A Longitudinal Study Examining Changes in Street Connectivity, Land Use, and Density of Dwellings and Walking for Transport in Brisbane, Australia

Changes in neighbourhood walkability and body mass index: An analysis of residential mobility from a longitudinal multilevel study in Brisbane, Australia

This study examined associations between changes in neighbourhood walkability and body mass index (BMI) among 1041 residents who relocated within Brisbane, Australia between 2007 and 2016 over five waves of the HABITAT study. Measures included spatially-derived neighbourhood walkability (dwelling density, street connectivity, and land use mix) and self-reported height and weight. No associations were found between any neighbourhood walkability characteristics and BMI. Examining these associations over the life course, and the impact of residential relocation in the younger years, remains a priority for future research.

Associations between changes in crime and changes in walking for transport with effect measure modification by gender: A fixed-effects analysis of the multilevel longitudinal HABITAT study (2007-2016)

Walking for transport is a potential solution to increasing physical activity in mid to older aged adults however neighbourhood crime may be a barrier. Using data from the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study 2007-2016, this study examined associations between changes in crime (perceived crime and objectively measured crime) and changes in transport walking, and whether this association differed by gender. Fixed effects regression modelled associations between changes in crime and changes in transport walking, with interaction terms examining effect modification by gender. Positive associations were found between crimes against person and walking for transport. There was no evidence of effect modification by gender. Understanding the relationship between crime and walking for transport can inform policies aimed at promoting transport walking.

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.

Spatial scale analysis for the relationships between the built environment and cardiovascular disease based on multi-source data

To examine what built environment characteristics improve the health outcomes of human beings is always a hot issue. While a growing literature has analyzed the link between the built environment and health, few studies have investigated this relationship across different spatial scales. In this study, eighteen variables were selected from multi-source data and reduced to eight built environment attributes using principal component analysis. These attributes included socioeconomic deprivation, urban density, street walkability, land-use diversity, blue-green space, transportation convenience, ageing, and street insecurity. Multiscale geographically weighted regression was then employed to clarify how these attributes relate to cardiovascular disease at different scales. The results indicated that: (1) multiscale geographically weighted regression showed a better fit of the association between the built environment and cardiovascular diseases than other models (e.g., ordinary least squares and geographically weighted regression), and is thus an effective approach for multiscale analysis of the built environment and health associations; (2) built environment variables related to cardiovascular diseases can be divided into global variables with large scales (e.g., socioeconomic deprivation, street walkability, land-use diversity, blue-green space, transportation convenience, and ageing) and local variables with small scales (e.g., urban density and street insecurity); and (3) at specific spatial scales, global variables had trivial spatial variation across the area, while local variables showed significant gradients. These findings provide greater insight into the association between the built environment and lifestyle-related diseases in densely populated cities, emphasizing the significance of hierarchical and place-specific policy formation in health interventions.

Associations between neighborhood walkability and walking following residential relocation: Findings from Alberta's Tomorrow Project

Introduction

Cross-sectional studies consistently find that the neighborhood built environment (e.g., walkability) is associated with walking. However, findings from the few existing longitudinal residential relocation studies that have estimated associations between changes in neighborhood built characteristics and walking are equivocal. The study objective was to estimate whether changes in neighborhood walkability resulting from residential relocation were associated with leisure, transportation, and total walking levels among adults.

Methods

This study included longitudinal data from the "Alberta's Tomorrow Project"-a province-wide cohort study (Alberta, Canada). The analysis included data collected at two time points (i.e., baseline and follow-up) from 5,977 urban adults. The International Physical Activity Questionnaire (IPAQ) captured self-reported walking. We estimated neighborhood walkability, an index capturing intersection, destination, and population counts for the 400 m Euclidean buffer around participants' homes. Using household postal codes reported at baseline and follow-up, we categorized participants into three groups reflecting residential relocation ("non-movers:" n = 5,679; "movers to less walkability:" n = 164, and; "movers to more walkability:" n = 134). We used Inverse-Probability-Weighted Regression Adjustment to estimate differences [i.e., average treatment effects in the treated (ATET)] in weekly minutes of leisure, transportation, and total walking at follow-up between residential relocation groups, adjusting for baseline walking, sociodemographic characteristics, and walkability. The median time between baseline and follow-up was 2-years.

Results

The three residential relocation groups mainly included women (61.6-67.2%) and had a mean age of between 52.2 and 55.7 years. Compared to "non-movers" (reference group), weekly minutes of transportation walking at follow-up was significantly lower among adults who moved to less walkable neighborhoods (ATET: -41.34, 95 CI: -68.30, -14.39; p < 0.01). We found no other statistically significant differences in walking between the groups.

Discussion

Our findings suggest that relocating to less walkable neighborhoods could have detrimental effects on transportation walking to the extent of adversely affecting health. Public health strategies that counteract the negative impacts of low walkable neighborhoods and leverage the supportiveness of high walkable neighborhoods might promote more walking.

The role of neighbourhood design in cycling activity during COVID-19: An exploration of the Melbourne experience

COVID-19 restrictions imposed significant changes on human mobility patterns, with some studies finding significant increases or decreases in cycling. However, to date there is little understanding on how the neighbourhood-level built environment influenced cycling behaviour during the COVID-19 restrictions. As different neighbourhood have different built environment characteristics, it is possible that cycling trends varied across different built environment settings. We aimed to answer this question by examining recreational cycling during different stages of lockdown in Melbourne, Australia. We compared self-reported recreational cycling frequency (weekly) data from 1344 respondents between pre-COVID and two different stages in lockdown. We tested whether the built environment of their residential neighbourhood and different sociodemographic characteristics influenced leisure cycling rates and whether the effect of these factors varied between different stages of COVID-19 restriction. We found that cycling declined significantly during the two stages of COVID-19 lockdown. Cycling infrastructure density and connectivity are two built environment factors that had a significant effect on limiting the decline in leisure cycling during the pandemic. Furthermore, men and younger people had higher cycling rates in comparison to other groups, suggesting that restrictions on indoor activities and travel limits were not enough to encourage women or older people to cycle more during the pandemic.

The association between street connectivity and depression among older Japanese adults: the JAGES longitudinal study

Mental health is important in older age; neighborhood environment is considered a protective factor of depression. Research has established that a critical indicator of neighborhood environment, street connectivity, is related to older people's health. However, little is known about the relationship between street connectivity and depression. We examined the relationship between street connectivity and depression among older people. Using Japan Gerontological Evaluation Study 2013-2016, the target population comprised 24,141 independent older people without depression (Geriatric Depression Scale scores below 5) in 2013. The outcome variable was depression in 2016; the explanatory variable was street connectivity calculated by intersection density and space syntax within 800 m around the subject's neighborhood in 2013. We used logistic regression analysis to calculate the odds ratio and 95% confidence interval for the new occurrence of depression among participants in 2016. This analysis demonstrated incidence of new depression after 3 years that is 17% and 14% lower among participations living in high-intersection density and high-street-connectivity areas, respectively, than those living in low-intersection density and low-street-connectivity areas. The association held after adjusting for physical activities and social interaction. Given the established connection between street connectivity and mental health, the findings can contribute to healthy urban 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.

Urban Densification and Physical Activity Change: A 12-Year Longitudinal Study of Australian Adults

Urbanization, a major force driving changes in neighborhood environments, may affect residents' health by influencing their daily activity levels. We examined associations of population density changes in urban areas with adults' physical activity changes over 12 years using data from the Australian Diabetes, Obesity and Lifestyle Study (1999-2012). The analytical sample contained 2,354 participants who remained at the same residential address throughout the study period in metropolitan cities and regional cities (42 study areas). Census-based population density measures were calculated for 1-km-radius buffers around their homes. Population density change was estimated using linear growth models. Two-level linear regression models were used to assess associations between changes in population density and changes in self-reported walking and physical activity durations. The average change in population density was 0.8% per year (range, -4.1 to 7.8) relative to baseline density. After adjustment for confounders, each 1% annual increase in population density was associated with 8.5-minutes/week (95% confidence interval: 0.6, 16.4) and 19.0-minutes/week (95% confidence interval: 3.7, 34.4) increases in walking and physical activity, respectively, over the 12-year study period. Increasing population density through urban planning policies of accommodating population growth within the existing urban boundary, rather than expanding city boundaries, could assist in promoting physical activity at the population level.

Health and Wellbeing Benefits from Nature Experiences in Tropical Settings Depend on Strength of Connection to Nature

A growing number of policies and programmes in cities aim to increase the time people spend in nature for the health and wellbeing benefits delivered by such interactions. Yet, there is little research investigating the extent to which, and for whom, nature experiences deliver such benefits outside Europe, North America, and Australia. Here, we assessed the relationships between nature dose (frequency, duration, and intensity) and three mental wellbeing (depression, stress, and anxiety) and two physical health (high blood pressure, diabetes) outcomes in Singapore, an intensely urbanised tropical city. Our analyses accounted for individual factors, including socio-economic status, nature connection (nature relatedness), and whether people with poor health are prevented by their condition from visiting green spaces. Our results show that the association between nature dose (specifically duration) and mental wellbeing is moderated by a nature connection. Specifically, people with a stronger nature connection were less likely to be depressed, stressed, and anxious, regardless of the duration of their nature dose. For those with a weaker connection to nature, spending longer in nature was associated with being more depressed, stressed, and anxious. We did not find a relationship between nature dose and high blood pressure or diabetes. Our results highlight that the relationship between nature dose and wellbeing might vary substantially among cities.

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.

Factors influencing walking trips. Evidence from Gdynia, Poland

Political support for active mobility is growing for many reasons, including land use planning, health, and improved mobility. As the vital part of many cities is their central area, decision-makers need to know what factors are essential for increasing walkability. This paper aims to identify the main factors affecting the walkability of the city centre of Gdynia (Poland). To achieve this, the research design was adjusted to the specificity of the local use case. Based on primary data collected via personal interviews, factor analysis was applied to rule out potential collinearity and reduce dimensions. Logistic regression models were then constructed. The results were compared with the research carried out in other cities. The results show that only two of the analysed factors are significant, namely accessibility and safety. Both are extensive categories and include many subcomponents that are influential among different groups of citizens. Our research also confirms that walkability is a city-specific issue that is influenced by many local factors.

Associations of changes in neighbourhood walkability with changes in walking activity in older adults: a fixed effects analysis

Background

Supporting older adults to engage in physically active lifestyles requires supporting environments. Walkable environments may increase walking activity in older adults, but evidence for this subgroup is scarce, and longitudinal studies are lacking. This study therefore examined whether changes in neighbourhood walkability were associated with changes in walking activity in older adults, and whether this association differed by individual-level characteristics and by contextual conditions beyond the built environment.

Methods

Data from 668 participants (57.8–93.4 years at baseline) across three waves (2005/06, 2008/09 and 2011/12) of the Longitudinal Aging Study Amsterdam (LASA) were used. These individuals did not relocate during follow-up. Self-reported outdoor walking activity in minutes per week was assessed using the LASA Physical Activity Questionnaire. Composite exposure measures of neighbourhood walkability (range: 0 (low)-100 (high)) within 500-m Euclidean buffer zones around each participant’s residential address were constructed by combining objectively measured high-resolution Geographic Information System data on population density, retail and service destination density, land use mix, street connectivity, green space density, and sidewalk density. Fixed effects linear regression analyses were applied, adjusted for relevant time-varying confounders.

Results

Changes in neighbourhood walkability were not statistically significantly associated with changes in walking activity in older adults (β_500m = − 0.99, 95% CI = -6.17–4.20). The association of changes in neighbourhood walkability with changes in walking activity did not differ by any of the individual-level characteristics (i.e., age, sex, educational level, cognitive impairment, mobility disability, and season) and area-level characteristics (i.e., road traffic noise, air pollution, and socioeconomic status).

Conclusions

This study did not show evidence for an association between changes in neighbourhood walkability and changes in walking activity in older adults. If neighbourhood walkability and walking activity are causally linked, then changes in neighbourhood walkability between 2005/06 and 2011/12 might have been not substantial enough to produce meaningful changes in walking activity in older adults.

Australia in 2030: what is our path to health for all?

CHAPTER 1: HOW AUSTRALIA IMPROVED HEALTH EQUITY THROUGH ACTION ON THE SOCIAL DETERMINANTS OF HEALTH: Do not think that the social determinants of health equity are old hat. In reality, Australia is very far away from addressing the societal level drivers of health inequity. There is little progressive policy that touches on the conditions of daily life that matter for health, and action to redress inequities in power, money and resources is almost non-existent. In this chapter we ask you to pause this reality and come on a fantastic journey where we envisage how COVID-19 was a great disruptor and accelerator of positive progressive action. We offer glimmers of what life could be like if there was committed and real policy action on the social determinants of health equity. It is vital that the health sector assists in convening the multisectoral stakeholders necessary to turn this fantasy into reality. CHAPTER 2: ABORIGINAL AND TORRES STRAIT ISLANDER CONNECTION TO CULTURE: BUILDING STRONGER INDIVIDUAL AND COLLECTIVE WELLBEING: Aboriginal and Torres Strait Islander peoples have long maintained that culture (ie, practising, maintaining and reclaiming it) is vital to good health and wellbeing. However, this knowledge and understanding has been dismissed or described as anecdotal or intangible by Western research methods and science. As a result, Aboriginal and Torres Strait Islander culture is a poorly acknowledged determinant of health and wellbeing, despite its significant role in shaping individuals, communities and societies. By extension, the cultural determinants of health have been poorly defined until recently. However, an increasing amount of scientific evidence supports what Aboriginal and Torres Strait Islander people have always said - that strong culture plays a significant and positive role in improved health and wellbeing. Owing to known gaps in knowledge, we aim to define the cultural determinants of health and describe their relationship with the social determinants of health, to provide a full understanding of Aboriginal and Torres Strait Islander wellbeing. We provide examples of evidence on cultural determinants of health and links to improved Aboriginal and Torres Strait Islander health and wellbeing. We also discuss future research directions that will enable a deeper understanding of the cultural determinants of health for Aboriginal and Torres Strait Islander people. CHAPTER 3: PHYSICAL DETERMINANTS OF HEALTH: HEALTHY, LIVEABLE AND SUSTAINABLE COMMUNITIES: Good city planning is essential for protecting and improving human and planetary health. Until recently, however, collaboration between city planners and the public health sector has languished. We review the evidence on the health benefits of good city planning and propose an agenda for public health advocacy relating to health-promoting city planning for all by 2030. Over the next 10 years, there is an urgent need for public health leaders to collaborate with city planners - to advocate for evidence-informed policy, and to evaluate the health effects of city planning efforts. Importantly, we need integrated planning across and between all levels of government and sectors, to create healthy, liveable and sustainable cities for all. CHAPTER 4: HEALTH PROMOTION IN THE ANTHROPOCENE: THE ECOLOGICAL DETERMINANTS OF HEALTH: Human health is inextricably linked to the health of the natural environment. In this chapter, we focus on ecological determinants of health, including the urgent and critical threats to the natural environment, and opportunities for health promotion arising from the human health co-benefits of actions to protect the health of the planet. We characterise ecological determinants in the Anthropocene and provide a sobering snapshot of planetary health science, particularly the momentous climate change health impacts in Australia. We highlight Australia's position as a major fossil fuel producer and exporter, and a country lacking cohesive and timely emissions reduction policy. We offer a roadmap for action, with four priority directions, and point to a scaffold of guiding approaches - planetary health, Indigenous people's knowledge systems, ecological economics, health co-benefits and climate-resilient development. Our situation requires a paradigm shift, and this demands a recalibration of health promotion education, research and practice in Australia over the coming decade. CHAPTER 5: DISRUPTING THE COMMERCIAL DETERMINANTS OF HEALTH: Our vision for 2030 is an Australian economy that promotes optimal human and planetary health for current and future generations. To achieve this, current patterns of corporate practice and consumption of harmful commodities and services need to change. In this chapter, we suggest ways forward for Australia, focusing on pragmatic actions that can be taken now to redress the power imbalances between corporations and Australian governments and citizens. We begin by exploring how the terms of health policy making must change to protect it from conflicted commercial interests. We also examine how marketing unhealthy products and services can be more effectively regulated, and how healthier business practices can be incentivised. Finally, we make recommendations on how various public health stakeholders can hold corporations to account, to ensure that people come before profits in a healthy and prosperous future Australia. CHAPTER 6: DIGITAL DETERMINANTS OF HEALTH: THE DIGITAL TRANSFORMATION: We live in an age of rapid and exponential technological change. Extraordinary digital advancements and the fusion of technologies, such as artificial intelligence, robotics, the Internet of Things and quantum computing constitute what is often referred to as the digital revolution or the Fourth Industrial Revolution (Industry 4.0). Reflections on the future of public health and health promotion require thorough consideration of the role of digital technologies and the systems they influence. Just how the digital revolution will unfold is unknown, but it is clear that advancements and integrations of technologies will fundamentally influence our health and wellbeing in the future. The public health response must be proactive, involving many stakeholders, and thoughtfully considered to ensure equitable and ethical applications and use. CHAPTER 7: GOVERNANCE FOR HEALTH AND EQUITY: A VISION FOR OUR FUTURE: Coronavirus disease 2019 has caused many people and communities to take stock on Australia's direction in relation to health, community, jobs, environmental sustainability, income and wealth. A desire for change is in the air. This chapter imagines how changes in the way we govern our lives and what we value as a society could solve many of the issues Australia is facing - most pressingly, the climate crisis and growing economic and health inequities. We present an imagined future for 2030 where governance structures are designed to ensure transparent and fair behaviour from those in power and to increase the involvement of citizens in these decisions, including a constitutional voice for Indigenous peoples. We imagine that these changes were made by measuring social progress in new ways, ensuring taxation for public good, enshrining human rights (including to health) in legislation, and protecting and encouraging an independent media. Measures to overcome the climate crisis were adopted and democratic processes introduced in the provision of housing, education and community development.

What affects how far individuals walk?

The number of studies that explore contributing factors that encourage individuals to do more walking trips is proliferated in recent years. However, there is still a lot to know about differentiating between short and long walking trips and their associated influencing factors. The current research investigated the impact of the influencing factors on the share of short and long walking trips across four different trips in 112 traffic analysis zones of Rasht, Iran. The share of walking trips was defined as the proportion of walking trips that originated/ended in an area on all trips that originated/ended in that area. In four trip purposes in short, long, and all trips, the factors associated with the share of walking in origins and destinations were investigated in 24 separate models. The factors included built environmental indices, such as transportation network connectivity and land-use variables, as well as socio-demographic. To differentiate between short and long walking trips, 600 m walking distance was recognized as a proxy. According to the results, the population density was found significantly increase share of walking in both the origins and destinations of short walking trips. Moreover, the models’ goodness of fits were relatively higher in short walking trips comparing long walking trips. This research's findings would give a profound assessment to city planners and decision makers who favor expanding walking as a sustainable mode of transportation.

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

Background Walking is a good and simple way to increase people's energy expenditure, but there is limited evidence whether the neighborhood environment correlates differently with recreational and transportation walking. AimTo investigate how recreational walking and transportation walking are associated with the natural and built environmental characteristics of the living environment in the Netherlands, and examine the differences in their associations between weekdays and weekends. Method and data We extracted the total duration of daily walking (in minutes per person) for recreation and transportation of adults aged 18 years and above from the Dutch National Travel Survey 2015-2017 (N = 65,785) and analyzed it as an outcome variable. Objective measures of the natural (i.e., normalized difference vegetation index (NDVI), blue space and meteorological conditions) and built environment (i.e., crossing density, land-use mix, and residential building density) around respondents' home addresses were determined for buffers with 300, 600, and 1000 m radii using a geographic information system. To assess associations between recreational and transportation walking and the environmental exposures separately, we fitted Tobit regression models to the walking data, adjusted for multiple confounders. ResultsOn weekdays, people living in areas with less NDVI, higher land-use mix, and higher crossing density were more likely to engage in transportation walking. Recreational walking was negatively associated with NDVI, blue space, crossing density, precipitation and daily average temperature. At weekends, land-use mix supports both recreational and transportation walking. A negative association appeared for NDVI and transportation walking. Daily average rainfall and temperature were inversely correlated with recreational walking. Sensitivity tests indicated that some associations depend on the buffer size. ConclusionsOur findings suggest that the built and natural environments are differently associated with people's recreational and transportation walking. We also found differences in the walking-environment associations between weekdays and weekends. Place-based policies to design walking-friendly neighborhoods may have different implications for different types of walking.

Land use mix and physical activity in middle-aged and older adults: a longitudinal study examining changes in land use mix in two Dutch cohorts

Background

With urbanization and aging increasing in coming decades, societies face the challenge of keeping aging populations active. Land use mix (LUM) has been associated with cycling and walking, but whether changes in LUM relate to changes in cycling/walking is less known.

Objectives

Our objective was to study the effect of LUM on cycling/walking in two Dutch aging cohorts using data with 10 years of follow-up.

Methods

Data from 1183 respondents from the Health and Living Conditions of the Population of Eindhoven and Surroundings (GLOBE) study and 918 respondents from the Longitudinal Aging Study Amsterdam (LASA) were linked to LUM in 1000-m sausage network buffers at three time-points. Cycling/walking outcomes were harmonized to include average minutes spent cycling/walking per week. Data was pooled and limited to respondents that did not relocate between follow-up waves. Associations between LUM and cycling/walking were estimated using a Random Effects Within-Between (REWB) model that allows for the estimation of both within and between effects. Sensitivity analyses were performed on smaller (500-m) and larger (1600-m) buffers.

Results

We found evidence of between-individual associations of LUM in 1000-m buffers and walking (β: 11.10, 95% CI: 0.08; 21.12), but no evidence of within-associations in 1000-m buffers. Sensitivity analyses using 500-m buffers showed similar between-associations, but negative within-associations (β: -35.67, 95% CI: − 68.85; − 2.49). We did not find evidence of between-individual associations of LUM in any buffer size and cycling, but did find evidence of negative within-associations between LUM in 1600-m buffers and cycling (β: -7.49, 95% CI: − 14.31; − 0.66).

Discussion

Our study found evidence of positive associations between LUM and average walking time, but also some evidence of negative associations between a change in LUM and cycling/walking. LUM appears to be related to cycling/walking, but the effect of changes in LUM on cycling/walking is unclear.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01083-1.

Reliability of T-WSI to Evaluate Neighborhoods Walkability and Its Changes over Time

More walkable neighborhoods are linked to increased physical activity. The Walking Suitability Index of the territory (T-WSI) is an easy method to evaluate walkability on the basis of direct observation. T-WSI provides 12 indicators divided into 4 categories (practicability, safety, urbanity, pleasantness); the weighted analysis of these indicators gives an overall score of the actual usability of the neighborhood. The aim of the study is to evaluate the ability of T-WSI’ indicators to measure, in a reliable way, any street’s walkability variations occurred over time. The investigation was performed in 2018 in nine urban neighborhoods of Rieti city. Cronbach’s α is used to evaluate internal consistency of T-WSI; Intraclass Correlation Coefficient (ICC) is used to evaluate the reproducibility of measurements (or ratings) made by different investigators. Cronbach’s α is 0.89 (± 0.02); ICC is also good (ICC = 0.89; 95% CI: 0.84–0.92). The results of the 2018 investigation are also compared with those collected in 2016 in the same districts. The results show that T-WSI is a reliable and easy to use tool, useful to measure the effectiveness of the interventions already realized at local level, but it could also contribute to making decisions to develop regeneration projects.

Walkable Urban Environments: An Ergonomic Approach of Evaluation

Background. The salutogenicity of urban environments is significantly affected by their ergonomics, i.e., by the quality of the interactions between citizens and the elements of the built environment. Measuring and modelling urban ergonomics is thus a key issue to provide urban policy makers with planning solutions to increase the well-being, usability and safety of the urban environment. However, this is a difficult task due to the complexity of the interrelations between the urban environment and human activities. The paper contributes to the definition of a generalized model of urban ergonomics and salutogenicity, focusing on walkability, by discussing the relevant parameters from the large and variegated sets proposed in the literature, by discussing the emerging model structure from a data mining process, by considering the background of the relevant functional dependency already established in the literature, and by providing evidence of the solutions’ effectiveness. The methodology is developed for a case study in central Italy, with a focus on the mobility issue, which is a catalyst to generate more salutogenic and sustainable behaviors.

Windows of opportunity for daily physical activity

Air pollution is a serious concern to people who want to engage in physical activities to improve and maintain their health. However, air quality data collected at the nearest monitoring site may not be the best source of information because the data may be incomplete (e.g., some pollutants are not monitored) or not representative. This paper puts forward a method that uses air quality data from a large area to derive a diurnal profile of air quality variation for that area and identify the time window in which the air quality is typically the best during a day. If people exercise in that time window then they can minimize their exposure to air pollution. Three years’ worth of air quality data in five California counties were analyzed to identify the general pattern of diurnal variation of air quality. The analysis shows the pattern of air quality variation is very similar among those five counties which represent diverse geographical and meteorological conditions. The analysis further reveals that in California air quality is generally the best in early mornings; as such, people should exercise in the early morning if their daily schedule allows it. A similar analysis can be performed for other areas to help people choose the best time window to exercise.

A GIS-Based Method for Analysing the Association Between School-Built Environment and Home-School Route Measures with Active Commuting to School in Urban Children and Adolescents

In the current call for a greater human health and well-being as a sustainable development goal, to encourage active commuting to and from school (ACS) seems to be a key factor. Research focusing on the analysis of the association between environmental factors and ACS in children and adolescents has reported limited and inconclusive evidence, so more knowledge is needed about it. The main aim of this study is to examine the association between different built environmental factors of both school neighbourhood and home-school route with ACS of children and adolescents belonging to urban areas. The ACS level was evaluated using a self-reported questionnaire. Built environment variables (i.e., density of residents, street connectivity and mixed land use) within a school catchment area and home-school route characteristics (i.e., distance and pedestrian route directness—PRD) were measured using a geographic information system (GIS) and examined together with ACS levels. Subsequently, the association between environmental factors and ACS was analysed by binary logistic regression. Several cut-off points of the route measures were explored using receiver operating characteristic (ROC) curves. In addition, the PRD was further studied regarding different thresholds. The results showed that 70.5% of the participants were active and there were significant associations between most environmental factors and ACS. Most participants walked to school when routes were short (distance variable in children: OR = 0.980; p = 0.038; and adolescents: OR = 0.866; p < 0.001) and partially direct (PRD variable in children: OR = 11.334; p < 0.001; and adolescents: OR = 3.513; p < 0.001), the latter specially for children. Mixed land uses (OR = 2.037; p < 0.001) and a high density of street intersections (OR = 1.640; p < 0.001) clearly encouraged adolescents walking and slightly discouraged children walking (OR = 0.657, p = 0.010; and OR = 0.692, p = 0.025, respectively). The assessment of ACS together with the environmental factors using GIS separately for children and adolescents can inform future friendly and sustainable communities.

Urban Moveability and physical activity in children: longitudinal results from the IDEFICS and I.Family cohort

Background

Physical activity (PA) is one of the major protective behaviours to prevent non-communicable diseases. Positive effects of the built environment on PA are well investigated, although evidence of this association is mostly based on cross-sectional studies. The present study aims to investigate the longitudinal effects of built environment characteristics in terms of a moveability index on PA of children in their transition phase to adolescence using data of the IDEFICS/I.Family cohort.

Methods

We used data on 3394 accelerometer measurements of 2488 children and adolescents aged 3 to 15 years old from survey centres of three countries, Germany, Italy, and Sweden, who participated in up to three surveys over 6 years. In network-dependent home neighbourhoods, a moveability index was calculated based on residential density, land use mix, street connectivity, availability of public transport and public open spaces such as green spaces and public playgrounds in order to quantify opportunities for PA of children and adolescents. Linear trajectories of light PA (LPA) and moderate-to-vigorous PA (MVPA) were estimated using linear mixed models accounting for repeated measurements nested within individuals. Least squares means were estimated to quantify differences in trajectories over age.

Results

LPA and MVPA declined annually with age by approximately 20 min/day and 2 min/day respectively. In girls, the moveability index showed a consistent significantly positive effect on MVPA (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \hat{\beta} $$\end{document}β^ = 2.14, 95% CI: (0.11; 4.16)) for all ages, while in boys the index significantly lessened the decline in LPA with age for each year. (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \hat{\beta} $$\end{document}β^ = 2.68, 95% CI: (0.46; 4.90)).

Availability of public open spaces was more relevant for MVPA in girls and LPA in boys during childhood, whereas in adolescence, residential density and intersection density became more important.

Conclusion

Built environment characteristics are important determinants of PA and were found to have a supportive effect that ameliorates the decline in PA during the transition phase from childhood to adolescence. In childhood environmental support for leisure time PA through public open spaces was found to be the most protective factor whereas in adolescence the positive influence of street connectivity and residential density was most supportive of physical activity.

Residential relocation trajectories and neighborhood density, mixed land use and access networks as predictors of walking and bicycling in the Northern Finland Birth Cohort 1966

Background

Given the high global prevalence of physical inactivity, there is a need to design cities that support active modes of transportation. High density diverse neighborhoods with good access networks have been associated with enhanced walking and cycling, but there is a lack of large-scale longitudinal studies utilizing a life course perspective to model residential relocation trajectories. The objectives of the present longitudinal study were to model and visualize residential relocation trajectories between 31 and 46 years of age based on neighborhood density, mixed land use and access networks (DMA), and to assess neighborhood DMA as a predictor of self-reported regular walking and cycling and objectively measured physical activity.

Methods

Based on data from the Northern Finland Birth Cohort 1966 (N = 5947), we used self-reported regular walking and cycling and objectively measured physical activity as outcome variables and objectively assessed neighborhood DMA as the main explanatory variable. We conducted sequence analysis to model residential relocation trajectories, and generalized linear mixed models and Fisher’s exact test were used to explore longitudinal associations between neighborhood DMA and physical activity.

Results

Over 80% of the participants lived in a neighborhood with the same level of neighborhood DMA during the follow-up. Relocation occurred more often from higher to lower DMA neighborhoods than reverse. Increased neighborhood DMA was associated with increased regular walking (OR 1.03; 95% CI: 1.00, 1.05; p = 0.023) and cycling (OR 1.17; 95% CI: 1.12, 1.23; p <  0.001). Residential relocation trajectory from lower to highest neighborhood DMA increased the odds of starting regular walking (OR 3.15; 95% CI: 1.50, 7.14; p = 0.001) and cycling (OR 2.63; 95% CI: 1.23, 5.79; p = 0.009) as compared to higher to lower neighborhood DMA trajectory.

Conclusions

The results strongly support the hypothesis that increasing urban DMA can enhance regular walking and cycling at population level and so improve public health. The findings have implications for zoning and transportation policies, favoring the creation of dense and diverse neighborhoods with good access networks to support regular walking and cycling.

The Importance of Pedestrian Network Connectivity for Adolescent Health: A Cross-sectional Examination of Associations between Neighbourhood Built Environments and Metabolic Health in the Pacific Islands Families Birth Cohort Study

The research aim was to investigate associations between objectively-assessed built environment attributes and metabolic risk in adolescents of Pacific Islands ethnicity, and to consider the possible mediating effect of physical activity and sedentary time. Youth (n = 204) undertook a suite of physical assessments including body composition, blood sampling, and blood pressure measurements, and seven day accelerometry. Objective measures of the neighbourhood built environment were generated around individual addresses. Logistic regression and linear modelling were used to assess associations between environment measures and metabolic health, accounting for physical activity behaviours. Higher pedestrian connectivity was associated with an increase in the chance of having any International Diabetes Federation metabolic risk factors for males only. Pedestrian connectivity was related to fat free mass in males in unadjusted analyses only. This study provides evidence for the importance of pedestrian network connectivity for health in adolescent males. Future research is required to expand the limited evidence in neighbourhood environments and adolescent metabolic health.

Correlates of Walking for Travel in Seven European Cities: The PASTA Project

BACKGROUND

Although walking for travel can help in reaching the daily recommended levels of physical activity, we know relatively little about the correlates of walking for travel in the European context.

OBJECTIVE

Within the framework of the European Physical Activity through Sustainable Transport Approaches (PASTA) project, we aimed to explore the correlates of walking for travel in European cities.

METHODS

The same protocol was applied in seven European cities. Using a web-based questionnaire, we collected information on total minutes of walking per week, individual characteristics, mobility behavior, and attitude (N=7,875). Characteristics of the built environment (the home and the work/study addresses) were determined with geographic information system (GIS)-based techniques. We conducted negative binomial regression analyses, including city as a random effect. Factor and principal component analyses were also conducted to define profiles of the different variables of interest.

RESULTS

Living in high-density residential areas with richness of facilities and density of public transport stations was associated with increased walking for travel, whereas the same characteristics at the work/study area were less strongly associated with the outcome when the residential and work/study environments were entered in the model jointly. A walk-friendly social environment was associated with walking for travel. All three factors describing different opinions about walking (ranging from good to bad) were associated with increased minutes of walking per week, although the importance given to certain criteria to choose a mode of transport provided different results according to the criteria.

DISCUSSION

The present study supports findings from previous research regarding the role of the built environment in the promotion of walking for travel and provides new findings to help in achieving sustainable, healthy, livable, and walkable cities. https://doi.org/10.1289/EHP4603.

Urban Densification and 12-Year Changes in Cardiovascular Risk Markers

Background

Population densities of many cities are increasing rapidly, with the potential for impacts on cardiovascular health. This longitudinal study examined the potential impact of population‐density increases in urban areas (urban densification) on cardiovascular risk markers among Australian adults.

Methods and Results

Data were from the Australian Diabetes, Obesity and Lifestyle Study, in which adult participants’ cardiovascular risk markers were collected in 3 waves (in 1999–2000, 2004–2005, and 2011–2012). We included 2354 participants with a mean age of 51 years at baseline who did not change their residence during the study period. Outcomes were 12‐year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2‐hour postload plasma glucose, high‐density lipoprotein cholesterol, and triglycerides. The exposure was neighborhood population densification, defined as 12‐year change in population density within a 1‐km radius buffer around the participant’s home. Multilevel linear growth models, adjusting for potential confounders, were used to examine the relationships. Each 1% annual increase in population density was related with smaller increases in waist circumference (b=−0.043 cm/y; 95% CI, −0.065 to −0.021 [P<0.001]), weight (b=−0.019 kg/y; 95% CI, −0.039 to 0.001 [P=0.07]), and high‐density lipoprotein cholesterol (b=−0.035 mg/dL per year; 95% CI, −0.067 to −0.002 [P=0.04]), and greater increases in diastolic blood pressure (b=0.032 mm Hg/y; 95% CI, −0.004 to 0.069 [P=0.08]).

Conclusions

Our findings suggest that, at least in the context of Australia, urban densification may be protective against obesity risk but may have adverse effects on blood lipids and blood pressure. Further research is needed to understand the mechanisms through which urban densification influences cardiovascular health.

Built Environment, Psychosocial Factors and Active Commuting to School in Adolescents: Clustering a Self-Organizing Map Analysis

Although the built environment and certain psychosocial factors are related to adolescents' active commuting to and from school (ACS), their interrelationships have not been explored in depth. This study describes these interrelationships and behavioral profiles via a self-organizing map (SOM) analysis. The sample comprised 465 adolescents from the IPEN (International Physical Activity and the Environment Network) Adolescent study in Valencia, Spain. ACS, barriers to ACS, physical self-efficacy, social support and sociodemographics were measured by questionnaire. Street-network distance to school, net residential density and street intersection density were calculated from the Geographic Information System. The clustering of the SOM outcomes resulted in eight areas or clusters. The clusters which correspond to the lowest and highest ACS levels were then explored in depth. The lowest ACS levels presented interactions between the less supportive built environments (i.e., low levels of residential density and street connectivity in the neighborhood and greater distances to school) and unfavorable psychosocial variables (i.e., low values of physical self-efficacy and medium social support for ACS) and good access to private motorized transport at home. The adolescents with the lowest ACS values exhibited high ACS environment/safety and planning/psychosocial barrier values. Future interventions should be designed to encourage ACS and change multiple levels of influence, such as individual, psychosocial and environmental factors.