Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands

Assessing runners' exposure to natural and built environments in the Netherlands: A descriptive assessment based on GPS tracking

Running is a convenient physical activity that has gained popularity. However, little is known about runners' running environments and how they differ from their residential environments. To fill this gap, this study examines runners' exposure to natural and built environments along their running routes and assesses the difference between running and residential environments. We collected running track data from Endmondo, a fitness data platform, and used it to determine runners' residency. Moreover, we used open geographical data to calculate a range of environmental variables within their residential areas and along their running trajectories. We applied t-tests to assess differences across objectively measured environmental variables between urban and rural runners, considering geographic, temporal and track-specific strata. We found that the running environments of urban and rural runners were diverse and had distinct characteristics. The results suggest policies to promote running acknowledging these differences between running environments in urban and rural areas.

Urban Form Metrics for Promoting Walking: Street Layouts and Destinations

There is evidence that higher street connectivity and availability of destinations can support walking behavior. However, the availability of data and comparability between previous studies remain a challenge. Based on a large Canadian adult sample, this study examined the associations between street layout and walking behaviors and explored whether objectively measured destinations may mediate these relationships. This study used data from 12,378 adults from Alberta's Tomorrow Project (ATP), a prospective cohort study conducted in Alberta, Canada. Walking behaviors were obtained by questionnaires. Street layout and destination measures were calculated objectively. Covariate-adjusted multivariate linear models estimated the associations between the space syntax street integration and duration of transport and leisure walking. The mediation effects of the availability of destinations in these associations were tested by the structural equation modelling. Street integration was significantly positively associated with transportation walking (b=0.01, 95% CI 0.00, 0.01, p = 0.01) (indirect effect). The availability of destinations partially mediated this association. Using the natural movement theory in space syntax, our study provides insights into using street layouts as a primary measure to (re)design the built environment to support walking.

The role of the perceived environment for recreational walking among adults in socioeconomically disadvantaged situations: A study using walk-along interviews

Background

Persons in socioeconomically disadvantaged situations (PSEDS) are generally less likely to engage in recreational walking (RW) compared to higher socioeconomic groups and are often more dependent on their local environment. Studies on RW have primarily focused on the role of the built environment for the general adult population and the older population in urban areas. The aim of this study is to qualitatively identify the perceived environmental factors affecting RW among PSEDS in peri-urban areas.

Methods

In two peri-urban municipalities in Belgium, walk-along interviews were conducted until data saturation with a purposeful convenience sampling of 38 PSEDS (25-65y/o) to identify local environmental factors affecting RW. A subsample of 22 participants joined a focus group (n = 4) to categorize the identified factors into environmental types (physical, sociocultural, political, and economic) of the Analysis Grid for Environments Linked to Obesity (ANGELO) framework. The interviews were transcribed and analyzed thematically using Maxqda 2022.0.

Results

The information environment (dissemination, retrieving and understanding of information) was added to the ANGELO framework, highlighting the importance of digital literacy. Availability and accessibility of well-maintained walking surfaces, toilets, street lighting and seating options (physical environment), social support, dog-ownership, stigmatization, social isolation, and a sense of belonging (sociocultural environment) and indirect costs (economic environment) were identified as important environmental factors in RW among PSEDS. The identified political and economic factors are intertwined with the other environments.

Conclusions

Perceived environmental factors affect RW among PSEDS and peri-urban settings offer specific challenges. Local governments should incorporate citizen perception into decision-making processes to create supportive environments that have the potential to promote RW among PSEDS in a peri-urban setting.

Neighbourhood Walkability and Its Influence on Physical Activity and Cardiometabolic Disease: A Cross-Sectional Study in a Caribbean Small Island Developing State

Introduction Cities and neighborhoods may provide opportunities for population-level environmental interventions to reduce physical inactivity and cardiometabolic risk. In this study, we describe the association between neighborhood walkability, physical activity (PA), and cardiometabolic outcomes, by linking data from a nationally representative survey of adults (25 years and older) collected in 2012-2013 with spatial data on built environment features in Barbados. Methods We estimated a walkability index for 45 neighborhoods using objectively measured built environment features (residential density, street connectivity, and land use mix). We used the Recent Physical Activity Questionnaire to capture time spent in outdoor walking, active commuting, moderate-to-vigorous PA (MVPA), and total PA. Our primary cardiometabolic outcome was a predicted 10-year cardiovascular risk (CVD) score, estimated using the American College of Cardiology/American Heart Association pooled cohort equation. Our secondary cardiometabolic outcomes were hypertension and diabetes. We explored the effect of neighborhood walkability on PA and cardiometabolic outcomes using several multivariable regression models (tobit and linear and logistic multi-level mixed effects), with the model choice depending on the structure of the outcome.  Results The average time spent walking weekly for any purpose among participants was 75 minutes/week, time spent on active commuting was 15 minutes/week, and MVPA was 221 minutes/week. We estimated that the average 10-year CVD risk in the study population was 11.7% (95%CI 10.9-12.5). Our confounder-adjusted analyses showed positive linear relationships between neighborhood walkability and each PA outcome (p<0.05 in all cases), and a negative relationship between walkability and predicted 10-year CVD risk (p<0.001). Conclusion In our setting, adults residing in higher walkability neighborhoods spent more time engaged in PA, had a lower predicted 10-year CVD risk, and were less likely to have diabetes. Urban planners may consider shorter-term interventions, such as those on a microscale, which may provide additional ways to increase activity in a mostly fixed macroscale environment.

Effects of built and natural environments on leisure physical activity in residential and workplace neighborhoods

Few studies have investigated relative contributions of the built and natural environments to and their nonlinear associations with leisure physical activity (PA) in different spatial contexts. Applying gradient boosting decision tree models to data comprising 1049 adults collected in Shanghai, we investigated the associations between built and natural environments and leisure PA in residential and workplace neighborhoods. Results show that the built environment is more important than the natural environment to leisure PA in both residences and workplaces. Environmental attributes have nonlinear and threshold effects. Within certain ranges, land use mix and population density have opposite associations with leisure PA in residences and workplaces, whereas the distance to the city center and the area of water are associated with leisure PA in residences and workplaces with the same direction. These findings help urban planners design context-specific environmental interventions for supporting leisure PA.

Development of an objectively measured walkability index for the Netherlands

Background

Walkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations.

Methods

Components of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18–65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex.

Results

In fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1–9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index’s association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36–49 years) compared to young (18–35 years old) and older adults (50–65 years old).

Conclusions

The walkability index was cross-sectionally associated with Dutch adult’s walking behaviours, indicating its validity for further use in research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01270-8.

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.

Mechanisms of Impact of Blue Spaces on Human Health: A Systematic Literature Review and Meta-Analysis

Blue spaces have been found to have significant salutogenic effects. However, little is known about the mechanisms and pathways that link blue spaces and health. The purpose of this systematic review and meta-analysis is to summarise the evidence and quantify the effect of blue spaces on four hypothesised mediating pathways: physical activity, restoration, social interaction and environmental factors. Following the PRISMA guidelines, a literature search was conducted using six databases (PubMed, Scopus, PsycInfo, Web of Science, Cochrane Library, EBSCOHOST/CINAHL). Fifty studies were included in our systematic review. The overall quality of the included articles, evaluated with the Qualsyst tool, was judged to be very good, as no mediating pathway had an average article quality lower than 70%. Random-effects meta-analyses were conducted for physical activity, restoration and social interaction. Living closer to blue space was associated with statistically significantly higher physical activity levels (Cohen’s d = 0.122, 95% CI: 0.065, 0.179). Shorter distance to blue space was not associated with restoration (Cohen’s d = 0.123, 95% CI: −0.037, 0.284) or social interaction (Cohen’s d = −0.214, 95% CI: −0.55, 0.122). Larger amounts of blue space within a geographical area were significantly associated with higher physical activity levels (Cohen’s d = 0.144, 95% CI: 0.024, 0.264) and higher levels of restoration (Cohen’s d = 0.339, 95% CI: 0.072, 0.606). Being in more contact with blue space was significantly associated with higher levels of restoration (Cohen’s d = 0.191, 95% CI: 0.084, 0.298). There is also evidence that blue spaces improve environmental factors, but more studies are necessary for meta-analyses to be conducted. Evidence is conflicting on the mediating effects of social interaction and further research is required on this hypothesised pathway. Blue spaces may offer part of a solution to public health concerns faced by growing global urban populations.