwise regression models between recreation and transit walking and the built environment. The results found that land use mix and NDVI were positively correlated with transport walking in low-density areas and that transport walking was negatively correlated with roadway mediated centrality (BtE) and Point-of-Interest (PoI) density. Moreover, recreational walking in medium density areas was negatively correlated with self-rated health, road intersection density, and PoI density while positively correlated with educational attainment, population density, land use mix, street connectivity, PoIs density, and NDVI. Transport walking was negatively correlated with land-use mix, number of road crossings while positively correlated with commercial PoI density. Street connectivity, road intersection density, DNVI, and recreational walking in high-density areas showed negative correlations. Moreover, the built environment of older people in Guangzhou differed between recreational and transport walking at different densities. The richness of PoIs has different effects on different types of walking.

Green Space and Physical Activity in China: A Systematic Review

Green space may play an essential role in residents’ physical activity (PA), but evidence remains scattered in China. This study systematically reviewed scientific evidence regarding the influence of green space on PA among residents in China. Keyword and reference searches were conducted in PubMed, Web of Science, Scopus, EBSCO, and CNKI from the inception of an electronic bibliographic database to May 2021. Eligibility criteria included the following: study designs—observational (e.g., longitudinal or cross-sectional studies) and experimental studies; study subjects—people of all ages; exposures—green space (e.g., parks, vegetation areas, open green fields); outcomes—leisure-time and work/school-related PA (e.g., active commuting); and country—China. All but two studies identified at least one measure of green space to be associated with PA. Street greenness was associated with increased odds of active commuting (e.g., cycling) and walking, and a reduced risk of physical inactivity. Access to green space was associated with increased PA levels and green space usage. Distance to green space was inversely associated with the odds of PA. By contrast, evidence linking overall greenness exposure to PA remains limited. Future studies adopting experimental study design are warranted to establish more robust scientific evidence of causality between green space and PA in China. Future studies are also warranted to examine the underlining mechanisms and the differential impacts of green space on population subgroups in China.

Towards Healthy Aging: Influence of the Built Environment on Elderly Pedestrian Safety at the Micro-Level

As vulnerable road users, elderly pedestrians are more likely to be injured in road crashes due to declining physical and perceptual capabilities. Most previous studies on the influence of the built environment on elderly pedestrian safety focused on intersections or areal units. Using a district of Shanghai as the study area, this research investigated the effects of the built environment at the road segment level with elderly pedestrian collision, taxi tracking point, point of interest, street view image, open street map, land use, housing price, and elderly population datasets. In particular, this research employed both Poisson and geographically weighted Poisson regression (GWPR) models to account for spatial nonstationarity. The Poisson model indicates that green space, sidewalks, and junctions on the roads significantly affected elderly pedestrian safety, and roads around nursing homes, schools, bus stops, metro stations, traditional markets, and supermarkets were hazardous for elderly pedestrians. The results of the GWPR model suggest that the influence of factors varied across the study area. Green space could decrease the risk of elderly pedestrian collisions only in areas without congested environments. Separations need to be installed between roadways and sidewalks to improve elderly road safety.

Spatially Varying Effects of Street Greenery on Walking Time of Older Adults

Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults’ walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults’ walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent.

Non-linear Relationships Between the Built Environment and Walking Frequency Among Older Adults in Zhongshan, China

Aim: Promoting walking activity is an effective way to improve the health of older adults. Walking frequency is a critical component of walking behavior and an essential determinant of daily walking levels. To decipher the association between the built environment and walking frequency among older adults, this study's aims are as follows: (1) to empirically test whether non-linear relationships between the two exist, and (2) to identify the thresholds of the built environment characteristics that promote walking.

Methods: The walking frequency of old adults was derived from the Zhongshan Household Travel Survey (ZHTS) in 2012. The sample size of old adults aged 60 or over was 4784 from 274 urban and rural neighborhoods. A semi-parametric generalized additive model (GAMM) is used to analyze the non-linear or non-monotonic relationships between the built environment and the walking frequency among older adults.

Results: We found that non-linear relationships exist among five out of the six built environment characteristics. Within certain thresholds, the population density, sidewalk density, bus stop density, land use mixture, and the percentage of green space are positively related to older adults' walking trips. Furthermore, the land use mixture and the percentage of green space show an inverse “V”-shaped relationship.

Conclusions: Built environment features can either support or hinder the walking frequency among older adults. The findings in the current study contribute to effective land use and transport policies for promoting active travel among older adults.

Panoramic Street-Level Imagery in Data-Driven Urban Research: A Comprehensive Global Review of Applications, Techniques, and Practical Considerations

The release of Google Street View in 2007 inspired several new panoramic street-level imagery platforms including Apple Look Around, Bing StreetSide, Baidu Total View, Tencent Street View, Naver Street View, and Yandex Panorama. The ever-increasing global capture of cities in 360° provides considerable new opportunities for data-driven urban research. This paper provides the first comprehensive, state-of-the-art review on the use of street-level imagery for urban analysis in five research areas: built environment and land use; health and wellbeing; natural environment; urban modelling and demographic surveillance; and area quality and reputation. Panoramic street-level imagery provides advantages in comparison to remotely sensed imagery and conventional urban data sources, whether manual, automated, or machine learning data extraction techniques are applied. Key advantages include low-cost, rapid, high-resolution, and wide-scale data capture, enhanced safety through remote presence, and a unique pedestrian/vehicle point of view for analyzing cities at the scale and perspective in which they are experienced. However, several limitations are evident, including limited ability to capture attribute information, unreliability for temporal analyses, limited use for depth and distance analyses, and the role of corporations as image-data gatekeepers. Findings provide detailed insight for those interested in using panoramic street-level imagery for urban research.